Family structure and depressive symptoms among older adults in China: A marginal structural model analysis

Background: Mental well-being in the aging population is inevitably linked to families due to the reliance of older adults on family members. This study investigates the causal relationship between family structure and depressive symptoms among Chinese older adults in general and between gender and residential areas.Methods: We used China Health and Retirement Longitudinal Study (CHARLS) panel data, covering four data collection rounds over seven years. Family structure was classified into single-member, couple, nuclear family, and extended family. Taking into account time-varying confounding, we estimated the causal effects of family structure on depressive symptoms using marginal structural models.Results: Older people with cumulative exposure to single-member family type had an increased odds of depressive symptoms by an average of 33 % (95 % CI: 1.22-1.44) than their counterparts who lived in the couple family. Additionally, older people living in extended families also had 6 % higher odds of experiencing depressive symptoms (95 % CI: 1.00, 1.11). The longitudinal associations were consistent across gender groups and residential areas (p-value for interaction is 0.6638 for gender and 0.7043 for the residential area). Limitation: The time-varying confounders (e.g., chronic health conditions) included in the analysis are based on self-reported data, which may be subject to measurement errors.Conclusion: The risk of depressive symptoms is greater for older individuals living alone and in extended families. Screening for depression in the older population, particularly those living in at-risk households, is recommended.

Automated summary

This study investigates the causal relationship between family structure and depressive symptoms among Chinese older adults, finding that older individuals living alone and in extended families are more likely to experience depressive symptoms. Screening for depression in the older population, particularly those living in at-risk households, is recommended.