A practical equation to predict resting metabolic rate in older men

Abstract

The accuracy of previous equations for predicting resting metabolic rate (RMR) in healthy older men is questionable because they are based on limited sample sizes and the absence of cross-validation procedures. The purposes of this study were to (1) examine biological predictors of RMR in healthy older men; (2) develop a practical equation to predict RMR from easily measured variables and examine its accuracy using cross-validation procedures; and (3) test the validity of existing equations in the literature to predict RMR in older men by comparison with measured RMR values. RMR, body composition, anthropometric measurements, leisure time activity (LTA), maximal aerobic power (Vo 2max), energy intake, and plasma thyroid hormone levels were determined in 89 healthy older men aged 50 to 78 years. Stepwise regression analysis showed that RMR was best predicted by fat-free weight ([FFW] R 2 = 85%), free 3,5,3′-triiodothyronine (T 3) level ( R 2 = 1%), and Vo 2max ( R 2 = 1%); these variables predicted RMR with a residual error of ±30 kcal/d. A practical equation was developed in a randomly selected subsample (N = 61) using easily measured variables as potential predictors, and was successfully cross-validated in a random subsample of older men (N = 28). The pooled equation to predict RMR is as follows: RMR (in kilocalories per day) = 9.7 (weight in kilograms) − 6.1 (chest skinfold thickness in millimeters) − 1.8 (age in years) + 0.1 (leisure time activity [LTA] in kilocalories per day) + 1,060. These variables accounted for 76% ( R 2) of the variation, and predicted RMR with a residual error of ±42 kcal/d. When four previously published equations were applied to predict RMR in our sample of older men, individual predicted values deviated −19% to +14% from measured values. We conclude that variations in FFW account for the greatest source of variation in RMR in older men. Current equations to predict RMR are generally imprecise on an individual basis when applied to older men. We offer a practical and successfully cross-validated equation to predict RMR in healthy older men based on measures of body weight, LTA, and chest skinfold thickness.