Latent dimension of comorbidities and depression in older adults: a cross-sectional study using National Health Survey data, Brazil, 2019

Abstract

Abstract Objective: To build a latent dimension of comorbidities and assess its association with depression among older Brazilian adults. Methods: This was a cross-sectional study using Brazilian National Health Survey 2019 data, including individuals aged 60 years or older. The latent dimension of comorbidities was built based on five self-reported conditions: hypertension, diabetes mellitus, high cholesterol, coronary artery disease and stroke. Generalized Structural Equation Modeling (GSEM) was employed. Prevalence ratios (PR) and 95% confidence intervals (95%CI) were estimated using Poisson regression with robust variance. Results: A total of 22,705 older adults were analyzed, whereby prevalence of depression was 11.8%. Hypertension was the most frequent condition (56.4%). The latent dimension of comorbidities showed strong positive association with depression (PR 12.61; 95%CI 11.59; 12.65). Outcome prevalence was higher among women (PR 2.82; 95%CI 2.55; 3.12) and those with higher income (PR 1.11-1.16), whereas advancing age was inversely associated with depression (PR 0.98; 95%CI 0.97; 0.99). Conclusion: Depression among older Brazilian adults was significantly associated with comorbidity burden, female sex, age and income. Latent dimension modeling contributed to an integrated understanding of chronic conditions, revealing that the accumulation of these pathologies has a substantial impact on the mental health of this population, reinforcing the need for multiprofessional and integrated approaches to elderly care within the Brazilian Unified Health System.