Racial and ethnic minority enrollment in randomized clinical trials of behavioural weight loss utilizing technology: a systematic review.

Many racial and ethnic minority groups (minorities) are disproportionately affected by overweight and obesity; however, minorities are often under-represented in clinical trials of behavioural weight loss (BWL) treatment, potentially limiting the generalizability of these trials' conclusions. Interventions involving technology may be particularly well suited to overcoming the barriers to minority enrollment in BWL trials, such as demanding or unpredictable work schedules, caregiving responsibilities and travel burdens. Thus, this systematic review aimed to describe minority enrollment in trials utilizing technology in interventions, as well as to identify which form(s) of technology yield the highest minority enrollment. Results indicated relatively low enrollment of minorities. Trials integrating smartphone use exhibited significantly greater racial minority enrollment than trials that did not; trials with both smartphone and in-person components exhibited the highest racial minority enrollment. This review is the first to explore how the inclusion of technology in BWL trials relates to minority enrollment and can help address the need to improve minority enrollment in weight loss research.

Personal history of dieting and family history of obesity are unrelated: implications for understanding weight gain proneness.

Identifying predictors of future weight gain is important in obesity prevention efforts. Both family history of obesity and personal dieting history have been established as predictors of future weight gain; however, it is unknown if they are independent or overlapping predictors. The purpose of this study was to examine the degree of overlap between these two predictors using cross-sectional data. Baseline data from four studies were examined separately and in combination for a total of 561 female participants, and analyses were conducted to examine parent anthropometric variables by dieting status within and across studies. All participants were female university students between the ages of 17 and 30. For each study, as well as for the entire sample combined, parent anthropometric variables were examined by dieting status using factorial ANOVAs. No meaningful pattern was found when examining parent anthropometric variables by dieting status, which suggests that the two risk factors are largely independent. This suggests that the processes associated with the development of future weight gain by each variable are different; therefore, future research should use a longitudinal study to test the hypothesis that using both variables to predict future weight gain would account for more variance than using either variable alone.

The mind your health project: a randomized controlled trial of an innovative behavioral treatment for obesity.

OBJECTIVE: To determine whether acceptance-based behavioral treatment (ABT) would result in greater weight loss than standard behavioral treatment (SBT), and whether treatment effects were moderated by interventionist expertise or participants' susceptibility to eating cues. Recent research suggests that poor long-term weight-control outcomes are due to lapses in adherence to weight-control behaviors and that adherence might be improved by enhancing SBT with acceptance-based behavioral strategies. DESIGN AND METHODS: Overweight participants (n = 128) were randomly assigned to 40 weeks of SBT or ABT. RESULTS: Both groups produced significant weight loss, and when administered by experts, weight loss was significantly higher in ABT than SBT at post-treatment (13.17% vs. 7.54%) and 6-month follow-up (10.98% vs. 4.83%). Moreover, 64% of those receiving ABT from experts (vs. 46% for SBT) maintained at least a 10% weight loss by follow-up. Moderation analyses revealed a powerful advantage, at follow-up, of ABT over SBT in those potentially more susceptible to eating cues. For participants with greater baseline depression symptomology, weight loss at follow-up was 11.18% in ABT versus 4.63% in SBT; other comparisons were 10.51% versus 6.00% (emotional eating), 8.29% versus 6.35% (disinhibition), and 9.70% versus 4.46% (responsivity to food cues). Mediation analyses produced partial support for theorized food-related psychological acceptance as a mechanism of action. CONCLUSIONS: Results offer strong support for the incorporation of acceptance-based skills into behavioral weight loss treatments, particularly among those with greater levels of depression, responsivity to the food environment, disinhibition, and emotional eating, and especially when interventions are provided by weight-control experts.

Attrition from randomized controlled trials of pharmacological weight loss agents: a systematic review and analysis.

Clinical trials of obesity treatments have been limited by substantial dropout. Participant-level variables do not reliably predict attrition, and study-level variables have not yet been examined. We searched MEDLINE and identified 24 large randomized controlled trials of weight loss medications. These trials were comprised of 23 placebo and 32 drug groups. Two authors independently extracted the following for each treatment group: (i) treatment received; (ii) design characteristics (inclusion of a lead-in period, selection of participants with weight-related comorbidities, study location and number of study visits); (iii) sample characteristics (sample size, % female, and mean baseline age and body mass index); and (iv) attrition (total, adverse event [AE]-related and non-AE-related) at 1 year. The primary outcome was total attrition, which was significantly related to treatment (i.e. 34.9%, 28.6%, 28.3% and 35.1% in placebo, orlistat, sibutramine and rimonabant groups, respectively, P < 0.0001). In adjusted multivariable models, total attrition was significantly lower in groups that completed a pre-randomization lead-in period than in those that did not (29.1% vs. 39.9%, P < 0.01). Gender also was significantly related to total attrition; groups with more women had higher dropout (P < 0.01). The pattern was similar for predicting non-AE-related attrition. Findings suggest ways to design studies that maximize retention.