Amy A. Rydin, Cameron Severn, Laura Pyle, Nazeen Morelli, Ashley H. Shoemaker, Stephanie T. Chung, Jack A. Yanovski, Joan C. Han, Janine A. Higgins, Kristen J. Nadeau, Claudia Fox, Aaron S. Kelly, Melanie G. Cree
{"title":"Prediction of resting energy expenditure for adolescents with severe obesity: A multi-centre analysis","authors":"Amy A. Rydin, Cameron Severn, Laura Pyle, Nazeen Morelli, Ashley H. Shoemaker, Stephanie T. Chung, Jack A. Yanovski, Joan C. Han, Janine A. Higgins, Kristen J. Nadeau, Claudia Fox, Aaron S. Kelly, Melanie G. Cree","doi":"10.1111/ijpo.13123","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background and Objectives</h3>\n \n <p>Resting energy expenditure (REE) assessments can help inform clinical treatment decisions in adolescents with elevated body mass index (BMI), but current equations are suboptimal for severe obesity. We developed a predictive REE equation for youth with severe obesity and obesity-related comorbidities and compared results to previously published predictive equations.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>Data from indirect calorimetry, clinical measures, and body composition per Dual x-ray absorptiometry (DXA) were collected from five sites. Data were randomly divided into development (<i>N</i> = 438) and validation (<i>N</i> = 118) cohorts. A predictive equation was developed using Elastic Net regression, using sex, race, ethnicity, weight, height, BMI percent of the 95th%ile (BMIp95), waist circumference, hip circumference, waist/hip ratio, age, Tanner stage, fat and fat-free mass. This equation was verified in the validation cohort and compared with 11 prior equations.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Data from the total cohort (<i>n</i> = 556, age 15 ± 1.7 years, 77% female, BMIp95 3.3 ± 0.94) were utilized. The best fit equation was REE = −2048 + 18.17 × (Height in cm) – 2.57 × (Weight in kg) + 7.88 × (BMIp95) + 189 × (1 = male, 0 = female), <i>R</i><sup>2</sup> = 0.466, and mean bias of 23 kcal/day.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>This new equation provides an updated REE prediction that accounts for severe obesity and metabolic complications frequently observed in contemporary youth.</p>\n </section>\n </div>","PeriodicalId":217,"journal":{"name":"Pediatric Obesity","volume":"19 7","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pediatric Obesity","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/ijpo.13123","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PEDIATRICS","Score":null,"Total":0}
引用次数: 0
Abstract
Background and Objectives
Resting energy expenditure (REE) assessments can help inform clinical treatment decisions in adolescents with elevated body mass index (BMI), but current equations are suboptimal for severe obesity. We developed a predictive REE equation for youth with severe obesity and obesity-related comorbidities and compared results to previously published predictive equations.
Methods
Data from indirect calorimetry, clinical measures, and body composition per Dual x-ray absorptiometry (DXA) were collected from five sites. Data were randomly divided into development (N = 438) and validation (N = 118) cohorts. A predictive equation was developed using Elastic Net regression, using sex, race, ethnicity, weight, height, BMI percent of the 95th%ile (BMIp95), waist circumference, hip circumference, waist/hip ratio, age, Tanner stage, fat and fat-free mass. This equation was verified in the validation cohort and compared with 11 prior equations.
Results
Data from the total cohort (n = 556, age 15 ± 1.7 years, 77% female, BMIp95 3.3 ± 0.94) were utilized. The best fit equation was REE = −2048 + 18.17 × (Height in cm) – 2.57 × (Weight in kg) + 7.88 × (BMIp95) + 189 × (1 = male, 0 = female), R2 = 0.466, and mean bias of 23 kcal/day.
Conclusion
This new equation provides an updated REE prediction that accounts for severe obesity and metabolic complications frequently observed in contemporary youth.
期刊介绍:
Pediatric Obesity is a peer-reviewed, monthly journal devoted to research into obesity during childhood and adolescence. The topic is currently at the centre of intense interest in the scientific community, and is of increasing concern to health policy-makers and the public at large.
Pediatric Obesity has established itself as the leading journal for high quality papers in this field, including, but not limited to, the following:
Genetic, molecular, biochemical and physiological aspects of obesity – basic, applied and clinical studies relating to mechanisms of the development of obesity throughout the life course and the consequent effects of obesity on health outcomes
Metabolic consequences of child and adolescent obesity
Epidemiological and population-based studies of child and adolescent overweight and obesity
Measurement and diagnostic issues in assessing child and adolescent adiposity, physical activity and nutrition
Clinical management of children and adolescents with obesity including studies of treatment and prevention
Co-morbidities linked to child and adolescent obesity – mechanisms, assessment, and treatment
Life-cycle factors eg familial, intrauterine and developmental aspects of child and adolescent obesity
Nutrition security and the "double burden" of obesity and malnutrition
Health promotion strategies around the issues of obesity, nutrition and physical activity in children and adolescents
Community and public health measures to prevent overweight and obesity in children and adolescents.