Commercial Weight Loss Program Research Articles

Optimising a digitally delivered behavioural weight loss programme: study protocol for a factorial cluster randomised controlled trial

BackgroundDigitally delivered weight loss programmes can provide a convenient, potentially cheaper, and scalable treatment option for people who may need to lose weight. However, outcomes are often inferior to in-person interventions in the long-term. This trial will use principles from the Multiphase Optimisation Strategy (MOST) framework to test whether it can enhance the effectiveness of a commercial digital behavioural weight loss programme. This trial aims to identify an optimised combination of four intervention components to enhance weight loss over a 24-week period. We will also explore which components contribute to improvements in participant retention and engagement with the programme.MethodsApproximately 1400 adults with a BMI > 21 kg/m2 will be enrolled and randomised to one of 16 experimental conditions in a 24 factorial cluster design. The trial will test four intervention components: an introductory video call with the health coach, drop-in webchat sessions with the health coach, goal setting statements, and food diary review and feedback. All participants will receive the core digital behavioural weight loss programme and up to four new intervention components. Participation in the trial will last for 24 weeks. The primary outcome will be weight change at 16 weeks. Other outcomes, measured at 4, 16, and 24 weeks, include programme drop-out and engagement (number of interactions with the three main app functions). Fidelity and acceptability will be assessed using data on component adherence and self-report questionnaires. Decision-making for the enhanced programme will be based on components that contribute to at least a minimal improvement in weight loss, defined as ≥ 0.75kg, alone or in combination with other components.DiscussionThe factorial design is an efficient way to test the efficacy of behavioural components alone, or in combination, to improve the effectiveness of digital weight loss programmes. This trial will test the implementation of the MOST framework in an industry setting, using routinely collected data, which may provide a better way to refine and evaluate these types of interventions in a model of continuous service improvement.Trial registrationTrial registration: ISRCTN, ISRCTN14407868. Registered 5 January 2024, 10.1186/ISRCTN14407868.

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.

Predictive capacity of COVID-19-related risk beliefs on weight management behaviors on a commercial weight loss program and speed of COVID-19 vaccination uptake: prospective cohort study

BackgroundRecent work has shown that obesity may be a risk factor for severe COVID-19. However, it is unclear to what extent individuals have heard or believe this risk factor information, and how these beliefs may predict their preventive behaviors (e.g., weight management behaviors or COVID-19 preventive behaviors). Previous work has primarily looked at overall risk likelihood perceptions (i.e., not about obesity as a risk factor) within general populations of varying weight and concentrated on COVID-19-related preventive behaviors. Therefore, this prospective cohort study explored whether beliefs about obesity as a risk factor and overall risk likelihood perceptions predicted weight management and COVID-19 preventive behaviors over the next 16 weeks in individuals with obesity or overweight.MethodsParticipants were 393 individuals in the US who joined a commercial weight management program in January, 2021. We leveraged the mobile program’s automatic measurement of real-time engagement in weight management behaviors (e.g., steps taken), while surveys measured risk beliefs at baseline as well as when individuals received COVID-19 vaccination doses (asked monthly) over the next 16 weeks. Mixed effects models predicted engagement and weight loss each week for 16 weeks, while ordinal logistic regression models predicted the month that individuals got vaccinated against COVID-19.ResultsWe found that belief in obesity as a risk factor at baseline significantly predicted greater engagement (e.g., steps taken, foods logged) in program-measured weight management behaviors over the next 16 weeks in models adjusted for baseline BMI, age, gender, and local vaccination rates (minimally adjusted) and in models additionally adjusted for demographic factors. Belief in obesity as a risk factor at baseline also significantly predicted speed of COVID-19 vaccination uptake in minimally adjusted models but not when demographic factors were taken into account. Exposure to obesity risk factor information at baseline predicted greater engagement over 16 weeks in minimally adjusted models.ConclusionsThe results highlight the potential utility of effective education to increase individuals’ belief in obesity risk factor information and ultimately promote engagement or faster vaccination. Future research should investigate to what extent the results generalize to other populations.

Effectiveness of Goal-Directed and Outcome-Based Financial Incentives for Weight Loss in Primary Care Patients With Obesity Living in Socioeconomically Disadvantaged Neighborhoods

Financial incentives for weight management may increase use of evidence-based strategies while addressing obesity-related economic disparities in low-income populations. To examine the effects of 2 financial incentive strategies developed using behavioral economic theory when added to provision of weight management resources. Three-group, randomized clinical trial conducted from November 2017 to May 2021 at 3 hospital-based clinics in New York City, New York, and Los Angeles, California. A total of 1280 adults with obesity living in low-income neighborhoods were invited to participate, and 668 were enrolled. Participants were randomly assigned to goal-directed incentives, outcome-based incentives, or a resources-only group. The resources-only group participants were given a 1-year commercial weight-loss program membership, self-monitoring tools (digital scale, food journal, and physical activity monitor), health education, and monthly one-on-one check-in visits. The goal-directed group included resources and linked financial incentives to evidence-based weight-loss behaviors. The outcome-based arm included resources and linked financial incentives to percentage of weight loss. Participants in the incentive groups could earn up to $750. Proportion of patients achieving 5% or greater weight loss at 6 months. The mean (SD) age of the 668 participants enrolled was 47.7 (12.4) years; 541 (81.0%) were women, 485 (72.6%) were Hispanic, and 99 (14.8%) were Black. The mean (SD) weight at enrollment was 98.96 (20.54) kg, and the mean body mass index (calculated as weight in kilograms divided by height in meters squared) was 37.95 (6.55). At 6 months, the adjusted proportion of patients who lost at least 5% of baseline weight was 22.1% in the resources-only group, 39.0% in the goal-directed group, and 49.1% in the outcome-based incentive group (difference, 10.08 percentage points [95% CI, 1.31-18.85] for outcome based vs goal directed; difference, 27.03 percentage points [95% CI, 18.20-35.86] and 16.95 percentage points [95% CI, 8.18-25.72] for outcome based or goal directed vs resources only, respectively). However, mean percentage of weight loss was similar in the incentive arms. Mean earned incentives was $440.44 in the goal-directed group and $303.56 in the outcome-based group, but incentives did not improve financial well-being. In this randomized clinical trial, outcome-based and goal-directed financial incentives were similarly effective, and both strategies were more effective than providing resources only for clinically significant weight loss in low-income populations with obesity. Future studies should evaluate cost-effectiveness and long-term outcomes. ClinicalTrials.gov Identifier: NCT03157713.

The Social Impact of Advertising: How Commercial Weight Loss Program Advertising Promotes Thinness Ideology

Raised body mass index (BMI) is one of the significant risk factors for non-communicable diseases. Regardless of their BMI, more than half of Americans strongly desire to lose weight. As a result, commercial weight loss programs (WLP) have emerged and proliferated in the United States. This study examines WLP advertising as a vehicle for promoting the thinness ideology and how these advertisements impact women’s beliefs and attitudes about self-perceived ideal body image. This study defines thinness ideology as emphasizing being thin and self-perceived ideal body image as individuals’ desired body shapes formed by internalization through advertising messages. By employing four significant theories, this study focuses on how women form their self-perceived ideal body image and, as a result, change their beliefs and attitudes as measured by their changing levels of self-esteem and body (dis)satisfaction. The model is theoretically based on the elaboration likelihood model (ELM) and has been incorporated with social learning theory, social comparison theory, and satisfaction theory. The model also explains the linear transmission of weight loss program advertisements and changes in individuals’ perceptions, beliefs, and attitudes about ideal body image. According to the model, beliefs and attitudes change depending on individuals’ self-esteem and body dissatisfaction levels, often influenced by WLP advertisements promoting the thinness ideology. Keywords: Weight loss program advertising, Theoretical Mapping, Thinness Ideology, Elaboration likelihood model, Social learning theory, Social comparison theory, Satisfaction theory DOI: 10.7176/NMMC/102-03 Publication date: October 31 st 2022

Weight loss strategies, weight change, and type 2 diabetes in US health professionals: A cohort study.

BackgroundWeight loss is crucial for disease prevention among individuals with overweight or obesity. This study aimed to examine associations of weight loss strategies (WLSs) with weight change and type 2 diabetes (T2D) risk among US health professionals.Methods and findingsThis study included 93,110 participants (24 to 60 years old; 11.6% male) from the Nurses’ Health Study (NHS), NHSII, and Health Professionals Follow-Up Study (HPFS) cohorts who were free of T2D, cardiovascular disease, and cancer at baseline (1988 for NHS/HPFS and 1989 for NHSII) for analyses of weight change and 104,180 (24 to 78 years old; 14.2% male) for T2D risk assessment. WLSs used to achieve an intentional weight loss of 4.5+ kg were collected in 1992 (NHS/HPFS)/1993 (NHSII) and grouped into 7 mutually exclusive categories, including low-calorie diet, exercise, low-calorie diet and exercise, fasting, commercial weight loss program (CWLP), diet pills, and FCP (selected at least 2 methods from fasting, CWLP, and pill). The reference group was participants who did not attempt to lose weight. Generalized estimating equations and Cox regression were applied to estimate up to 10-year weight change trajectory and incident T2D risk through 2016 (NHS/HPFS)/2017 (NHSII), respectively.The associations of WLSs with weight change and T2D risk were differential by baseline body weight (Pinteraction < 0.01). Among individuals with obesity, all WLSs tended to associate with less weight gain [ranging from −4.2% (95% confidence interval (CI), −5.1% to −3.2%; P < 0.001) for exercise to −0.3% (−1.2% to 0.7%; P > 0.99) for FCP] and a lower T2D risk [hazard ratios (HRs) ranging from 0.79 (0.66 to 0.95; P = 0.04) for exercise to 0.87 (0.66 to 1.13; P = 0.30) for pill]. Such a pattern was less clear among overweight individuals: the difference of weight change varied from −2.5% (−3.0% to −2.1%; P < 0.001) for exercise to 2.0% (1.3% to 2.7%; P < 0.001) for FCP, and HRs of T2D varied from 0.91 (0.77 to 1.07; P = 0.29) for exercise to 1.42 (1.11 to 1.81; P = 0.02) for pill. The pattern was further inverted among lean individuals in that weight change ranged from −0.4% (−0.6% to −0.1%; P = 0.02) for exercise to 3.7% (3.1% to 4.3%; P < 0.001) for FCP, and the HRs of T2D ranged from 1.09 (0.91 to 1.30; P = 0.33) for exercise to 1.54 (1.13 to 2.10; P = 0.008) for pill. Approximately 15.6% to 46.8% of the association between WLSs and the T2D risk was attributed to weight changes. This study was limited by a single assessment of WLSs, heterogeneity within each WLS, and potential misclassification of the timing of weight loss and weight regain.ConclusionsThe current study showed that individuals with obesity who attempted to lose weight, regardless of the WLSs used, tended to gain less body weight and have a lower diabetes risk. In contrast, lean individuals who intentionally lost weight tended to gain more weight and have a higher diabetes risk. These data support the notion that intentional weight loss may not be beneficial for lean individuals and the use of WLSs for achieving weight loss shall be guided by medical indications only.

Severe type 2 diabetes (T2D) remission using a very low-calorie ketogenic diet (VLCKD).

SummaryThere is a close association between obesity and type 2 diabetes (T2D). The value of weight loss in the management of patients with T2D has long been known. Loss of 15% or more of body weight can have a disease-modifying effect in people with diabetes inducing remission in a large proportion of patients. Very low-carbohydrate ketogenic diets (VLCKDs) have been proposed as an appealing nutritional strategy for obesity management. The diet was shown to result in significant weight loss in the short, intermediate, and long terms and improvement in body composition parameters as well as glycemic and lipid profiles. The reported case is a 35-year-old man with obesity, dyslipidemia, and T2D for 5 years. Despite the use of five antidiabetic medications, including insulin, HbA1c was 10.1%. A VLCKD through a commercial multidisciplinary weight loss program (PnK method) was prescribed and all medications were discontinued. The method is based on high-biological-value protein preparations and has 5 steps, the first 3 steps (active stage) consist of a VLCKD (600–800 kcal/d) that is low in carbohydrates (<50 g daily from vegetables) and lipids. The amount of proteins ranged between 0.8 and 1.2 g/kg of ideal body weight. After only 3 months, the patient lost 20 kg with weight normalization and diabetes remission, and after 2 years of follow-up, the patient remained without the pathologies. Due to the rapid and significant weight loss, VLCKD emerges as a useful tool in T2D remission in patients with obesity.Learning pointsObesity and type 2 diabetes (T2D) are conditions that share key pathophysiological mechanisms.Loss of 15% or more of body weight can have a disease-modifying effect in people with T2D inducing remission in a large proportion of patients.Diabetes remission should be defined as a return of HbA1c to <6.5% and which persists for at least 3 months in the absence of usual glucose-lowering pharmacotherapy.The very low-carbohydrate ketogenic diet (VLCKD) is a nutritional approach that has significant beneficial effects on anthropometric and metabolic parameters.Due to the rapid and significant weight loss, VLCKD emerges as a useful tool in T2D remission in patients with obesity.

Evaluating environmental and inhibitory control strategies to improve outcomes in a widely available weight loss program

BackgroundAlthough many people try to lose weight, a large proportion of individuals do not achieve clinically significant weight loss. Nonresponse and relapse rates in lifestyle interventions are largely explained by challenges in avoiding or resisting temptation in the context of omnipresent food access. Innovative enhancement strategies are needed to help individuals manage temptation in evidence-based lifestyle interventions. MethodsThis prospective, four-parallel-arm, randomized controlled trial tests the efficacy of two weight management enhancement strategies on weight and dietary outcomes among individuals with overweight or obesity: (1) an environmental control strategy combining modification of the home food environment and grocery delivery (AVOID) and (2) an impulse control strategy involving daily, gamified inhibitory control training (RESIST). Women and men (n = 500) with overweight or obesity (Body Mass Index between 25 and 40.0 kg/m2) will be enrolled in a 12-month commercial weight-loss program (WW, formerly Weight Watchers©) and randomly assigned to one of four conditions: (1) WW alone, (2) WW + AVOID, (3) WW + RESIST, or (4) WW + AVOID + RESIST. Anthropometric, dietary, cognitive, and household food environment assessments will be conducted in English or Spanish at enrollment and at 6- and 12-month follow-up. DiscussionThis research addresses the pragmatic question of how to best optimize behavior change: Should we modify the choice environment, strengthen individuals' self-regulation, or both, to maximize behavior change? This work can inform the development of enhancement strategies to promote adherence to lifestyle recommendations and other impulse control challenges.

Weight Loss Trajectory Patterns and Short-Term Prediction in a Weight Management Program

ObjectivesThere is controversy over the extent to which initial weight loss in behavioral weight control interventions predicts long-term success. In this study, we aimed to identify typical weight trajectories, develop an algorithm to automatically classify participants’ performance, and examine the capacity for long-term prediction of weight loss from weight records in the first 14 days.MethodsA commercial weight loss program offering clinically impactful behavioral support provided weight data for unrestricted use to Tufts University (Instinct Health Science, www.theidiet.com). We analyzed 302,762 weight records for 2508 participants who enrolled in the program between 2012 and 2019 and were asked to self-report weight daily. For this analysis, we focused on 73,545 records from 747 participants who met the following criteria: weight records for a duration of 70–365 days with the interval between consecutive records <30 days and with a minimum of 5 records over the recorded duration. We applied sequential polynomial regressions with linear, quadratic, and cubic terms to model the individual weight trajectory. Based on models’ fit, coefficients, and estimated critical values, we classified individual weight trajectories into 7 distinct weight loss patterns. We applied a multinomial logistic regression to test the weight records in the first 14 days can predict the late outcomes of the individuals’ trajectory.ResultsAmong the selected participants, the average weight loss was 6.9 ± 5.1 kg over 163.1 ± 85.4 days. We identified 7 weight trajectory patterns: 1-Steady decrease over time (31%); 2-Decrease to a plateau with subsequent decline (11%); 3-Decrease to a plateau with subsequent increase (48%); 4-Prominent short-term increase at the start followed by decrease (2%); 5-Decrease with a prominent increase at the end (3%); 6-No detectable increase or decrease (4%); 7-Steady increase over time (1%). Participants with the shallower weight loss and less frequent recording in the first 14 days along with the longer duration are more likely to adhere to Pattern 3 as compared to Pattern 1 (52%: 0.48 [0.26,0.89]; 7%: 0.93 [0.87,0.99]; 0.9%: 1.009 [1.005,1.012], respectively).ConclusionsSequential predictive modeling of weight change patterns could help to inform personalized weight management programs.Funding SourcesNone.

Association between weight loss, change in physical activity, and change in quality of life following a corporately sponsored, online weight loss program

BackgroundThe physiological benefits associated with corporately sponsored weight loss programs are increasingly well documented. However, less is known about how these programs affect employees’ quality of life (QoL). The purpose of the present analysis was to examine the association between weight loss, change in physical activity, and change in QoL following a corporately sponsored, online weight loss program.MethodsWe examined the relationship between weight loss, self-reported change in physical activity, and change in several QoL indices in 26,658 participants (79% women) after the initial 10 weeks of the online weight loss program. The trend in changes in each QoL index with increasing weight loss and change in physical activity was examined using logistic regression analysis.ResultsWe observed greater improvements in each QoL index with increasing weight loss (p-for-trend, < 0.001) as well as with progressive increases in physical activity (p-for-trend, < 0.001). The combination of increasing weight loss and increases in physical activity were associated with the greatest improvements in each QoL index (additive effect). The percentage of employees reporting improvements in QoL (“improved” or “very much improved”) was 64% for energy, 63% for mood, 33% for sleep, 65% for self-confidence, 68% for indigestion, and 39% for musculoskeletal pain.ConclusionsAmong people, who engage with a commercial weight loss program, greater weight loss during the program was associated with greater improvements in QoL, and increases in physical activity further enhanced the QoL-related benefits.

Epidemiological study on short and long-term weight loss with improvement of metabolic control in obese diabetic patients with a standardized multidisciplinary weight loss program (DIAMEX Study).

Purpose of Study: Obesity in Mexico has risen since the 1980s affecting 30% of the adult population, and 15% of adults had diabetes in Mexico. The rise in the rates of obesity and diabetes is linked to an increased consumption of calorically dense foods and sedentary lifestyle. The present study (DIAMEX) was aimed to evaluate the effect of a VLCK diet as part of a commercial weight loss program (PnKDiaprokal®) in patients with Diabetes and Obesity. It is an epidemiological study on weight loss and improvement of metabolic control in obese diabetic patients with a standardized multidisciplinary program that includes diet, physical exercise, and emotional support.

The effect of cognitive behavioral stress management on perceived stress, biological stress markers and weight loss/regain, from a diet-induced weight loss program: A randomized controlled trial

Obesity and psychosocial stress are inter-related chronic conditions which lead to increased cardiovascular morbidity and mortality. The aim of this parallel randomized controlled trial was to determine whether the addition of a structured cognitive behavioral stress management (CBSM) on to a commercial online weight loss program, resulted in greater weight loss than the standard weight loss program in isolation. Eligible participants were adults between the ages 18–65, BMI 30–45 kg/m2, with no major systemic or psychiatric conditions. Seventy-four participants were assigned according to simple randomization using computer generated random numbers to either a 3-month online Weight Watchers® program (n = 36), or Weight Watchers® plus 10 weekly sessions of CBSM (n = 38). The primary outcome was weight at 3 months compared to baseline. Secondary outcomes were weight at 12 months and subjective/objective stress system measures and metabolic markers at 3 and 12 months. The study was powered at 90% to detect a 5 kg difference in weight between the two groups at 3 months. Independent sample t-tests were used to analyze the difference in weight (in kg) between the groups and paired sample t-tests were used to analyze the difference within group at different time intervals. At follow-up, there was no significant difference in weight loss between the groups (1.8 kg, 2.1 kg). However, CBSM was effective in reducing psychological measures of stress (p < 0.05) and salivary cortisol (waking, 20-min post-waking) at 3-months; with the effect on stress persisting at 12-months within the CBSM group. The reduction in PSS at 3 months was significantly greater in the CBSM group (3.84, p = 0.028) compared to WW only group at 3 months. Addition of CBSM to a standard weight loss intervention did not improve the weight loss over the standard approach on its own, but the CBSM intervention improved psychological stress parameters and cortisol secretion in participants living with obesity.

Momentary predictors of dietary lapse from a mobile health weight loss intervention.

Identifying factors that influence risk of dietary lapses (i.e., instances of dietary non-adherence) is important because lapses contribute to suboptimal weight loss outcomes. Existing research examining lapse risk factors has had methodological limitations, including retrospective recall biases, subjective operationalizations of lapse, and has investigated lapses among participants in gold-standard behavioral weight loss programs (which are not accessible to most Americans). The current study will address these limitations by being the first to prospectively assess several risk factors of lapse (objectively operationalized) in the context of a commercial mobile health (mHealth) intervention, a highly popular and accessible method of weight loss. N = 159 adults with overweight or obesity enrolled in an mHealth commercial weight loss program completed ecological momentary assessments (EMAs) of 15 risk factors and lapses (defined as exceeding a point target for a meal/snack) over a 2-week period. N = 9 participants were excluded due to low EMA compliance, resulting in a sample of N = 150. Dietary lapses were predicted by momentary increases in urges to deviate from one's eating plan (b = .55, p < .001), cravings (b = .55, p < .001), alcohol consumption (b = .51, p < .001), and tiredness (b = .19, p < .001), and decreases in confidence related to meeting dietary goals (b = -.21, p < .001) and planning food intake (b = -.15, p < .001). This study was among the first to identify prospective predictors of lapse in the context of a commercial mHealth weight loss program. Findings can inform mHealth weight loss programs, including just-in-time interventions that measure these risk factors, calculate when risk of lapse is high, and deliver momentary interventions to prevent lapses.

Effect of ideal protein versus low-fat diet for weight loss: A randomized controlled trial.

BackgroundCurrent guidelines call for peer‐reviewed evidence of efficacy and safety for commercial weight loss programs to be recommended as options for those seeking to lose weight.ObjectivesThis study investigated the Ideal Protein (IP) system, a commercial weight loss program, compared to a guideline‐based, low‐calorie/low‐fat (LCLF) dietary behavioral intervention on body weight and CVD risk factors in adults with obesity.MethodsIn this randomized, assessor‐blinded, parallel‐group trial, 192 participants with body mass index (BMI) ≥30 and ≤49 kg/m2 were assigned to either the IP Phase I diet or LFLC diet interventions. The IP Phase I is focused on lean protein and vegetables with avoidance of fruit and dairy, while the LFLC diet goals include <30% of daily energy from fat, <7% from saturated fat, 55% from carbohydrate, and an energy deficit of 500 kcal/day. The primary endpoint was change in body weight at 3 months. Secondary endpoints included change in waist circumference (WC), hip circumference (HC), total cholesterol (TC), low‐density lipoprotein cholesterol (LDL‐C) and high‐density lipoprotein cholesterol (HDL‐C), triglycerides (TG), fasting glucose (FG), systolic blood pressure (SBP) and diastolic blood pressure (DBP).ResultsThe mean ± SD of change in weight at 3 months was −9.6 ± 12.7 kg in the IP group as compared to −1.6 ± 27.2 kg in the LFLC group. The mean between‐group difference in change at 3 months was −8.1 kg (95% confidence interval [CI] −16.6 to 0.6; p = 0.05). Additional significant between‐group differences included WC, HC, TC, and TG levels, all favoring the IP group. There were no serious adverse events during the intervention period.ConclusionsThe present findings demonstrate the efficacy and safety of the IP weight loss program as compared to a guideline‐based LCLF dietary behavioral intervention among black and white adults with obesity and CVD risk factors, providing support for the effectiveness of the program.

Effectiveness and Safety of a Very Low-Calorie Ketogenic Diet on Weight Regain Following Bariatric Surgery.

Obesity is one of the major public health problems worldwide and bariatric surgery is considered the gold standard treatment for severe obesity. Although the literature supports the safety and efficacy of the very low-calorie ketogenic diet (VLCKD) in patients with obesity, there is no study analyzing the use in case of failure or weight regain after bariatric surgery. This work has the purpose of assessing the response to a VLCKD (Pnk® method) in this population. We have conducted an observational, retrospective, and descriptive study with the analysis of medical charts of private offices where patients were examined between 2014 and 2019, totalizing 11 participants who underwent Roux-en-Y gastric bypass (RYGB) without a reduction of 50% in body weight excess or any weight regain after the surgery. The patients followed the first stage of a commercial weight loss program (Pnk® method) which consists of a VLCKD (600-800kcal/day), low in carbohydrates and lipids. A significant reduction was observed (p-value < 0.05) in weight, body mass index (BMI), abdominal circumference (AC), and glycated hemoglobin (A1C) post-ketogenic diet. Uric acid, transaminases, urea, and creatinine values did not show differences between pre- and post-ketosis. During the course of the study, no serious adverse events were reported. This study has shown that the ketogenic diet can be recommended as an effective and safe treatment for patients who progressed with insufficient weight loss or regain after bariatric surgery.

Comparing ecological momentary assessment to sensor-based approaches in predicting dietary lapse.

Ecological momentary assessment (EMA; brief self-report surveys) of dietary lapse risk factors (e.g., cravings) has shown promise in predicting and preventing dietary lapse (nonadherence to a dietary prescription), which can improve weight loss interventions. Passive sensors also can measure lapse risk factors and may offer advantages over EMA (e.g., objective, automatic, semicontinuous data collection), but currently can measure only a few lapse predictors, a notable limitation. This study preliminarily compared the burden and accuracy of commercially available sensors versus established EMA in lapse prediction. N = 23 adults with overweight/obesity completed a 6-week commercial app-based weight loss program. Participants wore a Fitbit, enabled GPS tracking, completed EMA, and reported on EMA and sensor burden poststudy via a 5-point Likert scale. Sensed risk factors were physical activity and sleep (accelerometer), geolocation (GPS), and time, from which 233 features (measurable characteristics of sensor signals) were extracted. EMA measured 19 risk factors, lapse, and categorized GPS into meaningful geolocations. Two supervised binary classification models (LASSO) were created: the sensor model predicted lapse with 63% sensitivity (true prediction rate of lapse) and 60% specificity (true prediction rate of non-lapse) and EMA model with 59% sensitivity and 72% specificity. EMA model accuracy was higher, but self-reported EMA burden (M = 2.96, SD = 1.02) also was higher (M = 1.50, SD = 0.94). EMA model accuracy was superior, but EMA burden was higher than sensor burden. Findings highlight the promise of sensors in contributing to lapse prediction, and future research may use EMA, sensors, or both depending on prioritization of accuracy versus participant burden.

Comparing Outcomes of a Digital Commercial Weight Loss Program in Adult Cancer Survivors and Matched Controls with Overweight or Obesity: Retrospective Analysis.

Maintaining a healthy weight is beneficial for cancer survivors. However, weight loss program effectiveness studies have primarily been in highly controlled settings. This is a retrospective study exploring real-world outcomes (weight loss and program engagement) after use of a digital commercial weight loss program (Noom) in cancer survivors and matched controls. All participants had voluntarily self-enrolled in Noom. Weight and engagement data were extracted from the program. Cancer-related quality of life was secondarily assessed in a one-time cross-sectional survey for survivors. Controls were a sample of Noom users with overweight/obesity who had no history of cancer but 0–1 chronic conditions. Primary outcomes were weight change at 16 weeks and program engagement over 16 weeks. Engagement included frequency of weight, food, and physical activity logging, as well as number of coach messages. Multiple regression controlling for baseline age, gender, engagement, and BMI showed that survivors lost less weight than controls (B = −2.40, s.e. = 0.97, p = 0.01). Survivors also weighed in less (survivors: 5.4 [2.3]; controls: 5.7 [2.1], p = 0.01) and exercised less (survivors: 1.8 [3.2]; controls: 3.2 [4.1], p < 0.001) than controls. However, survivors sent more coach messages (survivors: 2.1 [2.4]; controls: 1.7 [2.0], p < 0.001). Despite controls losing more weight than cancer survivors (−7.0 kg vs. −5.3 kg), survivors lost significant weight in 4 months (M = −6.2%). Cancer survivors can have success on digital commercial programs available outside of a clinical trial. However, they may require additional support to engage in weight management behaviors.

Enrolling Caregivers in Obesity Interventions to Improve Obesity-Related Outcomes in Children.

In this study, we assessed the influences of change in moderate-to-vigorous physical activity (MVPA)/sedentary time (ST) of caregivers participating in a commercial weight-loss program on their children's change in MVPA/ST. Data from 29 caregivers and their children were collected over 8 weeks. We used multivariable linear regression to assess associations of changes in caregiver's percent of time spent in MVPA/ST and changes in their child's percent of time spent in MVPA/ST. For caregivers that decreased body mass index (BMI) over 8 weeks, changes in caregivers' MVPA was strongly associated with the change in children's MVPA (β = 2.61 [95% CI: 0.45, 4.77]) compared to caregivers who maintained/increased BMI (β = 0.24 [-2.16, 2.64]). Changes in caregivers' ST was strongly associated with changes in children's ST (β = 2.42 [1.02, 3.81]) compared to caregivers who maintained/increased BMI (β = 0.35 [-0.45, 1.14]). Findings reinforce encouraging caregivers to enroll in weight-loss programs for the benefit of their children as well as for themselves.

Patterns of Weight Change in a Commercial Weight Loss Program

Objectives: In this study, we examined compliance and progress factors associated with weight loss and maintenance, individual patterns of weight trends following weight loss, and impact of early weight loss on longer-term weight change. Methods: We conducted secondary analysis of pre-post data. Participants were 8769 persons (mean age = 47.63 ± 13.78 years; 77.74% women; mean weight = 97.20 ± 22.82 kilograms; BMI = 34.09 ± 6.84) in a commercial weight management program. We carried out multiple regression analyses on weight change and percentage, and used ANOVA and the Pearson chi-square test to examine participant characteristics, weight change patterns, and early weight loss success. Results: Participants were active in the program for 222 ± 158 days, completed 15 ± 13 appointments, achieving -8.53 ± 7.87 kilograms lost (-8.61% ± 7.64%). Greater weight loss was associated with appointment frequency (β = -0.46) and total spending (β = -2.89) (p < .01). We identified 5 weight change patterns (F = 37.56, p < .001) (total weight loss for each group was: Stable = -10.4% [N=2036]; Minimal Regain = -10.5% [N=3766]; Modest Regain = -8.8% [N=1476]; Large Regain = -7.3% [N=753]; No Loss/Gain = +3.7% [N=737]; all p < .05). Over 5000 participants achieved early weight loss (losing > 5%) within the first 2 months resulting in significantly greater final weight loss (-8.43% to -14.56% vs -1.18% to -3.15%). Conclusions: We identified several weight patterns; increased health coaching attendance was associated with greater weight loss.

The association between meal regularity and weight loss among women in commercial weight loss programs.

BACKGROUND/OBJECTIVESWhile many obesity studies have pointed out the importance of meal regularity, few have conducted empirical analyses using data from food diaries. We examined the association between meal regularity (i.e., meal time regularity [MTR] and calorie intake regularity [CIR]) and weight loss.SUBJECTS/METHODSWe collected food diary data from 637 women who had participated in commercial weight loss programs for 28–168 days (4–24 weeks). This study defined “meal regularity” in terms of two concepts: MTR and CIR. MTR refers to how regularly people eat their meals (i.e., at certain times each day), whereas CIR refers to how regularly people consume a certain amount of calories at each meal. We conducted multiple regression analyses.RESULTSMTR (model 1: β = −2,576.526, P < 0.001; model 2: β = −1511.447, P < 0.05; model 3: β = −1,721.428, P < 0.05) and CIR (model 1: β = −1,231.551, P < 0.01; model 2: β = −2,082.353, P < 0.001; model 3: β = −1,343.490, P < 0.01) turned out to be significant determinants of the amount of weight loss in breakfast, lunch, and dinner contexts. While meal regularity (i.e., MTR and CIR) was significantly associated with weight loss, daily calorie intake from meals was not significantly associated with the amount of weight loss (model 1: β = 0.13, P > 0.05; model 2: β = 0.11, P > 0.05; model 3: β = 0.14, P > 0.05). Subjects who consumed an equal amount of calories per meal throughout the day lost more weight than those who did not (model 4: β = −3,675.51, P < 0.001).CONCLUSIONSEating each meal (i.e., breakfast, lunch, and dinner) at a certain time every day may increase weight loss success. Also, consuming the same amount of calories at each meal may help weight loss success.