Weight loss in Weight Watchers Online with and without an activity tracking device compared to control: A randomized trial

Dietary patterns and multiple chronic diseases in older adults

BACKGROUND

The prevalence rate of multiple chronic diseases among the elderly is relatively high, posing a risk to their health and also imposing a financial burden on them. Optimal dietary patterns have positive effects on multiple chronic diseases. This study aimed to identify dietary patterns associated with multiple chronic diseases in older adults.

METHODS

Dietary intake was assessed through two non-consecutive 24-hour dietary recalls. The presence of multiple chronic diseases was assessed based on the existence of dyslipidemia, hypertension, chronic kidney disease, sleep disorders, diabetes, moderate or severe depressive symptoms, and cognitive impairment, with two or more of these conditions being considered. Latent class analysis was used to identify types of multiple chronic diseases, and two-step cluster analysis was used to determine individual dietary patterns. Logistic regression analysis with robust standard errors was conducted to determine the associations between dietary patterns and types of multiple chronic diseases.

RESULTS

Three dietary patterns and three types of multiple chronic diseases were identified. Individuals following a diet rich in legumes, meat, vegetables and fruits (HLMVF dietary pattern) were 59% less likely to have the cardiometabolic cognitive impairment comorbidity (CCC) than those following a diet rich in milk and eggs but with low grain intake (HME-LG) (OR = 0.41, 95% CI: 0.27-0.64, P < 0.001) and 66% less likely to have the especially sleep disorders comorbidity (ESC) than those following a diet rich in grains but lacking milk and eggs (HG-LME) (OR = 0.34, 95% CI: 0.14-0.87, P < 0.05).

DISCUSSION

The HLMVF dietary pattern may serve as a healthy dietary pattern to reduce the incidence of multiple chronic diseases and should be promoted among the older adult population.

Successful dietary changes correlate with weight-loss outcomes in a new dietary weight-loss program

Background

Currently available behavioral and dietary weight-loss programs lack magnitude and sustainability compared with bariatric surgery. A novel dietary weight-loss program was developed to assist participants in achieving sustainable diet changes by building knowledge and skills in food self-selection. Although the approach worked, a large variation was observed in outcome among participants.

Objective

Determine factors affecting weight-loss outcomes among participants to further improve the efficacy of the program.

Methods

Participants attended 19 dietary educational sessions during a 1-year intervention which included prescribed homework. Changes in weight, diet, and body composition were assessed.

Results

Participants (n = 22) achieved mean body weight loss of -6.49(8.37%, p < 0.001) from baseline at 12 months. Nine participants (41%) achieved weight loss >5% of initial bodyweight; two reached a Body Mass Index 25 kg/m2. A large divergence in weight loss among participants was observed; successful (n = 9) achieved -12.9(9.6)% while unsuccessful achieved -2.03(2.78)%. Dietary protein and fiber density by 24-h records showed a significant and inverse correlation with weight loss (%) throughout the program. Weight loss at 3 months and 12 months showed a strong correlation (r = 0.84). Participants with self-reported depression lost significantly less weight than those without depression at 12 months (p < 0.03).

Conclusions

Divergence in weight-loss outcomes among the participants is likely due to a difference in successful dietary implementation. Intra-cohort analysis indicates early weight-loss success and early dietary implementation was predictive of long-term success.

Impact of a digital employer-based weight loss program on individuals age 65 or older

Introduction

Older adults are not protected from obesity, which has been linked to frailty, cognitive impairment, and other aging-related factors. Intensive lifestyle interventions have been shown to be effective for weight loss in older adults; however, these have typically been highly intensive and less feasible for dissemination. This analysis describes weight loss in a large-scale, commercially available, digital intervention in a subset of older adults.

Methods

Older adults (N = 20,443, males = 6,238; females = 14,205) between 65 and 85 years of age with overweight (43.3%) or obesity (46.7%) participated in an online, self-directed weight loss program. Behavioral-based content was delivered through weekly video lessons within an online platform that included weight and physical activity tracking, an online community, a reference library, and access to coaching support. Self-reported measures taken at the time of entry into the program were used for this analysis (demographics, height, body weight, and health status). Weight was reported across weeks of engagement in the curriculum.

Results

The average weight loss was -3.15 kg (95% CI: [-3.20, -3.11]) at 15.5 weeks. Weight loss was significantly greater in male individuals (-3.79 kg [95% CI: -3.89, -3.71]) versus female individuals (-2.87 kg [95% CI: -2.94, -2.82]) (p < 0.001), with a similar engagement in curriculum weeks. Percent weight loss was statistically significant for all age categories (p < 0.05) and self-reported health conditions (p < 0.05).

Discussion

Short-term weight loss was observed in older adults exposed to a low-touch, self-guided, and digital behavioral-based weight loss program. Weight loss was also observed even in the presence of various chronic health conditions.

Effectiveness of Different Online Intervention Modalities for Middle-Aged Adults with Overweight and Obesity: A 20-Year Systematic Review and Meta-analysis

The main objectives of this systematic review and meta-analysis study include evaluating the methodological quality of existing randomized controlled trials (RCTs) for weight loss and features of online intervention [OI]s in each trial, examining the associations between the methodological quality, intervention features and the effectiveness of OIs, and comparing the effectiveness of OIs and other intervention modalities through systematic review and meta-analysis. Systematic searches were conducted using PubMed, Cochrane Library, CINAHL, and PsycINFO in the past two decades (2000 through 2019). Inclusion criteria includes Online intervention (intervention modality), middle-aged adults with overweight or obesity, at least six months or longer study period, an RCT, and 70% plus retention rate. Risk of Bias was assessed using Miller et al. in (Hester, Miller (eds) Handbook of alcoholism treatment approaches: Effective alternatives (3rd ed.). Allyn & Bacon, Boston, 2003)'s Methodological Quality Rating Scale (MQRS) and GRADE. MOOSE guidelines was referred for data synthesis. In total, 29 OIs were evaluated using 10 criteria for methodological quality and eight criteria for intervention features. Results revealed that the mean methodological quality score of the RCTs was 12.1 (out of 16), and the mean intervention features score was 6.6 (out of 8). RCTs with higher scores were more effective in weight loss than those with lower scores. Results of meta-regression showed that methodological quality was more important than intervention features to increase the effectiveness. Results of meta-analysis showed that OIs were significantly more effective than controls. Compared to OIs only, OIs with interactions with others and professionals were more effective. The study limitation includes assessing 'effectiveness' based on weight only due to lack of other indicators to compare between studies; some results are self-reported; and feedback from intervention participants were hard to review. Nevertheless, this study may contribute to improving the effectiveness of existing OIs for weight loss considering methodological quality and better intervention features.

Why more successful? An analysis of participants' self-monitoring data in an online weight loss intervention

BACKGROUND

Self-monitoring is crucial for behavioral weight loss. However, few studies have examined the role of self-monitoring using mixed methods, which may hinder our understanding of its impact.

METHODS

This study examined self-monitoring data from 61 Chinese adults who participated in a 5-week online group intervention for weight loss. Participants reported their baseline Body Mass Index (BMI), weight loss motivation, and engaged in both daily quantitative self-monitoring (e.g., caloric intake, mood, sedentary behavior, etc.) and qualitative self-monitoring (e.g., daily log that summarizes the progress of weight loss). The timeliness of participants' daily self-monitoring data filling was assessed using a scoring rule. One-way repeated measurement ANOVA was employed to analyze the dynamics of each self-monitoring indicator. Correlation and regression analyses were used to reveal the relationship between baseline data, self-monitoring indicators, and weight change. Content analysis was utilized to analyze participants' qualitative self-monitoring data. Participants were categorized into three groups based on their weight loss outcomes, and a chi-square test was used to compare the frequency distribution between these groups.

RESULTS

After the intervention, participants achieved an average weight loss of 2.52 kg (SD = 1.36) and 3.99% (SD = 1.96%) of their initial weight. Daily caloric intake, weight loss satisfaction, frequency of daily log, and the speed of weight loss showed a downward trend, but daily sedentary time gradually increased. Moreover, regression analysis showed that baseline BMI, weight loss motivation, and timeliness of daily filling predicted final weight loss. Qualitative self-monitoring data analysis revealed four categories and nineteen subcategories. A significant difference in the frequency of qualitative data was observed, with the excellent group reporting a greater number of daily logs than expected in all categories and most subcategories, and the moderate and poor groups reporting less than expected in all categories and most subcategories.

CONCLUSION

The self-monitoring data in short-term online group intervention exhibited fluctuations. Participants with higher baseline BMI, higher levels of weight loss motivation, and timely self-monitoring achieved more weight loss. Participants who achieved greater weight loss reported a higher quantity of qualitative self-monitoring data. Practitioners should focus on enhancing dieters' weight loss motivation and promote adherence to self-monitoring practices.

Wearable sensor platforms for real-time monitoring and early warning of metabolic disorders in humans

Nowadays, the prevalence of metabolic syndromes (MSs) has attracted increasing concerns as it is closely related to overweight and obesity, physical inactivity and overconsumption of energy, making the diagnosis and real-time monitoring of the physiological range essential and necessary for avoiding illness due to defects in the human body such as higher risk of cardiovascular disease, diabetes, stroke and diseases related to artery walls. However, the current sensing techniques are inconvenient and do not continuously monitor the health status of humans. Alternatively, the use of recent wearable device technology is a preferable method for the prevention of these diseases. This can enable the monitoring of the health status of humans in different health domains, including environment and structure. The use wearable devices with the purpose of facilitating rapid treatment and real-time monitoring can decrease the prevalence of MS and long-time monitor the health status of patients. This review highlights the recent advances in wearable sensors toward continuous monitoring of blood pressure and blood glucose, and further details the monitoring of abnormal obesity, triglycerides and HDL. We also discuss the challenges and future prospective of monitoring MS in humans.

An Evaluation of a Personalized Multicomponent Commercial Digital Weight Management Program: Single-Arm Behavioral Trial

BACKGROUND

Digital behavioral weight loss programs are scalable and effective, and they provide an opportunity to personalize intervention components. However, more research is needed to test the acceptability and efficacy of personalized digital behavioral weight loss interventions.

OBJECTIVE

In a 6-month single-arm trial, we examined weight loss, acceptability, and secondary outcomes of a digital commercial weight loss program (WeightWatchers). This digital program included a personalized weight loss program based on sex, age, height, weight, and personal food preferences, as well as synchronous (eg, virtual workshops and individual weekly check-ins) and asynchronous (eg, mobile app and virtual group) elements. In addition to a personalized daily and weekly PersonalPoints target, the program provided users with personalized lists of ≥300 ZeroPoint foods, which are foods that do not need to be weighed, measured, or tracked.

METHODS

We conducted a pre-post evaluation of this 6-month, digitally delivered, and personalized WeightWatchers weight management program on weight loss at 3 and 6 months in adults with overweight and obesity. The secondary outcomes included participation, satisfaction, fruit and vegetable intake, physical activity, sleep quality, hunger, food cravings, quality of life, self-compassion, well-being, and behavioral automaticity.

RESULTS

Of the 153 participants, 107 (69.9%) were female, and 65 (42.5%) identified as being from a minoritized racial or ethnic group. Participants' mean age was 41.09 (SD 13.78) years, and their mean BMI was 31.8 (SD 5.0) kg/m2. Participants had an average weight change of -4.25% (SD 3.93%) from baseline to 3 months and -5.05% (SD 5.59%) from baseline to 6 months. At 6 months, the percentages of participants who experienced ≥3%, ≥5%, and ≥10% weight loss were 63.4% (97/153), 51% (78/153), and 14.4% (22/153), respectively. The mean percentage of weeks in which participants engaged in ≥1 aspects of the program was 87.53% (SD 23.40%) at 3 months and 77.67% (SD 28.69%) at 6 months. Retention was high (132/153, 86.3%), and more than two-thirds (94/140, 67.1%) of the participants reported that the program helped them lose weight. Significant improvements were observed in fruit and vegetable intake, physical activity, sleep quality, hunger, food cravings, quality of life, and well-being (all P values <.01).

CONCLUSIONS

This personalized, digital, and scalable behavioral weight management program resulted in clinically significant weight loss in half (78/153, 51%) of the participants as well as improvements in behavioral and psychosocial outcomes. Future research should compare personalized digital weight loss programs with generic programs on weight loss, participation, and acceptability.

Physical activity changes during an automated online weight loss program

Evidence-based online behavioral weight loss (BWL) treatment targets a combination of diet, physical activity, and behavioral skills training. While weight loss outcomes are well documented, little is known about changes in physical activity. This study examined changes in objectively measured physical activity across the energy expenditure spectrum during a fully automated, online BWL program. Adults with overweight or obesity (n = 63) completed a 12-week, online BWL program. Participants wore an accelerometer for 7 days and body weight was measured in-clinic at pre- and post-treatment. At post-treatment, mean daily moderate-to-vigorous physical activity increased by about 4 min (SE = 1.59, p = 0.01). There were no statistically significant changes in light physical activity or time spent sedentary (p's > 0.05). Despite only minimal changes in moderate-to-vigorous physical activity overall, larger increases correlated with greater weight loss (r = - 0.28, p = 0.02), which averaged 6.1% of baseline weight at post-treatment. Though achieving important weight loss outcomes, online programs may fail to produce clinically relevant improvements in physical activity, which can put weight loss maintenance at risk.

Effects of a Web-Based Lifestyle Intervention on Weight Loss and Cardiometabolic Risk Factors in Adults With Overweight and Obesity: Randomized Controlled Clinical Trial

BACKGROUND

The high proportion of people with overweight and obesity has become a worldwide problem in recent decades, mainly due to health consequences, such as cardiovascular diseases, neoplasia, and type 2 diabetes mellitus. Regarding effective countermeasures, the digitization of health services offers numerous potentials, which, however, have not yet been sufficiently evaluated. Web-based health programs are becoming increasingly interactive and can provide individuals with effective long-term weight management support.

OBJECTIVE

The purpose of this randomized controlled clinical trial was to evaluate the effectiveness of an interactive web-based weight loss program on anthropometric, cardiometabolic, and behavioral variables and to compare it with a noninteractive web-based weight loss program.

METHODS

The randomized controlled trial included people who were aged between 18 and 65 years (mean 48.92, SD 11.17 years) and had a BMI of 27.5 to 34.9 kg/m² (mean 30.71, SD 2.13 kg/m²). Participants (n=153) were assigned to either (1) an interactive and fully automated web-based health program (intervention) or (2) a noninteractive web-based health program (control). The intervention program focused on dietary energy density and allowed for dietary documentation with appropriate feedback on energy density and nutrients. The control group only received information on weight loss and energy density, but the website did not contain interactive content. Examinations were performed at baseline (t0), at the end of the 12-week intervention (t1), and at 6 months (t2) and 12 months (t3) thereafter. The primary outcome was body weight. The secondary outcomes were cardiometabolic variables as well as dietary and physical activity behaviors. Robust linear mixed models were used to evaluate the primary and secondary outcomes.

RESULTS

The intervention group showed significant improvements in anthropometric variables, such as body weight (P=.004), waist circumference (P=.002), and fat mass (P=.02), compared with the control group over the course of the study. The mean weight loss after the 12-month follow-up was 4.18 kg (4.7%) in the intervention group versus 1.29 kg (1.5%) in the control group compared with the initial weight. The results of the nutritional analysis showed that the energy density concept was significantly better implemented in the intervention group. Significant differences in cardiometabolic variables were not detected between the 2 groups.

CONCLUSIONS

The interactive web-based health program was effective in reducing body weight and improving body composition in adults with overweight and obesity. However, these improvements were not associated with relevant changes in cardiometabolic variables, although it should be noted that the study population was predominantly metabolically healthy.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00020249; https://drks.de/search/en/trial/DRKS00020249.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.3390/ijerph19031393.

Digital Health Solutions for Weight Loss and Obesity: A Narrative Review

Personal exercise programmes have long been used and prescribed for weight loss and the improvement of quality of life in obese patients. While individualised programmes are usually the preferred option, they can be more costly and challenging to deliver in person. A move to digital programmes with a wider reach has commenced, and demand has increased due to the SARS-CoV-2 pandemic. In this review, we evaluate the current status of digital exercise programme delivery and its evolution over the past decade, with a focus on personalisation. We used specific keywords to search for articles that met our predetermined inclusion and exclusion criteria in order to provide valuable evidence and insights for future research. We identified 55 studies in total in four key areas of focus, from the more recent development of apps and personal digital assistants to web-based programmes and text or phone call interventions. In summary, we observed that apps may be useful for a low-intensity approach and can improve adherence to programmes through self-monitoring, but they are not always developed in an evidence-based manner. Engagement and adherence are important determinants of weight loss and subsequent weight maintenance. Generally, professional support is required to achieve weight loss goals.

Pre-Enrollment Steps and Run-Ins in Weight Loss Trials: A Meta-Regression

INTRODUCTION

The generalizability of study findings may be influenced by pre-enrollment trial procedures, including the use of behavioral run-in periods. The study goals were to determine whether behavioral run-in periods and other pre-enrollment processes affect outcomes in randomized trials of behavioral weight loss interventions that have contributed to clinical guidelines.

METHODS

The sample was behavioral weight loss intervention trials included in the 2018 U.S. Preventive Services Task Force systematic review. Information on pre-enrollment processes (total steps, in-person steps, behavioral run-in) was abstracted, and meta-regressions were conducted in 2022 to test whether pre-enrollment processes were associated with weight loss at 6 or 12 months and trial retention at 12 months.

RESULTS

Across 80 trials, the median number of total pre-enrollment steps was 2 (range=1-5), and that of in-person pre-enrollment steps was 1 (range=0-4). Almost one-third of the trials (k=24; 30%) used a behavioral run-in. The most common run-in tasks were self-monitoring physical activity (k=9) or both physical activity and diet (k=6). Greater weight loss was observed in trials with behavioral run-ins at 6 months (-2.33 kg; 95% CI= -3.72, -0.93) and, to an attenuated extent, at 12 months (-0.86 kg; 95% CI= -1.72, 0.01) compared to those without run-ins. The total number of pre-enrollment steps was also associated with greater 6-month weight loss (-0.85 kg; 95% CI= -1.59, -0.11). Higher retention was associated with total number of pre-enrollment steps and in-person steps and marginally with the presence of run-ins.

DISCUSSION

The use of more pre-enrollment processes is associated with greater weight loss in behavioral weight loss trials and may impact the generalizability of outcomes.

Effectiveness of Telemedicine for Reducing Cardiovascular Risk: A Systematic Review and Meta-Analysis

BACKGROUND

Cardiovascular diseases are the leading cause of death globally. There are six cardiovascular risk factors: diabetes, hypertension, hypercholesterolemia, overweight, sedentary lifestyle and smoking. Due to the low attendance of healthy people in the health system, the use of telemedicine can influence the acquisition of a heart-healthy lifestyle.

OBJECTIVE

this systematic review and meta-analysis aimed to determine the effectiveness of telemedicine and e-health in reducing cardiovascular risk.

METHODS

A systematic review and meta-analysis were carried out using the PubMed, Scopus, Cinhal and WOS databases. Randomized controlled studies between 2017 and 2022 in which telemedicine was used to reduce any of the risk factors were included. The methodological quality was assessed using the "PEDro" scale.

RESULTS

In total, 763 studies were obtained; after the review, 28 target articles were selected and finally grouped as follows: 13 studies on diabetes, six on hypertension, seven on obesity and two on physical activity. For all of the risk factors, a small effect of the intervention was seen.

CONCLUSIONS

although the current evidence is heterogeneous regarding the statistically significant effects of telemedicine on various cardiovascular risk factors, its clinical relevance is undeniable; therefore, its use is recommended as long as the necessary infrastructure exists.

Evaluation of an Interactive Web-Based Health Program for Weight Loss-A Randomized Controlled Trial

Personal behavior patterns, such as unhealthy diet and lack of physical activity, lead to the development of overweight and obesity. These are associated with other comorbidities, reduced quality of life, premature frailty and increased mortality. Personalized web-based interventions are promising in inducing behavioral change leading to effective reductions in body weight at relatively low costs. However, the long-term effects have not been thoroughly investigated. This work evaluates the effectiveness of web-based interactive weight loss coaching and compares it to a non-interactive web-based health program. Therefore, a randomized controlled trial (RCT) was implemented, measuring primary and secondary outcomes at four time points (program start; end of the 12-week-program; 6 months after program end, 12 months after program end). The net sample covered 1499 subjects in the intervention group and 1492 in the control group. On average, the IG was 43 years old (±13.6), 80.1% male, and had 86.4 kg body weight (±16.1) at baseline. The CG was 42.7 years old (±13.9), 79.5% male and had a mean body weight of 86.1 (±15.7). Multilevel analyses with fixed effects were carried out both from the perspective of an intention-to-treat (ITT) and a complete cases approach (CCA). In sum, our adjusted models suggest a weight loss of 0.4 kg per time point. At the end of the program, significant differences in weight loss in % to baseline (delta M = 1.8 in the CCA) were observed in favor of the intervention group. From a long-term perspective, no superiority of the intervention group in comparison to the control group could be found. More intensive use of the program was not statistically associated with higher weight loss.

A Health Care Professional Delivered Low Carbohydrate Diet Program Reduces Body Weight, Haemoglobin A1c, Diabetes Medication Use and Cardiovascular Risk Markers-A Single-Arm Intervention Analysis

This study examined the effectiveness of a health care professional delivered low-carbohydrate diet program (Diversa Health Program) aiming to improve obesity/type-2-diabetes management for people living in Australia. 511 adults (Age:57.1 ± 13.7 [SD] yrs) who participated between January 2017−August 2021 for ≥30 days with pre-post data collected for ≥1 key outcome variable (body weight and HbA1c) were included in the analysis. Average participation duration was 218 ± 207 days with 5.4 ± 3.9 reported consultation visits. Body weight reduced from 92.3 ± 23.0 to 86.3 ± 21.1 kg (n = 506, p < 0.001). Weight loss was 0.9 ± 2.8 kg (1.3%), 4.5 ± 4.3 kg (5.7%) and 7.9 ± 7.2 kg (7.5%), respectively, for those with a classification of normal weight (n = 67), overweight (n = 122) and obese (n = 307) at commencement. HbA1c reduced from 6.0 ± 1.2 to 5.6 ± 0.7% (n = 212, p < 0.001). For members with a commencing HbA1c of <5.7% (n = 110), 5.7−6.4% (n = 55), and ≥6.5% (n = 48), HbA1c reduced −0.1 ± 0.2%, −0.3 ± 0.3%, and −1.4 ± 1.3%, respectively. For members with a commencing HbA1c ≥6.5%, 90% experienced a HbA1c reduction and 54% achieved a final HbA1c < 6.5%. With inclusion and exclusion of metformin, respectively, 124 and 82 diabetes medications were prescribed to 63 and 42 members that reduced to 82 and 35 medications prescribed to 51 and 26 members at final visit. A health care professional delivered low-carbohydrate diet program can facilitate weight loss and improve glycaemic control with greatest improvements and clinical relevance in individuals with worse baseline parameters.

Exercise in Obesity-the Role of Technology in Health Services: Can This Approach Work?

PURPOSE OF REVIEW

Physical activity (PA) is an important strategy to prevent and treat obesity. Electronic health (eHealth) interventions, such as wearable activity monitors and smartphone apps, may promote adherence to regular PA and successful weight loss. This review highlights the evidence for eHealth interventions in promoting PA and reducing weight.

RECENT FINDINGS

Wearables can increase PA and are associated with moderate weight loss in middle/older-aged individuals, with less convincing effects long-term (> 1 year) and in younger people. Data for interventions such as mobile phone applications, SMS, and exergaming are less robust. Investigations of all eHealth interventions are often limited by complex, multi-modality study designs, involving concomitant dietary modification, making the independent contribution of each eHealth intervention on body weight challenging to assess. eHealth interventions may promote PA, thereby contributing to weight loss/weight maintenance; however, further evaluation is required for this approach to be adopted into routine clinical practice.

A systematic review of inequalities in the uptake of, adherence to, and effectiveness of behavioral weight management interventions in adults

The extent to which behavioral weight management interventions affect health inequalities is uncertain, as is whether trials of these interventions directly consider inequalities. We conducted a systematic review, synthesizing evidence on how different aspects of inequality impact uptake, adherence, and effectiveness in trials of behavioral weight management interventions. We included (cluster-) randomized controlled trials of primary care-applicable behavioral weight management interventions in adults with overweight or obesity published prior to March 2020. Data about trial uptake, intervention adherence, attrition, and weight change by PROGRESS-Plus criteria (place of residence, race/ethnicity, occupation, gender, religion, education, socioeconomic status, social capital, plus other discriminating factors) were extracted. Data were synthesized narratively and summarized in harvest plots. We identified 91 behavioral weight loss interventions and 12 behavioral weight loss maintenance interventions. Fifty-six of the 103 trials considered inequalities in relation to at least one of intervention or trial uptake (n = 15), intervention adherence (n = 15), trial attrition (n = 32), or weight outcome (n = 34). Most trials found no inequalities gradient. If a gradient was observed for trial uptake, intervention adherence, and trial attrition, those considered "more advantaged" did best. Alternative methods of data synthesis that enable data to be pooled and increase statistical power may enhance understanding of inequalities in behavioral weight management interventions.

A feasibility study to test a novel approach to dietary weight loss with a focus on assisting informed decision making in food selection

Obesity is a significant contributor to the development of chronic diseases, some of which can be prevented or reversed by weight loss. However, dietary weight loss programs have shortcomings in the success rate, magnitude, or sustainability of weight loss. The Individualized Diet Improvement Program's (iDip) objective was to test the feasibility of a novel approach that helps individuals self-select a sustainable diet for weight loss and maintenance instead of providing weight loss products or rigid diet instructions to follow. The iDip study consisted of 22 dietary improvement sessions over 12 months with six months of follow-up. Daily weights were collected, and a chart summarizing progress was provided weekly. Six 24-hour dietary records were collected, and dietary feedback was provided in the form of a protein-fiber plot, in which protein/energy and fiber/energy of foods were plotted two-dimensionally together with a target box specific to weight loss or maintenance. An exit survey was conducted at 12 months. Twelve (nine female, 46.3±3.1 years (mean±SE)) of the initial 14 participants (BMI>28 kg/m2) completed all sessions. Mean percent weight loss (n = 12) at six and 12 months was -4.9%±1.1 (p = 0.001) and -5.4%±1.7 (p = 0.007), respectively. Weight loss varied among individuals at 12 months; top and bottom halves (n = 6 each) achieved -9.7%±1.7 (p = 0.0008) and -1.0%±1.4 weight loss, respectively. The 24-hour records showed a significant increase in protein density from baseline to final (4.1g/100kcal±0.3 vs. 5.7g/100kcal±0.5; p = 0.008). Although mean fiber density showed no significant change from the first month (1.3g/100kcal±0.1), the top half had significantly higher fiber/energy intake than the bottom half group. The survey suggested that all participants valued the program and its self-guided diet approach. In conclusion, half of the participants successfully lost >5% and maintained the lost weight for 12 months without strict diet instructions, showing the feasibility of the informed decision-making approach.

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.

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Cognitive behavioral stress management (CBSM) reduced morning cortisol levels.

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Addition of CBSM to a weight loss program did not augment weight loss.

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CBSM reduced stress scores.

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CBSM improved psychometric parameters –SF–12, AAQ-II and PSS.

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Weight loss may have an effect on reducing stress.

Long-term Effectiveness of a Smartphone App Combined With a Smart Band on Weight Loss, Physical Activity, and Caloric Intake in a Population With Overweight and Obesity (Evident 3 Study): Randomized Controlled Trial

BACKGROUND

Multicomponent mobile health approaches can improve lifestyle intervention results, although little is known about their long-term effectiveness.

OBJECTIVE

This study aims to evaluate the long-term effectiveness (12 months) of a multicomponent mobile health intervention-combining a smartphone app, an activity tracker wristband, and brief counseling, compared with a brief counseling group only-on weight loss and improving body composition, physical activity, and caloric intake in Spanish sedentary adults with overweight or obesity.

METHODS

We conducted a randomized controlled, multicenter clinical trial (Evident 3). A total of 650 participants were recruited from 5 primary care centers, with 318 participants in the intervention group (IG) and 332 in the control group (CG). All participants were briefly counseled about a healthy diet and physical activity at the baseline visit. For the 3-month intervention period, the IG received training to use the app to promote healthy lifestyles and the smart band (Mi Band 2, Xiaomi). All measurements were performed at baseline and at 3 and 12 months. Physical activity was measured using the International Physical Activity Questionnaire-Short Form. Nutritional habits were assessed using the Food Frequency Questionnaire and Adherence to Mediterranean diet questionnaire.

RESULTS

Of the 650 participants included, 563 (86.6%) completed the 3-month visit and 443 (68.2%) completed the 12-month visit. After 12 months, the IG showed net differences in weight (-0.26, 95% CI -1.21 to 0.70 kg; P=.02), BMI (-0.06, 95% CI -0.41 to 0.28 points; P=.01), waist-height ratio (-0.25, 95% CI -0.94 to 0.44; P=.03), body adiposity index (-0.33, 95% CI -0.77 to 0.11; P=.03), waist circumference (-0.48, 95% CI -1.62 to 0.66 cm, P=.04) and hip circumference (-0.69, 95% CI -1.62 to 0.25 cm; P=.03). Both groups lowered daily caloric intake and increased adherence to the Mediterranean diet, with no differences between the groups. The IG increased light physical activity time (32.6, 95% CI -30.3 to 95.04 min/week; P=.02) compared with the CG. Analyses by subgroup showed changes in body composition variables in women, people aged >50 years, and married people.

CONCLUSIONS

The low-intensity intervention of the Evident 3 study showed, in the IG, benefits in weight loss, some body composition variables, and time spent in light physical activity compared with the CG at 3 months, but once the devices were collected, the downward trend was not maintained at the 12-month follow-up. No differences in nutritional outcomes were observed between the groups.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03175614; https://clinicaltrials.gov/ct2/show/NCT03175614.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1097/MD.0000000000009633.

Describing Transitions in Adherence to Physical Activity Self-monitoring and Goal Attainment in an Online Behavioral Weight Loss Program: Secondary Analysis of a Randomized Controlled Trial

Background

Standard behavioral weight loss interventions often set uniform physical activity (PA) goals and promote PA self-monitoring; however, adherence remains a challenge, and recommendations may not accommodate all individuals. Identifying patterns of PA goal attainment and self-monitoring behavior will offer a deeper understanding of how individuals adhere to different types of commonly prescribed PA recommendations (ie, minutes of moderate-to-vigorous physical activity [MVPA] and daily steps) and guide future recommendations for improved intervention effectiveness.

Objective

This study examined weekly patterns of adherence to step-based and minute-based PA goals and self-monitoring behavior during a 6-month online behavioral weight loss intervention.

Methods

Participants were prescribed weekly PA goals for steps (7000-10,000 steps/day) and minutes of MVPA (50-200 minutes/week) as part of a lifestyle program. Goals gradually increased during the initial 2 months, followed by 4 months of fixed goals. PA was self-reported daily on the study website. For each week, participants were categorized as adherent if they self-monitored their PA and met the program PA goal, suboptimally adherent if they self-monitored but did not meet the program goal, or nonadherent if they did not self-monitor. The probability of transitioning into a less adherent status was examined using multinomial logistic regression.

Results

Participants (N=212) were predominantly middle-aged females with obesity, and 67 (31.6%) self-identified as a racial/ethnic minority. Initially, 73 (34.4%) participants were categorized as adherent to step-based goals, with 110 [51.9%] suboptimally adherent and 29 [13.7%] nonadherent, and there was a high probability of either remaining suboptimally adherent from week to week or transitioning to a nonadherent status. However, 149 (70.3%) participants started out adherent to minute-based goals (34 [16%] suboptimally adherent and 29 [13.7%] nonadherent), with suboptimally adherent seen as the most variable status. During the graded goal phase, participants were more likely to transition to a less adherent status for minute-based goals (odds ratio [OR] 1.39, 95% CI 1.31-1.48) compared to step-based goals (OR 1.24, 95% CI 1.17-1.30); however, no differences were seen during the fixed goal phase (minute-based goals: OR 1.06, 95% CI 1.05-1.08; step-based goals: OR 1.07, 95% CI 1.05-1.08).

Conclusions

States of vulnerability to poor PA adherence can emerge rapidly and early in obesity treatment. There is a window of opportunity within the initial 2 months to bring more people toward adherent behavior, especially those who fail to meet the prescribed goals but engage in self-monitoring. Although this study describes the probability of adhering to step- and minute-based targets, it will be prudent to determine how individual characteristics and contextual states relate to these behavioral patterns, which can inform how best to adapt interventions.

Trial Registration

ClinicalTrials.gov NCT02688621; https://clinicaltrials.gov/ct2/show/NCT02688621

Effectiveness of physical activity monitors in adults: systematic review and meta-analysis

OBJECTIVE

To estimate the effectiveness of physical activity monitor (PAM) based interventions among adults and explore reasons for the heterogeneity.

DESIGN

Systematic review and meta-analysis.

STUDY SELECTION

The electronic databases MEDLINE, Embase, SPORTDiscus, CINAHL, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched on 4 June 2021. Eligible randomised controlled trials compared interventions in which adults received feedback from PAMs with control interventions in which no feedback was provided. No restrictions on type of outcome measurement, publication date, or language were applied.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently extracted data and assessed risk of bias. Random effects meta-analyses were used to synthesise the results. The certainty of evidence was rated by the Grading of Recommendations Assessment and Evaluation (GRADE) approach.

MAIN OUTCOME MEASURES

The three primary outcomes of interest were physical activity, moderate to vigorous physical activity, and sedentary time.

RESULTS

121 randomised controlled trials with 141 study comparisons, including 16 743 participants, were included. The PAM based interventions showed a moderate effect (standardised mean difference 0.42, 95% confidence interval 0.28 to 0.55) on physical activity, equivalent to 1235 daily steps; a small effect (0.23, 0.16 to 0.30) on moderate to vigorous physical activity, equivalent to 48.5 weekly minutes; and a small insignificant effect (-0.12, -0.25 to 0.01) on sedentary time, equal to 9.9 daily minutes. All outcomes favoured the PAM interventions.

CONCLUSIONS

The certainty of evidence was low for the effect of PAM based interventions on physical activity and moderate for moderate to vigorous physical activity and sedentary time. PAM based interventions are safe and effectively increase physical activity and moderate to vigorous physical activity. The effect on physical activity and moderate to vigorous physical activity is well established but might be overestimated owing to publication bias.

STUDY REGISTRATION

PROSPERO CRD42018102719.

Internet-based platform for a low-calorie dietary intervention involving prepackaged food for weight loss in overweight and obese individuals in China: protocol for a randomised controlled trial

INTRODUCTION

Obesity is a global health issue that impacts quality of life. A calorie-restricted diet with high-intensity consultation provided via the internet may be an effective way to lose weight. The objective of this study was to assess the effectiveness of a practitioner-guided, mobile internet-based low-energy dietary intervention in overweight and obese populations in China.

METHODS AND ANALYSIS

This open-label randomised controlled trial enrolled 220 overweight and obese adults aged 18-70 years who met the inclusion criteria. Participants were assigned to the control group (n=110) or trial group (n=110). The trial group will be enrolled in the MetaWell programme, a weight loss programme using diet replacement products, wireless scales and a mobile phone app. Participants in the control group will receive paper material containing a sample diet for weight loss. The follow-up period will be 1 year, and measurements will occur at 3, 6 and 12 months. Dual-emission X-ray absorptiometry and abdominal quantitative CT will be performed to estimate the percentage of overall body fat and areas of visceral and subcutaneous fat, alongside several cardiometabolic measurements. The primary outcome of this study is the change in body mas index (BMI) at 6 months after enrolment. A mixed-effects model will be used to compare BMI and body fat changes between the two groups.

ETHICS AND DISSEMINATION

This study was approved by the ethics committee of the Hospital of Chengdu Office of the People's Government of the Tibetan Autonomous Region. Advertisements for recruitment will be sent via official accounts using WeChat. The results will be disseminated via publications in academic journals and our clinic. Our study group will maintain contact with the participants to inform them of the study findings.

TRIAL REGISTRATION NUMBER

ChiCTR1900021630.

Wearable body sensor network: SDGs panacea for an holistic SARS-CoV-2 mitigation, diagnostic, therapeutic, and health informatics interventions

The COVID-19 pandemic offers enormous potential for digital health solutions, with social distancing being the only current approach that has thus far been established to reduce the risk. Wearable Activity Tracker (WATs) is an appealing, successful, and inexpensive choice in this context. This technology is of vital significance in ensuring the well-being of both patients and healthcare professionals following sustainable development goals. The application of technological interventions will in no doubt help in tackling the debilitating effect of health emergencies in the world population. However, there is a shortage of literature explaining the programming resources needed to effectively treat this novel infection which is briefly addressed in this review. This study prominently addressed the potential of wearable Activity Tracker as a technological solution to healthcare disaster management.

Longitudinal evaluation of an mHealth overweight and obesity management tool

BACKGROUND

Efficient obesity treatment protocols are lacking. This study reports treatment results from a web-based application, originally developed for use in an in-person healthcare setting providing health, overweight, and obesity management.

METHODS

The web application DrHolmApp (WADHA) was evaluated in adult users two years after it was launched. The WADHA provides a personal and tailored treatment plan comprising a series of detailed action advices on everyday life, constructed from the user's input to a thorough online questionnaire. Throughout the subscription period, the WADHA users have full access to online healthcare professional support. We conducted a longitudinal cohort study using self-reported data.

RESULTS

This study included 940 adult WADHA users (861 female). The median body mass index (BMI) change across all WADHA users was -0.63 BMI points (95% CI: -0.7 to -0.57, P<0.001). 665 (71%) of all WADHA users reduced their BMI (median reduction: 0.94, 95% CI: 0.88 to 1.02). In the subset with obesity (n=675), BMI was reduced in 72%. The median number of days per week with physical activity for at least one hour per day increased with 1.5 days per week (from 2 days per week at baseline, P<0.001). Subsequently, the WADHA users improved their mood, quality of life, and body image satisfaction and reduced their appetite, bullying, and wish for weight loss (all P<0.001). A higher number of consultations associated with greater weight loss (P<0.001) independent of age and degree of obesity at treatment initiation.

CONCLUSIONS

Seventy-one percent of the WADHA users experienced weight loss, concomitant to an increased level of physical activity, improved mood, quality of life, and body image satisfaction, and reduced appetite, degree of bullying, and wish for weight loss.

KEYWORDS

Body mass index (BMI); mobile health (mHealth); obesity; treatment; weight loss.

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.

A systematic review of the use of dietary self-monitoring in behavioural weight loss interventions: delivery, intensity and effectiveness

OBJECTIVE

To identify dietary self-monitoring implementation strategies in behavioural weight loss interventions.

DESIGN

We conducted a systematic review of eight databases and examined fifty-nine weight loss intervention studies targeting adults with overweight/obesity that used dietary self-monitoring.

SETTING

NA.

PARTICIPANTS

NA.

RESULTS

We identified self-monitoring implementation characteristics, effectiveness of interventions in supporting weight loss and examined weight loss outcomes among higher and lower intensity dietary self-monitoring protocols. Included studies utilised diverse self-monitoring formats (paper, website, mobile app, phone) and intensity levels (recording all intake or only certain aspects of diet). We found the majority of studies using high- and low-intensity self-monitoring strategies demonstrated statistically significant weight loss in intervention groups compared with control groups.

CONCLUSIONS

Based on our findings, lower and higher intensity dietary self-monitoring may support weight loss, but variability in adherence measures and limited analysis of weight loss relative to self-monitoring usage limits our understanding of how these methods compare with each other.

Examination of the relationship between lapses and weight loss in a smartphone-based just-in time adaptive intervention

We developed a smartphone-based just-in-time adaptive intervention (JITAI), called OnTrack, that provides personalized intervention to prevent dietary lapses (i.e., nonadherence from the behavioral weight loss intervention diet). OnTrack utilizes ecological momentary assessment (EMA; repeated electronic surveys) for self-reporting lapse triggers, predicts lapses using machine learning, and provides brief intervention to prevent lapse. We have established preliminary feasibility, acceptability, and efficacy of OnTrack, but no study has examined our hypothesized mechanism of action: reduced lapse frequency will be associated with greater weight loss while using OnTrack. This secondary analysis investigated the association between lapse frequency and the weekly percentage of weight loss. Post hoc analyses evaluated the moderating effect of OnTrack engagement on this association. Participants (N = 121) with overweight/obesity (MBMI = 34.51; 84.3% female; 69.4% White) used OnTrack with a digital weight loss program for 10 weeks. Engagement with OnTrack (i.e., EMA completed and interventions accessed) was recorded automatically, participants self-reported dietary lapses via EMA, and weighed weekly using Bluetooth scales. Linear mixed models with a random effect of subject and fixed effect of time revealed a nonsignificant association between weekly lapses and the percentage of weight loss. Post hoc analyses revealed a statistically significant moderation effect of OnTrack engagement such that fewer EMA and interventions completed conferred the expected associations between lapses and weight loss. Lapses were not associated with weight loss in this study and one explanation may be the influence of engagement levels on this relationship. Future research should investigate the role of engagement in evaluating JITAIs.

Feasibility and potential efficacy of commercial mHealth/eHealth tools for weight loss in African American breast cancer survivors: pilot randomized controlled trial

Weight management after breast cancer (BC) treatment in African American (AA) women is crucial to reduce comorbid conditions and health disparities. We examined feasibility and potential efficacy of commercial eHealth/mHealth tools for weight management in AA BC survivors in New Jersey. Participants (N = 35) were randomized to an intervention (SparkPeople) plus activity tracker, Fitbit Charge (n = 18), or wait-list active control group (Fitbit only, n = 17). Anthropometric, behavioral, and quality of life (QOL) outcomes were collected at baseline, 3, 6, and 12 months. Differences in outcomes were assessed using intent-to-treat analysis. Retention was 97.1%. Both groups lost weight, with no significant differences between groups. At month 6, mean weight change was: intervention: -1.71 kg (SD 2.33; p = .006), 33.3% lost ≥3% of baseline weight; control: -2.54 kg (SD 4.00, p = .002), 23.5% lost ≥3% weight. Intervention participants achieved significant improvements in waist circumference (-3.56 cm, SD 4.70, p = .005), QOL (p = .030), and use of strategies for healthy eating (p = .025) and decreasing calories (p < .001). Number of days logged food per week was associated with decreases in waist circumference at 6 months (β -0.79, 95% CI, -1.49, -0.09, p = .030) and 12 months (β -2.16, 95% CI, -4.17, -0.15, p = .038). Weight loss was maintained at 12 months. This is the first study to demonstrate potential efficacy of commercial eHealth/mHealth tools for weight loss in AA BC survivors, without additional counseling from the research team. If effective, they may be convenient weight loss tools that can be easily and widely disseminated. Clinical Trials registration: ClinicalTrials.gov NCT02699983.

Pilot evaluation of a personalized commercial program on weight loss, health outcomes, and quality of life

WW is a validated behavioral weight management program that encourages healthy habits. WW developed a method of personalizing the SmartPoints® budget depending on dietary and lifestyle preferences, and participants were placed into one of three plans as a pilot evaluation of this new program. In this 6-month, single-arm pilot study, participants attended weekly workshops and used an app to monitor eating and physical activity. Baseline and 6-month assessments included weight, waist circumference, blood pressure, energy intake, cravings, happiness, health-related quality of life, hunger, and fullness. Of 145 adults assessed at baseline, 126 (87%) provided follow-up data. Pre-post changes showed significant reductions in body weight (7.39% ± 5.93%), calories consumed (24.79% ± 32.35%) and significant improvements in cravings, happiness, all SF-36 scales and hunger but not in fullness. Greater % weight loss was related to greater improvements in happiness (r = .38, p < .001), general health perceptions (r = .29, p = .001), and health change (r = .31, p = .001), and greater reduction in role limitations due to personal or emotional problems (r = .24, p = .01). Greater % reduction in caloric intake was associated with greater reductions in cravings (r = .23, p = .01), as well as with greater improvements in happiness (r = .23, p = .01), physical functioning (r = .23, p = .01), and general health perceptions (r = .23, p = .01). Participants in this modified program achieved significant weight loss, regardless of dietary plan, as well as improvements in a variety of other physical and psychological constructs. Those who achieved greater reductions in weight also reported greater improvements in cravings, happiness and some quality of life measures.

Effectiveness of web-based feedback interventions for people with overweight and obesity: systematic review and network meta-analysis of randomized controlled trials

BACKGROUND

Web-based delivered interventions have become an innovative option to treat health problems, like obesity. The aim of this systematic review and network meta-analysis was to analyze the effectiveness of web-based behavioral treatments for adults with overweight and obesity. Web-based interventions and comparison interventions (traditional weight control programs) were classified according to the following feedback characteristics: frequency, personalization, and provider (human versus machine).

METHOD

From the initial 1789 studies, 15 were included in this review. A network meta-analysis was conducted to analyze the efficacy of web-based programs with traditional interventions, considering direct and indirect comparisons. The main outcome was the weight loss mean difference (kg) between baseline and post-treatment. Heterogeneity and consistency assumptions were validated to conduct the network meta-analysis.

RESULTS

Network meta-analysis showed comparisons between different treatment options. The main results were that Intensive Contact Web-based programs were more effective than wait-list (Mean Difference - 1.86 kg; 95% Confidence Interval: - 3.61, - 0.12). Moreover, Intensive Contact Web-based programs were more effective than the other web-based options and self-help traditional interventions. However, the only significant comparison was Intensive Contact Web-based programs versus Guided Self-Help Web-based programs (Mean Difference - 4.31 kg; 95% Confidence Interval: - 5,22, - 3,41). Intensive Contact Web-based programs were the most effective treatment option according the obtained results, achieving the first place in the ranking provided by the network meta-analysis with 98.5% of probabilities.

CONCLUSIONS

Intensive Contact Web-based interventions have obtained the first position in the ranking, proving the relevance of frequent, personalized, and professional feedback and their association with a better prognosis for people with overweight and obesity. These results provide relevant information to design more effective treatments for people with overweight and obesity, in a new format especially appropriate for the current situation.

Identifying behavioral types of dietary lapse from a mobile weight loss program: Preliminary investigation from a secondary data analysis

Success in behavioral weight loss (BWL) programs depends on adherence to the recommended diet to reduce caloric intake. Dietary lapses (i.e., deviations from the BWL diet) occur frequently and can adversely affect weight loss outcomes. Research indicates that lapse behavior is heterogenous; there are many eating behaviors that could constitute a dietary lapse, but they are rarely studied as distinct contributors to weight outcomes. This secondary analysis aims to evaluate six behavioral lapse types during a 10-week mobile BWL program (eating a large portion, eating when not intended, eating an off-plan food, planned lapse, being unaware of caloric content, and endorsing multiple types of lapse). Associations between weekly behavioral lapse type frequency and weekly weight loss were investigated, and predictive contextual characteristics (psychological, behavioral, and environmental triggers for lapse) and individual difference (e.g., age, gender) factors were examined across lapse types. Participants (N = 121) with overweight/obesity (M_BMI = 34.51; 84.3% female; 69.4% White) used a mobile BWL program for 10 weeks, self-weighed weekly using Bluetooth scales, completed daily ecological momentary assessment of lapse behavior and contextual characteristics, and completed a baseline demographics questionnaire. Linear mixed models revealed significant negative associations between unplanned lapses and percent weight loss. Unplanned lapses from eating a large portion, eating when not intended, and having multiple "types" were significantly negatively associated with weekly percent weight loss. A lasso regression showed that behavioral lapse types share many similar stable factors, with other factors being unique to specific lapse types. Results add to the prior literature on lapses and weight loss in BWL and provide preliminary evidence that behavioral lapse types could aid in understanding adherence behavior and developing precision medicine tools to improve dietary adherence.

Weight Loss and Usage of an Online Commercial Weight Loss Program (the CSIRO Total Wellbeing Diet Online) Delivered in an Everyday Context: Five-Year Evaluation in a Community Cohort

BACKGROUND

Obesity is a global public health challenge, and there is a need for more evidence-based self-management programs that support longer-term, sustained weight loss.

OBJECTIVE

This study used data from the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Total Wellbeing Diet Online program to determine the reach and weight loss results over its first 5 years.

METHODS

Participants were adults who joined the commercial weight loss program of their own volition between October 2014 and September 2019 (N=61,164). Information collected included year of birth, sex, height, weight, and usage data (eg, entries into the food diary, views of the menu, and program content). Weight loss and percentage of starting body weight lost were calculated. Members were divided into 2 groups for analysis: "stayers" were members who signed up for at least 12 weeks of the program and recorded a weight entry at baseline and at the end of the program, while "starters" began the program but did not record a weight after 12 weeks. Descriptive statistics and multiple linear regression were used to describe weight loss and determine the member and program characteristics associated with weight loss.

RESULTS

Data were available from 59,686 members for analysis. Members were predominately female (48,979/59,686, 82.06%) with an average age of 50 years (SD 12.6). The average starting weight was 90.2 kg (SD 19.7), and over half of all members (34,195/59,688, 57.29%) were classified as obese. At week 12, 94.56% (56,438/59,686) of the members had a paid program membership, which decreased to 41.48% (24,756/59,686) at 24 weeks. At week 12, 52.03% (29,115/55,958) of the remaining members were actively using the platform, and by week 24, 26.59% (14,880/55,958) were using the platform. The average weight loss for all members was 2.8 kg or 3.1% of their starting body weight. Stayers lost 4.9 kg (5.3% of starting body weight) compared to starters, who lost 1.6 kg (1.7% of starting body weight). Almost half (11,082/22,658, 48.91%) the members who stayed on the program lost 5% or more of their starting body weight, and 15.48% (3507/22,658) achieved a weight loss of 10% or more. Of the members who were classified as class 1 obese when they joined the program, 41.39% (3065/7405) who stayed on the program were no longer classified as obese at the end, and across all categories of obesity, 24% (3180/13,319) were no longer classified as obese at the end of the program. Based on multiple linear regression, platform usage was the strongest predictor of weight loss (β=.263; P<.001), with higher usage associated with greater weight loss.

CONCLUSIONS

This comprehensive evaluation of a commercial, online weight loss program showed that it was effective for weight loss, particularly for members who finished the program and were active in using the platform and tools provided. If the results demonstrated here can be achieved at an even greater scale, the potential social and economic benefits will be extremely significant.

Commercial Weight Loss Programs in the Management of Obesity: an Update

PURPOSE OF REVIEW

Comprehensive lifestyle programs are cornerstones of obesity management, but clinician referrals may be limited by program availability. Commercial weight loss programs may be an alternative, but clinicians may be unaware of their efficacy and safety. This review describes the evidence for commercial programs, particularly 12-month weight loss, among individuals with obesity.

RECENT FINDINGS

Several programs are concordant with evidence-based recommendations (i.e., lower-calorie diet, increased physical activity, and behavioral strategies). Among the guideline-concordant programs, National Diabetes Prevention Program, WW, Jenny Craig, Medifast, and OPTIFAST have demonstrated 12-month weight loss efficacy and safety. While other programs show promise, more evidence is needed before clinician referral may be recommended. Clinical practice guidelines support referrals to commercial weight loss programs that have peer-reviewed evidence to support their efficacy and safety. Clinicians should consider the available evidence, patient preference, and cost when considering referrals to these programs for weight management.

Wearable activity trackers for promoting physical activity: A systematic meta-analytic review

PURPOSE

Although wearable activity trackers hold a promise of nudging people toward a more active lifestyle, current research reveals inconsistent findings regarding the effectiveness of them. The objectives of this paper are two-fold: (1) to synthesize evidence on the effects of wearable activity trackers for improving physical activities, and (2) to identify potential moderators of effect size.

METHODS

A systematic meta-analytic review was conducted. Forty-eight eligible papers based on forty-four distinct trials were identified through a systematic literature search process. Two authors independently extracted information from each study based on predefined data fields. Random-effects meta-analysis, subgroup analysis, and meta-regression analysis were employed.

RESULTS

First, interventions with wearable activity trackers significantly increased daily steps and weekly moderate-to-vigorous physical activity but had no impact on light physical activity or sedentary behavior. Second, daily steps and weekly moderate-to-vigorous physical activity were associated with participants' characteristics (i.e., gender, age, medical condition, and baseline physical activity level) and intervention features (i.e., sensors, modes of expert support, and intervention duration). The identified factors explained 53 % of the total variance for weekly moderate-to-vigorous physical activity.

CONCLUSIONS

The use of wearable activity trackers effectively improves conscious exercise behavior, including daily steps and weekly moderate-to-vigorous physical activity, but not effective for modifying habitual behavior, such as light physical activity and sedentary behavior. We also explicitly show that the extent to which the interventions with wearable activity trackers help users is contingent on the type of users and the design and delivery of interventions. Future studies are called to validate the findings and to offer theoretical explanations.

Effectiveness of Minimal Contact Interventions: An RCT

INTRODUCTION

Around 23% of adults worldwide are insufficiently active. Wearable devices paired with virtual coaching software could increase physical activity. The effectiveness of 3 minimal contact interventions (paper-based physical activity diaries, activity trackers, and activity trackers coupled with virtual coaching) in increasing physical activity energy expenditure and cardiorespiratory fitness were compared over 12 weeks among inactive adults.

METHODS

This was an open label, parallel-group RCT. Inactive adults (aged ≥18 years, N=488) were randomized to no intervention (Control; n=121), paper-based diary (Diary; n=124), activity tracker (Activity Band; n=122), or activity tracker plus virtual coaching (Activity Band PLUS; n=121) groups. Coprimary outcomes included 12-week changes in physical activity energy expenditure and fitness (May 2012-January 2014). Analyses were conducted in 2019-2020.

RESULTS

There were no differences between groups overall (physical activity energy expenditure: p=0.114, fitness: p=0.417). However, there was a greater increase in physical activity energy expenditure (4.21 kJ/kg/day, 95% CI=0.42, 8.00) in the Activity Band PLUS group than in the Diary group. There were also greater decreases in BMI and body fat percentage in the Activity Band PLUS group than in the Control group (BMI= -0.24 kg/m2, 95% CI= -0.45, -0.03; body fat= -0.48%, 95% CI= -0.88, -0.08) and in theActivity Band PLUS group than in the Diary group (BMI= -0.30 kg/m2, 95% CI= -0.50, -0.09; body fat= -0.57%, 95% CI= -0.97, -0.17).

CONCLUSIONS

Coupling activity trackers with virtual coaching may facilitate increases in physical activity energy expenditure compared with a traditional paper‒based physical activity diary intervention and improve some secondary outcomes compared with a traditional paper‒based physical activity diary intervention or no intervention.

TRIAL REGISTRATION

This study is registered at www.clinicaltrials.gov ISRCTN31844443.

Self-Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity

OBJECTIVE

Self-monitoring is a core component of behavioral obesity treatment, but it is unknown how digital health has been used for self-monitoring, what engagement rates are achieved in these interventions, and how self-monitoring and weight loss are related.

METHODS

This systematic review examined digital self-monitoring in behavioral weight loss interventions among adults with overweight or obesity. Six databases (PubMed, Embase, Scopus, PsycInfo, CINAHL, and ProQuest Dissertations & Theses) were searched for randomized controlled trials with interventions ≥ 12 weeks, weight outcomes ≥ 6 months, and outcomes on self-monitoring engagement and their relationship to weight loss.

RESULTS

Thirty-nine studies from 2009 to 2019 met inclusion criteria. Among the 67 interventions with digital self-monitoring, weight was tracked in 72% of them, diet in 81%, and physical activity in 82%. Websites were the most common self-monitoring modality, followed by mobile applications, wearables, electronic scales, and, finally, text messaging. Few interventions had digital self-monitoring engagement rates ≥ 75% of days. Rates were higher in digital- than in paper-based arms in 21 out of 34 comparisons and lower in just 2. Interventions with counseling had similar rates to standalone interventions. Greater digital self-monitoring was linked to weight loss in 74% of occurrences.

CONCLUSIONS

Self-monitoring via digital health is consistently associated with weight loss in behavioral obesity treatment.

Financial implications of New York City's weight management initiative

Purpose

To estimate potential annual savings in medical expenditures from a subsidized weight management program from the NYC Government perspective.

Design

Longitudinal observational study.

Setting

Employees of New York City (NYC) government and enrolled dependents.

Sample

14,946 participants with overweight and obesity.

Intervention

WW (formerly Weight Watchers®) ‘Workshop’ and ‘Digital’ programs.

Measures

Participation rate, enrollment duration, weight change, and predicted gross and net total and per capita medical expenditure savings and return on investment (ROI).

Analysis

Participation rate, enrollment duration, weight change, and program costs are based on direct observation. Predicted savings are simulated based on published data relating weight loss to medical expenditure reductions.

Results

In total, 47% of participating employees and 50% of participating dependents lost weight during the enrollment period. Mean (median) enrollment duration for employees was 7.1 months (7.0) and for dependents was 6.9 months (6.0). Mean (median) weight losses for the employees in ‘Workshops’ and ‘Digital’ was 6.6 lbs (2.80) and 6.3 lbs (0.0). For dependents, weight losses were 7.4 lbs (3.59) and 11.6 lbs (2.0). Per capita and total predicted net savings to NYC Government from employees was estimated to be $120 and $1,486,102 for an ROI of 143%. Including dependents, predicted net savings increases to $1,963,431 for an ROI of 189%. Over 80% of savings came from participants in the Obese III category.

Conclusion

An evidence-based weight management program has the potential to generate a positive ROI for employers. Future studies should validate these estimates using actual data and more rigorous designs.

Examination of a partial dietary self-monitoring approach for behavioral weight management

INTRODUCTION

Dietary self-monitoring in behavioral weight loss programmes traditionally involves keeping track of all foods and beverages to achieve a calorie deficit. While effective, adherence declines over time. WW™ (formerly Weight Watchers), a widely available commercial weight management programme, sought to pilot an approach that permitted participants to consume over 200 foods without monitoring them.

METHODS

The current study used a pre-post evaluation design with anthropometric, psychosocial and physical health assessments at baseline, 3 and 6 months.

RESULTS

Participants (N = 152) were, on average, 48.4 (±12.3) years old, with body mass index (BMI) of 32.8 (±4.8) m/kg2 and 94% female. Mean weight loss was 6.97 + 5.55 kg or 7.9 ± 6.1% of initial body weight (ps < .0001) at 6 months. One third (32.6%) of the sample lost 10% or more of initial body weight. Significant improvements in hunger, cravings, happiness, sleep, quality of life, aerobic stamina, flexibility and blood pressure were observed. Attendance at group meetings, as well as decreases in hunger, and fast food cravings from baseline to 3 months were associated with achieving 10% weight loss at 6 months (p < .01).

CONCLUSIONS

Using an approach that does not require self-monitoring of all foods and beverages produced significant weight losses and other physical and psychosocial improvements.

Role of Commercial Weight-Loss Programs in Medical Management of Obesity

Rates of obesity counseling are low among physicians because of the lack of time and training in this area. In recognition of this challenge, recent national guidelines encourage physicians to refer patients with obesity to intensive, comprehensive lifestyle programs to lose weight. Some commercial weight-loss programs meet these criteria, and this article reviews the evidence from randomized controlled trials regarding such programs' weight-loss efficacy and safety as well as glycemic outcomes among patients with and without diabetes mellitus. A discussion of how physicians might approach the referral process and continued management of patients participating in these programs is included.

Digital self-monitoring: Does adherence or association with outcomes differ by self-monitoring target?

OBJECTIVE

Digital self-monitoring of eating, physical activity, and weight is increasingly prescribed in behavioural weight loss programmes. This study determined if adherence rates or associations with outcomes differed according to self-monitoring target (ie, self-monitoring of eating versus physical activity versus weight).

METHODS

Participants in a 3-month, group-based weight loss programme were instructed to use an app to record food intake, wear a physical activity sensor, and use a wireless body weight scale. At post-treatment, weight loss was measured in clinic and moderate-to-vigorous physical activity (MVPA) was measured by research-grade accelerometer.

RESULTS

Adherence to self-monitoring decreased significantly over time for eating and weight but not physical activity. Overall, adherence to self-monitoring of weight was lower than that of eating or physical activity. Greater adherence to self-monitoring of eating, physical activity, and weight each predicted greater weight loss. Only greater adherence to self-monitoring of eating was associated with greater bouted minutes of MVPA.

CONCLUSIONS

Findings from this study suggest that self-monitoring should be considered a target-specific behaviour rather than a unitary construct when conceptualizing adherence and association with treatment outcomes.

Refining an algorithm-powered just-in-time adaptive weight control intervention: A randomized controlled trial evaluating model performance and behavioral outcomes

Suboptimal weight losses are partially attributable to lapses from a prescribed diet. We developed an app (OnTrack) that uses ecological momentary assessment to measure dietary lapses and relevant lapse triggers and provides personalized intervention using machine learning. Initially, tension between user burden and complete data was resolved by presenting a subset of lapse trigger questions per ecological momentary assessment survey. However, this produced substantial missing data, which could reduce algorithm performance. We examined the effect of more questions per ecological momentary assessment survey on algorithm performance, app utilization, and behavioral outcomes. Participants with overweight/obesity (n = 121) used a 10-week mobile weight loss program and were randomized to OnTrack-short (i.e. 8 questions/survey) or OnTrack-long (i.e. 17 questions/survey). Additional questions reduced ecological momentary assessment adherence; however, increased data completeness improved algorithm performance. There were no differences in perceived effectiveness, app utilization, or behavioral outcomes. Minimal differences in utilization and perceived effectiveness likely contributed to similar behavioral outcomes across various conditions.

Changing the Physical Activity Behavior of Adults With Fitness Trackers: A Systematic Review and Meta-Analysis

OBJECTIVE

To examine whether a fitness tracker (FT) intervention changes physical activity (PA) behavior compared to a control condition or compared to an alternative intervention.

DATA SOURCE

Searches between January 01, 2010, and January 01, 2019, were conducted in PubMed, CINAHL, Cochrane CENTRAL, EMBASE, and PsycINFO.

INCLUSION/EXCLUSION CRITERIA

Randomized clinical trials of adults using an FT to change PA behavior were included. Nonclinical trials, studies that included the delivery of structured exercise, and/or studies that only used the FT to assess PA were excluded.

DATA EXTRACTION

Extracted features included characteristics of the study population, intervention components, PA outcomes, and results.

DATA SYNTHESIS

Papers were pooled in a statistical meta-analysis using a fixed effects model. Where statistical pooling was not possible, standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated. Findings were presented in a narrative form and tables.

RESULTS

Of 2076 articles found, 21 were included in the review. A small yet significant positive effect (SMD = 0.25, 95% CI = 0.17-0.32; P < .01; I² = 56.9%; P = .03) was found in step count for interventions compared to control. A small yet significant negative effect (SMD = -0.11, 95% CI = -0.20 to -0.02; P = .02; I² = 58.2%; P = 0.03) was found in moderate-to-vigorous PA for interventions compared to an alternative intervention.

CONCLUSION

Trackers may enhance PA interventions, as a general positive effect is found in step count compared to a control. However, there is no evidence of a positive effect when interventions are compared to an alternative intervention. It is unknown whether results are due to other intervention components and/or clinical heterogeneity.

Feasibility and acceptability of a rural, pragmatic, telemedicine-delivered healthy lifestyle programme

BACKGROUND

The public health crisis of obesity leads to increasing morbidity that are even more profound in certain populations such as rural adults. Live, two-way video-conferencing is a modality that can potentially surmount geographic barriers and staffing shortages.

METHODS

Patients from the Dartmouth-Hitchcock Weight and Wellness Center were recruited into a pragmatic, single-arm, nonrandomized study of a remotely delivered 16-week evidence-based healthy lifestyle programme. Patients were provided hardware and appropriate software allowing for remote participation in all sessions, outside of the clinic setting. Our primary outcomes were feasibility and acceptability of the telemedicine intervention, as well as potential effectiveness on anthropometric and functional measures.

RESULTS

Of 62 participants approached, we enrolled 37, of which 27 completed at least 75% of the 16-week programme sessions (27% attrition). Mean age was 46.9 ± 11.6 years (88.9% female), with a mean body mass index of 41.3 ± 7.1 kg/m2 and mean waist circumference of 120.7 ± 16.8 cm. Mean patient participant satisfaction regarding the telemedicine approach was favourable (4.48 ± 0.58 on 1-5 Likert scale-low to high) and 67.6/75 on standardized questionnaire. Mean weight loss at 16 weeks was 2.22 ± 3.18 kg representing a 2.1% change (P < .001), with a loss in waist circumference of 3.4% (P = .001). Fat mass and visceral fat were significantly lower at 16 weeks (2.9% and 12.5%; both P < .05), with marginal improvement in appendicular skeletal muscle mass (1.7%). In the 30-second sit-to-stand test, a mean improvement of 2.46 stands (P = .005) was observed.

CONCLUSION

A telemedicine-delivered, intensive weight loss intervention is feasible, acceptable, and potentially effective in rural adults seeking weight loss.

Enhancing group-based internet obesity treatment: A pilot RCT comparing video and text-based chat

OBJECTIVE

Internet delivery of behavioural weight control interventions offers potential for broad geographic reach and accessibility, but weight losses online fall short of those produced with the same programme delivered in-person. This pilot study examined feasibility and preliminary efficacy of a video-based platform for delivering weekly chat as part of a 6-month, 24-session online group behavioural weight control programme compared with the established text-based format, which has produced the best online weight losses to date.

METHOD

Women with obesity (N = 32) were randomized to either (a) weekly video group chat sessions and provided with a cellular-enabled scale (Video) or (b) Text-based weekly chat sessions and given a digital scale (Text) and followed for 6 months to determine weight loss and treatment engagement.

RESULTS

Women randomized to the ideo condition lost more weight than those in the Text condition (-5.0 ± 6.0% vs. -3.0 ± 4.1%, respectively) at 6 months, although the difference was not statistically significant. However, women in the Video condition had significantly greater treatment engagement, with greater self-monitoring and website utilization than those in the Text condition.

CONCLUSIONS

Videoconference delivery of group-based online weight control accompanied by a cellular-connected scale may promote greater treatment engagement and weight loss than text-based chat. A larger, adequately powered study is warranted to determine which elements drive these enhanced treatment outcomes.

Remotely Delivered Interventions for Obesity Treatment

PURPOSE OF REVIEW

This review synthesizes recent research on remotely delivered interventions for obesity treatment, including summarizing outcomes and challenges to implementing these treatments as well as outlining recommendations for clinical implementation and future research.

RECENT FINDINGS

There are a wide range of technologies used for delivering obesity treatment remotely. Generally, these treatments appear to be acceptable and feasible, though weight loss outcomes are mixed. Engagement in these interventions, particularly in the long term, is a significant challenge. Newer technologies are rapidly developing and enable tailored and adaptable interventions, though research in this area is in its infancy. Further research is required to optimize potential benefits of remotely delivered interventions for obesity.

Can Mobile Technology Improve Weight Loss in Overweight Adults? A Systematic Review

The purpose of this systematic review was to identify evidence concerning the effectiveness of mobile applications and wearable devices for weight loss in overweight adults. A database search of PubMed and CINAHL yielded 12 eligible articles following the application of inclusion and exclusion criteria. Inclusion criteria consisted of studies primarily pertaining to obesity, inclusion of adult population only (18 years and older), use of experimental study designs only, use of mobile apps or wearable devices as intervention(s), and primary outcome of weight loss. Overall, the research evidence suggests that mobile apps and wearables are effective self-regulating tools for weight loss. Although study design concerns, such as lack of non-intervention comparator groups, prevent a definitive conclusion regarding the relative power of mobile apps and wearables over other self-monitoring methods, evidence indicates that mobile technology can be used as integral tools within overarching weight loss strategies recommended in the primary care setting.

Randomized controlled trial of OnTrack, a just-in-time adaptive intervention designed to enhance weight loss

This randomized trial demonstrated qualified support for the ability of a machine learning-powered, smartphone-based just-in-time, adaptive intervention to enhance weight loss over and above a commercial weight loss program.