Human Nutrition Research Centre, Institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, UK.
International Center for the Assessment of Nutritional Status, (ICANS), Department of Food, Environmental and Nutritional Science (DeFENS), Università degli Studi di Milano, Via Colombo 60, 20133 Milano, Italy.
Clin Nutr. 2014 Aug;33(4):613-9. doi: 10.1016/j.clnu.2013.09.009. Epub 2013 Sep 25.
The measurement of resting energy expenditure (REE) is important to assess individual total energy requirements in older subjects. The validity of REE prediction equations in this population has not been thoroughly evaluated and therefore the main aim of this analysis was to assess the accuracy of REE prediction equations in older subjects.
Weight, height and body mass index (BMI) were measured. REE was measured by indirect calorimetry (IC) in 68 older subjects (age: 60-94 years, M/F: 13/55, BMI: 26.3 ± 5.0 kg/m(2)). Measured REE was compared to 14 equations for the calculation of REE estimates. In addition, two novel approaches (Aggregate model and meta-regression equations) for the prediction of REE were evaluated. Paired t test and Bland-Altman method were used to assess the agreement of the equations.
The average measured REE was 1298 ± 264 kcal/day. The equation with the smallest bias was proposed by Muller (Bias ± 2SD = +3 ± 294 kcal/day) whereas the Mifflin equation was associated with the largest error (Bias ± 2SD = -172 ± 282 kcal/day). The Aggregate, Muller, Harris-Benedict and Fredrix equations were characterised by a prediction within ±10% of measured REE in more than 60% of subjects. Of the four algorithms, only the Aggregate equation did not show a significant association of the measurement bias with age, BMI and gender.
The Aggregate algorithm was characterised by a higher, overall accuracy for the prediction of REE in older subjects and its use should be advocated in older subjects. However, due to the large variability of the estimates, the measurement of REE by IC is still recommended for an accurate assessment of individual REE.
静息能量消耗（REE）的测量对于评估老年受试者的个体总能量需求非常重要。然而，这些人群中 REE 预测方程的有效性尚未得到充分评估，因此本分析的主要目的是评估 REE 预测方程在老年受试者中的准确性。
测量体重、身高和体重指数（BMI）。在 68 名老年受试者（年龄：60-94 岁，男/女：13/55，BMI：26.3±5.0kg/m²）中通过间接测热法（IC）测量 REE。将测量的 REE 与 14 种 REE 计算方程进行比较。此外，还评估了两种新的 REE 预测方法（综合模型和荟萃回归方程）。使用配对 t 检验和 Bland-Altman 方法评估方程的一致性。
平均测量的 REE 为 1298±264kcal/天。Muller 方程的偏差最小（Bias±2SD=+3±294kcal/天），而 Mifflin 方程的误差最大（Bias±2SD=-172±282kcal/天）。Aggregate、Muller、Harris-Benedict 和 Fredrix 方程在超过 60%的受试者中，预测值与测量值的偏差在±10%以内。在这四个算法中，只有 Aggregate 方程的测量偏差与年龄、BMI 和性别没有显著相关性。
Aggregate 算法在预测老年受试者 REE 方面具有更高的总体准确性，应在老年受试者中提倡使用。然而，由于估计值的变异性较大，仍建议通过 IC 测量 REE 来准确评估个体 REE。
