Depression adds a significant burden in individuals with coexisting hypertension and diabetes, particularly in middle-aged and older adults. These conditions often coexist with depressive symptoms, complicating management and accelerating functional decline. Earlier prediction models were largely designed for psychiatric populations or relied on general risk factors, limiting their applicability in chronic disease settings. Importantly, functional measures such as activities of daily living (ADL), along with behavioral and social factors, have been underrepresented despite their strong association with both physical illness and depression.

A retrospective study was aimed to develope a simple and practical tool for estimating depression risk in middle-aged and older adults with hypertension and diabetes. The study was conducted using data from the fifth wave of the China Health and Retirement Longitudinal Study (CHARLS, 2020). Adults aged >=45 years with both conditions were included. A total of 42 candidate predictors spanning clinical, psychological, and social domains were evaluated. Least absolute shrinkage and selection operator (LASSO) regression identified key predictors, while Shapley additive explanations (SHAP) values quantified their contribution.

Among 1504 participants (mean age ~66 years; 54.9% women), 42.2% were classified as having possible depression. The model demonstrated strong agreement between predicted and observed outcomes, with minimal error (0.006 in training; 0.018 in testing). Decision curve analysis showed clear clinical utility, outperforming both “treat-all” and “treat-none” strategies.

Functional impairment emerged as the strongest predictor. Participants with depression had significantly higher ADL scores (1.20 vs 0.34; P<0.001), and each unit increase in ADL score was associated with a threefold rise in depression risk, especially beyond scores >=2. Retirement showed a protective effect, with lower depression prevalence among retirees compared with nonretirees (16.2% vs 31.0%; P<0.001).

The study findings suggested that the developed nomogram, incorporating routinely collected variables, effectively stratifies depression risk in this population. Functional impairment plays a central role, highlighting the need for integrated screening and targeted interventions.

Source: Peng T, Zhang Y, Miao R, et al. Development of a Practical Nomogram for Depression Risk Stratification in Older Adults With Hypertension and Diabetes: Retrospective Analysis of Data From the China Health and Retirement Longitudinal Study. JMIR Med Inform. 2026;14:e81529.