Measures Of Food Environment Research Articles

Associations of Neighborhood Food and Physical Activity Environments in Young Adulthood With Cardiovascular Health in Midlife: The CARDIA Study.

Adults who maintain ideal cardiovascular health (CVH) profiles up to midlife have lower risk of several chronic diseases and better quality of life. Some evidence suggests that individual-level exposures earlier in life shape midlife CVH, but the impact of neighborhood-level exposures over the life course remains understudied. Participants were 3017 Black and White men and women aged 18 to 30 years at baseline (1985-1986), recruited from Birmingham, Alabama; Minneapolis, Minnesota; Chicago, Illinois; and Oakland, California, as part of the CARDIA (Coronary Artery Risk Development in Young Adults) study. Measures of the neighborhood food and physical activity environment were linked to participant addresses collected at baseline. CVH was measured on the basis of the American Heart Association's Life's Simple 7 criteria in young adulthood and 30 years later (2015-2016) when participants were midlife (aged 48-60 years). Associations of young adult neighborhood food environment and physical activity resources with midlife CVH (moderate versus high and low versus high) were examined using multinomial logistic regression. Models were adjusted for young adult sociodemographic factors. Participants who lived farther away from a major park in young adulthood were more likely to have low versus high CVH scores (odds ratio, 1.54 [95% CI, 1.22-1.96]) and more likely to have moderate versus high CVH scores (odds ratio, 1.39 [95% CI, 1.12-1.73]) in midlife. No other neighborhood measures were significantly associated with CVH. Young adulthood may be a sensitive period in which having convenient access to physical activity-promoting resources may help them establish healthy habits that can carry into midlife.

Community profiles in northeastern and central Pennsylvania characterized by distinct social, natural, food, and physical activity environments and their relation to type 2 diabetes.

Understanding geographic disparities in type 2 diabetes (T2D) requires approaches that account for communities' multidimensional nature. In an electronic health record nested case-control study, we identified 15,884 cases of new-onset T2D from 2008 to 2016, defined using encounter diagnoses, medication orders, and laboratory test results, and frequency-matched controls without T2D (79,400; 65,069 unique persons). We used finite mixture models to construct community profiles from social, natural, physical activity, and food environment measures. We estimated T2D odds ratios (OR) with 95% confidence intervals (CI) using logistic generalized estimating equation models, adjusted for sociodemographic variables. We examined associations with the profiles alone and combined them with either community type based on administrative boundaries or Census-based urban/rural status. We identified four profiles in 1069 communities in central and northeastern Pennsylvania along a rural-urban gradient: "sparse rural," "developed rural," "inner suburb," and "deprived urban core." Urban areas were densely populated with high physical activity resources and food outlets; however, they also had high socioeconomic deprivation and low greenness. Compared with "developed rural," T2D onset odds were higher in "deprived urban core" (1.24, CI = 1.16-1.33) and "inner suburb" (1.10, CI = 1.04-1.17). These associations with model-based community profiles were weaker than when combined with administrative boundaries or urban/rural status. Our findings suggest that in urban areas, diabetogenic features overwhelm T2D-protective features. The community profiles support the construct validity of administrative-community type and urban/rural status, previously reported, to evaluate geographic disparities in T2D onset in this geography.

Identifying Potential Factors Associated With Racial Disparities in COVID-19 Outcomes: Retrospective Cohort Study Using Machine Learning on Real-World Data.

Racial disparities in COVID-19 incidence and outcomes have been widely reported. Non-Hispanic Black patients endured worse outcomes disproportionately compared with non-Hispanic White patients, but the epidemiological basis for these observations was complex and multifaceted. This study aimed to elucidate the potential reasons behind the worse outcomes of COVID-19 experienced by non-Hispanic Black patients compared with non-Hispanic White patients and how these variables interact using an explainable machine learning approach. In this retrospective cohort study, we examined 28,943 laboratory-confirmed COVID-19 cases from the OneFlorida Research Consortium's data trust of health care recipients in Florida through April 28, 2021. We assessed the prevalence of pre-existing comorbid conditions, geo-socioeconomic factors, and health outcomes in the structured electronic health records of COVID-19 cases. The primary outcome was a composite of hospitalization, intensive care unit admission, and mortality at index admission. We developed and validated a machine learning model using Extreme Gradient Boosting to evaluate predictors of worse outcomes of COVID-19 and rank them by importance. Compared to non-Hispanic White patients, non-Hispanic Blacks patients were younger, more likely to be uninsured, had a higher prevalence of emergency department and inpatient visits, and were in regions with higher area deprivation index rankings and pollutant concentrations. Non-Hispanic Black patients had the highest burden of comorbidities and rates of the primary outcome. Age was a key predictor in all models, ranking highest in non-Hispanic White patients. However, for non-Hispanic Black patients, congestive heart failure was a primary predictor. Other variables, such as food environment measures and air pollution indicators, also ranked high. By consolidating comorbidities into the Elixhauser Comorbidity Index, this became the top predictor, providing a comprehensive risk measure. The study reveals that individual and geo-socioeconomic factors significantly influence the outcomes of COVID-19. It also highlights varying risk profiles among different racial groups. While these findings suggest potential disparities, further causal inference and statistical testing are needed to fully substantiate these observations. Recognizing these relationships is vital for creating effective, tailored interventions that reduce disparities and enhance health outcomes across all racial and socioeconomic groups.

Healthy eating in globalized food environments: market access and consumer behavior in the Galápagos Islands of Ecuador

Abstract Food environments are the interface between food systems and consumers. Although market access contributes to diet intake, consumer behavior determines food acquisition practices yet is often neglected in food environment research. Implementing sustainable food system transformations in climate-vulnerable, trade-dependent settings requires effective integration of both geographic and experienced-based measures of access. This study in the Galápagos Islands (i) develops measures for geographic and experience-based food environments (EFEs) and (ii) links diet outcomes to these food environment measures independently and when interacted. Cross-sectional household data including diet recalls come from 388 participants in the Healthy Family Study from San Cristóbal Island, Galápagos in 2018. Geocoded market inventory and price data were obtained in 2018 using the Nutritional Environment Measurement Survey for Stores (n = 60). Geographic food environments were created from market scores and distribution. EFEs were based on factor analyzed consumer behavior strategies. Diet quality was defined using the global dietary recommendations score. Adjusted linear regressions tested the relationships between diet and food environment measures and included sociodemographic covariates. Interactions between geographic and EFEs were tested. This study showed that higher prioritization of convenience when food shopping was associated with lower healthy food intake. However, the relationship between food environment measures and diet is strongly modified by consumer behavior. For convenience-prioritizing households, the nearest market proved most associated with healthy diet outcomes. For households with a food-driven purchasing strategy, the preferred market was most associated with healthy diet outcomes. These findings show that market inventory can be healthful or deleterious to diets, depending on how individuals navigate their food environments. Empirical measures of food access that neglect to consider consumer behavior may fail to capture realistic representations of food environment and diet relationships. These findings underscore the importance of tailoring food system changes to incorporate context-specific consumer behavior.

Perceived but not objective measures of neighborhood safety and food environments are associated with longitudinal changes in processing speed among urban older adults

BackgroundAlthough a growing body of literature documents the importance of neighborhood effects on late-life cognition, little is known about the relative strength of objective and subjective neighborhood measures on late-life cognitive changes. This study examined effects of objective and subjective neighborhood measures in three neighborhood domains (neighborhood safety, physical disorder, food environments) on longitudinal changes in processing speed, an early marker of cognitive aging and impairment.MethodsThe analysis sample included 306 community-dwelling older adults enrolled in the Einstein Aging Study (mean age = 77, age range = 70 to 91; female = 67.7%; non-Hispanic White: 45.1%, non-Hispanic Black: 40.9%). Objective and subjective measures of neighborhood included three neighborhood domains (i.e., neighborhood safety, physical disorder, food environments). Processing speed was assessed using a brief Symbol Match task (unit: second), administered on a smartphone device six times a day for 16 days and repeated annually for up to five years. Years from baseline was used as the within-person time index.ResultsResults from mixed effects models showed that subjective neighborhood safety (β= -0.028) and subjective availability of healthy foods (β= -0.028) were significantly associated with less cognitive slowing over time. When objective and subjective neighborhood measures were simultaneously examined, subjective availability of healthy foods remained significant (β= -0.028) after controlling for objective availability of healthy foods. Associations of objective neighborhood crime and physical disorder with processing speed seemed to be confounded by individual-level race and socioeconomic status; after controlling for these confounders, none of objective neighborhood measures showed significant associations with processing speed.ConclusionSubjective neighborhood safety and subjective availability of healthy foods, rather than objective measures, were associated with less cognitive slowing over time over a five-year period. Perception of one’s neighborhood may be a more proximal predictor of cognitive health outcomes as it may reflect one’s experiences in the environment. It would be important to improve our understanding of both objective and subjective neighborhood factors to improve cognitive health among older adults.

Neighborhood Access to the Built Environment and Allostatic Load: A Systematic Review of the Use of Geographic Information Systems

Objectives: This paper systematically reviews how spatial analysis has been used to measure relationships between access to the built environment and Allostatic Load (AL) or biomarkers relevant to the stress pathway. Geographic Information Systems (GIS) facilitate objective measurement of built environment access that may explain unequal health outcomes linked to living in stressful environments.Methods: Systematic review, search date 13 July 2022 with methods published a priori. Included studies that quantitatively assessed associations between GIS measures of neighborhood attributes and biomarkers of stress.Results: 23 studies from 14 countries were included having used GIS measures to assess relationships between access to the built environment and biomarkers relevant to AL, with 17 being cross-sectional and 6 longitudinal. Just 2 studies explicitly assessed associations between GIS measures and AL, but 21 explored biomarkers relevant to the stress pathway. GIS was used to calculate density (how much of x within y) and proximity (how far from a to b) measures.Conclusion: GIS measures of greenspace, the food environment, area-level demographics, and land-use measures were found to influence biomarkers relevant to the stress pathway, highlighting the utility of this approach. GIS use is extremely limited when measuring the built environment and its influence on AL but has been widely used to consider effects on individual biomarkers of stress.Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=348355], identifier [CRD42022348355].

Food environment research in Canada: a rapid review of methodologies and measures deployed between 2010 and 2021.

Numerous research methodologies have been used to examine food environments. Existing reviews synthesizing food environment measures have examined a limited number of domains or settings and none have specifically targeted Canada. This rapid review aimed to 1) map research methodologies and measures that have been used to assess food environments; 2) examine what food environment dimensions and equity related-factors have been assessed; and 3) identify research gaps and priorities to guide future research. A systematic search of primary articles evaluating the Canadian food environment in a real-world setting was conducted. Publications in English or French published in peer-reviewed journals between January 1 2010 and June 17 2021 and indexed in Web of Science, CAB Abstracts and Ovid MEDLINE were considered. The search strategy adapted an internationally-adopted food environment monitoring framework covering 7 domains (Food Marketing; Labelling; Prices; Provision; Composition; Retail; and Trade and Investment). The final sample included 220 articles. Overall, Trade and Investment (1%, n = 2), Labelling (7%, n = 15) and, to a lesser extent, Prices (14%, n = 30) were the least studied domains in Canada. Among Provision articles, healthcare (2%, n = 1) settings were underrepresented compared to school (67%, n = 28) and recreation and sport (24%, n = 10) settings, as was the food service industry (14%, n = 6) compared to grocery stores (86%, n = 36) in the Composition domain. The study identified a vast selection of measures employed in Canada overall and within single domains. Equity-related factors were only examined in half of articles (n = 108), mostly related to Retail (n = 81). A number of gaps remain that prevent a holistic and systems-level analysis of food environments in Canada. As Canada continues to implement policies to improve the quality of food environments in order to improve dietary patterns, targeted research to address identified gaps and harmonize methods across studies will help evaluate policy impact over time.

Prenatal Urban Environment and Blood Pressure Trajectories From Childhood to Early Adulthood

BackgroundPrenatal urban environmental exposures have been associated with blood pressure in children. The dynamic of these associations across childhood and later ages is unknown. ObjectivesThe purpose of this study was to assess associations of prenatal urban environmental exposures with blood pressure trajectories from childhood to early adulthood. MethodsRepeated measures of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were collected in up to 7,454 participants from a UK birth cohort. Prenatal urban exposures (n = 43) covered measures of noise, air pollution, built environment, natural spaces, traffic, meteorology, and food environment. An exposome-wide association study approach was used. Linear spline mixed-effects models were used to model associations of each exposure with trajectories of blood pressure. Replication was sought in 4 independent European cohorts (up to 9,261). ResultsIn discovery analyses, higher humidity was associated with a faster increase (mean yearly change in SBP for an interquartile range increase in humidity: 0.29 mm Hg/y, 95% CI: 0.20-0.39) and higher temperature with a slower increase (mean yearly change in SBP per interquartile range increase in temperature: −0.17 mm Hg/y, 95% CI: −0.28 to −0.07) in SBP in childhood. Higher levels of humidity and air pollution were associated with faster increase in DBP in childhood and slower increase in adolescence. There was little evidence of an association of other exposures with change in SBP or DBP. Results for humidity and temperature, but not for air pollution, were replicated in other cohorts. ConclusionsReplicated findings suggest that higher prenatal humidity and temperature could modulate blood pressure changes across childhood.

Associations of objective and subjective neighborhood measures with cognitive change in a repeated measurement burst design

AbstractBackgroundPrior studies have reported associations between neighborhood characteristics and late‐life cognition. These studies assessed neighborhood using either objective (e.g., area‐level data from public database) or subjective (individual‐level perception) measures. However, little research has been done to examine effects of objective and subjective measures simultaneously. The present study aims to investigate the independent associations of objective and subjective neighborhood characteristics with cognitive change in older adults.MethodParticipants include 316 individuals in the Einstein Aging Study (mean age = 77; 67% females; 45% non‐Hispanic Whites, 40% non‐Hispanic Blacks). Subjective neighborhood measures included perceived neighborhood safety, aesthetic quality, social cohesion, and availability of healthy foods (range = 1 poor to 5 excellent). Objective neighborhood measures included violent crime, neighborhood deprivation, volunteering rates, percentage of healthy food retailers, and low access to healthy food. Processing speed was assessed using the brief, smartphone‐administered Symbol Search Test, and was completed 6x/day over two weeks; this was repeated annually from 2017 to 2022. To account for non‐linear retest/practice effects, double negative exponential models were used to estimate the relation of neighborhood measures to asymptotic performance (i.e., fastest response time) at baseline and to change in asymptotic performance over time.ResultMost subjective and objective neighborhood measures were significantly correlated with each other (Table 1). In models containing both objective and subjective neighborhood measures, better perceived safety was associated with greater annual improvement in asymptotic performance (40 milliseconds/year for one point increase in safety) while the objective measure of violent crime was not. Perceived availability of healthy foods was independently associated with a faster baseline asymptotic processing speed (estimate = 160 milliseconds) and with greater annual improvement rate (estimate = 54 milliseconds/year) while the objective measures of food environment were not (Table 2).ConclusionSubjective rather than objective neighborhood characteristics were strongly associated with annual rates of change in processing speed over five years in community‐dwelling older adults. Perception of one’s neighborhood may be a more proximal predictor of cognitive health as it may reflect an individual’s lived experiences and determine one’s psychological states and health‐related behaviors. Alternatively, more fine‐grained objective neighborhood measures (e.g., individual‐level) would be necessary to better characterize objective neighborhood environments.

Concepts, Characterizations, and Cautions: A Public Health Guide and Glossary for Planning Food Environment Measurement.

There is no singular approach to measuring the food environment suitable for all studies. Understanding terminology, methodology, and common issues is crucial to choosing the best approach. This review is designed to support a shared understanding so diverse multi-institutional teams engaged in food environment measurement can justify their measurement choices and have informed discussions about reasons for measurement strategies to vary across projects. This guide defines key terms and provides annotated resources identified as a useful starting point for exploring the food environment literature. The writing team was an academic-practice collaboration, reflecting on the experience of a multi-institutional team focused on retail environments across the US relevant to cardiovascular disease. Terms and annotated resources are divided into three sections: food environment constructs, classification and measures, and errors and strategies to reduce error. Two examples of methods and challenges encountered while measuring the food environment in the context of a US health department are provided. Researchers and practice professionals are directed to the Food Environment Electronic Database Directory (https://www.foodenvironmentdirectory.com/) for comparing available data resources for food environment measurement, focused on the US; this resource incorporates updates informed by user input and literature reviews. Measuring the food environment is complex and risks oversimplification. This guide serves as a starting point but only partially captures some aspects of neighborhood food environment measurement. No single food environment measure or data source meets all research and practice objectives. This shared starting point can facilitate theoretically grounded food environment measurement.

Demographic, social and geographic factors associated with glycaemic control among US Veterans with new onset type 2 diabetes: a retrospective cohort study

ObjectivesThis study evaluated whether a range of demographic, social and geographic factors had an influence on glycaemic control longitudinally after an initial diagnosis of diabetes.Design, setting and participantsWe used the...

Shaping food environments to support sustainable healthy diets in low and middle-income countries

The global ambitions to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture demand a complex transition of the current food environments for enabling sustainable healthy diets. The food environments in Low and Middle-Income Countries (LMICs) have been experiencing rapid and dynamic transitions across the globe, necessitating a system-level thinking and systemic approach to understand opportunities for improvement. There is a need for valid, reliable measures of food and nutrition environments for reorienting thinking and data collection toward determinants of food demand, especially the food environment components, which are critical to understand the transforming food systems. Food environment transformations are urgently required to provide consumers with more affordable and nutritious diets capable of meeting social and environmental challenges. In the present perspective, we aim to provide insights on prioritizing research on understanding and designing evidence based inclusive food environments which is crucial for promoting long-term food system innovations that are economically, socially, and environmentally sustainable and, above all, contribute to sustainable healthy diets.

Availability of healthy foods, fruit and vegetable consumption, and cognition among urban older adults

Background. Although prior studies have examined the associations between neighborhood characteristics and cognitive health, little is known about whether local food environments, which are critical for individuals’ daily living, are associated with late-life cognition. Further, little is known about how local environments may shape individuals’ health-related behaviors and impact cognitive health. The aim of this study is to examine whether objective and subjective measures of healthy food availability are associated with ambulatory cognitive performance and whether behavioral and cardiovascular factors mediate these associations among urban older adults.Methods. The sample consisted of systematically recruited, community-dwelling older adults (N = 315, mean age = 77.5, range = 70–91) from the Einstein Aging Study. Objective availability of healthy foods was defined as density of healthy food stores. Subjective availability of healthy foods and fruit/vegetable consumption were assessed using self-reported questionnaires. Cognitive performance was assessed using smartphone-administered cognitive tasks that measured processing speed, short-term memory binding, and spatial working memory performance 6 times a day for 14 days.Results. Results from multilevel models showed that subjective availability of healthy foods, but not objective food environments, was associated with better processing speed (estimate= -0.176, p = .003) and more accurate memory binding performance (estimate = 0.042, p = .012). Further, 14~16% of the effects of subjective availability of healthy foods on cognition were mediated through fruit and vegetable consumption.Conclusions. Local food environments seem to be important for individuals’ dietary behavior and cognitive health. Specifically, subjective measures of food environments may better reflect individuals’ experiences regarding their local food environments not captured by objective measures. Future policy and intervention strategies will need to include both objective and subjective food environment measures in identifying impactful target for intervention and evaluating effectiveness of policy changes.

What counts? Adding nuance to retail food environment measurement tools in a Canadian context.

Limitations of traditional geospatial measures, like the modified Retail Food Environment Index (mRFEI), are well documented. In response, we aimed to: (1) extend existing food environment measures by inductively developing subcategories to increase the granularity of healthy v. less healthy food retailers; (2) establish replicable coding processes and procedures; and (3) demonstrate how a food retailer codebook and database can be used in healthy public policy advocacy. We expanded the mRFEI measure such that 'healthy' food retailers included grocery stores, supermarkets, hypermarkets, wholesalers, bulk food stores, produce outlets, butchers, delis, fish and seafood shops, juice/smoothie bars, and fresh and healthy quick-service retailers; and 'less healthy' food retailers included fast-food restaurants, convenience stores, coffee shops, dollar stores, pharmacies, bubble tea restaurants, candy stores, frozen dessert restaurants, bakeries, and food trucks. Based on 2021 government food premise licences, we used geographic information systems software to evaluate spatial accessibility of healthy and less healthy food retailers across census tracts and in proximity to schools, calculating differences between the traditional v. expanded mRFEI. Calgary and Edmonton, Canada. N/A. Of the 10 828 food retailers geocoded, 26 % were included using traditional mRFEI measures, while 53 % were included using our expanded categorisation. Changes in mean mRFEI across census tracts were minimal, but the healthfulness of food environments surrounding schools significantly decreased. Overall, we show how our mRFEI adaptation, and transparent reporting on its use, can promote more nuanced and comprehensive food environment assessments to better support local research, policy and practice innovations.

Effects of Socioeconomic Status on Nutrition and Nutrition Policy Studies in Asia.

Many studies in Western countries have reported that people with low socioeconomic status (SES) have a greater risk of obesity and non-communicable diseases. However, the relationship between SES and nutrition is considered to differ from country to country among Asian countries. Based on studies since 2010, the nutritional status of populations with low SES can be summarized as follows. In India, undernutrition among children and women has been reported. In China, low energy and nutrient intakes and undernutrition are common among children and the elderly, while both obesity and undernutrition are common in adults. In Japan and Korea, weight faltering in preschool children, low dietary quality among groups from school children to adults, and high obesity among adolescents and adult women have been reported. There are two types of policies aimed at reducing nutrition disparities: approaches for population and those for households with low SES. Nutrition disparities due to SES disparities in Asia need to be monitored. In Asia, studies on nutrition policy have focused on cash subsidies and food assistance for low SES households with the aim of improving undernutrition, but food environment measures for the population as a whole also need to be studied in order to reduce under- and over-nutrition, the double burden of malnutrition.

Differential Associations Between Changes in Food Environment and Changes in BMI Among Adults Living in Urban, Low-Income Communities

Food environments can contribute to excess weight gain among adults, but the evidence is mixed. This longitudinal study investigated the associations between changes in the food environment and changes in BMI in adults and whether changes in the food environment differentially impact various subgroups. At 2 time points, BMI was calculated using self-reported height and weight data from 517 adults (mean age, 41 years) living in 4 New Jersey cities. The counts of different types of food outlets within 0.4, 0.8, and 1.6 km of respondents' residences were collected at baseline and tracked until follow-up. A binary measure of social standing (social-advantage group, n = 219; social-disadvantage group, n = 298) was created through a latent class analysis using social, economic, and demographic variables. Multivariable linear regression modeled the associations between changes in BMI with measures of the food environment; additionally, interaction terms between the measures of food environment and social standing were examined. Overall, over 18 months, an increase in the number of small grocery stores within 0.4 km of a respondent's residence was associated with a decrease in BMI (β = -1.0; 95% CI: -1.9, -0.1; P = 0.024), while an increase in the number of fast-food restaurants within 1.6 km was associated with an increase in BMI (β = 0.1; 95% CI: 0.01, 0.2; P = 0.027). These overall findings, however, masked some group-specific associations. Interaction analyses suggested that associations between changes in the food environment and changes in BMI varied by social standing. For instance, the association between changes in fast-food restaurants and changes in BMI was only observed in the social-disadvantage group (β = 0.1; 95% CI: 0.02, 0.2; P = 0.021). In a sample of adults living in New Jersey, changes in the food environment had differential effects on individuals' BMIs, based on their social standing.

Enhancing the Retail Food Environment Index (RFEI) with Neighborhood Commuting Patterns: A Hybrid Human-Environment Measure.

The Retail Food Environment Index (RFEI) and its variants have been widely used in public health to measure people’s accessibility to healthy food. These indices are purely environmental as they only concern the geographic distribution of food retailers, but fail to include human factors, such as demographics, socio-economy, and mobility, which also shape the food environment. The exclusion of human factors limits the explanatory power of RFEIs in identifying neighborhoods of the greatest concern. In this study, we first proposed a hybrid approach to integrate human and environmental factors into the RFEI. We then demonstrated this approach by incorporating neighborhood commuting patterns into a traditional RFEI: we devised a multi-origin RFEI (MO_RFEI) that allows people to access food from both homes and workplaces, and further an enhanced RFEI (eRFEI) that allows people to access food with different transportation modes. We compared the traditional and proposed RFEIs in a case study of Florida, USA, and found that the eRFEI identified fewer and more clustered underserved populations, allowing policymakers to intervene more effectively. The eRFEI depicts more realistic human shopping behaviors and better represents the food environment. Our study enriches the literature by offering a new and generic approach for assimilating a neighborhood context into food environment measures.

Associations between neighbourhood fast-food environments and hypertension in Canadian adults.

ObjectivesHypertension is a leading cause of cardiovascular disease and premature death. Neighbourhoods characterized by a high proportion of fast-food outlets may contribute to hypertension in residents; however, limited research has explored these associations. The objectives of this study were to assess associations between neighbourhood fast-food environments, measured and self-reported hypertension.
 ApproachWe used data from 10,700 adults who participated in six cycles of the Canadian Health Measures Survey (CHMS). Measured hypertension was defined as having an average systolic blood pressure (BP) of ≥140, a diastolic BP ≥90 mm Hg or being on BP lowering medication. Participants were also asked if they had been diagnosed with high BP or if they take BP lowering medication (i.e., self-reported hypertension). We characterized the fast-food environment of each participant’s neighbourhood using the Canadian Food Environment Dataset (Can-FED). We considered the proportion of fast-food outlets relative to fast-food outlets and full-service restaurants as a continuous variable.
 ResultsThe mean proportion of fast-food outlets was 23.3% (SD 26.8%). A one standard deviation (SD) increase in the proportion to fast-food outlets was associated with higher odds of measured hypertension in the full sample (OR=1.17, 95% CI 1.05 to 1.31) and in sex-specific models (women: OR=1.14, 95% CI 1.01 to 1.29; and men: OR=1.21, 95% CI 1.03 to 1.43). A one standard deviation (SD) increase in the proportion to fast-food outlets was associated with higher odds of self-reported hypertension in the full sample (OR=1.13, 95% CI 1.02 to 1.24); however, associations were inconclusive in sex-specific models (women: OR=1.11, 95% CI 0.99 to 1.26; and men: OR=1.14, 95% CI 0.99 to 1.33).
 ConclusionBy linking neighbourhood food environment measures that were created from an administrative data source (the Statistics Canada Business Register) to individual-level data from the CHMS, we were able to demonstrate that reducing the proportion of fast-food outlets in neighbourhoods may reduce rates of hypertension and support individually targeted interventions.

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.

Navigating Globalized Food Environments: Market Access, Consumer Behavior, and Dietary Diversity in the Galapagos Islands of Ecuador

ObjectivesThis study has two objects: (1) determine whether different types of food environment measures shape diet outcomes; (2) determine whether consumer behavior modifies the association between geographic food environments and diet outcomes. MethodsHousehold sociodemographic data and individual data including diet recalls are from 429 participants in the Healthy Family Study conducted in San Cristóbal island Galápagos in 2018. Geocoded market inventory and price data were obtained at the same time using the Nutritional Measurement Survey for stores (NEMS-S). Geographic food environment measures were based on market access and market survey stores. Experience-based food environment measures were based on factor analyzed consumer behavior strategies for each household. Diet quality and diversity scores were based on Global Dietary Recommendations (GDR) scoring schema. Linear regressions tested the relationships between diet outcomes and food environment measures and included key sociodemographic covariates. Interactions terms between geographic and experience-based food environment measures were included. ResultsObjective 1: Increasing nearest market score was associated with lower healthy food intake (β = –0.14) and higher unhealthy food intake (β = 0.14). Increasing preferred market price index was associated with lower unhealthy food intake (β = –0.31). Higher prioritization of convenience when food shopping was associated with lower of healthy food intake (β = –0.47). Objective 2: the relationship between food environment measures and diet outcomes is strongly modified by consumer behavior. For households that prioritize convenience when food shopping, price and inventory at the nearest market was most associated with diet. For households that prioritize quality when food shopping, price and inventory at the preferred market was most associated with diet. ConclusionsMarket inventory can be healthful to some and deleterious to diets of others, depending how they navigate their food environments. “Objective” measures of quality and access that fail to consider consumer behavior may fail to capture realistic representations of food environment and diet relationships. Funding SourcesThis research is funded by an NIH/FIC R21 and the Carolina Population Center for training support and general support.