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How is the way we spend our time related to psychological wellbeing? A cross-sectional analysis of time-use patterns in the general population and their associations with wellbeing and life satisfaction

Aufsätze referiert extern - Web of Science

Samuel Tomczyk, Laura Altweck, Silke Schmidt

In: BMC Public Health 21 (2021), 1, 1858


Background: Time-use surveys can closely monitor daily activities, times of stress and relaxation, and examine predictors and trajectories with regard to health. However, previous studies have often neglected the complex interaction of daily activities when looking at health outcomes. Methods: Using latent profile analysis, this study examined patterns of self-reported daily time use (0–12h hours) for nine types of behaviour (work, errands, housework, childcare, care of persons in need, education, repairs and gardening, physical activity, and hobbies/leisure-time activities) in the 2018 wave of the German Socio-Economic Panel (N = 30,152; 51.9% female; M = 46.87 years). Sociodemographic variables, affective wellbeing, general and domain-specific life satisfaction, and self-rated health were inspected as predictors via multinomial logistic regression models. Results: Six latent profiles emerged: full-time work (47.2%), leisure (33.8%), childcare (8.9%), education (7.0%), part-time work & care (2.6%), and care (0.5%). Overall, the care and part-time work & care profiles showed the lowest wellbeing scores, lower subjective health, and life satisfaction. Women were more likely to be members of the care and childcare profiles. Men were more likely to belong to the full-time work profile, and they reported significantly higher wellbeing than women. Conclusions: The analysis revealed distinct patterns of time use and a burden on women, given their investment in care and childcare. Part-time work, and care seemed particularly demanding, and thus, are important areas for prevention, for instance, regarding mental health problems. However, time use was assessed via self-reports, therefore future studies could implement objective measures like digital trackers to validate findings.

Keywords: Quality of life, Cluster analysis, Life style, Mental health, Public health
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