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Background The aim of obesity treatment is to promote loss of fat relative to lean mass. However, body composition changes with calorie restriction differ among individuals. Objectives The goal of this study was to test the hypothesis that insulin secretion predicts body composition changes among young and middle-age adults with high BMI (in kg/m2) following major weight loss. Methods Exploratory analyses were conducted with pre-randomization data from 2 large feeding trials: the Framingham, Boston, Bloomington, Birmingham, and Baylor study (FB4; n = 82, 43.9% women, BMI ≥27) and the Framingham State Food Study [(FS)2; n = 161, 69.6% women, BMI ≥25]. Participants in the 2 trials consumed calorie-restricted moderate-carbohydrate or very-low-carbohydrate diets to produce 12-18% weight loss in ∼14 wk or 10-14% in ∼10 wk, respectively. We determined insulin concentration 30 min after a 75-g oral glucose load (insulin-30) as a measure of insulin secretion and HOMA-IR as a measure of insulin resistance at baseline. Body composition was determined by DXA at baseline and post-weight loss. Associations were analyzed using general linear models with adjustment for covariates. Results In FB4, higher insulin-30 was associated with a smaller decrease in fat mass (0.441 kg per 100 μIU/mL increment in baseline insulin-30; P = 0.005; -1.20-kg mean difference between the first compared with the fifth group of insulin-30) and a larger decrease in lean mass (-0.465 kg per 100 μIU/mL; P = 0.004; 1.27-kg difference). Participants with higher insulin-30 lost a smaller proportion of weight loss as fat (-3.37% per 100 μIU/mL; P = 0.003; 9.20% difference). Greater HOMA-IR was also significantly associated with adverse body composition changes. Results from (FS)2 were qualitatively similar but of a smaller magnitude. Conclusions Baseline insulin dynamics predict substantial individual differences in body composition following weight loss. These findings may inform understanding of the pathophysiological basis for weight regain and the design of more effective obesity treatment. Registered at clinicaltrials.gov as NCT03394664 and NCT02068885.

Background Carbohydrate restriction shows promise for diabetes, but concerns regarding high saturated fat content of low-carbohydrate diets limit widespread adoption. Objectives This preplanned ancillary study aimed to determine how diets varying widely in carbohydrate and saturated fat affect cardiovascular disease (CVD) risk factors during weight-loss maintenance. Methods After 10–14% weight loss on a run-in diet, 164 participants (70% female; BMI = 32.4 ± 4.8 kg/m2) were randomly assigned to 3 weight-loss maintenance diets for 20 wk. The prepared diets contained 20% protein and differed 3-fold in carbohydrate (Carb) and saturated fat as a proportion of energy (Low-Carb: 20% carbohydrate, 21% saturated fat; Moderate-Carb: 40%, 14%; High-Carb: 60%, 7%). Fasting plasma samples were collected prerandomization and at 20 wk. Lipoprotein insulin resistance (LPIR) score was calculated from triglyceride-rich, high-density, and low-density lipoprotein particle (TRL-P, HDL-P, LDL-P) sizes and subfraction concentrations (large/very large TRL-P, large HDL-P, small LDL-P). Other outcomes included lipoprotein(a), triglycerides, HDL cholesterol, LDL cholesterol, adiponectin, and inflammatory markers. Repeated measures ANOVA was used for intention-to-treat analysis. Results Retention was 90%. Mean change in LPIR (scale 0–100) differed by diet in a dose-dependent fashion: Low-Carb (–5.3; 95% CI: –9.2, –1.5), Moderate-Carb (–0.02; 95% CI: –4.1, 4.1), High-Carb (3.6; 95% CI: –0.6, 7.7), P = 0.009. Low-Carb also favorably affected lipoprotein(a) [–14.7% (95% CI: –19.5, –9.5), –2.1 (95% CI: –8.2, 4.3), and 0.2 (95% CI: –6.0, 6.8), respectively; P = 0.0005], triglycerides, HDL cholesterol, large/very large TRL-P, large HDL-P, and adiponectin. LDL cholesterol, LDL-P, and inflammatory markers did not differ by diet. Conclusions A low-carbohydrate diet, high in saturated fat, improved insulin-resistant dyslipoproteinemia and lipoprotein(a), without adverse effect on LDL cholesterol. Carbohydrate restriction might lower CVD risk independently of body weight, a possibility that warrants study in major multicentered trials powered on hard outcomes. The registry is available through ClinicialTrials.gov: https://clinicaltrials.gov/ct2/show/NCT02068885.

The obesity pandemic continues unabated despite a persistent public health campaign to decrease energy intake (“eat less”) and increase energy expenditure (“move more”). One explanation for this failure is that the current approach, based on the notion of energy balance, has not been adequately embraced by the public. Another possibility is that this approach rests on an erroneous paradigm. A new formulation of the energy balance model (EBM), like prior versions, considers overeating (energy intake > expenditure) the primary cause of obesity, incorporating an emphasis on “complex endocrine, metabolic, and nervous system signals” that control food intake below conscious level. This model attributes rising obesity prevalence to inexpensive, convenient, energy-dense, “ultra-processed” foods high in fat and sugar. An alternative view, the carbohydrate-insulin model (CIM), proposes that hormonal responses to highly processed carbohydrates shift energy partitioning toward deposition in adipose tissue, leaving fewer calories available for the body’s metabolic needs. Thus, increasing adiposity causes overeating to compensate for the sequestered calories. Here, we highlight robust contrasts in how the EBM and CIM view obesity pathophysiology and consider deficiencies in the EBM that impede paradigm testing and refinement. Rectifying these deficiencies should assume priority, as a constructive paradigm clash is needed to resolve long-standing scientific controversies and inform the design of new models to guide prevention and treatment. Nevertheless, public health action need not await resolution of this debate, as both models target processed carbohydrates as major drivers of obesity.

BACKGROUND The effect of macronutrient composition on total energy expenditure (TEE) remains controversial, with divergent findings among studies. One source of heterogeneity may be study duration, as physiological adaptation to lower carbohydrate intake may require 2 to 3 wk. OBJECTIVE We tested the hypothesis that the effects of carbohydrate [expressed as % of energy intake (EI)] on TEE vary with time. METHODS The sample included trials from a previous meta-analysis and new trials identified in a PubMed search through 9 March 2020 comparing lower- and higher-carbohydrate diets, controlled for EI or body weight. Three reviewers independently extracted data and reconciled discrepancies. Effects on TEE were pooled using inverse-variance-weighted meta-analysis, with between-study heterogeneity assessed using the I2 statistic. Meta-regression was used to quantify the influence of study duration, dichotomized at 2.5 wk. RESULTS The 29 trials ranged in duration from 1 to 140 d (median: 4 d) and included 617 participants. Difference in carbohydrate between intervention arms ranged from 8% to 77% EI (median: 30%). Compared with reported findings in the prior analysis (I2 = 32.2%), we found greater heterogeneity (I2 = 90.9% in the reanalysis, 81.6% in the updated analysis). Study duration modified the diet effect on TEE (P

The obesity pandemic continues unabated despite a persistent public health campaign to decrease energy intake ("eat less") and increase energy expenditure ("move more"). One explanation for this failure is that the current approach, based on the notion of energy balance, has not been adequately embraced by the public. Another possibility is that this approach rests on an erroneous paradigm. A new formulation of the energy balance model (EBM), like prior versions, considers overeating (energy intakeexpenditure) the primary cause of obesity, incorporating an emphasis on "complex endocrine, metabolic, and nervous system signals" that control food intake below conscious level. This model attributes rising obesity prevalence to inexpensive, convenient, energy-dense, "ultra-processed" foods high in fat and sugar. An alternative view, the carbohydrate-insulin model (CIM), proposes that hormonal responses to highly processed carbohydrates shift energy partitioning toward deposition in adipose tissue, leaving fewer calories available for the body's metabolic needs. Thus, increasing adiposity causes overeating to compensate for the sequestered calories. Here, we highlight robust contrasts in how the EBM and CIM view obesity pathophysiology and consider deficiencies in the EBM that impede paradigm testing and refinement. Rectifying these deficiencies should assume priority, as a constructive paradigm clash is needed to resolve long-standing scientific controversies and inform the design of new models to guide prevention and treatment. Nevertheless, public health action need not await resolution of this debate, as both models target processed carbohydrates as major drivers of obesity.

Background Longer-term feeding studies suggest that a low-carbohydrate diet increases energy expenditure, consistent with the carbohydrate-insulin model of obesity. However, the validity of methodology utilized in these studies, involving doubly labeled water (DLW), has been questioned. Objective The aim of this study was to determine whether dietary energy requirement for weight-loss maintenance is higher on a low- compared with high-carbohydrate diet. Methods The study reports secondary outcomes from a feeding study in which the primary outcome was total energy expenditure (TEE). After attaining a mean Run-in weight loss of 10.5%, 164 adults (BMI ≥25 kg/m2; 70.1% women) were randomly assigned to Low-Carbohydrate (percentage of total energy from carbohydrate, fat, protein: 20/60/20), Moderate-Carbohydrate (40/40/20), or High-Carbohydrate (60/20/20) Test diets for 20 wk. Calorie content was adjusted to maintain individual body weight within ± 2 kg of the postweight-loss value. In analyses by intention-to-treat (ITT, completers, n = 148) and per protocol (PP, completers also achieving weight-loss maintenance, n = 110), we compared the estimated energy requirement (EER) from 10 to 20 wk of the Test diets using ANCOVA. Results Mean EER was higher in the Low- versus High-Carbohydrate group in models of varying covariate structure involving ITT [ranging from 181 (95% CI: 8–353) to 246 (64–427) kcal/d; P ≤0.04] and PP [ranging from 245 (43–446) to 323 (122–525) kcal/d; P ≤0.02]. This difference remained significant in sensitivity analyses accounting for change in adiposity and possible nonadherence. Conclusions Energy requirement was higher on a low- versus high-carbohydrate diet during weight-loss maintenance in adults, commensurate with TEE. These data are consistent with the carbohydrate-insulin model and lend qualified support for the validity of the DLW method with diets varying in macronutrient composition. This trial was registered at clinicaltrials.gov as NCT02068885.

A large feeding study reported that total energy expenditure (TEE) was greater on a low- versus high-carbohydrate diet, supporting the carbohydrate-insulin model of obesity. Recently, the validity of this finding was challenged in a post-hoc analysis excluding participants with putative non-adherence to the study diets. Here, we show why that analysis, based on a post-randomization variable linked to the outcome, introduced severe confounding bias. With control for confounding, the diet effect on TEE remained strong in a reanalysis. Together with sensitivity analyses demonstrating robustness to plausible levels of non-adherence, these data provide experimental support for a potentially novel metabolic effect of macronutrients that might inform the design of more effective obesity treatment.

According to a commonly held view, the obesity pandemic is caused by overconsumption of modern, highly palatable, energy-dense processed foods, exacerbated by a sedentary lifestyle. However, obesity rates remain at historic highs, despite a persistent focus on eating less and moving more, as guided by the energy balance model (EBM). This public health failure may arise from a fundamental limitation of the EBM itself. Conceptualizing obesity as a disorder of energy balance restates a principle of physics without considering the biological mechanisms that promote weight gain. An alternative paradigm, the carbohydrate-insulin model (CIM), proposes a reversal of causal direction. According to the CIM, increasing fat deposition in the body—resulting from the hormonal responses to a high-glycemic-load diet—drives positive energy balance. The CIM provides a conceptual framework with testable hypotheses for how various modifiable factors influence energy balance and fat storage. Rigorous research is needed to compare the validity of these 2 models, which have substantially different implications for obesity management, and to generate new models that best encompass the evidence.

Accurate and precise body composition estimates, notably of total body adiposity, are a vital component of in vivo physiology and metabolic studies. The reference against which other body composition approaches are usually validated or calibrated is the family of methods referred to as multicomponent "body density" models. These models quantify three to six components by combining measurements of body mass, body volume, total body water, and osseous mineral mass. Body mass is measured with calibrated scales, volume with underwater weighing or air-displacement plethysmography, total body water with isotope dilution, and osseous mineral mass by dual-energy X-ray absorptiometry. Body density is then calculated for use in model as body mass/volume. Studies over the past decade introduced a new approach to quantifying body volume that relies on dual-energy X-ray absorptiometry measurements, an advance that simplifies multicomponent density model development by eliminating the need for underwater weighing or air-displacement plethysmography systems when these technologies are unavailable and makes these methods more accessible to research and clinical programs. This review critically examines these new dual-energy X-ray approaches for quantifying body volume and density, explores their shortcomings, suggests alternative derivation approaches, and introduces ideas for potential future research studies.

Summary The doubly labeled water (DLW) method measures total energy expenditure (TEE) in free-living subjects. Several equations are used to convert isotopic data into TEE. Using the International Atomic Energy Agency (IAEA) DLW database (5,756 measurements of adults and children), we show considerable variability is introduced by different equations. The estimated rCO2 is sensitive to the dilution space ratio (DSR) of the two isotopes. Based on performance in validation studies, we propose a new equation based on a new estimate of the mean DSR. The DSR is lower at low body masses (, Graphical Abstract, Highlights 5,756 doubly labeled water (DLW) measures highlight variation from calculation equation We derive here new equations for calculating CO2 production when using DLW These equations outperform previous equations in validation studies We recommend these equations should be adopted in future studies using DLW in humans, Speakman et al. use a large database of doubly labeled water measurements to show the choice of equation for the calculation of energy expenditure introduces significant variation into the final estimate. They then derive new equations that outperform previous equations in validation studies against chamber calorimetry.

ObjectiveTo determine the effects of diets varying in carbohydrate to fat ratio on total energy expenditure.DesignRandomized trial.SettingMulticenter collaboration at US two sites, August 2014 to May 2017.Participants164 adults aged 18-65 years with a body mass index of 25 or more.InterventionsAfter 12% (within 2%) weight loss on a run-in diet, participants were randomly assigned to one of three test diets according to carbohydrate content (high, 60%, n=54; moderate, 40%, n=53; or low, 20%, n=57) for 20 weeks. Test diets were controlled for protein and were energy adjusted to maintain weight loss within 2 kg. To test for effect modification predicted by the carbohydrate-insulin model, the sample was divided into thirds of pre-weight loss insulin secretion (insulin concentration 30 minutes after oral glucose).Main outcome measuresThe primary outcome was total energy expenditure, measured with doubly labeled water, by intention-to-treat analysis. Per protocol analysis included participants who maintained target weight loss, potentially providing a more precise effect estimate. Secondary outcomes were resting energy expenditure, measures of physical activity, and levels of the metabolic hormones leptin and ghrelin.ResultsTotal energy expenditure differed by diet in the intention-to-treat analysis (n=162, P=0.002), with a linear trend of 52 kcal/d (95% confidence interval 23 to 82) for every 10% decrease in the contribution of carbohydrate to total energy intake (1 kcal=4.18 kJ=0.00418 MJ). Change in total energy expenditure was 91 kcal/d (95% confidence interval −29 to 210) greater in participants assigned to the moderate carbohydrate diet and 209 kcal/d (91 to 326) greater in those assigned to the low carbohydrate diet compared with the high carbohydrate diet. In the per protocol analysis (n=120, PConclusionsConsistent with the carbohydrate-insulin model, lowering dietary carbohydrate increased energy expenditure during weight loss maintenance. This metabolic effect may improve the success of obesity treatment, especially among those with high insulin secretion.Trial registrationClinicalTrials.govNCT02068885.

BackgroundA 2018 American Heart Association science advisory indicated that, pending further research, artificially sweetened beverages (ASBs) may be an appropriate initial replacement for sugar‐sweetened beverages (SSBs) during transition to unsweetened beverages (USBs).Methods and ResultsWe randomly assigned 203 adults (121 males, 82 females; 91.6% retention), who habitually consumed SSBs, to 3 groups and delivered free SSBs, ASBs, or USBs to their homes for 12 months. Outcomes included serum triglyceride to high‐density lipoprotein cholesterol ratio (primary), body weight, and sweet taste preference (experimental assessment, 0%–18% sucrose solutions). Change in serum triglyceride to high‐density lipoprotein cholesterol ratio was not different between groups. Although overall change in weight also was not different between groups, we found effect modification (P=0.006) by central adiposity. Among participants in the highest tertile of baseline trunk fat but not other tertiles, weight gain was greater (P=0.002) for the SSB (4.4±1.0 kg, estimate±SE) compared with ASB (0.5±0.9 kg) or USB (−0.2±0.9 kg) group. Both sweetness threshold (–1.0±0.2% m/v;P=0.005) and favorite concentration (–2.3±0.4% m/v;PP=0.02). Pairwise comparison between the ASB and USB groups indicated a difference in sweetness threshold (P=0.015).ConclusionsReplacing SSBs with noncaloric beverages for 12 months did not affect serum triglyceride to high‐density lipoprotein cholesterol ratio. Among individuals with central adiposity, replacing SSBs with either ASBs or USBs lowered body weight. However, USBs may have the most favorable effect on sweet taste preference.RegistrationURL:https://www.clinicaltrials.gov; unique identifier: NCT01295671.

Context According to the carbohydrate-insulin model of obesity, an elevated insulin-to-glucagon ratio in response to a high-carbohydrate diet directs metabolic fuels toward storage, resulting in lower circulating energy. Objective To determine differences in total circulating energy post-meal related to dietary carbohydrate. Design Ancillary study within the Framingham State Food Study. Setting University community. Participants 29 adults (aged 20 to 65 years) with overweight or obesity (body mass index ≥25 kg/m2) Intervention After achieving 10% to 14% weight loss on a run-in diet, participants were randomized to weight-loss-maintenance test diets varying in carbohydrate content (high-carbohydrate, 60% of total energy, n = 11; moderate-carbohydrate, 40%, n = 8; low-carbohydrate, 20%, n = 10) and controlled for protein (20%). During 24-hour metabolic ward admissions between 10 and 15 weeks on the test diets, metabolic fuels and hormones were measured. Main Outcome Measure Energy availability (EA) based on energy content of blood glucose, beta-hydroxybutyrate, and free fatty acids, in the late postprandial period (180 to 300 minutes). Insulin at 30 minutes into the test meal (Meal Insulin-30) was measured as an effect modifier. Results Insulin-to-glucagon ratio was 7-fold higher in participants on the high- vs low-carbohydrate diet (2.5 and 0.36, respectively). Late postprandial EA was 0.58 kcal/L lower on the high- vs low-carbohydrate diet (P < 0.0001), primarily related to suppression of free fatty acids. Early postprandial EA (30 to 180 minutes) declined fastest in the high-carbohydrate group, and Meal Insulin-30 modified this diet effect. Conclusions During weight-loss maintenance on a high-carbohydrate diet, late postprandial EA is reduced, consistent with the carbohydrate-insulin model.

Summary In view of the prevalence, health consequences, and costs of childhood obesity, there has been substantial interest in identifying effective interventions to prevent excess weight gain in young people. In this systematic review, we expand on previous reviews of obesity prevention interventions by including recent studies (until May 23, 2017) from all parts of the world. We searched MEDLINE, Embase, CINAHL Plus, Web of Science, CAB Abstracts, and PAIS Index and included randomised controlled trials, quasi-experimental studies, or natural experiments with: (1) a control group; (2) minimum follow-up of 12 months for community-based and home-based interventions or 6 months for school-based and preschool-based interventions; and (3) a primary outcome of BMI, BMI Z score, BMI percentile, body fat percentage, skinfold thickness, waist circumference, or prevalence of overweight or obesity. School-based interventions with combined diet and physical activity components and a home element (n=41) had greatest effectiveness; evidence in support of the effect of preschool-based (n=6), community-based (n=7), and home-based (n=2) interventions was limited by a paucity of studies and heterogeneity in study design. The effectiveness of school-based interventions that combined diet and physical activity components suggests that they hold promise for childhood obesity prevention worldwide. More research with rigorous evaluation and consistent reporting is needed in non-school settings and in combinations of settings.

Background While many people with overweight or obesity can lose weight temporarily, most have difficulty maintaining weight loss over the long term. Studies of dietary composition typically focus on weight loss, rather than weight-loss maintenance, and rely on nutrition education and dietary counseling, rather than controlled feeding protocols. Variation in initial weight loss and insufficient differentiation among treatments confound interpretation of results and compromise conclusions regarding the weight-independent effects of dietary composition. The aim of the present study was to evaluate three test diets differing in carbohydrate-to-fat ratio during weight-loss maintenance. Design and dietary interventions Following weight loss corresponding to 12 ± 2% of baseline body weight on a standard run-in diet, 164 participants aged 18 to 65 years were randomly assigned to one of three test diets for weight-loss maintenance through 20 weeks (test phase). We fed them high-carbohydrate (60% of energy from carbohydrate, 20% fat), moderate-carbohydrate (40% carbohydrate, 40% fat), and low-carbohydrate (20% carbohydrate, 60% fat) diets, controlled for protein content (20% of energy). During a 2-week ad libitum feeding phase following the test phase, we assessed the effect of the test diets on body weight. Outcomes The primary outcome was total energy expenditure, assessed by doubly-labeled water methodology. Secondary outcomes included resting energy expenditure and physical activity, chronic disease risk factors, and variables to inform an understanding of physiological mechanisms by which dietary carbohydrate-to-fat ratio might influence metabolism. Weight change during the ad libitum feeding phase was conceptualized as a proxy measure of hunger.

For many years, low-fat diets were the cornerstone of public health and clinical guidelines for preventing and treating obesity. The US Senate Select Committee on Nutrition released the first national guidelines in 1977. At that time, Dietary Goals for the United States included recommendations to “increase carbohydrate consumption to between 55% and 60% of the energy (caloric) intake” and “reduce fat consumption from over 40% down to 30% of energy intake.” These recommendations were based, in part, on the idea that consuming fat promotes obesity because fat is the most concentrated source of energy in the diet. Despite limited data, the recommendation to reduce dietary fat was underscored in 1984 by an expert panel at the NIH Consensus Development Conference on Lowering Blood Cholesterol to Prevent Heart Disease , and again in 1987 by the National Cholesterol Education Program (NCEP). Dietary fat was viewed as a “foe” to good health from 1984 through the 1990s. Currently, Dietary Guidelines for Americans 2015–2020 (Eighth Edition) focus on eating patterns, and associated food and nutrient profiles, rather than on nutrient intakes. While there is no explicit limit on total fat intake, the Guidelines continue to advocate

Background: Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects.Objective: We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol.Design: Twenty-one adults with a high body mass index (in kg/m2; mean ± SD: 34.4 ± 4.9) were given hypocaloric diets to promote weight loss corresponding to 10-15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography-tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons.Results: Of 333 metabolites, we identified 152 whose concentrations differed for ≥1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (>95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors.Conclusions: Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in observational studies. In addition, this methodology may help elucidate mechanistic pathways linking diet to chronic disease risk. This trial was registered at clinicaltrials.gov as NCT00315354.

Despite intensive research, the causes of the obesity epidemic remain incompletely understood and conventional calorie-restricted diets continue to lack long-term efficacy. According to the carbohydrate-insulin model (CIM) of obesity, recent increases in the consumption of processed, high-glycemic-load carbohydrates produce hormonal changes that promote calorie deposition in adipose tissue, exacerbate hunger, and lower energy expenditure. Basic and genetic research provides mechanistic evidence in support of the CIM. In animals, dietary composition has been clearly demonstrated to affect metabolism and body composition, independently of calorie intake, consistent with CIM predictions. Meta-analyses of behavioral trials report greater weight loss with reduced-glycemic load vs low-fat diets, though these studies characteristically suffer from poor long-term compliance. Feeding studies have lacked the rigor and duration to test the CIM, but the longest such studies tend to show metabolic advantages for low-glycemic load vs low-fat diets. Beyond the type and amount of carbohydrate consumed, the CIM provides a conceptual framework for understanding how many dietary and nondietary exposures might alter hormones, metabolism, and adipocyte biology in ways that could predispose to obesity. Pending definitive studies, the principles of a low-glycemic load diet offer a practical alternative to the conventional focus on dietary fat and calorie restriction.

BackgroundLonger-term feeding studies suggest that a low-carbohydrate diet increases energy expenditure, consistent with the carbohydrate-insulin model of obesity. However, the validity of methodology utilized in these studies, involving doubly-labeled water, has been questioned.ObjectiveThe aim of this study was to determine whether dietary energy requirement for weight-loss maintenance is higher on a low-versus high-carbohydrate diet.MethodsThe study reports secondary outcomes and exploratory analyses from a feeding study in which the primary outcome was total energy expenditure. After attaining a mean Run-in weight loss of 10.5%, 164 adults with pre-weight-loss BMI of ≥25 were randomly assigned to Test diets containing Low (20%), Moderate (40%) or High (60%) carbohydrate for 20 weeks. Calorie content of Test diets was adjusted to maintain individual body weight within 2 kg of the post-weight-loss value. In analyses by Intention-to-Treat (ITT, study completers, n=148) and Per Protocol (PP, those achieving the weight-loss maintenance target, n=110), we compared estimated energy requirement from 10 to 20 weeks on the Test diets using ANCOVA. Insulin secretion was assessed pre-weight-loss as insulin concentration 30 minutes following 75 grams oral glucose (Insulin-30).ResultsEstimated energy requirement was higher in the Low vs High group by models involving ITT (ranging from 181 [CI 8–353] to 223 [40–406] kcal/d; P≤0.04) and PP (ranging from 245 [43–446] to 295 [91–499] kcal/d; P≤0.02). This difference remained significant in sensitivity analyses accounting for change in adiposity and possible non-adherence. In observational analyses, pre-weight loss Insulin-30 predicted adverse change in body composition following weight loss.ConclusionsEnergy requirement was higher on a low-versus high-carbohydrate diet during weight-loss maintenance, commensurate with total energy expenditure. These data are consistent with the carbohydrate-insulin model and lend qualified support for the validity of the doubly-labeled water method with diets varying in macronutrient composition.

Summary In an integrated care model, involving primary care providers (PCPs) and obesity specialists, telehealth may be useful for overcoming barriers to treating childhood obesity. We conducted a pilot study comparing body mass index (BMI) changes between two arms (i) PCP in-person clinic visits plus obesity specialist tele-visits ( PCP visits + specialist tele-visits) and (ii) PCP in-person clinic visits only ( PCP visits only), with ongoing tele-consultation between PCPs and obesity specialists for both arms. Patients (N = 40, 10–17 years, BMI ≥ 95th percentile) were randomized to Group 1 or 2. Both groups had PCP visits every 3 months for 12 months. Using a cross-over protocol, Group 1 had PCP visits + specialist tele-visits during the first 6 months and PCP visits only during the second 6 months, and Group 2 followed the opposite sequence. Each of 12 tele-visits was conducted by a dietitian or psychologist with a patient and parent. Retention rates were 90% at 6 months and 80% at 12 months. BMI (z-score) decreased more for Group 1 (started with PCP visits + specialist tele-visits) vs. Group 2 (started with PCP visits only) at 3 months (−0.11 vs. −0.05, P = 0.049) following frequent tele-visits. At 6 months (primary outcome), BMI was lower than baseline within Group 1 (−0.11, P = 0.0006) but not Group 2 (−0.06, P = 0.08); however, decrease in BMI at 6 months did not differ between groups. After crossover, BMI remained lower than baseline for Group 1 and dropped below baseline for Group 2. An integrated care model utilizing telehealth holds promise for treating children with obesity.

SummaryBackground Telehealth offers opportunities to extend clinical and research interventions for paediatric obesity. Objectives To assess utility of a telephone intervention, implemented through a national primary care paediatric research network, for promoting differentiation in dietary intake, consistent with either a low-glycemic load (Low GL) or Low Fat prescription, among overweight/obese school-age children. Methods Five-week telephone dietary counselling intervention for parents of overweight/obese school-age children recruited through the Slone Center Office-based Research Network. Parent-child dyads were randomized to Low GL or Low Fat diet. Primary outcomes were dietary GL and dietary fat, adjusted for energy intake and assessed by 24-h dietary recall. Results Subjects were randomized to Low GL (n = 11, 8.1 ± 1.7 years, 45.5% male) or Low Fat (n = 11, 8.2 ± 2.0 years, 36.4% male), with no baseline differences. Overall, 86% of subjects attended at least four of five counselling sessions, and study completion rate was 91% (based on completion of the final dietary recalls). Reported satisfaction was high. In adjusted analyses limited to ‘recall completers,’ reduction in dietary GL (g/1000 kcal) achieved within the Low GL group was significant (p = 0.01) and greater than the change in dietary GL in the Low Fat group (mean ± SE; −12.9 ± 4.4 vs. 5.1 ± 4.9, p = 0.03). Similarly, reduction in dietary fat (% of total energy) within the Low Fat group was significant (−5.6 ± 2.5, p = 0.046) but with no difference between groups (p = 0.25). Conclusion A telephone-based dietary intervention for overweight/obese children, implemented through a national paediatric research network, fostered prescribed dietary changes. ClinicalTrials.gov registration: NCT00620152

ObjectiveFinancial conflicts of interest involving the food industry have been reported to bias nutrition studies. However, some have hypothesized that independently funded studies may be biased if the authors have strong a priori beliefs about the healthfulness of a food product (‘white hat bias’). The extent to which each source of bias may affect the scientific literature has not been examined. We aimed to explore this question with research involving sugar-sweetened beverages (SSB) as a test case, focusing on a period during which scientific consensus about the adverse health effects of SSB emerged from uncertainty.DesignPubMed search of worldwide literature was used to identify articles related to SSB and health risks published between 2001 and 2013. Financial relationships and article conclusions were classified by independent groups of co-investigators. Associations were explored by Fischer’s exact tests and regression analyses, controlling for covariates.ResultsA total of 133 articles published in English met inclusion criteria. The proportion of industry-related scientific studies decreased significantly with time, from approximately 30 % at the beginning of the study period to P=0·003). A ‘strong’ or ‘qualified’ scientific conclusion was reached in 82 % of independent v. 7 % of industry-related SSB studies (PConclusionIndustry-related research during a critical period appears biased to underestimate the adverse health effects of SSB, potentially delaying corrective public health action.

BACKGROUND A fundamental precept of the carbohydrate–insulin model of obesity is that insulin secretion drives weight gain. However, fasting hyperinsulinemia can also be driven by obesity-induced insulin resistance. We used genetic variation to isolate and estimate the potentially causal effect of insulin secretion on body weight. METHODS Genetic instruments of variation of insulin secretion [assessed as insulin concentration 30 min after oral glucose (insulin-30)] were used to estimate the causal relationship between increased insulin secretion and body mass index (BMI), using bidirectional Mendelian randomization analysis of genome-wide association studies. Data sources included summary results from the largest published metaanalyses of predominantly European ancestry for insulin secretion (n = 26037) and BMI (n = 322154), as well as individual-level data from the UK Biobank (n = 138541). Data from the Cardiology and Metabolic Patient Cohort study at Massachusetts General Hospital (n = 1675) were used to validate genetic associations with insulin secretion and to test the observational association of insulin secretion and BMI. RESULTS Higher genetically determined insulin-30 was strongly associated with higher BMI (β = 0.098, P = 2.2 × 10−21), consistent with a causal role in obesity. Similar positive associations were noted in sensitivity analyses using other genetic variants as instrumental variables. By contrast, higher genetically determined BMI was not associated with insulin-30. CONCLUSIONS Mendelian randomization analyses provide evidence for a causal relationship of glucose-stimulated insulin secretion on body weight, consistent with the carbohydrate–insulin model of obesity.

Objective To examine associations of baseline insulin dynamics with changes in body composition and resting energy expenditure (REE) following weight loss.

Objective Diet modification is recommended to treat childhood cardiovascular (CV) risk factors; however, the optimal dietary strategy is unknown. Methods In a randomized trial, the effect of a low-fat (LF) and a low-glycemic-load (LGL) reduced-calorie diet were examined in youth with overweight/obesity with CV risk factors. Using a novel intervention, we delivered LF or LGL meals and nutrition education to the home for 8 weeks (Intensive Phase), followed by 4 months Maintenance without food provision. Between-group differences in the change in insulin area under the curve (InsAUC) by oral glucose tolerance test and other risk factors were analyzed. Results Overall, participants (n = 27) showed substantial improvement during the Intensive Phase, including InsAUC (−59 ± 18.2 µU/ml × 120 min, P = 0.004), total cholesterol (−9.9 ± 3.6 mg/dl, P = 0.01), weight (−2.7 ± 0.5 kg, P

Excess adiposity is the main phenotypic feature that defines human obesity and that plays a pathophysiological role in most chronic diseases. Measuring the amount of fat mass present is thus a central aspect of studying obesity at the individual and population levels. Nevertheless, a consensus is lacking among investigators on a single accepted 'reference' approach for quantifying fat mass in vivo. While the research community generally relies on the multi-component body volume class of 'reference' models for quantifying fat mass, no definable guide discerns among different applied equations for partitioning the four (fat, water, protein and mineral mass) or more quantified components, standardizes 'adjustment' or measurement system approaches for model-required labelled water dilution volumes and bone mineral mass estimates, or firmly establishes the body temperature at which model physical properties are assumed. The resulting differing reference strategies for quantifying body composition in vivo leads to small, but under some circumstances, important differences in the amount of measured body fat. Recent technological advances highlight opportunities to expand model applications to new subject groups and measured components such as total body protein. The current report reviews the historical evolution of multi-component body volume-based methods in the context of prevailing uncertainties and future potential.

Few topics are of greater concern for public health, including the delivery of healthcare and the development of policy, than obesity and its myriad complications. Dramatic increases in the prevalence of obesity in high-income countries over the past 50 years (Fig. 1), and the increasing problem of obesity in low- and middle-income countries, are undisputed. The lifetime costs of a patient with obesity (compared with a patient with normal weight) underscore the societal impact of the problem (Fig. 2). However, causes of obesity and best strategies to reverse trends in prevalence of the disease are topics of much debate. The role of nutrition and genetics, impact of physical activity, neurohormonal drivers and mediators of obesity, and mechanisms that underpin the development of obesity-related complications all remain central to ongoing research. In this context, we believe that it is …

Importance Health care professionals commonly recommend increased water consumption, typically to 8 cups per day, as part of a weight-reducing diet. However, this recommendation is based on limited evidence and virtually no experimental data from the pediatric population. Objective To compare 2 standardized weight-loss diets among adolescents with overweight or obesity, either with or without additional advice and behavioral support to increase habitual water intake to 8 cups per day. Design, Setting, and Participants A randomized clinical, parallel-group trial was conducted between February 2, 2011, and June 26, 2014, at Boston Children’s Hospital, Boston, Massachusetts, among 38 adolescents with overweight or obesity who reported drinking 4 cups or less of water per day. Interventions All participants in both groups received similar weight-reducing interventions, differentiated by advice about water intake (the water group received advice to increase water intake to 8 cups per day; the control group did not receive such advice) but controlled for other dietary recommendations and treatment intensity. The interventions included dietary counseling, daily text messages, and a cookbook with health guides. To support adherence to 8 cups of water per day, the water group received well-defined messages about water through counseling and daily text messages, a water bottle, and a water pitcher with filters. Main Outcomes and Measures The primary outcome was 6-month change in body mass index z score. Data analyses followed the intention-to-treat principle. Results All 38 participants (27 girls and 11 boys; mean [SD] age, 14.9 [1.7] years) completed the study. Both groups reported drinking approximately 2 cups of water per day at baseline. Self-reported change in water intake at 6 months was greater in the water group (difference from baseline, 2.8 cups per day [95% CI, 1.8 to 3.8]; P P = .02) (difference between groups, 1.6 cups per day [95% CI, 0.2 to 3.0 cups per day]; P = .03). The 6-month change in body mass index z score did not differ between the water group (difference from baseline, –0.1 [95% CI, –0.2 to –0.0]; P = .005) and the control group (difference from baseline, –0.1 [95% CI, –0.2 to –0.0]; P = .008) (difference between groups, –0.0 [95% CI, −0.1 to 0.1]; P = .88). Conclusions and Relevance Advice and behavioral supports to consume 8 cups of water per day in the context of a weight-reducing diet did not affect body weight among adolescents with overweight or obesity. Despite intensive behavior supports, few adolescents achieved the target of 8 cups of water per day. Environmental interventions to reduce barriers to water consumption at school may be necessary in future research of the feasibility and effectiveness to achieve the target of an intake of 8 cups of water per day in adolescents. Trial Registration clinicaltrials.gov Identifier:NCT01044134

Background and aims Nutritional therapy is the first line approach to treatment of hyperlipidemia in childhood. Proprotein convertase subtilisin kexin type 9 (PCSK9) is a key regulator of plasma cholesterol levels and a target of novel lipid-lowering pharmacotherapies. We examined the effects of an intensive nutritional intervention on PCSK9 levels in overweight adolescents with cardiovascular disease (CVD) risk factors. Methods and results Twenty seven obese and overweight adolescents with CVD risk factors were assigned to either a low fat or low glycemic load diet. During an 8-week " Intensive Phase ," assigned meals were delivered to the home, and all participants received weekly in-person home nutrition counseling and phone calls. The subjects then underwent a 4-month " Maintenance Phase " without food provision and with no in-person contact. Anthropometric measurements, laboratory data, and serum PCSK9 protein levels were measured at baseline, 8 weeks, and 6 months. PCSK9 decreased by 16.5% at 8 weeks (201.2 ± 56.3 vs 165.6 ± 58.4 ng/mL; p Maintenance Phase . Change in PCSK9 was associated with change in fasting insulin, HOMA-IR, and AUC insulin, independent of weight loss. Conclusions PCSK9 decreased in youth participating in an intensive dietary intervention. Change in HOMA-IR was associated with change in PCSK9, independent of weight loss, suggesting an important relationship with insulin sensitivity. ClinicalTrials.gov Identifier: NCT01080339.

Given the high prevalence of obesity in the USA, much recent attention has focused on dietary strategies for weight control. Several medical and scientific societies currently recommend reducing consumption of sugar-sweetened beverages (SSBs). However, the evidence base for a public health recommendation has been a topic of debate. The purpose of this review is not to underscore the debate but rather to consider how recently published data pertaining to SSBs contribute to the evidence base for preventing and treating obesity, with application to caring for patients.Consumption of SSBs remains prevalent in the USA. Emerging data from epidemiological studies and clinical trials indicate that consumption contributes to positive energy balance and reducing consumption has beneficial effects on body weight. Some individuals may be more susceptible to the adverse effects of consuming SSBs owing to their ethnicity or genetic predisposition. Plausible physiological mechanisms link consumption of SSBs with weight control.Available data provide an evidence base for counselling patients to reduce consumption of SSBs. Nevertheless, additional research is needed to strengthen the evidence base, particularly studies aimed at understanding susceptibility to the adverse effects of consuming SSBs on body weight and mechanisms for these effects.

This cross-sectional study examines discrepancies between registered protocols and subsequent publications for drug and diet trials whose findings were published in prominent clinical journals in the last decade.

Background: Qualitative aspects of diet influence eating behavior, but the physiologic mechanisms for these calorie-independent effects remain speculative. Objective: We examined effects of the glycemic index (GI) on brain activity in the late postprandial period after a typical intermeal interval. Design: With the use of a randomized, blinded, crossover design, 12 overweight or obese men aged 18‐35 y consumed high- and low-GI meals controlled for calories, macronutrients, and palatability on 2 occasions. The primary outcome was cerebral blood flow as a measure of resting brain activity, which was assessed by using arterial spin-labeling functional magnetic resonance imaging 4 h after test meals. We hypothesized that brain activity would be greater after the high-GI meal in prespecified regions involved in eating behavior, reward, and craving. Results: Incremental venous plasma glucose (2-h area under the curve) was 2.4-fold greater after the high- than the low-GI meal (P = 0.0001). Plasma glucose was lower (mean 6 SE: 4.7 6 0.14 compared with 5.3 6 0.16 mmol/L; P = 0.005) and reported hunger was greater (P = 0.04) 4 h after the high- than the low-GI meal. At this time, the high-GI meal elicited greater brain activity centered in the right nucleus accumbens (a prespecified area; P = 0.0006 with adjustment for multiple comparisons) that spread to other areas of the right striatum and to the olfactory area. Conclusions: Compared with an isocaloric low-GI meal, a high-GI meal decreased plasma glucose, increased hunger, and selectively stimulated brain regions associated with reward and craving in the late postprandial period, which is a time with special significance to eating behavior at the next meal. This trial was registered at clinicaltrials.gov as NCT01064778. Am J Clin Nutr 2013;98:641‐7.

From the New Balance Foundation Obe- sity Prevention Center (C.B.E., D.S.L.) and the Clinical Research Center (H.A.F., T.A.A., S.K.O.), Boston Children's Hospi - tal, Boston; the Institute for Community Health, Cambridge (V.R.C.); and the De- partment of Society, Human Develop- ment, and Health, Harvard School of Public Health, Boston (S.L.G.) — all in Massachusetts. Address reprint requests to Dr. Ludwig at the New Balance Foun- dation Obesity Prevention Center, Bos- ton Children's Hospital, 300 Longwood Ave., Boston, MA 02115, or at david A B S T R AC T Background Consumption of sugar-sweetened beverages may cause excessive weight gain. We aimed to assess the effect on weight gain of an intervention that included the provi- sion of noncaloric beverages at home for overweight and obese adolescents. Methods We randomly assigned 224 overweight and obese adolescents who regularly con- sumed sugar-sweetened beverages to experimental and control groups. The experi- mental group received a 1-year intervention designed to decrease consumption of sugar-sweetened beverages, with follow-up for an additional year without interven- tion. We hypothesized that the experimental group would gain weight at a slower rate than the control group. Results Retention rates were 97% at 1 year and 93% at 2 years. Reported consumption of sugar-sweetened beverages was similar at baseline in the experimental and control groups (1.7 servings per day), declined to nearly 0 in the experimental group at 1 year, and remained lower in the experimental group than in the control group at 2 years. The primary outcome, the change in mean body-mass index (BMI, the weight in ki- lograms divided by the square of the height in meters) at 2 years, did not differ sig- nificantly between the two groups (change in experimental group minus change in control group, −0.3; P = 0.46). At 1 year, however, there were significant between- group differences for changes in BMI (−0.57, P = 0.045) and weight (−1.9 kg, P = 0.04). We found evidence of effect modification according to ethnic group at 1 year (P = 0.04) and 2 years (P = 0.01). In a prespecified analysis according to ethnic group, among Hispanic participants (27 in the experimental group and 19 in the control group), there was a significant between-group difference in the change in BMI at 1 year (−1.79, P = 0.007) and 2 years (−2.35, P = 0.01), but not among non-Hispanic partici- pants (P>0.35 at years 1 and 2). The change in body fat as a percentage of total weight did not differ significantly between groups at 2 years (−0.5%, P = 0.40). There were no adverse events related to study participation. Conclusions Among overweight and obese adolescents, the increase in BMI was smaller in the experimental group than in the control group after a 1-year intervention designed to reduce consumption of sugar-sweetened beverages, but not at the 2-year follow- up (the prespecified primary outcome). (Funded by the National Institute of Diabe- tes and Digestive and Kidney Diseases and others; ClinicalTrials.gov number, NCT00381160.)

Background: The circumstances under which the glycemic index (GI) and glycemic load (GL) are derived do not reflect real-world eating behavior. Thus, the ecologic validity of these constructs is incompletely known. Objective: This study examined the relation of dietary intake to glycemic response when foods are consumed under free-living conditions. Design: Participants were 26 overweight or obese adults with type 2 diabetes who participated in a randomized trial of lifestyle modification. The current study includes baseline data, before initiation of the intervention. Participants wore a continuous glucose monitor and simultaneously kept a food diary for 3 d. The dietary variables included GI, GL, and intakes of energy, fat, protein, carbohydrate, sugars, and fiber. The glycemic response variables included AUC, mean and SD of continuous glucose monitoring (CGM) values, percentage of CGM values in euglycemic and hyperglycemic ranges, and mean amplitude of glycemic excursions. Relations between daily dietary intake and glycemic outcomes were examined. Results: Data were available from 41 d of monitoring. Partial correlations, controlled for energy intake, indicated that GI or GL was significantly associated with each glycemic response outcome. In multivariate analyses, dietary GI accounted for 10% to 18% of the variance in each glycemic variable, independent of energy and carbohydrate intakes (P < 0.01). Conclusions: The data support the ecologic validity of the GI and GL constructs in free-living obese adults with type 2 diabetes. GI was the strongest and most consistent independent predictor of glycemic stability and variability.

Some short-term pediatric studies have suggested beneficial effects of low glycemic load (LGL) meals on feelings of hunger and on energy intake. However, the effects of LGL diets have not been systematically studied in obese Hispanic children, who stand to benefit from successful interventions.To examine the effects of LGL and high-GL (HGL) meals on appetitive responses and ad libitum energy intake of obese Hispanic youth.A total of 88 obese Hispanic youth aged 7-15 years were enrolled in a community-based obesity intervention program and randomly assigned to consume meals designed as either LGL (n = 45) or HGL (n = 43). After 12 weeks, participants were admitted for a 24-hour metabolic study. Following the morning test meal, subjects serially reported hunger, fullness, and satiety using a visual analog scale. Blood insulin and glucose were measured. After 5 hours, participants were fed another test meal and given a snack platter from which to eat ad libitum. All test food was weighed and the energy, macronutrients, and glycemic load (GL) of consumed foods were calculated.The HGL group had significantly higher insulin (p = 0.0005) and glucose (p = 0.0001) responses to the breakfast meal compared with the LGL group. There were no significant between-group differences in energy consumed from the snack platter (1303 vs. 1368 kcal, p = 0.5), or in the subjective feelings of hunger (p = 0.3), fullness (p = 0.5) or satiety (p = 0.3) between the two groups.Our study provides no evidence that, for obese Hispanic youth, changing the GL of the diet affects short-term hunger, fullness, satiety, or energy intake. ClinicalTrials.gov Identifier: NCT01068197.

Aims To compare the effects of lifestyle modification programs that prescribe low-glycemic load (GL) vs. low-fat diets in a randomized trial. Methods Seventy-nine obese adults with type 2 diabetes received low-fat or low-GL dietary instruction, delivered in 40-week lifestyle modification programs with identical goals for calorie intake and physical activity. Changes in weight, HbA1c, and other metabolic parameters were compared at weeks 20 and 40. Results Weight loss did not differ between groups at week 20 (low-fat: −5.7 ± 3.7%; low-GL: −6.7 ± 4.4%, p = .26) or week 40 (low-fat: −4.5 ± 7.5%; low-GL: −6.4 ± 8.2%, p = .28). Adjusting for changes in antidiabetic medications, subjects on the low-GL diet had larger reductions in HbA1c than those on the low-fat diet at week 20 (low-fat: −0.3 ± 0.6%; low-GL: −0.7 ± 0.6%, p = .01), and week 40 (low-fat: −0.1 ± 1.2%; low-GL: −0.8 ± 1.3%; p = .01). Groups did not differ significantly on any other metabolic outcomes (p ≥ .06). Conclusions Results suggest that targeting GL, rather than dietary fat, in a low-calorie diet can significantly enhance the effect of weight loss on HbA1c in patients with type 2 diabetes.

Despite intensive research, the causes of the obesity epidemic remain incompletely understood and conventional calorie-restricted diets continue to lack long-term efficacy. According to the carbohydrate-insulin model (CIM) of obesity, recent increases in the consumption of processed, high-glycemic-load carbohydrates produce hormonal changes that promote calorie deposition in adipose tissue, exacerbate hunger, and lower energy expenditure. Basic and genetic research provides mechanistic evidence in support of the CIM. In animals, dietary composition has been clearly demonstrated to affect metabolism and body composition, independently of calorie intake, consistent with CIM predictions. Meta-analyses of behavioral trials report greater weight loss with reduced-glycemic load vs low-fat diets, though these studies characteristically suffer from poor long-term compliance. Feeding studies have lacked the rigor and duration to test the CIM, but the longest such studies tend to show metabolic advantages for low-glycemic load vs low-fat diets. Beyond the type and amount of carbohydrate consumed, the CIM provides a conceptual framework for understanding how many dietary and nondietary exposures might alter hormones, metabolism, and adipocyte biology in ways that could predispose to obesity. Pending definitive studies, the principles of a low-glycemic load diet offer a practical alternative to the conventional focus on dietary fat and calorie restriction.

OBJECTIVE. Eating large amounts of food at a rapid rate, defined as gorging, may contribute to excess energy intake. We aimed to evaluate whether altering portion sizes and eating rate could decrease energy intake during an extra-large fast food meal. METHODS. Subjects were adolescents (n = 18), 13 to 17 years of age, who reported eating fast food ≥1 time per week. BMI exceeded the 80th percentile for all subjects. Three feeding conditions were evaluated with a crossover design. Total amounts and types of foods and beverage served during the meal were held constant across conditions, equaling ∼125% of that consumed during a baseline assessment visit when subjects were offered unlimited amounts. The meal (chicken nuggets, French fries, and cola) was presented as 1 large serving at a single time point (condition A, standard), portioned into 4 smaller servings presented at a single time point (condition B, effects of portioning), or portioned into 4 smaller servings presented at 15-minute intervals (condition C, effects of portioning and eating rate). Energy intake across conditions was compared by using analysis of variance. RESULTS. Energy intake was not significantly different, whether expressed in kilojoules (mean ± SEM: condition A, 5552 ± 357 kJ; condition B, 5321 ± 433 kJ; condition C, 5762 ± 500 kJ) or relative to total daily energy expenditure (mean ± SEM: condition A, 51.9 ± 3.5%; condition B, 48.2 ± 4.0%; condition C, 53.0 ± 4.3%). CONCLUSIONS. Adolescents consumed ∼50% of energy needs regardless of manipulations in portion sizes and eating rate to attenuate gorging. This finding suggests that nutritional factors inherent to fast food, such as low levels of dietary fiber, high palatability, high energy density, high fat content, high glycemic load, and high content of sugar in liquid form promote excess energy intake.

Diet modification is recommended to treat childhood cardiovascular (CV) risk factors; however, the optimal dietary strategy is unknown.In a randomized trial, the effect of a low-fat (LF) and a low-glycemic-load (LGL) reduced-calorie diet were examined in youth with overweight/obesity with CV risk factors. Using a novel intervention, we delivered LF or LGL meals and nutrition education to the home for 8 weeks (Intensive Phase), followed by 4 months Maintenance without food provision. Between-group differences in the change in insulin area under the curve (InsAUC) by oral glucose tolerance test and other risk factors were analyzed.Overall, participants (n = 27) showed substantial improvement during the Intensive Phase, including InsAUC (-59 ± 18.2 µU/ml × 120 min, P = 0.004), total cholesterol (-9.9 ± 3.6 mg/dl, P = 0.01), weight (-2.7 ± 0.5 kg, P0.001), waist circumference (-3.1 ± 0.8 cm, P0.001), HOMA-IR (-1.7 ± 0.4, P0.001), systolic blood pressure (-5 ± 1.4 mm Hg, P = 0.002), and CRP (-0.1 ± 0.1 mg/dl, P = 0.04). There were minimal between-group differences; the LF group showed greater declines in HDL (P = 0.005) and fasting glucose (P = 0.01) compared to the LGL group. Improvements waned during Maintenance.Home delivery of LF or LGL diets resulted in rapid and clinically important improvements in CV risk factors that diminished without food delivery and did not differ based on dietary intervention. If scalable, food provision may represent an alternative nutrition treatment strategy.

To examine associations of baseline insulin dynamics with changes in body composition and resting energy expenditure (REE) following weight loss.Twenty-one participants with overweight or obesity achieved 10-15% weight loss and then received 3 weight loss maintenance diets (high-carbohydrate, moderate-carbohydrate, and low-carbohydrate) in random order, each for 4 weeks. Body composition was measured at baseline and after weight loss. Insulin 30 min after glucose consumption (insulin-30; insulin response), C-peptide deconvolution analysis, HOMA, hepatic insulin sensitivity (IS), and REE were assessed at baseline and after each maintenance diet.Insulin-30, but not maximal insulin secretion, hepatic IS, or HOMA, predicted changes in fat mass (standardized β = 0.385, 1.7 kg difference between 10th and 90th centile of insulin-30, P = 0.04) after weight loss. Insulin-30 (β = -0.341, -312 kcal day(-1) , P = 0.008), maximal insulin secretion (β = -0.216, -95 kcal day(-1) , P = 0.0002), HOMA (β = -0.394, -350 kcal day(-1) , P = 0.002), and hepatic IS (β = 0.217, 225 kcal day(-1) , P = 0.0003) predicted change in REE during weight loss maintenance, independent of changes in body composition. The inverse relationship between insulin-30 and REE was substantially attenuated when the low-carbohydrate diet was consumed first.These findings distinguish a novel phenotype, characterized by high insulin response, at risk for weight regain, and identify a dietary approach to ameliorate this risk.

OBJECTIVE. The role of sugar-sweetened beverages (SSBs) in promoting obesity is controversial. Observational data link SSB consumption with excessive weight gain; however, randomized, controlled trials are lacking and necessary to resolve the debate. We conducted a pilot study to examine the effect of decreasing SSB consumption on body weight.METHODS. We randomly assigned 103 adolescents aged 13 to 18 years who regularly consumed SSBs to intervention and control groups. The intervention, 25 weeks in duration, relied largely on home deliveries of noncaloric beverages to displace SSBs and thereby decrease consumption. Change in SSB consumption was the main process measure, and change in body mass index (BMI) was the primary end point.RESULTS. All of the randomly assigned subjects completed the study. Consumption of SSBs decreased by 82% in the intervention group and did not change in the control group. Change in BMI, adjusted for gender and age, was 0.07 ± 0.14 kg/m2 (mean ± SE) for the intervention group and 0.21 ± 0.15 kg/m2 for the control group. The net difference, −0.14 ± 0.21 kg/m2, was not significant overall. However, baseline BMI was a significant effect modifier. Among the subjects in the upper baseline-BMI tertile, BMI change differed significantly between the intervention (−0.63 ± 0.23 kg/m2) and control (+0.12 ± 0.26 kg/m2) groups, a net effect of −0.75 ± 0.34 kg/m2. The interaction between weight change and baseline BMI was not attributable to baseline consumption of SSBs.CONCLUSIONS. A simple environmental intervention almost completely eliminated SSB consumption in a diverse group of adolescents. The beneficial effect on body weight of reducing SSB consumption increased with increasing baseline body weight, offering additional support for American Academy of Pediatrics guidelines to limit SSB consumption.

Background. Fast-food consumption has increased greatly in the USA during the past three decades. However, the effect of fast food on risk of obesity and type 2 diabetes has received little attention. We aimed to investigate the association between reported fast-food habits and changes in bodyweight and insulin resistance over a 15-year period in the USA. Methods. Participants for the CARDIA study included 3031 young (age 18–30 years in 1985–86) black and white adults who were followed up with repeated dietary assessment. We used multiple linear regression models to investigate the association of frequency of fast-food restaurant visits (fast-food frequency) at baseline and follow-up with 15-year changes in bodyweight and the homoeostasis model (HOMA) for insulin resistance. Findings. Fast-food frequency was lowest for white women (about 1·3 times per week) compared with the other ethnic-sex groups (about twice a week). After adjustment for lifestyle factors, baseline fast-food frequency was directly associated with changes in bodyweight in both black (p=0·0050) and white people (p=0·0013). Change in fast-food frequency over 15 years was directly associated with changes in bodyweight in white individuals (p

Conventional techniques which employ weight-for-height (WH), triceps skinfold (TSF), and body mass index (BMI) for assessing pediatric obesity were compared in the present investigation. Subjects were children aged 6 to 9 years (585 boys, 586 girls) from the NHANESII sample. Criterion-referenced standards consisting of morbidity-related cutoff points of 25% and 30% fat for boys and girls, respectively, were used to define obesity and served as the basic screening criteria for comparison among conventional techniques. The conventional techniques used to identify obese children which employ specified norm-referenced cutoff points were 1) WH ≥ 120 of median, 2) TSF ≥ 85th percentile, 3) WH ≥ 120% of median and TSF ≥ 85th percentile, and 4) BMI ≥ 85th percentile. Sensitivities (Se), specificities (Sp), and positive (V+) and negative (V−) predictive values were calculated with respect to screening criteria for comparison among conventional techniques. To explore alternative cutoff points, receiver operator characteristic (ROC) curves were used to illustrate trade-offs between improving Se or Sp for a series of potential TSF and BMI cutoff points. While the method employing both WH and TSF yielded the highest V+ among the conventional techniques, the necessary exclusion of children from analyses incorporating WH limits the utility of this technique. Classification of subjects according to obesity status using 85th percentiles for TSF and BMI furnished V+ ≤ 0.5. The cutoff points derived from ROC curves with respect to TSF (17 mm for boys; 20 mm for girls) and BMI (19.5 kg/m 2 for both genders) were comparable to values associated with respective 95th percentiles and provided favorable V+. Accurate, yet practical, techniques for identifying children at risk for obesity-related diseases are needed. Cutoff points which correspond to 95 th percentiles should be applied when using a norm-referenced approach. When using a criterion-referenced approach, a BMI of 19.5 kg/m 2 for both genders and TSF values of 17 mm and 20 mm for boys and girls, respectively, are suggested at the present time. Additional research is warranted to validate the clinical utility of these cutoff points.

Hypocaloric therapy may adversely affect protein utilization in obese children given that metabolic reactions involving protein, a nutrient essential for growth, are energy-dependent. Because physical activity influences nutrient utilization and may modulate the effects of reduced energy intake, exercise combined with diet therapy may be beneficial with regard to protein metabolism. The primary purpose of this study was to evaluate changes in protein utilization in response to sequential addition of an exercise program to dietary intervention in obese children.After a 2-wk baseline period, five subjects aged 8-10 yr reduced energy intake [-2092 to -2510 kJ.d(-1)(-500 to -600 kcal.d(-1))] for 12 wk. A walking program [5 d.wk(-1), 3.2-4.8 km.d(-1) (2-3 miles.d(-1))] was implemented during the final 6 wk of diet therapy. At baseline and after phases I (diet only) and II (exercise and diet) of intervention, 15N-glycine was used to assess protein synthesis (PS), protein breakdown (PB), net turnover (NET = PS - PB), and nitrogen flux (Q).Subjects lost 4.2+/-0.4 kg during the 12-wk intervention period (Por = 0.05). With diet only, NET decreased (Por = 0.05) due to a reduction in PS (Por = 0.05) accompanied by no change in PB. Although PS increased with walking (Por = 0.05), NET did not return to baseline levels due to a concurrent increase in PB (Por = 0.05). Changes in PS and PB yielded an increase in Q (Por = 0.05), a measure of amino acid cycling between protein and free amino acid pools.These results suggest that exercise offers metabolic benefits for obese children during diet-induced weight loss. Longitudinal studies are needed to assess long-term health outcomes associated with the observed changes in protein utilization.

Recommendations for preventing and treating pediatric obesity suggest a staged approach with escalating intensity of care.1 Stage 1 is Prevention Plus, requiring sufficient capacity in a primary care setting to provide basic messages pertaining to healthful dietary and physical activity behaviors. Stages 2 and 3 are Structured Weight Management and Comprehensive Multidisciplinary Intervention, respectively, requiring more frequent clinical encounters and involving a registered dietitian (RD) and a behavioral medicine provider. Stage 2 may be appropriate in a primary care setting, although inadequate training and financial support for structured intervention often are limiting factors. Stage 3 requires primary care providers (PCPs) to coordinate patient care with a pediatric weight management clinic and, in some cases, community partners that provide opportunities for physical activity. Stage 4 is Tertiary Care Intervention and may include a very low-calorie diet, medication, and surgery. Outcomes of clinical interventions for pediatric obesity are variable. In primary care settings, some interventions promote changes in diet, physical activity, or television viewing but do not achieve reductions in BMI2,3; others have favorable, albeit sometimes small, effects on BMI.4– … Address correspondence to Cara B. Ebbeling, PhD, New Balance Foundation Obesity Prevention Center, Boston Children’s Hospital, 300 Longwood Ave (AU307), Boston, MA 02115. E-mail: cara.ebbeling{at}childrens.harvard.edu

Fatty liver is highly prevalent among obese children and represents a major risk factor for chronic liver diseases and severe metabolic complications.We randomly assigned 17 obese children 8-17 years of age with fatty liver to either an experimental low-glycemic-load or conventional low-fat diet for 6 months. Participants in both groups received nutrition education and behavioral counseling of equal intensity. The primary outcome was hepatic lipid content measured by proton magnetic resonance spectroscopy. Secondary outcomes included change in visceral fat, BMI, anthropometrics, alanine aminotransferase (ALT), and insulin resistance.A total of 16 participants completed the study. Reported glycemic load decreased in the low-glycemic-load group and reported dietary fat decreased in the low-fat group. At baseline, liver fat was 23.8% [standard deviation (SD) 12.2] in the low-glycemic-load group and 29.3% (14.1) in the low-fat group. Liver fat decreased substantially in both groups at 6 months expressed as absolute percentage change, with no between-group differences [-8.8 (standard error (SE) 4.1) vs. -10.5 (3.7)%, respectively, p=0.76 for group×time interaction]. Secondary outcomes also improved on both diets, with no between-group differences. Baseline and change in ALT were strongly associated with hepatic fat content.Weight-reducing diets focused either on glycemic load or dietary fat improved hepatic steatosis over 6 months. Additional research is needed to determine whether these diets differ in effectiveness over the long term.clinicaltrials.gov Identifier: NCT00480922.

Background The major circulating metabolic fuels regulate hunger, and each is affected by dietary composition. An integrated measure of postprandial energy availability from circulating metabolic fuels may help inform dietary recommendations for weight maintenance after weight loss. Aim We examined the effect of low-fat (LF, 60% of energy from carbohydrate, 20% fat, 20% protein), low-glycemic index (LGI, 40%–40%-20%), and very low-carbohydrate (VLC, 10%–60%-30%) diets on total postprandial metabolic fuel energy availability (EA) during weight loss maintenance. Methods Eight obese young adults were fed a standard hypocaloric diet to produce 10–15% weight loss. They were then provided isocaloric LF, LGI, and VLC diets in a randomized crossover design, each for a 4-week period of weight loss maintenance. At the end of each dietary period, a test meal representing the respective diet was provided, and blood samples were obtained every 30 minutes for 5 hours. The primary outcome was EA, defined as the combined energy density (circulating level×relative energy content) of glucose, free fatty acids, and β-hydroxybutyrate. Secondary outcomes were individual metabolic fuels, metabolic rate, insulin, glucagon, cortisol, epinephrine, and hunger ratings. Respiratory quotient was a process measure. Data were analyzed by repeated-measures analysis of variance, with outcomes compared in the early (30 to 150 min) and late (180 to 300 min) postprandial periods. Results EA did not differ between the test meals during the early postprandial period (p = 0.99). However, EA in the late postprandial period was significantly lower after the LF test meal than the LGI (p