Macena Mateus de Lima, Paula Déborah Tenório da Costa, da Silva Júnior André Eduardo, Praxedes Dafiny Rodrigues Silva, Pureza Isabele Rejane de Oliveira Maranhão, de Melo Ingrid Sofia Vieira, Bueno Nassib Bezerra
Faculdade de Nutrição, Universidade Federal de Alagoas, Maceió, Alagoas, Brasil.
Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, São Paulo, Brasil.
Nutr Rev. 2022 Oct 10;80(11):2113-2135. doi: 10.1093/nutrit/nuac031.
Energy expenditure predictive equations can generate inaccurate estimates for overweight or obese individuals.
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.
Searches were performed in January 2022 in MEDLINE, Web of Science, Scopus, CENTRAL, and the gray literature databases.
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).
Sixty-one studies were included. The FAO/WHO/UNU (1985) equation, which uses only body weight in its formula, showed the lowest bias in estimating REE (mean difference [MD] = 8.97 kcal; 95% CI = -26.99; 44.94). In the subgroup analysis for individuals with obesity, the Lazzer (2007) equation showed the lowest bias (MD = 4.70 kcal; 95% CI = -95.45; 104.86). The Harris-Benedict equation (1919) showed the highest precision values for individuals with overweight (60.65%) and for individuals with obesity (62.54%). Equations with body composition data showed the highest biases. The equation proposed by the Institute of Medicine (2005) showed the lowest bias (MD = -2.52 kcal; 95% CI = -125.94; 120.90) in estimating the TEE. Most analyses showed high heterogeneity (I2 > 90%). There was no evidence of publication bias.
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.
PROSPERO registration no. CRD42021262969.
能量消耗预测方程可能会对超重或肥胖个体产生不准确的估计。
本综述的目的是确定在超重和肥胖成年人中，哪些静息能量消耗（REE）和总能量消耗（TEE）预测方程的偏差最低且精度最高。
2022年1月在MEDLINE、科学网、Scopus、CENTRAL和灰色文献数据库中进行了检索。
对纳入1项以上研究的方程进行荟萃分析。在定量分析中，采用DerSimonian和Laird随机效应模型以及I2统计量来量化异质性。进行Egger检验以评估潜在的发表偏倚，并进行元回归以探索异质性。结果按参与者的体重指数分类（超重和肥胖）分别呈现。
纳入61项研究。粮农组织/世界卫生组织/联合国大学（1985年）方程在其公式中仅使用体重，在估计REE方面显示出最低的偏差（平均差[MD]=8.97千卡；95%可信区间=-26.99；44.94）。在肥胖个体的亚组分析中，Lazzer（2007年）方程显示出最低的偏差（MD=4.70千卡；95%可信区间=-95.45；104.86）。哈里斯-本尼迪克特方程（1919年）在超重个体（60.65%）和肥胖个体（62.54%）中显示出最高的精度值。包含身体成分数据的方程显示出最高的偏差。医学研究所（2005年）提出的方程在估计TEE方面显示出最低的偏差（MD=-2.52千卡；95%可信区间=-125.94；120.90）。大多数分析显示出高度异质性（I2>90%）。没有证据表明存在发表偏倚。
对于超重个体，粮农组织/世界卫生组织/联合国大学（1985年）方程和哈里斯-本尼迪克特方程（1919年）在预测REE方面分别显示出最低的偏差和最高的精度。对于肥胖个体，哈里斯-本尼迪克特方程（1919年）显示出最高的精度，而Lazzer方程（2007年）显示出最低的偏差。需要更多关于预测方程的研究来估计TEE。
PROSPERO注册号CRD42021262969。
