Mental and physical disorders are leading contributors to global disability. However, estimates of their health-related burden often overlook the pervasive comorbidity among conditions. This study aimed to quantify the independent and combined effects of these disorders on self-rated health in nationally representative Chinese adults, explicitly accounting for comorbidity.

Data were drawn from the China Mental Health Survey (CMHS), a cross-sectional nationally representative survey. Mental disorders were assessed using the Composite International Diagnostic Interview 3.0, and physical disorders were measured through structured self-report. Health-related burden was assessed using a 0–100 visual analogue scale (VAS) of self-rated health over the past 30 days. Nested regression models examined disorder-specific and multimorbidity effects, followed by interaction-based counterfactual simulations to estimate disorder-specific burden net of comorbidity at individual and population levels.

Among 27,505 respondents included in multivariate analyses, comorbidity was highly prevalent. In crude models, all 20 disorders were associated with lower VAS scores, with the largest decrements observed for mental disorders such as generalized anxiety disorder (GAD), bipolar disorder and major depressive disorder (MDD). After accounting for disorder type and comorbidity structure, many associations were attenuated and the independent effect of disorder count became non-significant. Counterfactual simulations showed the largest individual-level burdens for GAD (–14.71), cancer (–9.02), bipolar disorder (–8.59) and MDD (–8.53). At the population level, insomnia symptoms (–1.56), arthritis (–0.81) and cardiovascular disorders (–0.64) contributed the greatest burden.

Accounting for comorbidity substantially alters estimates of disorder-specific health burden. Mental disorders impose the greatest impairment at the individual level, whereas prevalent physical conditions dominate population burden.