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Heterogeneous Health Classes for Older Adults in China: Based on Multidimensional Health


 Background

The concept of health is multidimensional, so the evaluation of the health status of the elderly and the analysis of the influencing factors should also be multidimensional. This study aims to identify the heterogeneity of the health status of Chinese older adults.
Methods

Data were derived from the China Health and Retirement Longitudinal Study (CHARLS) 2015 (n = 4190). Latent class analysis was performed based on 6 health indicators, including self-reported health status, the number of chronic diseases, activity of daily living (ADL), depressive symptoms, cognitive ability, and social activities participation. Logistic regression was used to analyze the predictive effect of demographic characteristics variables on different health classes of older adults.
Results

Three health latent classes were identified and labeled as Relatively Healthy Group (n = 1003, 23.94%), Multiple Chronic Conditions with High Social Participation Group (n = 1744, 41.62%), and Frail Group (n = 1443, 34.44%). The health status of Chinese older adults is not optimistic. In particular, our study found that older adults with multiple chronic diseases had the highest social participation frequency among the three classes. When Frail Group was the reference, the logistic regression results showed that older-aged adults, those without spouses, those with low educational level, and those with agricultural household registration were more likely to be Frail Group.
Conclusion

There is heterogeneity in the health status of older adults, and identifying the health status of older adults from a multidimensional health perspective can help provide better health services to them based on health latent classes.