Objectives: To explore how clusters of chronic health problems can impact depression in older adults.

Methods: We performed a latent class analysis using the baseline data from The Brazilian Longitudinal Study of Aging (ELSI-Brazil). Depression was assessed using the Center for Epidemiological Studies Depression Scale (CES- D8). Scores of 4 or higher on the CES-D8 were considered positive for depression. Fourteen self-reported conditions (Diabetes, Systemic Arterial Hypertension, Angina, Myocardial Infarction, Chronic Kidney Disease, Heart Failure, Stroke, Low Back Pain, Arthritis, Osteoporosis, Asthma, Chronic Obstructive Pulmonary Disease, High Cholesterol, and Cancer) were evaluated and combined as a total number of chronic conditions.

Results: The total number of individuals in the sample was 4672. The best resulting model is composed of 4 latent classes. The latent classes were organized as follows: Cardiovascular Multimorbidity (Class1); No multimorbidity (Class 2); Musculoskeletal Multimorbidity (Class 3); and Inflammatory Multimorbidity (Class 4). We identified that, in comparison with class 2, (considered the reference class due to the absence of multimorbidity), the odds ratio for depression was 2.56 for the Cardiovascular Multimorbidity class, 2.86 for the Musculoskeletal Multimorbidity class, and 4.59 for the Inflammatory Multimorbidity class.

Conclusions: We found that various patterns of multimorbidity are associated with depression when compared with a single disease and that Inflammatory Multimorbidity has the greatest impact on depression.