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

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

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

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.

Carbohydrate restriction, used since the 1700s to prolong survival in people with diabetes, fell out of favor after the discovery of insulin. Despite costly pharmacological and technological developments in the last few decades, current therapies do not achieve optimal outcomes, and most people with diabetes remain at high risk for micro- and macrovascular complications. Recently, low-carbohydrate diets have regained popularity, with preliminary evidence of benefit for body weight, postprandial hyperglycemia, hyperinsulinemia, and other cardiometabolic risk factors in type 2 diabetes and, with more limited data, in type 1 diabetes. High-quality, long-term trials are needed to assess safety concerns and determine whether this old dietary approach might help people with diabetes attain clinical targets more effectively, and at a lower cost, than conventional treatment.

Researchers have become increasingly concerned with the relation between traditional ecological knowledge (TEK) and academic ecological knowledge (AEK). TEK includes complex predictive resources that often remain insufficiently reflected in ecological research, conservation practices, and ecosystem services. At the same time, knowledge integration comes with methodological and political challenges of negotiating differences between knowledge systems. In this article, we provide evidence from different scales (population, community, and ecosystems) about how TEK and AEK can be related when addressing the same phenomena. Finally, we discuss the possibilities of relating TEK and AEK through a perspective of complementarity of knowledge, taking existing differences as opportunities for dialogue.

"This book develops an integrated perspective on the practices and politics of making knowledge work in inclusive development and innovation. While debates about development and innovation commonly appeal to the authority of academic researchers, many current approaches emphasize the plurality of actors with relevant expertise for addressing livelihood challenges. Adopting an action-oriented and reflexive approach, this volume explores the variety of ways in which knowledge works, paying particular attention to dilemmas and controversies. The six parts of the book address the complex interplay of knowledge and politics, starting with the need for knowledge integration in the first part and decolonial perspectives on the politics of knowledge integration in the second part. The following three parts focus on the practices of inclusive development and innovation through three major themes of transformative learning, evidence, and digitization. The final part of the book addresses the governance of knowledge and innovation in the light of political struggles about inclusivity. Exploring conceptual and practical themes through case studies from the Global North and South, this book will be of great interest to students, scholars and practitioners researching and working in development studies, epistemology, innovation studies, science and technology studies and sustainability studies more broadly"

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.

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.

The heterogeneous disease course of COVID-19 is unpredictable, ranging from mild self-limiting symptoms to cytokine storms, acute respiratory distress syndrome (ARDS), multi-organ failure and death. Identification of high-risk cases will enable appropriate intervention and escalation. This study investigates the routine laboratory tests and cytokines implicated in COVID-19 for their potential application as biomarkers of disease severity, respiratory failure and need of higher-level care.From analysis of 203 samples, CRP, IL-6, IL-10 and LDH were most strongly correlated with the WHO ordinal scale of illness severity, the fraction of inspired oxygen delivery, radiological evidence of ARDS and level of respiratory support (p≤0.001). IL-6 levels of ≥3.27pg/ml provide a sensitivity of 0.87 and specificity of 0.64 for a requirement of ventilation, and a CRP of ≥37mg/L of 0.91 and 0.66.Reliable stratification of high-risk cases has significant implications on patient triage, resource management and potentially the initiation of novel therapies in severe patients.

In Part II of the book we asked why RRI develops differently in different national contexts. We argued that this is because RRI can be regarded as a model of the relation between science and society. As all studied countries have established STI systems, all of them have different imaginaries that cover this relationship, though these are not always fully explicit. National imaginaries have different features for different reasons. They cannot simply be ordered on a linear scale of ‘progression’ towards RRI (Mejlgaard et al. 2018). RRI promotors have to engage with these imaginaries in order to properly align RRI with them. We have illustrated our claim by studying twelve countries’ sociotechnical imaginaries on STI in Chap. 7, using RRI-Practice’s national reports as data. In this chapter we compare and abstract from the national sociotechnical imaginaries on STI. While some policy goals and participation models are common across many countries, there are also salient differences with regards to policy goals, framings of the responsibilities of scientists, administrative styles and public participation goals and mechanisms. We sketch salient differences and how they matter for the implementation of the ‘RRI model’.

In this chapter, we build on and extend the discussion on how we may further the implementation of Responsible Research and Innovation across types of organizations. We consider first the structure of universities as a driver and barrier for RRI, using Mintzberg’s study on the structure of organisations with an emphasis on expert bureaucracies; second, we consider academic culture as a barrier and opportunity for RRI, using Schein’s layered model of organizational culture; and third, we discuss isomorphism and the role of funding organisations as a salient environment for research performing organisations, using core insights from neo-institutional theory.

In this Chapter, we give an overview of the book and the RRI-Practice study. The book is an analysis of data collected in the RRI-Practice study. It comprises an organizational analysis and an analysis of national discourses, thus analysing conditions for the uptake of RRI in research funding and research performing organisations in the science system.

In this Chapter, we give an overview of drivers furthering the implementation of RRI. We analyse drivers as structural, cultural and interchange related, using a framework derived from neo-institutional theory. We include a discussion based on types of organisation (such as research funding versus performing organisation) and we provide overall reflections the role of on drivers in implementing RRI.

In this Chapter, we give an overview of structural, cultural and interchange related barriers to implementing RRI in organisations, using a framework derived from neo-institutional theory. We discuss barriers related to different types of organisations, such as research funding and research performing organisations. Finally, we provide overall reflections on the role of barriers, and discuss how barriers to RRI intersect.

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

High vs. low glycemic index (GI) foods elicit late postprandial activation of mesolimbic brain areas, which may contribute to the associated increases in hunger, food intake and cravings. It is unknown whether changes in blood glucose or higher insulin levels mediate this activation and its potential adverse downstream effects. Fifteen men with T1D, mean (SD) BMI 21 (1.4) kg/m2, aged 21 (1.6) yr underwent three conditions in random order: C1 - high GI (GI=84) meal with IV insulin to maintain euglycemia; C2 - macronutrient matched low GI (37) meal with IV insulin to maintain euglycemia; C3 - high GI meal with IV insulin to match C2. Insulin was algorithmically adjusted for 4.5 hr with blood glucose checks every 5 min. Brain imaging (arterial spin labeling) was obtained at baseline, in the early (1 hr) and late (4 hr) postprandial period. This design allowed us to compare high vs. low GI meals with similar glucose response (incremental area under the curve 192 [22] vs. 41 [12], p=0.6) but different insulin doses (25 [2] vs. 17 [1] units, p=0.003; C1 vs. C2) or similar insulin doses (17 [1] units each, p=0.5) with different glucose response (1257 [37] vs. 41 [12] mg/dl*h, p Disclosure B.S. Lennerz: None. F. Munsch: None. D.C. Alsop: Other Relationship; Self; General Electric, Hitachi America, Ltd., Philips Healthcare, Siemens Corporation. G.M. Steil: Consultant; Self; Eli Lilly and Company. D.C. Simonson: Stock/Shareholder; Self; GI Windows. Stock/Shareholder; Spouse/Partner; Phase V Technologies, Inc. D.S. Ludwig: None.

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.

Milk and Health This review summarizes the evidence for the benefits and possible risks associated with consumption of cow’s milk. The authors describe the relationship of milk consumption to the r...

For decades, dietary advice was based on the premise that high intakes of fat cause obesity, diabetes, heart disease, and possibly cancer. Recently, evidence for the adverse metabolic effects of processed carbohydrate has led to a resurgence in interest in lower-carbohydrate and ketogenic diets with high fat content. However, some argue that the relative quantity of dietary fat and carbohydrate has little relevance to health and that focus should instead be placed on which particular fat or carbohydrate sources are consumed. This review, by nutrition scientists with widely varying perspectives, summarizes existing evidence to identify areas of broad consensus amid ongoing controversy regarding macronutrients and chronic disease.

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

Preliminary data suggest that people with obesity are at increased risk of severe COVID-19. However, as data on metabolic parameters (such as BMI and levels of glucose and insulin) in patients with COVID-19 are scarce, increased reporting is needed to improve our understanding of COVID-19 and the care of affected patients.

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.

High compared to low glycemic index (GI) foods elicit larger glycemic and insulinemic excursions, and are associated with lower satiety. However, it is unclear whether the satiety effect is attributable to differences in glycemia or insulinemia, and whether insulin delivery in individuals with T1D could be optimized for satiety per se. Fifteen men with T1D, BMI 25 (SD 3) kg/m2, aged 23 (5) years, HbA1c 7.4 (0.7)% underwent three experimental conditions in a randomized cross-over design: High GI, high insulin (HGI/HI): meal GI of 84 with intravenous insulin (IVI) to maintain euglycemia; Low GI (LGI): meal GI of 37 with IVI to maintain euglycemia (comparison condition); High GI, low insulin (HGI/LI): high GI meal as above with IVI matched to LGI. Test meals provided 25% of daily calories (60% carbohydrate, 15% protein, 25% fat). IVI was adjusted using a PID algorithm with blood glucose measurements every 5 minutes for 4.5 hr. When using matched insulin doses, blood glucose area under the curve (AUC) was 789 (145) vs. 493 (48) mg/dl*h (p Disclosure B.S. Lennerz: None. D.C. Simonson: Stock/Shareholder; Self; GI Windows, Inc. Stock/Shareholder; Spouse/Partner; Phase V Technologies, Inc. G.M. Steil: Consultant; Self; Eli Lilly and Company, Profusa, Inc. D.S. Ludwig: Other Relationship; Self; Various publishers. Funding National Institute of Diabetes and Digestive and Kidney Diseases (K12DK094721, K24DK082730)

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

Summary We aimed to reduce attrition of newly referred patients in a paediatric weight management programme by implementing an orientation to address families’ expectations and screen for and support behavioural and mental health problems and psychosocial stressors at programme outset. Orientation impact was monitored with run charts with percentages of scheduled encounters completed. Long-term impact was assessed by comparing patients in the initial 6 months of the orientation to a baseline group of referred patients during the same 6-month time interval in the prior year (Pre-Orientation Group). The outcome measure was programme attrition within 15 months. Groups were compared using Kaplan–Meier survival analysis and Cox proportional hazards regression modelling. Patients in the Orientation Group had a 23% increased odds of attrition compared to patients in the Pre-Orientation group (adjusted Hazard ratio, aHR 1.23; 95% confidence interval, CI: 1.01, 1.51) and shorter median duration of follow-up (2.0 vs. 2.9 months, P = 0.004). An increase in body mass index z-score of 1 unit resulted in a nearly fivefold increased odds of attrition (aHR 5.24; 95% CI: 2.95, 9.3). An orientation for new patients did not reduce attrition within 15 months. We suggest that ongoing retention strategies should be embedded into the treatment phase of the programme.

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.

After 35 years of unremittingly bad news about childhood obesity, a plateau in overall prevalence and a statistically significant decline among 2- to 5-year-olds had been suggested in national data from earlier this decade.1–3 News reports in 2014 celebrated “the first clear evidence that America’s youngest children have turned a corner in the obesity epidemic.”4 Perhaps Michelle Obama’s Let’s Move campaign, the Robert Wood Johnson Foundation’s $500 million prevention initiative, and growing public awareness had finally begun to pay off. Unfortunately, this optimistic picture was not to be, according to an article in this issue of Pediatrics . Using nationally representative data from 1999 to 2016, Skinner et al5 examined changes in body weight status (ranging from overweight to class III obesity [BMI ≥140% over the 95th percentile]) among children ages 2 to 19 years. The study revealed that obesity prevalence did not decrease for any age group and continued upward among many subgroups. Of particular concern, previously documented racial and ethnic disparities, especially at the most extreme weight categories, showed no sign of abating. For instance, class III obesity is … Address correspondence to David S. Ludwig, MD, PhD, Endocrinology, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115. E-mail: david.ludwig{at}childrens.harvard.edu

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.

This article uses the case study of ethnobiological classification to develop a positive and a negative thesis about the state of natural kind debates. On the one hand, I argue that current accounts of natural kinds can be integrated in a multidimensional framework that advances understanding of classificatory practices in ethnobiology. On the other hand, I argue that such a multidimensional framework does not leave any substantial work for the notion “natural kind” and that attempts to formulate a general account of naturalness have become an obstacle to understanding classificatory practices.

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

This study evaluated the feasibility of a home-based intervention to reduce sugar-sweetened beverage intake and television viewing among children. Lower income parents of overweight children aged 5-12 years (n = 40) were randomized to a home environment intervention to reduce television viewing with locking devices and displace availability of sugar-sweetened beverages with home delivery of non-caloric beverages (n = 25), or to a no-intervention control group (n = 15) for 6 months. Data were collected at baseline and 6 months. After 6 months, television viewing hours per day was significantly lower in the intervention group compared with the control group (1.7 [SE = .02] vs. 2.6 [SE = .25] hours/day, respectively, P

Summary Background Evidence is lacking to recommend one diet over another when treating polycystic ovary syndrome (PCOS). Objectives To obtain preliminary data, comparing the impact of a low-glycaemic load (LGL) vs. low-fat (LF) diet on biochemical hyperandrogenism in overweight and obese adolescents with PCOS. To ascertain feasibility of recruiting study participants, in partnership with an adolescent clinic, and implementing dietary interventions. Methods Randomized controlled trial of 19 overweight and obese adolescents with PCOS and not using hormonal contraceptives (HCs). Interventions comprised nutrition education, dietary counselling and cooking workshops to foster adherence to a LGL (45% carbohydrate, 35% fat, 20% protein) or LF (55% carbohydrate, 25% fat, 20% protein) diet over 6 months. Serum bioavailable testosterone was the primary outcome. Results Sixteen (LGL, n = 7; LF, n = 9) participants completed the study. Body fat percentage decreased (P

Background There are limited data regarding the timing of carbohydrate ingestion during a meal and postprandial glucose regulation. Methods Sixteen subjects with type 2 diabetes mellitus (T2DM) consumed the same meal on 3 days in random order: carbohydrate first, followed 10 min later by protein and vegetables; protein and vegetables first, followed 10 min later by carbohydrate; or all components together. Blood was sampled for glucose, insulin, glucagon-like peptide-1 (GLP-1), and glucagon measurements at baseline (just before meal ingestion) and subsequently at 30 min intervals up to 180 min. Results The incremental areas under the curve for glucose (iAUC0–180) and incremental glucose peaks were 53% and 54% lower, respectively, when carbohydrate was consumed last compared with carbohydrate consumed first (3124.7±501.2 vs 6703.5±904.6 mg/dL×180min, p

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

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