Validity of Predictive Equations for Resting Energy Expenditure in Greek Adults

Maraki, Maria I.; Panagiotakos, Demosthenes B.; Jansen, Lisa T.; Anastasiou, Costas A.; Papalazarou, Anastasios; Yannakoulia, Mary; Sidossis, Labros S.; Kavouras, Stavros A.

doi:10.1159/000486320

Cited by 8 publications

(7 citation statements)

References 27 publications

(40 reference statements)

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“…The overestimation observed using the FAO/WHO/UNU model (1985) supports the results obtained in a study conducted with Greek adults (Maraki et al, 2018). Although the groups were similar in age, the participants of the study by Maraki et al (2018) included a wider range of BMI (16.6–67.7 kg/m 2 ), and a different calorimeter was used, Vmax Encore 29 System (Viasys Healthcare, Inc., Yorba Linda, CA, USA).…”

Section: Discussionsupporting

confidence: 83%

Are predictive equations a valid method of assessing the resting metabolic rate of overweight or obese former athletes?

Jesus

Nunes

Matias

et al. 2020

European Journal of Sport Science

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Athletes retiring from their sports career, an understudied population, are susceptible to become overweight/obese because of decreased energy expenditure not followed by a reduction in energy intake. Therefore, their energy requirements, through resting metabolic rate (RMR), should be accurately addressed for weight management purposes. This study aimed to determine the validity of predictive equations (PEq) for RMR estimation using indirect calorimetry as the reference method in a sample of overweight/obese former athletes. The study uses cross-sectional data collected during baseline measurements of a lifestyle intervention (NCT03031951). The RMR of 56 overweight/obese (31.5 (4.0 kg/m 2 )) individuals (78.6% male, 37.5% obese, 95.8 (14.8 kg), 174.2 (8.7 cm)) was measured by indirect calorimetry and predicted using seven PEq: Harris-Benedict, Cunningham, Schofield, FAO/WHO/UNU, Owen, Mifflin-St. Jeor, and Katch-McArdle. Dual-energy X-ray absorptiometry was used to assess body composition. The PEq overestimated the RMR measured by the indirect calorimetry, 70-300 kcal/day (4.3-14.9%). The linear regression between the reference and each of the PEq did not differ from the identity line with estimated values explaining around 50% of the variability of the measured values. The agreement between the methods was weak for all the PEq showing wide limits of agreement. The Harris-Benedict equation was the only one in which the difference between the methods was not related to the magnitude of the measured RMR. Given the weak performance of the various RMR models in overweight/obese former athletes, an effective weight management intervention based on estimated resting energy requirements may be compromised.

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Section: Discussionsupporting

confidence: 83%

Are predictive equations a valid method of assessing the resting metabolic rate of overweight or obese former athletes?

Jesus

Nunes

Matias

et al. 2020

European Journal of Sport Science

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“…The equations of Schofield (7) , Henry (8) , Mifflin-St Jeor (9) , Harris-Benedict (10) and Owen (11,12) are all widely used. There have been several studies evaluating prediction equation accuracy over the years, including investigations in European (13)(14)(15)(16)(17) and US populations (13,(18)(19)(20) , but regular revalidation and updating of recommendations remain important due to changing demographics of modern populations, as well as changes in body composition. More specifically, in recent years the European Food Safety Authority recommended the Henry equation for predicting RMR in all European Union countries (21) , and it is recommended for use by UK dietitians (22) , yet its predictive accuracy still needs to be established within the current population (23) , particularly within studies across BMI categories.…”

mentioning

confidence: 99%

Validity of predictive equations to estimate RMR in females with varying BMI

et al. 2020

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Estimation of RMR using prediction equations is the basis for calculating energy requirements. In the present study, RMR was predicted by Harris–Benedict, Schofield, Henry, Mifflin–St Jeor and Owen equations and measured by indirect calorimetry in 125 healthy adult women of varying BMI (17–44 kg/m2). Agreement between methods was assessed by Bland–Altman analyses and each equation was assessed for accuracy by calculating the percentage of individuals predicted within ± 10 % of measured RMR. Slopes and intercepts of bias as a function of average RMR (mean of predicted and measured RMR) were calculated by regression analyses. Predictors of equation bias were investigated using univariate and multivariate linear regression. At group level, bias (the difference between predicted and measured RMR) was not different from zero only for Mifflin–St Jeor (0 (sd 153) kcal/d (0 (sd 640) kJ/d)) and Henry (8 (sd 163) kcal/d (33 (sd 682) kJ/d)) equations. Mifflin–St Jeor and Henry equations were most accurate at the individual level and predicted RMR within 10 % of measured RMR in 71 and 66 % of participants, respectively. For all equations, limits of agreement were wide, slopes of bias were negative, and intercepts of bias were positive and significantly (P < 0⋅05) different from zero. Increasing age, height and BMI were associated with underestimation of RMR, but collectively these variables explained only 15 % of the variance in estimation bias. Overall accuracy of equations for prediction of RMR is low at the individual level, particularly in women with low and high RMR. The Mifflin–St Jeor equation was the most accurate for this dataset, but prediction errors were still observed in about one-third of participants.

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“…), were not excluded from the sample. Subjects with pregnancy [ 33 ], lactation [ 34 ], active infections [ 35 ], and unregulated diseases were excluded from participation in the study. The characteristics of the participants are presented in Table 2 .…”

Section: Methodsmentioning

confidence: 99%

Revised Harris–Benedict Equation: New Human Resting Metabolic Rate Equation

et al. 2023

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This paper contains a revision of the Harris–Benedict equations through the development and validation of new equations for the estimation of resting metabolic rate (RMR) in normal, overweight, and obese adult subjects, taking into account the same anthropometric parameters. A total of 722 adult Caucasian subjects were enrolled in this analysis. After taking a detailed medical history, the study enrolled non-hospitalized subjects with medically and nutritionally controlled diseases such as diabetes mellitus, cardiovascular disease, and thyroid disease, excluding subjects with active infections and pregnant or lactating women. Measurement of somatometric characteristics and indirect calorimetry were performed. The values obtained from RMR measurement were compared with the values of the new equations and the Harris–Benedict, Mifflin–St Jeor, FAO/WHO/UNU, and Owen equations. New predictive RMR equations were developed using age, body weight, height, and sex parameters. RMR males: (9.65 × weight in kg) + (573 × height in m) − (5.08 × age in years) + 260; RMR females: (7.38 × weight in kg) + (607 × height in m) − (2.31 × age in years) + 43; RMR males: (4.38 × weight in pounds) + (14.55 × height in inches) − (5.08 × age in years) + 260; RMR females: (3.35 × weight in pounds) + (15.42 × height in inches) − (2.31 × age in years) + 43. The accuracy of the new equations was tested in the test group in both groups, in accordance with the resting metabolic rate measurements. The new equations showed more accurate results than the other equations, with the equation for men (R-squared: 0.95) showing better prediction than the equation for women (R-squared: 0.86). The new equations showed good accuracy at both group and individual levels, and better reliability compared to other equations using the same anthropometric variables as predictors of RMR. The new equations were created under modern obesogenic conditions, and do not exclude individuals with regulated (dietary or pharmacological) Westernized diseases (e.g., cardiovascular disease, diabetes, and thyroid disease).

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Validity of Predictive Equations for Resting Energy Expenditure in Greek Adults

Cited by 8 publications

References 27 publications

Are predictive equations a valid method of assessing the resting metabolic rate of overweight or obese former athletes?

Are predictive equations a valid method of assessing the resting metabolic rate of overweight or obese former athletes?

Validity of predictive equations to estimate RMR in females with varying BMI

Revised Harris–Benedict Equation: New Human Resting Metabolic Rate Equation

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