Feng Ren1,2,3,4,5, Xin Yu1,2,3,4, Weimin Dang1,2,3,4, Wenyi Niu6, Tianhang Zhou1,2,3,4, Yongqiang Lin7, Zijun Wu8, Lin Lin9, Baoliang Zhong10, Hongling Chu6, Jinpeng Zhou8, Hong Ding9, Ping Yuan5. 1. Peking University Sixth Hospital, Peking University, Beijing, China. 2. Peking University Institute of Mental Health, Peking University, Beijing, China. 3. Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China. 4. National Clinical Research Center for Mental Disorders, Peking University Sixth Hospital, Beijing, China. 5. Peking University Shougang Hospital, Beijing, China. 6. School of Public Health, Peking University, Beijing, China. 7. Guangdong Mental Health Center, Guangdong General Hospital, Guangzhou, China. 8. Department of Occupational Health Surveillance, Shenzhen Hospital for the Prevention and Treatment of Occupational Disease, Shenzhen, China. 9. Longgang District Center for Disease Control and Prevention, Shenzhen, China. 10. Wuhan Mental Health Center, Wuhan, China.
Abstract
INTRODUCTION: Assembly-line migrant workers (AMWs), as a major workforce in China, may be at particularly high risk of depression due to their relative low social economic status and particular job characteristics. However, little is known about the frequency and characteristics of depression among Chinese AMWs. This study investigated the prevalence and correlates of depressive symptoms in Chinese AMWs. METHODS: In this cross-sectional survey, 915 Chinese AMWs from two shoe-making factories completed a standardized questionnaire to report their socio-demographics, physical health, migration, and work. They also reported their depressive symptoms by completing the Beck Depression Inventory-Short Form (BDI-SF). We conducted multiple logistic regression analysis to identify factors related to depression. RESULTS: We found that 31.7% of AMWs were clinically depressed (BDI-SF ≥ 8). The multiple regression model included age, self-rated physical health, pain, family relationships, having no good friends at the same factory, and working under high pressure. DISCUSSION: Our findings suggest that depression is common among Chinese AMWs. We argue that there is an urgent need for health care providers and factory managers to work on the early identification of AMWs, who are at high risk for depression. Psychological and psychiatric treatments are necessary in the Chinese labor-intensive industries.
INTRODUCTION: Assembly-line migrant workers (AMWs), as a major workforce in China, may be at particularly high risk of depression due to their relative low social economic status and particular job characteristics. However, little is known about the frequency and characteristics of depression among Chinese AMWs. This study investigated the prevalence and correlates of depressive symptoms in Chinese AMWs. METHODS: In this cross-sectional survey, 915 Chinese AMWs from two shoe-making factories completed a standardized questionnaire to report their socio-demographics, physical health, migration, and work. They also reported their depressive symptoms by completing the Beck Depression Inventory-Short Form (BDI-SF). We conducted multiple logistic regression analysis to identify factors related to depression. RESULTS: We found that 31.7% of AMWs were clinically depressed (BDI-SF ≥ 8). The multiple regression model included age, self-rated physical health, pain, family relationships, having no good friends at the same factory, and working under high pressure. DISCUSSION: Our findings suggest that depression is common among Chinese AMWs. We argue that there is an urgent need for health care providers and factory managers to work on the early identification of AMWs, who are at high risk for depression. Psychological and psychiatric treatments are necessary in the Chinese labor-intensive industries.
Authors: Ha Ngoc Do; Anh Tuan Nguyen; Hoa Quynh Thi Nguyen; Thanh Phuong Bui; Quy Van Nguyen; Ngan Thu Thi Tran; Long Hoang Nguyen; Hai Quang Pham; Giang Hai Ha; Chi Linh Hoang; Bach Xuan Tran; Carl A Latkin; Roger C M Ho; Cyrus S H Ho Journal: Int J Environ Res Public Health Date: 2020-04-23 Impact factor: 3.390
Authors: Giulia Menculini; Francesco Bernardini; Luigi Attademo; Pierfrancesco Maria Balducci; Tiziana Sciarma; Patrizia Moretti; Alfonso Tortorella Journal: Int J Environ Res Public Health Date: 2021-04-08 Impact factor: 3.390
Authors: Kendall Searle; Grant Blashki; Ritsuko Kakuma; Hui Yang; Shurong Lu; Baoqi Li; Yingying Xiao; Harry Minas Journal: Int J Ment Health Syst Date: 2022-02-15
Authors: Kendall Searle; Grant Blashki; Ritsuko Kakuma; Hui Yang; Harry Minas Journal: Int J Environ Res Public Health Date: 2022-02-23 Impact factor: 3.390