Correlates of Mental Illness and Health Categories among Older Adults in China: An Empirical Study Based on the Two Continua Model

Abstract

ABSTRACTObjective: Keyes’ two continua model is a useful concept in which mental health and mental illness exist on two separate axes. Based on this model, this study examined the prevalence and correlates of three mental health categories among older adults in China.Methods: Cross-sectional data were derived from Wave 1 of the Study on Global AGEing and Adult Health. Participants were categorized into complete mental health (CMH), complete mental illness (CMI), and moderate mental health (MMH) groups. Multinomial logistic regressions were used.Results: The prevalence of CMH, CMI, and MMH in China was 18%, 16%, and 66%, respectively. Being female, unmarried, younger, and feeling unhealthy were more likely to result in placement in the CMI category. Employment, education, and cognitive function were identified as important protective factors of CMH. Age, income, urban or rural residence, and physical function difficulty were associated with all three categories.Discussion: We demonstrated the utility of the two continua model in identifying mental health needs in Chinese contexts. The findings suggest that future policy reforms and clinical interventions should establish a more comprehensive mental health category as a screening tool nationwide. The promotion of social engagement could play an important role in treating mental illness and improving positive mental health.