Effect of meal composition on postprandial glucagon-like peptide-1, insulin, glucagon, C-peptide, and glucose responses in overweight/obese subjects.

BACKGROUND: Glucagon-like peptide-1 (GLP-1), an incretin hormone, is released in response to food intake. It is unclear how meals high in protein (HP) and monounsaturated fat (HMF) affect GLP-1 response. PURPOSE: To examine the effect of a HP versus a HMF meal on GLP-1 response. METHODS: Twenty-four overweight/obese participants consumed two meals (HP: 31.9 % energy from protein; HMF: 35.2 % fat and 20.7 % monounsaturated fat) in a random order. Both meals contained the same energy and carbohydrate content. GLP-1, insulin, glucagon, C-peptide, and glucose were assessed from blood drawn in the fasting and postprandial states. The effect of meal condition on hormone and glucose responses and appetite ratings were assessed by repeated measures analysis. RESULTS: Statistically significant (p < 0.01) time by meal condition effect was observed on active GLP-1, total GLP-1, insulin, C-peptide, and glucagon, but not glucose (p = 0.83). Area under the curve was significantly higher during the HP versus the HMF meal conditions for active GLP-1 (23.7 %; p = 0.0007), total GLP-1 (12.2 %; p < 0.0001), insulin (54.4 %; p < 0.0001), C-peptide (14.8 %; p < 0.0001), and glucagon (40.7 %; p < 0.0001). Blood glucose was not different between the HP versus HMF conditions (-4.8 %; p = 0.11). Insulin sensitivity was higher during the HMF versus HP conditions (Matsuda index mean difference: 16.3 %; p = 0.007). Appetite ratings were not different by meal condition. CONCLUSIONS: GLP-1 and insulin responses were higher during the HP condition. However, no difference was found in blood glucose between conditions, and insulin sensitivity was higher during the HMF condition, indicating that a HMF meal may be optimal at regulating blood glucose in overweight/obese individuals without type 2 diabetes.

Machine Learning-Augmented Propensity Score-Adjusted Multilevel Mixed Effects Panel Analysis of Hands-On Cooking and Nutrition Education versus Traditional Curriculum for Medical Students as Preventive Cardiology: Multisite Cohort Study of 3,248 Trainees over 5 Years.

BACKGROUND: Cardiovascular disease (CVD) annually claims more lives and costs more dollars than any other disease globally amid widening health disparities, despite the known significant reductions in this burden by low cost dietary changes. The world's first medical school-based teaching kitchen therefore launched CHOP-Medical Students as the largest known multisite cohort study of hands-on cooking and nutrition education versus traditional curriculum for medical students. METHODS: This analysis provides a novel integration of artificial intelligence-based machine learning (ML) with causal inference statistics. 43 ML automated algorithms were tested, with the top performer compared to triply robust propensity score-adjusted multilevel mixed effects regression panel analysis of longitudinal data. Inverse-variance weighted fixed effects meta-analysis pooled the individual estimates for competencies. RESULTS: 3,248 unique medical trainees met study criteria from 20 medical schools nationally from August 1, 2012, to June 26, 2017, generating 4,026 completed validated surveys. ML analysis produced similar results to the causal inference statistics based on root mean squared error and accuracy. Hands-on cooking and nutrition education compared to traditional medical school curriculum significantly improved student competencies (OR 2.14, 95% CI 2.00-2.28, p < 0.001) and MedDiet adherence (OR 1.40, 95% CI 1.07-1.84, p = 0.015), while reducing trainees' soft drink consumption (OR 0.56, 95% CI 0.37-0.85, p = 0.007). Overall improved competencies were demonstrated from the initial study site through the scale-up of the intervention to 10 sites nationally (p < 0.001). DISCUSSION: This study provides the first machine learning-augmented causal inference analysis of a multisite cohort showing hands-on cooking and nutrition education for medical trainees improves their competencies counseling patients on nutrition, while improving students' own diets. This study suggests that the public health and medical sectors can unite population health management and precision medicine for a sustainable model of next-generation health systems providing effective, equitable, accessible care beginning with reversing the CVD epidemic.

Modified activity-stress paradigm in an animal model of the female athlete triad.

The exercising woman with nutritional deficits and related menstrual irregularities is at risk of compromising long-term bone health, i.e., the female athlete triad. There is no animal model of the female athlete triad. The purpose of this study was to examine long-term energy restriction in voluntary wheel-running female rats on estrous cycling, bone mineral content, and leptin levels. Twelve female Sprague-Dawley rats (age 34 days) were fed ad libitum and given access to running wheels during an initial 14-wk period, providing baseline and age-related data. Daily collection included dietary intake, body weight, estrous cycling, and voluntary running distance. At 4 mo, rats were randomized into two groups, six restrict-fed rats (70% of ad libitum intake) and six rats continuing as ad libitum-fed controls. Energy intake, energy expenditure, and energy availability (energy intake - energy expenditure) were calculated for each animal. Serum estradiol and leptin concentrations were measured by RIA. Femoral and tibial bone mineral density and bone mineral content (BMC) were determined by dual-energy X-ray absorptiometry. Restrict-fed rats exhibited a decrease in energy availability during Weight Loss and Anestrous phases (P = 0.002). Compared with controls after 12 wk, restrict-fed rats showed reduced concentrations of serum estradiol (P = 0.002) and leptin (P = 0.002), lower ovarian weight (P = 0.002), and decreased femoral (P = 0.041) and tibial (P = 0.05) BMC. Decreased energy availability resulted in anestrus and significant decreases in BMC, estrogen and leptin levels, and body weight. Finally, there is a critical level of energy availability to maintain estrous cycling.

Healthy Weigh (El camino saludable) phase 1: a retrospective critical examination of program evaluation.

BACKGROUND: Healthy Weigh (El camino saludable) is an obesity prevention program for low-income, predominantly Hispanic and African American families in an urban community in Tarrant County, Texas. Healthy Weigh Phase 1 was a successful community-campus partnership that took place in summer (June-August) and fall (September-November) 2003. The program met stated objectives and extensively engaged students from several health disciplines in service learning. This article describes what we learned about the evaluation of the program by examining the phase 1 evaluation process. CONTEXT: Family environments are important intervention settings for establishing life-long dietary practices. Available in English and Spanish, Healthy Weigh Phase 1 helped families that were at risk for overweight and obesity to adopt healthy eating, physical activity, and weight management patterns. METHODS: Analysis of a program logic model and formative evaluation data identified evaluation questions that could have improved the phase 1 evaluation process. Questions were categorized according to Donabedian's structure-process-outcome framework, and potential benefits of each question were identified. The Centers for Disease Control and Prevention's Framework for Program Evaluation in Public Health standards were used to judge the overall quality of the phase 1 evaluation process. CONSEQUENCES: The phase 1 evaluation process successfully assessed the program's effects and generally met evaluation standards. Our critical examination also highlighted structure and process evaluation issues with potential for strengthening future interventions, community partnerships, and program outcomes. INTERPRETATION: Lessons learned influenced the phase 2 grant activities. Most importantly, we learned that involvement of program participants as full partners in program design, evaluation, and implementation is essential. Our understanding and practice of program evaluation evolved as Healthy Weigh became a true community-based participatory research endeavor.

Effect of calorie or exercise labels on menus on calories and macronutrients ordered and calories from specific foods in Hispanic participants: a randomized study.

The effect of menu labels on food choices is unknown in Hispanics. This study evaluated the impact of menu labels on calories and macronutrients ordered in Hispanics. 372 Hispanics (18-65 years) were randomly assigned to menus with no labels (NL) (n=127), rank-ordered calorie labels plus a statement on energy needs per meal (CL) (n=123), or rank-ordered exercise labels showing minutes of brisk walking necessary to burn the food calories (EL) (n=122). The menus had identical food choices. Participants were instructed to select foods from the assigned menu as if having lunch in a fast food restaurant. One-way analysis of variance found no difference in calories ordered (median (25th and 75th centiles)) by menu condition (NL: 785.0 (465.0, 1010.0) kcal; CL: 790.0 (510.0, 1020.0) kcal; EL: 752.5 (520.0, 1033.8) kcal; p=0.75). Calories from specific foods and macronutrient intake were not different by menu condition. Menu label use was 26.8% in the CL and 25.4% in the EL condition. Calories ordered were not different between those who used and those who did not use the labels. Regression analysis showed that perception of being overweight (p=0.02), selecting foods based on health value (p<0.0001), and meeting exercise guidelines (p<0.0001) were associated with fewer calories ordered. Logistic regression showed that selecting foods based on health value (p=0.01) was associated with higher food label use. Menu labels did not affect food choices in Hispanic participants. Future studies should determine if nutrition, exercise, and weight perception counseling prior to menu labels intervention would result in better food choices. TRIAL REGISTRATION NUMBER: NCT02804503; post-results.

The effect of eating speed at breakfast on appetite hormone responses and daily food consumption.

BACKGROUND: The effect of eating speed at a meal on appetite gut hormone responses and future food consumption is not clear. This study examined the effect of eating speed at breakfast on postprandial gut hormone responses, subjective appetite, and daily food consumption. METHODS: Twenty-five participants [68% men; age, 25.9 (8.1) years; body mass index, 25.0 (3.2) kg/m] were recruited. Each participant consumed the same breakfast at a slow (30 minutes) and fast (10 minutes) speed, on 2 separate days, in a randomized crossover design. Blood samples were collected in the fasting state and 3 hours postprandially during each eating condition. Appetite was assessed over the same period using visual analog scales. Blood concentrations of orexigenic hormone, ghrelin, and anorexigenic hormones, glucagon-like peptide-1 (GLP-1) and peptide YY (PYY), were determined. Daily food intake was measured, by food recall, after the slow and fast breakfast. RESULTS: Mixed-model repeated-measures analysis showed no eating condition or eating condition by time interaction effect on ghrelin, GLP-1, PYY, hunger, or fullness. Significant eating speed by time interaction effect on desire to eat was found (P=0.007). Desire to eat was lower at 60 minutes (P=0.007) after breakfast began during the slow versus fast eating condition. Eating speed at breakfast did not affect daily energy and macronutrient intake. CONCLUSIONS: Eating speed at breakfast did not affect postprandial ghrelin, GLP-1, PYY, hunger, and fullness values or daily energy and macronutrient intake. Desire to eat was lower at 60 minutes in the slow versus fast eating condition, but this result could not be explained by the changes in meal-related hormones measured in the study.

Slower eating speed lowers energy intake in normal-weight but not overweight/obese subjects.

BACKGROUND: The effect of eating speed on energy intake by weight status is unclear. OBJECTIVE: To examine whether the effect of eating speed on energy intake is the same in normal-weight and overweight/obese subjects. DESIGN: The effect of slow and fast eating speed on meal energy intake was assessed in a randomized crossover design. PARTICIPANTS/SETTING: Thirty-five normal-weight (aged 33.3±12.5 years; 14 women and 21 men) subjects and 35 overweight/obese (44.1±13.0 years; 22 women and 13 men) subjects were studied on 2 days during lunch in a metabolic kitchen. INTERVENTION: The subjects consumed the same meal, ad libitum, but at different speeds during the two eating conditions. The weight and energy content of the food consumed was assessed. Perceived hunger and fullness were assessed at specific times using visual analog scales. STATISTICAL ANALYSES: Effect of eating speed on ad libitum energy intake, eating rate (energy intake/meal duration), energy density (energy intake per gram of food and water consumed), and satiety were assessed by mixed-model repeated measures analysis. RESULTS: Meal energy intake was significantly lower in the normal-weight (804.5±438.9 vs 892.6±330.2 kcal; P=0.04) but not the overweight/obese (667.3±304.1 vs 724.8±355.5 kcal; P=0.18) subjects during the slow vs the fast eating condition. Both groups had lower meal energy density (P=0.005 and P=0.001, respectively) and eating rate (P<0.0001 in both groups) during the slow vs the fast eating condition. Both groups reported less hunger (P=0.01 and P=0.03, respectively), and the normal-weight subjects reported more fullness (P=0.02) at 60 minutes after the meal began during the slow compared with the fast eating condition. There was no eating speed by weight status interaction for any of the variables. CONCLUSIONS: Eating slowly significantly lowered meal energy intake in the normal-weight but not in the overweight/obese group. It lowered eating rate and energy density in both groups. Eating slowly led to lower hunger ratings in both groups and increased fullness ratings in the normal-weight group at 60 minutes from when the meal began.