Socio-demographic, behavioural and cognitive correlates of work-related sitting time in German men and women

Abstract

BackgroundSitting time is ubiquitous for most adults in developed countries and is most prevalent in three domains: in the workplace, during transport and during leisure time. The correlates of prolonged sitting time in workplace settings are not well understood. Therefore, the aim of this study was to examine the gender-specific associations between the socio-demographic, behavioural and cognitive correlates of work-related sitting time.MethodsA cross-sectional sample of working German adults (n = 1515; 747 men; 43.5 ± 11.0 years) completed questionnaires regarding domain-specific sitting times and physical activity (PA) and answered statements concerning beliefs about sitting. To identify gender-specific correlates of work-related sitting time, we used a series of linear regressions.ResultsThe overall median was 2 hours of work-related sitting time/day. Regression analyses showed for men (β = -.43) and for women (β = -.32) that work-related PA was negatively associated with work-related sitting time, but leisure-related PA was not a significant correlate. For women only, transport-related PA (β = -.07) was a negative correlate of work-related sitting time, suggesting increased sitting times during work with decreased PA in transport. Education and income levels were positively associated, and in women only, age (β = -.14) had a negative correlation with work-related sitting time. For both genders, TV-related sitting time was negatively associated with work-related sitting time. The only association with cognitive correlates was found in men for the belief ‘Sitting for long periods does not matter to me’ (β = .10) expressing a more positive attitude towards sitting with increasing sitting durations.ConclusionsThe present findings show that in particular, higher educated men and women as well as young women are high-risk groups to target for reducing prolonged work-related sitting time. In addition, our findings propose considering increasing transport-related PA, especially in women, as well as promoting recreation-related PA in conjunction with efforts to reduce long work-related sitting times.

Prevalence and socioeconomic determinants of leisure time physical activity among Polish farmers

“…This concerns the group of farmers from the presented research group as the sitting time on weekdays in their case is 4.4±2.9 and 4.5±3.2 hrs/day at weekends, and these results are close to those for people with sedentary work, e.g. highly educated employees (about 5 hours) [37] and office workers (about 6 hours during a working day) [38]. When taking into consideration the youngest farmers (aged 18-29-7.4±1.0 and 30-39 − 5.1±3.3 hours on weekdays) and those with the highest incomes (3,000-4,499 PLN/Є750-1,124 − 5.7±2.1 and ≥4500 PLN/Є1125 − 6.8±1.5 hours at weekends), the described unfavourable phenomenon is even more prevalent.…”

Prediction of objectively measured physical activity and sedentariness among blue-collar work using survey questionnaires

“…The predictors used for modelling in this study were Gupta et al selected a priori from the questionnaire based on (i) whether they would likely predict time spent sedentary or in physical activity according to previous studies (26,29,30,32,(36)(37)(38), (ii) whether they are commonly available in large epidemiological studies and surveys, and (iii) whether they showed a large relative dispersion between workers in our material. Based on these criteria, we arrived at including self-reported information on age, gender, body mass index (BMI), job type, OST, and OPA.…”

“…Explicit prediction models have been proposed before to predict time spent sedentary and in physical activity (23)(24)(25), but these studies have not developed models for exposures at work, which may show associations with self-reported predictors other than leisure time exposures. A few previous studies have, indeed, developed prediction models for time spent sedentary and in physical activity specifically at work (26)(27)(28)(29)(30). However, they have mainly focused on predicting answers to some self-reported variables by another type of self-reported information.…”

“…Another limitation of previous prediction models addressing time spent sedentary and in physical activity at work is that the predictors included in the models, such as cognitive (32) and psychosocial variablesincluding social norms, self-efficacy and advantages of sitting less (26) -are not normally available in large epidemiological studies and surveys. Developing models based on predictors that typically appear in large epidemiological studies and surveys would increase the utility of the models in the context of, for instance, public health surveys and cohort studies of occupational health.…”

Sozioökonomische Unterschiede in der körperlich-sportlichen Aktivität von Erwerbstätigen im mittleren Lebensalter

“…So erfordern insbesondere einfache manuelle Berufe körperlich anstrengende Arbeiten, die meist von Ungelernten oder Geringqualifizierten ausgeübt werden. Besserqualifizierte wie auch Besserverdienende verbringen auf der Arbeit dagegen vergleichsweise mehr Zeit im Sitzen [11]. …”