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Objective Food cravings are thought to be the result of conditioning or pairing hunger with consumption of certain foods. Methods In a two-year weight loss trial, subjects were randomized to one of four diets that varied in macronutrient content. The Food Craving Inventory (FCI) was used to measure cravings at baseline, 6, and 24 months. Also, food intake was measured at those time points. To measure free-living consumption of food items measured in the FCI, items on the FCI were matched to the foods consumed from the food intake assessments. Secondarily, we analyzed the amount of food consumed on food intake assessments from foods on the FCI. Results 367 subjects who were overweight and obese were included. There was an association between change from baseline FCI item consumption and change in cravings at months 6 (p

When a hypocaloric, low-fat diet is prescribed, intake of currently consumed foods can decrease, foods naturally low in fat and/or added sugar may increase, or fat- or sugar-modified foods may increase.To examine food group intake change and its relation to reductions in energy and fat intake and weight during a lifestyle intervention.Secondary cohort analysis.One hundred sixty-nine participants (aged 52.0±8.6 years, body mass index 34.9±4.5, 92% white, 97.6% non-Hispanic, and 56.8% women) with complete data at 0 and 6 months collected in a research setting.From three 24-hour telephone dietary recalls, 165 food groups from Nutrition Data System for Research software were coded into 25 larger food groups assessing intake of higher-fat and/or added-sugar food groups vs naturally lower-fat and/or added-sugar food groups and into 17 larger food groups assessing intake of nonmodified vs fat- and/or sugar-modified food groups.Repeated measures analyses of covariance (intervention group: covariate) assessed changes from 0 to 6 months. Hierarchical regressions examined changes in food group intake and changes in energy intake, percent energy from fat intake, and weight from 0 to 6 months.Significant reductions (P0.05) in intake of high-fat and/or high-added-sugar food groups (Higher-Fat Dairy; Higher-Fat Eggs; Higher-Fat Fats; Higher-Fat Fruit; Higher-Fat Meat; Nonmodified Higher-Fat Fats, Oils, and Sweets; Nonmodified Higher-Fat Sugar-Sweetened Fats, Oils, and Sweets; Nonmodified Regular-Fat Dairy; and Nonmodified Regular-Fat Sugar-Sweetened Dairy) occurred. Decreases in the Higher-Fat Meat group were significantly (P0.05) related to decreases in energy intake, percent energy from fat intake, and weight.When a hypocaloric, low-fat diet is prescribed, reductions in high-fat and/or high-added-sugar food groups occur. Targeting reductions in high-fat meats may improve outcomes.

Objective To develop and validate the Weight Control Strategies Scale (WCSS), a self-report instrument to assess use of specific behaviors thought to facilitate weight loss. Design and Methods Factor analysis was conducted on 323 overweight and obese adults (mean age=48.7±10.9 years, mean BMI=35.4±4.9 kg/m2, 74% female) enrolled in three different behavioral weight loss trials who completed the WCSS prior to starting treatment. To evaluate construct validity, additional data on dietary intake, physical activity, treatment session attendance, and weight change were obtained from a subsample of participants before and after participation in a 48-week weight loss program. Results Principal components analysis with varimax rotation revealed a four component solution for the WCSS, representing the following subscales: Dietary Choices, Self-monitoring Strategies, Physical Activity, and Psychological Coping (a’s from 0.79–0.89). Longitudinal analyses showed that WCSS subscale scores increased during treatment (p’s

We propose that enjoyment is an important factor in the adoption and long-term maintenance of exercise. Television (TV) viewing is believed to be a highly enjoyed leisure-time activity, combining it with exercise may make for a more enjoyable exercise experience. The objective of this study was to examine the effects of television (TV) viewing on psychological and physiological variables during a moderate-intensity exercise bout. Twenty-eight insufficiently active ( 0.05) and dissociation from walking (self-selected TV: 38.1 ± 6.7 and standardized TV: 33.2 ± 3.9); they also resulted in more dissociation than the no TV condition (TV: 72.6 ± 5.6, p = 0.002). The findings indicate that TV viewing, regardless of whether the programming is self-selected or standardized, associates with greater enjoyment of exercise.

Objective: Food reinforcement and delay discounting (DD) independently predict body mass index (BMI), but there is no research studying whether these variables interact to improve prediction of BMI. Methods: BMI, the relative reinforcing value of high (PMAX(HED)) and low (PMAX(LED)) energy dense food, and DD for $ 10 and $ 100 future rewards (DD10, DD100) were measured in 199 adult females. Results: PMAX(HED) (P = 0.017), DD10 ( P = 0.003), and DD100 (P = 0.003) were independent predictors of BMI. The interaction of PMAX(LED) x DD10 (P = 0.033) and DD100 (P = 0.039), and PMAX(HED) x DD10 (P = 0.038) and DD100 (P = 0.045) increased the variance accounted for predicting BMI beyond the base model controlling for age, education, minority status, disinhibition, and dietary restraint. Based on the regression model, BMI differed by about 2 BMI units for low versus high food reinforcement, by about 3 BMI units for low versus high DD, and by about 4 BMI units for those high in PMAXHED, but low in DD versus high in PMAXHED and high in DD. Conclusion: Reducing DD may help prevent obesity and improve treatment of obesity in those who are high in food reinforcement.

Previous research suggests that reducing sedentary screen behaviors may be a strategy for preventing and treating obesity in children. This systematic review describes strategies used in interventions designed to either solely target sedentary screen behaviors or multiple health behaviors, including sedentary screen behaviors. Eighteen studies were included in this paper; eight targeting sedentary screen behaviors only, and ten targeting multiple health behaviors. All studies used behavior modification strategies for reducing sedentary screen behaviors in children (aged 1–12 years). Nine studies only used behavior modification strategies, and nine studies supplemented behavior modification strategies with an electronic device to enhance sedentary screen behaviors reductions. Many interventions (50%) significantly reduced sedentary screen behaviors; however the magnitude of the significant reductions varied greatly (−0.44 to −3.1 h/day) and may have been influenced by the primary focus of the intervention, number of behavior modification strategies used, and other tools used to limit sedentary screen behaviors.

The objective of this study was to examine the efficacy of U.S. primary care paediatric obesity treatment recommendations, within two randomized trials.Between November 2005 to September 2007, 182 families (children aged 4-9 years, body mass index [BMI] ≥85th percentile) were recruited for two separate trials and randomized within trial to a 6-month intervention. Each trial had one intervention that increased child growth-monitoring frequency and feedback to families (GROWTH MONITORING). Each trial also had two interventions, combining GROWTH MONITORING with an eight-session, behavioural, parent-only intervention targeting two energy-balance behaviours (Trial 1: reducing snack foods and sugar-sweetened beverages [DECREASE], and increasing fruits, vegetables and low-fat dairy [INCREASE]; Trial 2: decreasing sugar-sweetened beverages and increasing physical activity [TRADITIONAL] and increasing low-fat milk consumption and reducing television watching [SUBSTITUTES]). Child standardized BMI (ZBMI) and energy intake were assessed at 0, 6 and 12 months.In both trials, main effects of time were found for ZBMI, which decreased at 6 and 12 months (P 0.01). In Trial 1, ZBMI reduced from 0 to 6 months, which was maintained from 6 to 12 months (ΔZBMI 0 to 12 months = -0.12 ± 0.22). In Trial 2, ZBMI reduced from 0 to 6 and from 6 to 12 months (ΔZBMI 0-12 months = -0.16 ± 0.31). For energy intake, main effects of time were found in both trials and intake reduced from 0 to 6 months (P 0.05), with Trial 1 reducing intake from 0 to 12 months (P 0.05).All interventions improved weight status. Future research should examine effectiveness and translatability of these approaches into primary care settings.