Clinical Correlates of Measured and Predicted Resting Energy Expenditure in Patients with Anorexia Nervosa: A Retrospective Cohort Study

Resting energy expenditure (REE; i.e., the calorie amount required for 24 h during a non-active period) is an important parameter in nutritional rehabilitation of patients with anorexia nervosa (AN). This study determined whether age, body mass index, AN duration/subtype/specific symptoms/clinical severity, cognitive function alterations, and psychiatric comorbidities influenced REE or the difference between the calculated and estimated REE. Patients with AN who were followed at a daycare treatment facility between May 2017 and January 2020 (n = 138) underwent a complete assessment that included the MINI, Eating Disorder Examination Questionnaire, d2 test of attention, body fat composition by bioelectrical impedance analysis (BIA) and REE measurement by indirect calorimetry (REE_IC). AN subtype (N = 66 for restrictive subtype and N = 69 for non-restrictive subtype; p = 0.005), free-fat mass (<0.001), and fat mass (<0.001) were associated with REE_IC. Age (p < 0.001), height (p = 0.003), and AN duration (N = 46 for <3 years and N = 82 for ≥3 years; p = 0.012) were associated with the difference between estimated REE (using the Schebendach equation) and measured REE_IC. Therefore, the Schebendach equation was adjusted differently in the two patients’ subgroups (AN duration ≤ or >3 years). Overall, REE was higher in patients with restrictive than non-restrictive AN. In the absence of BIA measures, REE-estimating equations should take into account AN duration.     

Within-Day Energy Balance and Metabolic Suppression in Male Collegiate Soccer Players

Metabolic suppression due to relative energy deficiency can cause various physiological impairments in athletes. The purpose of this study was to evaluate within-day energy balance (WDEB) and the ratio between measured and predicted resting energy expenditure (REE_ratio) and to investigate the relationships between the markers of metabolic suppression. Ten male collegiate soccer players completed a 7-day food diary, physical activity, and heart rate records during the training and rest days. Energy intake (EI) and energy expenditure (EE) were analyzed to evaluate WDEB components. Body composition was measured using dual-energy X-ray absorptiometry (DXA), and blood sampling was conducted for hormonal analysis. The REE was measured using the Douglas bag method and predicted using the DXA-predicted method to calculate the REE_ratio. Participants were categorized into the normal (REE_ratio ≥ 0.94, n = 5) and suppressed (REE_ratio < 0.94, n = 5) groups. There were no group differences in the components of WDEB, except diet-induced thermogenesis (DIT), but EI was significantly higher in the normal group than in the suppressed group (7-day total: 3660 ± 347 vs. 3024 ± 491 kcal/day, p = 0.046 and rest days: 3772 ± 463 vs. 2796 ± 800 kcal/day, p = 0.046). Analysis of hormonal markers of metabolic suppression only showed a significant positive association between insulin-like growth factor-1 (IGF-1) and REE_ratio (r = 0.771, p = 0.009). The relationships between metabolic suppression and the markers of energy deficiency were inconclusive. There are possible associations of insufficient EI and IGF-1 levels with metabolic suppression, and further study is required to understand energy deficiency in male soccer players.     

Predictive Equation to Estimate Resting Metabolic Rate in Older Chilean Women

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.     

Protein Quality in Infant Formulas Marketed in Brazil: Assessments on Biodigestibility,Essential Amino Acid Content and Proteins of Biological Importance

Infant formulas, designed to provide similar nutritional composition and performance to human milk, are recommended when breastfeeding is not enough to provide for the nutritional needs of children under 12 months of age. In this context, the present study aimed to assess the protein quality and essential amino acid content of both starting (phase 1) and follow-up (phase 2) formulas from different manufacturers. The chemical amino acid score and protein digestibility corrected by the amino acid score were calculated. The determined protein contents in most formulas were above the maximum limit recommended by FAO and WHO guidelines and at odds with the protein contents declared in the label. All infant formulas contained lactoferrin (0.06 to 0.44 g·100 g⁻¹) and α-lactalbumin (0.02 to 1.34 g·100 g⁻¹) below recommended concentrations, whereas ĸ-casein (8.28 to 12.91 g·100 g⁻¹), α-casein (0.70 to 2.28 g·100 g⁻¹) and β-lactoglobulin (1.32 to 4.19 g·100 g⁻¹) were detected above recommended concentrations. Essential amino acid quantification indicated that threonine, leucine and phenylalanine were the most abundant amino acids found in the investigated infant formulas. In conclusion, infant formulas are still unconforming to nutritional breast milk quality and must be improved in order to follow current global health authority guidelines.     

Development and cross-validation of a prediction equation for estimating resting energy expenditure in healthy African-American and European-American women

OBJECTIVE: To develop, validate, and cross-validate a formula for predicting resting energy expenditure (REE) in African-American and European-American women. DESIGN: A cross-sectional study of REE in women. Participants were randomly assigned to one of two groups. One group served to develop and validate a new equation for predicting REE while the second was used to cross-validate the prediction equation. The accuracy of the equation was compared to several existing formulae. SETTING: University metabolic laboratory, Memphis, TN, USA. SUBJECTS: Healthy, premenopausal African-American and European-American women between 18 and 39 y of age. The validation sample included 239 women (age: 28.4 y, wt: 70.7 kg, body mass index (BMI): 25.2 kg/m(2), REE: 5840 kJ/day), while the cross-validation sample consisted of 232 women (age: 27.5 y, wt: 70.7 kg, BMI: 25.2 kg/m(2), REE: 5784 kJ/day). RESULTS: The prediction equation derived from the current sample, which included adjustments for ethnicity, was the only formula that demonstrated a high level of accuracy for predicting REE in both African-American and European-American women. The mean difference between REE predicted from the new formula and measured REE was 28 kJ/day (s.d.=668) for European-American women and 142 kJ/day (s.d.=584) for African-American women. CONCLUSIONS: Previous equations for predicting energy needs may not be appropriate for both African-American and European-American women due to ethnic differences in REE. A new equation that makes adjustments in predicted REE based on ethnicity is recommended for determining energy needs in these groups (Predicted REE (kJ/day)=616.93-14.9 (AGE (y))+35.12 (WT (kg))+19.83 (HT (cm))-271.88 (ETHNICITY: 1=African American; 0=European American)). SPONSORSHIP: Support for this study was provided by Grant #HL53261 from the National Heart, Lung, and Blood Institute.     

Energy Expenditure,Protein Oxidation and Body Composition in a Cohort of Very Low Birth Weight Infants

The nutritional management of preterm infants is a critical point of care, especially because of the increased risk of developing extrauterine growth restriction (EUGR), which is associated with worsened health outcomes. Energy requirements in preterm infants are simply estimated, so the measurement of resting energy expenditure (REE) should be a key point in the nutritional evaluation of preterm infants. Although predictive formulae are available, it is well known that they are imprecise. The aim of our study was the evaluation of REE and protein oxidation (Ox) in very low birth weight infants (VLBWI) and the association with the mode of feeding and with body composition at term corrected age. Methods: Indirect calorimetry and body composition were performed at term corrected age in stable very low birth weight infants. Urinary nitrogen was measured in spot urine samples to calculate Ox. Infants were categorized as prevalent human milk (HMF) or prevalent formula diet (PFF). Results: Fifty VLBWI (HMF: 23, PFF: 27) were evaluated at 36.48 ± 0.85 post-conceptional weeks. No significant differences were found in basic characteristics or nutritional intake in the groups at birth and at the assessment. No differences were found in the REE of HMF vs. PFF (59.69 ± 9.8 kcal/kg/day vs. 59.27 ± 13.15 kcal/kg/day, respectively). We found statistical differences in the protein-Ox of HMF vs. PFF (1.7 ± 0.92 g/kg/day vs. 2.8 ± 1.65 g/kg/day, respectively, p < 0.01), and HMF infants had a higher fat-free mass (kg) than PFF infants (2.05 ± 0.26 kg vs. 1.82 ± 0.35 kg, respectively, p < 0.01), measured with air displacement plethysmography. Conclusion: REE is similar in infants with a prevalent human milk diet and in infants fed with formula. The HMF infants showed a lower oxidation rate of proteins for energy purposes and a better quality of growth. A greater amount of protein in HMF is probably used for anabolism and fat-free mass deposition. Further studies are needed to confirm our hypothesis.     

Can Vco2‐Based Estimates of Resting Energy Expenditure Replace the Need for Indirect Calorimetry in Critically Ill Children?

Background: Optimal energy provision, guided by measured resting energy expenditure (REE), is fundamental in the care of critically ill children. REE should be determined by indirect calorimetry (IC), which has limited availability. Recently, a novel equation was developed for estimating REE derived from carbon dioxide production (Vco ₂). The aim of this study was to validate the accuracy of this equation in a population of critically ill children following cardiopulmonary bypass (CPB). Methods: This is an ancillary study to a larger trial of children undergoing CPB. Respiratory mass spectrometry was used measure oxygen consumption (Vo ₂) and Vco ₂. REE was then calculated according to the established Weir equation (REE_W) and the modified, Vco ₂‐based equation (REE_CO2). The agreement between the 2 measurements was assessed using Bland‐Altman plots and mixed‐model regressions accounting for repeated measures. Results: Data from 104 patients, which included 575 paired measurements, were included. The agreement between REE_W and REE_CO2 was biased during the 72‐hour observation period post CPB, with a mean percentage error between measurements of 11% (±7%). The most important determinant of the bias with the Vco ₂‐based equation was the respiratory quotient (RQ). The percentage error between REE_W and REE_CO2 dropped to 4.4% (±2.4%) in those with an RQ between 0.8 and 1. The within‐subject variability for RQ in this cohort was wide (11%). Conclusions: IC remains the most accurate method to determine the REE of critically ill patients. Widespread availability of Vco ₂ data renders Vco ₂‐based approaches to measurement of REE attractive; however, further research is needed to ensure that REE is estimated accurately.     

New equation for the prediction of resting energy expenditure during pregnancy

ObjectiveThe equation for the prediction of resting energy expenditure (REE) during pregnancy is unknown. The aim of this prospective longitudinal study was to determine a new equation for prediction of REE in pregnancy.MethodsA total of 152 randomly recruited healthy pregnant Czech women (nonsmokers, not users of chronic medications or abusers of alcohol or drugs, normoglycemic, euthyroid, and not anemic) were divided into two cohorts: group 1 (n = 31) was used for determination of the equation for calculation of pregnant REE and group 2 (n = 121) for cross-validation of this formula. The REE of the pregnant women in both study groups was examined by indirect calorimetry (REE-IC) along with anthropometry after 12 h of fasting in four periods of pregnancy. A statistical comparison of three basic equations (Harris Benedict, Schofield, and Kleiber) was used for the prediction of REE.ResultsThrough correlation analysis and linear regression, a new predictive equation of REE during pregnancy (P REE) was derived from the Harris Benedict equation. We observed high concordance between values from P REE and REE-IC in group 2. Analysis of alternative predictive equations of REE with the addition of kilocalories and a corrected multiplication factor for each stage of pregnancy expressed low concordance.ConclusionsThe equation for REE in kilocalories during pregnancy, P REE = 346.43943 + 13.962564 × W + 2.700416 × H ? 6.826376 × A (W, weight; H, height; A, age), with SD 116 kcal/d, corresponds closely to REE-IC and maternal changes in each phase of pregnancy. P REE can be applied for prediction of REE during gestation.     

Validity of predictive equations for resting energy expenditure in US and Dutch overweight and obese class I and II adults aged 18-65 y

BACKGROUND: Individual energy requirements of overweight and obese adults can often not be measured by indirect calorimetry. OBJECTIVE: The objective was to analyze which resting energy expenditure (REE) predictive equation was the best alternative to indirect calorimetry in US and Dutch adults aged 18-65 y with a body mass index (in kg/m(2)) of 25 to 40. DESIGN: Predictive equations based on weight, height, sex, age, fat-free mass, and fat mass were tested. REE in Dutch adults was measured with indirect calorimetry, and published data from the Institute of Medicine were used for US adults. The accuracy of the equations was evaluated on the basis of the percentage of subjects predicted within 10% of the REE measured, the root mean squared prediction error (RMSE), and the mean percentage difference (bias) between predicted and measured REE. RESULTS: Twenty-seven predictive equations (9 of which were based on FFM) were included. Validation was based on 180 women and 158 men from the United States and on 154 women and 54 men from the Netherlands aged <65 y with a body mass index (in kg/m(2)) of 25 to 40. Most accurate and precise for the US adults was the Mifflin equation (prediction accuracy: 79%; bias: -1.0%; RMSE: 136 kcal/d), for overweight Dutch adults was the FAO/WHO/UNU weight equation (prediction accuracy: 68%; bias: -2.5%; RMSE: 178), and for obese Dutch adults was the Lazzer equation (prediction accuracy: 69%; bias: -3.0%; RMSE: 215 kcal/d). CONCLUSIONS: For US adults aged 18-65 y with a body mass index of 25 to 40, the REE can best be estimated with the Mifflin equation. For overweight and obese Dutch adults, there appears to be no accurate equation.     

World Health Organization equations have shortcomings for predicting resting energy expenditure in persons from a modern, affluent population: generation of a new reference standard from a retrospective analysis of a German database of resting energy expenditure

BACKGROUND: Reference standards for resting energy expenditure (REE) are widely used. Current standards are based on measurements made in the first part of the past century in various races and locations. OBJECTIVE: The aim of the present study was to investigate the application of the World Health Organization (WHO) equations from 1985 in healthy subjects living in a modern, affluent society in Germany and to generate a new formula for predicting REE. DESIGN: The study was a cross-sectional and retrospective analysis of data on REE and body composition obtained from 2528 subjects aged 5-91 y in 7 different centers between 1985 and 2002. RESULTS: Mean REE varied between 5.63 and 8.07 MJ/d in males and between 5.35 and 6.46 MJ/d in females. WHO prediction equations systematically overestimated REE at low REE values but underestimated REE at high REE values. There were significant and independent effects of sex, age, body mass or fat-free mass, and fat mass on REE. Multivariate regression analysis explained up to 75% of the variance in REE. Two prediction formulas including weight, sex, and age or fat-free mass, fat mass, sex, and age, respectively, were generated in a subpopulation and cross-validated in another subpopulation. Significant deviations were still observed for underweight and normal-weight subjects. REE prediction formulas for specific body mass index groups reduced the deviations. The normative data for REE from the Institute of Medicine underestimated our data by 0.3 MJ/d. CONCLUSIONS: REE prediction by WHO formulas systematically over- and underestimates REE. REE prediction from a weight group-specific formula is recommended in underweight subjects.     

Low validity of predictive equations for calculating resting energy expenditure in overweight and obese women with polycystic ovary syndrome

Background

Predictive equations are the main clinical tools for determining resting energy expenditure (REE ). However, their adequate use in overweight and obese individuals is unclear. Thus, we investigated the best predictive equations for estimating REE in overweight and obese women with polycystic ovary syndrome (PCOS ).

Methods

Eleven analyses were performed with prediction equations (pREE ) based on anthropometric parameters in 30 overweight or obese women with PCOS without other chronic diseases. The measured REE (mREE ) was calculated by indirect calorimetry. The validity of the equations was investigated by comparison, accuracy and agreement tests between pREE and mREE at both the individual and group level.

Results

Four analyses were similar to those of mREE , and smallest mean differences were observed for the World Health Organization/Food and Agriculture Organization of the United Nations/United Nations University (WHO /FAO /UNU ) considering weight (W) [0.07 (1.13) MJ (16 [270] kcal)]. Individual accuracy was greater than 50% for Harris and Benedict, Müller and Lazzer equations. The percentage of REE underestimation ranged between 16.7% and 73.3%, whereas higher rates of overestimation were observed in the De Luis (66.7%) and Ireton‐Jones (43.3%) equations. Mean bias at the group level was lowest in the WHO /FAO /UNU W and WHO /FAO /UNU considering weight and height (WH ), Müller and Lazzer equations (–2.8 to 0.5). The WHO /FAO /UNU W and WHO /FAO /UNU WH formulas were optimal in individual agreement (33.3%).

Conclusions

FAO /WHO /UNU W equations may estimate the REE in overweight and obese women with PCOS . However, the low individual accuracy and agreement in relation to mREE suggest caution regarding when to use the formula to perform an individual nutritional plan.

     

Which REE prediction equation should we use in normal-weight,overweight and obese women?

BACKGROUND & AIMS: In our modern society, there is a growing and increasing prevalence of overweight, obesity and eating disorders and young female subjects frequently ask for nutritional counselling. Resting energy expenditure (REE) is essential to provide a sound diet to subjects seeking nutritional support. We perform a critical selection of accurate and reliable prediction equations employed on normal-weight, overweight and obese young women. METHODS: REE of 157 young women of Caucasian race (18-35 years)was measured with indirect calorimetry and was compared with the principal prediction equations (Harris and Benedict, Owen, Mifflin, WHO, Bernstein and Robertson and Reid). The statistical analysis used to compare measured and the predicted REE was paired t -test, +/-95% confidence interval and Bland and Altman method. The influence of weight loss on the prediction error was estimated in 31 subjects. An additional REE measurement was performed on patients who had lost >or=5% of the initial body weight due to a sound low-calorie diet. RESULTS: The equations more reliable in our study are Owen's equation in normal-weight subjects, Bernstein's equation in overweight subjects and Robertson and Reid's equation in obese subjects. Weight was a significant variable according to the stepwise regression analysis resulting in the following equation: 542.2 + 11.5 kg;R(2) : 0.59. Weight loss decisively increased the overestimation of the equations and only Owen's equation maintained the error of prediction within acceptable limits. CONCLUSIONS: The equation of Owen in normal weight, Bernstein in overweight and of Robertson and Reid in obese subjects should be chosen when we have to predict REE in young women. Due to metabolic adaptation occurring during therapeutic or spontaneous energy restriction, we suggest to use Owen' s equation.     

Which equation best predicts energy expenditure in amyotrophic lateral sclerosis?

Objective

The purpose of this study was to compare measured resting energy expenditure (REE) with estimates from three common prediction equations with the goal of determining which equation best estimates REE in amyotrophic lateral sclerosis (ALS).

Design

Cross-sectional measurements of REE from indirect calorimetry were compared to calculations from the Harris Benedict, Mifflin-St Jeor, and Ireton-Jones equations. Additional measurements to identify predictors of REE included pulmonary function tests, fat-free mass by bioelectrical impedance, and anthropometrics.

Subjects/setting

Participants were 56 men and women with ALS. For comparison, subjects were categorized by disease progression into three groups.

Statistical analyses

Pearson correlations and paired t tests were used to compare measured REE with predicted REE from each equation, and the accuracy of each equation was quantified by the root mean squared prediction error and the percentage of REE estimates within 10% of measured values. Bias for each equation was calculated as the mean percentage difference between calculated and measured REE. Multiple linear regression was used to determine the best predictor variables for REE.

Results

Across the disease spectrum, the Harris Benedict and Mifflin-St Jeor equations provided clinically acceptable estimates of REE, whereas the Ireton-Jones equations consistently overestimated REE. The best predictors of REE among this cohort were fat-free mass, sex, and age.

Conclusions

When estimating energy requirements for patients with ALS, clinicians should choose prediction equations that incorporate sex and age as predictor variables, such as the Harris Benedict and Mifflin-St Jeor equations.     

Elevated Resting Energy Expenditure in Adolescents With Sickle Cell Anemia

Objective To assess the reliability of standard prediction equations in estimating resting energy expenditure (REE) values in adolescents with sickle cell anemia.Subjects/design Body composition and metabolic measurements were performed in 8 adolescents, aged 11 to 18 years, with homozygous sickle cell anemia. REE was measured by indirect calorimetry under standard conditions, and measurements were compared with 4 prediction formulas (Harris-Benedict, Schofield, Mayo Clinic, and Food and Agriculture Organization/World Health Organization/United Nations University). Fat-free mass was measured to assess REE per unit of actively metabolizing tissue. Fat-free mass was expressed as a mean of values obtained by densitometry, deuterium dilution, ⁴⁰K-counting, and total body electrical conductivity.Statistical analyses Repeated measures analysis of variance was performed to determine whether measured REE values and predicted values differed. The Fischer test was used to identify which predicted values differed significantly from the measured REE.Results All 4 prediction formulas significantly underestimated REE. Group mean values for the prediction formulas ranged from 83% to 89% of the measured value. REE averaged 47.7±10.0 kcal/kg fat-free mass per day, which is 30% to 50% higher than reported values in healthy adolescent populations.Conclusions These data suggest that REE is elevated in adolescents with sickle cell anemia. Standard equations used to predict REE are unreliable in these patients.Applications REE in patients with sickle cell anemia is best determined by indirect or direct measurement of energy expenditure. Clinically useful formulas to estimate REE should be developed for patients with conditions, including sickle cell anemia, where the metabolic rate may be altered.J Am Diet Assoc. 1999;99:195–199.     

The Inhibitory Effects of New Zealand Pine Bark (Enzogenol®) on α-Amylase, α-Glucosidase,and Dipeptidyl Peptidase-4 (DPP-4) Enzymes

The New Zealand pine bark extract (Enzogenol^®) has previously been shown to elicit acute hypoglycaemic effects in humans. The present study investigated the underlying mechanisms of Enzogenol^® in reducing postprandial glucose in humans. The potential inhibitory action of Enzogenol^® against digestive enzymes: α-amylase and α-glucosidase, and dipeptidyl peptidase-4 (DPP-4) enzyme was determined. Enzogenol^® demonstrated the ability to inhibit all three enzymes: α-amylase enzyme activity (IC₅₀ 3.98 ± 0.11 mg/mL), α-glucosidase enzyme activity (IC₅₀ 13.02 ± 0.28 μg/mL), and DPP-4 enzyme activity (IC₅₀ 2.51 ± 0.04 mg/mL). The present findings indicate the potential for Enzogenol^® to improve postprandial glycaemia by delaying carbohydrate digestion via the inhibition of digestive enzymes (α-amylase and α-glucosidase), and enhancing the incretin effect via inhibiting the dipeptidyl-peptidase-4 enzyme. The inhibitory actions of Enzogenol^® on enzymes should therefore be further validated in humans for its potential use in type 2 diabetes mellitus prevention and management.     

Biological Variability and Impact of Oral Contraceptives on Vitamins B6, B12 and Folate Status in Women of Reproductive Age

Vitamins B₆, B₁₂ and folate play crucial metabolic roles especially during the reproductive years for women. There is limited reporting of within-subject variability of these vitamins. This study aimed to determine the within and between subject variability in serum vitamins B₆, B₁₂, folate and erythrocyte folate concentrations in young women; identify factors that contribute to variability; and determine dietary intakes and sources of these vitamins. Data were obtained from the control group of a trial aimed at investigating the effect of iron on the nutritional status of young women (age 25.2 ± 4.2 year; BMI 21.9 ± 2.2 kg/m²). The coefficients of variability within-subject (CV_I) and between-subject (CV_G) for serum vitamins B₆, B₁₂ and folate, and erythrocyte folate were calculated. Food frequency questionnaires provided dietary data. CV_I and CV_G were in the range 16.1%–25.7% and 31.7%–62.2%, respectively. Oral contraceptive pill (OCP) use was associated (P = 0.042) with lower serum vitamin B₁₂ concentrations. Initial values were 172 ± 16 pmol/L and 318 ± 51 pmol/L for OCP and non-OCP users, respectively; with differences maintained at four time points over 12 weeks. BMI, age, physical activity, alcohol intake and haematological variables did not affect serum or erythrocyte vitamin concentrations. Vitamin B₁₂ intakes were derived from traditional and unexpected sources including commercial energy drinks. Young women using OCP had significantly lower serum vitamin B₁₂ concentrations. This should be considered in clinical decision making and requires further investigation.     

Energy prediction equations are inadequate for obese Hispanic youth

Assessing energy requirements is a fundamental activity in clinical dietetics practice. A study was designed to determine whether published linear regression equations were accurate for predicting resting energy expenditure (REE) in fasted Hispanic children with obesity (aged 7 to 15 years). REE was measured using indirect calorimetry; body composition was estimated with whole-body air displacement plethysmography. REE was predicted using four equations: Institute of Medicine for healthy-weight children (IOM-HW), IOM for overweight and obese children (IOM-OS), Harris-Benedict, and Schofield. Accuracy of the prediction was calculated as the absolute value of the difference between the measured and predicted REE divided by the measured REE, expressed as a percentage. Predicted values within 85% to 115% of measured were defined as accurate. Participants (n=58; 53% boys) were mean age 11.8±2.1 years, had 43.5%±5.1% body fat, and had a body mass index of 31.5±5.8 (98.6±1.1 body mass index percentile). Measured REE was 2,339±680 kcal/day; predicted REE was 1,815±401 kcal/day (IOM-HW), 1,794±311 kcal/day (IOM-OS), 1,151±300 kcal/day (Harris-Benedict), and, 1,771±316 kcal/day (Schofield). Measured REE adjusted for body weight averaged 32.0±8.4 kcal/kg/day (95% confidence interval 29.8 to 34.2). Published equations predicted REE within 15% accuracy for only 36% to 40% of 58 participants, except for Harris-Benedict, which did not achieve accuracy for any participant. The most frequently accurate values were obtained using IOM-HW, which predicted REE within 15% accuracy for 55% (17/31) of boys. Published equations did not accurately predict REE for youth in the study sample. Further studies are warranted to formulate accurate energy prediction equations for this population.