Portal de Periódicos da CAPES

Artigo Acesso aberto Produção Nacional Revisado por pares

BIBTEX RIS

Patterns of metabolic syndrome and associated factors in women from the ELSA-Brasil: a latent class analysis approach

2023; Escola Nacional de Saúde Pública, Fundação Oswaldo Cruz; Volume: 39; Issue: 12 Linguagem: Inglês

10.1590/0102-311xen039923

1678-4464

Nila Mara Smith Galvão Bahamonde, Sheila Maria Alvim Matos, Maria da Conceição Chagas de Almeida, Lígia Gabrielli, Sandhi Maria Barreto, Estela M. L. Aquino, María Inês Schmidt, Leila Denise Alves Ferreira Amorim,

Cardiovascular Health and Risk Factors

This study aimed to identify patterns of metabolic syndrome among women and estimate their prevalence and relationship with sociodemographic and biological characteristics. In total, 5,836 women were evaluated using baseline data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Patterns of metabolic syndrome were defined via latent class analysis, using the following metabolic abnormalities as indicators: abdominal obesity, hyperglycemia, hypertension, hypertriglyceridemia, and reduced HDL cholesterol. The relationship between these patterns and individual characteristics was assessed using latent class analysis with covariates. Three patterns of metabolic syndrome were identified: high metabolic expression, moderate metabolic expression, and low metabolic expression. The first two patterns represented most women (53.8%) in the study. Women with complete primary or secondary education and belonging to lower social classes were more likely to have higher metabolic expression. Black and mixed-race women were more likely to have moderate metabolic expression. Menopausal women aged 50 years and older were more often classified into patterns of greater health risk. This study addressed the heterogeneous nature of metabolic syndrome, identifying three distinct profiles for the syndrome among women. The combination of abdominal obesity, hyperglycemia, and hypertension represents the main metabolic profile found among ELSA-Brasil participants. Sociodemographic and biological factors were important predictors of patterns of metabolic syndrome.