Latent profile analysis of depression and its influencing factors in older adults raising grandchildren in China

Objective: To explore the latent profile of depression in older adults raising grandchildren in China, and to analyze the differences in the characteristics of the different profiles of the population and the factors influencing them. Methods: This study utilized the 2018 China Health and Retirement Longitudinal Study (CHARLS). Through a cross-sectional study, the latent profile analysis was used to analyze the potential classification of depression among older adults raising grandchildren, and using ordered multi-categorical logistic regression analyses to assess the effects of each factor on their different classifications. Results: The 1271 older adults raising grandchildren with depression symptoms were divided into three categories: low-level depression (55.4%), moderate-level depression (31.2%), and high-level depression (13.4%). Ordered multi-categorical Logistic results showed: Gender, marital status, pension insurance, physical health status, life satisfaction, and IADL were predictors of latent profile classification of depression symptoms in older adults raising grandchildren (P < 0.05). Conclusions: In the future of primary care, it will be more meaningful to provide targeted interventions for different subgroups of depression in older adults raising grandchildren. (c) 2024 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.