Obese Women Have a High Carbohydrate Intake without Changes in the Resting Metabolic Rate in the Luteal Phase

Maury‐Sintjago, Eduard; Rodríguez‐Fernández, Alejandra; Parra‐Flores, Julio; Fuente, Marcela Ruíz-De la

doi:10.3390/nu14101997

Cited by 3 publications

(3 citation statements)

References 40 publications

(49 reference statements)

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“…To control the effect of the menstrual cycle on body composition and resting metabolic rate (RMR), all measurements were taken by the same evaluator between days 6 and 13 of the follicular phase of the menstrual cycle; this period was obtained from the analysis of each participant’s menstrual cycle [ 17 ]. The anthropometric measurements of weight and height [ 18 ] used the cutoff points established by the World Health Organization (WHO) [ 19 ].…”

Section: Methodsmentioning

confidence: 99%

Predictive Equations Overestimate Resting Metabolic Rate in Young Chilean Women with Excess Body Fat

2023

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Underestimating/overestimating resting metabolic rate (RMR) affects energy prescription. The objective was to compare RMR by indirect calorimetry (RMR IC) and RMR estimated by predictive equations in women with excess body fat. This was an analytical cross-sectional study with 41 women aged 18–28 with overnutrition according to body composition. The RMR IC was measured and RMR estimated using the FAO/WHO/UNU (1985), FAO/WHO/UNU (2004), Harris–Benedict, and Mifflin–St Jeor equations. The percentage of adequacy (90–110%), overestimation (>110%), and underestimation (<90%) were evaluated for RMR IC. Data were described by percentiles because of non-normal distribution according to the Shapiro–Wilk test. The Kruskal–Wallis test and Bland–Altman analysis were applied at a significance level of α < 0.05. The RMR IC was 1192 and 1183 calories/day (p = 0.429) in women with obesity and overweight, respectively. The FAO/WHO/UNU (1985), FAO/WHO/UNU (2004), Harris–Benedict, and Mifflin–St Jeor equations overestimated the RMR IC by 283.2, 311.2, 292.7, and 203.0 calories/day and by 296.7, 413.8, 280.0, and 176.6 calories/day for women with overweight and obesity (p < 0.001), respectively. The Harris–Benedict adjusted weight (0.5) equation underestimated RMR IC by 254.7 calories/day. The predictive equations overestimated RMR IC in women with excess body fat. The Mifflin–St Jeor equation showed less overestimation and better adequacy, but was not exempt from inaccuracy.

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Section: Methodsmentioning

confidence: 99%

Predictive Equations Overestimate Resting Metabolic Rate in Young Chilean Women with Excess Body Fat

2023

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“…Basal metabolic rate (BMR) accounts for 60-75% of total energy expenditure and can be defined as the minimum rate of energy expenditure in an awake, relaxed person lying on a bed in a thermoneutral environment after an overnight fast [4]. The accurate assessment of the BMR of an individual or a certain population is essential for the development of national energy requirement recommendations and patient management [5,6].…”

Section: Introductionmentioning

confidence: 99%

Predictive Equation for Basal Metabolic Rate in Normal-Weight Chinese Adults

Wang,

Mao,

et al. 2023

Nutrients

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This study aimed to develop a predictive equation for basal metabolic rate (BMR) in normal-weight Chinese adults and provide a reference for establishing the national recommended dietary energy intake. A new equation for BMR was derived from a sample of 516 normal-weight Chinese adults (men = 253, women = 263), and this sample was collected from two previous studies. Furthermore, the accuracy of this new equation and eight other previous predictive equations was reviewed. The agreement and reliability were compared in terms of bias, accuracy, the intraclass correlation coefficient, and Bland–Altman plots between predictive equations. In addition, the newly developed equation was further verified using a small independent sample, which contained 41 healthy Chinese adults (men = 21, women = 20). The measured BMR (mBMR) of all participants, measured using indirect calorimetry, was 1346.2 ± 358.0 kcal/d. Thirty participants were excluded based on Cook’s distance criteria (Cook’s distance of ≥0.008). Previous equations developed by Henry, Schofield, Harris–Benedict (H-B), Yang, and Hong overestimated the BMR of healthy Chinese adults. The present equation displayed the smallest average bias (0.2 kcal/d) between the mBMR and predicted basal metabolic rate (pBMR). The limits of agreement of the present equation from Bland–Altman plots were −514.3 kcal/d and 513.9 kcal/d, which is the most narrow and balanced limit of agreement. Moreover, in the verification of the testing database, the pBMR of the new equation was not significantly different from the mBMR, and the accuracy was 75.6%. Compared with pre-existing equations, the present equation is more applicable to the prediction of BMR in healthy Chinese adults. However, further studies are required to verify the accuracy of this new equation.

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“…The principal determinant factors of BMR include fat-free mass (FFM), body size, age, sex, and hormone production [ 4 ], with FFM as the main determinant [ 5 ]. However, body fat also influences BMR according to studies conducted with youth, middle-aged adults [ 6 ], and persons with obesity [ 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

Predictive Equation to Estimate Resting Metabolic Rate in Older Chilean Women

et al. 2022

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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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Obese Women Have a High Carbohydrate Intake without Changes in the Resting Metabolic Rate in the Luteal Phase

Cited by 3 publications

References 40 publications

Predictive Equations Overestimate Resting Metabolic Rate in Young Chilean Women with Excess Body Fat

Predictive Equations Overestimate Resting Metabolic Rate in Young Chilean Women with Excess Body Fat

Predictive Equation for Basal Metabolic Rate in Normal-Weight Chinese Adults

Predictive Equation to Estimate Resting Metabolic Rate in Older Chilean Women

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