Abstract
BACKGROUND: Sub-health status (SHS) refers to the physical condition in which a person falls between being healthy and having a disease. The sub-health status of medical students is related to many factors. The aim of this study is to explore the current situation and related factors of sub-health of medical students from the perspective of health ecology, to provide a basis for the formulation of intervention measures and improve the health level of medical students. METHODS: The data for this study came from a nationwide cross-sectional survey conducted in June-August 2022, covering 32 provinces and autonomous regions in mainland China. Multi-stage random sampling was used to recruit. 30,505 valid questionnaires were finally collected. According to the purpose of this study, the subjects were medical students. A total of 1878 subjects were included in the study. Binary stepwise logistic regression and back propagation neural network (BPNN) were used to explore the influencing factors of sub-health. RESULTS: The prevalence of sub-health among medical students in mainland China is 57.5%. Results revealed that negative life events (odds ratio [OR] = 1.64; 95%CI = 1.31-2.04), anxiety (OR = 1.97; 95%CI = 1.27-3.10), depression (OR = 1.80; 95%CI = 1.30-2.51), second-hand smoke exposure (OR = 1.32; 95%CI = 1.06-1.64), problematic Internet use (OR = 1.15; 95%CI = 1.12-1.17), and perceived stress (OR = 1.16; 95%CI = 1.10-1.22) were identified as risk factors for sub-health among medical students, and the level of health literacy was found to be a protective factor for sub-health (OR = 0.96 (95%CI = 0.94-0.98). Sub-health risk increased with increasing smartphone use 1-2 h (OR = 1.34; 95%CI = 1.03-1.73) and ≥ 2 h (OR = 1.44; 95%CI = 1.05-1.98). Four important variables were determined according to the BPNN results: perceived stress, problematic Internet use, depression, and health literacy. CONCLUSIONS: Medical students in mainland China have a high rate of SHS, indicating it's a pressing public health issue for them. Factors like mental health, internet use problems, and health literacy are linked to SHS occurrence in this group. This study provides a scientific basis for early identification of high-risk groups, and provides a reference for developing personalized intervention measures based on the perspective of health ecology.