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ORIGINAL RESEARCH article
Front. Public Health
Sec. Life-Course Epidemiology and Social Inequalities in Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1459661
Health Risky Behaviors among Rural-to-Urban Migrant Workers in China: Prevalence, patterns and Association with Distal and Proximal Factors
Provisionally accepted- 1 Third People's Hospital of Huzhou, Huzhou, China
- 2 Wenzhou Medical University, Wenzhou, Zhejiang Province, China
- 3 Lishui Second People's Hospital, Lishui, Zhejiang, China
Background: Health Risky Behaviors (HRBs) pose a significant public health challenge, particularly among migrant workers in China who face unfavorable living and working conditions. This study aimed to investigate the prevalence and characteristics of HRBs in rural-to-urban migrant workers, as well as explore factors associated with HRBs from both distal and proximal perspectives.Methods: A cross-sectional survey involving 2,065 rural-to-urban migrant workers was conducted. Participants completed a structured questionnaire assessing HRBs, distal factors (school dropout, peer victimization, physical neglect/abuse, emotional neglect/abuse) and proximal factors (work burnout, parent -child conflict, adulthood poverty, divorce intention, core self-evaluation).Logistic regression analysis was utilized to identify predictors of HRBs, leading to the development and validation of a prediction model (nomograms) for HRBs among migrant workers. The model's performance was assessed using metrics such as the area under the curve (AUC), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA). Results: Significant predictors of HRBs included gender, school dropout, peer victimization, abuse/neglect experiences, work burnout, parent -child conflict, adulthood poverty, divorce intention, and core self-evaluation. The developed nomogram showed promising predictive accuracy with an AUC of 0.77 for the training set and 0.76 for the validation set. The calibration curve demonstrated good alignment with the diagonal, and the DCA illustrated the model's utility across different threshold ranges. Conclusion: This study highlighted a high prevalence of HRBs among migrant workers in China, and the predictive tool developed can be instrumental in informing targeted interventions and policies to address and manage HRBs effectively among this population.
Keywords: Health risky behaviors, Rural-to-urban migrant workers, Nomograms, prediction, Migrant health
Received: 04 Jul 2024; Accepted: 10 Feb 2025.
Copyright: © 2025 Wang, Wang, Pan, Jian, Zheng and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Weikai Wang, Third People's Hospital of Huzhou, Huzhou, 313000, China
Hong Pan, Wenzhou Medical University, Wenzhou, 325035, Zhejiang Province, China
Wenqian Jian, Wenzhou Medical University, Wenzhou, 325035, Zhejiang Province, China
Yawen Zheng, Lishui Second People's Hospital, Lishui, 323000, Zhejiang, China
Li Chen, Wenzhou Medical University, Wenzhou, 325035, Zhejiang Province, China
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