Impact of built, social, and economic environments on adolescent obesity and related health behaviors

Place effects on adult obesity and cardiometabolic health: Evidence from a natural experiment

Despite considerable evidence on clustering of obesity within geographic areas causal estimates of place effects on cardiometabolic health, and their causal pathways, remain rare. This study utilizes a natural experiment based on the quasi-random assignment of military families to different installations to show that adults exposed to places with higher obesity prevalence have a greater likelihood of obesity and other downstream cardiometabolic conditions. We find no evidence to support shared environments as a causal pathway for these place effects, suggesting that alternate pathways such as social influence may be at play. We also provide the first real-world evidence on the effect of exogenous exposure to obesogenic places on theoretically-grounded social influence constructs, such as social norms and social networks. We find evidence of place effects on individuals' perceptions of descriptive norms and obesogenic composition of social networks, but not on injunctive and subjective norms. The mediating role of social influence in explaining place effects on cardiometabolic health should be examined further in future work.

The neighourhood obesogenic built environment characteristics (OBCT) index: Practice versus theory

BACKGROUND

Obesity is a key risk factor for major chronic diseases such as type 2 diabetes and cardiovascular diseases. To extensively characterise the obesogenic built environment, we recently developed a novel Obesogenic Built environment CharacterisTics (OBCT) index, consisting of 17 components that capture both food and physical activity (PA) environments.

OBJECTIVES

We aimed to assess the association between the OBCT index and body mass index (BMI) in a nationwide health monitor. Furthermore, we explored possible ways to improve the index using unsupervised and supervised methods.

METHODS

The OBCT index was constructed for 12,821 Dutch administrative neighbourhoods and linked to residential addresses of eligible adult participants in the 2016 Public Health Monitor. We split the data randomly into a training (two-thirds; n = 255,187) and a testing subset (one-third; n = 127,428). In the training set, we used non-parametric restricted cubic regression spline to assess index's association with BMI, adjusted for individual demographic characteristics. Effect modification by age, sex, socioeconomic status (SES) and urbanicity was examined. As improvement, we (1) adjusted the food environment for address density, (2) added housing price to the index and (3) adopted three weighting strategies, two methods were supervised by BMI (variable selection and random forest) in the training set. We compared these methods in the testing set by examining their model fit with BMI as outcome.

RESULTS

The OBCT index had a significant non-linear association with BMI in a fully-adjusted model (p<0.05), which was modified by age, sex, SES and urbanicity. However, variance in BMI explained by the index was low (<0.05%). Supervised methods increased this explained variance more than non-supervised methods, though overall improvements were limited as highest explained variance remained <0.5%.

DISCUSSION

The index, despite its potential to highlight disparity in obesogenic environments, had limited association with BMI. Complex improvements are not necessarily beneficial, and the components should be re-operationalised.

A natural experiment: The opening of a supermarket in a public housing community and impacts on children's dietary patterns

Objective

The aim of the present study is to utilize a natural experiment and examine changes in dietary patterns of predominantly low-income, racial and ethnic minority children who live in a public housing community following the opening of a new supermarket.

Methods

Data comes from the Watts Neighborhood Health Study (WNHS), an ongoing study in South Los Angeles, United States, that follows residents of Jordan Downs, a public housing community undergoing redevelopment. Surveys were administered to children aged 9-17 years (n = 297), as well as an adult in the household. The second baseline data collection was conducted June-December 2019, and follow-up was conducted June 2020-April 2021, shortly after the introduction of the new supermarket in January 2020. ANCOVA linear regression models were estimated to examine the association between children's proximity to the new supermarket with dietary outcomes at follow-up. Interactions with barriers to food access were also explored.

Results

Living close to the new supermarket was not significantly associated with dietary outcomes at follow-up. However, for children who lived in households with no vehicle access, living close to the new supermarket was associated with increased fruit and vegetable consumption, compared to children in the comparison group.

Conclusion

Proximity to the new supermarket was not associated with improved dietary outcomes among children unless they had transportation barriers. This adds to the growing body of literature that suggests that the effects of neighborhood food environments may be modified by individuals' mobility, and that comprehensive interventions are needed.

Place of Residence Is Associated with Dietary Intake and BMI-SDS in Children and Adolescents: Findings from the DONALD Cohort Study

We aimed to determine whether place of residence in the German urban food environment is associated with habitual dietary intake (energy, macronutrients, and food groups) and body mass index (standard deviation score of BMI and BMI-SDS). Our hypothesis was that place of residence may explain some variation in dietary intake and nutritional outcomes. For the cross-sectional analyses of DONALD study data, we grouped participants according to their geocoded residence in the north or south of Dortmund. We applied robust multi-level mixed effects regression models using residence as a predictor and (1) BMI-SDS or (2) dietary data (daily intake of energy (kcal), macronutrients (energy percentage), or food groups (g/1000 kcal)) as the outcome. Models were adjusted for age, sex, and household socio-economic status. An analysis was carried out on 1267 anthropometric measurements collected annually from 360 participants aged 6-18 years (935 3-day weighed dietary records from 292 participants) between 2014 and 2019. In the fully adjusted models, residence in the south was associated with a lower BMI-SDS (β = -0.42, p = 0.02), lower intake of sugar-sweetened beverages (β = -47.00, p = 0.04), and higher intake of vegetables (β = 11.13, p = 0.04). Findings suggest that the place of residence, beyond individuals' socio-economic statuses, may be a contributing factor to dietary quality.