Relationships of resting energy expenditure with body fat distribution and abdominal fatness in Japanese population

Body fat distribution and abdominal fatness are indicators of risks for coronary heart disease. However, the relationships between resting energy expenditure (REE) and the body fat distribution or the abdominal fatness are unclear. We examined the relationships of REE with whole-body fat distribution (waist, hip and waist-to-hip ratio: WHR) and abdominal fatness (intra-abdominal fat: IF and subcutaneous fat: SF) after adjustment for body composition. 451 men and 471 women were subdivided into two groups, 40-59 years: middle-aged group and 60-79 years: elderly group. REE was measured by an indirect calorimetry system. Percentage of fat mass (%FM), fat mass (FM) and fat-free mass (FFM) were assessed by a dual-energy x-ray absorptiometry method. The IF area (IFA) and SF area (SFA) at the level of the umbilicus were measured using computed tomography. Circumference of waist and hip were measured in a standing position. The WHR, waist circumference and SFA did not significantly (p>0.05) associate with the REE after adjusting for FM, FFM and age in any of the groups. The adjusted REE was significantly and inversely correlated with hip (r=-0.159, p<0.05) and IFA (r=-0.131, p<0.05) in the elderly men. These results suggest that lower REE may contribute to greater hip and IFA rather than WHR and waist in elderly men.     

Serum transaminases concentrations in obese children and adolescents

The aim of the study was to investigate the relationship between liver transaminase levels and metabolic syndrome (MS) features in obese children and adolescents. A total of 132 children and adolescents (73 males and 59 females) aged 8–16, participated in the study. All were studied at the department of Paediatrics, University Hospital of Zaragoza (Spain). Inclusion criteria were the existence of obesity as defined by body mass index (BMI) according to Cole cut-off values (when BMI was higher than the age and sex specific equivalent to 30 kg/m²). The definition of metabolic syndrome was according to the International Diabetes Federation criteria. Weight (kg), height (cm), waist circumference (cm), blood pressure and BMI were measured. Laboratory determinations after overnight fasting included: transaminases (ALT, AST, GGT), fasting glucose, insulin, triglycerides and HDL-C. The MS was found in 21.6% of the obese children and adolescents and the prevalence was higher in males (25.9%) than in females (15.9%). Serum transaminases (ALT, AST and GGT) mean concentrations were higher in males than in females, and decreased during pubertal development. The obese children and adolescents with the MS did not show higher transaminases concentrations when compared with those without the MS. Some MS manifestations (mainly waist circumference) showed a correlation with ALT, although all transaminases values were normal according to adult references. Liver transaminases, a surrogate marker of NAFLD, did not show an early and consistent manifestation of abnormalities in the obese children and adolescents studied. In order to define the presence of the disease, it would be necessary to obtain aminotransferase reference standards for children and adolescents, considering pubertal stage and gender.     

Pedometer-determined physical activity among obese and non-obese 8- to 12-year-old Saudi schoolboys

Physical activity levels were measured in obese and non-obese 8- to 12- year-old schoolboys (n=296). Anthropometric measures included weight, height, body mass index (BMI), triceps and subscapular skinfolds, predicted fat percentage, fat mass (FM), fat-free mass (FFM), FM index (FMI), and FFM index (FFMI). Physical activity was assessed using an electronic pedometer for three continuous weekdays. Boys were divided into active and inactive groups based on daily accumulation of pedometer counts above or below 13,000 steps. Obesity was defined as body fat content that equals or exceeds 25% of body weight. The international age- and gender-specific child BMI cut-off points were also used to define overweight and obesity. Estimated fat content for the whole sample averaged 23.3+/-9.7%. More than 37% of the boys were classified as obese. The mean step counts were about 13,489+/-5,791 steps per day (range: 335-29,169 steps). Over 71% of the boys accumulated 10,000 steps or more per day. Based on BMI standards, mean step counts for the obese group (10,602+/-4,800 steps/day) were significantly (p=0.004) lower than in the normal group (14,271+/-5,576 steps/day). Based on fat percentage, obese boys also accumulated significantly (p=0.009) lower numbers of steps per day (12,682+/-5,236) than did non-obese boys (14,915+/-5,643). Further, there were significant differences (p<0.05) between active and inactive boys in weight, BMI, triceps and subscapular skinfolds, fat percentage, FMI, and flexibility. It is concluded that the prevalence of obesity and inactivity among Saudi boys aged 8-12 years was high. Active boys exhibited significantly lower body fat percentage and BMI than inactive peers. Obese boys, on the other hand, were significantly less active than non-obese boys. Increased prevalence of obesity and physical inactivity among Saudi children is a major public health concern.     

Validation of BIA in Obese Children and Adolescents and Re‐evaluation in a Longitudinal Study

Decrease in fat mass (FM) is a one of the aims of pediatric obesity treatment; however, measurement techniques suitable for routine clinical assessment are lacking. The objective of this study was to validate whole‐body bioelectrical impedance analysis (BIA; TANITA BC‐418MA) against the three‐component (3C) model of body composition in obese children and adolescents, and to test the accuracy of our new equations in an independent sample studied longitudinally. A total of 77 white obese subjects (30 males) aged 5–22 years, BMI‐standard deviation score (SDS) 1.6–3.9, had measurements of weight, height (HT), body volume, total body water (TBW), and impedance (Z). FM and fat‐free mass (FFM) were calculated using the 3C model or predicted from TANITA. FFM was predicted from HT²/Z. This equation was then evaluated in 17 other obese children (5 males) aged 9–13 years. Compared to the 3C model, TANITA manufacturer's equations overestimated FFM by 2.7 kg (P < 0.001). We derived a new equation: FFM = ?2.211 + 1.115 (HT²/Z), with r² of 0.96, standard error of the estimate 2.3 kg. Use of this equation in the independent sample showed no significant bias in FM or FFM (mean bias 0.5 ± 2.4 kg; P = 0.4), and no significant bias in change in FM or FFM (mean bias 0.2 ± 1.8 kg; P = 0.7), accounting for 58% (P < 0.001) and 55% (P = 0.001) of the change in FM and FFM, respectively. Our derived BIA equation, shown to be reliable for longitudinal assessment in white obese children, will aid routine clinical monitoring of body composition in this population.     

Contributing factors and variability of energy expenditure in non-obese, obese, and post-obese adolescents

Energy expenditure (EE) is a major determinant of energy balance and body composition. The objectives of this paper were to review the contributing factors of the main components of daily EE (DEE) and the inter-individual variability in these components in non-obese (NOb), obese (Ob), and post-obese (POb) adolescents. Body composition especially fat-free mass (FFM), is the major determinant of the basal metabolic rate which contributes 50-70% of DEE, whereas fat mass (FM) is a significant factor only in obese subjects. Physical activity is the second main variation factor of DEE, whereas growth, the thermic effect of food, and thermoregulation are generally of marginal importance. The energy costs and EE associated with various sedentary and physical activities were assessed in NOb, Ob and POb subjects both in standardised and in free-living conditions. The interindividual variability of DEE is high, even after adjustment for body composition, mainly because of great differences in time devoted to the various physical activities. DEE and EE associated with sleep and sedentary activities are significantly higher in Ob than in NOb, but not after adjustment for FFM. On the contrary, EE associated with physical activities is not significantly different between Ob and NOb adolescents, but 61% lower in Ob subjects after adjustment for body composition. Multidisciplinary weight-reduction programmes including moderate energy restriction and physical training result in great FM loss, maintenance of FFM, improvement of physical capacities, but reductions in organ and tissue metabolic rate and in EE associated with the various sedentary and physical activities, which may favour body weight regain in the less active POb subjects.     

Accuracy of SenseWear Pro2 Armband to Predict Resting Energy Expenditure in Childhood Obesity

Objective: The accuracy of the SenseWear Pro2 Armband (SWA) in estimating resting energy expenditure (REE) in children and adolescents with obesity, using indirect calorimetry (IC) as a reference was evaluated. Design and Methods: REE was assessed using both the SWA and IC in 40 obese subjects (26 M/14 F, age 11.5 ± 2.57 years, z‐score BMI 3.14 ± 0.53). The agreement between methods was assessed by the Bland‐Altman procedure. The relationship between REE assessments and patients' characteristics was also analyzed. Results : SWA‐ and IC‐derived estimates of REE showed a significant correlation (r = 0.614; P < 0.001), but the SWA overestimated mean REE by 13% (P < 0.001). Age and kilogram of fat‐free mass (kg‐FFM) were significantly correlated with both REE estimation by SWA (r = 0.434 and r = 0.564, respectively) and IC (r = 0.401 and r = 0.518, respectively). Only kg‐FFM was demonstrated to be the main predictor factor of REE variability (r² 79% SWA; 75% IC). Conclusions: The SWA overestimated mean REE in childhood obesity, suggesting that the SWA and IC are not yet interchangeable methods. This would require improving the SWA by developing better algorithms for predicting REE and, probably, bias in each individual REE could be reduced by an adjustment for subjects' kg‐FFM.     

New specific equation to estimate resting energy expenditure in severely obese patients

Calculating the estimated resting energy expenditure (REE) in severely obese patients is useful, but there is controversy concerning the effectiveness of available prediction equations (PE) using body weight (BW). We evaluated the efficacy of REE equations against indirect calorimetry (IC) in severely obese subjects and aimed to develop a new equation based on body composition compartments. One hundred and twenty severely obese patients had their REE measured (MREE) by IC and compared to the most commonly used PE (Harris-Benedict (HB), Ireton-Jones, Owen, and Mifflin St. Jeor). In a random sample (n = 60), a new REE equation based on fat-free mass (FFM) was developed and validated. All PE studied failed to estimate REE in severe obesity (low concordance correlation coefficient (CCC) and limits of agreement of nearly 50% of the sample ±10% of MREE). The HB equation using actual BW exhibited good results for all samples when compared to IC (2,117 ± 518 kcal/day by HB vs. 2,139 ± 423 kcal/day by MREE, P > 0.01); these results were blunted when patients were separated by gender (2,771 vs. 2,586 kcal/day, P < 0.001 in males and 1,825 vs. 1,939 kcal/day, P < 0.001 in females). A new resting energy expenditure equation prediction was developed using FFM, Horie-Waitzberg, & Gonzalez, expressed as 560.43 + (5.39 × BW) + (14.14 × FFM). The new resting energy expenditure equation prediction, which uses FFM and BW, demonstrates higher accuracy, precision, CCC, and limits of agreement than the standard PE in patients when compared to MREE (2,129 ± 45 kcal/day vs. 2,139 ± 423 kcal/day, respectively, P = 0.1).The new equation developed to estimate REE, which takes into account both FFM and BW, provides better results than currently available equations.     

Subclinical Hypothyroidism in Obese Patients: Relation to Resting Energy Expenditure,Serum Leptin,Body Composition,and Lipid Profile

Objective: To evaluate whether subclinical hypothyroidism (SH) affects resting energy expenditure (REE) as well as body composition, lipid profile, and serum leptin in obese patients. Research Methods and Procedures: A total of 108 obese patients with SH defined as normal free thyroxine levels and thyroid‐stimulating hormone (TSH) values of >4.38 μU/ml (mean ± 2 SD of the values of our reference group of obese patients with normal thyroid function) were compared with a group of 131 obese patients matched for age, sex, and body mass index (BMI) but with normal TSH levels. We assessed estimated daily caloric intake by 7‐day recall, REE by indirect calorimetry, body composition by bioelectrical impedance analysis, serum leptin by radioimmunoassay, and lipid profile (i.e., total cholesterol, high‐density lipoprotein cholesterol, low‐density lipoprotein cholesterol, and triglycerides). Results: All of the variables measured were not different between the euthyroid obese patients and those with SH. In a multiple regression model with REE expressed for kilograms of fat free mass (REE/kgFFM) as a dependent variable and percentage of fat mass, BMI, waist‐to‐hip ratio, age, TSH, free thyroxine, serum leptin, and caloric intake as independent variables, only percentage of fat mass was significantly correlated with REE/kgFFM in both groups. In the SH group only, BMI, waist‐to‐hip ratio, age, and TSH were related to REE/kgFFM and explained 69.5% of its variability. After dividing the patients with SH using a cutoff TSH value of 5.7 μU/ml, which represents 3 SD above the mean of TSH levels of the group of obese patients with normal thyroid function, only REE/kgFFM was significantly different and lower in the group of more severely hypothyroid patients. Discussion: In patients with obesity, SH affects energy expenditure only when TSH is clearly above the normal range; it does not change body composition and lipid profile. We suggest that, at least in obese patients, evaluation of TSH levels may be useful to rule out a possible impairment of resting energy expenditure due to a reduced peripheral effect of thyroid hormones.     

Differences in daily energy expenditure in lean and obese women: the role of posture allocation

Objective: A low resting metabolic rate (RMR) is considered a risk factor for weight gain and obesity; however, due to the greater fat‐free mass (FFM) found in obesity, detecting an impairment in RMR is difficult. The purposes of this study were to determine the RMR in lean and obese women controlling for FFM and investigate activity energy expenditure (AEE) and daily activity patterns in the two groups. Methods and Procedures: Twenty healthy, non‐smoking, pre‐menopausal women (10 lean and 10 obese) participated in this 14‐day observational study on free‐living energy balance. RMR was measured by indirect calorimetry; AEE and total energy expenditure (TEE) were calculated using doubly labeled water (DLW), and activity patterns were investigated using monitors. Body composition including FFM and fat mass (FM) was measured by dual energy X‐ray absorptiometry (DXA). Results: RMR was similar in the obese vs. lean women (1601 ± 109 vs. 1505 ± 109 kcal/day, respectively, P = 0.12, adjusting for FFM and FM). Obese women sat 2.5 h more each day (12.7 ± 3.2 h vs. 10.1 ± 2.0 h, P < 0.05), stood 2 h less (2.7 ± 1.0 h vs. 4.7 ± 2.2 h, P = 0.02) and spent half as much time in activity than lean women (2.6 ± 1.5 h vs. 5.4 ± 1.9 h, P = 0.002). Discussion: RMR was not lower in the obese women; however, they were more sedentary and expended less energy in activity than the lean women. If the obese women adopted the activity patterns of the lean women, including a modification of posture allocation, an additional 300 kcal could be expended every day.     

Relationship Between Basal Metabolic Rate,Gender, Age,and Body Composition in 8,780 White Obese Subjects

The objective of the present study was to explore the relationship between basal metabolic rate (BMR), gender, age, anthropometric characteristics, and body composition in severely obese white subjects. In total, 1,412 obese white children and adolescents (BMI > 97° percentile for gender and age) and 7,368 obese adults (BMI > 30 kg/m²) from 7 to 74 years were enrolled in this study. BMR was measured using an indirect calorimeter equipped with a canopy and fat free mass (FFM) were obtained using tetrapolar bioelectrical impedance analysis (BIA). Using analysis of covariance, we tested the effect of gender on the relationship between BMR, age, anthropometry, and body composition. In children and adolescents, the predictor × gender interaction was significant in all cases except for FFM × gender. In adults, all predictor × gender interactions were significant. A prediction equation based on body weight (BW), age, and gender had virtually the same accuracy of the one based on FFM, age, and gender to predict BMR in both children and adults (R²_adj = 0.59 and 0.60, respectively). In conclusion, gender was a significant determinant of BMR in children and adolescents but not in adults. Our results support the hypothesis that the age‐related decline in BMR is due to a reduction in FFM. Finally, anthropometric predictors of BMR are as accurate as body composition estimated by BIA.     

Birth weight and subsequent adiposity gain in Swedish children and adolescents: a 6-year follow-up study

We examined whether birth weight (BW) predicts changes in body composition over a 6-year period in Swedish children and adolescents. For this purpose, a total of 247 children (55.5% girls) and 162 adolescents (60.5% girls) were included in the study and were followed up 6 years later. BW was obtained from parental records. We measured weight, height, waist circumference, and the bicep, tricep, subscapular, suprailiac, and medial calf skinfolds, and we calculated BMI, fat-free mass (FFM), and the sum of five skinfolds. Physical activity was assessed by accelerometry. Changes in pubertal status and baseline anthropometric estimates were used as confounders in all analysis. In the children cohort, we observed that BW was inversely associated with changes in BMI (β = -0.736, P = 0.002) and the sum of five skinfolds (β = -6.381, P = 0.009) regardless of confounders and physical activity, only in girls. We did not find any significant association between BW and adiposity gain estimates in the adolescent cohort. These findings give further support to the concept that low BW may have a programming effect of subsequent adiposity gain from childhood to adolescence. We also confirm the sex-related differences in the programming effect of body composition.     

Missense mutations and polymorphisms of the <Emphasis Type="Italic">MC4R</Emphasis> gene in Polish obese children and adolescents in relation to the relative body mass index

Extensive studies of the MC4R gene polymorphism showed that, among numerous variants, there are mutations responsible for monogenic obesity, as well as polymorphisms negatively correlated with the risk of obesity. In this report, we present the first studies of the whole coding sequence of the MC4R gene in 243 Polish obese children and adolescents (the mean relative body mass index [RBMI] was 163.6). In addition, 101 non-obese adults were also analyzed. Direct sequencing facilitated the identification of six missense (K73R, V103I, T112M, S127L, M215L, and I251L) and one silent (c.756 C > T) single-nucleotide polymorphisms (SNPs). Two non-synonymous polymorphisms (K73R and M215L) appeared to be novel and one was found in obese patients (M215L, one patient) and one in non-obese adults (K73R, one person). The overall frequency of non-synonymous variant carriers reached 4.1% and 6.9% in obese patients and non-obese adults, respectively. Only one obesity-associated variant (127L) was found in two obese patients (0.82%) and in two non-obese adults (1.98%). The obesity-protecting variants (103I and 251L) appeared to be the most common in both groups: 3.3% and 4.0%, respectively. It was also observed that the RBMI in obese children and adolescents carrying the minor variants did not differ significantly from the non-carriers; however, the expected trends for the associated and protecting variants were observed. We conclude that the contribution of the MC4R gene variants to the pathogenesis of obesity in Polish children and adolescents is low.     

Pubertal alterations in growth and body composition. V. Energy expenditure, adiposity, and fat distribution

We determined whether activity energy expenditure (AEE, from doubly labeled water and indirect calorimetry) or physical activity [7-day physical activity recall (PAR)] was more related to adiposity and the validity of PAR estimated total energy expenditure (TEE(PAR)) in prepubertal and pubertal boys (n = 14 and 15) and girls (n = 13 and 18). AEE, but not physical activity hours, was inversely related to fat mass (FM) after accounting for the fat-free mass, maturation, and age (partial r = -0.35, P < or = 0.01). From forward stepwise regression, pubertal maturation, AEE, and gender predicted FM (r(2) = 0.36). Abdominal visceral fat and subcutaneous fat were not related to AEE or activity hours after partial correlation with FM, maturation, and age. When assuming one metabolic equivalent (MET) equals 1 kcal. kg body wt(-1). h(-1), TEE(PAR) underestimated TEE from doubly labeled water (TEE bias) by 555 kcal/day +/- 2 SD limits of agreement of 913 kcal/day. The measured basal metabolic rate (BMR) was >1 kcal. kg body wt(-1). h(-1) and remained so until 16 yr of age. TEE bias was reduced when setting 1 MET equal to the measured (bias = 60 +/- 51 kcal/day) or predicted (bias = 53 +/- 50 kcal/day) BMR but was not consistent for an individual child (+/- 2 SD limits of agreement of 784 and 764 kcal/day, respectively) or across all maturation groups. After BMR was corrected, TEE bias remained greatest in the prepubertal girls. In conclusion, in children and adolescents, FM is more strongly related to AEE than activity time, and AEE, pubertal maturation, and gender explain 36% of the variance in FM. PAR should not be used to determine TEE of individual children and adolescents in a research setting but may have utility in large population-based pediatric studies, if an appropriate MET value is used to convert physical activity data to TEE data.     

Small birth weight and later body composition and fat distribution in adolescents: the Avena study

Objective: To assess the association between birth weight and body composition and fat distribution in adolescents, and to test the possible sex‐specific effect in these relationships. Methods and Procedures: A total of 1,223 adolescents 13–18.5 years old (553 male adolescents and 670 female adolescents) born at >35 weeks, were selected from a cross‐sectional multicenter study conducted in five Spanish cities in 2000–2002. BMI was calculated from weight and height. Triceps and subscapular skinfold thickness (ST) were measured on the left side, and fat mass (FM) and fat‐free mass (FFM) were estimated according to the equations of Slaughter et al. Subscapular skinfold adjusted by tricipital (ST) and waist circumference were used as markers of central adiposity. Results: Birth weight Z‐score was positively associated with FFM in female adolescents (P < 0.001), but not in male adolescents, after controlling for age, pubertal stage, gestational age, socioeconomic status, physical activity, and current height (P < 0.001 for interaction between adjusted birth weight Z‐score and sex). Adjusted birth weight Z‐score was inversely associated with central adiposity in male and female adolescents as measured by ST (P = 0.026). Discussion: These results provide further evidence that gender has an important influence on the programming effect of birth weight on later FFM in adolescents because the effect was only observed in female adolescents. Our results suggest that small size for gestational age at birth could program more central subcutaneous fat deposition in adolescents of both sexes, but further research is needed on this issue.     

Role of resting metabolic rate and energy expenditure in hunger and appetite control: a new formulation

A long-running issue in appetite research concerns the influence of energy expenditure on energy intake. More than 50 years ago, Otto G. Edholm proposed that “the differences between the intakes of food [of individuals] must originate in differences in the expenditure of energy”. However, a relationship between energy expenditure and energy intake within any one day could not be found, although there was a correlation over 2 weeks. This issue was never resolved before interest in integrative biology was replaced by molecular biochemistry. Using a psychobiological approach, we have studied appetite control in an energy balance framework using a multi-level experimental system on a single cohort of overweight and obese human subjects. This has disclosed relationships between variables in the domains of body composition [fat-free mass (FFM), fat mass (FM)], metabolism, gastrointestinal hormones, hunger and energy intake. In this Commentary, we review our own and other data, and discuss a new formulation whereby appetite control and energy intake are regulated by energy expenditure. Specifically, we propose that FFM (the largest contributor to resting metabolic rate), but not body mass index or FM, is closely associated with self-determined meal size and daily energy intake. This formulation has implications for understanding weight regulation and the management of obesity.     

Leptin and metabolic syndrome in obese and non-obese children.

Metabolic syndrome is characterized by a clustering of metabolic abnormalities: insulin resistance - hyperinsulinemia, dyslipidemia (high triglycerides and low HDL - cholesterol serum concentrations), impaired glucose tolerance and/or type 2 diabetes, and hypertension. The aim of this study was to analyse the role of different variables of metabolic syndrome, including leptin, in 74 non-obese children and 68 children with non-syndromal obesity. As metabolic syndrome variables, we have included body mass index, waist circumference, trunk-to-total skinfolds (%), systolic blood pressure, diastolic blood pressure, glucose, uric acid, fasting insulin, triglycerides and high-density lipoprotein-cholesterol (HDL-C). Factor analysis showed 4 factors in each group. In non-obese children, waist circumference, BMI, fasting insulin, triglycerides, trunk-to-total skinfolds (%), leptin and uric acid loaded positively on factor 1, and HDL-C loaded negatively on this factor; systolic and diastolic blood pressure had high positive loadings in factor 2; HDL-C and leptin showed positive loadings and triglycerides and uric acid, negative loadings in factor 3; and, finally, glucose and insulin showed positive loadings in factor 4. These four factors explained 72.16 % of the total variance in the non-obese group. In obese children, BMI, waist circumference, leptin, diastolic blood pressure and systolic blood pressure loaded positively on factor 1; diastolic blood pressure, trunk-to-total skinfolds (%), uric acid and systolic blood pressure showed high positive loadings in factor 2; fasting insulin, glucose and triglycerides showed positive loadings in factor 3; and, finally, triglycerides showed positive loadings and HDL-C negative loadings in factor 4. These four factors explained 74.18 % of the total variance in the obese group. Our results point to a different homeostatic control of metabolic syndrome characteristics in obese and non-obese children. Leptin seems to play a key underlying role in metabolic syndrome, especially in the obese group.     

Infrequent Breakfast Consumption Is Associated with Higher Body Adiposity and Abdominal Obesity in Malaysian School-Aged Adolescents

Unhealthy dietary pattern increases the risk of obesity and metabolic disorders in growing children and adolescents. However, the way the habitual pattern of breakfast consumption influences body composition and risk of obesity in adolescents is not well defined. Thus, the aim of the present study was to assess any associations between breakfast consumption practices and body composition profiles in 236 apparently healthy adolescents aged 12 to 19 years. A self-administered questionnaire on dietary behaviour and lifestyle practices and a dietary food frequency questionnaire were used. Body composition and adiposity indices were determined using standard anthropometric measurement protocols and dual energy χ-ray absorptiometry (DXA). Mean age of the participants was 15.3±1.9 years. The majority of participants (71.2%) fell in the normal body mass index (BMI) ranges. Breakfast consumption patterns showed that only half of the participants (50%) were consuming breakfast daily. Gender-specific multivariate analyses (ANCOVA) showed that in both boys and girls, those eating breakfast at least 5 times a week had significantly lower body weight, body mass index (BMI), BMI z-scores, waist circumference, body fat mass and percent body fat (%BF) compared to infrequent breakfast eaters, after adjustment for age, household income, pubertal status, eating-out and snacking practices, daily energy intakes, and daily physical activity levels. The present findings indicate that infrequent breakfast consumption is associated with higher body adiposity and abdominal obesity. Therefore, daily breakfast consumption with healthy food choices should be encouraged in growing children and adolescents to prevent adiposity during these critical years of growth.     

A Weight Reduction Program Preserves Fat‐Free Mass but Not Metabolic Rate in Obese Adolescents

Objective: To determine the effects of a multidisciplinary weight reduction program on body composition and energy expenditure (EE) in severely obese adolescents. Research Methods and Procedures: Twenty‐six severely obese adolescents, 12 to 16 years old [mean BMI: 33.9 kg/m²; 41.5% fat mass (FM)] followed a 9‐month weight reduction program including moderate energy restriction and progressive endurance and resistance training. Body composition was assessed by DXA, basal metabolic rate by indirect calorimetry, and EE by whole‐body indirect calorimetry with the same activity program over 36‐hour periods before starting and 9 months after the weight reduction period. Results: Adolescents gained (least‐square mean ± SE) 2.9 ± 0.2 cm in height, lost 16.9 ± 1.3 kg body weight (BW), 15.2 ± 0.9 kg FM, and 1.8 ± 0.5 kg fat‐free mass (FFM) (p < 0.001). Basal metabolic rate, sleeping, sedentary, and daily EE were 8% to 14% lower 9 months after starting (p < 0.001) and still 6% to 12% lower after adjustment for FFM (p < 0.05). Energy cost of walking decreased by 22% (p < 0.001). The reduction in heart rate during sleep and sedentary activities (?10 to ?13 beats/min), and walking (?20 to ?25 beats/min) (p < 0.001) resulted from both the decrease in BW and physical training. Discussion: A weight reduction program combining moderate energy restriction and physical training in severely obese adolescents resulted in great BW and FM losses and improvement of cardiovascular fitness but did not prevent the decline in EE even after adjustment for FFM.     

Energy imbalance underlying the development of childhood obesity

Objective: To develop a model based on empirical data and human energetics to predict the total energy cost of weight gain and obligatory increase in energy intake and/or decrease in physical activity level associated with weight gain in children and adolescents. Research Methods and Procedures: One‐year changes in weight and body composition and basal metabolic rate (BMR) were measured in 488 Hispanic children and adolescents. Fat‐free mass (FFM) and fat mass (FM) were measured by DXA and BMR by calorimetry. Model specifications include the following: body mass (BM) = FFM + FM, each with a specific energy content, cff (1.07 kcal/g FFM) and cf (9.25 kcal/g FM), basal energy expenditure (EE), kff and kf, and energetic conversion efficiency, eff (0.42) for FFM and ef (0.85) for FM. Total energy cost of weight gain is equal to the sum of energy storage, EE associated with increased BM, conversion energy (CE), and diet‐induced EE (DIEE). Results: Sex‐ and Tanner stage–specific values are indicated for the basal EE of FFM (kff) and the fat fraction in added tissue (fr). Total energy cost of weight gain is partitioned into energy storage (24% to 36%), increase in EE (40% to 57%), CE (8% to 13%), and DIEE (10%). Observed median (10th to 90th percentile) weight gain of 6.1 kg/yr (2.4 to 11.4 kg/yr) corresponds at physical activity level (PAL) = 1.5, 1.75, and 2.0 to a total energy cost of weight gain of 244 (93 to 448 kcal/d), 267 (101 to 485 kcal/d), and 290 kcal/d (110 to 527 kcal/d), respectively, and to a total energy intake of 2695 (1890 to 3730), 3127 (2191 to 4335), and 3551 (2487 to 4930) kcal/d, respectively. If weight gain is caused by a change in PAL alone and PAL₀ = 1.5 at baseline t = 0, the model indicates a drop in PAL of 0.22 (0.08 to 0.34) units, which is equivalent to 60 (18 to 105) min/d of walking at 2.5 mph. Discussion: Halting the development or progression of childhood obesity, as observed in these Hispanic children and adolescents, by counteracting its total energy costs will require a sizable decrease in energy intake and/or reciprocal increase in physical activity.     

Comparison of High-Calorie,Low-Nutrient-Dense Food Consumption among Obese and Non-Obese Adolescents

BANDINI, LINDA G. DUNG VU, AVIVA MUST, HELENE CYR, ALISON GOLDBERG, AND WILLIAM H. DIETZ. Comparison of high-calorie, low-nutrient-dense food consumption among obese and non-obese adolescents. ObesRes. Objective: The purpose of this study was to determine whether obese adolescents eat more high-calorie low-nutrient-dense foods than non-obese adolescents. Research Methods and Procedures: Using a cross-sectional design, 22 non-obese and 21 obese adolescents kept 14-day food records. Records provided estimates of total daily energy intake and caloric intake from five categories of high-calorie, low-nutrient-dense (HC) foods: candy, chips, soda, baked goods, and ice cream. Body composition was determined by ¹⁸O dilution and daily energy expenditure by doubly labeled water. Percentage of energy intake reported (%report) was calculated as the ratio of reported energy intake to measured energy expenditure (x 100%). Results: Both groups underreported energy intake, but the percentage reported was significantly greater in the non-obese group (78. ±20. 5% non-obese vs. 55. 5±21. 8% obese, p<0. 001). Consumption of calories from chips and soda was similar among non-obese and obese adolescents. However, total energy intake from all HC foods was higher in the non-obese group than among the obese (617±356 kcal/day vs. 362plusnum;223 kcallday; p<0. 01) and represented 27. 2±10. 5% and 19. 9±9. 6% of reported energy intake in the non-obese and obese groups, respectively. After adjustment for underreporting, the percentage of calories provided by each of the HC foods was similar in the obese and non-obese groups except for ice cream, which remained significantly greater in the non-obese group (p<0. 05). Discussion: Our findings suggest that both non-obese and obese adolescents consume a substantial portion of reported calories from HC foods and that obese adolescents do not consume more calories from these foods than non-obese adolescents. These data offer no evidence to support the widespread notion that obese adolescents eat more “junk food” than non-obese adolescents. Health professionals who treat obese adolescents must be aware that the excess calories in their diets may come from a variety of food sources and not solely from high-calorie snack foods.