Combined Associations of Diabetes and Depressive Symptoms on Cognitive Impairment Risk in the Population Aged 60 or Older: Cross-Cohort Comparisons From NHANES and CHARLS

Abstract

Objective Diabetes mellitus (DM) and cognitive impairment (CoI) are correlated, but the combined impact of depressive symptoms on CoI risk in older adults remains unclear. Methods This study included 1,200 U.S. adults aged ≥60 years (National Health and Nutrition Examination Survey, NHANES) and 1,500 Chinese adults (China Health and Retirement Longitudinal Study, CHARLS). DM was defined by laboratory measures or self-report; depressive symptoms were assessed via the Patient Health Questionnaire-9 (PHQ-9) (NHANES) and CES-D-10 (CHARLS); CoI was measured using the CERAD battery (NHANES) and situational memory/mental integrity scores (CHARLS). Multivariate logistic regression estimated associations of DM and depressive symptoms with CoI. Additive interaction was evaluated by the relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (S). Restricted cubic spline (RCS) analyses examined nonlinear DM–depressive symptoms interactions. Results Both DM and depressive symptoms were independently and significantly associated with CoI. After multivariate adjustment, diabetic patients exhibited significantly increased CoI risk; depressive symptoms similarly elevated CoI risk. Interaction analysis revealed an additive effect when DM co-occurred with depressive symptoms in CHARLS but not in NHANES. Mediation analyses further suggest bidirectional associations: in CHARLS, diabetes and depressive symptoms appear to mediate each other’s effects on CoI. Additionally, RCS analysis in NHANES indicated a nonlinear interaction between depressive symptom severity (PHQ-9) and DM on CoI (p<0.05). Conclusion The observed associations varied across cohorts, with a significant additive interaction between diabetes and depressive symptoms found only in the CHARLS cohort. Integrating metabolic and mental health screening and interventions may optimize cognitive outcomes in high-risk older adult populations.