6-month Weight Loss Research Articles

771-P: Impact of Maintenance Session Attendance and 6-Month Weight-Loss Goal Achievement on Weight-Loss Success in a One-Year Community Diabetes Prevention Program (DPP) Program

The DPP lifestyle intervention showed that meeting weight loss (WL) and activity goals can prevent/delay T2D. The success of community translated versions of it (e.g., Group Lifestyle Balance, DPP-GLB) has led to Medicare reimbursement based on session attendance (at 6 and 12 months) and participant success at meeting a 5% WL goal at 12 months. Although attendance has been suggested to be related to WL success, the impact of the 6 monthly maintenance sessions (mos 7-12) after the more frequent 16 core sessions (mos 0-6) on one-year WL is not known. This effort examines how maintenance session attendance and WL goal status at 6 months in DPP-GLB affects achievement of the 12-month 5% WL goal. Data were combined from two identical intervention trials that delivered the 12-month DPP-GLB in a community setting to overweight/obese adults (mean age 62 years, 76% women) with prediabetes and/or metabolic syndrome. Participants who attended ≥4 core sessions during the first 6 months and had complete data on maintenance attendance and WL were included (n=238). Meeting the 6-month WL goal was associated with greater odds of meeting the 12-month WL goal (p<.0001). Odds of meeting the 12-month 5% WL goal were significantly greater for those who attended ≥4 maintenance sessions vs. those who did not (OR=6.0, 95% CI: 2.4-15.0). When stratified by achieving the 5% WL goal at 6 months, those who attended ≥4 maintenance sessions and met the 6-month WL goal were more likely to meet the WL goal at 12 months (OR=11.4, CI: 3.2- 40.7) compared to those who failed to meet the WL goal at 6 months (OR=1.5, CI: 0.3-7.5). Adjustment for age, gender and 6-month physical activity yielded similar results. Attending DPP-GLB maintenance sessions and meeting the 6-month WL goal increased the odds of meeting ≥5% WL at 12 months. For those who failed to meet the 6-month WL goal, attending maintenance sessions did not significantly improve their chance of 12-month WL success. Disclosure J. Napoleone: None. R.G. Miller: None. S. Devaraj: None. B. Rockette-Wagner: None. V.C. Arena: None. E.M. Venditti: None. K. Kramer: None. A. Kriska: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R18DK100933, R18DK081323)

Bone Mineral Density and Fracture Risk in Obese Older Adults 12 Months After Completion of a 6-Month Higher Protein Diet and Exercise Intervention

Abstract Objectives Weight loss interventions for older adults often reduce bone mineral density (BMD), increasing risk of subsequent detrimental outcomes. This study explored the long-term impact of a higher protein diet plus exercise versus a diet plus exercise control treatment on body weight, bone mineral density at 3 sites, and fracture risk. Methods Obese (BMI 34.3 ± 4.7 kg/m2) older adults (n = 55; age = 70.0 ± 6.1 yrs) with Short Physical Performance Battery (SPPB) score = 9.2 ± 1.4 (out of 12) who completed a 6-month weight loss plus exercise trial were invited to return for assessment 12 months later. The original randomization was to either 0.8 g protein/kg body weight (Control) or 1.2 g protein/kg body weight, predominantly dairy (Protein). The 18-month assessment included BMD by DEXA (Hologic, Horizon model A) for femoral neck (FN), total hip (TH), and spine (lumbar vertebrae 1–4; LS), as well body weight and secondary outcomes for Fracture Risk Assessment Tool (FRAX). Results A total of 38 (69.1%) study completers were assessed at 18 mo. Body weight was lower than baseline for both Control and Protein (P < 0.01), with Control (−4.8%) trending towards better maintenance of weight loss vs Protein (−2.3%) (P = 0.06). BMD at 18 mo. was not different from baseline in both Control and Protein for LS (0.01 ± 0.05 g/cm2 and −0.0002 ± 0.05 g/cm2; P = 0.512), FN (−0.01 ± 0.07 g/cm2 and −.009 ± 0.04 g/cm2; P = 0.814) and TH (−0.012 ± 0.03 g/cm2 and −.008 ± 0.033 g/cm2; P = 0.685). Change in BMD at 18 mo. did not differ by group at any site; the previously reported Protein group increase in LS at 6 mo. was not sustained. For individual fracture risk, between 0 and 18 mo., 6 improved (5 osteopenia to normal, 1 osteoporosis to osteopenia) and 1 worsened (normal to osteopenia but FRAX score below total and hip fracture thresholds). Conclusions The finding that obese older adults can maintain a lower body weight for 12 months without a decline in BMD and no increase in fracture risk amplifies our previous findings of legacy benefits of a short term obesity intervention for older adults. Further study is needed to determine if the protein benefit to LS is sustained if the higher protein intake is continued long term. Funding Sources This study was funded by the National Dairy Council and the US Department of Veterans Affairs Rehabilitation Research and Development Program.

Gut Microbiota Are Predictive of Coach-Directed Behavioral Weight Loss Success over 6 Months in Randomized Trial

Abstract Objectives Several studies have demonstrated human gut microbiota are involved in energy balance and obesity, but little is known on how it may influence weight loss efforts. The objective of this study is to determine whether features of the gut microbiota predict weight loss at 6 months in participants enrolled in a trial of coach-directed behavioral weight loss. Methods We used baseline clinical and microbiome data to predict 6-month weight loss in participants (n = 36) randomized to a coach-directed weight loss program that included diet and lifestyle modification. We sequenced the microbial 16S rRNA V4 region of stool samples collected at baseline and assigned reads into amplicon sequence variants (ASVs). Successful weight loss was defined as >5% weight loss from baseline to 6 months. We first used Variable Selection Using Random Forests (VSURF) on 571 ASVs that were present in >10% of samples, measures of alpha diversity (observed species and Shannon index), along with sex, age, BMI, and race to identify the strongest predictors of weight loss. The features selected by VSURF were then included with clinical characteristics in a final leave-one-out cross-validated random forest model to predict weight loss. We used log Poisson regression models with robust variance estimates to assess the direction and significance (FDR P < 0.05) of each predictor's association with weight loss. Results After 6 months of coach-directed behavioral weight loss, 12 (33%) participants met the goal of losing >5% of their baseline weight. VSURF selected 30 bacterial ASVs for model interpretation. Sex, age, BMI, and race were not selected by VSURF, and when these participant characteristics were forced into the model, they were ranked last. Our final cross-validated random forest model had a kappa of 0.73 (out-of-bag error = 13.9%) for classifying 5% weight loss. Among the top predictors were ASVs from the Ruminococcaceae family (lower with weight loss; FDR P < 0.05), Eubacterium coprostanoligenes (higher with weight loss; FDR P < 0.05). Conclusions Gut microbiota sequencing improved prediction of successful weight loss. The top predictors of weight loss included bacteria that produce butyrate, secondary bile acids, and succinate, adding support to the hypothesis that gut microbiome composition may influence weight loss efforts. Funding Sources NHLBI.

Testing a self-directed lifestyle intervention among veterans: The D-ELITE pragmatic clinical trial

Nearly half of Veterans have obesity, fueling chronic diseases. The Department of Veterans Affairs (VA) offers an evidence-based behavioral weight management intervention called MOVE!, mostly delivered through in-person group sessions. Few eligible Veterans participate due to factors like distance and preferences, mirroring barriers in the general population. Practical alternatives to standard in-person programs are needed to improve access and engagement. A self-directed lifestyle intervention called D-ELITE—delivered through pre-recorded videos by DVD or online streaming—previously efficacious in a general primary care population, may provide such an alternative. This pragmatic clinical trial will evaluate whether D-ELITE improves weight and general health status among Veterans with obesity, relative to VA usual care. The yearlong intervention includes one orientation by phone, supplemental lifestyle coaching primarily via technology-based messages, 12 DVD or online streaming sessions over 3 months, and continued self-directed weight management for months 4–12. Participants use MyFitnessPal.com or paper booklets for self-monitoring weight, diet, and physical activity. Follow-up assessments at 12 and 24 months are administered by mail or phone. The study hypothesis is that compared with usual care, D-ELITE will lead to greater improvements in 12-month weight loss, per VA electronic health records, and general physical health status, assessed using the self-reported SF-12 physical composite score. We will also explore D-ELITE's effects on secondary biometric (e.g., HbA1c) and intermediate (e.g., diet) outcomes, reach, and budget impact. If effective, D-ELITE will offer a potentially scalable, low-cost alternative to VA's existing weight loss interventions by mitigating barriers presented by distance and technology.

0176 Short Sleep Duration and Poor Sleep Quality Predict Blunted Weight Loss in a Behavioral Weight Loss Intervention

Abstract Introduction Short sleep duration and poor sleep quality have each been associated with obesity and weight gain. However, less is known regarding how sleep may impact attempted weight loss. The purpose of this study was to investigate the associations between sleep duration and sleep quality, both independently and in combination, with weight loss in a 12-month behavioral weight loss intervention. Methods Young to middle-aged adults who were overweight or obese (N=296) completed a 12-month behavioral weight loss intervention, with weight assessed at baseline, 6 and 12 months. Sleep duration and quality were derived from the Pittsburgh Sleep Quality Index. Analyses examined the change in sleep over time and the association between baseline sleep and changes in sleep with 6- and 12-month weight loss following adjustment for relevant covariates including age, gender, race, education, baseline body mass index, and baseline risk for sleep apnea. Results Participants (with an average baseline weight of 97.0±1.0 kg) lost 6.6±1.1 kg (6.8%) and 6.7±1.2 kg (6.9%) at 6 and 12 months relative to baseline, respectively. Global sleep quality significantly improved over the 12-month intervention (P=.03), but average sleep duration and the prevalence of short sleep duration (<6 h) or poor sleep quality did not change significantly (each P≥.45). Adults with short sleep duration at baseline lost 3.3±0.9% less weight than those with ≥6 h sleep duration (P<.001). Adults with poor sleep quality at baseline lost 1.6±0.8% less weight than those with good sleep quality (P=.04). When considered together, adults with both short sleep duration and poor sleep quality lost at least 5.0% less weight compared with all other sleep duration/quality group combinations (P<.001). Conclusion Our findings highlight the importance of both sleep duration and sleep quality as predictors of behavioral weight loss and suggest that screening for sleep disturbance may be useful to determine who may benefit from additional counseling and resources. Support R01HL077525, K23HL118318

The impact of weight loss on physical function in overweight or obese breast cancer survivors.

12053 Background: In the prospective POWER-remote trial, 51% and 12% of overweight/obese breast cancer survivors randomized to either a remotely delivered behavioral intervention or self-directed approach, respectively, lost ≥5% of baseline weight. We collected patient-reported outcomes (PROs) to examine the impact of >5% weight loss on symptoms, physical function (PF), and wellbeing. We hypothesized a priori that, regardless of study arm, those with ≥5% weight loss would have improved PF at 6 months v. those who did not. Methods: Women with stage 0-III breast cancer, who completed local therapy and chemotherapy, with a BMI ≥25 kg/m2 were randomized to the 12-month intervention or self-directed weight loss. POWER-remote consists of telephone coaching and online tracking of diet, activity and weight. Women in the self-directed arm received a lifestyle booklet. All women completed PROs at baseline, 6 and 12 months: PROMIS PF, pain, fatigue, anxiety, depression, sleep; FACT-endocrine symptoms; MOS-sexual function. PROs were summarized descriptively and changes within and between groups were tested with multivariable mixed effects models, adjusted for age and baseline weight. Results: From 2013-2015, 96 women enrolled; 83 were evaluable at 6 months. At 6 months, PF scores improved in those with ≥5% weight loss v. not. While endocrine symptoms, fatigue, and anxiety improved in the group who lost ≥5%, differences between groups were not statistically significant. There was no significant change in sexual function, depression, or sleep within or between groups. Similar findings were seen across domains at 12 months, except pain improved in the group losing ≥5%. Conclusions: For overweight/obese breast cancer survivors, PF and other PROs improved among patients who lost ≥5%. These results support the patient-centered benefits of weight loss in this population. Clinical trial information: NCT01871116 . [Table: see text]

Weight loss after minimally-invasive esophagectomy for esophageal cancer.

e16565 Background: Nutritional deficiencies are common in esophageal cancer patients after esophagectomy. Patients frequently present with weight loss due to obstruction. Cancer therapies (chemoradiation and esophagectomy) further compromise nutrient intake through alterations in appetite, gastrointestinal function, and the catabolic effects of therapy. We aimed to understand and identify risk factors associated with post-esophagectomy weight loss. Methods: Patients undergoing minimally-invasive esophagectomy via laparoscopic and thoracoscopic techniques with intra-thoracic anastomosis between January 2015 and July 2019 were identified. Post-operative weight loss at 3- and 6-months post-surgery was calculated as percent change from preoperative weight. Univariate and multivariable generalized linear method (GLM) analysis was performed. Results: 176 patients (145 male, 31 female) underwent esophagectomy, with a median age of 64 [IQR 57-71] and median 3-month postoperative weight loss of 7.9% [IQR 1.5-12.3%]. The majority of patients were Caucasian (89%), histologically diagnosed adenocarcinoma (90%), and received neoadjuvant chemoradiation (71%). Median preoperative BMI was 28.3 [IQR 25.5-32.5]. Preoperative enteral feeding tubes were placed in 86 patients (49%). Five patients (2.8%) were converted to open surgery (laparotomy) and anastomotic leaks occurred in 12 (6.8%) patients. The median length of stay was 9 days [IQR 8-13]. Among a subset of 147 patients with data available, the median 6-month postoperative weight loss was 10% [IQR 5.3-15.0%]. On multivariable analysis, greater preoperative BMI and anastomotic leak were associated with increased weight loss at 3 and 6 months post-esophagectomy. Conclusions: Significant postoperative weight loss is common among minimally-invasive esophagectomy patients. Higher preoperative BMI and postoperative anastomotic complications are significantly associated with increased postoperative weight loss at 3 and 6 months. Need for preoperative feeding tube and conversion to open surgery were further associated with postoperative weight loss. [Table: see text]

SAT-575 Association Between Baseline Fitness and Changes in Physical Activity and Weight Loss in an 18-Month Behavioral Weight Loss Program

BACKGROUND: Baseline cardiovascular fitness may be a significant predictor of future success in a comprehensive behavioral weight loss program (BWLP). Yet, few studies have examined the association between baseline fitness and future weight loss. PURPOSE: To determine the association between baseline fitness and changes in body weight and device-measured levels of moderate-to-vigorous physical activity (MVPA) during a BWLP. METHODS: Adults (n=85) were enrolled in an 18-month BWLP combining a calorie-restricted diet, group-based behavioral support, and 6 months of supervised exercise (progressing to 300 min/wk of moderate-intensity) followed by 12 months of unsupervised exercise. Data from 60 completers (age 41.0±9.5 years, BMI 34.6±4.2 kg/m2, 80% female) were used in this analysis. MVPA was measured over 1 week with the Sensewear Armband at months 0, 6, 12, and 18. Fitness (VO2max) was measured on a treadmill using indirect calorimetry and categorized based on published age and sex norms (Physical Fitness Specialist Certification Manual, 1997). A linear mixed effects model with unstructured covariance was used to examine the association between baseline fitness category and changes in body weight, total MVPA, and MVPA in bouts ≥10 min at the four time points. RESULTS: Of the 60 completers, 33% (n=20) were classified as having very poor fitness, 45% (n=27) poor, 18% (n=11) fair, 3% (n=2) good, and 0% (n=0) excellent or superior. Due to the low proportion of participants categorized as having fair or better fitness, we created a binary fitness variable (very poor vs. poor or better). Baseline BMI was higher in those in the very poor category compared to those in the poor or better category (36.2±4.2 vs 33.7±4.0, p=0.03). There were no significant differences between the two fitness categories in weight change at 6 or 12 months. However, at 18 months, mean weight loss was 4.3±1.7 kg in those in the very poor category and 8.2±1.2 kg in those in the poor or better category, with a marginally significant between-group difference (p=0.07). There were no differences in changes in total or bout MVPA. However, those with very poor fitness had lower bout MVPA at baseline vs. those with poor or better fitness (16±20 vs 33±31 min/d, p=0.03). At 18 months, both groups increased bout MVPA, however bout MVPA remained lower in the very poor vs. poor or better group (24±29 vs 42±29 min/d, p=0.03). Total MVPA showed a similar pattern. CONCLUSION: Baseline fitness may moderate 18-month weight loss, as those with very poor fitness lost less weight compared to those with poor or better fitness levels. Those with poor or better fitness at baseline achieved significantly higher mean levels of MVPA at 18 months compared to those with very poor fitness. Participants with very poor fitness at baseline may require additional exercise support during a BWLP to achieve the high levels of MVPA recommended for weight loss maintenance.

Pilot Trial of Acceptance-Based Behavioral Weight Loss and Neurocognition Among American Indians

Acceptance-based behavioral therapies (ABTs) for obesity may be superior to standard behavioral therapies but have not been adequately tested with American Indians (AIs). Neurocognitive function is also unexamined in relation to behavioral weight loss among AIs despite findings that neurocognition predicts outcomes in general samples, may help explain some of the benefits of ABTs, and may be relevant to marginalized groups. The primary objective of this pilot was to examine the feasibility/acceptability of ABT in an AI sample. Exploratory analyses examined the relationship between neurocognition and weight loss. Forty-eight AI adults with overweight/obesity (ages 43.3 ± 10.3 years, 85% female; baseline body mass index = 36.8 ± 4.4 kg/m2) enrolled in a 6-month open ABT weight loss trial. Feasibility indices, including screening/enrollment, session attendance, retention rates for posttreatment assessments, and program acceptability were examined. Percent weight loss (%WL) was assessed as well as fluid and crystalized neurocognition (National Institutes of Health Toolbox Cognition Battery [NIHTB-CB]). We enrolled 79% of the eligible sample and retained 75% (N = 36) at posttreatment assessments. Program completers lost an average of 5.2 ± 4.9% of initial body weight (dz = 1.14), whereas intent-to-treat analyses show a mean loss of 4.1 ± 4.7%. Participants reported high satisfaction, effectiveness, and cultural appropriateness. Exploratory analyses of neurocognitive domains suggested that crystalized cognition was higher among completers, and higher baseline cognitive flexibility predicted greater %WL (β = .34, p = .05). ABT resulted in clinically significant weight loss in an AI sample. A controlled trial of ABT in a larger, more diverse sample is warranted to determine whether (a) the findings are robust, generalizable, and/or superior to other treatments and (b) neurocognitive factors moderate outcomes.

Weight Regain in Formerly Obese Mice Hastens Development of Hepatic Steatosis Due to Impaired Adipose Tissue Function.

Weight regain after weight loss is common, and there is evidence to suggest negative effects on health because of weight cycling. This study sought to investigate the impact of weight regain in formerly obese mice on adipose tissue architecture and stromal cell function. A diet-switch model was employed for obesity induction, weight loss, and weight regain in mice. Flow cytometry quantified adipose tissue leukocytes in adipose tissue. Liver and adipose tissue depots were compared to determine tissue-specific effects of weight cycling. Epididymal white adipose tissue of formerly obese mice failed to expand in response to repeat exposure to high-fat diet and retained elevated numbers of macrophages and T cells. Weight regain was associated with disproportionally elevated liver mass, hepatic triglyceride content, serum insulin concentration, and serum transaminase concentration. These effects occurred despite an extended 6-month weightloss cycle and theydemonstrate that formerly obese mice maintain durable alterations in their physiological response to weight regain. Conditioned media from epididymal adipose tissue of formerly obese mice inhibited adipogenesis of 3T3-L1 preadipocytes, suggesting a potential mechanism to explain failed epididymal adipose tissue expansion during weight regain. Metabolic abnormalities related to defects in adipose tissue expansion and ongoing dysfunction manifest in formerly obese mice during weight regain.

Physical discomfort intolerance as a predictor of weight loss and physical activity in a lifestyle modification program.

This study examined physical discomfort intolerance (DI) as a baseline predictor of weight loss and physical activity outcomes, and assessed whether changes in DI during the initial phase of weight loss prospectively predicted long-term treatment outcomes among adults enrolled in a group-based lifestyle modification program for obesity. DI was measured at baseline and 6months, and weight and accelerometer-measured physical activity were assessed at baseline, 6months, and 12months. Baseline DI was not related to weight loss or physical activity at either timepoint. Change in DI during the first 6months of treatment was not related to concurrent (i.e., 6-month) weight loss and physical activity, but was significantly predictive of weight loss and physical activity at 12months. Assessing early changes in DI may help to identify individuals at risk for suboptimal outcomes. Future research should evaluate behavioral weight loss interventions designed to target DI.

Individual vs. group-based strategies for weight loss and management in adults: Pen profile perceptions

AimsThe aim of this study was to explore perceptions of barriers, facilitators, strategies and successes in individual vs. group-based weight management programmes. MethodsForty-two, overweight (Body Mass Index ≥ 25-kg.m2) participants (aged 32-63y) volunteered to take part in this study. All participants completed a 3-month weight loss programme, randomised to a group-based (n = 21), or self-monitoring only (n = 21) approach, respectively. Participants subsequently participated in a semi-structured interview (60 ± 7 min) to explore individual and collective perceptions of barriers, facilitators, strategies and successes. ResultsConvergent themes were found for individual and group strategies for facilitators, strategies and successes. Divergent themes were found between groups for barriers, group participants highlighted expense of commercial products, and knowledge of nutrition and dieting, whilst individual participants reported (lack of) social support from peers, (lack of) motivation, and occupation. ConclusionKey stakeholders, facilitators, and individuals must consider these factors prior to the advocation any weight loss strategy.

Abstract MP21: Better Sleep Health is Associated With Greater Weight Loss During a 12-month Behavioral Weight Loss Intervention

Introduction: Sleep is consistently associated with obesity risk, but minimal research has examined its relationship with attempted weight loss. Most of the available evidence has focused on sleep duration, which fails to recognize the multidimensional nature of sleep. Purpose: To examine the relationship between a composite measure of sleep health and weight change in a sample of adults who participated in a 12-month behavioral weight loss intervention. Methods: 125 adults with overweight or obesity enrolled in the EMPOWER study (50.3±10.6 years, 91% female, 81% white) were included in analyses. All individuals participated in a 12-month behavioral weight loss intervention, with assessments at baseline, 6 months, and 12 months. Six dimensions of sleep were included in our operationalization of sleep health: regularity, satisfaction, alertness, timing, efficiency, and duration. Sleep dimensions were assessed using validated questionnaires and actigraphy, with values dichotomized into ‘good’ and ‘poor’ sleep. A composite sleep health score was calculated based upon the sum of the ‘good’ individual dimensions (range: 0-6), with higher scores indicating better sleep health. Obstructive sleep apnea (OSA) was assessed in a subset of participants (n=117) with a portable home sleep testing device, using the apnea-hypopnea index (AHI) as a marker of OSA severity. Linear mixed modeling was used to examine the relationship between sleep health and weight change during the subsequent 6-month interval with adjustment for age, gender, bed partner, and race. An additional model adjusted for AHI along with the previously noted covariates. Results: Mean sleep health was 4.5±1.1 at baseline and 4.5±1.2 at 6 months, and mean % weight change from 0 to 6 months and 6 to 12 months was -9.3±6.1% and 0.4±4.8%, respectively. In the adjusted model, greater sleep health was associated with greater weight loss (b=-0.77, SE=0.32; P=.02). Following additional adjustment for AHI, the relation between sleep health and weight loss was no longer significant (b=-0.53, SE=0.34; P=.12). Among individual sleep dimensions, only regularity and satisfaction showed trends to be associated with weight change (b=-1.28, SE=0.72 [P=.08] and b=-1.67, SE=0.86 [P=.06], respectively); however, these marginal associations were not retained after AHI adjustment (each P=.15). Conclusions: Better sleep health was associated with greater weight loss, but this association did not persist after accounting for OSA severity. Because OSA negatively impacts sleep health, future research should address whether improving sleep health, OSA, and/or the combination leads to better weight loss.

Modeling interactions between brain function, diet adherence behaviors, and weight loss success.

SummaryIntroductionObesity is linked to altered activation in reward and control brain circuitry; however, the associated brain activity related to successful or unsuccessful weight loss (WL) is unclear.MethodsAdults with obesity (N = 75) completed a baseline functional magnetic resonance imaging (fMRI) scan before entering a WL intervention (ie,3‐month diet and physical activity [PA] program). We conducted an exploratory analysis to identify the contributions of baseline brain activation, adherence behavior patterns, and the associated connections to WL at the conclusion of a 3‐month WL intervention. Food cue‐reactivity brain regions were functionally identified using fMRI to index brain activation to food vs nonfood cues. Food consumption, PA, and class attendance were collected weekly during the 3‐month intervention.ResultsThe left middle frontal gyrus (L‐MFG, BA 46) and right middle frontal gyrus (R‐MFG; BA 9) were positively activated when viewing food compared with nonfood images. Structural equation modeling with bootstrapping was used to investigate a hypothesized path model and revealed the following significant paths: (1) attendance to 3‐month WL, (2) R‐MFG to attendance, and (3) indirect effects of R‐MFG through attendance on WL.ConclusionFindings suggest that brain activation to appetitive food cues predicts future WL through mediating session attendance, diet, and PA. This study contributes to the growing evidence of the importance of food cue reactivity and self‐regulation brain regions and their impact on WL outcomes.

DIAL now protocol: A randomized trial examining the provision of phone coaching to those with sub-optimal early weight loss during an Internet weight management program

BackgroundWhile low-intensity Internet-delivered weight loss (IDWL) programs are efficacious, many patients fail to achieve clinically significant weight loss (WL). Given the positive association between 4-week and post-treatment WL, providing a more intensive intervention for those with sub-optimal 4-week WL may improve outcomes for a greater proportion of individuals. This stepped-care approach would minimize cost by reserving more aggressive treatment for those with sub-optimal early WL. ObjectiveThis randomized trial examines whether the provision of brief or extended phone coaching for those with sub-optimal early WL improves 4- and 12-month WL when compared to no coaching. Secondary aims include examination of cost/kg WL and intervention engagement. Methods450 individuals (age 18–70 years, BMI: 25–45 kg/m2) will be randomized to: 1) IDWL+3 weeks of coaching (‘Brief’), 2) IDWL+12 weeks of coaching (‘Extended’), or 3) IDWL only (‘Control’). All individuals will receive a 4-month IDWL program followed by an 8-month IDWL maintenance program. At week 4, individuals will be classified as early sub-optimal responders (<4% WL) or initial responders (≥4% WL). Individuals with sub-optimal early WL randomized to ‘Brief’ or ‘Extended’ will receive 3 and 12 weeks of phone coaching respectively, starting at week 5. Those with sub-optimal early WL randomized to ‘Control’, and initial responders will not receive any coaching. Assessments will occur at 4 and 12 months. DiscussionStudy findings can inform the development of more effective IDWL programs. This model which provides additional support to those with sub-optimal early WL can easily be translated into healthcare and community settings.

Four main barriers to weight loss maintenance? A quantitative analysis of difficulties experienced by obese patients after successful weight reduction

Weight maintenance remains to be a challenge for patients in a reduced obese state and it has been recommended to provide them more individualized support. For this purpose it is crucial to understand the barriers patients are experiencing after weight loss. Many have been identified by qualitative studies. We evaluated if a quantitative assessment of patient perspective during weight maintenance can help identify major barriers that refer to actual regain. Follow-up data were analyzed from patients attempting weight maintenances after successful completion of a nonsurgical weight loss and lifestyle intervention for morbid obesity. The data were acquired at mandatory follow-up assessments and included rating of 26 probable difficulties. A principal component analysis was carried out to explore whether these difficulties could be grouped into meaningful factors. Associations with socio-demographics, follow-up time, and weight changes were evaluated. Data from 88 out of 102 patients were available (baseline BMI 49.5 ± 7.4 kg/m2; 12-month weight loss 24.3 ± 9.6%; follow-up time 1.48 ± 0.6 years). Four solid factors, composed of 21 items and explaining 56% of the variance were extracted and interpreted as 'Hedonic Hunger', 'Mental Distress', 'Binge Eating', and 'Demoralization'. Weight regain (12.4 ± 12%) was correlated with each factor, most closely with 'Mental Distress' (r = 0.38). When controlling for age and follow-up time, 'Binge Eating' was the most important predictor (adj. R2 = 0.297). A quantitative assessment of patient perspective during the first years after weight loss can help identify valid barriers to weight loss maintenance.

Gut microbiota plasticity is correlated with sustained weight loss on a low-carb or low-fat dietary intervention

While low-carbohydrate and low-fat diets can both lead to weight-loss, a substantial variability in achieved long-term outcomes exists among obese but otherwise healthy adults. We examined the hypothesis that structural differences in the gut microbiota explain a portion of variability in weight-loss using two cohorts of obese adults enrolled in the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) study. A total of 161 pre-diet fecal samples were sequenced from a discovery cohort (n = 66) and 106 from a validation cohort (n = 56). An additional 157 fecal samples were sequenced from the discovery cohort after 10 weeks of dietary intervention. We found no specific bacterial signatures associated with weight loss that were consistent across both cohorts. However, the gut microbiota plasticity (i.e. variability), was correlated with long-term (12-month) weight loss in a diet-dependent manner; on the low-fat diet subjects with higher pre-diet daily plasticity had higher sustained weight loss, whereas on the low-carbohydrate diet those with higher plasticity over 10 weeks of dieting had higher 12-month weight loss. Our findings suggest the potential importance of gut microbiota plasticity for sustained weight-loss. We highlight the advantages of evaluating kinetic trends and assessing reproducibility in studies of the gut microbiota.

Modelling multiple health behavior change with network analyses: results from a one-year study conducted among overweight and obese adults.

This study examined the between-person associations of seven health behaviors in adults with obesity participating in a weight loss intervention, as well as the covariations between these behaviors within-individuals across the intervention. The present study included data from a 12-month weight loss trial (N = 278). Seven health behaviors (physical activity, sedentary behavior, sleep duration, and consumption of fruits, vegetables, total fat and added sugar) were measured at baseline, 6- and 12-months. Between- and within-participants network analyses were conducted to examine how these behaviors were associated through the 12-month intervention and covaried across months. At the between-participants level, associations were found within the different diet behaviors and between total fat and sedentary behaviors. At the within-participants level, covariations were found between sedentary and diet behaviors, and within diet behaviors. Findings suggest that successful multiple health behaviors change interventions among adults with obesity will need to (1) simultaneously target sedentary and diet behaviors; and (2) prevent potentialcompensatory behaviors in the diet domain.

Association between objectively measured sleep duration, adiposity and weight loss history

An association between sleep and obesity has been suggested in several studies, but many previous studies relied on self-reported sleep and on BMI as the only adiposity measure. Moreover, a relationship between weight loss history and attained sleep duration has not been thoroughly explored. The study comprised of 1202 participants of the European NoHoW trial who had achieved a weight loss of ≥5% and had a BMI of ≥25 kg/m2 prior to losing weight. Information was available on objectively measured sleep duration (collected during 14 days), adiposity measures, weight loss history and covariates. Regression models were conducted with sleep duration as the explanatory variable and BMI, fat mass index (FMI), fat-free mass index (FFMI) and waist-hip ratio (WHR) as response variables. Analyses were conducted with 12-month weight loss, frequency of prior weight loss attempts or average duration of weight maintenance after prior weight loss attempts as predictors of measured sleep duration. After adjusting for physical activity, perceived stress, smoking, alcohol consumption, education, sex and age, sleep duration was associated to BMI (P < 0.001), with the highest BMI observed in the group of participants sleeping <6 h a day [34.0 kg/m2 (95% CI: 31.8-36.1)]. Less difference in BMI was detected between the remaining groups, with the lowest BMI observed among participants sleeping 8-<9 h a day [29.4 kg/m2 (95% CI: 28.8-29.9)]. Similar results were found for FMI (P = 0.008) and FFMI (P < 0.001). We found no association between sleep duration and WHR. Likewise, we found no associations between weight loss history and attained sleep duration. In an overweight population who had achieved a clinically significant weight loss, short sleep duration was associated with higher BMI, with similar associations for fat and lean mass. We found no evidence of association between weight loss history and attained sleep duration.

Weight loss after one-anastomosis/mini-gastric bypass - The impact of biliopancreatic limb: A retrospective cohort study.

Background:One-anastomosis/mini-gastric bypass (OAGB/MGB), as a popular bariatric surgery method, has many advantages; however, the biliopancreatic limb length (BPL) in this surgery is under debate. The aim of the study was to evaluate the effect of BPL on weight-loss outcome after OAGB/MGB.Materials and Methods:A retrospective cohort study was performed on 653 patients who underwent OAGB/MGB with adjusted BPL based on preoperative body mass index (BMI) and patient's age, between 2010 and 2015 with 12-month follow-ups. Weight-loss outcomes and complications were analyzed in these patients, considering BPL.Results:Weight, age, sex, and type 2 diabetes mellitus were the most contributory predictors as independent predictors of 12-month excess weight loss, respectively, and BPL was the least contributory predictor.Conclusion:Tailoring BPL in OAGB/MGB based on patient's age and preoperative BMI seems to have acceptable results.