Week-to-week predictors of weight loss and regain

Design of Project STAR: A randomized controlled trial evaluating the impact of an adaptive intervention on long-term weight-loss maintenance

BACKGROUND

Without provision of additional intervention, most individuals regain weight after the end of weight-loss programs. Extended-care programs have been demonstrated to improve long-term weight-loss maintenance, but effects are modest.

METHODS

We proposed to evaluate whether delivering extended-care telephone sessions on an ADAPTIVE (provided when individuals are deemed to be at high-risk for weight regain) versus STATIC (the once-per-month schedule typically used in extended-care programs) schedule improves weight regain after initial weight loss. Adults with obesity were initially recruited for a 16-week lifestyle weight-loss program, and those who lost ≥5 % of their initial weight were eligible for enrollment in the Project STAR maintenance trial.

RESULTS

A total of 449 individuals (mean ± SD age = 49.5 ± 11.4 years, BMI = 35.7 ± 4.0 kg/m2, 83.5 % female, 23.4 % Black or African American, 9.8 % Hispanic) were recruited for the initial weight-loss program and lost an average of 6.4 ± 4.9 % of their initial body weight; 255 were randomized to the maintenance trial. There were no significant differences between participants randomized to the trial versus those who were not in terms of baseline weight, gender, race/ethnicity, education, or marital status, all ps > 0.05; however, participants who were randomized to the trial were older, p = .014, and reported higher incomes, p < .001.

CONCLUSION

Results from Project STAR will demonstrate whether providing extended-care intervention on an individually adaptable schedule improves long-term weight-loss maintenance. Moreover, the rich longitudinal dataset collected during the trial will serve as a foundation for building future predictive algorithms of weight regain and novel weight-maintenance interventions.

Psychological and behavioral responses to daily weight gain during behavioral weight loss treatment

Self-weighing is consistently associated with more effective weight control. However, patterns show that participants disengage from their weight control behaviors following weight gain. Women with BMIs in the overweight/obese range (N = 50) enrolled in a long-term behavioral weight loss program completed ecological momentary assessment (EMA) surveys immediately after their daily weigh-ins. Nightly EMA surveys and self-monitoring data through Fitbit measured their weight control behavior that day. On days when participants gained weight (vs. lost or maintained), they reported more negative mood, more guilt/shame, and lower confidence in weight control. Motivation following daily weight gain depended on participants' overall satisfaction with their weight loss so far: more satisfied participants had marginally higher, but less satisfied participants had marginally lower motivation in response to daily weight gain. Greater guilt/shame and lower motivation after the weigh-in predicted less effective weight control behavior that day (e.g., lower likelihood of calorie tracking, fewer minutes of physical activity). Results demonstrate that even small weight gain is distressing and demoralizing for women in BWL programs, which can lead to goal disengagement. These findings have implications for future BWL interventions, including the potential utility of just-in-time adaptive interventions to promote more adaptive responses in the moments after weigh-ins.

MyTrack+: Human-centered design of an mHealth app to support long-term weight loss maintenance

A growing body of research has focused on the utility of adaptive intervention models for promoting long-term weight loss maintenance; however, evaluation of these interventions often requires customized smartphone applications. Building such an app from scratch can be resource-intensive. To support a novel clinical trial of an adaptive intervention for weight loss maintenance, we developed a companion app, MyTrack+, to pair with a main commercial app, FatSecret (FS), leveraging a user-centered design process for rapid prototyping and reducing software engineering efforts. MyTrack+ seamlessly integrates data from FS and the BodyTrace smart scale, enabling participants to log and self-monitor their health data, while also incorporating customized questionnaires and timestamps to enhance data collection for the trial. We iteratively refined the app by first developing initial mockups and incorporating feedback from a usability study with 17 university students. We further improved the app based on an in-the-wild pilot study with 33 participants in the target population, emphasizing acceptance, simplicity, customization options, and dual app usage. Our work highlights the potential of using an iterative human-centered design process to build a companion app that complements a commercial app for rapid prototyping, reducing costs, and enabling efficient research progress.

Identification of minimum thresholds for dietary self-monitoring to promote weight-loss maintenance

OBJECTIVE

Reduced schedules of dietary self-monitoring are typically recommended after the end of behavioral weight-loss programs; however, there exists little empirical evidence to guide these recommendations.

METHODS

We explored potential thresholds for dietary self-monitoring during a 9-month maintenance period following a 3-month weight-loss program in 74 adults with overweight or obesity (mean [SD] age = 50.7 [10.4] years, BMI = 31.2 [4.5] kg/m2) who were encouraged to self-monitor weight, dietary intake, and physical activity daily and report their adherence to self-monitoring each week via a study website.

RESULTS

Greater self-monitoring was correlated with less weight regain for thresholds of ≥3 days/week, with the largest benefit observed for thresholds of ≥5 to ≥6 days/week (all p < 0.05); significant weight gain was observed for thresholds of ≥1 to ≥2 days/week, whereas no change in weight was observed for thresholds of ≥3 to ≥4 days/week, and weight loss was observed with thresholds of ≥5 or more days/week.

CONCLUSIONS

Results demonstrate that self-monitoring at least 3 days/week may be beneficial for supporting long-term maintenance, although greater benefit (in relation to weight loss) may be realized at thresholds of 5 to 6 days/week. Future research should investigate whether individuals who were randomized to self-monitor at these different thresholds demonstrate differential patterns of weight-loss maintenance.

Characterising individual variability in associations between self-monitoring and weight change during and after a behavioral weight management program

Objective

Greater self-monitoring of caloric intake and weight has been associated with success at both initial weight loss and long-term maintenance. Given the existence of wide variability in weight loss outcomes and the key role of self-monitoring within behavioral weight management interventions, this study examined individual variability in associations between self-monitoring and weight change and whether demographic factors could predict who may best benefit from self-monitoring.

Methods

Participants were 72 adults with overweight or obesity (mean ± SD, age = 50.6 ± 10.3; body mass index = 31.2 ± 4.5 kg/m2; 71%Female; 83%White) enrolled in a 12-week weight loss program followed by a 40-week observational maintenance period. Participants were encouraged to self-monitor caloric intake and weight daily and to report these data via a study website each week. Multilevel mixed models were used to estimate week-to-week associations between self-monitoring and weight change, by individual and linear regressions and ANOVAs were used to explore demographic differences in these associations.

Results

Most participants (68%) demonstrated statistically significant negative associations between self-monitoring of either caloric intake or weight and weight change. Of these, 76% benefited from self-monitoring both caloric intake and weight, 18% from self-monitoring caloric intake only, and 6% from self-weighing only. The magnitude of associations between self-monitoring and weight change did not significantly differ by age, gender, race/ethnicity, education, or income, all ps > 0.05.

Conclusions

Differences in the effectiveness of self-monitoring for weight loss were not observed by demographic characteristics. Future research should examine if other factors may predict the effectiveness of self-monitoring.

Predicting high-risk periods for weight regain following initial weight loss

OBJECTIVE

The aim of this study was to develop a predictive algorithm of "high-risk" periods for weight regain after weight loss.

METHODS

Longitudinal mixed-effects models and random forest regression were used to select predictors and develop an algorithm to predict weight regain on a week-to-week basis, using weekly questionnaire and self-monitoring data (including daily e-scale data) collected over 40 weeks from 46 adults who lost ≥5% of baseline weight during an initial 12-week intervention (Study 1). The algorithm was evaluated in 22 adults who completed the same Study 1 intervention but lost <5% of baseline weight and in 30 adults recruited for a separate 30-week study (Study 2).

RESULTS

The final algorithm retained the frequency of self-monitoring caloric intake and weight plus self-report ratings of hunger and the importance of weight-management goals compared with competing life demands. In the initial training data set, the algorithm predicted weight regain the following week with a sensitivity of 75.6% and a specificity of 45.8%; performance was similar (sensitivity: 81%-82%, specificity: 30%-33%) in testing data sets.

CONCLUSIONS

Weight regain can be predicted on a proximal, week-to-week level. Future work should investigate the clinical utility of adaptive interventions for weight-loss maintenance and develop more sophisticated predictive models of weight regain.

Examining demographic and psychosocial factors related to self-weighing behavior during pregnancy and postpartum periods

Black childbearing individuals in the US experience a higher risk of postpartum weight retention (PPWR) compared to their White counterparts. Given that PPWR is related to adverse health outcomes, it is important to investigate predictors of weight-related health behaviors, such as self-weighing (i.e., using a scale at home). Regular self-weighing is an evidence-based weight management strategy, but there is minimal insight into sociodemographic factors related to frequency. The Postpartum Mothers Mobile Study (PMOMS) facilitated longitudinal ambulatory weight assessments to investigate racial inequities in PPWR. Our objective for the present study was to describe self-weighing behavior during and after pregnancy in the PMOMS cohort, as well as related demographic and psychosocial factors. Applying tree modeling and multiple regression, we examined self-weighing during and after pregnancy. Participants (N = 236) were 30.2 years old on average (SD = 4.7), with the majority being college-educated (53.8%, n = 127), earning at least $30,000 annually (61.4%, n = 145), and self-identifying as non-Hispanic White (NHW; 68.2%, n = 161). Adherence to regular self-weighing (at least once weekly) was highest among participants during pregnancy, with a considerable decline after giving birth. Low-income Black participants (earning < $30,000) were significantly less likely to reach a completion rate of ≥ 80% during pregnancy (AOR = 0.10) or the postpartum period (AOR = 0.16), compared to NHW participants earning at least $30,000 annually. Increases in perceived stress were associated with decreased odds of sustained self-weighing after delivery (AOR = 0.79). Future research should consider behavioral differences across demographic intersections, such as race and socioeconomic status, and the impact on efficacy of self-weighing.

Physical activity changes during an automated online weight loss program

Evidence-based online behavioral weight loss (BWL) treatment targets a combination of diet, physical activity, and behavioral skills training. While weight loss outcomes are well documented, little is known about changes in physical activity. This study examined changes in objectively measured physical activity across the energy expenditure spectrum during a fully automated, online BWL program. Adults with overweight or obesity (n = 63) completed a 12-week, online BWL program. Participants wore an accelerometer for 7 days and body weight was measured in-clinic at pre- and post-treatment. At post-treatment, mean daily moderate-to-vigorous physical activity increased by about 4 min (SE = 1.59, p = 0.01). There were no statistically significant changes in light physical activity or time spent sedentary (p's > 0.05). Despite only minimal changes in moderate-to-vigorous physical activity overall, larger increases correlated with greater weight loss (r = - 0.28, p = 0.02), which averaged 6.1% of baseline weight at post-treatment. Though achieving important weight loss outcomes, online programs may fail to produce clinically relevant improvements in physical activity, which can put weight loss maintenance at risk.

Hunger, temptation, and dietary adherence during weight management

Preliminary evidence suggests that hunger and temptation may predict nonadherence to dietary intake goals; however, no studies have investigated the potential interaction between hunger and temptation in relation to dietary nonadherence nor have any investigated whether these associations may be different after the end of active behavioral intervention. Thus, the current study examined the week-to-week associations between hunger, temptation, and dietary adherence in 74 adults with overweight or obesity (mean ± SD age = 50.7 ± 10.4, BMI = 31.2 ± 4.5 kg/m2) enrolled in a 12-week, Internet-based weight loss program followed by a 40-week post-intervention observational maintenance period. Each week during the study, participants completed a questionnaire on which they rated their hunger, temptation, and dietary adherence on 7-point scales. Multilevel models demonstrated that higher levels of hunger and temptation were associated with lower ratings of dietary adherence during the same week, ps < 0.0001, such that 1-point higher ratings of hunger or temptation were associated with 0.2- and 0.5-point lower ratings of dietary adherence, respectively. Further, there was an interaction between hunger and temptation such that the association between temptation and dietary nonadherence was stronger when ratings of hunger were lower, p = .028. There were no differences in associations between the initial weight loss period and the maintenance period. Results suggest that hunger and temptation may serve as potential treatment targets for interventions aimed at improving adherence to dietary intake goals. Future studies should investigate whether interventions targeting hunger and temptation can improve dietary adherence and weight loss outcomes.

Obesity in Adults: Position Statement of Polish Association for the Study on Obesity, Polish Association of Endocrinology, Polish Association of Cardiodiabetology, Polish Psychiatric Association, Section of Metabolic and Bariatric Surgery of the Association of Polish Surgeons, and the College of Family Physicians in Poland

Obesity in adults and its complications are among the most important problems of public health. The search was conducted by using PubMed/MEDLINE, Cochrane Library, Science Direct, MEDLINE, and EBSCO databases from January 2010 to December 2022 for English language meta-analyses, systematic reviews, randomized clinical trials, and observational studies from all over the world. Six main topics were defined in the joint consensus statement of the Polish Association for the Study on Obesity, the Polish Association of Endocrinology, the Polish Association of Cardio-diabetology, the Polish Psychiatric Association, the Section of Metabolic and Bariatric Surgery of the Society of Polish Surgeons, and the College of Family Physicians in Poland: (1) the definition, causes and diagnosis of obesity; (2) treatment of obesity; (3) treatment of main complications of obesity; (4) bariatric surgery and its limitations; (5) the role of primary care in diagnostics and treatment of obesity and barriers; and (6) recommendations for general practitioners, regional authorities and the Ministry of Health. This statement outlines the role of an individual and the adequate approach to the treatment of obesity: overcoming obstacles in the treatment of obesity by primary health care. The approach to the treatment of obesity in patients with its most common complications is also discussed. Attention was drawn to the importance of interdisciplinary cooperation and considering the needs of patients in increasing the long-term effectiveness of obesity management.

Recovery from weight regain among long-term weight loss maintainers in WW

OBJECTIVE

This study sought to understand the process and strategies to recover from regain among weight loss maintainers.

METHODS

Participants in WeightWatchers (WW; n = 2457) had lost ≥9 kg for ≥1 year and were grouped based on self-reported weight change after maximum loss: sustained maintenance ("Stable"), ups and downs ("Gain-Lose"), and regain ("Gain"). The groups were compared on weight control strategies, and the Gain-Lose and Gain groups reported on attempts to reverse weight regain.

RESULTS

Mean weight loss was 28.5 kg and duration of ≥9 kg loss was 3.5 years. During this time, 48% reported weight stability, and the remaining reported some regain (Gain-Lose, 29% or Gain, 23%). Among Gain and Gain-Lose, action to lose regained weight occurred after gaining >4 kg. Compared with Gain, Gain-Lose sustained reengagement efforts longer (16 vs. 10 weeks) and had better dietary choices (3.4 vs. 3.2), self-monitoring (2.9 vs. 2.7), and psychological coping (2.5 vs. 2.4) scores. Among Gain-Lose, the most successful (< 2.3 kg vs. >2.3 kg regain) initiated weight loss efforts after less regain (2.3 vs. 4.5 kg).

CONCLUSIONS

Reengaging with weight loss after regains may be most successful if focused on diet, self-monitoring, and psychological coping and initiated with less regain.

Behaviors and psychological states associated with transitions from regaining to losing weight

OBJECTIVE

Little is known about week-to-week recovery from regains following a behavioral weight loss intervention (BWLI). This study examined changes in behaviors, cognitions, and moods associated with transitioning from weight regain to weight loss during the nine-month weight loss maintenance period after a three-month Internet-based BWLI.

METHOD

Participants (n = 68) self-weighed daily via "smart" scales and answered 40 weekly questionnaires about their weight-related behaviors and psychological states. Mixed models were used to (a) determine whether weight gain in a given week predicted changes in weight, behaviors (e.g., self-monitoring), and psychological states (e.g., mood, temptation) the following week and to (b) compare back-to-back weeks when individuals recovered from weight gain (gained in the first week and lost in the second) versus those in which they gained both weeks.

RESULTS

Weight gain in a given week predicted greater weight gain and greater report of behaviors and psychological states associated with weight gain the following week. Back-to-back weeks when individuals switched from gaining to losing were few (5%) compared with weeks when individuals continued gaining (60%). Switching from gaining to losing was associated with greater physical activity during the initial weight gain week and greater self-reported behaviors/cognitions consistent with weight loss (e.g., greater calorie self-monitoring, greater importance of "staying on track") during the following week.

CONCLUSIONS

Engagement in more weight loss consistent behaviors and more favorable ratings of key psychological variables were associated with the rare shifts from gaining to losing. Future research should investigate interventions to help individuals quickly recover from weight regain. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Effect of Tailored, Daily Smartphone Feedback to Lifestyle Self-Monitoring on Weight Loss at 12 Months: The SMARTER Randomized Clinical Trial (Preprint)

Background

Self-monitoring (SM) is the centerpiece of behavioral weight loss treatment, but the efficacy of smartphone-delivered SM feedback (FB) has not been tested in large, long-term, randomized trials.

Objective

The aim of this study was to establish the efficacy of providing remote FB to diet, physical activity (PA), and weight SM on improving weight loss outcomes when comparing the SM plus FB (SM+FB) condition to the SM-only condition in a 12-month randomized controlled trial. The study was a single-site, population-based trial that took place in southwestern Pennsylvania, USA, conducted between 2018 and 2021. Participants were smartphone users age ≥18 years, able to engage in moderate PA, with a mean BMI between 27 and 43 kg/m².

Methods

All participants received a 90-minute, one-to-one, in-person behavioral weight loss counseling session addressing behavioral strategies, establishing participants’ dietary and PA goals, and instructing on use of the PA tracker (Fitbit Charge 2), smart scale, and diet SM app. Only SM+FB participants had access to an investigator-developed smartphone app that read SM data, in which an algorithm selected tailored messages sent to the smartphone up to 3 times daily. The SM-only participants did not receive any tailored FB based on SM data. The primary outcome was percent weight change from baseline to 12 months. Secondary outcomes included engagement with digital tools (eg, monthly percentage of FB messages opened and monthly percentage of days adherent to the calorie goal).

Results

Participants (N=502) were on average 45.0 (SD 14.4) years old with a mean BMI of 33.7 (SD 4.0) kg/m². The sample was 79.5% female (n=399/502) and 82.5% White (n=414/502). At 12 months, retention was 78.5% (n=394/502) and similar by group (SM+FB: 202/251, 80.5%; SM: 192/251, 76.5%; P=.28). There was significant percent weight loss from baseline in both groups (SM+FB: –2.12%, 95% CI –3.04% to –1.21%, P<.001; SM: –2.39%, 95% CI –3.32% to –1.47%; P<.001), but no difference between the groups (–0.27%; 95% CI –1.57% to 1.03%; t =–0.41; P=.68). Similarly, 26.3% (66/251) of the SM+FB group and 29.1% (73/251) of the SM group achieved ≥5% weight loss (chi-square value=0.49; P=.49). A 1% increase in FB messages opened was associated with a 0.10 greater percent weight loss at 12 months (b=–0.10; 95% CI –0.13 to –0.07; t =–5.90; P<.001). A 1% increase in FB messages opened was associated with 0.12 greater percentage of days adherent to the calorie goal per month (b=0.12; 95% CI 0.07-0.17; F=22.19; P<.001).

Conclusions

There were no significant between-group differences in weight loss; however, the findings suggested that the use of commercially available digital SM tools with or without FB resulted in a clinically significant weight loss in over 25% of participants. Future studies need to test additional strategies that will promote greater engagement with digital tools.

Trial Registration

Clinicaltrials.gov NCT03367936; https://clinicaltrials.gov/ct2/show/NCT03367936

The Relationship Between Weight Loss Outcomes and Engagement in a Mobile Behavioral Change Intervention: Retrospective Analysis

BACKGROUND

There is large variance in weight loss outcomes of digital behavior change interventions (DBCIs). It has been suggested that different patterns of engagement in the program could be responsible for this variance in outcomes. Previous studies have found that the amount of engagement on DBCIs, such as the number of meals logged or articles read, is positively associated with weight loss.

OBJECTIVE

This retrospective study extends previous research by observing how important weight loss outcomes (high weight loss: 10% or greater body weight loss; moderate weight loss: between 5% to 10%; stable weight: 0 plus or minus 1%) are associated with engagement on a publicly available mobile DBCI (Noom) from 9 to 52 weeks.

METHODS

Engagement and weight data for eligible participants (N=11,252) were extracted from the Noom database. Engagement measures included the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week. Weight was self-reported on the program. Multiple linear regressions examined how weight loss outcome (moderate and high vs stable) was associated with each engagement measure across 3 study time periods: 9-16 weeks, 17-32 weeks, and 33-52 weeks.

RESULTS

At 9-16 weeks, among the 11,252 participants, 2594 (23.05%) had stable weight, 6440 (57.23%) had moderate weight loss, and 2218 (19.71%) had high weight loss. By 33-52 weeks, 525 (18.21%) had stable weight, 1214 (42.11%) had moderate weight loss, and 1144 (39.68%) had high weight loss. Regression results showed that moderate weight loss and high weight loss outcomes were associated with all engagement measures to a significantly greater degree than was stable weight (all P values <.001). These differences held across all time periods with the exception of exercise for the moderate weight loss category at 1 time period of 33-52 weeks. Exercise logging increased from 9 to 52 weeks regardless of the weight loss group.

CONCLUSIONS

Our results suggest that these clinically important weight loss outcomes are related to the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week both in the short-term and long-term (ie, 1 year) on Noom. This provides valuable data on engagement patterns over time on a self-directed mobile DBCI, can help inform how interventions tailor recommendations for engagement depending on how much weight individuals have lost, and raises important questions for future research on engagement in DBCIs.

Randomized trial of a novel lifestyle intervention compared with the Diabetes Prevention Program for weight loss in adult dependents of military service members

BACKGROUND

Lifestyle interventions are the first-line treatment for obesity, but participant weight loss is typically low.

OBJECTIVES

We evaluated the efficacy of an alternative lifestyle intervention [Healthy Weight for Living (HWL)] compared with a modified Diabetes Prevention Program (m-DPP). HWL was based on a revised health behavior change model emphasizing hunger management and the development of healthy food preferences. m-DPP was a standard Diabetes Prevention Program implemented with counselor time matched to HWL. Participants were adult dependents of military personnel and had overweight or obesity.

METHODS

Participants were randomly assigned to HWL (n = 121) or m-DPP (n = 117), delivered primarily by group videoconference with additional midweek emails. The primary outcome was 12-mo weight change. Secondary outcomes included 6-mo changes in cardiometabolic risk factors and diet. Intention-to-treat (ITT) and complete case (CC) analyses were performed using linear mixed models.

RESULTS

Retention did not differ between groups (72% and 66% for HWL and m-DPP at 12 mo, respectively; P = 0.30). Mean ± SE adjusted 12-mo weight loss in the ITT cohort was 7.46 ± 0.85 kg for HWL and 7.32 ± 0.87 kg for m-DPP (P = 0.91); in the CC cohort, it was 7.83 ± 0.82 kg for HWL and 6.86 ± 0.88 kg for m-DPP (P = 0.43). Thirty-eight percent of HWL and 30% of m-DPP completers achieved ≥10% weight loss (P = 0.32). Improvements in systolic blood pressure, LDL cholesterol, triglycerides, fasting glucose, general health, sleep, and mood were similar across groups; improvements in diastolic blood pressure were greater in m-DPP. Adjusted group mean reductions in energy intake were not significantly different between groups, but HWL participants were more adherent to their dietary prescription for lower glycemic index and high fiber and protein (P = 0.05 to <0.001 for ITT).

CONCLUSIONS

HWL and m-DPP showed equivalent and clinically impactful mean weight loss with cardiometabolic benefits. These results identify an alternative approach for behavioral treatment of overweight and obesity.This trial was registered at clinicaltrials.gov as NCT02348853.

How Do Emotions during Goal Pursuit in Weight Change over Time? Retrospective Computational Text Analysis of Goal Setting and Striving Conversations with a Coach during a Mobile Weight Loss Program

During behavioral weight management, individuals reflect on their progress and barriers through goal pursuit (goal setting and goal striving). Emotions during goal pursuit are largely unknown, and previous investigations of emotions in weight management have primarily relied on self-report. In this retrospective study, we used a well-validated computational text analysis approach to explore how emotion words changed over time during goal setting and striving conversations with a coach in a mobile weight loss program. Linear mixed models examined changes in emotion words each month from baseline to program end and compared emotion words between individuals who set an overall concrete goal for the program (concrete goal setters) and those who set an overall abstract goal (abstract goal setters). Contrary to findings using self-report, positive emotion words were stable and negative emotion words significantly increased over time. There was a marginal trend towards greater negative emotion word use being associated with greater weight loss. Concrete goal setters used more positive words than abstract goal setters, with no differences in negative emotion words and weight loss. Implications include the possibility that individuals may need increasing support over time for negative emotions expressed during goal setting and striving, and concrete goals could boost positive emotion. Future research should investigate these possibilities.

Food reward sensitivity, impulsivity, and weight change during and after a 3-month weight loss program

Background

Greater sensitivity to food rewards and higher levels of impulsivity (and an interaction between these variables, termed “reinforcement pathology”) have been associated with obesity in cross-sectional studies. Less is known regarding how these constructs may impact attempts at weight loss or longer-term weight loss maintenance.

Methods

We provided 75 adults (69%Female, 84%White, age = 50.8y, BMI = 31.2kg/m²) with a 3-month Internet-based weight loss program and assessed weight, food reward sensitivity (via the Power of Food Scale [PFS]), and impulsivity (via Go No-Go [GNG] and Delay Discounting [DD] computer tasks) at baseline and at Months 3, 6, 9, and 12. No additional intervention was provided Months 3–12. Multi-level mixed-effect models were used to examine changes in PFS, GNG, and DD over time and associations between these measures and weight loss/regain.

Results

Participants lost 6.0±1.1kg Months 0–3 and regained 2.4±1.1kg Months 3–12. Across time points, higher PFS scores were associated with higher weight, p = .007; however, there were no significant associations between GNG or DD and weight nor between the interactions of PFS and GNG or DD and weight, ps>.05. There were significant decreases from Months 0–3 in PFS, GNG, and DD, ps < .05; however, neither baseline values nor changes were significantly associated with weight change and there were no significant associations between the interactions of PFS and GNG or DD and weight change, ps>.05.

Conclusion

Results demonstrated an association between food reward sensitivity and weight. Further, decreases in both food reward sensitivity and impulsivity were observed during an initial weight loss program, but neither baseline levels nor improvements were associated with weight change. Taken together, results suggest that the constructs of food reward sensitivity, impulsivity, and reinforcement pathology may have limited clinical utility within behavioral weight management interventions. Future intervention studies should examine whether food-related impulsivity tasks lead to a similar pattern of results.

Associations between effort, importance, and self-monitoring during and after a 12-week behavioural weight management program

Objective

Self‐monitoring of weight and caloric intake has been associated with improved weight loss and weight loss maintenance in behavioural weight loss programs; however, participants' adherence to self‐monitoring tends to decrease over time. To identify potential barriers to self‐monitoring adherence, the current study examined week‐to‐week associations between ratings of perceived effort, relative importance of weight loss goals, and adherence to self‐monitoring of weight and caloric intake during and after a behavioural weight loss programme.

Method

Participants were 74 adults with overweight and obesity enrolled in a 12‐week, Internet‐based weight loss programme followed by a 40‐week “maintenance” period during which no additional intervention was provided. Participants self‐reported adherence to self‐monitoring and completed ratings of effort and importance on a study website weekly throughout the study period (1 year).

Results

Longitudinal multilevel models demonstrated that higher ratings of effort were associated with fewer days of self‐monitoring of weight, β = −0.100, p < .0001, and caloric intake, β = −0.300, p < .0001. Conversely, higher ratings of importance were associated with more frequent self‐monitoring of weight, β = 0.360, p < .0001, and caloric intake, β = 0.742, p < .0001. Moreover, the magnitude of these associations were stronger during the maintenance period than during initial intervention, ps < .01.

Conclusions

Perceptions of effort and importance are both independently associated with adherence to self‐monitoring weight and caloric intake, and this effect appears to be stronger after the end of initial intervention. Future research should investigate whether tailoring intervention content based on these constructs can improve adherence to self‐monitoring.

Frequency and Consistency of Self-Weighing to Promote Weight-Loss Maintenance

OBJECTIVE

This study aimed to investigate the roles of frequency and consistency of self-weighing in promoting weight-loss maintenance.

METHODS

Participants were 74 adults who completed a 3-month internet-based weight-loss program followed by a 9-month no-intervention maintenance period. Frequency of self-weighing was defined as the number of days that participants self-weighed during the maintenance period via a study-provided smart scale. Consistency was defined as the number of weeks that participants self-weighed at a certain frequency, with multiple minimum thresholds examined. Hierarchical regression analyses were used to assess associations among frequency, consistency, and weight change during the maintenance period.

RESULTS

Greater consistency was significantly associated with less weight regain when defined as the number of weeks that participants self-weighed on ≥6 d/wk or 7 d/wk (P values < 0.05). Contrary to hypotheses, frequency was not associated with weight change (P = 0.141), and there was not a significant interaction between frequency and consistency.

CONCLUSIONS

Results demonstrate that consistency of self-weighing may be more important than total frequency for preventing weight regain after the end of a weight-loss program. Further, results suggest that a high level of consistency (self-weighing for ≥6 d/wk or 7 d/wk) may be necessary to promote successful weight-loss maintenance.

Weight change among repeat participants of an Aboriginal community-based weight loss program

Background

Community-based weight loss programs may have potential to address overweight and obesity at the population level. However, participation patterns and individual outcomes from these programs are understudied. This study examined repeat participation patterns and participant weight change between contests over seven years of an Aboriginal Australian team-based program in order to identify (1) predictors of repeat participation and (2) associations with weight change between contests.

Methods

Data for the 12 contests from 2012 to 2018 were merged, with probabilistic record matching. A total of 7510 enrolments were registered for the 12 contests, representing 4438 unique people. Contest lengths varied from 10 to 16 weeks in duration. Non-repeat participants were those who only competed once in the program by the end of 2018, and repeaters were those who competed in at least two contests. Associations between repeat participation and participant baseline (i.e., first participation occasion) characteristics, change in diet and physical activity and percent change in weight during the first participation occasion were examined using crossed random effects (for person and team) regression adjusted for exposure to the program. Weight percentage change between contests was calculated for consecutive participation occasions occurring at least three months apart, converted to percent change per month. Weight change was regressed on number of repeat participation occasions adjusted for age, gender, baseline weight at first participation occasion, and weight percent change in the immediately preceding contest.

Results

One-third of the 4433 participants participated more than once, with women more likely than men to repeat. A 1% reduction in weight during a competition was associated with an increase in weight of 0.05% per month between competition end and subsequent participation. Regain was smaller the heavier participants were at their first participation.

Conclusions

While individuals benefit from weight loss through program participation, strengthening strategies for weight loss maintenance within or following the program could improve long-term weight outcomes and reduce weight cycling.

The need for a living donor wellness program

PURPOSE OF REVIEW

Living donation has a tremendous impact in bridging the gap between the shortage of organs and the growing list of transplant candidates but remains underutilized as a percentage of total transplants performed. This review focuses on obesity and social determinants of health as potential barriers to the expansion of living kidney donation.

RECENT FINDINGS

The growing rate of obesity and associated metabolic syndrome make many potential donors unacceptable as donor candidates because of the future risk for developing chronic health conditions, such as hypertension and diabetes. There is also increasing evidence demonstrating socioeconomic differences and racial disparities potentially limit access to living donation in certain populations. These potentially modifiable factors are not exclusive of each other and together serve as significant contributing factors to lower rates of living donation.

SUMMARY

Living donors make sacrifices to provide the gift of life to transplant recipients, despite the potential risks to their own health. Studies describing risk factors to living donation call attention to the overall need for more action to prioritize and promote the health and well being of living donors.

Bidirectional association between stress and physical activity in adults with overweight and obesity

Research has suggested that there may be a bidirectional association between stress and physical activity; however, much of this work has been conducted in athletes or adults with normal weight. The current study investigated the bidirectional association between stress and physical activity in adults with overweight and obesity. For a full year, during and after a 12-week, Internet-based weight loss program, 74 participants (BMI = 31.2 kg/m²) were asked to report stress and minutes of physical activity each week. An increase in stress was associated with less physical activity during the same week and predicted fewer minutes of physical activity the following week. Finally, each 1 h increase in physical activity on a given week was associated with a small decrease in stress ratings the following week. Results confirmed the bidirectional association between stress and physical activity in a sample of adults with overweight/obesity, and supported results highlighting stress as a barrier to physical activity. Future studies should investigate whether adding intervention components to decrease stress or to reinforce physical activity can improve physical activity engagement in this population.