To analyze the prevalence of multimorbidity and disability among urban and rural elderly in China, exploretheir association, and inform policy optimization.

Using the 2020 CHARLS database, descriptive analysis, chi-square tests, and Kruskal-Wallis H tests were used to depict the urban-rural differences. Cluster analysis identified multimorbidity patterns. Binary logistic regression (for BADL disability) and generalized ordered logistic regression (for IADL disability levels) were used to analyze the impact of multimorbidity patterns on disability.

Chronic disease prevalence was 88.38%, and multimorbidity prevalence was 69.84%. Urban older adults had a higher multimorbidity rate (73.27%) than their rural counterparts (68.62%). Cluster analysis identified five comorbidity patterns, with Pattern 5 (complex multimorbidity pattern) being the most prevalent (urban:39.97%, rural:28.93%). Rural older adults exhibited significantly higher proportions of moderate and severe IADL disability (11.65%, 8.04%) compared to urban residents (7.83%, 6.94%). Regression analyses demonstrated a significant association between multimorbidity and higher disability prevalence, with Pattern 5 having the strongest impact on both BADL (OR=2.87, 95% CI:2.22-3.71) and IADL (moderate disability: OR=3.16, 95% CI:2.60-3.84; severe disability: OR=2.62, 95% CI:1.98-3.47).

Multimorbidity is highly prevalent and significantly associated with disability among older adults in both urban and rural China, with the complex multimorbidity pattern (Pattern 5) showing the strongest association. Urban older adults experience more complex multimorbidity patterns, while rural older adults face more severe disability. Policy development should address urban-rural disparities through targeted health management strategies and interventions.