Background: Nowadays, the "Healthy China" and "Actively Addressing Population Aging" are two important national strategies in China. Promoting high-quality development of demand-driven older adults health services is an important way to achieve these strategies. From the perspective of active ageing, assessing the health status of older adults from multiple dimensions becomes crucial as it helps identify their specific health service needs, intervention measures, and health policies tailored to this population.
Methods: Data were derived from the China Health and Retirement Longitudinal Study (CHARLS) wave 4 (2018). A total of 4190 older adults (aged ≥60 years) were included as the analysis sample. Latent class analysis was performed to categorize older adults based on 6 health indicators, including Activities of Daily Living (ADLs), Instrumental Activities of Daily Living (IADLs), doctor diagnosed chronic diseases, depressive symptoms, cognitive function, and social participation. Multinomial logistic model was used to explore determinants associated with the various patterns of multidimensional health of older adults.
Results: The multidimensional health of older people was classified into three latent classes: Relatively Healthy (Class 1, n = 2806, 66.97%), Highly Depressed and Relatively Health Risk (Class 2, n = 1189, 28.38%), and Functional Impairment (Class 3, n = 195, 4.65%). Gender, age, education, marital status, number of children, alcohol consumption, physical activity, savings, residence, air quality satisfaction, and medical service satisfaction had significant effects on the attribution of all multidimensional health latent classes.
Conclusion: Heterogeneous and multidimensional health classes exist in China's older population, and these classes are influenced by a variety of factors and to varying degrees. Policymakers and healthcare providers can use these evidence to further address the diverse needs of older adults and improve older-care health services, ultimately achieving the goal of Active Ageing and Healthy China.
Keywords: Active ageing; Latent class analysis; Multidimensional health; Older adults.
© 2023 The Authors. Published by Elsevier Ltd.