Prevalence and determinants of multimorbidity in older Chinese adults: a nationwide cross-sectional study using CLASS data

Background Multimorbidity, the coexistence of two or more chronic conditions, is rising in China’s aging population, with limited data on prevalence and regional drivers. Methods Using 2020 China Longitudinal Aging Social Survey data for adults aged ≥ 60, supplemented by official regional statistics, we defined multimorbidity from 22 self-reported conditions. A Generalized Linear Mixed Model (GLMM) with village/community-level random effects was used to identify individual-level correlates of multimorbidity, while Random Forests (RF) evaluated county-level determinants. Results Among 11,372 participants (mean [Standard Deviation, SD] 71.6 [6.6] years), 46.03% had multimorbidity. Higher odds of multimorbidity were associated with older age (Odds Ratio [OR] = 2.24; 95% Confidence Interval [CI] 1.81–2.76), female (OR = 1.32; 95% CI 1.20–1.45), receiving ≥ 3 social security benefits (OR = 1.64; 95% CI 1.09–2.48), and obesity (OR = 1.90; 95% CI 1.48–2.44). Lower odds were associated with higher educational level (OR = 0.55; 95% CI 0.39–0.75), being physically active (OR = 0.66; 95% CI 0.56–0.77), better access to medical institutions (OR = 0.67; 95% CI 0.45–0.99) and beds (OR = 0.55; 95% CI 0.37–0.80). Random Forests prioritized physical activity, disposable income, sleep duration, social security benefits, and Body Mass Index (BMI) as top county-level associated factors. Conclusions These insights advocate optimizing medical resources, bolstering primary care, and fostering healthy lifestyles to reduce the burden of multimorbidity among older Chinese adults.