Physical Workload and Work Capacity across Occupational Groups

Brighenti-Zogg, Stefanie; Mundwiler, Jonas; Schüpbach, Ulla; Dieterle, Thomas; Wolfer, David P; Leüppi, Jörg D.; Malka, David

doi:10.1371/journal.pone.0154073

Cited by 40 publications

(39 citation statements)

References 30 publications

(45 reference statements)

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“…We are not aware of any other large-scale investigation examining a combination of several health risk indicators in different high-resolution occupational groups. Though, the physical activity patterns at work and in leisure time in the present study are partly similar to previous reports in both major occupational groups and in some sub-major groups (9,10,21). For example, white collar/professional occupations are consistently reported to have a higher amount of leisure time moderate-to-vigorous physical activity compare to blue collar workers (4,21), with less differences in leisure time sitting (22,23).…”

Section: Single Risk Indicators In Occupational Groupssupporting

confidence: 89%

“…As these are heterogeneous groups of occupations with a diversity of work situations that could have an effect on health outcomes. For instance, previous reports have indicated variations in overweight, smoking and occupational physical activity between a larger range of occupational groups (9,10,8). Other studies found differences in physical activity but con icting results of cardiorespiratory tness between occupational groups (9,11).…”

Section: Introductionmentioning

confidence: 97%

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Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72 855 workers

Väisänen

Kallings

Andersson

et al. 2020

Preprint

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ObjectivesIdentify and compare health risk indicators for common chronic diseases between different occupational groups. Methods A total of 72,855 participants (41% women) participating in an occupational health servicescreening in 2014–2019 were included. Occupation was defined by the Swedish Standard Classification of Occupation, and divided into nine major and additionally eight sub-major groups. These were analysed separately, as white- and blue-collar occupations and as low- and high-skilled occupations. Seven health risk indicators were self-reported: exercise, physical work situation, sitting at work and leisure, smoking, diet, and perceived health, whereas cardiorespiratory fitness, BMI and blood pressure were measured. These were further dichotomized (yes/no) and as clustering of risk indicators (≥3 vs. <3).ResultsThe greatest variation in OR across sub-major and major occupational groups were seen for daily smoking (OR=0.68 to OR=5.12), physically demanding work (OR=0.55 to OR=45.74) and high sitting at work (OR=0.04 to OR=1.86). For clustering of health risk indicators, blue-collar workers had significantly higher clustering of health risks (OR: 1.80; 95% CI 1.71-1.90) compared to white-collar workers (reference). Compared to high-skilled white-collar workers, low-skilled white-collar workers had similar OR (2.00; 1.88-2.13) as high-skilled blue-collar workers (1.98; 1.86-2.12), with low-skilled blue-collar workers having the highest clustered risk (2.32; 2.17-2.48).ConclusionThere were large differences in health risk indicators across occupational groups, mainly between high-skilled white-collar occupations and the other occupations, with important variations also between major and sub-major occupational groups. Future health interventions should target the occupational groups identified with the highest risk for effective disease prevention.

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Section: Single Risk Indicators In Occupational Groupssupporting

confidence: 89%

Section: Introductionmentioning

confidence: 97%

Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72 855 workers

Väisänen

Kallings

Andersson

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…One study found Swiss workers with manual jobs (e.g. craftsmen, machine operators and labourers) to be more active on workdays than non-workdays [37]. Another study reported adults with low educational level as less likely to be active during the weekend (i.e.…”

Section: Discussionmentioning

confidence: 99%

Day-to-Day Pattern of Work and Leisure Time Physical Behaviours: Are Low Socioeconomic Status Adults Couch Potatoes or Work Warriors?

Rasmussen

Dumuid

Hron

et al. 2020

Preprint

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BackgroundMost studies on day-to-day patterns of physical behaviours (i.e. physical activities and sedentary behaviour) are based on adult populations of high socioeconomic status (SES) and without differentiating between work and leisure time. Thus, we aimed to characterise the day-to-day leisure time physical behaviours patterns among low SES adults and investigate if a day of the week, workday, work duration, and work physical behaviours influence these leisure-time patterns.MethodsThis cross-sectional study included 1012 adults from typical low SES occupations (e.g. manufacturing, cleaning and transportation). The participants wore accelerometers for 1-7 days to measure daily physical behaviours during work and leisure time, expressed as 3-part time-use compositions consisting of time spent 1) sedentary, 2) standing or 3) being active (i.e. walking, running, stair climbing, or cycling). Multivariate multilevel log-ratio models were used to regress leisure time-use composition on day-of-week and the interaction between day-of-week and (1) type of day, (i.e., work/non-work), (3) work duration, and (4) work time-use composition. Models were adjusted for sex, age, BMI, and smoking-status. ResultsOver the course of a week, the workers were primarily sedentary during leisure time, while spending most work time standing or being active. Leisure time physical behaviours were associated with type of day (p < 0.005, more sedentary on workdays vs. non-workdays), day-of-week (p < 0.005, more sedentary on Friday, Saturday and Sunday), standing work (p < 0.005, more sedentary and less active leisure time on Sunday), active work (p < 0.005, less sedentary and more active leisure time on Sunday), and work duration (p < 0.005, less active leisure time on Friday). ConclusionsOur findings suggest that while low SES adults’ leisure time is mostly sedentary, their work time is predominantly standing or active. Leisure time was spent more sedentary on workdays compared to non-workdays, indicating that work factors influenced day-to-day leisure time behaviours. Accordingly, work physical behaviours and work duration were differently associated with leisure time physical behaviours. Our findings support the value of considering the influence of work factors when planning strategies aiming to increase health-enhancing leisure time activities among low SES adults.

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“…The VO 2 max can be estimated applying a specific equation [85]. It has been used to asses cardiorespiratory fitness in several studies [86,87].…”

Section: Indirect Field Testsmentioning

confidence: 99%

Fitness Assessment as an Anti-Aging Marker: A Narrative Review

Amaro‐Gahete¹,

De-la-O²,

Jurado‐Fasoli³

et al. 2017

J Gerontol Geriatr Res

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Aging is a natural, physiological, and inevitable process, but it can be also influenced. Although aging is not a disease, it has several characteristics that could indicate so, such as a functional decline at different levels, which may determine clinical manifestations, and it is associated with several disease processes. Consequently, it is essential to create and adopt strategies to delay the aging process. Nowadays, any strategy adopted without including physical exercise seems inconceivable. Recent studies published in relation to this population have shown that the maintenance of acceptable levels of physical fitness is associated with the prevention of many of premature aging consequences, good rates of health, and quality of life of the person. cardiorespiratory fitness and muscular strength (as physical fitness components) are excellent life expectancy and quality of life predictors. Therefore, reaching a good fitness level is the most powerful clinical method to prevent and delay the aging process. Not only their years to live increase, but also their quality, with health and without diseases or mobility dependence.

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Physical Workload and Work Capacity across Occupational Groups

Cited by 40 publications

References 30 publications

Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72 855 workers

Lifestyle-associated health risk indicators across a wide range of occupational groups: a cross-sectional analysis in 72 855 workers

Day-to-Day Pattern of Work and Leisure Time Physical Behaviours: Are Low Socioeconomic Status Adults Couch Potatoes or Work Warriors?

Fitness Assessment as an Anti-Aging Marker: A Narrative Review

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