Justin R Ryder1, Alexander M Kaizer2, Kyle D Rudser2, Stephen R Daniels3, Aaron S Kelly4. 1. Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN. 2. Division of Biostatistics, University of Minnesota School of Public Health, Minneapolis, MN. 3. Department of Pediatrics, Children's Hospital Colorado, University of Colorado School of Medicine, Aurora, CO. 4. Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN; Department of Medicine, University of Minnesota Medical School, Minneapolis, MN.
Abstract
OBJECTIVES: To determine the proportion of youth within a given body mass index (BMI) obesity category with excess adiposity using dual energy x-ray absorptiometry (DXA). Furthermore, to examine whether mean differences in cardiometabolic risk factors based upon various excess adiposity cutpoints were present. STUDY DESIGN: DXA data from the National Health and Nutrition Examination Survey 1999-2006 (n = 10 465; 8-20 years of age) were used for this analysis. Obesity categories were defined using Centers for Disease Control and prevention definitions for age and sex. Excess adiposity was defined using cohort-specific cutpoints at 75th, 85th, and 90th percentiles of DXA body fat (%) by age and sex using quantile regression models. Additionally, we examined differences in cardiometabolic risk factors among youth (BMI percentile >85th) above and below various excess adiposity cutpoints. RESULTS: Nearly all youth with class 3 obesity (100% male, 100% female; 97% male, 99% female; and 95% male, 96% female; using the 75th, 85th, and 90th DXA percentiles, respectively) and a high proportion of those with class 2 obesity (98% male, 99% female; 92% male, 91% female; and 76% male, 76% female) had excess adiposity. Significant discordance was observed between BMI categorization and DXA-derived excess adiposity among youth with class 1 obesity or overweight. Elevated cardiometabolic risk factors were present in youth with excess adiposity, regardless of the cutpoint used. CONCLUSIONS: BMI correctly identifies excess adiposity in most youth with class 2 and 3 obesity but a relatively high degree of discordance was observed in youth with obesity and overweight. Cardiometabolic risk factors are increased in the presence of excess adiposity, regardless of the cutpoint used.
OBJECTIVES: To determine the proportion of youth within a given body mass index (BMI) obesity category with excess adiposity using dual energy x-ray absorptiometry (DXA). Furthermore, to examine whether mean differences in cardiometabolic risk factors based upon various excess adiposity cutpoints were present. STUDY DESIGN: DXA data from the National Health and Nutrition Examination Survey 1999-2006 (n = 10 465; 8-20 years of age) were used for this analysis. Obesity categories were defined using Centers for Disease Control and prevention definitions for age and sex. Excess adiposity was defined using cohort-specific cutpoints at 75th, 85th, and 90th percentiles of DXA body fat (%) by age and sex using quantile regression models. Additionally, we examined differences in cardiometabolic risk factors among youth (BMI percentile >85th) above and below various excess adiposity cutpoints. RESULTS: Nearly all youth with class 3 obesity (100% male, 100% female; 97% male, 99% female; and 95% male, 96% female; using the 75th, 85th, and 90th DXA percentiles, respectively) and a high proportion of those with class 2 obesity (98% male, 99% female; 92% male, 91% female; and 76% male, 76% female) had excess adiposity. Significant discordance was observed between BMI categorization and DXA-derived excess adiposity among youth with class 1 obesity or overweight. Elevated cardiometabolic risk factors were present in youth with excess adiposity, regardless of the cutpoint used. CONCLUSIONS: BMI correctly identifies excess adiposity in most youth with class 2 and 3 obesity but a relatively high degree of discordance was observed in youth with obesity and overweight. Cardiometabolic risk factors are increased in the presence of excess adiposity, regardless of the cutpoint used.
Authors: D S Freedman; J Wang; L M Maynard; J C Thornton; Z Mei; R N Pierson; W H Dietz; M Horlick Journal: Int J Obes (Lond) Date: 2005-01 Impact factor: 5.095
Authors: Dale A Schoeller; Frances A Tylavsky; David J Baer; William C Chumlea; Carrie P Earthman; Thomas Fuerst; Tamara B Harris; Steven B Heymsfield; Mary Horlick; Timothy G Lohman; Henry C Lukaski; John Shepherd; Roger M Siervogel; Lori G Borrud Journal: Am J Clin Nutr Date: 2005-05 Impact factor: 7.045
Authors: Justin R Ryder; Michael O'Connell; Tyler A Bosch; Lisa Chow; Kyle D Rudser; Donald R Dengel; Claudia K Fox; Julia Steinberger; Aaron S Kelly Journal: Pediatr Res Date: 2015-09-21 Impact factor: 3.756
Authors: Aviva B Sopher; John C Thornton; Jack Wang; Richard N Pierson; Steven B Heymsfield; Mary Horlick Journal: Pediatrics Date: 2004-05 Impact factor: 7.124
Authors: Carolyn T Bramante; Elise F Palzer; Kyle D Rudser; Justin R Ryder; Claudia K Fox; Eric M Bomberg; Megan O Bensignor; Amy C Gross; Nancy E Sherwood; Aaron S Kelly Journal: Int J Obes (Lond) Date: 2021-10-30 Impact factor: 5.551
Authors: Megan O Bensignor; Eric M Bomberg; Carolyn T Bramante; T V S Divyalasya; Paula M Hale; Chethana K Ramesh; Kyle D Rudser; Aaron S Kelly Journal: Pediatr Obes Date: 2021-02-25 Impact factor: 3.910
Authors: Amber L Fyfe-Johnson; Justin R Ryder; Alvaro Alonso; Richard F MacLehose; Kyle D Rudser; Claudia K Fox; Amy C Gross; Aaron S Kelly Journal: J Am Heart Assoc Date: 2018-04-13 Impact factor: 5.501
Authors: Taumoha Ghosh; Michaela Richardson; Peter M Gordon; Justin R Ryder; Logan G Spector; Lucie M Turcotte Journal: Cancer Med Date: 2020-07-24 Impact factor: 4.452
Authors: David Monasor-Ortolá; Jose Antonio Quesada-Rico; Ana Pilar Nso-Roca; Mercedes Rizo-Baeza; Ernesto Cortés-Castell; Asier Martínez-Segura; Francisco Sánchez-Ferrer Journal: Int J Environ Res Public Health Date: 2021-11-18 Impact factor: 3.390