Predictive Equation to Estimate Resting Metabolic Rate in Older Chilean Women.

Nutrients

Department of Nutrition and Public Health, Universidad del Bío-Bío, Chillan 3780000, Chile.

Published: August 2022

AI Article Synopsis

  • Resting metabolic rate (RMR) is influenced by body composition, specifically fat-free mass and fat mass, but the role of waist circumference in predicting RMR hasn't been thoroughly explored.
  • An analytical cross-sectional study with 45 older Chilean women (ages 60-85) measured various body metrics and found that RMR was significantly linked to factors like fat-free mass and waist circumference.
  • The study proposed a new estimation equation for RMR that considers waist circumference, which showed better accuracy in predictions compared to existing equations, helping to reduce overestimations in RMR specifically for older women.

Article Abstract

Resting metabolic rate (RMR) depends on body fat-free mass (FFM) and fat mass (FM), whereas abdominal fat distribution is an aspect that has yet to be adequately studied. The objective of the present study was to analyze the influence of waist circumference (WC) in predicting RMR and propose a specific estimation equation for older Chilean women. This is an analytical cross-sectional study with a sample of 45 women between the ages of 60 and 85 years. Weight, height, body mass index (BMI), and WC were evaluated. RMR was measured by indirect calorimetry (IC) and %FM using the Siri equation. Adequacy (90% to 110%), overestimation (>110%), and underestimation (<90%) of the FAO/WHO/UNU, Harris−Benedict, Mifflin-St Jeor, and Carrasco equations, as well as those of the proposed equation, were evaluated in relation to RMR as measured by IC. Normal distribution was determined according to the Shapiro−Wilk test. The relationship of body composition and WC with RMR IC was analyzed by multiple linear regression analysis. The RMR IC was 1083.6 ± 171.9 kcal/day, which was significantly and positively correlated with FFM, body weight, WC, and FM and inversely correlated with age (p < 0.001). Among the investigated equations, our proposed equation showed the best adequacy and lowest overestimation. The predictive formulae that consider WC improve RMR prediction, thus preventing overestimation in older women.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370421PMC
http://dx.doi.org/10.3390/nu14153199DOI Listing

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