SHU Chang, ZHANG Dan, DAI Jun-ming, SUN Cheng-xun, CHENG Rui, WU Ning. Effects of occupational stress and social support on depressive symptoms among employees from a state grid corporation[J]. Journal of Environmental and Occupational Medicine, 2018, 35(10): 905-909, 923. DOI: 10.13213/j.cnki.jeom.2018.17593
Citation: SHU Chang, ZHANG Dan, DAI Jun-ming, SUN Cheng-xun, CHENG Rui, WU Ning. Effects of occupational stress and social support on depressive symptoms among employees from a state grid corporation[J]. Journal of Environmental and Occupational Medicine, 2018, 35(10): 905-909, 923. DOI: 10.13213/j.cnki.jeom.2018.17593

Effects of occupational stress and social support on depressive symptoms among employees from a state grid corporation

  • Objective To investigate the status of occupational stress, social support, and depressive symptoms of employees in a state grid corporation, and analyze the effects of occupational stress and social support on depressive symptoms.

    Methods In March 2017, a total of 1 069 workers from a state grid corporation were enrolled in a cross-sectional survey through cluster sampling method, and were asked to complete a self-administered questionnaire after informed consent. Brief Occupational Stress Questionnaire and Patient Health Questionnaire (PHQ-9) were used to assess occupational stress, social support, and depressive symptoms. The t-test and ANOVA were used to compare the differences in occupational stress and depressive symptoms among subjects with different characteristics. Binary logistic regression model was used to assess the associations of depressive symptoms with occupational stress and social support.

    Results The valid response rate of questionnaires reached 87.1% in this study. The average occupational stress score of the respondents was 1.15±0.33, the positive rate of occupational stress was 63.1%, and there were significant differences in occupational stress scores among groups with different ages, educational levels, weekly working hours, and shift modes (P < 0.01). The positive rate of depressive symptoms reached 66.7%, and there were significant differences in the scores of PHQ-9 and the positive rates of depressive symptoms among groups with different ages, monthly household income per capita, and weekly working hours (P < 0.01). The results of logistic regression analyses showed that high job demand (OR=1.97) was a risk factor of depressive symptoms, while high job control (OR=0.73) and social support (OR=0.53) were protective factors.

    Conclusion High job demand, low job control, and low social support may increase the risk of depressive symptoms among employees from the selected state grid corporation.

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