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Bo
dy@
Wo
rk
Worksite health promotion in
the construction industry
Laura Viester
Laura Viester W
orksite h
ealth p
rom
otio
n in
the co
nstru
ction
ind
ustry
Uitnodigingvoor het bijwonen van de openbare verdediging van
mijn proefschrift
Worksite health promotion in
the construction industry
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
ParanimfenLinda Eijckelhof
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
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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.
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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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14. Seitsamo J, Ilmarinen J: Life-style, aging and work ability among active Finnish workers in 1981-1992. Scand J Work Environ Health 1997, 23 Suppl 1: 20-26.
15. Arndt V, Rothenbacher D, Daniel U, Zschenderlein B, Schuberth S, Brenner H: Construction work and risk of occupational disability: a ten year follow up of 14,474 male workers. Occup Environ Med 2005, 62: 559-566.
16. Claessen H, Arndt V, Drath C, Brenner H: Overweight, obesity and risk of work disability: a cohort study of construction workers in Germany. Occup Environ Med 2009, 66: 402-409.
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.
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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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16 | Chapter 1
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.
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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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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
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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.
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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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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.
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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].
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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
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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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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.
33. Hart DJ, Spector TD: The relationship of obesity, fat distribution and osteoarthritis in women in the general population: the Chingford Study. J Rheumatol 1993, 20:331–335.
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.
38. Jensen JN, Holtermann A, Clausen T, Mortensen OS, Carneiro IG, Andersen LL: The greatest risk for low-back pain among newly educated female health care workers; body weight or physical work load? BMC Musculoskelet Disord 2012, 13:87.
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.
40. Slemenda C, Brandt KD, Heilman DK, Mazzuca S, Braunstein EM, Katz BP, et al: Quadriceps weakness and osteoarthritis of the knee. Ann Intern Med 1997, 127:97–104.
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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42. Hills AP, Parker AW: Gait characteristics of obese children. Arch Phys Med Rehabil 1991, 72:403–407.
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.
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Study design | 37
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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.
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Study design | 39
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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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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
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Study design | 41
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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.
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Study design | 43
3
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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44 | Chapter 3
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.
Wo
rkre
late
do
utc
om
es
Sic
kle
ave
Pro
duct
ivity
Vita
lity
Wor
kab
ility
Wor
ksa
tisfa
ctio
n
Hea
lth
MS
D
Hea
lth
rel
ated
fact
ors
Bod
y co
mpo
sitio
n(w
eig
ht,
BM
I, W
C)
Phy
sica
lfitn
ess
Phy
siol
ogic
alm
easu
res
(BP
, Cho
l)
Key
det
erm
inan
ts
Kno
wle
dge
Ski
llsA
war
enes
sH
ealth
bel
iefs
Ris
k pe
rcep
tion
Out
com
eex
pect
atio
ns
En
erg
y re
late
db
ehav
iou
r
Phy
sica
lact
ivity
Die
tary
beha
viou
rS
ede
ntar
yb
ehav
iour
Sel
f-ef
ficac
yIn
tent
ion
stag
e
heal
thpr
oble
min
terv
entio
n
Soc
iali
nflu
ence
Att
itude
habi
tba
rrie
rs
Wo
rkre
late
do
utc
om
es
Sic
kle
ave
Pro
duct
ivity
Vita
lity
Wor
kab
ility
Wor
ksa
tisfa
ctio
n
Hea
lth
MS
D
Hea
lth
rel
ated
fact
ors
Bod
y co
mpo
sitio
n(w
eig
ht,
BM
I, W
C)
Phy
sica
lfitn
ess
Phy
siol
ogic
alm
easu
res
(BP
, Cho
l)
Key
det
erm
inan
ts
Kno
wle
dge
Ski
llsA
war
enes
sH
ealth
bel
iefs
Ris
k pe
rcep
tion
Out
com
eex
pect
atio
ns
En
erg
y re
late
db
ehav
iou
r
Phy
sica
lact
ivity
Die
tary
beha
viou
rS
ede
ntar
yb
ehav
iour
Sel
f-ef
ficac
yIn
tent
ion
stag
e
heal
thpr
oble
min
terv
entio
n
Soc
iali
nflu
ence
Att
itude
habi
tba
rrie
rs
Fig
ure
2 C
once
ptua
l mod
el o
f th
e V
IP in
Con
stru
ctio
n in
terv
entio
n.
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Study design | 45
3
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.
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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
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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.
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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.
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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)
Follow-up 2: (15 min; telephone)
Follow-up 3: (15 min; telephone)
BIntake (60 min face-to-face)
Follow-up 1: (30 min; telephone)
Follow-up 2: (15 min; telephone)
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.
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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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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
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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.
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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
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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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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
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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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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.
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62. Kemper HGC, Ooijendijk WTM, Stiggelbout M: Consensus over de Nederlandse Norm voor Gezond Bewegen. Tijdschr Soc Gezondheidsz 2000, 78:180–183.
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64. 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.
65. van Assema P, Brug J, Ronda G, Steenhuis I, Oenema A: A short dutch questionnaire to measure fruit and vegetable intake: relative validity among adults and adolescents. Nutr Health 2002, 16:85–106.
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80. van Buuren S: Multiple imputation of discrete and continuous data by fully conditional specification. Stat Methods Med Res 2007, 16:219–242.
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82. Stinnett AA, Mullahy J: Net health benefits: a new framework for the analysis of uncertainty in cost-effectiveness analysis. Med Decis Making 1998, 18:S68–S80.
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83. Verweij LM, Proper KI, Weel ANH, Hulshof CTJ, van Mechelen W: Design of the Balance@Work project: systematic development, evaluation and implementation of an occupational health guideline aimed at the prevention of weight gain among employees. BMC Public Health 2009, 9:461.
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85. Strijk JE, Proper KI, van der Beek AJ, van Mechelen W: The Vital@Work Study: The systematic development of a lifestyle intervention to improve older workers’ vitality and the design of a randomised controlled trial evaluating this intervention. BMC Public Health 2009, 9:408.
86. Harden A, Peersman G, Oliver S, Mauthner M, Oakley A: A systematic review of the effectiveness of health promotion interventions in the workplace. Occup Med (Lond) 1999, 49:540–548.
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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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.
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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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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.
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Process evaluation | 69
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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)
Follow-up 3(15 min; telephone)
Contemplation/Preparation stage
B Intake (60 min face-to-face)
Follow-up 1 (30 min; telephone)
Follow-up 2(15 min; telephone)
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
le 2
. Pro
cess
eva
luat
ion
co
mp
on
ents
an
d le
vels
, th
eir
defi
nit
ion
s, a
nd
dat
a co
llect
ion
met
ho
ds.
Com
pone
ntLe
vel
Defi
nitio
nD
ata
colle
ctio
nRe
ach
indi
vidu
al a
nd
orga
nisa
tion
num
ber
of w
orke
rs p
artic
ipat
ing
in t
he s
tudy
, par
ticip
ants
’ re
pres
enta
tiven
ess,
and
sou
rces
and
pro
cedu
res
used
to
recr
uit
empl
oyee
s,
part
icip
ant
base
line
data
and
co
mpa
ny d
ata
Effe
ctiv
enes
sIn
divi
dual
shor
t te
rm (6
mon
ths)
inte
rven
tion
effe
cts
on (d
eter
min
ants
of)
be
havi
our
chan
gepa
rtic
ipan
t ba
selin
e, a
nd 6
m
onth
s fo
llow
-up
ques
tionn
aire
Ado
ptio
nO
rgan
isat
ion
dist
ribut
ion
of w
orke
rs p
artic
ipat
ing
in o
rgan
isat
iona
l uni
ts, a
nd
cont
ext
of t
he p
rogr
amm
edi
rect
obs
erva
tion
Impl
emen
tatio
nD
ose
deliv
ered
Prog
ram
me
num
ber
of w
orke
rs t
hat
rece
ived
coa
chin
g ap
poin
tmen
ts;
num
ber
of p
lann
ed c
onta
cts
and
rece
ived
mat
eria
lspa
rtic
ipan
t fo
llow
-up
ques
tionn
aire
and
coa
chin
g re
gist
ratio
ns
Fide
lity
Prog
ram
me
exte
nt t
o w
hich
the
ste
ps o
f th
e co
achi
ng p
rogr
amm
e w
ere
deliv
ered
as
inte
nded
(tim
ing
and
cont
ent
of t
he s
essi
ons)
coac
hing
reg
istr
atio
ns a
nd
inte
rvie
ws
Satis
fact
ion
Indi
vidu
alsa
tisfa
ctio
n of
par
ticip
ants
, who
rec
eive
d th
e co
achi
ng, t
owar
ds
the
prog
ram
me,
the
coa
chin
g’s
com
pete
nces
, num
ber
of
coac
hing
con
tact
s, a
nd t
he p
rogr
amm
e m
ater
ials
part
icip
ant
follo
w-u
p qu
estio
nnai
re
Dos
e re
ceiv
edIn
divi
dual
expo
sure
to
the
inte
rven
tion:
num
ber
of w
orke
rs w
ho a
tten
ded
the
coac
hing
con
tact
s, a
nd c
ompl
eted
the
pro
gram
me,
use
d m
ater
ials
coac
hing
reg
istr
atio
ns
and
part
icip
ant
follo
w-u
p qu
estio
nnai
re
Part
icip
atio
n ra
teIn
divi
dual
prop
ortio
n of
wor
kers
allo
cate
d to
the
inte
rven
tion
grou
p th
at
part
icip
ates
in t
he in
terv
entio
n co
mpo
nent
spr
ogra
mm
e an
d co
achi
ng
regi
stra
tions
Mai
nten
ance
Org
anis
atio
nor
gani
satio
nal i
nten
tion
for
long
ter
m im
plem
enta
tion
inte
rvie
ws
Prog
ram
me
reco
mm
enda
tions
fro
m in
terv
entio
n pr
ovid
ers
inte
rvie
ws
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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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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
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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.
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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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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.
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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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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
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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.
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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.
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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.
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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.
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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
Laura Viester, Evert A. L. M. Verhagen, Paulien M. Bongers, Allard J. van der Beek
(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.
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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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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
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Effect evaluation on primary outcomes | 89
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].
Energy balance-related behaviour
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
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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.
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Effect evaluation on primary outcomes | 91
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).
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Effect evaluation on primary outcomes | 93
5
Tab
le 2
. D
ata
on
pri
mar
y o
utc
om
e m
easu
res
for
com
ple
te c
ases
at
bas
elin
e (m
ean
, SD
) at
6 a
nd
12
mo
nth
s fo
llow
-up
in
th
e in
terv
enti
on
an
d
con
tro
l gro
up
.
Out
com
e m
easu
reM
odel
IM
odel
II
Inte
rven
tion
Mea
n (S
D)
Con
trol
Mea
n (S
D)
B(95
% C
I)p-
valu
eB(
95%
CI)
p-va
lue
Wei
ght,
kg
N12
712
9Ba
selin
e88
.3 (1
2.3)
89.1
(15.
1)6
mon
ths
88.7
(12.
1)90
.3 (1
5.1)
-0.9
2 (-
1.69
; -0
.14)
0.02
1-1
.06
(-1.
87 ;
-0.2
6)0.
010
12 m
onth
s88
.7 (1
2.4)
90.2
(15.
2)-0
.81
(-1.
80 ;
0.18
)0.
110
-1.0
0 (-
2.01
; 0.
01)
0.05
3
Body
mas
s in
dex,
kg/
m2
N12
712
9Ba
selin
e27
.3 (3
.5)
27.5
(4.0
)6
mon
ths
27.5
(3.3
)27
.9 (4
.0)
-0.2
9 (-
0.52
; -0
.05)
0.01
7-0
.32
(-0.
57 ;
-0.0
8)0.
010
12 m
onth
s27
.5 (3
.5)
27.9
(4.0
)-0
.25
(-0.
55 ;
0.05
)0.
107
-0.3
0 (-
0.61
; 0.
01)
0.05
7
Wai
st C
ircum
fere
nce,
cm
N11
911
4Ba
selin
e99
.2 (1
0.0)
100.
3 (1
2.3)
6 m
onth
s97
.6 (9
.7)
100.
0 (1
1.8)
-1.3
8 (-
2.58
; -0
.18)
0.02
4-1
.38
(-2.
63 ;
-0.1
2)0.
032
12 m
onth
s97
.9 (9
.7)
99.9
(11.
8)-0
.95
(-2.
23 ;
0.32
)0.
142
-0.9
1 (-
2.25
; 0.
44)
0.18
7
B-va
lues
refl
ect
abso
lute
diff
eren
ces
betw
een
grou
ps c
orre
cted
for
bas
elin
e va
lues
of
the
mea
sure
s.
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
(cat
egor
ical
), m
arita
l sta
tus
(dic
hoto
mou
s), a
nd s
mok
ing
(dito
chom
ous)
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94 | Chapter 5
Tab
le 3
. Bas
elin
e d
ata
and
est
imat
ed e
ffec
ts o
f th
e in
terv
enti
on
on
blo
od
pre
ssu
re (
BP)
an
d c
ho
lest
ero
l.
Out
com
e m
easu
reM
odel
IM
odel
II
Inte
rven
tion
Mea
n (S
D)
Con
trol
Mea
n (S
D)
B(95
% C
I)p-
valu
eB(
95%
CI)
p-va
lue
Syst
olic
BP,
mm
Hg
N12
812
9Ba
selin
e13
1.0
(15.
8)13
1.5
(14.
4)6
mon
ths
134.
5 (1
4.8)
135.
3 (1
4.6)
-0.5
0 (-
3.90
; 2.
90)
0.77
0-1
.12
(-4.
63; 2
.40)
0.53
212
mon
ths
133.
9 (1
8.4)
133.
7 (1
3.3)
0.50
(-3.
07; 4
.07)
0.78
30.
16 (-
3.49
; 3.8
1)0.
932
Dia
stol
ic B
P, m
mH
gN
128
129
Base
line
82.5
(10.
3)83
.6 (9
.1)
6 m
onth
s82
.1 (1
0.7)
82.7
(9.6
)-0
.05
(-2.
34 ;
2.24
)0.
967
0.25
(-2.
10; 2
.61)
0.83
212
mon
ths
82.3
(12.
1)80
.9 (9
.5)
2.02
(-0.
41; 4
.45)
0.10
22.
22 (-
0.28
; 4.7
1)0.
081
Bloo
d ch
oles
tero
l (TC
), m
mol
/lN
116
115
Base
line
5.3
(1.0
)5.
3 (1
.0)
6 m
onth
s5.
0 (1
.0)
4.9
(0.8
)0.
03 (-
0.15
; 0.
21)
0.72
50.
05 (-
0.13
; 0.2
3)0.
583
12 m
onth
s4.
8 (0
.9)
4.7
(0.8
)0.
07 (-
0.10
; 0.2
4)0.
404
0.07
(-0.
11; 0
.25)
0.42
4
B-va
lues
refl
ect
abso
lute
diff
eren
ces
betw
een
grou
ps c
orre
cted
for
bas
elin
e va
lues
of
the
mea
sure
s.M
odel
I =
cru
de m
odel
, adj
uste
d fo
r ba
selin
e va
lues
M
odel
II =
adj
uste
d m
odel
for
bas
elin
e va
lues
, age
(con
tinuo
us),
educ
atio
n(ca
tego
rical
), m
arita
l sta
tus(
dich
otom
ous)
, and
sm
okin
g (d
icho
tom
ous)
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Effect evaluation on primary outcomes | 95
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)
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Effect evaluation on primary outcomes | 97
5
N12
412
6Ba
selin
e10
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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
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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].
Energy balance-related behaviour
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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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.
Strengths and limitations
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].
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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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17. Groeneveld IF, Proper KI, van der Beek AJ et al.: 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.
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.
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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.
24. Ainsworth BE, Haskell WL, Whitt MC et al.: Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc 2000, 32: S498-S504.
25. Haskell WL, Lee IM, Pate RR 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.
26. Kemper HGC OWSM: Consensus over de Nederlandse Norm voor Gezond Bewegen. Tijdschr Soc Gezondheidsz 2000, 78: 180-183.
27. Groeneveld IF, Proper KI, van der Beek AJ et al.: 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.
28. Verweij LM, Coffeng J, van MW, Proper KI: Meta-analyses of workplace physical activity and dietary behaviour interventions on weight outcomes. Obes Rev 2010.
29. Wing RR, Hill JO: Successful weight loss maintenance. Annu Rev Nutr 2001, 21: 323-341.
30. Pi-Sunyer X, Blackburn G, Brancati FL et al.: Reduction in weight and cardiovascular disease risk factors in individuals with type 2 diabetes: one-year results of the look AHEAD trial. Diabetes Care 2007, 30: 1374-1383.
31. Hamman RF, Wing RR, Edelstein SL et al.: Effect of weight loss with lifestyle intervention on risk of diabetes. Diabetes Care 2006, 29: 2102-2107.
32. Wing RR: Behavioral treatment of obesity. Its application to type II diabetes. Diabetes Care 1993, 16: 193-199.
33. Lemmens VEPP, Oenema A, Klepp KI et al.: A systematic review of the evidence regarding efficacy of obesity prevention interventions among adults. Obes Rev 2008, 9: 446-455.
34. Ross R, Dagnone D, Jones PJ et al.: Reduction in obesity and related comorbid conditions after diet-induced weight loss or exercise-induced weight loss in men. A randomized, controlled trial. Ann Intern Med 2000, 133: 92-103.
35. Visscher TLS, Seidell JC: Time trends (1993-1997) and seasonal variation in body mass index and waist circumference in the Netherlands. Int J Obes Relat Metab Disord 2004, 28: 1309-1316.
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.
42. Hardeman W, Griffin S, Johnston M et al.: Interventions to prevent weight gain: a systematic review of psychological models and behaviour change methods. Int J Obes Relat Metab Disord 2000, 24: 131-143.
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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
Laura Viester, Evert A. L. M. Verhagen, Paulien M. Bongers, Allard J. van der Beek
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.
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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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108 | Chapter 6
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.
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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)
Follow-up 2(15 min; telephone)
Follow-up 3(15 min; telephone)
Contemplation/Preparation stage
Intake (60 min face-to-face)
Follow-up 1 (30 min; telephone)
Follow-up 2(15 min; telephone)
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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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.
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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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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
Musculoskeletal symptoms
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.
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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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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.
Musculoskeletal symptoms
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
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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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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 and limitations
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
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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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35. Bartholomew, L. K., Parcel, G. S., Kok, G., Gottlieb, N. H., (2006). Planning health promotion programs: intervention mapping. Jossey-Bass, San Francisco, CA.
36. Hildebrandt, V. H., Bongers, P. M., van Dijk, F. J., Kemper, H. C., Dul, J., (2001). Dutch Musculoskeletal Questionnaire: description and basic qualities. Ergonomics 44, 1038-1055.
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39. Brazier, J. E., Harper, R., Jones, N. M., O’Cathain, A., Thomas, K. J., Usherwood, T., Westlake, L., (1992). Validating the SF-36 health survey questionnaire: new outcome measure for primary care. BMJ 305, 160-164.
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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.
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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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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.
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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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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).
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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)
Contemplation/Preparation stage
The participant wants to change his risk behavior(s), but does not know how
B Intake
(60 min face-to-face)
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
(30 min face-to-face)
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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“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.
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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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(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
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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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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).
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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)
Lost to follow-up after baseline
(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)
Lost to follow-up after baseline
(n=32)
Lost to follow-up after baseline
(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
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Economic evaluation | 133
7
Tab
le 2
. Bas
elin
e ch
arac
teri
stic
s o
f th
e st
ud
y p
op
ula
tio
n
Inte
rven
tio
n g
rou
pC
on
tro
l gro
up
Base
line
char
acte
ristic
sA
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
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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).
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Economic evaluation | 135
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)).
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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
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Economic evaluation | 137
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).
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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
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Economic evaluation | 139
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
R1R2R3R4R5R6R7R8R9
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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
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Economic evaluation | 141
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
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Economic evaluation | 143
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.
Strengths and limitations
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
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Economic evaluation | 145
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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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
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150 | Chapter 7
Ap
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Economic evaluation | 151
7
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Chapter 8General discussion
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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
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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.
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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.
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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].
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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
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General discussion | 163
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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.
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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
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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.
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Summary
Samenvatting
Dankwoord
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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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176 | Summary
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
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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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178 | Samenvatting
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Samenvatting | 179
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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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180 | Samenvatting
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.
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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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182 | Dankwoord
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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.
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Dankwoord | 185
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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.
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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
dy@
Wo
rk
Worksite health promotion in
the construction industry
Laura Viester
Laura Viester W
orksite h
ealth p
rom
otio
n in
the co
nstru
ction
ind
ustry
Uitnodigingvoor het bijwonen van de openbare verdediging van
mijn proefschrift
Worksite health promotion in
the construction industry
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
ParanimfenLinda Eijckelhof
Mirka [email protected]