Association between activity space exposure to food establishments and individual risk of overweight

Association of activity-based food environment index with obesity-related cancer mortality in the US

BACKGROUND

Obesity and obesity-related cancers contribute to rising healthcare costs and declining life expectancy in the US and improving diet quality plays a crucial role in reversing such trends. Existing studies on the relationship between healthy food access and obesity-related cancer mortality present mixed findings, whereas food procurement activities are largely overlooked. The paper aims to construct a novel food environment index based on residents' food retailer visits, and then compare it with the location-based food environment index regarding the strength of associations with obesity-related cancer mortality rates.

METHODS

This cross-sectional ecologic study used business location data from InfoGroup and aggregated GPS-based food retailer visit data from SafeGraph in 2018-2019, and mortality data from the Centers for Disease Control and Prevention in 2015-2020. A total of 2925 counties or equivalents with complete information were included. Activity-based index was calculated as the percentage of visits to healthy food retailers out of total visits to all qualified food retailers for residents in each county. Location-based index was calculated as the percentage of healthy food retailers out of all qualified food retailers in each county. The main outcome is age-adjusted obesity-related cancer (13 types of cancer based on evidence from the International Agency for Research on Cancer) mortality rates, which were calculated for each county and counties were further categorized into high- and low-risk (≥ 60.2 and < 60.2 cases per 100,000 population) areas. Linear, non-linear, logistic, and spatial regression analyses were performed to examine the association between each food environment index and obesity-related cancer mortality rates.

RESULTS

The activity-based index demonstrated significant negative association with the 2015-2020 obesity-related cancer mortality rates (coefficient [95% CI]: - 0.980 [- 1.385, - 0.575], P < 0.001), and each standard deviation increase in the activity-based index was associated with an 18% decrease in the odds of being in a high-risk area (odds ratio [95% CI]: 0.821 [0.749, 0.900], P < 0.001), while the location-based index showed much weaker and non-significant effects.

CONCLUSIONS

Our findings suggest that health policies and initiatives that combat obesity and obesity-related cancers should consider incorporating food retailer visits into policy formation.

Using global positioning systems to explore food insecurity among older adults living with HIV, with and without criminal justice involvement

This study assessed the feasibility and acceptability of using global positioning systems (GPS) to evaluate food insecurity among older people living with HIV (PLWH), including those with criminal justice involvement. Approximately 25 PLWH participants were recruited via community engagement from September 2023 to January 2024. Bivariate analyses identified demographic characteristics, and chi-square tests investigated the association between arrest/incarceration history and food security. Spatial analysis examined patterns, calculated distances traveled and determined the frequency of visits to specific locations over seven days. Around 20.8% (n = 5) of participants had a CD4 count of ≤299 cells/mm³, indicating possible advanced HIV status. Food insecurity was higher among participants with lower education levels (61.5%; n = 8) and incomes ≤$20,000 annually (69.2%; n = 9). Those with arrest histories had slightly higher food insecurity rates (54.5%; n = 6) compared to those never arrested (45.5%; n = 5), though differences were not statistically significant. Most participants successfully charged and carried their GPS devices and retained food receipts. GPS compliance was higher at the start and middle of the study period but declined toward the end. Findings support that integrating geospatial technology is both feasible and acceptable for assessing food insecurity among older PLWH.

A linear tessellation model for the identification of "food desert": A case study of Shanghai, China

The "food desert" problem has been treated under a national strategy in the United States and other countries. At present, there is little research on the phenomenon of "food desert" in China. This study takes Shanghai as the research area and proposes a multiscale analysis method using a linear tessellation model that splits the street network into homogeneous linear units. Firstly, the network kernel density estimation using a linear tessellation model is used to measure the travel-mode-based food accessibility. Considering the actual travel constraints, the GPS trajectory data of four travel modes (walking, bicycle, metro and taxi) are applied to calculate the speed of each linear unit. Secondly, the "food desert" phenomenon in Shanghai are identified combing with the results of the network K-function. Finally, the resident income conditions in different modes are fitted based on the housing price data and the spatial distribution of four "food desert" patterns are detected by the overlay analysis of food accessibility and resident income conditions. The experimental results show that fifty percent of Shanghai is characterized by low food accessibility, and half of these areas are disadvantaged and low-income areas in suburbs, which are the locations experiencing the "food desert" phenomenon. Comparing the results of the proposed method and that of the traditional planar method, the identification results for all modes based on the traditional planar method underestimate the severity of the "food desert", especially for the bicycle and taxi modes. This study also provides corresponding decision-making reference for the alleviation and resolution of "food desert" issues. Moreover, the proposed method provides a new research perspective for urban research under the street network space.

Effect of mobile food environments on fast food visits

Poor diets are a leading cause of morbidity and mortality. Exposure to low-quality food environments saturated with fast food outlets is hypothesized to negatively impact diet. However, food environment research has predominantly focused on static food environments around home neighborhoods and generated mixed findings. In this work, we leverage population-scale mobility data in the U.S. to examine 62M people's visits to food outlets and evaluate how food choice is influenced by the food environments people are exposed to as they move through their daily routines. We find that a 10% increase in exposure to fast food outlets in mobile environments increases individuals' odds of visitation by 20%. Using our results, we simulate multiple policy strategies for intervening on food environments to reduce fast-food outlet visits. This analysis suggests that optimal interventions are informed by spatial, temporal, and behavioral features and could have 2x to 4x larger effect than traditional interventions focused on home food environments.

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.

Integrating human activity into food environments can better predict cardiometabolic diseases in the United States

The prevalence of cardiometabolic diseases in the United States is presumably linked to an obesogenic retail food environment that promotes unhealthy dietary habits. Past studies, however, have reported inconsistent findings about the relationship between the two. One underexplored area is how humans interact with food environments and how to integrate human activity into scalable measures. In this paper, we develop the retail food activity index (RFAI) at the census tract level by utilizing Global Positioning System tracking data covering over 94 million aggregated visit records to approximately 359,000 food retailers across the United States over two years. Here we show that the RFAI has significant associations with the prevalence of multiple cardiometabolic diseases. Our study indicates that the RFAI is a promising index with the potential for guiding the development of policies and health interventions aimed at curtailing the burden of cardiometabolic diseases, especially in communities characterized by obesogenic dietary behaviors.

Egalitarian Attitudes and Activity Spaces in Chitwan, Nepal

Connections between individuals' sociodemographic characteristics and their social attitudes have been widely studied, but there has been less research on how individuals' spatial patterns are related to attitudes. Studies that do incorporate space have focused on residential locations, neglecting spatial experience outside residential neighborhoods. To fill this gap, we test hypotheses relating multiple measures of activity space (AS) to social attitudes, using innovative spatial data from Nepal. First, we hypothesize that the gender and caste attitudes of a focal individual will be positively associated with the gender and caste attitudes of others in the focal individual's AS, including spaces beyond the residential neighborhood. Second, we hypothesize that privileged individuals (i.e., males and those of the Chhetri/Brahmin caste) with greater potential exposure to females and those of lower castes in their AS will have more egalitarian attitudes about gender and caste than those with less exposure in their AS. Linear regression models provide support for both hypotheses.

Selective Daily Mobility Bias in the Community Food Environment: Case Study of Greater Hartford, Connecticut

The community food environment has potential influences on community members' dietary health outcomes, such as obesity and Type II diabetes. However, most existing studies evaluating such health effects neglect human mobility. In food patrons' daily travels, certain locations may be preferred and patronized more frequently than others. This behavioral uncertainty, known as the selective daily mobility bias (SDMB), is less explored in community-food-environment research. In this paper, we aim to confirm the existence of the SDMB by systematically exploring the large-scale GPS-based restaurant-visit patterns in the Greater Harford region, Connecticut. Next, we explore the restaurant and neighborhood characteristics that are associated with the restaurant-visit patterns. Our primary results demonstrate that (1) most restaurant customers originate from areas outside of the census tract where the restaurant is located, and (2) restaurants located in socially vulnerable areas attract more customers in total, more customers from local areas, and more customers from other socially vulnerable areas. These results confirm the relevance of the SDMB to the community food environment, and suggest ways that the SDMB can be moderated by an uneven socio-economic landscape. The findings demonstrate the necessity of incorporating human-mobility data into the study of the community food environment.

Investigating where adolescents engage in moderate to vigorous physical activity and sedentary behaviour: An exploratory study

BACKGROUND

There is a persistent lack of understanding on the influence of the environment on behaviour and health. While the environment is considered an important modifiable determinant of health behaviour, past research assessing environments often relies on static, researcher-defined buffers of arbitrary distance. This likely leads to misrepresentation of true environmental exposures. This exploratory study aims to compare researcher-defined and self-drawn buffers in reflecting the spaces and time adolescents engage in physical activity (PA) and sedentary behaviour. It also investigates if adolescent's access the PA facility and greenspace nearest their home or school for PA, as well as examine how much time adolescents spent in PA at any PA facilities and greenspaces.

METHODS

Adolescents (aged 14-18 years; n = 34) were recruited from schools in West Yorkshire, England. Seven consecutive days of global positioning system (GPS) and accelerometer data were collected at 15 second intervals. Using ArcGIS, we compared 30 different researcher-defined buffers including: radial, network and ellipse buffers at 400m, 800m, 1000m, 1600m and 3000m and participant-defined self-drawn neighbourhoods to objectively measured PA and sedentary space and PA time. Location of PA was also compared to Points of Interest data to determine if adolescents use the nearest PA facility or greenspace to their home or school and to examine how much PA was undertaken within these locations.

RESULTS

Our exploratory findings show the inadequacy of researcher-defined buffer size in assessing MVPA space or sedentary space. Furthermore, less than 35% of adolescents used the greenspaces or PA facilities nearest to their home or school. Approximately 50% of time spent in PA did not occur within the home, school, PA facility, or greenspace environments.

CONCLUSION

Our exploratory findings help to begin to quantify the inadequacy of researcher-defined, and self-drawn buffers in capturing adolescent MVPA and sedentary space, as well as time spent in PA. Adolescents often do not use PA facilities and greenspaces nearest their home and school and a large proportion of PA is achieved outside PA facilities and greenspaces. Further research with larger samples are needed to confirm the findings of this exploratory study.

The Weight of Place: Built Environment Correlates of Obesity and Diabetes

In recent decades, the prevalence of obesity and diabetes has risen substantially in North America and worldwide. To address these dual epidemics, researchers and policymakers alike have been searching for effective means to promote healthy lifestyles at a population level. As a consequence, there has been a proliferation of research examining how the "built" environment in which we live influences physical activity levels, by promoting active forms of transportation, such as walking and cycling, over passive ones, such as car use. Shifting the transportation choices of local residents may mean that more members of the population can participate in physical activity during their daily routine without structured exercise programs. Increasingly, this line of research has considered the downstream metabolic consequences of the environment in which we live, raising the possibility that "healthier" community designs could help mitigate the rise in obesity and diabetes prevalence. This review discusses the evidence examining the relationship between the built environment, physical activity, and obesity-related diseases. We also consider how other environmental factors may interact with the built environment to influence metabolic health, highlighting challenges in understanding causal relationships in this area of research.

Air pollution and metabolic disorders: Dynamic versus static measures of exposure among Hispanics/Latinos and non-Hispanics

INTRODUCTION

Exposure to air pollution disproportionately affects racial/ethnic minorities that could contribute to health inequalities including metabolic disorders. However, most existing studies used a static assessment of air pollution exposure (mostly using the residential address) and do not account for activity space when modelling exposure to air pollution. The aim of this study is to understand how exposure to air pollution impacts metabolic disorders biomarkers, how this effect differs according to ethnicity, and for the first time compare these findings with two methods of exposure assessment: dynamic and static measures.

METHODS

Among the Community of Mine study, a cross-sectional study conducted in San Diego County, insulin resistance, diabetes, hypertension, obesity, dyslipidemia, and metabolic syndrome (MetS) were assessed. Exposure to air pollution (PM_2.5, NO₂, traffic) was calculated using static measures around the home, and dynamic measures of mobility derived from Global Positioning Systems (GPS) traces using kernel density estimators to account for exposure variability across space and time. Associations of air pollution with metabolic disorders were quantified using generalized estimating equation models to account for the clustered nature of the data.

RESULTS

Among 552 participants (mean age 58.7 years, 42% Hispanic/Latino), Hispanics/Latinos had a higher exposure to PM_2.5 compared to non-Hispanics using static measures. In contrast, Hispanics/Latinos had less exposure to PM_2.5 using dynamic measures. For all participants, higher dynamic exposure to PM_2.5 and NO₂ was associated with increased insulin resistance and cholesterol levels, and increased risk of obesity, dyslipidemia and MetS (RR 1.17, 95% CI: 1.07-1.28; RR 1.21, 95% CI: 1.12-1.30, respectively). The association between dynamic PM_2.5 exposure and MetS differed by Hispanic/Latino ethnicity.

CONCLUSION

These results highlight the importance of considering people's daily mobility in assessing the impact of air pollution on health.

GPS2space: An Open-source Python Library for Spatial Measure Extraction from GPS Data

Global Positioning System (GPS) data have become one of the routine data streams collected by wearable devices, cell phones, and social media platforms in this digital age. Such data provide research opportunities in that they may provide contextual information to elucidate where, when, and why individuals engage in and sustain particular behavioral patterns. However, raw GPS data consisting of densely sampled time series of latitude and longitude coordinate pairs do not readily convey meaningful information concerning intra-individual dynamics and inter-individual differences; substantial data processing is required. Raw GPS data need to be integrated into a Geographic Information System (GIS) and analyzed, from which the mobility and activity patterns of individuals can be derived, a process that is unfamiliar to many behavioral scientists. In this tutorial article, we introduced GPS2space, a free and open-source Python library that we developed to facilitate the processing of GPS data, integration with GIS to derive distances from landmarks of interest, as well as extraction of two spatial features: activity space of individuals and shared space between individuals, such as members of the same family. We demonstrated functions available in the library using data from the Colorado Online Twin Study to explore seasonal and age-related changes in individuals' activity space and twin siblings' shared space, as well as gender, zygosity and baseline age-related differences in their initial levels and/or changes over time. We concluded with discussions of other potential usages, caveats, and future developments of GPS2space.

GPS2space: An Open-source Python Library for Spatial Measure Extraction from GPS Data

Global Positioning System (GPS) data have become one of the routine data streams collected by wearable devices, cell phones, and social media platforms in this digital age. Such data provide research opportunities in that they may provide contextual information to elucidate where, when, and why individuals engage in and sustain particular behavioral patterns. However, raw GPS data consisting of densely sampled time series of latitude and longitude coordinate pairs do not readily convey meaningful information concerning intra-individual dynamics and inter-individual differences; substantial data processing is required. Raw GPS data need to be integrated into a Geographic Information System (GIS) and analyzed, from which the mobility and activity patterns of individuals can be derived, a process that is unfamiliar to many behavioral scientists. In this tutorial article, we introduced GPS2space, a free and open-source Python library that we developed to facilitate the processing of GPS data, integration with GIS to derive distances from landmarks of interest, as well as extraction of two spatial features: activity space of individuals and shared space between individuals, such as members of the same family. We demonstrated functions available in the library using data from the Colorado Online Twin Study to explore seasonal and age-related changes in individuals' activity space and twin siblings' shared space, as well as gender, zygosity and baseline age-related differences in their initial levels and/or changes over time. We concluded with discussions of other potential usages, caveats, and future developments of GPS2space.

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.

Linking the Flint Food Store Survey: Is Objective or Perceived Access to Healthy Foods Associated with Glycemic Control in Patients with Type 2 Diabetes?

Type 2 diabetes mellitus (DM-2) remains a significant public health concern, particularly in low-income neighborhoods where healthy foods may be scarcer. Despite the well-known relationship between diet and diabetes, little evidence exists on the connections among the objectively measured community and consumer food environment, perception of food access, and diabetes management or outcomes. This cross-sectional, ecological study represents the first example of combining a GIS-based, objectively measured food store audit considering quality, variety, and price of foods in stores with a clinical survey of patients with DM-2 (n = 126). In this way, we offer evidence on the relationship between healthy food access-measured more robustly than proximity to or density of certain store types-and diabetes management knowledge, medication adherence, and glycemic control. Better glycemic control was not correlated with better overall food store score, meaning that people in neighborhoods with better access to healthy foods are not necessarily more likely to manage their diabetes. While perceived healthy food access was not correlated with glycemic control, it was strongly correlated with objective healthy food access at shorter distances from home. These results have great importance both for clinical understanding of the persistence of poor diabetes management outcomes and for the understanding of the influence of the food environment on health behaviors.

Comparing competing geospatial measures to capture the relationship between the neighborhood food environment and diet

PURPOSE

To examine how the choice of neighborhood food environment definition impacts the association with diet.

METHODS

Using food frequency questionnaire data from the Reasons for Geographic and Racial Differences in Stroke study at baseline (2003-2007), we calculated participants' dietary inflammation score (DIS) (n = 20,331); higher scores indicate greater pro-inflammatory exposure. We characterized availability of supermarkets and fast food restaurants using several geospatial measures, including density (i.e., counts/km2) and relative measures (i.e., percentage of all food stores or restaurants); and various buffer distances, including administrative units (census tract) and empirically derived buffers ("classic" network, "sausage" network) tailored to community type (higher density urban, lower density urban, suburban/small town, rural). Using generalized estimating equations, we estimated the association between each geospatial measure and DIS, controlling for individual- and neighborhood-level sociodemographics.

RESULTS

The choice of buffer-based measure did not change the direction or magnitude of associations with DIS. Effect estimates derived from administrative units were smaller than those derived from tailored empirically derived buffer measures. Substantively, a 10% increase in the percentage of fast food restaurants using a "classic" network buffer was associated with a 6.3 (SE = 1.17) point higher DIS (P< .001). The relationship between the percentage of supermarkets and DIS, however, was null. We observed high correlation coefficients between buffer-based density measures of supermarkets and fast food restaurants (r = 0.73-0.83), which made it difficult to estimate independent associations by food outlet type.

CONCLUSIONS

Researchers should tailor buffer-based measures to community type in future studies, and carefully consider the theoretical and statistical implications for choosing relative (vs. absolute) measures.

Exploring factors affecting individual GPS-based activity space and how researcher-defined food environments represent activity space, exposure and use of food outlets

Background

Obesity remains one of the most challenging public health issues of our modern time. Despite the face validity of claims for influence, studies on the causes of obesity have reported the influence of the food environment to be inconsistent. This inconsistency has been attributed to the variability of measures used by researchers to represent the food environments—Researcher-Defined Food Environments (RDFE) like circular, street-network buffers, and others. This study (i.) determined an individual’s Activity Space (AS) (ii.) explored the accuracy of the RDFE in representing the AS, (iii.) investigated the accuracy of the RDFE in representing actual exposure, and (iv.) explored whether exposure to food outlet reflects the use of food outlets.

Methods

Data were collected between June and December 2018. A total of 65 participants collected Global Positioning System (GPS) data, kept receipt of all their food purchases, completed a questionnaire about their personal information and had their weight and height measured. A buffer was created around the GPS points and merged to form an AS (GPS-based AS).

Results

Statistical and geospatial analyses found that the AS size of participants working away from home was positively related to the Euclidean distance from home to workplace; the orientation (shape) of AS was also influenced by the direction of workplace from home and individual characteristics were not predictive of the size of AS. Consistent with some previous studies, all types and sizes of RDFE variably misrepresented individual exposure in the food environments. Importantly, the accuracy of the RDFE was significantly improved by including both the home and workplace domains. The study also found no correlation between exposure and use of food outlets.

Conclusions

Home and workplace are key activity nodes in modelling AS or food environments and the relationship between exposure and use is more complex than is currently suggested in both empirical and policy literature.

Measurement of neighborhood-based physical activity bouts

This study examined how buffer type (shape), size, and the allocation of activity bouts inside buffers that delineate the neighborhood spatially produce different estimates of neighborhood-based physical activity. A sample of 375 adults wore a global positioning system (GPS) data logger and accelerometer over 2 weeks under free-living conditions. Analytically, the amount of neighborhood physical activity measured objectively varies substantially, not only due to buffer shape and size, but by how GPS-based activity bouts are identified with respect to containment within neighborhood buffers. To move the "neighborhood-effects" literature forward, it is critical to delineate the spatial extent of the neighborhood, given how different ways of measuring GPS-based activity containment will result in different levels of physical activity across different buffer types and sizes.

Accuracy of buffers and self-drawn neighbourhoods in representing adolescent GPS measured activity spaces: An exploratory study

BACKGROUND

There continues to be a lack of understanding as to the geographical area at which the environment exerts influence on behaviour and health. This exploratory study compares different potential methods of both researcher- and participant-defined definitions of neighbourhood reflect an adolescent's activity space.

METHODS

Seven consecutive days of global positioning system (GPS) tracking data were collected at 15 s intervals using a small exploratory adolescent sample of 14-18 year olds (n = 69) in West Yorkshire, England. A total of 304,581 GPS tracking points were collected and compared 30 different definitions of researcher-defined neighbourhoods including radial, network and ellipse buffers at 400 m, 800 m, 1000 m, 1600 m and 3000 m, as well as participant-defined self-drawn neighbourhoods.

RESULTS

This exploratory study supports emerging evidence cautioning against the use of static neighbourhood definitions for defining exposure. Traditional buffers (network and radial) capture at most 67% of activity space (home radial), and at worst they captured only 3.5% (school network) and range from capturing between 3 and 88% of total time. Similarly, self-drawn neighbourhoods captured only 10% of actual daily movement. Interestingly, 40% of an adolescent's self-drawn neighbourhood was not used. We also demonstrate that buffers capture a range of space (22-95%) where adolescents do not go, thus misclassifying the exposure.

CONCLUSION

Our exploratory findings demonstrate that neither researcher- nor participant-defined definition of neighbourhood adequately captures adolescent activity space. Further research with larger samples are needed to confirm the findings of this exploratory study.

Neighborhood social environments, healthy resources, and adult diabetes: Accounting for activity space exposures

This study broadens contextual environments to include adults' activity spaces-inside and outside the residential neighborhood-to examine how contextual exposures shape type 2 diabetes risk. We use novel longitudinal data from the Los Angeles Family and Neighborhood Survey, construct time-weighted exposure measures of adults' social-structural and healthy resource environments, and execute random effects logistic models predicting the probability of being diabetic. Results indicate that residential and activity space exposures are independently associated with adult diabetes, and that residential and activity space healthy resources combine to influence diabetes risk in synergistic ways. Living in more socioeconomically advantaged neighborhoods reduces diabetes risk, particularly when spending time in activity spaces with greater access to recreational facilities. Moreover, healthier activity space environments may compensate for living in neighborhoods devoid of healthy food options to lessen diabetes risk. Adopting an activity space framework can inform multilevel interventions aimed at alleviating type 2 diabetes and other chronic ailments.

An activity space approach to understanding how food access is associated with dietary intake and BMI among urban, low-income African American women

Inconclusive evidence for how food environments affect health may result from an emphasis on residential neighborhood-based measures of exposure. We used an activity space approach to examine whether 1) measures of food access and 2) associations with diet and BMI differ between residential and activity space food environments among low-income African American women in Atlanta, Georgia (n = 199). Although residential and activity space environments differed across all dimensions of food access, being located farther away from 'unhealthy' outlets was associated with lower BMI in both environments. Future research should move beyond asking whether residential and activity space environments differ, toward examining if, how, and under what conditions these differences impact the estimation of health effects.

The use and misuse of ratio and proportion exposure measures in food environment research

Background

The food stores within residential environments are increasingly investigated as a possible mechanism driving food behaviours and health outcomes. Whilst increased emphasis is being placed on the type of study designs used and how we measure the outcomes, surprisingly little attention gets diverted to the measures of the food environment beyond calls for standardised approaches for food store coding and geographic scales of exposure. Food environments are a challenging concept to measure and model and the use of ratio and proportion measures are becoming more common in food environment research. Whilst these are seemingly an advance on single store type indicators, such as simply counting the number of supermarkets or fast food restaurants present, they have several limitations that do not appear to have been fully considered.

Main body

In this article we report on five issues related to the use of ratio and proportion food environment measures: 1) binary categorisation of food stores; 2) whether they truly reflect a more or less healthy food environment; 3) issues with these measures not reflecting the quantity of food stores; 4) difficulties when no stores are present; and 5) complications in statistical treatment and interpretation of ratio and proportion measures. Each of these issues are underappreciated in the literature to date and highlight that ratio and proportion measures need to be treated with caution.

Conclusion

Calls for the broader adoption of relative food environment measures may be misguided. Whilst we should continue to search for better ways to represent the complexity of food environments, ratio and proportion measures are unlikely to be the answer.

Comparison of Geographic Information System and Subjective Assessments of Momentary Food Environments as Predictors of Food Intake: An Ecological Momentary Assessment Study

Background

It has been observed that eating is influenced by the presence and availability of food. Being aware of the presence of food in the environment may enable mobile health (mHealth) apps to use geofencing techniques to determine the most appropriate time to proactively deliver interventions. To date, however, studies on eating typically rely on self-reports of environmental contexts, which may not be accurate or feasible for issuing mHealth interventions.

Objective

This study aimed to compare the subjective and geographic information system (GIS) assessments of the momentary food environment to explore the feasibility of using GIS data to predict eating behavior and inform geofenced interventions.

Methods

In total, 72 participants recorded their food intake in real-time for 14 days using an ecological momentary assessment approach. Participants logged their food intake and responded to approximately 5 randomly timed assessments each day. During each assessment, the participants reported the number and type of food outlets nearby. Their electronic diaries simultaneously recorded their GPS coordinates. The GPS data were later overlaid with a GIS map of food outlets to produce an objective count of the number of food outlets within 50 m of the participant.

Results

Correlations between self-reported and GIS counts of food outlets within 50 m were only of a small size (r=0.17; P<.001). Logistic regression analyses revealed that the GIS count significantly predicted eating similar to the self-reported counts (area under the curve for the receiver operating characteristic curve [AUC-ROC] self-report=0.53, SE 0.00 versus AUC-ROC 50 m GIS=0.53, SE 0.00; P=.41). However, there was a significant difference between the GIS-derived and self-reported counts of food outlets and the self-reported type of food outlets (AUC-ROC self-reported outlet type=0.56, SE 0.01; P<.001).

Conclusions

The subjective food environment appears to predict eating better than objectively measured food environments via GIS. mHealth apps may need to consider the type of food outlets rather than the raw number of outlets in an individual’s environment.

Looking Back and Moving Forward: The Evolution and Potential Opportunities for the Future of Alcohol Outlet Density Measurement

The literature consistently finds that areas with greater density of alcohol outlets (places that sell alcohol) tend to have higher levels of public health harms. However, conflicting findings arise when researchers drill down to identify the type(s) of alcohol outlets with the strongest associations with harms and the mechanisms that explain these associations. These disagreements could be a result of the outdated methods commonly used to quantify the alcohol environment: counts of the number of outlets in an area. This manuscript reviews the events and ideas that shaped the literature on the physical alcohol environment. It then defines the three main methods used to measure alcohol outlet density, conducts an exploratory factor analysis to explore the constructs underlying each method, and presents a novel conceptual framework that summarizes the three methods, their respective underlying constructs, and the setting(s) in which each may be most appropriate. The framework proposes that counts of alcohol outlets measure availability, proximity to the nearest outlet measures accessibility, and spatial access measures measure access, which comprises both availability and accessibility. We argue that researchers should consider using proximity and spatial access measures when possible and outline how doing so may present opportunities to advance theory and the design and implementation of alcohol outlet zoning regulations. Finally, this manuscript draws on research from other areas of the built environment to suggest opportunities to use novel methods to overcome common hurdles (e.g., separating subtypes of outlets, ecologic designs) and a new challenge on the horizon: home delivery.

Identifying Urban Residents’ Activity Space at Multiple Geographic Scales Using Mobile Phone Data

Residents’ activity space reflects multiple aspects of human life related to space, time, and type of activity. How to measure the activity space at multiple geographic scales remains a problem to be solved. Recently, the emergence of big data such as mobile phone data and point of interest data has brought access to massive geo-tagged datasets to identify human activity at multiple geographic scales and to explore the relationship with built environment. In this research, we propose a new method to measure three types of urban residents’ activity spaces—i.e., maintenance activity space, commuting activity space, and recreational activity space—using mobile phone data. The proposed method identifies the range of three types of residents’ activity space at multiple geographic scales and analyzing the relationship between the built environment and activity space. The research takes Zhuhai City as its case study and discovers the spatial patterns for three activity space types. The proposed method enables us to achieve a better understanding of the human activities of different kinds, as well as their relationships with the built environment.

Field Validation of Commercially Available Food Retailer Data in the Netherlands

The aim of this study was to validate a Dutch commercial dataset containing information on the types and locations of food retailers against field audit data. Field validation of a commercial dataset ("Locatus") was conducted in February 2019. Data on the location and classification of food retailers were collected through field audits in 152 streets from four urban and four rural neighborhoods in the Netherlands. The classification of food retailers included eight types of grocery stores (e.g., supermarkets, bakeries) and four types of food outlets (e.g., cafés, take away restaurants). The commercial dataset in the studied area listed 322 food retailers, whereas the field audit counted 315 food retailers. Overall, the commercially available data showed "good" to "excellent" agreement statistics (>0.71) with field audit data for all three levels of analysis (i.e., location, classification and both combined) and across urban as well as rural areas. The commercial dataset under study provided an accurate description of the measured food environment. Therefore, policymakers and researchers should feel confident in using this commercial dataset as a source of secondary data.

Obesity and the Built Environment: A Reappraisal

The built environment (BE) has been viewed as an important determinant of health. Numerous studies have linked BE exposure, captured using a variety of methods, to diet quality and to area prevalence of obesity, diabetes, and cardiovascular disease. First-generation studies defined the neighborhood BE as the area around the home. Second-generation studies turned from home-centric to person-centric BE measures, capturing an individual's movements in space and time. Those studies made effective uses of global positioning system tracking devices and mobile phones, sometimes coupled with accelerometers and remote sensors. Activity space metrics explored travel paths, modes, and destinations to assess BE exposure that was both person and context specific. However, as measures of the contextual exposome have become ever more fine-grained and increasingly complex, connections to long-term chronic diseases with complex etiologies, such as obesity, are in danger of being lost. Furthermore, few studies on obesity and the BE have included intermediate energy balance behaviors, such as diet and physical activity, or explored the potential roles of social interactions or psychosocial pathways. Emerging survey-based applications that identify habitual destinations and associated travel patterns may become the third generation of tools to capture health-relevant BE exposures in the long term.

Impression formation via #foodporn: Effects of posting gender-stereotyped food pictures on instagram profiles

Previous studies suggested that food may have gender connotations and plays an important role in impression formation. Since sharing food images through social networks is becoming more and more common, the aim of the present study was to examine whether such images influence observers' judgements of a target. Specifically, we hypothesised that posting images of gender-stereotyped dishes would affect impression formation as a function of their congruence with the sex of the profile owner. In a 2 × 3 study, we varied the sex of the owner of a fictitious Instagram profile, and the image-set composition (masculine dishes vs feminine dishes vs neutral images). Subsequently, we measured the perceived femininity/masculinity, gender-stereotyped traits, and the desire to interact with the profile owner. Results confirmed that food pictures can communicate a profile owner's characteristics, showing that posting masculine dishes dampened women's femininity and the attribution of feminine traits to the target, irrespective of gender, and indirectly reduced participants' intention to meet both targets through the lower attribution of feminine traits (i.e., communion). Moreover, posting gender-congruent food images promoted the congruent gendered impression in observers (i.e., femininity for the woman and masculinity for the man) and in turn increased the desire to interact with him/her. These findings contribute to the understanding of the socio-psychological functions at the basis of sharing one's own eating/cooking experiences on social networks, showing that this behavior has an informational role for observers.

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.

Neighbourhood retail food outlet access, diet and body mass index in Canada: a systematic review

INTRODUCTION

There is growing interest in the role of food environments in suboptimal diet and overweight and obesity. This review assesses the evidence for the link between the retail food environment, diet quality and body mass index (BMI) in the Canadian population.

METHODS

We conducted a systematic keyword search in two bibliometric databases. We tabulated proportions of conclusive associations for each outcome and exposure of interest. Absolute and relative measures of exposure to the food environment were compared and theoretical framing of the associations noted. We assessed two key methodological issues identified a priori-measurement of BMI, and validation of the underlying retail food environment data.

RESULTS

Seventeen studies were included in the review. There was little evidence of a food environment-diet quality relationship and modest evidence of a food environment-BMI relationship. Relative measures of the food environment were more often associated with an outcome in the expected direction than absolute measures, but many results were inconclusive. Most studies adopted ecological theoretical frameworks but methodologies were similar regardless of stated theoretical approaches. Self-reported BMI was common and there was no "gold standard" database of food outlets nor a consensus on best ways to validate the data.

CONCLUSION

There was limited evidence of a relationship between the food environment and diet quality, but stronger evidence of a relationship between the food environment and BMI for Canadians. Studies with broad geographic scope that adopt innovative methods to measure diet and health outcomes and use relative measures of the food environment derived in geographic information systems are warranted. Consensus on a gold standard food environment database and approaches to its validation would also advance the field.

Impact of multiple food environments on body mass index

Background

Although the relationship between residential food environments and health outcomes have been extensively studied, the relationship between body mass index (BMI) and multiple food environments have not been fully explored. We examined the relationship between characteristics of three distinct food environments and BMI among elementary school employees in the metropolitan area of New Orleans, LA. We assessed the food environments around the residential and worksite neighborhoods and the commuting corridors.

Research methodology/principal findings

This study combined data from three different sources: individual and worksite data (ACTION), food retailer database (Dunn and Bradstreet), and the U.S. Census TIGER/Line Files. Spatial and hierarchical analyses were performed to explore the impact of predictors at the individual and environmental levels on BMI. When the three food environments were combined, the number of supermarkets and the number of grocery stores at residential food environment had a significant association with BMI (β = 0.56 and β = 0.24, p < 0.01), whereas the number of full-service restaurants showed an inverse relationship with BMI (β = -0.15, p < 0.001). For the commute corridor food environment, it was found that each additional fast-food restaurant in a vicinity of one kilometer traveled contributed to a higher BMI (β = 0.80, p <0.05), while adjusting for other factors. No statistical associations were found between BMI and worksite food environment.

Conclusions

The current study was the first to examine the relationship between BMI and food environments around residential neighborhoods, work neighborhoods, and the commuting corridor. Significant results were found between BMI and the availability of food stores around residential neighborhoods and the commuting corridor, adjusted for individual-level factors. This study expands the analysis beyond residential neighborhoods, illustrating the importance of multiple environmental factors in relation to BMI.

Stability of activity space footprint, size, and environmental features over six months

As activity space measures are increasingly used to estimate exposure to environmental determinants of health, little is known about the stability of these measures over time. To test the stability of GPS-derived measures of activity-space footprint, size, and environmental features over time, we compared 14-day measures at baseline and six months later for 35 adults in a large city. Activity-space measures were based on convex hulls and 500 m route buffers, and included the geographic footprint (i.e. location of the activity space), size (i.e., area in square miles; (Cummins, 2007)), and environmental features including supermarket, fast-food restaurant, and parkland density. The proportion of the participants' smaller geographic footprint covered by the larger was, on average, 0.64 (SD 0.17) for the 500 m route buffer and 0.84 (SD 0.18) for the convex hull. Mean percent change in activity space size ranged from 36.3% (mean daily 500 m route buffer) to 221.3% (cumulative convex hull). Mean percent change in the density of environmental features ranged from 28.8 to 66.5%. Forty-one percent to 92.4% of the variance at one timepoint was predicted by environmental features measured within approximately six months. Activity-space size and environmental features were moderately to highly stable over six months, although there was considerable variation in stability between measures. Strategies for addressing measurement error in studies of activity space-health associations are discussed.

Moderation of the Association Between Individual Food Security and Poor Mental Health by the Local Food Environment Among Adult Residents of Flint, Michigan

Purpose: Food insecurity is a psychosocial stressor with deleterious effects on mental health. This study examined whether the local food environment moderates the association of individual food insecurity with poor mental health. Methods: Cross-sectional survey data were collected from adult residents of Flint, Michigan (n=291), in 2015. Multivariate logistic models assessed whether quality of the local food environment moderated the relationship of food insecurity with poor mental health. A binary indicator of poor mental health was created. Participants were asked to rate their overall "mental or emotional health" using a 5-point Likert scale. Individuals were classified as having either good mental health (i.e., ratings of good, very good, or excellent) or poor mental health (i.e., ratings of fair or poor). Results: In fully adjusted models, food insecurity was associated with 3.2 (95% confidence interval [CI]: 1.6-6.2) times higher odds of poor mental health. However, increased proximate access to vegetables and fruits moderated this association. For example, those in the bottom 25th percentile of access to vegetables had 7.4 (95% CI: 2.7-20.5) times higher odds of poor mental health. In contrast, for those in the top 25th percentile of vegetable access, food insecurity was only marginally associated with poor mental health (odds ratio=2.2; 95% CI: 1.0-4.7). Conclusion: Greater proximate access to vegetables and fruits moderated food insecurity's association with poor mental health. Longitudinal evaluation of programs and policies that improve availability of nutrient-rich foods in food insecure communities is needed to determine whether they yield a mental health benefit.

A scoping review on the relations between urban form and health: a focus on Canadian quantitative evidence

INTRODUCTION

Despite the accumulating Canadian evidence regarding the relations between urban form and health behaviours, less is known about the associations between urban form and health conditions. Our study aim was to undertake a scoping review to synthesize evidence from quantitative studies that have investigated the relationship between built environment and chronic health conditions, self-reported health and quality of life, and injuries in the Canadian adult population.

METHODS

From January to March 2017, we searched 13 databases to identify peer-reviewed quantitative studies from all years that estimated associations between the objectively-measured built environment and health conditions in Canadian adults. Studies under-taken within urban settings only were included. Relevant studies were catalogued and synthesized in relation to their reported study and sample design, and health outcome and built environment features.

RESULTS

Fifty-five articles met the inclusion criteria, 52 of which were published after 2008. Most single province studies were undertaken in Ontario (n = 22), Quebec (n = 12), and Alberta (n = 7). Associations between the built environment features and 11 broad health outcomes emerged from the review, including injury (n = 19), weight status (n = 19), cardiovascular disease (n = 5), depression/anxiety (n = 5), diabetes (n = 5), mortality (n = 4), self-rated health (n = 2), chronic conditions (n = 2), metabolic condi-tions (n = 2), quality of life (n = 1), and cancer (n = 1). Consistent evidence for associations between aggregate built environment indicators (e.g., walkability) and diabetes and weight and between connectivity and route features (e.g., transportation route, trails, pathways, sidewalks, street pattern, intersections, route characteristics) and injury were found. Evidence for greenspace, parks and recreation features impacting multiple health outcomes was also found.

CONCLUSION

Within the Canadian context, the built environment is associated with a range of chronic health conditions and injury in adults, but the evidence to date has limitations. More research on the built environment and health incorporating rigorous study designs are needed to provide stronger causal evidence to inform policy and practice.

How many days of global positioning system (GPS) monitoring do you need to measure activity space environments in health research?

This study examined the number of days of global positioning system (GPS) monitoring needed to measure attributes of an individual's routine activity space. Multiple alternative activity space representations (cumulative, mean daily), measures (kernel density, route buffer, convex hull), and attributes (area size, supermarkets, fast food restaurants, parks) were examined. Results suggested wide variability in required GPS days to obtain valid estimates of activity space attributes (1-23 days). In general, fewer days were needed for mean daily activity space representations, kernel density measures, and densities of environmental exposures (vs. counts). While kernel density measures reliably estimated between-person differences in attributes after just a few days, most variability in environmental attributes for convex hull and route buffer measures was within-person. Based on these results, a minimum of 14 days of valid GPS data is recommended to measure activity spaces.

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.

Community-engaged development of a GIS-based healthfulness index to shape health equity solutions

Addressing health disparities requires both community engagement and an understanding of the social determinants of health. Although elements of the built environment can influence behavior change in public health interventions, such determinants have not been explicitly teased out via participatory mapping. An opportunity exists to integrate community voice in the development of such metrics. To fill this gap and inform the deployment of public health interventions in the Flint (USA) Center for Health Equity Solutions (FCHES), we created a means of assessing spatially-varying community needs and assets in a geographic information system (GIS), what we refer to as a healthfulness index. We engaged community and academic partners in their expert opinions on features of Flint's built environment that may promote or inhibit healthy behaviors via a multiple-criteria decision analysis framework. Experts selected from and ranked 29 variables in 6 categories (including amenities, environment, greenspace, housing, infrastructure, and social issues) using the analytic hierarchy process. The resulting matrices of expert opinions were aggregated and appended as weights for each variable's corresponding map layer. When combined through map algebra, composite scores yield spatially-varying healthfulness indices which signal any neighborhood's relative health promoting qualities (along a 0-100 scale). Results varied substantially across Flint, with the middle belt scoring highest and older neighborhoods in the northeast and north center of the city scoring lowest. Scores were aggregated to 38 Flint neighborhoods; for each of two project-specific indices, these ranged from lows of 38.7 (Hilborn Park) and 41.8 (Columbia Heights) to highs of 52.9 (College Cultural) and 58.0 (University Ave Corridor). We hypothesize that-even when controlling for individual-level factors-we will measure better and more sustained behavior change among participants living in neighborhoods with high healthfulness scores. Future work will examine this hypothesis and determine the importance of such indices in other similar communities.

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.

The "Residential" Effect Fallacy in Neighborhood and Health Studies: Formal Definition, Empirical Identification, and Correction

BACKGROUND

Because of confounding from the urban/rural and socioeconomic organizations of territories and resulting correlation between residential and nonresidential exposures, classically estimated residential neighborhood-outcome associations capture nonresidential environment effects, overestimating residential intervention effects. Our study diagnosed and corrected this "residential" effect fallacy bias applicable to a large fraction of neighborhood and health studies.

METHODS

Our empirical application investigated the effect that hypothetical interventions raising the residential number of services would have on the probability that a trip is walked. Using global positioning systems tracking and mobility surveys over 7 days (227 participants and 7440 trips), we employed a multilevel linear probability model to estimate the trip-level association between residential number of services and walking to derive a naïve intervention effect estimate and a corrected model accounting for numbers of services at the residence, trip origin, and trip destination to determine a corrected intervention effect estimate (true effect conditional on assumptions).

RESULTS

There was a strong correlation in service densities between the residential neighborhood and nonresidential places. From the naïve model, hypothetical interventions raising the residential number of services to 200, 500, and 1000 were associated with an increase by 0.020, 0.055, and 0.109 of the probability of walking in the intervention groups. Corrected estimates were of 0.007, 0.019, and 0.039. Thus, naïve estimates were overestimated by multiplicative factors of 3.0, 2.9, and 2.8.

CONCLUSIONS

Commonly estimated residential intervention-outcome associations substantially overestimate true effects. Our somewhat paradoxical conclusion is that to estimate residential effects, investigators critically need information on nonresidential places visited.

An Innovative Context-Based Crystal-Growth Activity Space Method for Environmental Exposure Assessment: A Study Using GIS and GPS Trajectory Data Collected in Chicago

Scholars in the fields of health geography, urban planning, and transportation studies have long attempted to understand the relationships among human movement, environmental context, and accessibility. One fundamental question for this research area is how to measure individual activity space, which is an indicator of where and how people have contact with their social and physical environments. Conventionally, standard deviational ellipses, road network buffers, minimum convex polygons, and kernel density surfaces have been used to represent people’s activity space, but they all have shortcomings. Inconsistent findings of the effects of environmental exposures on health behaviors/outcomes suggest that the reliability of existing studies may be affected by the uncertain geographic context problem (UGCoP). This paper proposes the context-based crystal-growth activity space as an innovative method for generating individual activity space based on both GPS trajectories and the environmental context. This method not only considers people’s actual daily activity patterns based on GPS tracks but also takes into account the environmental context which either constrains or encourages people’s daily activity. Using GPS trajectory data collected in Chicago, the results indicate that the proposed new method generates more reasonable activity space when compared to other existing methods. This can help mitigate the UGCoP in environmental health studies.

Activity space-based measures of the food environment and their relationships to food purchasing behaviours for young urban adults in Canada

OBJECTIVE

To examine the potential links between activity spaces, the food retail environment and food shopping behaviours for the population of young, urban adults.

DESIGN

Participants took part in the Canada Food Study, which collected information on demographics, food behaviour, diet and health, as well as an additional smartphone study that included a seven-day period of logging GPS (global positioning system) location and food purchases. Using a time-weighted, continuous representation of participant activity spaces generated from GPS trajectory data, the locations of food purchases and a geocoded food retail data set, negative binomial regression models were used to explore what types of food retailers participants were exposed to and where food purchases were made.

SETTING

Toronto, Montreal, Vancouver, Edmonton and Halifax, Canada.

SUBJECTS

Young adults aged 16-30 years (n 496). These participants were a subset of the larger Canada Food Study.

RESULTS

Demographics, household food shopper status and city of residence were significantly associated with different levels of exposure to various types of food retailers. Food shopping behaviours were also statistically significantly associated with demographics, the activity space-based food environment, self-reported health and city of residence.

CONCLUSIONS

The study confirms that food behaviours are related to activity space-based food environment measures, which provide a more comprehensive accounting of food retail exposure than home-based measures. In addition, exposure to food retail and food purchasing behaviours of an understudied population are described.

Using Individual GPS Trajectories to Explore Foodscape Exposure: A Case Study in Beijing Metropolitan Area

With the growing interest in studying the characteristics of people’s access to the food environment and its influence upon individual health, there has been a focus on assessing individual food exposure based on GPS trajectories. However, existing studies have largely focused on the overall activity space using short-period trajectories, which ignores the complexity of human movements and the heterogeneity of the spaces that are experienced by the individual over daily life schedules. In this study, we propose a novel framework to extract the exposure areas consisting of the localized activity spaces around daily life centers and non-motorized commuting routes from long-term GPS trajectories. The newly proposed framework is individual-specific and can incorporate the internal heterogeneity of individual activities (spatial extent, stay duration, and timing) in different places as well as the dynamics of the context. A pilot study of the GeoLife dataset suggests that there are significant variations in the magnitude as well as the composition of the food environment in different parts of the individual exposure area, and residential environment is not representative of the overall foodscape exposure.

Spatial access to food: Retiring the food desert metaphor

The food desert metaphor has been widely used over the past few decades as a way to identify regions as being at risk for having little or no access to healthy food. While the simplicity of the metaphor is attractive, this article argues that its usefulness to researchers interested in understanding the relationship between the geography of healthy food opportunities and dietary behaviours is limited. More nuanced approaches to incorporating geography into food access studies, like including transportation, economic factors, and time use, in addition to considering other dimensions of accessibility, are warranted.

The Flint Food Store Survey: combining spatial analysis with a modified Nutrition Environment Measures Survey in Stores (NEMS-S) to measure the community and consumer nutrition environments

OBJECTIVE

The goal of the present study was to use a methodology that accurately and reliably describes the availability, price and quality of healthy foods at both the store and community levels using the Nutrition Environment Measures Survey in Stores (NEMS-S), to propose a spatial methodology for integrating these store and community data into measures for defining objective food access.

SETTING

Two hundred and sixty-five retail food stores in and within 2 miles (3·2 km) of Flint, Michigan, USA, were mapped using ArcGIS mapping software.

DESIGN

A survey based on the validated NEMS-S was conducted at each retail food store. Scores were assigned to each store based on a modified version of the NEMS-S scoring system and linked to the mapped locations of stores. Neighbourhood characteristics (race and socio-economic distress) were appended to each store. Finally, spatial and kernel density analyses were run on the mapped store scores to obtain healthy food density metrics.

RESULTS

Regression analyses revealed that neighbourhoods with higher socio-economic distress had significantly lower dairy sub-scores compared with their lower-distress counterparts (β coefficient=-1·3; P=0·04). Additionally, supermarkets were present only in neighbourhoods with <60 % African-American population and low socio-economic distress. Two areas in Flint had an overall NEMS-S score of 0.

CONCLUSIONS

By identifying areas with poor access to healthy foods via a validated metric, this research can be used help local government and organizations target interventions to high-need areas. Furthermore, the methodology used for the survey and the mapping exercise can be replicated in other cities to provide comparable results.

Integrating activity spaces in health research: Comparing the VERITAS activity space questionnaire with 7-day GPS tracking and prompted recall

BACKGROUND

Accounting for daily mobility allows assessment of multiple exposure to environments. This study compares spatial data obtained (i) from an interactive map-based questionnaire on regular activity locations (VERITAS) and (ii) from GPS tracking.

METHODS

234 participants of the RECORD GPS Study completed the VERITAS questionnaire and wore a GPS tracker for 7 days. Analyses illustrate the spatial match between both datasets.

RESULTS

For half of the sample, 85.5% of GPS data fell within 500 m of a VERITAS location. The median minimum distance between a VERITAS location and a GPS coordinate ranged from 0.4 m for home to slightly over 100 m for a recreational destination.

CONCLUSIONS

There is a spatial correspondence between destinations collected through VERITAS and 7-day GPS tracking. Both collection methods offer complementary ways to assess daily mobilities, useful to study environmental determinants of health and health inequities.

Chemical and non-chemical stressors affecting childhood obesity: a systematic scoping review

Childhood obesity in the United States has doubled over the last three decades and currently affects 17% of children and adolescents. While much research has focused on individual behaviors impacting obesity, little research has emphasized the complex interactions of numerous chemical and non-chemical stressors found in a child's environment and how these interactions affect a child's health and well-being. The objectives of this systematic scoping review were to (1) identify potential chemical stressors in the context of non-chemical stressors that impact childhood obesity; and, (2) summarize our observations for chemical and non-chemical stressors in regards to child-specific environments within a community setting. A review was conducted to identify chemical and non-chemical stressors related to childhood obesity for the childhood life stages ranging from prenatal to adolescence. Stressors were identified and grouped into domains: individual behaviors, family/household behaviors, community stressors, and chemical exposures. Stressors were related to the child and the child's everyday environments and used to characterize child health and well-being. This review suggests that the interactions of chemical and non-chemical stressors are important for understanding a child's overall health and well-being. By considering these relationships, the exposure science research community can better design and implement strategies to reduce childhood obesity.

The daycourse of place

The present paper aims to contribute to the debate about the temporal relationships between place and health. It explores the notion of 'daycourse of place' echoing the discussion which recently occurred in this journal about the 'lifecourse of place' (Andrews, 2017; Lekkas et al., 2017a, b). When highlighting the importance of time in shaping health within places, most of studies focus either on the trajectories of places over a matter of years or the daily trajectories of people in link with their activity space. However, daily trajectories of places remain a poor cousin in place and health literature. This paper is intended to overcome 'jetlag', which places suffer when they are labelled with frozen attributes over a 24-h period. It explores the values and feasibility of exploring daily trajectories of places to investigate place effects on health or to design area-based interventions for public health action. More than just a metaphor, the 'daycourse of place' appears to be an inspiring framework to elaborate the importance of daily temporal relationalities for research and action in place-based health inequalities.

Investigating the importance of the local food environment for fruit and vegetable intake in older men and women in 20 UK towns: a cross-sectional analysis of two national cohorts using novel methods

BACKGROUND

Local neighbourhood environments can influence dietary behavior. There is limited evidence focused on older people who are likely to have greater dependence on local areas and may suffer functional limitations that amplify any neighbourhood impact.

METHODS

Using multi-level ordinal regression analysis we investigated the association between multiple dimensions of neighbourhood food environments (captured by fine-detail, foot-based environmental audits and secondary data) and self-reported frequency of fruit and vegetable intake. The study was a cross-sectional analysis nested within two nationally representative cohorts in the UK: the British Regional Heart Study and the British Women's Heart and Health Study. Main exposures of interest were density of food retail outlets selling fruits and vegetables, the density of fast food outlets and a novel measure of diversity of the food retail environment.

RESULTS

A total of 1124 men and 883 women, aged 69 - 92 years, living in 20 British towns were included in the analysis. There was strong evidence of an association between area income deprivation and fruit and vegetable consumption, with study members in the most deprived areas estimated to have 27% (95% CI: 7, 42) lower odds of being in a higher fruit and vegetable consumption category relative to those in the least deprived areas. We found no consistent evidence for an association between fruit and vegetable consumption and a range of other food environment domains, including density of shops selling fruits and vegetables, density of premises selling fast food, the area food retail diversity, area walkability, transport accessibility, or the local food marketing environment. For example, individuals living in areas with greatest fruit and vegetable outlet density had 2% (95% CI: -22, 21) lower odds of being in a higher fruit and vegetable consumption category relative to those in areas with no shops.

CONCLUSIONS

Although small effect sizes in environment-diet relationships cannot be discounted, this study suggests that older people are less influenced by physical characteristics of neighbourhood food environments than is suggested in the literature. The association between area income deprivation and diet may be capturing an important social aspect of neighbourhoods that influence food intake in older adults and warrants further research.

Does exposure to the food environment differ by socioeconomic position? Comparing area-based and person-centred metrics in the Fenland Study, UK

Background

Retail food environments (foodscapes) are a recognised determinant of eating behaviours and may contribute to inequalities in diet. However, findings from studies measuring socioeconomic inequality in the foodscape have been mixed, which may be due to methodological differences. The aim of this cross-sectional study was to compare exposure to the foodscape by socioeconomic position using different measures, to test whether the presence, direction or amplitude of differences was sensitive to the choice of foodscape metric or socioeconomic indicator.

Methods

A sample of 10,429 adults aged 30–64 years with valid home address data were obtained from the Fenland Study, UK. Of this sample, 7270 participants also had valid work location data. The sample was linked to data on food outlets obtained from local government records. Foodscape metrics included count, density and proximity of takeaway outlets and supermarkets, and the percentage of takeaway outlets relative to all food outlets. Exposure metrics were area-based (lower super output areas), and person-centred (proximity to nearest; Euclidean and Network buffers at 800 m, 1 km, and 1 mile). Person-centred buffers were constructed using home and work locations. Socioeconomic status was measured at the area-level (2010 Index of Multiple Deprivation) and the individual-level (highest educational attainment; equivalised household income). Participants were classified into socioeconomic groups and average exposures estimated. Results were analysed using the statistical and percent differences between the highest and lowest socioeconomic groups.

Results

In area-based measures, the most deprived areas contained higher takeaway outlet densities (p < 0.001). However, in person-centred metrics lower socioeconomic status was associated with lower exposure to takeaway outlets and supermarkets (all home-based exposures p < 0.001) and socioeconomic differences were greatest at the smallest buffer sizes. Socioeconomic differences in exposure was similar for home and combined home and work measures. Measuring takeaway exposure as a percentage of all outlets reversed the socioeconomic differences; the lowest socioeconomic groups had a higher percentage of takeaway outlets compared to the middle and highest groups (p < 0.001).

Conclusions

We compared approaches to measuring socioeconomic variation in the foodscape and found that the association was sensitive to the metric used. In particular, the direction of association varied between area- and person-centred measures and between absolute and relative outlet measures. Studies need to consider the most appropriate measure for the research question, and may need to consider multiple measures as a single measure may be context dependent.

Personal and situational predictors of everyday snacking: An application of temporal self-regulation theory

OBJECTIVES

This study aims at testing predictions derived from temporal self-regulation theory (TST) in relation to discretionary food choices (snacks). TST combines a motivational sphere of influence (cognitions and temporal valuations resulting in intentions) with a momentary sphere (encompassing social and physical environmental cues). This dual approach differs from current health behaviour theories, but can potentially improve our understanding of the interplay of personal and environmental factors in health behaviour self-regulation.

DESIGN

A mixed event-based and time-based (Ecological Momentary Assessment) study in 61 adults aged between 18 and 64, with a BMI range between 18.34 and 39.78 (M = 25.66, SD = 4.82) over two weeks.

METHODS

Participants recorded their food and drink intake for two weeks in real time using electronic diaries. Participants also responded to non-consumption assessments at random intervals throughout each day. Momentary cues (individual, situational, and environmental factors) were assessed both during food logs and non-consumption assessments. Motivational factors, past behaviour, and trait self-regulation were assessed during baseline.

RESULTS

Multilevel logistic regression analyses showed that across all snack types, environmental cues and negative affect were associated with an increased likelihood of snacking. Perceiving a cost of healthy eating to occur before eating was associated with an increased likelihood of snacking, whereas intentions and self-regulation were not.

CONCLUSIONS

Discretionary food intake is largely guided by momentary cues, and motivational-level factors, such as intention and self-regulation, are less important in the initiation of discretionary food intake. Statement of contribution What is already known on this subject? Overweight and obesity are a result of prolonged periods of energy imbalance between energy intake and expenditure (Hill & Peters, ). One of the key behavioural determinants of energy imbalances results from food intake, specifically from discretionary food choices (snacking). Temporal self-regulation theory (Hall & Fong, ) takes into account both deliberate and momentary influences on health behaviour, which is especially relevant to exploring the drivers of snacking. What does this study add? Offers new insight into the application of TST in explaining momentary eating behaviours. Snacking initiation is guided by momentary cues, not person-level factors. Dietary interventions should acknowledge the momentary cues that are associated with snacking.