The Relationship Between Intuitive Eating and Postpartum Weight Loss.

Objective Postpartum weight loss is challenging for new mothers who report limited time and difficulties following traditional weight loss methods. Intuitive eating (IE) is a behavior that includes eating based on physical hunger and fullness and may have a role in encouraging weight loss. The purpose of this study was to examine the relationship between IE and postpartum weight loss. Methods Women 12-18 months postpartum completed a questionnaire regarding weight changes surrounding pregnancy, exercise, breastfeeding and intuitive eating using the Intuitive Eating Scale. Latent growth curve modeling was utilized to determine the relationship between IE, breastfeeding, weight gain during pregnancy, and postpartum weight trajectories. Results Participants (n = 50) were 28.5 ± 4.9 years old, had an average pre-pregnancy BMI of 26.4 ± 6.8 and the majority were married, and non-Hispanic white. The conditional model revealed that more intuitive eating practices predicted greater postpartum BMI decreases (Est. = -0.10, p < .05) when controlling for breastfeeding duration, exercise duration, and initial BMI and pregnancy BMI changes. Greater pregnancy BMI increases were associated with more rapid postpartum BMI decreases (Est. = -0.34, p < .001) while breastfeeding duration, exercise and initial BMI were not related. Conclusions for Practice Postpartum weight retention is a challenge for many women. Following a more intuitive eating approach to food consumption may encourage postpartum weight loss without the required weighing, measuring, recording and assessing dietary intake that is required of traditional weight loss programs. IE could offer an alternative approach that may be less arduous for new mothers.

THE EFFECT OF BLOOD GLUCOSE ON QUIET STANDING BALANCE IN YOUNG HEALTHY INDIVIDUALS.

Falling is one of the leading causes of accidental injury and death among elderly adults and construction workers, with costs exceeding US$31 billion each year. Having good balance reduces the likelihood of falling - therefore it is important to determine which possible factors might influence balance. The purpose of this study was to determine if consuming three different types of breakfast altered blood glucose levels in such a way that young healthy individual's balance control was compromised. Balance was then measured while the subjects completed single- and dual-task standing trials with eyes open and closed. Although changing blood glucose did alter quiet standing balance - as measured by the separation distance between the COG and COP, the velocity of the COM, and the total distance traveled by the COG and COP along the anterior-posterior (AP) and medial-lateral (ML) axes - the results were contradictory to what was hypothesized. Subjects with lower blood glucose swayed less than those with higher blood glucose. This could potentially be due to the habitual skipping of breakfast in young adults. Though the changing of blood glucose did influence quiet standing balance of young healthy adults, it was not in a way which increased the risk of falling.

Sources of food group intakes among the US population, 2001-2002.

BACKGROUND: Food guides are typically built around a system of food groups. Accordingly, the US Department of Agriculture's MyPyramid includes both food groups and subgroups, as well as an allowance for discretionary calories, in its guidance. OBJECTIVE: To identify the major dietary contributors to food group intake in the US population. METHODS: This cross-sectional study used 2001-2002 National Health and Nutrition Examination Survey data to determine weighted population proportions for the contribution of each subgroup to its MyPyramid food group (ie, proportion), and the contribution of specific foods to the subgroups oils, solid fats, and added sugars (ie, major contributors). Food codes associated with each food were sorted into 96 categories, termed specific foods, and were linked to the MyPyramid Equivalents Database to obtain food group equivalents. RESULTS: In regard to proportion, dark green vegetables (6%), orange vegetables (5%), and legumes (6%) fell well short of recommended levels. Intake of whole grains (10% of total) was far below the recommendation that at least half of all grains be whole. In regard to major contributors, top sources of oils were potato chips, salad dressing, and nuts/seeds; major contributors of solid fats were grain-based desserts, cheese, and sausages. Sweetened carbonated beverages provided 37% of added sugars. CONCLUSIONS: Americans do not, in general, consume the most nutrient-dense forms of basic food groups, instead consuming foods that are high in solid fats and added sugars. The main culprits-the foods that contribute most to discrepancies between recommendations and actual intake-are sweetened carbonated beverages and other sweetened beverages, grain-based desserts, nonskim dairy products, and fatty meats.

Reported Influences on Restaurant-Type Food Selection Decision Making in a Grocery Store Chain.

OBJECTIVE: To examine food decision-making priorities for restaurant-type foods at grocery stores and determine whether adding calorie information, as required by federal menu labeling laws, affected decision-making priorities. DESIGN: Natural experiment: intervention and control groups with baseline and follow-up. SETTING: Regional grocery store chain with 9 locations. PARTICIPANTS: Participants (n = 393; mean age, 54.8 ± 15.1 years) were primarily women (71%) and Caucasian (95%). INTERVENTION: Data were collected before and after calorie information was added to restaurant-type foods at 4 intervention locations. MAIN OUTCOME MEASURE(S): Primary influencers of food selection decision making for restaurant-type foods and frequency of use of nutrition information. ANALYSIS: Quantitative analysis examined the top 3 influencers of food selections and chi-square goodness of fit test determined whether the calorie labeling intervention changed food decision-making priorities. Qualitative data were used to describe responses. RESULTS: Taste, cost, and convenience were the most frequently reported influencers of restaurant-type food selections; 20% of participants rated calories as influential. Calorie labeling did not affect food selection decision making; 16% of participants in intervention stores noticed calorie labels. Qualitative explanations confirmed these findings. CONCLUSIONS AND IMPLICATIONS: Menu labeling laws increase access to calorie information; however, use of this information is limited. Additional interventions are needed to encourage healthier restaurant-type food selections in grocery stores.

Meaningful weight loss in obese postmenopausal women: a pilot study of high-intensity interval training and wearable technology.

OBJECTIVE: Postmenopausal women cite lack of time as their primary barrier to exercise and related weight control behaviors. The purpose of this study was to address this barrier via testing the feasibility and initial outcomes of a short-duration/high-intensity interval training (HIIT)-based weight loss program among obese postmenopausal women, with descriptive comparison to an endurance-focused exercise program. METHODS: A 16-week behavioral program incorporated (1) HIIT to limit time necessary to produce health benefits of exercise, and (2) wearable activity sensors to facilitate self-monitoring exercise. Participants (n = 11; MAge = 59 ±â€Š5.33; MBMI = 32.0 ±â€Š2.53 kg/m) were randomly assigned to HIIT or endurance exercise. Both groups followed a calorie-restricted diet, attended monthly in-person meetings, weekly weigh-ins and electronic check-ins to review behavioral skills, and monitored their exercise with a Fitbit ChargeHR. Adherence to exercise programs, assessed with the Fitbit sensor, was used to determine feasibility. RESULTS: Participants in the HIIT group (6/6) adhered to their program, whereas 3 of 5 adhered to the Endurance program. Participants in the HIIT group lost twice as much weight as those in the Endurance group (8.7% vs 4.3% of initial body weight), and lost an additional 6 in. of body mass. In addition, only the HIIT group significantly changed fat mass, body mass index, and fat-free mass (Ps < 0.04). CONCLUSIONS: These findings support the feasibility and potential effectiveness of HIIT for weight loss and body composition changes in obese postmenopausal women, and indicate that additional investigation of this approach is warranted to reduce postmenopausal chronic disease risk.

Exercising in the Fasted State Reduced 24-Hour Energy Intake in Active Male Adults.

The effect of fasting prior to morning exercise on 24-hour energy intake was examined using a randomized, counterbalanced design. Participants (12 active, white males, 20.8 ± 3.0 years old, VO2max: 59.1 ± 5.7 mL/kg/min) fasted (NoBK) or received breakfast (BK) and then ran for 60 minutes at 60% VO2max. All food was weighed and measured for 24 hours. Measures of blood glucose and hunger were collected at 5 time points. Respiratory quotient (RQ) was measured during exercise. Generalized linear mixed models and paired sample t-tests examined differences between the conditions. Total 24-hour (BK: 19172 ± 4542 kJ versus NoBK: 15312 ± 4513 kJ; p < 0.001) and evening (BK: 12265 ± 4278 kJ versus NoBK: 10833 ± 4065; p = 0.039) energy intake and RQ (BK: 0.90 ± 0.03 versus NoBK: 0.86 ± 0.03; p < 0.001) were significantly higher in BK than NoBK. Blood glucose was significantly higher in BK than NoBK before exercise (5.2 ± 0.7 versus 4.5 ± 0.6 mmol/L; p = 0.025). Hunger was significantly lower for BK than NoBK before exercise, after exercise, and before lunch. Blood glucose and hunger were not associated with energy intake. Fasting before morning exercise decreased 24-hour energy intake and increased fat oxidation during exercise. Completing exercise in the morning in the fasted state may have implications for weight management.

Greater energy reduction in 6-n-propylthiouracil (PROP) super-tasters as compared to non-tasters during a lifestyle intervention.

Little is known as to how 6-n-propylthiouracil (PROP) taster status may influence changes in dietary intake in adults participating in a lifestyle intervention to assist with reducing weight. This secondary data analysis examined changes in energy, percent energy from macronutrients, and food group intake; physical activity; and body mass index (BMI) in super-tasters and non-tasters participating in two randomized controlled trials implementing a lifestyle obesity intervention. One trial focused on lowering energy density of the diet and the other trial focused on changing eating frequency. Overweight and obese participants (n = 57) who completed measures of dietary intake, physical activity, and anthropometrics at 0 and 3 months were included in the analyses. Taster status was determined at baseline: 46 non-tasters and 11 super-tasters. After controlling for condition assignment and baseline values, results indicated that a significantly greater reduction in energy intake occurred for super-tasters as compared to non-tasters (-1149 ± 561 kcal/day vs. -902 ± 660 kcal/day, p < 0.05). No other significant differences in changes in dietary intake, physical activity, or BMI were found. These results suggest that in situations of reducing energy intake, overweight and obese super-tasters may be more successful than overweight and obese non-tasters. More research is needed to understand the influence of taster-status on dietary change during a lifestyle intervention and how this may impact weight loss.

Effects of manipulating eating frequency during a behavioral weight loss intervention: a pilot randomized controlled trial.

Eating frequency has been inversely related to BMI but the impact of eating frequency on weight loss is unclear. This randomized controlled trial pilot study examined the effect of eating frequency on hunger, energy intake, and weight loss during a 6-month behavioral weight loss intervention. Participants (age: 51.0 ± 9.9 years, BMI: 35.5 ± 4.8 kg/m(2), 57.8% female, 94.1% white) were randomized to one of two eating frequency prescriptions: Three meal (n = 25): three eating bouts/day; or grazing (n = 26): eat at least 100 kcals every 2-3 h. Both groups attended 20 sessions and had identical dietary (1,200-1,500 kcals/day, <30% kcals from fat) and physical activity goals (200 min/week). Assessments were conducted at 0, 3, and 6 months. Using intent-to-treat analyses, grazing reported a greater eating frequency than three meal at 6 months (5.8 ± 1.1 eating bouts/day vs. 3.2 ± 0.6 eating bouts/day, P < 0.001). Grazing reported a significant reduction in hunger from 0 to 6 months (56.3 ± 15.7 mm vs. 47.9 ± 18.5 mm, P < 0.05). Energy intake and BMI were significantly (P < 0.001) reduced from 0 to 6 months (energy intake: 2,198 ± 692 kcals/day vs. 1,266 ± 353 kcals/day; BMI: 35.5 ± 4.8 kg/m(2) vs. 30.6 ± 4.9 kg/m(2)). There were no significant differences in energy intake or BMI between the groups. While eating more frequently reduced hunger, it may not be related to greater reductions in energy intake or BMI during a behavioral weight loss intervention.

Eating frequency is higher in weight loss maintainers and normal-weight individuals than in overweight individuals.

Eating frequency has been negatively related to body mass index (BMI). The relationship between eating frequency and weight loss maintenance is unknown. This secondary analysis examined eating frequency (self-reported meals and snacks consumed per day) in weight loss maintainers (WLM) who had reduced from overweight/obese to normal weight, normal weight (NW) individuals, and overweight (OW) individuals. Data collected July 2006 to March 2007 in Providence, RI, included three 24-hour dietary recalls (2 weekdays, 1 weekend day) analyzed using Nutrient Data System for Research software from 257 adults (WLM n=96, 83.3% women aged 50.0±11.8 years with BMI 22.1±1.7; NW n=80, 95.0% women aged 46.1±11.5 years with BMI 21.1±1.4; OW n=81, 53.1% women aged 51.4±9.0 years with BMI 34.2±4.1) with plausible intakes. Participant-defined meals and snacks were ≥50 kcal and separated by more than 1 hour. Self-reported physical activity was highest in WLM followed by NW, and then OW (3,097±2,572 kcal/week, 2,062±1,286 kcal/week, and 785±901 kcal/week, respectively; P<0.001). Number of daily snacks consumed was highest in NW, followed by WLM, and then OW (2.3±1.1 snacks/day, 1.9±1.1 snacks/day, and 1.5±1.3 snacks/day, respectively; P<0.001). No significant group differences were observed in mean number of meals consumed (2.7±0.4 meals/day). Eating frequency, particularly in regard to a pattern of three meals and two snacks per day, may be important in weight loss maintenance.

Dietary energy density and successful weight loss maintenance.

Research shows a positive relationship between dietary energy density (ED) and body mass index (BMI), but dietary ED of weight loss maintainers is unknown. This preliminary investigation was a secondary data analysis that compared self-reported dietary ED and food group servings consumed in overweight adults (OW: BMI=27-45kg/m(2)), normal weight adults (NW: BMI=19-24.9 kg/m(2)), and weight loss maintainers (WLM: current BMI=19-24.9kg/m(2) [lost≥10% of maximum body weight and maintained loss for ≥5years]) participating in 2 studies, with data collected from July 2006 to March 2007. Three 24-h phone dietary recalls from 287 participants (OW=97, NW=85, WLM=105) assessed self-reported dietary intake. ED (kcal/g) was calculated by three methods (food+all beverages except water [F+AB], food+caloric beverages [F+CB], and food only [FO]). Differences in self-reported consumption of dietary ED, food group servings, energy, grams of food/beverages, fat, and fiber were assessed using one-way MANCOVA, adjusting for age, sex, and weekly energy expenditure from self-reported physical activity. ED, calculated by all three methods, was significantly lower in WLM than in NW or OW (FO: WLM=1.39±0.45kcal/g; NW=1.60±0.43 kcal/g; OW=1.83±0.42 kcal/g). Self-reported daily servings of vegetables and whole grains consumed were significantly higher in WLM compared to NW and OW (vegetables: WLM=4.9±3.1 servings/day; NW=3.9±2.0 servings/day; OW=3.4±1.7 servings/day; whole grains: WLM=2.2±1.8 servings/day; NW=1.4±1.2 servings/day; OW=1.3±1.3 servings/day). WLM self-reported consuming significantly less energy from fat and more fiber than the other two groups. Self-reported energy intake per day was significantly lower in WLM than OW, and WLM self-reported consuming significantly more grams of food/beverages per day than OW. These preliminary findings suggest that consuming a diet lower in ED, characterized by greater intake of vegetables and whole grains, may aid with weight loss maintenance and should be further tested in prospective randomized controlled trials.