| Titre : | Estimates of resting energy expenditure and total energy expenditure using predictive equations in adults with overweight and obesity: a systematic review with meta-analysis (2022) |
| Auteurs : | Mateus de Lima Macena ; Déborah Tenório da Costa Paula ; André Eduardo da Silva Júnior ; Dafiny Rodrigues Silva Praxedes ; Isabele Rejane de Oliveira Maranhão Pureza ; Ingrid Sofia Vieira de Melo ; Nassib Bezerra Bueno |
| Type de document : | Article |
| Dans : | Nutrition reviews (Vol. 80, n° 11, November 2022) |
| Article en page(s) : | p. 2113-2135 |
| Note générale : | https://doi.org/10.1093/nutrit/nuac031 |
| Langues: | Anglais |
| Descripteurs : |
HE Vinci Calorimétrie ; Indice de masse corporelle ; Métabolisme énergétique ; Obésité ; Surpoids ; Valeur prédictive des tests |
| Résumé : | Context: Energy expenditure predictive equations can generate inaccurate estimates for overweight or obese individuals.; Objective: The objective of this review was to determine which predictive equations for resting energy expenditure (REE) and total energy expenditure (TEE) have the lowest bias and the highest precision in adults with overweight and obesity.; Data Sources: Searches were performed in January 2022 in MEDLINE, Web of Science, Scopus, CENTRAL, and the gray literature databases.; Data Extraction: Meta-analyses were performed with equations included in more than 1 study. The DerSimonian and Laird random-effects model and the I2 statistic were used to quantify heterogeneity in the quantitative analyses. The Egger test was performed to assess potential publication biases, and metaregressions were conducted to explore the heterogeneity. Findings were presented separated by participants' body mass index classification (overweight and obesity).; Conclusion: For individuals with overweight, the FAO/WHO/UNU (1985) and the Harris-Benedict equations (1919) showed the lowest bias and the highest precision in predicting the REE, respectively. For individuals with obesity, the Harris-Benedict equation (1919) showed the highest precision and the Lazzer equation (2007) showed the lowest bias. More studies are needed on predictive equations to estimate the TEE. |
| Disponible en ligne : | Oui |
| En ligne : | https://login.ezproxy.vinci.be/login?url=https://academic.oup.com/nutritionreviews/article/80/11/2113/6585249 |
Bibliothèques HE Vinci
