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Open Access 01-12-2021 | Research

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

Authors: Samuel Tomczyk, Laura Altweck, Silke Schmidt

Published in: BMC Public Health | Issue 1/2021

Abstract

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.

Available only for authorised users

The category “no employment” does not only include persons that are unemployed (i.e. that lost their job and are seeking employment) but also persons who are currently not employed due to other circumstances (e.g., illness or full-time childcare).

Bauman A, Bittman M, Gershuny J. A short history of time use research; implications for public health. BMC Public Health. 2019;19(S2):607. https://doi.org/10.1186/s12889-019-6760-y.CrossRefPubMedPubMedCentral

Hamermesh DS, Frazis H, Stewart J. Data watch: the American time use survey. J Econ Perspect. 2005;19(1):221–32. https://doi.org/10.1257/0895330053148029.CrossRef

Smith DM. Time use and well-being, and large survey studies. Forum Health Econ Policy. 2011;14(2). https://doi.org/10.2202/1558-9544.1266.

Glorieux I, Laurijssen I, Minnen J, van Tienoven TP. In search of the harried leisure class in contemporary society: time-use surveys and patterns of leisure time consumption. J Consum Policy. 2010;33(2):163–81. https://doi.org/10.1007/s10603-010-9124-7.CrossRef

Molina-García J, Castillo I, Queralt A. Leisure-time physical activity and psychological well-being in university students. Psychol Rep. 2011;109(2):453–60. https://doi.org/10.2466/06.10.13.PR0.109.5.453-460.CrossRefPubMed

Smith L, Jacob L, Trott M, Yakkundi A, Butler L, Barnett Y, et al. The association between screen time and mental health during COVID-19: a cross sectional study. Psychiatry Res. 2020;292:113333. https://doi.org/10.1016/j.psychres.2020.113333.CrossRefPubMedPubMedCentral

Virtanen M, Jokela M, Madsen IE, Magnusson Hanson LL, Lallukka T, Nyberg ST, et al. Long working hours and depressive symptoms: systematic review and meta-analysis of published studies and unpublished individual participant data. Scand J Work Environ Health. 2018;44(3):239–50. https://doi.org/10.5271/sjweh.3712.CrossRefPubMed

Jonsson KR, Oberg G, Samkange-Zeeb F, Adjei NK. Determinants and impact of role-related time use allocation on self-reported health among married men and women: a cross-national comparative study. BMC Public Health. 2020;20(1):1–15. https://doi.org/10.1186/s12889-020-09306-z.

Wang S, Mak HW, Fancourt D. Arts, mental distress, mental health functioning & life satisfaction: Fixed-effects analyses of a nationally-representative panel study. BMC Public Health. 2020;20(1):1–9. https://doi.org/10.1186/s12889-019-8109-y.

10.

Meyer OL, Castro-Schilo L, Aguilar-Gaxiola S. Determinants of mental health and self-rated health: a model of socioeconomic status, neighborhood safety, and physical activity. Am J Public Health. 2014;104(9):1734–41. https://doi.org/10.2105/AJPH.2014.302003.CrossRefPubMedPubMedCentral

11.

Franco OH, Wong YL, Kandala N-B, Ferrie JE, Dorn JM, Kivimäki M, et al. Cross-cultural comparison of correlates of quality of life and health status: the Whitehall II study (UK) and the Western New York health study (US). Eur J Epidemiol. 2012;27(4):255–65. https://doi.org/10.1007/s10654-012-9664-z.CrossRefPubMedPubMedCentral

12.

Gimenez-Nadal JI, Molina JA. Health status and the allocation of time: cross-country evidence from Europe. Econ Model. 2015;46:188–203. https://doi.org/10.1016/j.econmod.2014.12.034.CrossRef

13.

Svedberg P, Bardage C, Sandin S, Pedersen NL. A prospective study of health, life-style and psychosocial predictors of self-rated health. Eur J Epidemiol. 2006;21(10):767–76. https://doi.org/10.1007/s10654-006-9064-3.CrossRefPubMed

14.

Müller G, Tisch A, Wöhrmann AM. The impact of long working hours on the health of German employees. German J Human Res Manage. 2018;32(3-4):217–35. https://doi.org/10.1177/2397002218786020.CrossRef

15.

Cho S-S, Ju Y-S, Paek D, Kim H, Jung-Choi K. The combined effect of long working hours and low job control on self-rated health: an interaction analysis. J Occup Environ Med. 2018;60(5):475–80. https://doi.org/10.1097/JOM.0000000000001241.CrossRefPubMed

16.

McKee-Ryan F, Song Z, Wanberg CR, Kinicki AJ. Psychological and physical well-being during unemployment: a meta-analytic study. J Appl Psychol. 2005;90(1):53–76. https://doi.org/10.1037/0021-9010.90.1.53.CrossRefPubMed

17.

Hentschel T, Heilman ME, Peus CV. The multiple dimensions of gender stereotypes: a current look at Men’s and Women’s characterizations of others and themselves. Front Psychol. 2019;10:11. https://doi.org/10.3389/fpsyg.2019.00011.CrossRefPubMedPubMedCentral

18.

van der Meer PH. Gender, unemployment and subjective well-being: why being unemployed is worse for men than for women. Soc Indic Res. 2014;115(1):23–44. https://doi.org/10.1007/s11205-012-0207-5.CrossRef

19.

Forret ML, Mainiero LA, Sullivan SE. Gender role differences in reactions to unemployment: exploring psychological mobility and boundaryless careers. J Organiz Behav. 2010;31(5):647–66. https://doi.org/10.1002/job.703.CrossRef

20.

Altweck L, Hahm S, Muehlan H, Gfesser T, Ulke C, Speerforck S, et al. The interplay of gender, social context, and long-term unemployment effects on subjective health trajectories. BMC Public Health. 2021;21(1):290. https://doi.org/10.1186/s12889-021-10324-8.CrossRefPubMedPubMedCentral

21.

Sullivan O. Gender inequality in work-family balance. Nat Hum Behav. 2019;3(3):201–3. https://doi.org/10.1038/s41562-019-0536-3.CrossRefPubMed

22.

Shockley KM, Shen W, DeNunzio MM, Arvan ML, Knudsen EA. Disentangling the relationship between gender and work–family conflict: an integration of theoretical perspectives using meta-analytic methods. J Appl Psychol. 2017;102(12):1601–35. https://doi.org/10.1037/apl0000246.CrossRefPubMed

23.

Musick K, Meier A, Flood S. How parents fare. Am Sociol Rev. 2016;81(5):1069–95. https://doi.org/10.1177/0003122416663917.CrossRef

24.

Bhan N, Rao N, Raj A. Gender differences in the AssociationsBetween informal caregiving and Wellbeingin low- and middle-income countries. J Women's Health. 2020;29(10):1328–37. https://doi.org/10.1089/jwh.2019.776.CrossRef

25.

Tabler J, Geist C. Do gender differences in housework performance and informal adult caregiving explain the gender gap in depressive symptoms of older adults? J Women Aging. 2021;33(1):41–56. https://doi.org/10.1080/08952841.2019.1681243.CrossRefPubMed

26.

Flood SM, Hill R, Genadek KR. Daily temporal pathways: a latent class approach to time diary data. Soc Indic Res. 2018;135(1):117–42. https://doi.org/10.1007/s11205-016-1469-0.CrossRefPubMed

27.

Liebig S, Goebel J, Schröder C, Grabka M, Richter D, Schupp J, et al. Sozio-oekonomisches Panel (SOEP), Daten der Jahre 1984-2018. SOEP Socio-Economic Panel Study. 2019;239(2):360. https://doi.org/10.1515/jbnst-2018-0022.CrossRef

28.

Goebel J, Grabka MM, Liebig S, Kroh M, Richter D, Schröder C, et al. The German socio-economic panel (SOEP). Jahrbücher Nationalökonomie Stat. 2019;239(2):345–60. https://doi.org/10.1515/jbnst-2018-0022.CrossRef

29.

Schimmack U. Measuring wellbeing in the SOEP. Schmollers Jahr. 2009;129(2):241–9. https://doi.org/10.3790/schm.129.2.241.CrossRef

30.

Schimmack U, Schupp J, Wagner GG. The influence of environment and personality on the affective and cognitive component of subjective well-being. Soc Indic Res. 2008;89(1):41–60. https://doi.org/10.1007/s11205-007-9230-3.CrossRef

31.

R Core Team. R: a language and environment for statistical computing. Vienna: R Foundation for statistical Computing; 2019.

32.

van Buuren SG-OK. mice: Multivariate Imputation by Chained Equations in R. J Stat Software. 2011;45:1–67.CrossRef

33.

Muthén LK, Muthén BO. Mplus User’s Guide. 7th ed. Los Angeles: Muthén & Muthén; 1998-2015.

34.

Nylund KL, Asparouhov T, Muthén BO. Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Equ Model Multidiscip J. 2007;14(4):535–69. https://doi.org/10.1080/10705510701575396.CrossRef

35.

Tomczyk S, Isensee B, Hanewinkel R. Latent classes of polysubstance use among adolescents—a systematic review. Drug Alcohol Depend. 2016;160:12–29. https://doi.org/10.1016/j.drugalcdep.2015.11.035.CrossRefPubMed

36.

Asparouhov T, Muthén B. Auxiliary variables in mixture modeling: three-step approaches using M plus. Struct Equ Modeling. 2014;21(3):329–41. https://doi.org/10.1080/10705511.2014.915181.CrossRef

37.

Boll C, Leppin J. Zeitverwendung von Eltern auf Familie und Beruf im internationalen Vergleich; 2011.

38.

Penning MJ, Wu Z. Caregiver stress and mental health: impact of caregiving relationship and gender. Gerontologist. 2016;56(6):1102–13. https://doi.org/10.1093/geront/gnv038.CrossRefPubMed

39.

Zick CD, Buder I, Waitzman NJ, Simonsen S, Digre K. The nexus between health and time use among racially and ethnically diverse women. Ethn Health. 2019;24(2):147–67. https://doi.org/10.1080/13557858.2017.1315529.CrossRefPubMed

40.

Xiong C, Biscardi M, Astell A, Nalder E, Cameron JI, Mihailidis A, et al. Sex and gender differences in caregiving burden experienced by family caregivers of persons with dementia: a systematic review. PLoS One. 2020;15(4):e0231848. https://doi.org/10.1371/journal.pone.0231848.CrossRefPubMedPubMedCentral

41.

Ryff CD. Possible selves in adulthood and old age: a tale of shifting horizons. Psychol Aging. 1991;6(2):286–95. https://doi.org/10.1037/0882-7974.6.2.286.CrossRefPubMed

42.

Meléndez JC, Mayordomo T, Sancho P, Tomás JM. Coping strategies: gender differences and development throughout life span. Spanish J Psychol. 2012;15(3):1089–98. https://doi.org/10.5209/rev_SJOP.2012.v15.n3.39399.CrossRef

43.

Infratest Burke Sozialforschung. SOEP-IS – 2018. Berlin: Survey Reporton the 2018 SOEP innovation sample; 2018.

Title: 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
Authors: Samuel Tomczyk
Laura Altweck
Silke Schmidt
Publication date: 01-12-2021
Publisher: BioMed Central
Published in: BMC Public Health / Issue 1/2021
Electronic ISSN: 1471-2458
DOI: https://doi.org/10.1186/s12889-021-11712-w

2024 ASCO Annual Meeting

Springer Medicine

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

Abstract

Background

Methods

Results

Conclusions

2024 ASCO Annual Meeting

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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