Search

The carbohydrate–insulin model of obesity posits that high-carbohydrate diets lead to excess insulin secretion, thereby promoting fat accumulation and increasing energy intake. Thus, low-carbohydrate diets are predicted to reduce ad libitum energy intake as compared to low-fat, high-carbohydrate diets. To test this hypothesis, 20 adults aged 29.9 ± 1.4 (mean ± s.e.m.) years with body mass index of 27.8 ± 1.3 kg m−2 were admitted as inpatients to the National Institutes of Health Clinical Center and randomized to consume ad libitum either a minimally processed, plant-based, low-fat diet (10.3% fat, 75.2% carbohydrate) with high glycemic load (85 g 1,000 kcal−1) or a minimally processed, animal-based, ketogenic, low-carbohydrate diet (75.8% fat, 10.0% carbohydrate) with low glycemic load (6 g 1,000 kcal−1) for 2 weeks followed immediately by the alternate diet for 2 weeks. One participant withdrew due to hypoglycemia during the low-carbohydrate diet. The primary outcomes compared mean daily ad libitum energy intake between each 2-week diet period as well as between the final week of each diet. We found that the low-fat diet led to 689 ± 73 kcal d−1 less energy intake than the low-carbohydrate diet over 2 weeks (P

OBJECTIVES: To investigate differences in ad libitum energy intake when inpatient adults were exposed to diets with equal calories and protein but varied widely in the ratio of carbohydrate to fat. METHODS: 16 adults without diabetes were admitted to the Metabolic Clinical Research Unit in the NIH Clinical Center for four continuous weeks and were randomized to receive either a plant-based, low-fat (LF) diet or an animal-based, low-carbohydrate (LC) diet for two weeks, followed by the alternate diet for two weeks. The LF diet was ∼75% carbohydrate and ∼10% fat, whereas the LC was ∼10% carbohydrate and ∼75% fat. The LF diet had ∼4-fold more fiber and was ∼60% of the energy density of the LC diet. Both diets were matched for protein and the presented calories were double each subject's maintenance energy requirements, as calculated from their measured resting energy expenditure multiplied by 1.6. Participants received three daily meals, had continuous access to snacks, and were instructed to eat as much or as little as they wanted. Leftovers were weighed to determine food intake. ProNutra software was used to calculate energy and nutrient intake. RESULTS: The study enrolled 9 men and 7 women with an age (mean ± SE) of 29 ± 1.7 years and body mass index (BMI) of 27.5 ± 1.5. During exposure to the LF diet, participants consumed 726 ± 84 kcal/d less than during the LC diet (P

OBJECTIVES: To explore postprandial responses to isocaloric meals after ∼2 weeks on an ad libitum Low Carbohydrate (LC) diet vs. a Low Fat (LF) diet. METHODS: 16 healthy volunteers without diabetes were admitted to the NIH Clinical Center and randomized to consume a LC or LF diet for 2 weeks immediately followed by 2 weeks of the alternate diet. The LC diet was composed of ∼75% fat, ∼10% carbohydrate, and ∼15% protein; the LF diet was ∼75% carbohydrate, ∼10% fat, and ∼15% protein. Daily meals and snacks were matched for presented calories and participants were instructed to consume as much or as little as desired. On day 13 of each diet after an 8 hour fast, participants consumed a liquid meal containing 30% of energy requirements with a macronutrient composition corresponding to the prevailing diet. Blood was drawn at 0, 10, 20, 30, 60, 90, 120, 180, 240, 300, 360 minutes post meal consumption. Plasma concentrations of glucose, lactate, insulin, c-peptide, free fatty acids, and triglycerides were measured. RESULTS: 7 females and 9 males with an age of (mean ± SE) 28.7 ±1.7 y and BMI of 27.5 ± 1.5 kg/m(2) completed the study. During the LC diet, baseline levels of triglycerides and lactate were significantly lower (−33.5 ± 9.1 mg/dl; P = 0.003, −0.18 ± 0.05 mM; P = 0.002, respectively) and glucose, insulin, and c-peptide also tended to be lower (−3.7 ± 2.0 mg/dl; P = 0.09, −2.2 ± 1.2 µU/ml; P = 0.08, −0.35 ± 0.17 ng/ml; P = 0.06, respectively) whereas free fatty acids were significantly higher (0.28 ± 0.06 mM; P = 0.0005) compared to the LF diet. Average postprandial levels of glucose, lactate, insulin, and c-peptide were significantly lower following the LC meal (−11 ± 3 mg/dl; P = 0.003, −0.88 ± 0.06 mM; P

Competing models of obesity and its treatment often contrast the relative roles of dietary fat versus carbohydrate. Advocates of low-carbohydrate diets posit that intake of high glycemic carbohydrates leads to elevated postprandial insulin thereby promoting body fat accumulation while increasing hunger and energy intake according to the carbohydrate-insulin model of obesity. Alternatively, proponents of low-fat diets argue that high fat intake promotes body fat storage due to passive overconsumption of energy resulting from the high energy density of dietary fat. To test these competing models, 20 adults without diabetes aged (mean±SE) 29.9±1.4 y with BMI=27.8±1.3 kg/m2 were admitted as inpatients to the NIH Clinical Center and randomized to consume ad libitum either a plant-based, low-fat (PBLF) diet (75.2% carbohydrate, 10.3% fat, non-beverage energy density = 1.1 kcal/g) or an animal-based, ketogenic, low-carbohydrate (ABLC) diet (75.8% fat,10.0% carbohydrate, non-beverage energy density = 2.2 kcal/g) for two weeks followed immediately by the alternate diet for two weeks. Three daily meals plus snacks amounting to twice each subject’s estimated energy requirements were provided and subjects were instructed to eat as much or as little as desired. The PBLF diet resulted in substantially greater glucose and insulin levels whereas the ABLC diet led to increased blood ketones of ~3 mM which is thought to suppress appetite. However, ad libitum energy intake was 689±73 kcal/d lower during the PBLF diet as compared to the ABLC diet (p

OBJECTIVES: To describe the effects of ad libitum low-fat (LF) and low-carbohydrate (LC) diets on body weight and fat mass. METHODS: Sixteen adults without diabetes spent 29 continuous days residing at the Metabolic Clinical Research Unit of the NIH Clinical Center where they were fed ad libitum either an animal-based, LC diet (75% fat, 10% carbohydrates, 15% protein) or a plant-based, LF diet (75% carbohydrates, 10% fat, 15% protein). Participants were randomly assigned to one diet for the first phase of the study (14 days), after which they were switched to the other diet for the remainder of the study. Participants were given three meals daily and were provided with additional snacks amounting to 200% of their daily energy requirements as determined by their resting energy expenditure multiplied by 1.6. Subjects were told that this was not a weight loss study and were not informed about the primary study aim. They were instructed to eat as much or as little as they desired. Total body weight and fat mass were measured using a calibrated scale and dual-energy X-ray absorptiometry, respectively. Subjects were blinded to their data and wore loose-fitting scrubs to avoid any feedback regarding changes in the fit of their clothing. RESULTS: Subjects included 7 women and 9 men, with an age of (mean ± SE) 29 ± 1.7 years and BMI of 27.5 ± 1.5 at baseline. Participants lost weight on both diets, with the LC diet resulting in 1.34 ± 0.31 kg of weight loss (P = 0.0006) and the LF diet resulting in 1.09 ± 0.31 kg of weight loss (P = 0.003) which was not significantly different from the LC diet (P = 0.58). However, participants lost 0.6 ± 0.17 kg of body fat on the LF diet (P = 0.002) but the LC diet did not result in significant body fat loss (0.04 ± 0.17 kg; P = 0.8) and the difference in body fat loss between the diets was statistically significant (P = 0.03). CONCLUSIONS: While participants lost similar amounts of weight on both diets, only the LF diet led to significant body fat loss. Early weight loss with a LC diet does not necessarily reflect a similar state of negative energy balance as compared with a LF diet. FUNDING SOURCES: Intramural Research Program of the National Institutes of Diabetes and Digestive and Kidney Diseases.

In the face of stiff competition, many organizations turn to business intelligence tools to successfully compete in the marketplace. However, successfully implementing and growing a business intelligence solution to combat market pressure is an arduous task. The stages of growth models present one approach that could guide organizations in the implementation and growth of successful business intelligence (BI) efforts. At Monster.com, upper management chose to design and implement a business intelligence framework to compete in the online job search arena. While the progressive steps that led to Monster’s successful BI solution did not strictly follow established BI stage models, it helped the company effectively steer clear of competition and remain a major player in the online job search marketplace.