RESUMO
Objectives: As a specific group with high health inequality, it is crucial to improve the health status and health inequalities of rural-to-urban migrant workers. This study aimed to evaluate the health inequality of migrant and urban workers in China and decompose it. Methods: A cross-sectional study was carried out, using a standardized questionnaire to obtain basic information, self-rated health to evaluate health status, concentration index to measure health inequalities, and WDW decomposition to analyze the causes of health inequalities. Results: The concentration index of health for migrants was 0.021 and 0.009 for urban workers. The main factors contributing to health inequality among rural-to-urban migrant workers included income, exercise, and age. In contrast, the main factors of health inequality among urban workers included income, the number of chronic diseases, social support, and education. Conclusion: There were health inequalities in both rural-to-urban migrant and urban workers. The government and relevant authorities should formulate timely policies and take targeted measures to reduce income disparities among workers, thereby improving health inequality.
Assuntos
Disparidades nos Níveis de Saúde , População Rural , Migrantes , População Urbana , Humanos , Estudos Transversais , China , Migrantes/estatística & dados numéricos , Feminino , Masculino , Adulto , População Rural/estatística & dados numéricos , População Urbana/estatística & dados numéricos , Inquéritos e Questionários , Pessoa de Meia-Idade , Fatores SocioeconômicosRESUMO
The environmental pollution caused by mineral exploitation and energy consumption poses a serious threat to ecological security and human health, particularly in resource-based cities. To address this issue, a comprehensive investigation was conducted on potentially toxic elements (PTEs) in road dust from different seasons to assess the environmental risks and influencing factors faced by Datong City. Multivariate statistical analysis and absolute principal component score were employed for source identification and quantitative allocation. The geo-accumulation index and improved Nemerow index were utilized to evaluate the pollution levels of PTEs. Monte Carlo simulation was employed to assess the ecological-health risks associated with PTEs content and source orientation. Furthermore, geo-detector and random forest analysis were conducted to examine the key environmental variables and driving factors contributing to the spatiotemporal variation in PTEs content. In all PTEs, Cd, Hg, and Zn exhibited higher levels of content, with an average content/background value of 3.65 to 4.91, 2.53 to 3.34, and 2.15 to 2.89 times, respectively. Seasonal disparities were evident in PTEs contents, with average levels generally showing a pattern of spring (winter) > summer (autumn). PTEs in fine road dust (FRD) were primarily influenced by traffic, natural factors, coal-related industrial activities, and metallurgical activities, contributing 14.9-33.9 %, 41.4-47.5 %, 4.4-8.3 %, and 14.2-29.4 % to the total contents, respectively. The overall pollution and ecological risk of PTEs were categorized as moderate and high, respectively, with the winter season exhibiting the most severe conditions, primarily driven by Hg emissions from coal-related industries. Non-carcinogenic risk of PTEs for adults was within the safe limit, yet children still faced a probability of 4.1 %-16.4 % of unacceptable risks, particularly in summer. Carcinogenic risks were evident across all demographics, with children at the highest risk, mainly due to Cr and smelting industrial sources. Geo-detector and random forest model indicated that spatial disparities in prioritized control elements (Cr and Hg) were primarily influenced by particulate matter (PM10) and anthropogenic activities (industrial and socio-economic factors); variations in particulate matter (PM10 and PM2.5) and meteorological factors (wind speed and precipitation) were the primary controllers of seasonal disparities of Cr and Hg.