To understand the heavy metal pollution in agricultural soils along the East River basin and assess the pollution related health effect to local residents, interviews and archived data were obtained to identify the study sites affected by polluted tailing. Soil samples were collected and tested for heavy metal content and the Comprehensive Pollution Index (CPI). The degree of pollution of agricultural soils in the area was assessed using GIS-based Spatial distribution map of heavy metals and the trend of soil heavy metal risk. Two villages (Matian and Zhudui) near the East River were included in this study for health effect assessment. A total of 193 residents aged 15 or above from each village were tested for the present status of chronic diseases. Convenient sampling method was used to collect blood samples from 78 residents for heavy metal concentration. The contents of Pb, Cd, As, Zn, and Cu in the agricultural soils were all over the standards with a moderate to severe CPI. Among these metals, Cd was the highest followed by Pb, and Cu was the lowest. The contents of Pb, Cd, As, and Zn tend to be higher in soils closer to the river. The prevalence of chronic diseases was over 30%, which is significantly higher than the report from the national central region (23.15%). The average blood lead level (BLL) among children under 14 years is 7.42 μg/dL. Although the adults in Matian village had a significantly higher BLL (χ² = 8.70, p = 0.03) as compared to Zhudui village, there was no significant difference for the prevalence of chronic diseases between the two villages (χ² = 3.23, p = 0.09). The mean BLL of children and the proportion of children with BLL ≥ 10 µg/dL in this study are equivalent to the national average. The higher BLL concentration and prevalence of chronic diseases in adults might be due to their long-term exposure to heavy metal contamination environment and higher background level of heavy metals. Findings from this study will form the baseline information for local government to the development of effective approaches to control the heavy metal contamination and reduce the pollution related adverse health effect on local residents.

Background: Influenza and pneumococcal vaccinations play a crucial role in disease prevention among older adults and are recommended to older adults aged 60 years and over in China, but the vaccination rates are suboptimal. Behavioral spillover indicates that a change in one behavior may lead to changes in other related behaviors. Objective: Based on the Behavioral Spillover Theory, this study aimed to investigate the association between influenza vaccination history and pneumococcal vaccination intention, as well as the mediating role of negative attitudes toward general vaccination among older adults in China. Method: A multi-center cross-sectional survey was conducted among 1031 older adults, and 658 participants (median age: 65.0 ± 9.0 years) who had not received pneumococcal vaccination were included in the analysis. Correlation analysis and path analysis were performed. Results: A significant positive association was observed between influenza vaccination history and pneumococcal vaccination intention (r = 0.167, p < 0.001). In contrast, negative attitudes toward general vaccination, including mistrust of vaccine benefits (r = −0.253, p < 0.001), worries about unforeseen future effects (r = −0.180, p < 0.001), concerns about commercial profiteering (r = −0.360, p < 0.001), and a preference for natural immunity (r = −0.212, p < 0.001) were negatively associated with pneumococcal vaccination intention. Negative attitudes toward general vaccination mediated the association between influenza vaccination history and pneumococcal vaccination intention (total indirect effect = 0.119, p < 0.001, effect size = 50.0%). Conclusion: These findings demonstrated that influenza vaccination history may reduce negative attitudes toward general vaccination, which may further increase pneumococcal vaccination intention, indicating spillover effects of influenza vaccination history. To promote vaccination behavior among older adults, addressing negative attitudes toward general vaccination is crucial.

Introduction: As college students emerge as a key HIV-vulnerable population in China, HIV self-testing (HIVST) presents a critical strategy for enhancing detection rates and enabling timely intervention. While observational studies have identified multifactorial influences on HIVST willingness, few investigations integrate behavioral theory with machine learning approaches among college students. This study aims to fill this gap by exploring the determinants of HIVST willingness among college students using the Health Belief Model (HBM) and random forest analytics.Methods: This cross-sectional study employed stratified cluster sampling to recruit 1,015 undergraduates from Xiangnan College (July-August 2022), The Health Belief Model (HBM) was synthesized with random forest analytics to elucidate determinants of HIVST willingness. Data were collected through questionnaires, and logistic regression and random forest modeling were used for analysis.Results: Among participants, 69.3% (n = 703) expressed willingness to adopt HIVST within the next 6 months. 15.0% reported sexual activity (n = 152), with 12.0% (n = 122) of sexually active participants demonstrating concurrent engagement in unprotected intercourse and HIV testing willingness. HBM-based logistic regression revealed that self-efficacy (OR = 1.64, 95% CI: 1.21-2.21) and cues to action (OR = 1.34, 1.04-1.75) were significant facilitators, contrasting with the inhibitory effects of perceived barriers (OR = 0.69, 0.55-0.86). Random forest modeling prioritized these psychological constructs (mean decrease Gini >2.5), identifying male students and arts majors as critical subpopulations requiring targeted intervention.Discussion: Our dual-method analysis establishes that campus HIV control necessitates: 1) Gender-specific prevention programs addressing male students’ elevated risk exposure; 2) HBM-informed education strengthening self-efficacy and environmental cues; 3) Structural interventions reducing testing barriers through discreet service delivery. This theoretical-empirical integration advances predictive understanding of HIVST behaviors, providing actionable insights for developing precision public health strategies in academic settings.