Social System Design Lab, George Warren Brown School of Social Work, Washington University, St Louis, MO, USA.
Int J Obes (Lond). 2013 Oct;37(10):1364-70. doi: 10.1038/ijo.2012.218. Epub 2013 Jan 15.
Basal metabolic rate (BMR) represents the largest component of total energy expenditure and is a major contributor to energy balance. Therefore, accurately estimating BMR is critical for developing rigorous obesity prevention and control strategies. Over the past several decades, numerous BMR formulas have been developed targeted to different population groups. A comprehensive literature search revealed 248 BMR estimation equations developed using diverse ranges of age, gender, race, fat-free mass, fat mass, height, waist-to-hip ratio, body mass index and weight. A subset of 47 studies included enough detail to allow for development of meta-regression equations. Utilizing these studies, meta-equations were developed targeted to 20 specific population groups. This review provides a comprehensive summary of available BMR equations and an estimate of their accuracy. An accompanying online BMR prediction tool (available at http://www.sdl.ise.vt.edu/tutorials.html) was developed to automatically estimate BMR based on the most appropriate equation after user-entry of individual age, race, gender and weight.
基础代谢率 (BMR) 代表了总能量消耗的最大组成部分,是能量平衡的主要贡献者。因此,准确估计 BMR 对于制定严格的肥胖预防和控制策略至关重要。在过去的几十年中,已经开发出了针对不同人群的许多 BMR 公式。全面的文献检索显示,已经开发出了 248 种使用不同年龄段、性别、种族、去脂体重、脂肪量、身高、腰臀比、体重指数和体重的 BMR 估计公式。有 47 项研究包含足够的详细信息,可以开发出元回归方程。利用这些研究,针对 20 个特定人群组开发了元方程。本综述提供了可用的 BMR 方程的全面总结,并对其准确性进行了评估。还开发了一个在线 BMR 预测工具(可在 http://www.sdl.ise.vt.edu/tutorials.html 上获得),可根据用户输入的个人年龄、种族、性别和体重,自动选择最合适的方程来估计 BMR。