Healthcare-seeking behavior and spatial variation of internal migrants with chronic diseases: a nationwide empirical study in China

Submitted: 27 November 2023
Accepted: 3 May 2024
Published: 28 May 2024
Abstract Views: 1427
PDF: 71
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Individuals migrating with chronic diseases often face substantial health risks, and their patterns of healthcare-seeking behavior are commonly influenced by mobility. However, to our knowledge, no research has used spatial statistics to verify this phenomenon. Utilizing data from the China Migrant Dynamic Survey of 2017, we conducted a geostatistical analysis to identify clusters of chronic disease patients among China’s internal migrants. Geographically weighted regressions were utilized to examine the driving factors behind the reasons why treatment was not sought by 711 individuals among a population sample of 9272 migrant people with chronic diseases. The results indicate that there is a spatial correlation in the clustering of internal migrants with chronic diseases in China. The prevalence is highly clustered in Zhejiang and Xinjiang in north-eastern China. Hotspots were found in the northeast (Jilin and Liaoning), the north (Hebei, Beijing, and Tianjin), and the east (Shandong) and also spread into surrounding provinces. The factors that affect the migrants with no treatment were found to be the number of hospital beds per thousand population, the per capita disposable income of medical care, and the number of participants receiving health education per 1000 Chinese population. To rectify this situation, the local government should “adapt measures to local conditions.” Popularizing health education and coordinating the deployment of high-quality medical facilities and medical workers are effective measures to encourage migrants to seek reasonable medical treatment.



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How to Cite

Li, D., Gao, D., Yamada, M., Chen, C., Xiang, L., & Nie, H. (2024). Healthcare-seeking behavior and spatial variation of internal migrants with chronic diseases: a nationwide empirical study in China. Geospatial Health, 19(1).