School of Health Sciences, Wuhan University, Wuhan, Hubei Province, China.
Wuhan Blood Center, Wuhan, Hubei Province, China.
Int Psychogeriatr. 2021 Feb;33(2):157-167. doi: 10.1017/S1041610220001398. Epub 2020 Aug 4.
To establish a structural equation model for exploring the direct and indirect relationships of depressive symptoms and their associated factors among the Chinese elderly population.
A cross-sectional research. The 2015 data from the China Health and Retirement Longitudinal Study (CHARLS) were adopted.
CHARLS is an ongoing longitudinal study assessing the social, economic, and health status of nationally representative samples of middle-aged and elderly Chinese residents.
A total of 5791 participants aged 60 years and above were included.
Depressive symptoms were used as the study outcome. Sociodemographic characteristics, poor health status, unhealthy habits, and sleep duration were used as predictors. Confirmatory factor analysis was first conducted to test the latent variables. Structural equation model was then utilized to examine the associations among latent variables and depressive symptoms.
The mean age of the participants was 68.82 ± 6.86 years, with 55.53% being males. The total prevalence of depressive symptoms was 37.52%. The model paths indicated that sociodemographic characteristics, poor health status, unhealthy habits, and sleep duration were directly associated with depressive symptoms, and the effects were 0.281, 0.509, -0.067, and -0.162, respectively. Sociodemographic characteristics, unhealthy habits, and sleep duration were indirectly associated with depressive symptoms, mediating by poor health status. Their effects on poor health status were -0.093, 0.180, and -0.279, respectively. All paths of the model were significant (P < 0.001). The model could explain 40.9% of the variance in the depressive symptoms of the Chinese elderly population.
Depressive symptoms were significantly associated with sociodemographic characteristics, poor health status, unhealthy habits, and sleep duration among Chinese elderly population. The dominant predictor of depressive symptoms was poor health status. Targeting these results might be helpful in rationally allocating health resources during screening or other mental health promotion activities for the elderly.
建立一个结构方程模型，以探索中国老年人群体中抑郁症状及其相关因素的直接和间接关系。
横断面研究。采用 2015 年中国健康与退休纵向研究（CHARLS）的数据。
CHARLS 是一项正在进行的纵向研究，评估全国代表性的中老年中国居民的社会、经济和健康状况。
共纳入 5791 名 60 岁及以上的参与者。
抑郁症状作为研究结果。社会人口统计学特征、健康状况不佳、不健康习惯和睡眠时间作为预测因素。首先进行验证性因子分析以测试潜在变量。然后利用结构方程模型来检验潜在变量与抑郁症状之间的关联。
参与者的平均年龄为 68.82±6.86 岁，其中 55.53%为男性。抑郁症状的总患病率为 37.52%。模型路径表明，社会人口统计学特征、健康状况不佳、不健康习惯和睡眠时间与抑郁症状直接相关，其影响分别为 0.281、0.509、-0.067 和-0.162。社会人口统计学特征、不健康习惯和睡眠时间通过健康状况不佳间接与抑郁症状相关，其对健康状况不佳的影响分别为-0.093、0.180 和-0.279。模型的所有路径均具有统计学意义（P<0.001）。该模型可以解释中国老年人群体抑郁症状的 40.9%。
在中国老年人群体中，抑郁症状与社会人口统计学特征、健康状况不佳、不健康习惯和睡眠时间显著相关。抑郁症状的主要预测因素是健康状况不佳。针对这些结果，在对老年人进行筛查或其他心理健康促进活动时，有助于合理分配卫生资源。
