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

Resting Energy Expenditure Equations Have Lower Accuracy for Adolescents with Overweight/Obesity Versus Healthy-Weight Adolescents

Objective: The objectives of the study were (1) to assess whether resting energy expenditure (REE) equations have comparable validity for adolescents with overweight/obesity vs. adolescents with healthy weight and (2) to examine determinants of measured REE in adolescents with overweight/obesity vs. adolescents with healthy weight. Methods: Ten equations were used to predict REE for 109 adolescents (70% males; 36.7% with overweight/obesity); 95% equivalence testing was used to assess how well each equation agreed with the criterion measure of indirect calorimetry. Linear regression models were fitted to examine how much REE variance was accounted for by age, sex, race, fat-free mass (FFM), and fat mass. Results: For adolescents with healthy weight, all ten equations were significantly equivalent to the criterion measure within ±8.4% (p < 0.05), whereas for participants with overweight/obesity, only three equations were equivalent within the same range (p < 0.05). Controlling for age, sex, race, fat mass, and FFM accounted for 74% of REE variance. FFM explained the greatest amount (26%) of variance in REE, while weight status itself explained an additional 22%. Conclusions: Prediction equations tend to be more accurate for adolescents with healthy weight than adolescents with overweight/obesity unless the original sample specifically included participants with overweight/obesity. Determinants of REE are similar regardless of weight status.

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.

Predictive Equation for Basal Metabolic Rate in Normal-Weight Chinese Adults

This study aimed to develop a predictive equation for basal metabolic rate (BMR) in normal-weight Chinese adults and provide a reference for establishing the national recommended dietary energy intake. A new equation for BMR was derived from a sample of 516 normal-weight Chinese adults (men = 253, women = 263), and this sample was collected from two previous studies. Furthermore, the accuracy of this new equation and eight other previous predictive equations was reviewed. The agreement and reliability were compared in terms of bias, accuracy, the intraclass correlation coefficient, and Bland-Altman plots between predictive equations. In addition, the newly developed equation was further verified using a small independent sample, which contained 41 healthy Chinese adults (men = 21, women = 20). The measured BMR (mBMR) of all participants, measured using indirect calorimetry, was 1346.2 ± 358.0 kcal/d. Thirty participants were excluded based on Cook's distance criteria (Cook's distance of ≥0.008). Previous equations developed by Henry, Schofield, Harris-Benedict (H-B), Yang, and Hong overestimated the BMR of healthy Chinese adults. The present equation displayed the smallest average bias (0.2 kcal/d) between the mBMR and predicted basal metabolic rate (pBMR). The limits of agreement of the present equation from Bland-Altman plots were -514.3 kcal/d and 513.9 kcal/d, which is the most narrow and balanced limit of agreement. Moreover, in the verification of the testing database, the pBMR of the new equation was not significantly different from the mBMR, and the accuracy was 75.6%. Compared with pre-existing equations, the present equation is more applicable to the prediction of BMR in healthy Chinese adults. However, further studies are required to verify the accuracy of this new equation.

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.

Cross-sectional study of characteristics of body composition of 24,845 children and adolescents aged 3-17 years in Suzhou

BACKGROUND

We aimed to analyze the characteristics of the body composition of children and adolescents aged 3-17 in Suzhou, China.

METHODS

A cross-sectional study between January 2020 and June 2022 using bioelectrical impedance was conducted to determine the fat mass (FM), fat-free mass (FFM), skeletal muscle mass, and protein and mineral contents of 24,845 children aged 3-17 who attended the Department of Child and Adolescent Healthcare, Children's Hospital of Soochow University, China. Measurement data was presented in tables as mean ± SD, and groups were compared using the independent samples t-test.

RESULTS

FM and fat-free mass increased with age in both boys and girls. The fat-free mass of girls aged 14-15 decreased after reaching a peak, and that of boys in the same age group was higher than that of the girls (p < 0.05). There were no significant differences in FM between boys and girls younger than 9- and 10-years old. The percentage body fat (PBF) and FM index of girls increased rapidly between 11 and 15 years of age (p < 0.05), and those of boys aged 11-14 were significantly lower (p < 0.05), suggesting that the increase in body mass index (BMI) was mainly contributed by muscle mass (MM) in boys.

CONCLUSIONS

The body composition of children and adolescents varies according to their age and sex. A misdiagnosis of obesity made on the basis of BMI alone can be avoided if BMI is used in combination with FM index, percentage body fat, and other indexes.

Body composition in preschool children with short stature: a case-control study

Background

Short stature is defined as height below 2 standard deviations of the population with the same age, gender. This study is aimed to assess the characteristics of body composition in preschool children with short stature.

Methods

Anthropometric measurements and body composition were assessed in 68 preschool children aged 3 to 6 years old with short stature and 68 normal controls matched on age and gender. Height, weight and body composition (total body water, protein, minerals, body fat mass, fat-free mass, soft lean mass, skeletal muscle mass, and bone mineral contents) in the two groups were measured and compared.

Results

The total body water, protein, minerals, body fat mass, fat-free mass, soft lean mass, skeletal muscle mass, and bone mineral contents were lower in preschool children with short stature than controls (P < 0.05). Body mass index and fat mass index did not differ between groups. Fat-free mass index was significantly lower in short stature group than controls (t = 2.17, P = 0.03). Linear regression analysis showed that there was a positive correlation between height and fat-free mass index [β, 1.99 (0.59, 3.39), P = 0.01], a negative correlation between height and body fat percentage [β, − 0.20 (− 0.38, − 0.01), P = 0.04]. The proportions of fat-free mass in the upper limbs were significantly lower (Right,t = − 2.78,Left t = − 2.76, P < 0.05, respectively) in short stature, although body fat distribution was not.

Conclusions

The fat-free mass such as protein and bone minerals is lower in preschool children with short stature, suggesting the monitoring of fat-free mass for early identification and intervention.

The Diagnostic-Measurement Method-Resting Energy Expenditure Assessment of Polish Children Practicing Football

Establishing the amount of energy needed to cover the energy demand of children doing sport training and thus ensuring they achieve an even energy balance requires the resting energy expenditure (REE) to be estimated. One of the methods that measures REE is the indirect calorimetry method, which may be influenced by many factors, including body composition, gender, age, height or blood pressure. The aim of the study was to assess the correlation between the resting energy expenditure of children regularly playing football and selected factors that influence the REE in this group. The study was conducted among 219 children aged 9 to 17 using a calorimeter, a device used to assess body composition by the electrical bioimpedance method by means of segment analyzer and a blood pressure monitor. The results of REE obtained by indirect calorimetry were compared with the results calculated using the ready-to-use formula, the Harris Benedict formula. The results showed a significant correlation of girls’ resting energy expenditure with muscle mass and body height, while boys’ resting energy expenditure was correlated with muscle mass and body water content. The value of the REE was significantly higher (p ≤ 0.001) than the value of the basal metabolic rate calculated by means of Harris Benedict formula. The obtained results can be a worthwhile suggestion for specialists dealing with energy demand planning in children, especially among those who are physically active to achieve optimal sporting successes ensuring proper functioning of their body.

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].