OBJECTIVES: To compare the diagnostic performance of the Centers for Disease Control and Prevention (CDC) and FITNESSGRAM (FGram) BMI standards for quantifying metabolic risk in youth. METHODS: Adolescents in the NHANES (n = 3385) were measured for anthropometric variables and metabolic risk factors. BMI percentiles were calculated, and youth were categorized by weight status (using CDC and FGram thresholds). Participants were also categorized by presence or absence of metabolic syndrome. The CDC and FGram standards were compared by prevalence of metabolic abnormalities, various diagnostic criteria, and odds of metabolic syndrome. Receiver operating characteristic curves were also created to identify optimal BMI percentiles to detect metabolic syndrome. RESULTS: The prevalence of metabolic syndrome in obese youth was 19% to 35%, compared with <2% in the normal-weight groups. The odds of metabolic syndrome for obese boys and girls were 46 to 67 and 19 to 22 times greater, respectively, than for normal-weight youth. The receiver operating characteristic analyses identified optimal thresholds similar to the CDC standards for boys and the FGram standards for girls. Overall, BMI thresholds were more strongly associated with metabolic syndrome in boys than in girls. CONCLUSIONS: Both the CDC and FGram standards are predictive of metabolic syndrome. The diagnostic utility of the CDC thresholds outperformed the FGram values for boys, whereas FGram standards were slightly better thresholds for girls. The use of a common set of thresholds for school and clinical applications would provide advantages for public health and clinical research and practice.
OBJECTIVES: To compare the diagnostic performance of the Centers for Disease Control and Prevention (CDC) and FITNESSGRAM (FGram) BMI standards for quantifying metabolic risk in youth. METHODS: Adolescents in the NHANES (n = 3385) were measured for anthropometric variables and metabolic risk factors. BMI percentiles were calculated, and youth were categorized by weight status (using CDC and FGram thresholds). Participants were also categorized by presence or absence of metabolic syndrome. The CDC and FGram standards were compared by prevalence of metabolic abnormalities, various diagnostic criteria, and odds of metabolic syndrome. Receiver operating characteristic curves were also created to identify optimal BMI percentiles to detect metabolic syndrome. RESULTS: The prevalence of metabolic syndrome in obese youth was 19% to 35%, compared with <2% in the normal-weight groups. The odds of metabolic syndrome for obeseboys and girls were 46 to 67 and 19 to 22 times greater, respectively, than for normal-weight youth. The receiver operating characteristic analyses identified optimal thresholds similar to the CDC standards for boys and the FGram standards for girls. Overall, BMI thresholds were more strongly associated with metabolic syndrome in boys than in girls. CONCLUSIONS: Both the CDC and FGram standards are predictive of metabolic syndrome. The diagnostic utility of the CDC thresholds outperformed the FGram values for boys, whereas FGram standards were slightly better thresholds for girls. The use of a common set of thresholds for school and clinical applications would provide advantages for public health and clinical research and practice.
Authors: Paula F Rosenbaum; Ruth S Weinstock; Allen E Silverstone; Andreas Sjödin; Marian Pavuk Journal: Environ Int Date: 2017-08-02 Impact factor: 9.621
Authors: Katrina D DuBose; Andrew J McKune; Patricia Brophy; Gabriel Geyer; Robert C Hickner Journal: Pediatr Exerc Sci Date: 2015-04-22 Impact factor: 2.333
Authors: Emelia J Benjamin; Michael J Blaha; Stephanie E Chiuve; Mary Cushman; Sandeep R Das; Rajat Deo; Sarah D de Ferranti; James Floyd; Myriam Fornage; Cathleen Gillespie; Carmen R Isasi; Monik C Jiménez; Lori Chaffin Jordan; Suzanne E Judd; Daniel Lackland; Judith H Lichtman; Lynda Lisabeth; Simin Liu; Chris T Longenecker; Rachel H Mackey; Kunihiro Matsushita; Dariush Mozaffarian; Michael E Mussolino; Khurram Nasir; Robert W Neumar; Latha Palaniappan; Dilip K Pandey; Ravi R Thiagarajan; Mathew J Reeves; Matthew Ritchey; Carlos J Rodriguez; Gregory A Roth; Wayne D Rosamond; Comilla Sasson; Amytis Towfighi; Connie W Tsao; Melanie B Turner; Salim S Virani; Jenifer H Voeks; Joshua Z Willey; John T Wilkins; Jason Hy Wu; Heather M Alger; Sally S Wong; Paul Muntner Journal: Circulation Date: 2017-01-25 Impact factor: 29.690
Authors: Maria Cristina C Kuschnir; Katia Vergetti Bloch; Moyses Szklo; Carlos Henrique Klein; Laura Augusta Barufaldi; Gabriela de Azevedo Abreu; Beatriz Schaan; Gloria Valeria da Veiga; Thiago Luiz Nogueira da Silva; Maurício T L de Vasconcellos; Ana Júlia Pantoja de Moraes; Ana Luíza Borges; Ana Mayra Andrade de Oliveira; Bruno Mendes Tavares; Cecília Lacroix de Oliveira; Cristiane de Freitas Cunha; Denise Tavares Giannini; Dilson Rodrigues Belfort; Eduardo Lima Santos; Elisa Brosina de Leon; Elizabeth Fujimori; Elizabete Regina Araújo Oliveira; Erika da Silva Magliano; Francisco de Assis Guedes Vasconcelos; George Dantas Azevedo; Gisela Soares Brunken; Isabel Cristina Britto Guimarães; José Rocha Faria Neto; Juliana Souza Oliveira; Kenia Mara B de Carvalho; Luis Gonzaga de Oliveira Gonçalves; Maria Inês Monteiro; Marize M Santos; Pascoal Torres Muniz; Paulo César B Veiga Jardim; Pedro Antônio Muniz Ferreira; Renan Magalhães Montenegro; Ricardo Queiroz Gurgel; Rodrigo Pinheiro Vianna; Sandra Mary Vasconcelos; Stella Maris Seixas Martins; Tamara Beres Lederer Goldberg Journal: Rev Saude Publica Date: 2016-02-23 Impact factor: 2.106