Estimation of Resting Energy Expenditure: Validation of Previous and New Predictive Equations in Obese Children and Adolescents

Prediction of resting energy expenditure for adolescents with severe obesity: A multi-centre analysis

BACKGROUND AND OBJECTIVES

Resting energy expenditure (REE) assessments can help inform clinical treatment decisions in adolescents with elevated body mass index (BMI), but current equations are suboptimal for severe obesity. We developed a predictive REE equation for youth with severe obesity and obesity-related comorbidities and compared results to previously published predictive equations.

METHODS

Data from indirect calorimetry, clinical measures, and body composition per Dual x-ray absorptiometry (DXA) were collected from five sites. Data were randomly divided into development (N = 438) and validation (N = 118) cohorts. A predictive equation was developed using Elastic Net regression, using sex, race, ethnicity, weight, height, BMI percent of the 95th%ile (BMIp95), waist circumference, hip circumference, waist/hip ratio, age, Tanner stage, fat and fat-free mass. This equation was verified in the validation cohort and compared with 11 prior equations.

RESULTS

Data from the total cohort (n = 556, age 15 ± 1.7 years, 77% female, BMIp95 3.3 ± 0.94) were utilized. The best fit equation was REE = -2048 + 18.17 × (Height in cm) - 2.57 × (Weight in kg) + 7.88 × (BMIp95) + 189 × (1 = male, 0 = female), R2 = 0.466, and mean bias of 23 kcal/day.

CONCLUSION

This new equation provides an updated REE prediction that accounts for severe obesity and metabolic complications frequently observed in contemporary youth.

Accuracy of equations for estimating resting energy expenditure in children and adolescents living with phenylketonuria

BACKGROUND

Measuring resting energy expenditure (REE) in individuals living with phenylketonuria (PKU) using indirect calorimetry (IC) is unusual in healthcare facilities because it requires specific protocols and expensive equipment. Considering that determining REE is crucial for devising nutritional strategies for the management of PKU, the aim of this study was to identify the predictive equations that provide the best estimates of REE in children and adolescents living with PKU and to propose a predictive equation for determining REE in this population.

METHODS

An REE concordance study was conducted with children and adolescents living with PKU. Anthropometric and body composition assessments using bioimpedance and REE assessment using IC were performed. The results were compared to 29 predictive equations.

RESULTS

Fifty-four children and adolescents were evaluated. The REE obtained using IC differed from all estimated REE, except Henry's equation for male children (p = 0.058). Only this equation showed good agreement (0.900) with IC. Eight variables were associated with the REE obtained using IC with emphasis on fat-free mass (kg) (r = 0.786), weight (r = 0.775), height (r = 0.759) and blood phenylalanine (r = 0.503). With these variables, three REE equations were suggested, with R2  = 0.660, 0.635 and 0.618, respectively, and the third equation, which involves weight and height, showed adequate sample size for a statistical power of 0.942.

CONCLUSION

Most equations, not specific for individuals living with PKU, overestimate the REE of this population. We propose a predictive equation for assessing REE for children and adolescents living with PKU to be used in settings where IC is not available.

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.

Time-restricted eating (16/8) and energy-restricted diet: effects on diet quality, body composition and biochemical parameters in healthy overweight females

BACKGROUND

Time-restricted eating (TRE) is a current popular dietary strategy for noncommunicable diseases. However, studies demonstrated contradictory results for it and in all dietary strategies, diet quality is an the important part of the well-being. Our study aimed to investigate the effect of TRE and energy-restricted diet (ERD) on the nutritional status and diet quality of individuals.

METHODS

This pilot study was completed 23 healthy overweight female. Anthropometric and body composition measurements of individuals were taken. The energy expenditure was measured using indirect calorimetry. Blood pressure and heart rate measurements were made. Biochemical parameters were evaluated and food consumption were taken. The quality of dietary intake was assessed using the Healthy Eating Index (HEI) -2015. The physical activity levels of the individuals were estimated using the physical activity record. The Statistical Package for the Social Sciences (version 22.0) software was used for all analyses. A p-value of less than 0.05 was considered to be statistically significant.

RESULTS

After 8 weeks of intervention, while no change was observed in the diet quality of the individuals in the TRE group (p > 0.05), a significant increase was found in the diet quality score of the individuals in the ERD group (p < 0.05). There was a 3.2% and 5.5% decrease in body weight of individuals in the TRE and ERD groups, respectively (p < 0.05). While no significant change was observed in the body fat percentage of individuals in the TRE group (p > 0.05), a 7.1% decrease was observed in the ERD group (p < 0.05). A statistically significant decrease was found in the total cholesterol (3.7%) in the ERD group, and in the total cholesterol (6.7%) and low density lipoprotein cholesterol (LDL-C) (6.5%) in the TRE group. In addition, a statistically significant increase was found in adiponectin (77.3%) and total antioxidant status (TAS) (13.2%) in the ERD group.

CONCLUSION

Energy-restricted diet yielded better results in weight loss and improvement of body composition and diet quality compared to TRE. Also, a decrease in total cholesterol level was found in the ERD group. However, more studies should be done with longer follow-ups and high sample sizes are very important in terms of creating public health-based recommendations.

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 Prediction Equations in the Pediatric Population: A Systematic Review

Background and Aims: The determination of energy requirements is necessary to promote adequate growth and nutritional status in pediatric populations. Currently, several predictive equations have been designed and modified to estimate energy expenditure at rest. Our objectives were (1) to identify the equations designed for energy expenditure prediction and (2) to identify the anthropometric and demographic variables used in the design of the equations for pediatric patients who are healthy and have illness. Methods: A systematic search in the Medline/PubMed, EMBASE and LILACS databases for observational studies published up to January 2021 that reported the design of predictive equations to estimate basal or resting energy expenditure in pediatric populations was carried out. Studies were excluded if the study population included athletes, adult patients, or any patients taking medications that altered energy expenditure. Risk of bias was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Results: Of the 769 studies identified in the search, 39 met the inclusion criteria and were analyzed. Predictive equations were established for three pediatric populations: those who were healthy (n = 8), those who had overweight or obesity (n = 17), and those with a specific clinical situation (n = 14). In the healthy pediatric population, the FAO/WHO and Schofield equations had the highest R ² values, while in the population with obesity, the Molnár and Dietz equations had the highest R ² values for both boys and girls. Conclusions: Many different predictive equations for energy expenditure in pediatric patients have been published. This review is a compendium of most of these equations; this information will enable clinicians to critically evaluate their use in clinical practice. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=226270, PROSPERO [CRD42021226270].

A Comparison of the Indirect Calorimetry and Different Energy Equations for the Determination of Resting Energy Expenditure of Patients With Renal Transplantation

OBJECTIVE

We aimed to evaluate the agreement between the resting energy expenditure (REE) obtained by indirect calorimetry and eight prediction equations in adult patients with renal transplantation and a newly developed REE prediction equation for use in patients with renal transplantation in the clinic.

METHODS

A total of 51 patients (30 males and 21 females) were involved in the study. The REE was measured by indirect calorimetry and compared with the previous prediction equations. The agreement was assessed by the interclass correlation coefficient and by Bland-Altman plot analysis.

RESULTS

No significant difference was found in terms of age and body mass index between the genders. Differences between the predicted and measured REEs were maximum in the Bernstein equation (-478 kcal) and minimum in the Cunningham equation (-69 kcal). It was found that underprediction values varied from 27.5% (chronic kidney disease equation) to 98.0% (Bernstein equation). The highest overprediction value was found in the Schofield equation (17.7%). The Cunningham equation and the new equation had the lowest root mean square error (265 kcal/day). In this study, fat-free mass (FFM) was found to be the most significant variable in multiple regression analysis (r²: 0.55). The new specific equation based on FFM was generated as 424.2 + 24.7∗FFM (kg). Besides that, it was found that the new equation and Cunningham equation were distributed randomly according to Bland-Altman analysis. A supplementary new equation based on available anthropometric measurements was developed as -1996.8 + 19.1∗height (cm) + 7.2∗body weight (kg).

CONCLUSION

This study showed that most of the predictive equations significantly underestimated REE. In patients with renal transplantation, if the REE is not measurable by indirect calorimetry, the use of the proposed equations will be more accurate.

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.

Prediction of Resting Energy Expenditure in Children: May Artificial Neural Networks Improve Our Accuracy?

The inaccuracy of resting energy expenditure (REE) prediction formulae to calculate energy metabolism in children may lead to either under- or overestimated real caloric needs with clinical consequences. The aim of this paper was to apply artificial neural networks algorithms (ANNs) to REE prediction. We enrolled 561 healthy children (2-17 years). Nutritional status was classified according to World Health Organization (WHO) criteria, and 113 were obese. REE was measured using indirect calorimetry and estimated with WHO, Harris-Benedict, Schofield, and Oxford formulae. The ANNs considered specific anthropometric data to model REE. The mean absolute error (mean ± SD) of the prediction was 95.8 ± 80.8 and was strongly correlated with REE values (R² = 0.88). The performance of ANNs was higher in the subgroup of obese children (101 ± 91.8) with a lower grade of imprecision (5.4%). ANNs as a novel approach may give valuable information regarding energy requirements and weight management in children.

Central Nervous System and Peripheral Hormone Responses to a Meal in Children

CONTEXT

Behavioral studies suggest that responses to food consumption are altered in children with obesity (OB).

OBJECTIVE

To test central nervous system and peripheral hormone response by functional MRI and satiety-regulating hormone levels before and after a meal.

DESIGN AND SETTING

Cross-sectional study comparing children with OB and children of healthy weight (HW) recruited from across the Puget Sound region of Washington.

PARTICIPANTS

Children (9 to 11 years old; OB, n = 54; HW, n = 22), matched for age and sex.

INTERVENTION AND OUTCOME MEASURES

Neural activation to images of high- and low-calorie food and objects was evaluated across a set of a priori appetite-processing regions that included the ventral and dorsal striatum, amygdala, substantia nigra/ventral tegmental area, insula, and medial orbitofrontal cortex. Premeal and postmeal hormones (insulin, peptide YY, glucagon-like peptide-1, active ghrelin) were measured.

RESULTS

In response to a meal, average brain activation by high-calorie food cues vs objects in a priori regions was reduced after meals in children of HW (Z = -3.5, P < 0.0001), but not in children with OB (z = 0.28, P = 0.78) despite appropriate meal responses by gut hormones. Although premeal average brain activation by high-calorie food cues was lower in children with OB vs children of HW, postmeal activation was higher in children with OB (Z = -2.1, P = 0.04 and Z = 2.3, P = 0.02, respectively). An attenuated central response to a meal was associated with greater degree of insulin resistance.

CONCLUSIONS

Our data suggest that children with OB exhibit an attenuated central, as opposed to gut hormone, response to a meal, which may predispose them to overconsumption of food or difficulty with weight loss.

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.

Accuracy and Validity of Resting Energy Expenditure Predictive Equations in Middle-Aged Adults

Indirect calorimetry (IC) is considered the reference method to determine the resting energy expenditure (REE), but its use in a clinical context is limited. Alternatively, there is a number of REE predictive equations to estimate the REE. However, it has been shown that the available REE predictive equations could either overestimate or underestimate the REE as measured by IC. Moreover, the role of the weight status in the accuracy and validity of the REE predictive equations requires further attention. Therefore, this study aimed to determine the accuracy and validity of REE predictive equations in normal-weight, overweight, and obese sedentary middle-aged adults. A total of 73 sedentary middle-aged adults (53% women, 40⁻65 years old) participated in the study. We measured REE by indirect calorimetry, strictly following the standard procedures, and we compared it with the values obtained from 33 predictive equations. The most accurate predictive equations in middle-aged sedentary adults were: (i) the equation of FAO/WHO/UNU in normal-weight individuals (50.0% of prediction accuracy), (ii) the equation of Livingston in overweight individuals (46.9% of prediction accuracy), and (iii) the equation of Owen in individuals with obesity (52.9% of prediction accuracy). Our study shows that the weight status plays an important role in the accuracy and validity of different REE predictive equations in middle-aged adults.