Does Effectiveness of Weight Management Programs Depend on the Food Environment?

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 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.

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.

Heart Health and Behavior Change in HIV-Infected Individuals

Management of cardiovascular disease risk requires many lifestyle changes involving diet, smoking, and exercise. Individuals with arterial plaque are encouraged to adopt these changes to promote longevity through a variety of interventions. This study examined behavioral changes in response to the standard of care after detection of arterial plaque, specifically among HIV-infected cocaine users. 127 individuals (HIV - COC - n = 43, HIV + COC - n = 19, HIV + COC + n = 35, HIV - COC + n = 30) were followed after a standard of care intervention and assessed 1 and 2 years later on a variety of lifestyle (diet, exercise, smoking) and physiological (blood pressure, body mass index, number of arterial plaques) outcomes. Arterial plaque was found to increase over time (b = 0.003, SE = 0.002, p = .031), and a composite measure of cardiovascular disease risk did not change (b = - 0.004, SE = 0.01, p = .548). Following provision of a standard of care cardiovascular risk reduction intervention, important health behaviors related to CVD risk were resistant to change among both those HIV-infected and uninfected and among cocaine users and non-users.

Differences in the sugar content of fast-food products across three countries

OBJECTIVE

To compare the sugar content of items at four multinational fast-food chains, across three countries.

DESIGN

Total sugar (g)/per serving was extracted from online nutrition information, and sugar/100 g serving was calculated. Foods were categorised as: breakfast sandwiches, burgers, sandwiches, desserts and condiments. Beverages were categorised as fountain, frozen or pre-packaged. Sugar (g) was compared across countries using linear mixed-effects models. Pairwise comparisons were performed with Tukey-Kramer adjustments.

SETTING

USA, Germany and Australia.

PARTICIPANTS

Burger King™ (Hungry Jack's™), Kentucky Fried Chicken™, McDonald's™ and Subway™.

RESULTS

Differences in total sugar/100 g or ml were observed across countries for burgers (n 104), desserts (n 110), sandwiches (n 178), pre-packaged beverages (n 36) and frozen beverages (n 72). Comparing identical items across countries (e.g. BigMacTM from McDonalds in USA, Germany and Australia), burgers (n 10 available in all three countries) had lower sugar content in Australia (3·4 g/100 g) compared with the USA (4·7 g/100 g, P = 0·02) or Germany (4·6 g/100 g, P = 0·04), yet no differences were observed in other food categories. Comparing the same beverages across countries (e.g. chocolate shake from Burger King), frozen beverages (n 4 available in all three countries) had lower sugar content in Australia (14·2 g/100 ml), compared with the USA (20·3 g/100 ml, P = 0·0005) or Germany (17·8 g/100 ml, P = 0·0148), yet no differences were observed in other beverage categories.

CONCLUSIONS

Heterogeneity in fast-food sugar content across countries suggests that reductions are possible and should be implemented to reduce health risks associated with excess added sugar intake.

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.