Empirical analysis of health-related behaviors among older Hakka adults: a latent class analysis.

Background: Little is known about health-related behaviors of the older Hakka population in China. We aimed to explore the characteristics and correlates of health-related behaviors among older Hakka adults.

Methods: We used data from the China's Health-Related Quality of Life Survey for Older Adults 2018. Latent class analysis (LCA) defined latent classes of health-related behaviors for 1,262 older Hakka adults aged 60 and above. Generalized linear regression and multinomial logistic regression analysis were used to identify factors influencing the number and the latent classes of health-related behaviors, respectively.

Results: The LCA showed that the latent classes could be stratified as the risk group (14.82%), healthy group (55.71%), and inactive group (29.48%). Sex, age, years of education, current residence, living arrangement, average annual household income, and currently employed were associated with the number of healthy behaviors. Compared with the participants in the healthy group, widowed/others ( = 5.85, 95%  = 3.27, 10.48), had 15,001-30,000 ( = 2.05, 95%  = 1.21, 3.47) and 60,001 or higher ( = 3.78, 95%  = 1.26, 11.36) average annual household income, and currently employed ( = 3.40, 95%  = 1.99, 5.81) were highly associated with risk group. Additionally, the participants who are widowed/others ( = 4.30, 95%  = 2.70, 6.85) and currently employed ( = 1.95, 95%  = 1.27, 2.98) were highly associated with the inactive group.

Conclusion: This study identified factors specifically associated with older Hakka adults' health-related behaviors from an LCA perspective. The findings indicate that policymakers should give more attention to older adults living alone and implement practical interventions to promote health-related behaviors among them.