Long work hours, weekend working and depressive symptoms in men and women: findings from a UK population-based study
Gillian Weston, 1 Afshin Zilanawala, 1,2 Elizabeth Webb, 3 Livia A Carvalho, 4 Anne McMunn 1
To cite: Weston G, Zilanawala A, Webb E, et al. J Epidemiol Community Health Epub ahead of print: [please include Day Month Year].
doi:10.1136/jech-2018- 211309
1
Research Department of Epidemiology and Public Health, University College London, London, UK
2
Human Development and Family Science, Oregon State University, Corvallis, Oregon, USA
3Department of Research and Policy, Age UK, London, UK
4
Department of Clinical Pharmacology, William Harvey Research Institute, Queen Mary University of London, London, UK
Correspondence to Ms Gillian Weston, Research Department of Epidemiology and Public Health, University College, London WC1E 6BT, UK;
gillian. weston. 14@ ucl. ac. uk Received 9 July 2018 Revised 24 October 2018 Accepted 10 January 2019
© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.
AbsTrACT
background Globalised and 24/7 business operations have fuelled demands for people to work long hours and weekends. Research on the mental health effects of these intensive temporal work patterns is sparse, contradictory or has not considered gender differences.
Our objective was to examine the relationship between these work patterns and depressive symptoms in a large nationally representative sample of working men and women in the UK.
Method The current study analysed data from Understanding Society, the UK Household Longitudinal Study, of 11 215 men and 12 188 women in employment or self-employment at the time of the study. Ordinary least squares regression models, adjusted for potential confounders and psychosocial work factors, were used to estimate depressive symptoms across categories of work hours and weekend work patterns.
results Relative to a standard 35–40 hours/week, working 55 hours/week or more related to more depressive symptoms among women (ß=0.75, 95% CI 0.12 to 1.39), but not for men (ß=0.24, 95% CI −0.10 to 0.58). Compared with not working weekends, working most or all weekends related to more depressive symptoms for both men (ß=0.34, 95% CI 0.08 to 0.61) and women (ß=0.50, 95% CI 0.20 to 0.79); however, working some weekends only related to more depressive symptoms for men (ß=0.33, 95% CI 0.11 to 0.55), not women (ß=0.17, 95% CI −0.09 to 0.42).
Conclusion Increased depressive symptoms were independently linked to working extra-long hours for women, whereas increased depressive symptoms were associated with working weekends for both genders, suggesting these work patterns may contribute to worse mental health.
InTroduCTIon
The demands of operating a 24/7 globalised society is partially met by work patterns that elongate working hours and extend the working week.
1In eastern Asian countries the risk of karoshi (death due to overwork) has increased,
2 3while across EU countries atypical work hours have become a feature for a significant proportion of people.
4In the UK, there are concerns about unregulated and frequently unpaid overtime,
5and work-re- lated stress, often linked to workload, accounts for millions of lost working days every year.
6Despite this, other than studies on shift work,
7few
epidemiological studies have considered the impact of temporal work patterns on mental health.
To our knowledge, although weekend working has been associated with poor work-life balance
8and work-family conflict,
9 10just four studies have examined its relationship to mental health. While three found evidence of job stress or psycholog- ical strain among weekend workers relative to weekday workers,
11–13in the fourth there was no association between working weekends and depres- sive symptoms.
14Long work hours has attracted more research attention. Recent reviews and a meta-analysis concluded there were some adverse effects of long hours on depressive mood, but these were often small, non-significant, or greater for women.
15–17Research has shown that gender plays a significant role in the way that work is organised, experienced and rewarded, not least in terms of occupational segregation, job status, mobility, and inequality in earnings, but also in work attitudes, behaviour and social relations.
18There are also suggestions that men and women perceive and respond differently to work demands such as the quantity of work and time-pressures.
19Despite this and recom- mendations that studies about work and health should address gender differences,
20most studies on temporal work patterns focus only on men or do not separate men and women in their analysis.
Furthermore, although psychosocial work factors link to both working patterns and depression, few of the studies on temporal work patterns take them into account.
21Moreover, there is heterogeneity in the way that long hours are defined,
22with part- time workers sometimes categorised as the refer- ence group despite part-time work being associated with health problems.
23A further limitation is that much of the existing research on UK workers relates to specific workplaces or occupations such as civil servants which, though informative, may not be representative of the general population of workers.
24To facilitate generalisability, disaggregate by gender, adjust for a range of covariates including psychosocial work factors, and use the stan- dard working week of 35–40 hours and weekday working as our reference categories, our aim was to investigate the linkages of temporal work patterns with mental health using workers’ data from a large nationally representative sample of the UK popu- lation. Our hypothesis was that in comparison
on 14 March 2019 by guest. Protected by copyright. http://jech.bmj.com/
Table 1 Characteristics of men and women by work pattern
sampleMen (n=11 215)Women (n=12 188)Men (n=11 215)Women (n=12 188) Work patternWeekly work hours (hours/wk)Weekend working <3535–4041–54≥55<3535–4041–54≥55nonesomeMost/allnonesomeMost/all N1645410141041365588136532191463379448392582609137202377 %14.835.936.912.448.728.718.64.032.944.123.049.430.620.0 Age (years) Mean (95% CI)45.441.341.142.343.640.239.642.343.142.039.842.642.239.3 (44.4 to 46.4)(40.8 to 41.8)(40.7 to 41.5)(41.5 to 43.1)(43.1 to 44.0)(39.7 to 40.7)(39.0 to 40.2)(40.9 to 43.6)(42.5 to 43.6)(41.8 to 42.6)(39.2 to 40.5)(42.2 to 43.0)(41.7 to 42.7)(38.6 to 39.9) 16–3431.332.932.828.12535.538.628.4***29.530.039.6***28.229.139.2*** ≥3568.767.167.271.97564.561.471.670.570.060.471.870.960.8 Marital status*** ********* Single27.521.917.615.014.524.326.021.719.018.425.917.319.726.0 Married/cohabit66.173.377.879.873.863.562.863.476.576.269.271.468.161.3 Seperated/divorced/ widowed6.44.74.65.111.712.211.214.94.45.44.911.312.212.7 Children in the household*** ********* None77.865.061.960.152.175.177.077.268.063.065.362.066.267.3 0–4 years11.817.018.719.318.78.47.47.314.917.918.913.312.414.0 5–9 years5.68.69.19.514.26.15.34.38.48.87.711.39.46.8 10–15 years4.89.410.311.115.010.410.211.28.610.48.013.412.011.8 Education attainment*** ********* Degree37.640.842.641.537.748.361.165.945.242.831.845.353.437.6 A level23.023.823.920.319.321.218.411.821.423.425.919.717.421.5 GCSE20.620.320.220.925.719.915.213.318.519.524.821.419.125.9 Other qualification10.08.79.010.99.26.73.56.88.79.310.17.96.07.9 No qualification8.86.34.26.48.23.91.82.36.34.97.35.64.27.2 NS-SEC occupations*** ********* Manager/professional28.742.547.845.527.847.061.865.250.444.827.841.349.028.7 Intermediate29.621.718.822.926.227.816.719.718.522.725.229.120.620.0 Routine41.835.833.431.746.125.221.415.131.232.647.029.631.351.3 Equivalised household income*** ********* Quintile 1 (lowest)16.75.74.16.812.14.63.04.35.45.810.97.07.011.8 Quintile 220.713.710.79.220.710.77.97.412.311.816.314.413.019.2 Quintile 320.722.418.316.223.421.015.111.020.817.922.321.219.021.8 Quintile 419.729.327.824.823.530.927.020.726.527.425.827.925.123.7 Quintile 5 (highest)22.229.039.143.120.332.747.056.634.937.024.729.635.923.4 Chronic illness*** ******** None diagnosed74.381.482.681.580.884.685.783.479.980.183.481.783.784.8 Diagnosed25.718.617.418.519.215.414.316.620.119.916.618.316.315.2 Smoker status********* Non-smoker35.741.039.935.045.647.045.345.042.337.537.548.944.241.2 Ex-smoker41.836.437.636.834.331.927.037.537.439.135.433.335.630.4 Smoker22.522.622.528.320.221.022.017.520.423.427.117.820.228.4
Continued on 14 March 2019 by guest. Protected by copyright. http://jech.bmj.com/
sampleMen (n=11 215)Women (n=12 188)Men (n=11 215)Women (n=12 188) Work pattern
Weekly work hours (hours/wk)Weekend working <3535–4041–54≥55<3535–4041–54≥55nonesomeMost/allnonesomeMost/all Income satisfaction*** ********* Satisfied55.457.962.562.656.259.264.864.961.361.154.960.760.153.2 Neutral13.714.012.512.112.711.410.28.412.313.413.910.911.614.0 Dissatisfied30.828.225.025.431.129.325.026.726.325.431.228.428.332.9 Job physicality*** ********* Not at all26.223.324.732.322.116.519.128.118.725.135.214.421.033.0 Not very41.735.837.235.443.335.436.742.633.737.641.236.440.347.3 Fairly19.724.625.423.421.429.830.418.528.324.716.630.025.414.0 Very physical12.416.312.79.013.218.313.810.819.312.66.919.0113.35.7 Job satisfaction ***** Satisfied77.775.177.680.079.780.579.978.174.479.176.780.980.077.0 Neutral8.58.57.96.67.06.24.56.19.37.18.25.85.78.0 Dissatisfied13.816.514.513.413.413.315.615.816.313.915.213.214.414.9 Work autonomy** ******* Mean (95% CI)10.911.411.912.510.311.111.511.911.612.011.210.811.010.4 (10.6 to 11.2)(11.3 to 11.6)(11.8 to 12.1)(12.3 to 12.8)(10.2 to 10.4)(10.9 to 11.2)(11.3 to 11.6)(11.4 to 12.3)(11.4 to 11.7)(11.8 to 12.1)11.0 to 11.5)(10.7 to 10.9)(10.8 to 11.2)(10.2 to 10.6) Figures are percentages unless stated otherwise. Percentages are weighted. Sample sizes are unweighted. *P<0.05; **P<0.01; ***P<0.001. NS-SEC, National Statistics Socio-Economic Classification.