Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Behavioral Domain

The relationship between sleep quantity, sleep quality and weight loss in adults: A scoping review

Sleep is hypothesized to interact with weight gain and loss; however, modelling this relationship remains elusive. Poor sleep perpetuates a cascade of cardiovascular and metabolic consequences that may not only increase risk of adiposity, but also confound weight loss efforts. We conducted a scoping review to assess the research on sleep and weight loss interventions. We searched six databases for studies of behavioural weight loss interventions that included assessments of sleep in the general, non-clinical adult human population. Our synthesis focused on dimensions of Population, Intervention, Control, and Outcomes (PICO) to identify research and knowledge gaps. We identified 35 studies that fell into one of four categories: (a) sleep at baseline as a predictor of subsequent weight loss during an intervention, (b) sleep assessments after a history of successful weight loss, (c) concomitant changes in sleep associated with weight loss and (d) experimental manipulation of sleep and resulting weight loss. There was some evidence of improvements in sleep in response to weight-loss interventions; however, randomized controlled trials of weight loss interventions tended not to report improvements in sleep when compared to controls. We conclude that baseline sleep characteristics may predict weight loss in studies of dietary interventions and that sleep does not improve because of weight loss alone. Future studies should enrol large and diverse, normal, overweight and obese short sleepers in trials to assess the efficacy of sleep as a behavioural weight loss treatment.

Randomized controlled trial of a novel lifestyle intervention used with or without meal replacements in work sites

OBJECTIVE

Lifestyle interventions have had limited effectiveness in work sites when evaluated in randomized trials. This study assessed the effectiveness of a novel lifestyle intervention for weight loss (Healthy Weight for Living [HWL]) implemented with or without meal replacements (MR) in work sites. HWL used a new behavioral approach emphasizing reducing hunger and building healthy food preferences, and, unlike traditional lifestyle interventions, it did not require calorie counting.

METHODS

Twelve work sites were randomized to an 18-month intervention (n = 8; randomization within work sites to HWL, HWL + MR) or 6-month wait-listed control (n = 4). Participants were employees with overweight or obesity (N = 335; age = 48 [SD 10] years; BMI = 33 [6] kg/m2 ; 83% female). HWL was group-delivered in person or by videoconference. The primary outcome was 6-month weight change; secondary outcomes included weight and cardiometabolic risk factors measured at 6, 12, and 18 months in intervention groups.

RESULTS

Mean 6-month weight change was -8.8% (95% CI: -11.2% to -6.4%) for enrollees in HWL and -8.0% (-10.4% to -5.5%) for HWL + MR (p < 0.001 for both groups vs. controls), with no difference between interventions (p = 0.40). Clinically meaningful weight loss (≥5%) was maintained at 18 months in both groups (p < 0.001).

CONCLUSIONS

A new lifestyle intervention approach, deliverable by videoconference with or without MR, supported clinically impactful weight loss in employees.

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

OBJECTIVE

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

DESIGN

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

SETTING

Adults with obesity recruited via web-based survey hyperlink.

PARTICIPANTS

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

VARIABLES MEASURED

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

ANALYSIS

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

RESULTS

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

CONCLUSION AND IMPLICATION

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

Technical report: an online international weight control registry to inform precision approaches to healthy weight management

BACKGROUND

Personalizing approaches to prevention and treatment of obesity will be a crucial aspect of precision health initiatives. However, in considering individual susceptibility to obesity, much remains to be learned about how to support healthy weight management in different population subgroups, environments and geographical locations.

SUBJECTS/METHODS

The International Weight Control Registry (IWCR) has been launched to facilitate a deeper and broader understanding of the spectrum of factors contributing to success and challenges in weight loss and weight loss maintenance in individuals and across population groups. The IWCR registry aims to recruit, enroll and follow a diverse cohort of adults with varying rates of success in weight management. Data collection methods include questionnaires of demographic variables, weight history, and behavioral, cultural, economic, psychological, and environmental domains. A subset of participants will provide objective measures of physical activity, weight, and body composition along with detailed reports of dietary intake. Lastly, participants will be able to provide qualitative information in an unstructured format on additional topics they feel are relevant, and environmental data will be obtained from public sources based on participant zip code.

CONCLUSIONS

The IWCR will be a resource for researchers to inform improvements in interventions for weight loss and weight loss maintenance in different countries, and to examine environmental and policy-level factors that affect weight management in different population groups. This large scale, multi-level approach aims to inform efforts to reduce the prevalence of obesity worldwide and its associated comorbidities and economic impacts.

TRIAL REGISTRATION

NCT04907396 (clinicaltrials.gov) sponsor SB Roberts; Tufts University IRB #13075.

Comparison of weight loss induced by daily caloric restriction versus intermittent fasting (DRIFT) in individuals with obesity: study protocol for a 52-week randomized clinical trial

BACKGROUND

The standard of care for treating overweight and obesity is daily caloric restriction (DCR). While this approach produces modest weight loss, adherence to DCR declines over time and weight regain is common. Intermittent fasting (IMF) is an alternative dietary strategy for reducing energy intake (EI) that involves >60% energy restriction on 2-3 days per week, or on alternate days, with habitual intake on fed days. While numerous studies have evaluated IMF as a weight loss strategy, there are several limitations including lack of a standard-of-care DCR control, failure to provide guideline-based behavioral support, and failure to rigorously evaluate dietary and PA adherence using objective measures. To date, only three longer-term (52-week) trials have evaluated IMF as a weight loss strategy. None of these longer-duration studies reported significant differences between IMF and DCR in changes in weight. However, each of these studies has limitations that prohibit drawing generalizable conclusions about the relative long-term efficacy of IMF vs. DCR for obesity treatment.

METHODS

The Daily Caloric Restriction vs. Intermittent Fasting Trial (DRIFT) is a two-arm, 52-week block randomized (1:1) clinical weight loss trial. The two intervention arms (DCR and IMF) are designed to prescribe an equivalent average weekly energy deficit from baseline weight maintenance energy requirements. Both DCR and IMF will be provided guideline-based behavioral support and a PA prescription. The primary outcome is change in body weight at 52 weeks. Secondary outcomes include changes in body composition (dual-energy x-ray absorptiometry (DXA)), metabolic parameters, total daily energy expenditure (TDEE, doubly labeled water (DLW)), EI (DLW intake-balance method, 7-day diet diaries), and patterns of physical activity (PA, activPAL device).

DISCUSSION

Although DCR leads to modest weight loss success in the short-term, there is wide inter-individual variability in weight loss and poor long-term weight loss maintenance. Evidence-based dietary approaches to energy restriction that are effective long-term are needed to provide a range of evidence-based options to individuals seeking weight loss. The DRIFT study will evaluate the long-term effectiveness of IMF vs. DCR on changes in objectively measured weight, EI, and PA, when these approaches are delivered using guideline-based behavioral support and PA prescriptions.

Using psycho-behavioral phenotyping for overweight and obesity: Confirmation of the 6 factor questionnaire

Objective

Questionnaires that assess dietary habits, eating behaviors, and relevant psychosocial constructs are routinely used in obesity research and clinical practice. The 6 factor questionnaire (6FQ) was previously developed as an assessment tool for psycho-behavioral phenotyping. The primary purpose of this study was to confirm and validate the original findings in a large diverse adult population.

Methods

A total of 5399 self-selected participants (mean age of 48 ± 13 years and body mass index of 32 ± 8 kg/m2) completed the 6FQ online. The association between self-reported demographic data and 6FQ responses was assessed using linear regression models.

Results

Mean factor score and odds ratio analyses consistently demonstrated a statistically significant relationship between factors and body weight even after adjusting for age, sex, and race/ethnicity.

Conclusions

Although the study was correlational in design, the results demonstrate that the 6FQ, an instrument that represents multidimensional unhealthful lifestyle patterns associated with diet, physical activity, cognition, and self-perception worsen with increasing body weight. Psycho-behavioral phenotyping may be a useful approach when assessing and treating patients with obesity.

Use of Natural Spoken Language With Automated Mapping of Self-reported Food Intake to Food Composition Data for Low-Burden Real-time Dietary Assessment: Method Comparison Study

Background

Self-monitoring food intake is a cornerstone of national recommendations for health, but existing apps for this purpose are burdensome for users and researchers, which limits use.

Objective

We developed and pilot tested a new app (COCO Nutritionist) that combines speech understanding technology with technologies for mapping foods to appropriate food composition codes in national databases, for lower-burden and automated nutritional analysis of self-reported dietary intake.

Methods

COCO was compared with the multiple-pass, interviewer-administered 24-hour recall method for assessment of energy intake. COCO was used for 5 consecutive days, and 24-hour dietary recalls were obtained for two of the days. Participants were 35 women and men with a mean age of 28 (range 20-58) years and mean BMI of 24 (range 17-48) kg/m².

Results

There was no significant difference in energy intake between values obtained by COCO and 24-hour recall for days when both methods were used (mean 2092, SD 1044 kcal versus mean 2030, SD 687 kcal, P=.70). There were also no significant differences between the methods for percent of energy from protein, carbohydrate, and fat (P=.27-.89), and no trend in energy intake obtained with COCO over the entire 5-day study period (P=.19).

Conclusions

This first demonstration of a dietary assessment method using natural spoken language to map reported foods to food composition codes demonstrates a promising new approach to automate assessments of dietary intake.

Randomized trial of a novel lifestyle intervention compared with the Diabetes Prevention Program for weight loss in adult dependents of military service members

BACKGROUND

Lifestyle interventions are the first-line treatment for obesity, but participant weight loss is typically low.

OBJECTIVES

We evaluated the efficacy of an alternative lifestyle intervention [Healthy Weight for Living (HWL)] compared with a modified Diabetes Prevention Program (m-DPP). HWL was based on a revised health behavior change model emphasizing hunger management and the development of healthy food preferences. m-DPP was a standard Diabetes Prevention Program implemented with counselor time matched to HWL. Participants were adult dependents of military personnel and had overweight or obesity.

METHODS

Participants were randomly assigned to HWL (n = 121) or m-DPP (n = 117), delivered primarily by group videoconference with additional midweek emails. The primary outcome was 12-mo weight change. Secondary outcomes included 6-mo changes in cardiometabolic risk factors and diet. Intention-to-treat (ITT) and complete case (CC) analyses were performed using linear mixed models.

RESULTS

Retention did not differ between groups (72% and 66% for HWL and m-DPP at 12 mo, respectively; P = 0.30). Mean ± SE adjusted 12-mo weight loss in the ITT cohort was 7.46 ± 0.85 kg for HWL and 7.32 ± 0.87 kg for m-DPP (P = 0.91); in the CC cohort, it was 7.83 ± 0.82 kg for HWL and 6.86 ± 0.88 kg for m-DPP (P = 0.43). Thirty-eight percent of HWL and 30% of m-DPP completers achieved ≥10% weight loss (P = 0.32). Improvements in systolic blood pressure, LDL cholesterol, triglycerides, fasting glucose, general health, sleep, and mood were similar across groups; improvements in diastolic blood pressure were greater in m-DPP. Adjusted group mean reductions in energy intake were not significantly different between groups, but HWL participants were more adherent to their dietary prescription for lower glycemic index and high fiber and protein (P = 0.05 to <0.001 for ITT).

CONCLUSIONS

HWL and m-DPP showed equivalent and clinically impactful mean weight loss with cardiometabolic benefits. These results identify an alternative approach for behavioral treatment of overweight and obesity.This trial was registered at clinicaltrials.gov as NCT02348853.

Evaluation of PIQNIQ, a Novel Mobile Application for Capturing Dietary Intake

BACKGROUND

Accurate measurement of dietary intake is vital for providing nutrition interventions and understanding the complex role of diet in health. Traditional dietary assessment methods are very resource intensive and burdensome to participants. Technology may help mitigate these limitations and improve dietary data capture.

OBJECTIVE

Our objective was to evaluate the accuracy of a novel mobile application (PIQNIQ) in capturing dietary intake by self-report. Our secondary objective was to assess whether food capture using PIQNIQ was comparable with an interviewer-assisted 24-h recall (24HR).

METHODS

This study was a single-center randomized clinical trial enrolling 132 adults aged 18 to 65 y from the general population. Under a provided-food protocol with 3 menus designed to include a variety of foods, participants were randomly assigned to 1 of 3 food capture methods: simultaneous entry using PIQNIQ, photo-assisted recall using PIQNIQ, and 24HR. Primary outcomes were energy and nutrient content (calories, total fat, carbohydrates, protein, added sugars, calcium, dietary fiber, folate, iron, magnesium, potassium, saturated fat, sodium, and vitamins A, C, D, and E) captured by the 3 methods.

RESULTS

The majority of nutrients reported were within 30% of consumed intake in all 3 food capture methods (n = 129 completers). Reported intake was highly (>30%) overestimated for added sugars in both PIQNIQ groups and underestimated for calcium in the photo-assisted recall group only (P < 0.001 for all). However, in general, both PIQNIQ methods had similar levels of accuracy and were comparable to the 24HR except in their overestimation (>30%) of added sugars and total fat (P < 0.001 for both).

CONCLUSIONS

Our results suggest that intuitive, technology-based methods of dietary data capture are well suited to modern users and, with proper execution, can provide data that are comparable to data obtained with traditional methods. This trial was registered at clinicaltrials.gov as NCT03578458.

Metabolic Adaptations to Weight Loss: A Brief Review

ABSTRACT

Martínez-Gómez, MG and Roberts, BM. Metabolic adaptations to weight loss: A brief review. J Strength Cond Res XX(X): 000-000, 2021-As the scientific literature has continuously shown, body mass loss attempts do not always follow a linear fashion nor always go as expected even when the intervention is calculated with precise tools. One of the main reasons why this tends to happen relies on our body's biological drive to regain the body mass we lose to survive. This phenomenon has been referred to as "metabolic adaptation" many times in the literature and plays a very relevant role in the management of obesity and human weight loss. This review will provide insights into some of the theoretical models for the etiology of metabolic adaptation as well as a quick look into the physiological and endocrine mechanisms that underlie it. Nutritional strategies and dietetic tools are thus necessary to confront these so-called adaptations to body mass loss. Among some of these strategies, we can highlight increasing protein needs, opting for high-fiber foods or programming-controlled diet refeeds, and diet breaks over a large body mass loss phase. Outside the nutritional aspects, it might be wise to increase the physical activity and thus the energy flux of an individual when possible to maintain diet-induced body mass loss in the long term. This review will examine these protocols and their viability in the context of adherence and sustainability for the individual toward successful body mass loss.

The association between sleep health and weight change during a 12-month behavioral weight loss intervention

BACKGROUND

Prior research on the relationship between sleep and attempted weight loss failed to recognize the multidimensional nature of sleep. We examined the relationship between a composite measure of sleep health and change in weight and body composition among adults in a weight loss intervention.

METHODS

Adults (N = 125) with overweight or obesity (50.3 ± 10.6 years, 91% female, 81% white) participated in a 12-month behavioral weight loss intervention, with assessments of sleep, weight, fat mass, and fat-free mass at baseline, 6 months, and 12 months. Six sleep dimensions (regularity, satisfaction, alertness, timing, efficiency, and duration) were categorized as "good" or "poor" using questionnaires and actigraphy. A composite score was calculated by summing the number of "good" dimensions. Obstructive sleep apnea (OSA) was assessed in a subsample (n = 117), using the apnea-hypopnea index (AHI) to determine OSA severity. Linear mixed modeling was used to examine the relationships between sleep health and outcomes of percent weight, fat mass, or fat-free mass change during the subsequent 6-month interval, adjusting for age, sex, bed partner, and race; an additional model adjusted for AHI.

RESULTS

Mean baseline and 6-month sleep health was 4.5 ± 1.1 and 4.5 ± 1.2, respectively. Mean weight, fat mass, and fat-free mass changes from 0 to 6 months were -9.3 ± 6.1%, -16.9 ± 13.5%, and -3.4 ± 3.4%, respectively, and 0.4 ± 4.8%, -0.3 ± 10.3%, and 0.7 ± 4.1% from 6 to 12 months. Better sleep health was associated with greater subsequent weight loss (P = 0.016) and fat loss (P = 0.006), but not fat-free mass loss (P = 0.232). Following AHI adjustment, the association between sleep health and weight loss was attenuated (P = 0.102) but remained significant with fat loss (P = 0.040). Regularity, satisfaction, timing, and efficiency were each associated with weight and/or fat loss (P ≤ 0.041).

CONCLUSIONS

Better sleep health was associated with greater weight and fat loss, with associations attenuated after accounting for OSA severity. Future studies should explore whether improving sleep health, OSA, or the combination improves weight loss.

Review of the validity and feasibility of image-assisted methods for dietary assessment

Accurately quantifying dietary intake is essential to understanding the effect of diet on health and evaluating the efficacy of dietary interventions. Self-report methods (e.g., food records) are frequently utilized despite evident inaccuracy of these methods at assessing energy and nutrient intake. Methods that assess food intake via images of foods have overcome many of the limitations of traditional self-report. In cafeteria settings, digital photography has proven to be unobtrusive and accurate and is the method of choice for assessing food provision, plate waste, and food intake. In free-living conditions, image capture of food selection and plate waste via the user's smartphone, is promising and can produce accurate energy intake estimates, though accuracy is not guaranteed. These methods foster (near) real-time transfer of data and eliminate the need for portion size estimation by the user since the food images are analyzed by trained raters. A limitation that remains, similar to self-report methods where participants must truthfully record all consumed foods, is intentional and/or unintentional underreporting of foods due to social desirability or forgetfulness. Methods that rely on passive image capture via wearable cameras are promising and aim to reduce user burden; however, only pilot data with limited validity are currently available and these methods remain obtrusive and cumbersome. To reduce analysis-related staff burden and to allow real-time feedback to the user, recent approaches have aimed to automate the analysis of food images. The technology to support automatic food recognition and portion size estimation is, however, still in its infancy and fully automated food intake assessment with acceptable precision not yet a reality. This review further evaluates the benefits and challenges of current image-assisted methods of food intake assessment and concludes that less burdensome methods are less accurate and that no current method is adequate in all settings.

Minority and low-income patients are less likely to have a scale for self-weighing in their home: A survey in primary care

Daily self-weighing is a weight management behaviour that requires a scale; however, scale ownership may be cost-prohibitive for some patients. Our objective was to understand the proportion of primary care patients with a scale at home, and factors associated with home scale access, to potentially inform future interventions that facilitate scale access. Cross sectional survey of 216 adult patients from three primary care clinics: mixed-income urban/suburban (n = 68); mixed-income urban (n = 70); low-income urban (n = 74). The dependent variable was presence of a home scale; bivariate associations were conducted with variables including demographics, insurance type, clinic setting and self-reported height/weight. Mean age was 53 years; 71% women; 71% racial minority; mean body mass index 32 kg/m2 . Overall, 56% had a home scale. Most (79%) white patients owned a scale, compared to 46% of racial minority patients (P < .01); 33% of low-income patients owned scale, compared to over 66% of patients at the clinics serving mixed-income populations (P < .01). Most low-income urban clinic patients do not own a home scale. Because self-weighing is an effective weight-management behaviour, clinicians could consider assessing scale access, and future research should assess the health impact of providing scales to patients with overweight/obesity who desire weight loss or maintenance.

Biobehavioural approaches to prevention and treatment: A call for implementation science in obesity research

Much progress has been made in the last 30 years in understanding the causes and mechanisms that contribute to obesity, yet widely available and successful strategies for prevention and treatment remain elusive at population levels. This paper discusses the biobehavioural framework and provides suggestions for applying it to enable greater progress in the science of obesity prevention and treatment, including an increased focus on implementation of science strategies. The objective is to promote a re-evaluation of current views about preventing and treating obesity within a unified biobehavioural framework. Further integration of research exploring how both behavioural and biological components interact is a critical step forward.

OBEDIS Core Variables Project: European Expert Guidelines on a Minimal Core Set of Variables to Include in Randomized, Controlled Clinical Trials of Obesity Interventions

Heterogeneity of interindividual and intraindividual responses to interventions is often observed in randomized, controlled trials for obesity. To address the global epidemic of obesity and move toward more personalized treatment regimens, the global research community must come together to identify factors that may drive these heterogeneous responses to interventions. This project, called OBEDIS (OBEsity Diverse Interventions Sharing - focusing on dietary and other interventions), provides a set of European guidelines for a minimal set of variables to include in future clinical trials on obesity, regardless of the specific endpoints. Broad adoption of these guidelines will enable researchers to harmonize and merge data from multiple intervention studies, allowing stratification of patients according to precise phenotyping criteria which are measured using standardized methods. In this way, studies across Europe may be pooled for better prediction of individuals' responses to an intervention for obesity - ultimately leading to better patient care and improved obesity outcomes.

Effectiveness of Intermittent Fasting and Time-Restricted Feeding Compared to Continuous Energy Restriction for Weight Loss

The current obesity epidemic is staggering in terms of its magnitude and public health impact. Current guidelines recommend continuous energy restriction (CER) along with a comprehensive lifestyle intervention as the cornerstone of obesity treatment, yet this approach produces modest weight loss on average. Recently, there has been increased interest in identifying alternative dietary weight loss strategies that involve restricting energy intake to certain periods of the day or prolonging the fasting interval between meals (i.e., intermittent energy restriction, IER). These strategies include intermittent fasting (IMF; >60% energy restriction on 2-3 days per week, or on alternate days) and time-restricted feeding (TRF; limiting the daily period of food intake to 8-10 h or less on most days of the week). Here, we summarize the current evidence for IER regimens as treatments for overweight and obesity. Specifically, we review randomized trials of ≥8 weeks in duration performed in adults with overweight or obesity (BMI ≥ 25 kg/m²) in which an IER paradigm (IMF or TRF) was compared to CER, with the primary outcome being weight loss. Overall, the available evidence suggests that IER paradigms produce equivalent weight loss when compared to CER, with 9 out of 11 studies reviewed showing no differences between groups in weight or body fat loss.

The Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures Project: Rationale and Approach

BACKGROUND

Individual variability in response to multiple modalities of obesity treatment is well documented, yet our understanding of why some individuals respond while others do not is limited. The etiology of this variability is multifactorial; however, at present, we lack a comprehensive evidence base to identify which factors or combination of factors influence treatment response.

OBJECTIVES

This paper provides an overview and rationale of the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project, which aims to advance the understanding of individual variability in response to adult obesity treatment. This project provides an integrated model for how factors in the behavioral, biological, environmental, and psychosocial domains may influence obesity treatment responses and identify a core set of measures to be used consistently across adult weight-loss trials. This paper provides the foundation for four companion papers that describe the core measures in detail.

SIGNIFICANCE

The accumulation of data on factors across the four ADOPT domains can inform the design and delivery of effective, tailored obesity treatments. ADOPT provides a framework for how obesity researchers can collectively generate this evidence base and is a first step in an ongoing process that can be refined as the science advances.