Homeostasis model assessment of insulin resistance (HOMA-IR) and metabolic syndrome at baseline of a multicentric Brazilian cohort : ELSA-Brasil study

• Autor(a) principal: Diniz, Maria de Fátima Haueisen Sander
• Data de Publicação: 2020
• Outros Autores: Beleigoli, Alline Maria Rezende, Schmidt, Maria Inês, Duncan, Bruce Bartholow, Ribeiro, Antônio Luiz Pinho, Vidigal, Pedro Guatimosim, Benseñor, Isabela Judith Martins, Lotufo, Paulo Andrade, Santos, Itamar de Souza, Griep, Rosane Harter, Barreto, Sandhi Maria
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRGS
• Texto Completo: http://hdl.handle.net/10183/230473
• topic: Estudos de coortes; Síndrome metabólica; Resistência à insulina; Metabolic syndrome; Insulin resistance; Cohort studies

Homeostasis model assessment of insulin resistance (HOMA-IR) is a method to measure insulin resistance. HOMA-IR cut-offs for identifying metabolic syndrome might vary across populations and body mass index (BMI) levels. We aimed to investigate HOMA-insulin resistance cut-offs that best discriminate individuals with insulin resistance and with metabolic syndrome for each BMI category in a large sample of adults without diabetes in the baseline of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Among the 12,313 participants with mean age of 51.2 (SD 8.9) years, the prevalence of metabolic syndrome was 34.6%, and 60.1% had overweight or obesity. The prevalence of metabolic syndrome among normal weight, overweight and obesity categories were, respectively, 13%, 43.2% and 60.7%. The point of maximum combined sensitivity and specificity of HOMA-IR to discriminate the metabolic syndrome was 2.35 in the whole sample, with increasing values at higher BMI categories. This investigation contributes to better understanding HOMA-IR values associated with insulin resistance and metabolic syndrome in a large Brazilian adult sample, and that use of cut-off points according to ROC curve may be the better strategy. It also suggests that different values might be appropriate across BMI categories.