Effect of Long Working Hours on Depression and Mental Well-Being among Employees in Shanghai: The Role of Having Leisure Hobbies

Int J Environ Res Public Health. 2019 Dec 7;16(24):4980. doi: 10.3390/ijerph16244980.


Our aim is to examine the associations between long working hours and depression and mental well-being among the working population in Shanghai, as well as to identify the impact of having hobbies on these relationships. A cross-sectional study was conducted in Shanghai, with depression assessed by the Patient Health Questionnaire-9 (PHQ-9) scale and mental well-being assessed by the World Health Organization five-item Well-Being Index (WHO-5) scale. The phenomenon of long working hours (69.3%) was quite common among employees in Shanghai, and the rate of working over 60 h was 19.3%. Those who worked over 60 h had the highest prevalence of poorer mental health compared with individuals working ≤40 h per week. After adjustment in the logistic regression model, those who reported weekly working time over 60 h were 1.40 (95%CI: 1.03-1.90) and 1.66 (95%CI: 1.26-2.18) times more likely to have depression and poor mental well-being (PMWB), respectively. Adjusted ORs for having hobbies were 0.78 (95%CI: 0.62-0.97) and 0.62 (95%CI: 0.51-0.75), respectively. Meanwhile, having hobbies could significantly lower the mean score on the PHQ-9 and elevate the mean score on the WHO-5 in each working time group, with no interaction effect. Long working hours could have a significantly negative impact on workers' psychological health. Importantly, having hobbies in their daily lives might help to mitigate the adverse effects of long working hours on workers' depression and mental well-being.

Keywords: depression; having hobbies; long working hours; mental well-being.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • China / epidemiology
  • Cross-Sectional Studies
  • Depression / epidemiology*
  • Female
  • Hobbies / psychology*
  • Humans
  • Logistic Models
  • Male
  • Mental Health / statistics & numerical data*
  • Middle Aged
  • Occupational Health
  • Personnel Staffing and Scheduling / statistics & numerical data*
  • Prevalence
  • Young Adult