Productive activity profiles and depressive symptoms of urban Chinese elderly: evidence from a national survey

Abstract

OBJECTIVES: This study aims to identify latent clusters of productive activity among urban Chinese elderly by considering multiple productive activities simultaneously. Once clusters were identified, we further explore the effect of engaging in these clusters on depressive symptoms of these elderly, controlling for individual characteristics. METHODS: We present second analyses of data from the 2011 national baseline survey of China Health and Retirement Longitudinal Study (CHARLS). Elderly aged 55 and over were included (N = 4,417). Latent class analysis (LCA) was used to empirically identify the productive clusters through estimating 6 productive activities (e.g., working, grandchildren care, parental care, spousal care, informal help, and civic participation). Analysis of covariance was used to examine the effects of engaging in different clusters on depressive symptoms after controlling for individual characteristics. RESULTS: A four-class model was revealed as best fitting the data, with interpretable set of classes as: Low/Spousal Carers, Super Helpers, Workers, and Grandchild Carers. Further, a significant effect of activity clusters on depressive symptoms has been found, after controlling for individual characteristics of importance. ‘Workers’ and ‘Super Helpers’ were more likely to have less depressive symptoms as compared to Low/ Spousal Carers and Grandchild Carers. CONCLUSIONS: Our individual-oriented approach captured the patterned ways of productive activities of urban Chinese elderly. Through employing clusters to predict depression, we further identified vulnerable groups of individuals caring for their spouses or grandchildren, as well as benefitted groups of individuals engaging in multiple activities concurrently, which may further confirm the role accumulation perspective.