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.

2024 Adult Compendium of Physical Activities: A third update of the energy costs of human activities

BACKGROUND

The Compendium of Physical Activities was published in 1993 to improve the comparability of energy expenditure values assigned to self-reported physical activity (PA) across studies. The original version was updated in 2000, and again in 2011, and has been widely used to support PA research, practice, and public health guidelines.

METHODS

This 2024 update was tailored for adults 19-59 years of age by removing data from those ≥60 years. Using a systematic review and supplementary searches, we identified new activities and their associated measured metabolic equivalent (MET) values (using indirect calorimetry) published since 2011. We replaced estimated METs with measured values when possible.

RESULTS

We screened 32,173 abstracts and 1507 full-text papers and extracted 2356 PA energy expenditure values from 701 papers. We added 303 new PAs and adjusted 176 existing MET values and descriptions to reflect the addition of new data and removal of METs for older adults. We added a Major Heading (Video Games). The 2024 Adult Compendium includes 1114 PAs (912 with measured and 202 with estimated values) across 22 Major Headings.

CONCLUSION

This comprehensive update and refinement led to the creation of The 2024 Adult Compendium, which has utility across research, public health, education, and healthcare domains, as well as in the development of consumer health technologies. The new website with the complete lists of PAs and supporting resources is available at https://pacompendium.com.

Older Adult Compendium of Physical Activities: Energy costs of human activities in adults aged 60 and older

PURPOSE

To describe the development of a Compendium for estimating the energy costs of activities in adults ≥60 years (OA Compendium).

METHODS

Physical activities (PAs) and their metabolic equivalent of task (MET) values were obtained from a systematic search of studies published in 4 sport and exercise databases (PubMed, Embase, SPORTDiscus (EBSCOhost), and Scopus) and a review of articles included in the 2011 Adult Compendium that measured PA in older adults. MET values were computed as the oxygen cost (VO2, mL/kg/min) during PA divided by 2.7 mL/kg/min (MET60+) to account for the lower resting metabolic rate in older adults.

RESULTS

We identified 68 articles and extracted energy expenditure data on 427 PAs. From these, we derived 99 unique Specific Activity codes with corresponding MET60+ values for older adults. We developed a website to present the OA Compendium MET60+ values: https://pacompendium.com.

CONCLUSION

The OA Compendium uses data collected from adults ≥60 years for more accurate estimation of the energy cost of PAs in older adults. It is an accessible resource that will allow researchers, educators, and practitioners to find MET60+ values for older adults for use in PA research and practice.

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.

The energetics of childhood: Current knowledge and insights into human variation, evolution, and health

How organisms capture and ultimately use metabolic energy-a limiting resource of life-has profound implications for understanding evolutionary legacies and current patterns of phenotypic variation, adaptation, and health. Energetics research among humans has a rich history in biological anthropology and beyond. The energetics of childhood, however, remains relatively underexplored. This shortcoming is notable given the accepted importance of childhood in the evolution of the unique human life history pattern as well as the known sensitivity of childhood development to local environments and lived experiences. In this review, I have three objectives: (1) To overview current knowledge regarding how children acquire and use energy, highlighting work among diverse human populations and pointing to recent advances and remaining areas of uncertainty; (2) To discuss key applications of this knowledge for understanding human variation, evolution, and health; (3) To recommend future avenues for research. A growing body of evidence supports a model of trade-offs and constraint in childhood energy expenditure. This model, combined with advancements on topics such as the energetics of immune activity, the brain, and the gut, provides insights into the evolution of extended human subadulthood and the nature of variation in childhood development, lifetime phenotype, and health.

Resting energy expenditure in adolescents with Down syndrome: a comparison of commonly used predictive equations

BACKGROUND

Adolescents with Down syndrome (DS) are two to three times more likely to be obese than their typically developing peers. When preventing or treating obesity, it is useful for clinicians to understand an individual's energy intake needs. Predictive resting energy expenditure (REE) equations are often recommended for general use in energy intake recommendations; however, these predictive equations have not been validated in youth with DS. The aim of this study was to compare the accuracy of seven commonly used predictive equations for estimating REE in adolescents who are typically developing to REE measured by indirect calorimetry in adolescents with DS.

METHODS

Adolescents with DS participated in a 90-min laboratory visit before 10:00 a.m. after a 12-h overnight fast and a 48-h abstention from aerobic exercise. REE was measured via indirect calorimetry, and estimated REE was derived using the Institute of Medicine, Molnar, Muller and World Health Organization equations. Mean differences between the measured and predicted REE for each equation were evaluated with equivalency testing, and P-values were adjusted for multiple comparisons using the Holm method.

RESULTS

Forty-six adolescents with DS (age: 15.5 ± 1.7 years, 47.8% female, 73.9% non-Hispanic White) completed the REE assessment. Average measured REE was 1459.5 ± 267.8 kcal/day, and the Institute of Medicine equations provided the most accurate prediction of REE with a 1.7 ± 11.2% (13.9 ± 170.3 kcal/day) overestimation. This prediction was not statistically different from the measured REE [P-value = 0.582; 95% confidence interval (CI): -64.5, 36.7], and the difference between the measured and predicted REE was statistically equivalent to zero (P-value = 0.024; 90% CI: -56.1, 28.3).

CONCLUSIONS

The results suggest that the Institute of Medicine equation may be useful in predicting REE in adolescents with DS. Future research should confirm these results in a larger sample and determine the utility of the Institute of Medicine equation for energy intake recommendations during a weight management intervention.

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.

Resting Energy Expenditure and Related Factors in 6- to 9-Year-Old Southern African Children of Diverse Population Groups

Lower resting energy expenditure (REE) may partially explain the disproportionate prevalence of overweight/obesity among black African women. As no previous studies have investigated the REE of Southern African (South. Afr.) children, we aimed to determine, by sex and population group, the REE of 6- to 9-year-old urban school children. In a cross-sectional study with quota sampling, REE was measured with indirect calorimetry (IC). Confounders considered were: body composition (BC) (fat-free mass (FFM), FFM index, fat mass (FM), FM index), assessed using multifrequency bioelectrical impedance analysis, and physical activity (PA) measured with a pedometer. Multivariate regression was used to calculate REE adjusted for phenotypes (BC, z-scores of weight-for-age, height-for-age, body mass index-for-age) and PA. Sex and population differences in REE were determined with two-way ANOVA. Ninety-four healthy children (59.6% girls; 52.1% black) with similar socioeconomic status and PA opportunities participated. Despite BC variations, sex differences in REE were not significant (41 kcal/day; P = 0.375). The REE of black participants was lower than of white (146 kcal/day; P = 0.002). When adjusted for FFM and HFA z-score, the differences in REE declined but remained clinically meaningful at 91 kcal/day (P = 0.039) and 82 kcal/day (P = 0.108), respectively. We recommend the development of population-specific REE prediction equations for South. Afr. children.

Physical activity in children and adolescents with CHD: review from a measurement methodological perspective

AIM

To compile a literature overview of physical activity in children with CHD and to critically evaluate the methodology used for physical activity assessment.

METHODS

A review of the literature was performed using PubMed to identify studies examining accelerometer and subjectively assessed physical activity in children and adolescents with CHD.

RESULT

A total of 15 studies were included (6 studies using subjective measures and 9 articles using accelerometers for the assessment of physical activity). The patients generally failed to meet the recommendations of physical activity. When compared to healthy controls, the results were widely divergent in the subjectively assessed measures and the accelerometer-based studies showed a tendency of no difference in physical activity. Neither subjective methods nor accelerometer-based studies reported any difference in physical activity in general, in relation to the severity of the heart disease.

CONCLUSION

Methodological variation and limitations in the assessment of physical activity largely explain the divergent results and the inability to establish differences in physical activity between children with CHD of different severity and compared to healthy controls. Methodological knowledge and guidelines are provided for improved assessment of physical activity using accelerometers in clinical research.

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.

Cross-sectional comparison of body composition and resting metabolic rate in Premier League academy soccer players: Implications for growth and maturation

For the first time we aimed to: (1) assess fat-free mass (FFM) and RMR in youth soccer players, (2) compare measured RMR to estimated RMR using previously published prediction equations, and (3) develop a novel population-specific prediction equation. In a cross-sectional design, 99 males from a Premier League academy underwent assessments of body composition (DXA) and RMR (indirect-calorimetry). Measured RMR was compared to estimated values from five prediction equations. A novel RMR prediction equation was developed using stepwise multiple regression. FFM increased (P<0.05) between U12 (31.6±4.2 kg) and U16 (56.3±5.3 kg) after which no further increases occurred (P>0.05). RMR in the U12s (1655±195 kcal.day^-1), U13s (1720±205 kcal.day^-1) and U14s (1846±218kcal.day^-1) was significantly lower than the U15s (1957±128 kcal.day^-1), U16s (2042±155 kcal.day^-1), U18s (1875±180 kcal.day^-1) and U23s (1941±197 kcal.day^-1) squads (P>0.05). FFM was the single best predictor of RMR (r²=0.43; P<0.01) and was subsequently included in the novel prediction equation: RMR (kcal.day^-1) = 1315 + (11.1 x FFM in kg). Both FFM and RMR increase from 12-16 years old, thus highlighting the requirement to adjust daily energy intake to support growth and maturation. The novel prediction RMR equation developed may help to inform daily energy requirements.

Quantifying energy expenditure in childhood: utility in managing pediatric metabolic disorders

BACKGROUND

Energy expenditure prediction equations are used to estimate energy intake based on general population measures. However, when using equations to compare with a disease cohort with known metabolic abnormalities, it is important to derive one's own equations based on measurement conditions matching the disease cohort.

OBJECTIVE

We aimed to use newly developed prediction equations based on a healthy pediatric population to describe and predict resting energy expenditure (REE) in a cohort of pediatric patients with thyroid disorders.

METHODS

Body composition was measured by DXA and REE was assessed by indirect calorimetry in 201 healthy participants. A prediction equation for REE was derived in 100 healthy participants using multiple linear regression and z scores were calculated. The equation was validated in 101 healthy participants. This method was applied to participants with resistance to thyroid hormone (RTH) disorders, due to mutations in either thyroid hormone receptor β or α (β: female n = 17, male n = 9; α: female n = 1, male n = 1), with deviation of REE in patients compared with the healthy population presented by the difference in z scores.

RESULTS

The prediction equation for REE = 0.061 * Lean soft tissue (kg) - 0.138 * Sex (0 male, 1 female) + 2.41 (R2 = 0.816). The mean ± SD of the residuals is -0.02 ± 0.44 kJ/min. Mean ± SD REE z scores for RTHβ patients are -0.02 ± 1.26. z Scores of -1.69 and -2.05 were recorded in male (n = 1) and female ( n = 1) RTHα patients.

CONCLUSIONS

We have described methodology whereby differences in REE between patients with a metabolic disorder and healthy participants can be expressed as a z score. This approach also enables change in REE after a clinical intervention (e.g., thyroxine treatment of RTHα) to be monitored.

Reexamination of Accelerometer Calibration with Energy Expenditure as Criterion: VO2net Instead of MET for Age-Equivalent Physical Activity Intensity

Accelerometer calibration for physical activity (PA) intensity is commonly performed using Metabolic Equivalent of Task (MET) as criterion. However, MET is not an age-equivalent measure of PA intensity, which limits the use of MET-calibrated accelerometers for age-related PA investigations. We investigated calibration using VO_2net (VO_2gross - VO_2stand; mL⋅min^-1⋅kg^-1) as criterion compared to MET (VO_2gross/VO_2rest) and the effect on assessment of free-living PA in children, adolescents and adults. Oxygen consumption and hip/thigh accelerometer data were collected during rest, stand and treadmill walk and run. Equivalent speed (Speed_eq) was used as indicator of the absolute speed (Speed_abs) performed with the same effort in individuals of different body size/age. The results showed that VO_2net was higher in younger age-groups for Speed_abs, but was similar in the three age-groups for Speed_eq. MET was lower in younger age-groups for both Speed_abs and Speed_eq. The same VO_2net-values respective MET-values were applied to all age-groups to develop accelerometer PA intensity cut-points. Free-living moderate-and-vigorous PA was 216, 115, 74 and 71 min/d in children, adolescents, younger and older adults with VO_2net-calibration, but 140, 83, 74 and 41 min/d with MET-calibration, respectively. In conclusion, VO_2net calibration of accelerometers may provide age-equivalent measures of PA intensity/effort for more accurate age-related investigations of PA in epidemiological research.

The ActiGraph counts processing and the assessment of vigorous activity

The purpose of this study was to investigate the effect of different band-pass filters on the measurement bias with ActiGraph counts during high speed running and for estimating free-living vigorous physical activity (VPA). Two alternative band-pass filters were designed, extending the original frequency range from 0·29 to 1·66 Hz (AG) to 0·29-4 Hz (AC4) and 0·29-10 Hz (AC10). Sixty-two subjects in three age groups participated in a structured locomotion protocol consisting of multiple walking and running speeds. The time spent in free-living VPA using the three different band-pass filters were evaluated in 1121 children. Band-pass filter specific intensity cut-points from both linear regression and ROC analysis was identified from a calibration experiment using indirect calorimetry. The ActiGraph GT3X+ device recording raw acceleration at 30 Hz was used in all experiments. The linear association between counts and running speed was negative for AG but positive for AC4 and AC10 across all age groups. The time spent in free-living VPA was similar for all band-pass filters. Considering higher frequency information in the generation of ActiGraph counts with a hip/waist worn device reduces the measurement bias with running above 10 km·h^-1 . However, additional developments are required to accurately capture all VPA, including intermittent activities.

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.

Utility of the Youth Compendium of Physical Activities

PURPOSE

The purposes of this article are to: (a) describe the rationale and development of the Youth Compendium of Physical Activities (Youth Compendium); and (b) discuss the utility of the Youth Compendium for audiences in research, education, community, health care, public health, and the private sector.

METHODS

The Youth Compendium provides a list of 196 physical activities (PA) categorized by activity types, specific activities, and metabolic costs (youth metabolic equivalents of task [MET_y]) as measured by indirect calorimetry. The utility of the Youth Compendium was assessed by describing ways in which it can be used by a variety of audiences.

RESULTS

Researchers can use MET_y values to estimate PA levels and determine changes in PA in intervention studies. Educators can ask students to complete PA records to determine time spent in physical activities and to identify health-enhancing activities for classroom PA breaks. Community leaders, parents, and health care professionals can identify activity types that promote healthful behaviors. Public health agencies can use the MET_y values for surveillance and as a resource to inform progress toward meeting national physical activity guidelines. Applications for the private sector include the use of MET_y in PA trackers and other applications.

CONCLUSION

The National Collaborative on Childhood Obesity Research Web site presents the Youth Compendium and related materials to facilitate measurement of the energy cost of nearly 200 physical activities in children and youth. The Youth Compendium provides a way to standardize energy costs in children and youth and has application for a wide variety of audiences.