Jose P Lopez-Lopez1,2, Daniel D Cohen2, Daniela Ney-Salazar1, Daniel Martinez2, Johanna Otero2, Diego Gomez-Arbelaez2, Paul A Camacho1, Gregorio Sanchez-Vallejo3, Edgar Arcos4, Claudia Narvaez5, Henry Garcia6, Maritza Perez7, Dora I Molina8, Carlos Cure9, Aristides Sotomayor10, Álvaro Rico11, Eric Hernandez-Triana12, Myriam Duran2, Fresia Cotes13, Darryl P Leong14, Sumathy Rangarajan14, Salim Yusuf14, Patricio Lopez-Jaramillo15,16. 1. Institute Masira, Medical School, Universidad de Santander, Santander, Colombia. 2. Facultad de Ciencias de La Salud, Instituto de Investigaciones Masira, Universidad de Santander (UDES), Bloque G, piso 6. Bucaramanga, Santander, Colombia. 3. Universidad del Quindío and Hospital San Juan de Dios de Armenia, Armenia, Quindío, Colombia. 4. Fundación Cometa, Pasto, Colombia. 5. Hospital Susana López, Popayán, Colombia. 6. Fundación RIESCAR, El Espinal, Colombia. 7. Facultad de Medicina, Universidad Militar Nueva Granada, Bogotá, Colombia. 8. Universidad de Caldas y Médicos Internistas de Caldas, Manizales, Colombia. 9. BIOMELAB Research Center, Barranquilla, Colombia. 10. Centro Cardiovascular Santa Lucia, Cartagena, Colombia. 11. FINDEMOS, Yopal, Colombia. 12. ENDOCARE, Bogotá, Colombia. 13. Universidad de Santander, Valledupar, Colombia. 14. PHRI, McMaster University, Hamilton, ON, Canada. 15. Institute Masira, Medical School, Universidad de Santander, Santander, Colombia. jplopezj@gmail.com. 16. Facultad de Ciencias de La Salud, Instituto de Investigaciones Masira, Universidad de Santander (UDES), Bloque G, piso 6. Bucaramanga, Santander, Colombia. jplopezj@gmail.com.
Abstract
BACKGROUND: Adiposity is a major component of the metabolic syndrome (MetS), low muscle strength has also been identified 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 defined 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 (handgrip/kg bodyweight (HGS/BW)) and the cluster of MetS, we created a MetS score. For each alteration (high triglycerides, 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-specific 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.
BACKGROUND: Adiposity is a major component of the metabolic syndrome (MetS), low muscle strength has also been identified 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 defined 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 (handgrip/kg bodyweight (HGS/BW)) and the cluster of MetS, we created a MetS score. For each alteration (high triglycerides, 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-specific 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.
Entities:
Keywords:
Abdominal obesity; Body mass index; Cardiovascular disease; Handgrip strength; Metabolic syndrome
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