Background: With rapid population ageing, depressive symptoms in older adults have become a pressing public health concern. While functional dependency is a known risk factor, the impact of changes in dependency over time remains unclear. Objective: To examine the association between changes in daily living dependency and incident depressive symptoms in older adults across international cohorts. Methods: We used data from 46 327 adults aged ≥50 years across four longitudinal ageing studies: China Health and Retirement Longitudinal Study (China), Health and Retirement Study (USA), English Longitudinal Study of Ageing (England) and Survey of Health, Ageing and Retirement in Europe (Europe). Daily living dependency was classified into three levels based on difficulties in activities of daily living (ADLs) and instrumental ADLs (IADLs). Change in dependency was assessed using baseline and 2-year follow-up data. Depressive symptoms were measured using the Center for Epidemiologic Studies depressive symptoms Scale or the European Depression Scales (EURO-D). Cox proportional hazard models estimated HRs and 95% CIs for incident depressive symptoms over a median follow-up of 4.2–5.1 years. Findings: A total of 12 902 new depressive symptom cases occurred during follow-up. Compared with participants whose dependency status remained unchanged, those who recovered to independency had a significantly reduced risk of depressive symptoms. Functional deterioration, including transitions from independency to ADL or IADL dependency, was associated with increased risk of depressive symptoms (both pooled HRs 1.55), while functional improvement, from ADL or IADL dependency to independency, was linked to reduced risk (HRs 0.83 and 0.80, respectively). Conclusions: Improvement in ADL dependency is linked to a lower risk of depressive symptoms, while worsening dependency significantly increases depressive symptoms risk. Clinical implications: Routine assessment of functional status and early interventions to maintain or restore daily living independency may help prevent depressive symptoms in older adults. Targeted rehabilitation and support services could play a key role in reducing the mental health burden of ageing populations.

While comorbid depression and stroke are a major concern for public health, the effect of dietary nutrient patterns on their concurrent occurrence is still largely unexplored. From NHANES, a survey of the U.S. civilian, non‐institutionalized population, we included 814 participants with complete data on diet, depression, and stroke. Of these, 140 were identified with comorbid depression and stroke. Baseline characteristics were compared between groups, and Weighted Quantile Sum (WQS) regression was used to evaluate the collective effects of nutrient mixtures. Machine learning models aimed at predicting comorbid conditions were developed, incorporating Synthetic Minority Oversampling Technique (SMOTE) for oversampling and Boruta for selecting features. The interpretability of these models was analyzed using SHapley Additive exPlanations (SHAP) and Local Interpretable Model‐agnostic Explanations (LIME). Participants with comorbidities were younger and had lower socioeconomic status, along with reduced intake of thiamin, vitamin B6, total folate, added vitamin B12, and vitamin C. Although neither WQS‐negative nor WQS‐positive indices showed statistically significant associations with comorbidity risk, specific nutrients such as alcohol, alpha‐carotene, added vitamin B12, theobromine, and vitamin E emerged as predominant contributors within the mixture models. The Random Forest classifier achieved the highest area under the receiver operating characteristic curve (AUC = 0.945) when adjusted for covariates and maintained consistently high performance in the unadjusted setting. SHAP and LIME analyses consistently identified vitamin B1, vitamin B12, zinc, vitamin C, and caffeine as influential predictors, with SHAP plots revealing mirrored feature contribution patterns depending on comorbidity status. Covariate adjustment improved directional stability and interpretability, particularly in SHAP dependence plots and waterfall visualizations. LIME explanations at the individual level corroborated these findings, showing consistent yet class‐dependent feature effects. Although the overall mixture effect was not significant, machine learning identified nutrient‐specific signals associated with comorbid depression and stroke. These results indicate that integrating dietary indicators with explainable artificial intelligence may improve transparency in risk prediction and guide future longitudinal and interventional research.

The study’s objective was to assess the connection between ramelteon usage and mortality from any cause in ischemic stroke patients in the intensive care unit (ICU). Utilizing the MIMIC-IV database, we analyzed a cohort of adult patients who had been diagnosed with ischemic stroke. During their time in the hospital, patients were sorted into ramelteon and non-ramelteon groups according to drug exposure. To achieve balance in baseline covariates, propensity score matching (PSM) was utilized. The primary focus was on mortality from all causes over 28 days, with secondary focuses on all-cause mortality over 90 and 365 days. Using Cox proportional hazards models, hazard ratios (HR) and 95% confidence intervals (CI) were estimated, taking into account potential confounding factors. Subgroup analyses were done to assess effect modification across clinical strata. The study encompassed 3413 patients, with 535 pairs matched after PSM. Ramelteon use was significantly associated with decreased 28-day all-cause mortality rates both before and after PSM, with adjusted HR of 0.34 and 0.23, both with P < 0.001. The fully adjusted post-PSM models showed similar protective associations for 90-day (HR = 0.43) and 365-day (HR = 0.55) all-cause mortality, both with P < 0.001. Prolonged use of ramelteon for more than 14 days and cumulative doses exceeding 300 mg were consistently linked to lower all-cause mortality at all time intervals. Through subgroup and sensitivity analyses, the associations were confirmed to be consistent across different clinical strata. In critically ill patients with ischemic stroke, ramelteon usage was independently associated with lower short- and long-term all-cause mortality. Graphical Abstract