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Background: Evaluating effects of different macronutrient diets in randomized trials requires well defined infrastructure and rigorous methods to ensure intervention fidelity and adherence., Methods: This controlled feeding study comprised two phases. During a Run-in phase (14-15 weeks), study participants (18-50 years, BMI, ≥27 kg/m 2 ) consumed a very-low-carbohydrate (VLC) diet, with home delivery of prepared meals, at an energy level to promote 15 ± 3% weight loss. During a Residential phase (13 weeks), participants resided at a conference center. They received a eucaloric VLC diet for three weeks and then were randomized to isocaloric test diets for 10 weeks: VLC (5% energy from carbohydrate, 77% from fat), high-carbohydrate (HC)-Starch (57%, 25%; including 20% energy from refined grains), or HC-Sugar (57%, 25%; including 20% sugar). Outcomes included measures of body composition and energy expenditure, chronic disease risk factors, and variables pertaining to physiological mechanisms. Six cores provided infrastructure for implementing standardized protocols: Recruitment, Diet and Meal Production, Participant Support, Assessments, Regulatory Affairs and Data Management, and Statistics. The first participants were enrolled in May 2018. Participants residing at the conference center at the start of the COVID-19 pandemic completed the study, with each core implementing mitigation plans., Results: Before early shutdown, 77 participants were randomized, and 70 completed the trial (65% of planned completion). Process measures indicated integrity to protocols for weighing menu items, within narrow tolerance limits, and participant adherence, assessed by direct observation and continuous glucose monitoring., Conclusion: Available data will inform future research, albeit with less statistical power than originally planned., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: David S. Ludwig Dr. Ludwig has received royalties for books that recommend a carbohydrate-modified diet. David B. Allison In the last thirty-six months, Dr. Allison has received personal payments or promises for same from: Alkermes, Inc.; Amin Talati Wasserman for KSF Acquisition Corp (Glanbia); General Mills; Kaleido Biosciences; Law Offices of Ronald Marron; Novo Nordisk Fonden; and Zero Longevity Science (as stock options). Donations to a foundation have been made on his behalf by the Northarvest Bean Growers Association. He has served as an unpaid consultant/advisor to the USDA Agricultural Research Service. Dr. Allison’s institution, Indiana University, and the Indiana University Foundation have received funds or donations to support his research or educational activities from: Alliance for Potato Research and Education; American Egg Board; Arnold Ventures; Eli Lilly and Company; Mars, Inc.; National Cattlemen’s Beef Association; National Pork Board; Pfizer, Inc.; Soleno Therapeutics; WW (formerly Weight Watchers); and numerous other for-profit and non-profit organizations to support the work of the School of Public Health and the university more broadly. Steven B. Heymsfield Dr. Heymsfield reports personal fees from Medifast Corporation, Tanita Corporation, Novo Nordisk, and Amgen, outside the submitted work. Tapan Mehta Dr. Mehta has received fees from Novo Nordisk, Heart Rhythm Clinical and Research Solutions, The Obesity Journal, and PLOS One., (Copyright © 2024 Elsevier Inc. All rights reserved.)

An influential 2-wk cross-over feeding trial without a washout period purported to show advantages of a low-fat diet (LFD) compared with a low-carbohydrate diet (LCD) for weight control. In contrast to several other macronutrient trials, the diet order effect was originally reported as not significant. In light of a new analysis by the original investigative group identifying an order effect, we aimed to examine, in a reanalysis of publicly available data (16 of 20 original participants; 7 female; mean BMI, 27.8 kg/m 2 ), the validity of the original results and the claims that trial data oppose the carbohydrate-insulin model of obesity (CIM). We found that energy intake on the LCD was much lower when this diet was consumed first compared with second (a difference of -1164 kcal/d, P = 3.6 × 10 -13 ); the opposite pattern was observed for the LFD (924 kcal/d, P = 2.0 × 10 -16 ). This carry-over effect was significant (P interaction = 0.0004) whereas the net dietary effect was not (P = 0.4). Likewise, the between-arm difference (LCD - LFD) was -320 kcal/d in the first period and +1771 kcal/d in the second. Body fat decreased with consumption of the LCD first and increased with consumption of this diet second (-0.69 ± 0.33 compared with 0.57 ± 0.32 kg, P = 0.007). LCD-first participants had higher β-hydroxybutyrate levels while consuming the LCD and lower respiratory quotients while consuming LFD when compared with LFD-first participants on their respective diets. Change in insulin secretion as assessed by C-peptide in the first diet period predicted higher energy intake and less fat loss in the second period. These findings, which tend to support rather than oppose the CIM, suggest that differential (unequal) carry-over effects and short duration, with no washout period, preclude causal inferences regarding chronic macronutrient effects from this trial., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: Whether physical activity could mitigate the adverse impacts of sugar-sweetened beverages (SSBs) or artificially sweetened beverages (ASBs) on incident cardiovascular disease (CVD) remains uncertain., Objectives: This study aimed to examine the independent and joint associations between SSB or ASB consumption and physical activity and risk of CVD, defined as fatal and nonfatal coronary artery disease and stroke, in adults from 2 United States-based prospective cohort studies., Methods: Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% CIs between SSB or ASB intake and physical activity with incident CVD among 65,730 females in the Nurses' Health Study (1980-2016) and 39,418 males 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-y and physical activity biannually., Results: A total of 13,269 CVD events were ascertained during 3,001,213 person-years of follow-up. Compared with those who never/rarely consumed SSBs or ASBs, the HR for CVD for participants consuming ≥2 servings/d was 1.21 (95% CI: 1.12, 1.32; P-trend < 0.001) for SSBs and 1.03 (95% CI: 0.97, 1.09; P-trend = 0.06) for those consuming ≥2 servings/d of ASBs. The HR for CVD per 1 serving increment of SSB per day was 1.18 (95% CI: 1.10, 1.26) and 1.12 (95% CI: 1.04, 1.20) for participants meeting and not meeting physical activity guidelines (≥7.5 compared with <7.5 MET h/wk), respectively. Compared with participants who met physical activity guidelines and never/rarely consumed SSBs, the HR for CVD was 1.47 (95% CI: 1.37, 1.57) for participants not meeting physical activity guidelines and consuming ≥2 servings/wk of SSBs. No significant associations were observed for ASB when stratified by physical activity., Conclusions: Higher SSB intake was associated with CVD risk regardless of physical activity levels. These results support current recommendations to limit the intake of SSBs even for physically active individuals., (Copyright © 2024 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

Background: Low-density lipoprotein (LDL) cholesterol change with consumption of a low-carbohydrate diet (LCD) is highly variable. Identifying the source of this heterogeneity could guide clinical decision-making., Objectives: To evaluate LDL cholesterol change in randomized controlled trials involving LCDs, with a focus on body mass index (BMI) in kg/m 2 ., Methods: Three electronic indexes (Pubmed, EBSCO, and Scielo) were searched for studies between 1 January, 2003 and 20 December, 2022. Two independent reviewers identified randomized controlled trials involving adults consuming <130 g/d carbohydrate and reporting BMI and LDL cholesterol change or equivalent data. Two investigators extracted relevant data, which were validated by other investigators. Data were analyzed using a random-effects model and contrasted with results of pooled individual participant data., Results: Forty-one trials with 1379 participants and a mean intervention duration of 19.4 wk were included. In a meta-regression accounting for 51.4% of the observed variability on LCDs, mean baseline BMI had a strong inverse association with LDL cholesterol change [β = -2.5 mg/dL/BMI unit, 95% confidence interval (CI): -3.7, -1.4], whereas saturated fat amount was not significantly associated with LDL cholesterol change. For trials with mean baseline BMI <25, LDL cholesterol increased by 41 mg/dL (95% CI: 19.6, 63.3) on the LCD. By contrast, for trials with a mean of BMI 25-<35, LDL cholesterol did not change, and for trials with a mean BMI ≥35, LDL cholesterol decreased by 7 mg/dL (95% CI: -12.1, -1.3). Using individual participant data, the relationship between BMI and LDL cholesterol change was not observed on higher-carbohydrate diets., Conclusions: A substantial increase in LDL cholesterol is likely for individuals with low but not high BMI with consumption of an LCD, findings that may help guide individualized nutritional management of cardiovascular disease risk. As carbohydrate restriction tends to improve other lipid and nonlipid risk factors, the clinical significance of isolated LDL cholesterol elevation in this context warrants investigation. This trial was registered at PROSPERO as CRD42022299278., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Worldwide dietary guidelines in the late 20th century promoted a low-fat diet, based, in part, on the notion that dietary fat, the most energy dense macronutrient, causes excess weight gain. However, high-quality evidence accumulating since then refute a direct association between dietary fat and adiposity. Moreover, substitution of carbohydrates for unsaturated fat can increase insulin resistance and cardiometabolic disease, especially among populations with highly prevalent insulin resistance. In this context, the recent WHO conditional recommendation to carry forward the guidance to limit dietary fat to ≤30% seems ill advised and should be reconsidered., (Copyright © 2023 American Society for Nutrition. Published by Elsevier Inc. All rights reserved.)

On September 7 and 8, 2022, Healthy Environment and Endocrine Disruptors Strategies, an Environmental Health Sciences program, convened a scientific workshop of relevant stakeholders involved in obesity, toxicology, or obesogen research to review the state of the science regarding the role of obesogenic chemicals that might be contributing to the obesity pandemic. The workshop's objectives were to examine the evidence supporting the hypothesis that obesogens contribute to the etiology of human obesity; to discuss opportunities for improved understanding, acceptance, and dissemination of obesogens as contributors to the obesity pandemic; and to consider the need for future research and potential mitigation strategies. This report details the discussions, key areas of agreement, and future opportunities to prevent obesity. The attendees agreed that environmental obesogens are real, significant, and a contributor at some degree to weight gain at the individual level and to the global obesity and metabolic disease pandemic at a societal level; moreover, it is at least, in theory, remediable., (Copyright © 2023 American Society for Nutrition. All rights reserved.)

Background: Recent 3-dimensional optical (3DO) imaging advancements have provided more accessible, affordable, and self-operating opportunities for assessing body composition. 3DO is accurate and precise in clinical measures made by DXA. However, the sensitivity for monitoring body composition change over time with 3DO body shape imaging is unknown., Objectives: This study aimed to evaluate the ability of 3DO in monitoring body composition changes across multiple intervention studies., Methods: A 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 the 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, which were used to predict whole-body and regional body composition values using published equations. Body composition changes (follow-up minus the baseline) were compared with those of DXA using a linear regression analysis., Results: The analysis included 133 participants (45 females) in 6 studies. The mean (SD) length of follow-up was 13 (5) wk (range: 3-23 wk). Agreement between 3DO and DXA (R 2 ) for changes in total FM, total FFM, and appendicular lean mass were 0.86, 0.73, and 0.70, with root mean squared errors (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, respectively. Further adjustment with demographic descriptors improved the 3DO change agreement to changes observed with DXA., Conclusions: Compared with 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. This trial was registered at clinicaltrials.gov as NCT03637855 (Shape Up! Adults; https://clinicaltrials.gov/ct2/show/NCT03637855); NCT03394664 (Macronutrients and Body Fat Accumulation: A Mechanistic Feeding Study; https://clinicaltrials.gov/ct2/show/NCT03394664); NCT03771417 (Resistance Exercise and Low-Intensity Physical Activity Breaks in Sedentary Time to Improve Muscle and Cardiometabolic Health; https://clinicaltrials.gov/ct2/show/NCT03771417); NCT03393195 (Time Restricted Eating on Weight Loss; https://clinicaltrials.gov/ct2/show/NCT03393195), and NCT04120363 (Trial of Testosterone Undecanoate for Optimizing Performance During Military Operations; https://clinicaltrials.gov/ct2/show/NCT04120363)., (Copyright © 2023 American Society for Nutrition. All rights reserved.)

Background: The Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) trial demonstrated that meaningful weight loss can be achieved with either a "healthy low-carbohydrate diet" (LCD) or "healthy low-fat diet" (LFD). However, because both diets substantially decreased glycemic load (GL), the dietary factors mediating weight loss remain unclear., Objectives: We aimed to explore the contribution of macronutrients and GL to weight loss in DIETFITS and examine a hypothesized relationship between GL and insulin secretion., Design: This study is a secondary data analysis of the DIETFITS trial, in which participants with overweight or obesity (aged 18-50 y) were randomized to a 12-mo LCD (N = 304) or LFD (N = 305)., Results: Measures related to carbohydrate intake (total amount, glycemic index, added sugar, and fiber) showed strong associations with weight loss at 3-, 6-, and 12-mo time points in the full cohort, whereas those related to total fat intake showed weak to no associations. A biomarker of carbohydrate (triglyceride/HDL cholesterol ratio) predicted weight loss at all time points (3-mo: β [kg/biomarker z-score change] = 1.1, P = 3.5 × 10 -9 ; 6-mo: β = 1.7, P = 1.1 × 10 -9 ; and 12-mo: β = 2.6, P = 1.5 × 10 -15 ), whereas that of fat (low-density lipoprotein cholesterol + HDL cholesterol) did not (all time points: P = NS). In a mediation model, GL explained most of the observed effect of total calorie intake on weight change. Dividing the cohort into quintiles of baseline insulin secretion and GL reduction revealed evidence of effect modification for weight loss, with P = 0.0009 at 3 mo, P = 0.01 at 6 mo, and P = 0.07 at 12 mo., Conclusions: As predicted by the carbohydrate-insulin model of obesity, weight loss in both diet groups of DIETFITS seems to have been driven by the reduction of GL more so than dietary fat or calories, an effect that may be most pronounced among those with high insulin secretion. These findings should be interpreted cautiously in view of the exploratory nature of this study., Trial Registration: ClinicalTrials.gov (NCT01826591)., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

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., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

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 Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

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., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Background: Obesity has one of the highest refractory rates of all chronic diseases, in part because weight loss induced by calorie restriction, the first-line treatment for obesity, elicits biological adaptations that promote weight regain. Although acute feeding trials suggest a role for macronutrient composition in modifying brain activity related to hunger and satiety, relevance of these findings to weight-loss maintenance has not been studied., Objectives: We investigated effects of weight-loss maintenance diets varying in macronutrient content on regional cerebral blood flow (rCBF) in brain regions involved in hunger and reward., Methods: In conjunction with a randomized controlled feeding trial, we investigated the effects of weight-loss maintenance diets varying in carbohydrate content [high, 60% of total energy: n = 20; 6 men/14 women; mean age: 32.5 y; mean BMI (in kg/m 2): 27.4; moderate, 40% of total energy: n = 22; 10 men/12 women; mean age: 32.5 y; mean BMI: 29.0; low, 20% of total energy: n = 28; 12 men/16 women; mean age: 33.2 y; mean BMI: 27.7] on rCBF in brain regions involved in hunger and reward preprandial and 4 h postprandial after 14-20 wk on the diets. The primary outcome was rCBF in the nucleus accumbens (NAcc) at 4 h postprandial; the secondary outcome was preprandial rCBF in the hypothalamus., Results: Consistent with a priori hypothesis, at 4 h postprandial, NAcc rCBF was 43% higher in adults assigned to the high- compared with low-carbohydrate diet {P[family-wise error (FWE)-corrected] < 0.05}. Preprandial hypothalamus rCBF was 41% higher on high-carbohydrate diet [P(FWE-corrected) < 0.001]. Exploratory analyses revealed that elevated rCBF on high-carbohydrate diet was not specific to prandial state: preprandial NAcc rCBF [P(FWE-corrected) < 0.001] and 4 h postprandial rCBF in hypothalamus [P(FWE-corrected) < 0.001]. Insulin secretion predicted differential postprandial activation of the NAcc by diet., Conclusions: We report significant differences in rCBF in adults assigned to diets varying in carbohydrate content for several months, which appear to be partially associated with insulin secretion. These findings suggest that chronic intake of a high-carbohydrate diet may affect brain reward and homeostatic activity in ways that could impede weight-loss maintenance. This trial was registered at clinicaltrials.gov as NCT02300857., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

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 < 0.001). Among 23 shorter trials, TEE was reduced on lower-carbohydrate diets (-50.0 kcal/d; 95% CI: -77.4, -22.6 kcal/d) with substantial heterogeneity (I2 = 69.8). Among 6 longer trials, TEE was increased on low-carbohydrate diets (135.4 kcal/d; 95% CI: 72.0, 198.7 kcal/d) with low heterogeneity (I2 = 26.4). Expressed per 10% decrease in carbohydrate as %EI, the TEE effects in shorter and longer trials were -14.5 kcal/d and 50.4 kcal/d, respectively. Findings were materially unchanged in sensitivity analyses., Conclusions: Lower-carbohydrate diets transiently reduce TEE, with a larger increase after ∼2.5 wk. These findings highlight the importance of longer trials to understand chronic macronutrient effects and suggest a mechanism whereby lower-carbohydrate diets may facilitate weight loss., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Society for Nutrition.)

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., (Copyright © The Author(s) on behalf of the American Society for Nutrition 2020.)

Low- and very-low-carbohydrate diets have long attracted popular interest in the US and variably throughout the world. The potential value of these diets was recognized recently in a Consensus Report from the American Diabetes Association and expanded in a Scientific Statement from the National Lipid Association. Scientific evidence remains incomplete, but is beginning to catch up with popular trends. In this JCL Roundtable, 3 experts discuss the evidence behind these diets, their current place in nutrition practice, and areas needing more study. The carbohydrate-insulin model of obesity is presented as one explanation for dietary effectiveness. Ongoing research will delineate this model further. The experts, all clinicians, give practical advice for when and how to incorporate low-carbohydrate principles into dietary counseling., (Copyright © 2020. Published by Elsevier Inc.)

For >50 y, dietary guidelines in the United States have focused on reducing intakes of saturated and total fat. However, rates of obesity and diabetes rose markedly throughout this period, with potentially catastrophic implications for public health and the economy. Recently, ketogenic diets have received substantial attention from the general public and nutrition research community. These very-low-carbohydrate diets, with fat comprising >70% of calories, have been dismissed as fads. However, they have a long history in clinical medicine and human evolution. Ketogenic diets appear to be more effective than low-fat diets for treatment of obesity and diabetes. In addition to the reductions in blood glucose and insulin achievable through carbohydrate restriction, chronic ketosis might confer unique metabolic benefits of relevance to cancer, neurodegenerative conditions, and other diseases associated with insulin resistance. Based on available evidence, a well-formulated ketogenic diet does not appear to have major safety concerns for the general public and can be considered a first-line approach for obesity and diabetes. High-quality clinical trials of ketogenic diets will be needed to assess important questions about their long-term effects and full potential in clinical medicine., (Copyright © The Author(s) 2019.)

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 65years were randomly assigned to one of three test diets for weight-loss maintenance through 20weeks (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., (Copyright © 2017 Elsevier Inc. All rights reserved.)

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/m 2 ; 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., (© 2017 American Society for Nutrition.)

Background: Dietary guidelines recommend interchanging protein foods (e.g., chicken for red meat), but they may be exchanged for carbohydrate-rich foods varying in quality [glycemic load (GL)]. Whether such exchanges occur and how they influence long-term weight gain are not established., Objective: Our objective was to determine how changes in intake of protein foods, GL, and their interrelationship influence long-term weight gain., Design: We investigated the association between 4-y changes in consumption of protein foods, GL, and their interaction with 4-y weight change over a 16- to 24-y follow-up, adjusted for other lifestyle changes (smoking, physical activity, television watching, sleep duration), body mass index, and all dietary factors simultaneously in 3 prospective US cohorts (Nurses' Health Study, Nurses' Health Study II, and Health Professionals Follow-Up Study) comprising 120,784 men and women free of chronic disease or obesity at baseline., Results: Protein foods were not interchanged with each other (intercorrelations typically <|0.05|) but with carbohydrate (negative correlation as low as -0.39). Protein foods had different relations with long-term weight gain, with positive associations for meats, chicken with skin, and regular cheese (per increased serving/d, 0.13-1.17 kg; P = 0.02 to P < 0.001); no association for milk, legumes, peanuts, or eggs (P > 0.40 for each); and relative weight loss for yogurt, peanut butter, walnuts, other nuts, chicken without skin, low-fat cheese, and seafood (-0.14 to -0.71 kg; P = 0.01 to P < 0.001). Increases in GL were independently associated with a 0.42-kg greater weight gain per 50-unit increase (P < 0.001). Significant interactions (P-interaction < 0.05) between changes in protein foods and GL were identified; for example, increased cheese intake was associated with weight gain when GL increased, with weight stability when GL did not change, and with weight loss when exchanged for GL (i.e., decrease in GL)., Conclusion: Protein foods were commonly interchanged with carbohydrate, and changes in protein foods and GL interacted to influence long-term weight gain., (© 2015 American Society for Nutrition.)

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 ± SE: 4.7 ± 0.14 compared with 5.3 ± 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.

Background: In Hispanic children and adolescents, the prevalence of obesity and insulin resistance is considerably greater than in non-Hispanic white children. A low-glycemic load diet (LGD) has been proposed as an effective dietary intervention for pediatric obesity, but to our knowledge, no published study has examined the effects of an LGD in obese Hispanic children., Objective: We compared the effects of an LGD and a low-fat diet (LFD) on body composition and components of metabolic syndrome in obese Hispanic youth., Design: Obese Hispanic children (7-15 y of age) were randomly assigned to consume an LGD or an LFD in a 2-y intervention program. Body composition and laboratory assessments were obtained at baseline and 3, 12, and 24 mo after intervention., Results: In 113 children who were randomly assigned, 79% of both groups completed 3 mo of treatment; 58% of LGD and 55% of LFD subjects attended 24-mo follow-up. Compared with the LFD, the LGD decreased the glycemic load per kilocalories of reported food intakes in participants at 3 mo (P = 0.02). Both groups had a decreased BMI z score (P < 0.003), which was expressed as a standard z score relative to CDC age- and sex-specific norms, and improved waist circumference and systolic blood pressure (P < 0.05) at 3, 12, and 24 mo after intervention. However, there were no significant differences between groups for changes in BMI, insulin resistance, or components of metabolic syndrome (all P > 0.5)., Conclusions: We showed no evidence that an LGD and an LFD differ in efficacy for the reduction of BMI or aspects of metabolic syndrome in obese Hispanic youth. Both diets decreased the BMI z score when prescribed in the context of a culturally adapted, comprehensive weight-reduction program.

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.

Background: Little is known about the joint association between glycemic index (GI), glycemic load (GL), and alcohol intake with type 2 diabetes (T2D)., Objective: The objective of this study was to examine whether alcohol intake alters the associations between carbohydrate quality (GI) or quality and quantity (GL) and T2D incidence in women., Design: Participants from the Nurses' Health Study who were free of T2D, cardiovascular disease, or cancer (n = 81,827) at baseline in 1980 were followed for 26 y. Cumulative averages of GI, GL, total carbohydrates, and alcohol intake were calculated every 2-4 y from validated food-frequency questionnaires. Cox proportional hazard models were used to adjust for covariates., Results: We documented 6950 cases of T2D during follow-up. After adjustment for lifestyle and dietary factors, the positive association between GL and T2D risk was attenuated in subjects with higher alcohol intakes. RRs that compared the top and bottom quintiles of GL were 1.29 (95% CI: 1.11, 1.49; P-trend < 0.001) in women with alcohol intakes of 0 to <5 g/d, 1.34 (95% CI: 0.93, 1.92; P-trend = 0.05) in women with alcohol intakes of 5 to <15 g/d, and 0.99 (95% CI: 0.60, 1.65; P-trend = 0.82) in women with alcohol intakes ≥15 g/d (P-interaction = 0.02). However, a higher intake of alcohol did not modify the positive association between GI and T2D (P-interaction = 0.76)., Conclusion: Our findings suggest that a higher alcohol intake (≥15 g/d) attenuates the positive association between GL and T2D incidence.

Background: The optimal diet for pregnancy that is complicated by excessive weight is unknown., Objective: We aimed to examine the effects of a low-glycemic load (low-GL) diet in overweight and obese pregnant women., Design: We randomly assigned 46 overweight or obese pregnant women to receive a low-GL or a low-fat diet. Participants received carbohydrate-rich foods, fats, and snack foods through home delivery or study visits. The primary outcome was birth weight z score. Other endpoints included infant anthropometric measurements, gestational duration, maternal weight gain, and maternal metabolic parameters., Results: There were no significant differences in birth weight z score or other measures of infant adiposity between groups. However, in the low-GL compared with the low-fat group, gestational duration was longer (mean ± SD: 39.3 ± 1.1 compared with 37.9 ± 3.1 wk; P = 0.05) and fewer deliveries occurred at ≤ 38.0 wk (13% compared with 48%, P = 0.02; with exclusion of planned cesarean deliveries: 5% compared with 53%; P = 0.002). Adjusted head circumference was greater in the low-GL group (35.0 ± 0.8 compared with 34.2 ± 1.3 cm, P = 0.01). Women in the low-GL group had smaller increases in triglycerides [median (interquartile range): 49 (19, 70) compared with 93 (34, 129) mg/dL; P = 0.03] and total cholesterol [13 (0, 36) compared with 33 (22, 56) mg/dL, P = 0.04] and a greater decrease in C-reactive protein [-2.5 (-5.5, -0.7) compared with -0.4 (-1.4, 1.5) mg/dL, P = 0.007]., Conclusions: A low-GL diet resulted in longer pregnancy duration, greater infant head circumference, and improved maternal cardiovascular risk factors. Large-scale studies are warranted to evaluate whether dietary intervention during pregnancy aimed at lowering GL may be useful in the prevention of prematurity and other adverse maternal and infant outcomes. This trial is registered at clinicaltrials.gov as NCT00364403.

Background: Excessive weight gain during pregnancy seems to increase birthweight and the offspring's risk of obesity later in life. However, this association might be confounded by genetic and other shared effects. We aimed to examine the association between maternal weight gain and birthweight using state-based birth registry data that allowed us to compare several pregnancies in the same mother., Methods: In this population-based cohort study, we used vital statistics natality records to examine all known births in Michigan and New Jersey, USA, between Jan 1, 1989, and Dec 31, 2003. From an initial sample of women with more than one singleton birth in the database, we made the following exclusions: gestation less than 37 weeks or 41 weeks or more; maternal diabetes; birthweight less than 500 g or more than 7000 g; and missing data for pregnancy weight gain. We examined how differences in weight gain that occurred during two or more pregnancies for each woman predicted the birthweight of her offspring, using a within-subject design to reduce confounding to a minimum., Findings: Our analysis included 513 501 women and their 1 164 750 offspring. We noted a consistent association between pregnancy weight gain and birthweight (β 7·35, 95% CI 7·10-7·59, p<0·0001). Infants of women who gained more than 24 kg during pregnancy were 148·9 g (141·7-156·0) heavier at birth than were infants of women who gained 8-10 kg. The odds ratio of giving birth to an infant weighing more than 4000 g was 2·26 (2·09-2·44) for women who gained more than 24 kg during pregnancy compared with women who gained 8-10 kg., Interpretation: Maternal weight gain during pregnancy increases birthweight independently of genetic factors. In view of the apparent association between birthweight and adult weight, obesity prevention efforts targeted at women during pregnancy might be beneficial for offspring., Funding: US National Institutes of Health., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Background: During the nutrition transition in Chile, dietary changes were marked by increased consumption of high-energy, nutrient-poor products, including sugar-sweetened beverages (SSBs). Obesity is now the primary nutritional problem in posttransitional Chile., Objective: We conducted a randomized controlled trial to examine the effects on body composition of delivering milk beverages to the homes of overweight and obese children to displace SSBs., Design: We randomly assigned 98 children aged 8-10 y who regularly consumed SSBs to intervention and control groups. During a 16-wk intervention, children were instructed to drink 3 servings/d (approximately 200 g per serving) of the milk delivered to their homes and to not consume SSBs. Body composition was measured by dual-energy X-ray absorptiometry. Data were analyzed by multiple regression analysis according to the intention-to-treat principle., Results: For the intervention group, milk consumption increased by a mean (+/- SEM) of 452.5 +/- 37.7 g/d (P < 0.0001), and consumption of SSBs decreased by -711.0 +/- 33.7 g/d (P < 0.0001). For the control group, milk consumption did not change, and consumption of SSBs increased by 71.9 +/- 33.6 g/d (P = 0.04). Changes in percentage body fat, the primary endpoint, did not differ between groups. Nevertheless, the mean (+/- SE) accretion of lean body mass was greater (P = 0.04) in the intervention (0.92 +/- 0.10 kg) than in the control (0.62 +/- 0.11 kg) group. The increase in height was also greater (P = 0.01) in the intervention group (2.50 +/- 0.21 cm) than in the control group (1.77 +/- 0.20 cm) for boys but not for girls., Conclusion: Replacing habitual consumption of SSBs with milk may have beneficial effects on lean body mass and growth in children, despite no changes in percentage body fat. This trial was registered at clinicaltrials.gov as NCT00149695.

Background: Clinical trials of low-fat diets characteristically produce small mean long-term weight loss but a large interindividual variation in response. This variation has been attributed to psychological and behavioral factors, although biological differences may also play a role., Objective: The objective was to determine whether physiologic differences in insulin secretion explain differences in weight gain among individuals consuming low- and high-fat diets., Design: Of 276 individuals followed in the Quebec Family Study for a mean of 6 y, we compared those in the lowest with those in the highest dietary fat tertiles. We performed oral-glucose-tolerance tests at baseline and examined the insulin concentration at 30 min (insulin-30) as a proxy measure of insulin secretion. Six-year changes in body weight and waist circumference were the primary endpoints. We determined the associations between insulin-30 and the primary endpoints by linear regression analysis, with adjustment for potentially confounding factors., Results: Mean changes in body weight and waist circumference did not differ significantly between the lowest- and highest-fat diet groups. However, these endpoints were strongly associated with insulin-30, especially among individuals consuming the lowest-fat diet. Insulin-30 at baseline was significantly associated with 6-y weight gain (r = 0.51, P < 0.0001) and change in waist circumference (r = 0.55, P < 0.0001) in the lowest diet fat, group [corrected], but not in the highest diet fat group (r = 0.18, P = 0.086 and r = 0.20, P = 0.058, respectively) [corrected] Individuals in the highest insulin-30 and lowest dietary fat group gained 1.8 kg more than did those in the highest insulin-30 and highest dietary fat group (51%; P = 0.034); they gained 4.5 kg more than did those in the lowest insulin-30 and lowest dietary fat group (6.5-fold; P = 0.0026)., Conclusion: A proxy measure of insulin secretion strongly predicts changes in body weight and waist circumference over 6 y in adults, especially among those consuming lower-fat diets, which demonstrates the existence of a novel diet-phenotype interaction.

Objective: The American Diabetes Association (ADA) recommends screening children at risk for type 2 diabetes with a fasting plasma glucose test or an oral glucose tolerance test. The purpose of this study was to describe attitudes, barriers, and practices related to type 2 diabetes screening in children among pediatric clinicians., Methods: Pediatricians, nurse practitioners and physician assistants from a multispecialty, group practice in Eastern Massachusetts completed a mailed survey. To assess screening practice, three vignettes were presented representing pediatric patients with low, moderately high, and high risk for type 2 diabetes. The moderately high-risk and high-risk patients met ADA criteria for screening. ADA-consistent practice was defined as only screening the moderately high-risk and high-risk patients; lower-threshold practice was defined as also screening the low-risk patient; and higher threshold practice was screening only the high-risk patient., Results: Sixty-two of 90 clinicians responded (69%). Based on intent to screen in the 3 vignettes, 21% of respondents reported ADA-consistent screening practice, 39% lower-threshold, and 35% higher-threshold screening practice. Five percent had incomplete or nonclassifiable responses. Many clinicians ordered screening tests other than those recommended by the ADA; few (< or =8% in any vignette) ordered only an ADA-recommended test. Preferences for nonfasting tests were influenced by nonmedical factors such as access to or cost of transportation. Inadequate patient education materials and unclear recommendations for appropriate screening methods were the most frequently reported moderate/strong barriers to screening., Conclusions: Most respondents reported type 2 diabetes screening practices that differed from current ADA recommendations. Our findings suggest that type 2 diabetes screening tests must be practical for clinicians and patients if they are to be used in pediatric practice. Further study of the benefits and cost-effectiveness of type 2 diabetes screening in children is warranted to clarify the role and optimal methods for screening in pediatric primary care.

Background: The optimal nutritional approach for the prevention of cardiovascular disease among obese persons remains a topic of intense controversy. Available approaches range from conventional low-fat to very-low-carbohydrate diets., Objective: The aim of this pilot study was to evaluate the efficacy of an ad libitum low-glycemic load diet, without strict limitation on carbohydrate intake, as an alternative to a conventional low-fat diet., Design: A randomized controlled trial compared 2 dietary treatments in obese young adults (n = 23) over 12 mo. The experimental treatment emphasized ad libitum consumption of low-glycemic-index foods, with 45-50% of energy from carbohydrates and 30-35% from fat. The conventional treatment was restricted in energy (250-500 kcal/d deficit) and fat (<30% of energy), with 55-60% of energy from carbohydrate. We compared changes in study outcomes by repeated-measures analysis of log-transformed data and expressed the results as mean percentage change., Results: Body weight decreased significantly over a 6-mo intensive intervention in both the experimental and conventional diet groups (-8.4% and -7.8%, respectively) and remained below baseline at 12 mo (-7.8% and -6.1%, respectively). The experimental diet group showed a significantly greater mean decline in plasma triacylglycerols than did the conventional diet group (-37.2% and -19.1%, respectively; P = 0.005). Mean plasminogen activator inhibitor 1 concentrations decreased (-39.0%) in the experimental diet group but increased (33.1%) in the conventional diet group (P = 0.004). Changes in cholesterol concentrations, blood pressure, and insulin sensitivity did not differ significantly between the groups., Conclusion: An ad libitum low-glycemic load diet may be more efficacious than a conventional, energy-restricted, low-fat diet in reducing cardiovascular disease risk.

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<0.0001), with a weaker association recorded in black people (p=0.1004). Changes were also directly associated with insulin resistance in both ethnic groups (p=0.0015 in black people, p<0.0001 in white people). By comparison with the average 15-year weight gain in participants with infrequent (less than once a week) fast-food restaurant use at baseline and follow-up (n=203), those with frequent (more than twice a week) visits to fast-food restaurants at baseline and follow-up (n=87) gained an extra 4.5 kg of bodyweight (p=0.0054) and had a two-fold greater increase in insulin resistance (p=0.0083)., Interpretation: Fast-food consumption has strong positive associations with weight gain and insulin resistance, suggesting that fast food increases the risk of obesity and type 2 diabetes.