Proefschrift Viester

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Worksite health promotion in

the construction industry

Laura Viester

Laura Viester W

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Uitnodigingvoor het bijwonen van de openbare verdediging van

mijn proefschrift



op dinsdag 24 november 2015 om 13.45 uur in de aula van

de Vrije Universiteit aan de Boelelaan 1105

te Amsterdam

Na afloop bent u van harte welkom op de receptie

Laura ViesterOhmstraat 4-II

1098 SR Amsterdam06-24472241

[email protected]

ParanimfenLinda Eijckelhof

[email protected]

Mirka [email protected]

Worksite health promotion in the construction industry

Laura Viester

The study presented in this thesis was conducted at the EMGO+ Institute for Health and Care

Research, Department of Public and Occupational Health of the VU University Medical Center. The

EMGO+ Institute participates in the Netherlands School of Primary Care Research (CaRe), which

was acknowledged in 2005 by the Royal Netherlands Academy of Arts and Sciences (KNAW). The

study described in this thesis originated from Body@Work, Research Center on Physical Activity,

Work, and Health, which is a joint initiative of the VU University Medical Center (Department of

Public and Occupational Health, EMGO+ Institute for Health and Care Research), VU University

Amsterdam, and the Netherlands Organisation of Applied Scientific Research (TNO).

The study presented in this thesis is part of a research programme “Vitality in practice”, which is

financed by Fonds Nuts Ohra (Nuts Ohra Foundation).

Financial support for the printing of this thesis has kindly been provided by Body@Work, Research

Center on Physical Activity, Work, and Health.

English title: Worksite health promotion in the construction industry

Nederlandse titel: Gezondheidsbevordering voor werknemers in de bouwsector

ISBN: 978-94-6233-109-9

Layout: Gildeprint– Enschede, the Netherlands

Printed by: Gildeprint – Enschede, the Netherlands

© Copyright 2015, Laura Viester

All rights reserved. No part of this publication may be reproduced, stored or transmitted in any

form or by any means without permission of the referenced journals or the author.

VRIJE UNIVERSITEIT

Worksite health promotion in the construction industry

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad Doctor aan

de Vrije Universiteit Amsterdam,

op gezag van de rector magnificus

prof.dr. F.A. van der Duyn Schouten,

in het openbaar te verdedigen

ten overstaan van de promotiecommissie

van de Faculteit der Geneeskunde

op dinsdag 24 november 2015 om 13.45 uur

in de aula van de universiteit,

De Boelelaan 1105

door

Laura Viester

geboren te Amsterdam

promotoren: prof.dr. A.J. van der Beek

prof.dr.ir. P.M. Bongers

copromotor: dr. E.A.L.M. Verhagen

Contents

Chapter 1 General introduction 7

Chapter 2 The relation between body mass index and musculoskeletal symptoms 17

in the working population

Chapter 3 VIP in construction: systematic development and evaluation of a 35

multifaceted health programme aiming to improve physical activity

levels and dietary patterns among construction workers

Chapter 4 Process evaluation of a multifaceted health programme aiming to 65

improve physical activity levels and dietary patterns among construction

workers

Chapter 5 Improvements in dietary and physical activity behaviours and body mass 85

index as a result of a worksite intervention in construction workers:

results of a randomised controlled trial

Chapter 6 The effect of a health promotion intervention for construction workers 105

on work-related outcomes: results from a randomised controlled trial

Chapter 7 Cost-effectiveness and return-on-investment analysis of a worksite 123

intervention aimed at improving physical activity and nutrition among

construction workers

Chapter 8 General discussion 153

Summary 175

Samenvatting 179

Dankwoord 183

Chapter 1General Introduction

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8 | Chapter 1

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Introduction | 9

1Developments in the construction sector

The labour market is changing dramatically. Between 1990 and 2011 the average age in the

actively employed increased by 5 years, to over 41 years of age [1]. From 2013 on this will

accelerate. According to the Statistics Netherlands (CBS) population’s prognosis, the number of

people aged > 65 are projected to rise from 2.7 million in 2012 to 4.7 million in 2041 [2].

The ratio of economically active individuals to pensioners will become unfavourable, and as a

result retirement age will be raised. Hence, the workforce is ageing and this also applies to the

construction sector, where currently more workers are in their 50s than in their 30s.

In the upcoming years, despite the counteracting consequences on employment as a result

of the current economic recession, in several sectors a shortage in workers is expected. In the

construction sector this shortage will also result from a decrease in the number of young workers

entering the sector. An additional concern is that sickness absence is also more common in

blue collar occupations [3]. The combination of ageing with high physical demands at work for

this occupational group results in relatively high risk for increased sickness absence and work

disability. Keeping ageing employees at work is a key goal of European labour policy, and from

the perspective of employers it is essential to invest in the health of their employees.

Another consequence of an ageing workforce is the increase in health risks. Body weight increases

with age, and older workers suffer increasingly from musculoskeletal complaints, especially in

physically demanding professions [4,5]. These developments, especially in combination with

unfavourable health and lifestyle indicators, provide challenges for maintaining a healthy and

productive workforce, and emphasise the need of interventions in the construction sector.

Overweight, lifestyle and musculoskeletal disorders

Overweight becomes an ever greater public health problem. During the last decades the prevalence

of obesity has increased worldwide, and the World Health Organization (WHO) lists overweight

and obesity as one of the leading global risks for mortality [6]. Increased prevalence in overweight

and obesity also applies to the Netherlands. In 2011, according to the Dutch Bureau of Statistics

(CBS) over 50% of the male and 40% of the female population was overweight [7]. Of this

population 10% of the men and 13% of the women were categorised as severely overweight,

i.e. obese. Although the steep increase of the last three decades seems to be reaching a plateau,

the obesity numbers are still rising.

Overweight and obesity are associated with a series of secondary complications and serious

comorbid diseases, such as elevated rates of diabetes, cardiovascular disease, cancer and

musculoskeletal disorders (MSD) [8-10]. Along with these detrimental effects on a person’s health

and well-being, there are substantial economic consequences to consider. The annual medical

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10 | Chapter 1

costs of overweight in the Netherlands have been estimated at €500 million [11]. In addition to

these direct health care costs, indirect costs of overweight for employers resulting from loss of

productivity due to both sickness absenteism and presenteism, and work disability are even more

substantial [12].

Among Dutch construction workers, the prevalence of overweight and obesity is even higher than

in the general population. In this specific occupational group 64% of the workers is overweight,

of which almost a quarter is obese [13]. Moreover, it seems that blue collar workers also have

poorer scores when other lifestyle and health indicators are considered, including cardiovascular

risk factors, leisure time physical activity and smoking [14-16].

Prevalence of overweight and obesity is lower among populations with healthier lifestyle

behaviours [17]. A stable body weight requires a long-term balance between energy intake

and energy expenditure. If energy intake exceeds expenditure, the excess of energy is stored as

adipose tissue. The development of overweight and obesity is either the result of detrimental

food intake behaviour, decreased physical activity behaviour, or a combination of both, with the

consequence of an imbalance between energy uptake and expenditure. The effects of a positive

energy balance can therefore be prevented and reversed by caloric restriction and increasing

physical activity.

Although blue collar workers might be more than average physically active at work, this is not

accompanied by better health or improved physical capacity [18,19]. Recent research indicates

that contrasting health associations of physical activity at work and leisure time physical activity

exist [20]. Physical activity at work does not induce positive changes in aerobic capacity or muscular

strength in workers [21]. Furthermore, being physically active at work might be compensated

by more sedentary/inactive behaviour in leisure time. Although more likely to meet the weekly

recommendations of overall physical activity [22], individuals from lower socioeconomic

backgrounds and blue collar workers are less likely to engage in sports and leisure time activities

[22-26]. Aiming at increasing leisure time physical activity in construction workers might therefore

be a relevant strategy to improve both energy balance and general health.

Another main cause of overweight is poor diet. Unhealthy eating is known to be more prevalent

among individuals with lower socioeconomic status, with less fruit and vegetable consumption

and higher consumption in refined products based on different household incomes, educational

levels or occupational groups [27,28].

Apart from health problems most commonly related to overweight, such as diabetes or

cardiovascular disease, overweight is also negatively associated with muscular strength

[29,30] and increased risk for musculoskeletal pain [31,32]. Among blue collar workers in the

construction sector, long-term sickness absence and work disability are primarily caused by MSD.

When considering the high prevalence of MSD and overweight and the possible association

between overweight/obesity and MSD, preventing and reducing excessive body weight among

workers with a high physical work demand, might also be a strategy to decrease musculoskeletal


Introduction | 11

1symptoms. Epidemiological studies have shown that some personal risk factors for MSD, such

as high BMI, or lifestyle factors, such as smoking, are the same factors as those related to poor

general health. Therefore, general health promotion might be an option to prevent MSD. In a

systematic review of Proper et al. [33] it was concluded that there is strong evidence for positive

effects of worksite physical activity programmes on physical activity and MSD. Since overweight

and MSD are possibly associated, and (consequently) have joint risk factors, addressing these

health related problems simultaneously should be considered.

In order to prevent and reduce overweight and its related health and economic consequences, this

thesis describes the systematic development and evaluation of a lifestyle and health-enhancing

programme tailored to workers in the construction industry.

Worksite health promotion

Although there is a variety of settings and contexts available to provide health promotion

programmes, the WHO has described the workplace as one of the priority settings for health

promotion into the 21st century [34].

Traditionally, worksite health promotion (WHP) has been concerned as a part of occupational

safety and health, by influencing important health determinants at work, and as a strategy to

reduce sickness absence. More recently, issues of productivity and sustainability, well-being and

lifestyle choices have been addressed and WHP can be regarded even as a part of organisational

development. The concept of WHP is becoming increasingly relevant as more employers recognise

that (sustainably) realising organisational goals in the current competitive business environment,

economic climate, with increasing pressure on the labour market, and in combination with an

aging workforce, can only be achieved with a motivated and healthy workforce. WHP in the

construction industry could contribute to a better balance between organisational targets on the

one hand and employees’ health needs on the other.

The worksite as setting for health promotion has several advantages. First, it provides the

possibility to reach large groups, and the working population spends a large proportion of their

waking hours at the workplace. These opportunities are of specific importance in construction

workers who are often involved in shift work and spend a lot of time commuting to and from

work. Second, there is the possibility to incorporate the programmes in existing organisational

infrastructure and make use of existing communication and education channels. Third, the

workplace provides the presence of a natural social network.

In addition to efforts of worksite health programmes to increase health and vitality of the

workforce, the worksite as setting provides opportunities to address health inequalities in the

workforce. While for the population as a whole, and for all social classes, life expectancy has

improved, social health inequalities remain. Generally, blue collar construction workers consist

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12 | Chapter 1

of a lower socioeconomic group than white collar workers. Physical working conditions explain

part of the social gradient in health [35,36]. To improve health among lower socioeconomic

status workers, workplace health promotion programmes need to focus on workers in blue collar

occupations, especially since this group is harder to reach in general public health efforts. There is

evidence that workplace programmes are both clinically effective and cost-effective in industries

employing blue collar workers [37].

Thus, worksites are regarded as a promising context for health promotion while they provide

many opportunities to reinforce health behaviours, especially in groups that are hard to reach

outside this setting.

Context and project setting

The project is part of a larger research programme ‘Vitality in Practice’ aiming at enhancing

vitality of companies and their employees by developing and evaluating tailored worksite health

promotion programmes. The study described in this thesis was developed and evaluated among

blue collar construction workers employed by a large construction company. Investing in health

and vitality of their workers is essential for the company to realise its ambitious goals, along with

an aging and shrinking workforce.

As other employers in the construction industry, the company was already engaged in WHP

activities for their employees. WHP consists of various components and activities, such as for

example periodic health screenings (PHS), company fitness programmes, and courses in smoking

cessation. However, the health benefits, and effects on work-related outcomes, such as sickness

absence and work ability, of these activities have not been identified. Moreover, it is not established

whether these efforts reach the target population. Participation in these activities is on voluntary

basis. As a result it is not clear if those most at risk are being reached. Based on studies on

participation in health promotion programmes, it is hypothesised that low risk and healthier

employees are more likely to enrol in worksite health programmes, and not necessarily those

most in need [38,39]. As a result it is crucial to develop strategies to include all workers starting

by investigating reasons for non-participation. In the previous paragraphs it was concluded

that lifestyle behaviour is an important factor for the existence and increase in unhealthy body

weight with health-impairing consequences. Since several risk factors are present in this particular

group of workers, and potentially large health benefits can be obtained it seems justified to

develop a sector specific approach. To increase likelihood of effectiveness, interventions should be

developed systematically, need a theoretical basis, and should match the context and the target

population [40,41]. Interventions designed for other target groups might not be suitable for this

specific occupational group. Tailoring of WHP is relevant to address specific health concerns and

health behaviours in construction workers, the specific work conditions and characteristics of the

work setting.


Introduction | 13

1Organisational factors that are involved in adoption of evidence-based interventions should also

be included in the evaluation of the programme. Providing employers with information on the

potential benefits of WHP, for example by including financial return data in the evaluation of

programmes, might be an incentive for employers to invest in these activities [42,43]. This might

also lead to increased implementation of research results into practice.

Therefore, research is needed to gain more insight into the feasibility and (cost-)effectiveness of

preventive measures in evidence-based intervention programmes, and to support organisational

decision making.

Aims and outline of this thesis

Following the rationale in the previous paragraphs, the primary aim of this thesis is to examine

the effect of a tailored intervention developed in consultation with the target population

and management of a construction company. To gain insight into prevention possibilities for

overweight/obesity and musculoskeletal symptoms in blue collar workers it is important to further

explore the relation between these major health concerns. Therefore, the current thesis addresses

the following objectives:

1) To provide insight into the association of overweight/obesity and musculoskeletal

symptoms,

2) To describe the systematic development of a worksite intervention tailored to a specific

group of workers,

3) To evaluate this newly developed intervention on its (cost-)effectiveness and evaluate the

process of implementation.

First, chapter 2 addresses the association between the central health problems in this thesis,

overweight and musculoskeletal symptoms. It additionally examines the hypothesised interaction

with work-related physical exposure.

The second objective is introduced in chapter 3, describing the process of systematic development

of the intervention and its evaluation plan. Chapters 4 to 7 describe the evaluation of the

programme, and the trial results are presented in these chapters. Chapter 4 describes the

results of the process evaluation following the RE-AIM framework. In chapter 5 the effects on

physiological and behavioural outcomes are evaluated, and chapter 6 investigates the effects on

musculoskeletal symptoms and several work-related outcomes. The purpose of chapter 7 is to

explore the cost-effectiveness and return-on-investment of the VIP in Construction intervention

from a societal as well as employer’s perspective.

Finally, this thesis concludes with a general discussion in chapter 8, where the findings of this

thesis are summarised and discussed. After discussing the applied theoretical model, methods,

and results, future directions for research as well as practice are given.

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14 | Chapter 1

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17. Martinez-Gonzalez MA, Martinez JA, Hu FB, Gibney MJ, Kearney J: Physical inactivity, sedentary lifestyle and obesity in the European Union. Int J Obes Relat Metab Disord 1999, 23: 1192-1201.

18. Holtermann A, Jorgensen MB, Gram B, Christensen JR, Faber A, Overgaard K et al.: Worksite interventions for preventing physical deterioration among employees in job-groups with high physical work demands: background, design and conceptual model of FINALE. BMC Public Health 2010, 10: 120.

19. Holtermann A, Hansen JV, Burr H, Sogaard K, Sjogaard G: The health paradox of occupational and leisure-time physical activity. Br J Sports Med 2012, 46: 291-295.

20. Clays E, Lidegaard M, De Bacquer D, Van Herck K, De Backer G, Kittel F et al.: The combined relationship of occupational and leisure-time physical activity with all-cause mortality among men, accounting for physical fitness. Am J Epidemiol 2014, 179: 559-566.


Introduction | 15

121. Ruzic L, Heimer S, Misigoj-Durakovic M, Matkovic BR: Increased occupational physical activity does

not improve physical fitness. Occup Environ Med 2003, 60: 983-985.

22. Poortinga W: Do health behaviors mediate the association between social capital and health? Prev Med 2006, 43: 488-493.

23. Makinen T, Kestila L, Borodulin K, Martelin T, Rahkonen O, Leino-Arjas P et al.: Occupational class differences in leisure-time physical inactivity--contribution of past and current physical workload and other working conditions. Scand J Work Environ Health 2010, 36: 62-70.

24. Niknian M, Linnan LA, Lasater TM, Carleton RA: Use of population-based data to assess risk factor profiles of blue and white collar workers. J Occup Med 1991, 33: 29-36.

25. Mensink GB, Loose N, Oomen CM: Physical activity and its association with other lifestyle factors. Eur J Epidemiol 1997, 13: 771-778.

26. Burton NW, Turrell G: Occupation, hours worked, and leisure-time physical activity. Prev Med 2000, 31: 673-681.

27. Darmon N, Drewnowski A: Does social class predict diet quality? Am J Clin Nutr 2008, 87: 1107-1117.

28. Turrell G, Hewitt B, Patterson C, Oldenburg B: Measuring socio-economic position in dietary research: is choice of socio-economic indicator important? Public Health Nutr 2003, 6: 191-200.

29. Blimkie CJ, Sale DG, Bar-Or O: Voluntary strength, evoked twitch contractile properties and motor unit activation of knee extensors in obese and non-obese adolescent males. Eur J Appl Physiol Occup Physiol 1990, 61: 313-318.

30. Maffiuletti NA, Jubeau M, Munzinger U, Bizzini M, Agosti F, De Col A et al.: Differences in quadriceps muscle strength and fatigue between lean and obese subjects. Eur J Appl Physiol 2007, 101: 51-59.

31. Felson DT, Lawrence RC, Dieppe PA, Hirsch R, Helmick CG, Jordan JM et al.: Osteoarthritis: new insights. Part 1: the disease and its risk factors. Ann Intern Med 2000, 133: 635-646.

32. Miranda H, Viikari-Juntura E, Martikainen R, Takala EP, Riihimaki H: A prospective study of work related factors and physical exercise as predictors of shoulder pain. Occup Environ Med 2001, 58: 528-534.

33. Proper KI, Koning M, van der Beek AJ, Hildebrandt VH, Bosscher RJ, van Mechelen W: The effectiveness of worksite physical activity programs on physical activity, physical fitness, and health. Clin J Sport Med 2003, 13: 106-117.

34. World Health Organization. Workplace health promotion: the workplace: a priority setting for health promotion. 2010. Ref Type: Report

35. Hammig O, Bauer GF: The social gradient in work and health: a cross-sectional study exploring the relationship between working conditions and health inequalities. BMC Public Health 2013, 13: 1170.

36. Bauer GF, Huber CA, Jenny GJ, Muller F, Hammig O: Socioeconomic status, working conditions and self-rated health in Switzerland: explaining the gradient in men and women. Int J Public Health 2009, 54: 23-30.

37. Novak B, Bullen C, Howden-Chapman P, Thornley S: Blue-collar workplaces: a setting for reducing heart health inequalities in New Zealand? N Z Med J 2007, 120: U2704.

38. Lewis RJ, Huebner WW, Yarborough CM: Characteristics of participants and nonparticipants in worksite health promotion. Am J Health Promot 1996, 11: 99-106.

39. Lerman Y, Shemer J: Epidemiologic characteristics of participants and nonparticipants in health-promotion programs. J Occup Environ Med 1996, 38: 535-538.

40. Bartholomew LK, Parcel GS, Kok G, Gottlieb NH: Planning health promotion programs: intervention mapping. San Francisco, CA: Jossey-Bass; 2006.

41. Kok G, van den Borne B, Mullen PD: Effectiveness of health education and health promotion: meta-analyses of effect studies and determinants of effectiveness. Patient Educ Couns 1997, 30: 19-27.

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42. van Dongen JM, Tompa E, Clune L, Sarnocinska-Hart A, Bongers PM, van Tulder MW et al.: Bridging the gap between the economic evaluation literature and daily practice in occupational health: a qualitative study among decision-makers in the healthcare sector. Implement Sci 2013, 8: 57.

43. Downey AM, Sharp DJ: Why do managers allocate resources to workplace health promotion programmes in countries with national health coverage? Health Promot Int 2007, 22: 102-111.

Chapter 2The relation between body mass index and musculoskeletal

symptoms in the working population

Laura Viester, Evert A. L. M. Verhagen, Karen M. Oude Hengel,

Lando L.J. Koppes, Allard J. van der Beek, Paulien M. Bongers

BMC Musculoskeletal Disorders. 2013 12;14-238

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18 | Chapter 2

Abstract

Background: The primary aim of this study was to investigate the association between BMI and

musculoskeletal symptoms in interaction with physical workload. In addition, it was aimed to

obtain insight into whether overweight and obesity are associated with an increase in occurrence

of symptoms and/or decrease in recovery from symptoms.

Methods: Based on a large working population sample (n = 44,793), using the data from The

Netherlands Working Conditions Survey (NWCS), logistic regression analyses were carried out

to investigate the association between BMI and musculoskeletal symptoms, with adjustment

for potential confounders. Longitudinal data from the Netherlands Working Conditions Cohort

Study (NWCCS) of 7,909 respondents was used for the second research aim (i.e., to investigate

the transition in musculoskeletal symptoms).

Results: For high BMI an increased 12-month prevalence of musculoskeletal symptoms was

found (overweight: OR 1.13, 95% CI: 1.08-1.19 and obesity: OR 1.28, 95% CI: 1.19-1.39).

The association was modified by physical workload, with a stronger association for employees

with low physical workload than for those with high physical workload. Obesity was related to

developing musculoskeletal symptoms (OR 1.37, 95% CI: 1.05-1.79) and inversely related to

recovery from symptoms (OR 0.76, 95% CI: 0.59-0.97).

Conclusion: BMI was associated with musculoskeletal symptoms, in particular symptoms of the

lower extremity. Furthermore, the association differed for employees with high or low physical

workload. Compared to employees with normal weight, obese employees had higher risk for

developing symptoms as well as less recovery from symptoms. This study supports the role of

biomechanical factors for the relationship between BMI and symptoms in the lower extremity.


The relation between body mass index and musculoskeletal symptoms in the working population | 19

2

Background

Musculoskeletal disorders (MSDs) represent a considerable health problem in the working

population, with low back pain (LBP) as one of the most common MSDs [1]. MSDs have a high

impact on the individual worker, due to problems such as pain and limitations in daily activities.

Moreover, it has consequences at society level, including employers, as MSDs have been identified

as the most common cause of absenteeism from work and work disability [2] and generate high

impact on healthcare costs and on costs due to productivity loss in particular [3-5]. As MSDs have

a high impact for the individual as well as for society, it is important to gain insight in the risk

factors of such disorders in order to find opportunities for prevention.

The origin of MSDs is complex and multi-factorial. Amongst various risk factors, such as heavy

lifting [6] and high job demands [7-9], it has been suggested that high body mass index (BMI)

(overweight and obesity) might be an independent risk factor for MSDs. To date, the relationship

between BMI and MSDs has mainly been investigated in studies on LBP [10]. These cross-sectional

and cohort studies showed that overweight and obesity were associated with LBP [10]. While

this relationship has been suggested, it could also be argued that BMI is associated with MSDs in

other body regions. For symptoms of neck/shoulder, upper and lower limbs, evidence was also

found that high BMI is an independent risk factor for the development of (symptoms of) MSDs

[11-18].

Multiple hypotheses might explain the link between overweight and obesity and musculoskeletal

symptoms including, amongst others, increased mechanical demands [19,20] and metabolic

factors associated with obesity [19,21]. Increased forces across the joints are likely to play a

larger role in the relationship between a high BMI and weight-bearing joints (back and lower

extremities), compared to symptoms in non-weight-bearing joints (in the shoulder/neck and upper

extremities). For carpal tunnel syndrome (CTS) an increase in upper extremity musculoskeletal

symptoms associated with obesity has been attributed to increased adipose tissue in the carpal

tunnel, causing median nerve compression [22,23]. Therefore, it seems relevant to make a

distinction in different body regions because of potentially different (importance of) risk factors,

underlying mechanisms, and natural course of the symptoms.

Weight reduction in overweight and obese workers is assumed to reduce the incidence of

musculoskeletal pain [24]. Since overweight and obesity are a growing public health problem,

interventions reducing BMI could - if the hypothesised relationship exists - also be an effective

primary and secondary prevention strategy for musculoskeletal symptoms.

Epidemiological studies that have demonstrated that high BMI is linked to MSD have not revealed

factors that explain this link. Among mechanical factors, adjustment for physical workload could

affect the relationship between BMI and MSDs. Occupational physical workload has found to be

associated with MSD [25,26]. In a working population, work-related physical load could modify

the effect of high BMI on the prevalence of MSD. Our hypothesis is that in workers with high

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20 | Chapter 2

physical workload, the association in weight bearing joints will be increased, through additional

physical strain, since overweight and obese individuals experience greater loads on their joints

than normal-weight individuals. Analysis of the possible difference in the relationship between

high BMI and musculoskeletal symptoms among workers by work-related physical exposure

would provide directions for prevention strategies.

The primary research aim of this study was therefore to cross-sectionally investigate the

association between BMI and musculoskeletal symptoms in interaction with physical workload.

Secondly, since MSDs are of episodic nature, it is of interest to obtain insight into whether high

BMI is associated with an increase in occurrence of symptoms in a symptom-free population, or

whether high BMI is associated with less recovery from symptoms in a population with symptoms

at baseline occurs (or a combination of these options).

Methods

Sample / Study population

Based on a large working population cohort, we examined BMI in association with prevalence of

musculoskeletal symptoms in employees, with adjustment for potential confounders. Additionally,

within a subcohort, transitions in musculoskeletal symptoms were longitudinally investigated in

relation to BMI.

Data were obtained from The Netherlands Working Conditions Survey (NWCS) [27]. This dataset

constitutes of a representative sample of the Dutch workforce in the 15–64 years age group,

but excluded self-employed individuals. Each year, 80,000 individuals were sampled from the

Dutch working population database by Statistics Netherlands. This database contains information

on all jobs that fall under the worker national insurance schemes and are liable to income tax.

Sampling was random, except for a 50% over-sampling of employees with lower response rates,

namely employees under the age of 25 years and employees with a non-western background.

Individuals in the sample received the questionnaire mailed to their home address. After three

to four weeks, reminders were sent to those who had not yet responded. Data collection was

stopped after two months. To be representative for employees in the Netherlands, the response

was weighted for gender, age, sector, ethnic origin, level of urbanization, geographical region

and level of education.

The sample was extensively informed about the study in a letter that accompanied the

questionnaire. The burden for respondents was low given the topics covered in the questionnaire.

Consequently, and in accordance with ethics regulations in the Netherlands, ethical approval was

not required for this study.

A total of 44,793 employees completed the NWCS questionnaire in 2008 or 2009 (2008: n =

22,025, 2009: n = 22,768; overall response rate: 28%) and these employees were eligible for



2

the cross-sectional analysis. In addition to the regular annual survey, respondents of the NWCS

questionnaire in 2007, who gave consent for being contacted in the future, were invited to

respond to follow-up questionnaires in 2008 and 2009 (Netherlands Working Conditions Cohort

Study (NWCCS)).

In this cohort, a total of 7,909 completed the NWCCS questionnaire in 2009 (response rate:

35%). Respondents who participated at follow-up were more often higher educated and slightly

older than expected based on the NWCS sample. No selective differences were found for the

dependent variables BMI and musculoskeletal symptoms. Data retrieved from the NWCCS of

these 7,909 respondents were used for the second research aim (i.e., to investigate the transition

in musculoskeletal symptoms).

Measurement of BMI

Self-reported body weight in kilogrammes (kg) and body height in centimetres (cm) were used to

determine BMI. BMI was computed as weight (kg)/height (m)2. Subsequently, BMI was classified

into three categories (normal weight (BMI 18.5-24.9 kg/m2), overweight (BMI 25.0-29.9 kg/m2),

and obese (BMI ≥ 30 kg/m2)), which is in accordance with the international classification system

of the WHO [28].

Measurement of musculoskeletal symptoms

The questions on musculoskeletal symptoms were based on the Dutch Musculoskeletal

Questionnaire [29,30]. Employees were asked to rate the occurrence of pain or discomfort in

the neck, shoulders, back, arms/elbows, hands/wrists, and lower extremity, in the previous 12

months using 6 questions with five answering categories (‘never’, ‘only once, of short duration’,

‘only once, prolonged’, ‘frequently, of short duration’, ‘frequently and prolonged’). Employees

who answered ‘never’ or ‘only once, of short duration’ on all questions were classified as having

no musculoskeletal symptoms. Those who answered ‘prolonged’ or ‘frequently’ for one or

more locations were classified as having musculoskeletal symptoms overall. Hence, this overall

prevalence is reported for any location, in addition to location-specific prevalences for which the

responses on neck and shoulders were combined (neck/shoulder), as were those on arms/elbows

and hands/wrists (upper extremity).

Potential confounders and effect modifiers

Employees were asked questions on current use of force, work in awkward positions, use of

vibrating tools (tools, machines or vehicles), and repetitive motions on a 3-point scale (‘never’, ‘yes,

occasionally’, yes, regularly’). Employees who answered ‘yes, regularly’ on use of force or work in

awkward positions were classified as having high physical workload. Those who answered ‘no,

never’ or ‘yes, occasionally’ on both questions were classified as having low physical workload.

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Additional potential confounders were gender, age, education (categorised into low, intermediate,

and high educational level), contractual working hours (part time/full time), current smoking (yes/

no), and physical activity (days a week physically active for at least 30 minutes and of at least

moderate intensity). Physical activity was dichotomized as physically active (yes/no) according to

the Dutch public health recommendation for moderate intensity physical activity [31].

Analysis

For the first research aim, using the weighted cross-sectional data, logistic regression analyses

were carried out to investigate the association between BMI and musculoskeletal symptoms. The

measure of association was expressed by the Odds Ratio (OR) and its 95% confidence interval

(CI). In the categorical analyses involving BMI, the interval 18.5-24.9 was considered as the

reference group. In adjusted analysis potential confounders were added to the regression model

(full model).

Effect modification was defined as a significant interaction term (p < 0.05) between potential

effect modifiers (age, gender, physical workload) and BMI. Analyses were presented stratified for

age, gender, or physical workload if the associations between BMI and musculoskeletal symptoms

differed based on significant interaction terms.

For the second research aim, using the cohort data (no weighting), the analyses were stratified

for respondents without symptoms and those with symptoms in the baseline survey. To determine

the difference in the risk of developing symptoms (occurrence) between employees who are

overweight and those who are not, outcome was the 12-month incidence of musculoskeletal

symptoms. Cases of musculoskeletal symptoms were identified as those who reported frequent

or prolonged symptoms at follow-up. To study the influence of BMI on recovery from symptoms,

a separate analysis for employees who reported frequent or prolonged symptoms in the last

12 months was performed. Hence, the OR expressed the association between the risk factor at

baseline (high BMI) and transition from symptoms to no symptoms, or the reverse, at follow-up.

Results

Characteristics and prevalence of symptoms

Table 1 presents the characteristics of the cross-sectional sample. After excluding 865 employees

with missing data on BMI (1.9%), and underweight employees (BMI < 18.5; 1.6%), in total

43,221 employees were included in the analysis. Of the employees with normal weight, 50%

reported musculoskeletal symptoms within the past 12 months. Musculoskeletal symptoms were

reported by 52.3% and 57.6% of the overweight and obese employees, respectively.



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Table 1. Sample characteristics of musculoskeletal symptoms, demographic, work, and lifestyle-related factors across BMI categories

Total ‘Normal’ weight Overweight ObeseN 43,221 24,025 14,905 4,291Symptoms (overall) % 51.6 50.0 52.3 57.6Neck/Shoulder 30.2 30.0 29.7 33.0Upper Extremity 20.0 18.3 21.0 26.2Back 24.0 24.2 23.3 26.0Lower Extremity 24.5 21.4 26.7 34.3GenderMale 54.2 48.0 64.4 53.4Female 45.8 52.0 35.6 46.6Age (in years (sd)) 40.3(12.1) 37.9(12.3) 43.1(11.2) 43.7(10.9)EmploymentFull time (> = 36 hrs/wk) 56.5 51.8 63.7 57.0Part time (<36 hrs/wk) 43.5 48.2 36.3 43.0Physical workload: Repetitive motionsRegular 33.8 33.1 33.4 38.8Occasional 22.1 22.3 22.0 21.2None 44.2 44.6 44.7 40.0Physical workload: Use of vibrating toolsRegular 9.5 8.0 11.0 12.0Occasional 9.0 8.2 10.1 9.9None 81.5 83.8 78.9 78.1Physical workload: Use of forceRegular 19.2 18.9 19.1 20.6Occasional 22.5 21.6 23.0 24.9None 58.3 59.5 57.9 54.4Physical workload: Awkward positionRegular 10.6 10.0 11.3 11.9Occasional 25.9 25.6 25.9 27.3None 63.5 64.4 62.8 60.9Combined physical workloadHigh 22.0 21.7 21.9 23.6Low 78.0 78.3 78.1 76.4Lifestyle-related factorsPhysically acive (yes) 52.5 54.8 50.3 47.5Smoking (yes) 27.6 28.1 26.9 27.0

Variables are presented as proportions, with the exception of age (mean (standard deviation)).

Associations between categories BMI and musculoskeletal symptoms

Table 2 shows the ORs adjusted for age and gender, as well as the ORs after adjustment for all

potential confounders (full model). Overall, high BMI (overweight and obesity) was associated

with an increased 12-month prevalence of musculoskeletal symptoms. This association was

significant for both overweight (OR 1.13, 95% CI: 1.08-1.19) and obesity (OR 1.28, 95% CI:

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1.19-1.39) regarding overall musculoskeletal symptoms. Regarding the specific body regions,

overweight as well as obesity were associated with increased odds for symptoms. Overweight

was associated with upper and lower extremity symptoms (OR 1.10, 95% CI: 1.03-1.17; OR

1.29, 95% CI: 1.21-1.36). Obesity was associated with neck/shoulder (OR 1.12; 95% CI: 1.03-

1.21), upper extremity (OR 1.37, 95% CI: 1.25-1.50), back (OR 1.10, 95% CI: 1.01-1.20), and

lower extremity symptoms (OR 1.68, 95% CI: 1.55-1.83). Additional (full model) adjustment for

employment status (working full time/ part time), level of education, smoking status, physical

workload factors, and physical activity level, did not affect the associations.

Table 2 Cross-sectional associations between BMI and musculoskeletal symptoms

Adjusted for age and genderOverall Neck/shoulder Upper extremity Back Lower extremity

Normal weight 1.00 1.00 1.00 1.00 1.00Overweight 1.14 1.04 1.14 1.03 1.31

(1.09-1.19) (0.99-1.09) (1.08-1.21) (0.98-1.08) (1.24-1.37)Obese 1.35 1.13 1.45 1.10 1.82

(1.26-1.44) (1.06-1.22) (1.34-1.57) (1.02-1.19) (1.69-1.96)Adjusted for age, gender, smoking, education, contractual working hours(part-time/full-time), use of force, work in awkward positions, use of vibrating tools, repetitive motions, and physical activity

Normal weight 1.00 1.00 1.00 1.00 1.00Overweight 1.13 1.03 1.10 1.02 1.29

(1.08-1.19) (0.98-1.09) (1.03-1.17) (0.96-1.08) (1.21-1.36)Obese 1.28 1.12 1.37 1.10 1.68

(1.19-1.39) (1.03-1.21) (1.25-1.50) (1.01-1.20) (1.55-1.83)

Data are presented as Odds Ratios (95% confidence interval), with normal weight as reference category. Significant associations are printed in bold.

No effect modification on the association between BMI and musculoskeletal symptoms was

found for age or gender. For physical workload, effect modification was found, meaning that

the association between BMI and both overall musculoskeletal symptoms and lower extremity

symptoms differed between employees with low and high physical workload. This effect

modification was not found for neck/shoulder, upper extremity, and back symptoms. Tables 3

and 4 present the model for musculoskeletal symptoms overall and lower extremity symptoms

among employees with high as well as low physical workload. Musculoskeletal symptoms overall

and lower extremities were reported significantly more often by obese and overweight employees

with low physical workload compared to normal weight employees with low physical workload.

For high physical workload, only an association was found for obesity and lower extremity

symptoms.



2

Table 3 Prevalence of musculoskeletal symptoms across BMI categories presented separately for high and low combined physical workload

Total ‘Normal’ weight Overweight ObesePhysical workload = low N = 31,622 N = 17,709 N = 10,873 N = 3,040Overall 15,135 8,156 5,323 1,656Neck/Shoulder 8,621 4,839 2,869 913Upper Extremity 5,349 2,754 1,905 690Back 6,935 3,944 2,276 715Lower Extremity 6,317 2,982 2,422 913Physical workload = high N = 8,897 N = 4,905 N = 3,052 N = 940Overall 5,713 3,141 1,940 632Neck/Shoulder 3,231 1,778 1,101 352Upper Extremity 2,355 1,202 858 295Back 2,424 1,347 809 268Lower Extremity 3,220 1,678 1,137 405

Table 4 Associations between BMI and Overall musculoskeletal symptoms and Lower Extremity symptoms stratified for physical workload

Physical workload = high (n = 8,897)

Overall Lower extremityNormal weight 1.00 1.00Overweight 0.98 1.07

(0.88-1.09) (0.96-1.19)Obese 1.08 1.28

(0.92-1.28) (1.09-1.50)Physical workload = low (n = 31,623)Normal weight 1.00 1.00Overweight 1.17 1.38

(1.11-1.24) (1.29-1.48)Obese 1.34 1.86

(1.23-1.46) (1.69-2.05)

*Neck/shoulder, upper extremity and back ORs are not presented separately, since no effect modification was found for these body regions. The complete model is presented in Additional files 1 and 2.Data are presented as Odds Ratios (95% confidence interval), with normal weight as reference category, adjusted for age, gender, smoking, education, contractual working hours(part-time/full-time), use of vibrating tools, repetitive motions, and physical activity (full model). Significant associations are printed in bold.

Effects on the development and recovery of musculoskeletal symptoms

Table 5 presents the effects of BMI on developing musculoskeletal symptoms for employees

without symptoms at baseline. The findings on overall symptoms indicated that being obese

statistically significantly increased the risk of developing musculoskeletal symptoms during

12-month follow-up (OR 1.37, 95% CI: 1.05- 1.78). Regarding the different body regions, the

relationship also existed for lower extremity symptoms for overweight employees (OR 1.35, 95%

CI: 1.13-1.61), and for obese employees (OR 2.12, 95% CI: 1.64-2.73). For the upper extremity

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26 | Chapter 2

there was an effect of BMI on occurrence of symptoms for overweight employees (OR 1.22, 95%

CI: 1.01-1.46) and for obese employees (OR 1.51, 95% CI: 1.14-1.98). In obese employees the

OR was higher than in overweight employees, suggesting a dose–response relationship.

Table 5 Occurrence and recovery of musculoskeletal symptoms after 12 months for categories of BMI (overweight and obese), adjusted for age and gender

Occurrence (from no symptoms to symptoms)Overall Neck/shoulder Upper extremity Back Lower extremityN = 3,663 N = 5,071 N = 5,591 N = 5,085 N = 5,410

Normal weight 1.00 1.00 1.00 1.00 1.00

Overweight1.17 1.07 1.23 1.13 1.34(0.99-1.37) (0.90-1.28) (1.01-1.47) (0.95-1.35) (1.13-1.60)

Obese1.37 1.00 1.51 0.94 2.11(1.05-1.79) (0.76-1.33) (1.14-1.98) (0.69-1.28) (1.64-2.72)

Recovery (from symptoms to no symptoms)Overall Neck/shoulder Upper extremity Back Lower extremityN = 3,841 N = 2,086 N = 1,378 N = 2,005 N = 1,667

Normal weight 1.00 1.00 1.00 1.00 1.00

Overweight0.97 0.99 0.95 1.06 0.80(0.82-1.13) (0.82-1.22) (0.75-1.21) (0.86-1.30) (0.65-1.00)

Obese0.76 0.95 0.84 0.99 0.57(0.59-0.97) (0.70-1.30) (0.59-1.18) (0.73-1.33) (0.42-0.78)

Data are presented as Odds Ratios (95% confidence interval), with normal weight as reference category.

Table 6 Associations between BMI and Overall musculoskeletal symptoms and Lower Extremity symptoms

Overall Lower extremityNormal weight and low workload 1.00 1.00Normal weight and high workload 2.22 (2.06 - 2.39) 2.50 (2.31 - 2.71)Overweight and low workload 1.18 (1.11 - 1.24) 1.37 (1.29 - 1.47)Overweight and high workload 2.21 (2.02 - 2.42) 2.78 (2.53 - 3.06)Obese and low workload 1.36 (1.25 - 1.48) 1.88 (1.70 - 2.07)Obese and high workload 2.47 (2.12 - 2.89) 3.29 (2.82 - 3.82)

Data are presented as Odds Ratios (95% confidence interval), with normal weight and low workload as reference category, adjusted for age, gender, smoking, education, contractual working hours(full-time/part-time), and physical activity.



2

Table 7 Univariable and multivariable associations between BMI, workload, and BMI*workload and musculoskeletal symptoms

Univariable modelOverall Neck/

shoulderUpper extremity

Back Lower extremity

BMINormal weight 1.00 1.00 1.00 1.00 1.00Overweight 1.13 1.03 1.10 1.02 1.29

(1.08-1.19) (0.98-1.09) (1.03-1.17) (0.96-1.08) (1.21-1.36)Obese 1.28 1.12 1.37 1.10 1.68

(1.19-1.39) (1.03-1.21) (1.25-1.50) (1.01-1.20) (1.55-1.83)Combined workloadLow physical workload 1.00 1.00 1.00 1.00 1.00High physical workload 1.77 1.48 1.46 1.37 1.84

(1.66-1.88) (1.39-1.58) (1.36-1.57) (1.28-1.47) (1.72-1.97)Multivariable modelBMIOverweight 1.18 1.04 1.10 1.03 1.39

(1.12-1.24) (0.98-1.11) (1.02-1.18) (0.96-1.10) (1.30-1.48)Obese 1.34 1.14 1.41 1.11 1.86

(1.23-1.46) (1.04-1.25) (1.27-1.56) (1.00-1.23) (1.69-2.05)High physical workload 1.92 1.52 1.49 1.39 2.11

(1.77-2.08) (1.40-1.65) (1.36-1.64) (1.27-1.51) (1.93-2.30)BMI*combined workload P = 0.003 P = 0.610 P = 0.600 P = 0.950 P <0.00001Overweight*workload 0.84 0.97 0.98 0.98 0.77

(0.74-0.94) (0.85-1.09) (0.85-1.12) (0.86-1.12) (0.68-0.88)Obese*workload 0.81 0.91 0.90 0.98 0.69

(0.67-0.98) (0.76-1.11) (0.73-1.10) (0.80-1.20) (0.57-0.83)

Data are presented as Odds Ratios (95% confidence interval), mutually adjusted, and adjusted for age, gender, smoking, education, contractual working hours(part-time/full-time), use of vibrating tools, repetitive motions, and physical activity. Significant associations are printed in bold.The effect of BMI on the recovery from musculoskeletal symptoms after 12 months of follow-up is also presented in Table 5. Employees with obesity recovered less often from musculoskeletal symptoms than employees with normal weight (OR 0.75, 95% CI: 0.59 0.96). This relationship was also found for symptoms in the lower extremity (OR 0.57, 95% CI: 0.42-0.78).

Discussion

The primary aim of this study was to examine the association between BMI and musculoskeletal

symptoms in interaction with physical workload. Overall, high BMI (overweight and obesity) was

moderately associated with an increased prevalence of musculoskeletal symptoms in the past

12 months. This association was modified by physical workload. Regarding the second research

aim, our longitudinal results showed that for obese employees the association was caused by an

increased risk of developing musculoskeletal symptoms during 12-month follow-up as well as less

recovery from musculoskeletal symptoms compared to employees with normal weight.

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Lower extremity

Consistent with findings from other studies [31,32] we found the association to be strongest

for lower extremity symptoms. The most common joint diseases that cause lower extremity

symptoms are osteoarthritis (OA) and rheumatoid arthritis (RA), whereas other causes include

musculoskeletal injuries. In the literature it is also suggested that knee pain is a more persistent

type of pain, supporting the hypothesis for OA as the cause for symptoms. However, in this

cohort lower extremity symptoms were not found to be more persistent than other symptoms in

normal weight individuals (data not shown). Obesity had a significant negative effect on recovery

from lower extremity symptoms (OR 0.57). Obesity has also, among those with OA as well as in

the general population, been found to be associated with disability in mobility [32]. Therefore,

biomechanics may explain part of the contribution of the effect of excessive weight on lower

extremity symptoms.

Upper extremity, and neck/shoulder

The association between high BMI and upper extremity as well as neck/shoulder symptoms could

be supporting a non-mechanical hypothesis. This hypothesis is supported by studies showing

the association between BMI and the development of OA in non-weight bearing joints, such as

the hands [15,33], as well as the link between high BMI and other rheumatic diseases, such as

fibromyalgia [34-36]. In a study aimed at weight loss among an obese working population [37]

upper extremity symptoms (except for shoulder complaints) decreased with weight loss. In this

study it was suggested that many obese subjects use their upper extremities as weight bearing

limbs when arising from a seated position, which may account for the increased upper extremity

symptoms in obese subjects. However, this explanation is less likely for overweight (non-obese)

individuals, for whom in the present study also an association was found. For the upper extremity,

an effect of BMI on occurrence of symptoms was found, but not on recovery from symptoms.

Overall, the results on upper extremity and neck/shoulder symptoms indicate that most likely

metabolic factors are part of the underlying mechanism in the association with high BMI.

Back

Yet, in contrast to studies included in a recent meta-analysis [10] no association for overweight

and back symptoms in the past 12 months was found. The strength of the association with obesity

was modest comparable to the pooled OR from the meta-analysis (1.10 vs. 1.33). Additionally,

neither for occurrence nor recovery of back symptoms, overweight or obesity was found to be

a risk factor. The finding that workers with high BMI are not at higher risk for developing back

symptoms than workers with a normal BMI is in line with a prospective cohort study among

health care workers [38].



2

Physical workload

It has been argued that for MSD, physical workload as a risk factor itself is more important

than BMI [38]. In a study on risk factors for LBP the strength of the association with workload

and health behavior (sum of BMI, physical exercise, and smoking) was found to be age-related;

workload predicted LBP among those younger than 50 years while health behavior increased

the risk among those 50 years or older [39]. In the present study, the association between BMI

and MSD differed between employees with low and high physical workload. For musculoskeletal

symptoms overall and lower extremity symptoms the association was stronger in those with low

physical workload compared to those with high physical workload. No effect modification was

found for upper extremity, neck/shoulder, or back symptoms. Contradictory to our hypothesis, the

association of BMI and lower extremity symptoms was found to be weaker for employees with

higher physical workload. This implies that the association may not be simply due to weight related

increased excessive loading of the joint. Based on these results, it is possible that for employees

with high BMI and high physical workload, muscle mass around the knee joint is protective for

the development of MSD. Weakness of the quadriceps have been considered a primary risk factor

for knee pain and disability in persons with OA [40]. There is evidence to hypothesise that muscle

mass protects the knee joint, with increased muscle strength protecting against incidence knee

OA (greater joint stability and cartilage volume) [41]. Further support for this explanation comes

from research on functional limitations as a consequence of obesity. Increased body mass can

have negative influences on the control of postural stability and locomotion [42]. Poorer balance

was found to be associated with higher pain in the presence of less muscle strength [43]. Support

for this notion also comes from literature that shows that muscle strengthening, as a part of

treatment, reduces disability from MSD [44-46]. In addition, loss of muscle mass as well as central

obesity (not BMI) were found to be possible risk factors for LBP [47].

Methodological strengths, and limitations

The main strength of this study is the large sample that included a nationally representative

sample of the Dutch workforce. This provided sufficient statistical power to examine overweight

and obesity in association with musculoskeletal symptoms in employees for physical workload

categories, as well as different locations of symptoms.

Some limitations should be considered as well. The study is conducted in a worker population,

and when translating the results to the general population, the healthy worker (survival) effect

should be taken into account. By exploring the association in a working population it is possible

that workers, who have severe MSD, are no longer employed or change to work with lower

exposure.

In the analysis the association was controlled for several potential confounding factors, however

some potential psychosocial confounders, for instance stress, anxiety or depression disorders,

were not measured, and consequently could not be controlled for.

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The use of self-reported measures could be considered a limitation as they are susceptible to possible

bias. Self-reported workload might be biased by the presence of symptoms. In workers performing

the same job, workers with MSD reported higher exposure rates than workers without MSD [48].

However, in the present study self-reported workload was used to identify high exposure from

low exposure, with highly contrasting jobs and working conditions. Misclassification in categories

BMI, as a result of underreporting of body weight, could hypothetically lead to underestimation

of the association with MSD. Furthermore, BMI as a measure does not discriminate adipose from

non-adipose body mass, nor does it indicate the distribution of body fat. Stronger associations

with abdominal obesity than general obesity and LBP were found in population-based studies

[49]. Additional measurements of fat distribution would provide insight in possible factors of the

mechanism of the effect (posture, loading etc.).

For the first research question the cross-sectional design prevents conclusions of causality. Weight

gain may also occur as a consequence of musculoskeletal pain and physical inactivity. Therefore,

the measured BMI may not in all cases reflect BMI before the onset of symptoms. Weight gain

following the onset of symptoms (e.g. because of reduced physical activity due to symptoms)

may have caused overestimation of the associations. For the second research aim prior history (>1

year) of symptoms are not taken into account. In this study, the definition of the symptom-free

population was based on reporting no symptoms in the previous 12 months, which is considered

long enough to exclude those with frequently recurring symptoms. Selection bias may have

occurred as a result of the low response rate. Persons lost to follow-up were younger and less

often highly educated than those who responded to the follow up questionnaire. However, no

difference was found for BMI and dependent variables musculoskeletal symptoms between those

lost to follow-up and respondents.

Conclusions

In summary, in this study, BMI was associated with musculoskeletal symptoms, in particular

symptoms of the lower extremity. Furthermore, the association was stronger for employees with

low physical workload compared to those with high physical workload. Compared to employees

with normal weight, obese employees had higher risk for developing symptoms as well as less

recovery from symptoms. This study supports the role of biomechanical factors for the relationship

between BMI and MSD in the lower extremity.

With an increasing public health problem resulting from overweight and obesity, and since

overweight and obesity are a preventable or modifiable risk factor, these findings give directions

to prevention strategies. The risk on musculoskeletal health problems should be taken into

account in primary as well as secondary prevention strategies. To address MSD in a worker

population, weight loss or preventing weight gain strategies alone may not be sufficient. The



2

physical consequences of loading of major structures, particularly in the lower extremity as a

consequence of overweight and obesity deserve attention.

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12. Felson DT, Anderson JJ, Naimark A, Walker AM, Meenan RF: Obesity and knee osteoarthritis. The Framingham Study. Ann Intern Med 1988, 109:18–24.

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18. Peltonen M, Lindroos AK, Torgerson JS: Musculoskeletal pain in the obese: a comparison with a general population and long-term changes after conventional and surgical obesity treatment. Pain(Amsterdam) 2003, 104:549–557.

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20. Wearing SC, Hennig EM, Byrne NM, Steele JR, Hills AP: Musculoskeletal disorders associated with obesity: a biomechanical perspective. Obes Rev 2006, 7:239–250.



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22. Becker J, Nora DB, Gomes I, Stringari FF, Seitensus R, Panosso JS, et al: An evaluation of gender, obesity, age and diabetes mellitus as risk factors for carpal tunnel syndrome. Clin Neurophysiol 2002, 113:1429–1434.

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32. Tukker A, Visscher TLS, Picavet HSJ: Overweight and health problems of the lower extremities: osteoarthritis, pain and disability. Public Health Nutr 2009, 12:359–368.

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34. Ursini F, Naty S, Grembiale RD: Fibromyalgia and obesity: the hidden link. Rheumatol Int 2011, 31:1403–1408.

35. Mork PJ, Vasseljen O, Nilsen TIL: Association between physical exercise, body mass index, and risk of fibromyalgia: longitudinal data from the Norwegian Nord-Trondelag Health Study. Arthritis Care Res (Hoboken) 2010, 62:611–617.

36. Cordero MD, cocer-Gomez E, Cano-Garcia FJ, Sanchez-Dominguez B, Fernandez-Riejo P, Moreno Fernandez AM, et al: Clinical symptoms in fibromyalgia are associated to overweight and lipid profile. Rheumatol Int 2013. doi:10.1007/s00296-012-2647-2.

37. Hooper MM, Stellato TA, Hallowell PT, Seitz BA, Moskowitz RW: Musculoskeletal findings in obese subjects before and after weight loss following bariatric surgery. Int J Obes (Lond) 2007, 31:114–120.

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39. Miranda H, Viikari-Juntura E, Punnett L, Riihimaki H: Occupational loading, health behavior and sleep disturbance as predictors of low-back pain. Scand J Work Environ Health 2008, 34:411–419.

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41. Berry PA, Wluka AE, vies-Tuck ML, Wang Y, Strauss BJ, Dixon JB, et al: The relationship between body composition and structural changes at the knee. Rheumatology (Oxford) 2010, 49:2362–2369.

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43. Jadelis K, Miller ME, Ettinger WHJ, Messier SP: Strength, balance, and the modifying effects of obesity and knee pain: results from the Observational Arthritis Study in Seniors (oasis). J Am Geriatr Soc 2001, 49:884–891.

44. Ettinger WHJ, Burns R, Messier SP, Applegate W, Rejeski WJ, Morgan T, et al: A randomized trial comparing aerobic exercise and resistance exercise with a health education program in older adults with knee osteoarthritis. The Fitness Arthritis and Seniors Trial (FAST). JAMA 1997, 277:25–31.

45. Messier SP, Loeser RF, Miller GD, Morgan TM, Rejeski WJ, Sevick MA, et al: Exercise and dietary weight loss in overweight and obese older adults with knee osteoarthritis: the Arthritis, Diet, and Activity Promotion Trial. Arthritis Rheum 2004, 50:1501–1510.

46. Fransen M, McConnell S: Exercise for osteoarthritis of the knee. Cochrane Database Syst Rev 2008(4). doi:10.1002/14651858.CD004376.pub2.

47. Toda Y, Segal N, Toda T, Morimoto T, Ogawa R: Lean body mass and body fat distribution in participants with chronic low back pain. Arch Intern Med 2000, 160:3265–3269.

48. Hildebrandt VH, Bongers PM, Dul J, Van Dijk FJ, Kemper HC: Identification of high-risk groups among maintenance workers in a steel company with respect to musculoskeletal symptoms and workload. Ergonomics 1996, 39:232–242.

49. Shiri R, Solovieva S, Husgafvel-Pursiainen K, Taimela S, Saarikoski LA, Huupponen R, et al: The association between obesity and the prevalence of low back pain in young adults: the Cardiovascular Risk in Young Finns Study. Am J Epidemiol 2008, 167:1110–1119.

Chapter 3VIP in construction: systematic development and evaluation

of a multifaceted health programme aiming to improve

physical activity levels and dietary patterns among

construction workers

Laura Viester, Evert A. L. M. Verhagen, Karin I. Proper,

Johanna M. van Dongen, Paulien M. Bongers, Allard J. van der Beek

BMC Public Health. 2012 30;12;89

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Abstract

Background: The prevalence of both overweight and musculoskeletal disorders (MSD) in the

construction industry is high. Many interventions in the occupational setting aim at the prevention

and reduction of these health problems, but it is still unclear how these programmes should be

designed. To determine the effectiveness of interventions on these health outcomes randomised

controlled trials (RCTs) are needed. The aim of this study is to systematically develop a tailored

intervention for prevention and reduction of overweight and MSD among construction workers

and to describe the evaluation study regarding its (cost-)effectiveness.

Methods/Design: The Intervention Mapping (IM) protocol was applied to develop and implement

a tailored programme aimed at the prevention and reduction of overweight and MSD. The (cost-)

effectiveness of the intervention programme will be evaluated using an RCT. Furthermore, a

process evaluation will be conducted. The research population will consist of blue collar workers

of a large construction company in the Netherlands.

Intervention: The intervention programme will be aimed at improving (vigorous) physical

activity levels and healthy dietary behaviour and will consist of tailored information, face-to-face

and telephone counselling, training instruction (a fitness “card” to be used for exercises), and

materials designed for the intervention (overview of the company health promoting facilities,

waist circumference measuring tape, pedometer, BMI card, calorie guide, recipes, and knowledge

test).

Main study parameters/endpoints: The intervention effect on body weight and waist

circumference (primary outcome measures), as well as on lifestyle behaviour, MSD, fitness, CVD

risk indicators, and work-related outcomes (i.e. productivity, sick leave) (secondary outcome

measures) will be assessed.

Discussion: The development of the VIP in construction intervention led to a health programme

tailored to the needs of construction workers. This programme, if proven effective, can be directly

implemented.


Study design | 37

3

Background

The worldwide prevalence of overweight and obesity is increasing at a high rate. This also

affects the Dutch population, where in 2009, according to the Central Bureau of Statistics

Netherlands (CBS), more than 50% of the male population and 40% of the female population

was overweight [body mass index (BMI) ≥ 25 kg m-2] [1]. Of this population 11% of the men

and 12% of the women were obese (BMI ≥ 30 kg m-2). Excess body weight is associated with

increased mortality and morbidity rates. To illustrate, obesity has a short-term negative impact

on health, e.g. musculoskeletal disorders [2-5], as well as long-term consequences, e.g. diabetes

mellitus type II and cardiovascular disease [6,7]. In addition to health-related problems in the

individual, overweight and obesity are related to work-related measures, such as increased sick

leave and decrease of productivity [8-14]. More than 10% of sick leave and productivity loss at

work may be attributed to lifestyle behaviours and obesity [14]. Consequently, the economic

consequences of overweight and obesity are high. In the Netherlands the annual direct costs have

been estimated at €500 million, approximately 2% of the total national health care costs [15].

However, the indirect costs resulting from work absence and work disability related to overweight

and obesity are estimated at €2 billion [16].

Recent data obtained from periodic health screenings among 39,400 construction workers

showed that the prevalence of overweight and obesity in construction workers is higher than in

the general Dutch adult population. Of all construction workers 63% is overweight and 15% is

obese [17]. It is argued that within this specific population negative health-related lifestyle factors

(e.g. low levels of daily life physical activity, smoking, and dietary patterns) are more prominently

present than in the general population. Furthermore, the average age of construction workers

has been steadily increasing in the past decade, and will do so in the decade ahead. As a result,

employee health is an important concern for the construction industry, both from a corporate

social responsibility as well as a risk management view. Fit and healthy employees working in

a healthy environment are of critical importance to realise organisational goals. Operating in

a highly competitive business environment with increasing pressure on the labour market, and

an aging workforce, employers are becoming aware that they need to implement measures to

improve productivity and efficiency, and to invest in the health of their employees.

Workplace health promotion has been shown to play a major role in achieving such outcomes;

directly by educating the workforce and providing opportunities for physical activity, and indirectly

by influencing social norms [18]. Workplace health promotion may constitute of a diverse set of

health promoting activities, such as periodic health screenings (PHS), courses in smoking cessation,

and enhanced access to physical activity. Many employers are offering such fringe benefits to their

employees. However, the health enhancing effects of these facilities are not yet identifiable and it

remains unclear whether the actual group of workers at risk is being reached. It has been argued

that these facilities are predominantly used by the healthy part of the workforce. Therefore, in

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38 | Chapter 3

order to increase effectiveness it is crucial to provide a supporting health promotion programme

that promotes the utilisation of the offered health enhancing facilities by employees with lifestyle-

related risk factors for disease. The overall aim of this study is to develop and evaluate such

a supporting health promotion programme (VIP in Construction). More specifically the current

study aims to systematically develop a tailored intervention programme for the prevention and

reduction of overweight and musculoskeletal disorders (MSD) in construction workers and to

describe the evaluation study regarding the (cost-)effectiveness of this programme.

Methods

The present study consists of 2 phases. In the first phase a health enhancing intervention was

developed, tailored specifically to the possibilities, needs and wishes of the management and

employees of the participating construction company. The second phase of this study involves the

evaluation of the intervention.

The “VIP in construction” intervention was systematically designed based on the Intervention

Mapping (IM) protocol [19]. IM describes a process for developing theory- and evidence-based

health promotion programmes, and involves a systematic process that prescribes a series of

six steps: (i) performing a needs assessment; (ii) defining suitable programme objectives; (iii)

selecting theory-based intervention methods and practical strategies; (iv) producing programme

components and materials; (v) designing an implementation plan; and (vi) designing an evaluation

plan (Figure 1). Collaboration between the developers, the users of the intervention and the

target population is a basic assumption in the IM process [19]. This paper describes in detail the

development of a health enhancing intervention programme for construction workers by using

the steps of the IM process. Step 6 of the process describes in detail how the (cost-) effectiveness

of the developed programme will be evaluated.


Study design | 39

3

Figure 1 Steps of the Intervention Mapping process.

Phase 1: Intervention development

Step 1: Needs assessment

Literature was reviewed and interviews, questionnaires, and focus group interviews with

management, employees and other stakeholders were carried out. This provided insight into

the ruling health issues, underlying risk factors (behaviour and environmental conditions), and

determinants of the underlying behaviours. In addition, the reach, success and failure factors of

current company health promotion activities were summarised. This needs assessment results in

the formulation of programme outcomes.

Health problem and target group

The target group for this intervention was specified as all blue collar workers of a construction

company. From interviews with the management of the company and from information obtained

from Occupational Health Services (OHS) reports it was concluded that the main health concerns

for the target population are overweight and MSD. In general, in the construction industry MSD

are the primary reason for long-term sickness absence and disability [20,21]. Also the company

records show that long-term sickness absence among blue collar workers is mainly caused by

MSD.

Especially in professions with heavy physical demands, such as those in the construction industry,

muscle fatigue or musculoskeletal discomfort may be perceived during work and may eventually

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40 | Chapter 3

result in musculoskeletal pain [22]. Several work-related physical factors have been identified

that can increase the risk of musculoskeletal pain among workers [22-27]. Besides work-related

factors, health-related factors, such as obesity may play a role in musculoskeletal pain. Findings of

a meta-analysis on the association between obesity and low back pain indicate that overweight

and obesity increase the risk of low back pain [5]. In a cohort study of construction workers [28]

it was found that MSD represent the most frequent cause of work disability and that obesity

increased this risk. Since overweight and MSD are possibly associated, the intervention will aim at

addressing these health problems together.

Key determinants & risk factors for overweight and MSD

Literature was reviewed to identify which theoretical constructs best predict overweight and MSD.

Energy-balance-related behaviour is an important factor to consider in the development of

health interventions aiming at healthy lifestyle. Weight gain, overweight, and obesity have

been associated with various specific behaviours related to diet and physical activity. Risk factors

for obesity are considered to be: sedentary lifestyles (i.e., time spent sitting), a high intake of

energy-dense high-fat and low-fiber diet, consumption of sugar-sweetened soft drinks, frequent

snacking, and large portion sizes [29,30]. Protective factors against obesity are considered to be:

regular physical activity and consumption of a high-fiber diet (for instance, a diet high in fruits

and vegetables) [29,30].

MSD have a multifactor origin, several work-related and non work-related risk factors contribute

to their development [22,31,32]. According to the model of workload and capacity by Van

Dijk et al. [33], health effects may result from an imbalance between workload and capacity.

A prospective study of Hamberg-van Reenen et al. (2006) [34] confirmed that an imbalance

between physical capacity and exposure to work-related physical factors was a risk factor for

future musculoskeletal pain. For example, it is generally assumed that for workers with high

muscle strength, high exposure to physical factors may result in less musculoskeletal pain than

for workers with low muscle strength [35].

Questionnaire and focus group interviews

In order to be relevant, the intervention needs to account for the lifestyle habits and preferences

of the target group. Therefore, to obtain information on specific dietary and physical activity

behaviour in the target group, a short questionnaire was completed by a sample of 42 construction

workers. These specific behaviours were further discussed in the focus group interviews. The

aims of the focus groups were: identifying the main and modifiable determinants of the lifestyle

behaviours (physical activity and diet), risk factors for MSD, and the reach and participation of

the current company health promoting activities. Also, input from the focus group interviews was

used to determine the content and design of the intervention. A total of 8 focus group interviews


Study design | 41

3

with construction workers (n = 62) were carried out. The focus group interviews were held at

different worksites of the company to reach workers from different professions, and participants

were randomly selected to avoid getting input only from workers who are already motivated to

participate in health programmes.

Risk factors and determinants for the health problems

Health beliefs and health behaviours related to diet and physical activity were discussed in focus

group interviews. From the focus group interviews it could be concluded that workers have some

basic knowledge of nutritional standards, but they are not aware of their personal intake levels.

The methods most often listed by the construction workers to improve their energy balance

were less snacking and reducing alcohol consumption. Further solutions mentioned: decreasing

intake of sugar-sweetened beverages or replacing them with healthier options, increasing fruit

intake, and decreasing dinner portion size. From the focus group interviews we also learned that,

in general, the workers’ partner mainly determines the food choice at home, and the workers

preferred to get personalised information on diet, as opposed to general information.

The interviewed workers indicated that they believed that their work activities provided enough

physical activity. However, from periodic health screening data [17] it is clear that a substantial

percentage of workers still do not reach healthy levels of physical activity according to the

Nederlandse Norm Gezond Bewegen (NNGB) (33%) and the guideline to achieve a good fitness

level (Fitnorm) (80%). According to physical activity guidelines these levels should be achieved to

improve and maintain health [36].

Workplace physical demands, such as manual material handling (lifting heavy objects), extreme

weather and workplace conditions (uneven terrain, awkward working postures), work pace and

planning were most mentioned to be risk factors at work for developing MSD. Also behavioural

risk factors were mentioned, such as not taking enough rest-breaks during work, wrong work

posture, and wrong use of (ergonomic) work aids. A social/managerial factor that was considered

important was poor communication between supervisors and the workers concerning problems

or solutions for prevention or reduction of MSD in combination with perceived barriers for

addressing those problems.

Intervention input from focus group interviews

Although poor physical fitness was not frequently mentioned as one of the risk factors for MSD

in the focus groups, improving physical capacity was mentioned as a possible preventive measure

or solution. According to the literature increasing vigorous physical activity (PA) is a preventive

method that targets body weight control as well as MSD [37-42]. Strong evidence was found

for the effectiveness of workplace physical activity programmes in increasing strenuous physical

activity levels as well as in preventing MSD [43].

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To design a feasible intervention programme, the reach of current company health promoting

activities and the requirements and design for an intervention programme were also discussed in

focus group interviews. From the interviews amongst employees it could be concluded that the

current health promoting activities were not optimally reaching the workers. The most important

reason indicated by the interviewees was that workers were not aware of the present prevention

practices, i.e. that these were not communicated in the right way. Also those who were aware of

the possibilities (e.g., the reduction of gym membership fees) were often under the impression

that these measures were mainly initiated for office workers of the company. From the interviews

it became clear that communicating the health promoting activities in a suitable manner for the

target group should be an important objective for the intervention programme.

Furthermore, workers were asked about the necessary requirements and design for an intervention

programme in order to reach non-participants and motivate them to participate in prevention

programmes. Workers argued that an intervention programme should focus on communicating

personal health risks, since perceived health was considered to be a necessary motivator for

changing behaviour. From the focus group interviews we learned that the regular company

periodic health screening (PHS) was generally seen as a positive starting point for discussing

lifestyle. However, during the PHS there is often not enough time to discuss the outcomes. It

became clear that linking the intervention to the PHS could improve participation to worksite

health promoting activities.

Programme objectives and outcomes

The needs assessment indicated that the intervention should address both dietary habits and

physical activity with the overall programme objective being the prevention and reduction of

overweight and MSD among construction workers. In addition, to specifically target and prevent

MSD by improving physical capacity, workers could be stimulated to increase their general physical

activity by means of specific exercises, sports, and daily physical activities during leisure time.

Based on literature and focus group input, intervention strategies to prevent or reduce MSD could

focus on (1) increasing physical capacity by improving general physical activity or specific exercises

and/or (2) decreasing workload. However, there was no management support for implementing

strategies aimed at decreasing workload. The management indicated that other company

projects have already started considering physical workload; therefore decreasing workload is not

a programme objective for the VIP in construction intervention.

The risk behaviours described in the needs assessment were translated into health-promoting

behaviours. The health behaviours that should be targeted were then formulated in programme

outcomes of the VIP in construction intervention, and are presented in Table 1.


Study design | 43

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Table 1 Programme outcomes

Programme outcomes1) Energy intake quantity: Workers reduce their energy intake by decreasing portion size and alcohol consumption

2) Energy intake quality:Workers replace energy dense products by healthier options (fibre rich products and beverages without sugar)

3) Energy output quantity:Workers increase their levels of physical activity

4) Energy output quality:Workers perform specific exercises to prevent or reduce MSD

Step 2: Performance objectives, determinants, and change objectives

Step 2 provides the foundation for the intervention programme by specifying who and what will

change as a result of the intervention. The product of this step is a set of matrices that combines

performance objectives with selected personal and external determinants to produce the target

of the intervention (change objectives).

Performance objectives

The programme outcomes formulated in the needs assessment were translated into performance

objectives: what do the participants have to do to accomplish these outcomes? Based on the

self-regulation theory and determinants for behaviour obtained from literature and focus group

interviews, performance objectives were stated for each of the programme objectives. As an

example, the performance objectives for the third programme objective are illustrated in Table 2.

Table 2 Performance objectives

Performance objective related to Programme Outcome 3: “Workers increase their levels of physical activity”

Workers should:1) Self-monitor physical activity2) Set goals to increase physical activity levels3) Form implementation intentions4) Implement healthy levels of physical activity5) Evaluate personal goals

Determinants of behaviour change

IM states that for health promotion intervention development, instead of searching for predictors

of present behaviour, health-related behaviour (e.g. high energy intake) should be translated

into a health-promoting behaviour or behaviour change (e.g. energy intake reduction) and then

search for determinants of the required change. The determinants for the performance objectives

in this study were based on literature review and focus group interviews and were selected on

importance and changeability for the specific target group. The following personal and external

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determinants for physical activity were identified: skills, self-efficacy, attitudes, barriers, habits,

outcome expectations, resources, awareness, risk perception, and health beliefs. For dietary

behaviour, the following personal and external determinants were selected for this intervention:

knowledge, awareness, risk-perception, health beliefs, habits, and social support. The conceptual

model of the VIP in construction intervention is described in Figure 2.

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Change objectives

Change objectives were created by crossing performance objectives with determinants in a

matrix. An example of the matrix for performance objective 3 is given in Table 3.

Table 3 Selected change objectives for performance objective 3

Performance Objectives Skills and self-efficacy Awareness and attitudes Outcome expectationsPO.3. “Workers increase their levels of physical activity (by increasing PA of vigorous intensity and decreasing sitting time)”

A.3 Express positive attitude towards increasing levels of physical activity

OE.3.Expect that increasing levels of physical activity will have positive health outcomes

PO.3.1 Self-monitor physical activity

SSE.3.1 Know how to self-monitor PA

A.3.1 Express positive attitude towards self monitoring of PA

PO 3.2.Set goals to increase physical activity levels

SSE.3.2 Express confidence for setting goals to increase PA levels

A.3.2 Express positive attitudes towards goal setting

OE.3.2. Expect that goal setting will increase PA levels

Step 3: Methods and strategies

After constructing the change matrices, the next step was to select appropriate theoretical

methods for behaviour change and to translate these into practical strategies.

Theory-based intervention methods

For each determinant (e.g. self-efficacy, skills, knowledge, social support) appropriate theoretical

methods were identified from literature and from guidance of Bartholomew et al. (2006) [19].

Theoretical input for these methods and strategies was derived from behavioural theory literature.

This includes health behaviour models (theory of planned behaviour (TPB) [44] and the health

belief model (HBM) [45]) as well as behaviour change models (transtheoretical model (TTM) [46]

and the precaution adoption process model (PAPM)[47]). Decisions about suitable strategies were

made based on feedback of key contacts within the organisation, and focus group data. These

were then translated into strategies suitable for implementation in the workplace. The results of

this step are presented in Tables 4 and 5.

R1R2R3R4R5R6R7R8R9


46 | Chapter 3

Tab

le 4

Met

ho

ds

and

str

ateg

ies

sele

cted

fo

r d

ieta

ry b

ehav

iou

r (p

rog

ram

me

ou

tco

mes

1&

2)

Det

erm

inan

tTh

eore

tical

Met

hods

Stra

tegy

Tool

s/ M

ater

ials

a) P

erso

nal

Kn

ow

led

ge

Pass

ive

lear

ning

/ pro

vidi

ng

info

rmat

ion

Prov

idin

g w

ritte

n an

d/or

ver

bal

info

rmat

ion

Tailo

red

broc

hure

s

Act

ive

proc

essi

ng o

f in

form

atio

nK

now

ledg

e te

sts

Aw

aren

ess

of

per

son

al in

take

le

vels

Self-

eval

uatio

n C

ompa

ring

inta

ke in

rel

atio

n to

st

anda

rds

Wor

kshe

et s

elf-

test

on

heal

thy

stan

dard

s

Feed

back

Feed

back

on

inta

ke le

vels

Pers

onal

fee

dbac

k PH

CH

abit

sIm

plem

enta

tion

inte

ntio

ns (g

oal

sett

ing)

Form

ulat

ion

of s

peci

fic p

erso

nal

inte

ntio

nsPH

C a

ssis

ts in

for

mul

atin

g pr

actic

al g

oals

+

PEP

for

m

Aw

aren

ess,

ris

k p

erce

pti

on

&

hea

lth

bel

ieve

sIn

form

atio

n ab

out

pers

onal

ris

kPe

rson

aliz

ed r

isk

feed

back

fro

m

heal

th s

cree

ning

Expe

rt m

onito

ring

and

eval

uatio

n of

BM

I, w

aist

circ

umfe

renc

e, b

lood

pre

ssur

e,

beha

viou

r et

c. in

rel

atio

n to

hea

lthy

stan

dard

s (P

HC

)

Scen

ario

-bas

ed r

isk

info

rmat

ion

Prov

idin

g ta

ilore

d ris

k in

form

atio

n on

lo

ng-t

erm

eff

ects

and

info

rmat

ion

on

bene

fits

of h

ealth

y be

havi

our

Tailo

red

broc

hure

s

Re-e

valu

atio

n, s

elf-

eval

uatio

n,

and

cons

ciou

snes

s ra

isin

g A

war

enes

s of

ow

n bo

dy c

ompo

sitio

n by

sel

f-m

onito

ring

Wai

st c

ircum

fere

nce

mea

surin

g ta

pe B

MI

card

Del

iver

ing

info

rmat

ion

on t

he

rela

tions

hip

betw

een

calo

ries

& P

AC

alor

ie g

uide

(# m

in P

A r

equi

red

to lo

se a

ce

rtai

n am

ount

of

calo

ries)

b) E

xter

nal

Soci

al s

up

po

rtM

obili

sing

soc

ial s

uppo

rt f

rom

sp

ouse

/fam

ilyPr

ovid

ing

heal

thy

reci

pes

tailo

red

to

targ

et p

opul

atio

n Te

st r

ecip

es


Study design | 47

3

Tab

le 5

Met

ho

ds

and

str

ateg

ies

sele

cted

fo

r PA

(p

rog

ram

me

ou

tco

me

3&4)

Det

erm

inan

tTh

eore

tical

Met

hods

St

rate

gyTo

ols/

Mat

eria

lsa)

Per

sona

lSe

lf-

Effi

cacy

Goa

l set

ting

Form

ulat

ion

of im

plem

enta

tion

inte

ntio

nsW

orks

heet

(PEP

for

m) +

PH

C a

ssis

ts in

go

al s

ettin

g

Rein

forc

emen

tEv

alua

tion

of c

hang

e pr

oces

sFo

llow

-up

cont

acts

PH

CA

ttit

ud

esFe

edba

ck

Prov

ide

pers

onal

fee

dbac

k PH

C p

rovi

des

feed

back

on

(per

ceiv

ed)

posi

tive

cons

eque

nces

of

PA

Skill

sG

uide

d pr

actic

eIn

stru

ctio

n/sk

ills

trai

ning

Trai

ning

inst

ruct

ion

exer

cise

car

d (c

ore

stab

ility

& s

tren

gth)

Hab

its

Impl

emen

tatio

n in

tent

ions

(goa

l se

ttin

g)Fo

rmul

atio

n of

spe

cific

per

sona

l in

tent

ions

Wor

kshe

et (P

EP f

orm

) + P

HC

ass

ists

in

goal

set

ting

Aw

aren

ess,

ris

k p

erce

pti

on

&

hea

lth

bel

ieve

sIn

form

atio

n ab

out

pers

onal

ris

kPe

rson

aliz

ed r

isk

feed

back

fro

m

heal

th s

cree

ning

Expe

rt m

onito

ring

and

eval

uatio

n of

BM

I, w

aist

circ

umfe

renc

e, b

lood

pre

ssur

e et

c.

in r

elat

ion

to h

ealth

y st

anda

rds

Scen

ario

-bas

ed r

isk

info

rmat

ion

Prov

idin

g ris

k in

form

atio

n on

long

-te

rm e

ffec

ts a

nd in

form

atio

n on

be

nefit

s of

hea

lthy

beha

viou

r

Tailo

red

broc

hure

s

Re-e

valu

atio

n, s

elf-

eval

uatio

n,

and

cons

ciou

snes

s ra

isin

g A

war

enes

s of

ow

n en

ergy

bal

ance

(P

A) b

ehav

iour

Pedo

met

er

Del

iver

ing

info

rmat

ion

on t

he

rela

tions

hip

betw

een

calo

ries

& P

AC

alor

ie g

uide

(ene

rgy

bala

nce

info

rmat

ion

# m

in P

A r

equi

red

to lo

se c

alor

ies)

b) E

xter

nal

Perc

eive

d p

hys

ical

en

viro

nm

ent

Prom

otio

n/fa

cilit

atio

nPr

ovid

ing

info

rmat

ion

on w

orkp

lace

he

alth

pro

mot

ion

PHC

pro

vide

s (c

onta

ct) i

nfor

mat

ion

on t

he

com

pani

es f

acili

ties

and

cost

red

uctio

n

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48 | Chapter 3

Practical strategies

Literature was reviewed to identify which strategies are most frequently found as part of

successful interventions aimed at increasing (vigorous) physical activity and improving dietary

habits. Synergies between diet and exercise in modifying body composition have been reported

[48,49]. Furthermore, a combination of interventions on physical activity and dietary habits were

found to be more (cost-)effective than interventions on physical activity alone [50].

A review on determinants of participation in worksite health promotion programmes showed

that programmes that offer a multi-component strategy and focus on multiple behaviours have a

higher overall participation level [51]. When targeting multiple lifestyle behaviours, identifying an

individual’s stage-of-change on behaviour can help to determine which behaviours an individual

should be targeted for change (at various points) in the intervention [52]. The stage-of-change

construct can facilitate tailoring of interventions by matching intervention strategies to individuals’

motivational readiness. Furthermore, in weight management in which multiple diet and activity

changes can achieve weight change, individuals may be more motivated to change some specific

behaviours than in others. Therefore, participants should be able to choose which behaviour they

intend to change.

A strategy for increasing risk awareness could be feedback on health screening. The review

of Soler et al. 2010 [53] indicates that assessment of health risks with feedback is useful as a

gateway intervention to a broader worksite health promotion programme that may include a

set of health promotion activities to improve the health of employees. The workers indicated

in the focus group interviews that there often is no sufficient follow-up or feedback during or

after the PHS. Standardised follow-up is available only in the case of high risk (for example high

blood pressure). Also, as a preventive measure, feedback and personal information could be very

important to induce behaviour change [54,55]. This was also found to be effective in construction

workers [56]. Therefore, personal counselling with extra feedback for behaviour change should

be an important element of the intervention.

Step 4: Producing programme components and materials

In this step of the IM process methods and practical strategies are translated into programme

components and materials. The starting point of the intervention should be informing the

employees about the company health promotion activities. Personal health coaching and

information materials should be added to the current health promoting activities of the company

to include all determinants of the formulated programme objectives.


Study design | 49

3

Programme description

The intervention will take place during a 6-month period and will consist of materials and

tailored information on physical activity and diet, personal health coaching (PHC), and training

instruction. Both the PHC protocol and specific materials were developed to be able to connect

the intervention to the PHS and tailor the intervention to the needs (individual risk factors) and

wishes of the participants. Based on the baseline measurements and questionnaires a quick scan

will be applied to tailor the intervention to the participants. Tailoring variables will be health

indicators (BMI and waist circumference), current lifestyle behaviour (physical activity) and stage-

of-change (for physical activity as well as dietary behaviour).

Programme materials

The programme materials were made attractive and recognisable for the target group by using a

standard lay-out and logo. The “VIP in Construction toolbox” will consist of tailored brochures,

a calorie guide, a pedometer, a BMI card and waist circumference measuring tape, recipes and

a knowledge tests, an overview of the company health promoting facilities, PEP forms, and

an exercise card. The exercises will consist of strengthening and stabilization exercises for the

abdominal and dorsal muscles and will be well described on an exercise card. The exercises

should be performed 3 times a week. The participants will receive instruction for the use of the

exercise card from the PHC. The exercises on the card should be easily fitted in daily life routines;

participants should be able to perform the exercises at home, and without any use or purchase of

materials which potentially enhances compliance.

PHC

The coaching contacts will specifically aim at the programme outcomes as formulated in the

needs assessment. The coaching contacts will consist of the following elements: 1) feedback, 2)

goal setting, 3) feedback on formulated goals, 4) instructions for self-monitoring, and 5) training

instruction.

1) The participants will receive additional feedback on their health screening and current lifestyle

behaviour.

2) The PHC will support in goal setting, by helping the participants in formulating a personal

motivation and action plan. These plans will contain physical activities, healthy food choices or a

combination. Participants will be encouraged to target behaviour that is not at the desired level.

Questions will be asked on what participants want to change, and they will be asked to formulate

and write down specific goals and strategies to change the behaviour. In addition, information

about the company’s health promoting activities will be given and the intervention materials will

be distributed and clarified.

3) Feedback on formulated goals will be given during the follow-up contacts. The PHC will keep

a record of the goals and plans of the participant; in the follow-up contacts these goals should be

evaluated. Possible barriers should be discussed and/or new goals should be formulated.

R1R2R3R4R5R6R7R8R9


50 | Chapter 3

4) Participants will receive instructions for self-monitoring by using the PEP forms and materials.

5) The PHC will give instructions how to use the exercise card.

During the intervention, participants will be coached face-to-face in formulating their personal

motivation and action plan. Follow-up contacts (feedback and motivating) will be conducted by

telephone. The number and duration of contacts will vary with the outcome of the quick scan,

with a minimum of 2 and a maximum of 4 contacts. The number of contacts (A, B, C) will be

determined by a participant’s stage-of-change (for physical activity as well as dietary behaviour).

An overview of the contacts is given in Table 6. A web-based system will be used to register

the participants’ appointments, follow-up contacts, and content of the contacts (goals & action

plans).

Table 6 Coaching contact schedule

PHC contacts

2 weeks after baseline measurements

1 month 2 months 3 months 4 months

AIntake (60 min face-to-face)

Follow-up 1: (30 min; telephone)



BIntake (60 min face-to-face)



CIntake (30 min face-to-face)

Follow-up 1: (10 min telephone)

Step 5: Adoption & implementation plan

The product of step 5 is a plan for accomplishing programme adoption and implementation

by influencing behaviour of individuals who will make decisions about adopting and using the

programme and the individuals who deliver the programme.

Company involvement

To gain insight into facilitating factors and possible barriers regarding the adoption and

implementation, management and (potential) users of the programme were interviewed. The

human recourse management was involved in the programme development from the start

to ensure top-down adoption in the organisation and increase of the chance of long-term

implementation. During the intervention period the process will be monitored for unforeseen

difficulties and possible barriers in adoption. Also a communication plan was written for the

company. The main goal of this communication plan was to inform the target group and the

management about the project and to obtain support from the direct management.


Study design | 51

3

Participants’ compliance (important factors to encourage the adoption of the

intervention by the participants)

To decrease barriers for participation, communication to the participants will be performed in

cooperation with their employers, to show company involvement and support for the programme.

Furthermore, the invitation to the study will be done simultaneously with the invitation to the

PHS, to adapt the programme to the regular procedures. To make participation feasible for the

participants the follow-up measurements as well as the first face-to-face contact with the coach

will take place at the worksite and during work hours.

In the planning of the programme, the planning of regular health screening was taken into

consideration. Based on de schedules of the health screening, it was decided that the recruitment

for the intervention should last at least 12 months, to ensure exposure to all the companies’

business units, and worker age groups.

The participating occupational physicians (OP) and nurses received instructions during a kick-off

meeting as well as by e-mail and telephone, as they will have an important role in linking the

intervention to the PHS and motivating the workers to participate. To ensure that a standardised

protocol will be used by the PHCs, all coaches received a manual describing the protocol and

goals for the coaching sessions in detail. Just before the start of the intervention a training session

will be held.

Phase II evaluation

Step 6: Evaluation plan

Study design

The effectiveness of the programme will be measured by performing an RCT. Participants will

be measured at baseline (T0), at 6 months (T1), and at 12 months (T2). Consenting participants

will be randomised to the intervention or control group after the baseline measurement. The

control group will receive care as usual and will only be contacted for the baseline and follow-

up measurements. The study design and procedures have been approved by the Medical Ethics

Committee of the VU University Medical Centre.

Study population and setting

The research population will consist of all blue collar workers of a construction company. This will

include construction site workers as well as factory workers of the company. The recruitment of

participants will be conducted through the usual communication channels of the company at a

non-compulsory PHS.

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52 | Chapter 3

Power calculation

Sample size was based on detecting a difference in change in body weight between the

intervention and the control group. In each group (intervention and control) 130 participants

will be needed, based on a power of 80% and an alpha of 5%, and an expected weight loss of

1.5 kg (sd 4.3 kg) as result of the intervention. The used standard deviation was subtracted from

previous work from our research group, studying construction workers [56]. Taking into account

a loss to follow-up of 20%, 324 workers should be included in this study.

Randomisation

Randomisation will take place at an individual level. After baseline measurements the participant

will be randomly assigned to either the intervention or the control group by a computer generated

list using SPSS (version 15). The randomisation will be prepared and performed by an independent

researcher (i.e. the research assistant).

Measurements

Assessment of the study parameters will be done using a combination of questionnaires and

physiological measurements. Part of the study parameters will be obtained from physical

examinations and questions on outcome measures are based on questions used for the PHS

survey in the construction industry. In the Netherlands, this survey is widely used and tested on

validity among construction workers who participate in PHS.

Together with the invitation for this company PHS, all workers will receive a brochure about the

study, an informed consent form, and an additional questionnaire in order to measure those

variables not included in the PHS. For each study parameter, the following paragraphs describe

how it will be measured for this study.

Primary outcome measures

Body composition

Body weight and BMI: Body weight and height will be measured at the OHS by the occupational

physician or the assistant during the PHS. Weight will be measured using a digital weight scale.

Body weight and height will be measured with the participants standing without shoes and heavy

outer garments. Data on body weight and height will be used to calculate Body Mass Index (BMI)

(kg/m2).

Waist circumference: BMI does not give insight into body fat distribution; therefore waist

circumference will be measured as an indicator of health risks associated with visceral obesity

[57]. Waist circumference will be measured during the PHS by the OP or assistant as midway

between the lower rib margin and the iliac crest with participants in standing position at the

end of expiration [58]. To standardise waist circumference measurement, OPs and assistants


Study design | 53

3

will be provided with a Seca 201 waist circumference measure (Seca, Hamburg, Germany) and

measuring protocol.

Secondary outcome measures

Musculoskeletal disorders (MSD)

The prevalence of MSD will be assessed using questions derived from the PHS. Using a dichotomous

scale (yes/no), questions relate to the prevalence of regular pain or stiffness in both the upper and

lower extremity regions. Additionally, using the validated Dutch Musculoskeletal Questionnaire

[59], the prevalence of MSD during the past three months will be measured for the different body

regions. The intensity of pain will be measured using Von Korff scales [60]. Workers will be asked

to indicate their intensity of pain (i.e. average pain and worst pain experienced) on an 11-point

numerical scale (0–10).

Energy balance-related behaviour

Physical activity: The frequency of vigorous activities will be obtained from the PHS questionnaire

and moderate physical activity will be assessed by the number of days per week moderate

intensity activities are performed (such as walking and cycling) for at least 30 minutes. These

questions relate to international physical activity guidelines [61] as well as to the Dutch guidelines

[62]. Additionally, the validated Short Questionnaire to Assess Health enhancing physical activity

(SQUASH) will be applied [63]. The SQUASH measures duration, frequency and intensity of

different domains of physical activity (active work transportation, occupational physical activity,

household activities, and leisure time activities). Data from the SQUASH will be expressed as

energy expenditure in METminutes per week.

As a complementary method, physical activity and sedentary behaviour will be assessed objectively

using accelerometers in a random sample of 50 participants of both the intervention (n = 25)

and control group (n = 25). This random sample will wear an accelerometer (Actigraph) during 7

consecutive days. The accelerometer will register the actual physical activity during and outside

work hours.

Dietary intake: Alcohol consumption will be obtained from the PHS questionnaire asking

participants to report their average consumption (in glasses per week). Portion size at dinner,

number of beverages and slices bread, as well as consumption of energy dense snacks will be

assessed using questions that were also used in the Health under Construction study [64]. Average

weekly intake and daily portions of several food groups during a usual week during the past

month are indicated in these questions. Fruit and vegetable consumption will be measured using

the validated Short Fruit and Vegetable questionnaire (validity r = 0.50) [65]. The number of days

per week and the number of daily servings of fruit, vegetables and fruit juice will be measured

using five items on citrus fruit, other fruits, cooked vegetables, raw vegetables, and fruit juice.

R1R2R3R4R5R6R7R8R9


54 | Chapter 3

Determinants of energy balance-related behaviour

The intervention will aim at improving energy balance-related behaviour (physical activity and

dietary behaviour). Personal coaching and feedback will be tailored to self-efficacy and stage-

of-change. Therefore, it is necessary to measure these constructs for physical activity and dietary

behaviour. Based on models of behaviour and behaviour change, questions will be asked

on knowledge, attitudes, self-efficacy and stage-of-change for physical activity and dietary

behaviours [46,47].

Health-related measures

Self-reported Physical Functioning: Subjective physical functioning will be measured using the

RAND-36 [66,67]. The RAND-36 health survey is a widely known and reasonably reliable and

valid measurement of health-related quality-of-life [68]. The RAND-36 consists of 36 questions,

with clusters of: physical functioning, social functioning, role limitations (physical problem), role

limitations (emotional problem), mental health, pain, general health perception, and health

change. In the present study, the validated Dutch version will be used.

Fitness: Although maximal volume of oxygen consumption (VO2max) is considered the gold-

standard for measuring aerobic capacity, its measurement requires strict protocols and trained

personnel. For this study fitness will be measured by using a non-exercise test estimation model

including age, BMI, resting heart rate, and self-reported physical activity [69,70].

Cardiovascular disease (CVD) risk profile: CVD risk profile will be assessed using the European

Systematic Coronary Risk Evaluation (SCORE) [71]. The SCORE is based on the CVD risk variables

smoking, systolic blood pressure, and blood cholesterol levels (either total cholesterol or the ratio

total/HDL cholesterol). All variables will be measured by the OP or the assistant during the PHS.

Blood cholesterol (mmol/l) will be measured by taking a venous blood sample. The SCORE will be

filled in based on blood pressure and cholesterol levels, as assessed in the medical examination

and smoking behaviour as assessed in the PHS questionnaire.

Work-related measures

Workplace productivity loss: Sickness absence data (work absenteeism) will be collected from

company records. Presenteeism (reduced productivity while at work) will be measured using the

WHO Work Performance Questionnaire (WHO-HPQ) [72,73] and the PROductivity and DISease

Questionnaire (PRODISQ) [74]. Participants will be asked to complete these questionnaires at 3,

6, 9, and 12 months.

Work ability: For companies work ability is an indicator of the productivity of its own human

resources. Work ability will be assessed by the Work Ability Index as measured in the PHS

questionnaire.

Work engagement, work satisfaction & vitality: Vitality will be assessed by the six items of

the Utrecht Engagement Scale (UWES) that refer to high levels of energy and resilience, the


Study design | 55

3

willingness to invest effort, not being easily fatigued, and persistence in the face of difficulties

[75]. In addition, work related measures such as organisational commitment and work satisfaction

will be evaluated.

Use of company facilities: Since the intervention aims to increase the use of company health

promoting facilities (e.g. company sponsored fitness), the use of these facilities will be reported

by the participants at 6 and 12 months.

Cost measures

Intervention costs: These include the costs for the “VIP in Construction toolbox” and the PHC.

PHC costs include costs for the health coach, housing costs, costs for printed materials, and travel

expenses of the PHC. Since the PHC contacts will take place during work hours, the costs of lost

productivity due to the intervention will be included as well. Coaches will record the frequency

and duration of the face-to-face and telephone contacts. Intervention costs will be valued using

a bottom-up approach.

Other workplace health promotion costs: The use of company facilities will be valued using

invoices of contractors.

Health care costs: These include care by the general practitioner, allied health care, medical

specialist, complementary and alternative medicine, hospitalisation, and medications. Data on

resource use will be collected at a three monthly basis using retrospective questionnaires. Dutch

standard costs will be used to value health care utilization [76]. If these are not available, prices

according to professional organisations will be used. Medication use will be valued using unit

prices provided by the Dutch Society of Pharmacy [77].

Productivity-related costs: Workplace productivity losses (i.e. work absenteeism and presenteeism)

will be valued using salaries of the participants when using the employer’s perspective and using

average salaries per gender and five-year age group when using the societal perspective.

Participant costs: Since the intervention stimulates participants to engage in regular physical

activity, self-reported costs related to sports activities (membership fees and sports equipment

costs) will be collected on a three monthly basis.

Effect analysis

The effectiveness of the lifestyle intervention will be assessed using a regression analysis with

the outcome measures at follow-up (6 months and 12 months) as the dependent variables and

adjusting for the baseline levels of the outcome measure. Both crude and adjusted analyses will

be performed. Linear and logistic (longitudinal) regression analyses will be performed using SPSS

18.0 (SPSS Inc. Chicago, Illinois, USA). According to the intention-to-treat principle, all available

data of the participants will be used for data analysis. For all analyses, a two-tailed significance

level of <0.05 will be considered statistically significant.

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56 | Chapter 3

Process evaluation

A process evaluation with the aid of the RE-AIM framework will be performed to evaluate the

diverse intervention components [78]. The RE-AIM model assesses 5 dimensions: reach, efficacy,

adoption, implementation, and maintenance. These dimensions interact to determine the impact

of the programme. In addition, an adapted version of the framework of Steckler and Linnan

will be applied [79]. The following process indicators will be measured in the first follow-up

questionnaire (at 6 months after baseline) and continuously during the intervention period:

context, recruitment, reach, dose delivered, dose received, satisfaction about the intervention,

and fidelity.

Economic evaluation

The economic evaluation aims to determine the cost-effectiveness of the intervention compared

with usual care from the societal and employer’s perspective. Also, the cost-benefit will be

determined from the employer’s perspective. The time horizon will be one year, similar to the

trial. Analyses will be performed according to the intention-to-treat principle. In the main analysis,

missing data will be imputed using multiple imputation techniques [80]. Sensitivity analyses will

be done to assess the robustness of the results.

First, the total societal and employer’s costs will be estimated, and compared between the

intervention and control group. The 95% confidence intervals will be estimated using approximate

bootstrap confidence (ABC) intervals [81]. Societal costs include all cost measures described in

the method section. From the employer’s perspective, only costs relevant to the employer are

included (i.e. intervention costs, other workplace health promotion costs, and productivity-

related costs). For the cost-effectiveness analysis (CEA), incremental cost-effectiveness ratios will

be calculated by dividing the difference in costs between both groups by the difference in effects

on the primary outcome measures (societal perspective), and outcomes measures relevant to the

company (employer’s perspective). Bootstrapped cost-effect pairs will be graphically presented

on cost-effectiveness planes [82]. Cost acceptability curves will be generated, showing the

probability for cost-effectiveness of the intervention at different ceiling ratios. Also, a cost-benefit

analysis (CBA) will be performed, in which the incremental intervention and other workplace

health promotion costs will be compared to the incremental productivity-related costs.

Discussion

The aim of this design article was to describe the development and plan for the evaluation

of a (lifestyle) programme aimed at prevention and reduction of overweight and MSD among

construction workers. This study may be of importance at company level to gain more insight in

the effects of preventive measures, and to support decision making on which health promoting


Study design | 57

3

activities should be applied. Because the intervention is conducted in the occupational setting a

large number of people can be reached, which may have an impact on health outcomes, and

company as well as health care costs.

Strengths

The intervention was designed following the IM protocol. This has been done before in health

promotion interventions [83-85]. The development has been conducted with key figures in the

organisation as well as with the target group aiming at a better compliance of employers and

OHS with the VIP in construction protocol and allowing a scientific approach with consideration

of daily practice. If the intervention proves to be effective, then the programme can be directly

implemented.

Although the components of the intervention will not be evaluated separately, the process

evaluation will give qualitative insight into the success factors, applicability and usefulness of the

separate intervention components. Furthermore, the process evaluation outcomes can improve

the programme before it will be really implemented.

Limitations

Creating matrices in step 5 of the intervention mapping protocol was not fully applied, as this is

a very time-consuming process. However, since the most important stakeholders were involved

during the design of the study, it is expected that the adoption and implementation of the

programme is ensured.

Health promotion efforts, particularly those directed to somewhat resistant workers who are at

high risk, should preferably be integrated with the provision of improved working conditions.

A systematic review of the effectiveness of health promotion interventions in the workplace

concluded that participation in workplace health promotion may be increased if interventions also

take into account health risks arising from work activities [86]. In this study, not all input of the

intended target group has been implemented. This resulted from the fact that the programme has

been developed in close cooperation with the management of the organisation, their approval

was needed to carry out programme components. It is possible that the programme would have

involved other components if only the input of the target group had been taken into account.

However, this programme was developed with the intention to be implemented. Therefore, we

believe that involving all important stakeholders is necessary.

Finally, this programme has been developed within a specific organisation. In this study, only

stakeholders from the participating company and its OHSs were involved in the feasibility

assessment and the focus group interviews. Also, a specific characteristic of the construction

industry is that most employees are not working at a set location. The optimal infrastructure to

reach workers is possibly different in other companies/branches. Therefore, it is possible that the

IM process would have led to a different protocol in other workplace settings. This should be

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58 | Chapter 3

taken into account when implementing the intervention outside the construction industry. When

generalising this programme to another context, the IM procedure can be applied to modify the

existing programme.

Conclusion

In conclusion, the development of the VIP in construction intervention resulted in a health

programme tailored to the needs of construction workers. The method of IM provided the tools

to do this systematically. If proven (cost-)effective the programme can be directly implemented,

and with minor adaptations in other companies involving blue collar workers or companies that

are already offering regular health screening. OHSs or human resource managers may incorporate

this method in their usual prevention management. The results of the (process) evaluation will

help policy makers decide which elements of the intervention can best be used.

The (cost-)effectiveness and the (implementation) process regarding this intervention will be

evaluated. The results of this RCT will be available in 2012.


Study design | 59

3

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Chapter 4Process evaluation of a multifaceted health programme

aiming to improve physical activity levels and dietary

patterns among construction workers

Laura Viester, Evert A. L. M. Verhagen, Paulien M. Bongers, Allard J. van der Beek

Journal of Occupational and Environmental Medicine. 2014 56:1210-1217

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66 | Chapter 4

Abstract

Objective: To evaluate the process of a health promotion programme, aiming to improve physical

activity levels and diet among construction workers.

Methods: The process evaluation was conducted following the RE-AIM framework for the

evaluation of the public health impact of health promotion interventions. Effectiveness was

assessed on motivational stage-of-change, self-efficacy and decisional balance for physical activity

as well as dietary behaviour.

Results: The external validity of the trial was satisfactory with representative reach of workers

and adoption of workplace units in the participating construction company. The extent to which

the programme was implemented as intended was modest. The intervention was effective on

participants’ progress through stages of behaviour change.

Conclusions: Based on the RE-AIM dimensions it is concluded that for construction workers the

programme is feasible and potentially effective, but adjustments are required before widespread

implementation.


Process evaluation | 67

4

Introduction

The worldwide prevalence of overweight and musculoskeletal disorders (MSD) is high [1]. In the

Netherlands, prevalence of overweight is over 40% in the adult female population and over 50%

in the adult male population [2]. For MSD this is 39% in men and 45% in women [3]. Excess

body weight is associated with increased mortality and morbidity rates (e.g. type 2 diabetes,

cardiovascular disease, cancer, and MSD) [4-6]. In addition to health-related problems for the

individual, overweight as well as MSD are causally related to work-related measures, such as

increased sick leave and decreased productivity [7-14]. Consequently, the economic consequences

of overweight and MSD are high. In the Netherlands in 2007, back pain alone accounted for an

estimated €3.5 billion societal costs [15]. Estimates of annual societal costs of overweight are

€500 million direct health care costs, and €2 billion indirect costs, resulting from sick leave and

work disability [16,17].

To prevent and reduce these health problems worksite intervention programmes are applied, since

these have the potential to reach large groups of the employed population and have shown to

be effective in improving health outcomes [18] as well as work-related outcomes [9]. Measuring

outcomes of worksite health promotion programmes without providing insight into whether

and how programme components are delivered could be considered a black box evaluation.

Issues such as translatability and public health impact have been identified as critical. To provide

insight into these issues, an important, but infrequently conducted component of evaluating

the impact of health promotion interventions, is process evaluation. Process evaluations provide

understanding on how and why interventions achieve their effects, how best to conduct

intervention programmes to maximise effects, and enhance information on the internal and

external validity of the intervention studies.

For newly developed health programmes, knowledge of how a successful or an unsuccessful

outcome was obtained will have an impact on future decision making. For example, if the

outcome of an intervention is not effective, then it can be attributable to lack of implementation

or lack of efficacy of the programme. Especially in intervention studies, assessment and reporting

of adherence to an intervention programme (compliance with health programme components)

is important, since outcomes of these studies can be biased by the level of adherence to the

intervention. Furthermore, it provides insight into feasibility of interventions.

This paper describes the process evaluation of the VIP in Construction intervention, using the

RE-AIM (Reach, Efficacy, Adoption, Implementation, and Maintenance) framework. The results

of this evaluation can be used to modify the programme for long term implementation. Also,

these findings could provide useful information for the design of future intervention studies in a

workplace setting.

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68 | Chapter 4

Methods

Study population

This process evaluation was part of the VIP in Construction study, a randomised controlled trial

(RCT) evaluating the multifaceted health programme aiming to improve physical activity levels

and dietary patterns among construction workers. Blue collar workers (i.e. construction site and

production workers) of a Dutch construction company who attended the voluntary periodical

health screening (PHS) at the occupational health service between February 2010 and October

2011 were invited to participate. A total of 314 workers were included. Workers were randomised

to an intervention group (n = 162) or a control group (n =152). The study protocol (trial number

NTR2095) was approved by the Medical Ethics Committee of the VU University Medical Center

Amsterdam (VUmc). The study design and intervention have been described in detail elsewhere

[19].

Intervention programme

A worksite intervention was developed, aiming at prevention and reduction of overweight and

musculoskeletal disorders (MSD) among construction workers [19]. The VIP in Construction

intervention programme was designed following the intervention mapping protocol [20], and

key figures within the organisation as well as the target group were involved in the development

of the programme. The programme consisted of tailored information, face-to-face and telephone

counselling, exercises, and materials designed for the intervention (waist circumference measuring

tape, pedometer, Body Mass Index (BMI) card, calorie guide, a cookbook including healthy recipes

and knowledge tests, Personal Energy Plan (PEP) forms, and an overview of the company health

promoting facilities). The intervention was tailored to the participant’s body weight status (BMI

and waist circumference), physical activity level, and stage-of-change. The Transtheoretical

Model (TTM) is a theory-based, widely used approach for conceptualizing behavioural change

[21,22]. For interventions aiming at nutrition and physical activity, it is a widely supported model,

allowing stratification of participants based on their readiness to change. Behavioural change

progresses through a series of stages (pre-contemplation, contemplation, preparation, action, and

maintenance). Participants in these strata of stage-of-change have contrasting levels of readiness

to change, which requires different intervening strategies and intensity. Coaching intensity (i.e.

number and duration of contacts) was tailored to the participants’ stage-of-change for improving

physical activity and nutrition by using a quick scan (table 1). Face-to-face and telephone

coaching contacts were provided by personal health coaches (PHC), during work hours. Face-to-

face coaching contacts took place at the construction sites. The coaching contacts consisted of

the following elements: feedback, goal setting, feedback on formulated goals, instructions for

self-monitoring, and training instruction.



4

Table 1. Coaching contact schedule

Stage-of-change PHC contact schedule

2 weeks 1 month 2 months 3 months 4 months

Pre-contemplation stage

A Intake (60 min face-to-face)

Follow-up 1 (30 min; telephone)

Follow-up 2(15 min; telephone)


Contemplation/Preparation stage

B Intake (60 min face-to-face)



Action/maintenance stage

C Intake (30 min face-to-face)

Follow-up 1(10 min telephone)

PHC = personal health coach

Data collection

The process evaluation was conducted using the RE-AIM framework for the evaluation of the public

health impact of health promotion interventions [23]. The RE-AIM model assesses 5 dimensions:

Reach, Efficacy, Adoption, Implementation, and Maintenance. These dimensions interact to

determine the (public health) impact of the programme. Each component was evaluated by

qualitative and/or quantitative aspects. Process indicators were measured continuously in a web-

based registration system during the intervention period by the coaches, as well as in the first

follow-up questionnaire for participants allocated to the intervention group (at 6 months after

baseline, following the intervention period). After the follow-up period, four interviews with

providers and one interview with key persons in the organisation were held, with an average

duration of 30 minutes. Table 2 provides a more detailed explanation of the procedures of the

process evaluation.

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70 | Chapter 4

Tab

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4

Outcome measures

Table 2 presents how each of the RE-AIM dimensions was evaluated. First, the reach of the

programme was studied at individual and organisational level. Next, the effectiveness component

evaluates the intervention effectiveness on (determinants of) behaviour change. To assess

whether transitions between TTM stages could be induced by the intervention, motivation for

change was assessed for PA as well as dietary behaviour. For the purpose of analysis, motivational

stage-of-change was categorised into three categories (similar to the tailoring categories for the

intervention): pre-contemplation, contemplation/preparation, and action/maintenance. The TTM

involves intermediate measures sensitive to progress through the stages as well. These include

pros and cons (decisional balance construct) and the self-efficacy construct. Self-efficacy was

assessed using one item measured with a 5-point response, where 1 = very confident and 5 = not

at all confident. The item addressed the person’s degree of confidence in being able to change

physical activity and nutritional behaviour. Decisional balance was assessed using one item as

attitude towards changing physical activity or nutritional behaviour, with 3 response categories:

‘I see more pros than cons’, I see as many pros as cons’, and ‘I see more cons than pros’. In the

analysis the last two categories were combined due to a small number of subjects in the last

category.

The intention-to-treat analysis of the effectiveness of the intervention on health outcomes

(biometric measures and lifestyle) and work-related outcomes (sick leave, work-related vitality)

will be described elsewhere. Adoption was studied at organisation level (i.e. business unit and

subunit level). Implementation was assessed at the level of either the programme (dose delivered

and fidelity) or the individual (satisfaction, dose received, and participation rate). Elements for

the assessment of the implementation dimension were defined by an adapted version of the

framework of Steckler and Linnan [24]. Finally, Maintenance was considered at both organisation

and programme level (see table 2).

Data analyses

Descriptive statistics were used to illustrate the process quantitatively. Furthermore, logistic

regression analyses for ordinal variables (proportional odds model) were performed to determine

effects of the intervention on stage progression and determinants of behaviour at follow-up,

corrected for baseline values. All interviews were audio-recorded and fully transcribed, coded

based on the underlying structure of the interview, and subsequently analysed according to the

principles of thematic content analyses [25].

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72 | Chapter 4

Results

Reach

Workers of the company were recruited through the usual communication channels of the

company, together with the invitation to the PHS, which was sent with an accompanying letter

to the home address. Participation in these screenings is generally high (>85% for this company).

During the recruitment period approximately 1,021 workers were invited to the PHS. Based on the

number of participants and the number of workers in the company eligible for participation in the

study, it was estimated that 31% (314/1,021) of the workers were included. In table 3 baseline

characteristics of participants are compared to characteristics of the company workers based on

PHS data and company records. Mean age of participants was 46.6 (SD 9.7). Participants were

slightly older with an over representation of the age group 50-plus (37% of the company workers

versus 46% of the participants) and under representation of the group below 40 years of age

(29% of the company workers versus 21% of the participants). BMI levels in the study population

reflected those of the company as estimated by the PHS data.

Table 3. Characteristics (age, levels of BMI) of study participants compared to blue collar workers of the construction company, and PHS participants.

Study (n=314) CompanyAge< 20 0% 0%*

20 – 30 7% 9%*30 – 40 14% 20%*40 – 50 34% 34%*50 – 60 42% 31%*=>60 4% 6%*

BMIOverweight (BMI >= 25) 71% 71%**Obesity (BMI >=30) 23% 21%**

*Based on total company records 2011**Based on periodical health screening (PHS) data 2010/2011 (n=645)

Effectiveness

Intervention effects on stage-of-change, self-efficacy and decisional balance are presented in

table 4. At baseline, based upon the stage-of-change question for dietary behaviour, 52% of

the participants were in the action/maintenance stage, 31% in the contemplation/preparation

stage, and 17% in the pre-contemplation stage. Proportionately more intervention group

participants improved (i.e. moved towards action and maintenance) compared to control group

participants from baseline to follow-up (OR: 3.18, 95%CI: 1.82-5.54). After 6 months 74% were

in the action/maintenance stage in the intervention group versus 48% in the control group. For

physical activity, at baseline 32% of the subjects were in the action/maintenance stage, 49% in



4

the contemplation/preparation stage, and 18% in the pre-contemplation stage. The intervention

group more often progressed through the stages than the control group (OR: 2.13, 95%CI:

1.33-3.42). After 6 months 52% of the intervention group was in the action/maintenance stage

compared to 30% in the control group. No significant intervention effects were found on self-

efficacy (for changing dietary as well as physical activity behaviour). For dietary behaviour the

intervention had a significant positive effect on decisional balance for changing behaviour (OR:

1.95, 95%CI: 1.08-3.54). For physical activity this improvement was not significant by group

assignment (OR: 1.45, 95%CI: 0.83-2.45).

Table 4. Baseline and follow-up descriptives, and intervention effects on stage-of-change, self-efficacy, and decisional balance.

Physical activity Dietary behaviourIntervention

(n=135)Control(n=137)

Intervention(n=136)

Control(n=138)

T0 T1 T0 T1 T0 T1 T0 T1Stage-of-changeAction/maintenance (%) 35.2 51.1 29.1 29.9 53.2 75.0 51.0 47.8Contemplation/preparation(%) 47.5 37.8 51.4 51.8 34.8 15.4 27.8 36.2Pre-contemplation (%) 17.3 11.1 19.6 18.2 12.0 9.6 21.2 15.9

OR (95%CI): 2.13 (1.33-3.42)

p-value 0.002 OR (95%CI): 3.18 (1.82-5.54)

p-value: <0.001

Self-efficacyVery confident 23.1 33.6 28.8 24.3 20.5 26.9 24.0 25.2Confident 42.9 43.3 43.5 43.4 46.2 53.7 42.7 45.2Not sure 24.5 14.9 20.1 25.0 26.3 14.2 24.0 23.0Not confident 9.5 8.2 7.8 7.4 7.0 5.2 9.3 6.6

OR (95%CI): 1.41 (0.89-2.23) p-value: 0.146

OR (95%CI): 1.53 (0.96-2.45) p-value: 0.073

Decisional balanceMore pros than cons 66.7 76.7 61.8 65.7 57.4 76.7 55.9 62.2As many pros as cons 23.3 20.3 25.0 29.2 40.6 23.3 39.2 35.6More cons than pros 10.1 3.0 13.2 5.1 1.9 0 4.9 2.2

OR (95%CI): 1.45 (0.83-2.54) p-value: 0.196

OR (95%CI): 1.95 (1.08-3.54) p-value: 0.033

T0 = baseline, T1 = follow-up at 6 months, OR = odds ratio, CI = confidence interval.

Adoption

The programme was developed and implemented in one large company. In the Netherlands,

only a small percentage of all construction companies are large companies (>100 employees)

[26]. At business unit level, representativeness was satisfactory. Participation rates did not differ

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74 | Chapter 4

between the two main company units, general construction and infrastructure. However, within

infrastructure participation rate varied between the subunits. The subunits that were under

represented in participation were two specialised units involving road construction and earth

moving.

Implementation

Programme level

Dose delivered: Of all planned coaching appointments 98.4% was provided by the PHC. One

participant did not receive coaching at all, and for another participant one follow-up appointment

was missed. The percentage of provided materials was 98.8%; two participants did not receive

the VIP in construction toolbox.

Fidelity: The intended start of the coaching contacts was two weeks after the participants were

included in the study. The first planned contact took place on average 5.7 (SD 3.6) weeks after

randomisation. As a consequence three participants did not receive their last follow-up coaching

contact before the short term follow-up measurements. Follow-up contacts were planned

according to the protocol. However, if a scheduled appointment took place during a vacation

period, in some cases the follow-up contact was postponed and the protocol was continued from

that point in time. Based on the coaching registration in 6.3% (n=8) of the intakes, goal setting

and formulating action plans were not adequately part of the intake session. During follow-

up contacts in 98.2% barriers/successes and long term goals were addressed. The planned 30

minutes for intake C turned out to be insufficient for attending to all intake components; these

contacts usually lasted longer than planned according to protocol. In addition to programme

information on energy-balance related behaviour, the results of the exercise tests or cholesterol

and blood pressure measurements proved useful starting points to motivate participants in goal

setting. Not all PHCs prescribed the exercise card in all cases as stated by the protocol. One

PHC indicated to have used the card only if participants explicitly mentioned musculoskeletal

symptoms. Another PHC had the opinion that the exercises were too advanced for participants

with obesity.

Table 5. Participation rate and mean number of attended coaching contacts for each coaching group (A,B,C).

Number of contacts Allocated

Perc. Non-adherence*

Mean number attended coaching appointments(n=150; allocated, incl.

non-participants)

Mean number attended coaching appointments (n=126;

those starting the coaching sessions)

A 4 40 30.0% 2.2 (1.7) 3.2 (1.0)B 3 61 11.5% 2.3 (1.1) 2.5 (0.8)C 2 49 10.2% 1.8 (0.8) 2.0 (0.4)Total 150 16%

*The percentage of study participants in the intervention group allocated to the coaching that did not participate in the coaching at all.



4

Individual level

Dose received (exposure): Of the 162 workers allocated to the intervention group, based on

baseline BMI, waist circumference and amount of physical activity, 150 were eligible for coaching.

Based on the coaching registration system, 84% (n=126) of the workers allocated to the PHC

attended at least one coaching session. Main reasons for not participating were “not interested”

or “no time”, other reasons included health-related issues, and alleged privacy issues (e.g.

employer aware of participation in health promotion programme). Table 5 shows participation

and mean number of attended coaching contacts for each group. Participation rate differed

between coaching groups. In group B (contemplation/preparation) and C (action/ maintenance)

this was 11.5 and 10.2%, respectively. The most intensive group A (four sessions), which was the

group pre-contemplators, had the highest non-response (30.0%).

Of the participants, 61.1% completed all coaching sessions. Main reasons given by the

participants for not finishing the contacts were: lack of interest, time, or conflicting expectations

of the programme. PHCs confirmed that in some cases during the intake it became apparent that

participant’s expectations differed from the actual programme content, such as receiving training

guidance or treatment (physiotherapy) from the coaches. Questionnaires on participation and

usage of the programme materials and satisfaction were completed by 121 workers at 6 months

of follow-up. According to the interviewed PHCs the PEP forms were used in all intake sessions.

However, from the questionnaire data it was concluded that only 26% of the participants used

the forms further on during the intervention period. Practical materials were used more than

informational materials: pedometer (52%), waist circumference measuring tape (43%), and BMI

card (30%). The calorie card and cookbook were less used (15%). For the exercise card: 62% of

participants indicated to have used the card at least once. However, only 13% used it regularly

(once per week), and only 4% used the card as prescribed by the programme (three times per

week).

Participants’ attitudes: Overall, the mean rating of the programme was 7.6 (SD 1.0) on a scale

from 0-10. By the participants who received at least one coaching appointment, the coaching

was scored with 7.8 (sd 0.9). The majority of the participants was satisfied with the number of

coaching contacts (86.5%), 2.1% perceived the number as too many, and 11.5% as too few.

The mean rating of the programme materials was 7.2 (SD 1.1). Of all programme components

(materials and coaching) the most appreciated component was the coaching contact.

Maintenance

The senior human resource manager was interviewed on intention of continuation of the

programme after the trial phase. The intention of the organisational decision makers is to

implement the programme provided that there is reasonable evidence that the programme will

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76 | Chapter 4

produce long term benefits on sick leave or related health outcomes. Barriers for maintenance

that were identified from the interview were related to organisational support and the current

economic recession. As a consequence of the current economic situation in the construction

sector, organisational issues such as financial resource allocation were prominent. Since resources

to address worker health issues are limited, there has been a shift to decision making based

on short term goals and effects. Lost work time due to participation in the programme might

negatively influence support for the programme.

A possible facilitator for maintenance that was identified from the interview is that the company

is currently changing its policy on work disability prevention, towards a more active role for the

employer. As a result of this present organisational transition, follow-up of PHS, becomes integral

part of the organisational policy. Within the new situation, the programme would become a more

central (as opposed to peripheral) part of the organisation. This could positively contribute to

organisational culture for sustainable implementation of the programme.

PHCs were interviewed on usability of the programme. Tailoring of the intensity of the coaching

based on the stage-of-change questions was in most cases perceived as successful. However, in

some cases, based on the intake, the coaches would have assigned the participant to a more or

less intensive contact schedule. The first face-to-face contact was perceived as essential to build

confidence between coach and participant. According to the coaches, for the follow-up contacts

to be more effective, the first follow-up contacts should be planned shortly after the intake.

Further, coaches encountered participants with emotional/psychological issues, such as stress or

addiction, which probably should be addressed first before changes in lifestyle behaviour can be

discussed. These issues might also be associated with unhealthy behaviour [27]; in the current

protocol these issues were not addressed.

Discussion

The aim of this paper was to evaluate the process of the VIP in Construction intervention, using the

RE-AIM framework. The external validity of this worksite health promotion trial was satisfactory

with representative reach of workers and adoption of workplace units in the participating

construction company. The intervention was effective on participants’ progress through stages

of behaviour change. The extent to which the programme was implemented as intended was

modest. Satisfaction and dose delivered was high. However, adjustments to the programme

should be made to improve exposure and fidelity. For the programme to be sustainably integrated

into the health promotion practice of organisations, appropriate organisational context and

information on health-related, work-related, as well as financial outcomes are essential.



4

The two RE-AIM dimensions reach and adoption, at different levels, refer to broadness and

representativeness of the study sample [28]. Information on the reach of the programme is

needed to gain insight in potentially selective participation and external validity. Participation rate

in the VIP in Construction programme was 31% of the eligible workers. Participation in worksite

health promotion programmes aimed at physical activity and nutrition levels are typically below

50% [29]. In general, blue collar workers appear less likely to participate in worksite health

promotion programmes [28]. However, this programme was developed with input of this specific

worker population, which was expected to improve participation rate. PHS was found to be a

successful starting point for intervention. Worksites with small numbers of employees are less

likely to provide health promotion programmes than larger companies, such as in the present

study [30]. Linking programmes to PHS to increase reach might support health promotion in these

settings as well.

When generalising the results from the specific setting of the RCT to the entire worker population,

it should be taken into account that in the study population older workers were slightly over

represented. Older workers being more likely to participate, is in line with other trials [31,32].

Some reports find that participants that actively engage in health programmes are those that

already have a healthier lifestyle and therefore are more motivated to participate [33,34]. Lack

of participation by high-risk employees has been cited as a barrier to adopt WHP programmes

[30]. In this programme, based on PHS data of the company, the programme has reached a

representative sample regarding levels of BMI.

Contextual factors could have played a role in the adoption of the programme. First, during

the recruitment period of the study, the economic crisis started to have a negative effect on the

construction sector resulting in termination of employment, and workers reporting increased

work pressure and job insecurity. Second, the company units that were under represented are,

more than other units, characterised by shift work, irregular work hours, and temporary worksites.

These characteristics might be barriers for adoption of the programme. Another explanation is

that management engagement influenced participation in the programme. In another worksite

intervention for construction workers it was found that organisational support was an important

factor for participation [35]. In the present study the role of direct supervisors was larger than

anticipated in the development of the programme. Appointments (follow-up measurements as

well as coaching contacts) for workers in these units were usually made through their supervisors,

and as a consequence of increased time and financial pressure the programme might not have

had highest priority. Conflicts of work demands have increasingly been found a barrier to offering

worksite health promotion programmes [30]. Although top management support was excellent

(during the development and continuously during the trial phase), for these units facilitation

of participation by supervisors during work hours is probably also essential and could increase

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78 | Chapter 4

enrolment. Regarding the representativeness of the setting it should be mentioned that recruiting

construction companies for another health promotion intervention was found to be difficult, and

company size was found to influence process outcomes [35]. Smaller construction companies

might have other factors or decision making processes that are relevant for adoption of health

promotion programmes.

Tailoring by motivational stage can be used to predetermine readiness for behaviour change

in energy-related behaviour, which potentially enables addressing low completion rates in

health promotion programmes and its related cost issues [36]. In contrast to another worksite

individual counselling study [37] the programme was able to reach a substantial group of pre-

contemplators. Regarding physical activity 26% of the Dutch adult population is considered

to be pre-contemplator [38], for dietary change this is approximately 50% [39]. Of the group

pre-contemplators included in the study, two third actually started the coaching programme. To

increase this rate, a stage-based adjustment of the programme preceding the coaching contacts

might be advisable to increase exposure to the programme and motivate workers to the next

stage.

Furthermore, it has been suggested that tailored interventions may be more effective to induce

behaviour changes [21], and stage progression could be a good indicator of the effectiveness of

stage-of-change based tailoring as a basis for intervention. Regardless of an already substantial

percentage of workers in the action/maintenance stage at baseline, the intervention helped a

significantly greater number of workers in the intervention group to progress through the stages

of change than did in the control group. Stage movement is a proxy measure of behavioural

change, and does not necessarily result in actual behaviour change [21]. However, since a

substantial group moved to the action/maintenance stage, the progression could be regarded as

intervention effectiveness.

At programme level, implementation was defined by dose delivered and fidelity. Dose delivered

was satisfactory, but fidelity was moderate. By pilot testing the coaching schedules, some of the

practical issues could have been prevented. At individual level dose received and satisfaction

were assessed. Satisfaction with the programme and PHCs was high. The majority of participants

reported to be satisfied with the number of coaching contacts. Although the intake contacts

were organised at the worksite and also the follow-up coaching sessions could be completed

in company time, which potentially increases adherence [40], the number of actually received

contacts was suboptimal, since 38% of the participants in the coaching sessions did not fully

finish the programme. Thus, although in a previous weight loss intervention an association

was found between number of contacts and intervention effectiveness on weight loss [41],

for this population, increasing number of contacts might be hardly feasible. Practical tools for



4

self-monitoring were used more often than paper materials. Since the use of self-monitoring in

behavior change has both theoretical foundation and significant association with weight loss

[42], successful use of these materials might induce actual change in programme outcomes.

Implementation of the exercise component was not successful. This could in part be a result of

the PHCs not always prescribing the exercises.

For a worksite health promotion programme to be implemented and remain viable in the long

term, organisational support and institutionalisation are important factors [43]. First, to decide

whether or not to provide worksite health promotion interventions to their employees, employers

need information about the trade-off between costs and effects. Economic evaluation of the

program from the company’s perspective, especially when resources are limited, would provide

essential input for making a business case to obtain senior management support. Further, even if

there are no financial limitations for implementation, feasibility of long term implementation of the

programme requires appropriate organisational infrastructure and capacity. For the programme

maintenance after the trial phase, the role of the researcher/research assistant should be easily

transferable to agents in the company. The coaching was delivered by external professionals,

who could continue after the trial phase. However, planning and organisation was almost entirely

done by the study staff. This was time- consuming and it decreases the influence on company

maintenance after the trial phase. Therefore, it is recommended that sustainability, for example

by appointing key persons within the company to integrate the programme, becomes part of the

design of such programmes.

Strengths and limitations

The first strength was that in this process evaluation study compliance with the programme was

obtained by objective measures. The coaching attendance was registered for each appointment,

as well as reasons for not attending. Secondly, process measures were evaluated at different

levels. Data were collected from organisational decision makers, participants in the study, as well

as intervention deliverers (PHCs).

A limitation of this evaluation is that supervisory staff was not involved. Their role was larger than

anticipated, and input and support from this particular management level could improve adoption

and implementation. Another limitation of this study was that the fidelity concept was partly

measured by self-report, instead of fully by objective measurement. To objectively measure the

content of coaching appointments, audio recording and analysing the actual conversations would

give a more reliable representation of the actual implementation process. Finally, the concepts of

the TTM (stage-of-change, self-efficacy, and decisional balance) were measured using single-item

questions. Preferably these constructs are measured with more extensive multi-item questions

(or algorithms) since physical activity as well as dietary behaviour are complex behaviours. For

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80 | Chapter 4

tailoring in a large-scale intervention this would be unpractical. However, this would be a more

suitable and valid approach when tailoring is applied in the individual counselling setting.

Conclusions

Based on the reach dimension, the external validity of the study is satisfactory, with a representative

study population. Based on the RE-AIM dimensions implementation and effectiveness, it is

concluded that for construction workers the programme is feasible. In addition, the programme

is potentially effective based on the intervention effect on movement through the motivational

stages-of-change for PA as well as dietary behaviour. However, some adjustments to improve

exposure and fidelity should be made. A contextual factor of importance in the process of

conducting the programme was the current economic climate in general and specifically in the

Dutch building and construction industry. This had consequences for adoption, and could have

consequences for the future implementation and maintenance of the programme as well.

This evaluation provides insights for researchers and practitioners planning and implementing

intervention programmes in a workplace setting. In addition, it may help employers to make

informed decisions about worksite health programme adoption and implementation.



4

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13. Robroek SJW, van den Berg TIJ, Plat JF, Burdorf A: The role of obesity and lifestyle behaviours in a productive workforce. Occup Environ Med 2011, 68: 134-139.

14. Andersson GB: Epidemiological features of chronic low-back pain. Lancet 1999, 354: 581-585.

15. Lambeek LC, van Tulder MW, Swinkels ICS, Koppes LLJ, Anema JR, van Mechelen W: The trend in total cost of back pain in The Netherlands in the period 2002 to 2007. Spine (Phila Pa 1976) 2011, 36: 1050-1058.

16. Polder JJ, Takkern J, Meerding WJ, Kommer GJ, Stokx LJ. Cost of illness in the Netherlands. 270751005. 2002. Bilthoven, The Netherlands: RIVM. Ref Type: Report

17. Raad voor de Volksgezondheid en Zorg: Gezondheid en gedrag. 2002. Zoetermeer, The Netherlands: RVZ. Ref Type: Report

18. Verweij LM, Coffeng J, van Mechelen W, Proper KI: Meta-analyses of workplace physical activity and dietary behaviour interventions on weight outcomes. Obes Rev 2011, 12: 406-429.

19. Viester L, Verhagen EALM, Proper KI, van Dongen JM, Bongers PM, van der Beek AJ: VIP in construction: systematic development and evaluation of a multifaceted health programme aiming to improve physical activity levels and dietary patterns among construction workers. BMC Public Health 2012, 12: 89.

20. Bartholomew LK, Parcel GS, Kok G, Gottlieb NH: Planning health promotion programs: intervention mapping. San Francisco, CA: Jossey-Bass; 2006.

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21. Bridle C, Riemsma RP, Pattenden J, Sowden AJ, Mather L, Watt IS et al.: Systematic review of the effectiveness of health behavior interventions based on the transtheoretical model. Psychology & Health 2005, 20: 283-301.

22. Prochaska JO, DiClemente CC: Stages and processes of self-change of smoking: Toward an integrative model of change. Journal of Consulting and Clinical Psychology 1983, 51: 390-395.

23. Glasgow RE, Vogt TM, Boles SM: Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health 1999, 89: 1322-1327.

24. Steckler A, Linnan L: Process evaluation for public health interventions and research. An overview. In Process Evaluation for public Health Interventions and Research. San Fransisco, CA: Jossey-Bass Incorporated Publishers; 2002:1-23.

25. Green J, Thorogood N: Qualitative methods for health research. London: Sage; 2004.

26. CBS. http://statline.cbs.nl/StatWeb/ublication/?DM=SLNL&PA=81588NED&D1=a&D2=0,3,9,13, 52,54,59,63,70,77,80,90,94,98,108,117,119,121,127&D3=l&HDR=G2,T&STB= G1&VW=T. 2012. 2-2-2012. Ref Type: Internet Communication

27. Ng DM, Jeffery RW: Relationships between perceived stress and health behaviors in a sample of working adults. Health Psychol 2003, 22: 638-642.

28. Glasgow RE, McCaul KD, Fisher KJ: Participation in worksite health promotion: a critique of the literature and recommendations for future practice. Health Educ Q 1993, 20: 391-408.

29. Robroek SJ, van Lenthe FJ, van Empelen P, Burdorf A: Determinants of participation in worksite health promotion programmes: a systematic review. Int J Behav Nutr Phys Act 2009, 6: 26.

30. Linnan L, Bowling M, Childress J, Lindsay G, Blakey C, Pronk S et al.: Results of the 2004 National Worksite Health Promotion Survey. Am J Public Health 2008, 98: 1503-1509.

31. Groeneveld IF, Proper KI, van der Beek AJ, Hildebrandt VH, van Mechelen W: Factors associated with non-participation and drop-out in a lifestyle intervention for workers with an elevated risk of cardiovascular disease. Int J Behav Nutr Phys Act 2009, 6: 80.

32. Emmons KM, Linnan LA, Shadel WG, Marcus B, Abrams DB: The Working Healthy Project: a worksite health-promotion trial targeting physical activity, diet, and smoking. J Occup Environ Med 1999, 41: 545-555.

33. Lewis RJ, Huebner WW, Yarborough CM: Characteristics of participants and nonparticipants in worksite health promotion. Am J Health Promot 1996, 11: 99-106.

34. Lerman Y, Shemer J: Epidemiologic characteristics of participants and nonparticipants in health-promotion programs. J Occup Environ Med 1996, 38: 535-538.

35. Oude Hengel KM, Blatter BM, van der Molen HF, Joling CI, Proper KI, Bongers PM et al.: Meeting the challenges of implementing an intervention to promote work ability and health-related quality of life at construction worksites: a process evaluation. J Occup Environ Med 2011, 53: 1483-1491.

36. Shephard RJ: Worksite fitness and exercise programs: a review of methodology and health impact. Am J Health Promot 1996, 10: 436-452.

37. Proper KI, Hildebrandt VH, van der Beek AJ, Twisk JWR, van Mechelen W: Effect of individual counseling on physical activity fitness and health: a randomized controlled trial in a workplace setting. Am J Prev Med 2003, 24: 218-226.

38. Kearney JM, de Graaf C, Damkjaer S, Engstrom LM: Stages of change towards physical activity in a nationally representative sample in the European Union. Public Health Nutr 1999, 2: 115-124.

39. de Graaf C, Van der Gaag M, Kafatos A, Lennernas M, Kearney JM: Stages of dietary change among nationally-representative samples of adults in the European Union. Eur J Clin Nutr 1997, 51 Suppl 2: S47-S56.

40. Linnan LA, Sorensen G, Colditz G, Klar DN, Emmons KM: Using theory to understand the multiple determinants of low participation in worksite health promotion programs. Health Educ Behav 2001, 28: 591-607.



4

41. Wadden TA, West DS, Neiberg RH, Wing RR, Ryan DH, Johnson KC et al.: One-year weight losses in the Look AHEAD study: factors associated with success. Obesity (Silver Spring) 2009, 17: 713-722.

42. Burke LE, Wang J, Sevick MA: Self-monitoring in weight loss: a systematic review of the literature. J Am Diet Assoc 2011, 111: 92-102.

43. Goodman RM, McLeroy KR, Steckler AB, Hoyle RH: Development of level of institutionalization scales for health promotion programs. Health Educ Q 1993, 20: 161-178.

Chapter 5Improvements in dietary and physical activity

behaviours and body mass index as a result of a

worksite intervention in construction workers:

results of a randomised controlled trial


(submitted)

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86 | Chapter 5

Abstract

Purpose: To evaluate the effectiveness of an individually tailored intervention for improvement

of lifestyle behaviour and prevention and reduction of overweight disorders among construction

workers.

Design: Randomised controlled trial.

Setting: Construction industry

Subjects: Blue collar workers, randomised to an intervention (n=162) or control group (n = 152).

Intervention: The intervention group received individual coaching sessions, tailored information

and tailored materials to improve lifestyle behavior, the control group received usual care.

Measures: Body weight, body mass index (BMI), waist circumference, physical activity levels (PA),

dietary behaviour, blood pressure, and blood cholesterol were assessed.

Analysis: Linear and logistic regression analyses were applied, with outcome measures at 6- and

12-month follow-up as dependent variables, adjusting for their baseline levels.

Results: After 6 months a statistically significant intervention effect was found on body weight

(B -1.06, p=0.010), BMI (B -0.32, p=0.010), and waist circumference (B -1.38, p=0.032). At 6

months vigorous PA increased significantly in the intervention group compared to the control

group (B 2.06, p=0.032), and for sugar-sweetened beverages (SSB) an intervention effect was

found at 6 months as well (B -2.82, p=0.003). At 12 months, for weight related outcomes, these

differences were still present, however slightly smaller and no longer statistically significant.

Conclusion: Intervention participants showed positive changes in vigorous PA and dietary

behavior compared to controls, as well as effects on weight-related outcomes at 6 months. Long-

term effects were still promising, but no longer statistically significant.


Effect evaluation on primary outcomes | 87

5

Introduction

The worldwide increased prevalence of overweight and obesity is associated with considerable

health concern. Excess body weight is associated with increased mortality [1] and adverse health

outcomes [2]. The predominant health issues associated with overweight and obesity include type

2 diabetes, cardiovascular disease (CVD), cancer, and musculoskeletal disorders (MSD) [3,4]. The

economic burden of overweight is substantial and is expected to increase [5]. In the Netherlands

annual overweight related health care costs are estimated at €500 million, while indirect costs,

reflecting the value of lost productivity resulting from work absence and disability, are projected

to be about €2 billion [6,7].

In general, even after adjustment for socio-demographic factors, the prevalence of overweight

and obesity in construction workers is higher than in the general adult population [8-10]. Although

in white collar workers with a more sedentary daily routine the overweight issue has also been

described, in blue collar (construction) workers the overweight problem is of specific concern.

Blue collar workers in the construction industry have an increased risk for sick leave, disability,

and decreased productivity as a result of (a combination of) obesity, a high physical workload [11],

and musculoskeletal symptoms [12-14]. In addition, due to the physically demanding nature of

construction work, we hypothesised that overweight and obesity in this specific group also have

more individual and larger economic consequences.

This increased prevalence of overweight justifies occupational and sector specific preventive

strategies [6] for construction workers. Preventing and reducing excessive body weight among

workers with a high physical work demand, might be a strategy to increase or preserve work

ability [12], decrease sick leave [11] and musculoskeletal symptoms by lowering the relative load

on the musculoskeletal system.

In several systematic reviews and a recent meta-analysis evidence was found for effectiveness

of worksite physical activity and dietary behaviour interventions on weight outcomes [15,16].

These did not include effective interventions specifically designed for blue collar workers in the

construction industry. A lifestyle programme aimed at improving health of construction workers

with a high risk for CVD showed promising effects of lifestyle counselling on weight related

outcomes [17]. However, this programme aimed at a high risk group, while it could be argued

that for prevention in a population with a relatively high prevalence of unhealthy weight, a

population approach might be the most appropriate strategy. The World Health Organisation

(WHO) has recommended that prevention of overweight and obesity should target adults even

while body mass index (BMI) is still within an acceptable range [18].

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88 | Chapter 5

The aim of the present study was to evaluate the effectiveness of an individually tailored

intervention, ‘VIP in construction’, among blue collar construction workers on body weight-related

measures (i.e. body weight, BMI, and waist circumference), blood pressure, and cholesterol. In

addition, to gain insight into which behavioural changes may have led to the effects on these

outcomes, physical activity and dietary intake were evaluated.

Methods

Trial design

The effectiveness of the programme was measured by performing a randomised controlled

trial (RCT). Participants were measured at baseline (T0), at 6 months (T1), and at 12 months

(T2). Written informed consent was obtained from participants before enrolment in the study.

Consenting participants were randomised to the intervention or control group after the baseline

measurement. The control group received care as usual and was only contacted for the baseline

and follow-up measurements. The study design and procedures have been approved by the

Medical Ethics Committee of the VU University Medical Center, and the trial has been registered

in the Netherlands Trial Register (NTR): NTR2095.

Participants

The research population consisted of consenting blue collar workers of a construction company

who attended a non-compulsory periodic health screening (PHS). The exclusion criterion was

being on sick leave > 4 weeks at baseline. In total 314 workers were recruited over a 15-month

period (March 2010 to June 2011), and randomised to an intervention (n=162) or control group

(n = 152).

Randomisation and blinding

After baseline measurements the participants were randomly assigned to either the intervention

or the control group by a computer generated list using SPSS (version 15). The randomisation

was prepared and performed by an independent researcher (i.e. the research assistant). After

randomisation, workers assigned to the control group received general information on the

follow-up measurements. Intervention providers could not be blinded for allocation; however,

they were not involved in the outcome assessment.

Intervention

The intervention programme aimed at the prevention and reduction of overweight and MSD,

and was developed and implemented by applying the Intervention Mapping protocol [19,20].

The programme was offered at the worksite during working hours. The intervention commenced

preferably within two weeks after the baseline measurements delivered by study-trained



5

health professionals (personal health coaches, PHC) during face-to-face and telephone health

coaching sessions. Participants also received personal energy plan (PEP) forms to record their

goals and action plans, and which they could use during the follow-up health coaching sessions.

The intervention was tailored to the participant’s weight status (BMI and waist circumference),

physical activity level, and stage-of-change. The intervention programme focussed on improving

(vigorous) physical activity levels and healthy dietary behaviour, and in addition to the coaching

sessions consisted of tailored information, training instruction (a fitness “card” to be used for

core stability and strengthening exercises), and the ‘VIP in construction toolbox’ (overview of the

company health promoting facilities, waist circumference measuring tape, pedometer, BMI card,

calorie guide, recipes, and knowledge test).

Outcome measures

Questionnaire and physiological measurement data were collected from 2009 until 2012, at

baseline before the randomisation (n=314), 6 months after baseline, following the intervention

(n=277), and 12 months follow-up after baseline (n=261). The periodical health screening provided

baseline data and was performed by the occupational physician (OP) or assistant. Participants

filled in an additional study questionnaire. Follow-up measurements at 6 and 12 months were

performed by study trained research assistants. To ensure standardisation of measurements OPs

and assistants were provided with measurement protocols.

Body weight and BMI: Body weight was measured using a digital weight scale. Body weight and

height were measured with the participants standing without shoes and heavy outer garments.

Data on body weight and height were used to calculate BMI (kg/m2).

Waist circumference: Waist circumference was measured as midway between the lower rib

margin and the iliac crest with participants in standing position at the end of expiration [21]. To

standardise waist circumference measurement, OPs and assistants were provided with a Seca 201

waist circumference measure (Seca, Hamburg, Germany).

Blood pressure: At follow-up systolic and diastolic blood pressure (mmHg) was measured twice

with a fully automated blood pressure monitor (type: OMRON M6). The mean value of the two

measurements was computed.

Blood cholesterol (total cholesterol, TC): TC (mmol/l) was measured with non-fasting finger

stick samples analysed on a Cholestech LDX desktop analyser (Cholestech, Hayward, USA). This

analyser has been validated for lipid measurements in clinical practice [22].


Physical activity: In the study questionnaire the validated Short Questionnaire to Assess Health

enhancing physical activity (SQUASH) was applied [23]. The SQUASH measures duration,

frequency and intensity of different domains of physical activity (active work transportation,

occupational physical activity, household activities, and leisure time activities). For the leisure time

R1R2R3R4R5R6R7R8R9


90 | Chapter 5

domain, activities were subdivided into age dependent intensity categories, by the metabolic

equivalents (METs) derived from the compendium of physical activities [24]. Since the VIP in

Construction intervention was aimed at improving leisure time moderate and vigorous physical

activities (MVPA), the outcome measure for this study was total minutes per week for moderate

to vigorous activities in leisure time including sports activities, walking, cycling, doing odd jobs,

and gardening. Additionally, the frequency of vigorous activities was obtained from the PHS

questionnaire as assessed by the number of days per week vigorous intensity leisure time activities

that are performed at least 20 minutes. These questions relate to international physical activity

guidelines [25] as well as to the Dutch guidelines [26].

Dietary intake: Alcohol consumption was obtained from the PHS questionnaire asking participants

to report their average consumption (in glasses per week). Portion size at dinner, number of

beverages, as well as consumption of energy dense snacks, fruit and vegetables were assessed

using questions that were also used in the Health under Construction study [27]. In these

questions average weekly intake and daily portions of several food groups during a usual week

during the past month are indicated.

Potential confounders and effect modifiers

Data on potential confounders and effect modifiers were assessed by questionnaire including

age, smoking (yes/no), education (low=elementary school, medium=secondary education, and

high=college/university), and marital status (married/ cohabitating, single/ divorced/ widowed).

Sample size

The sample size calculation has been described elsewhere [19]. In each study group (intervention

and control) 130 participants were needed at follow-up.

Statistical methods

Randomisation was checked for differences in baseline values between the intervention and

control group, using independent t-test for continuous variables and Pearson’s Chi-square tests

for categorical and dichotomous variables. Regression models were presented as crude (model I)

and adjusted full models (model II).

The effectiveness of the lifestyle intervention was assessed using a regression analysis with

the outcome measures at 6 months and 12 months follow-up as the dependent variables and

adjusting for the baseline levels of the outcome measure. Both crude and adjusted analyses

were performed. Linear and logistic regression analyses were performed using SPSS 20.0 (SPSS

Inc. Chicago, Illinois, USA). According to the intention-to-treat principle, all available data of the

participants, regardless of whether or not they actually received the complete intervention, were

used for data analysis. The analysis was conducted with all available data of the respondents at

the time of follow-up. For all analyses, a two-tailed significance level of <0.05 was considered

statistically significant.



5

Results

Between March 2010 and June 2011, 314 participants were enrolled in the study. Figure 1

presents the CONSORT flow chart of the participants throughout the trial. A total of 162 workers

were assigned to the intervention group and 152 to the control group; 83% of the workers

remained in the study during the 12-month follow-up.

Figure 1. Flow chart of the study participants

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92 | Chapter 5

Baseline and confounding

Baseline characteristics of the two study groups are presented in table 1. All participants were

male. Of the total study population 70% was overweight, and 22.7% obese. No statistically

significant baseline differences between the intervention or control group were found for

outcome measures or potential confounders.

Table 1. Baseline characteristics of the total study population and by group allocation.

All Intervention ControlNumber of participants N= 314 N= 162 N= 152Age, mean (SD) 46.6 (9.7) 46.3 (9.9) 47.0 (9.5)Weight, kg (SD) 88.8 (13.6) 88.7 (12.9) 88.9 (14.4)BMI (kg/m2) 27.4 (3.7) 27.3 (3.5) 27.4 (3.9) Normal (<25) (%) 30.0 29.2 30.9 Overweight (25-29,9) (%) 47.3 50.9 43.4 Obese (>30) (%) 22.7 19.9 25.7Waist circumference (SD) 99.4 (11.0) 99.1 (10.2) 100.0 (11.8)Systolic BP, mmHg (SD) 131.1 (14.6) 131.1 (15.4) 131.1 (13.7)Diastolic BP, mmHg (SD) 82.8 (9.7) 82.0 (10.4) 83.6 (8.9)Blood cholesterol, mmol/l (SD) 5.4 (1.0) 5.3 (1.0) 5.4 (1.1)Smoking (Yes, %) 29.4 29.0 29.7

Physiological outcomes

Table 2 presents the means (SD) for body weight, BMI and waist circumference at baseline, 6

and 12 months follow-up for the intervention and control group, as well as the results of the

linear regression analysis. At 6 months, there was a significant intervention effect on body weight

(B -1.06, 95%CI: -1.87;-1.26), BMI (B -0.32, 95%CI: -0.57; -0.08), and waist circumference (B

-1.38, 95%CI: -2.63; -0.12) (table 2). Directly following the intervention period, body weight

and BMI increased in the control group, while it did not change significantly in the intervention

group. Waist circumference decreased for the intervention participants. At 12 months, analyses

within groups (paired t-tests) showed that the decrease in waist circumference in the intervention

group and the increase in body weight and BMI in the control group compared to baseline

values were still significant. However, the effects for body weight and BMI in the between group

analyses were only marginally significant (p=0.053 and p=0.057, respectively) and even further

from statistically significant for waist circumference (p=0.187).

No significant intervention effects in diastolic or systolic BP or total cholesterol levels were found

(table 3).



5

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R1R2R3R4R5R6R7R8R9


94 | Chapter 5

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5

Physical activity

No intervention effects were found from complete cases analysis on leisure-time MVPA (table 4).

At 6 months intervention group participants increased their leisure time MVPA, but no significant

intervention effect was found (B 70.6, 95%CI: -23.3; 165.5). At 6 months after baseline there

was a significant intervention effect on meeting the public health guideline of vigorous physical

activity (OR 2.06 95%CI: 1.07 ; 3.99). Participants in the intervention group meeting the guideline

increased with 8%. After 12 months there was no significant difference between the intervention

and the control group.

Dietary intake

A statistically significant intervention effect on intake of sugar-sweetened beverages was found

after 6 months (table 4). Participants in the intervention group decreased their intake with one

glass per week, while control group participants increased their intake (B -2.82, 95%CI: -4.67;

-0.97). At 12 months after baseline no effect was found on SSB (B -0.96, 95%CI: -2.68; 0.63). No

significant short-term or long-term intervention effects were found for any of the other dietary

outcome measures.

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96 | Chapter 5

Tab

le 4

Dif

fere

nce

s in

min

ute

s p

er w

eek

spen

t o

n a

t le

ast

mo

der

ate

inte

nsi

ty o

f p

hys

ical

act

ivit

y, m

eeti

ng

th

e p

ub

lic h

ealt

h g

uid

elin

e fo

r vi

go

rou

s p

hys

ical

act

ivit

y, a

nd

die

tary

inta

ke b

etw

een

inte

rven

tio

n a

nd

co

ntr

ol g

rou

p a

t 6

mo

nth

s an

d 1

2 m

on

ths

follo

w-u

p, c

orr

ecte

d f

or

bas

elin

e va

lues

.

Out

com

e m

easu

reM

odel

IM

odel

IIIn

terv

entio

nM

ean

(SD

) or

%C

ontr

olM

ean

(SD

) or

%B(

95%

CI)

or

O

R(95

% C

I)*p-

valu

eB(

95%

CI)

or

O

R(95

% C

I)*p-

valu

e

Phys

ical

Act

ivity

Leis

ure

time-

MV

PA (m

in/w

eek)

N12

712

9Ba

selin

e36

5.7

(359

.4)

370.

4 (5

04.7

)6

mon

ths

428.

6 (4

42.5

)35

4.0

(444

.6)

77.3

(-12

.7 ;

167.

3)0.

092

70.6

(-24

.3 ;

165.

5)0.

144

12 m

onth

s37

0.8

(374

.3)

396.

9 (4

30.3

)-2

3.3(

-100

.5 ;

53.8

)0.

552

-27.

0 (-

104.

7; 5

0.7)

0.49

4Pu

blic

hea

lth g

uide

line

VPA

(%)

N12

212

3Ba

selin

e28

%20

%6

mon

ths

36%

21%

2.03

(1.0

8 ; 3

.82)

*0.

029

2.06

(1.0

7 ; 3

.99)

*0.

032

12 m

onth

s38

%27

%1.

51 (0

.82

; 2.7

9)*

0.18

41.

52 (0

.81

; 2.8

3)*

0.19

1

Die

tary

inta

keA

lcoh

ol (g

lass

es† /

wee

k)N

126

127

Base

line

12.7

(19.

2)11

.0 (1

8.8)

6 m

onth

s11

.8 (1

5.6)

10.6

(12.

2)0.

45 (-

2.48

; 3.

37)

0.76

3-0

.33

(-3.

20 ;

2.54

)0.

821

12 m

onth

s12

.5 (1

7.3)

9.7

(11.

0)2.

18 (-

0.93

; 5.

28)

0.16

82.

33 (-

0.90

; 5.

56)

0.15

7SS

Bs (g

lass

es/w

eek)

N12

412

7Ba

selin

e6.

4 (8

.8)

5.5

(7.4

)6

mon

ths

5.5

(6.5

)7.

5 (1

0.5)

-2.5

7 (-

4.35

; -0

.77)

0.00

5-2

.82

(-4.

67 ;

-0.9

7)0.

003

12 m

onth

s6.

2 (8

.5)

6.4

(8.5

)-0

.93

(-2.

52 ;

0.66

)0.

248

-0.9

6 (-

2.68

; 0.

63)

0.24

3Sn

acks

(pie

ces/

wee

k)N

119

121

Base

line

10.5

(9.1

)11

.9 (1

1.0)

6 m

onth

s8.

9 (7

.4)

10.2

(8.9

)-0

.82

(-2.

48 ;

0.83

)0.

327

-0.9

3 (-

2.66

; 0.

80)

0.28

912

mon

ths

8.9

(8.5

)10

.0 (8

.0)

-0.5

8 (-

2.33

; 1.

16)

0.51

1-0

.63

(-2.

47 ;

1.20

)0.

497

Frui

t (p

iece

s/w

eek)



5

N12

412

6Ba

selin

e10

.6 (7

.3)

11.6

(8.4

)6

mon

ths

11.3

(7.0

)10

.7 (8

.5)

1.15

(-0.

32 ;

2.62

)0.

125

1.19

(-0.

34 ;

2.62

)0.

101

12 m

onth

s11

.5 (7

.4)

11.9

(8.3

)0.

19 (-

1.46

; 1.

83)

0.82

40.

25 (-

1.44

; 1.

94)

0.76

9Ve

geta

bles

(spo

ons‡ /

wee

k)N

125

126

Base

line

12.3

(8.0

)12

.4 (7

.6)

6 m

onth

s12

.1 (6

.9)

11.1

(6.8

)0.

96 (-

0.61

; 2.

52)

0.22

91.

12 (-

0.48

; 2.

72)

0.16

812

mon

ths

11.9

(7.2

)11

.5 (8

.5)

0.44

(-1.

41 ;

2.29

)0.

639

0.62

(-1.

19 ;

2.43

)0.

498

B: u

nsta

ndar

dise

d re

gres

sion

coe

ffici

ent,

OR:

odd

s ra

tio,

MV

PA:

mod

erat

e to

vig

orou

s ph

ysic

al a

ctiv

ity,

VPA

: vi

goro

us p

hysi

cal a

ctiv

ity,

SSBs

: su

gar-

swee

tene

d be

vera

ges

Mod

el I

= c

rude

mod

el, a

djus

ted

for

base

line

valu

es

Mod

el II

= a

djus

ted

mod

el f

or b

asel

ine

valu

es, a

ge (c

ontin

uous

), ed

ucat

ion(

cate

goric

al),

mar

ital s

tatu

s(di

chot

omou

s), a

nd s

mok

ing

(dic

hoto

mou

s)*T

he n

umbe

rs in

the

tab

le r

epre

sent

val

ues

for

B, n

umbe

rs m

arke

d w

ith ‘*

’ rep

rese

nt o

dds

ratio

s†

glas

ses

= s

tand

ard

drin

k co

ntai

ning

app

roxi

mat

ely

10 g

ram

s of

alc

ohol

‡spo

on =

50

gram

s

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98 | Chapter 5

Discussion

Overall, the VIP in construction intervention positively impacted diet and physical activity, and

resulted in short-term favourable body weight related outcomes when compared to usual care.

After the intervention period, intervention participants showed significantly more positive changes

in physical activity and dietary behaviour. These effects did not translate into weight loss. While

changes in mean body weight and BMI were negligible across the intervention period for the

intervention group, the control group participants gained weight at 6 months, which resulted in

an intervention effect on body weight and BMI. Furthermore, the intervention group participants

showed a decrease in waist circumference which resulted in a significant intervention effect on

waist circumference at 6 months as well. At 12 months follow-up, differences were still present,

however slightly smaller and no longer statistically significant.

Weight-related outcomes

From the perspective of many worksite health promotion programmes, and the overall trend in

increasing body weight in the present study, preventing weight gain may be a positive and realistic

outcome. The net body weight effects are modest compared to other worksite interventions

ranging from -1.2 to -1.3kg and -0.3 to 0.5 kg/m2 for BMI [15,28]. An explanation for these

modest results might be that participation this worksite health promotion trial was not restricted

to a high risk group only (employees were not pre-selected on high body weight). The present

study started with participants that as a group at baseline were overweight, but not obese (mean

BMI < 28). In contrast, in weight loss interventions where participants are obese or who otherwise

present a specific risk profile, weight loss results are likely to be larger than those obtained from

a general worker population. Therefore, the weight loss results are not directly comparable to

the overall weight loss literature or to most studies conducted in other clinical settings. Still, the

lack of more impressive weight loss results in this study raises questions about the relevance of

the effects. Clinically relevant weight loss is associated with an improvement in the clinical risk of

adverse health problems [29]. Although often weight loss of 5% has been indicated as clinically

relevant, even smaller reductions in weight have been shown to result in clinically meaningful

reductions in important CVD risk factors and on risk of diabetes [30,31]. This indicates that very

small reductions in body weight could be considered relevant.

The goal of the intervention was to improve lifestyle behaviours that would be easy to implement

and could be maintained over time. These type of interventions can be incorporated in or

linked to routine health screening, which potentially increases reach as well as the likelihood of

implementation. It is important to address that the intervention was not designed to maximise

short-term weight loss. The lack of overall weight loss in the intervention group could be

attributable to intervention intensity. In other studies where weight loss has been a primary

outcome, more intensive approaches have typically been more effective than those with less



5

contact [32,33]. However, such intensive approaches have a number of limitations. Applying

high intensity programmes leads to more expenses and these are likely to appeal to only a small

percentage of those who would benefit because of the level of commitment required. In the

present study, even though the coaching sessions mostly took place during working hours and at

the workplace, some participants indicated lack of time as a reason not to participate or did not

complete all contacts.

It has been suggested that waist circumference is more sensitive to changes in energy balance

than is BMI [34-36]. In the present study, the overall effect on waist circumference was not

accompanied by reduction in body weight. Although reductions in central obesity are larger

when accompanied by weight loss, increases in physical activity have been associated with

significant reductions in waist circumference, despite small or no changes in body weight [37].

BMI reflects lean tissues as well as body fat. Physical activity provides metabolic adaptations

that are associated with reductions in abdominal fat and increases in fat free (skeletal muscle

mass) as well as metabolic efficiency of muscle. Since a substantial percentage of the study

participants had baseline waist circumferences that represent health risk (>102cm), the effect on

waist circumference is considered relevant also when considering the association with MSD and

central obesity [38].


Both changes in physical activity and diet could have contributed to the effects on weight

related outcomes. The intervention showed a positive effect on meeting the public guidelines

for vigorous physical activity. However, no intervention effects were found for leisure time MVPA.

This is in line with the study of Groeneveld et al. [39], who suggested that lack of effect may be

related to average high levels of baseline PA at work for construction workers. Furthermore, the

SQUASH questionnaire was not designed to measure energy expenditure and changes over time,

but to give an indication of habitual PA level [23]. It has been suggested that high intensity activity

measures might be more reliable, presumably because these activities are easier to recall. As a

result, responsiveness in measures of more intensive levels of PA could be higher. The intervention

effect on decreased intake of sugar-sweetened beverages (SSBs) could have contributed to the

effect on weight-related outcomes. Intakes of SSBs have been found to significantly contribute to

increased caloric intake and higher body weight [40,41].

Although short-term post intervention effects were found, comparable to other weight loss

or weight gain prevention studies [42,43], maintaining health behaviour changes and effects

on weight-related measures remains difficult. In general, this might be a result of relapse (not

maintaining behaviour change) in the intervention participants. A decrease in between-group

differences could also be the result of changes in favour of the control group participants. In the

present study, at 12-month follow-up, participants in the control group showed slight improvement

in several behavioural outcomes. The measurements conducted for the evaluation of the study

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100 | Chapter 5

effectiveness itself may have motivated control participants to improve health-related behaviour.

In addition, contamination between the intervention group participants and the controls could

not be completely ruled out. Contamination of the control group was expected to be minimal,

since personal coaching was only available for the intervention participants. However, behaviour

change in colleagues, especially dietary behaviour at work could have influenced control

participants. This could partly explain the decreased contrast in outcome measures between the

two groups at 12 months follow-up.


A strength of the present study is that it was conducted as a randomised controlled trial.

Randomisation was performed at the level of the individual, which reduces the probability of

confounding factors through baseline differences between intervention and control participants.

Another strength was that the intervention was tailored to the individual worker, which might

be especially important in a heterogeneous group of workers (e.g. ranging from crane drivers to

bricklayers) and when intervening on complex behaviours.

Several methodological limitations deserve attention as well. Diet and physical activity were

measured by self-report. The original study design comprised additional accelerometer

measurements. In the present trial, this appeared not feasible; insufficient complete data

samples were gathered suitable for analysis. Further, social desirability may have resulted in

an overestimation of fruit and vegetable intake, and underestimation of snack, alcohol, and

sugar-sweetened beverages intake, particularly in intervention group participants [44]. Accurate

assessment of actual behaviour without imposing a large burden on respondents (especially in

occupational groups where illiteracy is present) remains challenging.

Implications for future research

It is clear that (sustained) change to energy balance-related behaviour will result in effects on body

weight. It is recommended that further worksite health promotion research aims at identifying

methods to achieve long-term sustainable impact. Lifestyle interventions aimed at weight loss

achieve short-term success, but body weight re-gain is common. To prevent weight regain for

those who lost weight, specific strategies are required to maintain specific weight loss goals.

These strategies to maintain weight loss may also play an important role in preventing weight

gain among normal-weight individuals. However, there is still little evidence from trials what might

be effective long-term strategies. From observational studies it is suggested that, for example,

continued intervention contacts (face-to-face or by e-mail) [45] or continued self-monitoring

of weight [46] lead to sustained effects on body weight related outcomes. Complementary

intervention components at company level, for example strategies to enhance social support by

colleagues and supervisors, might also reinforce sustained effects [47].



5

Implications for practice

The intervention programme appeared feasible for blue collar workers with a relatively low

intensive intervention and promising short term effects. The programme needs to be adapted

to improve long term effectiveness, before implementation or broader implementation in other

settings can be recommended.

Conclusions

The results of this study indicate that a relatively low-intensive worksite intervention has the

potential to improve dietary and physical activity behaviour in blue collar construction workers,

and to contribute to the prevention of body weight gain. Further research is needed to improve

long-term effectiveness, and insight into effectiveness might be increased if more objective

measures of physical activity and diet are used.

So What? Implications for Health Promotion Practitioners and Researchers

What is already known on this topic

In the literature evidence is found for effectiveness of worksite physical activity and dietary

behaviour interventions on weight outcomes. The prevalence of overweight and obesity in blue

collar construction workers is higher than in the general adult population, however no effective

weight management programmes have been found targeted at this specific occupational group.

What does this article add?

The effectiveness of a newly developed targeted and tailored intervention is assessed in a

randomised controlled trial. The relatively low intensive lifestyle intervention appeared feasible

for blue collar workers with promising short-term effects.

What are the implications for health promotion practice or research?

Before implementation can be recommended, the programme needs to be adapted to improve

long-term effectiveness. It is recommended that for successful weight management further

worksite health promotion research aims at identifying methods to achieve long-term sustainable

impact.

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102 | Chapter 5

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18. Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser 2000, 894: i-253.

19. Viester L, Verhagen EALM, Proper KI et al.: VIP in construction: systematic development and evaluation of a multifaceted health programme aiming to improve physical activity levels and dietary patterns among construction workers. BMC Public Health 2012, 12: 89.

20. Bartholomew LK, Parcel GS, Kok G et al.: Planning health promotion programs: intervention mapping. San Francisco, CA: Jossey-Bass; 2006.

21. Lean ME, Han TS, Morrison CE: Waist circumference as a measure for indicating need for weight management. BMJ 1995, 311: 158-161.



5

22. Carey M, Markham C, Gaffney P et al.: Validation of a point of care lipid analyser using a hospital based reference laboratory. Ir J Med Sci 2006, 175: 30-35.

23. Wendel-Vos GCW, Schuit AJ, Saris WHM et al.: Reproducibility and relative validity of the short questionnaire to assess health-enhancing physical activity. J Clin Epidemiol 2003, 56: 1163-1169.

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36. Church TS, Martin CK, Thompson AM et al.: Changes in weight, waist circumference and compensatory responses with different doses of exercise among sedentary, overweight postmenopausal women. PLoS ONE 2009, 4: e4515.

37. Ross R, Bradshaw AJ: The future of obesity reduction: beyond weight loss. Nat Rev Endocrinol 2009, 5: 319-325.

38. Shiri R, Solovieva S, Husgafvel-Pursiainen K et al.: The association between obesity and the prevalence of low back pain in young adults: the Cardiovascular Risk in Young Finns Study. Am J Epidemiol 2008, 167: 1110-1119.

39. Groeneveld IF, Proper KI, van der Beek AJ et al.: Short and long term effects of a lifestyle intervention for construction workers at risk for cardiovascular disease: a randomized controlled trial. BMC Public Health 2011, 11: 836.

40. Malik VS, Schulze MB, Hu FB: Intake of sugar-sweetened beverages and weight gain: a systematic review. Am J Clin Nutr 2006, 84: 274-288.

41. Vartanian LR, Schwartz MB, Brownell KD: Effects of soft drink consumption on nutrition and health: a systematic review and meta-analysis. Am J Public Health 2007, 97: 667-675.

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104 | Chapter 5

43. Perri MG, Sears SFJ, Clark JE: Strategies for improving maintenance of weight loss. Toward a continuous care model of obesity management. Diabetes Care 1993, 16: 200-209.

44. Miller TM, bdel-Maksoud MF, Crane LA et al.: Effects of social approval bias on self-reported fruit and vegetable consumption: a randomized controlled trial. Nutr J 2008, 7: 18.

45. Wadden TA, Butryn ML, Wilson C: Lifestyle modification for the management of obesity. Gastroenterology 2007, 132: 2226-2238.

46. Wing RR, Phelan S: Long-term weight loss maintenance. Am J Clin Nutr 2005, 82: 222S-225S.

47. Greaves CJ, Sheppard KE, Abraham C et al.: Systematic review of reviews of intervention components associated with increased effectiveness in dietary and physical activity interventions. BMC Public Health 2011, 11: 119.

Chapter 6The effect of a health promotion intervention

for construction workers on work-related outcomes:

results from a randomised controlled trial


International Archives of Occupational and Environmental Health. 2015 88;789-798

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106 | Chapter 6

Abstract

Purpose: The objective of the present study is to investigate the effects of a worksite health

promotion intervention on musculoskeletal symptoms, physical functioning, work ability, work-

related vitality, work performance, and sickness absence.

Methods: In a randomised controlled design, 314 construction workers were randomised into

an intervention group (n=162) receiving personal coaching, tailored information and materials,

and a control group (n=152) receiving usual care. Sickness absence was recorded continuously

in company records, and questionnaires were completed before, directly after the 6-month

intervention period, and 12 months after baseline measurements. Linear and logistic regression

analyses were performed to determine intervention effects.

Results: No significant changes at 6 or 12 months follow-up were observed in musculoskeletal

symptoms, physical functioning, work ability, work-related vitality, work performance, and

sickness absence as a result of the intervention.

Conclusions: This study shows that the intervention was not statistically significantly effective on

secondary outcomes. Although the intervention improved physical activity, dietary, and weight-

related outcomes, it was not successful in decreasing musculoskeletal symptoms and improving

other work-related measures. Presumably, more multifaceted interventions are required to

establish significant change in these outcomes.


Effect evaluation on secondary outcomes | 107

6

Introduction

Workers in the construction industry are often exposed to physically demanding work tasks.

These include, amongst others, the lifting of heavy loads and working in awkward postures.

High physical work demands increase the risk for the development of musculoskeletal symptoms

[1,2]. In blue collar construction workers musculoskeletal disorders (MSD) are the most prevalent

work-related health problem [3,4]. In addition, in the Netherlands, the workforce in physically

demanding work is aging and the risk of MDS also increases with age [5,6]. As such, MSD are a

major cause for sickness absence, work disability, early exit from work, and are related to lower

work performance, and consequently constitute an extensive social, medical as well as economic

problem [7,8].

The prevalence of overweight and obesity in construction workers is higher than in the general

adult population [9-11]. Both MSD and a high BMI are negatively associated with several work-

related outcomes, but are also associated with each other [12-16]. Since both factors are

highly prevalent in blue collar construction workers, these might contribute to the high risk for

developing health disorders and associated adverse work-related outcomes compared to workers

in other industries and the general population [17,18]. This emphasises the importance to reduce

the burden of overweight and obesity in this particular group of workers.

Both diet and physical activity are considered of importance in achieving and maintaining a

healthy body weight [19,20]. Worksite health promotion programmes aimed at physical activity

and diet were found to be effective on weight-related outcomes [21-23]. Moreover, workplace

health promotion programs that improve physical activity levels have been shown to also reduce

the risk on MSD [24]. A lifestyle intervention among those with jobs involving moderately heavy

or heavy work also showed a reduction in prevalence of low back pain [25]. Although intervention

studies with MSD as primary outcome have not often been targeted at lifestyle factors, there is

evidence from observational studies suggesting that health promotion should be considered in

the prevention of MSD [26-29]. Beneficial effects on work-related outcomes, including sickness

absence, productivity and work ability, have been reported resulting from preventative measures

targeted at healthy lifestyle [30-33]. Consequently, implementation of worksite programmes

targeted at lifestyle factors may be a promising strategy to improve worker health and other

outcomes relevant to employers.

In the Vitality in Practice (VIP) in Construction study it was hypothesised that a worksite health

promotion intervention, aiming at improving physical activity and diet, could positively change

body weight related outcomes, musculoskeletal symptoms and work-related measures [34]. The

aim of the present study was to evaluate whether the intervention programme for blue collar

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construction workers reduced musculoskeletal symptoms, limitations in physical functioning and

sickness absence, and increased work-related vitality, work performance and work ability.

Methods

Study design and population

The effectiveness of the programme was assessed in a randomised controlled trial (RCT). The

research population consisted of consenting blue collar employees of a construction company.

All employees who attended a non-compulsory periodic health screening (PHS) and who were

not on sick leave for more than 4 weeks prior to the PHS were eligible for inclusion. In total, 314

participants were recruited over a 15-month period (March 2010 to June 2011), and randomised

to an intervention (n=162) or control group (n = 152). Participants completed questionnaires at

baseline (T0), at 6 months (T1), and at 12 months (T2). Written informed consent was obtained

from participants before enrolment in the study.

The study design and procedures were approved by the Medical Ethics Committee of the VU

University Medical Center, and the trial has been registered in the Netherlands Trial Register (NTR,

www.trialregister.nl): NTR2095.

Randomisation, blinding and sample size

Following baseline measurements, participants were randomly assigned to either the intervention

or the control group by a computer generated list using SPSS 15 (SPSS Inc. Chicago, Illinois,

USA). The randomization was prepared and performed by an independent researcher. Whereas

participants could have been aware of the allocated arm, data collectors and analyst were kept

blinded to the allocation. The sample size was calculated to identify an effect on body weight

(Viester et al., 2012). Based on that calculation in each study group (intervention and control) 130

participants were needed at follow-up.

Intervention

The intervention programme aimed at the prevention and reduction of overweight and

musculoskeletal symptoms, and was developed and implemented via the Intervention Mapping

protocol [34,35]. The full programme has been described previously [34]. In short the intervention

consisted of an on-site lifestyle coaching program tailored to the participant’s weight status

(BMI and waist circumference), physical activity level, and stage-of-change. The intervention

program focused on improving (vigorous) physical activity levels and healthy dietary behaviour.

The programme consisted of tailored lifestyle information, lifestyle coaching sessions, exercise

instructions, and the ‘VIP in construction toolbox’. This toolbox consisted of an overview of the

company’s health promoting facilities, a waist circumference measuring tape, a pedometer, a BMI

card, a calorie guide, healthy recipes, and a lifestyle knowledge test.



6

The intervention was delivered face-to-face and via telephone by personal health coaches

(PHC) who were trained specifically for the study. Face-to-face coaching sessions took place at

the worksite during working hours. An overview of the timing and duration of the contacts is

presented in table 1. Participants additionally received “Personal Energy Plan” (PEP) forms to

record their goals and action plans, and to be used during the follow-up health coaching sessions.

Intervention providers were not involved in the outcome assessment.

Table 1 Coaching contact schedule

PHC contact schedule 2 weeks 1 month 2 months 3 months 4 monthsPre-contemplation stage Intake (60 min

face-to-face)Follow-up 1 (30 min; telephone)




Intake (60 min face-to-face)



Action/maintenance stage

Intake (30 min face-to-face)

Follow-up 1(10 min telephone)

PHC = personal health coach

The control group received care as usual and was only contacted for the baseline and follow-up

measurements.

Outcome measures

The present study investigated the effectiveness of the intervention on musculoskeletal symptoms,

physical functioning and work-related outcomes (work ability, work performance, work-related

vitality, and sickness absence). Sickness absence data were obtained from the company’s

registration system after follow-up measurements were completed. All other data were obtained

using questionnaires.

Health-related measures

Musculoskeletal symptoms

The prevalence of musculoskeletal symptoms during the past three months was assessed using

the Dutch Musculoskeletal Questionnaire (DMQ), which has been validated for different body

regions [36]. The occurrence of pain or discomfort was rated on a four-point scale (never,

sometimes, frequently, and prolonged). For the current analysis the measure was dichotomized;

answer categories ‘frequently’ or ‘prolonged’ were classified as having musculoskeletal symptoms,

whereas categories ‘never’ or ‘sometimes’ were classified as having no musculoskeletal symptoms.

Body regions were grouped into back (upper and lower back), neck/shoulders, upper extremities

(elbows and wrist/hands), and lower extremities (hips/thighs, knees, and ankle/feet).

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110 | Chapter 6

Physical functioning

Physical functioning was measured using a sub-scale of the RAND-36, evaluating functional

status [37,38]. The RAND-36 cluster on role limitations caused by physical problems consists of

4 items, and ranges from 0-100 points (higher scores indicating less limitations), with a score of

79.4 considered average [38]. The RAND-36 health survey is a widely adopted, and reliable and

valid measurement of health-related quality-of-life [39]. In the present study, the validated Dutch

version was used.

Work-related measures

Work ability was assessed with the Work Ability Index (WAI) [40-42]. The WAI covers 7 dimensions;

current work ability, work ability in relation to job demands, number of current diseases, work

impairment due to diseases, sickness absence days during past 12 months, own prognosis of

work ability in next two years, and mental resources. Total scores over all dimensions range

from 7–49, with 4 categories: poor (7-27 points), moderate (28-36 points), good (37-43 points),

excellent (44-49 points).

Work-related vitality, defined as vigour, was assessed through a subscale of the Utrecht

Engagement Scale (UWES) that refer to high levels of energy and resilience, the willingness to

invest effort, not being easily fatigued, and persistence in the face of difficulties [43]. The answers

were rated on a 7 point scale from never (0) to daily (6). The mean score of the items resulted in

the work-related vitality score, with a higher score indicating a better work-related vitality.

Work performance was measured using a single item from the Health Work Performance

Questionnaire (WHO-HPQ)[44,45] asking workers to report their overall work performance on a

10-point scale over the past four weeks.

Sickness absence data were collected directly from company records. For the analysis, cumulative

sickness absence data over 6-month periods were used (pre-, during-, and post-intervention).

Sickness absence has a skewed distribution with a substantial fraction clustered at the value zero.

Therefore, sickness absence was dichotomized into no or short-term sickness absence (<=7 days),

and long-term sickness absence (> 7 days).

Statistical analysis

The analysis was conducted with all available subjects at 6 and 12 months of follow-up. All

available data of the participants, regardless of whether or not they actually (fully) received

the intervention, were used for analysis. Data on potential confounders and effect modifiers

were assessed through the baseline questionnaire and included age, smoking status, education

level, and marital status. For all variables potential baseline differences were checked between

intervention and control group.



6

Linear and logistic regression analyses were performed for the different outcome measures, both

with 6-month and 12-month follow-up as the dependent variables. Analyses were adjusted for

the baseline levels. Analyses were performed using SPSS 20.0 (SPSS Inc. Chicago, Illinois, USA).

For all analyses, a two-tailed p-value of <0.05 was considered statistically significant.

Results

In total, 314 workers responded to the baseline questionnaire. At 12 months follow-up, 83%

of the participants completed all measurements; 22 workers of the control group (14%) and 31

workers of the intervention group (19%) did not complete all follow-up measurements. Figure

1 presents the flow chart of the participants throughout the trial. Baseline characteristics are

presented in table 2. No differences between groups were found for key variables.

Table 2 Baseline characteristics

All Intervention ControlNumber of participants N= 314 N= 162 N= 152Age, mean (SD) 46.6 (9.7) 46.3 (9.9) 47.0 (9.5)

Current musculoskeletal symptoms Back (%) 28.3 (89/314) 32.7 (53/162) 23.7 (36/152) Neck/shoulder (%) 20.1 (63/314) 20.4 (33/162) 19.7 (30/152) Upper extremity (%) 13.4 (42/314) 15.4 (25/162) 11.2 (17/152) Lower extremity (%) 28.7 (90/314) 29.6 (48/162) 27.6 (42/152)

BMI (kg/m2) 27.4 (3.7) 27.3 (3.5) 27.4 (3.9) Normal (<25) (%) 30.0 29.2 30.9 Overweight (25-29.9) (%) 47.3 50.9 43.4 Obese (>30) (%) 22.7 19.9 25.7

Smoking (Yes, %) 29.4 29.0 29.7

Table 3 shows complete cases intervention effects on work-related vitality, work performance,

work ability, and physical functioning. For all outcome measures, a positive value for B, which

represents the estimate (unstandardised coefficient) resulting from the regression analyses, can

be interpreted as a positive intervention effect. No statistically significant differences were found

for any of the outcome variables after 6 and 12 months of follow-up.

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112 | Chapter 6

Table 3 Intervention effects for work-related vitality, work performance, and work ability after 6 and 12 months follow-up

Intervention group(mean, SD)

Control group(mean, SD)

B 95%CI p-value

Work-related vitality N 113 110Baseline 4.98 (0.90) 4.99 (1.04)6 months 5.01 (0.94) 4.83 (1.08) 0.19 (-0.02 ; 0.40) 0.08112 months 4.82 (1.12) 4.82 (1.10) 0.01 (-0.22 ; 0.23) 0.938Work performance N 113 116Baseline 7.6 (1.1) 7.9 (1.0)6 months 7.7 (0.8) 7.6 (1.2) 0.13 (-0.13 ; 0.38) 0.34012 months 7.5 (1.4) 7.6 (1.4) -0.08 (-0.45 ; 0.28) 0.656Work ability N 99 93Baseline 40.6 (5.3) 40.8 (4.9)6 months 41.3 (4.1) 40.7 (5.2) 0.72 (-0.33 ; 1.77) 0.17712 months 41.3 (4.7) 40.9 (5.1) 0.53 (-0.59 ; 1.65) 0.348

Physical functioningN 127 125Baseline 88.6 (25.3) 87.8 (26.7)6 months 88.0 (27.6) 88.0 (25.0) -0.29 (-6.38 ; 5.79) 0.92512 months 86.2 (28.7) 85.4 (28.8) 0.45 (-6.21 ; 7.10) 0.895


The intervention did not result in statistically significant effects on musculoskeletal symptoms

(table 4). Although for back symptoms at 6 and 12 months follow-up (OR 0.69, 95%CI: 0.36-

1.36, and 0.76, 95%CI: 0.38-1.52, respectively) and lower extremity symptoms at 12 months (OR

0.61, 95%CI: 0.32-1.16) the odds ratios were in favour of the intervention group, differences

reached no statistical significance.

Sickness absence

Table 5 shows mean days of sickness absence in the past 6 months and table 3 presents the

course of sickness absence for the study group, dichotomized into no or short term, and long-

term sickness absence. Directly following the intervention, the 6-month prevalence of long-

term sickness absence was lower in the intervention group than in the control group. At 12

months sickness absence was slightly higher in the intervention group compared to the control

group. However, at both 6 and 12 months the between group differences were not statistically

significant.



6

Table 4 Intervention effects (OR (95%CI) or B (95%CI)) for musculoskeletal symptoms and sickness absence after 6 and 12 months follow-up

Intervention group Control group OR 95%CIN % N %

Musculoskeletal symptomsBack symptomsBaseline 39 30.2 32 24.86 months 25 19.8 30 23.4 0.69 (0.36; 1.36)12 months 23 18.6 25 19.4 0.76 (0.38; 1.52)Neck/shoulder symptomsBaseline 21 16.2 27 20.96 months 20 15.8 24 18.8 0.92 (0.46; 1.84)12 months 21 16.2 23 17.8 1.02 (0.50; 2.10)Upper extremity symptoms Baseline 17 13.3 16 12.56 months 12 9.6 11 8.7 1.18 (0.46; 2.98)12 months 13 10.2 13 10.2 0.98 (0.42; 2.28)Lower extremity symptomsBaseline 35 27.1 37 28.96 months 31 24.6 29 22.8 1.16 (0.62; 2.19)12 months 26 20.2 36 28.1 0.61 (0.32; 1.16)Sickness absenceBaseline No or short-term (<=7days) 87 69.0 94 72.9 Long-term 39 31.0 35 27.16 months 0.86 (0.47; 1.58) No or short-term (<=7days) 100 79.4 100 77.5 Long-term 26 20.6 29 22.512 months 1.19 (0.66; 2.15) No or short-term (<=7days) 94 74.6 101 78.3 Long-term 32 25.4 28 21.7

Table 5 Average number of sickness absence days for the intervention and the control group during 6 month periods before the baseline and follow-up measurements.

Intervention ControlN Mean SD Median N Mean SD Median

Baseline 126 11.1 21.8 2.0 129 8.4 17.6 06 months 126 7.7 21.8 0 129 7.5 20.2 012 months 126 8.5 20.6 0 129 7.5 16.9 0

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114 | Chapter 6

Discussion

The aim of this study was to evaluate the effectiveness on secondary outcomes of a health

promotion intervention aiming at increasing physical activity and improving dietary behaviour

in construction workers. No significant short- or long-term intervention effects were found on

musculoskeletal symptoms, physical functioning, work-related vitality, work performance, work

ability, or sickness absence. These findings will be discussed for the different outcome measures.


The lack of observed statistically significant intervention effects on musculoskeletal symptoms is

in line with other intervention studies in the construction sector [46-48]. Overall in the present

study, the prevalence of workers reporting musculoskeletal symptoms declined. For back and

lower extremity symptoms, odds ratios were in favour of the intervention group, although not

statistically significant. Since sample size calculations were performed to determine effects on the

study’s primary outcome measure (body weight), for other outcome measures the study could

have been underpowered.

In the current study it was hypothesised that an improvement in physical capacity through

increased physical activity, and a decrease in workload through a reduction of overweight, would

be effective in preventing or reducing musculoskeletal symptoms.

Although it is still not clear what type of exercise should be recommended, several reviews support

the use of exercise as an effective strategy for the prevention or treatment of musculoskeletal

conditions, including a wide range of interventions, such as increasing general physical activity

levels, general exercise, and specific body-region exercises for strength and flexibility [49,50].

The current intervention consisted of a combination of exercise prescription and coaching on

improving physical activity levels, which implied that participants self-selected their physical

activity goals. Although an increase in vigorous physical activity in the intervention group was

found, this may not have been exercise or physical activity selected for the purpose to prevent

or reduce musculoskeletal symptoms, and might as a result not have been the most appropriate

type of activity or exercise to reduce or prevent specific symptoms. Additionally, the increase

in physical activity levels may not have led to sufficient physical capacity improvements to be

effective on musculoskeletal symptoms.

Presumably, the effects on outcomes related to body weight, as found in this study, were not

substantial enough to have a direct effect on MSD. Another explanation could be that the

intervention period was not long enough for effects on MSD to occur. However, prevention of

body weight gain or reducing excess body weight could have future effects by lowering both

systemic and metabolic risk factors. Systemic risk factors include a combination of mechanical

load on weight bearing joints and work postures. Obesity is one of the components of the



6

metabolic syndrome, and metabolic risk factors are increasingly being recognised as a possible

cause of MSD [51,52].

To reduce or prevent musculoskeletal symptoms it has been suggested that multi-component

interventions are potentially more effective [53]. In these programmes exercise or training

interventions are combined with components addressing environmental and/or organisational

issues. For example, the physical and psycho-social work environment has been recognised as

risk factors for MSD in the construction sector. This is supported by findings from interviews with

employees during the development of the present study as well as in the study of Oude Hengel

et al. [34,54]. Combining health and lifestyle promotion with efforts to decrease workload and/or

change working conditions is probably necessary for programs to be effective.

Work-related vitality, physical functioning, work performance, and work ability

In addition to the explanation of the lack of effect as described in the section on musculoskeletal

symptoms, the initially high scores for work-related vitality, physical functioning and WAI could

explain the lack of further detectable increase in these outcomes, i.e. a ceiling effect. For work-

related vitality, this was also found in previous studies [55]. The lack of effect on the WAI in the

current study is in accordance with previous studies on work ability [48,56,57]. The average

baseline WAI score of 40.7 was only slightly higher compared to the average score of Finnish

men in the same age group and engaged in physical work [58], and scores ranging from 37 to 43

are regarded as good work ability. For the physical functioning dimension of the SF-36, baseline

values of the study population largely exceeded norm values of a reference population.

Sickness absence

With regard to sickness absence, the lack of effects is in line with other studies among blue collar

worker [48,59]. During the trial period, several factors in addition to illness, which are related to

sickness absence, may have influenced the results. Not all absence can be attributed to sickness;

sickness absence has been associated with, for example, socioeconomic factors, organisational

features, job content and attitudes to work [60]. This is especially of concern when using total

sickness absence data, compared to absence related to a specific condition, such as MSD. The

current economic recession, that strongly affected the construction sector during the trial period,

may have distorted effects on total sickness absence or patterns of sickness absence. Stress,

increased (perceived) workload, and fear of job-loss are factors that might have played a larger

role under these circumstances during the study period.

For all outcome measures, the lack of intervention effects can in part be attributed to the level

of implementation of the program. In a process evaluation of the program it was concluded

that the extent to which the program was implemented as intended was modest [61]. Although

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116 | Chapter 6

participants’ satisfaction with the program and dose delivered by the health coaches was high,

exposure and fidelity were not optimal. The compliance to the coaching sessions was acceptable,

but the implementation of the exercise component was not successful. Although approximately

two thirds of the participants indicated to have done the exercises, only a small percentage

exercised regularly as prescribed by the program.

The trial findings could be applicable to a larger population of manual labour workers. The

intervention was implemented in a diverse group of blue collar workers with comparable

participation rates for the subunits of the construction company. However, when generalizing the

results from the specific setting of the RCT to a larger worker population, it should be taken into

account that compared to the original population older workers were slightly overrepresented in

the study population [61].


Strengths of the study include the randomised controlled trial design, and obtaining sickness

absence data from company records. The use of sickness absence data from company records is

preferred since it is more accurate than data gathered via self-report [62].

Some limitations have to be addressed as well. First, power calculation was performed on the

primary outcome measure of the study, i.e. body weight. As a result, group sizes might have

been below the required number to establish inter-group differences for other study outcomes.

Further, missing data on items of the work ability index resulted in a reduced number of complete

cases. For participants who did not complete all 7 items, the index could not be determined.

With exception of sickness absence, all outcome measures were obtained using self-report which

may lead to over- or under-estimations of the outcomes. Finally, although contamination of the

control group participants was expected to be minimal, since only intervention participants had

access to coaching and the toolbox, it could not be completely ruled out. Behaviour change in

colleagues working at the same worksites could have influenced control participants.

Implications for practice and future research

Maintaining a healthy and productive workforce depends on a wide variety of factors. It is

recommended that future interventions aiming to improve work-related outcomes also include

organisational and/or environmental components to more effectively target factors related to

work ability and performance.

Theoretically, improving physical capacity (i.e. improving muscle function or increasing oxidative

capacity) by increasing physical activity and exercise might prevent or reduce musculoskeletal

symptoms. In the present study we did not include measures to monitor possible effects of

increased physical activity levels on physical capacity. To increase knowledge on the relevance



6

of increasing physical capacity in this group of workers and to contribute to insight into optimal

type, duration and intensity of exercise, future studies should include such measures related to

physical capacity.

Conclusion

The results of this RCT did not show effects of the programme on musculoskeletal symptoms,

physical functioning, work-related vitality, work performance, work ability, or sickness absence.

Although the intervention programme improved physical activity levels, dietary outcomes, and

weight-related outcomes at 6 months, it was not successful in improving other health-related

and work-related outcomes. In conclusion, for all outcome measures in the present paper it

could be argued that they are affected by additional factors to those included in the current

conceptual model of the study [34]. Based on the results of the present study, organisations

attempting to improve worker health- and work-related outcomes should provide additional

program components. Although a non-significant decline in musculoskeletal symptoms was

observed, without co-intervening on (psycho-social) organisational aspects in a more multifaceted

intervention, the potential of improving these outcomes by health promotion is probably limited.

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30. Cancelliere, C., Cassidy, J. D., Ammendolia, C., Cote, P., (2011). Are workplace health promotion programs effective at improving presenteeism in workers? A systematic review and best evidence synthesis of the literature. BMC.Public Health 11, 395.

31. Proper, K. I., van der Beek, A. J., Hildebrandt, V. H., Twisk, J. W. R., van Mechelen, W., (2004). Worksite health promotion using individual counselling and the effectiveness on sick leave; results of a randomised controlled trial. Occup Environ.Med 61, 275-279.

32. Kuoppala, J., Lamminpaa, A., Husman, P., (2008). Work health promotion, job well-being, and sickness absences--a systematic review and meta-analysis. J Occup Environ.Med 50, 1216-1227.

33. von Thiele Schwarz, U., Hasson, H., (2012). Effects of worksite health interventions involving reduced work hours and physical exercise on sickness absence costs. J Occup Environ.Med 54, 538-544.

34. Viester, L., Verhagen, E. A. L. M., Proper, K. I., van Dongen, J. M., Bongers, P. M., van der Beek, A. J., (2012). VIP in construction: systematic development and evaluation of a multifaceted health programme aiming to improve physical activity levels and dietary patterns among construction workers. BMC.Public Health 12, 89.

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44. Kessler, R. C., Barber, C., Beck, A., Berglund, P., Cleary, P. D., McKenas, D., Pronk, N., Simon, G., Stang, P., Ustun, T. B., Wang, P., (2003). The World Health Organization Health and Work Performance Questionnaire (HPQ). J Occup Environ.Med 45, 156-174.

45. Kessler, R. C., Ames, M., Hymel, P. A., Loeppke, R., McKenas, D. K., Richling, D. E., Stang, P. E., Ustun, T. B., (2004). Using the World Health Organization Health and Work Performance Questionnaire (HPQ) to evaluate the indirect workplace costs of illness. J Occup Environ.Med 46, S23-S37.

46. Gram, B., Holtermann, A., Sogaard, K., Sjogaard, G., (2012). Effect of individualized worksite exercise training on aerobic capacity and muscle strength among construction workers - a randomized controlled intervention study. Scand.J Work Environ.Health. 38:467-475

47. Gram, B., Holtermann, A., Bultmann, U., Sjogaard, G., Sogaard, K., (2012). Does an exercise intervention improving aerobic capacity among construction workers also improve musculoskeletal pain, work ability, productivity, perceived physical exertion, and sick leave?: a randomized controlled trial. J Occup Environ.Med 54, 1520-1526.

48. Oude Hengel, K. M., Blatter, B. M., van der Molen, H. F., Bongers, P. M., van der Beek, A. J., (2013). The effectiveness of a construction worksite prevention program on work ability, health, and sick leave: results from a cluster randomized controlled trial. Scand.J Work Environ.Health. 39:456-467

49. Roddy, E., Zhang, W., Doherty, M., (2005). Aerobic walking or strengthening exercise for osteoarthritis of the knee? A systematic review. Ann.Rheum.Dis. 64, 544-548.

50. Hayden, J. A., van Tulder, M. W., Malmivaara, A. V., Koes, B. W., (2005). Meta-analysis: exercise therapy for nonspecific low back pain. Ann.Intern.Med 142, 765-775.

51. Berenbaum, F., (2013). Osteoarthritis as an inflammatory disease. Osteoarthritis.Cartilage. 21, 16-21.

52. Sellam, J., Berenbaum, F., (2013). Is osteoarthritis a metabolic disease? Joint Bone Spine 80, 568-573.

53. Kennedy, C. A., Amick, B. C., Dennerlein, J. T., Brewer, S., Catli, S., Williams, R., Serra, C., Gerr, F., Irvin, E., Mahood, Q., Franzblau, A., Van Eerd, D., Evanoff, B., Rempel, D., (2010). Systematic review of the role of occupational health and safety interventions in the prevention of upper extremity musculoskeletal symptoms, signs, disorders, injuries, claims and lost time. J Occup Rehabil. 20, 127-162.

54. Oude Hengel, K. M., Joling, C. I., Proper, K. I., Blatter, B. M., Bongers, P. M., (2010). A worksite prevention program for construction workers: design of a randomized controlled trial. BMC.Public Health 10, 336.



6

55. Strijk, J. E., Proper, K. I., van Mechelen, W., van der Beek, A. J., (2013). Effectiveness of a worksite lifestyle intervention on vitality, work engagement, productivity, and sick leave: results of a randomized controlled trial. Scand.J Work Environ.Health 39, 66-75.

56. Nurminen, E., Malmivaara, A., Ilmarinen, J., Ylostalo, P., Mutanen, P., Ahonen, G., Aro, T., (2002). Effectiveness of a worksite exercise program with respect to perceived work ability and sick leaves among women with physical work. Scand.J Work Environ.Health 28, 85-93.

57. Pohjonen, T., Ranta, R., (2001). Effects of worksite physical exercise intervention on physical fitness, perceived health status, and work ability among home care workers: five-year follow-up. Prev.Med 32, 465-475.

58. Ilmarinen, J., Tuomi, K., Klockars, M., (1997). Changes in the work ability of active employees over an 11-year period. Scand.J Work Environ.Health 23 Suppl 1, 49-57.

59. Jorgensen, M. B., Faber, A., Hansen, J. V., Holtermann, A., Sogaard, K., (2011). Effects on musculoskeletal pain, work ability and sickness absence in a 1-year randomised controlled trial among cleaners. BMC.Public Health 11, 840.

60. Briner, R. B., (1996). ABC of work related disorders. Absence from work. BMJ 313, 874-877.

61. Viester, L., Verhagen, E. A. L. M., Bongers, P. M., van der Beek, A. J., (2014). Process evaluation of a multifaceted health programme aiming to improve physical activity levels and dietary patterns among construction workers. J Occup Environ Med 56,1210-7.

62. Ferrie, J. E., Kivimaki, M., Head, J., Shipley, M. J., Vahtera, J., Marmot, M. G., (2005). A comparison of self-reported sickness absence with absences recorded in employers’ registers: evidence from the Whitehall II study. Occup Environ.Med 62, 74-79.

Chapter 7Cost-effectiveness and return-on-investment of a worksite

intervention aimed at improving physical activity and

nutrition among construction workers

Johanna M. van Dongen, Laura Viester, Marieke F. van Wier, Judith E. Bosmans,

Evert A.L.M. Verhagen, Maurits W. van Tulder, Paulien M. Bongers, Allard J. van der Beek

To be submitted

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124 | Chapter 7

Abstract

Objectives: To conduct a cost-effectiveness and return-on-investment (ROI) analysis of a worksite

physical activity and nutrition program for construction workers in comparison with usual practice.

Methods: The intervention consisted of generic as well as tailored health information and

personal health counseling. A total of 314 participants were randomized to the intervention

(n=162) or control group (n=152). Data on body weight, waist circumference, musculoskeletal

disorders (MSD), work-related vitality, and job satisfaction were collected at baseline, 6, and 12

months. Sickness absence data were collected from company records. Other cost data were

collected with 3-monthly questionnaires. Missing data were imputed using multiple imputation.

Cost-effectiveness analyses were conducted from both the societal and employer’s perspective.

A ROI analysis was performed from the employer’s perspective. Bootstrapping techniques were

used to assess the uncertainty of the results.

Results: Intervention costs per participant were €178 from the societal perspective (bottom-

up micro-costed) and €287 from that of the employer (market prices). At 12-month follow-

up, no statistically significant cost and effect differences were found. The probabilities of cost-

effectiveness for body weight, waist circumference, and MSD gradually increased with an

increasing ceiling ratio to 0.84 (willingness-to-pay = €21,000/kg), 0.77 (willingness-to-pay =

€18,000/cm), and 0.84 (willingness-to-pay = €42,000/person prevented from having a MSD),

respectively. The probabilities of cost-effectiveness for work-related vitality and job satisfaction

were low at all ceiling ratios (≤0.54). Financial return estimates were positive, but their confidence

intervals were rather wide and none of them was statistically significant.

Conclusion: The intervention’s cost-effectiveness in improving weight-related outcomes and

MSD depends on the societal and employer’s willingness-to-pay for these effects and the

probability of cost-effectiveness that they consider acceptable. From the employer´s perspective,

the intervention was not cost-effective in improving work-related vitality and job satisfaction.

Also, due to a high level of uncertainty, it cannot be concluded that the intervention was cost-

beneficial to the employer.


Economic evaluation | 125

7

Introduction

Excessive body weight and musculoskeletal disorders (MSD) have a serious impact on public

health in many developed countries (1-5). In the Netherlands, the combined prevalence of

overweight (Body Mass Index [BMI] 25 - 30 kg/m2) and obesity (BMI ≥ 30 kg/m2) is 48% among

adults (6), and that of MSD is estimated to be 39% in adult men and 45% in adult women (7).

Among construction workers, these prevalences are even higher (8;9). Both conditions not only

reduce a person’s well-being, but also impose a large economic burden on companies and society

as a whole due to increased absenteeism, presenteeism (i.e. reduced productivity while at work),

and healthcare consumption (10-12).

The workplace presents a useful setting to combat the high prevalence of excessive body weight

and MSD, as it provides social and organizational support structures that can help improve risk

behaviours and many companies have the infrastructure available to offer behaviour change

interventions at relatively low costs (13). In addition, worksite physical activity and nutrition

programs in particular, cannot only reduce body weight (14) and MSD prevalence (15), but may

also generate cost savings to a company through reduced absenteeism (16) and presenteeism (17).

Therefore, in the VIP in Construction study, a worksite physical activity and nutrition program was

developed aimed at preventing and reducing overweight and MSD among construction workers

(i.e. VIP in Construction intervention) (18). An evaluation of the intervention’s effectiveness has

been reported elsewhere (19;20).

Decisions about investments in worksite health promotion programs typically lie by the company

management. In doing so, they are not just interested in the effectiveness of such interventions,

but also in their impact on the company’s bottom-line (21;22). To provide this information,

return-on-investment (ROI) analyses can be performed in which the costs of an intervention are

compared to the company’s resulting financial savings (23;24). However, as health outcomes

are not directly considered in a ROI analysis and other stakeholders may reap a large part of the

benefits (e.g. health insurance companies), cost-effectiveness analyses (CEAs) and analyses from

the broader societal perspective are of importance as well.

The present study aimed to conduct CEAs and a ROI analysis, in which the VIP in Construction

intervention was compared to usual practice. CEAs were performed from both the societal and

employer’s perspective, and the ROI analysis from that of the employer.

Methods

Study design

Analyses were conducted alongside a 12-month randomized controlled trial (RCT), which took

place from 2010 to 2012. The study protocol was approved by the Medical Ethics Committee of

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126 | Chapter 7

the VU University Medical Center (18), and the trial has been registered in the Netherlands Trial

Register (NTR2095).

Participants

All blue collar workers of a Dutch construction company who were invited for a voluntary

periodical health screening at the occupational health service between February 2010 and October

2011 were recruited for the study. Workers who were on long-term sick leave (≥4 weeks) were

excluded. At baseline, all workers who decided to participate in the study provided informed

consent. After baseline measurements, participants were randomized to the intervention or

control group. Randomization took place at the individual level and was performed by a research

assistant using a computer-generated randomization sequence in SPSS (v15, Chicago, IL). The

research assistant had no information on the participants to ensure allocation concealment (18).

Intervention and control condition

All participants received practice as usual. Additionally, intervention group participants received

the VIP in Construction intervention. A detailed description of the intervention has been

given elsewhere (18). In brief, the intervention consisted of generic as well as tailored health

information (i.e. VIP in Construction toolbox) and personal health counseling (PHC). Participants

with a healthy weight status (i.e. BMI<25 and waist circumference<94) and a healthy physical

activity level (i.e. meeting physical activity recommendations (25;26)) only received the VIP in

Construction toolbox; all others also received PHC.

The VIP in Construction toolbox consisted of health information brochures tailored to the

participants’ physical activity level and weight status, a calorie guide, a pedometer, a BMI card, a

waist circumference measuring tape, a cookbook including healthy recipes and a knowledge test,

“personal energy plan” forms, an overview of the health promotion facilities of the company,

and an exercise card.

PHC intensity (i.e. number and duration of contacts) was tailored to the participants’ stage-of-

change for improving physical activity and nutrition (Table 1) (18;27). Face-to-face and telephone

coaching contacts were provided during work hours and were given by physiotherapists

specialized in lifestyle coaching (i.e. health coaches). Face-to-face coaching contacts took place at

the worksite. A web-based system was used to register the participants’ coaching contacts (i.e.

date, time), as well as their content (i.e. goals, action plans).



7

Table 1. Personal health coaching (PHC) contact schedule

Stage-of-change(27) PHC-group

2 weeks 1 month 2 months 3 months 4 months

Pre-contemplation stage

The participant does not intend to change his risk behavior(s)

A Intake

(60 min face-to-face)

Follow-up 1:

(30 min; telephone)

Follow-up 2:

(15 min; telephone)

Follow-up 3:

(15 min; telephone)


The participant wants to change his risk behavior(s), but does not know how

B Intake


Follow-up 1:

(30 min; telephone)

Follow-up 2

(15 min; telephone)

Action stage

The participant already started changing his risk behavior(s)

C Intake


Follow-up 1

(10 min telephone)

Abbreviations: min: minutes

Effect measures

Primary and secondary outcomes were assessed at baseline, six, and 12 months.

Primary outcomes

Primary outcomes were body weight and waist circumference. Body weight was measured using

a calibrated scale with participants wearing light clothes and no shoes. Waist circumference was

measured midway between the lower rib margin and the iliac crest, and was rounded to the

nearest 0.1cm. Measurements were performed in a standing position, over bare skin, and at

the end of expiration (28). At baseline, these measurements were performed by occupational

physicians or their assistants. At 6 and 12 months, they were performed by the research team.

Secondary outcomes

Secondary outcomes were MSD, work-related vitality, and job satisfaction. The prevalence of

MSD was assessed using the “Dutch Musculoskeletal Questionnaire” (DMQ) (29). Participants

were asked to rate the occurrence of pain or discomfort in the neck, shoulders, upper and lower

back, elbows, wrists/hands, knees, and ankles/feet during the previous three months on a 4-point

scale (never, sometimes, frequent, and prolonged). Participants who answered “frequent” or

“prolonged” on one or more of the questions were classified as having MSD; all others as not

having MSD. Work-related vitality was assessed using a subscale of the “Utrecht Work Engagement

Scale” (i.e. UWES Vitality Scale). This scale included six items, scored on a 7-point scale ranging

from “never”(0) to “always”(6). The UWES Vitality Score ranged from 0-6 (higher scores indicate

a better work-related vitality) (30). Job satisfaction was assessed using a 1-item question of the

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128 | Chapter 7

“Netherlands Working Conditions Survey” (31). Participants were asked to rate their overall job

satisfaction on a 5-point scale ranging from “very dissatisfied”(1) to “very satisfied”(5).

Resource use and valuation

Intervention costs

For the societal perspective, bottom-up micro-costing was used to quantify intervention costs

(32). Intervention costs included those related to the development, implementation, and

operation of the intervention. Frequency, duration, preparation time, and locations of coaching

contacts were recorded by the coaches. Labor costs were valued by multiplying the intervention

staff’s time investments (hours) by their gross hourly salaries including overhead costs. Capital

costs were valued using cost data collected from finance department staff. Material costs were

estimated using invoices. Coaches’ travelling costs were valued according to the Dutch manual

of costing (33). As PHC contacts took place during work hours, the participants’ lost productivity

costs for the duration of the contacts were included as well, and were valued using the average

salary (including overhead costs) of Dutch construction workers (Economic Institute of the Dutch

construction industry, personal communication).

For the employer’s perspective, intervention costs were valued using charges paid. Lost productivity

due to PHC was valued using the average salary (including overhead costs) of blue collar workers

of the participating company.

Healthcare costs

Healthcare utilization was assessed using 3-monthly retrospective questionnaires and included

costs of primary healthcare (i.e. general practitioner, allied health professionals, complementary

medicine), secondary healthcare (i.e. medical specialist, hospitalization), and both prescribed and

over-the-counter medications. Dutch standard costs were used to value primary and secondary

healthcare utilization (33). If unavailable, prices according to professional organizations were

used. Medication use was valued using unit prices of the Royal Dutch Society of Pharmacy (34).

Occupational health costs

Occupational health costs consisted of gym membership subsidies, as provided by the employer.

The duration of the memberships was assessed using 3-monthly retrospective questionnaires. The

associated costs were calculated by multiplying the duration of the memberships (in months) by

the height of the subsidy (i.e. €10/month).

Sports costs

Sports costs were assessed using 3-monthly retrospective questionnaires asking participants to

report their sports membership fees and expenses on sports equipment during the previous three

months.



7

Absenteeism costs

Baseline (i.e. one year prior to baseline) and follow-up sickness absence data were collected from

company records. For the societal perspective, costs per sickness absence day were calculated by

dividing the average annual salary of Dutch construction workers (including overhead costs) by

the associated number of workable days (i.e. 214) (33). Absenteeism costs were estimated using

the “Friction Cost Approach”(FCA) (35). A friction period of 23 weeks (i.e. period needed to

replace a sick worker) and an elasticity of 0.8 (i.e. a 100% reduction in work time corresponds

with an 80% reduction in productivity) were assumed (33;35). For the employer’s perspective,

costs per sickness absence day were calculated using the average annual salary of blue collar

workers of the participating company (including overhead costs). Subsequently, absenteeism

costs were estimated using the “Human Capital Approach”(HCA), in which absenteeism costs

are neither truncated as in the FCA, nor is elasticity considered (33).

Presenteeism costs

Presenteeism was assessed on a 3-monthly basis using an item of “The World Health Organization

Health and Work Performance Questionnaire”(WHO-HPQ) (36;37). In the WHO-HPQ, presenteeism

is conceptualized as a measure of actual work performance in relation to “best performance”,

irrespective of the presence or absence of health complaints (37). Participants were asked to rate

their overall work performance during the previous three months on an 11-point scale ranging

from “worst performance”(0) to “best performance”(10). Their average work performance

during follow-up (Wown) was estimated and the participants’ level of presenteeism (PHPQ) was

calculated using the following formula:

PHPQ = (10 – Wown)/10

Presenteeism days were calculated by multiplying the participants’ PHPQ by their number of days

worked during follow-up; i.e. working days minus sickness absence days. Presenteeism days were

valued using the average salary of Dutch construction workers (societal perspective) and that of

blue collar workers of the participating company (employer’s perspective).

Using consumer price indices, all costs were converted to 2011 Euros (38). Discounting of costs

and effects was not necessary, because the follow-up of the trial was one year (39). Price weights

used for valuing resource use are given in Appendix 1.

Data analysis

Analyses were performed according to the intention-to-treat method. Descriptive statistics were

used to compare baseline characteristics between intervention and control group participants,

and participants with complete and incomplete data. Missing data were imputed in IBM SPSS

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130 | Chapter 7

(v20, Chicago, IL) using Fully Conditional Specification and Predictive Mean Matching. An

imputation model was constructed that included variables related to the “missingness” of

data and those that predicted the outcome variables. The model included age, smoking status,

baseline sickness absence, baseline effect measure values, and available midpoint and follow-

up cost and effect measure values (6- and 12 months). Fifteen different data sets were created

(Loss of Efficiency≤5%) (40). Each data set was analyzed separately as specified below. Pooled

estimates were subsequently calculated using Rubin’s rules (41). Data were imputed at the cost

level. Therefore, a descriptive analysis of resource use was performed using the complete-cases

only. T-tests were used for continuous variables and Chi-square tests for dichotomous variables.

For skewed data, uncertainty was assessed using the bias-corrected accelerated (BCA) bootstrap

method (5000 replications). Unless otherwise stated, data were analyzed in STATA (V12, Stata

Corp, College Station, TX), with a level of significance of p<0.05.

Cost-effectiveness analysis

CEAs in terms of body weight and waist circumference were conducted from the societal

perspective (i.e. all costs were taken into consideration regardless of who pays or benefits). CEAs

in terms of work-related vitality, job satisfaction, and MSD were conducted from the employer’s

perspective (i.e. only the costs borne by employers were considered). Linear regression analyses

were used to compare outcomes between the intervention and control group. Follow-up outcomes

were adjusted for their baseline values. To compare costs between both groups, 95% confidence

intervals (95%CIs) around the unadjusted mean differences in total and disaggregated costs were

calculated using BCA bootstrapping (5000 replications). Seemingly unrelated regression (SUR)

analyses were performed, in which effect differences were corrected for their baseline values

and cost differences for baseline sickness absence and presenteeism scores (42). Incremental

cost-effectiveness ratios (ICERs) were calculated by dividing the corrected cost differences by

those in effects. Uncertainty was graphically illustrated by plotting bootstrapped incremental

cost-effect pairs (CE-pairs) on cost-effectiveness planes (CE-planes) (43). A summary measure

of the joint uncertainty of costs and effects was provided using cost-effectiveness acceptability

curves (CEACs), which provide an indication of the intervention’s probability of cost-effectiveness

at different ceiling ratios (i.e. the maximum amount of money decision-makers are willing to pay

per unit of effect) (44).

Return-on-investment analysis

The ROI analysis was performed from the employer’s perspective, in which only employer costs

and benefits were considered. Costs were defined as intervention costs. Benefits were defined

as the difference in total monetized outcome measures (i.e. absenteeism, presenteeism, and

occupational health costs) between the intervention and control group during follow-up,

with positive benefits indicating reduced spending. The ROI analysis (costs and benefits) was



7

conducted using SUR analyses, in which benefits were adjusted for baseline sickness absence and

presenteeism scores. Three ROI metrics were calculated; 1) Net Benefits (NB), 2) Benefit Cost Ratio

(BCR), and 3) Return On Investment (ROI) (23;24;45).

NB = Benefits – Costs

BCR = Benefits / Costs

ROI = ((Benefits – Costs)/Costs)*100

To quantify precision, 95% bootstrapped confidence intervals (5000 replications) were estimated

around the benefits and ROI metrics using the percentile method. Financial returns are positive if

the following criteria are met: NB>0, BCR>1, and ROI>0% (23;24;45).

Sensitivity analyses

Five sensitivity analyses were conducted to test the robustness of the results. First, analyses

were performed using the complete-cases only (SA1). Second, analyses were performed in

which intervention costs were estimated under the assumption that the intervention took place

outside work hours (SA2). Thus, the costs of lost productivity due to PHC were excluded. Third,

analyses were performed in which absenteeism costs were valued using the HCA for the societal

perspective and the FCA for the employer’s perspective (SA3). Fourth, analyses were performed

in which presenteeism costs were estimated using a slightly modified version of the “PROductivity

and DISease Questionnaire” (PRODISQ) (46;47). In this version of the PRODISQ, presenteeism

was conceptualized as reduced work performance due to health complaints and was valued by

considering both the quantity and quality of labor input (SA4). Fifth, as overall consensus about

whether or not to include presenteeism costs in economic evaluations does currently not exist,

analyses were performed in which presenteeism costs were excluded (SA5).

Results

Participants

After randomization, 162 participants were allocated to the intervention group and 152 to the

control group. At baseline, intervention group participants had approximately four more sickness

absence days than their control group counterparts. Also, the prevalence of MSD was higher in

the intervention group (55.6%) than in the control group (49.3%) (Table 2). After 12 months,

32 intervention group (19.7%) and 22 control group participants (14.5%) were lost to follow-

up, among others, because they lost their job or lost interest in the study (Figure 1). Complete

data were obtained from 62.4% of participants on the effect measures (n=196; 101 intervention

group participants and 95 control group participants) and 40.5% on the cost measures (n=127;

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132 | Chapter 7

62 intervention group participants and 65 control group participants). Some differences were

observed between participants with complete and incomplete data in both the intervention and

control group (Table 2).

Economic evaluation VIP in Construction

175

6

participants and 95 control group participants) and 40.5% on the cost measures

(n=127; 62 intervention group participants and 65 control group participants). Some

differences were observed between participants with complete and incomplete data

in both the intervention and control group (Table 2).

Imputed dataset (n=162; 100.0%)

Imputed dataset (n=152; 100.0%)

Multiple imputations (n=110)

Multiple imputations (n=105)

Willing to participate (n=327)

Excluded (n=13)

♦ Not meeting inclusion criteria (n=10)

♦ Other reasons (n=3)

Complete cases (n=52; 32.1%)

Effect data: n=101 Cost data: n=62

Lost to follow-up after baseline

(n=25)

Allocated to intervention (n=162)


(n=15)

Allocated to control (n=152)

Allocation

Follow-Up after 6 months

Randomized (n=314)

Enrollment

Blue collar workers invited to participate (n=1021)

Reasons at 6 months: Termination of employment (n=10); No time/interest (n=10); health problems (n=1); deceased (n=1); unknown (n=3)

Reasons at 6 months: Termination of employment (n=5); No time/interest (n=10)


(n=32)


(n=22)

Follow-Up after 12 months

Reasons at 12 months: Termination of employment (n=11); No time/interest (n=15); health problems (n=1); deceased (n=1); unknown (n=3); other (n=1)

Reasons at 12 months: Termination of employment (n=5); No time/interest (n=17)

Analysis

Complete cases (n=47; 30.1%)

Effect data: n=95 Cost data: n=65

Figure 1: Flow chart of participants to the VIP in Construction studyFigure 1. Flow chart of participants to the VIP in Construction study



7

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ll(n

=16

2)C

ompl

ete

(n=

52)

Inco

mpl

ete

(n=

110)

All

(n=

152)

Com

plet

e(n

=47

)In

com

plet

e(n

=10

5)

Mal

e [n

(%)]

162

(100

); n=

162

52 (1

00);

n=52

110

(100

); n=

110

152

(100

); n=

152

47 (1

00);

n=47

105

(100

); n=

105

Age

(yea

rs) [

mea

n (S

D)]

46.3

(9.9

); n=

162

48.2

(9.2

); n=

5245

.3 (1

0.1)

; n=

110

47.0

(9.5

); n=

151

47.5

(8.7

); n=

4746

.8 (9

.9);

n=10

4

Smok

ers

[n (%

)]45

(27.

8); n

=15

512

(23.

5); n

=51

33 (3

1.7)

; n=

104

44 (2

9.7)

; n=

148

14 (3

1.1)

; n=

4530

(29.

1); n

=10

3

Body

wei

ght

(kilo

gram

s) [m

ean

(SD

)]88

.7 (1

2.9)

; n=

161

87.4

(11.

8); n

=52

89.3

(13.

4); n

=11

088

.9 (1

4.4)

; n=

152

89.9

(16.

3); n

=47

88.5

(13.

5); n

=10

5

Body

Mas

s In

dex

(kg/

m-2) [

mea

n (S

D)]

27.3

(3.5

); n=

161

27.2

(3.3

); n=

5227

.4 (3

.6);

n=10

927

.4 (3

.9);

n=15

227

.9 (4

.4);

n=47

27.2

(3.7

); n=

105

Wai

st c

ircum

fere

nce

(cen

timet

res)

[mea

n (S

D)]

99.0

(10.

2); n

=15

299

.4 (1

0.1)

; n=

5298

.9 (1

0.3)

; n=

100

100.

0 (1

1.8)

; n=

133

100.

3 (1

2.9)

; n=

4799

.8 (1

1.2)

; n=

86

Mus

culo

skel

etal

dis

orde

rs [n

(%)]

Yes

90 (5

5.6)

; n=

162

30 (5

7.7)

; n=

5260

(54.

5); n

=11

075

(49.

3); n

=15

221

(44.

7); n

=47

54 (5

1.4)

; n=

105

No

72 (4

4.4)

; n=

162

11 (4

2.3)

; n=

5250

(45.

5); n

=11

077

(50.

7); n

=15

226

(55.

3); n

=47

51 (4

8.6)

; n=

105

Wor

k-re

late

d vi

talit

y (r

ange

: 0-6

) [m

ean

(SD

)]4.

9 (1

.0);

n=15

75.

0 (1

.00)

; n=

524.

8 (1

.1);

n=10

55.

0 (1

.0);

n=14

25.

0 (1

.0);

n=47

5.0

(1.0

); n=

95

Job

satis

fact

ion

(ran

ge: 1

-5) [

mea

n (S

D)]

4.0

(0.7

); n=

157

4.0

(0.8

); n=

524.

0 (0

.7);

n=10

53.

9 (0

.9);

n=14

64.

0 (0

.9);

n=47

3.9

(0.9

); n=

99

Sick

ness

abs

ence

: num

ber

of s

ickn

ess

abse

nce

days

dur

ing

the

year

prio

r to

bas

elin

e [m

ean

(SD

)]14

.0 (2

6.9)

; n=

162

11.9

(24.

7); n

=52

15.0

(27.

9); n

=11

09.

8 (2

0.6)

; n=

152

11.1

(25.

8); n

=47

9.3

(17.

8); n

=10

5

Wor

k pe

rfor

man

ce: W

HO

-HPQ

wor

k pe

rfor

man

ce

scor

e du

ring

a 4-

wee

k pe

riod

prio

r to

bas

elin

e [m

ean

(SD

)]

7.6

(1.1

); n=

154

7.7

(0.9

); n=

527.

5 (1

.2);

n=10

27.

9 (1

.0);

n=14

37.

9 (1

.0);

n=47

7.9

(1.0

); n=

96

Abb

revi

atio

ns: n

: num

ber,

SD: s

tand

ard

devi

atio

n, W

HO

-HPQ

: Wor

ld H

ealth

Org

aniz

atio

n W

ork

Perf

orm

ance

Que

stio

nnai

re

R1R2R3R4R5R6R7R8R9


134 | Chapter 7

Effectiveness

After 12 months, no statistically significant differences were found between the intervention and

control group for body weight (-0.7; 95%CI: -2.2 to 0.7), waist circumference (-0.7; 95%CI: -2.5

to 1.1), MSD (-0.07; 95%CI -0.22 to 0.08), work-related vitality (-0.03; 95%CI: -0.39 to 0.33),

and job satisfaction (-0.01; 95%CI: -0.34 to 0.32).

Resource use

Forty participants were allocated to PHC group A, 61 to PHC group B, 48 to PHC group C, and

13 only received the VIP in Construction toolbox (Table 1). During the intervention period, 126

face-to-face and 173 telephone counseling contacts were provided. Based on the complete-

cases, intervention and control group participants did not significantly differ in terms of their

average number of visits to a care provider (-2.4; 95%CI: -5.7 to 0.7), average number of days

of hospitalization (-0.1; 95%CI: -0.4 to 0.2), average number of months of gym membership

subsidies (0.5; 95%CI: -0.3 to 1.3), average number of sickness absence days (-2.7; 95%CI:

-9.7 to 3.0), and average number of presenteeism days (-2.6; 95%CI: -9.6 to 4.1). However,

significantly more intervention group participants (n=36) had sports costs than their control

group counterparts (n=23; X2: 5.3, p=0.02) (Appendix 1).

Costs

Average intervention costs per participant were €178 (SD=77) from the societal perspective and

€287 (SD=22) from the employer’s perspective (Appendix 2). No statistically significant differences

were found on all cost measures (Table 3).



7

Table 3. Mean costs per participant in the intervention and control group, and unadjusted mean cost differences between both groups during the 12-month follow-up period

Cost category Intervention groupn=162; mean (SEM)

Control groupn=152; mean (SEM)

Mean cost difference(95%CI)

Societal perspectiveIntervention costs 178 (6) 0 (0) 178 (166 to 190)Medical costs 1499 (356) 1033 (174) 457 (-129 to 1434)Occupational health costs 26 (4) 20 (3) 5 (-3 to 15)Sports costs 461 (98) 265 (46) 156 (32 to 497)Absenteeism costs 2214 (338) 2055 (345) 150 (-802 to 1094)Presenteeism costs 9382 (550) 9663 (975) -533 (-2449 to 1597)Total 13760 (725) 13037 (1025) 412 (-1572 to 3093)

Employer’s perspectiveIntervention costs 287 (2) 0 (0) 287 (283 to 290)Occupational health costs 26 (4) 20 (3) 5 (-3 to 15)Absenteeism costs 2543 (447) 2217 (374) 306 (-742 to 1551)Presenteeism costs 10088 (591) 10390 (1048) -573 (-2634 to 1717)Total 12943 (616) 12626 (1111) 25 (-2005 to 2485)

Abbreviations: n: number; SEM: Standard Error of the Mean, CI: Confidence Interval, NA: Not Applicable, SD: Standard DeviationNote: Costs are expressed in 2011 Euros

Societal perspective: cost-effectiveness

The ICER for body weight was -371, indicating that society has to pay €371 for an additional

kilogram body weight loss. An ICER in the similar direction was found for waist circumference

(ICER:-392). In both cases, the majority of CE-pairs were located in the north-east quadrant (Table

4; Figure 2 (1a-b)). These results imply that the intervention was more costly and more effective

than usual practice, but the wide distribution of CE-pairs around the quadrants of the CE-planes

indicates that the uncertainty surrounding these estimates was large (Table 4; Figure 2 (1a-b)).

The CEAC in Figure 2 (2a) indicates that if society is not willing to pay anything for a kilogram

body weight loss, the probability of cost-effectiveness is 0.41. This probability increased with

an increasing willingness-to-pay to 0.84 at a ceiling ratio of €21,000/kg. The CEAC for waist

circumference showed a similar picture, with a 0.41 probability at a ceiling ratio of €0/cm and a

maximum of 0.77 at a ceiling ratio of €18,000/cm (Figure 2(2b)).

R1R2R3R4R5R6R7R8R9


136 | Chapter 7

Economic evaluation VIP in Construction

179

6

(1) a (2) a

(1) b (2) b

(1) c (3) c

Figure 2: Cost-effectiveness planes indicating the uncertainty around the incremental cost-effectiveness ratios (1) and cost-effectiveness acceptability curves indicating the probability of the intervention being cost-effectiveness at different values (€) of willingness to pay per unit of effect gained (2) for weight loss (a), waist circumference (b), and MSD (c) (based on the imputed dataset). Note: Effects are expressed in terms of kilogram body weight loss and waist circumference, and MSD prevalence reduction

Figure 2. Cost-effectiveness planes indicating the uncertainty around the incremental cost-effectiveness ratios (1) and cost-effectiveness acceptability curves indicating the probability of the intervention being cost-effectiveness at different values (€) of willingness to pay per unit of effect gained (2) for weight loss (a), waist circumference (b), and MSD (c) (based on the imputed dataset). Note: Effects are expressed in terms of kilogram body weight loss and waist circumference, and MSD prevalence reduction



7

Employer’s perspective: cost-effectiveness

For MSD, an ICER of 2000 was found, indicating that employers save €2,000 per additional

person prevented from having a MSD. Most CE-pairs were contained in the north-east quadrant

(Table 4; Figure 2(1c)). This implies that the intervention was less costly and more effective than

usual practice, but the level of uncertainty was large. The CEAC in Figure 2 (2c) indicates that the

probability of cost-effectiveness was 0.55 at a ceiling ratio of €0/person, increasing to 0.84 at a

ceiling ratio of €42,000/person.

The ICERs for work-related vitality and job satisfaction were 3322 and 16328, respectively (Table

4). In both cases, the intervention was less costly and less effective than usual practice. CEACs

showed that the associated maximum probabilities of cost-effectiveness were 0.54 for both

outcomes, irrespective of the willingness-to-pay (Figures not shown).

Employer’s perspective: financial return

Total benefits in terms of absenteeism, presenteeism, and occupational health costs were on

average €424 (95%CI: -1789 to 2923) (Table 5). The NB was on average 138 (95%CI: -2073

to 2641), suggesting that the intervention resulted in a net saving to the employer of €138 per

participant. The BCR (i.e. amount of money returned per Euro invested) and ROI (i.e. percentage

of profit per Euro invested) were 1.48 (95%CI: -6.23 to 10.21) and 48% (95%CI: -723 to

921), respectively. However, their confidence intervals were rather wide and none of them was

statistically significant.

Sensitivity analyses

The results of SA2 and SA3 were similar to those of the main analysis, whereas the outcomes of

SA1 (complete-case analysis), SA4 (PRODISQ), and SA5 (Excluding presenteeism) differed in some

aspects from those of the main analysis (Table 4; Table 5).

R1R2R3R4R5R6R7R8R9


138 | Chapter 7

Tab

le 4

. Dif

fere

nce

s in

po

ole

d m

ean

co

sts

and

eff

ects

(95

% C

on

fid

ence

inte

rval

s), i

ncr

emen

tal c

ost

-eff

ecti

ven

ess

rati

os,

an

d t

he

dis

trib

uti

on

of

incr

emen

tal c

ost

-eff

ect

pai

rs a

rou

nd

th

e q

uad

ran

ts o

f th

e co

st-e

ffec

tive

nes

s p

lan

es

Ana

lysi

sSa

mpl

e si

zeO

utco

me

∆C

(95%

CI)

∆E

(95%

CI)

ICER

Dis

trib

utio

n C

E-pl

ane

(%)

Soci

etal

per

spec

tive

Inte

rven

tion

Con

trol

€Po

ints

€/po

int

NE1

SE2

SW3

NW

4

Mai

n a

nal

ysis

-

Impu

ted

data

set

162

152

Body

wei

ght

271

(-21

55 t

o 26

79)

-0.7

(-2.

2 to

0.7

)-3

7150

.034

.46.

59.

1

162

152

Wai

st c

ircum

fere

nce

272

(-21

40 t

o 26

92)

-0.7

(-2.

5 to

1.1

)-3

9248

.331

.29.

810

.7

SA1

-

Com

plet

e-ca

ses

5247

Body

wei

ght

-122

8 (-

3514

to

576)

-0.5

(-1.

8 to

0.8

)24

1810

.767

.917

.44.

0

5247

Wai

st c

ircum

fere

nce

-119

6 (-

3400

to

602)

-1.1

(-3.

0 to

0.8

)10

6813

.774

.410

.51.

4

SA2

-

Out

side

wor

k ho

urs

162

152

Body

wei

ght

245

(-21

81 t

o 26

53)

-0.7

(-2.

2 to

0.7

)-3

3449

.235

.36.

68.

9

162

152

Wai

st c

ircum

fere

nce

246

(-21

68 t

o 26

65)

-0.7

(-2.

5 to

1.1

)-3

5447

.631

.910

.010

.5

SA3

-

HC

A16

215

2Bo

dy w

eigh

t38

6 (-

2011

to

2794

)-0

.7 (-

2.2

to 0

.7)

-527

53.6

30.9

6.1

9.4

162

152

Wai

st c

ircum

fere

nce

386

(-20

01 t

o 28

00)

-0.7

(-2.

5 to

1.1

)-5

5651

.727

.89.

211

.3

SA4

-

PRO

DIS

Q16

215

2Bo

dy w

eigh

t-8

9 (-

1586

to

1559

)-0

.7 (-

2.2

to 0

.7)

122

39.2

45.3

9.5

6.1

162

152

Wai

st c

ircum

fere

nce

-89

(-15

86 t

o 15

64)

-0.7

(-2.

5 to

1.1

)12

836

.043

.511

.29.

3

SA5

-

Excl

udin

g pr

esen

teei

sm c

osts

162

152

Body

wei

ght

799

(-43

0 to

231

7)-0

.7 (-

2.2

to 0

.7)

-109

374

.59.

92.

113

.5

162

152

Wai

st c

ircum

fere

nce

796

(-43

3 to

232

7)-0

.7 (-

2.5

to 1

.1)

-114

769

.69.

92.

218

.4

Empl

oyer

’s pe

rspe

ctiv

e

Inte

rven

tion

Con

trol

€Po

ints

/ pro

port

ions

€/po

int

NE1

SE2

SW3

NW

4

Mai

n a

nal

ysis

-

Im

pute

d da

tase

t16

215

2M

SD

-142

(-26

74 t

o 20

56)

-0.0

7 (-

0.22

to

0.08

)20

0038

.944

.110

.07.

0

162

152

Wor

k-re

late

d vi

talit

y (r

ange

: 0-6

)-1

13 (-

2583

to

2083

)-0

.03

(-0.

39 t

o 0.

33)

3322

15.6

28.1

25.0

31.3

162

152

Job

satis

fact

ion

(ran

ge: 1

-5)

-129

(-26

10 t

o 20

70)

-0.0

1 (-

0.34

to

0.32

)16

328

20.2

27.7

26.1

26.0

SA1

-

Com

plet

e-ca

ses

5247

MSD

-116

1 (-

3027

to

706)

0.01

(-0.

19 –

0.1

8)24

8800

5.6

45.8

40.4

8.2

5247

Wor

k-re

late

d vi

talit

y (r

ange

: 0-6

)-1

180

(-33

00 t

o 49

6)-0

.05

(-0.

36 t

o 0.

25)

2212

13.

133

.153

.510

.3

5247

Job

satis

fact

ion

(ran

ge: 1

-5)

-112

6 (-

3266

to

550)

0.02

(-0.

22 t

o 0.

26)

-542

304.

452

.534

.48.

6

SA2

-

Out

side

wor

k ho

urs

162

152

MSD

-1

71 (-

2702

to

2028

)-0

.07

(-0.

22 t

o 0.

08)

2400

38.1

45.0

10.1

6.8

162

152

Wor

k-re

late

d vi

talit

y (r

ange

: 0-6

)-1

42 (-

2611

to

2055

)-0

.03

(-0.

39 t

o 0.

32)

4167

15.2

28.5

25.7

30.7

162

152

Job

satis

fact

ion

(ran

ge: 1

-5)

-158

(-26

38 t

o 20

41)

-0.0

1 (-

0.34

to

0.32

)19

960

19.6

28.2

26.6

25.6

SA3

-

FCA

162

152

MSD

-2

60 (-

2824

to

1914

)-0

.07

(-0.

22 t

o 0.

08)

3700

35.3

47.7

10.6

6.4

162

152

Wor

k-re

late

d vi

talit

y (r

ange

: 0-6

)-2

36 (-

2742

to

1954

)-0

.03

(-0.

39 t

o 0.

32)

9677

13.8

30.0

27.8

28.4

162

152

Job

satis

fact

ion

(ran

ge: 1

-5)

-294

(-27

61 t

o 19

46)

-0.0

1 (-

0.34

to

0.32

)30

671

18.1

29.7

28.6

23.7



7

SA4

-

PRO

DIS

Q16

215

2M

SD

-556

(-18

11 t

o 72

7)-0

.07

(-0.

22 t

o 0.

08)

7800

15.6

67.8

12.6

4.0

162

152

Wor

k-re

late

d vi

talit

y (r

ange

: 0-6

)-5

35 (-

1798

to

760)

-0.0

3 (-

0.39

to

0.32

)16

464

8.5

35.5

43.9

12.2

162

152

Job

satis

fact

ion

(ran

ge: 1

-5)

-544

(-18

07 t

o 74

4)-0

.01

(0.3

4 to

0.3

2)57

512

8.4

39.2

40.5

11.8

SA5

-

Excl

udin

g pr

esen

teei

sm16

215

2M

SD

408

(-56

7 to

148

7)-0

.07

(-0.

22 t

o 0.

08)

-570

064

.419

.03.

013

.6

162

152

Wor

k-re

late

d vi

talit

y (r

ange

: 0-6

)42

2 (-

559

to 1

517)

-0.0

3 (-

0.39

to

0.32

)-1

3155

34.9

9.1

12.2

43.7

162

152

Job

satis

fact

ion

(ran

ge: 1

-5)

416

(-56

3 to

150

4)-0

.01

(-0.

34 t

o 0.

32)

-437

5036

.211

.410

.242

.1

Abb

revi

atio

ns:

CI:

Con

fiden

ce I

nter

val,

C:

Cos

ts,

E: E

ffec

ts,

ICER

: In

crem

enta

l C

ost-

Effe

ctiv

enes

s Ra

tio,

CE-

plan

e: C

ost-

Effe

ctiv

enes

s pl

ane,

SA

: Se

nsiti

vity

A

naly

sis,

HC

A: H

uman

Cap

ital A

ppro

ach,

FC

A: F

rictio

n C

ost

App

roac

h, M

SD: M

uscu

losk

elet

al D

isor

ders

Not

e: C

osts

are

exp

ress

ed in

201

1 Eu

ros

1 Re

fers

to

the

nort

heas

t qu

adra

nt o

f th

e C

E pl

ane,

indi

catin

g th

at t

he V

IP in

Con

stru

ctio

n in

terv

entio

n is

mor

e ef

fect

ive

and

mor

e co

stly

tha

n us

ual p

ract

ice

2 Re

fers

to

the

sout

heas

t qu

adra

nt o

f th

e C

E pl

ane,

indi

catin

g th

at t

he V

IP in

Con

stru

ctio

n in

terv

entio

n is

mor

e ef

fect

ive

and

less

cos

tly t

han

usua

l pra

ctic

e3

Refe

rs t

o th

e no

rthw

est

quad

rant

of

the

CE

plan

e, in

dica

ting

that

the

VIP

in C

onst

ruct

ion

inte

rven

tion

is le

ss e

ffec

tive

and

mor

e co

stly

tha

n us

ual p

ract

ice

4 Re

fers

to

the

sout

hwes

t qu

adra

nt o

f th

e C

E pl

ane,

indi

catin

g th

at t

he V

IP in

Con

stru

ctio

n in

terv

entio

n is

less

eff

ectiv

e an

d le

ss c

ostly

tha

n us

ual p

ract

ice

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140 | Chapter 7

Tab

le 5

. In

terv

enti

on

co

sts,

ben

efits

, Net

Ben

efits

(N

B),

Ben

efit

Co

st R

atio

(B

CR

), a

nd

Ret

urn

-On

-In

vest

men

t (R

OI)

per

par

tici

pan

t

Ana

lysi

sSa

mpl

e si

zeC

osts

Bene

fits

Fina

ncia

l ret

urn

IC

€To

tal (

95%

CI)

NB1

(95%

CI)

BCR2

(95%

CI)

ROI (

%)3

(95%

CI)

Mai

n a

nal

ysis

-

Im

pute

d da

tase

t 16

215

228

7 (2

83 t

o 29

0)42

4 (-

1789

to

2923

)13

8 (-

2073

to

2641

)1.

48 (-

6.23

to

10.2

1)48

(-72

3 to

921

)SA

1

-

Com

plet

e da

tase

t52

4728

9 (2

83 t

o 29

5)14

47 (-

265

to 3

530)

1158

(-75

7 to

294

8)5.

00 (-

1.64

to

11.2

0)40

0 (-

264

to 1

020)

SA2

- O

utsi

de w

ork

hour

s16

215

225

8 (2

58 t

o 25

8)43

0 (-

1783

to

2928

)17

2 (-

2039

to

2677

)1.

67 (-

6.90

to

11.3

8)67

(-79

0 to

103

8)SA

3

-

HC

A16

215

228

7 (2

83 t

o 29

0)54

3 (-

1697

to

3034

)25

7 (-

1967

to

2769

)1.

90 (-

5.87

to

10.6

7)90

(-68

7 to

967

)SA

4

-

PRO

DIS

Q16

215

228

7 (2

83 t

o 29

0)84

0 (-

442

to 2

099)

553

(-72

8 to

181

4)2.

93 (-

1.54

to

7.33

)19

3 (-

254

to 6

33)

SA5

- E

xclu

ding

pre

sent

eeis

m16

215

228

7 (2

83 t

o 29

0)-1

23 (-

1142

to

910)

-410

(-14

58 t

o 59

5)-0

.43

(-4.

08 t

o 3.

08)

-143

(-50

8 to

208

)

Abb

revi

atio

ns:

CI:

Con

fiden

ce In

terv

al,

NB:

Net

Ben

efit,

BC

R: B

enefi

t C

ost

Ratio

, RO

I: Re

turn

-On-

Inve

stm

ent,

I: In

terv

entio

n, C

: C

ontr

ol,

SA:

Sens

itivi

ty A

naly

sis,

H

CA

: Hum

an C

apita

l App

roac

hN

ote

1: C

osts

are

exp

ress

ed in

201

1 Eu

ros

Not

e 2:

Fin

anci

al r

etur

ns a

re p

ositi

ve if

the

fol

low

ing

crite

ria a

re m

et: N

B>0,

BC

R>1,

and

RO

I>0

1 In

dica

tes

the

amou

nt o

f m

oney

ret

urne

d af

ter

inte

rven

tion

cost

s ar

e re

cove

red

2 In

dica

tes

the

amou

nt o

f m

oney

ret

urne

d pe

r Eu

ro in

vest

ed in

the

inte

rven

tion

3 In

dica

tes

the

perc

enta

ge o

f pr

ofit

per

Euro

inve

sted

in t

he in

terv

entio

n



7

In SA1, total societal and employer’s costs were lower in the intervention group than in the

control group. All cost and effect differences were not statistically significant. CEACs differed

from those of the main analysis (Figures not shown). Most notably, a 0.88 probability of cost-

effectiveness was found for body weight at a ceiling ratio of €0/kg, increasing to 0.94 at €1,000/

kg. In accordance with the main analysis, financial return estimates were positive, but their

confidence intervals were rather wide and not statistically significant.

When using the PRODISQ (SA4), total societal and employer’s costs were lower in the intervention

group than in the control group. All cost and effect differences were not statistically significant.

CEACs differed from those of the main analysis (Figure not shown). Most notably, a 0.54 probability

of cost-effectiveness was found for body weight at a ceiling ratio of €0/kg, increasing to 0.84

at €4,000/kg. In accordance with the main analysis, financial return estimates were positive, but

their confidence intervals were rather wide and not statistically significant.

When excluding presenteeism costs (SA5), total societal and employer’s costs were higher in the

intervention group than in the control group. All cost and effect differences were not statistically

significant. CEACs differed from those of the main analysis (Figures not shown). Most notably,

a 0.22 probability of cost-effectiveness was found for MSD at a ceiling ratio of €0/person,

increasing to 0.82 at €100,000/person. In contrast to the main analysis, financial return estimates

were negative, but statistically non-significant as well.

Discussion

This study evaluated the cost-effectiveness and financial return of a worksite physical activity and

nutrition program for construction workers. In comparison with usual practice, the intervention

had no significant effect on all cost and effect measures. The probabilities of cost-effectiveness

for body weight, waist circumference, and MSD increased with an increasing ceiling ratio to 0.84

(willingness-to-pay = €21,000/kg), 0.77 (willingness-to-pay = €18,000/cm), and 0.84 (willingness-

to-pay = €42,000/person prevented from having MSD), respectively. The probabilities of cost-

effectiveness for work-related vitality and job satisfaction were low at all ceiling ratios (≤0.54).

Also, per Euro invested in the program, €1.48 was returned to the employer, but the uncertainty

surrounding this estimate was large.

Effects and costs

Various reasons may explain the lack of significant effects at 12-month follow-up. First, as the

intervention focused on both the prevention and treatment of excessive body weight and MSD,

participation in the intervention was not restricted to high-risk individuals (e.g. employees were

not pre-selected on high body weight). As a consequence, many participants were relatively

healthy at baseline, leaving less room for improvement. Second, a lower than expected number

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142 | Chapter 7

of participants fully participated in the program; e.g. 39% of participants eligible for counselling

did not complete the PHC program and most of the VIP in Construction toolbox materials

were used by fewer than 50% of participants (48). Third, it is possible that the intensity of the

intervention was too low to improve the participants’ lifestyle behaviours in such a way that it

translates in long-term health improvements. To illustrate, the intervention was previously found

effective in reducing body weight at 6-month follow-up (19), but this effect was not sustained at

the long-term. To sustain this effect, more counselling contacts and/or booster sessions after the

termination of the intervention may be needed. As for the lack of significant cost differences, it is

known that cost data are right skewed and therefore require relatively large sample sizes to detect

relevant differences. Nonetheless, as in most trial-based economic evaluations, the sample size

was based on one of the primary outcomes (i.e. body weight) (18), which likely underpowered it

to detect relevant cost differences.

It is noteworthy that the present findings with respect to body weight-related outcomes (i.e. the

primary outcomes) contrast those of previous studies. Two systematic reviews found worksite

physical activity and nutrition programs to significantly reduce body weight by -1.3kg and -1.2kg

(14;49). In addition, Groeneveld et al. (2010) showed in an RCT that a similar intervention for

construction workers resulted in a statistically significant body weight loss of -1.8kg at 12-month

follow-up (50). The difference in effect between both studies is likely explained by the fact

that their intervention was more intensive than ours; i.e. three face-to-face and four telephone

contacts versus a maximum of one face-to-face and three telephone contacts. Furthermore, their

intervention was aimed at construction workers with an elevated risk of cardiovascular disease,

whereas the present intervention was aimed at construction workers in general. This supports our

reasoning that a more intensive program, aimed at high-risk individuals, may have been needed

to produce better effects.

Societal perspective: Cost-effectiveness

The intervention’s cost-effectiveness in improving weight-related outcomes depends on the

societal willingness-to-pay for these effects and the probability of cost-effectiveness that society

considers acceptable. Since both are unknown, however, strong conclusions cannot be made.

Nonetheless, decision-makers themselves can use the present results to consider whether they

perceive that the intervention provides “good value for money” at an acceptable probability of

cost-effectiveness.

The aforementioned study of Groeneveld et al. (2011) also evaluated the societal cost-

effectiveness of the worksite physical activity and nutrition program. They found an ICER of €145/

kg body weight loss, a 0.60 probability of cost-effectiveness at a ceiling ratio of €250/kg, which

increased to 0.95 at €2,000/kg (51). In contrast to the present study, however, presenteeism and

occupational health costs were not included. If we would exclude both cost categories as well,

an ICER of €1088/kg body weight loss would be found. Van Wier et al. (2013) evaluated the



7

societal cost-effectiveness of an occupational health guideline aimed at preventing weight gain

among Dutch employees. As the probabilities of cost-effectiveness were low for body weight and

waist circumference (≤0.52), the intervention was not considered cost-effective (52). Most other

studies that evaluated the cost-effectiveness of similar interventions in improving weight-related

outcomes solely included intervention costs (53).

Employer’s perspective: Cost-effectiveness

The intervention was not cost-effective in improving work-related vitality and job satisfaction

(≤0.54 probabilities of cost-effectiveness). If employers are not willing to pay anything for

preventing one person from having a MSD, there is a 0.55 probability of the intervention

being cost-effective. This probability increased with an increasing willingness-to-pay to 0.84 at

a ceiling ratio of €42,000/person. Again, however, strong conclusions about the intervention’s

cost-effectiveness in terms of this outcome cannot be made, and employers themselves should

consider whether the intervention provides “good value for money” at an acceptable probability

of cost-effectiveness.

To our knowledge, studies evaluating the employer’s cost-effectiveness of similar interventions in

improving work-related vitality and MSD are lacking. One study, however, evaluated the employer’s

cost-effectiveness in improving job satisfaction of a mindfulness-based worksite intervention

aimed at improving work engagement and energy balance-related behaviours (54). Irrespective

of the maximum willingness-to-pay, the intervention had a low probability of cost-effectiveness

(≤0.25) and was therefore not considered cost-effective in improving job satisfaction either.

Employer’s perspective: Financial return

On average, €1.48 was returned to the employer per Euro invested in the program. However,

as the uncertainty surrounding the financial return estimates was large and none of them was

statistically significant, it cannot be concluded that the intervention was cost-beneficial to the

employer.

A systematic review found worksite physical activity and/or nutrition programs to result in positive

financial returns in terms of absenteeism benefits according to non-randomized studies (BCR:

4.25), but negative financial returns according to RCTs (BCR: 0.51). If we would solely include

absenteeism benefits, our results would be in line with those of the review (BCR: 0.41). The

review also indicated that the current evidence on the financial return of such interventions is

limited by the fact that few studies incorporate presenteeism benefits and none of them report

on the uncertainty surrounding their results. The present findings underscore the importance of

addressing these limitations. Namely, as financial return estimates were positive, but statistically

non-significant, wrong conclusions would have been drawn if the level of uncertainty was not

taken into account. Furthermore, the direction of the financial return estimates proved to be

highly influenced by the in- or exclusion of presenteeism benefits; i.e. positive when included,

but negative when excluded.

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144 | Chapter 7

Robustness of the study results

In accordance with the main analysis, cost and effect differences as well as financial return

estimates were not statistically significant in all sensitivity analyses. Also, the overall conclusions

would not change when using the results of any of the sensitivity analyses. Nonetheless, it is

important to mention that the results of the complete-case analysis (SA1) were much more

favorable than those of the main analysis. Amongst others, relatively high probabilities of cost-

effectiveness were found at ceiling ratios of €0; e.g. a 0.88 probability at a ceiling ratio of €0/

kg body weight loss. However, as a post-hoc analysis indicated that participants with complete

data had fewer sickness absence days during follow-up than those with incomplete data (i.e. 6.7

versus 13.3 in the intervention group and 9.5 versus 10.9 in the control group), self-selection

of participants seems to have biased these results, and the results of the main analysis were

considered more valid.


An important strength of the present study is its pragmatic RCT design. The pragmatic aspect

of the trial enabled us to evaluate the intervention’s resource implications under “real world”

circumstances. This facilitates the generalizability of the results (i.e. external validity), whereas

the internal validity is guaranteed by the randomization of participants (55;56). Another strength

concerns the use of state-of-the-art statistical methods that are not or infrequently used

in occupational health research. Amongst others, multiple imputation was used to deal with

missing data, SUR analyses were performed to account for the possible correlation between

costs and effects/benefits, and bootstrapping was used to estimate the uncertainty surrounding

cost differences as well as cost-effectiveness and financial return estimates. Furthermore, both

absenteeism and presenteeism costs were included, whereas most previous studies solely included

absenteeism costs (45;53). This is of importance because efforts to improve health seem to have

a more immediate effect on presenteeism than on absenteeism (57).

Several limitations deserve attention as well. First, complete cost and effect data were only

obtained from 40.5% and 62.4% of participants, respectively. To deal with this issue, missing

values were imputed using multiple imputation. While having complete data is always preferred,

multiple imputation is increasingly being acknowledged as a more valid and precise way to

deal with missing data than a complete-case analysis (56;58).Complete-case analyses reduce

the power of a study and ignore available information of participants who only have missing

data on a few measurement points. Also, complete-case analyses only produce reliable estimates

when there are no systematic differences between the missing and observed values, which,

according to a post-hoc analysis, was probably not the case (40;58). Second, many cost and

effect data were gathered using self-report of participants, which may have causes “social

desirability bias” and/or “recall bias”. Amongst others, we had to rely on self-reported values of

healthcare utilization as health insurance claim data of participants are practically inaccessible in



7

Dutch economic evaluations. Also, the period over which participants had to report their resource

use was relatively long (i.e. 3 months). This might be a particular concern for presenteeism, as

relatively short recall periods seem to be needed for this outcome (59). In future studies, mobile

apps might provide a solution for this issue, as they can be used to collect data in a way that is

relatively non-burdensome to participants. Third, the presence of MSD was assessed in terms of

“self-reported pain or discomfort in one or more body regions”. As discomfort can be regarded

as an early manifestation of MSD, participants classified as having MSD may not necessarily have

serious functional limitations and/or low levels of health-related welfare. This should be kept in

mind while interpreting the results. It is also important to bear in mind that economic evaluation

results are not directly transferable between countries or jurisdictions due to differences in

healthcare and/or social security systems (60;61). In the Netherlands, for example, healthcare

costs are generally borne by the government and/or health insurance companies, whereas in

countries with employer-provided healthcare (e.g. The United States) they accrue to the employer.

Furthermore, for the employer’s perspective, the HCA was used for estimating absenteeism costs.

This was done because Dutch employers are obliged to pay at least 70% of the salary of sick

employees for a period of two years, and most of them top up the wage payments from 70% to

100% during the first year of sickness absence (62). Thus, although the initial productivity level

of a Dutch company may be restored after the friction period, employers still bear the salary costs

of a sick worker. Readers should keep in mind that alternative valuation methods may be more

appropriate in other countries or jurisdictions (61).

Conclusion

The intervention’s cost-effectiveness in improving weight-related outcomes and MSD depends

on the societal and employer’s willingness to pay for these effects and the probability of cost-

effectiveness that they consider acceptable. From the employer’s perspective, the intervention

was not cost-effective in improving work-related vitality and job satisfaction. Also, due to a large

degree of uncertainty, it cannot be concluded that the intervention is cost saving to the employer

Acknowledgements

This project is part of a research program called “Vitality In Practice”, which is funded by Fonds

Nuts Ohra (Nuts Ohra Foundation). The authors wish to thank Anneke van Paridon for her help

with the data collection. The authors would also like to thank all participants and health coaches.

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146 | Chapter 7

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56. Petrou S, Gray A. Economic evaluation alongside randomised controlled trials: design, conduct, analysis, and reporting. BMJ 2011;342: d1548.

57. Caverley N, Cunningham JB, MacGregor JN. Sickness Presenteeism, Sickness Absenteeism, and Health Following Restructuring in a Public Service Organization. Journal of Management Studies 2007;44(2):304-319.

58. Sterne JAC, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ 2009;29:338.

59. Zhang W, Bansback N, Anis AH. Measuring and valuing productivity loss due to poor health: A critical review. Soc Sci Med 2011;72(2):185-192.

60. Verbeek J, Pulliainen M, Kankaanpaa E, Taimela S. Transferring results of occupational safety and health cost-effectiveness studies from one country to another - a case study. Scand J Work Environ Health 2010;36(4):305-312.

61. Tompa E, Culyer AJ, Dolinschi J. Economic evaluation of interventions for occupational health and safety: Developing good practice. New York: Oxford University Press; 2008.

62. OECD. Sickness and Disability Schemes in the Netherlands: Country memo as a background paper for the OECD Disability Review. 2007. http://www.oecd.org/social/soc/41429917.pdf.

63. Groeneveld IF, Proper KI, van der Beek AJ, van Duivenbooden C, van Mechelen W. Design of a RCT evaluating the (cost-) effectiveness of a lifestyle intervention for male construction workers at risk for cardiovascular disease: the health under construction study. BMC Public Health 2008;8:1.

64. UWV. Brancheschets Bouw. Oktober 2012. https://www.werk.nl/pucs/groups/public/documents/document/wdo_007277.pdf



7

Appendix 1. Price weights used for valuing resource use and resources consumed by the intervention and control group participants during follow-up (based on the complete-cases)

Units [Units of measurement] Price weight Resources consumedSocietal perspective

Employer’s perspective

Intervention group(n=51)

Control group (n=48)

Intervention costs € 177.77 € 287.56

Medical costsVisits to a care provider [No. of visits; mean (SD)] General practitioner Office consultation € 28.96c N.A. 1.3 (1.9) 1.6 (2.2) Telephone consultation € 14.48c N.A. 0.2 (0.5) 0.2 (0.8) House call € 44.47c N.A. 0.0 (0.3) 0.0 (0.2) Allied health professionals Psychologist € 82.47c N.A. 0.8 (3.3) 0.2 (0.1) Dietician € 27.93c N.A. 0.0 (0.0) 0.0 (0.3) Physical therapist € 37.23c N.A. 0.7 (2.3) 3.8 (8.0)* Other allied health professionals Variablec,d N.A. 0.7 (3.7) 0.5 (1.9)Medical specialists Psychiatrist € 106.53c N.A. 0.0 (0.0) 0.0 (0.0) Other medical specialists € 74.47c N.A. 0.8 (1.7) 0.8 (1.8)Complementary medicine Variablec,d N.A. 0.2 (1.7) 0.4 (1.8)Hospitalization [No. of days; mean (SD)] Ward € 472.66c N.A. 0.2 (0.2) 0.3 (0.8) Intensive care € 2257.82c N.A. 0.0 (0.0) 0.0 (0.0)Medications [No. of participants using medica-tion; Number (%)]

Variablee N.A. 30 (58.8) 25 (52.1)

Absenteeism costs Sickness absence [days; Mean (SD)] 198.20f 213.10g 6.7 (9.5) 9.4 (21.9)

Presenteeism costsPresenteeism [days; Mean (SD)] 198.20f 213.10g 43.7 (14.5) 46.3 (19.7)

Sports costs [No. of participants with sports costs; Number (%)]

Variableh N.A. 36 (70.6) 23 (47.9)*

Occupational health costs In-company fitness [No. of months; mean (SD)] € 10.00i € 10.00i 0.9 (2.5) 0.4 (1.6)

* Significant at p<0.05Abbreviations: n: Number, SD: Standard Deviation, N.A.: Not ApplicableNote: Costs are expressed in 2011 EurosPrice weight sources: a Bottum-up micro-costed, valued using tariffs and depleted sources (See Appendix 2); b Market prices, valued using invoices of contractors; c Dutch Manual of Costing; d Professional organizations; e Dutch Society of Pharmacy; f Average gross annual salary of Dutch construction workers including holiday allowances and premiums; g Average gross annual salary of blue collar workers of the participating construction company including holiday allowances and premiums; h Self-reported expenses on sports memberships and sports equipment; i Height of the employer’s gym membership subsidy

R1R2R3R4R5R6R7R8R9


150 | Chapter 7

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Chapter 8General discussion

R1R2R3R4R5R6R7R8R9


154 | Chapter 8


General discussion | 155

8

As described in the general introduction the main goal of this dissertation was to systematically

develop a tailored intervention to prevent and reduce overweight and MSD in a specific high-risk

occupational group of blue collar construction workers, and to evaluate this programme in a

randomised controlled trial: VIP in Construction. In order to gain more insight into the potential

of body weight management as strategy for reducing MSD, we also studied the relation between

body weight and musculoskeletal symptoms in worker populations. In this final chapter the main

findings will be presented, discussed and interpreted in the context of recent literature. Finally,

these reflections will be translated into recommendations for future research and practice.

Main findings

To explore if interventions reducing body weight are potentially an effective primary and secondary

prevention strategy for musculoskeletal symptoms, we investigated the relation between these

two health problems in chapter 2. Based on analyses in a large working population sample we

found BMI to be associated with musculoskeletal symptoms, in particular symptoms of the lower

extremities. Additionally, compared to employees with normal weight, obese employees were

at increased risk for developing symptoms as well as having impaired recovery from symptoms.

Contradictory to our hypothesis, the association was stronger for employees with low physical

workload compared to those with high physical workload.

In chapter 3 the systematic development of the intervention programme as well as the design of

the RCT was described. The Intervention Mapping protocol was applied to systematically develop

the VIP in Construction programme, targeted at blue collar workers of a large construction

company. This resulted in specific programme objectives aimed at quantity and quality of energy

intake and output. After selecting relevant determinants and theoretical methods of behaviour

change, practical strategies were formulated. The intervention programme consisted of individual

face-to-face and telephone counselling, both employing information and materials aimed to

improve lifestyle behaviour. The programme was tailored to each participant’s motivational

readiness for change, varying in focus, number, and duration of counselling sessions. The

intervention was linked to the company’s periodic health screening and took place at the worksite

and during working hours. Management and workers were involved in the development of the

programme. Therefore, the programme matched the needs and preferences of the target group,

which facilitated implementation.

In chapter 4 the process evaluation of the intervention was reported. The process evaluation was

conducted following the RE-AIM framework for the evaluation of the public health impact of

health promotion interventions. The external validity of the trial was satisfactory with representative

R1R2R3R4R5R6R7R8R9


156 | Chapter 8

reach of workers and adoption of workplace units in the participating construction company.

Intervention participants showed significantly more progression through the different stages

of behaviour change than did controls. The extent to which the programme was implemented

as intended was concluded to be modest. The satisfaction of participants and dose delivered

was, however, high; 84% of the participants received at least one counselling session. However,

adjustments to the programme should be made to improve exposure and fidelity (the extent

to which the steps of the coaching programme were delivered as intended) to the protocol.

Overall, based on the RE-AIM dimensions, it was concluded that the programme is feasible and

based on improvements on determinants of behaviour change potentially effective in blue collar

construction workers.

Effectiveness of the programme on body weight, BMI, waist circumference, physical activity (PA),

dietary intake, blood pressure, and blood cholesterol was assessed in chapter 5. Linear and

logistic regression analyses were applied at 6- and 12-month follow-up. Initially, at 6-month

follow-up, intervention participants showed positive changes in vigorous physical activity and

dietary behaviour (decrease in intake of sugar-sweetened beverages) compared to controls, as

well as positive changes in weight-related outcomes (body weight, BMI and waist circumference).

Long-term effects on weight-related outcomes were still promising, but no longer statistically

significant.

Chapter 6 described the evaluation on secondary outcomes. Neither at 6-month follow-up nor

at 12-month follow-up statistically significant intervention effects were found on musculoskeletal

symptoms, physical functioning, work-related vitality, work performance, work ability, or sickness

absence.

Finally, a cost-effectiveness evaluation from both the societal and employers perspective was

conducted alongside the RCT with a follow-up of 12 months, as described in chapter 7.

Based on the economic evaluation, the programme appeared not cost-effective from the

employers perspective in improving work-related vitality and job satisfaction. It was concluded

that the cost-effectiveness of the programme, of which the costs were €287 per worker, depends

on the “willingness to pay” of decision makers for their effects. Financial return estimates were

positive for the employer, but these estimates showed a high level of uncertainty.

In conclusion, overall this tailored intervention showed no beneficial cost-effectiveness or

statistically significant financial return after the first year of implementation. Therefore, based on

the result of this thesis, we cannot recommend implementation of the programme in the current

form.



8

Methodological considerations

The RCT evaluating VIP in Construction was designed to meet most of the CONSORT statement

requirements, which is a standard for the reporting of trials [1]. RCTs are regarded as the gold

standard for evaluating effectiveness of interventions and are considered the most scientifically

rigorous method [2]. The main purpose of randomization is to avoid selection bias and distribute

known and unknown attributes that influence outcomes (i.e. confounding factors) randomly

between the groups that receive the interventions and the comparison groups. Still, bias may

occur even within the strict design of an RCT, for example as a result of non-response or drop-out.

Therefore, several important methodological aspects have to be discussed.

Validity and generalizability of the results

External validity of a study refers to the extent to which the results of a study can be generalised

to other settings, situations and populations [3]. The study as described in this thesis focused on

a specific occupational group; blue collar workers in the construction industry. As we did not have

many strict exclusion criteria for workers to participate in this programme, and it was carried out

under “real life” circumstances, it is expected that the results are transferable outside the research

trial setting. Various subgroups of blue collar workers were included, such as carpenters, masons,

crane drivers, workers in road construction and factory workers, which favours representativeness

for a broader group of workers involved in moderate to heavy physically demanding occupations.

Another element of external validity is the participation rate or reach, as described in chapter

4. The research population was recruited over a 15-month period and consisted of workers who

attended a non-compulsory periodic health screening and were not on long-term sick leave at

baseline. It was estimated that 31% of the eligible workers were included in the study. Differences

between efficacy and effectiveness of a programme may result from selective recruitment.

Participation in the trial was on voluntary basis, but there were no indications that participants

differed in health indicators compared to other workers attending screenings. Unfortunately,

we were not able to compare study participants’ health characteristics to workers who did not

participate in screenings. Baseline data of the study participants was also compared to company

data. No indication for selection bias based on health-related variables was found; percentages

overweight and obesity in the study group were similar to the company average. We did find

that older workers were slightly overrepresented in the study, which could be a result of older

workers being invited to participate in PHS more frequently than younger workers (every two

years, compared to every four years). We tried to identify reasons for declining the invitation

for participation among non-responders, but we did not succeed in getting answers from this

group. Increasing participation by more intensive recruitment strategies is not always preferable

considering that these strategies will probably also negatively affect compliance, by including

less motivated workers. Moreover, the company was already making an effort to maximise

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participation in the periodic health screenings, for example by performing the screenings at the

worksite.

When missing data are extensive this could also threaten the validity and generalizability of the

conclusions of an RCT. It has been proposed that, in general, more than 20% loss to follow-up

could be a threat to internal validity [4,5]. Dropout rate in obesity RCTs at 1 year after the start are

estimated to be as high as 37% [6]. After 1 year in the VIP in Construction study complete data

was obtained from 83% (17% dropout), which seems acceptable. Furthermore, dropout did not

seem to differ on health indicators compared to completers.

As described in chapter 5, long-term results of the trial showed decreased contrast between

intervention and control participants in weight-related and lifestyle behaviour outcomes. This

was the result of a combination of a relapse in the intervention group, as well as improvements in

the control group. Contamination might be one of the factors that contributed to improvement

in the control group. Workers in the intervention and control group were not isolated in the

trial setting, and crossover effects in lifestyle behaviour from the intervention participants to the

control participants could have occurred. Contamination of the control group was expected to

be minimal, since personal counselling and the toolbox were only available for the intervention

participants. Randomisation at the individual level, as performed in this RCT, could be regarded

as a weakness of the study design, since contamination could not be fully excluded. Within

companies cluster randomization, for example at department level, might therefore be preferred.

However, workers in the construction sector work at mobile and temporary worksites, which

complicates the cluster design. An additional explanation for the observed improvements in the

control group is a possible effect of the measurements as performed in this study. Feedback on

measurements concerning health status or behaviour at baseline and follow-up of an intervention

study can result in improvement of readiness for behaviour change [7].

Measurement issues

Measuring energy intake and energy expenditure

Most of the study outcomes, such as weight-related measures, were measured objectively, and

sickness absence data was collected from company records, which is regarded more reliable than

self-report [8]. For several other outcome measures, we did rely on self-report. Health behaviour

(physical activity and dietary behaviour) was measured by self-report and as a result potentially

differential misclassification in reporting of health behaviours in the follow-up measurements

between intervention and control participants should be considered. Although possible resulting

bias does not affect RCT results, because it is expected that it is the same for intervention and

control participants, it is conceivable that due to the intervention, intervention participants are

more aware of recommended standards for physical activity and diet and as a result report

differently at follow-up.



8

BMI as a measure for fatness

In chapter 2 BMI was used as identifier for excess fatness. BMI is a widely accepted, recommended,

and easy to use measure for assessing excess body weight in populations. There has been some

discussion, however, on the misclassification by BMI since it does not discriminate between lean

body mass or fat mass. In a group of workers that are on average more physically active at work,

with an expected higher percentage of muscle mass, this might result in overestimation of the

number of workers in high-risk categories. However, it could also be considered a conservative

measure when assessing health risks. In adults the use of BMI as a measure of adiposity (excessive

body fatness) was concluded to result in a serious underestimation of obesity prevalence [9].

Health-related excess of body fat is not always accompanied by BMI values above the standard

cut-off values for healthy body weight. Also in the relation with MSD, it is relevant to distinguish

between fat and fat-free mass; for example in knee osteoarthrosis, the relation between fat-free

mass and MSD has been found to be beneficial, while fat mass has been negatively related to

MSD [10]. As an additional measure in the trial waist circumference was included as a measure of

excess body weight. Waist circumference is a measure of central overweight and obesity directly

related to health risk, and changes in waist circumference have found to better reflect changes

in energy-balance-related behaviour than do changes in BMI [11]. It should be mentioned that

that this measure is prone to large measurement error [12]. Therefore, waist circumference is an

important additional measure, provided that the measurements are preceded by protocol and

training, repeated measures are used. By using average values of multiple measures, random

measurement error, which can be positive or negative about the true value, can be decreased.

Programme design

Understanding determinants of behaviour is a key component of developing effective behavioural

interventions [13,14]. Changes in the targeted determinants should result in changes in the

behaviour. If a programme has small or no effects, the intervention strategies for changing these

mediating variables may not be optimal or the proposed theoretical model should be revised to

include important mediating variables.

Theoretical framework

In the VIP in Construction programme several theoretical models were integrated (chapter

3) to match a specific population and its specific context. In this study the stages of change

construct from the transtheoretical model (TTM) that maps the process of behaviour change

[15] has been used to tailor the intervention. This was done by matching intervention strategy

and intensity to individuals’ motivational readiness to change (chapter 3) as well as to compare

workers longitudinal shift in readiness to change pre- and post-intervention (chapter 4). Several

reviews have questioned the effectiveness of health promotion and physical activity programmes

based on TTM [16-19]. At present, evidence is not very strong that stage-based interventions

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significantly increase effectiveness. Stage-based interventions have been found to be reasonably

effective in adoption of behaviour, but not on long term adherence [18]. Another critique is that

the TTM focusses on personal motivation and not on external and social factors, such as age or

socioeconomic position [19]. Therefore, the impact of TTM and the stages of change construct

as a theoretical basis in weight management may depend on how it is used as a framework for

intervention and in combination with other strategies aiming at diet and physical activities [20].

As a tool, TTM provides a useful basis for designing interventions. The model has the potential

to increase effectiveness of counselling. Yet, in effectiveness studies the results of changes in

stages of change should be interpreted with caution. The constructs of the model are not the

same for all types of behaviour, and for complex health behaviours, such as lifestyle behaviour,

validity of the constructs is not clear and should be tested in specific populations [21]. In chapter

4 we reported effects on psychosocial constructs related to behaviour. The observation that

motivational stage of change improved, does not necessarily demonstrate these constructs to

mediate physical activity and dietary behaviour. It would be of interest to further test this using

mediation analysis.

Intervention strategies and components aimed at MSD

Despite the high level of involvement of workers and the employer in the development of the

programme, not all factors that are considered important risks for MSD could be included in the

final programme (chapter 3). Known risk factors for MSD related to the workplace and workload

should also be considered. Although in the past decades primary prevention on physical work

demands has improved and biomechanical load for construction work has decreased, results from

long-term follow-up studies do not show a significant preventive effect for MSD [22]. Ergonomic

measures can be used to reduce the burden of physically demanding work tasks [23].

Linking the programme to periodical health screening

Motivating workers to participate in health promotion programmes is a challenge. Among

individuals with weight-related health risks, many are not considering to lose weight [24]. Blue

collar workers are less likely to participate in health promotion programmes [25]. Accurate

perception of body weight and awareness of associated health risks are motivators for individuals

to make changes in lifestyle behaviour [24,26]. From interviews with the target population

(chapter 3) we learned that overweight was perceived less as a health problem than for example

other risk for cardiovascular disease, such as high blood pressure. Recruiting through periodical

health screening is therefore considered a strength of the study, because it enabled linking the

lifestyle programme to several health outcomes. Further explanation of health risks might also

increase effectiveness of these screenings in construction workers [27].



8

Comparison of the findings with those of other studies

Considering the lack of sustained effects of the VIP in Construction intervention, it is of interest

to compare the study findings to the results of other studies.

Lifestyle weight loss interventions in the workplace

In general, it appears that worksite health promotion interventions targeting overweight

populations have positive effects on measures of dietary behaviour [28] and physical activity

[29] but effect sizes are small. Systematic reviews on workplace interventions aiming at reducing

body weight conclude that modest positive effects can be expected [30]. Many of these studies,

however, targeted workers in white-collar occupations. Intervention studies in blue collar

occupations with a high-risk approach, including only overweight workers (BMI > 25) or workers

with an elevated risk on CVD, with higher baseline BMI did show modest reductions in body

weight and BMI after 12 months [31,32].

Weight gain prevention

Worksites increasingly have a key role in public health strategies in preventing illness as well

as promoting health. Therefore, there has been a shift in focus towards primary prevention in

body weight management. Relatively few trials are found on the prevention of weight gain

[33-35]. Five studies reported a significant difference in body weight between intervention and

control group (1.0-3.5 kg) largely due to an increase in body weight in the control groups [34].

A meta-analyses of workplace interventions of Verweij et al. (2011) found interventions to be

moderately effective in reducing body weight with 1.2 kg, with subgroup analysis showing a

greater reduction for interventions containing an environmental component [36]. Compared to

the evidence on strategies for initiation of body weight loss, the evidence base of maintenance

strategies is very small.

A possible explanation for the lack of sustained effects has been proposed by Katan & Ludwig

(2010). They argue that single changes in diet or physical activity will elicit compensatory

mechanisms in the body that limit long-term effects on body weight. When reaching a lower

body weight, energy expenditure of maintaining and moving the body decreases. This implies

that after initial changes in body weight, even more effort has to be made to maintain the

lower body weight. This would require longer follow-up in intervention programmes, either by

increasing the number of contacts or other means to stimulate continuation of adjusting energy-

balance-related behaviour.

Compared to studies that show larger effects, the intervention studied in the present thesis was

rather low-intensive. Lifestyle and weight loss interventions have demonstrated larger effects

when comprising numerous contacts of long duration [37]. One study found an average of

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participants 43.6% in low intensity interventions lost no weight or gained weight [38]. In studies

with weight loss as a primary outcome, more intensive approaches have typically been more

effective than those with less contact [33,39]. However, for weight gain prevention there is no

similar evidence for larger effects with more intensive interventions [34]. Moreover, such intensive

approaches have a number of limitations. The costs are higher and they are likely to appeal to only

a small percentage of those who would benefit because of the level of commitment required.

Low-intensity, tailored interventions that can be incorporated in or linked to ongoing routine

health screenings will probably increase the likelihood of compliance. To increase the probability

of sustaining the initial effects, interventions should consist of longer follow-up periods. Follow-

up contacts with the coaches could be telephone contact, text messages or by e-mail. It should

be kept in mind that personal contact with the coaches was the most appreciated component of

the intervention. This is supported by weight gain prevention literature providing evidence that

interventions with some personal contact in delivery of the intervention were more successful

[34].

Lifestyle interventions and MSD

Workplace health promotion programmes that improve physical activity levels have been shown

to reduce the risk on MSD [40,41]. In the present study increased vigorous physical activity in the

intervention group was not accompanied by a significant decrease in MSD. We did not assess

if changes in physical capacity occurred resulting from an increase in physical activity. A study

that was effective in increasing the amount of physical activity in construction workers, but not

effective in decreasing musculoskeletal pain, showed an increase in aerobe capacity, but no

increase in muscle strength [42,43]. Therefore, this might not have been the appropriate type

of physical activity to increase functional capacity and the potential to reduce or prevent MSD.

International health guidelines recommend adults to perform at least 30 minutes of moderate

physical activity 5 days per week [44]. While these guidelines are based on prevention of metabolic

syndrome related disorders, the optimal duration and frequency of physical exercise for proper

musculoskeletal function, especially in physically straining jobs, remains to be established. In office

workers there is moderate to strong evidence for effectiveness of muscle strength training [45],

and a recent study that was effective on pain relief in industrial workers shows that programmes

should include high-intensity progressive strength training[46].

Reflections

Relevance of fatness as health indicator, fitness versus fatness

In apparently healthy individuals, physical health-related quality of life decreases with increasing

level of BMI [47]. Both overweight and physical activity levels (inactivity) have adverse effects



8

on health. However, contradictory findings from studies have led to debate about the relative

importance of fitness and body fatness on disease risks [48]. When considering all-cause mortality

risk, a recent study advocates focusing on physical activity and fitness-based interventions

rather than weight loss driven approaches [49]. There is also debate on the role of exercise and

cardiorespiratory fitness as potential modifiers in the relation between BMI and cardiovascular

disease [50]. A number of studies indeed suggest that physical activity counteracts some of the

health risk of overweight. Physical activity has beneficial effects on inflammatory processes and

insulin and blood sugar levels, resulting from excess weight, especially central obesity. However,

other studies found that abdominal obesity is a predictor of cardiovascular disease independent

of fitness level [51,52] or that BMI showed the highest risk [53]. It can be concluded that there

is conflicting evidence, and although in mildly overweight individuals physical activity will offset

some of the effects of extra weight, increasing physical activity or exercising will not completely

erase all health risk of being overweight [53]. Furthermore, the higher physical activity levels at

work of blue collar workers are not associated with higher cardiorespiratory fitness and health

[54,55]. Moreover, in addition to overweight and obesity related health problems, such as

cardiovascular disease or metabolic syndrome, musculoskeletal problems associated with high

BMI should be considered [56]. Weight loss has been found to reduce musculoskeletal pain,

which could encourage compliance with health promotion programmes [57]. Therefore, the

focus should be on healthy weight and physical activity should be an essential part of weight loss

or weight gain prevention programmes.

High-risk versus population based approach

Interventions to combat the obesity epidemic have mainly targeted at weight loss treatment in

obese adults, with limited long-term effects [33]. With the increasing number of people at risk

or being overweight, there has been a shift in focus towards prevention of obesity. Considering

the small short-term intervention effects on body weight-related outcomes in the group of

participants in this study, which consisted of a group of workers that were not specifically

selected on overweight, the question rises if we should specifically aim at a high-risk group,

where individual effects could be expected to be more substantial. In the present study, baseline

scores on BMI did not appear to be modifiers for the intervention; the intervention was effective

(short-term) on body weight-related measures, independent of participants being overweight,

obese or healthy weight (unpublished data). Based on these results, BMI should not be a basis

for assignment or exclusion for workers to the workplace intervention. In general, for long-term

health gains it is preferable to remove the underlying risk, which is the aim of primary prevention,

and supports the population approach. Also the potential negative impact by increasing weight-

based stigma of programmes that specifically target individuals based on their weight status

should be considered [58]. Although primary prevention is preferred, resources for prevention are

limited, which stresses the need to select priority groups [59]. Through workplaces there is the

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ability to reach specific occupational groups that consist of populations that are homogeneous

in working conditions, educational level, social class, and health. Based on their socioeconomic

status, blue collar construction workers can be considered a high-risk group regarding health

status, and health behaviour. Within the population approach it is possible to differentiate within

a programme to reduce the costs. In the VIP in Construction programme this was applied on

the level of the individual worker with differences in focus and intensity of the intervention.

In a modified programme, this could be applied in a more environmental focused intervention

including components and strategies that are suitable for a worker population consisting of a

group with varying motivational stages and risk levels.

Multicomponent comprehensive programmes and the Total Worker Health concept

The Total Worker Health concept as conceived by the National Institute for Occupational Safety

and Health (NIOSH) advocates integrating health protection and health promotion programmes

[60]. To decrease risk factors in the work environment, health protection programmes traditionally

focused on safety, whereas workplace health promotion programmes focus on lifestyle factors

off-the-job. The integrated approach potentially increases participation [61] and contributes to

larger improvements in behaviour change [62,63]. In this paragraph I will illustrate this with

examples on energy balance and MSD.

Dimensions beyond the energy balance

When summarizing the conclusions of reviews on worksite health promotion programmes,

although overall moderate positive results are found for interventions aiming at individual

determinants, effects are small and not easy to maintain, and more impact is expected from

comprehensive programmes when environmental and cultural changes in the workplace are also

included [64]. Integrating worksite health promotion to occupational safety and health might

also be relevant in targeting lifestyle behaviour, as unhealthy dietary habits and other health

behaviour, such as smoking, in blue collar workers have been found to correlate with increased

exposure to work-related risks[65].

Programmes should be tailored to meet the specific employee health concerns, and work

settings. Environmental strategies that are currently found in lifestyle interventions are usually

modifications in the physical environment, such as modifications in workplace canteens and

offering physical activity programmes at work. These strategies are not suitable or easy to

implement for all occupational groups, particularly in construction workers who often work

at mobile and temporary workplaces. This diversity and geographical dispersion of physical

work settings shows the need to focus on factors in the social context of the workplace, such

as management support and social norms. Changes in socio-cultural aspects of the worksite

therefore deserve more consideration in future interventions involving worker populations with

comparable characteristics.



8

Addressing the complexity and multicausality of MSD

As argued in the paragraph on programme design, workers health and safety problems are

recognised to result from both work-related factors and health factors beyond the workplace. For

the prevention of MSDs there is moderate evidence that interventions based on single measures are

ineffective. The multiple factors involved in the development of MSD, such as work related factors

(e.g. lifting, awkward postures), individual factors (e.g. age, body weight, physical capacity), and

also psychosocial risk factors (e.g. social support and job satisfaction) [66-68]. In addition to the

broad range of risk factors there are other arguments that support multi-component programmes.

Based on focus group interviews with the target population it can be concluded that risks outside

personal control are given highest priority. Therefore, workers may feel that the importance and

benefits of individual health behaviour changes are less than those of work-related factors. To

illustrate, blue collar workers were more likely to participate in smoking cessation and nutrition

programmes if they reported changes of their employer to reduce work-related risk factors [69].

Thus, more effect can be expected when workers perceive that the employer is not only initiating

a health promotion programme but simultaneously making changes in the work environment and

organisational culture in an effort to promote health. In blue collar occupations with increased

work-related risk of adverse health effects, integrating worksite health promotion to other efforts

for occupational health and safety may increase programme participation.

The previous paragraphs reinforce the rationale for the potential larger effects that could be

gained from a multidisciplinary approach, combining several intervention components, including

individual measures combined with organisational “redesign” to reduce workload.

A systematic review on occupational safety and health interventions to reduce musculoskeletal

symptoms in the health care sector concluded that there is moderate level of evidence for

exercise and multi-component interventions [70]. However, recent multi-component intervention

studies on musculoskeletal symptoms focusing on workers in physically demanding jobs, such as

construction workers or cleaners, did not show effects on symptoms [43,71,72]. Further research

for effective strategies is therefore warranted.

Towards Total Workforce Health

The VIP in Construction programme provided a strategy to reach workers who are at high risk but

may be unable to participate in traditional worksite health promotion. Linking the programme to

periodical health screening, tailoring the programme to make it personally relevant and planning

the counselling sessions at work and during working hours were elements of the programme

to match the context and individual worker need and preferences. In the VIP in Construction

programme external determinants for physical activity behaviour and dietary behaviour were

included in the conceptual model. However, the main focus in the current programme was on

personal determinants of lifestyle behaviour change. In an adapted and improved version of the

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VIP in Construction programme, the physical and social work environment should be considered

to improve reach and increase effectiveness. Based on the current thesis and the growing body

of evidence in this direction, I suggest integrating occupational health and safety and worksite

health promotion. Intervention developers should use the stages of change model to design and

include components for all motivational and health risk levels in programmes aiming at the total

workforce.

Implementation of worksite health promotion into practice

Managing human capital and human resource management will become one of company’s

most important business issues. Especially in a tight job market improving worker productivity by

decreasing sickness absenteeism and presenteism might be the most important incentive to invest

in health promotion. In the work setting, starting new projects or implementing health promotion

programmes is a business decision. It is challenging for employers to weigh effectiveness against

economic viability of worksite health promotion programmes. If consequences of improved

employee health cannot be quantified to support business decisions, employers may not be

willing to invest in health interventions. In my view, this would be a missed opportunity, as health

promotion and employee health can be considered an investment in ‘human capital’, with more

intangible factors, such as corporate image and job satisfaction, which probably have a less

detectable financial profit, and require long-term investment. Therefore, additional research is

required to investigate if and how improvements in workforce health translate into improvements

in work-related measures relevant to employers, in order to establish a better link between health

promoting programmes and business objectives. While research indicates that worksite health

promotion programmes are effective in reducing absenteeism and presenteism rates [73-75],

evidence on their impact on other endpoints remains limited. Recent work has been conducted to

better conceptualise and measure individual work performance [76], and more needs to be done

to further understand the relationship between these measures and individual or total workforce

health.

Implications and recommendations for practice

Following the results as described in the separate chapters of this thesis, and the reflections in

the current chapter, I would like to provide practical recommendations for programmes in the

occupational setting.

• It is not recommended to implement the VIP in Construction programme in its current

form. In order for worksite health promotion programmes to have a meaningful impact,

the programme’s effectiveness should be long lasting. However, transition in motivation



8

to change behaviour and initial short-term change in behaviour and health outcomes

as found in this trial is an important, although not sufficient, condition for long-term

change to occur. To increase the probability of sustaining the initial effects, interventions

should consist of longer follow-up contact periods.

• Increasing participation and effectiveness of worksite health promotion programmes

would require the design of these programmes to include the social and physical work

environment in addition to the individual level, and integrate health promotion with

occupational health and safety efforts. This applies to outcomes that are related to

health and health behaviour, as well as work-related outcomes, such as work ability and

sickness absence.

• To reach a worker population that is not highly motivated and difficult to reach in health

promotion practices, linking interventions to periodical health screening is a promising

strategy. It has the potential to increase participation, and could be a useful starting

point for further integration of worksite health promotion and occupational health and

safety programmes.

• It is recommended to combine the population and high-risk approach. Employers should

aim at health promotion initiatives for all their employees, provided that elements for

workers at different health risk and motivational levels are included.

Future scientific perspectives and recommendations

Some implications for research arise from the results of the current thesis:

• This thesis started with the question of whether managing overweight could also be

a potential effective strategy for the prevention or reduction of MSD. Overweight as a

modifying factor in the relation between strenuous work and musculoskeletal symptoms

has been rarely addressed in previous studies. To better understand the possible benefits

of lifestyle interventions on the musculoskeletal system, well designed studies that

assess the effects of significant body weight reduction and specific types of physical

activity and exercise on MSD are needed.

• In physical activity and exercise interventions aiming at improving MSD, physical capacity

measures should be included. This would provide more evidence for the type or intensity

of physical activity or specific exercises for preventing or improving musculoskeletal

symptoms.

• The process evaluation gave insight in the applicability of the programme components,

as well as effectiveness on potential mediating factors. However, since this does not

necessarily demonstrate these constructs to mediate lifestyle behaviour change, it

would be of interest to further test this using mediation analysis.

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• Given the general frequency of body weight rebound after short-term weight loss,

additional research is needed regarding the most effective means of maintaining initial

success. More research is needed to determine if successful body weight maintenance

or sustained body weight loss share the same behavioural determinants or metabolic

factors that play a role in initial body weight loss.

• In designing future programmes, environmental and cultural changes should be

considered. This would require the use of ecological frameworks for interventions

that include the complexity of the (work) environment and levels of intervention.

Thus, future research on worksite health promotion should also include looking into

the (cost-)effectiveness for programmes with combined individual and environmental

components.

Conclusion

Despite a systematic design and theory-based approach resulting in a tailored programme with

promising short-term results on intermediate and primary outcomes, overall the VIP in Construction

study did not prove to be (cost-)effective after 12 months follow-up. The results of this study

indicate that a relatively low-intensity worksite intervention has the potential to improve dietary

and physical activity behaviour, and to contribute to the prevention of body weight gain in blue

collar construction workers. Although these outcomes initially improved, the programme was not

successful in improving other health-related, work-related, or long-term outcomes. Organisations

attempting to improve worker health and work-related outcomes, should therefore provide a

more multifaceted intervention including (psycho-social) work organisational and environmental

aspects and focus additionally on effective maintenance strategies.



8

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28. Ni Mhurchu C, Aston LM, Jebb SA: Effects of worksite health promotion interventions on employee diets: a systematic review. BMC Public Health 2010, 10: 62.


30. Anderson LM, Quinn TA, Glanz K, Ramirez G, Kahwati LC, Johnson DB et al.: The effectiveness of worksite nutrition and physical activity interventions for controlling employee overweight and obesity: a systematic review. Am J Prev Med 2009, 37: 340-357.

31. Christensen JR, Overgaard K, Carneiro IG, Holtermann A, Sogaard K: Weight loss among female health care workers--a 1-year workplace based randomized controlled trial in the FINALE-health study. BMC Public Health 2012, 12: 625.

32. Groeneveld IF, Proper KI, van der Beek AJ, van Mechelen W: Sustained body weight reduction by an individual-based lifestyle intervention for workers in the construction industry at risk for cardiovascular disease: results of a randomized controlled trial. Prev Med 2010, 51: 240-246.

33. Lemmens VEPP, Oenema A, Klepp KI, Henriksen HB, Brug J: A systematic review of the evidence regarding efficacy of obesity prevention interventions among adults. Obes Rev 2008, 9: 446-455.

34. Lombard CB, Deeks AA, Teede HJ: A systematic review of interventions aimed at the prevention of weight gain in adults. Public Health Nutr 2009, 12: 2236-2246.

35. van Wier MF, Ariens GAM, Dekkers JC, Hendriksen IJM, Pronk NP, Smid T et al.: ALIFE@Work: a randomised controlled trial of a distance counselling lifestyle programme for weight control among an overweight working population [ISRCTN04265725]. BMC Public Health 2006, 6: 140.

36. Verweij LM, Coffeng J, van MW, Proper KI: Meta-analyses of workplace physical activity and dietary behaviour interventions on weight outcomes. Obes Rev 2010.

37. Greaves CJ, Sheppard KE, Abraham C, Hardeman W, Roden M, Evans PH et al.: Systematic review of reviews of intervention components associated with increased effectiveness in dietary and physical activity interventions. BMC Public Health 2011, 11: 119.

38. Christian JG, Tsai AG, Bessesen DH: Interpreting weight losses from lifestyle modification trials: using categorical data. Int J Obes (Lond) 2010, 34: 207-209.

39. Wing RR: Behavioral treatment of obesity. Its application to type II diabetes. Diabetes Care 1993, 16: 193-199.



8


41. Mattila R, Malmivaara A, Kastarinen M, Kivela SL, Nissinen A: The effects of lifestyle intervention for hypertension on low back pain: a randomized controlled trial. Spine (Phila Pa 1976) 2007, 32: 2943-2947.

42. Gram B, Holtermann A, Sogaard K, Sjogaard G: Effect of individualized worksite exercise training on aerobic capacity and muscle strength among construction workers - a randomized controlled intervention study. Scand J Work Environ Health 2011.

43. Gram B, Holtermann A, Bultmann U, Sjogaard G, Sogaard K: Does an exercise intervention improving aerobic capacity among construction workers also improve musculoskeletal pain, work ability, productivity, perceived physical exertion, and sick leave?: a randomized controlled trial. J Occup Environ Med 2012, 54: 1520-1526.

44. Haskell WL, Lee IM, Pate RR, Powell KE, Blair SN, Franklin BA et al.: Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 2007, 39: 1423-1434.

45. Andersen LL, Christensen KB, Holtermann A, Poulsen OM, Sjogaard G, Pedersen MT et al.: Effect of physical exercise interventions on musculoskeletal pain in all body regions among office workers: a one-year randomized controlled trial. Man Ther 2010, 15: 100-104.

46. Zebis MK, Andersen LL, Pedersen MT, Mortensen P, Andersen CH, Pedersen MM et al.: Implementation of neck/shoulder exercises for pain relief among industrial workers: a randomized controlled trial. BMC Musculoskelet Disord 2011, 12: 205.

47. Korhonen PE, Seppala T, Jarvenpaa S, Kautiainen H: Body mass index and health-related quality of life in apparently healthy individuals. Qual Life Res 2014, 23: 67-74.

48. McAuley PA, Beavers KM: Contribution of cardiorespiratory fitness to the obesity paradox. Prog Cardiovasc Dis 2014, 56: 434-440.

49. Barry VW, Baruth M, Beets MW, Durstine JL, Liu J, Blair SN: Fitness vs. fatness on all-cause mortality: a meta-analysis. Prog Cardiovasc Dis 2014, 56: 382-390.

50. Wing RR, Jakicic J, Neiberg R, Lang W, Blair SN, Cooper L et al.: Fitness, fatness, and cardiovascular risk factors in type 2 diabetes: look ahead study. Med Sci Sports Exerc 2007, 39: 2107-2116.

51. Berentzen T, Madsbad S, Sorensen TIA, Astrup AV: [The importance of physical activity and fitness in avoiding the complications of obesity]. Ugeskr Laeger 2006, 168: 144-149.

52. Fogelholm M: Physical activity, fitness and fatness: relations to mortality, morbidity and disease risk factors. A systematic review. Obes Rev 2010, 11: 202-221.

53. Jackson C, Herber-Gast GC, Brown W: Joint effects of physical activity and BMI on risk of hypertension in women: a longitudinal study. J Obes 2014, 2014: 271532.

54. Holtermann A, Jorgensen MB, Gram B, Christensen JR, Faber A, Overgaard K et al.: Worksite interventions for preventing physical deterioration among employees in job-groups with high physical work demands: background, design and conceptual model of FINALE. BMC Public Health 2010, 10: 120.

55. Holtermann A, Hansen JV, Burr H, Sogaard K, Sjogaard G: The health paradox of occupational and leisure-time physical activity. Br J Sports Med 2012, 46: 291-295.

56. Hooper MM: Tending to the musculoskeletal problems of obesity. Cleve Clin J Med 2006, 73: 839-845.

57. Kotowski SE, Davis KG: Influence of weight loss on musculoskeletal pain: Potential short-term relevance. Work 2010, 36: 295-304.

58. Barry CL, Gollust SE, Niederdeppe J: Are Americans ready to solve the weight of the nation? N Engl J Med 2012, 367: 389-391.

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62. Sorensen G, Stoddard AM, LaMontagne AD, Emmons K, Hunt MK, Youngstrom R et al.: A comprehensive worksite cancer prevention intervention: behavior change results from a randomized controlled trial (United States). Cancer Causes Control 2002, 13: 493-502.

63. Sorensen G, Barbeau E, Stoddard AM, Hunt MK, Kaphingst K, Wallace L: Promoting behavior change among working-class, multiethnic workers: results of the healthy directions--small business study. Am J Public Health 2005, 95: 1389-1395.

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65. Sorensen G, Stoddard A, Hammond SK, Hebert JR, Avrunin JS, Ockene JK: Double jeopardy: workplace hazards and behavioral risks for craftspersons and laborers. Am J Health Promot 1996, 10: 355-363.

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67. Macfarlane GJ, Pallewatte N, Paudyal P, Blyth FM, Coggon D, Crombez G et al.: Evaluation of work-related psychosocial factors and regional musculoskeletal pain: results from a EULAR Task Force. Ann Rheum Dis 2009, 68: 885-891.

68. Jacobsen HB, Caban-Martinez A, Onyebeke LC, Sorensen G, Dennerlein JT, Reme SE: Construction workers struggle with a high prevalence of mental distress, and this is associated with their pain and injuries. J Occup Environ Med 2013, 55: 1197-1204.

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72. Jorgensen MB, Faber A, Hansen JV, Holtermann A, Sogaard K: Effects on musculoskeletal pain, work ability and sickness absence in a 1-year randomised controlled trial among cleaners. BMC Public Health 2011, 11: 840.

73. Aldana SG, Pronk NP: Health promotion programs, modifiable health risks, and employee absenteeism. J Occup Environ Med 2001, 43:36-46.

74. Kuoppala J, Lamminpää A, Husman P: Work health promotion, job well-being, and sickness absenses-A systematic review and meta-analysis. J Occup Environ Med 2008, 50:1216-1227.

75. Cancelliere C, Cassidy JD, Ammendolia C, Cote P: Are workplace health promotion programs effective at improving presenteism in workers? A systematic review and best evidence synthesis of the literature. BMC Public Health 2011, 11:395.

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Summary

Samenvatting

Dankwoord

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Summary | 175

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Summary

In the construction industry, the workforce is ageing and despite technological innovations

workers are still facing high physical work demands. Especially in combination with unfavourable

health and lifestyle indicators this provides challenges for maintaining a sustainable and productive

workforce, which emphasises the need for interventions in the construction industry. Chapter 1

provides an introduction to the background and objectives of this thesis. The main goal of this

thesis was to systematically develop a tailored intervention to prevent and reduce overweight and

musculoskeletal disorders in blue collar construction workers. This intervention programme (VIP

in Construction) was evaluated in a randomised controlled trial.

In order to gain more insight into the potential of body weight management as a strategy for

reducing musculoskeletal disorders, the relation between body weight and musculoskeletal

symptoms was studied (chapter 2). Based on analyses in a large working population sample,

body mass index (BMI) was found to be positively associated with musculoskeletal symptoms, in

particular symptoms of the lower extremity. Additionally, compared to employees with normal

weight, obese employees were at increased risk for developing musculoskeletal symptoms and

suffered impaired recovery. Surprisingly, the association was stronger for employees with a low

physical workload compared to those with a high physical workload.

The systematic development of the VIP in Construction intervention, as well as the design of

the randomised controlled trial, is thoroughly described in chapter 3. The Intervention Mapping

protocol was applied to systematically develop the intervention. By doing so, the intervention

matched the needs and preferences of the target population and was based on the current

evidence for the effectiveness of lifestyle interventions. The intervention programme consisted

of individual face-to-face and telephone counselling, both employing information and materials

aimed to improve lifestyle behaviour. The intervention was tailored to each participant’s

motivational readiness for change, varying in focus, number, and duration of counselling sessions.

To further increase compliance, the intervention was linked to the company’s periodic medical

examinations and took place at the worksite and during working hours.

A process evaluation was conducted to better explain the study’s findings, and to give insight in

the implementation of the intervention. The process evaluation of the intervention (chapter 4)

was conducted following the RE-AIM framework for the evaluation of the public health impact

of health promotion interventions. Both qualitative and quantitative methods were applied to

evaluate process measures. The external validity of the trial was satisfactory, based on representative

reach of workers and adoption of workplace units in the participating construction company.

Intervention participants showed significantly more progression through the different stages of

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behaviour change than did controls. The extent to which the intervention was implemented

was, however, modest. The satisfaction of participants was, in contrast, high and 84% of the

participants received at least one counselling session. Still, adjustments to the intervention should

be made to improve exposure and fidelity to the protocol. Based on the RE-AIM dimensions, it

was concluded that the intervention is feasible and based on improvements on determinants of

behaviour change potentially effective in blue-collar construction workers.

Chapter 5 and 6 present the effect evaluation of the worksite health promotion intervention. A

total of 314 participants were randomised to the intervention (n=162) or control group (n=152).

Data were collected at baseline, at 6 months directly following the intervention, and at 12 months.

After 12 months the loss to follow-up was 17%. The effectiveness of the intervention compared

to usual care was assessed using regression analyses with the outcome measures at 6 months

and 12 months follow-up as the dependent variables and adjusting for the baseline levels of the

outcome measure. Effectiveness of the intervention on body weight, BMI, waist circumference,

physical activity, dietary intake, blood pressure, and blood cholesterol is presented in chapter 5.

Initially, at 6-month follow-up, intervention participants significantly showed positive changes

in physical activity and dietary behaviours (decrease in intake of sugar-sweetened beverages)

compared to controls, as well as positive effects in body weight and related outcomes (body

weight, BMI and waist circumference). Long-term effects on body weight and related outcomes

were still promising, but no longer statistically significant. Chapter 6 describes the evaluation

on musculoskeletal symptoms, physical functioning, work-related vitality, work performance,

work ability, and sickness absence. Neither at 6-month follow-up nor at 12-month follow-up

statistically significant intervention effects on these outcomes were found.

Chapter 7 describes a cost-effectiveness and financial return evaluation of the intervention

compared to usual care. The evaluation was conducted alongside the RCT with a follow-up of

12 months and included both the societal and the employer’s perspective. The intervention was

found to be not cost-effective from the employer’s perspective, in improving work-related vitality

and job satisfaction. It was concluded that the cost-effectiveness of the intervention, of which

the costs were €287 per worker, depends on the “willingness to pay” of decision makers for their

effects. Financial return estimates were positive for the employer, but these estimates showed a

high level of statistical uncertainty.

In the final chapter (chapter 8) the main findings are discussed and interpreted, and

recommendations for future research and practice are given. It was concluded that despite a

systematic design and theory-based approach resulting in promising short-term results on

intermediate and primary outcomes, overall the VIP in Construction intervention showed no

additional beneficial (cost-)effectiveness or statistically significant financial return after the


Summary | 177

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first year of implementation. Therefore, the implementation of the intervention in its current

form cannot be recommended. Based on the findings of this thesis, organisations attempting

to improve worker health and work-related outcomes should provide a more multifaceted

intervention including (psycho-social) work organisational and environmental aspects and should

additionally focus on effective maintenance strategies.

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Samenvatting

De bouwsector heeft te maken met vergrijzing van werknemers en met zware fysieke werk-

belasting. In combinatie met ongunstige gezondheids- en leefstijlindicatoren leidt dit tot

uitdagingen om werknemers in deze sector duurzaam inzetbaar en productief te houden.

Hoofdstuk 1 is een introductie op de achtergronden en doelstellingen van dit proefschrift. Het

primaire doel van de studie, zoals beschreven in dit proefschrift, was om op systematische wijze

een programma op maat te ontwikkelen ter preventie en reductie van zowel overgewicht als

bewegingsapparaat-klachten bij werknemers in de bouw. Het ontwikkelde programma (VIP in de

bouw) is vervolgens geëvalueerd in een gerandomiseerde en gecontroleerde trial (RCT).

Om het potentieel van beïnvloeding van lichaamsgewicht als strategie voor het verminderen

van bewegingsapparaat-klachten beter te begrijpen, is in hoofdstuk 2 de relatie tussen

lichaamsgewicht en bewegingsapparaat-klachten bestudeerd. In een grote steekproef van

de beroepsbevolking vonden we een positieve associatie tussen body mass index (BMI) en

bewegingsapparaat-klachten, in het bijzonder die van de onderste extremiteit (zoals knieklachten).

Daarnaast hadden werknemers met ernstig overgewicht (obesitas) meer risico op het ontwikkelen

van bewegingsapparaat-klachten en een kleinere kans op herstel ervan, vergeleken met

werknemers met gezond gewicht. We vonden het verassend dat deze associatie sterker was voor

werknemers met lage fysieke werkbelasting dan met hoge fysieke werkbelasting.

De systematische ontwikkeling van de VIP in de Bouw interventie en het design van de RCT

is beschreven in hoofdstuk 3. De interventie is ontwikkeld met behulp van het Intervention

Mapping protocol. Door het toepassen van dit protocol sluit de interventie zoveel mogelijk aan bij

de behoeften en voorkeuren van de doelgroep én bij beschikbare wetenschappelijke kennis. De

interventie bestond uit individuele face-to-face en telefonische counseling met een leefstijlcoach,

waarbij informatie en materialen werden aangeboden gericht op het verbeteren van voeding

en lichamelijke activiteit. De interventie was toegespitst op de motivatie van de individuele

deelnemer om aanpassingen te doen in zijn leefstijlgedrag, en varieerde daarmee in focus, aantal

en duur van de sessies met de leefstijlcoach. Om de deelname te vergroten werd de interventie

gekoppeld aan de bij het bouwbedrijf gebruikelijke periodiek medische keuringen en vond de

interventie gedurende werktijd plaats op de werkplek.

Om de resultaten van de studie beter te kunnen verklaren en ook om inzicht te geven in de

implementatie van de interventie, is er een procesevaluatie uitgevoerd. Deze evaluatie van het

proces van het programma (hoofdstuk 4) is uitgevoerd en beschreven volgens het RE-AIM

framework voor de evaluatie van de impact van gezondheidsbevorderende interventies. Om het

proces te evalueren is zowel van kwalitatieve als van kwantitatieve onderzoeksmethoden gebruik

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gemaakt. We concludeerden dat de studiepopulatie een representatieve afspiegeling was van

de verschillende afdelingen van het deelnemende bouwbedrijf. Deelnemers aan de interventie

lieten significant meer progressie zien door de verschillende fasen van gedragsverandering dan

de controlegroep. Maar de interventie bleek niet geheel te zijn geïmplementeerd zoals beoogd.

De tevredenheid van de deelnemers was echter hoog en 84% van de deelnemers ontving ten

minste één coaching sessie. Desalniettemin zouden er aanpassingen aan de interventie moeten

worden gedaan om blootstelling aan de interventie en het volgen van het protocol te verbeteren.

Gebaseerd op de dimensies van RE-AIM concludeerden we dat de interventie haalbaar is in

de uitvoering en implementatie. Daarnaast werden er verbeteringen in determinanten van

gedragsverandering gevonden.

Hoofdstukken 5 en 6 beschrijven de effect-evaluatie van de interventie. In totaal werden 314

werknemers gerandomiseerd; 162 werden toegewezen aan de interventiegroep en 152 aan

de controlegroep. Gegevens werden verzameld voor aanvang van de interventie, direct na

de interventieperiode (na 6 maanden), en na 12 maanden. Na 12 maanden was 17% van de

deelnemers uitgevallen. Met regressie-analyses onderzochten we de effectiviteit van de interventie,

waarbij gecorrigeerd werd voor de uitgangswaarden van de uitkomstmaten. Effectiviteit van de

interventie op lichaamsgewicht, BMI, middelomtrek, lichamelijke activiteit, voeding, bloeddruk

en cholesterol is beschreven in hoofdstuk 5. Op korte termijn (na 6 maanden), werden positieve

effecten gevonden voor werknemers in de interventiegroep op beweeg- en voedingsgedrag

(inname van gezoete dranken/frisdrank) vergeleken met hun collega’s in de controlegroep. Ook

werden positieve effecten op lichaamsgewicht en daaraan gerelateerde uitkomstmaten gevonden

(BMI en middelomtrek). Op lange termijn waren effecten op lichaamsgewicht en daaraan

gerelateerde uitkomsten nog steeds veelbelovend, maar niet langer statistisch significant. In

hoofdstuk 6 is de evaluatie van uitkomsten ten aanzien van klachten aan het bewegingsapparaat,

fysiek functioneren, werkgerelateerde vitaliteit, werkvermogen, werkprestatie en ziekteverzuim

beschreven. Voor deze uitkomsten werden zowel na 6 maanden als na 12 maanden geen

statistisch significante interventie-effecten gevonden.

Hoofdstuk 7 beschrijft de economische evaluatie van de interventie. Deze evaluatie is uitgevoerd

naast de RCT en vanuit zowel het maatschappelijke als het bedrijfsperspectief. De interventie

bleek niet kosten-effectief in het verbeteren van werkgerelateerde vitaliteit en werktevredenheid

vanuit het bedrijfsperspectief. We concludeerden dat de kosten-effectiviteit van de interventie,

waarvan de kosten €287 per werknemer bedragen, afhankelijk is van de investeringsbereidheid

van beslissers en de kans op kosten-effectiviteit die zij acceptabel achten. De schattingen van

het financiële rendement voor het bedrijf lieten een kostenbesparing zien, maar de statistische

onzekerheid rondom deze schatting was groot.


Samenvatting | 181

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In het afsluitende hoofdstuk (hoofdstuk 8) zijn de belangrijkste bevindingen samengevat,

bediscussieerd en geïnterpreteerd. Daarnaast zijn er aanbevelingen gedaan voor zowel de praktijk

als voor toekomstig onderzoek. Op basis van dit proefschrift kan geconcludeerd worden dat de

ontwikkelde interventie na 12 maanden niet tot positieve effecten of statistisch significante baten

heeft geleid. Dit ondanks een systematische ontwikkeling en een op theorie gebaseerde aanpak.

We vonden na 6 maanden wel veelbelovende korte termijn effecten op zowel intermediaire als

primaire uitkomstmaten. Op basis van deze conclusie kan de implementatie van de interventie in

de huidige vorm niet worden aanbevolen. Gebaseerd op de bevindingen in dit proefschrift is het

aan te bevelen dat organisaties die de gezondheid van hun medewerkers willen verbeteren en ook

werkgerelateerde uitkomsten positief willen beïnvloeden, een veelzijdiger programma aanbieden.

In een dergelijk programma zouden ook organisatie- en omgevingselementen moeten worden

meegenomen. Het is daarnaast raadzaam dat toekomstige interventies elementen bevatten die

er specifiek op gericht zijn om de effecten op lange termijn te behouden.

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Dankwoord

Nu is dan het moment dat alles op papier staat, met het dankwoord nog te gaan. Alleen daarvoor

ben ik al dankbaar. Promoveren doe je zeker niet alleen. Gelukkig heeft het me de afgelopen

jaren zeker niet ontbroken aan inspirerende, motiverende en lieve mensen om me heen. Graag

wil ik daarom hier de volgende mensen bedanken.

Begeleiding

Allereerst wil ik graag mijn promotoren, prof. dr. Allard van der Beek en prof. dr. ir. Paulien

Bongers en mijn co-promotor dr. Evert Verhagen bedanken.

Evert, een fijnere begeleider had ik me niet kunnen wensen. Ik heb veel bewondering voor je

snelle en analytische blik, en het vermogen om meteen to-the-point te komen. Met je eeuwige

optimisme en ‘alles komt goed’ bracht je me weer in balans als ik ergens over piekerde. Ondanks

dat je veel op reis was, kon ik altijd rekenen op razendsnelle respons.

Allard, ik heb het even in de van Dale opgezocht, pragmatisch=gericht op feiten, inspelend op

de praktijk; zakelijk. Een effectieve eigenschap die ik je toedicht en waar ik je hartelijk voor wil

danken. Daarnaast waardeer ik de persoonlijke aandacht die je aan je promovendi weet te geven

zeer. Heel bijzonder dat het ondanks je volle agenda toch altijd mogelijk was om op korte termijn

(‘loop zo maar even langs’) een overleg te regelen.

Paulien, naast dat ik veel respect heb voor jou als begeleider van dit traject, bewonder ik ook je

harde werk bij TNO. Hierdoor moest je je vaak snel inlezen in mijn stukken, en toch ontbrak het

nooit aan waardevolle feedback. Wat mij betreft zelfs onmisbaar voor het vasthouden van de

grote lijn en ook om het project te kunnen zien in de context van ontwikkelingen in de praktijk.

Graag wil ik ook de leden van de leescommissie bedanken voor hun aandacht en tijd die zij aan

het beoordelen van mijn proefschrift hebben besteed: dr. L.A.M. Elders, prof. A. Holtermann,

PhD, prof. dr. W. van Mechelen, dr. K.M. Oude Hengel, dr. S.J.W. Robroek, en prof. dr. J.K. Sluiter.

Bouw

Deelnemers aan VIP in de bouw project. Bedankt, zonder jullie deelname was dit project er niet

geweest. Dankzij jullie unieke en soms ook heel persoonlijke verhalen, bleef het project altijd met

twee benen in de praktijk staan.

Robbert en Teun, wat fijn dat jullie altijd ruimte in de agenda’s konden maken voor overleg en dat

jullie zo direct betrokken zijn gebleven tijdens het hele proces. Pim, Hans, en vele anderen, dank

voor het wegwijs maken in de bouw.

Alle mensen bij Ballast Nedam die bereid waren om tijd en energie in het project te steken, en

dat waren er heel wat, bedankt!

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184 | Dankwoord

Arbodiensten

Daarnaast ben ik veel dank verschuldigd aan alle deelnemende arbodiensten en mensen bij

Arbouw, Arbo Unie, ArboDuo/ArboNed en Bouw & Gezond die tijd hebben geïnvesteerd in het

project. Jos, Marco en Klaas, dank voor jullie inzet en professionele aanpak om het project op te

kunnen starten. Extra veel dank gaat uit naar Carla. Hoe druk je het ook had, ik kon altijd bij je

aankloppen voor planningen en speurwerk.

Ondersteuning

Anneke, onze Sherlock van het project. Je bleef altijd volhouden en daarmee heb je er zeker toe

bijgedragen dat zoveel deelnemers ook bereid waren om tot het einde toe met alle metingen

mee te doen.

Irene je hebt me als stagiair veel werk uit handen genomen en ik wil je bedanken voor de gezellige

tripjes naar de bouw. Ook alle anderen die zich hebben ingezet voor de metingen, dank.

Dank aan Rogier, Sandy en alle coaches van HC health die zich hebben ingezet tijdens het project!

De positieve feedback van de deelnemers zegt veel. Edwin, bedankt voor het kritisch bekijken van

het protocol en het begeleiden van de coaches.

Alle medewerkers van Arboriginals en Meester Ontwerpers, en in het bijzonder Jos, Marijke en

Linda, dank voor jullie creatieve input.

Sonja, Brahim, Trees en Inge, ook op de afdeling was er altijd iemand die klaarstond, voor eigenlijk

bijna alles!

Medeauteurs

Graag bedank ik ook mijn medeauteurs voor hun bijdragen aan de artikelen in dit proefschrift.

Karin, wat jammer dat jij niet bij het hele proces betrokken bent gebleven. Bedankt voor je

inspanningen bij het opstarten van het project en waardevolle bijdrage. Ik ben blij voor je dat je

zo’n fijne nieuwe uitdaging hebt gevonden.

Karen en Lando, dank dat ik gebruik heb mogen maken van jullie NEA expertise. Jullie hulp en

geduld heeft geleid tot een mooie publicatie.

Hanneke, Judith, Marieke en Maurits, ik ben dankbaar dat jullie je expertise op het gebied van

economische evaluaties op dit project hebben toegepast.

Collega’s

VIP collega’s Jantien, Hanneke, Jennifer, Arjella, Cecile, Ernst, Chantal en de rest van de VIP-

familie. Dank voor de getoonde interesse tijdens en ook nog nadat het project was afgerond. Alle

leden van de begeleidingscommissie, dank voor de input tijdens de bijeenkomsten.

Maaike, Frederieke en Han, dank dat ik ook bij jullie de ruimte kreeg om naast leuke projecten

het proefschrift nog af te ronden. Maaike wat bewonder ik je inzet voor zowel je werk als voor

de mensen in je omgeving, ik heb veel van je geleerd.


Dankwoord | 185

D

Hier mag ook, zoals inmiddels in heel wat dankwoorden, de G/H-0 gang niet ontbreken. De “oude

garde”, Karen B, Jorien, Lisanne, Iris, Nicolette, Marije, Marieke, Alwin, David, Maurice, wat fijn

dat jullie deuren altijd openstonden en er altijd tijd was voor dringende vragen en gezelligheid.

Esther, Myrthe, Susanne, Roos, Astrid, Linda K, Lieke, Joppe, Martine, Joeri, Ruben, Magdalena

en ik weet zeker dat ik ook hier nog mensen vergeet, maar jullie horen hier ook! Caro, fijn dat

ik ook nog even kort jouw kamergenootje mocht zijn. Babette, ik hoop dat je een fijne tijd hebt

in Stellenbosch, ik ben supertrots op je! Pieter, mijn mede-organisator van het juniorenoverleg,

veel succes in Australië! Femke en Anouk, mijn Gent-maatjes. Een gezelliger congres had ik me

niet kunnen wensen.

Sport en wetenschap gaan goed samen. SLHamsterdam collega’s en EMGO runners, Judith,

Joske, Kasper, Fenneke, Suzanne, Saskia en Saskia wat fijn dat ik een tijdje bij jullie kon aanhaken.

Ik ben benieuwd of onze eerste triathlon naar meer gaat smaken. En natuurlijk bedankt voor het

advies ‘what to wear’!

Een speciaal plekje hier in dit dankwoord voor mijn roomies. Linda en Jantien, wat een geluk dat

ik bij jullie op de kamer mocht zitten. Naast het delen van onze beperkte vierkante meters, onze

(werkgerelateerde) gesprekken, deelden we ook ervaringen rond het (prille) moederschap. H-032

was door jullie een beetje thuis. En dat bezoekje aan Artis komt vast nog wel een keer. Linda wat

fijn dat jij ook op de dag van de promotie naast mij wil staan.

Vriendschap

Lieve Mirka, wij delen sinds onze studie niet alleen een heleboel dezelfde interesses maar ook een

speciale vriendschap. Ik ben zo trots op wat jij allemaal doet, wat fijn dat jij tijdens de verdediging

naast mij wil staan.

Ragna en Eva mijn lieve meiden, wat hebben we nog een hoop verjaardags-etentjes tegoed. De

tijd konden we vaak niet vinden, als de plannen maar blijven. Dank voor alle koffie, het luisteren

en alle goede raad.

Annemieke, onze vriendschap gaat al heel ver terug en we delen al heel wat lief en leed. Jij bent

er altijd voor een gezonde dosis werkelijkheid.

Nynke en Ebelien, wij kwamen elkaar tegen op een voor ons allemaal bijzonder moment. Wat

gezellig dat we contact blijven houden! Texel was een goed startpunt voor onze reizen om de

wereld ;-)

Lieve El, ik ben zo blij voor je!

Lieve “MTB” vriendjes en vriendinnetjes. Jullie zijn zoveel meer dan dat. Het begon op het Spinoza

en de groep breidt nog steeds uit. De vaste uitjes naar de Ardennen waren altijd iets om naar toe

te leven, dat moeten we nog heel lang volhouden! Fijn dat een collega de in mijn agenda nogal

cryptische omschrijving GNO hielp ontcijferen, ik had de eerste nog bijna gemist.

Lieve buurtjes, dank voor jullie interesse en gezellige afleiding tijdens de laatste loodjes.

R1R2R3R4R5R6R7R8R9


186 | Dankwoord

Familie

Lieve schoonfamilie, met jullie komst uit Italië werd het hier een Dolce Vita. Fijn dat jullie deur/

pizzaoven altijd openstaat. Greet en Pieter, bedankt voor jullie interesse in hoe het met mij en

alle studies gaat.

Mijn meedenkers, meelezers en meelevers, lieve pappa en mamma, Rob en Christien, wat fijn

dat jullie altijd achter me staan (‘lekker uit de wind’). Met de (thuis)basis die jullie me hebben

gegeven, kan ik de hele wereld aan.

Lieve Viggo en Isabel. Mijn kleine grote wondertjes. Bedankt voor al jullie onvoorwaardelijke

liefde, lachjes, grapjes, driftbuien en meestal volslagen maling aan wat mamma verder uitspookt

dan mamma zijn. Het leven is zo mooi met jullie!

Chris, er is geen zonder jou.

Bo

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Laura Viester

Laura Viester W

orksite h

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Uitnodigingvoor het bijwonen van de openbare verdediging van

mijn proefschrift



op dinsdag 24 november 2015 om 13.45 uur in de aula van

de Vrije Universiteit aan de Boelelaan 1105

te Amsterdam

Na afloop bent u van harte welkom op de receptie

Laura ViesterOhmstraat 4-II

1098 SR Amsterdam06-24472241

[email protected]

ParanimfenLinda Eijckelhof

[email protected]

Mirka [email protected]

Proefschrift Viester

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Transcript of Proefschrift Viester