Identifying multimorbidity clusters among Brazilian older adults using network analysis: Findings and perspectives.

Abstract

In aging populations, multimorbidity (MM) is a significant challenge for health systems, however there are scarce evidence available in Low- and Middle-Income Countries, particularly in Brazil. A national cross-sectional study was conducted with 11,177 Brazilian older adults to evaluate the occurrence of MM and related clusters in Brazilians aged ≥ 60 years old. MM was assessed by a list of 16 physical and mental morbidities and it was defined considering ≥ 2 morbidities. The frequencies of MM and its associated factors were analyzed. After this initial approach, a network analysis was performed to verify the occurrence of clusters of MM and the network of interactions between coexisting morbidities. The occurrence of MM was 58.6% (95% confidence interval [CI]: 57.0–60.2). Hypertension (50.6%) was the most frequent morbidity and it was present all combinations of morbidities. Network analysis has demonstrated 4 MM clusters: 1) cardiometabolic; 2) respiratory + cancer; 3) musculoskeletal; and 4) a mixed mental illness + other diseases. Depression was the most central morbidity in the model according to nodes’ centrality measures (strength, closeness, and betweenness) followed by heart disease, and low back pain. Similarity in male and female networks was observed with a conformation of four clusters of MM and cancer as an isolated morbidity. The prevalence of MM in the older Brazilians was high, especially in female sex and persons living in the South region of Brazil. Use of network analysis could be an important tool for identifying MM clusters and address the appropriate health care, research, and medical education for older adults in Brazil.