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作 者:梁樱[1] LIANG Ying(Department of Sociology,Wuhan University,Wuhan 430072,China)
机构地区:[1]武汉大学社会学系,武汉430072
出 处:《北京社会科学》2018年第5期105-116,共12页Social Sciences of Beijing
基 金:武汉大学自主科研项目(人文社会科学)"认同分裂理论的修缮及初步经验验证"(2014410500013)
摘 要:农村老年人的抑郁水平显著高于城市老人,在极端情况下,甚至表现为自杀行为。通过中国健康与养老追踪调查(CHARLS)2011年基线数据,运用分层线性模型(HLM)分析村级社区水平的经济、人口、管理、设施、生态环境五个维度的特征对农村老人抑郁症状的影响,发现中国农村老人的抑郁水平具有显著的村间差异。加入村级水平的解释变量后发现,村子的平均收入水平高,村里具有高中学历的人口比例高,村主任的任职年限长以及村里的基础设施水平高,村里老人抑郁水平显著更低;而在工业污染排放中度和严重的村子里,老人抑郁显著更高。进一步的跨水平交互作用分析则探索了村级变量对具有不同个体特征的老人群体的作用差异。研究结果对于农村社区建设的政策发展以及农村老人的抑郁干预提供了实证依据。Older adults in rural China are significantly more depressive than their counterparts in urban areas,some of whom attempt to commit suicide in extreme cases.This paper uses 2011 baseline data from China Health and Retirement Longitudinal Study(CHARLS)and hierarchical linear modeling to analyze how village community level characteristics affect depressive symptoms of older adults in rural China.The results show that the depressive symptoms of those older adults vary significantly across villages.Furthermore,it finds that village per-capita net income,ratio of residents with middle-school education,working years of village leaders,and infrastructure level are all negatively associated with depressive symptoms of older residents.Industrial pollution in villages,however,increase their depressive symptoms.Some cross-level interaction effects are also found and illustrates how village-level and individual-level variables interact to affect depressive symptoms of older adults with different individual backgrounds.The results have important policy implication for new rural community construction in China.
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