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

Neighborhoods and Cardiovascular Health: A Scientific Statement From the American Heart Association

The neighborhoods where individuals reside shape environmental exposures, access to resources, and opportunities. The inequitable distribution of resources and opportunities across neighborhoods perpetuates and exacerbates cardiovascular health inequities. Thus, interventions that address the neighborhood environment could reduce the inequitable burden of cardiovascular disease in disenfranchised populations. The objective of this scientific statement is to provide a roadmap illustrating how current knowledge regarding the effects of neighborhoods on cardiovascular disease can be used to develop and implement effective interventions to improve cardiovascular health at the population, health system, community, and individual levels. PubMed/Medline, CINAHL, Cochrane Library reviews, and ClinicalTrials.gov were used to identify observational studies and interventions examining or targeting neighborhood conditions in relation to cardiovascular health. The scientific statement summarizes how neighborhoods have been incorporated into the actions of health care systems, interventions in community settings, and policies and interventions that involve modifying the neighborhood environment. This scientific statement presents promising findings that can be expanded and implemented more broadly and identifies methodological challenges in designing studies to evaluate important neighborhood-related policies and interventions. Last, this scientific statement offers recommendations for areas that merit further research to promote a deeper understanding of the contributions of neighborhoods to cardiovascular health and health inequities and to stimulate the development of more effective interventions.

Impact of the Neighborhood Food Environment on Dietary Intake and Obesity: a Review of the Recent Literature

PURPOSE OF REVIEW

The built environment impacts obesogenic behaviors and in turn body weight outcomes. This review summarizes recent research demonstrating environmental impacts on dietary intake and obesity with a specific focus on the neighborhood food environment.

RECENT FINDINGS

In the previous five years, an abundance of reviews and research studies have been undertaken to elucidate how the neighborhood food environment impacts diet and obesity. This includes studies using primary data collection and secondary data analyses in various populations across the globe. Taken together, current research presents mixed evidence on the impact of the neighborhood food environment on both dietary intake and obesity. While there is some evidence that certain features of the neighborhood food environment influence health behaviors and outcomes in particular populations, it is imperative to acknowledge the complexity of how neighborhood features interact and constantly evolve when considering place-based influences on health behaviors and outcomes.

Food Is Medicine: A Presidential Advisory From the American Heart Association

Unhealthy diets are a major impediment to achieving a healthier population in the United States. Although there is a relatively clear sense of what constitutes a healthy diet, most of the US population does not eat healthy food at rates consistent with the recommended clinical guidelines. An abundance of barriers, including food and nutrition insecurity, how food is marketed and advertised, access to and affordability of healthy foods, and behavioral challenges such as a focus on immediate versus delayed gratification, stand in the way of healthier dietary patterns for many Americans. Food Is Medicine may be defined as the provision of healthy food resources to prevent, manage, or treat specific clinical conditions in coordination with the health care sector. Although the field has promise, relatively few studies have been conducted with designs that provide strong evidence of associations between Food Is Medicine interventions and health outcomes or health costs. Much work needs to be done to create a stronger body of evidence that convincingly demonstrates the effectiveness and cost-effectiveness of different types of Food Is Medicine interventions. An estimated 90% of the $4.3 trillion annual cost of health care in the United States is spent on medical care for chronic disease. For many of these diseases, diet is a major risk factor, so even modest improvements in diet could have a significant impact. This presidential advisory offers an overview of the state of the field of Food Is Medicine and a road map for a new research initiative that strategically approaches the outstanding questions in the field while prioritizing a human-centered design approach to achieve high rates of patient engagement and sustained behavior change. This will ideally happen in the context of broader efforts to use a health equity-centered approach to enhance the ways in which our food system and related policies support improvements in health.

Impact of the built, social, and food environment on long-term weight loss within a behavioral weight loss intervention

Background

Behavioral weight loss interventions can lead to an average weight loss of 5%-10% of initial body weight, however there is wide individual variability in treatment response. Although built, social, and community food environments can have potential direct and indirect influences on body weight (through their influence on physical activity and energy intake), these environmental factors are rarely considered as predictors of variation in weight loss.

Objective

Evaluate the association between built, social, and community food environments and changes in weight, moderate-to-vigorous physical activity (MVPA), and dietary intake among adults who completed an 18-month behavioral weight loss intervention.

Methods

Participants included 93 adults (mean ± SD; 41.5 ± 8.3 years, 34.4 ± 4.2 kg/m2, 82% female, 75% white). Environmental variables included urbanicity, walkability, crime, Neighborhood Deprivation Index (includes 13 social economic status factors), and density of convenience stores, grocery stores, and limited-service restaurants at the tract level. Linear regressions examined associations between environment and changes in body weight, waist circumference (WC), MVPA (SenseWear device), and dietary intake (3-day diet records) from baseline to 18 months.

Results

Grocery store density was inversely associated with change in weight (β = -0.95; p = 0.02; R 2 = 0.062) and WC (β = -1.23; p < 0.01; R 2 = 0.109). Participants living in tracts with lower walkability demonstrated lower baseline MVPA and greater increases in MVPA versus participants with higher walkability (interaction p = 0.03). Participants living in tracts with the most deprivation demonstrated greater increases in average daily steps (β = 2048.27; p = 0.02; R 2 = 0.039) versus participants with the least deprivation. Limited-service restaurant density was associated with change in % protein intake (β = 0.39; p = 0.046; R 2 = 0.051).

Conclusion

Environmental factors accounted for some of the variability (<11%) in response to a behavioral weight loss intervention. Grocery store density was positively associated with weight loss at 18 months. Additional studies and/or pooled analyses, encompassing greater environmental variation, are required to further evaluate whether environment contributes to weight loss variability.

Social determinants of health, health disparities, and adiposity

Social determinants of health (SDoH), or the socioeconomic, environmental, and psychosocial conditions in which individuals spend their daily lives, substantially influence obesity as a cardiovascular disease (CVD) risk factor. The coronavirus disease 2019 (COVID-19) pandemic highlighted the converging epidemics of obesity, CVD, and social inequities globally. Obesity and CVD serve as independent risk factors for COVID-19 severity and lower-resourced populations most impacted by adverse SDoH have the highest COVID-19 mortality rates. Better understanding the interplay between social and biologic factors that contribute to obesity-related CVD disparities are important to equitably address obesity across populations. Despite efforts to investigate SDoH and their biologic effects as drivers of health disparities, the connections between SDoH and obesity remain incompletely understood. This review aims to highlight the relationships between socioeconomic, environmental, and psychosocial factors and obesity. We also present potential biologic factors that may play a role in the biology of adversity, or link SDoH to adiposity and poor adipo-cardiology outcomes. Finally, we provide evidence for multi-level obesity interventions targeting multiple aspects of SDoH. Throughout, we emphasize areas for future research to tailor health equity-promoting interventions across populations to reduce obesity and obesity-related CVD disparities.

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.

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.

The association between the obesogenic environment and 6-month and 24-month weight change in a rural weight loss intervention trial in the United States

The unique obesogenic environment may influence the ability to effectively maintain weight loss in rural areas. The aim of this study was to examine the contextual relationship of neighborhood disadvantage, distance to supermarkets and supercenters, and fast food, dollar store, and exercise facility environments on weight loss following a weight-loss intervention in the United States. This analysis (n = 1177) linked weight loss outcomes from a rural, primary care-based randomized controlled trial to contextual data collected from residential addresses. Outcomes include 6-month and 24-month percent weight loss. These outcomes were compared across contextual variables, including tract level disadvantage, food accessibility, and food/exercise availability. Covariates were included in ordinary least squares (OLS) multivariable regression models for 6-month and 24-month weight loss measures, across three weight loss interventions. Contextual variables were not significantly related to percent weight loss overall across treatment arms. Participants living in a 5-mile buffer to dollar stores experienced approximately a 2% (p < 0.05) lower weight loss, but only in the least effective counseling arm (individual clinic visits), while controlling for both individual and contextual factors. Our results suggest that specific contextual variables in rural populations may play an important role in moderating weight loss outcomes especially under the conditions of less effective interventions.

Identification of instruments for evaluation of behavioural and psychological parameters associated with obesity management: A systematic review with narrative synthesis of the findings

BACKGROUND AND AIMS

To identify instruments used to evaluate the predictors of successful weight loss across weight loss trials.

METHODS

We searched PubMed, PsychInfo, Cochrane Reviews and Scopus for weight loss trials reporting instruments published in the last 16 years.

RESULTS

A total of 46 significant behavioral and psychological predictors were identified, of which 32 instruments were finally selected. SF-36 questionnaire and Obesity Related Problem Scale for psychosocial health, TREMORE scale for motivation, Social Support Scale for support, Weight Efficacy Lifestyle Scale for self-efficacy and Body Shape Questionnaire for body image had moderate quality. Barriers to healthy eating questionnaire scale and Dutch Eating Behavior also had moderate quality.

CONCLUSION

Use of uniform instruments with optimum quality can benefit clinical and community-based researchers to generate reliable datasets.

Neighborhood environment perceptions associate with depression levels and cardiovascular risk among middle-aged and older adults: Data from the Washington, DC cardiovascular health and needs assessment

OBJECTIVES

Little is understood about associations between neighborhood characteristics and depression, a cardiovascular disease (CVD) risk factor, in diverse populations. We examined relationships between perceived/objective neighborhood characteristics, depression, and CVD markers within the Washington, DC CV Health/Needs Assessment, an evaluation among predominantly African-American (AA) adults in resource-limited DC communities.

METHOD

Factor analysis of overall neighborhood environment perception (NEP) identified three NEP sub-scores:1) violence; 2) physical/social environment; 3) social cohesion (higher score = more favorable perception). Objective neighborhood characteristics were measured by geospatially-derived scores of walkability, transportation, and crime. Depression was defined by the revised Center for Epidemiologic Studies Depression Scale (CESD-R). We used linear-regression modeling to examine neighborhood measures and CESD-R associations. To investigate a subsequent connection with CVD risk, we examined relationships between CESD-R and CVD-associated cytokines in a population subset.

RESULTS

Participants (N = 99; mean age = 59.06; 99% AA) had a mean CESD-R score = 5.8(SD = 8.88). In adjusted models, CESD-R scores decreased by 0.20 units (p = 0.01) for every overall NEP unit-increase. Perceived physical/social environment (β = -0.34, p = 0.04) and social cohesion (β = -0.82, p = 0.01) were related to CESD-R while perceived violence was not (β = -0.28, p = 0.1). Of objective neighborhood environment measures (i.e. walk, transit, bike, personal crime, and property crime scores), only property crime score was associated with depression (β = 4.99, p < 0.03). In population subset (n = 42), higher CESD-R associated with higher IL-1β (β = 21.25, p < 0.01) and IL-18 (β = 0.006, p = 0.01).

CONCLUSION

Favorable neighborhood perceptions are related to lower depressive symptoms in a predominantly AA cohort from Washington, DC resource-limited communities. Neighborhood perceptions appear to be strongly associated with depressive symptoms compared to objective characteristics. Increasing CESD-R scores were related to higher pro-inflammatory markers. Improving neighborhood perceptions may be beneficial to psychological well-being and CV health for urban minority residents.

Geospatial Analysis of Neighborhood Environmental Stress in Relation to Biological Markers of Cardiovascular Health and Health Behaviors in Women: Protocol for a Pilot Study

Background

Innovative analyses of cardiovascular (CV) risk markers and health behaviors linked to neighborhood stressors are essential to further elucidate the mechanisms by which adverse neighborhood social conditions lead to poor CV outcomes. We propose to objectively measure physical activity (PA), sedentary behavior, and neighborhood stress using accelerometers, GPS, and real-time perceived ecological momentary assessment via smartphone apps and to link these to biological measures in a sample of White and African American women in Washington, DC, neighborhoods.

Objective

The primary aim of this study is to test the hypothesis that living in adverse neighborhood social conditions is associated with higher stress-related neural activity among 60 healthy women living in high or low socioeconomic status neighborhoods in Washington, DC. Sub-aim 1 of this study is to test the hypothesis that the association is moderated by objectively measured PA using an accelerometer. A secondary objective is to test the hypothesis that residing in adverse neighborhood social environment conditions is related to differences in vascular function. Sub-aim 2 of this study is to test the hypothesis that the association is moderated by objectively measured PA. The third aim of this study is to test the hypothesis that adverse neighborhood social environment conditions are related to differences in immune system activation.

Methods

The proposed study will be cross-sectional, with a sample of at least 60 women (30 healthy White women and 30 healthy Black women) from Wards 3 and 5 in Washington, DC. A sample of the women (n=30) will be recruited from high-income areas in Ward 3 from census tracts within a 15% of Ward 3’s range for median household income. The other participants (n=30) will be recruited from low-income areas in Wards 5 from census tracts within a 15% of Ward 5’s range for median household income. Finally, participants from Wards 3 and 5 will be matched based on age, race, and BMI. Participants will wear a GPS unit and accelerometer and report their stress and mood in real time using a smartphone. We will then examine the associations between GPS-derived neighborhood variables, stress-related neural activity measures, and adverse biological markers.

Results

The National Institutes of Health Institutional Review Board has approved this study. Recruitment will begin in the summer of 2021.

Conclusions

Findings from this research could inform the development of multilevel behavioral interventions and policies to better manage environmental factors that promote immune system activation or psychosocial stress while concurrently working to increase PA, thereby influencing CV health.

International Registered Report Identifier (IRRID)

PRR1-10.2196/29191

When physical activity meets the physical environment: precision health insights from the intersection

BACKGROUND

The physical environment can facilitate or hinder physical activity. A challenge in promoting physical activity is ensuring that the physical environment is supportive and that these supports are appropriately tailored to the individual or group in question. Ideally, aspects of the environment that impact physical activity would be enhanced, but environmental changes take time, and identifying ways to provide more precision to physical activity recommendations might be helpful for specific individuals or groups. Therefore, moving beyond a "one size fits all" to a precision-based approach is critical.

MAIN BODY

To this end, we considered 4 critical aspects of the physical environment that influence physical activity (walkability, green space, traffic-related air pollution, and heat) and how these aspects could enhance our ability to precisely guide physical activity. Strategies to increase physical activity could include optimizing design of the built environment or mitigating of some of the environmental impediments to activity through personalized or population-wide interventions.

CONCLUSIONS

Although at present non-personalized approaches may be more widespread than those tailored to one person's physical environment, targeting intrinsic personal elements (e.g., medical conditions, sex, age, socioeconomic status) has interesting potential to enhance the likelihood and ability of individuals to participate in physical activity.

Associations between the built environment and dietary intake, physical activity, and obesity: A scoping review of reviews

There exists a large body of literature examining the association between built environment factors and dietary intake, physical activity, and weight status; however, synthesis of this literature has been limited. To address this gap, we conducted a scoping review of reviews and identified 74 reviews and meta-analyses that investigated the association between built environment factors and dietary intake, physical activity, and/or weight status. Results across reviews were mixed, with heterogeneous effects demonstrated in terms of strength and statistical significance; however, preliminary support was identified for several built environment factors. For example, quality of dietary intake appeared to be associated with the availability of grocery stores, higher levels of physical activity appeared to be most consistently associated with greater walkability, and lower weight status was associated with greater diversity in land-use mix. Overall, reviews reported substantial concern regarding methodological limitations and poor quality of existing studies. Future research should focus on improving study quality (e.g., using longitudinal methods, including natural experiments, and newer mobile sensing technologies) and consensus should be drawn regarding how to define and measure both built environment factors and weight-related outcomes.

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.

A randomized controlled trial of a theory-based weight-loss program for couples

OBJECTIVE

Weight gain occurs during marriage, yet obesity treatment is focused on individuals. Outcomes may be improved by targeting joint weight loss and the interpersonal milieu that fosters spousal interdependence. Self-determination theory (SDT) posits that autonomy-supportive environments (e.g., promote meaningful choice, minimize control) produce better health outcomes. This trial tested an SDT-informed weight-loss intervention intended to facilitate autonomy support in couples.

METHOD

Sixty-four couples were randomized to standard behavioral weight loss (BWL) that couples attended together or to a SDT-informed weight-loss intervention (SDT-WL) that aimed to bolster autonomy support (AS). Groups met weekly for 6 months with assessments at 0, 3, 6, and 12 months.

RESULTS

Percent weight loss at 6 and 12 months was 10.4% ± 6.5% and 9.2% ± 8.2%. No differences were observed between the BWL and SDT-WL conditions in percent weight loss or changes in AS. Across conditions, higher baseline AS predicted greater weight loss at 6 and 12 months (ps <.001). Increases in AS over time predicted greater weight loss at 6 and 12 months (ps ≤ .02). Post hoc moderation analysis indicated that only participants with low (but not high) baseline AS achieved greater gains in AS at 12 months in SDT-WL than in the BWL conditions (p < .02).

CONCLUSIONS

Although no differences were found between conditions on weight loss or changes in autonomy support behavior, autonomy support from one's spouse predicted weight loss in both couples-based weight-loss approaches. For couples with low levels of AS, an SDT-informed approach was effective at increasing this desirable interpersonal behavior. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

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.

The neighborhood social environment and physical activity: a systematic scoping review

BACKGROUND

Investigating the association of the neighborhood social environment on physical activity is complex. A systematic scoping review was performed to (1) provide an inventory of studies assessing the influence of the neighborhood social environment on physical activity since 2006; (2) describe methodologies employed; and (3) formulate recommendations for the field.

METHODS

Two databases were searched using terms related to 'physical activity,' 'neighborhood,' and 'social environment' in January 2017. Eligibility criteria included: 1) physical activity as an outcome; 2) neighborhood social environment as a predictor; 3) healthy population (without diagnosed clinical condition or special population); 4) observational or experimental design. Of 1352 studies identified, 181 were included. Textual data relevant to the social environment measurement and analysis were extracted from each article into qualitative software (MAXQDA) and coded to identify social environmental constructs, measurement methods, level of measurement (individual vs. aggregated to neighborhood), and whether authors explicitly recognized the construct as the social environment. The following measures were generated for each construct: number of unique measurements; % of times measured at an aggregate level; % of times authors referred to the construct as the social environment. Social environmental constructs were then grouped into larger descriptive dimensions.

RESULTS/FINDINGS

Fifty-nine social environmental constructs were identified and grouped into 9 dimensions: Crime & Safety (n = 133 studies; included in 73% of studies); Economic & Social Disadvantage (n = 55, 33%); Social Cohesion & Capital (n = 47, 26%); Social Relationships (n = 22, 12%); Social Environment (n = 16, 9%); Disorder & Incivilities (n = 15, 8%); Sense of Place/Belonging (n = 8, 4%); Discrimination/Segregation (n = 3, 2%); Civic Participation & Engagement (n = 2, 1%). Across all articles, the social environment was measured using 176 different methods, was measured at an aggregate-level 38% of the time, and referred to as the social environment 23% of the time.

CONCLUSIONS

Inconsistent terminology, definitions, and measurement of the social environment and the lack of explicit language identifying constructs as the social environment make it challenging to compare results across studies and draw conclusions. Improvements are needed to increase our understanding of social environmental correlates and/or determinants of physical activity and facilitate cross-disciplinary conversations necessary to effectively intervene to promote physical activity.

TRIAL REGISTRATION

PROSPERO CRD42017059580.

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.

Does the built environment influence the effectiveness of behavioral weight management interventions?

Outcomes of behavioral lifestyle interventions for promoting weight loss vary widely across participants. The effectiveness of a weight management intervention may depend on a person's environmental context. This study compared short- and longer-term effects of a structured nationwide weight management program for people living in neighborhoods with different levels of walkability and different access to recreational places (parks, fitness facilities). Drawing on the health production model, we tested competing hypotheses for whether treatment effects of the program complement environmental supports or substitute for environmental constraints. We studied the US Department of Veterans Affairs (VA) MOVE! weight management program using VA electronic heath record data (2009-2014) and a difference-in-differences design with an inverse propensity score matched comparison group. A total of 114,256 program participants and 498,494 non-participants comprised the sample. Built environment features were measured within one-mile of each person's home. We estimated program effects on body mass index (BMI) for subgroups with different built environments at 6-, 12-, 18-, and 24-month follow-up using linear regressions with person and year fixed effects. At 6 months, the program reduced BMI by 0.4-0.6 kg/m2 among men and 0.3-0.5 kg/m2 among women. The effect diminished at 12, 18, and 24 months. The program effect did not vary significantly across subgroups with different walkability, park access, or fitness facility access. The MOVE! program was not sensitive to environmental context. Results did not lend support to either hypothesis that the MOVE! program complements or substitutes for a person's built environment to affect weight management outcomes.

Innovation to Create a Healthy and Sustainable Food System: A Science Advisory From the American Heart Association

Current dietary intakes of North Americans are inconsistent with the Dietary Guidelines for Americans . This occurs in the context of a food system that precludes healthy foods as the default choices. To develop a food system that is both healthy and sustainable requires innovation. This science advisory from the American Heart Association describes both innovative approaches to developing a healthy and sustainable food system and the current evidence base for the associations between these approaches and positive changes in dietary behaviors, dietary intakes, and when available, health outcomes. Innovation can occur through policy, private sector, public health, medical, community, or individual-level approaches and could ignite and further public-private partnerships. New product innovations, reformulations, taxes, incentives, product placement/choice architecture, innovative marketing practices, menu and product labeling, worksite wellness initiatives, community campaigns, nutrition prescriptions, mobile health technologies, and gaming offer potential benefits. Some innovations have been observed to increase the purchasing of healthy foods or have increased diversity in food choices, but there remains limited evidence linking these innovations with health outcomes. The demonstration of evidence-based improvements in health outcomes is challenging for any preventive interventions, especially those related to diet, because of competing lifestyle and environmental risk factors that are difficult to quantify. A key next step in creating a healthier and more sustainable food system is to build innovative system-level approaches that improve individual behaviors, strengthen industry and community efforts, and align policies with evidence-based recommendations. To enable healthier food choices and favorably impact cardiovascular health, immediate action is needed to promote favorable innovation at all levels of the food system.

Neighborhood Social Environment and Cardiovascular Disease Risk

Purpose of review

Limited physical activity (PA) and obesity are two primary risk factors for cardiovascular disease (CVD). Within a socio-ecological framework, neighborhood social environment may play a key role in influencing PA and obesity. However, the mechanisms underlying this relationship remain ambiguous. Our goals in this review are: (1) to summarize findings from the recent studies on neighborhood social environment in relation to PA and obesity as CVD risk factors, and (2) to briefly describe several innovative approaches to assessing neighborhood social environment.

Recent findings

Almost all recent studies assessed neighborhood social environment around residential areas. There were consistent associations between neighborhood social environment and PA and obesity, with some exceptions (indicating null associations or paradoxical associations). However, a focus on residential social environment may limit results because these studies did not account for any exposures occurring away from individuals' homes. Additionally, the majority of studies utilized a cross-sectional design, which limits our ability to make inferences regarding the causality of the association between social environment and PA or obesity as CV risk factors.

Summary

The majority of the studies on neighborhood social environment characterized factors around residential areas and assessed participant activity via self-reported surveys. Future research should leverage tools to account for the spatial mismatch between environmental exposures and outcomes by using global positioning systems, ecological momentary assessments, virtual neighborhood audits, and simulation modeling. These approaches can overcome major limitations by tracking individuals' daily activity and real-time perceptions of neighborhood social environments linked to CVD events.

Merging heterogeneous clinical data to enable knowledge discovery

The vision of precision medicine relies on the integration of large-scale clinical, molecular and environmental datasets. Data integration may be thought of along two axes: data fusion across institutions, and data fusion across modalities. Cross-institutional data sharing that maintains semantic integrity hinges on the adoption of data standards and a push toward ontology-driven integration. The goal should be the creation of query-able data repositories spanning primary and tertiary care providers, disease registries, research organizations etc. to produce rich longitudinal datasets. Cross-modality sharing involves the integration of multiple data streams, from structured EHR data (diagnosis codes, laboratory tests) to genomics, imaging, monitors and patient-generated data including wearable devices. This integration presents unique technical, semantic, and ethical challenges; however recent work suggests that multi-modal clinical data can significantly improve the performance of phenotyping and prediction algorithms, powering knowledge discovery at the patient- and population-level.

Short-Term Effects of Healthy Eating Pattern Cycling on Cardiovascular Disease Risk Factors: Pooled Results from Two Randomized Controlled Trials

Adherence to healthy eating patterns (HEPs) is often short-lived and can lead to repetitive attempts of adopting—but not maintaining—HEPs. We assessed effects of adopting, abandoning, and readopting HEPs (HEP cycling) on cardiovascular disease risk factors (CVD-RF). We hypothesized that HEP cycling would improve, worsen, and again improve CVD-RF. Data were retrospectively pooled for secondary analyses from two randomized, crossover, controlled feeding trials (n = 60, 52 ± 2 years, 30.6 ± 0.6 kg/m²) which included two 5–6 week HEP interventions (Dietary Approaches to Stop Hypertension-style or Mediterranean-style) separated by a four-week unrestricted eating period. Ambulatory and fasting blood pressures (BP), fasting serum lipids, lipoproteins, glucose, and insulin were measured before and during the last week of HEP interventions. Fasting systolic BP and total cholesterol decreased (−6 ± 1 mm Hg and −19 ± 3 mg/dL, respectively, p < 0.05), returned to baseline, then decreased again (−5 ± 1 mm Hg and −13 ± 3 mg/dL, respectively, p < 0.05) when adopting, abandoning, and readopting a HEP; magnitude of changes did not differ. Ambulatory and fasting diastolic BP and high-density lipoprotein cholesterol concentrations followed similar patterns; glucose and insulin remained unchanged. Low-density lipoprotein cholesterol concentrations decreased with initial adoption but not readoption (−13 ± 3 and −6 ± 3, respectively, interaction p = 0.020). Healthcare professionals should encourage individuals to consistently consume a HEP for cardiovascular health but also encourage them to try again if a first attempt is unsuccessful or short-lived.

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.