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

The moderating effect of access to food facilities and recreational activity space on mHealth multiple health behavior change intervention

OBJECTIVE

To evaluate whether the neighborhood social and built environment moderates response to a mobile health multiple health behavior change intervention targeting fruit/vegetable intake, sedentary behavior, and physical activity.

METHODS

Participants were 156 Chicago-residing adults with unhealthy lifestyle behaviors. Using linear mixed models, we evaluated whether access to food facilities (fast food restaurants and grocery stores) and recreational activity spaces (gyms and parks) moderated the difference in behavior change between the active intervention condition relative to control. Using spatial data analysis (cross K functions), we also assessed whether participants who achieved goal levels of behaviors ("responders") were more or less likely than those who did not achieve intervention goals ("non-responders") to reside near fast food restaurants, grocery stores, gyms, or parks.

RESULTS

According to linear mixed models, none of the neighborhood social and built environment factors moderated the difference in behavior change between the active intervention condition and the control condition (Likelihood Ratio (χ²[1] = 0.02-2.33, P-values > 0.05). Cross K functions showed that diet behavior change responders were more likely than non-responders to reside near fast food restaurants, but not grocery stores. The results for activity behavior change were more variable. Sedentary screen time responders were more likely to reside around recreational activity spaces than non-responders. Moderate-vigorous physical activity responders had greater and lesser clustering than non-responders around parks, dependent upon distance from the park to participant residence.

CONCLUSIONS

A complex relationship was observed between residential proximity to Chicago facilities and response to multiple health behavior change intervention. Replication across diverse geographic settings and samples is necessary.

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.

Role of Built Environments on Physical Activity and Health Promotion: A Review and Policy Insights

As urbanization and motorization continue worldwide, various health issues have emerged as a burden between individuals, families and governments at all levels. Under the prevalence of chronic disease, this review synthesizes research on the impact of the various built environments on the multiple health outcomes from a methodological and mechanistic perspective. Besides, it attempts to provide useful planning and policy implications to promote physical activity and health benefits. The finds show that: (1) Current literature has used a variety of dataset, methods, and models to examine the built environment-health benefit connections from the perspective of physical activity; (2) The prevalence of chronic diseases is inextricably linked to the built environment, and policy interventions related to physical activity and physical and mental wellbeing of urban residents should be emphasized; (3) The impact of the built environment on health is manifested in the way various elements of the physical environment guide the lifestyle of residents, thereby influencing physical activity and travel; (4) Given the changes that have occurred in the built environment during the current urban expansion, the link between urban planning and the public health sector should be strengthened in the future, and the relevant authorities should actively pursue policies that promote urban public health in order to improve the health of residents. Finally, it proposes potential policy insights for urban planning and development toward a healthier city and society.

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.