Accuracy of Self-Report Versus Objective Smart-Scale Weights During a 12-Week Weight Management Intervention

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.

A low-burden, self-weighing intervention to prevent weight gain in adults with obesity who do not enroll in comprehensive treatment

Background

For individuals who are eligible but unlikely to join comprehensive weight loss programs, a low burden self-weighing intervention may be a more acceptable approach to weight management.

Methods

This was a single-arm feasibility trial of a 12-month self-weighing intervention. Participants were healthcare patients with a BMI ≥25 kg/m2 with a weight-related comorbidity or a BMI >30 kg/m2 who reported lack of interest in joining a comprehensive weight loss program, or did not enroll in a comprehensive program after being provided program information. In the self-weighing intervention, participants were asked to weigh themselves daily on a cellular connected scale and were sent text messages every other week with tailored weight change feedback, including messages encouraging use of comprehensive programs if weight gain occurred.

Results

Of 86 eligible patients, 39 enrolled (45.3%) in the self-weighing intervention. Self-weighing occurred on average 4.6 days/week (SD = 1.4). At 12 months, 12 participants (30.8%) lost ≥3% baseline weight, 11 (28.2%) experienced weight stability (±3% baseline), 6 (15.4%) gained ≥3% of baseline weight, and 10 (25.6%) did not have available weight data to evaluate. Three participants reported joining a weight loss program during the intervention (7.7%). Participants reported high intervention satisfaction in quantitative ratings (4.1 of 5), and qualitative interviews identified areas of satisfaction (e.g., timing and content of text messages) and areas for improvement (e.g., increasing personalization of text messages).

Conclusion

A low-burden self-weighing intervention can reach adults with overweight/obesity who would be unlikely to engage in comprehensive weight loss programs; the efficacy of this intervention for preventing weight gain should be further evaluated in a randomized trial.

#4Corners4Health Social Media Cancer Prevention Campaign for Emerging Adults: Protocol for a Randomized Stepped-Wedge Trial

BACKGROUND

Many emerging adults (EAs) are prone to making unhealthy choices, which increase their risk of premature cancer morbidity and mortality. In the era of social media, rigorous research on interventions to promote health behaviors for cancer risk reduction among EAs delivered over social media is limited. Cancer prevention information and recommendations may reach EAs more effectively over social media than in settings such as health care, schools, and workplaces, particularly for EAs residing in rural areas.

OBJECTIVE

This pragmatic randomized trial aims to evaluate a multirisk factor intervention using a social media campaign designed with community advisers aimed at decreasing cancer risk factors among EAs. The trial will target EAs from diverse backgrounds living in rural counties in the Four Corners states of Arizona, Colorado, New Mexico, and Utah.

METHODS

We will recruit a sample of EAs (n=1000) aged 18 to 26 years residing in rural counties (Rural-Urban Continuum Codes 4 to 9) in the Four Corners states from the Qualtrics' research panel and enroll them in a randomized stepped-wedge, quasi-experimental design. The inclusion criteria include English proficiency and regular social media engagement. A social media intervention will promote guideline-related goals for increased physical activity, healthy eating, and human papillomavirus vaccination and reduced nicotine product use, alcohol intake, and solar UV radiation exposure. Campaign posts will cover digital and media literacy skills, responses to misinformation, communication with family and friends, and referral to community resources. The intervention will be delivered over 12 months in Facebook private groups and will be guided by advisory groups of community stakeholders and EAs and focus groups with EAs. The EAs will complete assessments at baseline and at 12, 26, 39, 52, and 104 weeks after randomization. Assessments will measure 6 cancer risk behaviors, theoretical mediators, and participants' engagement with the social media campaign.

RESULTS

The trial is in its start-up phase. It is being led by a steering committee. Team members are working in 3 subcommittees to optimize community engagement, the social media intervention, and the measures to be used. The Stakeholder Organization Advisory Board and Emerging Adult Advisory Board were formed and provided initial input on the priority of cancer risk factors to target, social media use by EAs, and community resources available. A framework for the social media campaign with topics, format, and theoretical mediators has been created, along with protocols for campaign management.

CONCLUSIONS

Social media can be used as a platform to counter misinformation and improve reliable health information to promote health behaviors that reduce cancer risks among EAs. Because of the popularity of web-based information sources among EAs, an innovative, multirisk factor intervention using a social media campaign has the potential to reduce their cancer risk behaviors.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05618158; https://classic.clinicaltrials.gov/ct2/show/NCT05618158.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/50392.

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.

Should We "Wait and See"?: Change in Weight Status Among US Adolescents in the Population Assessment of Tobacco and Health Study

Background: Many parents and providers adopt a "wait and see" approach to obesity (OB) management. The goal of this study was to determine the likelihood that youth with overweight (OW) or OB would become normal weight over time. Methods: Data from the nationally representative Population Assessment of Tobacco and Health Study were used to examine the proportion of teens (aged 12-17 years) with OW/OB who tracked into a lower weight category over four waves of data collection (2013-2018). Analysis was restricted to those who completed all four waves of assessments (n = 10,086). Repeated-measures logistic regression models were used to describe the odds of having a BMI within the normal weight range at Waves 2-4, given an OW or obese weight status in the previous wave. Results: At Wave 1, 65% of the sample was normal weight, 18% had OW, and 17% had OB. By Wave 4, 24% had OW and 20% had OB. The adjusted odds of reporting a normal weight relative to OW/OB decreased by 13% each year. In Wave 4, only 2% [standard error (SE) 0.4%] of boys and 2% (SE 0.3%) of girls transitioned from OB to normal weight. For youth with OB in Wave 1, the probability of being in the normal weight category in Wave 2 was 0.04 (95% confidence interval 0.035-0.052), and decreased thereafter. Conclusion: Very few teens were able to return to normal weight once they developed OW/OB. Adopting a "wait and see" approach to OB management may be detrimental to a child's health.

Importance of self-weighing to avoid post-cessation weight gain: A secondary analysis of the fit and quit randomized trial

Background

Smoking cessation is associated with weight gain, and the risk of weight gain is a common deterrent to quitting smoking. Thus, the identification of strategies for reducing post-smoking cessation weight gain is critical.

Objective

Conduct secondary analysis of data from the Fit & Quit trial to determine if greater frequency of self-weighing is associated with less weight gain in the context of smoking cessation.

Methods

Participants (N = 305) were randomized to one of three 2-month weight interventions (i.e., Stability, Loss, Bibliotherapy), followed by a smoking cessation intervention. Stability and Loss conditions received different types of self-weighing feedback. All participants received e-scales at baseline, to capture daily self-weighing data over 12 months. General linear models were applied to test the main objective.

Results

Frequency of self-weighing was (mean ± SD) 2.67 ± 1.84 days/week. The Stability condition had significantly higher self-weighing frequency (3.18 ± 1.72 days/week) compared to the Loss (2.51 ± 1.99 days/week) and the Bibliotherapy conditions (2.22 ± 1.63 days/week). Adjusting for baseline weight and treatment condition, self-weighing 3-4 days/week was associated with weight stability (-0.77 kg, 95% CI: -2.2946, 0.7474, p = 0.3175), and self-weighing 5 or more days/week was associated with 2.26 kg weight loss (95% CI: -3.9249, -0.5953, p = 0.0080).

Conclusions

Self-weighing may serve as a useful tool for weight gain prevention after smoking cessation. Feedback received about self-weighing behaviors and weight trajectory (similar to the feedback Stability participants received) might enhance adherence.

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.

Weight Change over Ten Years Predicts Biological Aging in a Random Sample of 3070 U.S. Adults

This investigation was designed to study the relationship between weight change over 10 years and leukocyte telomere length (LTL) in a large sample of 3070 randomly selected U.S. adults, 36-70 years old. The National Health and Nutrition Examination Survey (NHANES) data were used to examine the relationship between percent weight change and LTL. Potential mediating variables were controlled using partial correlation. After adjusting for age, race, year, and housing status, the association between percent weight change over 10 years and LTL was significant in women (F = 6.9, p = 0.0138). Adjusting for the demographic and several other covariates weakened the relationship slightly (F = 4.7, p = 0.0392). With all the covariates controlled, for each one percentage point increase in weight over the previous 10 years, telomeres were, on average, 3.48 base pairs (bp) shorter in women. Given that each one-year increase in age was associated with telomeres that were 15.0 bp shorter in women, the median weight change in U.S. women over the previous 10 years (an increase of 10.4%) was predictive of LTLs that were 36 bp shorter, on average, or an increase of 2.4 years of biological aging. Percent weight change over 10 years was not associated with LTL in U.S. men. Percent weight change over 10 years is a strong predictor of biological aging in U.S. women, but not in men.

Combined Effect of Maternal Obesity and Diabetes on Excessive Fetal Growth: Pregnancy Risk Assessment Monitoring System (PRAMS), United States, 2012-2015

Introduction

Obesity and dysregulation in glucose metabolism are risk factors for excessive fetal growth, but their combined effects are not often examined in a single study.

Methods

Data from the Centers for Disease Control and Prevention's Pregnancy Risk Assessment Monitoring System Phase 7 (2012-2015) were used. Logistic regression was used to investigate the association between maternal prepregnancy BMI and pre-existing diabetes/gestational diabetes on the odds of delivering a large-for-gestational-age infant or an infant with macrosomia.

Results

Complete data for 128,199 singleton births were used. The proportions of large-for-gestational-age infants and infants with macrosomia increased with the degree of obesity (p<0.001) and were higher in women with diabetes than in those without (p<0.001). Compared with the AOR among normal-weight women, the AOR of delivering large-for-gestational-age infants and infants with macrosomia among women with morbid obesity (BMI≥40) were 2.82 (p<0.001) and 2.67 (p<0.001), respectively. Compared with the AOR among nondiabetic women, the AOR of delivering a large-for-gestational-age infant was 1.88 (p<0.001) among those with pre-existing diabetes and 1.49 (p<0.001) among those with gestational diabetes. Except for the underweight group, women with pre-existing diabetes were nearly twice as likely to deliver a large-for-gestational-age infant as those with similar BMI without diabetes. Women with morbid obesity and gestational diabetes were twice as likely to have a large-for-gestational-age infant and an infant with macrosomia as nondiabetic women with normal BMI.

Conclusions

We have shown that when maternal obesity and diabetes, particularly pre-existing diabetes, occur together, the risk of delivering large-for-gestational-age and macrosomia increases significantly. Our findings call for public health attention to address maternal obesity and diabetes to minimize suboptimal fetal growth.

Weight Loss Expectations of Adults With Binge Eating: Cross-sectional Study With a Human-Centered Design Approach

BACKGROUND

People tend to overestimate their expectations for weight loss relative to what is achievable in a typical evidence-based behavioral weight management program, which can impact treatment satisfaction and outcomes. We are engaged in formative research to design a digital intervention that addresses binge eating and weight management; thus, understanding expectations among this group can inform more engaging intervention designs to produce a digital intervention that can achieve greater clinical success. Studies examining weight loss expectations have primarily focused on people who have overweight or obesity. Only one study has investigated weight loss expectations among people with binge eating disorder, a population that frequently experiences elevated weight and shape concerns and often presents to treatment with the goal of losing weight.

OBJECTIVE

The aim of the study is to investigate differences in weight loss expectations among people with varying levels of binge eating to inform the design of a digital intervention for binge eating and weight management. Such an evaluation may be crucial for people presenting for a digital intervention, given that engagement and dropout are notable problems for digital behavior change interventions. We tested the hypotheses that (1) people who endorsed some or recurrent binge eating would expect to lose more weight than those who did not endorse binge eating and (2) people who endorsed a more severe versus a low or moderate overvaluation of weight and shape would have higher weight loss expectations.

METHODS

A total of 760 adults (n=504, 66% female; n=441, 58% non-Hispanic White) completed a web-based screening questionnaire. One-way ANOVAs were conducted to explore weight loss expectations for binge eating status as well as overvaluation of shape and weight.

RESULTS

Weight loss expectations significantly differed by binge eating status. Those who endorsed some and recurrent binge eating expected to lose more weight than those who endorsed no binge eating. Participants with severe overvaluation of weight or shape expected to lose the most weight compared to those with low or moderate levels of overvaluation of weight and shape.

CONCLUSIONS

In the sample, people interested in a study to inform a digital intervention for binge eating and weight management overestimated their expectations for weight loss. Given that weight loss expectations can impact treatment completion and success, it may be important to assess and modify weight loss expectations among people with binge eating prior to enrolling in a digital intervention. Future work should design and test features that can modify these expectations relative to individuals' intended treatment goals to facilitate engagement and successful outcomes in a digital intervention.

Association between weight-loss history and weight loss achieved in clinical obesity management: Retrospective chart review

OBJECTIVE

Weight history and its association with the weight loss achieved in a publicly funded clinical obesity management program were examined in 9348 patients.

METHODS

Weight history (frequency and magnitude of weight losses) was collected through questionnaires at enrollment, and weight change was assessed with retrospective electronic medical chart review.

RESULTS

The majority of patients reported developing overweight prior to the age of 40 years and having lost at least 4.5 kg (10 lb) of weight at least once in their lifetime. Those who had an earlier onset of overweight had a higher frequency of past weight loss and had more cumulative weight loss over their lifetime. In women, but not men, earlier age of overweight onset and lifetime weight loss were associated with modestly greater weight loss at the clinic.

CONCLUSIONS

Women with greater weight-loss history also have modestly greater weight loss at the obesity management clinic. Thus, successful long-term obesity management, particularly for women, may include a series of repeated attempts at weight loss that should not be viewed as failures but could be viewed instead as practice.

Long-Term Outcomes after Adolescent Bariatric Surgery

BACKGROUND

Metabolic and bariatric surgery (MBS) is a safe and effective treatment option for adolescents with severe obesity, but no long-term studies are available with more than10 years of follow-up data to document sustained improved outcomes.

METHODS

A total of 96 patients who completed MBS at 21 years of age or younger in a tertiary academic center 2002 to 2010 were contacted for a telehealth visit. Body weight, comorbidity status, social/physical function status, and long-term complications were evaluated 10 to 18 years after surgery.

RESULTS

Mean participant (83% female, 75% Hispanic) age at MBS was 18.8 (±1.6) years (median age 19 years, range 15-21 years), and median pre-MBS BMI was 44.7 kg/m 2 (SD 6.5). At follow-up (mean 14.2 [±2.2] years) post-MBS (90.6% Roux-en-Y gastric bypass [RYGB] or 8.3% laparoscopic adjustable gastric banding [LAGB]) mean total body weight decreased by 31.3% (interquartile range [IQR] 20.0% to 38.9%); 32.0% (IQR, 21.3% to 40.1%) among RYGB participants and 22.5% (IQR, 0.64% to 28.3%) among LAGB participants. Patients with pre-MBS hyperlipidemia (14.6%), asthma (10.4%), and diabetes/hyperglycemia (5.2%) reported 100% remission at follow-up (p < 0.05 for all). Pre-post decrease in hypertension (13.5% vs 1%, p = 0.001), sleep apnea (16.7% vs 1.0%, p < 0.001), gastroesophageal reflux disease (13.5% vs 3.1%, p = 0.016), anxiety (7.3% vs 2.1%, p = 0.169), and depression (27.1% vs 4.2%, p < 0.001) were also found.

CONCLUSIONS

Significant sustained reductions in weight and comorbidities, and low rates of long-term complications, a decade or more after completing MBS as an adolescent were found. These findings have important implications for adolescents who may be considering MBS for weight reduction and overall health improvements that extend into adulthood.

Using self-monitoring technology for nutritional counseling and weight management

Self-monitoring of weight, dietary intake, and physical activity is a key strategy for weight management in adults with obesity. Despite research suggesting consistent associations between more frequent self-monitoring and greater success with weight regulation, adherence is often suboptimal and tends to decrease over time. New technologies such as smartphone applications, e-scales, and wearable devices can help eliminate some of the barriers individuals experience with traditional self-monitoring tools, and research has demonstrated that these tools may improve self-monitoring adherence. To improve the integration of these tools in clinical practice, the current narrative review introduces the various types of self-monitoring technologies, presents current evidence regarding their use for nutrition support and weight management, and provides guidance for optimal implementation. The review ends with a discussion of barriers to the implementation of these technologies and the role that they should optimally play in nutritional counseling and weight management. Although newer self-monitoring technologies may help improve adherence to self-monitoring, these tools should not be viewed as an intervention in and of themselves and are most efficacious when implemented with ongoing clinical support.

Consistency With and Disengagement From Self-monitoring of Weight, Dietary Intake, and Physical Activity in a Technology-Based Weight Loss Program: Exploratory Study

BACKGROUND

Digital self-monitoring tools offer promise to improve adherence to self-monitoring of weight and weight-related behaviors; however, less is known regarding the patterns of participant consistency and disengagement with these tools.

OBJECTIVE

This study characterizes the consistency of use and time to disengagement with digital self-monitoring tools during a 6-month weight loss intervention and investigates whether the provision of phone-based intervention improved self-monitoring adherence.

METHODS

Participants were 54 adults with overweight or obesity (mean age 49.6 years, SD 12.4 years; mean BMI 32.6 kg/m², SD 3.2 kg/m²) enrolled in a pilot trial assessing the impact of self-monitoring technology (Fitbit Zip, Aria scale, and smartphone app), with and without additional interventionist contact, on weight loss. All participants received weight loss education and were asked to self-monitor weight, dietary intake, and physical activity daily throughout the 6-month program. Consistency was defined as the number of weeks that participants adhered to self-monitoring recommendations (7 out of 7 days). Disengagement was defined as the first of 2 consecutive weeks that the 7-day self-monitoring adherence goal was not met. Wilcoxon signed-rank tests were used to examine differences in consistency and disengagement by behavioral targets. t tests (2-tailed) and Cox proportional hazards models were used to examine whether providing additional interventionist contact would lead to significant improvements in consistency and time to disengagement from self-monitoring tools, respectively. Linear regressions were used to examine associations between consistency, time to disengagement, and weight loss.

RESULTS

Participants consistently self-monitored physical activity for more weeks (mean 17.4 weeks, SD 8.5 weeks) than weight (mean 11.1 weeks, SD 8.5 weeks) or dietary intake (mean 10.8 weeks, SD 8.7 weeks; P<.05). Similarly, participants had a significantly longer time to disengagement from self-monitoring of physical activity (median 19.5 weeks) than weight (4 weeks) or dietary intake (10 weeks; P<.001). Participants randomized to receive additional interventionist contact had significantly greater consistency and longer time to disengagement for self-monitoring of dietary intake compared with participants who did not (P=.006); however, there were no statistically significant differences between groups for self-monitoring of weight or physical activity (P=.24 and P=.25, respectively). Greater consistency and longer time to disengagement were associated with greater weight loss for self-monitoring of weight and dietary intake (P<.001 and P=.004, respectively) but not for physical activity (P=.57).

CONCLUSIONS

Results demonstrated that self-monitoring adherence differed by behavioral target, with greater consistency and longer time to disengagement associated with lower-burden tools (ie, self-monitoring of physical activity). Consistent with supportive accountability theory, additional interventionist contact improved consistency and lengthened time to disengagement from self-monitoring of dietary intake. Given the observed associations between consistency, disengagement, and weight loss outcomes, it is important to identify additional methods of increasing consistency and engagement with digital self-monitoring tools.

Optimization of an mHealth lifestyle intervention for families with hereditary cancer syndromes: Study protocol for a multiphase optimization strategy feasibility study

BACKGROUND

Individuals at increased hereditary risk of cancer are an important target for health promotion and cancer prevention interventions. Health-4-Families uses the Multiphase Optimization STrategy (MOST) framework and is designed to pilot digital delivery strategies for a distance-based, 16-week intervention to promote weight management, healthy diet, and increased physical activity among individuals with BRCA1/BRCA2 or DNA mismatch repair (MMR) pathogenic germline variants. This communication describes participant recruitment and the design of the Health-4-Families pilot study.

METHODS

Health-4-Families is a full-factorial (16 condition) randomized pilot study of four lifestyle intervention components: social networking, telephone or email coaching, text messaging, and self-monitoring. The primary outcome was feasibility and satisfaction with these study components. Participants with pathogenic germline variants were identified via clinic surveillance lists and advocacy organizations and were invited to participate with family members. All participants had to report meeting at least one of the following criteria: (1) having a BMI ≥ 25 kg/m², (2) consuming <5 servings of fruit and vegetables per day, or (3) getting <150 min of moderate-to-vigorous intensity activity per week.

RESULTS

The majority of screened potential participants with pathogenic variants (83%) were eligible; 86% of those eligible provided informed consent and 79% (n = 104) completed baseline. A total of 206 family members were nominated by study participants and 49% (n = 102) completed baseline.

DISCUSSION

Recruitment data suggest that individuals with pathogenic germline variants, who are at increased risk for hereditary cancers, are motivated to participate in digital lifestyle interventions. This recruitment success highlights the importance of identifying and prioritizing effective and efficient intervention components for hereditary cancer families. We intend to use the outcomes of our pilot study to inform a fully-powered factorial study for this community.

An analysis of weight loss efforts and expectations in a Canadian Cohort: A retrospective medical chart review

The weight loss history and weight loss goals were examined in 4108 patients referred to a publicly funded evidence-based clinical weight management program using a retrospective chart review. The majority of patients were white females, aged of 50.1 ± 13.7 years and a BMI of 39.0 ± 7.5 kg/m² . Pregnancy was the most common reason for weight gain in women (17.7%) and while the reasons in men are more varied (injury, stress and medication: all ~5%). Over 50% of patients cited no specific reason for their weight gain. Self-directed diet and exercise were the most commonly used self-reported weight loss methods. Women were more likely to report using medication and bariatric surgical weight loss methods than men (P < .05), and only 5% of women and 12.8% men report never having tried to lose weight in the past. Patients had an ideal weight loss goal of 28.9% to 34.4%, which was similar to the patient's lowest reported adult weight. Approximately 70% of patients enrolling at the clinic had previously lost at least 4.5 kg (10 lb) one or more times and 16.7% lost weight at least 5 times in their life, but patient weight at enrolment was similar to their highest adult reported weight. Thus, most patients referred to this clinical weight management program have previously attempted self-directed diet and exercise weight loss. Patients were close to their highest adult weight and had very large weight loss goals, similar to what is typically achieved only by surgical intervention, despite having already had several bouts of weight loss.

The Behavioral Intervention with Technology for E-Weight Loss Study (BITES): Incorporating Energy Balance Models and the Bite Counter into an Online Behavioral Weight Loss Program

This study evaluated feasibility and acceptability of adding energy balance modeling displayed on weight graphs combined with a wrist-worn bite counting sensor against a traditional online behavioral weight loss program. Adults with a BMI of 27–45 kg/m2 (83.3% women) were randomized to receive a 12-week online behavioral weight loss program with 12 weeks of continued contact (n = 9; base program), the base program plus a graph of their actual and predicted weight change based on individualized physiological parameters (n = 7), or the base program, graph, and a Bite Counter device for monitoring and limiting eating (n = 8). Participants attended weekly clinic weigh-ins plus baseline, midway (12 weeks), and study culmination (24 weeks) assessments of feasibility, acceptability, weight, and behavioral outcomes. In terms of feasibility, participants completed online lessons (M = 7.04 of 12 possible lessons, SD = 4.02) and attended weigh-ins (M = 16.81 visits, SD = 7.24). Six-month retention appears highest among nomogram participants, and weigh-in attendance and lesson completion appear highest in Bite Counter participants. Acceptability was sufficient across groups. Bite Counter use (days with ≥ 2 eating episodes) was moderate (47.8%) and comparable to other studies. Participants lost 4.6% ± 4.5 of their initial body weight at 12 weeks and 4.5% ± 5.8 at 24 weeks. All conditions increased their total physical activity minutes and use of weight control strategies (behavioral outcomes). Although all groups lost weight and the study procedures were feasible, acceptability can be improved with advances in the technology. Participants were satisfied with the online program and nomograms, and future research on engagement, adherence, and integration with other owned devices is needed. ClinicalTrials.gov Identifier: NCT02857595

Accuracy of Smart Scales on Weight and Body Composition: Observational Study

Background

Smart scales are increasingly used at home by patients to monitor their body weight and body composition, but scale accuracy has not often been documented.

Objective

The goal of the research was to determine the accuracy of 3 commercially available smart scales for weight and body composition compared with dual x-ray absorptiometry (DEXA) as the gold standard.

Methods

We designed a cross-sectional study in consecutive patients evaluated for DEXA in a physiology unit in a tertiary hospital in France. There were no exclusion criteria except patient declining to participate. Patients were weighed with one smart scale immediately after DEXA. Three scales were compared (scale 1: Body Partner [Téfal], scale 2: DietPack [Terraillon], and scale 3: Body Cardio [Nokia Withings]). We determined absolute error between the gold standard values obtained from DEXA and the smart scales for body mass, fat mass, and lean mass.

Results

The sample for analysis included 53, 52, and 48 patients for each of the 3 tested smart scales, respectively. The median absolute error for body weight was 0.3 kg (interquartile range [IQR] –0.1, 0.7), 0 kg (IQR –0.4, 0.3), and 0.25 kg (IQR –0.10, 0.52), respectively. For fat mass, absolute errors were –2.2 kg (IQR –5.8, 1.3), –4.4 kg (IQR –6.6, 0), and –3.7 kg (IQR –8.0, 0.28), respectively. For muscular mass, absolute errors were –2.2 kg (IQR –5.8, 1.3), –4.4 kg (IQR –6.6, 0), and –3.65 kg (IQR –8.03, 0.28), respectively. Factors associated with fat mass measurement error were weight for scales 1 and 2 (P=.03 and P<.001, respectively), BMI for scales 1 and 2 (P=.034 and P<.001, respectively), body fat for scale 1 (P<.001), and muscular and bone mass for scale 2 (P<.001 for both). Factors associated with muscular mass error were weight and BMI for scale 1 (P<.001 and P=.004, respectively), body fat for scales 1 and 2 (P<.001 for both), and muscular and bone mass for scale 2 (P<.001 and P=.002, respectively).

Conclusions

Smart scales are not accurate for body composition and should not replace DEXA in patient care.

Trial Registration

ClinicalTrials.gov NCT03803098; https://clinicaltrials.gov/ct2/show/NCT03803098

The association between prior physical fitness and depression in young adults during the COVID-19 pandemic-a cross-sectional, retrospective study

Background

The COVID-19 pandemic has led to a spike in deleterious mental health. This dual-center retrospective cross-sectional study assessed the prevalence of depression in young adults during this pandemic and explored its association with various physical fitness measures.

Methods

This study enrolled 12,889 (80% female) young adults (mean age 20 ± 1) who performed a National Student Physical Fitness battery from December 1st, 2019, to January 20th, 2020, and completed a questionnaire including Beck’s Depression Inventory in May 2020. Independent associations between prior physical fitness and depression during the pandemic were assessed using multivariable linear and binary logistic regressions accordingly, covariates including age, dwelling location, economic level, smoking, alcohol, living status, weight change, and exercise volume during the pandemic. Sex- and baseline stress-stratified analyses were performed.

Results

Of the study population 13.9% of men and 15.0% of women sampled qualified for a diagnosis of depression. After multivariable adjustment, anaerobic (mean change 95% CI −3.3 [−4.8 to 1.8]) aerobic (−1.5 [−2.64 to −0.5]), explosive (−1.64 [−2.7 to −0.6]) and muscular (−1.7 [−3.0 to −0.5]) fitness were independently and inversely associated with depression for the overall population. These remained consistent after sex- and baseline stress-stratification. In binary logistic regression, the combined participants with moderate, high or excellent fitness also showed a much lower risk compared to those least fit in anaerobic (odd ratio (OR) 95% CI 0.68 [0.55–0.82]), aerobic (0.80 [0.68–0.91]), explosive (0.72 [0.61–0.82]), and muscular (0.66 [0.57–0.75]) fitness.

Conclusions

These findings suggest that prior physical fitness may be inversely associated with depression in young adults during a pandemic.

Predictors of Weight Loss and Weight Gain in Weight Management Patients during the COVID-19 Pandemic

OBJECTIVE

To examine the associations between patient struggles, health, and weight management changes during the COVID-19 pandemic.

METHODS

585 patients attending a publicly funded clinical weight management program responded to an electronic survey.

RESULTS

Over half of the patients reported worsened overall health, mental health, physical activity, or diet during the pandemic. Approximately 30% of patients lost ≥3% of their body weight and 21% gained ≥3% of their body weight between March and July of the pandemic. Reports of social isolation was associated with increased odds for weight loss in women (OR = 2.0, 1.2-3.3), while low motivation (OR = 1.9, 1.0-3.7), depression (OR = 2.5, 1.0-6.3), and struggles with carbohydrate intake (OR = 2.1, 1.0-4.3) were associated with weight gain. Cooking more at home/eating less take out was associated with increased likelihood of weight loss (OR = 2.1, 1.1-3.9) and lower odds for weight gain (OR = 0.2, 0.1 to 0.97). Working from home was not associated with weight loss or weight gain (P > 0.6).

CONCLUSION

The COVID-19 pandemic is associated with certain factors that may facilitate weight loss and other factors that promote weight gain. Thus, depending on the patient experience during the pandemic, prevention of weight gain may be more appropriate than weight loss.

Internalized weight bias in patients presenting for bariatric surgery

INTRODUCTION

Internalized weight bias (IWB) is significantly related to poor psychosocial health outcomes in patients with increased body mass index (BMI). The objective of this study was to evaluate the psychometric properties and correlates of the Weight-Bias Internalization Scale in a pre-surgical bariatric population.

METHODS

Self-report measures were administered to patients prior to surgery. Measures assessed internalized weight bias, body dissatisfaction, depression, anxiety, quality of life, and eating behaviors. Statistical methods included confirmatory factor analysis to examine the factor structure [of the WBIS] in this population, descriptive statistics, correlations, and hierarchical linear regression between continuous variables to determine patterns of associations, and t-tests to compare levels of IWB between the current sample and previously documented samples.

RESULTS

Confirmatory factor analysis indicated an acceptable fit using a one-factor structure for the WBIS, with one item removed. Mean WBIS in the current sample was comparable to that documented in a community sample of adults with overweight and obesity, as well as a sample of adolescents seeking bariatric surgery. Additionally, IWB was positively associated with body dissatisfaction, restrained, emotional, and external eating, depression, and anxiety, and negatively associated with quality of life. Further, individuals endorsing episodes of loss of control over eating had significantly higher WBIS scores.

CONCLUSIONS

This study highlights the strong pattern of associations with measures of body image, disordered eating, and quality of life point toward the relevance of IWB to bariatric patients' experiences. Future studies to explore the longitudinal effects of IWB in a post-bariatric population are needed particularly to understand psychosocial and surgical health outcomes.

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.

Patterns in Weight and Physical Activity Tracking Data Preceding a Stop in Weight Monitoring: Observational Analysis

Background

Self-regulation for weight loss requires regular self-monitoring of weight, but the frequency of weight tracking commonly declines over time.

Objective

This study aimed to investigate whether it is a decline in weight loss or a drop in motivation to lose weight (using physical activity tracking as a proxy) that may be prompting a stop in weight monitoring.

Methods

We analyzed weight and physical activity data from 1605 Withings Health Mate app users, who had set a weight loss goal and stopped tracking their weight for at least six weeks after a minimum of 16 weeks of continuous tracking. Mixed effects models compared weight change, average daily steps, and physical activity tracking frequency between a 4-week period of continuous tracking and a 4-week period preceding the stop in weight tracking. Additional mixed effects models investigated subsequent changes in physical activity data during 4 weeks of the 6-week long stop in weight tracking.

Results

People lost weight during continuous tracking (mean −0.47 kg, SD 1.73) but gained weight preceding the stop in weight tracking (mean 0.25 kg, SD 1.62; difference 0.71 kg; 95% CI 0.60 to 0.81). Average daily steps (beta=−220 daily steps per time period; 95% CI −320 to −120) and physical activity tracking frequency (beta=−3.4 days per time period; 95% CI −3.8 to −3.1) significantly declined from the continuous tracking to the pre-stop period. From pre-stop to post-stop, physical activity tracking frequency further decreased (beta=−6.6 days per time period; 95% CI −7.12 to −6.16), whereas daily step count on the day’s activity was measured increased (beta=110 daily steps per time period; 95% CI 50 to 170).

Conclusions

In the weeks before people stop tracking their weight, their physical activity and physical activity monitoring frequency decline. At the same time, weight increases, suggesting that declining motivation for weight control and difficulties with making use of negative weight feedback might explain why people stop tracking their weight. The increase in daily steps but decrease in physical activity tracking frequency post-stop might result from selective measurement of more active days.

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.

Weight Gain Over 6 Years in Young Adults: The Study of Novel Approaches to Weight Gain Prevention Randomized Trial

OBJECTIVE

The study objective was to determine whether two self-regulation interventions that reduced 3-year weight gain in young adults remain effective at 6 years.

METHODS

A randomized trial was conducted in two academic settings in 599 young adults, aged 18 to 35 years, with normal weight or overweight; 504 (84%) reconsented for a 6-year extension (Study of Novel Approaches to Weight Gain Prevention-Extended [SNAP-E]) with ongoing intervention and assessments. Weight gain over 6 years was compared for all assigned to Control, Large Changes (LC; lose 5-10 pounds initially), and Small Changes (SC; make small daily changes in intake and activity).

RESULTS

Weight change from baseline to 6 years did not differ significantly among the three groups (Control = 3.9 kg, SC = 4.1 kg, and LC = 2.8 kg). However, there was a significant age-by-treatment interaction (P = 0.002). Among those < 25 years old, weight gain from baseline to 6 years averaged 7.3 kg in the Control group and was reduced by almost 50% in LC and SC. LC also significantly reduced mean weight gain (area under the curve) over 6 years compared with Control or SC.

CONCLUSIONS

Although the interventions did not reduce weight gain at 6 years for the full cohort, they were effective in those < 25 years old. Future efforts should focus on young adults aged 18 to 24.9 and test more intensive interventions with more diverse participants.

Week-to-week predictors of weight loss and regain

OBJECTIVES

Despite increased interest in the development of individually tailored weight management programs, little is known about what factors proximally predict weight change.

METHOD

The current study investigated proximal (week-to-week) predictors of weight loss and regain in 74 adults during a 3-month, Internet-based behavioral weight loss program followed by a 9-month "maintenance" period (during which no additional intervention was provided). Participants were asked to self-weigh daily using scales that transmitted weight via the cellular network and to answer a brief questionnaire each week querying mood, behaviors, and cognitions hypothesized to be associated with weight loss and regain.

RESULTS

Longitudinal multilevel models demonstrated that weight loss during initial intervention was proximally predicted by (a) greater frequency of self-monitoring weight and caloric intake, consistency between eating choices and weight loss goals, and importance of "staying on track" with these goals and (b) less negative mood, boredom with weight control efforts, hunger, and temptation to eat foods "not on plan" (ps < .05). Greater weight regain after intervention was also proximally predicted by these factors (with effects in the opposite direction) and additionally by less physical activity, less positive mood, more stress, greater temptation to skip planned physical activity, and higher ratings of the amount of effort required to stay on track (ps < .05).

CONCLUSIONS

Results confirmed the importance of self-monitoring for weight loss and maintenance and identified other key week-to-week predictors of weight change. Results also supported efforts to develop intervention approaches specifically focused on weight loss maintenance. Future research should investigate whether using identified predictors to tailor intervention content and timing can improve weight outcomes. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Factors associated with early non-response within an Internet-based behavioural weight loss program

OBJECTIVE

While behavioural weight loss interventions are effective overall, many individuals fail to achieve a clinically significant weight loss. Given that 4-week weight loss has been shown to predict longer term outcomes, one potential strategy for improving rates of success is to provide additional support to early non-responders. To inform these early rescue efforts, it is important to first identify how they may differ from their more successful peers.

METHODS

At week 4 of a 12-week Internet-delivered weight loss program, 130 adults (age: 49.8 ± 9.8 years, body mass index: 31.2 ± 4.6 kg m-2) were asked to complete an 11-item survey assessing mood and weight-related cognitions and behaviours. Participants were then categorized as early non-responders (4-week weight loss <2%) or initial responders (4-week weight loss ≥2%), and groups were compared on intervention adherence during weeks 1-4 and week 4 survey question responses.

RESULTS

Early non-responders and initial responders did not differ on any intervention adherence variables (ps > 0.05). Compared to initial responders, early non-responders reported less positive mood (p = 0.011), greater boredom with weight loss efforts (p = 0.036), greater temptation to eat foods not consistent with their goals (p = 0.023), and that their eating choices were less consistent with their goals (p < 0.001).

CONCLUSIONS

These findings identify important differences between early non-responders and initial responders, offering potential intervention targets for rescuing early non-responders (i.e. making it easier for individuals to choose healthier foods, reducing boredom in Internet-delivered weight loss programs and providing strategies to limit exposure to dietary temptations).