Food Environment Exposure Research Articles

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

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. 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. 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. 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.

Abstract 19: Time-Varying Exposure to Food Retailers and Cardiovascular Disease Incidence and Mortality in the Netherlands: A Nationwide Prospective Cohort Study

Background: The food environment is suggested as a risk factor of cardiovascular disease (CVD), but current evidence is inconsistent and does not account for changes in the food environment. We aimed to explore if time-varying exposure to the food environment was associated with hospitalisation and mortality due to total and specific types of CVD in The Netherlands. We hypothesized that favourable time-varying trends in food environment exposure would be associated with decreased risk of CVD, stroke, heart failure (HF), and coronary heart disease (CHD) morbidity and mortality among the Dutch general population. Methods: A prospective cohort study was performed among all Dutch residents aged 35+ years who did not change residence in 2002-2018 without CVD in 2004, identified through registry data from Statistics Netherlands (n=4,641,435; 51.3% female, 91.2% Dutch). Time-varying Food Environment Healthiness Index (FEHI) scores (range: -5 to 5) and time-varying Kernel density of six specific food retailers (food delivery outlets, fast food outlets, restaurants, local food shops, supermarkets and convenience stores) around the home location were based on bi-annual updates between 2004-2018. Hospitalisation and mortality due to overall CVD, stroke, HF, and CHD occurring between 2004 and 2020 were used as outcomes, based on hospital and death registries. Models were adjusted for age, sex, ethnic origin, household composition, income, marital status and neighbourhood urbanisation level and effect modification by age, sex, urbanization and income was studied. Results: Each unit increase in the FEHI, representing a 10% improvement, was associated with a lower hospitalisation and mortality of CVD (hospitalization Hazard Ratio (HR h )=0.90, 0.89-0.91, mortality Hazard Ratio (HR m )=0.85, 0.82-0.89), CHD (HR h =0.88, 0.85-0.91, HR m =0.80, 0.75-0.86), stroke (HR h =0.89, 0.84-0.93, HR m =0.89, 0.82-0.98), and HF (HR h =0.90, 0.84-0.96, HR m =0.84, 0.76-0.92). Increased density of local food shops, fast food outlets, supermarkets and convenience stores, and decreased density of food delivery outlets and restaurants were associated with a higher risk of CVD, CHD, stroke and HF incidence and mortality, albeit with small effect sizes. Stratified analyses suggest slightly stronger associations in highly urbanized areas, younger adults and those with higher incomes. Conclusions: Favourable trends in time-varying food retailer exposure were associated with a risk reduction in CVD hospitalisation and mortality, in particular in urbanized areas and for younger adults and those with higher incomes.

Global positioning system-based food environment exposures, diet-related, and cardiometabolic health outcomes: a systematic review and research agenda

BackgroundGeographic access to food may affect dietary choices and health outcomes, but the strength and direction of associations may depend on the operationalization of exposure measures. We aimed to systematically review the literature on up-to-date evidence on the association between food environment exposures based on Global Positioning System (GPS) and diet-related and cardiometabolic health outcomes.MethodsThe databases PubMed, Embase.com, APA PsycInfo (via Ebsco), Cinahl (via Ebsco), the Web of Science Core Collection, Scopus, and the International Bibliography of the Social Sciences (via ProQuest) were searched from inception to October 31, 2022. We included studies that measured the activity space through GPS tracking data to identify exposure to food outlets and assessed associations with either diet-related or cardiometabolic health outcomes. Quality assessment was evaluated using the criteria from a modified version of the Newcastle–Ottawa Scale (NOS) for cross-sectional studies. We additionally used four items from a quality assessment tool to specifically assess the quality of GPS measurements.ResultsOf 2949 studies retrieved, 14 studies fulfilled our inclusion criteria. They were heterogeneous and represent inconsistent evidence. Yet, three studies found associations between food outlets and food purchases, for example, more exposure to junk food outlets was associated with higher odds of junk food purchases. Two studies found associations between greater exposure to fast food outlets and higher fast food consumption and out of three studies that investigated food environment in relation to metabolic outcomes, two studies found that higher exposure to an unhealthy food environment was associated with higher odds of being overweight.ConclusionsThe current and limited evidence base does not provide strong evidence for consistent associations of GPS-based exposures of the food environment with diet-related and cardiometabolic health outcomes.

Food Environments Within and Outside of Schools Play a Critical Role in Curtailing the Rise in Obesity among School-Aged Children over Time

BackgroundSound evidence for effective community-based strategies is needed to curtail upward trends in childhood obesity in the United States (US). ObjectivesThe aim of the study was to assess the association between school and community food environments and the prevalence of obesity over time. MethodsData were collected from K–12 schools in 4 low-income New Jersey cities in the US. School-level obesity prevalence, calculated from nurse-measured heights and weights at 4 time points, was used as the outcome variable. Data on the school food environment (SFE) measured the healthfulness of school lunch and competitive food offerings annually. The community food environment (CFE), i.e., the number of different types of food outlets within 400 m of schools, was also captured annually. The count and presence of food outlets likely to be frequented by students were calculated. Exposure to composite environment profiles both within schools and in communities around schools was assessed using latent class analysis. Data from 106 schools were analyzed using multilevel linear regression. ResultsThe prevalence of obesity increased from 25% to 29% over the course of the study. Obesity rates were higher in schools that had nearby access to a greater number of limited-service restaurants and lower in schools with access to small grocery stores and upgraded convenience stores participating in initiatives to improve healthful offerings. Interaction analysis showed that schools that offered unhealthier, competitive foods experienced a faster increase in obesity rates over time. Examining composite food environment exposures, schools with unhealthy SFEs and high-density CFEs experienced a steeper time trend (β = 0.018, P < 0.001) in obesity prevalence compared to schools exposed to healthy SFE and low-density CFEs. ConclusionsFood environments within and outside of schools are associated with differential obesity trajectories over time and can play an important role in curtailing the rising trends in childhood obesity.

A longitudinal assessment of racial and ethnic inequities in food environment exposure and retail market concentration.

This paper assesses trends in food environment and market concentration and racial and ethnic inequities in food environment exposure and food retail market concentration at the US census tract level from 2000 to 2019. Establishment-level data from the National Establishment Time Series were used to measure food environment exposure and food retail market concentration. We linked that dataset to race, ethnicity and social vulnerability information from the American Community Survey and the Agency for Toxic Substances and Disease Registry. A geospatial hot-spot analysis was conducted to identify relatively low and high healthy food access clusters based on the modified Retail Food Environment Index (mRFEI). The associations were assessed using two-way fixed effects regression models. Census tracts spanning all US states. 69 904 US census tracts. The geospatial analysis revealed clear patterns of areas with high and low mRFEI values. Our empirical findings point to disparities in food environment exposure and market concentration by race. The analysis shows that Asian Americans are likelier to live in neighbourhoods with a low food environment exposure and low retail market concentration. These adverse effects are more pronounced in metro areas. The robustness analysis for the social vulnerability index confirms these results. US food policies must address disparities in neighbourhood food environments and foster a healthy, profitable, equitable and sustainable food system. Our findings may inform equity-oriented neighbourhood, land use and food systems planning. Identifying priority areas for investment and policy interventions is essential for equity-oriented neighbourhood planning.

Adult food choices in association with the local retail food environment and food access in resource-poor communities: a scoping review

BackgroundThere is a growing body of research on local retail food environments globally in both urban and rural settings. Despite this, little research has been conducted on adult food choices, local retail environments, and healthy food access in resource-poor communities. The purpose of this study is therefore to provide an overview of the evidence on adult food choices (measured as dietary intake) in association with the local retail food environment and food access in resource-poor communities (defined as low-income communities and/or households).MethodsWe searched nine databases for studies published from July 2005 to March 2022 and identified 2426 records in the primary and updated search. Observational studies, empirical and theoretical studies, focused on adults ≤ 65 years, published in English peer-reviewed journals, examining local retail food environments and food access, were included. Two independent reviewers screened identified articles using the selection criteria and data extraction form. Study characteristics and findings were summarized for all studies and relevant themes summarized for qualitative and mixed methods studies.ResultsA total of 47 studies were included in this review. Most studies were cross sectional (93.6%) and conducted in the United States of America (70%). Nineteen (40.4%) studies assessed the association between food choice outcomes and local retail food environment exposures, and evidence on these associations are inconclusive. Associations of certain food choice outcomes with healthy food retail environments were positive for healthy foods (in 11 studies) and unhealthy foods (in 3 studies). Associations of certain food choice outcomes with unhealthy retail food environment exposures were positive for unhealthy foods in 1 study and negative for healthy foods in 3 studies. In 9 studies, some of the food choice outcomes were not associated with retail food environment exposures. A healthy food store type and lower food prices were found to be major facilitators for healthy food access in resource-poor communities, while cost and transportation were the main barriers.ConclusionsMore research is needed on the local retail food environment in communities in low- and middle-income countries to develop better interventions to improve food choices and access to healthy foods in resource-poor communities.

Associations between the food environment and food and drink purchasing using large-scale commercial purchasing data: a cross-sectional study

BackgroundEvidence for an association between the local food environment, diet and diet-related disease is mixed, particularly in the UK. One reason may be the use of more distal outcomes such as weight status and cardiovascular disease, rather than more proximal outcomes such as food purchasing. This study explores associations between food environment exposures and food and drink purchasing for at-home and out-of-home (OOH) consumption.MethodsWe used item-level food and drink purchase data for London and the North of England, UK, drawn from the 2019 Kantar Fast Moving Consumer Goods panel to assess associations between food environment exposures and household-level take-home grocery (n=2,118) and individual-level out-of-home (n=447) food and drink purchasing. Density, proximity and relative composition measures were created for both supermarkets and OOH outlets (restaurants and takeaways) using a 1 km network buffer around the population-weighted centroid of households’ home postcode districts. Associations between food environment exposure measures and frequency of take-home food and drink purchasing, total take-home calories, calories from fruits and vegetables, high fat, salt and sugar products, and ultra-processed foods (UPF), volume of take-home alcoholic beverages, and frequency of OOH purchasing were modelled using negative binomial regression adjusted for area deprivation, population density, and individual and household socio-economic characteristics.ResultsThere was some evidence for an inverse association between distance to OOH food outlets and calories purchased from ultra-processed foods (UPF), with a 500 m increase in distance to the nearest OOH outlet associated with a 1.1% reduction in calories from UPF (IR=0.989, 95%CI 0.982–0.997, p=0.040). There was some evidence for region-specific effects relating to purchased volumes of alcohol. However, there was no evidence for an overall association between food environment exposures and take-home and OOH food and drink purchasing.ConclusionsDespite some evidence for exposure to OOH outlets and UPF purchases, this study finds limited evidence for the impact of the food environment on household food and drink purchasing. Nonetheless, region-specific effects regarding alcohol purchasing indicate the importance of geographical context for research and policy.

Characterizing food environments near schools in California: A latent class approach simultaneously using multiple food outlet types and two spatial scales

It is challenging to evaluate associations between the food environment near schools with either prevalence of childhood obesity or with socioeconomic characteristics of schools. This is because the food environment has many dimensions, including its spatial distribution. We used latent class analysis to classify public schools in urban, suburban, and rural areas in California into food environment classes based on the availability and spatial distribution of multiple types of unhealthy food outlets nearby. All urban schools had at least one unhealthy food outlet nearby, compared to seventy-two percent of schools in rural areas did. Food environment classes varied in the quantity of available food outlets, the relative mix of food outlet types, and the outlets’ spatial distribution near schools. Regardless of urbanicity, schools in low-income neighborhoods had greater exposure to unhealthy food outlets. The direction of associations between food environment classes and school size, type, and race/ethnic composition depends on the level of urbanicity of the school locations. Urban schools attended primarily by African American and Asian children are more likely to have greater exposures to unhealthy food outlets. In urban and rural but not suburban areas, schools attended primarily by Latino students had more outlets offering unhealthy foods or beverages nearby. In suburban areas, differences in the spatial distribution of food outlets indicates that food outlets are more likely to cluster near K-12 schools and high schools compared to elementary schools. Intervention design and future research need to consider that the associations between food environment exposures and school characteristics differ by urbanicity.

Geospatial Food Environment Exposure and Obesity among Low Income Baltimore City Children: Associations Differ by Data Source and Processing Method

ABSTRACT Due to the high prevalence of childhood obesity, it is imperative to assess the relationship children’s access to food retailers and obesity. However, the influence of methodological decisions on these associations has been understudied. We examined relationships between different measures of geospatial food environment (using 4 data sources, and 2 data processing methods), and BMI in a sample of low-income children in Baltimore, Maryland. The choice of data sources and data processing methods produced large differences in estimates of children’s exposures to certain store types, such as supermarket-like stores, but had less impact on associations with BMI z-scores.

Spatial and Social Determinants of Household Food Environments in Central North Carolina

Abstract Objectives This study explores sociodemographic predictors of household food environments and tests the hypothesis that they are associated with community food environments. Methods Data are from the baseline visit of the Mothers &amp; Others study, an early life obesity prevention trial among 430 African-American mothers in central North Carolina. Healthy Homes Survey (HHS) data assessed household food availability, type and variety. Exploratory factor analysis (EFA) with oblique rotations consolidated 45 HHS variables into household food environment (HFE) types. From data retailer InfoUSA we obtained geocoded data containing all food outlets in the study area to assess proximity and density of food outlets near households. Linear regressions tested associations between maternal and household characteristics and HFE factor scores. Adjusted models tested the association between HFE factor scores, community food environment exposures, and sociodemographic interactions. Results EFA retained four HFE types: Factor 1, the healthiest, contained fresh fruits/vegetables (F/V), Factor 2 contained canned F/V, sweets, and salty snacks, Factor 3 contained frozen F/V, candy and sweetened drinks and Factor 4, the least healthful, contained (diet) soda, candy and sweets. SNAP participation was associated with a 23% (CI: –0.42, –0.04) z-score reduction for Factor 1 only. Each additional education level was associated with a 20% (CI: 0.10, 0.31) and 18% (CI: 0.07, 0.29) z-score increase for Factors 1 and 3, respectively. Each 1-unit increase in household size and maternal age accompanied a 6% (CI: 0.001, 0.11) and 3% (CI: 0.01, 0.05) respective z-score increase for Factor 3 only. Each additional dollar store within a 1-mile radius was associated with a 13.8% (CI: –0.22, –0.06) z-score reduction for Factor 3 while each mile closer to a grocery store accompanied a 12.1% (CI: 0.003, 0.24) z-score increase for Factor 3. Among households not receiving SNAP or WIC benefits, each mile closer to a grocery store accompanied a 27% (CI: 0.05, 0.47) and 30% (CI: 0.04, 0.55) respective z-score increase for Factor 1. Conclusions Healthy food environments are associated with local food outlet access and household characteristics. However, enrollment in nutrition assistance programs strongly modifies this relationship. Funding Sources National Institute of Child Health and Human Development.

The influence of the local food environment on diet following residential relocation: longitudinal results from RESIDential Environments (RESIDE).

To examine the associations of changes in the local food environment, individual behaviours and perceptions with changes in dietary intake, following relocation from an established neighbourhood to a new residential development. Spatial food environment exposure measures were generated relative to each participant's home address using the locations of food outlets at baseline (before moving house) and follow-up (1-2 years after relocation). Self-reported data on socio-demographics, self-selection, usual dietary intake, individual behaviours and perceptions of the local food environment were sourced from the RESIDential Environments (RESIDE) Project. Changes in spatial exposure measures, individual behaviours and perceptions with changes in dietary outcomes were examined using mixed linear models. Perth, Western Australia, 2003-2007. Adults (n 1200) from the RESIDE Project. Moving to a new residential development with more convenience stores and café restaurants around the home was significantly associated with an increase in unhealthy food intake (β = 0·049, 95 % CI 0·010, 0·089; β = 0·020, 95 % CI 0·007, 0·033) and was partially mediated by individual behaviours and perceptions. A greater percentage of healthy food outlets around the home following relocation was significantly associated with an increase in healthy food (β = 0·003, 95 % CI 0·001, 0·005) and fruit/vegetable intake (β = 0·002, 95 % CI 0·001, 0·004). Policy and planning may influence dietary intakes by restricting the number of convenience stores and other unhealthy food outlets and increasing the relative percentage of healthy food outlets.

A Smartphone App Combining Global Positioning System Data and Ecological Momentary Assessment to Track Individual Food Environment Exposure, Food Purchases, and Food Consumption: Protocol for the Observational FoodTrack Study.

BackgroundOur understanding of how food choices are affected by exposure to the food environment is limited, and there are important gaps in the literature. Recently developed smartphone-based technologies, including global positioning systems and ecological momentary assessment, enable these gaps to be filled.ObjectiveWe present the FoodTrack study design and methods, as well as participants’ compliance with the study protocol and their experiences with the app. We propose future analyses of the data to examine individual food environmental exposure taking into account the accessible food environment and individual time constraints; to assess people’s food choices in relation to food environmental exposure; and to examine the moderating role of individual and contextual determinants of food purchases and consumption.MethodsWe conducted a 7-day observational study among adults (25-45 years of age) living in urban areas in the Netherlands. Participants completed a baseline questionnaire, used an app (incorporating global positioning system tracking and ecological momentary assessment) for 7 days, and then completed a closing survey. The app automatically collected global positioning system tracking data, and participants uploaded information on all food purchases over the 7-day period into the app. Participants also answered questions on contextual or individual purchase-related determinants directly after each purchase. During the final 3 days of the study, the participants also uploaded data on fruit, vegetable, and snack consumption and answered similar ecological momentary assessment questions after each intake.ResultsIn total, 140 participants completed the study. More than half of the participants said they liked the app (81/140, 57.9%) and found it easy to use (75/140, 53.6%). Of the 140 participants, 126 (90.0%) said that they had collected data on all or almost all purchases and intakes during the 7-day period. Most found the additional ecological momentary assessment questions “easy to answer” (113/140, 80.7%) with “no effort” (99/140, 70.7%). Of 106 participants who explored their trips in the app, 20 (18.8%) had trouble with their smartphone’s global positioning system tracking function. Therefore, we will not be able to include all participants in some of the proposed analyses, as we lack these data. We are analyzing data from the first study aim and we expect to publish the results in the spring of 2020.ConclusionsParticipants perceived the FoodTrack app as a user-friendly tool. The app is particularly useful for observational studies that aim to gain insight into daily food environment exposure and food choices. Further analyses of the FoodTrack study data will provide novel insights into individual food environmental exposure, evidence on the individual food environment-diet interaction, and insights into the underlying individual and contextual mechanisms of food purchases and consumption.International Registered Report Identifier (IRRID)DERR1-10.2196/15283

What We Eat and Where We Work Is What We Become: Worksite Food Environment Exposure and Cardio-Metabolic Health among Employed Adults of Urban Delhi, India.

The incidence of metabolic syndrome (MS) which is a predictor of increasing CVD is on the rise among adults in urban India. The present study was designed to measure the prevalence of cardio metabolic risk (CMR) as per MS among employed adults in Delhi, India. Study design was cross-sectional. Anthropometric and biochemical measurements were carried out using standard techniques on apparently healthy males and females (n=455) working in various government and private organisations in Delhi, India after obtaining ethical permissions. It was found that more than one-third of the study population had MS (43.8%). A significant difference in the prevalence of MS was seen among males (34.7%) and females (57.5%, p<0.05). The prevalence of MS components was: abdominal obesity (54.3%), hypertriglyceridemia (61.9%), hypertension (56.6%), hypertriglyceridemia (27.4%), low HDL-c levels (63.7%). CMR (assessed from 0-5, where 0 means no MS). It was found that CMR increased with age (β: 0.01; 95% CI: 0.009,0.01; p=0.000) especially among females (β: 0.29; 95% CI: 0.19,0.38; p=0.000) who were consuming frequent non-vegetarian foods (β: 0.04; 95% CI: 0.01,0.09; p=0.07), had family history of diseases (β: 0.08; 95% CI: 0.01,0.18; p=0.09) and were sedentary workers (β: 0.05; 95% CI: 0.00,0.10; p=0.06). Unhealthy worksite food environment characterised by high fast food outlet density (β: 0.003; 95% CI: 0.00,0.007; p=0.04) in close proximity (β: 0.17; 95% CI: 0.36,0.00; p=0.05) to worksite were also associated with MS. There is a high prevalence of individual components of MS and overall prevalence of MS. Food environment and physical inactivity were two paramount factors resulting in increased CMR among the study population.

Interaction of DRD2/ANKK1 Taq1A Genotype with in-Store Retail Food Environment Exposures on Diet Quality in a Cohort of Quebec Adults

Background/Aims: Gene-environment interactions may be relevant for nutrition outcomes. This study assessed the interaction between DRD2/ANKK1 Taq1A genotype and exposures to in-store retail food environment on diet quality. Methods: CARTaGENE biobank data (n = 3,532) were linked to provincial food retail data. The Canadian adaptation of the Healthy Eating Index 2010 (HEI-C) was calculated from food frequency questionnaires. Generalized linear models adjusted for sociodemographic factors, anthropometrics, and energy intake were used to assess interactions between the Taq1A variant and retail food measures. Results: A significant inverse interaction was observed between Taq1A and ice cream store displays on HEI-C score (estimate: –15.46 [95% confidence interval (CI): –24.83, –6.10], p = 0.0012) where, among allele carriers, increasing exposure to ice cream displays was associated with a lower HEI-C score as compared to allele carriers with a lower exposure. A significant positive interaction between Taq1A and price of vegetables was also observed, where, among allele carriers, increasing exposure to a higher price was associated with a higher HEI-C score compared to allele carriers with exposure to a lower price (estimate: 2.46 [95% CI: 0.78, 4.14], p = 0.0041). The opposite pattern was observed among non-carriers. Conclusions: DRD2/ANKK1 Taq1A is associated with adaptive responses to ice cream displays and vegetable prices, suggesting a differential susceptibility to retail environment food cues.

Towards Improved Measurement of Individual Diet Behaviors and Food Environment Exposures: Resources from the National Collaborative on Childhood Obesity Research (P16-026-19)

ObjectivesSelection of appropriate and robust measures for capturing individual-level diet behaviors and the environmental factors that influence these behaviors is critical to advancing the knowledge base on effective approaches to promote health and well-being among children. However, selecting appropriate measures for a given research or evaluation purpose from the wide-ranging options available can be challenging. MethodsTo provide guidance to researchers and practitioners working with child and adolescent populations, the National Collaborative on Childhood Obesity Research (NCCOR) has developed a suite of resources, including the Measures Registry, User Guides, and eLearning Modules. ResultsThe Measures Registry is a free searchable database of nearly 1400 diet and physical activity measures relevant to childhood obesity research. The User Guides, introduced in 2017 to complement the Measures Registry, discuss critical issues in measurement and walk users through the process of selecting and implementing appropriate measures for their research and evaluation. In 2018, the Registry was viewed almost 13,000 times, and the User Guides were viewed over 25,000 times. More recently, eLearning modules were introduced to summarize critical considerations from the User Guides in an engaging, interactive manner. ConclusionsUse of this suite of resources can support selection of the most appropriate measures of diet behaviors and food environment exposures for a given study or evaluation and foster greater standardization of measures across studies. In addition to highlighting the resources, in this session, we will provide an overview of key challenges and considerations in selecting measures of diet behaviors and food environments and demonstrate the use of the resources, the Registry, User Guides and eLearning Modules, to show how to identify appropriate measures for a given research purpose. In the long-term, robust measurement of diet behaviors and food environments can strengthen the evidence base for intervening to improve children’s health and well-being. Funding SourcesNCCOR is funded by NIH, CDC, USDA, and RWJF. Additional funding to support the development of the NCCOR measurement resources has been provided by The JPB Foundation.

A Time-Based Objective Measure of Exposure to the Food Environment.

Exposure to food environments has mainly been limited to counting food outlets near participants’ homes. This study considers food environment exposures in time and space using global positioning systems (GPS) records and fast food restaurants (FFRs) as the environment of interest. Data came from 412 participants (median participant age of 45) in the Seattle Obesity Study II who completed a survey, wore GPS receivers, and filled out travel logs for seven days. FFR locations were obtained from Public Health Seattle King County and geocoded. Exposure was conceptualized as contact between stressors (FFRs) and receptors (participants’ mobility records from GPS data) using four proximities: 21 m, 100 m, 500 m, and ½ mile. Measures included count of proximal FFRs, time duration in proximity to ≥1 FFR, and time duration in proximity to FFRs weighted by FFR counts. Self-reported exposures (FFR visits) were excluded from these measures. Logistic regressions tested associations between one or more reported FFR visits and the three exposure measures at the four proximities. Time spent in proximity to an FFR was associated with significantly higher odds of FFR visits at all proximities. Weighted duration also showed positive associations with FFR visits at 21-m and 100-m proximities. FFR counts were not associated with FFR visits. Duration of exposure helps measure the relationship between the food environment, mobility patterns, and health behaviors. The stronger associations between exposure and outcome found at closer proximities (<100 m) need further research.

Linking environment and health data to investigate the association between access to unhealthy food and child BMI

IntroductionModelling the daily exposure environment provides evidence for policy and practice. However, the dose-response relationship between exposure to food environments and obesity has not been widely investigated. This study investigated whether increased retail food environment (RFE) exposure in children was associated with a larger body mass index (BMI).&#x0D; Objectives and ApproachIndividually tailored environmental exposures were calculated in a GIS for home and school locations, and modelled walking routes to and from school. Exposures were linked to individual level health data in the SAIL databank for a cohort of individuals aged 11-13 years from south Wales who had BMI measurements. A fully adjusted multilevel regression model was fitted to investigate the association of RFE exposure with BMI. Based on the distance individuals lived from school, we investigated differences between children who have the potential to walk to school (“walkers” lived 4.8km).&#x0D; ResultsHome exposure and exposure along the walk to school was significantly greater for children living in deprived catchments, compared with children living in affluent school catchments (t = -5.25, p&#x0D; Conclusion/ImplicationsIncreased BMI was associated with greater RFE exposure along the walk home from school. The findings suggest that the walk home from school should be the focus for developing interventions and policies to discourage unhealthy eating. Research should be undertaken to better understand child purchasing habits.

Linking household level GIS-generated environmental exposure scores with individual level anonymised health data

IntroductionThe dose-response relationship between exposure to food and BMI, has not been widely investigated. Furthermore, household-level, GIS-generated food environment exposure scores have not previously been linked with individual-level, anonymised BMI data. This study linked GIS-generated residential level environmental exposure scores with historical anonymised, health data held in the SAIL databank.&#x0D; Objectives and ApproachHousehold level GIS-generated exposure data for a region of about 1 million people were anonymised into SAIL using the ‘split-file’ method. All individuals living in the 633,884 homes at the time of data collection (2009-2010) were flagged using a population register. Separately, a cohort of 1147, 11-13 year old pupils were linked to their health data before joining to their environmental exposures. Two subgroups were established within the linked dataset: individuals living at 4.8km or less from the school they attended were assumed to walk to school (“walkers”) and pupils who lived further than 4.8km were flagged as “non-walkers”.&#x0D; ResultsA total of 916 pupils (80%) were successfully linked to the population register. The BMIs were collected in 2009-2010, but more recent data is likely to have a greater proportion of successful links (more recently, 97% of individuals and their health data have been linked to their home and exposures in SAIL). Erroneous BMIs were removed (n=33, 2.9%). Anonymised exposure data were linked with the remaining 883 (77%) individuals. The dataset contained 352 males (39.9%) and 531 females (60.1%); of these, 38% were from deprived areas and 62% lived in affluent areas. There were 431 (48.8%) pupils in the “walkers” group and 452 (51.2%) in the “non-walkers” group. In the “walkers” group, 13% were obese compared with 22% of “non-walkers” (chi-squared = 12.3, p &lt;0.05).&#x0D; Conclusion/ImplicationsWe generated novel regional exposures to combine with historical anonymised health data. Household and individual level linkage of environmental data to health cohorts contributed to the literature to help develop beneficial societal policies. We recommend routine national collections of height and weight for children to allow longitudinal retrospective analyses.

An Analytical Framework for Integrating the Spatiotemporal Dynamics of Environmental Context and Individual Mobility in Exposure Assessment: A Study on the Relationship between Food Environment Exposures and Body Weight.

In past studies, individual environmental exposures were largely measured in a static manner. In this study, we develop and implement an analytical framework that dynamically represents environmental context (the environmental context cube) and effectively integrates individual daily movement (individual space-time tunnel) for accurately deriving individual environmental exposures (the environmental context exposure index). The framework is applied to examine the relationship between food environment exposures and the overweight status of 46 participants using data collected with global positioning systems (GPS) in Columbus, Ohio, and binary logistic regression models. The results indicate that the proposed framework generates more reliable measurements of individual food environment exposures when compared to other widely used methods. Taking into account the complex spatial and temporal dynamics of individual environmental exposures, the proposed framework also helps to mitigate the uncertain geographic context problem (UGCoP). It can be used in other environmental health studies concerning environmental influences on a wide range of health behaviors and outcomes.

Daily exposure to the retail food environment and the association with child BMI

BackgroundThe dose-response relationship between exposure to food environments and obesity has not been widely investigated. This study examined whether increased retail food environment (RFE) exposure in children was associated with a larger body mass index (BMI).&#x0D; ObjectivesGenerate household level daily exposure to the RFE for children aged 11-13 years and link these environmental exposure with health data in an anonymised data safe haven.&#x0D; MethodsIndividually tailored environmental exposures were calculated in a GIS for home and school locations, and modelled walking routes to and from school. Local Authority food outlet data were used to generate the temporally accurate exposures. Exposures were linked to individual level health data in the SAIL databank for a cohort of individuals from south Wales aged 11-13 years, with BMI measurements. A fully adjusted multilevel regression model was fitted to investigate the association of RFE exposure with BMI.&#x0D; FindingsHome exposure and exposure along the walk to school was significantly greater for children living in deprived catchments, compared with affluent school catchments (t = -5.25, p&lt;0.05; t = -0.277, p&lt;0.05, respectively). The RFE exposure along the walk home was the only environmental exposure positively associated with a higher BMI (0.22, p&lt;0.05).&#x0D; ConclusionsIncreased BMI was associated with greater REF exposure along the walk home from school. The findings suggest that the walk home from school may be important for developing interventions and policies to discourage unhealthy eating. Research should be undertaken to better understand child purchasing habits.