Internal disinhibition predicts weight regain following weight loss and weight loss maintenance

Objective: The disinhibition scale of the Eating Inventory predicts weight loss outcome; however, it may include multiple factors. The purpose of this study was to examine the factor structure of the disinhibition scale and determine how its factors independently relate to long‐term weight loss outcomes. Research Methods and Procedures: Exploratory factor analysis of the disinhibition scale was conducted on 286 participants in a behavioral weight loss trial (TRIM), and confirmatory factor analysis was conducted on 3345 members of the National Weight Control Registry (NWCR), a registry of successful weight loss maintainers. Multivariate regressions were used to examine the relationships between the disinhibition scale factors and weight over time in both samples. Results: Using baseline data from TRIM, two factors were extracted from the disinhibition scale: 1) an “internal” factor that described eating in response to internal cues, such as feelings and thoughts; and 2) an “external” factor that described eating in response to external cues, such as social events. This factor structure was confirmed using confirmatory factor analysis in the NWCR. In TRIM, internal disinhibition significantly predicted weight loss at 6 months (p = 0.03) and marginally significantly predicted weight loss at 18 months (p = 0.06), with higher levels of internal disinhibition at baseline predicting less weight loss; external disinhibition did not predict weight loss at any time‐point. In NWCR, internal disinhibition significantly predicted one‐year weight change (p = 0.001), while external disinhibition did not. Discussion: These results suggest that it is the disinhibition of eating in response to internal cues that is associated with poorer long‐term weight loss outcomes.     

Dietary adherence during weight loss predicts weight regain

This study examined the relationship between previous dietary adherence during a low-calorie diet weight loss intervention and subsequent weight change during a 2-year follow-up for weight maintenance. One hundred and sixteen healthy, recently weight reduced (lost ~12 kg, BMI 22-25 kg/m2) premenopausal women were studied. Dietary adherence was assessed by doubly labeled water (DLW) and body composition change. Comparisons were made between the upper and lower tertiles for previous dietary adherence and subsequent weight change at 1- and 2-year follow-up. Percent weight regained was significantly lower (30.9 ± 6.7% vs. 66.7 ± 9.4%; P < 0.05) in the upper compared to the lower adherence tertile for previous weight loss dietary adherence (49.9 ± 8.8% vs. 96.8 ± 12.8% P < 0.05) at 1- and 2-year follow-up, respectively. This difference was partly explained by increases in daily activity-related energy expenditure (AEE) (+95 ± 45 kcal/day vs. -44 ± 42 kcal/day, P < 0.05) and lower daily energy intake (2,066 ± 71 kcal/day vs. 2,289 ± 62 kcal/day, P < 0.05) in the higher tertile for previous dietary adherence, compared to the lower. These findings suggest that higher adherence (i.e., higher tertile) to the previous low-calorie diet predicts lower weight regain over 2-year follow-up for weight maintenance, which is explained by lower energy intake and higher physical activity. Finally, how well an individual adheres to a low-calorie diet intervention during weight loss may be a useful tool for identifying individuals who are particularly vulnerable to subsequent weight regain.     

Teammates and social influence affect weight loss outcomes in a team-based weight loss competition

Team-based internet interventions are increasing in popularity as a way of promoting weight loss in large numbers of individuals. Given that social networks influence health behavior change, this study investigated the effects of teammates and social influence on individual weight loss during a team-based weight loss competition. Shape Up Rhode Island (SURI) 2009 was a 12-week online program open to adult residents of Rhode Island. Participants joined with a team and competed with other teams on weight loss and/or physical activity. Overweight/obese (OW/OB) individuals (N = 3,330; 76% female; age = 46.1 ± 10.8; BMI = 31.2 ± 5.3 kg/m(2)), representing 987 teams, completed the weight loss program. Multilevel modeling was used to examine whether weight loss clustered among teammates and whether percentage of teammates in the weight loss division and reported teammate influence on weight loss were associated with individual weight outcomes. OW/OB completers reported losing 4.2 ± 3.4% of initial body weight. Weight loss was similar among teammates (intraclass correlation coefficient (ICC) = 0.10, P < 0.001). Moreover, having a greater percentage of teammates in the weight loss division and reporting higher social influence for weight loss were associated with greater percent weight loss (P's ≤ 0.002). Similarly, achieving a clinically significant (5%) weight loss tended to cluster within teams (ICC = 0.09; P < 0.001) and having more teammates in the weight loss division and higher social influence for weight loss were associated with increased likelihood of achieving a 5% weight loss (odds ratio (OR) = 1.06; OR = 1.20, respectively). These results suggest that teammates affect weight loss outcomes during a team-based intervention. Harnessing and maximizing teammate influence for weight loss may enhance weight outcomes in large-scale team-based programs.     

Leptin, superoxide dismutase, and weight loss: initial leptin predicts weight loss

Objective: Our goal was to study how plasma leptin concentration, superoxide dismutase (SOD) activity, and weight loss are related in obese adults. Research Methods and Procedures: Serum leptin concentration, SOD activities, general biochemical data, and body composition measurements were obtained for 62 overweight and obese subjects before and after an 8‐week body weight reduction (BWR) regimen. The subjects were on dietary control, performed moderate aerobic and strength training exercises, and attended educational lectures. Results: The measurement results indicated that the following criteria were significantly reduced: body weight [84.4 ± 17.0 vs. 79.3 ± 16.1 (standard error) kg, p < 0.001]; BMI (31.5 ± 4.3 vs. 29.4 ± 4.2 kg/m², p < 0.001), and fat mass (33.3 ± 10.0 vs. 29.8 ± 10.4 kg, p < 0.001). Plasma leptin levels also significantly decreased from 31.5 ± 17.6 to 26.5 ± 17.2 ng/mL (p < 0.001). Additionally, SOD activity was significantly increased from 261.4 ± 66.0 to 302.7 ± 30.9 U/mL (p < 0.001). Based on linear regression analysis results, a 3.78‐ to 8.13‐kg reduction in weight can be expected after the 8‐week BWR regimen when initial leptin concentration was 5 to 30 ng/mL. Discussion: We found that an 8‐week exercise and diet program was effective in reducing weight and fat mass and, notably, had further beneficial effects on leptin resistance and SOD activity. Additionally, this study demonstrated that initial plasma leptin concentration may be used as a predictor for weight loss outcome.     

Predictors of long-term weight loss in adults with modest initial weight loss, by sex and race

Effective weight management interventions could reduce race-sex disparities in cardiovascular disease (CVD), yet little is known about factors associated with successful weight loss maintenance in race-sex subgroups. In the Weight Loss Maintenance trial (WLM), overweight/obese (BMI 25-45 kg/m(2)) adults who lost ≥4 kg in a 6-month behavioral weight loss intervention (phase I) were randomized into one of three 30-month maintenance interventions (phase II). To investigate predictors in subgroups, randomized groups were combined for this analysis. Of 1,685 phase I participants, 1,032 (61%) entered phase II, including 12% black men (BM), 26% black women (BW), 25% white men (WM), and 37% white women (WW). Weight change over the 36-month study ranged from -2.3% (95% confidence interval = -3.1 to -1.5%) in BW to -4.5% (95% confidence interval = -5.7 to -4.0%) in WM, the result of differential weight loss during phase I. Within race, men lost significantly more weight than women, but within sex group, weight loss did not differ significantly between races. Although participants regained weight during phase II, regain did not differ by race-sex group, and mean weight at the end of the study was significantly lower than phase I entry weight for each subgroup. In regression models, phase I weight loss predicted overall 36-month weight loss in all race-sex groups. Healthy dietary pattern at entry, improvement in dietary pattern, or both were predictive in three of four race-sex groups. Few other variables other than initial weight loss and dietary pattern were predictive. Future research should identify additional modifiable influences on long-term maintenance after a modest weight loss.     

Adaptive thermogenesis with weight loss in humans

Adaptive thermogenesis (AT) with weight loss refers to underfeeding‐associated fall in resting and non‐resting energy expenditure (REE, non‐REE); this is independent of body weight and body composition. In humans, the existence of AT was inconsistently shown and its clinical significance has been questioned.

Objectives:

Discrepant findings are mainly due to different definitions of AT, the use of various and nonstandardized study protocols, and the limits of accuracy of methods to assess energy expenditure. With controlled underfeeding, AT takes more than 2 wk to develop. AT accounts to an average of 0.5 MJ (or 120 kcal) with a considerable between subject variance.

Design and Methods:

Low‐sympathetic nervous system activity, 3,5,3′‐tri‐iodothyronine (T3) and leptin are likely to add to AT; however, the kinetic changes of their plasma levels with underfeeding differ from the time course of AT and controlled intervention studies substituting and titrating these hormones are rare in humans. AT in response to underfeeding is independent of thermogenesis in response to either diet or cold. Although fat‐free mass (FFM) and, thus, liver, and skeletal muscle are considered as major sites of AT, cold‐induced nonshivering thermogenesis relates to the metabolism of brown adipose tissue (BAT). In humans, diet‐induced thermogenesis is related to postprandial substrate metabolism of FFM with a questionable role of BAT. Obviously, the REE component of AT differs from and its non‐REE component with respect to organ contribution as well as mechanisms. Thus, AT cannot be considered as unique.

Conclusions:

AT should be characterized based on individual components of daily energy expenditure, detailed body composition analyses, and mathematical modeling. The biological basis of AT as well as the influences of age, sex, obesity, stress, and inflammation remain to be established in humans.