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BackgroundThe extent to which physical activity attenuates the detrimental effects of sugar (SSBs)- or artificially-sweetened beverages (ASBs) on the risk of cardiovascular disease is unknown.MethodsWe used Cox proportional-hazards models to calculate hazard ratios and 95% confidence interval [HR (CI)] between SSB or ASB intake and physical activity with cardiovascular disease risk among 65,730 women in the Nurses’ Health Study (1980-2016) and 39,418 men in the Health Professional’s Follow-up Study (1986-2016), who were free from chronic diseases at baseline. SSBs and ASBs were assessed every 4-years and physical activity biannually.ResultsA total of 13,269 cardiovascular events were ascertained during 3,001,213 person-years of follow-up. Compared with those that never/rarely consumed SSBs or ASBs, HR and 95% CI for cardiovascular disease for participants consuming ≥2 servings/day were 1.21 (95% CI,1.12 to 1.32;P-trendP-trend=0.06), respectively. In the joint analyses, for participants meeting and not meeting physical activity guidelines (ConclusionsOur findings suggest that among physically active participants, higher SSB intake, but not ASBs, is associated with a higher cardiovascular risk. Our results support current recommendations to limit the intake of SSB and maintain adequate physical activity levels.Clinical PerspectiveWhat is new?Consumption of sugar- or artificially-sweetened beverages and physical activity are independently associated with cardiovascular disease; nevertheless, the role that physical activity plays in the associations between sugar- and artificially-sweetened beverages consumption and cardiovascular disease warrants further analysis since physical activity could offset the health risk that would have been induced by their consumption.In two US cohorts, not meeting physical activity guidelines jointly with a greater intake of sugar- or artificially-sweetened beverages was associated with a higher risk of cardiovascular disease; however, even when individuals were physically active, higher consumption of sugar-sweetened beverages was associated with a higher cardiovascular risk.What are the clinical implications?Our results provide further evidence of the intake of sugar-sweetened beverages and low physical activity as factors negatively impacting cardiovascular health.Our results support public health recommendations and policies to limit the intake of sugar-sweetened beverages and meet and maintain adequate physical activity levels.

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.

Adipocyte mitochondrial respiration may influence metabolic fuel partitioning into oxidation versus storage, with implications for whole-body energy expenditure. Although insulin has been shown to influence mitochondrial respiration, the effects of dietary macronutrient composition have not been well characterized. The aim of this exploratory study was to test the hypothesis that a high-carbohydrate diet lowers the oxygen flux of adipocyte mitochondria ex vivo. Among participants in a randomized-controlled weight-loss maintenance feeding trial, those consuming a high-carbohydrate diet (60% carbohydrate as a proportion of total energy, n = 10) had lower rates of maximal adipose tissue mitochondrial respiration than those consuming a moderate-carbohydrate diet (40%, n = 8, p = 0.039) or a low-carbohydrate diet (20%, n = 9, p = 0.005) after 10 to 15 weeks. This preliminary finding may provide a mechanism for postulated calorie-independent effects of dietary composition on energy expenditure and fat deposition, potentially through the actions of insulin on fuel partitioning.

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.

Background: Consumption of sugar-sweetened beverages (SSBs) or artificially sweetened beverages (ASBs) and physical activity are independently associated with type 2 diabetes (T2D) risk; however, it is unknown whether there is an interaction of SSB/ASB intake and physical activity on risk of T2D. Methods: We examined the independent and joint associations between habitual SSB/ASB intake and physical activity with incident T2D risk among 196,101 women and men from the Nurses’ Health Study (NHS, 1980-2016), NHSII (1991-2017), and Health Professional’s Follow-up Study (HPFS, 1986-2016), who were free from chronic diseases at baseline. Cox proportional hazards regressions were used to estimate hazard ratios and 95% confidence intervals (HR; CI), adjusting for demographic and lifestyle T2D risk factors. Results: There were 20,430 incident T2D cases over follow-up of 36, 26, and 30 years in NHS, NHSII, and HPFS, respectively. In multivariable-adjusted models, we confirmed that participants with higher SSBs, ASBs and lower physical activity were independently at higher T2D risk, compared to lower intakes and higher activity levels. In joint analyses for these exposures, participants who did not meet physical activity guidelines and consumed gt 2 servings/day of SSBs had a significantly higher risk of T2D than those who met physical activity guidelines and never/rarely consumed SSBs (1.51; 1.43, 1.60); we observed similar findings for ASBs: 1.29; 1.23, 1.36). Among participants who met physical activity guidelines, those who consumed gt 2 servings/day of SSBs had a HR of 1.23 (1.16, 1.30); the HR for ASBs was 1.07 (1.02, 1.13). Consistent results were observed for women and men. Conclusions: Long-term habitual intake of SSBs or ASBs combined with lower physical activity was associated with higher risk of T2D in three large prospective cohort studies. These findings suggest that even when individuals are physically active, higher consumption of SSBs is associated with a higher risk of T2D. Our results support recommendations and policies to limit the intake of SSB and increase physical activity levels.

BackgroundRecent three-dimensional optical (3DO) imaging advancements have provided more accessible, affordable, and self-operating opportunities for assessing body composition. 3DO is accurate and precise with respect to clinical measures made by dual-energy X-ray absorptiometry (DXA). However, the sensitivity for monitoring body composition change over time with 3DO body shape is unknown.ObjectiveTo evaluate 3DO’s ability to monitor body composition changes across multiple intervention studies.MethodsA retrospective analysis was performed using intervention studies on healthy adults that were complimentary to the cross-sectional study, Shape Up! Adults. Each participant received a DXA (Hologic Discovery/A system) and 3DO (Fit3D ProScanner) scan at baseline and follow-up. 3DO meshes were digitally registered and reposed using Meshcapade to standardize the vertices and pose. Using an established statistical shape model, each 3DO mesh was transformed into principal components (PCs), which were used to predict whole-body and regional body composition values using published equations. Body composition changes (follow-up minus baseline) were compared to DXA with linear regression.ResultsThe analysis included 133 participants (45 females) in six studies. The mean (SD) length of follow-up was 13 (5) weeks, range 3-23 weeks. Agreement between 3DO and DXA (R2) for changes in total fat mass (FM), total fat-free mass (FFM), and appendicular lean mass, respectively, were 0.86, 0.73, and 0.70 with RMSEs of 1.98 kg, 1.58 kg, and 0.37 kg in females, and 0.75, 0.75, and 0.52 with RMSEs of 2.31 kg, 1.77 kg, and 0.52 kg in males. Further adjustment with demographic descriptors improved the 3DO change agreement to changes observed with DXA.ConclusionsAs compared to DXA, 3DO was highly sensitive in detecting body shape changes over time. The 3DO method was sensitive enough to detect even small changes in body composition during intervention studies. The safety and accessibility of 3DO allows users to self-monitor on a frequent basis throughout interventions.

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.

OBJECTIVE: The carbohydrate-insulin model (CIM) claims that chronic exposure to hyperinsulinemia induced by dietary carbohydrates explains development of obesity via direct effects of insulin and/or low postprandial metabolic fuel levels. We aimed at testing whether indices of hyperinsulinemia and postprandial glucose levels can predict increases in the degree of obesity over time. RESEARCH DESIGN AND METHODS: Children and adolescents with obesity attending a pediatric obesity clinic performed oral glucose tolerance tests (OGTTs) and received standard obesity management. Indices of hyperinsulinemia and insulin secretion were derived from the OGTT and evaluated in the face of changes in the degree of obesity over time. RESULTS: A total of 591 children (217 males and 374 females) participated, and the mean follow-up was 1.86 ± 1.29 years. OGTT-derived area under the curve of insulin, peak insulin, fasting insulin, the insulinogenic index, or insulin at 30 min were not associated with greater changes in the degree of obesity in univariate or multivariate analyses (adjusted for baseline age, BMI z score, sex, and ethnicity). Low postprandial glucose 4 years, none of these parameters was associated with greater increases in the degree of obesity. CONCLUSIONS: In children and adolescents with obesity, exposure to hyperinsulinemia, greater insulin secretion, or low postprandial glucose is not associated with greater increases in the degree of obesity over 2–4 years. The CIM should be evaluated in children with lower BMI and for longer follow-up periods.

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.

OBJECTIVE Consuming ≥150 g/day carbohydrate is recommended for 3 days before an oral glucose tolerance test (OGTT) for diabetes diagnosis. For evaluation of this recommendation, time courses of glycemic changes following transition from a very-low-carbohydrate (VLC) to high-carbohydrate diet were assessed with continuous glucose monitoring (CGM). RESEARCH DESIGN AND METHODS After achieving a weight loss target of 15% (±3%) on the run-in VLC diet, participants (18–50 years old, BMI ≥27 kg/m2) were randomly assigned for 10 weeks to one of three isoenergetic diets: VLC (5% carbohydrate and 77% fat); high carbohydrate, high starch (HC-Starch) (57% carbohydrate and 25% fat, including 20% refined grains); and high carbohydrate, high sugar (HC-Sugar) (57% carbohydrate and 25% fat, including 20% sugar). CGM was done throughout the trial (n = 64) and OGTT at start and end (n = 41). All food was prepared in a metabolic kitchen and consumed under observation. RESULTS Glucose metrics continued to decline after week 1 in the HC-Starch and HC-Sugar groups (P < 0.05) but not VLC. During weeks 2–5, fasting and 2-h glucose (millimoles per liter per week) decreased in HC-Starch (fasting −0.10, P = 0.001; 2 h −0.10, P = 0.04). During weeks 6–9, 2-h glucose decreased in HC-Starch (−0.07, P = 0.01) and fasting and 2-h glucose decreased in HC-Sugar (fasting −0.09, P = 0.001; 2 h −0.09, P = 0.003). The number of participants with abnormal glucose tolerance by OGTT remained 10 (of 16) in VLC at start and end but decreased from 17 to 9 (of 25) in both high-carbohydrate groups. CONCLUSIONS Physiological adaptation from a low- to high-carbohydrate diet may require many weeks, with implications for the accuracy of diabetes tests, interpretation of macronutrient trials, and risks of periodic planned deviations from a VLC diet.

Adipocyte mitochondrial respiration may influence metabolic fuel partitioning into oxidation versus storage, with implications for whole-body energy expenditure. Although insulin has been shown to influence mitochondrial respiration, the effects of dietary macronutrient composition have not been well characterized. The aim of this exploratory study was to test the hypothesis that a high-carbohydrate diet lowers the oxygen flux of adipocyte mitochondria ex vivo. Among participants in a randomized-controlled weight-loss maintenance feeding trial, those consuming a high-carbohydrate diet (60% carbohydrate as a proportion of total energy, n = 10) had lower rates of maximal adipose tissue mitochondrial respiration than those consuming a moderate-carbohydrate diet (40%, n = 8, p = 0.039) or a low-carbohydrate diet (20%, n = 9, p = 0.005) after 10 to 15 weeks. This preliminary finding may provide a mechanism for postulated calorie-independent effects of dietary composition on energy expenditure and fat deposition, potentially through the actions of insulin on fuel partitioning.

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.

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.

BACKGROUND: The majority of children in North America consume cow-milk daily. Children aged >2 y are recommended to consume reduced-fat (0.1–2%) cow-milk to lower the risk of obesity. OBJECTIVES: To evaluate the relation between cow-milk fat consumption and adiposity in children aged 1–18 y. METHODS: Embase (Excerpta Medica Database), CINAHL (Cumulative Index to Nursing and Allied Health Literature), MEDLINE, Scopus, and Cochrane Library databases from inception to August 2019 were used. The search included observational and interventional studies of healthy children aged 1–18 y that described the association between cow-milk fat consumption and adiposity. Two reviewers extracted data, using the Newcastle–Ottawa Scale to assess risk of bias. Meta-analysis was conducted using random effects to evaluate the relation between cow-milk fat and risk of overweight or obesity. Adiposity was assessed using BMI z-score (zBMI). RESULTS: Of 5862 reports identified by the search, 28 met the inclusion criteria: 20 were cross-sectional and 8 were prospective cohort. No clinical trials were identified. In 18 studies, higher cow-milk fat consumption was associated with lower child adiposity, and 10 studies did not identify an association. Meta-analysis included 14 of the 28 studies (n = 20,897) that measured the proportion of children who consumed whole milk compared with reduced-fat milk and direct measures of overweight or obesity. Among children who consumed whole (3.25% fat) compared with reduced-fat (0.1–2%) milk, the OR of overweight or obesity was 0.61 (95% CI: 0.52, 0.72; P

Objective The objective of this study is to summarize evidence for strategies designed to reduce sugar-sweetened beverage (SSB) consumption among children aged 0 to 5 years. Data sources PubMed, Web of Science, EMBASE, CINAHL, ERIC, Cab Abstracts and the Cochrane Central Register of Controlled Trials are the electronic databases searched in this systematic review. Study selection Each included study evaluated an intervention to reduce SSB consumption in children aged 0 to 5 years, was conducted in a high-income country and was published between 1 January 2000 and 15 December 2017. Data synthesis Twenty-seven studies met the inclusion criteria. The primary intervention settings were healthcare (n = 11), preschool/daycare (n = 4), home (n = 3), community venues (n = 3) and other settings (n = 6). Overarching strategies which successfully reduced SSB consumption included (i) in-person individual education, (ii) in-person group education, (iii) passive education (e.g. pamphlets), (iv) use of technology, (v) training for childcare/healthcare providers and (vi) changes to the physical access of beverages. Studies were of moderate methodological quality (average score of 20.7/29.0 for randomized studies; 3.1/9.0 for non-randomized studies). Conclusions Evidence suggests that interventions successful at reducing SSB consumption among 0-year to 5-year olds often focused on vulnerable populations, were conducted in preschool/daycare settings, specifically targeted only SSBs or only oral hygiene, included multiple intervention strategies and had higher intervention intensity/contact time.

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.

Introduction: Given the adverse health effects of added sugars, particularly in liquid form, dietary guidelines recommend replacing sugar-sweetened beverages (SSB) with non-caloric options. However, data are limited regarding the effects of artificially sweetened (ASB) compared to unsweetened (USB) beverages. Hypothesis: We tested the hypothesis that, as replacements for SSB, USB vs. ASB would produce greater reductions in CVD risk factors (USB Methods: Participants were adults aged 18 to 40 y who habitually consumed SSB. We randomly assigned 203 participants (121 males, 82 females) to three groups, and delivered SSB, ASB, or USB to their homes for 12 months. Outcomes included ratio of serum triglyceride to HDL-cholesterol (TG:HDLC, primary outcome), insulin sensitivity (HOMA-S), body weight, and fat mass (DXA). To assess preference for sweet taste, we obtained sweetness ratings for sucrose solutions ranging in concentration (mass/volume) from 0% to 18% using a 10-cm visual analog scale (0=not at all sweet; 10=extremely sweet). We fitted a logistic curve to each participant’s ratings, and defined sweetness threshold as the concentration corresponding to 5 cm on the scale. Results: Participant retention was 92% (186 of 203). Consumption of assigned beverages increased by 1 to 2 servings/d (12 fl oz per serving) for each group (P0.20). Change in body weight did not differ between groups (P=0.65) despite observed weight gain with consumption of SSB (mean±SE 1.2±0.6 kg, P=0.03) but not with ASB or USB (both 0.6±0.6 kg, P>0.20). Consistent with an a priori hypothesis, we found effect modification by a measure of baseline adiposity (P=0.01). Body weight increased by 0.48±0.17 kg more for each kg of trunk fat with consumption of SSB vs. USB (P=0.005). The increase was 0.39±0.17 kg/kg with SSB vs. ASB (P=0.02). A similar pattern of effect modification was observed for change in fat mass. Change in sweetness threshold differed between groups (P=0.03), due to a decrease with consumption of USB (median -0.5%, interquartile range 1.3, P=0.005) and no change with SSB or ASB. Conclusions: Replacing SSB with non-caloric beverages had no effect on pre-specified CVD risk factors. Among individuals with central adiposity, replacing SSB with either ASB or USB had a favorable effect on body weight, consistent with prior findings. However, USB were a better replacement than ASB for altering taste preference, a finding with plausible implications for promoting adherence to prescribed low-sugar diets. Consistent with epidemiologic data, the benefits of eliminating consumption of SSB on CVD risk factors may require longer periods of study for the general population.

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

OBJECTIVES: To compare effects of diets varying in carbohydrate (carb) and fat on plasma lipids and lipoprotein subfractions. METHODS: Participants (N = 164, 70% female, 18–65 y, BMI ≥ 25 kg/m(2)) achieved 10–14% weight loss on a run-in diet and then were randomized to 3 test diets for 20 weeks of weight-loss maintenance. Percentages of total energy from carb-fat-protein for high-, moderate-, and low-carb diets were 60-20-20 (HI), 40-40-20 (MOD), and 20–60-20 (LO). Relative amounts of added sugar (15% total carb) and saturated fat (35% total fat) were fixed across diets. Plasma was collected at START (post-weight loss) and END of trial. The primary outcome for this ancillary study was lipoprotein insulin resistance (LPIR) – a 6-component weighted score of 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) (NMR spectroscopy, LabCorp). Other outcomes included large LDL-P concentration, triglycerides (TG), and cholesterol (HDL-C, LDL-C). Means (±SE) and END–START changes (mean [95% CI]) were constructed and compared from repeated measures ANOVA. RESULTS: Retention was 90% and 147 participants provided evaluable data, with no difference in body weight by diet after randomization. LPIR was 32.6 ± 1.5 at START. Change in LPIR differed by diet (P = 0.009): LO (−5.3 [−9.2, −1.5]), MOD (−0.02 [−4.1, 4.1]), HI (3.6 [−0.6, 7.7]). Diet effects favoring LO compared to HI were observed for large/very large TRL-P (P = 0.005), large HDL-P (P = 0.045), TG (P = 0.006), and HDL-C (P = 0.04). There were no mean differences between diets for particle sizes, LDL-P subfraction concentrations, and LDL-C (START: 79.3 ± 1.8 mg/dL; END–START: HI, 8.2 [4.2, 12.2]; MOD, 11.7 [7.8, 15.7]; LO, 10.0 [6.3, 13.7]). CONCLUSIONS: With 3-fold higher saturated fat content (21% vs 7% total energy), a low- vs high-carb diet improved LPIR, a biomarker of diabetes risk, and several other components of the metabolic syndrome, with no adverse effects on LDL-P or LDL-C. These results from a large feeding study suggest that carb restriction may help prevent cardiometabolic disease independent of body weight. FUNDING SOURCES: Nutrition Science Initiative (gifts from Arnold Ventures and Robert Lloyd Corkin Charitable Foundation), New Balance Foundation, Many Voices Foundation, Blue Cross Blue Shield.

A research team from Boston Children's Hospital and Harvard Medical School conducted a community-based feeding study in collaboration with Framingham State University (FSU) and Sodexo, the food service contractor at FSU. The study was a randomized controlled trial, implemented on the FSU campus. For the final year of the study, a satellite feeding site was established at Assabet Valley Regional Technical High School. The purpose of the study was to assess the biological effects of different macronutrient diets. An academia-industry partnership was developed to overcome common challenges associated with hospital-based feeding studies. Benefits included the following: a study site outside of Boston (reducing inconvenience for participants), access to a large commercial kitchen and study-specific kiosk (promoting efficiency), collaboration with Sodexo chefs (ensuring palatability of meals), and opportunity to procure food from contracted vendors. The research (academia) and food service (industry) teams worked together to design, plan, and execute intervention protocols using an integrated approach. During execution, the research team was primarily responsible for overseeing treatment fidelity, whereas the food service team provided culinary expertise, with a strong focus on hospitality and food quality. The study was conducted in 3 cohorts between August 2014 and May 2017. Participants received all of their food for ∼30 wk, totaling >160,000 meals. For all 3 cohorts combined, 234 participants provided informed consent, 229 started a standard run-in weight-loss diet, 164 lost a mean ± SD 12% ± 2% of baseline body weight and were randomly assigned to different macronutrient diets for weight-loss maintenance, and 148 completed the study. During the final and largest cohort, as many as 114 participants received daily meals concurrently. The daily cost per participant for preparation and service of weighed meals and snacks was ∼$65. This academia-industry partnership provides a model for controlled feeding protocols in nutrition research, potentially with enhanced cost-effectiveness, practicality, and generalizability. This trial was registered at http://www.clinicaltrials.gov as {"type":"clinical-trial","attrs":{"text":"NCT02068885","term_id":"NCT02068885"}}NCT02068885.

OBJECTIVES: To evaluate glycemic control among children and adults with type 1 diabetes mellitus (T1DM) who consume a very low–carbohydrate diet (VLCD). METHODS: We conducted an online survey of an international social media group for people with T1DM who follow a VLCD. Respondents included adults and parents of children with T1DM. We assessed current hemoglobin A1c (HbA1c) (primary measure), change in HbA1c after the self-reported beginning of the VLCD, total daily insulin dose, and adverse events. We obtained confirmatory data from diabetes care providers and medical records. RESULTS: Of 316 respondents, 131 (42%) were parents of children with T1DM, and 57% were of female sex. Suggestive evidence of T1DM (based on a 3-tier scoring system in which researchers took into consideration age and weight at diagnosis, pancreatic autoimmunity, insulin requirement, and clinical presentation) was obtained for 273 (86%) respondents. The mean age at diagnosis was 16 ± 14 years, the duration of diabetes was 11 ± 13 years, and the time following a VLCD was 2.2 ± 3.9 years. Participants had a mean daily carbohydrate intake of 36 ± 15 g. Reported mean HbA1c was 5.67% ± 0.66%. Only 7 (2%) respondents reported diabetes-related hospitalizations in the past year, including 4 (1%) for ketoacidosis and 2 (1%) for hypoglycemia. CONCLUSIONS: Exceptional glycemic control of T1DM with low rates of adverse events was reported by a community of children and adults who consume a VLCD. The generalizability of these findings requires further studies, including high-quality randomized controlled trials.

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.