scholarly journals Basal metabolic rate studies in humans: measurement and development of new equations

2005 ◽  
Vol 8 (7a) ◽  
pp. 1133-1152 ◽  
Author(s):  
CJK Henry
Keyword(s):  
Metabolic Rate ◽  
Basal Metabolic Rate ◽  
Historical Review ◽  
World Health ◽  
Energy Requirements ◽  
Tropical Region ◽  
Data Set ◽  
Predictive Equations ◽  
Protein Requirements ◽  
Health Organization

AbstractObjectiveTo facilitate the Food and Agriculture Organization/World Health Organization/United Nations University Joint (FAO/WHO/UNU) Expert Consultation on Energy and Protein Requirements which met in Rome in 1981, Schofield et al. reviewed the literature and produced predictive equations for both sexes for the following ages: 0–3, 3–10, 10–18, 18–30, 30–60 and >60 years. These formed the basis for the equations used in 1985 FAO/WHO/UNU document, Energy and Protein Requirements.While Schofield's analysis has served a significant role in re-establishing the importance of using basal metabolic rate (BMR) to predict human energy requirements, recent workers have subsequently queried the universal validity and application of these equations. A survey of the most recent studies (1980–2000) in BMR suggests that in most cases the current FAO/WHO/UNU predictive equations overestimate BMR in many communities. The FAO/WHO/UNU equations to predict BMR were developed using a database that contained a disproportionate number – 3388 out of 7173 (47%) – of Italian subjects. The Schofield database contained relatively few subjects from the tropical region.The objective here is to review the historical development in the measurement and application of BMR and to critically review the Schofield et al. BMR database presenting a series of new equations to predict BMR.DesignThis division, while arbitrary, will enable readers who wish to omit the historical review of BMR to concentrate on the evolution of the new BMR equations.SettingBMR data collected from published and measured values.SubjectsA series of new equations (Oxford equations) have been developed using a data set of 10 552 BMR values that (1) excluded all the Italian subjects and (2) included a much larger number (4018) of people from the tropics.ResultsIn general, the Oxford equations tend to produce lower BMR values than the current FAO/WHO/UNU equations in 18–30 and 30–60 year old males and in all females over 18 years of age.ConclusionsThis is an opportune moment to re-examine the role and place of BMR measurements in estimating total energy requirements today. The Oxford equations' future use and application will surely depend on their ability to predict more accurately the BMR in contemporary populations.

scholarly journals The conceptual framework for estimating food energy requirement

2005 ◽  
Vol 8 (7a) ◽  
pp. 940-952 ◽  
Author(s):  
Anna Ferro-Luzzi
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Energy Requirement ◽  
Historical Review ◽  
Activity Level ◽  
World Health ◽  
Future Research ◽  
Expert Consultation ◽  
Protein Requirements ◽  
Health Organization

AbstractObjectiveIn anticipation of the revision of the 1985 Food and Agricultural Organization/World Health Organization/United Nations University (FAO/ WHO/UNU) Expert Consultation Report on ‘Energy and Protein Requirements’, recent scientific knowledge on the principles underlying the estimation of energy requirement is reviewed.DesignThis paper carries out a historical review of the scientific rationale adopted by previous FAO/WHO technical reports on energy requirement, discusses the concepts used in assessing basal metabolic rate (BMR), energy expenditure, physical activity level (PAL), and examines current controversial areas. Recommendations and areas of future research are presented.ConclusionsThe database of the BMR predictive equations developed by the 1985 FAO/WHO/UNU Expert Consultation Report on Energy and Protein Requirements needs updating and expansion, applying strict and transparent selection criteria. The existence of an ethnic/tropical factor capable of affecting BMR is not supported by the available evidence. The factorial approach for the calculation of energy requirement, as set out in the 1985 report, should be retained. The estimate should have a normative rather than a prescriptive nature, except for the allowance provided for extra physical activity for sedentary populations, and for the prevention of non-communicable chronic diseases. The estimate of energy requirement of children below the age of 10 years should be made on the basis of energy expenditure rather than energy intake. The evidence of the existence of an ethnic/tropical factor is conflicting and no plausible mechanism has as yet been put forward.

scholarly journals Measured Versus Estimated Resting Metabolic Rate in Heart Failure With Preserved Ejection Fraction

2021 ◽  
Author(s):  
Theresa Anderson ◽  
Thomas M. Cascino ◽  
Todd M. Koelling ◽  
Daniel Perry ◽  
Gillian Grafton ◽  
...  
Keyword(s):  
Heart Failure ◽  
Ejection Fraction ◽  
Metabolic Rate ◽  
World Health Organization ◽  
Resting Metabolic Rate ◽  
World Health ◽  
Preserved Ejection Fraction ◽  
Predictive Equations ◽  
Health Organization ◽  
Nutrition And Dietetics

Background: Obesity is common in heart failure with preserved ejection fraction (HFpEF), and a hypocaloric diet can improve functional capacity. Malnutrition, sarcopenia, and frailty are also frequently present, and calorie restriction could harm some patients. Resting metabolic rate (RMR) is an essential determinant of caloric needs; however, it is rarely measured in clinical practice. The accuracy of commonly used predictive equations in HFpEF is unknown. Methods: RMR was measured with indirect calorimetry in 43 patients with HFpEF undergoing right heart catheterization at the University of Michigan, and among 49 participants in the SECRET trial (Study of the Effects of Caloric Restriction and Exercise Training in Patients With Heart Failure and a Normal Ejection Fraction); SECRET patients also had dual-energy X-ray absorptiometry body composition measures. Measured RMR was compared with RMR estimated using the Harris Benedict, Mifflin-St Jeor, World Health Organization, and Academy for Nutrition and Dietetics equations. Results: All predictive equations overestimated RMR (by >10%, P <0.001 for all), with mean (95% CI) differences Harris Benedict equation +250 (186–313), Mifflin-St. Jeor equation +169 (110–229), World Health Organization equation +300 (239–361), and Academy for Nutrition and Dietetics equation +794 (890–697) kcal/day. Results were similar across both patient groups, and the discrepancy between measured and estimated RMR tended to increase with body mass index. In SECRET, measured RMR was closely associated with lean body mass (ρ=0.74; by linear regression adjusted for age and sex: β=27 [95% CI, 18–36] kcal/day per kg, P <0.001; r 2 =0.56). Conclusions: Commonly used predictive equations systematically overestimate measured RMR in patients with HFpEF. Direct measurement of RMR may be needed to effectively tailor dietary guidance in this population. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique Identifier: NCT00959660.

Development of new predictive equations for basal metabolic rate in Iranian healthy adults: negligible effect of sex

2020 ◽  
pp. 1-10
Author(s):  
Bahareh Nikooyeh ◽  
Nastaran Shariatzadeh ◽  
Ali Kalayi ◽  
Maliheh Zahedirad ◽  
Tirang R. Neyestani
Keyword(s):  
Metabolic Rate ◽  
Thyroid Function ◽  
Basal Metabolic Rate ◽  
Age Groups ◽  
Thyroid Function Tests ◽  
Anthropometric Measures ◽  
Predictive Equations ◽  
Normal Thyroid Function ◽  
Asian People ◽  
Predictive Formulas

Abstract. Some studies have reported inaccuracy of predicting basal metabolic rate (BMR) by using common equations for Asian people. Thus, this study was undertaken to develop new predictive equations for the Iranian community and also to compare their accuracy with the commonly used formulas. Anthropometric measures and thyroid function were evaluated for 267 healthy subjects (18–60 y). Indirect calorimetry (InCal) was performed only for those participants with normal thyroid function tests (n = 252). Comparison of predicted RMR (both kcal/d and kcal.kg.wt−1.d−1) using current predictive formulas and measured RMR revealed that Harris-Benedict and FAO/WHO/UNU significantly over-estimated and Mifflin-St. Jeor significantly under-estimated RMR as compared to InCal measurements. In stepwise regression analysis for developing new equations, the highest r2 (=0.89) was from a model comprising sex, height and weight. However, further analyses revealed that unlike the subjects under 30 y, the association between age and the measured RMR in subjects 30 y and plus was negative (r = −0.241, p = 0.001). As a result, two separate equations were developed for these two age groups. Over 80 percent of variations were covered by the new equations. In conclusion, there were statistical significant under- and over-estimation of RMR using common predictive equations in our subjects. Using the new equations, the accuracy of the calculated RMR increased remarkably.

Risk Factor Identification, Classification and Prediction Summary of Chronic Kidney Disease

2020 ◽  
Vol 13 ◽  
Author(s):  
Pramila Arulanthu ◽  
Eswaran Perumal
Keyword(s):  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Disease Diagnosis ◽  
Medical Data ◽  
Machine Learning Algorithms ◽  
World Health ◽  
Medical Field ◽  
Data Set ◽  
Medical Issues ◽  
Health Organization

: The medical data has an enormous quantity of information. This data set requires effective classification for accurate prediction. Predicting medical issues is an extremely difficult task in which Chronic Kidney Disease (CKD) is one of the major unpredictable diseases in medical field. Perhaps certain medical experts do not have identical awareness and skill to solve the issues of their patients. Most of the medical experts may have underprivileged results on disease diagnosis of their patients. Sometimes patients may lose their life in nature. As per the Global Burden of Disease (GBD-2015) study, death by CKD was ranked 17th place and GBD-2010 report 27th among the causes of death globally. Death by CKD is constituted 2·9% of all death between the year 2010 and 2013 among people from 15 to 69 age. As per World Health Organization (WHO-2005) report, 58 million people expired by CKD. Hence, this article presents the state of art review on Chronic Kidney Disease (CKD) classification and prediction. Normally, advanced data mining techniques, fuzzy and machine learning algorithms are used to classify medical data and disease diagnosis. This study reviews and summarizes many classification techniques and disease diagnosis methods presented earlier. The main intention of this review is to point out and address some of the issues and complications of the existing methods. It is also attempts to discuss the limitations and accuracy level of the existing CKD classification and disease diagnosis methods.

Comparativa de modelos multivariados basados en aprendizaje automático para la predicción del riesgo de diabetes en etapas tempranas

2021 ◽  
Author(s):  
◽  
Zayra Ramírez Gaytán
Keyword(s):  
World Health ◽  
Degenerative Diseases ◽  
Decision Tree Algorithm ◽  
Data Set ◽  
The World ◽  
Long Time ◽  
Life Threatening ◽  
Health Organization ◽  
Logistic Regression Algorithm ◽  
Asymptomatic Phase

Diabetes is one of the fastest-growing, life-threatening, chronic degenerative diseases. According to the World Health Organization (WHO), it has affected 422 million people worldwide in 2018. Approximately 50% of all people who suffer diabetes are not diagnosed due to the asymptomatic phase which usually lasts a long time. In this work, a data set of 520 instances has been used. The data set has been analyzed with the next three algorithms: logistic regression algorithm, decision trees and random forest. The results show that the decision tree algorithm had better performance with an AUC of 98%. Also, it was found the most common symptoms that a person with a risk of diabetes presents are polyuria, polydipsia and sudden weight loss.

scholarly journals Estimates of mortality rates in people with diabetes and cardiovascular disease using administrative pharmaceutical data

2019 ◽  
Vol 4 (3) ◽  
Author(s):  
Shaun Purkiss ◽  
Tessa Keegel ◽  
Hassan Vally ◽  
Dennis Wollersheim
Keyword(s):  
Cardiovascular Disease ◽  
Mortality Risk ◽  
Age Groups ◽  
Mortality Rates ◽  
World Health ◽  
Data Set ◽  
Medication Discontinuation ◽  
Disease Mortality ◽  
Health Organization

BackgroundQuantifying the mortality risk for people with diabetes is challenging because of associated comorbidities. The recording of cause specific mortality from accompanying cardiovascular disease in death certificate notifications has been considered to underestimate the overall mortality risk in persons with diabetes. Main AimDevelop a technique to quantify mortality risk from pharmaceutical administrative data and apply it to persons diagnosed with diabetes, and associated cardiovascular disease and dyslipidaemia before death. MethodsPersons with diabetes, cardiovascular disease and dyslipidaemia were identified in a publicly available Australian Pharmaceutical data set using World Health Organization anatomic therapeutic codes assigned to medications received. Diabetes associated multi-morbidity cohorts were constructed and a proxy mortality (PM) event determined from medication and service discontinuation. Estimates of mortality rates were calculated from 2004 for 10 years and compared persons with diabetes alone and associated cardiovascular disease and dyslipidemia. ResultsThis study identified 346,201 individuals within the 2004 calendar year as having received treatments for diabetes (n=51,422), dyslipidaemia (n=169,323) and cardiovascular disease including hypertension (n=280,105). Follow up was 3.3 x 106 person-years. Overall crude PM was 26.1 per 1000 person-years. PM rates were highest in persons with cardiovascular disease and diabetes in combination (47.5 per 100 person years). Statin treatments significantly improved the mortality rates in all persons with diabetes and cardiovascular disease alone and in combination over age groups >44 years (p<.001). Age specific diabetes PM rates using pharmaceutical data correlated well with Australian data from the National Diabetes Service Scheme (r=0.82) ConclusionProxy mortality events calculated from medication discontinuation in persons with chronic conditions can provide an alternative method to estimate disease mortality rates. The technique also allows the assessment of mortality risk in persons with chronic disease multi-morbidity.

scholarly journals Measured and Predicted Basal Metabolic Rate in Inflammatory Bowel Disease Patients

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 624-624
Author(s):  
Luiz Dos Anjos ◽  
Tatiana Campos ◽  
Juliana Dantas ◽  
Fernanda Fernandes ◽  
Vivian Wahrlich
Keyword(s):  
Inflammatory Bowel Disease ◽  
Metabolic Rate ◽  
Basal Metabolic Rate ◽  
Bowel Disease ◽  
Anthropometric Measures ◽  
Predictive Equations ◽  
Women Subjects ◽  
Funding Sources ◽  
Chron's Disease ◽  
Inflammatory Bowel

Abstract Objectives To measure basal metabolic rate (BMR) and to compare the values with estimated BMR from international and local predictive equations in inflammatory bowel disease (IBD) patients. Methods A total of 72 (38 women) subjects with Chron's disease (n = 45, 19 women) and ulcerative colitis (n = 27, 19 women) from an outpatient care unit in Rio de Janeiro, Brazil, agreed to participate in the study. Anthropometric measures were obtained using standard procedures. Percent body fat (PBF) was assessed by DXA. BMR was measured (BMRm) by indirect calorimetry (Vmax Encore 29) under standardized conditions and compared with BMR estimated by internationally-recommended (Schofield, 1985) and locally-developed (Anjos et al., 2014) predictive equations. Bias was calculated as estimated - measured BMR. Results The mean ± SD (range) age was 38.0 ± 11.3 (20.1 – 58.3) years with a mean BMI of 24.7 ± 4.5 (16.1 – 39.1) kg.m−2 and PBF of 32.2 ± 9.1 (9.7 – 53.4). BMRm was significantly lower in women (1169.3 ± 205.0) than men (1439.0 ± 197.5) kcal.day−1. The Schofield's equations significantly overestimated BMR for both women (bias of 204.0 ± 148.3 kcal.day−1 or 17.4%) and men (306.7 ± 171.0 kcal.day−1 or 21.3%). The locally-developed equation yielded nonsignificant estimates for both women (−5.8 ± 143.7 kcal.day−1 or −0.5%) and men (−19.9 ± 165.5 kcal.day−1 or −1.4%). Conclusions The findings of the present study indicate that internationally-recommended BMR predictive equations are not accurate to estimate BMR in IBD patients in a tropical setting. As observed in samples of healthy adults from the same city, the locally-developed BMR equations yield unbiased and accurate estimates for IBD patients. Funding Sources CNPq (310,461/2016–20) and FAPERJ (E-26/202.514/2018; E-26/203.068/2018; E-26/203.068/2017; E-26/202.520/2016; E-26/210.747/2016).

Evaluating Percentage-Based Reporting of Glucose-6-Phosphate Dehydrogenase (G6PD) Enzymatic Activity in a National Reference Laboratory: Assessment of Patient Eligibility for Plasmodium vivax Radical Cure Therapy

2019 ◽  
Vol 152 (Supplement_1) ◽  
pp. S82-S82
Author(s):  
Emilia Calvaresi ◽  
Jonathan Genzen
Keyword(s):  
Normal Activity ◽  
Population Based ◽  
G6pd Activity ◽  
World Health ◽  
Reference Laboratory ◽  
Data Sets ◽  
Radical Cure ◽  
Laboratory Assessment ◽  
Data Set ◽  
Health Organization

Abstract Objectives The World Health Organization recommends measurement of G6PD activity prior to initiation of 8-aminoquinolones for the treatment of P vivax malaria. An estimated 400 million people worldwide have G6PD deficiency, making them susceptible to hemolysis under oxidative stress. A new single-dose therapy (radical cure) for malaria with tafenoquine is contraindicated in patients with <70% normal G6PD activity due to its prolonged circulating half-life. However, most clinical laboratories report G6PD activity in units g/Hb or units/1012 RBC and do not provide percentage of normal activity, making potential eligibility determination challenging. Methods Using an IRB-exempt protocol, a limited data set of consecutive G6PD quantitative results was retrieved from the clinical laboratory’s enterprise data warehouse. Laboratory testing of these specimens was previously performed at 37°C using an automated enzymatic assay (Pointe Scientific) configured on a cobas c501 chemistry analyzer (Roche Diagnostics). Data were assembled to include adults age 18 to 89 years and excluded repeat results from the same patients as well as outliers. Conclusion The final data set included 52,216 results (female, 55.9%, n = 29,173; male, 44.1%, n = 23,043) from 47 US states. An adjusted male median (100% G6PD activity) was derived using an approach proposed by the Bangkok Workshop guidelines (Domingo et al., Malaria Journal, 2013), modified to more accurately differentiate bimodal peaks in population G6PD histograms. The laboratory-specific, adjusted male median was 12.7 U g/Hb and was similar to peak values derived from alternative curve-fitting approaches. Applying this median to gender-specific data sets, 5.4% of males and 3.8% of females were found to have <70% of normal activity (<8.9 U g/Hb). This study demonstrates the feasibility of percentage-based G6PD result reporting in adults; further studies will query percentage-based reporting in pediatric populations. Population-based medians will vary based on G6PD assay type and temperature and should be established by laboratories prior to percentage-based reporting.

scholarly journals Seasonal Energetics of Mountain Chickadees and Juniper Titmice

The Condor ◽  
2000 ◽  
Vol 102 (3) ◽  
pp. 635-644 ◽  
Author(s):  
Sheldon J. Cooper
Keyword(s):  
Energy Expenditure ◽  
Metabolic Rate ◽  
Breeding Season ◽  
Basal Metabolic Rate ◽  
Energy Requirements ◽  
Daily Energy Expenditure ◽  
Poecile Gambeli ◽  
Daily Energy ◽  
Metabolic Data ◽  
Mountain Chickadees

Abstract I used behavioral, meteorological, and laboratory metabolism data to calculate daily energy expenditure (DEE) in seasonally acclimatized Mountain Chickadees (Poecile gambeli) and Juniper Titmice (Baeolophus griseus). Analyses of laboratory metabolic data revealed that foraging energy requirements were not significantly higher than alert perching energy requirements. Respective DEE of chickadees and titmice were 48.8 kJ day−1 and 48.3 kJ day−1 in summer and 66.3 kJ day−1 and 98.7 kJ day−1 in winter. DEE as a multiple of basal metabolic rate (BMR) was 2.31 in summer chickadees and 1.91 in summer titmice. DEE was 2.70 times BMR in winter chickadees and 3.43 times BMR in winter titmice. The marked increase in calculated DEE in winter birds compared to summer is in contrast to a pattern of increased DEE in the breeding season for several avian species. These data suggest that winter may be a period of even greater stringency for small birds than previously believed.

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