The prediction of Metabolic Syndrome alterations is improved by combining waist circumference and handgrip strength measurements compared to either alone
Portada
Citas bibliográficas
Código QR
Autores
Autor corporativo
Recolector de datos
Otros/Desconocido
Director audiovisual
Editor/Compilador
Editores
Tipo de Material
Fecha
Cita bibliográfica
Título de serie/ reporte/ volumen/ colección
Es Parte de
Resumen en español
Background: Adiposity is a major component of the metabolic syndrome (MetS), low muscle strength has also been identifed as a risk factor for MetS and for cardiovascular disease. We describe the prevalence of MetS and evaluate the relationship between muscle strength, anthropometric measures of adiposity, and associations with the cluster of the components of MetS, in a middle-income country. Methods: MetS was defned by the International Diabetes Federation criteria. To assess the association between anthropometric variables (waist circumference (WC), waist-to-hip ratio (W/H), body mass index (BMI)), strength (hand‑grip/kg bodyweight (HGS/BW)) and the cluster of MetS, we created a MetS score. For each alteration (high triglycer‑ides, low HDLc, dysglycemia, or high blood pressure) one point was conferred. To evaluate the association an index of fat:muscle and MetS score, participants were divided into 9 groups based on combinations of sex-specifc tertiles of WC and HGS/BW. Results: The overall prevalence of MetS in the 5,026 participants (64% women; mean age 51.2 years) was 42%. Lower HGS/BW, and higher WC, BMI, and W/H were associated with a higher MetS score. Amongst the 9 HGS/BW:WC groups, participants in the lowest tertile of HGS/BW and the highest tertile of WC had a higher MetS score (OR=4.69 in women and OR=8.25 in men;p<0.01) compared to those in the highest tertile of HGS/BW and in the lowest tertile of WC. Conclusion: WC was the principal risk factor for a high MetS score and an inverse association between HGS/BW and MetS score was found. Combining these anthropometric measures improved the prediction of metabolic alterations over either alone