The influence of physical characteristics on the resting energy expenditure of youth: A meta‐analysis. Issue 3 (30th November 2016)

• Record Type: Journal Article
• Authors: Herrmann, Stephen D.; McMurray, Robert G.; Kim, Youngdeok; Willis, Erik A.; Kang, Minsoo; McCurdy, Thomas
• Is Part Of: American journal of human biology. Volume 29:Issue 3(2017:May/Jun.)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-11-30
• Subjects: Human biology -- Periodicals; Physical anthropology -- Periodicals; Biologie humaine -- Périodiques; Anthropologie physique -- Périodiques; 612
• DOI: 10.1002/ajhb.22944
• Languages: English
• ISSNs: 1042-0533

Abstract

Abstract: Objective: To examine the literature on resting energy expenditure (REE) of youth and determine the influence of age, sex, BMI, and body composition on REE. Methods: A literature search was conducted using PubMed, BIOSIS Previews, NTIS, EMBASE, MEDLINE, and Pascal databases for studies with data on resting metabolic rate, REE, resting oxygen uptake (or VO2 ) in healthy children, youth, or adolescents (age = 1–18 years). Over 200 publications were identified; sixty‐one publications met criteria and were included in the meta‐analyses, resulting in 142 study population estimates (totaling 5, 397 youth) of REE. Results: Pooled mean was 1414 kcal·day −1 with a significant and moderate‐to‐high between‐study heterogeneity [ Q (140) = 7912.42, P < 0.001; I 2 = 98.97%]. A significantly greater ( P < 0.001) pooled mean kcal·day −1 was estimated for studies with male participants (1519 kcal·day −1 ) comparing to studies with female participants (1338 kcal·day −1 ). Age, height, and body mass resulted in the highest R 2 of 86.4 for males and 83.9% for females. Fat free mass and body mass index (BMI) did not improve total R 2 . Conclusions: These data suggest that using a linear equation including age, height, and body mass to estimate REE based on kcal·day −1 is more accurate than estimates based on body mass kcal·kg −1 ·h −1 . Further, if kcal·kg −1 ·h −1 is used, including a quadratic component for the physical characteristics improves the predictive ability of the equation. Regardless of the metric, separate equations should be used for each sex.