Literature DB >> 33714177

Long working hours and depressive symptoms: moderation by gender, income, and job status.

Eunsoo Choi1, Kwan Woo Choi2, Hyun-Ghang Jeong3, Moon-Soo Lee3, Young-Hoon Ko4, Changsu Han3, Byung-Joo Ham2, Jisoon Chang5, Kyu-Man Han6.   

Abstract

BACKGROUND: Long working hours can be a risk factor for poor mental health; however, little is known about the potential factors moderating their relation. This study investigates the association between working hours and depressive symptoms, and explores the potential moderating effect of gender, income level, and job status on this association using a nationally representative sample of working population in South Korea.
METHODS: Data of 7,082 workers aged 19 years or above were obtained from the Korea National Health and Nutrition Examination Surveys (KNHANES) conducted in 2014, 2016, and 2018 in South Korea. Working hours were categorized into 35-39, 40, 41-52, 53-68, and ≥69 hours/week. Depressive symptoms were evaluated using the Patient Health Questionnaire-9 (PHQ-9).
RESULTS: Individuals working ≥69 hours/week were more likely to have moderate to severe depressive symptoms compared to those working 40 hours/week. The association between longer working hours and depressive symptoms was especially prominent in female workers, standard wage workers, and workers with low income levels. We observed significant partial mediation pathways between working hours and PHQ-9 scores through both perceived usual stress level and self-rated health in the total sample. LIMITATIONS: The cross-sectional design of the study limits causal interpretation of the findings.
CONCLUSION: Working longer than the legal upper limit of 52 hours/week puts workers at a greater risk for depression. Females, low-income workers, and wage workers are more vulnerable to the negative consequences of long working hours on mental health.
Copyright © 2021. Published by Elsevier B.V.

Entities:  

Keywords:  Korea National Health and Nutrition Examination Survey; Work hours; depression; mental health; suicidal ideation

Mesh:

Year:  2021        PMID: 33714177     DOI: 10.1016/j.jad.2021.03.001

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


  3 in total

1.  A Machine Learning Approach for Predicting Wage Workers' Suicidal Ideation.

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Journal:  J Pers Med       Date:  2022-06-09

2.  The Influence of Long Working Hours, Occupational Stress, and Well-Being on Depression Among Couriers in Zhejiang, China.

Authors:  Yu Hong; Yixin Zhang; Panqi Xue; Xinglin Fang; Lifang Zhou; Fang Wei; Xiaoming Lou; Hua Zou
Journal:  Front Psychol       Date:  2022-06-23

3.  Working from home, work-time control and mental health: Results from the Brazilian longitudinal study of adult health (ELSA-Brasil).

Authors:  Rosane Harter Griep; Maria da Conceição C Almeida; Sandhi Maria Barreto; André R Brunoni; Bruce B Duncan; Luana Giatti; José Geraldo Mill; Maria Del Carmen B Molina; Arlinda B Moreno; Ana Luisa Patrão; Maria Inês Schmidt; Maria de Jesus Mendes da Fonseca
Journal:  Front Psychol       Date:  2022-10-03
  3 in total

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