Matthews Rachel, Höchsmann Christoph, Erickson Melissa L, Dorling James L, Spielmann Guillaume, Johannsen Neil M, Church Timothy S, Martin Corby K
School of Kinesiology, College of Human Sciences & Education, Louisiana State University, Baton Rouge, LA.
Department of Health and Sport Sciences, TUM School of Medicine and Health, Technical University of Munich, Munich, GERMANY.
Med Sci Sports Exerc. 2025 Mar 1;57(3):470-480. doi: 10.1249/MSS.0000000000003583. Epub 2024 Oct 15.
American College of Sports Medicine (ACSM) metabolic equations are used to estimate energy expenditure (EE) of physical activity and prescribe aerobic exercise to meet EE requirements. Limited evidence supports their accuracy in sedentary adults with overweight or obesity during controlled exercise interventions. The purpose of this study was to compare EE estimated by the ACSM walking equation versus EE measured by indirect calorimetry during a 24-wk aerobic exercise intervention, and identify potential modulators for their accuracy.
Data from the exercising groups (8 or 20 kcal·kg body weight -1 ·wk -1 ) of the E-MECHANIC study were utilized in this ancillary analysis ( N = 103). Every 2 wk for the initial 8 wk and monthly thereafter, EE was measured via indirect calorimetry during absolute (2 mph, 0% grade) and relative (65%-85% peak oxygen uptake (V̇O 2peak )) workload exercise. Resting metabolic rate, V̇O 2peak , and body composition were assessed at baseline and follow-up. An EE offset factor (EOF) was calculated to express measured EE as a percentage of the estimated EE at each workload (EOF < 100% represents an overestimation of ACSM estimated EE).
The accuracy of the equation decreased with increasing exercise workload (0.44%, 9.2%, and 20.3% overestimation at absolute, relative, and maximal workloads, respectively, at baseline) and overestimation of EE was greater after the exercise intervention. Furthermore, race, sex, age, fat mass, and V̇O 2peak were identified as modulators for equation accuracy. Greater overestimation of EE was observed in Black compared with White females, particularly at lower exercise workloads.
These findings support future efforts to improve the accuracy of metabolic equations, especially in diverse populations. Researchers should account for exercise efficiency adaptations when using metabolic equations to prescribe exercise precisely.
美国运动医学学院（ACSM）的代谢方程用于估算体力活动的能量消耗（EE），并规定有氧运动以满足EE需求。有限的证据支持其在超重或肥胖的久坐成年人进行有控制的运动干预期间的准确性。本研究的目的是比较在为期24周的有氧运动干预期间，通过ACSM步行方程估算的EE与通过间接量热法测量的EE，并确定其准确性的潜在调节因素。
本辅助分析使用了E-MECHANIC研究中运动组（8或20千卡·千克体重-1·周-1）的数据（N = 103）。在最初的8周内每2周测量一次，此后每月测量一次，在绝对（2英里/小时，0%坡度）和相对（65%-85%峰值摄氧量（V̇O2peak））工作量运动期间通过间接量热法测量EE。在基线和随访时评估静息代谢率、V̇O2peak和身体成分。计算EE偏移因子（EOF），以将测量的EE表示为每个工作量下估算EE的百分比（EOF < 100%表示ACSM估算的EE被高估）。
该方程的准确性随着运动工作量的增加而降低（基线时在绝对、相对和最大工作量下分别高估0.44%、9.2%和20.3%），并且运动干预后EE的高估更大。此外，种族、性别、年龄、脂肪量和V̇O2peak被确定为方程准确性的调节因素。与白人女性相比，黑人女性对EE的高估更大，尤其是在较低的运动工作量下。
这些发现支持未来为提高代谢方程准确性所做的努力，特别是在不同人群中。研究人员在使用代谢方程精确规定运动时应考虑运动效率的适应性。
