Latent class characteristics and related factors of health-risk behaviors among higher vocational college students in the Wuling Mountain Area

WEN Lizhong; ZHANG Tiancheng; WANG Aolun; ZHANG Fulan; GUO Shuyuan

doi:10.16835/j.cnki.1000-9817.2025226

Volume 46 Issue 8

Aug. 2025

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WEN Lizhong, ZHANG Tiancheng, WANG Aolun, ZHANG Fulan, GUO Shuyuan. Latent class characteristics and related factors of health-risk behaviors among higher vocational college students in the Wuling Mountain Area[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2025, 46(8): 1102-1106. doi: 10.16835/j.cnki.1000-9817.2025226

Citation:

WEN Lizhong, ZHANG Tiancheng, WANG Aolun, ZHANG Fulan, GUO Shuyuan. Latent class characteristics and related factors of health-risk behaviors among higher vocational college students in the Wuling Mountain Area[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2025, 46(8): 1102-1106. doi: 10.16835/j.cnki.1000-9817.2025226

Citation:

WEN Lizhong, ZHANG Tiancheng, WANG Aolun, ZHANG Fulan, GUO Shuyuan. Latent class characteristics and related factors of health-risk behaviors among higher vocational college students in the Wuling Mountain Area[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2025, 46(8): 1102-1106. doi: 10.16835/j.cnki.1000-9817.2025226

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Latent class characteristics and related factors of health-risk behaviors among higher vocational college students in the Wuling Mountain Area

doi: 10.16835/j.cnki.1000-9817.2025226

College of Sports Science, Jishou University, Jishou 416000, Hunan Province, China

Received Date: 2025-02-25
Rev Recd Date: 2025-06-06

Available Online: 2025-08-30

Publish Date: 2025-08-25

Abstract

Abstract

Objective To explore the latent class characteristics and related factors of health-risk behaviors among higher vocational college students (referred to as vocational students) in the Wuling Mountain Area, so as to provide references for promoting their healthy development and formulating effective intervention measures. Methods From April to June 2024, a stratified random cluster sampling method was used to survey 1 737 students from three higher vocational colleges in the Wuling Mountain Area (Xiangxi in Hunan, Enshi in Hubei, and Tongren in Guizhou). The study employed the Health-risk Behavior Questionnaire for College Students, the Parent-Child Relationship Scale, the Social Support Scale, and the School Connection Scale for data collection. Latent class analysis (LCA) was used to examine the heterogeneous distribution characteristics of health-risk behaviors among vocational students, and multivariate Logistic regression was applied to analyze the related factors of latent classes. Results The LCA results identified three latent classes based on 12 health-risk behaviors: the comprehensive high-risk group (151 students, 8.7%), the psychological distress group (883 students, 50.8%), and the low-risk group (703 students, 40.5%). The distribution of latent classes showed statistically significant differences in gender and only-child status (χ²=121.25, 9.85, both P < 0.05). The low-risk group scored higher in parent-child relationship (29.26±6.19), social support (63.98±18.16), and school connection (35.97±7.71) compared to the comprehensive high-risk group (27.28±6.03, 57.67±15.60, 32.97±7.55) and the psychological distress group (27.52±5.19, 62.06±14.54, 33.80±6.14) (F=20.37, 23.51, 9.89, all P < 0.05). Multivariate Logistic regression revealed that boys(OR=3.29) were more likely to belong to the comprehensive high-risk group, social support (OR=0.03, 0.21) and school connection (OR=0.92, 0.96) were less likely to belong to both the comprehensive high-risk and psychological distress groups (all P < 0.05). Conclusions There are three potential categories of health-harmful behaviors among vocational college students in Wuling Mountain Area. Schools, families and society should enhance the levels of parent-child relationship, school connections and social support for vocational college students of different categories to promote their physical and mental health development.
- Dangerous behavior,
- Mental health,
- Regression analysis,
- Students

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References(23)

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