Resting Energy Expenditure Prediction Equations in the Pediatric Population: A Systematic Review

被引:16
作者
Fuentes-Servin, Jimena [1 ]
Avila-Nava, Azalia [2 ]
Gonzalez-Salazar, Luis E. [3 ,4 ]
Perez-Gonzalez, Oscar A. [5 ]
Servin-Rodas, Maria Del Carmen [6 ]
Serralde-Zuniga, Aurora E. [3 ,7 ]
Medina-Vera, Isabel [1 ,7 ]
Guevara-Cruz, Martha [7 ,8 ]
机构
[1] Inst Nacl Pediat, Dept Metodol Invest, Mexico City, DF, Mexico
[2] Hosp Reg Alta Especialidad Peninsula Yucatan, Merida, Mexico
[3] Inst Nacl Nutr & Ciencias Med Salvador Zubiran, Serv Nutr Clin, Mexico City, DF, Mexico
[4] Inst Politecn Nacl, Secc Estudios Posgrad & Invest, Escuela Super Med, Mexico City, DF, Mexico
[5] Inst Nacl Pediat, Lab Oncol Expt, Mexico City, DF, Mexico
[6] Univ Nacl Autonoma Mexico, Escuela Nacl Enfermeria & Obstet, Mexico City, DF, Mexico
[7] Tecnol Monterrey, Escuela Med & Ciencias Salud, Mexico City, DF, Mexico
[8] Inst Nacl Nutr & Ciencias Med Salvador Zubiran, Dept Fisiol Nutr, Mexico City, DF, Mexico
关键词
energy expenditure; children; adolescents; indirect calorimetry; predictive equation; BASAL METABOLIC-RATE; OBESE CAUCASIAN CHILDREN; X-RAY ABSORPTIOMETRY; BODY-COMPOSITION; CROSS-VALIDATION; REQUIREMENTS; ADOLESCENTS; OVERWEIGHT; WEIGHT; FAT;
D O I
10.3389/fped.2021.795364
中图分类号
R72 [儿科学];
学科分类号
100202 ;
摘要
Background and Aims: The determination of energy requirements is necessary to promote adequate growth and nutritional status in pediatric populations. Currently, several predictive equations have been designed and modified to estimate energy expenditure at rest. Our objectives were (1) to identify the equations designed for energy expenditure prediction and (2) to identify the anthropometric and demographic variables used in the design of the equations for pediatric patients who are healthy and have illness.Methods: A systematic search in the Medline/PubMed, EMBASE and LILACS databases for observational studies published up to January 2021 that reported the design of predictive equations to estimate basal or resting energy expenditure in pediatric populations was carried out. Studies were excluded if the study population included athletes, adult patients, or any patients taking medications that altered energy expenditure. Risk of bias was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies.Results: Of the 769 studies identified in the search, 39 met the inclusion criteria and were analyzed. Predictive equations were established for three pediatric populations: those who were healthy (n = 8), those who had overweight or obesity (n = 17), and those with a specific clinical situation (n = 14). In the healthy pediatric population, the FAO/WHO and Schofield equations had the highest R-2 values, while in the population with obesity, the Molnar and Dietz equations had the highest R-2 values for both boys and girls.Conclusions: Many different predictive equations for energy expenditure in pediatric patients have been published. This review is a compendium of most of these equations; this information will enable clinicians to critically evaluate their use in clinical practice.
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页数:27
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