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Prevalence and determinants of multimorbidity in older Chinese adults: a nationwide cross-sectional study using CLASS
Yi Li1, Chenxi Zhao2,3, Xinhao Zhuang1
1Capital University of Physical Education and Sports, Beijing, 100191, China.
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.