Short-term weight loss patterns, baseline predictors, and longer-term follow-up within a randomized controlled trial

Weight Loss Trajectories and Short-Term Prediction in an Online Weight Management Program

The extent to which early weight loss in behavioral weight control interventions predicts long-term success remains unclear. In this study, we developed an algorithm aimed at classifying weight change trajectories and examined its ability to predict long-term weight loss based on weight early change. We utilized data from 667 de-identified individuals who participated in a commercial weight loss program (Instinct Health Science), comprising 69,363 weight records. Sequential polynomial regression models were employed to classify participants into distinct weight trajectory patterns based on key model parameters. Next, we applied multinomial logistic models to evaluate if early weight loss in the first 14 days and prolonged duration of participation were significantly associated with long-term weight loss patterns. The mean percentage of weight loss was 7.9 ± 5.1% over 133 ± 69 days. Our analysis revealed four main weight loss trajectory patterns: a steady decrease over time (30.6%), a decrease to a plateau with subsequent decline (15.8%), a decrease to a plateau with subsequent increase (46.9%), and no substantial decrease (6.7%). Early weight change rate and total participating duration emerged as significant factors in differentiating long-term weight loss patterns. These findings contribute to support the provision of tailored advice in the early phase of behavioral interventions for weight loss.

Examining paradoxical session attendance and weight loss relationships in a clinic based lifestyle modification intervention

Objective

Evaluations of lifestyle modification interventions (LMIs), modeled after the Diabetes Prevention Program, have repeatedly shown a dose-response relationship between session attendance and weight loss. Despite this, not all participants had "average" weight loss experiences. Nearly one-third of LMI participants experienced unexpected, paradoxical outcomes (i.e., high attendance with little weight loss, and low attendance with clinically significant weight loss). Paradoxical weight-loss outcomes were characterized based on session attendance among participants in a group-based LMI in a real-world healthcare setting. This group-based LMI was delivered over 1 year to participants with the possibility of attending up to 25 sessions total.

Methods

LMI participants identified in 2010-2017 from electronic health records were characterized as having low (<75%) or high (≥75%) session attendance. Weight-loss outcomes were defined as expected (≥5%, high-attendance; <5%, low-attendance) or paradoxical (≥5%, low-attendance; <5%, high-attendance). Paradoxical-outcome-associated characteristics were identified using logistic regression.

Results

Among 1813 LMI participants, 1498 (82.6%) had low and 315 (17.4%) high session attendance; 555 (30.6%) had paradoxical outcomes, comprising 415 (74.8%) responders (≥5% weight-loss) and 140 (25.2%) non-responders (<5% weight-loss). Among participants with high session attendance, paradoxical non-responders were more likely to be female (odds ratio [OR]: 2.76; 95% confidence interval [CI]: 1.32, 5.77) and have type 2 diabetes (OR: 3.32; 95% CI: 1.01, 10.95). Among low-attendance participants, paradoxical responders were more likely to be non-Hispanic White and less likely to be non-Hispanic Black (OR: 0.35; 95% CI: 0.18, 0.69), non-Hispanic Asian (OR: 0.40; 95% CI: 0.22, 0.73), or Hispanic (OR: 0.53; 95% CI: 0.35, 0.80).

Conclusions

In a healthcare setting, nearly one-third of LMI participants experienced paradoxical outcomes. More research is needed to understand the facilitators and barriers to weight loss above and beyond session attendance.

Contrasts of Initial and Gain Scores in Obesity Treatment-Targeted Psychosocial Variables by Women Participants' Weight Change Patterns Over 2 Years

The typical pattern of weight change associated with behavioral obesity treatments has been some loss in weight through approximately 6 months, followed by near complete regain. However, patterns vary widely across individuals. The objectives are to determine whether recent prediction model-based indications of relations among changes in psychosocial correlates of the weight loss behaviors of physical activity and controlled eating vary by patterns of weight change. Women with obesity enrolled in a community-based behavioral obesity treatment who failed to lose at least 5% of their baseline weight (Minimal Effect group, n = 44), lost 5% or greater and then regained most during months 6 to 24 (Loss/Regain group, n = 42), or lost 5% or greater and then maintained/continued loss (Loss/Loss group n = 42) were evaluated. Improvements in physical activity- and eating-related self-regulation and self-efficacy, mood, and emotional eating over 6 months were significant overall and generally most favorable in the Loss/Loss group and least favorable in the Minimal Effect group. Expected model-based relationships between 6-month changes in the aforementioned psychosocial variables were significant and generally not significantly affected by weight change group. However, group substantially affected the prediction of self-regulation of eating at month 24-a key correlate of long-term weight loss. Findings suggested community-based obesity treatment targets and emphases.

Validation of Tools to Assess Predictors of Successful Weight Loss Outcome in Individuals With Overweight and Obesity

OBJECTIVE

To develop and validate questionnaires to assess the behavioral, psychosocial, and environmental predictors of successful weight loss outcomes.

DESIGN

Mixed method study. Questionnaires were developed using 5 steps: item generation by literature review and preexisting questionnaires, expert evaluation, pilot testing, factor analysis, and internal consistency.

SETTING

Adults with obesity recruited via web-based survey hyperlink.

PARTICIPANTS

One hundred participants with a mean body mass index of 28.7 ± 4.4 kg/m².

VARIABLES MEASURED

The questionnaires were generated using 221 items. Establishing content, face and construct validity, and internal consistency.

ANALYSIS

Content validity was analyzed using content validity index and content validity ratio, internal consistency through Cronbach α (CA), and structural validity by factor analysis via principal varimax rotation.

RESULTS

All three questionnaires had good content validity. The Behavioral Predictor Questionnaire had good internal consistency (CA, 0.7) and excellent structural validity (69.7%). Psychosocial Predictors Questionnaire (CA, 0.8, 67.5%) and Environmental Predictors Questionnaire (CA: 0.8, 72.2%) had excellent internal consistency and structural validity.

CONCLUSION AND IMPLICATION

Questionnaires seem to be practical, valid, and reliable tools for baseline assessment of individual-specific factors related to weight loss success.

Weight Loss Trajectories and Related Factors in a 16-Week Mobile Obesity Intervention Program: Retrospective Observational Study

Background

In obesity management, whether patients lose ≥5% of their initial weight is a critical factor in clinical outcomes. However, evaluations that take only this approach are unable to identify and distinguish between individuals whose weight changes vary and those who steadily lose weight. Evaluation of weight loss considering the volatility of weight changes through a mobile-based intervention for obesity can facilitate understanding of an individual’s behavior and weight changes from a longitudinal perspective.

Objective

The aim of this study is to use a machine learning approach to examine weight loss trajectories and explore factors related to behavioral and app use characteristics that induce weight loss.

Methods

We used the lifelog data of 13,140 individuals enrolled in a 16-week obesity management program on the health care app Noom in the United States from August 8, 2013, to August 8, 2019. We performed k-means clustering with dynamic time warping to cluster the weight loss time series and inspected the quality of clusters with the total sum of distance within the clusters. To identify use factors determining clustering assignment, we longitudinally compared weekly use statistics with effect size on a weekly basis.

Results

The initial average BMI value for the participants was 33.6 (SD 5.9) kg/m², and it ultimately reached 31.6 (SD 5.7) kg/m². Using the weight log data, we identified five clusters: cluster 1 (sharp decrease) showed the highest proportion of participants who reduced their weight by >5% (7296/11,295, 64.59%), followed by cluster 2 (moderate decrease). In each comparison between clusters 1 and 3 (yo-yo) and clusters 2 and 3, although the effect size of the difference in average meal record adherence and average weight record adherence was not significant in the first week, it peaked within the initial 8 weeks (Cohen d>0.35) and decreased after that.

Conclusions

Using a machine learning approach and clustering shape-based time series similarities, we identified 5 weight loss trajectories in a mobile weight management app. Overall adherence and early adherence related to self-monitoring emerged as potential predictors of these trajectories.

Increases in physical activity are associated with a faster rate of weight loss during dietary energy restriction in women with overweight and obesity

This secondary analysis examined the influence of changes in physical activity (PA), sedentary time and energy expenditure (EE) during dietary energy restriction on the rate of weight loss (WL) and 1-year follow-up weight change in women with overweight/obesity.Measurements of body weight and composition (air-displacement plethysmography), resting metabolic rate (indirect calorimetry), total daily (TDEE) and activity EE (AEE), minutes of PA and sedentary time (PA monitor) were taken at baseline, after 2 weeks, after ≥5% WL or 12 weeks of continuous (25% daily energy deficit) or intermittent (75% daily energy deficit alternated with ad libitum day) energy restriction, and at 1-year post-WL. The rate of WL was calculated as total %WL/number of dieting weeks. Data from both groups were combined for analyses.Thirty-seven participants (age=35±10y; BMI=29.1±2.3kg/m2) completed the intervention (WL=-5.9±1.6%) and 18 returned at 1-year post-WL (weight change=+4.5±5.2%). Changes in sedentary time at 2 weeks were associated with the rate of WL during energy restriction (r=-0.38; p=0.03). Changes in total (r=0.54; p<0.01), light (r=0.43; p=0.01) and moderate-to-vigorous PA (r=0.55; p<0.01), sedentary time (r=-0.52; p<0.01), steps per day (r=0.39; p=0.02), TDEE (r=0.46; p<0.01) and AEE (r=0.51; p<0.01) during energy restriction were associated with the rate of WL. Changes in total (r=-0.50; p=0.04) and moderate-to-vigorous PA (r=-0.61; p=0.01) between post-WL and follow-up were associated with 1-year weight change (r=-0.51; p=0.04).These findings highlight that PA and sedentary time could act as modifiable behavioural targets to promote better weight outcomes during dietary energy restriction and/or weight maintenance.

Measuring social processes regarding eating, physical activity, and weight in higher-weight people: the weight-related interactions scale (WRIS)

PURPOSE

This study sought to develop a psychometrically sound measure to assess effective and ineffective forms of input from others regarding eating, physical activity, and weight in higher-weight people, namely, the Weight-Related Interactions Scale (WRIS).

METHODS

Participants (n = 736) were adults in the overweight/obese weight ranges who completed the WRIS and measures of weight-specific social support, emotional eating, weight stigma, eating-specific self efficacy, and social desirability.

RESULTS

Exploratory and confirmatory factor analyses of the WRIS supported a three-factor solution of 'Criticism', 'Minimization', and 'Collaboration' as forms of weight-related input from others. Support was found for the reliability and the concurrent, convergent, and divergent validity of the WRIS.

CONCLUSIONS

The WRIS is a promising new instrument for comprehensively assessing the input of others in relation to eating, physical activity, and weight among higher-weight individuals.

LEVEL OF EVIDENCE

Level III. Evidence obtained from well-designed cohort or case-control analytic studies.

Distinguishing early patterns of physical activity goal attainment and weight loss in online behavioral obesity treatment using latent class analysis

Physical activity (PA) goal adherence is consistently associated with greater weight loss during behavioral obesity treatment, and early weight loss response predicts future weight loss success. However, it remains unclear which behaviors during the initial weeks of treatment distinguish responders from nonresponders and might be effective targets for improving treatment outcomes. To characterize subgroups with distinct patterns of PA goal adherence during the initial 2 months of an online, group-based weight control program and determine associations between these patterns and 6-month weight loss. Participants received an online behavioral obesity intervention with PA goals and daily self-monitoring. Weekly adherence to step goals and moderate-to-vigorous PA (MVPA) minute goals based on self-monitoring records were examined using latent class analysis. Body weight was objectively measured at 0, 2, and 6 months. Participants (N = 212; 91.5% female, 31.6% race/ethnic minority, mean body mass index: 35.8 ± 5.9 kg/m2) clustered into three subgroups based on early goal attainment: "Both PA Goals," "MVPA Goals Only," and "Neither PA Goal." The "Both PA Goals" class had significantly greater 6-month weight loss (estimated mean weight loss [95% CI]: -9.4% [7.4 to 11.5]) compared to the "MVPA Goals Only" (-4.8% [3.4 to 6.1]) and "Neither PA Goal" classes (-2.5% [1.4 to 3.6]). Individuals meeting both PA goals early in treatment achieve greater weight losses than those meeting MVPA but not step goals, pointing to the need to explore factors associated with nonadherence to each of the PA goals to better understand these potential targets for treatment refinement and adaptive interventions.

Depression and obesity among females, are sex specificities considered?

This study aimed to systematically review the relationship of obesity-depression in the female sex. We carried out a systematic search (PubMed, MEDLINE, Embase) to quantify the articles (controlled trials and randomized controlled trials) regarding obesity and depression on a female population or a mixed sample. Successively, we established whether the sex specificities were studied by the authors and if they reported on collecting data regarding factors that may contribute to the evolution of obesity and depression and that could be responsible for the greater susceptibility of females to those conditions. After applying the inclusion and exclusion criteria, we found a total of 20 articles with a female sample and 54 articles with a mixed sample. More than half of all articles (51.35%, n = 38) evaluated the relationship between depression and obesity, but only 20 (27.03%) evaluated this relationship among females; still, 80% of those (n = 16) presented supporting results. However, few articles considered confounding factors related to female hormones (12.16%, n = 9) and none of the articles focused on factors responsible for the binomial obesity-depression in the female sex. The resulting articles also supported that depression (and related impairments) influencing obesity (and related impairments) is a two-way road. This systematic review supports the concurrency of obesity-depression in females but also shows how sex specificities are ultimately under-investigated. Female sex specificity is not being actively considered when studying the binomial obesity-depression, even within a female sample. Future studies should focus on trying to understand how the female sex and normal hormonal variations influence these conditions.

Predictors of long-term weight loss trajectories during a behavioral weight loss intervention: An exploratory analysis

BACKGROUND

Substantial interindividual variability in response to behavioral weight loss interventions remains a critical challenge in obesity treatment. An improved understanding of the complex factors that contribute to this variability may improve obesity treatment outcomes.

OBJECTIVE

To identify weight change trajectories during a behavioral weight loss intervention and to explore differences between trajectory groups in sociodemographic, biologic, behavioral, and psychosocial factors.

METHODS

Adults (n = 170, 40 ± 9 years, BMI 34 ± 4 kg/m2, 84% female) participated in an 18-month behavioral weight loss intervention. Weight was measured at 0, 3, 6, 9, 12, 15, 18, and 24 months. Among participants with at least two weights after baseline (n = 140), clusters of longitudinal trajectories of changes in weight were identified using a latent class growth mixture model. The association between baseline factors or changes in factors over time and trajectory group was examined.

RESULTS

Two weight change trajectories were identified: "weight regainers" (n = 91) and "weight loss maintainers" (n = 49). Black participants (90%, 19/21) were more likely than non-Black participants to be regainers versus maintainers (p < 0.01). Maintainers demonstrated greater increases in device-measured physical activity, autonomous motivation for exercise, diet self-efficacy, cognitive restraint, and engagement in weight management behaviors and greater reductions in barriers for exercise, disinhibition, and depressive symptoms over 24 months versus regainers (p < 0.05).

CONCLUSION

Maintainers and regainers appear to be distinct trajectories that are associated with specific sociodemographic, behavioral, and psychosocial factors. Study results suggest potential targets for more tailored, multifaceted interventions to improve obesity treatment outcomes.

Predictors of successful weight loss outcomes amongst individuals with obesity undergoing lifestyle interventions: A systematic review

Understanding the predictors of weight loss with lifestyle interventions can help to ascertain the probable outcomes of individuals with obesity who undergo such interventions. This systematic review assessed the evidence of predictors of successful weight loss among individuals who are overweight or with obesity undergoing lifestyle interventions. Four electronic databases (PubMed, Cochrane Reviews, PsychInfo and Wiley) were searched to find relevant literature published in the past 20 years. A total of 1351 titles were identified in the initial search, of which 23 studies were finally included. Predictors were synthesized in the domains of socio-demographic factors, anthropometric parameters, psychological and behavioural factors and intervention-based factors. The overall quality of evidence on predictors was then appraised using an adapted GRADE approach. Patient-specific factors such as being male, older in age, having existing cardiometabolic comorbidities and limited fat intake were significantly associated with weight loss success. Amongst intervention specific predictors, greater initial weight loss and higher adherence to lifestyle advice were associated with greater weight loss success. In this review, initial weight loss came out to be as the most important predictor of successful weight loss outcome.

Sex Moderates Treatment Effects of Integrated Collaborative Care for Comorbid Obesity and Depression: The RAINBOW RCT

BACKGROUND

Sex influences health and related behaviors due to biological and psychosocial/socioeconomic factors. Assessing sex-specific responses to integrated treatment for comorbid obesity and depression could inform intervention targeting.

PURPOSE

To test (a) whether sex moderates the effects of integrated collaborative care on weight and depression outcomes through 24 months and (b) whether treatment response at 6 months predicts 12 and 24 month outcomes by sex.

METHODS

Secondary data analyses on weight and depression severity (SCL-20) measured over 24 months among 409 adults with obesity and depression in the Research Aimed at Improving Both Mood and Weight trial.

RESULTS

Men achieved significantly greater weight reductions in intervention versus usual care than women, whereas women achieved significantly greater percentage reductions in SCL-20 than men at both 12 and 24 months. In logistic models, at 80% specificity for correctly identifying participants not achieving clinically significant long-term outcomes, women who lost <3.0% weight and men who lost <4.1% weight at 6 months had ≥84% probability of not meeting 5% weight loss at 24 months. Similarly, at 80% specificity, women who reduced SCL-20 by <39.5% and men who reduced by <53.0% at 6 months had ≥82% probability of not meeting 50% decrease in SCL-20 at 24 months.

CONCLUSIONS

Sex modified the integrated treatment effects for obesity and depression. Sex-specific responses at 6 months predicted clinically significant weight loss and depression outcomes through 24 months. Based on early responses, interventions may need to be tailored to address sex-specific barriers and facilitators to achieving healthy weight and depression outcomes at later time points.

CLINICAL TRIAL REGISTRATION

NCT02246413 (https://clinicaltrials.gov/ct2/show/NCT02246413).

Short-term weight trajectories and long-term weight outcomes from a lifestyle intervention in real-world clinical practice

Centers for Disease Control and Prevention aligned lifestyle change programs are effective in promoting weight loss among those with elevated cardiometabolic risk; yet, variability in weight outcomes among participants is high. Little is known about heterogeneity of short-term weight changes among participants in real-world clinical practice. We sought to identify short-term weight trajectory clusters among lifestyle change program participants in real-world clinical practice and to examine the relationship between cluster membership and long-term weight outcomes. We identified participants from the electronic health records (2010-2017) with weight measured ≤30 days prior to program initiation (baseline) and in four intervals (3-week segments) in the 12 weeks after baseline. Clustering analysis was performed to identify distinct trajectories in percent weight change over 12 weeks. Cluster-specific differences in weight change at 12 and 52 weeks were assessed. Among 1,148 participants, across 18 clinic sites, three clusters were identified: minimal-to-no weight loss (MWL), delayed-minimal weight loss (DWL), and steady-moderate weight loss (SWL), corresponding to mean weight changes of 0.4%, -2.3%, and -4.8% at 12 weeks follow-up, respectively. Mean weight changes were 0.4%, -1.8%, and -5.1% for MWL, DWL, and SWL clusters, respectively, at 52 weeks follow-up, which correlated in direction and magnitude with short-term weight changes. Clustering analysis reveals heterogeneous, short-term weight trajectories among lifestyle change program participants in real-world clinical practice. Given the relationship between the magnitudes of short- and long-term weight change, individual participant weight trajectories may be useful in identifying potential non-responders in need of adjunctive or alternative therapy.

Behavioural and psychosocial factors associated with 5-year weight trajectories within the PORTAL Overweight/Obesity Cohort

Objective

The purpose of this study was to model weight trajectories over a 5‐year time period (2012–2016) and their association with behavioural and psychosocial characteristics and health care–related experiences using data from the Patient Outcomes Research to Advance Learning (PORTAL) overweight/obesity cohort.

Methods

Weight trajectories for each eligible patient in the PORTAL overweight/obesity cohort (n = 2864) were identified first using growth modelling; trajectories were then grouped using a hierarchical cluster analysis. Weight trajectory clusters that emerged were compared on demographics, and predictors of cluster membership were examined. Clusters were also compared on responses to a survey assessing health behaviours, quality of life, and health care experience completed in 2015 by 49% of the total sample (n = 1391).

Results

Seven distinct weight trajectory clusters were identified: (a) significant weight loss then maintenance; (b) higher stable weight; (c) moderate stable weight; (d) steady weight loss then relapse; (e) weight gain then weight loss; (f) steady weight gain then maintenance; and (g) lower stable weight. Age, sex, race/ethnicity, and body mass index at baseline predicted patient's weight trajectory (P < .001). Over two thirds of patients maintained their weight over the 5‐year period. Significant weight loss then maintenance, weight gain then weight loss, and higher stable weight patients were more likely to report receiving weight counselling from their provider. Patients in the significant weight loss then maintenance and lower stable weight clusters were more likely to be physically active than the other clusters.

Conclusion

Findings suggest variability in patterns of weight change among adults with overweight or obesity who have access to health care and that these patterns differ on demographic, behavioural and psychosocial factors, and health care experience.

Beyond weight loss: Impact of a weight management programme for mid-older Australians in private health insurance

Weight-loss maintenance and lifestyle behaviour necessary to manage weight are undisputedly challenging. We evaluated a secondary prevention weight-loss maintenance programme for participants (n = 490) with weight-related chronic disease in the Australian private health insurance setting. This study investigated the impact of the maintenance programme on anthropometric and lifestyle risk behaviour changes after 6 and 12 months, and trends in weight-loss maintenance after 1 year. Using a pre- and post-test design, data were analysed with generalized linear mixed models for repeated measures to determine the effect of the programme on weight loss and lifestyle behaviour outcomes. After initially losing a clinically significant amount of weight (mean 9.1 kg), maintenance-programme participants maintained clinically significant weight loss (mean 7.6 kg) at 12 months. Rates of discontinuation in the programme were high (47% at 6 months and 73% at 12 months). Weight-loss maintenance was achieved by 76% of participants at 3 months and 62% at 6 months, stabilizing at 55% and 56% at 9 and 12 months, respectively. Greater initial weight loss was associated with weight-loss maintenance at 12 months. Participants <55 years demonstrated consistent weight-loss maintenance over this time but the odds for successful weight-loss maintenance for those ≥55 years continued to decrease over time. At maintenance-baseline, 68.3% of participants had sufficient physical activity for health; 61.4% and 19.8% met recommended fruit and vegetable consumption, respectively. All lifestyle risk behaviours were maintained at 12 months. A programme extending support strategies for maintaining weight-related behaviour shows promise to successfully support these changes over 12 months. There is a potentially important opportunity for targeted intervention at 6 to 9 months.

Variability in engagement and progress in efficacious integrated collaborative care for primary care patients with obesity and depression: Within-treatment analysis in the RAINBOW trial

INTRODUCTION

The RAINBOW randomized clinical trial validated the efficacy of an integrated collaborative care intervention for obesity and depression in primary care, although the effect was modest. To inform intervention optimization, this study investigated within-treatment variability in participant engagement and progress.

METHODS

Data were collected in 2014-2017 and analyzed post hoc in 2018. Cluster analysis evaluated patterns of change in weekly self-monitored weight from week 6 up to week 52 and depression scores on the Patient Health Questionnaire-9 (PHQ-9) from up to 15 individual sessions during the 12-month intervention. Chi-square tests and ANOVA compared weight loss and depression outcomes objectively measured by blinded assessors to validate differences among categories of treatment engagement and progress defined based on cluster analysis results.

RESULTS

Among 204 intervention participants (50.9 [SD, 12.2] years, 71% female, 72% non-Hispanic White, BMI 36.7 [6.9], PHQ-9 14.1 [3.2]), 31% (n = 63) had poor engagement, on average completing self-monitored weight in <3 of 46 weeks and <5 of 15 sessions. Among them, 50 (79%) discontinued the intervention by session 6 (week 8). Engaged participants (n = 141; 69%) self-monitored weight for 11-22 weeks, attended almost all 15 sessions, but showed variable treatment progress based on patterns of change in self-monitored weight and PHQ-9 scores over 12 months. Three patterns of weight change (%) represented minimal weight loss (n = 50, linear β1 = -0.06, quadratic β2 = 0.001), moderate weight loss (n = 61, β1 = -0.28, β2 = 0.002), and substantial weight loss (n = 12, β1 = -0.53, β2 = 0.005). Three patterns of change in PHQ-9 scores represented moderate depression without treatment progress (n = 40, intercept β0 = 11.05, β1 = -0.11, β2 = 0.002), moderate depression with treatment progress (n = 20, β0 = 12.90, β1 = -0.42, β2 = 0.006), and milder depression with treatment progress (n = 81, β0 = 7.41, β1 = -0.23, β2 = 0.003). The patterns diverged within 6-8 weeks and persisted throughout the intervention. Objectively measured weight loss and depression outcomes were significantly worse among participants with poor engagement or poor progress on either weight or PHQ-9 than those showing progress on both.

CONCLUSIONS

Participants demonstrating poor engagement or poor progress could be identified early during the intervention and were more likely to fail treatment at the end of the intervention. This insight could inform individualized and timely optimization to enhance treatment efficacy.

TRIAL REGISTRATION

ClinicalTrials.gov# NCT02246413.

Effect of an Intervention for Obesity and Depression on Patient-Centered Outcomes: An RCT

INTRODUCTION

An integrated collaborative care intervention was successful for treating comorbid obesity and depression. The effect of the integrated intervention on secondary outcomes of quality of life and psychosocial functioning were examined, as well as whether improvements in these secondary outcomes were correlated with improvements in the primary outcomes of weight and depressive symptoms.

STUDY DESIGN

This RCT compared an integrated collaborative care intervention for obesity and depression to usual care. Data were analyzed in 2018.

SETTING/PARTICIPANTS

Adult primary care patients (n=409) with a BMI ≥30 (≥27 if Asian) and 9-Item Patient Health Questionnaire score ≥10 were recruited from September 30, 2014 to January 12, 2017 from primary care clinics in Northern California.

INTERVENTION

The 12-month intervention integrated a behavioral weight loss program and problem-solving therapy with as-needed antidepressant medications for depression.

MAIN OUTCOME MEASURES

A priori secondary outcomes included health-related quality of life (Short Form-8 Health Survey), obesity-specific quality of life (Obesity-Related Problems Scale), sleep disturbance and sleep-related impairment (Patient-Reported Outcomes Measurement Information System), and functional disability (Sheehan Disability Scale) at baseline and 6 and 12 months.

RESULTS

Participants randomized to the intervention experienced significantly greater improvements in obesity-specific problems, mental health-related quality of life, sleep disturbance, sleep-related impairment, and functional disability at 6 months but not 12 months. Improvements in obesity-related problems (β=0.01, 95% CI=0.01, 0.02) and sleep disturbance (β= -0.02, 95% CI= -0.04, 0) were associated with lower BMI. Improvements in the physical (β= -0.01, 95% CI= -0.01, 0) and mental health components (β= -0.02, 95% CI= -0.03, -0.02) of the Short Form-8 Health Survey as well as sleep disturbance (β=0.01, 95% CI=0.01, 0.02) and sleep-related impairment (β=0.01, 95% CI=0, 0.01) were associated with fewer depressive symptoms.

CONCLUSIONS

An integrated collaborative care intervention for obesity and depression that was shown previously to improve weight and depressive symptoms may also confer benefits for quality of life and psychosocial functioning over 6 months.

TRIAL REGISTRATION

This study is registered at clinicaltrials.gov NCT02246413.

Predicting 2-year weight loss through temporally specific earlier losses, relevant behaviors, and their psychological correlates: Implications for behavioral treatment architectures

Maintaining loss of weight beyond an initial 6-9 months remains problematic, with research indicating little recent progress. A poor understanding of how and when prior weight loss, behavioral changes, and psychosocial predictors are associated with long-term weight changes persists. To better-inform behavioral treatments for long-term success with weight loss, women with obesity (N = 86; M_age  = 48.6 years) volunteered for research incorporating community-based weight-management treatments. They were assessed at months 6, 12, and 24 on theory-based psychosocial and behavioral factors, and over 24 months on weight. Considering the included times and temporal ranges, it was found that change in weight from month 6-24 was the strongest predictor of 24-month weight change, and physical activity and fruit/vegetable intake at month 24 best predicted that change in weight. Self-regulation, self-efficacy, and mood at month 24 best predicted both physical activity and fruit/vegetable intake at month 24, with body satisfaction also a significant predictor of physical activity. From these data, mediation analyses found that the predictions of long-term weight loss by scores of self-regulation, self-efficacy, body satisfaction, and mood at month 24 were significantly mediated by fruit/vegetable intake and physical activity in separate equations. Findings indicated both psychosocial and behavioral targets, and timing for those targets, most indicative of long-term success with weight loss.

Longitudinal Weight Outcomes From a Behavioral Lifestyle Intervention in Clinical Practice

PURPOSE

The purpose of this electronic health record (EHR)-based retrospective cohort study was to characterize a population of patients participating in a 12-month, lifestyle change program in a community-based health system and to examine longitudinal weight outcomes.

METHODS

Program participants were identified in the EHRs of a health care delivery system across 18 sites between 2010 and 2017. Outcomes were mean weight change and proportion of patients with ≥5% weight loss through 24 months from program initiation.

RESULTS

Among 4463 program participants, 3156 met study eligibility criteria, with a mean ± SD age of 53.5 ± 13.1 years; 77.7% were women. Mean baseline weight ± SD was 101.3 ± 23.8 kg. Three main cardiometabolic risk groups were identified: prediabetes/high risk for diabetes (47.3%), overweight/obese in the absence of elevated diabetes risk (27.2%), and existing diabetes (23.9%). Maximal mean weight loss was 3.9% at 6 months from baseline. At 12 and 24 months from baseline, mean weight loss was 3.2% and 2.3%, respectively, with 31% and 29% of participants attaining ≥5% weight loss. Long-term weight outcomes were similar across risk groups.

CONCLUSIONS

A lifestyle change program in a clinical practice setting is associated with modest weight loss, sustained through 24 months, among participants with a range of cardiometabolic risk factors. More than one-quarter of participants achieve ≥5% weight loss, regardless of cardiometabolic risk.

Precision medicine in adult and pediatric obesity: a clinical perspective

It remains largely unknown as to why some individuals experience substantial weight loss with obesity interventions, while others receiving these same interventions do not. Person-specific characteristics likely play a significant role in this heterogeneity in treatment response. The practice of precision medicine accounts for an individual's genes, environment, and lifestyle when deciding upon treatment type and intensity in order to optimize benefit and minimize risk. In this review, we first discuss biopsychosocial determinants of obesity, as understanding the complexity of this disease is necessary for appreciating how difficult it is to develop individualized treatment plans. Next, we present literature on person-specific characteristics associated with, and predictive of, weight loss response to various obesity treatments including lifestyle modification, pharmacotherapy, metabolic and bariatric surgery, and medical devices. Finally, we discuss important gaps in our understanding of the causes of obesity in relation to the suboptimal treatment outcomes in certain patients, and offer solutions that may lead to the development of more effective and targeted obesity therapies.

Measuring social support for healthy eating and physical activity in obesity

OBJECTIVES

This study sought to investigate the psychometric properties of two commonly used measures of social support in obesity, namely, the Social Support for Eating Habits (SSEH) and Social Support for Physical Activity (SSPA) scales.

DESIGN

Cross-sectional and longitudinal study design.

METHODS

Participants were 200 adults with obesity taking part in a 12-month cognitive behavioural weight loss programme. At pre-treatment, participants completed the SSEH and SSPA as well as measures of social support, motivation, self-efficacy, and health-related quality of life to assess concurrent validity. Predictive validity was assessed in terms of baseline SSEH and SSPA scores predicting post-treatment weight while controlling for pre-treatment weight.

RESULTS

Factor analysis supported a two-factor solution for both the SSEH ('Encouragement' and 'Discouragement') and SSPA ('Participation' and 'Punishment') scales, with each subscale demonstrating acceptable internal consistency. While the results provided some support for the concurrent validity of the SSEH Discouragement and SSPA Participation subscales, there was mixed support for the SSEH Encouragement subscale and poor support for the SSPA Punishment subscale. No support was found in terms of predictive validity.

CONCLUSIONS

The findings question the validity of the SSEH and SSPA scales in obesity, with behaviours deemed to be supportive in non-obese populations not necessarily perceived as such by people with obesity. The development of a psychometrically sound measure of social support in the obesity context is needed. Statement of contribution What is already known on this subject? Social support is a robust predictor of positive health outcomes. There is mixed support for the association between social support and weight-related outcomes in obesity. Discrepant findings may be due to social support measures of questionable reliability and validity in obesity. What does this study add? The SSEH and SSPA scales have questionable validity in obesity. Behaviours deemed to be supportive by family and friends may not be perceived as such by individuals with obesity. A psychometrically sound measure of social support in the obesity context is needed.

Predictors of Long-Term Adherence to Multiple Health Behavior Recommendations for Weight Management

BACKGROUND

We have demonstrated previously that patterns of behavioral adherence in the first 6 months of behavioral lifestyle interventions were associated with significant weight loss at 18 months. In this article, we extend this work to examine patterns of behavioral adherence over 18 months and to explore baseline demographic and psychosocial predictors.

METHOD

Latent class analysis was applied separately to the Weight Loss Maintenance and PREMIER trials data to examine patterns of adherence to the following recommendations: (1) consuming ≥9 servings of fruits and vegetables per day, (2) ≤25% of energy from total fat, (3) ≤7% energy from saturated fat, and (4) ≥180 minutes of moderate-to-vigorous physical activity per week. Multinomial logistic regression was used to test demographic and psychosocial predictors of latent class membership.

RESULTS

Four distinct subgroups with common patterns of behavioral adherence were identified in each trial including, Behavioral Maintainers, who maintained adherence to all behavioral recommendations for 1 year, Nonresponders, who did not adhere to the recommendations at any time point, and latent classes that reflected patterns of adherence to one or two behaviors or behavioral relapse. A significantly higher proportion of Behavioral Maintainers sustained ≥5% weight loss for 1 year compared with Nonresponders. Participants with higher vitality scores at baseline were more likely to belong to a latent class with long-term adherence to one or more recommendations than the Nonresponders class.

CONCLUSIONS

Regular assessment of health behaviors and psychosocial measures such as vitality may help identify nonresponders and inform treatment tailoring to improve long-term behavioral and weight outcomes.

Characteristics of Weight Loss Trajectories in a Comprehensive Lifestyle Intervention

OBJECTIVE

Focusing on average weight loss (WL) from interventions provides useful efficacy data but masks large variability across patients. In this study, parameters of weight loss trajectories were determined that differentiated individuals during a 15-week clinical lifestyle intervention.

METHODS

Patients (n = 595) were in a fee-for-service WL lifestyle program with a partial meal replacement diet and lifestyle change counseling. Parameters used in latent class analyses were percent WL (%WL), weight nadir, number of weekly weight gains, maximum weekly percent weight gain, standard deviation of weekly weight changes, linear slope values, and change in slope.

RESULTS

Average %WL was 9.73%. Latent class analyses revealed three groups with considerable overlap in %WL ranges but differing significantly on all trajectory parameters (Ps < 0.001). Group 1 had the most variable and least successful pattern of weight changes. Group 3 had the least variable and most successful pattern of weight changes. Group 2 fell between the others on all parameters.

CONCLUSIONS

Emphasis on average WL likely obscures considerable variability in individual courses of weight change. Moreover, patients with similar %WL can have different WL trajectories. Identification of behavioral/physiological characteristics associated with different weight loss trajectories may facilitate the development of more tailored interventions, particularly for trajectories associated with less optimal outcomes.

The use of support people to improve the weight-related and psychological outcomes of adults with obesity: A randomised controlled trial

OBJECTIVES

To investigate whether training individuals from the personal networks of adults with obesity in the skills of motivational interviewing enhances the anthropometric and psychological outcomes of a cognitive-behavioural weight loss intervention.

METHODS

Adults with obesity (N = 201) were randomised to participate in 26 sessions of cognitive behaviour therapy (CBT) for weight loss either alone (CBT-A) or with the addition of a support person (CBT-SP). Outcomes were assessed at the end of the 12-month intervention and at a follow-up one year later.

RESULTS

Analyses indicated negligible additive effect for the CBT-SP versus the CBT-A condition, although the quality of the patient's relationship with their support person predicted the anthropometric outcomes. Across conditions, significant improvements were observed for all anthropometric (weight, body mass index, and waist circumference) and psychological (self efficacy, weight-related quality of life, weight satisfaction, and binge eating) variables between baseline and post-treatment, and baseline and the follow-up.

CONCLUSIONS

The benefits of the cognitive-behavioural weight loss program were found to extend to psychological variables. Yet the lack of evidence for the additive benefits of including support people in treatment suggests a need to develop more effective training programs for support people in weight management.

TRIAL REGISTRATION

anzctr.org.au Trial ID: ACTRN12611000509965.

Longitudinal Weight Loss Patterns and their Behavioral and Demographic Associations

BACKGROUND

Identification of weight change patterns may allow tailored interventions to improve long-term weight loss.

PURPOSE

To identify patterns of weight change over 18 months, and assess participant characteristics and intervention adherence factors associated with weight change patterns in a sample of 359 overweight/obese adults.

METHODS

Weight loss (0-6 months) was achieved with reduced energy intake and increased physical activity (PA). Maintenance (7-18 months) provided adequate energy to maintain weight and continued PA.

RESULTS

Latent profile analysis identified three weight change profiles. During weight loss/maintenance, participants in profiles 2 and 3 (18-month weight loss ∼14 %) attended more behavioral sessions and performed more PA compared with profile 1 (18-month weight loss <1 %). Self-efficacy for both weight management and exercise barriers were higher in profiles 2 and 3 compared with profile 1 following weight loss and during maintenance.

CONCLUSION

Weight change patterns can be identified and are associated with both participant characteristics and intervention adherence.

The role of social support in weight loss maintenance: results from the MedWeight study

The role of social support in weight management is not fully understood, as more support has been linked to both favorable and unfavorable outcomes. We examined social support in relation to weight loss maintenance, comparing between maintainers and regainers of weight loss. The MedWeight study is a Greek registry of people who have intentionally lost ≥10 % of their weight and are either maintaining this loss for over a year (maintainers), or have regained weight (regainers). Demographics and lifestyle habits questionnaires are completed online. Dietary assessment is carried out by two telephone 24 h recalls. Perceived social support was assessed by validated scales examining support from family and friends regarding healthy eating and exercise. 289 maintainers and 122 regainers participated. Regainers received more support compared to maintainers. However, maintainers reported receiving compliments and active participation, whereas regainers receiving verbal instructions and encouragements. Maintainers who received diet support displayed improved dietary intakes, such as lower energy intake; regainers' diet was unaffected by support. Positive, rather than instructive, support appears beneficial in weight loss maintenance.

Stage of Change and Motivation to a Healthier Lifestyle before and after an Intensive Lifestyle Intervention

OBJECTIVE

Lifestyle modification programs are different but typically include both nutritional aspects and physical activity as main domains with different behavioral and/or psychological strategies designed to affect change. A fundamental role in modifying unhealthy habits is played by personal motivation for change. The present study sought to investigate, in a group of 100 overweight/obese outpatients with and/or without TMD2, treatment seeking, the effect of an intensive lifestyle program on medical measures and motivational profile for physical activity (PA) and healthy nutrition (NUTR).

METHOD

Subjects participated in an intensive multidisciplinary lifestyle intervention at C.U.R.I.A.MO. Before and after the intervention, patients received a comprehensive evaluation of their clinical, anthropometric, and metabolic states and motivation to lifestyle changes.

RESULTS

Data showed differences before and after intervention in both medical and motivational measures. Before the intervention patients reported to be ready, open, and determined to change and gave importance to healthy habits. After the intervention patients continued to be determined but increased the actions toward the change showing a higher degree of maintenance and of acquisition of habits especially in the physical domain of the new lifestyle.

CONCLUSION

Data support the notion that the motivation should be followed during all the lifestyle interventions to support the change on both domains of the lifestyle program.

Evaluation of physical activity reporting in community Diabetes Prevention Program lifestyle intervention efforts: A systematic review

INTRODUCTION

The Diabetes Prevention Program (DPP) lifestyle intervention has been translated to community settings using the DPP goals of 7% weight loss and 150min of moderate physical activity (PA) per week. Given that PA is a primary lifestyle goal and has been linked to improvements in metabolic health in the DPP, it is important to understand the role that PA plays in translation effort success. The purpose of this review is to thoroughly evaluate the reporting of PA methodology and results in DPP-based translations in order to guide future prevention efforts.

METHODS

PubMed and Ovid databases were searched to identify peer-reviewed original research articles on DPP-based translations for adults at-risk for developing diabetes or cardiovascular disease, limited to English language publications from January 2002-March 2015.

RESULTS

72 original research articles describing 57 translation studies met eligibility criteria. All 57 study interventions included a PA goal, 47 studies (82%) collected participant PA information, and 34 (60%) provided PA results.

CONCLUSIONS

Despite PA being a primary intervention goal, PA methodology and results are under-reported in published DPP translation studies. This absence and inconsistency in reporting PA needs addressed in order to fully understand translation efforts' impact on participant health.

Early-treatment weight loss predicts 6-month weight loss in women with obesity and depression: implications for stepped care

OBJECTIVE

Some adults with comorbid depression and obesity respond well to lifestyle interventions while others have poor outcomes. The objective of this study was to evaluate whether early-treatment weight loss progress predicts clinically significant 6-month weight loss among women with obesity and depression.

METHODS

We conducted a secondary analysis of data from 75 women with obesity and depression who received a standard lifestyle intervention. Relative risks (RRs) and 95% confidence intervals (CIs) for achieving ≥5% weight loss by 6 months were calculated based on whether they achieved ≥1 lb/week weight loss in weeks 2-8. Among those on target at week 3, we examined potential subsequent time points at which weight loss progress might identify additional individuals at risk for treatment failure.

RESULTS

At week 2, women who averaged ≥1 lb/week loss were twice as likely to achieve 5% weight loss by 6 months than those who did not (RR=2.40; 95% CI: 2.32-4.29); weight loss at weeks 3-8 was similarly predictive (RRs=2.02-3.20). Examining weight loss progress at week 3 and subsequently at a time point during weeks 4-8, 52-67% of participants were not on target with their weight loss, and those on target were 2-3 times as likely to achieve 5% weight loss by 6 months (RRs=1.82-2.92).

CONCLUSION

Weight loss progress as early as week 2 of treatment predicts weight loss outcomes for women with comorbid obesity and depression, which supports the feasibility of developing stepped care interventions that adjust treatment intensity based on early progress in this population.