Are some neighborhoods bad for your waistline? A test of neighborhood exposure effects on BMI

Association between neighborhood health behaviors and body mass index in Northern Norway: evidence from the Tromsø Study

AIM

The prevalence of overweight and obesity has risen rapidly worldwide, and the ongoing obesity pandemic is one of the most severe public health concerns in modern society. The average body mass index (BMI) of people living in Northern Norway has also steadily increased since the late 1970s. This study aimed to understand how individuals' health behavior is associated with the general health behavior of the people in their neighborhood.

METHODS

Using the population-based Tromsø Study, we examined the life course association between average leisure time physical activity at the neighborhood level and the BMI of individuals living in the same neighborhood. We used a longitudinal dataset following 25,604 individuals living in 33 neighborhoods and performed a linear mixed-effects analysis.

RESULTS

The results showed that participants living in neighborhoods whose residents were more physically active during their leisure time, were likely to have a significantly lower BMI (-0.9 kg/m², 95% CI -1.5 to -0.4). Also, individuals living in neighborhoods whose residents were doing mainly manual work, had significantly higher BMIs (0.7 kg/m², 95% CI 0.4-1.0).

CONCLUSIONS

Our results showed a strong association between the average leisure time physical activity level of neighborhood residents and the higher BMI levels of residents of the same neighborhood.

Heterogeneity in place effects on health: The case of time preferences and adolescent obesity

We leverage a natural experiment in combination with data on adolescents' time preferences to assess whether there is heterogeneity in place effects on adolescent obesity. We exploit the plausibly exogenous assignment of military servicemembers, and consequently their children, to different installations to identify place effects. Adolescents' time preferences are measured by a validated survey scale. Using the obesity rate in the assigned installation county as a summary measure of its obesity-related environments, we show that exposure to counties with higher obesity rates increases the likelihood of obesity among less patient adolescents but not among their more patient counterparts.

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

OBJECTIVE

This study aimed to estimate the effects of the built, social, and economic environments on adolescent obesity and related behaviors.

METHODS

Exploiting quasi-exogenous variation in military families' geographic location, this study estimated intent-to-treat models of the association between the assigned installation's county environments and adolescents' (mean age 13.5 years) self-reported and model-corrected BMI, overweight or obesity status, and self-reported diet and exercise. Three indices for the built, social, and economic environments characterized county-level environments (higher value implies more advantageous environments) based on 19 indicators. Multivariate linear and logistic models were estimated on the full sample (N = 1111) and on subsamples with greater exposure based on time (n = 682) and off-installation residence (n = 604).

RESULTS

Exposure to more advantageous built environments for more than 2 years was associated with lower probabilities of obesity (-0.18; 95% CI: -0.34 to -0.026) and overweight or obesity (-0.34; 95% CI: -0.56 to -0.12) and was associated with lower BMI z scores (-0.76; 95% CI: -1.45 to -0.02). Results for adolescents living off-installation were similar. More advantageous built environments were also associated with lower consumption of unhealthy foods, but not with physical activity. Social and economic environments were not associated with any outcomes.

CONCLUSIONS

The built environment, but not social and economic environments, was a strong predictor of adolescents' BMI, overweight or obesity status, and eating behaviors.

The effect of Internet access on body weight: Evidence from China

The Internet has significantly changed people's daily lives, including their health status. In this paper, we study the health implications of Internet access with a specific focus on body weight. We exploit an Internet speed upgrading project in China and conduct a difference-in-differences analysis, where the treatment intensity depends on cities' pre-existing Internet infrastructure conditions. We find consistent and robust evidence that increased Internet access reduces the incidence of being overweight. Regarding the mechanisms behind this result, we provide indirect evidence for the information channel, evidenced by improved health behaviors after the project: less engagement in risky health behaviors and increased participation in preventive health services and exercise. Internet diffusion also increases income, supporting the income channel through which the Internet can affect body weight.

Are the Slimmer More Wasteful? The Correlation between Body Mass Index and Food Wastage among Chinese Youth

With the economic growth and living standard improvement, food waste has become increasingly common among Chinese youth. To test whether body size affects the food waste performance of youth, we examined university students as representative of the Chinese youth and conducted a large-sample survey in 29 universities across 29 provinces. Based on 9192 questionnaires collected from Chinese college canteens, we found that body size was correlated with food waste. The smaller the body mass index (BMI) value, the higher the likelihood of plate waste, the higher the amount of waste, and the higher the ratio of food waste. Heterogeneity analyses revealed that BMI exerted a more significant impact on males than females, as well as a more substantial impact on northerners than southerners. Robust tests using other proxies to measure body size, robust regressions based on the new adjusted samples, and robust tests with an instrumental variable to overcome the endogenous issue suggested that the slimmer participants tended to be more wasteful. Hence, this study confirms that the slimmer youth tend to leave plate waste and waste more food per capita per meal. This study is the first attempt to analyze food wastage from the perspective of BMI in China to our best knowledge, and it provides a unique viewpoint for understanding young people’s food wastage.

Associations between Fast-Food Restaurants Surrounding Kindergartens and Childhood Obesity: Evidence from China

The prevalence of obesity among preschool children has risen dramatically due to the influx of Western fast food in China. In this study, we aimed to provide clear evidence on the associations between fast-food restaurants and childhood obesity. We collected and combined three unique cross-sectional datasets: physical fitness data, geographic information, and the financial data of each kindergarten. The two-stage least squares were used for empirical analyses. The final data including 75,730 children were from 785 kindergartens in 82 cities and 23 provinces in China in 2018. The mean age of participants was 4.94 ± 0.87; 34,249 (45.2%) females and 41,481 (54.8%) males. The number of fast-food restaurants within 1, 2, and 3 km radii had a significant and positive correlation with obesity, and this correlation decreased as the radius increased. Furthermore, the distance to the nearest fast-food restaurant had a significant and negative correlation with obesity. Western fast-food restaurants contributed more to obesity than the broader definition of fast-food restaurants. There was marked heterogeneity between urban and rural areas. Our findings documented that fast-food restaurants had a significant and positive association with childhood obesity, thus the restriction of fast-food restaurants surrounding kindergartens might be considered.

Does the built environment have independent obesogenic power? Urban form and trajectories of weight gain

OBJECTIVE

To determine whether selected features of the built environment can predict weight gain in a large longitudinal cohort of adults.

METHODS

Weight trajectories over a 5-year period were obtained from electronic health records for 115,260 insured patients aged 18-64 years in the Kaiser Permanente Washington health care system. Home addresses were geocoded using ArcGIS. Built environment variables were population, residential unit, and road intersection densities captured using Euclidean-based SmartMaps at 800-m buffers. Counts of area supermarkets and fast food restaurants were obtained using network-based SmartMaps at 1600, and 5000-m buffers. Property values were a measure of socioeconomic status. Linear mixed effects models tested whether built environment variables at baseline were associated with long-term weight gain, adjusting for sex, age, race/ethnicity, Medicaid insurance, body weight, and residential property values.

RESULTS

Built environment variables at baseline were associated with differences in baseline obesity prevalence and body mass index but had limited impact on weight trajectories. Mean weight gain for the full cohort was 0.06 kg at 1 year (95% CI: 0.03, 0.10); 0.64 kg at 3 years (95% CI: 0.59, 0.68), and 0.95 kg at 5 years (95% CI: 0.90, 1.00). In adjusted regression models, the top tertile of density metrics and frequency counts were associated with lower weight gain at 5-years follow-up compared to the bottom tertiles, though the mean differences in weight change for each follow-up year (1, 3, and 5) did not exceed 0.5 kg.

CONCLUSIONS

Built environment variables that were associated with higher obesity prevalence at baseline had limited independent obesogenic power with respect to weight gain over time. Residential unit density had the strongest negative association with weight gain. Future work on the influence of built environment variables on health should also examine social context, including residential segregation and residential mobility.