Hidde P. van der Ploeg

Occupational sitting and health risks: a systematic review

CONTEXT Emerging evidence suggests that sedentary behavior (i.e., time spent sitting) may be negatively associated with health. The aim of this study was to systematically review the evidence on associations between occupational sitting and health risks. EVIDENCE ACQUISITION Studies were identified in March-April 2009 by literature searches in PubMed, PsycINFO, CENTRAL, CINAHL, EMBASE, and PEDro, with subsequent related-article searches in PubMed and citation searches in Web of Science. Identified studies were categorized by health outcome. Two independent reviewers assessed methodologic quality using a 15-item quality rating list (score range 0-15 points, higher score indicating better quality). Data on study design, study population, measures of occupational sitting, health risks, analyses, and results were extracted. EVIDENCE SYNTHESIS 43 papers met the inclusion criteria (21% cross-sectional, 14% case-control, 65% prospective); they examined the associations between occupational sitting and BMI (n=12); cancer (n=17); cardiovascular disease (CVD, n=8); diabetes mellitus (DM, n=4); and mortality (n=6). The median study-quality score was 12 points. Half the cross-sectional studies showed a positive association between occupational sitting and BMI, but prospective studies failed to confirm a causal relationship. There was some case-control evidence for a positive association between occupational sitting and cancer; however, this was generally not supported by prospective studies. The majority of prospective studies found that occupational sitting was associated with a higher risk of DM and mortality. CONCLUSIONS Limited evidence was found to support a positive relationship between occupational sitting and health risks. The heterogeneity of study designs, measures, and findings makes it difficult to draw definitive conclusions at this time.

Daily Sitting Time and All-Cause Mortality: A Meta-Analysis

Objective To quantify the association between daily total sitting and all-cause mortality risk and to examine dose-response relationships with and without adjustment for moderate-to-vigorous physical activity. Methods Studies published from 1989 to January 2013 were identified via searches of multiple databases, reference lists of systematic reviews on sitting and health, and from authors’ personal literature databases. We included prospective cohort studies that had total daily sitting time as a quantitative exposure variable, all-cause mortality as the outcome and reported estimates of relative risk, or odds ratios or hazard ratios with 95% confidence intervals. Two authors independently extracted the data and summary estimates of associations were computed using random effects models. Results Six studies were included, involving data from 595,086 adults and 29,162 deaths over 3,565,569 person-years of follow-up. Study participants were mainly female, middle-aged or older adults from high-income countries; mean study quality score was 12/15 points. Associations between daily total sitting time and all-cause mortality were not linear. With physical activity adjustment, the spline model of best fit had dose-response HRs of 1.00 (95% CI: 0.98-1.03), 1.02 (95% CI: 0.99-1.05) and 1.05 (95% CI: 1.02-1.08) for every 1-hour increase in sitting time in intervals between 0-3, >3-7 and >7 h/day total sitting, respectively. This model estimated a 34% higher mortality risk for adults sitting 10 h/day, after taking physical activity into account. The overall weighted population attributable fraction for all-cause mortality for total daily sitting time was 5.9%, after adjusting for physical activity. Conclusions Higher amounts of daily total sitting time are associated with greater risk of all-cause mortality and moderate-to-vigorous physical activity appears to attenuate the hazardous association. These findings provide a starting point for identifying a threshold on which to base clinical and public health recommendations for overall sitting time, in addition to physical activity guidelines.

Are workplace interventions to reduce sitting effective? A systematic review

OBJECTIVE To systematically review the effectiveness of workplace interventions for reducing sitting. METHODS Studies published up to April 2009 were identified by literature searches in multiple databases. Studies were included if they were interventions to increase energy expenditure (increase physical activity or decrease sitting); were conducted in a workplace setting; and specifically measured sitting as a primary or secondary outcome. Two independent reviewers assessed methodological quality of the included studies, and data on study design, sample, measures of sitting, intervention and results were extracted. RESULTS Six studies met the inclusion criteria (five randomised trials and one pre-post study). The primary aim of all six was to increase physical activity; all had reducing sitting as a secondary aim. All used self-report measures of sitting; one specifically assessed occupational sitting time; the others used measures of general sitting. No studies showed that sitting decreased significantly in the intervention group, compared with a control or comparison group. CONCLUSION Currently, there is a dearth of evidence on the effectiveness of workplace interventions for reducing sitting. In light of the growing body of evidence that prolonged sitting is negatively associated with health, this highlights a gap in the scientific literature that needs to be addressed.

Sociodemographic Correlates of the Increasing Trend in Prevalence of Gestational Diabetes Mellitus in a Large Population of Women Between 1995 and 2005

OBJECTIVE—Gestational diabetes mellitus (GDM) is an increasingly prevalent risk factor for the development of type 2 diabetes in the mother and is responsible for morbidity in the child. To better identify women at risk of developing GDM we examined sociodemographic correlates and changes in the prevalence of GDM among all births between 1995 and 2005 in Australias largest state. RESEARCH DESIGN AND METHODS—A computerized database of all births (n = 956,738) between 1995 and 2005 in New South Wales, Australia, was used in a multivariate logistic regression that examined the association between sociodemographic characteristics and the occurrence of GDM. RESULTS—Between 1995 and 2005, the prevalence of GDM increased by 45%, from 3.0 to 4.4%. Women born in South Asia had the highest adjusted odds ratio (OR) of any region (4.33 [95% CI 4.12–4.55]) relative to women born in Australia. Women living in the three lowest socioeconomic quartiles had higher adjusted ORs for GDM relative to women in the highest quartile (1.54 [1.50–1.59], 1.74 [1.69–1.8], and 1.65 [1.60–1.70] for decreasing socioeconomic status quartiles). Increasing age was strongly associated with GDM, with women aged >40 years having an adjusted OR of 6.13 (95% CI 5.79–6.49) relative to women in their early 20s. Parity was associated with a small reduced risk. There was no association between smoking and GDM. CONCLUSIONS—Maternal age, socioeconomic position, and ethnicity are important correlates of GDM. Future culturally specific interventions should target prevention of GDM in these high-risk groups.

Cross-sectional associations between occupational and leisure-time sitting, physical activity and obesity in working adults.

AIM To examine associations between occupational and leisure-time sitting, physical activity and obesity in working adults. METHODS We analyzed data from workers from the 2007-08 Australian National Health Survey (n=10,785). Participants reported their activity at work (mostly sitting, standing, walking, or heavy labor), transport-related walking, leisure-time sitting and physical activity. Body mass index was objectively measured. Adjusted Cox proportional hazard regression models examined associations between occupational activity category, leisure-time sitting, physical activity and obesity risk. RESULTS Substantial proportions of men (42%) and women (47%) mostly sit at work. Workers with sitting jobs were significantly more likely to be sufficiently active during leisure-time than workers with mostly standing, walking or heavy labor jobs (RR=0.88, 0.80, 0.86 respectively). Workers with mostly sitting jobs had significantly higher overweight/obesity risk than workers with mostly standing jobs (RR=0.88, 95% CI: 0.82-0.95) independent of physical activity and leisure-time sitting. Workers with leisure-time sitting of less than four hours per day had significantly lower obesity risk than workers with four or more hours per day of leisure-time sitting (RR=0.77, 95%CI: 0.69-0.87) independent of physical activity and occupational activity. CONCLUSIONS Sitting time and physical activity are independently associated with obesity. Leisure-time sitting may have a stronger association with obesity risk than occupational sitting.

Physical activity for people with a disability: a conceptual model

The promotion of a physically active lifestyle has become an important issue in health policy in first-world countries. A physically active lifestyle is accompanied by several fitness and health benefits. Individuals with a disability can particularly benefit from an active lifestyle: not only does it reduce the risk for secondary health problems, but all levels of functioning can be influenced positively.The objective of this article is to propose a conceptual model that describes the relationships between physical activity behaviour, its determinants and functioning of people with a disability. The literature was systematically searched for articles considering physical activity and disability, and models relating both topics were looked for in particular. No models were found relating physical activity behaviour, its determinants and functioning in people with a disability. Consequently, a new model, the Physical Activity for people with a Disability (PAD) model, was constructed based on existing models of disability and models of determinants of physical activity behaviour. The starting point was the new WHO Model of Functioning and Disability, part of the International Classification of Functioning, Disability and Health (ICF), which describes the multidimensional aspects of functioning and disability. Physical activity behaviour and its determinants were integrated into the ICF model. The factors determining physical activity were based mainly on those used in the Attitude, Social influence and self-Efficacy (ASE) model. The proposed model can be used as a theoretical framework for future interventions and research on physical activity promotion in the population of people with a disability. The model currently forms the theoretical basis for a large physical activity promotion trial in ten Dutch rehabilitation centres.

Validity and repeatability of the EPIC physical activity questionnaire: a validation study using accelerometers as an objective measure

BackgroundA primary aim of the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort study is to examine the association between total physical activity levels (comprising occupational, household and recreational activity) and the incidence of cancer. We examined the validity and long-term repeatability of total physical activity measurements estimated from the past-year recall EPIC questionnaire, using accelerometers as an objective reference measure.MethodsParticipants included 100 men and 82 women aged 50–65 years. Criterion validity was assessed by comparing the physical activity estimates from the EPIC questionnaire with total activity estimated from the average of three separate 7-day accelerometer periods during the same (past-year) period. Long-term repeatability of the EPIC questionnaire was assessed by comparing the responses from the baseline and 10-month administrations. Past-year EPIC estimates were also compared with the Friedenreich Lifetime Total Physical Activity Questionnaire to examine whether recent activity reflected lifetime activity.ResultsAccelerometer total metabolic equivalent (MET)-hours/week were positively associated with a total physical activity index (Spearman rank correlation ρ = 0.29, 95% confidence interval (CI) 0.15, 0.42) and with non-occupational activity estimated in MET-hours/week (ρ = 0.21, 95% CI 0.07, 0.35). Stratified analyses suggested stronger correlations for non-occupational activity for participants who were male, had a lower BMI, were younger, or were not full-time workers, although the differences in correlations between groups were not statistically significant. The weighted kappa coefficient for repeatability of the total physical activity index was 0.62 (95% CI 0.53, 0.71). Spearman correlations for repeatability of components of activity were 0.65 (95% CI 0.55, 0.72) for total non-occupational, 0.58 (95% CI 0.48, 0.67) for recreational and 0.73 (95% CI 0.66, 0.79) for household activity. When past-year activity was compared to lifetime estimates of activity, there was fair agreement for non-occupational (ρ = 0.26) activity, which was greater for household activity (ρ = 0.46) than for recreational activity (ρ = 0.21).ConclusionOur findings suggest that the EPIC questionnaire has acceptable measurement characteristics for ranking participants according to their level of total physical activity. The questionnaire should be able to identify the presence or absence of reasonably strong aetiological associations when either recent or long-term activity is the responsible factor.

Development of Smartphone Applications for Nutrition and Physical Activity Behavior Change

Background Young adults (aged 18 to 35) are a population group at high risk for weight gain, yet we know little about how to intervene in this group. Easy access to treatment and support with self-monitoring of their behaviors may be important. Smartphones are gaining in popularity with this population group and software applications (“apps”) used on these mobile devices are a novel technology that can be used to deliver brief health behavior change interventions directly to individuals en masse, with potentially favorable cost-utility. However, existing apps for modifying nutrition or physical activity behaviors may not always reflect best practice guidelines for weight management. Objective This paper describes the process of developing four apps aimed at modifying key lifestyle behaviors associated with weight gain during young adulthood, including physical activity, and consumption of take-out foods (fast food), fruit and vegetables, and sugar-sweetened drinks. Methods The development process involved: (1) deciding on the behavior change strategies, relevant guidelines, graphic design, and potential data collection; (2) selecting the platform (Web-based versus native); (3) creating the design, which required decisions about the user interface, architecture of the relational database, and programming code; and (4) testing the prototype versions with the target audience (young adults aged 18 to 35). Results The four apps took 18 months to develop, involving the fields of marketing, nutrition and dietetics, physical activity, and information technology. Ten subjects provided qualitative feedback about using the apps. The slow running speed of the apps (due to a reliance on an active Internet connection) was the primary issue identified by this group, as well as the requirement to log in to the apps. Conclusions Smartphone apps may be an innovative medium for delivering individual health behavior change intervention en masse, but researchers must give consideration to the target population, available technologies, existing commercial apps, and the possibility that their use will be irregular and short-lived.

A systematic review of correlates of sedentary behaviour in adults aged 18–65 years: a socio-ecological approach

BackgroundRecent research shows that sedentary behaviour is associated with adverse cardio-metabolic consequences even among those considered sufficiently physically active. In order to successfully develop interventions to address this unhealthy behaviour, factors that influence sedentariness need to be identified and fully understood. The aim of this review is to identify individual, social, environmental, and policy-related determinants or correlates of sedentary behaviours among adults aged 18–65 years.MethodsPubMed, Embase, CINAHL, PsycINFO and Web of Science were searched for articles published between January 2000 and September 2015. The search strategy was based on four key elements and their synonyms: (a) sedentary behaviour (b) correlates (c) types of sedentary behaviours (d) types of correlates. Articles were included if information relating to sedentary behaviour in adults (18–65 years) was reported. Studies on samples selected by disease were excluded. The full protocol is available from PROSPERO (PROSPERO 2014:CRD42014009823).Results74 original studies were identified out of 4041: 71 observational, two qualitative and one experimental study. Sedentary behaviour was primarily measured as self-reported screen leisure time and total sitting time. In 15 studies, objectively measured total sedentary time was reported: accelerometry (n = 14) and heart rate (n = 1). Individual level factors such as age, physical activity levels, body mass index, socio-economic status and mood were all significantly correlated with sedentariness. A trend towards increased amounts of leisure screen time was identified in those married or cohabiting while having children resulted in less total sitting time. Several environmental correlates were identified including proximity of green space, neighbourhood walkability and safety and weather.ConclusionsResults provide further evidence relating to several already recognised individual level factors and preliminary evidence relating to social and environmental factors that should be further investigated. Most studies relied upon cross-sectional design limiting causal inference and the heterogeneity of the sedentary measures prevented direct comparison of findings. Future research necessitates longitudinal study designs, exploration of policy-related factors, further exploration of environmental factors, analysis of inter-relationships between identified factors and better classification of sedentary behaviour domains.

A tool for measuring workers' sitting time by domain: the Workforce Sitting Questionnaire

Background Sitting time is an emerging health risk, and many working adults spend large amounts of time sitting each day. It is important to have reliable and accurate measurement tools to assess sitting time in different contexts. Objective To validate the Workforce Sitting Questionnaire (WSQ), an adapted measure of total and domain-specific sitting time based on work and non-workdays for use in working adults. Methods A convenience sample (N=95, 63.2% women) was recruited from two workplaces and by word-of-mouth in Sydney, Australia. Participants completed the WSQ, which asked about sitting time (1) while travelling to and from places; (2) while at work; (3) while watching TV; (4) while using a computer at home; and (5) while doing other leisure activities on work and non-workdays on two occasions, 7 days apart. Participants also wore an accelerometer for the 7 days between test and retest. They recorded the times they wore the accelerometer, the days they worked and their work times in a logbook. Analyses determined test–retest reliability with intraclass correlation coefficients (ICCs) and assessed criterion validity against accelerometers using Spearmans r and Bland–Altman plots. Results Measuring total sitting time based on a workday, non-workday and on average had fair to excellent test–retest reliability (ICC=0.46–0.90) and had sufficient criterion validity against accelerometry in women (r=0.22–0.46) and men (r=0.18–0.29). Measuring domain-specific sitting at work on a workday was also reliable (ICC=0.63) and valid (r=0.45). Conclusions The WSQ has acceptable measurement properties for measuring sitting time at work on a workday and for assessing total sitting time based on work and non-workdays. This questionnaire would be suitable for use in research investigating the relationships between sitting time and health in working populations.