Department of Data Science, Zhejiang University of Finance and Economics Dongfang College, Haining, Zhejiang, 314408, China.
Department of Health Management and Policy, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, 63104, USA.
Soc Sci Med. 2021 Apr;275:113814. doi: 10.1016/j.socscimed.2021.113814. Epub 2021 Mar 6.
This study aims to examine the association between province-level socioeconomic welfare factors and depression symptoms among older adults in China. Province-level socioeconomic characteristics were merged with microdata for respondents over 65 years from the 2018 China Health and Retirement Longitudinal Study (CHARLS) Wave 4 (N = 6657). Principal component analysis (PCA) was used to extract three socioeconomic welfare factors constructed from 14 province-level variables. A Bayesian mixed-effects logistic model was applied to measure the association between the three socioeconomic welfare factors and depression symptoms while controlling for socio-demographic variables. The PCA showed that economic welfare, medical resource welfare, and social service welfare together explained 72.2 percent of the total variance of the 14 province-level variables. It was found that increasing economic welfare was significantly associated with a lower probability of depression symptoms (OR = 0.806, 95%CI: [0.674, 0.967]), while medical facilities were associated with a higher probability of depression symptoms (OR = 1.181, 95%CI: [1.029, 1.354]) among Chinese older adults. Uncertainty existed as to whether having access to social welfare (OR = 0.941, 95%CI: [0.835, 1.060]) was associated with prevalence of depression. Thus, improved socioeconomic welfare systems for older adults (which possibly require an increase in spending) are necessary to contribute further to reduced depression risk in China. Policymakers should also improve the utilization of medical resources to mitigate the incidence of depression among the elderly in China.
本研究旨在探讨中国老年人群体中省级社会经济福利因素与抑郁症状之间的关联。将省级社会经济特征与来自 2018 年中国健康与退休纵向研究（CHARLS）第四波（N=6657）的 65 岁以上受访者的微观数据合并。采用主成分分析（PCA）从 14 个省级变量中提取 3 个社会经济福利因素。应用贝叶斯混合效应逻辑模型，在控制社会人口统计学变量的情况下，测量三个社会经济福利因素与抑郁症状之间的关联。PCA 结果表明，经济福利、医疗资源福利和社会服务福利三个因素共同解释了 14 个省级变量总方差的 72.2%。研究发现，经济福利的提高与抑郁症状的发生概率降低显著相关（OR=0.806，95%CI：[0.674，0.967]），而医疗设施的增加与抑郁症状的发生概率升高显著相关（OR=1.181，95%CI：[1.029，1.354]）。然而，社会福利的获取是否与抑郁症状的流行相关尚不确定（OR=0.941，95%CI：[0.835，1.060]）。因此，需要为老年人建立更好的社会经济福利制度（可能需要增加支出），以进一步降低中国老年人的抑郁风险。决策者还应改善医疗资源的利用，以减轻中国老年人抑郁的发生率。
