Characteristics of Weight Loss Trajectories in a Comprehensive Lifestyle Intervention

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.

Percentage of maximum weight lost as an optimal parameter of weight regain after bariatric surgery in Chinese patients with diabetes

OBJECTIVE

The goal of this study was to compare measures of weight regain (WR) and their association with the glucose metabolism deterioration within 3 years following bariatric surgery among Chinese patients with obesity and type 2 diabetes mellitus (T2DM).

METHODS

Among a retrospective cohort of 249 patients with obesity and T2DM who underwent bariatric surgery and were followed up to 3 years, WR was assessed by weight changes, BMI changes, percentage of presurgery weight, percentage of nadir weight, and percentage of maximum weight lost (%MWL). Glucose metabolism deterioration was defined as a change from an absence of antidiabetic medication use to use, or absence of insulin use to use, or an increase in glycated hemoglobin by at least 0.5% to 5.7% or greater.

RESULTS

A comparison of C-index of glucose metabolism deterioration indicated %MWL had better discriminatory ability versus weight change, BMI change, percentage of presurgery weight, or percentage of nadir weight (all p < 0.01). The %MWL also had the highest prediction accuracy. The optimal %MWL cutoff point was 20%.

CONCLUSIONS

Among Chinese patients with obesity and T2DM who underwent bariatric surgery, WR quantified as %MWL predicted 3-year postoperative glucose metabolism deterioration better than the alternatives; 20% MWL was the optimal cutoff point.

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.

The Role of Psychological Well-Being in Weight Loss: New Insights from a Comprehensive Lifestyle Intervention

Background/Objective

Although the literature suggested that impaired psychological well-being (PWB) is associated with obesity, evidence on the role of PWB in weight outcomes is limited and inconclusive. This research aimed to investigate the joint role of PWB in achieving clinically significant weight loss (CWL; loss of 5% of the initial weight) through a comprehensive lifestyle intervention for obesity using a broad-based evaluation.

Method

This study is a prospective cohort of 96 patients with obesity attending a comprehensive lifestyle intervention for weight loss. Data on weight, lifestyle, PWB, and distress, were collected before and after the intervention.

Results

30.5% of the participants achieved CWL at the end of treatment. A more pronounced increase in autonomy (odds ratio = 0.80 [95% CI: 0.68, 0.93], p ≤ .01) and somatization (odds ratio = 0.83 [95% CI: 0.70, 0.98], p ≤ .05) from pre- to post-treatment were independently associated with a lower probability of CWL.

Conclusions

Unbalanced dimensions of PWB, in particular exceedingly high autonomy, may contribute to a poor weight loss outcome. This study paves the way for the addition of psychotherapeutic strategies geared to euthymia in comprehensive lifestyle intervention.

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.

The Gut Microbiota during a Behavioral Weight Loss Intervention

Altered gut microbiota has been linked to obesity and may influence weight loss. We are conducting an ongoing weight loss trial, comparing daily caloric restriction (DCR) to intermittent fasting (IMF) in adults who are overweight or obese. We report here an ancillary study of the gut microbiota and selected obesity-related parameters at the baseline and after the first three months of interventions. During this time, participants experienced significant improvements in clinical health measures, along with altered composition and diversity of fecal microbiota. We observed significant associations between the gut microbiota features and clinical measures, including weight and waist circumference, as well as changes in these clinical measures over time. Analysis by intervention group found between-group differences in the relative abundance of Akkermansia in response to the interventions. Our results provide insight into the impact of baseline gut microbiota on weight loss responsiveness as well as the early effects of DCR and IMF on gut microbiota.

Impact of Race and Ethnicity on Weight-Loss Outcomes in Pediatric Family-Based Obesity Treatment

INTRODUCTION

Minority children are disproportionately affected by obesity and little is known about how race/ethnicity impacts outcomes in pediatric weight-loss treatment. This study aimed to evaluate whether race/ethnicity affected weight-loss outcomes in a pediatric obesity intervention. Secondary aims included evaluating whether race/ethnicity was associated with energy intake, exercise, program adherence, acceptability, and attendance.

METHODS

One hundred fifty parent/child dyads (age 8-12 years, BMI% 85-99.9; 32% Hispanic, 24% Non-Hispanic, Non-White, 44% Non-Hispanic White) participated in a randomized control trial evaluating weight loss in family-based behavioral treatment with (FBT) or without child participation (i.e., Parent-Based Treatment, PBT). Assessments occurred at baseline, mid-treatment (month 3), post-treatment (month 6), and follow-up (months 12 and 24). Analyses included linear mixed effect models, linear models, and a negative binomial model.

RESULTS

Weight loss in Hispanic, Non-Hispanic White, and Non-Hispanic, Non-White children was not significantly different by race/ethnicity at months 6, 12, and 24 (p = 0.259) and was similar across both treatments (FBT = - 0.16 BMIz; PBT = - 0.21 BMIz; p = 0.61). There were no differences in energy intake, physical activity, acceptability ratings, or adherence to treatment (as measured by a post-treatment survey) (p's > 0.123). However, Hispanic families attended fewer treatment visits than Non-Hispanic White families (p = 0.017).

CONCLUSION

On average, children lost weight participating in our pediatric obesity treatment and there was no statistical difference in weight loss between groups. Future research evaluating whether culturally adapted treatments would be more effective for racial/ethnic minorities or whether the personalization inherent in family-based behavioral treatment may be sufficient is needed.

Gestational Weight Gain: Achieving a Healthier Weight Between Pregnancies

Rates of obesity continue to be a cause of morbidity and mortality, requiring intervention. Excessive gestational weight gain is related to postpartum weight retention and subsequent development of obesity, which translates into higher risk of adverse maternal and neonatal outcomes in future pregnancies and long-term excess cardiovascular disease and cancer for the mothers. Limiting gestational weight gain to within recommended limits prevents postpartum weight retention. This article provides an overview of methods and practices aimed at helping women achieve a healthy weight between pregnancies by improving gestational weight gain. These interventions include lifestyle behavioral changes, diet and exercise, and motivational interviewing.

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.

Patients' reasons for weight loss and their relations to clinical weight loss outcomes in a comprehensive lifestyle intervention

OBJECTIVE

Research suggests that individuals seeking weight loss treatment do so for a variety of reasons. Limited work has explored relations of reasons for weight loss to patient characteristics or to weight loss outcomes. The current study examined these relations.

METHODS

The sample consisted of 588 patients in a 15-week fee-for-service weight loss programme. Prior to the intervention, patients completed questionnaires including items on reasons for weight loss, demographic characteristics, and a variety of weight-based characteristics. Patients' weight change outcomes were expressed as percent weight loss and also categorized into one of three previously described weight loss trajectories.

RESULTS

The results of chi-squared and t-test analyses suggested that endorsement of health concerns, mobility concerns, or another person's recommendation was associated with higher body mass index (BMI) and older age. These reasons were more likely to be endorsed by White patients than Black patients and by male patients than female patients. Endorsement of doctor recommendation was more likely to be seen among Black patients than White patients. There was no significant relation of any weight loss reason with weight loss outcome.

CONCLUSIONS

While certain reasons for weight loss were more often cited by certain patient groups, no specific reason predicted a better or worse outcome.

Sauver J, Phelan SM, Croghan IT. Experience and expectations of patients on weight loss: The Learning Health System Network Experience

OBJECTIVE

Weight perception and degree of confidence in achieving healthy lifestyle can be determinants of engagement in obesity interventions. This study explored patients' perceived need for weight loss and the degree of self-confidence in ability to lose weight and sought to identify factors associated with patients' self-confidence in ability to lose weight.

METHODS

The authors analysed data from a survey mailed to primary care patients within five sites of the Learning Health Systems Network that explored participants' prior experience with weight management.

RESULTS

Among the 2,263 participants who completed the survey section on 'Patients' Experience with Weight Management', perceived need to lose 51 lb or more was statistically significant among those with class III obesity compared with other body mass index (BMI) groups (p value < 0.001). Reported desire to lose weight was also significantly higher among those with the highest BMI than those who were overweight (p value < 0.001). However, this same group had the lowest belief in ability to lose weight (p value < 0.001). In a multiple regression analysis, female gender, higher BMI and need to lose >10 lb were each independently associated with less belief in being able to lose weight.

CONCLUSIONS

Patients had varying perceptions on weight loss; those with category III obesity had the highest desire to lose weight but had the least confidence in ability to lose weight. Higher BMI, female gender and need to lose >10 lb were associated with decreased self-confidence in ability to lose weight.

Gut microbiome-targeted therapies in nonalcoholic fatty liver disease: a systematic review, meta-analysis, and meta-regression

BACKGROUND

Preclinical evidence suggests that modulation of the gut microbiome could represent a new therapeutic target in nonalcoholic fatty liver disease (NAFLD).

OBJECTIVES

The aim of this study was to evaluate the most current evidence for liver-specific and metabolic effects of microbiome-targeted therapies (MTTs) in persons with NAFLD.

METHODS

We searched multiple electronic databases for randomized controlled trials (RCTs) published from January 1, 2005 to December 1, 2018 that enrolled persons with NAFLD who received MTT rather than placebo or usual care. MTT was defined as antibiotics, probiotics, synbiotics, or fecal microbiota transplantation (FMT). Clinical outcomes were pooled with the use of random-effects models and heterogeneity was assessed with the I2 statistic. A random-effects meta-regression was performed to determine sources of heterogeneity in prevalence estimates between studies.

RESULTS

Twenty-one RCTs (1252 participants) were included; 9 evaluated probiotics and 12 evaluated synbiotics, with treatment duration ranging from 8 to 28 wk. No RCTs examined the efficacy of antibiotics or FMT. Probiotics/synbiotics were associated with a significant reduction in alanine aminotransferase activity [ALT, weighted mean difference (WMD): -11.23 IU/L; 95% CI: -15.02, -7.44 IU/L] and liver stiffness measurement (LSM) by elastography (reflecting inflammation and fibrosis) (WMD: -0.70 kPa; 95% CI: -1.00, -0.40 kPa), although analyses showed heterogeneity (I2 = 90.6% and I2 = 93.4%, respectively). Probiotics/synbiotics were also associated with increased odds of improvement in hepatic steatosis, as graded by ultrasound (OR: 2.40; 95% CI: 1.50, 3.84; I2 = 22.4%). No RCTs examined sequential liver biopsy findings. Probiotics (WMD: -1.84; 95% CI: -3.30, -0.38; I2 = 23.6%), but not synbiotics (WMD: -0.85; 95% CI: -2.17, 0.47; I2 = 96.6%), were associated with a significant reduction in body mass index.

CONCLUSIONS

The use of probiotics/synbiotics was associated with improvement in liver-specific markers of hepatic inflammation, LSM, and steatosis in persons with NAFLD. Although promising, given the heterogeneity in pooled analyses, additional well-designed RCTs are needed to define the efficacy of probiotics/synbiotics for treatment of NAFLD. This study was registered with PROSPERO as CRD42018091455.

Experience from the selection and nutritional preparation for Expedition ICE MAIDEN: the first successful all-female unassisted Antarctic traverse

INTRODUCTION

Expedition ICE MAIDEN (Ex IM) was the first all-female unsupported crossing of Antarctica. We describe the prerequisite selection and training, comparing those who formed the final team with other participants, and discuss how the expedition diet was established.

METHODS

All women serving in the British Army were invited to participate. Following initial assessments, successful women completed three training/selection ski expeditions. Between expeditions 1 and 2, participants completed 6 months rigorous UK-based training. Weight was measured before and after the 6 months UK-based training, expeditions 2 and 3, and body composition by skinfold before and after expedition 2. Participant feedback, body composition and weight changes were applied to modify the expedition diet and provide weight gain targets prior to Ex IM.

RESULTS

Following 250 applications, 50 women were assessed and 22, 12 and seven women attended training expeditions 1, 2 and 3, respectively. The final team of six women lost more weight than other participants during UK-based training (mean (SD) change -1.3 (1.5) kg vs -0.5 (1.6) kg, respectively, p=0.046) and during training expedition 2 (-2.8 (0.8) kg vs -1.7 (0.4) kg, respectively, p=0.048), when they also gained more lean mass (+2.1 (0.8) kg vs +0.4 (0.7) kg, respectively, p=0.004). The Ex IM diet provided 5000 kCal/day, comprising approximately 45% carbohydrate, 45% fat and 10% protein. Median (range) weight change between expedition 3 and Ex IM was +8.7 (-1.9 to +14.3) kg.

CONCLUSIONS

The selected Ex IM team demonstrated favourable training-associated body composition changes. Training-associated weight loss informed the expeditionary diet design.