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社区公共卫生服务对流动老年人口社会融合的影响研究——基于倾向得分匹配(PSM)的实证研究

Empirical Research on the Influence of Community Public Health Service on Social Integration of Floating Elderl opulation Based on Propensity Score Matching
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摘要 目的:考察社区公共卫生服务对流动老年人口社会融合的影响。方法:运用OLS模型和倾向得分匹配法(PSM)进行数据分析。结果:OLS模型结果显示接受过社区公共卫生服务能使流动老年人口的社会融合的指数提高1.1%(P<0.001);在用PSM方法纠正变量间的内生性之后,其结果显示接受社区公共卫生服务能使流动老年人口的社会融合指数提升1.2%(P<0.05)。结论:社区公共卫生服务显著影响流动老年人口的社会融合程度,且不同群组之间的影响程度存在差异,其中家庭人均月收入是影响流动老年人口社会融合程度的重要因素。社区应从公平性的角度去完善社区公共卫生服务,将流动老年人口纳入社区公共卫生服务的对象,提高流动老年人口的社会融入的程度,助力于积极老龄化的实现。 Objective To investigate the influence of community public health services on the social integration of the floating elderly population.Methods OLS model and propensity score matching(PSM)were used for data analysis.Results The results from OLS model showed that receiving community public health services could increase the social integration index of the floating elderly population by 1.1%(P<0.001).After correcting the endogeneity among variables with the PSM method,the results showed that receiving community public health services could increase the social integration index of the floating elderly population by 1.2%(P<0.05).Conclusion Community public health services significantly affect the social integration of the floating elderly popula-tion.And there are differences in the degree of influence among different groups,in which family monthly income is an important influencing factor.Communities should improve the community public medical service from the perspective of fairness,bring the floating elderly population into the object of community public health service,improve the degree of social integration of the floating elderly population,and help the realization of active aging.
作者 李晓钰 李含伟 Li Xiaoyu(Shanghai University of Engineering Science,Shanghai,P.R.China)
出处 《中国卫生事业管理》 北大核心 2023年第6期408-412,共5页 Chinese Health Service Management
基金 国家社会科学基金项目“流动老年人社会支持与社会融合研究”(21BRK006)。
关键词 社区公共卫生服务 社会融合 倾向得分匹配 流动老年人口 community public health care social integration propensity score matching floating elderly population
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