The roles of sleep and eating patterns in adiposity gain among preschool-aged children.

BACKGROUND: Short sleep durations are related to risks for obesity in preschool children. However, the underlying mechanism or mechanisms are not clear. OBJECTIVES: We evaluated the relationships between sleep characteristics and body composition, energetics, and weight-regulating behaviors in preschool-aged children, as well as the longitudinal associations between children's sleep and eating patterns and body composition at a 1-year follow-up. METHODS: Data were drawn from a longitudinal study of 118 children aged 3-5 years. Sleep (duration, midpoint, regularity) and physical activity (PA) were measured by accelerometry over 6 consecutive days; total energy expenditure (TEE) was measured using the doubly labeled water method; body composition (fat mass, fat-free mass, and percent body fat) was measured by DXA; and dietary intake (energy intake, timing) was measured using two 24-hour recalls. Multivariable regression was used to estimate interindividual associations of sleep parameters with body composition, PA, TEE, and dietary outcomes and to examine the relationships between sleep and dietary behaviors and body composition 1 year later. RESULTS: Cross-sectionally, later sleep midpoint is associated with having a greater fat mass (0.33; 95% CI: 0.05, 0.60) and a higher percent body fat (0.92; 95% CI: 0.15, 1.70). Later sleep midpoint was associated with delayed morning mealtimes (0.51; 95% CI: 0.28, 0.74) and evening mealtimes (0.41; 95% CI: 0.29, 0.53), higher nighttime energy intakes (45.6; 95% CI: 19.7, 71.4), and lower morning energy intakes (-44.8; 95% CI: -72.0, -17.6). Longitudinally, shorter sleep duration (-0.02; 95% CI: -0.03, 0.00) and later meal timing (0.83; 95% CI: 0.24, 1.42) were associated with higher percent body fat measurements 1 year later. CONCLUSIONS: Shorter sleep duration and later meal timing are associated with adiposity gains in preschoolers.

Behavior Modification of Diet and Parent Feeding Practices in a Community- Vs Primary Care-Centered Intervention for Childhood Obesity.

OBJECTIVE: To evaluate behavior modification of diet and parent feeding practices in childhood obesity interventions. DESIGN: Secondary analysis of randomized, controlled trial comparing Mind, Exercise, Nutrition … Do It! (MEND2-5 and MEND/Coordinated Approach to Child Health [CATCH6-12]) vs Next Steps at baseline and 3 and 12 months. SETTING: Austin and Houston, TX. PARTICIPANTS: A total of 549 Hispanic and black children randomized to programs by age groups (2-5, 6-8, and 9-12 years) INTERVENTIONS: Twelve-month MEND2-5 and MEND/CATCH6-12 vs Next Steps. MAIN OUTCOME MEASURE(S): Diet (MEND-friendly/unfriendly food groups and Healthy Eating Index-2010) and parent feeding practices (parental overt control, discipline, limit setting, monitoring, reinforcement, modeling, and covert control; and food neophobia). ANALYSIS: Mixed-effects linear regression. RESULTS: Changes in diet quality, consumption of MEND-unfriendly foods, and parent feeding practices did not differ between programs. In both interventions, MEND-unfriendly vegetables, grains, dairy and protein, added fat and desserts/sugar-sweetened beverages declined in 2-5- and 6-8-year-olds (P < .001). Healthy Eating Index-2010 improved in 2-5- (treatment; P = .002) and 6-8-year-olds (P = .001). Parental overt control decreased and limit setting, discipline, monitoring, reinforcement, and covert control increased with both interventions in 2-5- and 6-8-year-olds (P < 0.01-0.001). CONCLUSIONS: Diet quality, consumption of MEND-unfriendly foods, and parent feeding practices were altered constructively in 2 pediatric obesity interventions, especially in 2-5- and 6-8-year-olds.

Impact of changes in maternal body composition on birth weight and neonatal fat mass in dichorionic twin pregnancies.

Background: Although the impact of gestational weight gain (GWG) on birth weight in twin pregnancies has been demonstrated, the specific components of GWG have not been delineated for twin gestations. Fetal body composition has been shown to be modifiable in singleton gestations based on nutritional intervention strategies and may prove to have similar modifications in twin gestations. Objective: We aimed to determine the relation of maternal body composition changes to birth weight, birth length, and neonatal fat mass (FM) in dichorionic-diamniotic twin pregnancies. Design: This is a prospective study of 20 women with twin gestations. Comparisons were made between body composition variables during each trimester and for the entire pregnancy and compared with the outcomes of birth weight, neonatal fat percentage, and birth length. Results: GWG within or above compared with below the IOM recommendations was associated with higher birth weights (P = 0.03, P = 0.04, respectively), but also with higher postpartum weight retention (P = 0.001). Total maternal protein gain over the pregnancy was positively associated with birth weight (P = 0.03). Changes in maternal fat-free mass (FFM), total body water (TBW), and FM from the first to the third trimester were not associated with either birth weight or neonatal FM percentage. However, maternal FM change from the second to the third trimester was significantly correlated to neonatal FM percentage (P = 0.02). Third trimester GWG and total protein gain were positively correlated with neonatal birth length (P = 0.02 and 0.03, respectively). Maternal FFM over all 3 trimesters showed a positive relation with neonatal birth length (P = 0.01). Conclusions: Significant increases in maternal protein are associated with greater birth weight and neonatal birth length. Protein accretion, in contrast to TBW and FM gains, may be the most critical component of maternal GWG in dichorionic twin gestations.

Estimated energy requirements increase across pregnancy in healthy women with dichorionic twins.

Background: Estimated energy requirement (EER) has not been defined for twin pregnancy. This study was designed to determine the EER of healthy women with dichorionic-diamniotic (DCDA) twin pregnancies. Objectives: We aimed to estimate energy deposition from changes in maternal body protein and fat; to measure resting energy expenditure (REE), physical activity level (PAL), and total energy expenditure (TEE) throughout pregnancy and postpartum; and to define the EER based on the sum of TEE and energy deposition for twin gestation. Design: This is a prospective study of 20 women with DCDA twin gestations. Maternal EER, energy deposition, REE, TEE, and PAL were obtained during the first, second, and third trimesters of pregnancy and immediately postpartum. A mixed-effects linear regression model for repeated measures with random intercept was used to test for the effects of BMI groups and time. Results: Gains in total body protein (mean ± SD: 2.1 ± 0.7 kg) and fat mass (5.9 ± 2.8 kg) resulted in total energy deposition of 67,042 ± 25,586 kcal between 0 and 30-32 weeks of gestation. REE increased 26% from 1392 ± 162 to 1752 ± 172 kcal/d across the 3 trimesters, whereas TEE increased 17% from 2141 ± 283 to 2515 ± 337 kcal/d. Physical activity decreased steadily throughout pregnancy. Reductions in physical activity did not compensate for the rise in REE and energy deposition, thus requiring an increase in dietary energy intake as pregnancy progressed. EER increased 29% from 2257 ± 325 kcal/d in the first trimester to 2941 ± 407 kcal/d in the second trimester, and stayed consistent at 2906 ± 350 kcal/d in the third trimester. Conclusion: Increased energy intake, on average ∼700 kcal/d in the second and third trimesters when compared with the first trimester, is required to support gestational weight gain and the rise in energy expenditure of DCDA twin pregnancies.

Efficacy of a Community- Versus Primary Care-Centered Program for Childhood Obesity: TX CORD RCT.

OBJECTIVE: This randomized controlled trial was conducted to determine comparative efficacy of a 12-month community-centered weight management program (MEND2-5 for ages 2-5 or MEND/CATCH6-12 for ages 6-12) against a primary care-centered program (Next Steps) in low-income children. METHODS: Five hundred forty-nine Hispanic and black children (BMI ≥ 85th percentile), stratified by age groups (2-5, 6-8, and 9-12 years), were randomly assigned to MEND2-5 (27 contact hours)/MEND/CATCH6-12 (121.5 contact hours) or Next Steps (8 contact hours). Primary (BMI value at the 95th percentile [%BMIp95 ]) and secondary outcomes were measured at baseline, 3 months (Intensive Phase), and 12 months (Transition Phase). RESULTS: For age group 6-8, MEND/CATCH6-12 resulted in greater improvement in %BMIp95 than Next Steps during the Intensive Phase. Effect size (95% CI) was -1.94 (-3.88, -0.01) percentage points (P = 0.05). For age group 9-12, effect size was -1.38 (-2.87, 0.16) percentage points for %BMIp95 (P = 0.07). MEND2-5 did not differentially affect %BMIp95 . Attendance averaged 52% and 22% during the Intensive and Transition Phases. Intervention compliance was inversely correlated to change in %BMIp95 during the Intensive Phase (P < 0.05). In the Transition Phase, %BMIp95 was maintained or rebounded in both programs (P < 0.05). CONCLUSIONS: MEND/CATCH6-12 was more efficacious for BMI reduction at 3 months but not 12 months compared to Next Steps in underserved children. Intervention compliance influenced outcomes, emphasizing the need for research in sustaining family engagement in low-income populations.

Energy Cost of Activities in Preschool-Aged Children.

BACKGROUND: The absolute energy cost of activities in children increase with age due to greater muscle mass and physical capability associated with growth and developmental maturation; however, there is a paucity of data in preschool-aged children. Study aims were 1) to describe absolute and relative energy cost of common activities of preschool-aged children in terms of VO2, energy expenditure (kilocalories per minute) and child-specific metabolic equivalents (METs) measured by room calorimetry for use in the Youth Compendium of Physical Activity, and 2) to predict METs from age, sex and heart rate (HR). METHODS: Energy expenditure (EE), oxygen consumption (VO2), HR, and child-METs of 13 structured activities were measured by room respiration calorimetry in 119 healthy children, ages 3 to 5 years. RESULTS: EE, VO2, HR, and child-METs are presented for 13 structured activities ranging from sleeping, sedentary, low-, moderate- to high-active. A significant curvilinear relationship was observed between child-METs and HR (r2 = .85; P = .001). CONCLUSION: Age-specific child METs for 13 structured activities in preschool-aged children will be useful to extend the Youth Compendium of Physical Activity for research purposes and practical applications. HR may serve as an objective measure of MET intensity in preschool-aged children.

Role of physical activity and sleep duration in growth and body composition of preschool-aged children.

OBJECTIVE: The impact of physical activity patterns and sleep duration on growth and body composition of preschool-aged children remains unresolved. Aims were (1) to delineate cross-sectional associations among physical activity components, sleep, total energy expenditure (TEE), and body size and composition; and (2) to determine whether physical activity components, sleep, and TEE predict 1-year changes in body size and composition in healthy preschool-aged children. METHODS: Anthropometry, body composition, accelerometry, and TEE by doubly labeled water were measured at baseline; anthropometry and body composition were repeated 1 year later (n = 111). RESULTS: Cross-sectionally, positive associations between sedentary activity and weight and fat-free mass (FFM) (P = 0.009-0.047), and a negative association between moderate-vigorous physical activity (MVPA) and percent fat mass (FM) (P = 0.015) were observed. TEE and activity energy expenditure (AEE) were positively associated with weight, body mass index (BMI), FFM, and FM (P = 0.0001-0.046). Prospectively, TEE, AEE, physical activity level, and MVPA, but not sedentary activity, were positively associated with changes in BMI (P = 0.0001-0.051) and FFM (P = 0.0001-0.037), but not percent FM. Sleep duration inversely predicted changes in FM (P = 0.005) and percent FM (P = 0.006). CONCLUSIONS: Prospectively, MVPA, TEE, AEE, and physical activity level promote normal growth and accretion of FFM, whereas sleep duration inversely predicts changes in adiposity in preschool-aged children.

Energetic adaptations persist after bariatric surgery in severely obese adolescents.

OBJECTIVE: Energetic adaptations induced by bariatric surgery have not been studied in adolescents or for extended periods postsurgery. Energetic, metabolic, and neuroendocrine responses to Roux-en-Y gastric bypass (RYGB) surgery were investigated in extremely obese adolescents. METHODS: At baseline and at 1.5, 6, and 12 months post-baseline, 24-h room calorimetry, body composition, and fasting blood biochemistries were measured in 11 obese adolescents relative to five matched controls. RESULTS: In the RYGB group, mean weight loss was 44 ± 19 kg at 12 months. Total energy expenditure (TEE), activity EE, basal metabolic rate (BMR), sleep EE, and walking EE significantly declined by 1.5 months (P = 0.001) and remained suppressed at 6 and 12 months. Adjusted for age, sex, fat-free mass, and fat mass, EE was still lower than baseline (P = 0.001). Decreases in serum insulin, leptin, and triiodothyronine (T3), gut hormones, and urinary norepinephrine (NE) paralleled the decline in EE. Adjusted changes in TEE, BMR, and/or sleep EE were associated with decreases in insulin, homeostatic model assessment, leptin, thyroid stimulating hormone, total T3, peptide YY3-36, glucagon-like peptide-2, and urinary NE and epinephrine (P = 0.001-0.05). CONCLUSIONS: Energetic adaptations in response to RYGB-induced weight loss are associated with changes in insulin, adipokines, thyroid hormones, gut hormones, and sympathetic nervous system activity and persists 12 months postsurgery.

Revision of Dietary Reference Intakes for energy in preschool-age children.

BACKGROUND: Dietary Reference Intakes (DRI) for energy aim to balance energy expenditure at a level of physical activity consistent with health and support adequate growth in children. DRIs were derived from total energy expenditure (TEE) measured by using the doubly labeled water (DLW) method; however, the database was limited in the 3-5-y-old range. OBJECTIVE: We reexamined the DRI for energy for preschool-age children. DESIGN: Ninety-seven healthy, normal-weight, preschool-age children (mean ± SD age: 4.5 ± 0.9 y) completed a 7-d DLW protocol while wearing accelerometer and heart rate-monitoring devices. RESULTS: Mean TEE and physical activity level (PAL) averaged 1159 ± 171 kcal/d and 1.34 ± 0.14, respectively. TEE predicted by DRI equations agreed with observed TEE (+34 kcal/d or 3%) if the sedentary PAL category was assumed but was overestimated by using the low active (+219 kcal/d or 19%), active (398 kcal/d or 34%), and very active (593 kcal/d or 51%) PAL categories. PAL categories were redefined on the basis of the narrower PAL range observed in preschoolers (range: 1.05-1.70) compared with older children and adults (range: 1.0-2.5). Sex-specific nonlinear regression models were newly developed to predict TEE from age, weight, height, and new PAL categories. The mean absolute error of TEE prediction equations was 0.00 ± 35 kcal/d or 0.1 ± 3%. Ancillary measures, such as total accelerometer counts and total daily steps, that were significantly correlated (P = 0.01-0.05) with TEE (r = 0.26-0.38), TEE per kilogram (r = 0.31-0.41), and PAL (r = 0.36-0.48) may assist in the classification of preschoolers into PAL categories. CONCLUSIONS: Current DRIs for energy overestimate energy requirements of preschool-age children because of the erroneous classification of children into PAL categories. New TEE prediction equations that are based on DLW and appropriate PAL categories are recommended for preschool-age children. This trial was registered at clinicaltrials.gov as H12067.

Prediction of energy expenditure and physical activity in preschoolers.

PURPOSE: Accurate, nonintrusive, and feasible methods are needed to predict energy expenditure (EE) and physical activity (PA) levels in preschoolers. Herein, we validated cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on accelerometry and heart rate (HR) for the prediction of EE using room calorimetry and doubly labeled water (DLW) and established accelerometry cut points for PA levels. METHODS: Fifty preschoolers, mean ± SD age of 4.5 ± 0.8 yr, participated in room calorimetry for minute-by-minute measurements of EE, accelerometer counts (AC) (Actiheart and ActiGraph GT3X+), and HR (Actiheart). Free-living 105 children, ages 4.6 ± 0.9 yr, completed the 7-d DLW procedure while wearing the devices. AC cut points for PA levels were established using smoothing splines and receiver operating characteristic curves. RESULTS: On the basis of calorimetry, mean percent errors for EE were -2.9% ± 10.8% and -1.1% ± 7.4% for CSTS models and -1.9% ± 9.6% and 1.3% ± 8.1% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. On the basis of DLW, mean percent errors were -0.5% ± 9.7% and 4.1% ± 8.5% for CSTS models and 3.2% ± 10.1% and 7.5% ± 10.0% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. Applying activity EE thresholds, final accelerometer cut points were determined: 41, 449, and 1297 cpm for Actiheart x-axis; 820, 3908, and 6112 cpm for ActiGraph vector magnitude; and 240, 2120, and 4450 cpm for ActiGraph x-axis for sedentary/light, light/moderate, and moderate/vigorous PA (MVPA), respectively. On the basis of confusion matrices, correctly classified rates were 81%-83% for sedentary PA, 58%-64% for light PA, and 62%-73% for MVPA. CONCLUSIONS: The lack of bias and acceptable limits of agreement affirms the validity of the CSTS and MARS models for the prediction of EE in preschool-aged children. Accelerometer cut points are satisfactory for the classification of sedentary, light, and moderate/vigorous levels of PA in preschoolers.

Support vector machines classifiers of physical activities in preschoolers.

The goal of this study is to develop, test, and compare multinomial logistic regression (MLR) and support vector machines (SVM) in classifying preschool-aged children physical activity data acquired from an accelerometer. In this study, 69 children aged 3-5 years old were asked to participate in a supervised protocol of physical activities while wearing a triaxial accelerometer. Accelerometer counts, steps, and position were obtained from the device. We applied K-means clustering to determine the number of natural groupings presented by the data. We used MLR and SVM to classify the six activity types. Using direct observation as the criterion method, the 10-fold cross-validation (CV) error rate was used to compare MLR and SVM classifiers, with and without sleep. Altogether, 58 classification models based on combinations of the accelerometer output variables were developed. In general, the SVM classifiers have a smaller 10-fold CV error rate than their MLR counterparts. Including sleep, a SVM classifier provided the best performance with a 10-fold CV error rate of 24.70%. Without sleep, a SVM classifier-based triaxial accelerometer counts, vector magnitude, steps, position, and 1- and 2-min lag and lead values achieved a 10-fold CV error rate of 20.16% and an overall classification error rate of 15.56%. SVM supersedes the classical classifier MLR in categorizing physical activities in preschool-aged children. Using accelerometer data, SVM can be used to correctly classify physical activities typical of preschool-aged children with an acceptable classification error rate.

Sleep duration of underserved minority children in a cross-sectional study.

BACKGROUND: Short sleep duration has been shown to associate with increased risk of obesity. Childhood obesity is more prevalent among underserved minority children. The study measured the sleep duration of underserved minority children living in a large US urban environment using accelerometry and its relationship with BMI, socioeconomic status (SES), gender, ethnicity and physical activity. METHODS: Time spent on sleep and physical activity among 333 Hispanic and 150 black children (9-12 y) was measured objectively by accelerometry over 5-7 consecutive days. The children were recruited at 14 underserved community centers in Houston, Texas, between January 2009 and February 2011. Body weight and height were measured in duplicate. RESULTS: The majority of children (88.8%) wore the monitor for 6 consecutive days. The children slept 8.8 ± 0.6 (mean ± SD) h/d and spent 45 ± 24 min/d on moderate-vigorous physical activity (MVPA). Hispanic children slept 0.2 h/d longer (P<0.001) than black children. Obese children slept 0.2 h/d less (P<0.02) than normal-weight children. SES had no effect on sleep duration. There was a significant interaction between gender and age (P<0.03); girls aged 11-12 y slept 0.3 h/d less than boys and the younger girls. Children slept 0.6 h/d longer (P<0.001) during the weekend than weekdays. No relation was detected between sleep duration and MVPA time. CONCLUSIONS: Minority children living in a large metropolitan area in the US are not meeting the National Sleep Foundation recommendation for sleep duration of 10-11 h/d. Longitudinal studies based on objective measures are needed to establish causality between sleep duration and obesity risk among minority children.

Modeling energy expenditure in children and adolescents using quantile regression.

Advanced mathematical models have the potential to capture the complex metabolic and physiological processes that result in energy expenditure (EE). Study objective is to apply quantile regression (QR) to predict EE and determine quantile-dependent variation in covariate effects in nonobese and obese children. First, QR models will be developed to predict minute-by-minute awake EE at different quantile levels based on heart rate (HR) and physical activity (PA) accelerometry counts, and child characteristics of age, sex, weight, and height. Second, the QR models will be used to evaluate the covariate effects of weight, PA, and HR across the conditional EE distribution. QR and ordinary least squares (OLS) regressions are estimated in 109 children, aged 5-18 yr. QR modeling of EE outperformed OLS regression for both nonobese and obese populations. Average prediction errors for QR compared with OLS were not only smaller at the median τ = 0.5 (18.6 vs. 21.4%), but also substantially smaller at the tails of the distribution (10.2 vs. 39.2% at τ = 0.1 and 8.7 vs. 19.8% at τ = 0.9). Covariate effects of weight, PA, and HR on EE for the nonobese and obese children differed across quantiles (P < 0.05). The associations (linear and quadratic) between PA and HR with EE were stronger for the obese than nonobese population (P < 0.05). In conclusion, QR provided more accurate predictions of EE compared with conventional OLS regression, especially at the tails of the distribution, and revealed substantially different covariate effects of weight, PA, and HR on EE in nonobese and obese children.

Cross-sectional time series and multivariate adaptive regression splines models using accelerometry and heart rate predict energy expenditure of preschoolers.

Prediction equations of energy expenditure (EE) using accelerometers and miniaturized heart rate (HR) monitors have been developed in older children and adults but not in preschool-aged children. Because the relationships between accelerometer counts (ACs), HR, and EE are confounded by growth and maturation, age-specific EE prediction equations are required. We used advanced technology (fast-response room calorimetry, Actiheart and Actigraph accelerometers, and miniaturized HR monitors) and sophisticated mathematical modeling [cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS)] to develop models for the prediction of minute-by-minute EE in 69 preschool-aged children. CSTS and MARS models were developed by using participant characteristics (gender, age, weight, height), Actiheart (HR+AC_x) or ActiGraph parameters (AC_x, AC_y, AC_z, steps, posture) [x, y, and z represent the directional axes of the accelerometers], and their significant 1- and 2-min lag and lead values, and significant interactions. Relative to EE measured by calorimetry, mean percentage errors predicting awake EE (-1.1 ± 8.7%, 0.3 ± 6.9%, and -0.2 ± 6.9%) with CSTS models were slightly higher than with MARS models (-0.7 ± 6.0%, 0.3 ± 4.8%, and -0.6 ± 4.6%) for Actiheart, ActiGraph, and ActiGraph+HR devices, respectively. Predicted awake EE values were within ±10% for 81-87% of individuals for CSTS models and for 91-98% of individuals for MARS models. Concordance correlation coefficients were 0.936, 0.931, and 0.943 for CSTS EE models and 0.946, 0.948, and 0.940 for MARS EE models for Actiheart, ActiGraph, and ActiGraph+HR devices, respectively. CSTS and MARS models should prove useful in capturing the complex dynamics of EE and movement that are characteristic of preschool-aged children.

Validation of uniaxial and triaxial accelerometers for the assessment of physical activity in preschool children.

PURPOSE: Given the unique physical activity (PA) patterns of preschoolers, wearable electronic devices for quantitative assessment of physical activity require validation in this population. Study objective was to validate uniaxial and triaxial accelerometers in preschoolers. METHODS: Room calorimetry was performed over 3 hours in 64 preschoolers, wearing Actical, Actiheart, and RT3 accelerometers during play, slow, moderate, and fast translocation. Based on activity energy expenditure (AEE) and accelerometer counts, optimal thresholds for PA levels were determined by piecewise linear regression and discrimination boundary analysis. RESULTS: Established HR cutoffs in preschoolers for sedentary/light, light/moderate and moderate/vigorous levels were used to define AEE (0.015, 0.054, 0.076 kcal·kg-1·min-1) and PA ratio (PAR; 1.6, 2.9, 3.6) thresholds, and accelerometer thresholds. True positive predictive rates were 77%, 75%, and 76% for sedentary; 63%, 61%, and 65% for light; 34%, 52%, and 49% for moderate; 46%, 46%, and 49% for vigorous levels. Due to low positive predictive rates, we combined moderate and vigorous PA. Classification accuracy was improved overall and for the combined moderate-to-vigorous PA level (69%, 82%, 79%) for Actical, Actiheart, and RT3, respectively. CONCLUSION: Uniaxial and triaxial accelerometers are acceptable devices with similar classification accuracy for sedentary, light, and moderate-to-vigorous levels of PA in preschoolers.

Validation of cross-sectional time series and multivariate adaptive regression splines models for the prediction of energy expenditure in children and adolescents using doubly labeled water.

Accurate, nonintrusive, and inexpensive techniques are needed to measure energy expenditure (EE) in free-living populations. Our primary aim in this study was to validate cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on observable participant characteristics, heart rate (HR), and accelerometer counts (AC) for prediction of minute-by-minute EE, and hence 24-h total EE (TEE), against a 7-d doubly labeled water (DLW) method in children and adolescents. Our secondary aim was to demonstrate the utility of CSTS and MARS to predict awake EE, sleep EE, and activity EE (AEE) from 7-d HR and AC records, because these shorter periods are not verifiable by DLW, which provides an estimate of the individual's mean TEE over a 7-d interval. CSTS and MARS models were validated in 60 normal-weight and overweight participants (ages 5-18 y). The Actiheart monitor was used to simultaneously measure HR and AC. For prediction of TEE, mean absolute errors were 10.7 +/- 307 kcal/d and 18.7 +/- 252 kcal/d for CSTS and MARS models, respectively, relative to DLW. Corresponding root mean square error values were 305 and 251 kcal/d for CSTS and MARS models, respectively. Bland-Altman plots indicated that the predicted values were in good agreement with the DLW-derived TEE values. Validation of CSTS and MARS models based on participant characteristics, HR monitoring, and accelerometry for the prediction of minute-by-minute EE, and hence 24-h TEE, against the DLW method indicated no systematic bias and acceptable limits of agreement for pediatric groups and individuals under free-living conditions.

Multivariate adaptive regression splines models for the prediction of energy expenditure in children and adolescents.

Advanced mathematical models have the potential to capture the complex metabolic and physiological processes that result in heat production or energy expenditure (EE). Multivariate adaptive regression splines (MARS) is a nonparametric method that estimates complex nonlinear relationships by a series of spline functions of the independent predictors. The specific aim of this study is to construct MARS models based on heart rate (HR) and accelerometer counts (AC) to accurately predict EE, and hence 24-h total EE (TEE), in children and adolescents. Secondarily, MARS models will be developed to predict awake EE, sleep EE, and activity EE also from HR and AC. MARS models were developed in 109 and validated in 61 normal-weight and overweight children (ages 5-18 yr) against the criterion method of 24-h room respiration calorimetry. Actiheart monitor was used to measure HR and AC. MARS models were based on linear combinations of 23-28 basis functions that use subject characteristics (age, sex, weight, height, minimal HR, and sitting HR), HR and AC, 1- and 2-min lag and lead values of HR and AC, and appropriate interaction terms. For the 24-h, awake, sleep, and activity EE models, mean percent errors were -2.5 +/- 7.5, -2.6 +/- 7.8, -0.3 +/- 8.9, and -11.9 +/- 17.9%, and root mean square error values were 168, 138, 40, and 122 kcal, respectively, in the validation cohort. Bland-Altman plots indicated that the predicted values were in good agreement with the observed TEE, and that there was no bias with increasing TEE. Prediction errors for 24-h TEE were not statistically associated with age, sex, weight, height, or body mass index. MARS models developed for the prediction of EE from HR monitoring and accelerometry were demonstrated to be valid in an independent cohort of children and adolescents, but require further validation in independent, free-living populations.

Nutrient adequacy and diet quality in non-overweight and overweight Hispanic children of low socioeconomic status: the Viva la Familia Study.

OBJECTIVE: The role of diet quality and nutrient adequacy in the etiology of childhood obesity is poorly understood. The specific aims of these analyses were to assess overall diet quality and nutrient adequacy, and test for association between weight status and diet in children from low socioeconomic status (SES) Hispanic families at high risk for obesity. DESIGN: A cross-sectional study design was used to assess dietary intake in low-SES Hispanic children with and without overweight who were enrolled in the Viva la Familia Study. Multiple-pass 24-hour dietary recalls were recorded on two random, weekday occasions. Diet quality was evaluated according to the Dietary Guidelines for Americans. Nutrient adequacy was assessed using z scores based on estimated average requirement or adequate intake. SUBJECTS/SETTING: The study included 1,030 Hispanic children and adolescents, aged 4 to 19 years, in Houston, TX, who participated between November 2000 and August 2004. STATISTICAL ANALYSIS: STATA software (version 9.1, 2006, STATA Corp, College Station, TX) was used for generalized estimating equations and random effects regression. RESULTS: Diet quality did not adhere to the Dietary Guidelines for Americans for fat, cholesterol, saturated fatty acids, fiber, added sugar, and sodium. Although energy intake was significantly higher in children with overweight, food sources, diet quality, macro- and micronutrient composition were similar between non-overweight and overweight children. Relative to estimated average requirements or adequate intake levels, mean nutrient intakes were adequate (70% to 98% probability) in the children without and with overweight, except for vitamins D and E, pantothenic acid, calcium, and potassium, for which z scores cannot be interpreted given the uncertainty of their adequate intake levels. CONCLUSIONS: Whereas the diets of low-SES Hispanic children with and without overweight were adequate in most essential nutrients, other components of a healthful diet, which promote long-term health, were suboptimal. Knowledge of the diets of high-risk Hispanic children will inform nutritional interventions and policy.

Application of cross-sectional time series modeling for the prediction of energy expenditure from heart rate and accelerometry.

Accurate estimation of energy expenditure (EE) in children and adolescents is required for a better understanding of physiological, behavioral, and environmental factors affecting energy balance. Cross-sectional time series (CSTS) models, which account for correlation structure of repeated observations on the same individual, may be advantageous for prediction of EE. CSTS models for prediction of minute-by-minute EE and, hence, total EE (TEE) from heart rate (HR), physical activity (PA) measured by accelerometry, and observable subject variables were developed in 109 children and adolescents by use of Actiheart and 24-h room respiration calorimetry. CSTS models based on HR, PA, time-invariant covariates, and interactions were developed. These dynamic models involve lagged and lead values of HR and lagged values of PA for better description of the series of minute-by-minute EE. CSTS models with random intercepts and random slopes were investigated. For comparison, likelihood ratio tests were used. Log likelihood increased substantially when random slopes for HR and PA were added. The population-specific model uses HR and 1- and 2-min lagged and lead values of HR, HR(2), and PA and 1- and 2-min lagged values of PA, PA(2), age, age(2), sex, weight, height, minimum HR, sitting HR, HR x height, HR x weight, HR x age, PA x weight, and PA x sex interactions (P < 0.001). Prediction error for TEE was 0.9 +/- 10.3% (mean +/- SD). Errors were not correlated with age, weight, height, or body mass index. CSTS modeling provides a useful predictive model for EE and, hence, TEE in children and adolescents on the basis of HR and PA and other observable explanatory subject characteristics of age, sex, weight, and height.

Body size, body composition, and metabolic profile explain higher energy expenditure in overweight children.

Lower relative rates of energy expenditure (EE), increased energetic efficiency, and altered fuel utilization purportedly associated with obesity have not been demonstrated indisputably in overweight children. We hypothesized that differences in energy metabolism between nonoverweight and overweight children are attributable to differences in body size and composition, circulating thyroid hormones, sympathetic nervous system, and adrenomedullary activity. A total of 836 Hispanic children, 5-19 y old, participated in 24-h calorimetry, anthropometric, and dual-energy X-ray absorptiometry measurements. Biochemistries were determined by standard techniques. Absolute total EE (TEE) and its components (sleep EE, basal EE, sedentary EE, cycling EE, walking EE, activity EE, nonexercising activity thermogenesis) were higher in overweight children (P = 0.001). Net mechanical energetic efficiency of cycling was lower in overweight children (P = 0.001). Adjusting for body size and composition accounted for differences in TEE, its components, and energetic efficiency. Net carbohydrate and fat utilization did not differ between groups. TEE was independently influenced by sex, Tanner stage, fat free mass, fat mass (FM), fasting serum nonesterified fatty acids (NEFA), leptin, free thyroxine, triiodothyronine, and 24-h urinary norepinephrine and epinephrine. Fat utilization was independently associated with age2, sex, FM, fasting serum NEFA, triacylglycerol, adiponectin, leptin, total thyroxine, and free triiodothyronine. Higher EE in overweight children was largely explained by differences in body size and composition, with minor contributions of thyroid and sympathoadrenal systems. Alterations in EE, energetic efficiency, and substrate utilization were not evident in the overweight children.