Hongmei Han

Effects of stevia, aspartame, and sucrose on food intake, satiety, and postprandial glucose and insulin levels.

UNLABELLED Consumption of sugar-sweetened beverages may be one of the dietary causes of metabolic disorders, such as obesity. Therefore, substituting sugar with low calorie sweeteners may be an efficacious weight management strategy. We tested the effect of preloads containing stevia, aspartame, or sucrose on food intake, satiety, and postprandial glucose and insulin levels. DESIGN 19 healthy lean (BMI=20.0-24.9) and 12 obese (BMI=30.0-39.9) individuals 18-50 years old completed three separate food test days during which they received preloads containing stevia (290kcal), aspartame (290kcal), or sucrose (493kcal) before the lunch and dinner meal. The preload order was balanced, and food intake (kcal) was directly calculated. Hunger and satiety levels were reported before and after meals, and every hour throughout the afternoon. Participants provided blood samples immediately before and 20min after the lunch preload. Despite the caloric difference in preloads (290kcal vs. 493kcal), participants did not compensate by eating more at their lunch and dinner meals when they consumed stevia and aspartame versus sucrose in preloads (mean differences in food intake over entire day between sucrose and stevia=301kcal, p<.01; aspartame=330kcal, p<.01). Self-reported hunger and satiety levels did not differ by condition. Stevia preloads significantly reduced postprandial glucose levels compared to sucrose preloads (p<.01), and postprandial insulin levels compared to both aspartame and sucrose preloads (p<.05). When consuming stevia and aspartame preloads, participants did not compensate by eating more at either their lunch or dinner meal and reported similar levels of satiety compared to when they consumed the higher calorie sucrose preload.

A novel method to remotely measure food intake of free-living individuals in real time: the remote food photography method

The aim of the present study was to report the first reliability and validity tests of the remote food photography method (RFPM), which consists of camera-enabled cell phones with data transfer capability. Participants take and transmit photographs of food selection and plate waste to researchers/clinicians for analysis. Following two pilot studies, adult participants (n 52; BMI 20-35 kg/m2 inclusive) were randomly assigned to the dine-in or take-out group. Energy intake (EI) was measured for 3 d. The dine-in group ate lunch and dinner in the laboratory. The take-out group ate lunch in the laboratory and dinner in free-living conditions (participants received a cooler with pre-weighed food that they returned the following morning). EI was measured with the RFPM and by directly weighing foods. The RFPM was tested in laboratory and free-living conditions. Reliability was tested over 3 d and validity was tested by comparing directly weighed EI to EI estimated with the RFPM using Bland-Altman analysis. The RFPM produced reliable EI estimates over 3 d in laboratory (r 0.62; P < 0.0001) and free-living (r 0.68; P < 0.0001) conditions. Weighed EI correlated highly with EI estimated with the RFPM in laboratory and free-living conditions (r>0.93; P < 0.0001). In two laboratory-based validity tests, the RFPM underestimated EI by - 4.7 % (P = 0.046) and - 5.5 % (P = 0.076). In free-living conditions, the RFPM underestimated EI by - 6.6 % (P = 0.017). Bias did not differ by body weight or age. The RFPM is a promising new method for accurately measuring the EI of free-living individuals. Error associated with the method is small compared with self-report methods.

Measurement of Dietary Restraint: Validity Tests of Four Questionnaires

This study tested the validity of four measures of dietary restraint: Dutch Eating Behavior Questionnaire, Eating Inventory (EI), Revised Restraint Scale (RS), and the Current Dieting Questionnaire. Dietary restraint has been implicated as a determinant of overeating and binge eating. Conflicting findings have been attributed to different methods for measuring dietary restraint. The validity of four self-report measures of dietary restraint and dieting behavior was tested using: (1) factor analysis, (2) changes in dietary restraint in a randomized controlled trial of different methods to achieve calorie restriction, and (3) correlation of changes in dietary restraint with an objective measure of energy balance, calculated from the changes in fat mass and fat-free mass over a six-month dietary intervention. Scores from all four questionnaires, measured at baseline, formed a dietary restraint factor, but the RS also loaded on a binge eating factor. Based on change scores, the EI Restraint Scale was the only measure that correlated significantly with energy balance expressed as a percentage of energy required for weight maintenance. These findings suggest that, of the four questionnaires tested, the EI Restraint Scale was the most valid measure of the intent to diet and actual caloric restriction.

Validity of the Remote Food Photography Method (RFPM) for estimating energy and nutrient intake in near real-time.

Two studies are reported; a pilot study to demonstrate feasibility followed by a larger validity study. Study 1s objective was to test the effect of two ecological momentary assessment (EMA) approaches that varied in intensity on the validity/accuracy of estimating energy intake (EI) with the Remote Food Photography Method (RFPM) over 6 days in free‐living conditions. When using the RFPM, Smartphones are used to capture images of food selection and plate waste and to send the images to a server for food intake estimation. Consistent with EMA, prompts are sent to the Smartphones reminding participants to capture food images. During Study 1, EI estimated with the RFPM and the gold standard, doubly labeled water (DLW), were compared. Participants were assigned to receive Standard EMA Prompts (n = 24) or Customized Prompts (n = 16) (the latter received more reminders delivered at personalized meal times). The RFPM differed significantly from DLW at estimating EI when Standard (mean ± s.d. = −895 ± 770 kcal/day, P < 0.0001), but not Customized Prompts (−270 ± 748 kcal/day, P = 0.22) were used. Error (EI from the RFPM minus that from DLW) was significantly smaller with Customized vs. Standard Prompts. The objectives of Study 2 included testing the RFPMs ability to accurately estimate EI in free‐living adults (N = 50) over 6 days, and energy and nutrient intake in laboratory‐based meals. The RFPM did not differ significantly from DLW at estimating free‐living EI (−152 ± 694 kcal/day, P = 0.16). During laboratory‐based meals, estimating energy and macronutrient intake with the RFPM did not differ significantly compared to directly weighed intake.

Wise Mind Project: A School-based Environmental Approach for Preventing Weight Gain in Children

Objective: The Wise Mind pilot study compared the efficacy of an environmental approach for prevention of inappropriate weight gain in children with an active control condition that used an environmental approach for modifying expectancies related to the use of alcohol, tobacco, and drugs.

Change in food cravings, food preferences, and appetite during a low-carbohydrate and low-fat diet

The study objective was to evaluate the effect of prescribing a low‐carbohydrate diet (LCD) and a low‐fat diet (LFD) on food cravings, food preferences, and appetite. Obese adults were randomly assigned to a LCD (n = 134) or a LFD (n = 136) for 2 years. Cravings for specific types of foods (sweets, high‐fats, fast‐food fats, and carbohydrates/starches); preferences for high‐sugar, high‐carbohydrate, and low‐carbohydrate/high‐protein foods; and appetite were measured during the trial and evaluated during this secondary analysis of trial data. Differences between the LCD and LFD on change in outcome variables were examined with mixed linear models. Compared to the LFD, the LCD had significantly larger decreases in cravings for carbohydrates/starches and preferences for high‐carbohydrate and high‐sugar foods. The LCD group reported being less bothered by hunger compared to the LFD group. Compared to the LCD group, the LFD group had significantly larger decreases in cravings for high‐fat foods and preference for low‐carbohydrate/high‐protein foods. Men had larger decreases in appetite ratings compared to women. Prescription of diets that promoted restriction of specific types of foods resulted in decreased cravings and preferences for the foods that were targeted for restriction. The results also indicate that the LCD group was less bothered by hunger compared to the LFD group and that men had larger reductions in appetite compared to women.

Effect of an Environmental School-Based Obesity Prevention Program on Changes in Body Fat and Body Weight: A Randomized Trial

This study tested the efficacy of two school‐based programs for prevention of body weight/fat gain in comparison to a control group, in all participants and in overweight children. The Louisiana (LA) Health study utilized a longitudinal, cluster randomized three‐arm controlled design, with 28 months of follow‐up. Children (N = 2,060; mean age = 10.5 years, SD = 1.2) from rural communities in grades 4–6 participated in the study. Seventeen school clusters (mean = 123 children/cluster) were randomly assigned to one of three prevention arms: (i) primary prevention (PP), an environmental modification (EM) program, (ii) primary + secondary prevention (PP+SP), the environmental program with an added classroom and internet education component, or (iii) control (C). Primary outcomes were changes in percent body fat and BMI z scores. Secondary outcomes were changes in behaviors related to energy balance. Comparisons of PP, PP+SP, and C on changes in body fat and BMI z scores found no differences. PP and PP+SP study arms were combined to create an EM arm. Relative to C, EM decreased body fat for boys (−1.7 ± 0.38% vs. −0.14 ± 0.69%) and attenuated fat gain for girls (2.9 ± 0.22% vs. 3.93 ± 0.37%), but standardized effect sizes were relatively small (<0.30). In conclusion, this school‐based EM programs had modest beneficial effects on changes in percent body fat. Addition of a classroom/internet program to the environmental program did not enhance weight/fat gain prevention, but did impact physical activity and social support in overweight children.

Efficacy of SmartLoss, a smartphone-based weight loss intervention: results from a randomized controlled trial.

Test the efficacy of SmartLossSM, a smartphone‐based weight loss intervention, in a pilot study.

Adiposity and Physical Activity Are Not Related to Academic Achievement in School-Aged Children

Objective: To investigate the hypotheses that in elementary school students: (1) adiposity and academic achievement are negatively correlated and (2) physical activity and academic achievement are positively correlated. Methods: Participants were 1963 children in fourth to sixth grades. Adiposity was assessed by calculating body mass index (BMI) percentile and percent body fat and academic achievement with statewide standardized tests in 4 content areas. Socioeconomic status and age were control variables. A subset of participants (n = 261) wore an accelerometer for 3 days to provide objective measurement of physical activity. In addition, the association between weight status and academic achievement was examined by comparing children who could be classified as “extremely obese” and the rest of the sample, as well as comparing children who could be classified as normal weight, overweight, or obese. Extreme obesity was defined as ≥1.2 times the 95th percentile. Results: The results indicated that there were no significant associations between adiposity or physical activity and achievement in students. No academic achievement differences were found between children with BMI percentiles within the extreme obesity range and those who did not fall within the extreme obesity classification. In addition, no academic achievement differences were found for children with BMI percentiles within the normal weight, overweight, or obese ranges. Conclusions: These results do not support the hypotheses that increased adiposity is associated with decreased academic achievement or that greater physical activity is related to improved achievement. However, these results are limited by methodological weaknesses, especially the use of cross-sectional data.

Effects of Chromium Picolinate on Food Intake and Satiety

BACKGROUND Chromium picolinate (CrPic) has been shown to attenuate weight gain, but the mechanism underlying this effect is unknown. METHODS We assessed the effect of CrPic in modulating food intake in healthy, overweight, adult women who reported craving carbohydrates (Study 1) and performed confirmatory studies in Sprague-Dawley rats (Study 2). Study 1 utilized a double-blind placebo-controlled design and randomly assigned 42 overweight adult women with carbohydrate cravings to receive 1,000 mg of CrPic or placebo for 8 weeks. Food intake at breakfast, lunch, and dinner was directly measured at baseline, week 1, and week 8. For Study 2, Sprague-Dawley rats were fasted for 24 h and subsequently injected intraperitoneally with 0, 1, 10, or 50 microg/kg CrPic. Subsequently, rats were implanted with an indwelling third ventricular cannula. Following recovery, 0, 0.4, 4, or 40 ng of CrPic was injected directly into the brain via the intracerebroventricular cannula, and spontaneous 24-h food intake was measured. RESULTS Study 1 demonstrated that CrPic, as compared to placebo, reduced food intake (P<0.0001), hunger levels (P<0.05), and fat cravings (P<0.0001) and tended to decrease body weight (P=0.08). In study 2, intraperitoneal administration resulted in a subtle decrease in food intake at only the highest dose (P=0.03). However, when administered centrally, CrPic dose-dependently decreased food intake (P<0.05). CONCLUSIONS These data suggest CrPic has a role in food intake regulation, which may be mediated by a direct effect on the brain.