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Zhang M, Liu B, Ke W, Cai Y, Zhang L, Huang W, Yan X, Chen H. Correlation analysis between occupational stress and metabolic syndrome in workers of a petrochemical enterprise: based on two assessment models of occupational stress. BMC Public Health 2024; 24:802. [PMID: 38486274 PMCID: PMC10938751 DOI: 10.1186/s12889-024-18305-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 03/07/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND Occupational stress is becoming a common phenomenon around the world. Being in a high occupational stress state for a long time may destroy the metabolic balance of the body, thereby increasing the risk of metabolic diseases. There is limited evidence regarding the correlation between occupational stress and metabolic syndrome (MetS), particularly in the petrochemical workers. METHODS A total of 1683 workers of a petrochemical enterprise in China were included in the survey by cluster sampling method. The occupational stress assessment was carried out by the Job Content Questionnaire and the Effort-Reward Imbalance Questionnaire, and the general demographic characteristics, work characteristics, occupational hazards, lifestyle and health examination data of the participants were collected. Logistic regression and multiple linear regression were used to analyze the correlations and influencing factors between occupational stress and its dimensions with MetS and its components. RESULTS A total of 1683 questionnaires were sent out, and 1608 were effectively collected, with an effective recovery rate of 95.54%. The detection rates of occupational stress in Job Demand-Control (JDC) and Effort-Reward Imbalance (ERI) models were 28.4% and 27.2%, respectively. In this study, 257 participants (16.0%) were diagnosed with MetS. Compared with the non-MetS group, body mass index (BMI), waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), triglycerides (TG) and fasting blood-glucose (FBG) levels were significantly higher in the MetS group, and high density lipoprotein-cholesterol (HDL-C) levels were significantly lower (P < 0.001). The results of multiple linear regression showed that after adjusting for nation, marital status, education, work system, smoking and drinking, and further adjusting for occupational hazards, the D/C ratio was significantly negatively correlated with SBP in the JDC model. Social support was negatively correlated with WC. In the ERI model, there was a significant positive correlation between over-commitment and FBG. CONCLUSIONS The detection rates of occupational stress and MetS were high in workers of a petrochemical enterprise. In the JDC model, occupational stress was negatively correlated with SBP, and social support was negatively correlated with WC. In the ERI model, there was a significantly positive correlation between over-commitment and FBG.
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Affiliation(s)
- Min Zhang
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, 510300, Guangzhou, Guangdong, China
- School of Public Health, Shanxi Medical University, 030001, Taiyuan, Shanxi, China
| | - Bin Liu
- Shenzhen Luohu People's Hospital, 518000, Shenzhen, Guangdong, China
| | - Weiyi Ke
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, 510300, Guangzhou, Guangdong, China
| | - Yashi Cai
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, 510300, Guangzhou, Guangdong, China
| | - Lingyu Zhang
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, 510300, Guangzhou, Guangdong, China
| | - Weixu Huang
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, 510300, Guangzhou, Guangdong, China
| | - Xuehua Yan
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, 510300, Guangzhou, Guangdong, China.
| | - Huifeng Chen
- Guangdong Province Hospital for Occupational Disease Prevention and Treatment, 510300, Guangzhou, Guangdong, China.
- School of Public Health, Shanxi Medical University, 030001, Taiyuan, Shanxi, China.
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Zhou C, Chen F, Wang J, Jin N, Li J, Zheng B, Ye M. Association between occupational stress, occupational burnout, and depressive symptoms among medical staff during COVID-19: A cross-sectional study in Chongqing, China. Work 2024; 78:305-315. [PMID: 38189727 DOI: 10.3233/wor-230343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2024] Open
Abstract
BACKGROUND Studies have extensively examined the factors contributing to the onset of occupational stress, burnout, and depression. However, the relationship between these variables is limited. OBJECTIVE This study aimed to explore the association between occupational stress, burnout, and depressive symptoms and to investigate the mediating effect of burnout between occupational stress and depressive symptoms in medical staff. METHODS A cross-sectional survey was conducted among medical staff in Chongqing, China. The Core Occupational Stress Scale (COSS), Maslach Burnout Inventory: General Survey (MBI-GS), and Patient Health Questionnaire-9 (PHQ-9) were used to assess the status of occupational stress, burnout, and depressive symptoms, respectively. The bootstrapping analyses using SPSS PROCESS macros version 3 were conducted to examine mediating effects. RESULTS The study conducted on medical staff in Chongqing revealed that the detection rates of occupational stress, occupational burnout, and depressive symptoms were 31.8%, 23.3%, and 30.3%, respectively. Hierarchical regression analysis revealed that occupational stress and burnout accounted for 19.3% (p < 0.001) and 18.8% (p < 0.001) of the variance in depressive symptoms, respectively. Mediation analysis showed that occupational stress indirectly affected depressive symptoms through the mediating effect of occupational burnout, with a mediation effect value of 0.13 (bootstrap 95% CI: 0.116-0.144) and the mediation effect accounting for 44.8% of the total effect. CONCLUSION Our results indicated that occupational stress and burnout were predictors of depressive symptoms. Occupational stress had a significant indirect effect on depressive symptoms via burnout. These results suggest that reducing occupational stress and burnout could be effective strategies for preventing depression among medical staff.
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Affiliation(s)
- Chunmin Zhou
- College of Public Health, Chongqing Medical University, Chongqing, China
| | - Fengqiong Chen
- Chongqing Center for Disease Control and Prevention, Chongqing, China
| | - Jin Wang
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Nan Jin
- Chongqing Center for Disease Control and Prevention, Chongqing, China
| | - Jinshan Li
- College of Public Health, Chongqing Medical University, Chongqing, China
| | - Bailiang Zheng
- College of Public Health, Chongqing Medical University, Chongqing, China
| | - Mengliang Ye
- College of Public Health, Chongqing Medical University, Chongqing, China
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Watanabe K, Imamura K, Eguchi H, Hidaka Y, Komase Y, Sakuraya A, Inoue A, Kobayashi Y, Sasaki N, Tsuno K, Ando E, Arima H, Asaoka H, Hino A, Iida M, Iwanaga M, Inoue R, Otsuka Y, Shimazu A, Kawakami N, Tsutsumi A. Usage of the Brief Job Stress Questionnaire: A Systematic Review of a Comprehensive Job Stress Questionnaire in Japan from 2003 to 2021. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:1814. [PMID: 36767182 PMCID: PMC9914747 DOI: 10.3390/ijerph20031814] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/13/2023] [Accepted: 01/16/2023] [Indexed: 06/18/2023]
Abstract
The Brief Job Stress Questionnaire (BJSQ) is used widely in occupational health studies and practice. Summarizing scientific production based on measurement is crucial. This study aimed to systematically review observational studies that used the BJSQ and the New BJSQ to show their usability. A systematic search was conducted for studies investigating relationships between the BJSQ or the New BJSQ subscales and other validated measurements on 13 September 2021, in various literature databases. The BJSQ subscales, scoring methods, and other validated measurements in the studies were qualitatively summarized. In total, 145 published reports between 2003 and 2021 were included. Among the BJSQ subscales, job stressors (n = 95) such as quantitative job overload (n = 65) and job control (n = 64) were most often used. The subscales were utilized to investigate the relationships with several other measurements. Five reports used subscales from the New BJSQ. In the last two decades, the BJSQ and the New BJSQ help measure psychosocial factors (PF) at work and contribute to the publication of scientific papers in the occupational health field. This study would encourage the utilization of the questionnaires for future research and practice.
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Affiliation(s)
- Kazuhiro Watanabe
- Department of Public Health, Kitasato University School of Medicine, 1-15-1 Kitazato, Minami-ku, Sagamihara 252-0374, Japan
| | - Kotaro Imamura
- Department of Digital Mental Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Hisashi Eguchi
- Department of Mental Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, 1-1 Iseigaoka, Yahatanishi-ku, Kitakyushu 807-8555, Japan
| | - Yui Hidaka
- Department of Mental Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yu Komase
- Department of Mental Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Asuka Sakuraya
- Department of Digital Mental Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Akiomi Inoue
- Institutional Research Center, University of Occupational and Environmental Health, 1-1 Iseigaoka, Yahatanishi-ku, Kitakyushu 807-8555, Japan
| | - Yuka Kobayashi
- Faculty of Social Policy & Administration, Hosei University, 4342 Aiharamachi, Machida, Tokyo 194-0298, Japan
| | - Natsu Sasaki
- Department of Mental Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Kanami Tsuno
- School of Health Innovation, Kanagawa University of Human Services, 3-25-10 Tonomachi, Kawasaki-ku, Kawasaki 210-0821, Japan
| | - Emiko Ando
- Institute for Cancer Control, National Cancer Center, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
| | - Hideaki Arima
- Department of Mental Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Hiroki Asaoka
- Department of Psychiatric Nursing, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Ayako Hino
- Department of Mental Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, 1-1 Iseigaoka, Yahatanishi-ku, Kitakyushu 807-8555, Japan
| | - Mako Iida
- Department of Psychiatric Nursing, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Mai Iwanaga
- Department of Community Mental Health & Law, National Center of Neurology and Psychiatry, National Institute of Mental Health, 4-1-1 Ogawahigashi, Kodaira, Tokyo 187-0031, Japan
| | - Reiko Inoue
- Department of Public Health, Kitasato University School of Medicine, 1-15-1 Kitazato, Minami-ku, Sagamihara 252-0374, Japan
| | - Yasumasa Otsuka
- Faculty of Human Sciences, University of Tsukuba, 3-29-1 Otsuka, Bunkyo-ku, Tokyo 112-0012, Japan
| | - Akihito Shimazu
- Faculty of Policy Management, Keio University, 5322 Endo, Fujisawa 252-0882, Japan
| | - Norito Kawakami
- Department of Digital Mental Health, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Akizumi Tsutsumi
- Department of Public Health, Kitasato University School of Medicine, 1-15-1 Kitazato, Minami-ku, Sagamihara 252-0374, Japan
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