Silmara Salete de Barros Silva Mastroeni1,2, Marco Fabio Mastroeni2,3, John Paul Ekwaru2, Solmaz Setayeshgar2, Paul J Veugelers2, Muryel de Carvalho Gonçalves4, Patrícia Helen de Carvalho Rondó5. 1. Departamento de Educação Física, Universidade da Região de Joinville (Univille), Joinville, SC, Brasil. 2. Population Health Intervention Research Unit, School of Public Health, University of Alberta, Edmonton, Alberta, Canada. 3. Programa de Pós-Graduação em Saúde e Meio Ambiente, Universidade da Região de Joinville (Univille), Joinville, SC, Brasil. 4. Departamento de Ciências Biológicas, Universidade da Região de Joinville (Univille), Joinville, SC, Brasil. 5. Departamento de Nutrição, Faculdade de Saúde Pública, Universidade de São Paulo (FSP-USP), São Paulo, SP, Brasil.
Abstract
OBJECTIVE: To identify which anthropometric measurement would be the best predictor of metabolic syndrome (MetS) in Brazilian adolescents. SUBJECTS AND METHODS: Cross-sectional study conducted on 222 adolescents (15-17 years) from a city in southern Brazil. Anthropometric, physical activity, blood pressure and biochemical parameters were investigated. MetS criteria were transformed into a continuous variable (MetS score). Linear regression analyses were performed to assess the associations of BMI, hip circumference, neck circumference (NC), triceps skinfold, subscapular skinfold and body fat percentage with MetS score. ROC curves were constructed to determine the cutoff for each anthropometric measurement. RESULTS: The prevalence of MetS was 7.2%. Each anthropometric measurement was significantly (p < 0.001) associated with MetS score. After adjusting for potential confounding variables (age, sex, physical activity, and maternal education), the standardized coefficients of NC and body fat percentage appeared to have the strongest association (beta = 0.69 standard deviation) with MetS score. The regression of BMI provided the best model fit (adjusted R2 = 0.31). BMI predicted MetS with high sensitivity (100.0%) and specificity (86.4%). CONCLUSIONS: Our results suggest that BMI and NC are effective screening tools for MetS in adolescents. The early diagnosis of MetS combined with targeted lifestyle interventions in adolescence may help reduce the burden of cardiovascular diseases and diabetes in adulthood.
OBJECTIVE: To identify which anthropometric measurement would be the best predictor of metabolic syndrome (MetS) in Brazilian adolescents. SUBJECTS AND METHODS: Cross-sectional study conducted on 222 adolescents (15-17 years) from a city in southern Brazil. Anthropometric, physical activity, blood pressure and biochemical parameters were investigated. MetS criteria were transformed into a continuous variable (MetS score). Linear regression analyses were performed to assess the associations of BMI, hip circumference, neck circumference (NC), triceps skinfold, subscapular skinfold and body fat percentage with MetS score. ROC curves were constructed to determine the cutoff for each anthropometric measurement. RESULTS: The prevalence of MetS was 7.2%. Each anthropometric measurement was significantly (p < 0.001) associated with MetS score. After adjusting for potential confounding variables (age, sex, physical activity, and maternal education), the standardized coefficients of NC and body fat percentage appeared to have the strongest association (beta = 0.69 standard deviation) with MetS score. The regression of BMI provided the best model fit (adjusted R2 = 0.31). BMI predicted MetS with high sensitivity (100.0%) and specificity (86.4%). CONCLUSIONS: Our results suggest that BMI and NC are effective screening tools for MetS in adolescents. The early diagnosis of MetS combined with targeted lifestyle interventions in adolescence may help reduce the burden of cardiovascular diseases and diabetes in adulthood.
Authors: Sonimar de Souza; João Francisco de Castro Silveira; Kelin Cristina Marques; Anelise Reis Gaya; Silvia Isabel Rech Franke; Jane Dagmar Pollo Renner; James Philip Hobkirk; Sean Carroll; Cézane Priscila Reuter Journal: BMC Pediatr Date: 2022-06-02 Impact factor: 2.567
Authors: Rawan G Muhanna; Ghadeer S Aljuraiban; Najwa K Almadani; Mohammed Alquraishi; Mohamed S El-Sharkawy; Mahmoud M A Abulmeaty Journal: Healthcare (Basel) Date: 2022-02-23