{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T18:19:16Z","timestamp":1777486756181,"version":"3.51.4"},"reference-count":59,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T00:00:00Z","timestamp":1746662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Strengthening health education is an important measure to improve the health of mobile populations and a key objective of China\u2019s basic public health services. Existing studies demonstrate that health education affects the health of mobile populations, but insufficient attention is paid to the importance of factors that influence health education. Moreover, few studies examine how these factors contribute to health education equity among mobile populations in China. Therefore, this study aims to reveal the importance of factors affecting health education based on a comprehensive understanding of mobile populations\u2019 overall health education status. Furthermore, the contribution of these important factors to health education equity is analyzed to inform differentiated intervention strategies, thereby providing a reference for enhancing mobile populations\u2019 health level and achieving equal access to basic public health services.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>This study utilized data from the 2018 China Migrants Dynamic Survey (CMDS), with a final sample of 103,910 participants after data cleaning. Chi-square tests were first conducted to examine differences in health education across various characteristics of the mobile population. The relative importance of influencing factors was then assessed using a random forest model, followed by key factor identification through LASSO regression. Subsequently, binary logistic regression was performed to quantify the effects of these key factors. Finally, concentration indices were calculated to identify these factors\u2019 contributions to health education equity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The self-assessed health status of China\u2019s mobile population was good, with 81.89% reporting receipt of health education, while 18.11% had not received any health education. Seven key factors were identified as most influential in determining health education access among the mobile population: income, education, age, health record, scope of mobility, reason for mobility and gender. The health education concentration index of the mobile population was 0.0121, indicating a significant inequality in the utilization of health education services. Each important factor had a significant negative amplifying effect on health education equity among the mobile population.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Health education among the mobile population requires further enhancement. Special attention should be directed toward vulnerable groups, including low-income individuals, the older adult, those with lower educational levels, and those with wider migration ranges. Moreover, the impact of key factors on health education equity among the mobile population should be carefully considered to improve health education equity.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpubh.2025.1570633","type":"journal-article","created":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T10:16:13Z","timestamp":1746699373000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Analysis of influencing factors and equity in health education for mobile populations based on random forest model: evidence from the China migrants dynamic survey"],"prefix":"10.3389","volume":"13","author":[{"given":"Meng Han","family":"Jiang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shan Yan","family":"Lei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,5,8]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1167537","DOI":"10.3389\/fpubh.2023.1167537","article-title":"Social integration, physical and mental health and subjective well-being in the floating population-a moderated mediation analysis","volume":"11","author":"Fei","year":"2023","journal-title":"Front Public Health"},{"key":"ref2","year":"2021"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"717","DOI":"10.1186\/s12913-018-3522-y","article-title":"Comparing the needs and utilization of health services between urban residents and rural-to-urban migrants in China from 2012 to 2016","volume":"18","author":"Zheng","year":"2018","journal-title":"BMC Health 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