4.0 Article

Development of new predictive equations for basal metabolic rate in Iranian healthy adults: negligible effect of sex

Journal

Publisher

HOGREFE AG-HOGREFE AG SUISSE
DOI: 10.1024/0300-9831/a000669

Keywords

basal metabolic rate; RMR predictive equations; indirect calorimetry

Funding

  1. National Nutrition and Food Technology Research Institute (NNFTRI)

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Some studies have shown that commonly used equations for predicting basal metabolic rate (BMR) in Asian people are inaccurate. This study aimed to develop new equations for the Iranian community and compare their accuracy with the commonly used formulas. The results showed that the new equations significantly improved the accuracy of calculating BMR.
Some studies have reported inaccuracy of predicting basal metabolic rate (BMR) by using common equations for Asian people. Thus, this study was undertaken to develop new predictive equations for the Iranian community and also to compare their accuracy with the commonly used formulas. Anthropometric measures and thyroid function were evaluated for 267 healthy subjects (18-60 y). Indirect calorimetry (InCal) was performed only for those participants with normal thyroid function tests (n = 252). Comparison of predicted RMR (both kcal/d and kcal.kg.wt(-1).d(-1)) using current predictive formulas and measured RMR revealed that Harris-Benedict and FAO/WHO/UNU significantly over-estimated and Mifflin-St. Jeor significantly under-estimated RMR as compared to InCal measurements. In stepwise regression analysis for developing new equations, the highest r(2) (=0.89) was from a model comprising sex, height and weight. However, further analyses revealed that unlike the subjects under 30 y, the association between age and the measured RMR in subjects 30 y and plus was negative (r = -0.241, p = 0.001). As a result, two separate equations were developed for these two age groups. Over 80 percent of variations were covered by the new equations. In conclusion, there were statistical significant under- and over-estimation of RMR using common predictive equations in our subjects. Using the new equations, the accuracy of the calculated RMR increased remarkably.

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