Bidirectional relationships between cognition and depressive symptoms and effects of sociodemographic and lifestyle factors: random-intercept, cross-lagged panel model

认知与抑郁症状之间的双向关系以及社会人口学和生活方式因素的影响:随机截距交叉滞后面板模型

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Abstract

BACKGROUND: Existing panel studies on the relationships between cognition and depressive symptoms did not systematically separate between- and within-person components, with measurement time lags that are too long for precise assessment of dynamic within-person relationships. AIMS: To investigate the bidirectional relationships between cognition and depressive symptoms and examine the effects of sociodemographic characteristics and lifestyle factors via random-intercept, cross-lagged panel modelling (RI-CLPM) in middle-aged and older adults. METHOD: The sample comprised 24 425 community-based residents aged 45 years or above, recruited via five waves of the China Health and Retirement Longitudinal Study (2011-2020). Cognition was evaluated using the Telephone Interview of Cognition Status, and depressive symptoms were assessed by the ten-item Center for Epidemiologic Studies Depression Scale. RI-CLPM included sociodemographic and lifestyle factors as time-invariant and -varying covariates. Subgroup analysis was conducted across gender, age groups and urban/rural regions. RESULTS: RI-CLPM showed a superior fit to cross-lagged panel models. Male, higher education, married, urban region, non-smoking, currently working and participation in social activities were linked with better cognition and fewer depressive symptoms. Overall, cognition and depressive symptoms showed significant and negative bidirectional cross-lagged effects over time. Despite similar cross-lagged effects across gender, subgroup analysis across urbanicity found that cross-lagged effects were not significant in urban regions. CONCLUSIONS: The present study provided nuanced results on negative bidirectional relationships between cognition and depressive symptoms in Chinese middle-aged and older adults. Our results highlight the health disparities in cognitive and emotional health across urbanicity and age groups.

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