Predictive Equation to Estimate Resting Metabolic Rate in Older Chilean Women.
Maury-Sintjago EduardCarmen Muñoz-MendozaAlejandra Rodríguez-FernándezMarcela Ruíz-De la FuentePublished in: Nutrients (2022)
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.
Keyphrases
- body mass index
- body weight
- body composition
- polycystic ovary syndrome
- physical activity
- weight gain
- heart rate
- pregnancy outcomes
- adipose tissue
- heart rate variability
- cervical cancer screening
- breast cancer risk
- middle aged
- type diabetes
- bone mineral density
- community dwelling
- blood pressure
- pregnant women
- skeletal muscle
- metabolic syndrome
- high intensity
- atomic force microscopy