Effects of carbohydrate quantity and glycemic index on resting metabolic rate and body composition during weight loss.
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ABSTRACT:
SUBMITTER: Karl JP
PROVIDER: S-EPMC4634125 | biostudies-literature | 2015 Nov
REPOSITORIES: biostudies-literature
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Effects of carbohydrate quantity and glycemic index on resting metabolic rate and body composition during weight loss.
Karl J Philip JP Roberts Susan B SB Schaefer Ernst J EJ Gleason Joi A JA Fuss Paul P Rasmussen Helen H Saltzman Edward E Das Sai Krupa SK
Obesity (Silver Spring, Md.) 20151101 11
<h4>Objective</h4>To examine the effects of diets varying in carbohydrate and glycemic index (GI) on changes in body composition, resting metabolic rate (RMR), and metabolic adaptation during and after weight loss.<h4>Methods</h4>Adults with obesity (n = 91) were randomized to one of four provided-food diets for 17 weeks. Diets differed in percentage energy from carbohydrate (55% or 70%) and GI (low or high) but were matched for protein, fiber, and energy. Body weight, body composition, RMR, and ...[more]
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Project description:ObjectiveTo examine associations of baseline insulin dynamics with changes in body composition and resting energy expenditure (REE) following weight loss.MethodsTwenty-one participants with overweight or obesity achieved 10-15% weight loss and then received 3 weight loss maintenance diets (high-carbohydrate, moderate-carbohydrate, and low-carbohydrate) in random order, each for 4 weeks. Body composition was measured at baseline and after weight loss. Insulin 30 min after glucose consumption (insulin-30; insulin response), C-peptide deconvolution analysis, HOMA, hepatic insulin sensitivity (IS), and REE were assessed at baseline and after each maintenance diet.ResultsInsulin-30, but not maximal insulin secretion, hepatic IS, or HOMA, predicted changes in fat mass (standardized β = 0.385, 1.7 kg difference between 10th and 90th centile of insulin-30, P = 0.04) after weight loss. Insulin-30 (β = -0.341, -312 kcal day(-1) , P = 0.008), maximal insulin secretion (β = -0.216, -95 kcal day(-1) , P = 0.0002), HOMA (β = -0.394, -350 kcal day(-1) , P = 0.002), and hepatic IS (β = 0.217, 225 kcal day(-1) , P = 0.0003) predicted change in REE during weight loss maintenance, independent of changes in body composition. The inverse relationship between insulin-30 and REE was substantially attenuated when the low-carbohydrate diet was consumed first.ConclusionsThese findings distinguish a novel phenotype, characterized by high insulin response, at risk for weight regain, and identify a dietary approach to ameliorate this risk.
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Project description:Background: The potential endocrine-disrupting effects of perfluoroalkyl substances (PFASs) have been demonstrated in animal studies, but whether PFASs may interfere with body weight regulation in humans is largely unknown. This study aimed to examine the associations of PFAS exposure with changes in body weight and resting metabolic rate (RMR) in a diet-induced weight-loss setting.Methods and findings: In the 2-year POUNDS Lost randomized clinical trial based in Boston, Massachusetts, and Baton Rouge, Louisiana, that examined the effects of energy-restricted diets on weight changes, baseline plasma concentrations of major PFASs were measured among 621 overweight and obese participants aged 30-70 years. Body weight was measured at baseline and 6, 12, 18, and 24 months. RMR and other metabolic parameters, including glucose, lipids, thyroid hormones, and leptin, were measured at baseline and 6 and 24 months. Participants lost an average of 6.4 kg of body weight during the first 6 months (weight-loss period) and subsequently regained an average of 2.7 kg of body weight during the period of 6-24 months (weight regain period). After multivariate adjustment, baseline PFAS concentrations were not significantly associated with concurrent body weight or weight loss during the first 6 months. In contrast, higher baseline levels of PFASs were significantly associated with a greater weight regain, primarily in women. In women, comparing the highest to the lowest tertiles of PFAS concentrations, the multivariate-adjusted mean weight regain (SE) was 4.0 (0.8) versus 2.1 (0.9) kg for perfluorooctanesulfonic acid (PFOS) (Ptrend = 0.01); 4.3 (0.9) versus 2.2 (0.8) kg for perfluorooctanoic acid (PFOA) (Ptrend = 0.007); 4.7 (0.9) versus 2.5 (0.9) kg for perfluorononanoic acid (PFNA) (Ptrend = 0.006); 4.9 (0.9) versus 2.7 (0.8) kg for perfluorohexanesulfonic acid (PFHxS) (Ptrend = 0.009); and 4.2 (0.8) versus 2.5 (0.9) kg for perfluorodecanoic acid (PFDA) (Ptrend = 0.03). When further adjusted for changes in body weight or thyroid hormones during the first 6 months, results remained similar. Moreover, higher baseline plasma PFAS concentrations, especially for PFOS and PFNA, were significantly associated with greater decline in RMR during the weight-loss period and less increase in RMR during the weight regain period in both men and women. Limitations of the study include the possibility of unmeasured or residual confounding by socioeconomic and psychosocial factors, as well as possible relapse to the usual diet prior to randomization, which could have been rich in foods contaminated by PFASs through food packaging and also dense in energy.Conclusions: In this diet-induced weight-loss trial, higher baseline plasma PFAS concentrations were associated with a greater weight regain, especially in women, possibly explained by a slower regression of RMR levels. These data illustrate a potential novel pathway through which PFASs interfere with human body weight regulation and metabolism. The possible impact of environmental chemicals on the obesity epidemic therefore deserves attention.Trial registration: ClinicalTrials.gov NCT00072995.
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Project description:BackgroundThe quality of carbohydrate consumed, assessed by the glycemic index (GI), glycemic load (GL), or carbohydrate quality index (CQI), affects the postprandial glycemic and insulinemic responses, which have been implicated in the etiology of several chronic diseases. However, it is unclear whether plasma metabolites involved in different biological pathways could provide functional insights into the role of carbohydrate quality indices in health.ObjectivesWe aimed to identify plasma metabolomic profiles associated with dietary GI, GL, and CQI.MethodsThe present study is a cross-sectional analysis of 1833 participants with overweight/obesity (mean age = 67 y) from 2 case-cohort studies nested within the PREDIMED (Prevención con Dieta Mediterránea) trial. Data extracted from validated FFQs were used to estimate the GI, GL, and CQI. Plasma concentrations of 385 metabolites were profiled with LC coupled to MS and associations of these metabolites with those indices were assessed with elastic net regression analyses.ResultsA total of 58, 18, and 57 metabolites were selected for GI, GL, and CQI, respectively. Choline, cotinine, γ-butyrobetaine, and 36:3 phosphatidylserine plasmalogen were positively associated with GI and GL, whereas they were negatively associated with CQI. Fructose-glucose-galactose was negatively and positively associated with GI/GL and CQI, respectively. Consistent associations of 21 metabolites with both GI and CQI were found but in opposite directions. Negative associations of kynurenic acid, 22:1 sphingomyelin, and 38:6 phosphatidylethanolamine, as well as positive associations of 32:1 phosphatidylcholine with GI and GL were also observed. Pearson correlation coefficients between GI, GL, and CQI and the metabolomic profiles were 0.30, 0.22, and 0.27, respectively.ConclusionsThe GI, GL, and CQI were associated with specific metabolomic profiles in a Mediterranean population at high cardiovascular disease risk. Our findings may help in understanding the role of dietary carbohydrate indices in the development of cardiometabolic disorders. This trial was registered at isrctn.com as ISRCTN35739639.
| S-EPMC7779218 | biostudies-literature
Project description:BackgroundStudies of weight-control diets that are high in protein or low in glycemic index have reached varied conclusions, probably owing to the fact that the studies had insufficient power.MethodsWe enrolled overweight adults from eight European countries who had lost at least 8% of their initial body weight with a 3.3-MJ (800-kcal) low-calorie diet. Participants were randomly assigned, in a two-by-two factorial design, to one of five ad libitum diets to prevent weight regain over a 26-week period: a low-protein and low-glycemic-index diet, a low-protein and high-glycemic-index diet, a high-protein and low-glycemic-index diet, a high-protein and high-glycemic-index diet, or a control diet.ResultsA total of 1209 adults were screened (mean age, 41 years; body-mass index [the weight in kilograms divided by the square of the height in meters], 34), of whom 938 entered the low-calorie-diet phase of the study. A total of 773 participants who completed that phase were randomly assigned to one of the five maintenance diets; 548 completed the intervention (71%). Fewer participants in the high-protein and the low-glycemic-index groups than in the low-protein-high-glycemic-index group dropped out of the study (26.4% and 25.6%, respectively, vs. 37.4%; P=0.02 and P=0.01 for the respective comparisons). The mean initial weight loss with the low-calorie diet was 11.0 kg. In the analysis of participants who completed the study, only the low-protein-high-glycemic-index diet was associated with subsequent significant weight regain (1.67 kg; 95% confidence interval [CI], 0.48 to 2.87). In an intention-to-treat analysis, the weight regain was 0.93 kg less (95% CI, 0.31 to 1.55) in the groups assigned to a high-protein diet than in those assigned to a low-protein diet (P=0.003) and 0.95 kg less (95% CI, 0.33 to 1.57) in the groups assigned to a low-glycemic-index diet than in those assigned to a high-glycemic-index diet (P=0.003). The analysis involving participants who completed the intervention produced similar results. The groups did not differ significantly with respect to diet-related adverse events.ConclusionsIn this large European study, a modest increase in protein content and a modest reduction in the glycemic index led to an improvement in study completion and maintenance of weight loss. (Funded by the European Commission; ClinicalTrials.gov number, NCT00390637.).
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Project description:OBJECTIVE: To compare the effects of isocaloric, energy-restricted very low-carbohydrate ketogenic (VLCK) and low-fat (LF) diets on weight loss, body composition, trunk fat mass, and resting energy expenditure (REE) in overweight/obese men and women. DESIGN: Randomized, balanced, two diet period clinical intervention study. Subjects were prescribed two energy-restricted (-500 kcal/day) diets: a VLCK diet with a goal to decrease carbohydrate levels below 10% of energy and induce ketosis and a LF diet with a goal similar to national recommendations (%carbohydrate:fat:protein = ~60:25:15%). SUBJECTS: 15 healthy, overweight/obese men (mean +/- s.e.m.: age 33.2 +/- 2.9 y, body mass 109.1 +/- 4.6 kg, body mass index 34.1 +/- 1.1 kg/m2) and 13 premenopausal women (age 34.0 +/- 2.4 y, body mass 76.3 +/- 3.6 kg, body mass index 29.6 +/- 1.1 kg/m2). MEASUREMENTS: Weight loss, body composition, trunk fat (by dual-energy X-ray absorptiometry), and resting energy expenditure (REE) were determined at baseline and after each diet intervention. Data were analyzed for between group differences considering the first diet phase only and within group differences considering the response to both diets within each person. RESULTS: Actual nutrient intakes from food records during the VLCK (%carbohydrate:fat:protein = ~9:63:28%) and the LF (~58:22:20%) were significantly different. Dietary energy was restricted, but was slightly higher during the VLCK (1855 kcal/day) compared to the LF (1562 kcal/day) diet for men. Both between and within group comparisons revealed a distinct advantage of a VLCK over a LF diet for weight loss, total fat loss, and trunk fat loss for men (despite significantly greater energy intake). The majority of women also responded more favorably to the VLCK diet, especially in terms of trunk fat loss. The greater reduction in trunk fat was not merely due to the greater total fat loss, because the ratio of trunk fat/total fat was also significantly reduced during the VLCK diet in men and women. Absolute REE (kcal/day) was decreased with both diets as expected, but REE expressed relative to body mass (kcal/kg), was better maintained on the VLCK diet for men only. Individual responses clearly show the majority of men and women experience greater weight and fat loss on a VLCK than a LF diet. CONCLUSION: This study shows a clear benefit of a VLCK over LF diet for short-term body weight and fat loss, especially in men. A preferential loss of fat in the trunk region with a VLCK diet is novel and potentially clinically significant but requires further validation. These data provide additional support for the concept of metabolic advantage with diets representing extremes in macronutrient distribution.
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Project description:ObjectiveTo examine associations of body mass index (BMI) and weight loss with cause-specific mortality in rheumatoid arthritis (RA).MethodsA cohort of US veterans with RA was followed until death or through 2013. BMI was categorized as underweight, normal, overweight, and obese. Weight loss was calculated as the 1) annualized rate of change over the preceding 13 months, and 2) cumulative percent. Vital status and cause of death were obtained from the National Death Index. Multivariable competing-risks regression models were utilized to assess the time-varying associations of BMI and weight loss with cause-specific mortality.ResultsAmong 1,600 participants and 5,789 patient-years of followup, 303 deaths occurred (95 cardiovascular, 74 cancer, and 46 respiratory). The highest weight-loss rate and weight-loss percent were associated with a higher risk of cardiovascular mortality (rate: subdistribution hazard ratio [sHR] 2.27 [95% confidence interval (95% CI) 1.61-3.19]; percent: sHR 2.31 [95% CI 1.06-5.01]) and cancer mortality (rate: sHR 2.36 [95% CI 1.11-5.01]; percent: sHR 1.90 [95% CI 1.00-3.62]). Overweight BMI was protective of cardiovascular mortality (sHR 0.59 [95% CI 0.38-0.91]), while underweight BMI was associated with a near 3-fold increased risk of respiratory mortality (sHR 2.93 [95% CI 1.28-6.67]). Incorporation of time-varying BMI and weight loss in the same models did not substantially alter individual associations for cardiovascular and cancer mortality, but an association between weight-loss percentage and respiratory mortality was attenuated after BMI adjustment.ConclusionBoth BMI and weight loss are predictors of cause-specific mortality in RA. Weight loss is a strong predictor of cardiovascular and cancer mortality, while underweight BMI is a stronger predictor of respiratory mortality.
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Project description:IntroductionWeight loss reduces co-morbidities of obesity, but decreases bone mass.PurposeOur aims were to (1) determine if adequate dairy intake attenuates weight loss-induced bone loss; (2) evaluate the associations of endocrine, inflammatory and bone markers, anthropometric and other parameters to bone mineral density and content (BMD, BMC) pre- and post-weight loss; and (3) model the contribution of these variables to post weight-loss BMD and BMC.MethodsOverweight/obese women (BMI: 28-37 kg/m2) were enrolled in an energy reduced (-500 kcal/d; -2092 kJ/d) diet with adequate dairy (AD: 3-4 servings/d; n=25, 32.2±8.8 years) or low dairy (LD: ≤1 serving/d; n=26, 31.7±8.4 years). BMD, BMC and body composition were measured by DXA. Bone markers (CTX, PYD, BAP, OC), endocrine (PTH, vitamin D, leptin, adiponectin, ghrelin, amylin, insulin, GLP-1, PAI-1, HOMA) and inflammatory markers (CRP, IL1-β, IL-6, IL-8, TNF-α, cortisol) were measured in serum or plasma. PA was assessed by accelerometry.ResultsFollowing weight loss, AD intake resulted in significantly greater (p=0.004) lumbar spine BMD and serum osteocalcin (p=0.004) concentration compared to LD. Pre- and post-body fat was negatively associated with hip and lumbar spine BMC (r=-0.28, p=0.04 to -0.45, p=0.001). Of note were the significant negative associations among bone markers and IL-1β, TNFα and CRP ranging from r = -0.29 (p=0.04) to r = -0.34 (p=0.01); magnitude of associations did not change with weight loss. Adiponectin was negatively related to change in osteocalcin. Factor analysis resulted in 8 pre- and post-weight loss factors. Pre-weight loss factors accounted for 13.7% of the total variance in pre-weight loss hip BMD; post-weight loss factors explained 19.6% of the total variance in post-weight loss hip BMD. None of the factors contributed to the variance in lumbar spine BMD.ConclusionAD during weight loss resulted in higher lumbar spine BMD and osteocalcin compared to LD. Significant negative associations were observed between bone and inflammatory markers suggesting that inflammation suppresses bone metabolism. Using factor analysis, 19.6% of total variance in post-weight loss hip BMD could be explained by endocrine, immune, and anthropometric variables, but not lumbar spine BMD.
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Project description:ObjectiveWithin behavioral weight loss (BWL) programs, using measured resting metabolic rate (RMR) is a more accurate-yet costlier-alternative to the standard method of assigning calorie prescriptions using baseline weight. This investigation aimed to assess differences between calorie goals prescribed using each method including demographic predictors and associations with weight loss.MethodsThis is an ancillary study to a trial comparing approaches to motivational enhancement in a 6-months BWL program designed for emerging adults age 18-25 (N = 308). RMR was measured at baseline and used to derive calorie prescriptions; standard calorie goals were retrospectively assigned for the purpose of these analyses.ResultsStandard calorie prescriptions were significantly higher than those derived from RMR. Sex and race were significant predictors of calorie prescription discrepancies: using the standard method, women and Black participants were assigned higher calorie goals than their RMR would indicate. Calorie goal discrepancy did not predict 6-months weight change.ConclusionsDifferences in calorie prescriptions between approaches were significant; however, it remains to be determined whether measuring RMR is worth the cost, time, and participant burden. It may be the case that this consideration has greater impact for certain subgroups-namely, women and Black participants.
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Project description:Obese dogs seem to have a different gut microbiome (GM) composition compared to lean dogs, and in humans, GM composition may negatively impact the ability to lose weight in some individuals. The purpose of this study was to investigate the interaction between exercise, weight-loss and the composition of GM in dogs. Eighteen obese pet dogs were recruited for a 12-week weight-loss intervention. All dogs were fed restrictively with a commercial high-protein/high-fibre dry diet, and eight of these dogs were enrolled in an exercise program in addition to the diet intervention. Faecal samples were collected and the dogs were weighed at week 0, week 6 and week 12. GM composition was determined using MiSeq-based tag-encoded 16S rRNA gene high-throughput amplicon sequencing, and concentrations of short chain fatty acids (SCFA) by gas-liquid chromatography. Total weight loss, food allowance and GM were not changed by exercise inclusion. However, Megamonas abundance negatively correlated with weight loss rate and Ruminococcaceae relative abundance was lower at 12 weeks in dogs with a faster weight loss rate (≥1% per week) compared with slower weight loss rate (<1% per week) independent of exercise. Acetic and propionic acid concentrations decreased in the dogs with a faster weight loss rate. Members of Megamonas and Ruminococcaceae produce acetic and propionic acids and we therefore interpret that having a GM that favour SCFA production may negatively affect weight loss rate in dogs. Weight loss rate in dogs may be related to the composition of the GM and its production of metabolites.
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Project description:Carbohydrate intake affects postprandial glucose levels and insulin response, which plays a role in carcinogenesis. The relationship between carbohydrate intake, dietary glycemic index (GI) and glycemic load (GL), and risk of renal cell carcinoma (RCC) remains unclear. We conducted a case-control study including 854 patients with newly diagnosed RCC (cases) and 1255 healthy participants (controls) recruited since 2002. GI, GL and carbohydrate intake were obtained via a validated food frequency questionnaire. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression, adjusting for potential confounders. We found that higher GI was significantly associated with RCC risk with an OR of 1.32 (95% CI, 0.99-1.74; Ptrend = 0.026) (the highest versus the lowest quartiles). We also observed an inverse association between fiber intake and RCC risk with OR of 0.70 (95% CI = 0.50-0.99) as well as between starch intake and risk of RCC with OR of 0.65 (95% CI = 0.49-0.87). Individuals with a high-GI diet and hypertension or high body mass index (BMI) had a 2.7 times (OR = 2.67, 95% CI = 1.96-3.64) and two times (OR = 1.95, 95% CI = 1.29-2.92) higher RCC risk, respectively, than those without these factors. Our findings suggest that a high-GI diet is associated with an increased risk of RCC, whereas increased fiber and starch intakes appear to be associated with a decreased risk of RCC. We found that reducing GI levels and increasing fiber intake could be a dietary strategy to decrease RCC risk, especially for individuals with hypertension or high BMI.
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