Vol 19, Issue 2

A Gender-agnostic Inclusive Estimation for Resting Metabolic Rate

Authors

James W. Navalta, Department of Kinesiology and Nutrition Sciences, University of Nevada, Las Vegas, Las Vegas, Nevada, USA
Dustin W. Davis, Department of Kinesiology and Nutrition Sciences, University of Nevada, Las Vegas, Las Vegas, Nevada, USA
Michael W.H. Wong, Department of Kinesiology and Nutrition Sciences, University of Nevada, Las Vegas, Las Vegas, Nevada, USA
Olivia R. Perez, Department of Kinesiology and Nutrition Sciences, University of Nevada, Las Vegas, Las Vegas, Nevada, USA
Carolina Silva, Department of Kinesiology and Nutrition Sciences, University of Nevada, Las Vegas, Las Vegas, Nevada, USA
Matahn Blank, Department of Kinesiology and Nutrition Sciences, University of Nevada, Las Vegas, Las Vegas, Nevada, USA
International Journal of Exercise Science 19(2): 2019, 2026.

Abstract

Existing resting metabolic rate (RMR) prediction models do not accurately reflect the adult population because they do not include measures from individuals who are non-binary or gender diverse. The objective was to generate data for the purpose of deriving an inclusive, gender-agnostic equation for RMR estimation. Ninety-four individuals participated (gender diverse [transgender male-to-female, transgender female-to-male, genderqueer, gender nonconforming, neither exclusively female or male] n = 6, cisgender female n = 47, cisgender male n = 41). Participants reported to the laboratory between 0700 and 0830 for testing and circumference measurements and resting heart rate were obtained. RMR was measured via indirect calorimetry. Prediction equations were derived through stepwise multiple regression. The final model was RMR (kcal/day) = 14.708 x height (cm) + 10.421 x mass (kg) + 6.211 x resting heart rate − 2019.411 (R = 0.784, R2 = 0.614, SEE = 207.32). This is the first study providing RMR prediction to include participants who do not identify as exclusively cisgender female or cisgender male. This equation may be used in an inclusive manner to estimate various caloric needs, including daily energy balance and dietary prescription.

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