Samantha A Reina1, Maria M Llabre1, Denise C Vidot1, Carmen R Isasi2, Krista Perreira3, Mercedes Carnethon4, Christina M Parrinello2, Linda C Gallo5, Guadalupe X Ayala5, Alan Delamater1. 1. 1 Department of Psychology, University of Miami , Coral Gables, Florida. 2. 2 Department of Epidemiology & Population Health, Albert Einstein College of Medicine , Bronx, New York. 3. 3 Department of Social Medicine, University of North Carolina , Chapel Hill, North Carolina. 4. 4 Department of Preventive Medicine, Northwestern University , Chicago, Illinois. 5. 5 Department of Psychology, San Diego State University , San Diego, California.
Abstract
BACKGROUND: Metabolic syndrome (MetS), a cluster of cardiovascular risk factors, is being diagnosed in youth. Specific diagnostic criteria used to define MetS influence prevalence estimates and populations considered at risk for cardiovascular disease. The National Cholesterol Education Program's Adult Treatment Panel III (ATP), the World Health Organization (WHO), and the International Diabetes Federation (IDF) provide three MetS definitions used in medical research. This study examined concordance among these definitions in 1137 children 10-16 years of age, who participated in the Hispanic Community Children's Health Study/Study of Latino Youth. METHODS: Prevalence of MetS and of individual components was estimated using SAS. Mplus was used to test a single-factor model of MetS components (triglycerides, high-density lipoprotein cholesterol, systolic and diastolic blood pressure, waist circumference, and fasting glucose). RESULTS: The ATP definition identified most MetS cases in 10-15 (N = 19, 4.7%) and 16-year-old girls (N = 3, 7.3%). The IDF definition identified most cases of MetS in 10-15 (N = 16, 3.1%) and 16-year-old boys (N = 2, 2.8%). Fewest cases of MetS were identified with the WHO definition across age and sex groups. CONCLUSION: Only one participant was classified as having MetS across all three definitions. Confirmatory factor analysis indicated fasting glucose and systolic blood pressure did not reliably cluster with other risk factors that define MetS in Hispanic/Latino adolescents. We conclude that prevalence estimates of MetS in youth are unstable across current criteria, calling into question the accuracy of defining and diagnosing MetS in youth.
BACKGROUND:Metabolic syndrome (MetS), a cluster of cardiovascular risk factors, is being diagnosed in youth. Specific diagnostic criteria used to define MetS influence prevalence estimates and populations considered at risk for cardiovascular disease. The National Cholesterol Education Program's Adult Treatment Panel III (ATP), the World Health Organization (WHO), and the International Diabetes Federation (IDF) provide three MetS definitions used in medical research. This study examined concordance among these definitions in 1137 children 10-16 years of age, who participated in the Hispanic Community Children's Health Study/Study of Latino Youth. METHODS: Prevalence of MetS and of individual components was estimated using SAS. Mplus was used to test a single-factor model of MetS components (triglycerides, high-density lipoprotein cholesterol, systolic and diastolic blood pressure, waist circumference, and fasting glucose). RESULTS: The ATP definition identified most MetS cases in 10-15 (N = 19, 4.7%) and 16-year-old girls (N = 3, 7.3%). The IDF definition identified most cases of MetS in 10-15 (N = 16, 3.1%) and 16-year-old boys (N = 2, 2.8%). Fewest cases of MetS were identified with the WHO definition across age and sex groups. CONCLUSION: Only one participant was classified as having MetS across all three definitions. Confirmatory factor analysis indicated fasting glucose and systolic blood pressure did not reliably cluster with other risk factors that define MetS in Hispanic/Latino adolescents. We conclude that prevalence estimates of MetS in youth are unstable across current criteria, calling into question the accuracy of defining and diagnosing MetS in youth.
Authors: Carmen R Isasi; Mercedes R Carnethon; Guadalupe X Ayala; Elva Arredondo; Shrikant I Bangdiwala; Martha L Daviglus; Alan M Delamater; John H Eckfeldt; Krista Perreira; John H Himes; Robert C Kaplan; Linda Van Horn Journal: Ann Epidemiol Date: 2013-10-09 Impact factor: 3.797
Authors: Johanna L Grün; Aaron N Manjarrez-Reyna; Angélica Y Gómez-Arauz; Sonia Leon-Cabrera; Felix Rückert; José M Fragoso; Nallely Bueno-Hernández; Sergio Islas-Andrade; Guillermo Meléndez-Mier; Galileo Escobedo Journal: J Immunol Res Date: 2018-04-03 Impact factor: 4.818