Search

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 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.

The burden of diabetes and heart disease falls disproportionately on racial and ethnic minority groups in many developed nations. African Americans and Hispanics in the United States develop diabetes or die of heart disease at rates 50– 100% greater than Caucasians (1,2). Significant differences in socioeconomic status and conventional heart disease risk factors exist among racial/ethnic groups in the United States, Canada and the UK (3–6). However, these differences do not fully account for the observed disparities in disease prevalence (3–6), suggesting the presence of other biological factors. In recent years, attention has been focused on the importance of the insulin resistance syndrome (IRS, also called Syndrome X) as an underlying cause of both diabetes and heart disease (7,8). In this syndrome, insulin resistance and compensatory hyperinsulinemia place the pancreatic B-cell under chronic stress, and give rise to a variety of well known and novel heart disease risk factors, including glucose intolerance, hypertension, dyslipidemia, endothelial dysfunction, hypercoagulability and chronic inflammation. In the United States, the prevalence of IRS differs among racial/ethnic groups and increases with age, exceeding 40% in older adults (9,10). IRS has been noted in African-American children as young as 5 y of age (11). Obesity is a major cause of insulin resistance and, as a consequence, of IRS, although many genetic and lifestyle factors also affect insulin resistance (10,12–15). Thus, a fundamental issue in understanding disparities in diabetes and heart disease risk is how the natural history of IRS might differ among racial/ethnic groups. Data from the laboratories of Silva Arslanian (16) and Michael Goran (17) address this point. Firstand second-phase insulin responses were higher in African-American than in Caucasian children after adjusting for body mass index (BMI). Moreover, differences in insulin sensitivity and secretion between African-American and Caucasian children remained, after taking body composition, fat distribution, dietary patterns and physical activity level into account (17,18). In this context, the study by Dickinson et al. (19) in this issue of The Journal of Nutrition is of particular interest. The investigators fed 60 lean, healthy young adults from five racial/ ethnic groups white bread providing 75 g available carbohydrate, and measured changes in plasma glucose and insulin concentrations for a 2-h period. Mean fasting glucose concentrations were very similar among the groups. However, Southeast Asian and Chinese subjects showed markedly higher postprandial glycemia than European Caucasians, with 1.5to 2.0-fold higher mean incremental areas under the glucose curve. In fact, several Southeast Asian subjects had postprandial responses that would have met criteria for the diagnosis of impaired glucose tolerance. Mean incremental area under the insulin curve was 1.9to 2.7-fold higher among Southeast Asians, Chinese and Asian Indians compared with European Caucasians. The groups also differed significantly in insulin sensitivity, as assessed by homeostasis model assessment or the hyperinsulinemic euglycemic clamp technique; European Caucasians were most sensitive, whereas Southeast Asians were most resistant. The results do not appear to be attributable to the effects of sex, age, BMI or birth weight because these potentially confounding variables were either controlled for or matched among groups. These findings have three major implications. Abnormalities in glucose homeostasis are prevalent among individuals of certain racial/ethnic groups in the absence of obesity and advanced age, demonstrating an apparent predisposition to development of IRS. Pathophysiological abnormalities related to diabetes and heart disease risk may occur in apparently healthy individuals earlier than previously recognized. Also, measurements taken in fasting subjects may not reveal important abnormalities in glucose homeostasis, consistent with findings from a recent study of obese children (20). It is tempting to ascribe these racial/ethnic differences to genetic influences (21). Indeed, several genes or genetic loci have been identified that appear to increase risk for IRS in certain populations (22). However, other factors may also explain, at least in part, the present observations. Underor overnutrition at critical stages of fetal development appears to induce permanent changes in metabolism, neuroendocrine function or body composition that result in insulin resistance and B-cell dysfunction (23–25). It is especially noteworthy that intrauterine influences may be racial/ethnic group specific, in that low birth weight appears to increase risk for IRS in African Americans to a greater extent than in Caucasians (26). Duration of breast-feeding during infancy has been related to body composition later in life (27). A number of lifestyle factors may also affect risk for insulin resistance, independent of BMI, including diet (e.g., macronutrient composition, fiber, glycemic index, fatty acid profile and dairy consumption) (10,14,15,28–30), physical activity level and fitness (12) and perhaps psychosocial stress. As recognized by 1 Supported by grants from the National Institute of Diabetes, Digestive and Kidney Diseases (1R01DK59240) and the Charles H. Hood Foundation. 2 To whom correspondence should be addressed. E-mail: david.ludwig@tch.harvard.edu.