Energy expenditure and weight-related behaviors in youth with Down syndrome: a protocol.

Background: The consequences of obesity are ominous, yet healthcare professionals are not adequately preventing or treating obesity in youth with Down syndrome (DS). Total daily energy expenditure (TDEE) is the energy expended in 24 h through physical activity and life-sustaining physiologic processes. An individual's TDEE is essential for determining the daily caloric intake needed to maintain or change body weight. Successful prevention and treatment of obesity in youth with DS is severely compromised by the lack of data on TDEE and information on weight-related behaviors for this high-risk population. This manuscript describes the protocol for the federally funded study that is in process to determine daily energy expenditure in a large cohort of children with DS. Methods: This observational cross-sectional study will include a national sample of 230 youth with DS, stratified by age (5-11 and 12-18 years of age) and sex. Doubly Labeled Water analysis will provide the criterion body fat%, fat-free mass, and TDEE. To increase accessibility and decrease the burden on participants, the entire study, including obtaining consent and data collection, is conducted virtually within the participant's home environment on weekdays and weekends. The study team supervises all data collection via a video conferencing platform, e.g., Zoom. This study will (1) examine and determine average TDEE based on age and sex, (2) develop a prediction equation based on measured TDEE to predict energy requirements with a best-fit model based on fat-free mass, sex, age, and height and/or weight, and (3) use 24-hour dietary recalls, a nutrition and physical activity screener, wearable devices, and sleep questionnaire to describe the patterns and quality of dietary intake, sleep, and physical activity status in youth with DS. Discussion: The lack of accurate information on energy expenditure and weight-related behaviors in youth with DS significantly impedes the successful prevention and treatment of obesity for this vulnerable population. The findings of this study will provide a further understanding of weight-related behaviors as obesity risk factors, currently not well understood for this population. This study will advance the science of weight management in individuals with disabilities and shift clinical practice paradigms.

Total energy expenditure as assessed by doubly labeled water and all-cause mortality in a cohort of postmenopausal women.

BACKGROUND: The association of TEE with all-cause mortality is uncertain, as is the dependence of this association on age. OBJECTIVES: To examine the association between TEE and all-cause mortality, and its age interaction, in a Women's Health Initiative (WHI) cohort of postmenopausal United States women (1992-present). METHODS: A cohort of 1131 WHI participants having DLW TEE assessment of ∼10.0 y (median) following WHI enrollment with ∼13.7 y (median) of subsequent follow-up, was used to study the EE associations with all-cause mortality. To enhance the comparability of TEE and total EI, key analyses excluded participants having >5% weight change between WHI enrollment and DLW assessment. The influence of participant age on mortality associations was examined, as was the ability of concurrent and earlier weight and height measurements to explain the results. RESULTS: There were 308 deaths following the TEE assessment through 2021. TEE was unrelated to overall mortality (P = 0.83) in this cohort of generally healthy, older (mean 71 y at TEE assessment) United States women. However, this potential association varied with age (P = 0.003). Higher TEE was associated with a higher mortality rate at the age of 60 y and a lower mortality rate at the age of 80 y. Within the weight-stable subset (532 participants, 129 deaths), TEE was weakly positively related to overall mortality (P = 0.08). This association also varied with age (P = 0.03), with mortality HRs (95% CIs) for a 20% increment in TEE of 2.33 (1.24, 4.36) at the age of 60 y, 1.49 (1.10, 2.02) at 70 y of age, and 0.96 (0.66, 1.38) at 80 y of age. This pattern remained, although was somewhat attenuated, following control for baseline weight and weight changes between WHI enrollment and TEE assessment. CONCLUSIONS: Higher EE is associated with higher all-cause mortality among younger postmenopausal women, only partially explained by weight and weight change. This study is registered with clinicaltrials.gov identifier: NCT00000611.

Total Energy Expenditure and ad Libitum Fluid/Nutrient Intake During a 24-Hour Mountain-Bike Event: A Case Study.

Previous studies have used the doubly labeled water method to evaluate the total energy expenditure (TEE) during Ironman, ultramarathon trail runs, and competitive road cycling. However, the technique has not been applied to a 24-hour cross-country mountain-bike event. PURPOSE: This case study aimed to measure the TEE, cycling metrics, and ad libitum nutrient/fluid intake during a 24-hour cross-country mountain-bike race. METHODS: A trained male cyclist (41 y, 74.1 kg, 172.4 cm) received an oral dose of doubly labeled water prior to the 24-hour event for the calculations of TEE and water turnover. Nude body weight and urine samples were collected prerace, during the race, and postrace. Total nutrient intake and total fluid intake in addition to cycling metrics (speed, power output, cadence, and heart rate) were continuously recorded during the event. RESULTS: The rider completed 383 km coupled with a vertical gain of 7737 m during the 24-hour event. Average speed, power, and heart rate were 16.3 (2) km·h-1, 122 (29) W, and 134 (18) beats·min-1, respectively. TEE and total nutrient intake were 41 and 23.5 MJ, respectively. Total carbohydrate intake was 1192 g with an average hourly intake of 58 (22) g·h-1. Total body weight was 75.3 and 72.3 kg prerace and postrace, respectively, with a measured ad libitum total fluid intake of 13.3 L and a water turnover of 17.2 L. CONCLUSIONS: These data provide novel insights for measures of TEE, total energy intake, and total fluid intake during an ultraendurance cross-country mountain-biking event and provide a foundation for future race/training needs.

Human total, basal and activity energy expenditures are independent of ambient environmental temperature.

Lower ambient temperature (Ta) requires greater energy expenditure to sustain body temperature. However, effects of Ta on human energetics may be buffered by environmental modification and behavioral compensation. We used the IAEA DLW database for adults in the USA (n = 3213) to determine the effect of Ta (-10 to +30°C) on TEE, basal (BEE) and activity energy expenditure (AEE) and physical activity level (PAL). There were no significant relationships (p > 0.05) between maximum, minimum and average Ta and TEE, BEE, AEE and PAL. After adjustment for fat-free mass, fat mass and age, statistically significant (p < 0.01) relationships between TEE, BEE and Ta emerged in females but the effect sizes were not biologically meaningful. Temperatures inside buildings are regulated at 18-25°C independent of latitude. Hence, adults in the US modify their environments to keep TEE constant across a wide range of external ambient temperatures.

Effect of Exercise on Energy Expenditure and Body Composition in Astronauts Onboard the International Space Station: Considerations for Interplanetary Travel.

OBJECTIVE: Body mass (BM) loss and body composition (BC) changes threaten astronauts' health and mission success. However, the energetic contribution of the exercise countermeasure to these changes has never been investigated during long-term missions. We studied energy balance and BC in astronauts during 6-month missions onboard the International Space Station. METHODS: Before and after at least 3 months in space, BM, BC, total and activity energy expenditure (TEE and AEE) were measured using the doubly labeled water method in 11 astronauts (2011-2017). Physical activity (PA) was assessed by the SensewearPro® activity-device. RESULTS: Three-month spaceflight decreased BM (- 1.20 kg [SE 0.5]; P = 0.04), mainly due to non-significant fat-free mass loss (FFM; - 0.94 kg [0.59]). The decrease in walking time (- 63.2 min/day [11.5]; P < 0.001) from preflight was compensated by increases in non-ambulatory activities (+ 64.8 min/day [18.8]; P < 0.01). Average TEE was unaffected but a large interindividual variability was noted. Astronauts were stratified into those who maintained (stable_TEE; n = 6) and those who decreased (decreased_TEE; n = 5) TEE and AEE compared to preflight data. Although both groups lost similar BM, FFM was maintained and FM reduced in stable_TEE astronauts, while FFM decreased and FM increased in decreased_TEE astronauts (estimated between-group-difference (EGD) in ΔFFMindex [FFMI] 0.87 kg/m2, 95% CI + 0.32 to + 1.41; P = 0.01, ΔFMindex [FMI] - 1.09 kg/m2, 95% CI - 2.06 to - 0.11 kg/m2; P = 0.03). The stable_TEE group had higher baseline FFMI, and greater baseline and inflight vigorous PA than the decreased_TEE group (P < 0.05 for all). ΔFMI and ΔFFMI were respectively negatively and positively associated with both ΔTEE and ΔAEE. CONCLUSION: Both ground fitness and inflight overall PA are associated with spaceflight-induced TEE and BC changes and thus energy requirements. New instruments are needed to measure real-time individual changes in inflight energy balance components.

Measurement Error Affecting Web- and Paper-Based Dietary Assessment Instruments: Insights From the Multi-Cohort Eating and Activity Study for Understanding Reporting Error.

Few biomarker-based validation studies have examined error in online self-report dietary assessment instruments, and food records (FRs) have been considered less than food frequency questionnaires (FFQs) and 24-hour recalls (24HRs). We investigated measurement error in online and paper-based FFQs, online 24HRs, and paper-based FRs in 3 samples drawn primarily from 3 cohorts, comprising 1,393 women and 1,455 men aged 45-86 years. Data collection occurred from January 2011 to October 2013. Attenuation factors and correlation coefficients between reported and true usual intake for energy, protein, sodium, potassium, and respective densities were estimated using recovery biomarkers. Across studies, average attenuation factors for energy were 0.07, 0.07, and 0.19 for a single FFQ, 24HR, and FR, respectively. Correlation coefficients for energy were 0.24, 0.23, and 0.40, respectively. Excluding energy, the average attenuation factors across nutrients and studies were 0.22 for a single FFQ, 0.22 for a single 24HR, and 0.51 for a single FR. Corresponding correlation coefficients were 0.31, 0.34, and 0.53, respectively. For densities (nutrient expressed relative to energy), the average attenuation factors across studies were 0.37, 0.17, and 0.50, respectively. The findings support prior research suggesting different instruments have unique strengths that should be leveraged in epidemiologic research.

Physical Activity and Total Daily Energy Expenditure in Older US Adults: Constrained versus Additive Models.

PURPOSE: This study aimed to examine the shape of the relationship between physical activity (PA) and total energy expenditure (TEE) and to explore the role of energy balance status (negative, stable, positive) in influencing this association. METHODS: Cross-sectional. Participants were 584 older adults (50-74 yr) participating in the Interactive Diet and Activity Tracking in AARP study. TEE was assessed by doubly labeled water and PA by accelerometer. The relationship between PA and TEE was assessed visually and using nonlinear methods (restricted cubic splines). Percent weight change (>3%) over a 6-month period was used as a proxy measurement of energy balance status. RESULTS: TEE generally increased with increasing deciles of PA averaging 2354 (SD, 351) kcal·d-1 in the bottom decile to 2693 (SD, 480) kcal·d-1 in the top decile. Cubic spline models showed an approximate linear association between PA and TEE (linear relation, P < 0.0001; curvature, P = 0.920). Results were similar in subgroup analyses for individuals classified as stable or positive energy balance. For those in negative energy balance, TEE was generally flat with increasing deciles of PA averaging 2428 (SD, 285) kcal·d-1 in the bottom decile to 2372 (SD, 560) kcal·d-1 in the top decile. CONCLUSIONS: Energy balance status seems to play an important role in the relationship between PA and TEE. When in a positive energy balance, the relationship between TEE and PA was consistent with an additive model; however, when energy balance was negative, TEE seems to be consistent with a constrained model. These findings support PA for weight gain prevention by increasing TEE; however, the effect of PA on TEE during periods of weight loss may be limited. An adequately powered, prospective study is warranted to confirm these exploratory findings.

Performance and Feasibility of Recalls Completed Using the Automated Self-Administered 24-Hour Dietary Assessment Tool in Relation to Other Self-Report Tools and Biomarkers in the Interactive Diet and Activity Tracking in AARP (IDATA) Study.

BACKGROUND: Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a self-administered web-based tool designed to collect detailed dietary data at low cost in observational studies. OBJECTIVE: The objectives of this study were to describe, overall and by demographic groups, the performance and feasibility of ASA24-2011 recalls and compare Healthy Eating Index-2015 (HEI-2015) total and component scores to 4-day food records (4DFRs) and food frequency questionnaires (FFQs). DESIGN: Over 12 months, participants completed up to 6 ASA24 recalls, 2 web-based FFQs, and 2 unweighed paper-and-pencil 4DFRs. Up to 3 attempts were made to obtain each ASA24 recall. Participants were administered doubly-labeled water to provide a measure of total energy expenditure and collected two 24-hour urine samples to assess concentrations of nitrogen, sodium, and potassium. PARTICIPANTS/SETTING: From January through September 2012, 1,110 adult members of AARP, 50 to 74 years of age, were recruited from the Pittsburgh, PA, area to participate in the Interactive Diet and Activity Tracking in AARP (IDATA) study. After excluding 33 participants who had not completed any dietary assessments, 531 men and 546 women remained. MAIN OUTCOME MEASURES: Response rates, nutrient intakes compared to recovery biomarkers across each ASA24 administration day, and HEI-2015 total and component scores were measured. STATISTICAL ANALYSES PERFORMED: Means, medians, standard deviations, interquartile ranges, and HEI-2015 total and component scores computed using a multivariate measurement error model are presented. RESULTS: Ninety-one percent of men and 86% of women completed 3 ASA24 recalls. Approximately three-quarters completed 5 or more, higher than the completion rates for 2 4DFRs and 2 FFQs. Approximately, three-quarters of men and 70% of women completed ASA24 on the first attempt; 1 in 5 completed it on the second. Completion rates varied slightly by age and body mass index. Median time to complete ASA24-2011 (current version: ASA24-2020) declined with subsequent recalls from 55 to 41 minutes in men and from 58 to 42 minutes in women and was lowest in those younger than 60 years. Mean nutrient intakes were similar across recalls. For each recording day, energy intakes estimated by ASA24 were lower than energy expenditure. Reported intakes for protein, potassium, and sodium were closer to recovery biomarkers for women, but not for men. Geometric means of reported intakes of these nutrients did not systematically vary across ASA24 administrations, but differences between reported intakes and biomarkers differed by nutrient. Of 100 possible points, HEI-2015 total scores were nearly identical for 4DFRs and ASA24 recalls and higher for FFQs (men: 61, 60, and 68; women: 64, 64, and 72, respectively). CONCLUSIONS: ASA24, a freely available dietary assessment tool for use in large-scale nutrition research, was found to be highly feasible. Similar to previously reported data for nutrient intakes, HEI-2015 total and component scores for ASA24 recalls were comparable to those for 4DFRs, but not FFQs. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03268577 (http://www.clinicaltrials.gov).

Total energy expenditure measured using doubly labeled water compared with estimated energy requirements in older adults (≥65 y): analysis of primary data.

BACKGROUND: Contemporary energy expenditure data are crucial to inform and guide nutrition policy in older adults to optimize nutrition and health. OBJECTIVE: The aim was to determine the optimal method of estimating total energy expenditure (TEE) in adults (aged ≥65 y) through 1) establishing which published predictive equations have the closest agreement between measured resting metabolic rate (RMR) and predicted RMR and 2) utilizing the RMR equations with the best agreement to predict TEE against the reference method of doubly labeled water (DLW). METHODS: A database consisting of international participant-level TEE data from DLW studies was developed to enable comparison with energy requirements estimated by 17 commonly used predictive equations. This database included 31 studies comprising 988 participant-level RMR data and 1488 participant-level TEE data. Mean physical activity level (PAL) was determined for men (PAL = 1.69, n = 320) and women (PAL = 1.66, n = 668). Bland-Altman plots assessed agreement of measured RMR and TEE with predicted RMR and TEE in adults aged ≥65 y, and subgroups of 65-79 y and ≥80 y. Linear regression assessed proportional bias. RESULTS: The Ikeda, Livingston, and Mifflin equations most closely agreed with measured RMR and TEE in all adults aged ≥65 y and in the 65-79 y and ≥80 y subgroups. In adults aged ≥65 y, the Ikeda and Livingston equations overestimated TEE by a mean ± SD of 175 ± 1362 kJ/d and 86 ± 1344 kJ/d, respectively. The Mifflin equation underestimated TEE by a mean ± SD of 24 ± 1401 kJ/d. Proportional bias was present as energy expenditure increased. CONCLUSIONS: The Ikeda, Livingston, or Mifflin equations are recommended for estimating energy requirements of older adults. Future research should focus on developing predictive equations to meet the requirements of the older population with consideration given to body composition and functional measures.

Modelling the metabolism: allometric relationships between total daily energy expenditure, body mass, and height.

BACKGROUND/OBJECTIVES: Accurately predicting energy requirements form a critical component for initializing dynamic mathematical models of metabolism. The majority of such existing estimates rely on linear regression models that predict total daily energy expenditure (TDEE) from age, gender, height, and body mass, however, there is evidence these predictors obey a power function. SUBJECTS/METHODS: Baseline, free-living TDEE measured by doubly labeled water (DLW) in 20 studies with no overlapping subjects were obtained from the core lab at the University of Chicago and the University of Wisconsin-Madison (N = 2501 adults, 628 males, 1873 females). Linear regression models of log-transformed equations of the form: [Formula: see text] and [Formula: see text] were developed to determine the values of the exponents of body mass (M (kg)) and height (H (cm)) along with a gender effect (Sex). A nonlinear curve fit was performed to develop a power model that also includes age [Formula: see text]. RESULTS: The power for body mass, ß1 = 0.45 and the power for height was ß2 = 1.52 in the database with both genders combined. Adding gender reduced these to ß1 = 0.43 and ß2 = 1.04. All terms were significant (p < 0.01) except for height when including gender. The powers for height in the additive gender-specific models were both closer to 1 and the power for body mass was similar across all models ranging between 0.41 and 0.57. CONCLUSIONS: A nonlinear scaling relationship was found to hold for body mass and needs to be considered when adjusting TDEE for body mass or predicting human energy requirements as a function of body mass especially in individuals with obesity.

Combination of DXA and BIS body composition measurements is highly correlated with physical function-an approach to improve muscle mass assessment.

RATIONALE: Fluid volume estimates may help predict functional status and thereby improve sarcopenia diagnosis. MAIN RESULT: Bioimpedance-derived fluid volume, combined with DXA, improves identification of jump power over traditional measures. SIGNIFICANCE: DXA-measured lean mass should be corrected for fluid distribution in older populations; this may be a surrogate of muscle quality. PURPOSE: Sarcopenia, the age-related loss of muscle mass and function, negatively impacts functional status, quality of life, and mortality. We aimed to determine if bioimpedance spectroscopy (BIS)-derived estimates of body water compartments can be used in conjunction with dual-energy X-ray absorptiometry (DXA) measures to aid in the prediction of functional status and thereby, ultimately, improve the diagnosis of sarcopenia. METHODS: Participants (≥ 70 years) had physical and muscle function tests, DXA, and BIS performed. Using a BMI correction method, intracellular water (ICWc), extracellular water (ECWc), and ECWc to ICWc (E/Ic) ratio was estimated from standard BIS measures. Jump power was assessed using jump mechanography. RESULTS: The traditional measure used to diagnose sarcopenia, DXA-derived appendicular lean mass (ALM) corrected for height (ALM/ht2), was the least predictive measure explaining jump power variability (r2 = 0.31, p < 0.0001). The best measure for explaining jump power was a novel variable combining DXA ALM and BIS-derived E/Ic ratio (ALM/(E/Ic); r2 = 0.70, p < 0.0001). ALM/(E/Ic) and ICWc had the highest correlation with jump power and grip strength, specifically jump power (r = 0.84 and r = 0.80, respectively; p < 0.0001). CONCLUSIONS: The creation of a novel variable (ALM/(E/Ic)) improved the ability of DXA to predict jump power in an older population. ALM/(E/Ic) substantially outperformed traditional lean mass measures of sarcopenia and could well be an improved diagnostic approach to predict functional status. DXA-measured ALM should be corrected for fluid distribution, i.e., ALM/(E/Ic); this correction may be considered a surrogate of muscle quality.

Validation of rapid 4-component body composition assessment with the use of dual-energy X-ray absorptiometry and bioelectrical impedance analysis.

Background: The 4-component (4C) model is a criterion method for human body composition that separates the body into fat, water, mineral, and protein, but requires 4 measurements with significant cost and time requirements that preclude wide clinical use. A simplified model integrating only 2 measurements-dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA)-and 10 min of patient time has been proposed. Objective: We aimed to validate a rapid, simplified 4C DXA + BIA body composition model in a clinical population. Design: This was a cross-sectional observational study of 31 healthy adults. Participants underwent whole-body DXA, segmental BIA, air displacement plethysmography (ADP), and total body water (TBW) measurement by deuterium (D2O) dilution. 4C composition was calculated through the use of the Lohman model [DXA mineral mass, D2O TBW, ADP body volume (BV), scale weight] and the simplified model (DXA mineral mass and BV, BIA TBW, scale weight). Accuracy of percentage of fat (%Fat) and protein measurements was assessed via linear regression. Test-retest precision was calculated with the use of duplicate DXA and BIA measurements. Results: Of 31 participants, 23 were included in the analysis. TBWBIA showed good test-retest precision (%CV = 5.2 raw; 1.1 after outlier removal) and high accuracy to TBWD2O [TBWD2O = 0.956*TBWBIA, R2= 0.92, root mean squared error (RMSE) = 2.2 kg]. %Fat estimates from DXA, ADP, D2O, and BIA all showed high correlation with the Lohman model. However, only the 4C simplified model provides high accuracy for both %Fat (R2 = 0.96, RMSE = 2.33) and protein mass (R2= 0.76, RMSE = 1.8 kg). %Fat precision from 4C DXA + BIA was comparable with DXA (root mean square-SD = 0.8 and 0.6 percentage units, respectively). Conclusions: This work validates a simplified 4C method that measures fat, water, mineral, and protein in a 10-min clinic visit. This model has broad clinical application to monitor many conditions including over/dehydration, malnutrition, obesity, sarcopenia, and cachexia.

Accuracy of total energy expenditure predictive equations after a massive weight loss induced by bariatric surgery.

BACKGROUND AND AIMS: Predictive equations remain the clinical tool of choice to estimate the energy expenditure, however, poor accuracy has been found when applied in patients with severe obesity. The aim of this study was to test the accuracy of the total energy expenditure (TEE) those obtained by predictive equations of resting energy expenditure (REE) times individual estimates of metabolic equivalents (MET), taking as reference the TEE measured by doubly labeled water (DLW), before, six and twelve months after bariatric surgery. SUBJECTS AND METHODS: Twenty class III obese women (age: 29.4 ± 5.1 years; BMI: 44.9 ± 2.5 kg/m2), approved for Roux-en-Y gastric bypass participated in this study. TEE and body composition was measured after administration of a fixed dose of DLW. Predictive equations of REE were selected: Dietary Reference Intake (DRI), World Health Organization, Oxford, Harris-Benedict, Mifflin, De Lorenzo, Lazzer and Muller and their collaborators. The MET values were obtained individually by triaxial accelerometer. RESULTS: The patients showed 65% of excess weight loss. The body fat mass decreased 17% after 1 year of surgery. TEE (2930 ± 525 kcal.day-1) decreased by 20% (p < 0.05) by the sixth postoperative month (2319 ± 430 kcal.day-1), increasing 10% by the twelfth month (2538 ± 336 kcal.day-1). The Harris and Benedict (accuracy: 65%) and DRI equations (accuracy: 60%) yielded better results in the prediction of TEE values at pre-surgery. In the sixth month after surgery, only the equation of Harris and Benedict kept accuracy above 50%. At twelve months post-surgery, only the equation of Lazzer et al. considering body composition showed better prediction (accuracy: 50%) in this period. CONCLUSION: None of the prediction equations tested was accurate for estimating TEE for the 3 periods evaluated; however, while there are no reports of specific equations for class III obese women, the Harris and Benedict x MET and DRI equations, can describe the TEE with acceptable accuracy. After surgery, the best equation to be used will depend if the patient has been treated for weight loss and in which post-treatment period it is used. Registration of clinical trial as an observational study in Brazilian Clinical Trials Registry: RBR-8k5jsj. Universal Trial Number: U1111-1206-0858.

Resting Metabolic Rate, Total Daily Energy Expenditure, and Metabolic Adaptation 6 Months and 24 Months After Bariatric Surgery.

OBJECTIVE: Little is known about long-term metabolic (energy expenditure) adaptation after bariatric surgery. METHODS: Resting metabolic rate under basal conditions (RMR), total daily energy expenditure (TDEE), and body composition were measured in 25 participants in the Longitudinal Assessment of Bariatric Surgery-2. RESULTS: Six months after surgery, BMI (±SD) decreased (47 ± 6 kg/m2 to 37 ± 5 kg/m2 ), body fat went from 48% ± 6% to 40% ± 6% fat, and fat-free mass went from 67 ± 9 kg to 60 ± 9 kg. In absolute terms, RMR and TDEE both decreased significantly (1,730 ± 278 kcal/d vs. 1,430 ± 200 kcal/d and 2,879 ± 544 kcal/d vs. 2,369 ± 304 kcal/d), and the achieved energy balance was -1,293 ± 355 kcal/d. Sixteen of these participants underwent repeated measures at ∼24 months; TDEE decreased 6 months postoperatively (2,957 ± 540 kcal/d to 2,423 ± 324 kcal/d; P = 0.0003), but at ∼24 months, TDEE (2,602 ± 471 kcal/d) was not significantly different compared with month 6. The average negative energy balance from baseline to month 24 was -379 ± 131 kcal/d. CONCLUSIONS: RMR and TDEE fall precipitously in the first 6 months after bariatric surgery, but these adaptive changes were no longer significant after 2 years.

Total energy expenditure and body composition of children with developmental disabilities.

BACKGROUND: Obesity prevalence is increased in children with developmental disabilities, specifically in children with spina bifida and Down syndrome. Energy expenditure, a critical aspect of weight management, has been extensively studied in the typically developing population, but not adequately studied in children with developmental disabilities. OBJECTIVE: Determine energy expenditure, fat-free mass and body fat percentile and the impact of these findings on recommended caloric intake in children with spina bifida and Down syndrome. METHODS/MEASURES: This pilot study included 36 children, 18 with spina bifida, 9 with Down syndrome and 9 typically developing children. Half of the children with spina bifida were non-ambulatory. Doubly labeled water was used to measure energy expenditure and body composition. Descriptive statistics described the sample and MANOVA and ANOVA methods were used to evaluate differences between groups. RESULTS: Energy expenditure was significantly less for children with spina bifida who primarily used a wheelchair (p = .001) and children with Down syndrome (p = .041) when compared to children without a disability when adjusted for fat-free mass. However, no significant difference was detected in children with spina bifida who ambulated without assistance (p = .072). CONCLUSIONS: Children with spina bifida and Down syndrome have a significantly decreased energy expenditure which directly impacts recommended caloric intake. No significant difference was detected for children with spina bifida who ambulated, although the small sample size of this pilot study may have limited these findings. Validating these results in a larger study is integral to supporting successful weight management of these children.

Independent association of resting energy expenditure with blood pressure: confirmation in populations of the African diaspora.

BACKGROUND: Obesity is a major risk factor for hypertension, however, the physiologic mechanisms linking increased adiposity to elevations in blood pressure are not well described. An increase in resting energy expenditure (REE) is an obligatory consequence of obesity. Previous survey research has demonstrated that REE is an independent predictor of blood pressure, and eliminates the co-linear association of body mass index. This observation has received little attention and there have been no attempts to provide a causal explanation. METHODS: At baseline in an international comparative study on obesity, 289 participants aged 25-44 were recruited from communities in the US, the Seychelles, Ghana and South Africa and had REE measured with indirect calorimetry. All participants were thought to be free of major illness. RESULTS: In multivariate regression models, both systolic and diastolic blood pressure were positively associated with REE (p < 0.01), while body mass index and fat mass were negatively correlated with systolic blood pressure (p < 0.01, and p < 0.05 respectively), but not diastolic blood pressure. CONCLUSIONS: These data confirm previous reports and suggest that a common physiologic abnormality links REE and blood pressure. Elevated catecholamines, a putative metabolic characteristic of obesity, is a possible candidate to explain this association. The direct role of excess adipose tissue is open to question.

Surveying predictors of late-life longitudinal change in daily activity energy expenditure.

BACKGROUND: Total daily energy expenditure (TEE) is composed of resting metabolic rate (RMR), post-prandial thermogenesis and activity energy expenditure (AEE). Higher AEE is strongly associated with lower mortality and physical limitations among older adults, but factors that predict changes in AEE in septu and octogenarians are not clearly understood. OBJECTIVE: To identify factors associated with late-life longitudinal change in AEE. DESIGN: Energy expenditure was re-assessed in 83 participants (average age at baseline, 74.4±3.2 years)-an average of 7.5±0.54 years since the baseline measure. RMR was measured using indirect calorimetry and the thermic effect of meals was estimated at 10% of TEE. AEE was calculated as: TEE(0.9)-RMR. Participants were categorized into two groups according to the estimated day-to-day precision of the doubly-labeled water technique. Those who were within 10% or increased relative to their initial AEE measurement were categorized as having preserved AEE. Participants who declined greater than 10% of their initial measurement were categorized as having reduced AEE. A variety of socio-demographic, functional and mental factors, body composition, community and personal behaviors, blood measurements and health conditions were evaluated between groups at baseline and changes during follow-up. RESULTS: Daily AEE declined 106.61±293.25 kcal, which equated to a 14.63±40.57 kcal/d decrease per year. Fifty-nine percent (n = 49) preserved their AEE and 41% (n = 34) declined. Those who demonstrated a decline in AEE were older, had lower walking speed at baseline and showed a higher lean mass loss during follow up. Otherwise, groups were similar for socio-demographic characteristics, body composition, mental and physical function, health conditions and community and personal behaviors at baseline and change in these factors during follow-up. CONCLUSIONS: This study demonstrates that AEE declines through the 8th decade of life and is associated with age, lower walking speed at baseline and lean mass loss. Additionally, there are a significant number of individuals who appear to be resilient to these declines despite having health events that are expected to have a negative impact on their physical activity.

Constrained Total Energy Expenditure and Metabolic Adaptation to Physical Activity in Adult Humans.

Current obesity prevention strategies recommend increasing daily physical activity, assuming that increased activity will lead to corresponding increases in total energy expenditure and prevent or reverse energy imbalance and weight gain [1-3]. Such Additive total energy expenditure models are supported by exercise intervention and accelerometry studies reporting positive correlations between physical activity and total energy expenditure [4] but are challenged by ecological studies in humans and other species showing that more active populations do not have higher total energy expenditure [5-8]. Here we tested a Constrained total energy expenditure model, in which total energy expenditure increases with physical activity at low activity levels but plateaus at higher activity levels as the body adapts to maintain total energy expenditure within a narrow range. We compared total energy expenditure, measured using doubly labeled water, against physical activity, measured using accelerometry, for a large (n = 332) sample of adults living in five populations [9]. After adjusting for body size and composition, total energy expenditure was positively correlated with physical activity, but the relationship was markedly stronger over the lower range of physical activity. For subjects in the upper range of physical activity, total energy expenditure plateaued, supporting a Constrained total energy expenditure model. Body fat percentage and activity intensity appear to modulate the metabolic response to physical activity. Models of energy balance employed in public health [1-3] should be revised to better reflect the constrained nature of total energy expenditure and the complex effects of physical activity on metabolic physiology.

The Obesity Prevention Initiative: A Statewide Effort to Improve Child Health in Wisconsin.

BACKGROUND/SIGNIFICANCE: Obesity rates have increased dramatically, especially among children and disadvantaged populations. Obesity is a complex issue, creating a compelling need for prevention efforts in communities to move from single isolated programs to comprehensive multisystem interventions. To address these issues, we have established a childhood Obesity Prevention Initiative (Initiative) for Wisconsin. This Initiative seeks to test community change frameworks that can support multisystem interventions and provide data for local action as a means for influencing policies, systems, and environments that support individuals' healthy eating and physical activity. APPROACHES/AIMS: The Initiative is comprised of three components: (1) infrastructure to support a statewide obesity prevention and health promotion network with state- and local-level public messaging and dissemination of evidence-based solutions (healthTIDE); (2) piloting a local, multisetting community-led intervention study in 2 Wisconsin counties; and (3) developing a geocoded statewide childhood obesity and fitness surveillance system. RELEVANCE: This Initiative is using a new model that involves both coalition action and community organizing to align resources to achieve health improvement at local and state levels. We expect that it will help lead to the implementation of cohesive and sustainable policy, system, and environment health promotion and obesity prevention strategies in communities statewide, and it has the potential to help Wisconsin become a national model for multisetting community interventions to address obesity. Addressing individual-level health through population-level changes ultimately will result in reductions in the prevalence of childhood obesity, current and future health care costs, and chronic disease mortality.

School Gardens Enhance Academic Performance and Dietary Outcomes in Children.

BACKGROUND: Schools face increasing demands to provide education on healthy living and improve core academic performance. Although these appear to be competing concerns, they may interact beneficially. This article focuses on school garden programs and their effects on students' academic and dietary outcomes. METHODS: Database searches in CABI, Web of Science, Web of Knowledge, PubMed, Education Full Text, Education Resources Information Center (ERIC), and PsychINFO were conducted through May 2013 for peer-reviewed literature related to school-day garden interventions with measures of dietary and/or academic outcomes. RESULTS: Among 12 identified garden studies with dietary measures, all showed increases/improvements in predictors of fruit and vegetable (FV) consumption. Seven of these also included self-reported FV intake with 5 showing an increase and 2 showing no change. Four additional interventions that included a garden component measured academic outcomes; of these, 2 showed improvements in science achievement and 1 measured and showed improvements in math scores. CONCLUSIONS: This small set of studies offers evidence that garden-based learning does not negatively impact academic performance or FV consumption and may favorably impact both. Additional studies with more robust experimental designs and outcome measures are necessary to understand the effects of experiential garden-based learning on children's academic and dietary outcomes.