Challenging obesity and sex based differences in resting energy expenditure using allometric modeling, a sub-study of the DIETFITS clinical trial.
Challenging obesity and sex based differences in resting energy expenditure using allometric modeling, a sub-study of the DIETFITS clinical trial.
复制标题
使用异速生长模型挑战肥胖和基于性别的静息能量消耗差异，这是 DIETFITS 临床试验的一项子研究。
DOI：
10.1016/j.clnesp.2022.11.015
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发表时间：
2023
影响因子：
3
通讯作者：
Gardner,Christopher
中科院分区：
文献类型：
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作者：
Haddad,Francois;Li,Xiao;Perelman,Dalia;Santana,EvertonJose;Kuznetsova,Tatiana;Cauwenberghs,Nicholas;Busque,Vincent;Contrepois,Kevin;Snyder,MichaelP;Leonard,MaryB;Gardner,Christopher
背景与目的静息能量消耗（resting energy expenditure，REE）是能量平衡的重要组成部分。虽然REE通常与总体重（BW）相关，但在评估肥胖或减肥干预期间的REE时，这可能会引入偏倚。这项研究的主要目的是量化的偏差引入的REE使用BW的比例缩放在基线和以下体重减轻intervention.DesignParticipants在饮食干预研究（饮食干预检查与治疗成功的相互作用的因素）谁完成间接热量测定和双能X射线吸收测定法（DXA）被列入研究。在基线时有438名参与者的数据，在6个月时有340名参与者，在12个月时有323名参与者。我们使用乘异速生长模型的基础上瘦体重（LBM）和脂肪质量（FM），以获得身体大小无关的缩放REE。指数REE的纵向变化，然后评估减肥intervention.ResultsA乘法模型，包括LBM，FM，年龄，黑人种族和收缩压和心率的双产品（DP）解释了79%的变异REE。REE指数为[LBM 0.66 × FM 0.066]与体重指数相反，与体重指数呈显著负相关（雌性r =-0.47，雄性r =-0.44，p均< 0.001），与体型和性别无关（分别为p = 0.91和p = 0.73）。当以体重指数为指标时，在男性和女性之间（p < 0.001）以及在超重和肥胖个体之间（p < 0.001）观察到REE的显著基线差异，而当以REE/[LBM 0.66 × FM 0.066]为指标时，没有观察到显著差异，p > 0.05）。百分比预测REE调整LBM，FM和DP保持稳定的减肥干预（P = 0.614）。ConclusionAllometric缩放的基础上LBM和FM的REE消除身体成分相关的偏见，应考虑在肥胖和体重为基础的干预研究。
Background & aimsResting energy expenditure (REE) is a major component of energy balance. While REE is usually indexed to total body weight (BW), this may introduce biases when assessing REE in obesity or during weight loss intervention. The main objective of the study was to quantify the bias introduced by ratiometric scaling of REE using BW both at baseline and following weight loss intervention.DesignParticipants in the DIETFITS Study (Diet Intervention Examining The Factors Interacting with Treatment Success) who completed indirect calorimetry and dual-energy X-ray absorptiometry (DXA) were included in the study. Data were available in 438 participants at baseline, 340 at 6 months and 323 at 12 months. We used multiplicative allometric modeling based on lean body mass (LBM) and fat mass (FM) to derive body size independent scaling of REE. Longitudinal changes in indexed REE were then assessed following weight loss intervention.ResultsA multiplicative model including LBM, FM, age, Black race and the double product (DP) of systolic blood pressure and heart rate explained 79% of variance in REE. REE indexed to [LBM0.66× FM0.066] was body size and sex independent (p = 0.91 and p = 0.73, respectively) in contrast to BW based indexing which showed a significant inverse relationship to BW (r = −0.47 for female and r = −0.44 for male, both p < 0.001). When indexed to BW, significant baseline differences in REE were observed between male and female (p < 0.001) and between individuals who are overweight and obese (p < 0.001) while no significant differences were observed when indexed to REE/[LBM0.66× FM0.066], p > 0.05). Percentage predicted REE adjusted for LBM, FM and DP remained stable following weight loss intervention (p = 0.614).ConclusionAllometric scaling of REE based on LBM and FM removes body composition-associated biases and should be considered in obesity and weight-based intervention studies.