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Association between the location of social medical insurance and social integration among China’s elderly rural migrants: a nationwide cross-sectional study

BACKGROUND: Universal social medical insurance coverage is viewed as a major factor in promoting social integration, but insufficient evidence exists on the integration of elderly rural migrants (ERM), generally aged 60 years and above, in low- and middle-income countries. To address this problem, w...

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Detalles Bibliográficos
Autores principales: Ma, Xiaojie, Feng, Wenjia, Shi, Chaojun, Wang, Yifan, Gao, Qianqian, Cai, Weiqin, An, Hongqing, Jing, Qi, Gao, Runguo, Ma, Anning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10604806/
https://www.ncbi.nlm.nih.gov/pubmed/37884916
http://dx.doi.org/10.1186/s12889-023-16956-2
Descripción
Sumario:BACKGROUND: Universal social medical insurance coverage is viewed as a major factor in promoting social integration, but insufficient evidence exists on the integration of elderly rural migrants (ERM), generally aged 60 years and above, in low- and middle-income countries. To address this problem, we explore the relationship between the location of social medical insurance (SMI), such as a host city, and social integration in the context of Chinese ERM. METHODS: This study is based on data from the 2017 National Internal Migrant Dynamic Monitoring Survey in China. The study participants were Chinese ERM. An integration index was constructed to measure the degree of social integration in a multi-dimensional manner using a factor analysis method. This study used descriptive statistics and one-way analysis of variance to explore the differences in social integration between ERM with SMI from host cities and hometowns. Stepwise multiple linear regression analysis was used to test the correlation between SMI location and social integration level in the overall sample. Finally, the results were verified by propensity score matching. RESULTS: It was found that 606 (18.2%) of the insured ERM chose host city SMI, while 2727 (81.8%) chose hometown SMI. The level of social integration was lower among ERM with hometown SMI (-1.438 ± 32.795, F = 28.311, p ≤ 0.01) than those with host city SMI (6.649 ± 34.383). Among the dimensions of social integration, social participation contributed more than other factors, with a contribution rate of 45.42%. Host city SMI increased the probability of the social integration index by 647% among ERM (k-nearest neighbor caliper matched (n = 4, caliper = 0.02), with a full sample ATT value of 6.47 (T = 5.32, SE = 1.48, p < 0.05)). CONCLUSIONS: ERM with host city SMI have a higher social integration level than those with hometowns SMI. That is, host city SMI positively affects social integration. Policymakers should focus on the access of host city SMI for ERM. Removing the threshold of host city SMI coverage for ERM can promote social integration.