Resting energy expenditure in obese children aged 4 to 15 years: measured versus predicted data

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.

Development and validation of new predictive equations for resting energy expenditure in physically active boys

Measurement or estimation of resting energy expenditure (REE) should be the first step in determining energy demand in physically active boys. The purpose of this study was to develop and validate new equations for resting energy expenditure in male children and adolescents practicing soccer. The cross-sectional studywas carried out among 184 boys in the derivation group and 148 boys in the validation group (mean age 13.20 ± 2.16 years and 13.24 ± 1.75 years, respectively). The calorimeter and device for assessing body composition by bioelectrical impedance analysis (BIA) were used. Model of multiple regression showed that REE can be predicted in this population with Eq. (1) (with height and weight data) or Eq. (2) (with age, height, and fat free mass data). Predictive Eq. (1) had an average error of 51 ± 199 kcal and predictive Eq. (2) - 39 ± 193 kcal. Cohen's d coefficient was 0.2, which confirms the small difference. The bias was 4.7% and 3.9%, respectively. The accuracy was 61.2% in the population for predictive Eq. (1) and 66.2% for predictive Eq. (2). Therefore, the new equations developed and validated in this study are recommended for the estimation of REE in physically active boys, when the use of IC is not feasible or available.

Resting energy expenditure in children at risk of hypothalamic dysfunction

OBJECTIVE

Children with suprasellar brain damage are at risk of hypothalamic dysfunction (HD). HD may lead to decreased resting energy expenditure (REE). Decreased REE, however, is not present in all children with HD. Our aim was to assess which children suspect for HD have low REE, and its association with clinical severity of HD or radiological hypothalamic damage.

PATIENTS AND METHODS

A retrospective cohort study was performed. Measured REE (mREE) of children at risk of HD was compared to predicted REE (pREE). Low REE was defined as mREE <90% of predicted. The mREE/pREE quotient was associated to a clinical score for HD symptoms and to radiological hypothalamic damage.

RESULTS

In total, 67 children at risk of HD (96% brain tumor diagnosis) with a mean BMI SDS of +2.3 ± 1.0 were included. Of these, 45 (67.2%) had low mREE. Children with severe HD had a significant lower mean mREE/pREE quotient compared to children with no, mild, or moderate HD. Mean mREE/pREE quotient of children with posterior hypothalamic damage was significantly lower compared to children with no or anterior damage. Tumor progression or tumor recurrence, severe clinical HD, and panhypopituitarism with diabetes insipidus (DI) were significant risk factors for reduced REE.

CONCLUSION

REE may be lowered in children with hypothalamic damage and is associated to the degree of clinical HD. REE is, however, not lowered in all children suspect for HD. For children with mild or moderate clinical HD symptoms, REE measurements may be useful to distinguish between those who may benefit from obesity treatment that increases REE from those who would be better helped using other obesity interventions.

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].

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.

Enteral and parenteral nutrition considerations in pediatric patients

PURPOSE

Current clinical practice guidelines on management of enteral nutrition (EN) and parenteral nutrition (PN) in pediatric patients are reviewed.

SUMMARY

The provision of EN and PN in pediatric patients poses many unique considerations and challenges. Although indications for use of EN and PN are similar in adult and pediatric populations, recommended EN and PN practices differ for pediatric versus adult patients in areas such as selection of EN and PN formulations, timing of EN and PN initiation, advancement of nutrition support, and EN and PN goals. Additionally, provision of EN and PN to pediatric patients poses unique compounding and medication administration challenges. This article provides a review of current EN and PN best practices and special nutrition considerations for neonates, infants, and other pediatric patients.

CONCLUSION

The provision of EN and PN to pediatric patients presents many unique challenges. It is important for pharmacists to keep current with pediatric- and neonatal-specific guidelines on nutritional management of various disease states, as well as strategies to address compounding and medication administration challenges, in order to optimize EN and PN outcomes.

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.

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

OBJECTIVE

Accurate estimation of resting energy expenditure (REE) in childrenand adolescents is important to establish estimated energy requirements. The aim of the present study was to measure REE in obese children and adolescents by indirect calorimetry method, compare these values with REE values estimated by equations, and develop the most appropriate equation for this group.

METHODS

One hundred and three obese children and adolescents (57 males, 46 females) between 7 and 17 years (10.6 ± 2.19 years) were recruited for the study. REE measurements of subjects were made with indirect calorimetry (COSMED, FitMatePro, Rome, Italy) and body compositions were analyzed.

RESULTS

In females, the percentage of accurate prediction varied from 32.6 (World Health Organization [WHO]) to 43.5 (Molnar and Lazzer). The bias for equations was -0.2% (Kim), 3.7% (Molnar), and 22.6% (Derumeaux-Burel). Kim's (266 kcal/d), Schmelzle's (267 kcal/d), and Henry's equations (268 kcal/d) had the lowest root mean square error (RMSE; respectively 266, 267, 268 kcal/d). The equation that has the highest RMSE values among female subjects was the Derumeaux-Burel equation (394 kcal/d). In males, when the Institute of Medicine (IOM) had the lowest accurate prediction value (12.3%), the highest values were found using Schmelzle's (42.1%), Henry's (43.9%), and Müller's equations (fat-free mass, FFM; 45.6%). When Kim and Müller had the smallest bias (-0.6%, 9.9%), Schmelzle's equation had the smallest RMSE (331 kcal/d). The new specific equation based on FFM was generated as follows: REE = 451.722 + (23.202 * FFM). According to Bland-Altman plots, it has been found out that the new equations are distributed randomly in both males and females.

CONCLUSION

Previously developed predictive equations mostly provided unaccurate and biased estimates of REE. However, the new predictive equations allow clinicians to estimate REE in an obese children and adolescents with sufficient and acceptable accuracy.

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.

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

OBJECTIVE

To compare resting energy expenditure (REE) measured by indirect calorimetry with REE predicted using different equations in obese adolescents.

STUDY DESIGN

We recruited 264 obese patients (body mass index ranging from 30.0-70.0 kg/m(2)) between 14 and 18 years of age. Data were obtained comparing measured and predicted REE derived from published equations for normal weight and obese adolescents. The average differences between measured and predicted REE, as well as the accuracy at ± 10% level, were evaluated.

RESULTS

Evaluating the mean REE in 109 males (1938 ± 271 kcal/d) and 155 females (2569 ± 459 kcal/d), we found that the Lazzer equation in males had the smallest difference between measured and predicted REE; in females the Henry-1, Food and Agriculture Organization/World Health Organization/United Nations University, Schmelze, and Lazzer equations were the most accurate. The prediction accuracy was considered adequate within ± 10%.

CONCLUSIONS

REE predictive equations developed in obese patients and for specific age groups are more suitable than those for the general population. Inaccuracy of predicted REE could affect dietary prescription appropriateness and, consequently, dietary compliance in this age group.

Systematic review to identify and appraise outcome measures used to evaluate childhood obesity treatment interventions (CoOR): evidence of purpose, application, validity, reliability and sensitivity

BACKGROUND

Lack of uniformity in outcome measures used in evaluations of childhood obesity treatment interventions can impede the ability to assess effectiveness and limits comparisons across trials.

OBJECTIVE

To identify and appraise outcome measures to produce a framework of recommended measures for use in evaluations of childhood obesity treatment interventions.

DATA SOURCES

Eleven electronic databases were searched between August and December 2011, including MEDLINE; MEDLINE In-Process and Other Non-Indexed Citations; EMBASE; PsycINFO; Health Management Information Consortium (HMIC); Allied and Complementary Medicine Database (AMED); Global Health, Maternity and Infant Care (all Ovid); Cumulative Index to Nursing and Allied Health Literature (CINAHL) (EBSCOhost); Science Citation Index (SCI) [Web of Science (WoS)]; and The Cochrane Library (Wiley) - from the date of inception, with no language restrictions. This was supported by review of relevant grey literature and trial databases.

REVIEW METHODS

Two searches were conducted to identify (1) outcome measures and corresponding citations used in published childhood obesity treatment evaluations and (2) manuscripts describing the development and/or evaluation of the outcome measures used in the childhood intervention obesity evaluations. Search 1 search strategy (review of trials) was modelled on elements of a review by Luttikhuis et al. (Oude Luttikhuis H, Baur L, Jansen H, Shrewsbury VA, O'Malley C, Stolk RP, et al. Interventions for treating obesity in children. Cochrane Database Syst Rev 2009;1:CD001872). Search 2 strategy (methodology papers) was built on Terwee et al.'s search filter (Terwee CB, Jansma EP, Riphagen II, de Vet HCW. Development of a methodological PubMed search filter for finding studies on measurement properties of measurement instruments. Qual Life Res 2009;18:1115-23). Eligible papers were appraised for quality initially by the internal project team. This was followed by an external appraisal by expert collaborators in order to agree which outcome measures should be recommended for the Childhood obesity Outcomes Review (CoOR) outcome measures framework.

RESULTS

Three hundred and seventy-nine manuscripts describing 180 outcome measures met eligibility criteria. Appraisal of these resulted in the recommendation of 36 measures for the CoOR outcome measures framework. Recommended primary outcome measures were body mass index (BMI) and dual-energy X-ray absorptiometry (DXA). Experts did not advocate any self-reported measures where objective measurement was possible (e.g. physical activity). Physiological outcomes hold potential to be primary outcomes, as they are indicators of cardiovascular health, but without evidence of what constitutes a minimally importance difference they have remained as secondary outcomes (although the corresponding lack of evidence for BMI and DXA is acknowledged). No preference-based quality-of-life measures were identified that would enable economic evaluation via calculation of quality-adjusted life-years. Few measures reported evaluating responsiveness.

LIMITATIONS

Proposed recommended measures are fit for use as outcome measures within studies that evaluate childhood obesity treatment evaluations specifically. These may or may not be suitable for other study designs, and some excluded measures may be more suitable in other study designs.

CONCLUSIONS

The CoOR outcome measures framework provides clear guidance of recommended primary and secondary outcome measures. This will enhance comparability between treatment evaluations and ensure that appropriate measures are being used. Where possible, future work should focus on modification and evaluation of existing measures rather than development of tools de nova. In addition, it is recommended that a similar outcome measures framework is produced to support evaluation of adult obesity programmes.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Severe Prolonged Hypothyroidism

Background. Hashimoto’s thyroiditis usually presents with nonspecific systemic symptoms. The purpose of our study was to characterize the various properties of severe ongoing hypothyroidism and the rate of normalization following treatment. Methods. An adolescent girl with severe primary hypothyroidism was studied. Clinical evaluation, laboratory testing, brain magnetic resonance imaging, resting metabolic rate (RMR) testing, electroencephalogram, and visual field examination were performed at baseline and following treatment with levothyroxine. Results. At baseline, a significant psychomotor retardation was observed, serum thyroid-stimulating hormone concentration was 1088.4 mIU/mL. Magnetic resonance imaging showed a large intrasellar mass. Electroencephalogram was abnormal, and RMR was significantly reduced. Restoration of neurocognitive function and normalization of RMR, electroencephalogram, and laboratory tests occurred rapidly, alongside vanishing of the pituitary mass within 4 weeks of treatment. Conclusions. The various signs and symptoms of severe prolonged hypothyroidism may resolve rapidly with treatment, including the disappearance of a large pituitary mass.

Energy requirements for maintenance and growth in 3- to 4-year-olds may be overestimated by existing equations

OBJECTIVES

To give appropriate dietary advice to preschool children, an estimation of their energy requirements for both maintenance and activity is needed. We compared energy requirements for maintenance, measured by indirect calorimetry against existing equations predicting these requirements in 3- to 4-year-old children.

METHODS

In 30 children (age 3.4 ± 0.3) from the GECKO Drenthe cohort, height, weight, evening sleeping metabolic rate (SMR) (by indirect calorimetry), fat mass (FM), and fat-free mass (FFM) (by isotope dilution) were measured. For 25 children, a valid evening SMR was available as a measure for energy used for maintenance and growth. This SMR was compared with existing equations (Schofield, FAO/WHO/UNU, Oxford and Harris-Benedict). Correlations among SMR and weight, height, FM, and FFM were also calculated.

RESULTS

From the existing equations, significant higher values, ranging from 58 to 144 kcal/day, were calculated for the BMR compared with the measured SMR results, indicating 8% to 19% overestimation. This overestimation is higher at lower ranges of energy requirement. SMR was positively related to weight (r = 0.488, P = 0.013), height (r = 0.499, P = 0.011), and FFM (r = 0.482, P = 0.027), but not to FM (r = 0.211, P = 0.358).

CONCLUSIONS

Existing equations show higher values for the energy used for maintenance in young children compared to the results of our measurements of the SMR. Energy used for maintenance is correlated with FFM and not with FM.

Comparison of predictive equations and measured resting energy expenditure among obese youth attending a pediatric healthy weight clinic: one size does not fit all

BACKGROUND

The Academy of Nutrition and Dietetics recommends the use of indirect calorimetry for calculating caloric targets for weight loss in obese youth. Practitioners typically use predictive equations since indirect calorimetry is often not available. The objective of this study was to compare measured resting energy expenditure (MREE) with that estimated using published predictive equations in obese pediatric patients.

MATERIAL AND METHODS

Youth aged 7 to 18 years (n = 80) who were referred to a university-based healthy weight clinic and who were greater than the 95th percentile BMI for age and gender participated. MREE was measured via a portable indirect calorimeter. Predicted energy expenditure (pEE) was estimated using published equations including those commonly used in children. pEE was compared to the MREE for each subject. Absolute mean difference between MREE and pEE, mean percentage accuracy, and mean error were determined.

RESULTS

Mean percentage accuracy of pEE compared with MREE varied widely, with the Harris-Benedict, Lazzer, and Molnar equations providing the greatest accuracy (65%, 61%, and 60%, respectively). Mean differences between MREE and equation-estimated caloric targets varied from 197.9 kcal/day to 307.7 kcal/day.

CONCLUSIONS

The potential to either overestimate or underestimate calorie needs in the clinical setting is significant when comparing EE derived from predictive equations with that measured using portable indirect calorimetry. While our findings suggest that the Harris-Benedict equation has improved accuracy relative to other equations in severely obese youth, the potential for error remains sufficiently great to suggest that indirect calorimetry is preferred.

Klinische Methoden

Die Anamnese kranker Kinder ist überwiegend eine Fremdanamnese der Mutter, des Vaters oder einer Pflegeperson. Mit dem Älterwerden und besonders in der Pubertät wächst der Anspruch des kindlichen Patienten, das Gespräch selbst zu gestalten.

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.

Validation of predictive equations for resting energy expenditure in obese adolescents

BACKGROUND

When the resting energy expenditure (REE) of overweight and obese adolescents cannot be measured by indirect calorimetry, it has to be predicted with an equation.

OBJECTIVE

The aim of this study was to examine the validity of published equations for REE compared with indirect calorimetry in overweight and obese adolescents.

DESIGN

Predictive equations based on weight, height, sex, age, fat-free mass (FFM), and fat mass were compared with measured REE. REE was measured by indirect calorimetry, and body composition was measured by dual-energy X-ray absorptiometry. The accuracy of the REE equations was evaluated on the basis of the percentage of adolescents predicted within 10% of REE measured, the mean percentage difference between predicted and measured values (bias), and the root mean squared prediction error (RMSE).

RESULTS

Forty-three predictive equations (of which 12 were based on FFM) were included. Validation was based on 70 girls and 51 boys with a mean age of 14.5 y and a mean (+/-SD) body mass index SD score of 2.93 +/- 0.45. The percentage of adolescents with accurate predictions ranged from 74% to 12% depending on the equation used. The most accurate and precise equation for these adolescents was the Molnar equation (accurate predictions: 74%; bias: -1.2%; RMSE: 174 kcal/d). The often-used Schofield-weight equation for age 10-18 y was not accurate (accurate predictions: 50%; bias: +10.7%; RMSE: 276 kcal/d).

CONCLUSIONS

Indirect calorimetry remains the method of choice for REE in overweight and obese adolescents. However, the sex-specific Molnar REE prediction equation appears to be the most accurate for overweight and obese adolescents aged 12-18 y. This trial was registered at www.trialregister.nl with the Netherlands Trial Register as ISRCTN27626398.

Influence of extracurricular sport activities on body composition and physical fitness in boys: a 3-year longitudinal study

OBJECTIVE

To analyse the effect of extracurricular physical activities on fat mass accumulation and physical fitness during growth in early pubertal males.

DESIGN

Longitudinal study.

SUBJECTS

A total of 42 male children (9.4+/-1.4 years, Tanner I-II and 12.7+/-1.5 years, Tanner III-IV, before and after the 3.3 years follow-up, respectively), randomly sampled from the population of Gran Canaria (Spain), 26 of them physically active (PA, at least 3 h per week during 3 years) and 16 non-physically active (non-PA).

MEASUREMENTS

Body composition (dual-energy X-ray absorptiometry), anthropometrics (body circumferences and skinfolds) and physical fitness variables (dynamic and isometric force, anaerobic capacity and maximal aerobic power) were determined in all subjects.

RESULTS

Both groups had comparable body sizes at the start and the end of the study. Body mass index increased with growth more in the PA than in the non-PA group (P<0.05). However, fat mass accumulation with growth was lower in the PA than in the non-PA (P<0.05). There was a positive relationship between the increment of total and trunkal fat mass, especially in non-active children (r2=0.93). In contrast, there was an inverse relationship between the total lean mass growth and the accumulation of total and regional fat mass (r=-0.37 to -0.41, all P<0.05). Physical fitness was maintained in the PA, while it worsened in the non-PA children.

CONCLUSIONS

Without any dietary intervention, children who regularly participate in at least 3 h per week of sports activities are more protected against total and regional fat mass accumulation. They also increase their total lean and bone mass to a greater extent than children who do not participate in extracurricular sport activities. In addition, PA children maintain their physical fitness during growth, while it deteriorates in the non-PA children.

Evaluation of Lunar Prodigy dual-energy X-ray absorptiometry for assessing body composition in healthy persons and patients by comparison with the criterion 4-component model

BACKGROUND

Dual-energy X-ray absorptiometry (DXA) is widely used to assess body composition in research and clinical practice. Several studies have evaluated its accuracy in healthy persons; however, little attention has been directed to the same issue in patients.

OBJECTIVE

The objective was to compare the accuracy of the Lunar Prodigy DXA for body-composition analysis with that of the reference 4-component (4C) model in healthy subjects and in patients with 1 of 3 disease states.

DESIGN

A total of 215 subjects aged 5.0-21.3 y (n = 122 healthy nonobese subjects, n = 55 obese patients, n = 26 cystic fibrosis patients, and n = 12 patients with glycogen storage disease). Fat mass (FM), fat-free mass (FFM), and weight were measured by DXA and the 4C model.

RESULTS

The accuracy of DXA-measured body-composition outcomes differed significantly between groups. Factors independently predicting bias in weight, FM, FFM, and percentage body fat in multivariate models included age, sex, size, and disease state. Biases in FFM were not mirrored by equivalent opposite biases in FM because of confounding biases in weight.

CONCLUSIONS

The bias of DXA varies according to the sex, size, fatness, and disease state of the subjects, which indicates that DXA is unreliable for patient case-control studies and for longitudinal studies of persons who undergo significant changes in nutritional status between measurements. A single correction factor cannot adjust for inconsistent biases.