Differential risk profiles for geriatric depression, anxiety, and sleep disturbances in rural China: insights from the Taierzhuang cohort.

Background: Mental health disorders among older adults in rural China present substantial public health challenges, yet their differential risk factors and practical screening tools remain understudied. Methods: We analyzed data from 4,180 participants in the Taierzhuang Aging Cohort. Using multivariate logistic regression, we identified independent risk factors for depression, anxiety, and insomnia. Predictor variables were confirmed to be sufficiently independent by evaluating bivariate correlations, variance inflation factors, and linearity in the logit. Corresponding nomograms were developed for risk prediction. Results: The prevalence of anxiety symptoms, depressive symptoms, and insomnia was 22.1%, 22.7%, and 29.5%, respectively. Multivariate analysis revealed distinct risk profiles for each condition: the absence of a chronic disease (OR: 1.57; 95% CI: 1.28-1.94) and older age were independent predictors of depressive symptoms; while a poor spousal relationship (OR: 1.55; 95% CI: 1.11-2.16) was a risk factor for anxiety symptoms, while physical activity 1-2 times/week (vs. ≥3 times/week: OR = 0.69; 95% CI: 0.53-0.90) was associated with decreased risk; inconstrast, female gender (OR: 1.33; 95% CI: 1.06-1.67) and lower exercise frequency were significantly associated with insomnia. Based on these findings, we developed three clinical prediction nomograms that integrate these independent predictors to facilitate individualized risk assessment. Conclusion: This study establishes distinct risk profiles for common mental health conditions in rural Chinese older adults and provides practical nomograms for risk assessment in primary care settings, facilitating targeted prevention strategies for these under-served populations.