Accuracy of predictive equations for estimating resting energy expenditure in obese adolescents

Development and validation of novel equation for prediction of resting energy expenditure in active Saudi athletes

Being the most stable component of energy expenditure, resting metabolic rate (RMR) is usually used in the calculation of energy requirements for athletes. An adequate energy prescription is essential in supporting athlete development. This work aims to develop and validate an equation for calculating energy requirements for Arabic Saudi athletes. This cross-sectional study included 171 active athletes aged 18 to 45 years. The sample was divided into a development group (n = 127) and a validation group (n = 44). Anthropometry, indirect calorimetry, and body composition analysis via bioelectric impedance analysis were performed on all participants. The novel predictive equations were created by using stepwise linear regression analyses. The accuracy of the novel equations was compared with 10 equations, and Bland and Altman plots were used to estimate the limits of agreement between measured RMR and novel equations. The first novel equation used a set of basic measures, including weight, gender, and age, was [RMR = 1137.094 + (Wt × 14.560)-(Age × 18.162) + (G × 174.917)] (R = 0.753, and R2 = 0.567, wt = weight, G = gender; for male use 1 and female 0). The second equation used fat-free mass, age, and weight [RMR = 952.828 + (fat-free mass × 10.970)-(Age × 18.648) + (Wt × 10.297)] (R = 0.760 and R2 = 0.577). Validation of the second novel equation increased the prediction of measured RMR to 72.7% and reduced the amount of bias to 138.82 ± 133.18 Kcal. Finally, the new set of equations was designed to fit available resources in clubs and showed up to 72.73% accurate prediction and good agreement with measured RMR by Bland and Altman plots.

Validation of predictive equations for resting energy expenditure in children and adolescents with different body mass indexes

BACKGROUND

Accurate estimation of resting energy expenditure (REE) in children and adolescents is important to establish estimated energy requirements. The objective of this study was to assess the validity of existing equations in literature and a newly developed equation in estimating REE in children and adolescents.

METHODS

275 participants (148 boys, 127 girls) aged 6-18 years included in the study were classified as normal-weighted, overweight, obese based on BMI z-scores for age according to WHO-2007 growth curves for 5-19 years of age. REEs were measured using an indirect calorimeter, with various equations, and a newly established equation [REE = 505.412+(24.383*FFM);Adjusted R2 = 0.649] were compared with REE measured using Bland-Altman and further validation parameters.

RESULTS

When the predicted REEs were compared with the measured REEs, the highest prediction accuracy was achieved using the new Eq. (64.8%) and IOM (63.8%) for normal-weight participants, Müller FFM and new Eq. (59.6%) for overweight participants and Lazzer (44.9%) for obese participants. In normal and overweight participants, lowest root mean squared error (RMSE) values were acquired from Schmelzle's equation (respectively 136.2;159.9 kcal/d), and the highest values were found in Kim's Eq. (315.2; 295.2 kcal/d respectively). RMSE value of the new equation was 174.7 kcal/d for normal-weight children and adolescents, and 201.9 kcal/d for overweight ones. In obese participants, the lowest RMSE value was obtained from Schmelzle's Eq. (305.4 kcal/d) and the new Eq. (317.4 kcal/d), while the highest value was obtained from IOM Eq. (439.9 kcal/d). RMSE was higher in obese groups compared to the other BMI groups.

CONCLUSION

Indirect-calorimeter is the most suitable method for REE measurement in especially obese children and adolescents. The new equation and Schmelzle's equation appear to be most accurate equations for normal and overweight children and adolescents.

Comparison of bioelectrical impedance analysis-derived phase angle in individuals with different weight status

OBJECTIVE

Obesity is characterized not only by an increase of fat mass but also by alterations in skeletal muscle. Bioimpedance analysis (BIA)-derived phase angle (PhA) may provide specific information on the inherent characteristics of fat-free mass, and is widely used as an index of poor nutritional status. The aim of this study was to describe whether and to what extent PhA varies depending on age, sex, and body mass index (BMI) in individuals with different weight status.

METHODS

We selected 1877 participants for this retrospective study (two weight status groups): 983 individuals with obesity (age 40 ± 13.9 y; BMI 39.5 ± 7.2 kg/m²) and 894 controls (age 40 ± 13.3 y; BMI 24.6 ± 2.7 kg/m²). Anthropometry and PhA at 50 kHz for the whole body were performed in all participants.

RESULTS

PhA was greater in men than in women, although a decline of PhA was observed with age, which was linear in women and occurred in men after 40 y of age. On the other hand, no significant differences were observed with increasing BMI in either sex; lower values might be observed when BMI >50 kg/m².

CONCLUSIONS

A more detailed appraisal of BIA-derived PhA in obesity is reported in the present study, providing basic data that might be taken into consideration in prevention and clinical nutrition. Further studies are needed to explore differences of PhA in individuals with different weight status.

Time to achieve steady state for an accurate assessment of resting energy expenditure in adolescents with healthy weight and obesity: A cross-sectional study

Objective

The present study investigated the time needed to achieve a steady state for an accurate assessment of resting energy expenditure (REE) in adolescents with healthy weight and obesity.

Methods

Thirty adolescents aged 12-17 years were assigned to a group with healthy weight (GHW; n = 12, body mass index [BMI] 22.5 ± 3.6 kg/m²) and another group with obesity (GO; n = 18, BMI 34.1 ± 5.2 kg/m²). Participants underwent test-retest reliability of REE assessment as follows: a) 24 h of abstention from physical exercise, soft drinks, or caffeine; b) fasting for ~12 h; c) acclimation period of 10 min; d) 30-min assessment in a supine position.

Results

A significant change occurred during the 30 min in REE. Significant differences existed between consecutive means until the 20^th and 25^th min for the GHW and GO, respectively. Although significant differences between trials 1 and 2 were detected during the first 5-10 min of assessment, the REE for each 5-min time point exhibited high test-retest reliability across trials in both groups (intraclass correlation coefficients range 0.79-0.99).

Conclusion

The following recommendations are provided to promote accurate assessment of REE among adolescents: a) initiate the REE assessment with 10 min of acclimation to decrease restlessness; b) determine REE for a minimum of 20 min if healthy weight and 25 min if obesity; c) determine REE for a further 5 min, with the average of this last 5 min of REE data being regarded as the REE.

Comparison of total energy intakes estimated by 24-hour diet recall with total energy expenditure measured by the doubly labeled water method in adults

BACKGROUND/OBJECTIVES

The doubly labeled water (DLW) method is the gold standard for estimating total energy expenditure (TEE) and is also useful for verifying the validities of dietary evaluation tools. In this study, we compared the accuracy of total energy intakes (TEI) estimated by the 24-h diet recall method with TEE obtained using the doubly labeled water method.

SUBJECTS/METHODS

This study involved 71 subjects aged 20–49 yrs. Over a 14-day period, three 24-h diet recalls per subject (2 weekdays and 1 weekend day) were used to estimate energy intakes, while TEE was measured using the DLW method. The paired t-test was used to determine the significance of differences between TEI and TEE results, and the accuracy of the 24-h recall method was determined by accuracy predictions percentage, root mean square error, and bias.

RESULTS

Average study subject age was 33.4 ± 8.6 yrs. The association between TEI and TEE was positive and significant (r = 0.463, P < 0.001), and the difference between TEI (2,084.3 ± 684.2 kcal/day) and TEE (2,401.7 ± 480.3 kcal/day) was also significant (P < 0.001). In all study subjects, mean TEI was 12.0% (307.5 ± 629.3 kcal/day) less than mean TEE, and 12.2% (349.4 ± 632.5 kcal/day) less in men and 11.8% (266.7 ± 632.5 kcal/day) less in women. Rates of TEI underprediction for all study subjects, men, and women, were 60.5%, 51.4%, and 66.7%, respectively.

CONCLUSIONS

This study shows that 24-h diet recall underreports energy intakes. More research is needed to corroborate our findings and evaluate the accuracy of 24-h recall with respect to additional demographics.

Resting Energy Expenditure and Body Composition in Children and Adolescents With Genetic, Hypothalamic, Medication-Induced or Multifactorial Severe Obesity

BACKGROUND

Pediatric obesity is a multifactorial disease which can be caused by underlying medical disorders arising from disruptions in the hypothalamic leptin-melanocortin pathway, which regulates satiety and energy expenditure.

AIM

To investigate and compare resting energy expenditure (REE) and body composition characteristics of children and adolescents with severe obesity with or without underlying medical causes.

METHODS

This prospective observational study included pediatric patients who underwent an extensive diagnostic workup in our academic centre that evaluated endocrine, non-syndromic and syndromic genetic, hypothalamic, and medication-induced causes of obesity. REE was assessed by indirect calorimetry; body composition by air displacement plethysmography. The ratio between measured REE (mREE) and predicted REE (Schofield equations), REE%, was calculated, with decreased mREE defined as REE% ≤90% and elevated mREE ≥110%. Additionally, the influence of fat-free-mass (FFM) on mREE was evaluated using multiple linear regression.

RESULTS

We included 292 patients (146 [50%] with body composition measurements), of which 218 (75%) patients had multifactorial obesity and 74 (25%) an underlying medical cause: non-syndromic and syndromic genetic (n= 29 and 28, respectively), hypothalamic (n= 10), and medication-induced (n= 7) obesity. Mean age was 10.8 ± 4.3 years, 59% were female, mean BMI SDS was 3.8 ± 1.1, indicating severe obesity. Mean REE% was higher in children with non-syndromic genetic obesity (107.4% ± 12.7) and lower in children with hypothalamic obesity (87.6% ± 14.2) compared to multifactorial obesity (100.5% ± 12.6, both p<0.01). In 9 children with pseudohypoparathyroidism type 1a, mean REE% was similar (100.4 ± 5.1). Across all patients, mREE was decreased in 60 (21%) patients and elevated in 69 (24%) patients. After adjustment for FFM, mREE did not differ between patients within each of the subgroups of underlying medical causes compared to multifactorial obesity (all p>0.05).

CONCLUSIONS

In this cohort of children with severe obesity due to various etiologies, large inter-individual differences in mREE were found. Consistent with previous studies, almost half of patients had decreased or elevated mREE. This knowledge is important for patient-tailored treatment, e.g. personalized dietary and physical activity interventions and consideration of pharmacotherapy affecting central energy expenditure regulation in children with decreased mREE.

Resting energy expenditure in elite athletes: development of new predictive equations based on anthropometric variables and bioelectrical impedance analysis derived phase angle

Background

An accurate estimation of athletes’ energy needs is crucial in diet planning to improve sport performance and to maintain an appropriate body composition. This study aimed to develop and validate in elite athletes new equations for estimating resting energy expenditure (REE) based on anthropometric parameters as well as bioimpedance analysis (BIA)-derived raw variables and to validate the accuracy of selected predictive equations.

Methods

Adult elite athletes aged 18–40 yrs were studied. Anthropometry, indirect calorimetry and BIA were performed in all subjects. The new predictive equations were generated using different regression models. The accuracy of the new equations was assessed at the group level (bias) and at the individual level (precision accuracy), and then compared with the one of five equations used in the general population or three athletes-specific formulas.

Results

One-hundred and twenty-six male athletes (age 26.9 ± 9.1 yrs; weight 71.3 ± 10.9 kg; BMI 22.8 ± 2.7 kg/m²) from different sport specialties were randomly assigned to the calibration (n = 75) or validation group (n = 51). REE was directly correlated with individual characteristics, except for age, and raw BIA variables. Most of the equations from the literature were reasonably accurate at the population level (bias within ±5%). The new equations showed a mean bias −0.3% (Eq. A based on anthropometric parameters) and −0.6% (Eq. B based on BIA-derived raw variables). Precision accuracy (individual predicted-measured differences within ±5%) was ~75% in six out of eight of the selected equations and even higher for Eq. A (82.4%) and Eq. B (92.2%).

Conclusion

In elite athletes, BIA-derived phase angle is a significant predictor of REE. The new equations have a very good prediction accuracy at both group and individual levels. The use of phase angle as predictor of REE requires further research with respect to different sport specialties, training programs and training level.

Resting Energy Expenditure of Physically Active Boys in Southeastern Poland-The Accuracy and Validity of Predictive Equations

Optimization of energy intake in the diet of young athletes is of primary importance. In addition to the energy expenditure associated with their body development, the demand resulting from intensive physical activity also increases. The aim of this study was to compare the accuracy of formulas commonly used for resting energy expenditure (REE) calculations with values obtained from measurements using indirect calorimetry among male children and adolescents practicing football. The study was conducted among 184 boys aged 9 to 17 using a calorimeter and a device for assessing body composition by means of electrical bioimpedance using a segment analyzer. The mean error ranged from −477 kcal/d by the Maffeis formula to −182 kcal/d for the Institute of Medicine of the National Academies (IMNA) formula. A statistically significant difference was found for all formulas in the calculated value in relation to the measured REE value (p < 0.0001). Most “ready-to-use” formulas underestimate REE, which can be a risk in determining the total energy demand in a group that requires more calories, especially when due to intensive growth and development and the expenditure associated with regular training and increased physical activity.

Effects of High-Dose Selenium Supplementation on Oxidative Stress and Inflammatory Markers in Critically Ill Children After Gastrointestinal Surgery: A Randomized Clinical Trial

Background: Pediatric observational studies have indicated that most critically ill children have low serum selenium level, which is associated with the increased incidence of multiple organ failure and deteriorated clinical outcomes. Selenium plays a key role in the endogenous antioxidant defense mechanism and inflammatory pathways. Objectives: The present study aimed to assess the effects of high-dose selenium supplementation on the improvement of inflammatory and oxidative stress indices, as well as clinical outcomes, in pediatric patients with severe oxidative stress and inflammation following major gastrointestinal surgeries. Methods: This prospective, single-blind, randomized, parallel group superiority trial was conducted at the pediatric intensive care unit (PICU) of Akbar Pediatric Hospital in Mashhad, Iran in 2019. Patients were assigned to the supplementation (high-dose selenium: 20 µg/kg/d) and control groups (placebo with the recommended dietary allowance doses of selenium) using stratified blocks. Among 72 eligible critically ill children after gastrointestinal surgery, 66 patients completed the study. Inflammatory markers were measured and compared between the groups, including high-sensitivity C-reactive protein (hsCRP), interleukin 1 beta (IL-1β), prooxidant-antioxidant balance (PAB) assay, and clinical outcomes. Data analysis was performed in SPSS version 20 using the intention-to-treat approach. Results: Only 14 patients had optimal serum selenium concentrations before the surgery and PICU admission. At the end of the study, 90.6% of the patients (n = 29) in the intervention group and 100% (n = 34) of those in the placebo group had suboptimal serum selenium levels (< 50 ng/mL). Although supplementation with high-dose selenium decreased the inflammatory markers in the post-surgical critically ill children (-18 mg/mL and -37.5 pg/mL for hsCRP and IL-1β, respectively), the administered dose could not improve the serum glutathione peroxidase (GPx) concentrations as the selenium functional marker, as well as the PAB assay as the single test to assess the balance/imbalance of the oxidants and antioxidants simultaneously. Additionally, clinical outcomes such as infections, length of ICU stay, and 28-day mortality did not improve after the intervention. Conclusions: According to the results, high-dose selenium supplementation (20 µg/kg/d) in the post-surgical critically ill children could improve the serum inflammatory markers. However, the changes were suboptimal with no significant effects of the serum GPx concentrations, antioxidant defense system, and clinical outcomes.

External Validation of Equations to Estimate Resting Energy Expenditure in 2037 Children and Adolescents with and 389 without Obesity: A Cross-Sectional Study

We performed an external cross-validation study of 10 equations to estimate resting energy expenditure (REE) in 2037 children with and 389 without obesity. Inclusion criteria were Caucasian ethnicity, age ≤ 18 years, and availability of REE. REE was measured using indirect calorimetry. The correct classification fraction (CCF) of an equation was defined as the fraction of subjects whose estimated REE was within 10% of measured REE. The Molnár equation was the most accurate REE prediction equation with CCFs of 0.70 (95% CI 0.65 to 0.76) in girls without obesity, 0.64 (95% CI 0.61 to 0.66) in girls with obesity, 0.76 (95% CI 0.67 to 0.83) in boys without obesity, and 0.66 (95% CI 0.63 to 0.69) in boys with obesity. The Mifflin equation was the second most accurate equation with CCFs of 0.67 (95% CI 0.61 to 0.73) in girls without obesity, 0.61 (95% CI 0.58 to 0.64) in girls with obesity, 0.75 (95% CI 0.66 to 0.82) in boys without obesity, and 0.66 (95% CI 0.63 to 0.69) in boys with obesity.

Validity of the dietary reference intakes for determining energy requirements in older adults

BACKGROUND/OBJECTIVES

The objectives of this study were to evaluate the accuracy of the Dietary Reference Intakes (DRI) for estimating the energy requirements of older adults, and to develop and validate new equations for predicting the energy requirements of this population group.

MATERIALS/METHODS

The study subjects were 25 men and 23 women with a mean age of 72.2 ± 3.9 years and 70.0 ± 3.3 years, and mean BMI of 24.0 ± 2.1 and 23.9 ± 2.7, respectively. The total energy expenditure (TEE) was measured by using the doubly labeled water (DLW) method, and used to validate the DRI predictive equations for estimated energy requirements (EER) and to develop new EER predictive equations. These developed equations were cross-validated by using the leave-one-out technique.

RESULTS

In men, the DRI equation had a -7.2% bias and accurately predicted the EER (meaning EER values within ±10% of the measured TEE) for 64% of the subjects, whereas our developed equation had a bias of -0.1% and an accuracy rate of 84%. In women, the bias was -6.6% for the DRI equation and 0.2% for our developed equation, and the accuracy rate was 74% and 83%, respectively. The predicted EER was strongly correlated with the measured TEE, for both the DRI equations and our developed equations (Pearson's r = 0.915 and 0.908, respectively).

CONCLUSIONS

The DRI equations provided an acceptable prediction of EER in older adults and these study results therefore support the use of these equations in this population group. Our developed equations had a better predictive accuracy than the DRI equations, but more studies need to be performed to assess the performance of these new equations when applied to an independent sample of older adults.

Handheld Indirect Calorimetry as a Clinical Tool for Measuring Resting Energy Expenditure in Children with and without Obesity

Background: Resting energy expenditure (REE) is a valuable measure in clinical management of obesity and other chronic illnesses. Gold standard methods for measuring REE (e.g., Douglas bags and metabolic cart) are too expensive and cumbersome for an outpatient clinical setting. The purpose of this study was to determine the accuracy of a handheld indirect calorimeter (HHIC) and prediction equations (PEs) for measurement of REE in youth with and without obesity. Methods: Fifty-three children and adolescents (12.8 ± 4.3 years, 50.9% female) had REE measured first with a MedGem™ HHIC for 10 minutes, followed by a reference indirect calorimeter system (ParvoMedics TrueOne 2400™) with hood canopy and dilution pump for 30 minutes. REE was also estimated using nine PEs as follows: Henry-1, Henry-2, Schofield, World Health Organization, Molnar, Muller, Herrmann, Schmelzle, and Harris-Benedict. Concordance correlation coefficients and Bland-Altman analyses were used for comparisons among PEs, MedGem HHIC, and metabolic cart. Results: The observed correlation between the HHIC and the reference system was rc = 0.89 with a mean bias of 2.27 ± 3.41 kcal/(kg·d) (9.1% ± 14.7%). Regarding PE, Molnar had the highest agreement with the reference system [rc = 0.93, bias of 2.17 ± 2.04 kcal/(kg·d); 9.8% ± 8.1%], followed by Harris-Benedict (rc = 0.89; 13.8% ± 8.9%), Henry-2 (rc = 0.89; 15% ± 7.6%), and Henry-1 (rc = 0.86; 16.7% ± 7.3%). All PEs were less accurate for children with overweight/obesity. Conclusions: Compared to PE, the HHIC provided more accurate REE estimates for children across the age and BMI spectrum, although positive bias was present throughout. Difference in positive bias between the HHIC and the Molnar equation may be clinically significant for youth with overweight/obesity.

Are Raw BIA Variables Useful for Predicting Resting Energy Expenditure in Adults with Obesity?

This study aimed to develop and validate new predictive equations for resting energy expenditure (REE) in a large sample of subjects with obesity also considering raw variables from bioimpedance-analysis (BIA). A total of 2225 consecutive obese outpatients were recruited and randomly assigned to calibration (n = 1680) and validation (n = 545) groups. Subjects were also split into three subgroups according to their body mass index (BMI). The new predictive equations were generated using two models: Model 1 with age, weight, height, and BMI as predictors, and Model 2 in which raw BIA variables (bioimpedance-index and phase angle) were added. Our results showed that REE was directly correlated with all anthropometric and raw-BIA variables, while the correlation with age was inverse. All the new predictive equations were effective in estimating REE in both sexes and in the different BMI subgroups. Accuracy at the individual level was high for specific group-equation especially in subjects with BMI > 50 kg/m². Therefore, new equations based on raw-BIA variables were as accurate as those based on anthropometry. Equations developed for BMI categories did not substantially improve REE prediction, except for subjects with a BMI > 50 kg/m². Further studies are required to verify the application of those formulas and the role of raw-BIA variables for predicting REE.

Comparison of Measured and Estimated Resting Energy Expenditure in Adolescents and Young Adults With Severe Obesity Before and 1 Year After Sleeve Gastrectomy

Introduction: Resting energy expenditure (REE) is often evaluated in adults and adolescents with obesity to estimate caloric requirements when advising dietary changes. However, data are lacking regarding the accuracy of methods used to clinically assess REE in adolescents with severe obesity. Moreover, there are no data regarding the effects of sleeve gastrectomy (SG) on REE in adolescents. We evaluated the accuracy and error rate between estimated and measured REE in adolescents with severe obesity and changes in REE following (SG). Materials and Methods: Cross-sectional study (CSS): 64 adolescents and young adults, 14-22 years old, with moderate to severe obesity were enrolled. We measured REE (mREE) by indirect calorimetry and estimated REE (eREE) using Derumeaux (Deru), Mifflin-St Jeor (MS), Harris Benedict (HB), and World Health Organization (WHO) equations. DXA was used to determine body composition. Bland Altman analysis evaluated agreement between eREE and mREE. Longitudinal study: 12 subjects had repeat indirect calorimetry and DXA 1 year after SG. Longitudinal analysis was used to assess changes in REE and body composition. Results: CSS: Median BMI was 45.2 kg/m² and median age was 18.0 (16.3-19.9) years. mREE correlated strongly with eREE . Bland Altman analysis demonstrated that only a few points were beyond the 1.96 SD limit of disagreement. However, there was considerable overestimation of mREE by most equations. Longitudinal Study: In the subset that underwent SG, after 12-months, absolute REE decreased from 1709 (1567.7-2234) to 1580.5 (1326-1862.5) Calories (p = 0.002); however, the ratio of REE/Total Body Weight (TBW) increased from 13.5 ± 2.3 at baseline to 15.5 ± 2.2 at 1 year (p = 0.043). When evaluating parameters affecting % total weight loss, we found that it correlated positively with REE/TBW at 12 months (R = 0.625; p = 0.03) and negatively with % fat mass at 12 months (R = -0.669; p = 0.024). Discussion: In adolescents with moderate-severe obesity, despite a correlation between mREE using indirect calorimetry and eREE using the Deru, MS, HB, and WHO equations, there is significant over-estimation of REE at the individual level, challenging their clinical utility. One year after SG, REE/TBW increased and strongly correlated with % total weight loss in adolescents.

Validity of predictive equations for resting energy expenditure in Korean non-obese adults

BACKGROUND/OBJECTIVES

Indirect calorimetry is the gold-standard method for the measurement of resting energy expenditure. However, this method is time consuming, expensive, and requires highly trained personnel. To overcome these limitations, various predictive equations have been developed. The objective of this study was to assess the validity of predictive equations for resting energy expenditure (REE) in Korean non-obese adults.

SUBJECTS/METHODS

The present study involved 109 participants (54 men and 55 women) aged between 20 and 64 years. The REE was measured by indirect calorimetry. Nineteen REE equations were evaluated for validity, by comparing predicted and measured REE results. Predictive equation accuracy was assessed by determining percent bias, root mean squared prediction error (RMSE), and percentage of accurate predictions.

RESULTS

The measured REE was significantly higher in men than in women (P < 0.001), but the difference was not significant after adjusting for body weight (P > 0.05). The equation developed in this study had an accuracy rate of 71%, a bias of 0%, and an RMSE of 155 kcal/day. Among published equations, the FAOweight equation gave the highest accuracy rate (70%), along with a bias of -4.4% and an RMSE of 184 kcal/day.

CONCLUSIONS

The newly developed equation provided the best accuracy in predicting REE for Korean non-obese adults. Among the previously published equations, the FAOweight equation showed the highest overall accuracy. Regardless, at an individual level, the equations could lead to inaccuracies in a considerable number of subjects.

Evaluating the predictive factors of resting energy expenditure and validating predictive equations for Chinese obese children

BACKGROUND

To study the predictive factors of resting energy expenditure (REE) and evaluate the accuracy of predicted equations with indirect calorimeter (IC) in Chinese school-age children, particularly for the obese population.

METHODS

Recruited children were from the department of child healthcare in Nanjing children's hospital during July 2014-September 2015. Anthropometric parameters and body composition were measured by bioelectrical impedance. Measured REE was assessed by IC. Predicted REE was estimated using ten published equations.

RESULTS

248 children aged 7-13 years were recruited, including 148 obese [body mass index standard deviation score (BMISDS) = 2.48 ± 0.91] and 100 non-obese (BMISDS = - 0.96 ± 1.08). The unit mass of REE (REE/kg) in obese group (29.06 ± 5.74) was lower than that in non-obese group (37.51 ± 6.56). The stepwise regression showed that age, BMISDS and fat-free mass (FFM) had a major impact on REE/kg as the regression equation: Y = 54.41 - 1.36 × X₁ - 2.25 × X₂ - 0.16 × X₃ (Y REE/kg, X₁ age, X₂ BMISDS, X₃ FFM; R = 0.633, R² = 0.401, P < 0.01). The accuracy of predicted REE in obese subjects was 62.16% by the new predictive equations.

CONCLUSIONS

The REE/kg in obese children was lower and closely correlated with age, BMISDS and FFM. It is necessary to validate the new predictive equation in a larger sample to estimate energy requirements, particularly for children with obesity.

Estimating Resting Energy Expenditure by Different Methods as Compared With Indirect Calorimetry for Patients With Pulmonary Hypertension

BACKGROUND

For patients with pulmonary hypertension, nutrition status is an independent predictor of morbidity and mortality, and energy expenditure can be strongly influenced by lung disease. Indirect calorimetry (IC) is the gold standard for measuring resting energy expenditure (REE), this study aimed to compare the results of REE estimated by different methods with those obtained by IC for patients with pulmonary hypertension.

METHODS

In this cross-sectional study (n = 34), REE was estimated by bioelectrical impedance analysis and the predictive equations of Harris-Benedict, Food and Agriculture Organization / World Health Organization, Institute of Medicine, Cunningham, Katch-McArdle, and Mifflin-St Jeor.

RESULTS

Mean patient age was 47.0 ± 14.5 years, and 76.5% were women. REE obtained with IC was strongly correlated with all other estimation methods but showed higher mean values: IC 1750.8 ± 434.3 kcal vs bioelectrical impedance analysis, 1549.0 ± 417.8 kcal; Harris-Benedict, 1493.1 ± 337.0 kcal; FAO/WHO, 1536.1 ± 345.0 kcal; Institute of Medicine, 1457.1 ± 293.2 kcal; Cunningham, 1597.3 ± 292.3 kcal; Katch-McArdle, 1447.7 ± 287.0 kcal; and Mifflin-St Jeor, 1388.7 ± 303.9 kcal. The analysis of agreement showed a clinically significant bias of approximately -255 kcal in all estimation methods when compared with IC.

CONCLUSION

Although there was a strong correlation between REE estimation methods and IC, there was no agreement between them. All estimation methods underestimated energy needs by about 255 kcal for patients with pulmonary hypertension, and the Cunningham equation had the smallest difference in relation to IC.

Validation of dietary reference intake equations for estimating energy requirements in Korean adults by using the doubly labeled water method

BACKGROUND/OBJECTIVES

The doubly labeled water (DLW) method is considered the gold standard for the measurement of total energy expenditure (TEE), which serves to estimate energy requirements. This study evaluated the accuracy of predictive dietary reference intake (DRI) equations for determining the estimated energy requirements (EER) of Korean adults by using the DLW as a reference method.

SUBJECTS/METHODS

Seventy-one participants (35 men and 36 women) aged between 20 and 49 years were included in the study. The subjects' EER, calculated by using the DRI equation (EER_DRI), was compared with their TEE measured by the DLW method (TEE_DLW).

RESULTS

The DRI equations for EER underestimated TEE by -36.3 kcal/day (-1.3%) in men and -104.5 kcal/day (-4.9%) in women. The percentages of accurate predictions among subjects were 77.1% in men and 62.9% in women. There was a strong linear correlation between EER_DRI and TEE_DLW (r=0.783, P<0.001 in men and r=0.810, P<0.001 in women).

CONCLUSIONS

The present study supports the use of DRI prediction equations to determine EER in Korean adults. More studies are needed to confirm our results and to assess the validity of these equations in other population groups, including children, adolescents, and older adults.

Prediction and evaluation of resting energy expenditure in a large group of obese outpatients

Background/Objectives:

The aim of this study was to compare resting energy expenditure (REE) measured (MREE) by indirect calorimetry (IC) and REE predicted (PREE) from established predictive equations in a large sample of obese Caucasian adults.

Subjects/Methods:

We evaluated 1851 obese patients (body mass index (BMI)>30 kg m⁻²) aged between 18a and 65 years. Data were obtained by comparing MREE with PREE, derived from different equations, within and between normal weight and obese groups. The mean differences between PREE and MREE as well as the accuracy prediction within ±10% level were investigated in the whole sample and in three subgroups, classified by BMI (Group 1=30–39.9 kg m⁻²; Group 2=40–49.9 kg m⁻²; Group 3>50 kg m⁻²).

Results:

We observed that FAO, Henry and Muller3 (body composition (BC)) equations provided good mean PREE–MREE (bias −0.7, −0.3 and 0.9% root mean standard error (RMSE) 273, 263 and 269 kcal per day, respectively); HB and Henry equations were more accurate individually (57 and 56.9%). Only the Muller1 (BC) equation gave the lowest PREE–MREE difference (bias −1.7% RMSE 228 kcal per day) in females, while Johnstone and De Lorenzo equations were the most accurate (55.1 and 54.8%). When the sample was split into three subgroups according to BMI, no differences were found in males; however, the majority of the equations included in this study failed to estimate REE in severely obese females (BMI>40 kg m⁻²). Overall, prediction accuracy was low (~55%) for all predictive equations, regardless of BMI.

Conclusions:

Different established equations can be used for estimating REE at the population level in both sexes. However, the accuracy was very low for all predictive equations used, particularly among females and when BMI was high, limiting their use in clinical practice. Our findings suggest that the validation of new predictive equations would improve the accuracy of REE prediction, especially for severely obese subjects (BMI>40 kg m⁻²).

Resting Energy Expenditure in Adults with Becker's Muscular Dystrophy

PURPOSE

The purpose of this study was: 1) To compare Resting energy expenditure (REE) in adult males with Becker's Muscular Dystrophy (BeMD, n = 21, 39 ±12 years) and healthy controls (CTRL, n = 12, 37 ±12 years) 2) Determine whether other physiological parameters correlate with REE in BeMD, and 3) Compare current prediction methods of REE with measured REE.

METHODS

REE was calculated via indirect calorimetry using continuous, expired gas analysis following an overnight fast. Fat free mass (FFM) and fat mass were measured by bioelectrical impedance. B-mode ultrasound measured Tibialis Anterior (TA) and Gastrocnemius Medialis (GM) anatomical cross sectional area (ACSA). The Bone Specific Physical Activity Questionnaire measured physical activity.

RESULTS

No difference in REE was found between CTRL and BeMD groups (1913 ±203 & 1786 ±324 Kcal respectively). Other physiological comparisons showed increased fat mass (+54%), decreased TA ACSA (-42%), increased GM ACSA (+25%) as well as reduced respiratory function (FVC -28%; FEV1-27%) in BeMD adults compared to controls. REE estimated from prediction equations (Schofield's) in Muscular Dystrophy were different from measured REE (P<0.05, bias = -728kcal), while the Mifflin equation was no different from measured REE (r2 = 0.58, Bias = -8kcal). Within the present BeMD, REE predicted from FFM (REE = FFM x 34.57-270; r2 = 0.85) and body mass (REE = BM x 15.65 + 421.5; r2 = 0.66), were not different from measured REE (bias equals 0 and 0.2kcals, respectively).

CONCLUSIONS

Despite no differences in REE between CTRL and BeMD adults, increased fat masses highlights the requirement for explicit nutritional guidelines, as well as maintenance of physical activity levels, where possible. Prediction equations are frequently used in clinical settings, however these have been shown to be less accurate in BeMD; therefore, the equations proposed here should be used where possible.

Resting Energy Expenditure of Children and Adolescents With Nonalcoholic Fatty Liver Disease

BACKGROUND

The mainstay of treatment for pediatric nonalcoholic fatty liver disease (NAFLD) is lifestyle modification, which includes dietary changes that lead to slow but sustained weight loss or weight stabilization in growing children. Accurate estimation of energy requirements is necessary to achieve this goal. The objective of this study was to assess the accuracy of the most commonly used equations in predicting the resting energy expenditure (REE) of children with NAFLD.

METHODS

This was a retrospective study performed in a single institution. The predictive accuracy of various equations was assessed by comparing their estimates against the measured REE obtained with indirect calorimetry. Accuracy was defined as an estimate within 10% of measured REE.

RESULTS

Fifty-six children (70% male; 52% white and 36% Asian) with a median age of 13 years were included. The median measured REE was 1829 kcal/d. Of the equations studied, the Schofield had the smallest average bias (-32 kcal/d; confidence interval, -121 to 56). The Schofield and Molnar equations were the most accurate, providing REE estimates within 10% of measured in 59% of cases. The remaining equations had lower and variable predictive accuracy. The use of adjusted body weight in predictive equations did not improve the predictive accuracy.

CONCLUSION

In a cohort of children and adolescents with NAFLD, the Schofield and Molnar equations performed best in predicting energy expenditure. However, predictive equations were often inaccurate, suggesting that clinicians should interpret their results with caution and consider using indirect calorimetry when available.