Maurice Puyau, Roman Shypailo, Nancy F Butte, Salma Musaad, Fida Bacha
{"title":"基于室内量热法的儿童和青少年BMI谱基础能量消耗预测模型:一项横断面队列研究","authors":"Maurice Puyau, Roman Shypailo, Nancy F Butte, Salma Musaad, Fida Bacha","doi":"10.1016/j.ajcnut.2024.12.003","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Existing equations for prediction of basal energy expenditure (BEE) may not be accurate in children with overweight or obesity (OW/OB). We aimed to develop BEE prediction equations applicable to children and adolescents across a wide BMI spectrum using gold standard room calorimetry.</p><p><strong>Methods: </strong>We measured weight, height, and waist and hip circumferences; body composition (dual-energy X-ray absorptiometry); and BEE (whole room calorimetry) in a cross-sectional cohort of 1155 healthy children, aged 5-19 y; 67% of the males and 51% of the females were classified as OW/OB. We applied multiple linear regression analyses to develop BEE prediction models for each sex. Using relevant predictors, we developed models with fat-free mass; waist and hip circumferences; weight and height only; and weight only. A representative sample of participants (83 males, 125 females) served as a validation data set to test model performance. The models' performance in predicting BEE was compared with existing models in the literature.</p><p><strong>Results: </strong>Model fits (R<sup>2</sup>) for the new BEE prediction models were 0.84 (P < 0.0001). Our BEE prediction models performed equally in children with normal weight and OW/OB, with <1.5% difference between the measured and predicted BEE in the validation data set for both sexes. In Bland-Altman analysis, our BEE prediction models were superior to existing prediction models, especially for children with higher BEEs.</p><p><strong>Conclusions: </strong>New BEE prediction models developed and tested in cohorts representative of children with normal weight and OW/OB has superior performance compared with existing models. The BEE prediction equations based on simple anthropometrics or body composition provided improved accuracy and precision for children with NW or OW/OB (ages 5-19 y). More accurate estimates of BEE should allow for better estimates of energy requirements of children.</p>","PeriodicalId":50813,"journal":{"name":"American Journal of Clinical Nutrition","volume":" ","pages":""},"PeriodicalIF":6.5000,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction models of basal energy expenditure in children and adolescents across the BMI spectrum based on room calorimetry: a cross-sectional cohort study.\",\"authors\":\"Maurice Puyau, Roman Shypailo, Nancy F Butte, Salma Musaad, Fida Bacha\",\"doi\":\"10.1016/j.ajcnut.2024.12.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Existing equations for prediction of basal energy expenditure (BEE) may not be accurate in children with overweight or obesity (OW/OB). We aimed to develop BEE prediction equations applicable to children and adolescents across a wide BMI spectrum using gold standard room calorimetry.</p><p><strong>Methods: </strong>We measured weight, height, and waist and hip circumferences; body composition (dual-energy X-ray absorptiometry); and BEE (whole room calorimetry) in a cross-sectional cohort of 1155 healthy children, aged 5-19 y; 67% of the males and 51% of the females were classified as OW/OB. We applied multiple linear regression analyses to develop BEE prediction models for each sex. Using relevant predictors, we developed models with fat-free mass; waist and hip circumferences; weight and height only; and weight only. A representative sample of participants (83 males, 125 females) served as a validation data set to test model performance. The models' performance in predicting BEE was compared with existing models in the literature.</p><p><strong>Results: </strong>Model fits (R<sup>2</sup>) for the new BEE prediction models were 0.84 (P < 0.0001). Our BEE prediction models performed equally in children with normal weight and OW/OB, with <1.5% difference between the measured and predicted BEE in the validation data set for both sexes. In Bland-Altman analysis, our BEE prediction models were superior to existing prediction models, especially for children with higher BEEs.</p><p><strong>Conclusions: </strong>New BEE prediction models developed and tested in cohorts representative of children with normal weight and OW/OB has superior performance compared with existing models. The BEE prediction equations based on simple anthropometrics or body composition provided improved accuracy and precision for children with NW or OW/OB (ages 5-19 y). 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Prediction models of basal energy expenditure in children and adolescents across the BMI spectrum based on room calorimetry: a cross-sectional cohort study.
Background: Existing equations for prediction of basal energy expenditure (BEE) may not be accurate in children with overweight or obesity (OW/OB). We aimed to develop BEE prediction equations applicable to children and adolescents across a wide BMI spectrum using gold standard room calorimetry.
Methods: We measured weight, height, and waist and hip circumferences; body composition (dual-energy X-ray absorptiometry); and BEE (whole room calorimetry) in a cross-sectional cohort of 1155 healthy children, aged 5-19 y; 67% of the males and 51% of the females were classified as OW/OB. We applied multiple linear regression analyses to develop BEE prediction models for each sex. Using relevant predictors, we developed models with fat-free mass; waist and hip circumferences; weight and height only; and weight only. A representative sample of participants (83 males, 125 females) served as a validation data set to test model performance. The models' performance in predicting BEE was compared with existing models in the literature.
Results: Model fits (R2) for the new BEE prediction models were 0.84 (P < 0.0001). Our BEE prediction models performed equally in children with normal weight and OW/OB, with <1.5% difference between the measured and predicted BEE in the validation data set for both sexes. In Bland-Altman analysis, our BEE prediction models were superior to existing prediction models, especially for children with higher BEEs.
Conclusions: New BEE prediction models developed and tested in cohorts representative of children with normal weight and OW/OB has superior performance compared with existing models. The BEE prediction equations based on simple anthropometrics or body composition provided improved accuracy and precision for children with NW or OW/OB (ages 5-19 y). More accurate estimates of BEE should allow for better estimates of energy requirements of children.
期刊介绍:
American Journal of Clinical Nutrition is recognized as the most highly rated peer-reviewed, primary research journal in nutrition and dietetics.It focuses on publishing the latest research on various topics in nutrition, including but not limited to obesity, vitamins and minerals, nutrition and disease, and energy metabolism.
Purpose:
The purpose of AJCN is to:
Publish original research studies relevant to human and clinical nutrition.
Consider well-controlled clinical studies describing scientific mechanisms, efficacy, and safety of dietary interventions in the context of disease prevention or health benefits.
Encourage public health and epidemiologic studies relevant to human nutrition.
Promote innovative investigations of nutritional questions employing epigenetic, genomic, proteomic, and metabolomic approaches.
Include solicited editorials, book reviews, solicited or unsolicited review articles, invited controversy position papers, and letters to the Editor related to prior AJCN articles.
Peer Review Process:
All submitted material with scientific content undergoes peer review by the Editors or their designees before acceptance for publication.