Does unmeasured confounding influence associations between the retail food environment and body mass index over time? The Coronary Artery Risk Development in Young Adults (CARDIA) study

Associations between the neighbourhood food environment and food and drink purchasing in England during lockdown: A repeated cross-sectional analysis

INTRODUCTION

Evidence for the effect of neighbourhood food environment (NFE) exposures on diet in the UK is mixed, potentially due to exposure misclassification. This study used the first national COVID-19 lockdown in England as an opportunity to isolate the independent effects of the NFE exposure on food and drink purchasing, and assessed whether these varied by region.

METHODS

Transaction-level purchasing data for food and drink items for at-home (1,221 households) and out-of-home consumption (171 individuals) were available from the GB Kantar Fast Moving Consumer Goods Panel for London and the North of England. The study period included 23rd March to 10th May 2020 ('lockdown'), and the same period in 2019 for comparison. NFE exposures included food outlet density and proximity, and NFE composition within a 1 km network buffer around the home. Associations were estimated for both years separately, adjusted for individual and household characteristics, population density and area deprivation. Interaction terms between region and exposures were explored.

RESULTS

There were no consistent patterns of association between NFE exposures and food and drink purchasing in either time period. In 2019, there was some evidence for a 1.4% decrease in energy purchased from ultra-processed foods for each additional 500 m in the distance to the nearest OOH outlet (IR 0.986, 95% CI 0.977 to 0.995, p = 0.020). In 2020, there was some evidence for a 1.8% reduction in total take-home energy for each additional chain supermarket per km2 in the neighbourhood (IR 0.982, 95% CI 0.969, 0.995, p = 0.045). Region-specific effects were observed in 2019 only.

DISCUSSION

Findings suggest that the differences in exposure to the NFE may not explain differences in the patterns or healthiness of grocery purchasing. Observed pre-pandemic region-specific effects allude to the importance of geographical context when designing research and policy. Future research may assess associations for those who relied on their NFE during lockdown.

Change in the food environment and measured adiposity in adulthood in the Christchurch Health and development birth cohort, Aotearoa, New Zealand: A birth cohort study

This study investigated associations between change in the food environment and change in measured body mass index (BMI) and waist circumference (WC) in the Christchurch Health and Development Study (CHDS) birth cohort. Our findings suggest that cohort members who experienced the greatest proportional change towards better access to fast food outlets had the slightly larger increases in BMI and WC. Contrastingly, cohort members who experienced the greatest proportional change towards shorter distance and better access to supermarkets had slightly smaller increases in BMI and WC. Our findings may help explain the changes in BMI and WC at a population level.

Impact of Food Environments on Obesity Rates: A State-Level Analysis

Introduction

Limited access to healthy food in areas that are predominantly food deserts or food swamps may be associated with obesity. Other unhealthy behaviors may also be associated with obesity and poor food environments.

Methods

We calculated Modified Retail Food Environment Index (mRFEI) to assess food retailers. Using data collected from the Behavioral Risk Factor Surveillance System (BRFSS) survey, the NJ Department of Health (NJDOH), and the US Census Bureau, we conducted a cross-sectional analysis of the interaction of obesity with the food environment and assessed smoking, leisure-time physical activity (LPA), and poor sleep.

Results

There were 17.9% food deserts and 9.3% food swamps in NJ. There was a statistically significant negative correlation between mRFEI and obesity rate (Pearson's r -0.13, p < 0.001), suggesting that lack of access to healthy food is associated with obesity. Regression analysis was significantly and independently associated with increased obesity prevalence (adjusted R square 0.74 and p=0.008). Obesity correlated positively with unhealthy behaviors. Each unhealthy behavior was negatively correlated with mRFEI. The mean prevalence for smoking, LPA, and sleep <7 hours was 15.4 (12.5-18.6), 26.5 (22.5-32.3), and 37.3 (34.9-40.4), respectively.

Conclusion

Obesity tracks with food deserts and especially food swamps. It is also correlated with other unhealthy behaviors (smoking, LPA, and poor sleep).

An Indicator Measuring the Influence of the Online Public Food Environment: An Analytical Framework and Case Study

The online public food environment (OPFE) has had a considerable impact on people's lifestyles over the past decade; however, research on its exposure is sparse. The results of the existing research on the impact of the food environment on human health are inconsistent. In response to the lack of food elements in the definition of the food environment and the lack of a clear method to assess the health attributes and the impact degree of the food environment, we proposed a new analytical framework based on the latest disease burden research, combining the characteristics of China's current food environment, from the perspective of environmental science. We redefined the food environment and proposed that food and its physical space are two core elements of the food environment. Accordingly, we extracted four domains of characteristics to describe the basic components of the food environment. Using the sales records, we designed an approach by referring to the standard process of environmental health indicators, including the health attributes and the impact degree of the food environment, to measure the OPFE of takeaway food outlets. Further, we conducted a case study and extracted three domains of characteristics for more than 18,000 effective takeaway meals from 812 takeaway food outlets located in 10 administrative subdivisions in the Haidian District and Xicheng District of Beijing Municipality. The results showed that more than 60% of single meals sold by takeaway food outlets were considered as healthy, and only 15% of takeaway food outlets sold healthy meals exclusively. Additionally, there were significant differences in health effects among different types of food environments, and high-risk areas of different types of food environments can be spatially identified. Compared with the counting method in the availability of food environment, the proposed new approach can depict food environment characteristics not only in the macro-scale like the counting method but also in the meal-scale. The indicators could be useful for large-scale and long-term monitoring of food environmental changes due to their simple calculation and design depending on the food delivery platform.

The impact of the consumer and neighbourhood food environment on dietary intake and obesity-related outcomes: A systematic review of causal impact studies

BACKGROUND

The food environment has been found to impact population dietary behaviour. Our study aimed to systematically review the impact of different elements of the food environment on dietary intake and obesity.

METHODS

We searched MEDLINE, Embase, PsychInfo, EconLit databases to identify literature that assessed the relationship between the built food environments (intervention) and dietary intake and obesity (outcomes), published between database inception to March 26, 2020. All human studies were eligible except for those on clinical sub-groups. Only studies with causal inference methods were assessed. Studies focusing on the food environment inside homes, workplaces and schools were excluded. A risk of bias assessment was conducted using the CASP appraisal checklist. Findings were summarized using a narrative synthesis approach.

FINDINGS

58 papers were included, 55 of which were conducted in high-income countries. 70% of papers focused on the consumer food environments and found that in-kind/financial incentives, healthy food saliency, and health primes, but not calorie menu labelling significantly improved dietary quality of children and adults, while BMI results were null. 30% of the papers focused on the neighbourhood food environments and found that the number of and distance to unhealthy food outlets increased the likelihood of fast-food consumption and higher BMI for children of any SES; among adults only selected groups were impacted - females, black, and Hispanics living in low and medium density areas. The availability and distance to healthy food outlets significantly improved children's dietary intake and BMI but null results were found for adults.

INTERPRETATION

Evidence suggests certain elements of the consumer and neighbourhood food environments could improve populations dietary intake, while effect on BMI was observed among children and selected adult populations. Underprivileged groups are most likely to experience and impact on BMI. Future research should investigate whether findings translate in other countries.

Neighborhood Socioeconomic Environment and Risk of Type 2 Diabetes: Associations and Mediation Through Food Environment Pathways in Three Independent Study Samples

OBJECTIVE

We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: 1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); 2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and 3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract-level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of 1) fast-food restaurants and 2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural.

RESULTS

Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE-diabetes associations were mediated through food-environment pathways.

CONCLUSIONS

Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways.

Associations between online food outlet access and online food delivery service use amongst adults in the UK: a cross-sectional analysis of linked data

BACKGROUND

Online food delivery services facilitate 'online' access to food outlets that typically sell lenergy-dense nutrient-poor food. Greater online food outlet access might be related to the use of this purchasing format and living with excess bodyweight, however, this is not known. We aimed to investigate the association between aspects of online food outlet access and online food delivery service use, and differences according to customer sociodemographic characteristics, as well as the association between the number of food outlets accessible online and bodyweight.

METHODS

In 2019, we used an automated data collection method to collect data on all food outlets in the UK registered with the leading online food delivery service Just Eat (n = 33,204). We linked this with contemporaneous data on food purchasing, bodyweight, and sociodemographic information collected through the International Food Policy Study (analytic sample n = 3067). We used adjusted binomial logistic, linear, and multinomial logistic regression models to examine associations.

RESULTS

Adults in the UK had online access to a median of 85 food outlets (IQR: 34-181) and 85 unique types of cuisine (IQR: 64-108), and 15.1% reported online food delivery service use in the previous week. Those with the greatest number of accessible food outlets (quarter four, 182-879) had 71% greater odds of online food delivery service use (OR: 1.71; 95% CI: 1.09, 2.68) compared to those with the least (quarter one, 0-34). This pattern was evident amongst adults with a university degree (OR: 2.11; 95% CI: 1.15, 3.85), adults aged between 18 and 29 years (OR: 3.27, 95% CI: 1.59, 6.72), those living with children (OR: 1.94; 95% CI: 1.01; 3.75), and females at each level of increased exposure. We found no association between the number of unique types of cuisine accessible online and online food delivery service use, or between the number of food outlets accessible online and bodyweight.

CONCLUSIONS

The number of food outlets accessible online is positively associated with online food delivery service use. Adults with the highest education, younger adults, those living with children, and females, were particularly susceptible to the greatest online food outlet access. Further research is required to investigate the possible health implications of online food delivery service use.

Ultra-processed food consumption patterns among older adults in the Netherlands and the role of the food environment

PURPOSE

To describe the patterns of ultra-processed foods (UPFs) consumption in the Netherlands; to test if exposure to the food environment is associated with UPFs consumption; and if this association differed across educational levels and neighbourhood urbanisation.

METHODS

Cross-sectional study using 2015-data of 8104 older adults from the Dutch EPIC cohort. Proportion of UPFs consumption was calculated from a validated food-frequency questionnaire. Exposure to the food environment was defined as proximity and availability of supermarkets, fast-food restaurants, full-service restaurants, convenience stores, candy stores and cafés. Consumption of UPFs was expressed as both percentage of total grams and total kilocalories.

RESULTS

The study population was aged 70(± 10 SD) years and 80.5% was female. Average UPFs consumption was 17.8% of total food intake in grams and 37% of total energy intake. Those who consumed greater amounts of UPFs had a poorer overall diet quality. Adjusted linear regression models showed that closer proximity and larger availability to any type of food retailer was associated with lower UPFs consumption (both in grams and kilocalories). Somewhat stronger significant associations were found for proximity to restaurants (β = - 1.6%, 95% confidence interval (CI) = - 2.6; - 0.6), and supermarkets (β = - 2.2%, 95%CI = - 3.3; - 1.1); i.e., Individuals living within 500 m from the closest supermarket, as compared to 1500 m, had 2.6% less calories from UPFs. No differences were found on analyses stratified for urbanisation and education.

CONCLUSIONS

Using various measures of exposure to the food environment, we found that exposure to restaurants and supermarkets was associated with somewhat lower consumption of UPFs.

Socioeconomic inequalities in the food environment and body composition among school-aged children: a fixed-effects analysis

BACKGROUND

There is limited evidence regarding socioeconomic inequalities of exposure to the food environment and its contribution to childhood obesity.

METHODS

We used data from 4235 children from the Generation R Study, a large birth-cohort conducted in the city of Rotterdam, The Netherlands. We included 11,277 person-observations of body mass index (BMI) and 6240 person-observations of DXA-derived fat mass index (FMI) and fat-free mass index (FFMI) when children were between 4 and 14 years. We applied linear regression models to evaluate changes in the relative and absolute exposure of fast-food outlets, and the healthiness of the food environment within 400 m from home by maternal education. Furthermore, we used individual-level fixed-effects models to study changes in the food environment to changes in BMI, FMI and FFMI.

RESULTS

Children from lower educated mothers were exposed to more fast-food outlets at any time-point between the age of 4 and 14 years. Over a median period of 7.1 years, the absolute (0.6 fast-food outlet (95% CI: 0.4-0.8)) and relative (2.0%-point (95% CI: 0.7-3.4)) amount of fast-food outlets increased more for children from lower as compared to higher educated mothers. The food environment became more unhealthy over time, but no differences in trends were seen by maternal education level. Changes in the food environment were not associated with subsequent changes in BMI, FMI and FFMI. For children from lower educated mothers not exposed to fast-food at first, we found some evidence that the introduction of fast-food was associated with small increases in BMI.

CONCLUSIONS

Our findings provide evidence of widening inequalities in exposure to fast-food in an already poor food environment. Access to more fast-food outlets does not seem to have an additional impact on BMI in contemporary contexts with ubiquitous fast-food outlets.

Neighbourhood effects on obesity: scoping review of time-varying outcomes and exposures in longitudinal designs

CONTEXT AND OBJECTIVES

Neighbourhood effect research on obesity took off in the early 2000s and was composed of mostly cross-sectional observational studies interested in various characteristics of the built environment and the socioeconomic environment. To limit biases related to self-selection and life course exposures, many researchers apply longitudinal designs in their studies. Until now, no review has specifically and exclusively examined longitudinal studies and the specific designs of these studies. In this review, we intend to answer the following research question: how are the temporal measurements of contextual exposure and obesity outcomes integrated into longitudinal studies that explore how neighbourhood-level built and socioeconomic environments impact adult obesity?

DESIGN

A systematic search strategy was designed to address the research question. The search was performed in Embase, Web of Science and PubMed, targeting scientific papers published before 1 January 2018. The eligible studies reported results on adults, included exposure that was limited to neighbourhood characteristics at the submunicipal level, included an outcome limited to obesity proxies, and reported a design with at least two exposure measurements or two outcome measurements.

RESULTS

This scoping review identified 66 studies that fit the eligibility criteria. A wide variety of neighbourhood characteristics were also measured, making it difficult to draw general conclusions about associations between neighbourhood exposure and obesity. We applied a typology that classified studies by whether exposure and outcome were measured as varying or fixed. Using this typology, we found that 32 studies reported both neighbourhood exposure and obesity outcomes that were varying in time; 28 reported varying outcomes but fixed exposures; and 6 had fixed outcomes and varying exposures.

CONCLUSION

Our typology illustrates the variety of longitudinal designs that were used in the selected studies. In the light of our results, we make recommendations on how to better report longitudinal designs and facilitate comparisons between studies.

Assessing county-level determinants of diabetes in the United States (2003-2012)

Using data from the United States Behavioral Risk Factor Surveillance System (2003-2012; N = 3,397,124 adults), we estimated associations between prevalent diabetes and four county-level exposures (fast food restaurant density, convenience store density, unemployment, active commuting). All associations confirmed our a priori hypotheses in conventional multilevel analyses that pooled across years. In contrast, using a random-effects within-between model, we found weak, ambiguous evidence that within-county changes in exposures were associated with within-county change in odds of diabetes. Decomposition revealed that the pooled associations were largely driven by time-invariant, between-county factors that may be more susceptible to confounding versus within-county associations.

Associations of Unhealthy Food Environment With the Development of Coronary Artery Calcification: The CARDIA Study

Background

While prior studies have linked the neighborhood environment and development of subclinical atherosclerosis, it is unknown whether living in neighborhoods with greater availability of “unhealthy” food outlets (fast‐food chain restaurants and convenience stores) is associated with risk of developing coronary artery calcification (CAC).

Methods and Results

We included 2706 CARDIA study (Coronary Artery Risk Development in Young Adults) participants who underwent CAC measurement during follow‐up years 15 (2000–2001), 20 (2005–2006), and 25 (2010–2011). Neighborhood features examined included percentage of all food outlets that were convenience stores and fast‐food chain restaurants within a 3‐km Euclidean buffer distance from each participant's residence. Econometric fixed effects models, which by design control for all time‐invariant covariates, were used to model the longitudinal association between simultaneous within‐person change in percentage food outlet and change in CAC. At baseline (year 15), 9.7% of participants had prevalent CAC. During 10 years of follow‐up, 21.1% of participants developed CAC. Each 1‐SD increase in percentage of convenience stores was associated with a 1.34 higher odds of developing CAC (95% CI: 1.04, 1.72) after adjusting for individual‐ and neighborhood‐level covariates; however, there was no significant association between increased percentage of fast‐food chain restaurants and developing CAC (odds ratio=1.15; 95% CI: 0.96, 1.38). There were no significant associations between increases in either food outlet percentage and progression of CAC.

Conclusions

Our findings suggest that increases in the relative availability of convenience stores in participants' neighborhoods is related to the development of CAC over time.

Comparing Different Residential Neighborhood Definitions and the Association Between Density of Restaurants and Home Cooking Among Dutch Adults

The definition of neighborhoods as areas of exposure to the food environment is a challenge in food environment research. We aimed to test the association of density of restaurants with home cooking using four different definitions of residential neighborhoods. We also tested effect modification by age, length of residency, education, and income. This innovative cross-sectional study was conducted in the Netherlands (N = 1245 adults). We calculated geographic information system-based measures of restaurant density using residential administrative neighborhood boundaries, 800 m and 1600 m buffers around the home and respondents' self-defined boundaries (drawn by the respondents on a map of their residential area). We used adjusted Poisson regression to test associations of restaurant density (tertiles) and the outcome "weekly consumption of home-cooked meals" (six to seven as compared to five days per week (day/week) or fewer). Most respondents reported eating home-cooked meals for at least 6 day/week (74.2%). Regardless of the neighborhood definition used, no association between food environment and home cooking was observed. No effect modification was found. Although exposure in terms of density of restaurants was different according to the four different neighborhood definitions, we found no evidence that the area under study influences the association between density of restaurants and home cooking among Dutch adults.

The Moderating Role of Self-Control and Financial Strain in the Relation between Exposure to the Food Environment and Obesity: The GLOBE Study

Low self-control and financial strain may limit individuals’ capacity to resist temptations in the local food environment. We investigated the moderating role of self-control and financial strain in the relation between the food environment and higher body weight. We used data from 2812 Dutch adults who participated in the population-based GLOBE study in 2014. Participants’ home addresses and the location of food retailers in 2013 were mapped using GIS. The density of fast food retailers and the totality of food retailers in Euclidean buffers of 250, 400 and 800 m around the home were linked to body mass index and overweight status. A higher density of fast food outlets (B (95% confidence interval (CI)) = −0.04 (−0.07; −0.01)) and the totality of food outlets (B (95% CI) = −0.01 (−0.01; −0.00)) were associated with a lower body mass index. Stratification showed that associations were strongest for those experiencing low self-control or great financial strain. For example, every additional fast food outlet was associated with a 0.17 point lower BMI in those with great financial strain, while not significantly associated with BMI in those with no financial strain. In conclusion, we did find support for a moderating role of self-control and financial strain, but associations between the food environment and weight status were not in the expected direction.

Differences in the Neighborhood Retail Food Environment and Obesity Among US Children and Adolescents by SNAP Participation

OBJECTIVE

The goal of this study was to understand the association between children's neighborhood food access and overweight/obesity in a national sample of US households, and whether this association differs by Supplemental Nutrition Assistance Program (SNAP) participation or household purchases.

METHODS

Data were obtained from the National Household Food Acquisition and Purchase Survey (2012-2013; n = 3,748 children aged 2 to 18 years). Logistic regression was used to examine associations between neighborhood retail food access (≤1 mile from home), food purchases (including sugary beverages), and overweight/obesity, stratified by SNAP status (1,720 participants, 453 eligible nonparticipants, 1,575 SNAP ineligible). Store types included supermarkets/grocery, combination grocery/other (independent drug, dollar, and general stores), convenience, fast food, and non-fast food restaurants.

RESULTS

Odds of childhood overweight/obesity (OR [95% CI]) were higher with greater access to combination grocery/other stores overall (1.10 [1.03-1.17]) and for children in SNAP (1.14 [1.05-1.24]). Eligible non-SNAP children had higher odds of overweight/obesity with greater access to convenience stores (1.11 [1.04-1.18]). The average child lived in a household with 6.3% of total spending at food outlets on sugary beverages (SNAP: 8.3%, eligible non-SNAP: 7.7%, SNAP ineligible: 5.5%).

CONCLUSIONS

Greater neighborhood access to combination grocery/other stores is associated with higher obesity prevalence for children overall and those in SNAP.

Is adolescent body mass index and waist circumference associated with the food environments surrounding schools and homes? A longitudinal analysis

BACKGROUND

There has been considerable interest in the role of access to unhealthy food options as a determinant of weight status. There is conflict across the literature as to the existence of such an association, partly due to the dominance of cross-sectional study designs and inconsistent definitions of the food environment. The aim of our study is to use longitudinal data to examine if features of the food environment are associated to measures of adolescent weight status.

METHODS

Data were collected from secondary schools in Leeds (UK) and included measurements at school years 7 (ages 11/12), 9 (13/14), and 11 (15/16). Outcome variables, for weight status, were standardised body mass index and standardised waist circumference. Explanatory variables included the number of fast food outlets, supermarkets and 'other retail outlets' located within a 1 km radius of an individual's home or school, and estimated travel route between these locations (with a 500 m buffer). Multi-level models were fit to analyse the association (adjusted for confounders) between the explanatory and outcome variables. We also examined changes in our outcome variables between each time period.

RESULTS

We found few associations between the food environment and measures of adolescent weight status. Where significant associations were detected, they mainly demonstrated a positive association between the number of amenities and weight status (although effect sizes were small). Examining changes in weight status between time periods produced mainly non-significant or inconsistent associations.

CONCLUSIONS

Our study found little consistent evidence of an association between features of the food environment and adolescent weight status. It suggests that policy efforts focusing on the food environment may have a limited effect at tackling the high prevalence of obesity if not supported by additional strategies.

Food Swamps Predict Obesity Rates Better Than Food Deserts in the United States

This paper investigates the effect of food environments, characterized as food swamps, on adult obesity rates. Food swamps have been described as areas with a high-density of establishments selling high-calorie fast food and junk food, relative to healthier food options. This study examines multiple ways of categorizing food environments as food swamps and food deserts, including alternate versions of the Retail Food Environment Index. We merged food outlet, sociodemographic and obesity data from the United States Department of Agriculture (USDA) Food Environment Atlas, the American Community Survey, and a commercial street reference dataset. We employed an instrumental variables (IV) strategy to correct for the endogeneity of food environments (i.e., that individuals self-select into neighborhoods and may consider food availability in their decision). Our results suggest that the presence of a food swamp is a stronger predictor of obesity rates than the absence of full-service grocery stores. We found, even after controlling for food desert effects, food swamps have a positive, statistically significant effect on adult obesity rates. All three food swamp measures indicated the same positive association, but reflected different magnitudes of the food swamp effect on rates of adult obesity (p values ranged from 0.00 to 0.16). Our adjustment for reverse causality, using an IV approach, revealed a stronger effect of food swamps than would have been obtained by naïve ordinary least squares (OLS) estimates. The food swamp effect was stronger in counties with greater income inequality (p < 0.05) and where residents are less mobile (p < 0.01). Based on these findings, local government policies such as zoning laws simultaneously restricting access to unhealthy food outlets and incentivizing healthy food retailers to locate in underserved neighborhoods warrant consideration as strategies to increase health equity.