Estimation of basal metabolic rate in Chinese: are the current prediction equations applicable?
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ABSTRACT:
SUBMITTER: Camps SG
PROVIDER: S-EPMC5007802 | biostudies-other | 2016
REPOSITORIES: biostudies-other
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Project description:Basal metabolic rate (BMR) represents the largest component of total energy expenditure and is a major contributor to energy balance. Therefore, accurately estimating BMR is critical for developing rigorous obesity prevention and control strategies. Over the past several decades, numerous BMR formulas have been developed targeted to different population groups. A comprehensive literature search revealed 248 BMR estimation equations developed using diverse ranges of age, gender, race, fat-free mass, fat mass, height, waist-to-hip ratio, body mass index and weight. A subset of 47 studies included enough detail to allow for development of meta-regression equations. Utilizing these studies, meta-equations were developed targeted to 20 specific population groups. This review provides a comprehensive summary of available BMR equations and an estimate of their accuracy. An accompanying online BMR prediction tool (available at http://www.sdl.ise.vt.edu/tutorials.html) was developed to automatically estimate BMR based on the most appropriate equation after user-entry of individual age, race, gender and weight.
| S-EPMC4278349 | biostudies-literature
Project description:BackgroundResting metabolic rate (RMR) is a key determinant of daily caloric needs. Respirometry, a form of indirect calorimetry (IC), is considered one of the most accurate methods to measure RMR in clinical and research settings. It is impractical to measure RMR by IC in routine clinical practice; therefore, several formulas are used to predict RMR. In this study, we sought to determine the accuracy of these formulas in determining RMR and assess additional factors that may determine RMR.MethodsWe measured RMR in 114 subjects (67% female, 30% African American [AA]) using IC. Along with standard anthropometrics, dual-energy X-ray absorptiometry was used to obtain fat-free mass(FFM) and total fat mass. Measured RMR (mRMR) by respirometry was compared with predicted RMR (pRMR) generated by Mifflin-St.Joer, Cunningham, and Harris-Benedict (HB) equations. Linear regression models were used to determine factors affecting mRMR.ResultsMean age, BMI, and mRMR of subjects were 46 ± 16 years (mean ± SD), 35 ± 10 kg/m2, and 1658 ± 391 kcal/day, respectively. After adjusting for age, gender, and anthropometrics, the two largest predictors of mRMR were race (p < 0.0001) and FFM (p < 0.0001). For every kg increase in FFM, RMR increased by 28 kcal/day (p < 0.0001). AA race was associated with 144 kcal/day (p < 0.0001) decrease in mRMR. The impact of race on mRMR was mitigated by adding in truncal FFM to the model. When using only clinically measured variables to predict mRMR, we found race, hip circumference, age, gender, and weight to be significant predictors of mRMR (p < 0.005). Mifflin-St.Joer and HB equations that use just age, gender, height, and weight overestimated kcal expenditure in AA by 138 ± 148 and 242 ± 164 (p < 0.0001), respectively.ConclusionWe found that formulas utilizing height, weight, gender, and age systematically overestimate mRMR and hence predict higher calorie needs among AA. The lower mRMR in AA could be related to truncal fat-free mass representing the activity of metabolically active intraabdominal organs.
| S-EPMC6662665 | biostudies-literature
Project description:BackgroundResting metabolic rate (RMR) prediction equations are often used to calculate RMR in athletes; however, their accuracy and precision can vary greatly.ObjectiveThe aim of this systematic review and meta-analysis was to determine which RMR prediction equations are (i) most accurate (average predicted values closest to measured values) and (ii) most precise (number of individuals within 10% of measured value).Data sourcesA systematic search of PubMed, CINAHL, SPORTDiscus, Embase, and Web of Science up to November 2021 was conducted.Eligibility criteriaRandomised controlled trials, cross-sectional observational studies, case studies or any other study wherein RMR, measured by indirect calorimetry, was compared with RMR predicted via prediction equations in adult athletes were included.AnalysisA narrative synthesis and random-effects meta-analysis (where possible) was conducted. To explore heterogeneity and factors influencing accuracy, subgroup analysis was conducted based on sex, body composition measurement method, athlete characteristics (athlete status, energy availability, body weight), and RMR measurement characteristics (adherence to best practice guidelines, test preparation and prior physical activity).ResultsTwenty-nine studies (mixed sports/disciplines n = 8, endurance n = 5, recreational exercisers n = 5, rugby n = 3, other n = 8), with a total of 1430 participants (822 F, 608 M) and 100 different RMR prediction equations were included. Eleven equations satisfied criteria for meta-analysis for accuracy. Effect sizes for accuracy ranged from 0.04 to - 1.49. Predicted RMR values did not differ significantly from measured values for five equations (Cunningham (1980), Harris-Benedict (1918), Cunningham (1991), De Lorenzo, Ten-Haaf), whereas all others significantly underestimated or overestimated RMR (p < 0.05) (Mifflin-St. Jeor, Owen, FAO/WHO/UNU, Nelson, Koehler). Of the five equations, large heterogeneity was observed for all (p < 0.05, I2 range: 80-93%) except the Ten-Haaf (p = 0.48, I2 = 0%). Significant differences between subgroups were observed for some but not all equations for sex, athlete status, fasting status prior to RMR testing, and RMR measurement methodology. Nine equations satisfied criteria for meta-analysis for precision. Of the nine equations, the Ten-Haaf was found to be the most precise, predicting 80.2% of participants to be within ± 10% of measured values with all others ranging from 40.7 to 63.7%.ConclusionMany RMR prediction equations have been used in athletes, which can differ widely in accuracy and precision. While no single equation is guaranteed to be superior, the Ten-Haaf (age, weight, height) equation appears to be the most accurate and precise in most situations. Some equations are documented as consistently underperforming and should be avoided. Choosing a prediction equation based on a population of similar characteristics (physical characteristics, sex, sport, athlete status) is preferable. Caution is warranted when interpreting RMR ratio of measured to predicted values as a proxy of energy availability from a single measurement.Prospero registrationCRD42020218212.
| S-EPMC10687135 | biostudies-literature
Project description:BMR (Basal metabolic rate) is an important trait in animal life history as it represents a significant part of animal energy budgets. BMR has also been shown to be positively related to sustainable work rate and maximal thermoregulatory capacity. To this date, most of the studies have focused on the causes of interspecific and intraspecific variation in BMR, and fairly little is known about the fitness consequences of different metabolic strategies. In this study, we show that winter BMR affects local survival in a population of wild blue tits (Cyanistes caeruleus), but that the selection direction differs between years. We argue that this fluctuating selection is probably a consequence of varying winter climate with a positive relation between survival and BMR during cold and harsh conditions, but a negative relation during mild winters. This fluctuating selection can not only explain the pronounced variation in BMR in wild populations, but will also give us new insights into how energy turnover rates can shape the life-history strategies of animals. Furthermore, the study shows that the process of global warming may cause directional selection for a general reduction in BMR, affecting the general life-history strategy on the population level.
| S-EPMC4725447 | biostudies-other
Project description:BackgroundGlomerular filtration rate (GFR) is essential for renal function evaluation and classification of chronic kidney disease (CKD), while the reference method in children are cumbersome. In the Chinese children, there was no data about GFR measured through plasma or renal clearance of the exogenous markers, and therefore no validated GFR-estimating tools in this population.MethodsWe measured GFR with double-sample plasma clearance of 99mTc-DTPA (mGFR) in 87 hospitalized children with renal injury. Using mGFR as the golden standard, we evaluate the efficiency of four different GFR estimation equations (the original and update Schwartz equation, the Filler equation, the CKiD equation) by statistical parameters of correlation, precision and accuracy.ResultsIn our population, mGFR was 97.0± 31.9 mL/min/1.73m2. The updated Schwartz equation, the Filler equation and the CKiD equation, produced eGFR with strong correlation with mGFR, strong explanation capacity of variance in mGFR, small bias, satisfactory performance in Bland-Altman analysis, high intra-class correlation coefficients, high ratio of eGFR within mGFR±10% and eGFR within mGFR±30%, good agreement in CKD staging between eGFR and mGFR. The original Schwartz equation produced eGFR with large bias, poor precision and accuracy.ConclusionThe validated equations to estimate GFR in our patients are the updated Schwartz equation, which is simple for bedside use, the Filler equation and the CKiD equation, which provide more accurate eGFR. The original Schwartz equation should not be applied to estimate GFR in Chinese children with kidney injuries.
| S-EPMC5500331 | biostudies-literature
Project description:PurposeThe accurate estimative of energy needs is crucial for an optimal physical performance among athletes and the basal metabolic rate (BMR) equations often are not well adjusted for adolescent athletes requiring the use of specific methods, such as the golden standard indirect calorimetry (IC). Therefore, we had the aim to analyse the agreement between the BMR of adolescents pentathletes measured by IC and estimated by commonly used predictive equations.MethodsTwenty-eight athletes (17 males and 11 females) were evaluated for BMR, using IC and the predictive equations Harris and Benedict (HB), Cunningham (CUN), Henry and Rees (HR) and FAO/WHO/UNU (FAO). Body composition was obtained using DXA and sexual maturity data were retrieved through validated questionnaires. The correlations among anthropometric variables an IC were analysed by T-student test and ICC, while the agreement between IC and the predictive equations was analysed according to Bland and Altman and by survival-agreement plotting.ResultsThe whole sample average BMR measured by IC was significantly different from the estimated by FAO (p<0.05). Adjusting data by gender FAO and HR equations were statistically different from IC (p <0.05) among males, while female differed only for the HR equation (p <0.05).ConclusionThe FAO equation underestimated athletes' BMR when compared with IC (T Test). When compared to the golden standard IC, using Bland and Altman, ICC and Survival-Agreement, the equations underestimated the energy needs of adolescent pentathlon athletes up to 300kcal/day. Therefore, they should be used with caution when estimating individual energy requirements in such populations.
| S-EPMC4646488 | biostudies-literature
Project description:BackgroundSerum creatinine (S-Cr)-based prediction equations are commonly used for estimating glomerular filtration rate (GFR). However, S-Cr concentration is also affected by other factors such as tubular secretion, muscle mass, diet, gender and age. Serum cystatin C (S-Cys C)-based prediction equations have been proposed as an improved potential alternative as S-Cys C levels are not influenced by many of the factors that affect creatinine concentration other than GFR. This may be of great benefit to patients with low muscle mass such as those infected with human immunodeficiency virus who are at increased risk for the development of renal impairment. The aim of this study was to develop and evaluate a S-Cys C-based prediction equation for different stages of renal disease in black South Africans.MethodsOne hundred patients with varying degrees of renal function were enrolled in the study. The plasma clearance of (51)Cr-EDTA, a gold standard method, was used to measure GFR (mGFR). In addition, serum was analysed for S-Cr and S-Cys C on each participant. This dataset was split into a development dataset (n = 50) and a test dataset (n = 50). The development dataset was used to formulate a S-Cys C- and S-Cr-based prediction equation using multiple linear regression analysis. These equations together with the four-variable MDRD and CKD-EPI equation were then tested on the test dataset.ResultsIn the test dataset, accuracy within 15% of measured GFR was 68% for the S-Cys C equation and 48% for the S-Cr equation. Root mean square error for S-Cr eGFR was 10.7 mL/min/1.73 m(2) for those patients with mGFR < 60 mL/min/1.73 m(2) and 25.5 mL/min/1.73 m(2) for those patients with mGFR > 60 mL/min/1.73 m(2). Root mean square error for S-Cys C eGFR was 10.2 mL/min/1.73 m(2) for those patients with mGFR < 60 mL/min/1.73 m(2) and 11.9 mL/min/1.73 m(2) for those patients with mGFR > 60 mL/min/1.73 m(2).ConclusionsIn this study, S-Cys C-based prediction equations appear to be more precise than those of S-Cr for those patients with mGFR > 60 mL/min/1.73 m(2) and may therefore be of benefit in the earlier detection of renal impairment.
| S-EPMC3108353 | biostudies-literature
Project description:BackgroundSeveral equations for glomerular filtration rate (GFR) estimation based on serum creatinine (SCr) have been proposed for children, but most were developed among patients with kidney disease. The association between SCr and GFR may be distorted by kidney dysfunction and thus not applicable to healthy children. This study aimed to evaluate the applicability of existing SCr-based GFR estimation equations in healthy Chinese children.MethodsGFR estimation equations that developed in healthy children were mainly analysed, including the Flanders Metadata (FM), simple height-independent (Simple), full age spectrum (FAS) and FAS-height equations. The FM equation assumed that GFR is proportional to the ratio of height to SCr. The Simple, FAS and FAS-height equations assumed that the ratio of GFR to population mean is equal to the reciprocal ratio of SCr to population mean (denoted by Q). Estimated GFR were calculated using data of SCr, age, sex and height collected from 12 208 healthy Chinese children aged 3 months to <20 years. The performance of GFR estimation equations was evaluated by the sex and age distribution of the estimated GFR and the deviation from the measured GFR reported by other literatures.ResultsThe FM and Simple equations performed well in their applicable age of 1 month to 14 years, but presented undesirable sex difference after adolescence. The FAS and FAS-height equations showed reasonable development trend of estimated GFR throughout childhood, and the FAS equation had higher consistency than the FAS-height equation compared with measured GFR in healthy children. The GFR estimated by the FAS equation increased with age before 2 years, and reached the adult level thereafter without important sex difference.ConclusionsThe FAS equation is applicable to healthy Chinese children.
| S-EPMC10582894 | biostudies-literature
Project description:ObjectiveTo measure resting metabolic rate (RMR) in survivors of chronic (>3 months prior) stroke (mean ± SEM age, 61±7.5 years) and to compare to predicted RMR using predictive equations in adults without stroke.DesignCross-sectional study.SettingHospital.ParticipantsSurvivors of stroke (N=71).InterventionNot applicable.Main outcome measuresRMR was measured by indirect calorimetry. Participants underwent a total body dual-energy x-ray absorptiometry scan and treadmill test for peak oxygen consumption (V̇o2peak). RMR was calculated using 9 established equations.ResultsRMR measured (1552±319 kcal/d) was significantly lower than 9 predicted RMR values (all P<.001), with the best being McArdle-Katch (1652±233 kcal/d), Livingston (1677±230 kcal/d), and Mifflin (1707±242 kcal/d). The Institute of Medicine of the National Academies (2437±386 kcal/d) had the largest discrepancy with measured RMR. Predicted RMR determined with 8 of 9 equations was between 9% and 18% greater than measured RMR. Appendicular lean mass (r=0.64, P<.001), total lean mass (r=0.64, P<.001), and V̇o2peak (r=0.41, P<.001) were associated with measured RMR.ConclusionsRMR predictive equations established in adults without stroke are not appropriate for the population with stroke population, indicating the need to measure RMR until a more accurate predictive equation is developed. This could support modifications to nutritional intake guidelines in patients with conditions of muscle atrophy. If measurement of RMR is not feasible, the Katch-McArdle equation should be used to estimate RMR in a patient with stroke because on average it provides the lowest percentage overestimate compared with other equations.
| S-EPMC9246861 | biostudies-literature
Project description:Objective: The aim of this study was to assess the relationship between basal metabolic rate (BMR) and all-cause mortality in southern Chinese adults. Methods: We prospectively examined the relationship between BMR and all-cause mortality in 12,608 Southern Chinese adults with age ≥ 35 years who participated in the National Key R&D Program from 2013-2014 to 2019-2020. Cox proportional hazard models were used to examine the association between BMR and all-cause mortality. Results: A total of 809 deaths (including 478 men and 331 women) occurred during a median follow-up period of 5.60 years. All-cause mortality was higher in elderly individuals than in non-elderly individuals (11.48 vs. 2.04%, P < 0.001) and was higher in male subjects than in female subjects (9.84 vs. 4.56%, P < 0.001). There was a significantly inverse relationship between BMR levels and all-cause mortality in elderly male individuals (adjusted-HR per SD increase: 0.80, 95% CI: 0.70-0.91, P < 0.001). Compared with BMR levels ≤ 1,115 kJ/day, there was lower all-cause mortality in third and highest BMR quartiles in the elderly male subjects (adjusted-HR: 0.71, 95% CI: 0.53-0.95, P = 0.022; adjusted-HR: 0.60, 95% CI: 0.43-0.84, P = 0.003, respectively). Conclusion: An elevated BMR was independently inversely associated with all-cause mortality in elderly male subjects in a southern Chinese population.
| S-EPMC8763786 | biostudies-literature