Home versus nonhome neighborhood: quantifying differences in exposure to the built environment

Walking to work: The role of walkability around the workplace in a Dutch adult commuting population

Current evidence on neighborhood walkability and active commuting focuses on residential rather than workplace environment. This cross-sectional study investigated whether higher workplace walkability (WW) was associated with commute walking, both independently and together with residential walkability, using data from 6769 respondents of the 2017 Dutch national travel survey. In a fully adjusted logistic regression model, 10% increase in WW was associated with 32% higher odds of commute walking (Odds ratio (OR): 1.31, 95% Confidence Interval (CI: 1.27-1.36). The estimates were stronger in rural dwellers than urban residents, (ORrural 1.49, 95%CI: 1.34-1.64 vs ORhighly.urban 1.19, 95%CI: 1.13-1.26). In participants with both high residential walkability and WW, we observed 215% higher odds (OR 3.15, 95% CI: 2.48-3.99) of commute walking compared to those with low walkability in both. Our study indicated the importance and complementary nature of walkable residence and workplace in contribution to physical activity of working individuals through active commuting.

Creation and Validation of a New Socio-built Environment Index Measure of Opioid Overdose Risk for Use in Both Non-urban and Urban Settings

A great deal of literature has examined features of the physical built environment as predictors of opioid overdose and other substance use-related outcomes. Other literature suggests that social characteristics of settings are important predictors of substance use outcomes. However, there is a dearth of literature simultaneously measuring both physical and social characteristics of settings in an effort to better predict opioid overdose. There is also a dearth of literature examining built environment as a predictor of overdose in non-urban settings. The present study presents a novel socio-built environment index measure of opioid overdose risk comprised of indicators measuring both social and physical characteristics of settings - and developed for use in both urban and non-urban settings - and assesses its validity among 565 urban, suburban, and rural New Jersey municipalities. We found that this novel measure had good convergent validity, based on significant positive associations with a social vulnerability index and crime rates, and significant negative associations with a municipal revitalization index and high school graduation rates. The index measure had good discriminant validity, based on lack of association with three different racial isolation indices. Finally, our index measure had good health outcome-based criterion validity, based on significant positive associations with recent overdose mortality. There were no major differences between rural, suburban, and urban municipalities in validity analysis findings. This promising new socio-built environment risk index measure could improve ability to target and allocate resources to settings with the greatest risk, in order to improve their impact on overdose outcomes.

Cross-Sectional Study of Location-Based Built Environments, Physical Activity, Dietary Intake, and Body Mass Index in Adult Twins

We examined relationships between walkability and health behaviors between and within identical twin pairs, considering both home (neighborhood) walkability and each twin's measured activity space. Continuous activity and location data (via accelerometry and GPS) were obtained in 79 pairs over 2 weeks. Walkability was estimated using Walk Score^® (WS); home WS refers to neighborhood walkability, and GPS WS refers to the mean of individual WSs matched to every GPS point collected by each participant. GPS WS was assessed within (WHN) and out of the neighborhood (OHN), using 1-mile Euclidean (air1mi) and network (net1mi) buffers. Outcomes included walking and moderate-to-vigorous physical activity (MVPA) bouts, dietary energy density (DED), and BMI. Home WS was associated with WHN GPS WS (b = 0.71, SE = 0.03, p < 0.001 for air1mi; b = 0.79, SE = 0.03, p < 0.001 for net1mi), and OHN GPS WS (b = 0.18, SE = 0.04, p < 0.001 for air1mi; b = 0.22, SE = 0.04, p < 0.001 for net1mi). Quasi-causal relationships (within-twin) were observed for home and GPS WS with walking (ps < 0.01), but not MVPA, DED, or BMI. Results support previous literature that neighborhood walkability has a positive influence on walking.

Accounting for space, time, and behavior using GPS derived dynamic measures of environmental exposure

Time-weighted spatial averaging approaches (TWSA) are an increasingly utilized method for calculating exposure using global positioning system (GPS) mobility data for health-related research. They can provide a time-weighted measure of exposure, or dose, to various environments or health hazards. However, little work has been done to compare existing methodologies, nor to assess how sensitive these methods are to mobility data inputs (e.g., walking vs driving), the type of environmental data being assessed as the exposure (e.g., continuous surfaces vs points of interest), and underlying point-pattern clustering of participants (e.g., if a person is highly mobile vs predominantly stationary). Here we contrast three TWSA approaches that have been previously used or recently introduced in the literature: Kernel Density Estimation (KDE), Density Ranking (DR), and Point Overlay (PO). We feed GPS and accelerometer data from 602 participants through each method to derive time-weighted activity spaces, comparing four mobility behaviors: all movement, stationary time, walking time, and in-vehicle time. We then calculate exposure values derived from the various TWSA activity spaces with four environmental layer data types (point, line, area, surface). Similarities and differences across TWSA derived exposures for the sample and between individuals are explored, and we discuss interpretation of TWSA outputs providing recommendations for researchers seeking to apply these methods to health-related studies.

Mediating role of walking between perceived and objective walkability and cognitive function in older adults

The aim of this study was to examine the role of walking in explaining associations between perceived and objective measures of walkability and cognitive function among older adults. The study employed a cross-sectional design analyzing existing data. Data were obtained from the Adult Changes in Thought Activity Monitor study. Cognitive function and perceived walkability were measured by a survey. Objective walkability was measured using geographic information systems (GIS). Walking was measured using an accelerometer. We tested the mediating relationship based on 1,000 bootstrapped samples. Perceived walkability was associated with a 0.04 point higher cognitive function score through walking (p = 0.006). The mediating relationship accounted for 34% of the total relationship between perceived walkability and cognitive function. Walking did not have a significant indirect relationship on the association between objective walkability and cognitive function. Perceived walkability may be more relevant to walking behavior than objective walkability among older adults. Greater levels of perceived walkability may encourage older adults to undertake more walking, and more walking may in turn improve cognitive function in older adults.

Cross-sectional associations between neighbourhood walkability and objective physical activity levels in identical twins

OBJECTIVES

Physical activity is a cornerstone of chronic disease prevention and treatment, yet most US adults do not perform levels recommended for health. The neighborhood-built environment (BE) may support or hinder physical activity levels. This study investigated whether identical twins who reside in more walkable BEs have greater activity levels than twins who reside in less walkable BEs (between-twin analysis), and whether associations remain significant when controlling for genetic and shared environmental factors (within-twin analysis).

DESIGN

A cross-sectional study.

SETTING

The Puget Sound region around Seattle, Washington, USA.

PARTICIPANTS

The sample consisted of 112 identical twin pairs who completed an in-person assessment and 2-week at-home measurement protocol using a global positioning system (GPS)monitor and accelerometer.

EXPOSURE

The walkability of each participants' place of residence was calculated using three BE dimensions (intersection density, population density and destination accessibility). For each variable, z scores were calculated and summed to produce the final walkability score.

OUTCOMES

Objectively measured bouts of walking and moderate-to-vigorous physical activity (MVPA), expressed as minutes per week.

RESULTS

Walkability was associated with walking bouts (but not MVPA) within the neighbourhood, both between (b=0.58, SE=0.13, p<0.001) and within pairs (b=0.61, SE=0.18, p=0.001). For a pair with a 2-unit difference in walkability, the twin in a more walkable neighbourhood is likely to walk approximately 16 min per week more than the co-twin who lives in a less walkable neighbourhood.

CONCLUSIONS

This study provides robust evidence of an association between walkability and objective walking bouts. Improvements to the neighbourhood BE could potentially lead to increased activity levels in communities throughout the USA.

GPS-based activity space exposure to greenness and walkability is associated with increased accelerometer-based physical activity

INTRODUCTION

Built and natural environments may provide opportunities for physical activity. However, studies are limited by primarily using residential addresses to define exposure and self-report to measure physical activity. We quantified associations between global positioning systems (GPS)-based activity space measures of environmental exposure and accelerometer-based physical activity.

METHODS

Using a nationwide sample of working female adults (N = 354), we obtained seven days of GPS and accelerometry data. We created Daily Path Area activity spaces using GPS data and linked these activity spaces to spatial datasets on walkability (EPA Smart Location Database at the Census block group level) and greenness (satellite vegetation at 250 m resolution). We utilized generalized additive models to examine nonlinear associations between activity space exposures and accelerometer-derived physical activity outcomes adjusted for demographic characteristics, socioeconomic factors, and self-rated health.

RESULTS

Higher activity space walkability was associated with higher levels of moderate-vigorous physical activity, and higher activity space greenness was associated with greater numbers of steps per week. No strong relationships were observed for sedentary behavior or light physical activity. Highest levels of moderate-vigorous physical activity were observed for participants with both high walkability and high greenness in their activity spaces.

CONCLUSION

This study contributes evidence that higher levels of physical activity occur in environments with more dense, diverse, and well-connected built environments, and with higher amounts of vegetation. These data suggest that urban planners, landscape architects, and policy makers should implement and evaluate environmental interventions to encourage higher levels of physical activity.

Multi-use physical activity trails in an urban setting and cardiovascular disease: a difference-in-differences analysis of a natural experiment in Winnipeg, Manitoba, Canada

Objective

To determine if expansion of multi-use physical activity trails in an urban centre is associated with reduced rates of cardiovascular disease (CVD).

Methods

This was a natural experiment with a difference in differences analysis using administrative health records and trail-based cycling data in Winnipeg, Canada. Prior to the intervention, each year, 314,595 (IQR: 309,044 to 319,860) persons over 30 years without CVD were in the comparison group and 37,901 residents (IQR: 37,213 to 38,488) were in the intervention group. Following the intervention, each year, 303,853 (IQR: 302,843 to 304,465) persons were in the comparison group and 35,778 (IQR: 35,551 to 36,053) in the intervention group. The natural experiment was the construction of four multi-use trails, 4-7 km in length, between 2010 and 2012. Intervention and comparison areas were based on buffers of 400 m, 800 m and 1200 m from a new multi-use trail. Bicycle counts were obtained from electromagnetic counters embedded in the trail. The primary outcome was a composite of incident CVD events: CVD-related mortality, ischemic heart disease, cerebrovascular events and congestive heart failure. The secondary outcome was a composite of incident CVD risk factors: hypertension, diabetes and dyslipidemia.

Results

Between 2014 and 2018, 1,681,125 cyclists were recorded on the trails, which varied ~ 2.0-fold across the four trails (2358 vs 4264 counts/week in summer months). Between 2000 and 2018, there were 82,632 CVD events and 201,058 CVD risk events. In propensity score matched Poisson regression models, the incident rate ratio (IRR) was 1.06 (95% CI: 0.90 to 1.24) for CVD events and 0.95 (95%CI: 0.88 to 1.02) for CVD risk factors for areas within 400 m of a trail, relative to comparison areas. Sensitivity analyses indicated this effect was greatest among households adjacent to the trail with highest cycling counts (IRR = 0.85; 95% CI: 0.75 to 0.96).

Conclusions

The addition of multi-use trails was not associated with differences in CVD events or CVD risk factors, however the differences in CVD risk may depend on the level of trail use.

Trial registration

Trial registration number: NCT04057417.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12966-022-01279-z.

Geographic ecological momentary assessment methods to examine spatio-temporal exposures associated with marijuana use among young adults: A pilot study

BACKGROUND

This study demonstrates the use of geographic ecological momentary assessment (GEMA) methods among young adult marijuana users.

METHOD

Participants were 14 current marijuana users ages 21-27 living in Greater Seattle, Washington. They completed brief surveys four times per day for 14 consecutive days, including measures of marijuana use and desire to use. They also carried a GPS data logger that tracked their spatial movements over time.

RESULTS

Participants completed 80.1% of possible EMA surveys. Using the GPS data, we calculated daily number of exposures to (i.e., within 100-m of) marijuana retail outlets (mean = 3.9 times per day; SD = 4.4) and time spent per day in high poverty census tracts (mean = 7.3 h per day in high poverty census tracts; SD = 5.1).

CONCLUSIONS

GEMA may be a promising approach for studying the role spatio-temporal factors play in marijuana use and related factors.

Differential associations of the built environment on weight gain by sex and race/ethnicity but not age

OBJECTIVE

To explore the built environment (BE) and weight change relationship by age, sex, and racial/ethnic subgroups in adults.

METHODS

Weight trajectories were estimated using electronic health records for 115,260 insured Kaiser Permanente Washington members age 18-64 years. Member home addresses were geocoded using ArcGIS. Population, residential, and road intersection densities and counts of area supermarkets and fast food restaurants were measured with SmartMaps (800 and 5000-meter buffers) and categorized into tertiles. Linear mixed-effect models tested whether associations between BE features and weight gain at 1, 3, and 5 years differed by age, sex, and race/ethnicity, adjusting for demographics, baseline weight, and residential property values.

RESULTS

Denser urban form and greater availability of supermarkets and fast food restaurants were associated with differential weight change across sex and race/ethnicity. At 5 years, the mean difference in weight change comparing the 3rd versus 1st tertile of residential density was significantly different between males (-0.49 kg, 95% CI: -0.68, -0.30) and females (-0.17 kg, 95% CI: -0.33, -0.01) (P-value for interaction = 0.011). Across race/ethnicity, the mean difference in weight change at 5 years for residential density was significantly different among non-Hispanic (NH) Whites (-0.47 kg, 95% CI: -0.61, -0.32), NH Blacks (-0.86 kg, 95% CI: -1.37, -0.36), Hispanics (0.10 kg, 95% CI: -0.46, 0.65), and NH Asians (0.44 kg, 95% CI: 0.10, 0.78) (P-value for interaction <0.001). These findings were consistent for other BE measures.

CONCLUSION

The relationship between the built environment and weight change differs across demographic groups. Careful consideration of demographic differences in associations of BE and weight trajectories is warranted for investigating etiological mechanisms and guiding intervention development.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

International evaluation of the Microscale Audit of Pedestrian Streetscapes (MAPS) Global instrument: comparative assessment between local and remote online observers

OBJECTIVES

The use of online imagery by non-local observers to conduct remote, centralized collection of streetscape audit data in international studies has the potential to enhance efficiency of collection and comparability of such data for research on built environments and health. The objectives of the study were to measure (1) the consistency in responses between local in-field observers and non-local remote online observers and (2) the reliability between in-country online observers and non-local remote online observers using the Microscale Audit of Pedestrian Streetscapes Global tool to characterize pedestrian-related features along streets in five countries.

METHODS

Consistency and inter-rater reliability were analyzed between local and non-local observers on a pooled database of 200 routes in five study regions (Melbourne, Australia; Ghent, Belgium; Curitiba, Brazil; Hong Kong, China; and Valencia, Spain) for microscale environmental feature subscales and item-level variables using the intraclass correlation coefficient (ICC).

RESULTS

A local in-field versus remote online comparison had an ICC of 0.75 (95 % CI: 0.68-0.80) for the grand total score. An ICC of 0.91 (95 % CI: 0.88-0.93) was found for the local online versus remote online comparison. Positive subscales yielded stronger results in comparison to negative subscales, except for the similarly poor-performing positive aesthetics/social characteristics.

CONCLUSIONS

This study demonstrated remote audits of microscale built environments using online imagery had good reliability with local in-field audits and excellent reliability with local online audits. Results generally supported remote online environmental audits as comparable to local online audits. This identification of low-cost and efficient data acquisition methods is important for expanding research on microscale built environments and physical activity globally.

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.

Perceived neighbourhood characteristics and depressive symptoms: Potential mediators and the moderating role of employment status

Multiple neighbourhood characteristics have been linked to depressive symptoms. However, few studies have simultaneously considered multiple mechanisms that explain this relationship, and how they might interact. Further, most studies regard exposure to the residential environment as constant, and therefore disregard variation in exposure by individual factors. This study investigates whether and to what extent stress and physical activity mediate the association between neighbourhood characteristics and depression, and also to what extent employment status moderates this relationship. A population-representative survey of n = 11,505 people in the Netherlands was conducted. Depressive symptoms were measured using the Patient Health Questionnaire (PHQ-9). Neighbourhood characteristics were perceived green and blue space, pleasantness, environmental disturbance, social cohesion and safety. Employment status was combined with place of work to establish two groups: those who were non-working or who worked from home ('at home'), and those who worked somewhere outside of the home ('working'). Multi-group structural equation modelling was employed to understand the theorised relationships for both groups. Perceived environmental disturbance, social cohesion and safety were significantly indirectly related to depressive symptoms via stress, with larger effect sizes in the 'at home' group. Pleasantness was also significantly indirectly related to depressive symptoms via stress, in the 'at home' group only. There was no evidence for physical activity as a mediator. Our findings suggest that neighbourhood social characteristics may have a greater influence on depressive symptoms than physical characteristics. Stress appears to be a key mediator of this relationship. In addition, the neighbourhood appears to exert a greater influence on those who spend more time in their neighbourhood. Interventions to promote mental health should focus on the social environment, and in particular pay attention to those who are spatially confined in poorer quality neighbourhoods.

Influence of travel behaviour and daily mobility on exposure to traffic-related air pollution

This study evaluates the daily exposure of urban residents across various commuting modes and destinations by intersecting data from a travel survey with exposure surfaces for ultrafine particles and black carbon, in Toronto, Canada. We demonstrate that exposure misclassification is bound to arise when we approximate daily exposure with the concentration at the home location. We also identify potential inequities in the distribution of exposure to traffic-related air pollution whereby those who are mostly responsible for the generation of traffic-related air pollution (drivers and passengers) are exposed the least while active commuters and transit riders, are exposed the most.

How do natural features in the residential environment influence women's self-reported general health? Results from cross-sectional analyses of a U.S. national cohort

BACKGROUND

The relationship between health and human interaction with nature is complex. Here we conduct analyses to provide insights into potential health benefits related to residential proximity to nature.

OBJECTIVES

We aimed to examine associations between measures of residential nature and self-reported general health (SRGH), and to explore mediation roles of behavioral, social, and air quality factors, and variations in these relationships by urbanicity and regional climate.

METHODS

Using residential addresses for 41,127 women from the Sister Study, a U.S.-based national cohort, we derived two nature exposure metrics, canopy and non-gray cover, using Percent Tree Canopy and Percent Developed Imperviousness from the National Land Cover Database. Residential circular buffers of 250 m and 1250 m were considered. Gradient boosted regression trees were used to model the effects of nature exposure on the odds of reporting better SRGH (Excellent/Very Good versus the referent, Good/Fair/Poor). Analyses stratified by urbanicity and regional climate (arid, continental, temperate) and mediation by physical activity, social support, and air quality were conducted.

RESULTS

A 10% increase in canopy and non-gray cover within 1250 m buffer was associated with 1.02 (95% CI: 1.00-1.03) and 1.03 (95% CI: 1.01-1.04) times the odds of reporting better SRGH, respectively. Stronger associations were observed for the urban group and for continental climate relative to other strata. Social support and physical activity played a more significant mediation role than air quality for the full study population.

DISCUSSION

Findings from this study identified a small but important beneficial association between residential nature and general health. These findings could inform community planning and investments in neighborhood nature for targeted health improvements and potential societal and environmental co-benefits.

Residential neighbourhood greenspace is associated with reduced risk of cardiovascular disease: A prospective cohort study

Background

Living in a greener neighbourhood may reduce the risk of developing incident cardiovascular disease, but evidence is limited by reliance on cross-sectional comparisons. We use data from a longitudinal study with a time-independent measure of risk to explore the association between exposure to greenspace and cardiovascular disease.

Methods

Data was from the European Prospective Investigation of Cancer Norfolk UK cohort, baseline 1993–1997 (n = 24,420). Neighbourhoods were defined as 800m radius zones around participants’ home, according to their home postcode (zip code) in the year 2000. Greenspace exposure was identified using classified satellite imagery. Adjusted Cox proportional hazards regression examined associations between greenspace and incident cardiovascular disease. Mediation analysis assessed if physical activity mediated associations, whilst modification by rurality, socio-economic status and age was explored.

Results

The mean age of participants was 59.2 years at baseline, 54.7% were female, and mean follow-up time was 14.5 years. Individuals living in the greenest neighbourhood quartile had a 7% lower relative hazard of developing cardiovascular disease than other neighbourhoods (HR 0.93; 95% CI 0.88, 0.97; p = 0.003) after adjusting for age, sex, BMI, prevalent diabetes and socio-economic status (SES). Physical activity did not mediate the relationship (greenest compared to the least green quartile HR 0.99; 95% CI 0.97, 1.01; p = 0.416). Models predicted incidence of cardiovascular disease in the least green neighbourhoods (19.4% greenspace on average) would fall by 4.8% (95% CI 1.6%, 8.2% p = 0.003) if they were as green as the average neighbourhood (59.0% greenspace). Occupation moderated the relationship, whereby exposure to greenspace was not associated with incident CVD for participants engaged in manual occupations.

Conclusions

Greener home neighbourhoods may protect against risk of cardiovascular disease even after accounting for SES, whilst the mechanism does not appear to be strongly associated with physical activity. Putative causal mechanisms require investigation.

Neighborhood effect and obesity in adult survivors of pediatric cancer: A report from the St. Jude lifetime cohort study

Survivors of childhood cancer are at risk for obesity, a condition potentially modifiable if dietary intake and physical activity are optimized. These health behaviors are likely influenced by neighborhood of residence, a determinant of access to healthy, affordable food and safe and easy exercise opportunities. We examined associations between neighborhood level factors and obesity among survivors in the St. Jude Lifetime cohort and community comparison group members. Persons with residential addresses available for geocoding were eligible for analysis (n = 2,265, mean age 32.5 [SD 9.1] years, 46% female, 85% white). Survivors completed questionnaires regarding individual behaviors; percent body fat was assessed via dual X-ray absorptiometry (obesity: ≥25% males; ≥35% females); neighborhood effect was characterized using census tract of residence (e.g., neighborhood socioeconomic status [SES], rurality). Structural equation modeling was used to determine associations between neighborhood effect, physical activity, diet, smoking, treatment exposures and obesity. Obese survivors (n = 1,420, 62.7%) were more likely to live in neighborhoods with lower SES (RR: 1.23, 95% CI: 1.10-1.38) and rural areas (RR: 1.22, 95% CI: 1.07-1.39) compared to survivors with normal percent body fat. Resource-poor neighborhoods (standardized effect: 0.06, p < 0.001) and cranial radiation (0.16, p < 0.001) had direct effects on percent body fat. Associations between neighborhood of residence and percent body fat were increased (0.01, p = 0.04) among individuals with a poor diet. Neighborhoods where survivors reside as an adult is associated with obesity. Interventions targeting survivors should incorporate strategies that address environmental influences on obesity.

Cross-Country Comparison of School Neighborhood Food Environments in Houston, Texas and Guadalajara, Mexico

Studies in the U.S. and Mexico have observed the clustering of food resources around schools, which may promote the use of these resources. Our study characterized and compared school neighborhood food environments in Guadalajara, Jalisco, and Houston, Texas, and examined socioeconomic disparities in food resource availability across school neighborhoods. We used the Goods and Services Inventory to document the frequency and type of resources within each school neighborhood. School neighborhoods in Guadalajara had significantly more food resources than those in Houston. We found that convenience stores and table service restaurants were the most prevalent food resources in school neighborhoods in both cities. Guadalajara school neighborhoods had a higher prevalence of supermarkets and grocery stores than Houston. Low-income school neighborhoods in Guadalajara with poorly educated residents had significantly more food carts than high-income neighborhoods with more educated residents. In Houston, we found significantly more fast food restaurants and convenience stores in school neighborhoods with more educated residents than school neighborhoods with less educated residents. The influence of food resources within school neighborhoods on the dietary habits of schoolchildren should be further explored in both the U.S. and Mexico. The characterization of school neighborhood food environments can inform policymakers, city planners, and school officials who seek to implement policies to create healthier food environments.

Probabilistic walking models using built environment and sociodemographic predictors

Background

Individual sociodemographic and home neighborhood built environment (BE) factors influence the probability of engaging in health-enhancing levels of walking or moderate-to-vigorous physical activity (MVPA). Methods are needed to parsimoniously model the associations.

Methods

Participants included 2392 adults drawn from a community-based twin registry living in the Seattle region. Objective BE measures from four domains (regional context, neighborhood composition, destinations, transportation) were taken for neighborhood sizes of 833 and 1666 road network meters from home. Hosmer and Lemeshow’s methods served to fit logistic regression models of walking and MVPA outcomes using sociodemographic and BE predictors. Backward elimination identified variables included in final models, and comparison of receiver operating characteristic (ROC) curves determined model fit improvements.

Results

Built environment variables associated with physical activity were reduced from 86 to 5 or fewer. Sociodemographic and BE variables from all four BE domains were associated with activity outcomes but differed by activity type and neighborhood size. For the study population, ROC comparisons indicated that adding BE variables to a base model of sociodemographic factors did not improve the ability to predict walking or MVPA.

Conclusions

Using sociodemographic and built environment factors, the proposed approach can guide the estimation of activity prediction models for different activity types, neighborhood sizes, and discrete BE characteristics. Variables associated with walking and MVPA are population and neighborhood BE-specific.

Electronic supplementary material

The online version of this article (10.1186/s12963-019-0186-8) contains supplementary material, which is available to authorized users.

How Do Neighbourhood Definitions Influence the Associations between Built Environment and Physical Activity?

Researchers investigating relationships between the neighbourhood environment and health first need to decide on the spatial extent of the neighbourhood they are interested in. This decision is an important and ongoing methodological challenge since different methods of defining and delineating neighbourhood boundaries can produce different results. This paper explores this issue in the context of a New Zealand-based study of the relationship between the built environment and multiple measures of physical activity. Geographic information systems were used to measure three built environment attributes-dwelling density, street connectivity, and neighbourhood destination accessibility-using seven different neighbourhood definitions (three administrative unit boundaries, and 500, 800, 1000- and 1500-m road network buffers). The associations between the three built environment measures and five measures of physical activity (mean accelerometer counts per hour, percentage time in moderate-vigorous physical activity, self-reported walking for transport, self-reported walking for recreation and self-reported walking for all purposes) were modelled for each neighbourhood definition. The combination of the choice of neighbourhood definition, built environment measure, and physical activity measure determined whether evidence of an association was detected or not. Results demonstrated that, while there was no single ideal neighbourhood definition, the built environment was most consistently associated with a range of physical activity measures when the 800-m and 1000-m road network buffers were used. For the street connectivity and destination accessibility measures, associations with physical activity were less likely to be detected at smaller scales (less than 800 m). In line with some previous research, this study demonstrated that the choice of neighbourhood definition can influence whether or not an association between the built environment and adults' physical activity is detected or not. This study additionally highlighted the importance of the choice of built environment attribute and physical activity measures. While we identified the 800-m and 1000-m road network buffers as the neighbourhood definitions most consistently associated with a range of physical activity measures, it is important that researchers carefully consider the most appropriate type of neighbourhood definition and scale for the particular aim and participants, especially at smaller scales.

The Moving to Health (M2H) approach to natural experiment research: A paradigm shift for studies on built environment and health

Improving the built environment (BE) is viewed as one strategy to improve community diets and health. The present goal is to review the literature on the effects of BE on health, highlight its limitations, and explore the growing use of natural experiments in BE research, such as the advent of new supermarkets, revitalized parks, or new transportation systems. Based on recent studies on movers, a paradigm shift in built-environment health research may be imminent. Following the classic Moving to Opportunity study in the US, the present Moving to Health (M2H) strategy takes advantage of the fact that changing residential location can entail overnight changes in multiple BE variables. The necessary conditions for applying the M2H strategy to Geographic Information Systems (GIS) databases and to large longitudinal cohorts are outlined below. Also outlined are significant limitations of this approach, including the use of electronic medical records in lieu of survey data. The key research question is whether documented changes in BE exposure can be linked to changes in health outcomes in a causal manner. The use of geo-localized clinical information from regional health care systems should permit new insights into the social and environmental determinants of health.

Higher residential and employment densities are associated with more objectively measured walking in the home neighborhood

Understanding where people walk and how the built environment influences walking is a priority in active living research. Most previous studies were limited by self-reported data on walking. In the present study, walking bouts were determined by integrating one week of accelerometry, GPS, and a travel log data among 675 adult participants in the baseline sample of the Travel Assessment and Community study. Home neighborhood was defined as being within 0.5 mi of each participants' residence (a 10-minute walk), with home neighborhood walking defined as walking bout lines with at least one GPS point within the home neighborhood. Home neighborhood walkability was constructed with seven built environment variables derived from spatially continuous objective values (SmartMaps). A Zero Inflated Negative Binomial (ZINB) served to estimate associations between home neighborhood environment characteristics and home neighborhood walking frequency. Higher residential density and job density were the two neighborhood walkability measures related to higher likelihood and more time walking in the home neighborhood, highest tertile residential density (22.44 - 62.63 unit/acre) (coefficient=1.434; 95th CI of 1.003, 2.049) and highest tertile job density (12.4 - 272.3 jobs/acre) (coefficient=1.616; 95th CI of 1.102, 2.370). The large proportion of walking that takes place in the home neighborhood highlights the importance of continuing to examine the impact of the home neighborhood environment on walking. Potential interventions to increase walking behavior may benefit from increasing residential and employment density within residential areas.

Associations between spatial access to physical activity facilities and frequency of physical activity; how do home and workplace neighbourhoods in West Central Scotland compare?

BACKGROUND

Over a third of the Scottish population do not meet physical activity (PA) recommendations, with a greater proportion of those from disadvantaged areas not meeting recommended levels. There is a great need for detailed understanding of why some people are active while others are not. It has been established that features within home neighbourhoods are important for promoting PA, and although around 60% of time spent in exercise daily is undertaken outside the residential environment, relatively little research includes both home and workplace neighbourhood contexts. This study utilised an existing west central Scotland survey and spatial data on PA facilities to examine whether, for working adults, there are links between access to facilities, within home and workplace neighbourhoods, and frequency of PA, and whether such associations differ by socio-economic group.

METHODS

Using a Geographic Information System (GIS), home and workplace postcodes of a sub-sample of 'Transport, Health and Well-being' 2010 study respondents (n = 513) were mapped, along with public (i.e. public-sector funded) and private (i.e. private-sector funded) PA facilities (e.g. sports halls, gyms, pools etc.) within 800 m and 1600 m path/street network buffers of home and workplace postcodes. Using Analysis of Variance, associations between spatial access to PA facilities (i.e. facility counts within buffers) and self-reported PA (i.e. days being physically active in past month) were analysed. Models were run separately for access to any, public, private, and home, workplace, and home/workplace facilities. Associations were examined for all respondents, and stratified by age and income deprivation.

RESULTS

Respondents' PA frequency was associated with spatial access to specific types of facilities near home and near home or workplace (combined). In general, PA frequency was higher where individuals lived/worked in closer proximity to private facilities and frequency lower where individuals lived/worked nearby to public facilities. Results varied by age and income deprivation sub-groups.

CONCLUSION

This research contributes to methods exploring neighbourhood contextual influences on PA behaviour; it goes beyond a focus upon home neighbourhoods and incorporates access to workplace neighbourhood facilities. Results demonstrate the importance of examining both neighbourhood types, and such findings may feed into planning for behaviour-change interventions within both spaces.

Fast-food outlet availability and obesity: Considering variation by age and methodological diversity in 22,889 Yorkshire Health Study participants

This study investigated if the relationship between residential fast-food outlet availability and obesity varied due to methodological diversity or by age. Cross-sectional data (n = 22,889) from the Yorkshire Health Study, England were used. Obesity was defined using self-reported height and weight (BMI ≥ 30). Food outlets ("fast-food", "large supermarkets", and "convenience or other food retail outlets") were mapped using Ordnance Survey Points of Interest (PoI) database. Logistic regression was used for all analyses. Methodological diversity included adjustment for other food outlets as covariates and continuous count vs. quartile. The association between residential fast-food outlets and obesity was inconsistent and effects remained substantively the same when considering methodological diversity. This study contributes to evidence by proposing the use of a more comprehensive conceptual model adjusting for wider markers of the food environment. This study offers tentative evidence that the association between fast-food outlets and obesity varies by age.

Association between residential self-selection and non-residential built environment exposures

Studies employing 'activity space' measures of the built environment do not always account for how individuals self-select into different residential and non-residential environments when testing associations with physical activity. To date, no study has examined whether preferences for walkable residential neighborhoods predict exposure to other walkable neighborhoods in non-residential activity spaces. Using a sample of 9783 university students from Toronto, Canada, we assessed how self-reported preferences for a walkable neighborhood predicted their exposure to other walkable, non-residential environments, and further whether these preferences confounded observed walkability-physical activity associations. We found that residential walkability preferences and non-residential walkability were significant associated (β = 0.42, 95% CI: (0.37, 0.47)), and further that these preferences confounded associations between non-residential walkability exposure and time spent walking (reduction in association = 10.5%). These results suggest that self-selection factors affect studies of non-residential built environment exposures.

Geographic Accessibility Of Food Outlets Not Associated With Body Mass Index Change Among Veterans, 2009-14

In recent years, various levels of government in the United States have adopted or discussed subsidies, tax breaks, zoning laws, and other public policies that promote geographic access to healthy food. However, there is little evidence from large-scale longitudinal or quasi-experimental research to suggest that the local mix of food outlets actually affects body mass index (BMI). We used a longitudinal design to examine whether the proximity of food outlets, by type, was associated with BMI changes between 2009 and 2014 among 1.7 million veterans in 382 metropolitan areas. We found no evidence that either absolute or relative geographic accessibility of supermarkets, fast-food restaurants, or mass merchandisers was associated with changes in an individual's BMI over time. While policies that alter only geographic access to food outlets may promote equitable access to healthy food and improve nutrition, our findings suggest they will do little to combat obesity in adults.

Work and Home Neighborhood Design and Physical Activity

PURPOSE

To investigate relations of perceived worksite neighborhood environments to total physical activity and active transportation, over and above home neighborhood built environments.

DESIGN

Observational epidemiologic study.

SETTING

Baltimore, Maryland-Washington, DC, and Seattle-King County, Washington metropolitan areas.

PARTICIPANTS

One thousand eighty-five adults (mean age = 45.0 [10.2]; 46% women) recruited from 32 neighborhoods stratified by high/low neighborhood income and walkability.

MEASURES

The Neighborhood Environment Walkability Survey assessed perceptions of worksite and home neighborhood environments. Accelerometers assessed total moderate-to-vigorous physical activity (MVPA). The International Physical Activity Questionnaire assessed total active transportation and active transportation to and around work.

ANALYSIS

Mixed-effects regression tested relations of home and worksite neighborhood environments to each physical activity outcome, adjusted for demographics.

RESULTS

Home and worksite mixed land use and street connectivity had the most consistent positive associations with physical activity outcomes. Worksite traffic and pedestrian safety were also associated with multiple physical activity outcomes. The worksite neighborhood explained additional variance in physical activity outcomes than explained by the home neighborhood. Worksite and home neighborhood environments interacted in explaining active transportation to work, with the greatest impacts occurring when both neighborhoods were activity supportive.

CONCLUSION

Both worksite and home neighborhood environments were independently related to total MVPA and active transportation. Community design policies should target improving the physical activity supportiveness of worksite neighborhood environments and integrating commercial and residential development.

Mobile Phone Ownership Is Not a Serious Barrier to Participation in Studies: Descriptive Study

BACKGROUND

Rather than providing participants with study-specific data collection devices, their personal mobile phones are increasingly being used as a means for collecting geolocation and ecological momentary assessment (EMA) data in public health research.

OBJECTIVE

The purpose of this study was to (1) describe the sociodemographic characteristics of respondents to an online survey screener assessing eligibility to participate in a mixed methods study collecting geolocation and EMA data via the participants' personal mobile phones, and (2) examine how eligibility criteria requiring mobile phone ownership and an unlimited text messaging plan affected participant inclusion.

METHODS

Adult (≥18 years) daily smokers were recruited via public advertisements, free weekly newspapers, printed flyers, and word of mouth. An online survey screener was used as the initial method of determining eligibility for study participation. The survey screened for twenty-eight inclusion criteria grouped into three categories, which included (1) cell phone use, (2) tobacco use, and (3) additional criteria.

RESULTS

A total of 1003 individuals completed the online screener. Respondents were predominantly African American (605/1003, 60.3%) (60.4%), male (514/1003, 51.3%), and had a median age of 35 years (IQR 26-50). Nearly 50% (496/1003, 49.5%) were unemployed. Most smoked menthol cigarettes (699/1003, 69.7%), and had a median smoking history of 11 years (IQR 5-21). The majority owned a mobile phone (739/1003, 73.7%), could install apps (86.8%), used their mobile phone daily (89.5%), and had an unlimited text messaging plan (871/1003, 86.8%). Of those who completed the online screener, 302 were eligible to participate in the study; 163 were eligible after rescreening, and 117 were enrolled in the study. Compared to employed individuals, a significantly greater proportion of those who were unemployed were ineligible for the study based on mobile phone inclusion criteria (P<.001); yet, 46.4% (333/717) of the individuals who were unemployed met all mobile phone inclusion criteria.

CONCLUSIONS

Inclusion criteria requiring participants to use their personal mobile phones for data collection was not a major barrier to study participation for most respondents who completed the online screener, including those who were unemployed.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02261363; https://clinicaltrials.gov/ct2/show/NCT02261363 (Archived by WebCite at http://www.webcitation.org/6wOmDluSt).

Toward dynamic urban environmental exposure assessments in mental health research

It is increasingly recognized that mental disorders are affected by both personal characteristics and environmental exposures. The built, natural, and social environments can either contribute to or buffer against metal disorders. Environmental exposure assessments related to mental health typically rely on neighborhoods within which people currently live. In this article, I call into question such neighborhood-based exposure assessments at one point in time, because human life unfolds over space and across time. To circumvent inappropriate exposure assessments and to better grasp the etiologies of mental disease, I argue that people are exposed to multiple health-supporting and harmful exposures not only during their daily lives, but also over the course of their lives. This article aims to lay a theoretical foundation elucidating the impact of dynamic environmental exposures on mental health outcomes. I examine, first, the possibilities and challenges for mental health research to integrate people's environmental exposures along their daily paths and, second, how exposures over people's residential history might affect mental health later in life. To push the borders of scientific inquiries, I stress that only such mobility-based approaches facilitate an exploration of exposure duration, exposure sequences, and exposure accumulation.

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.

Differences in Behavior, Time, Location, and Built Environment between Objectively Measured Utilitarian and Recreational Walking

OBJECTIVES

Utilitarian and recreational walking both contribute to physical activity. Yet walking for these two purposes may be different behaviors. We sought to provide operational definitions of utilitarian and recreational walking and to objectively measure their behavioral, spatial, and temporal differences in order to inform transportation and public health policies and interventions.

METHODS

Data were collected 2008-2009 from 651 Seattle-King County residents, wearing an accelerometer and a GPS unit, and filling-in a travel diary for 7 days. Walking activity bouts were classified as utilitarian or recreational based on whether walking had a destination or not. Differences between the two walking purposes were analyzed, adjusting for the nested structure of walking activity within participants.

RESULTS

Of the 4,905 observed walking bouts, 87.4% were utilitarian and 12.6% recreational walking. Utilitarian walking bouts were 45% shorter in duration (-12.1 min) and 9% faster in speed (+0.3km/h) than recreational walking bouts. Recreational walking occurred more frequently in the home neighborhood and was not associated with recreational land uses. Utilitarian walking occurred in areas having higher residential, employment, and street density, lower residential property value, higher area percentage of mixed-use neighborhood destinations, lower percentage of parks/trails, and lower average topographic slope than recreational walking.

CONCLUSION

Utilitarian and recreational walking are substantially different in terms of frequency, speed, duration, location, and related built environment. Policies that promote walking should adopt type-specific strategies. The high occurrence of recreational walking near home highlights the importance of the home neighborhood for this activity.

Increased Walking's Additive and No Substitution Effect on Total Physical Activity

PURPOSE

We assessed the associations between a change in time spent walking and a change in total physical activity (PA) time within an urban living adult sample to test for additive or substitution effects.

METHODS

Participants living in the greater Seattle area were assessed in 2008-2009 and again 1-2 yr later (2010-2011). At each time point, they wore accelerometers and GPS units and recorded trips and locations in a travel diary for seven consecutive days. These data streams were combined to derive a more objective estimate of walking and total PA. Participants also completed the International Physical Activity Questionnaire to provide self-reported estimates of walking and total PA. Regression analyses assessed the associations between within-participant changes in objective and self-reported walking and total PA.

RESULTS

Data came from 437 participants. On average, a 1-min increase in total walking was associated with an increase in total PA of 1 min, measured by objective data, and 1.2-min, measured by self-reported data. A similar additive effect was consistently found with utilitarian, transportation, or job-related walking, measured by both objective and self-reported data. For recreational walking, the effect of change was mixed between objective and self-reported results.

CONCLUSION

Both objective and self-reported data confirmed an additive effect of utilitarian and total walking on PA.

The association between air pollution and type 2 diabetes in a large cross-sectional study in Leicester: The CHAMPIONS Study

BACKGROUND

Observational evidence suggests there is an association between air pollution and type 2 diabetes; however, there is high risk of bias.

OBJECTIVE

To investigate the association between air pollution and type 2 diabetes, while reducing bias due to exposure assessment, outcome assessment, and confounder assessment.

METHODS

Data were collected from 10,443 participants in three diabetes screening studies in Leicestershire, UK. Exposure assessment included standard, prevailing estimates of outdoor nitrogen dioxide and particulate matter concentrations in a 1×1km area at the participant's home postcode. Three-year exposure was investigated in the primary analysis and one-year exposure in a sensitivity analysis. Outcome assessment included the oral glucose tolerance test for type 2 diabetes. Confounder assessment included demographic factors (age, sex, ethnicity, smoking, area social deprivation, urban or rural location), lifestyle factors (body mass index and physical activity), and neighbourhood green space.

RESULTS

Nitrogen dioxide and particulate matter concentrations were associated with type 2 diabetes in unadjusted models. There was no statistically significant association between nitrogen dioxide concentration and type 2 diabetes after adjustment for demographic factors (odds: 1.08; 95% CI: 0.91, 1.29). The odds of type 2 diabetes was 1.10 (95% CI: 0.92, 1.32) after further adjustment for lifestyle factors and 0.91 (95% CI: 0.72, 1.16) after yet further adjustment for neighbourhood green space. The associations between particulate matter concentrations and type 2 diabetes were also explained away by demographic factors. There was no evidence of exposure definition bias.

CONCLUSIONS

Demographic factors seemed to explain the association between air pollution and type 2 diabetes in this cross-sectional study. High-quality longitudinal studies are needed to improve our understanding of the association.

GPS or travel diary: Comparing spatial and temporal characteristics of visits to fast food restaurants and supermarkets

To assess differences between GPS and self-reported measures of location, we examined visits to fast food restaurants and supermarkets using a spatiotemporal framework. Data came from 446 participants who responded to a survey, filled out travel diaries of places visited, and wore a GPS receiver for seven consecutive days. Provided by Public Health Seattle King County, addresses from food permit data were matched to King County tax assessor parcels in a GIS. A three-step process was used to verify travel-diary reported visits using GPS records: (1) GPS records were temporally matched if their timestamps were within the time window created by the arrival and departure times reported in the travel diary; (2) the temporally matched GPS records were then spatially matched if they were located in a food establishment parcel of the same type reported in the diary; (3) the travel diary visit was then GPS-sensed if the name of food establishment in the parcel matched the one reported in the travel diary. To account for errors in reporting arrival and departure times, GPS records were temporally matched to three time windows: the exact time, +/- 10 minutes, and +/- 30 minutes. One third of the participants reported 273 visits to fast food restaurants; 88% reported 1,102 visits to supermarkets. Of these, 77.3 percent of the fast food and 78.6 percent supermarket visits were GPS-sensed using the +/-10-minute time window. At this time window, the mean travel-diary reported fast food visit duration was 14.5 minutes (SD 20.2), 1.7 minutes longer than the GPS-sensed visit. For supermarkets, the reported visit duration was 23.7 minutes (SD 18.9), 3.4 minutes longer than the GPS-sensed visit. Travel diaries provide reasonably accurate information on the locations and brand names of fast food restaurants and supermarkets participants report visiting.

GPS-Based Exposure to Greenness and Walkability and Accelerometry-Based Physical Activity

Background: Physical inactivity is a risk factor for cancer that may be influenced by environmental factors. Indeed, dense and well-connected built environments and environments with natural vegetation may create opportunities for higher routine physical activity. However, studies have focused primarily on residential environments to define exposure and self-reported methods to estimate physical activity. This study explores the momentary association between minute-level global positioning systems (GPS)-based greenness exposure and time-matched objectively measured physical activity.Methods: Adult women were recruited from sites across the United States. Participants wore a GPS device and accelerometer on the hip for 7 days to assess location and physical activity at minute-level epochs. GPS records were linked to 250 m resolution satellite-based vegetation data and Census Block Group-level U.S. Environmental Protection Agency (EPA) Smart Location Database walkability data. Minute-level generalized additive mixed models were conducted to test for associations between GPS measures and accelerometer count data, accounting for repeated measures within participant and allowing for deviations from linearity using splines.Results: Among 360 adult women (mean age of 55.3 ± 10.2 years), we observed positive nonlinear relationships between physical activity and both greenness and walkability. In exploratory analyses, the relationships between environmental factors and physical activity were strongest among those who were white, had higher incomes, and who were middle-aged.Conclusions: Our results indicate that higher levels of physical activity occurred in areas with higher greenness and higher walkability.Impact: Findings suggest that planning and design policies should focus on these environments to optimize opportunities for physical activity. Cancer Epidemiol Biomarkers Prev; 26(4); 525-32. ©2017 AACRSee all the articles in this CEBP Focus section, "Geospatial Approaches to Cancer Control and Population Sciences."

Built Environment and Depression in Low-Income African Americans and Whites

INTRODUCTION

Urban environments are associated with a higher risk of adverse mental health outcomes; however, it is unclear which specific components of the urban environment drive these associations.

METHODS

Using data collected in 2002-2009 from 73,225 low-income, racially diverse individuals across the Southeastern U.S., analyses evaluated the cross-sectional relationship between a walkability index and depression. Walkability was calculated from population density, street connectivity, and destination count in the 1,200-meter area around participants' homes, and depression was measured using the Center for Epidemiologic Studies Depression Scale for depression symptomatology and questionnaire responses regarding doctor-diagnosed depression and antidepressant use. Data were analyzed in 2015.

RESULTS

Participants living in neighborhoods with the highest walkability index had 6% higher odds of moderate or greater depression symptoms (score ≥15, 95% CI=0.99, 1.14), 28% higher odds of doctor-diagnosed depression (95% CI=1.20, 1.36), and 16% higher odds of current antidepressant use (95% CI=1.08, 1.25), compared with those in the lowest walkability index. Higher walkability was associated with higher odds of depression symptoms in the most deprived neighborhoods only, whereas walkability was associated with lower odds of depression symptoms in the least deprived neighborhoods.

CONCLUSIONS

Living in a more walkable neighborhood was associated with modestly higher levels of doctor-diagnosed depression and antidepressant use, and walkability was associated with greater depression symptoms in neighborhoods with higher deprivation. Although dense urban environments may provide opportunities for physical activity, they may also increase exposure to noise, air pollution, and social stressors that could increase levels of depression.

Neighbourhood greenspace is associated with a slower decline in physical activity in older adults: A prospective cohort study

Maintaining physical activity in later life is important for maintaining health and function. Activity outdoors, such as walking, jogging and cycling, may provide an accessible, sociable and practical solution, but maintaining outdoor mobility may be a challenge in later life. Providing green environments which are supportive of physical activity may facilitate this, yet research into how greenspace could be best used is inconclusive. This study evaluates the role of greenspace in protecting against decline in physical activity over time in older adults. Data from the European Prospective Investigation of Cancer Norfolk, UK, cohort 1993-2009 (N=15,672) was used. Linear regression modelling was used to examine the association between exposure to greenspace in the home neighbourhood and change in overall, recreational and outdoor physical activity measured in terms of metabolic equivalent cost (MET) in hours/week. Mediation analysis was conducted to assess if dog walking explained the relationship between greenspace and physical activity change. Models were adjusted for known and hypothesised confounders. People living in greener neighbourhoods experienced less of a decline in physical activity than those living in less green areas. Comparing change for those living in the greenest versus least green quartiles, participants showed a difference in overall physical activity of 4.21 MET hours/week (trend P=0.001), adjusted for baseline physical activity, age, sex, BMI, social class and marital status. This difference was 4.03 MET hours/week for recreational physical activity (trend P<0.001) and 1.28 MET hours/week for outdoor physical activity (trend P=0.007). Dog walking partially mediated the association between greenspace and physical activity change, by 22.6% for overall, 28.1% for recreational and 50.0% for outdoor physical activity (all P<0.001). Greenspace in the home neighbourhood may be protective against decline in physical activity among older people as they age. Dog walking is a potential mechanism in this relationship, and warrants further investigation as a way of maintaining physical activity in later life.

The context of context: Examining the associations between healthy and unhealthy measures of neighborhood food, physical activity, and social environments

Multilevel health research often focuses on a singular dimension of the neighborhood environment in relation to individual-level health behaviors (e.g., diet, physical activity) and outcomes (e.g., obesity). This study examined associations between healthy and unhealthy neighborhood features across food, physical activity, and social environments. We used neighborhood-level (i.e., census block group) access (0/1) measures of the 1) food (grocery store, convenience store, fast food restaurant), 2) physical activity (fitness/recreation facility, park), and 3) social (crime, renter occupancy) environments to capture both healthy and unhealthy neighborhood features for a sample of neighborhoods (n=126) in East Baton Rouge Parish, Louisiana, United States. We employed a) bivariate correlations, or spatial regression where necessary, to identify significant associations between neighborhood access measures; and b) two-step cluster analysis to identify neighborhood typologies based upon neighborhood access measures. Results demonstrated multiple significant associations between healthy and unhealthy access measures across the three neighborhood environments. Cluster analysis further confirmed that neighborhoods are not completely healthy or unhealthy, but rather can be characterized by neighborhood features that are both health-promoting and health-constraining. This study elucidates a 'context of context' whereby no singular aspect of a neighborhood completely explains health in individuals. Rather, in order to effectively model the association between neighborhood and individual-level health, it may be necessary to account for the inter-related nature of neighborhood features.

Residential neighbourhood greenspace is associated with reduced risk of incident diabetes in older people: a prospective cohort study

BACKGROUND

Three cross sectional studies suggest that neighbourhood greenspace may protect against incident diabetes. This study uses data from a longitudinal study with a large sample size to investigate the association between greenspace and the occurrence of incident diabetes over time.

METHODS

Data was from the European Prospective Investigation of Cancer Norfolk, UK, cohort, recruitment 1993-2007 (N = 23,865). Neighbourhoods were defined as 800 m circular buffers around participants' home locations, according to their home postcode (zip code). Greenspace exposure was defined as the percentage of the home neighbourhood that was woodland, grassland, arable land, mountain, heath and bog, according to the UK Land Cover Map. Cox proportional hazards regression examined the association between neighbourhood greenspace exposure and incident diabetes. The population attributable fraction assessed the proportion of diabetes cases attributable to exposure to least green neighbourhoods. Mediation analysis assessed if physical activity explained associations between greenspace and diabetes. Interaction analysis was used to test for the modifying effect of rurality and socio-economic status on the relationship between greenspace and diabetes. Models were adjusted for known and hypothesised confounders.

RESULTS

The mean age of participants was 59 years at baseline and 55.1% were female. The mean follow-up time was 11.3 years. Individuals living in the greenest neighbourhood quartile had a 19% lower relative hazard of developing diabetes (HR 0.81; 95% CI 0.67, 0.99; p = 0.035; linear trend p = 0.010). The hazard ratio remained similar (HR 0.81; 95% CI 0.65, 0.99; p = 0.042) after adjusting for age, sex, BMI, whether a parent had been diagnosed with diabetes and socio-economic status at the individual and neighbourhood level. A HR of 0.97 was attributed to the pathway through physical activity in a fully adjusted model, although this was non-significant (95% CI 0.88, 1.08; p = 0.603). The incidence of diabetes in the least green neighbourhoods (with 20% greenspace on average) would fall by 10.7% (95% CI -2.1%, 25.2%; p = 0.106) if they were as green as the average neighbourhood observed across the whole cohort (59% greenspace on average). There were no significant interactions between rurality or socio-economic status and level of greenspace.

CONCLUSIONS

Greener home neighbourhoods may protect against risk of diabetes in older adults, although this study does not support a mediation role for physical activity. Causal mechanisms underlying the associations require further investigation.

Benefits of Mobile Phone Technology for Personal Environmental Monitoring

Background

Tracking individuals in environmental epidemiological studies using novel mobile phone technologies can provide valuable information on geolocation and physical activity, which will improve our understanding of environmental exposures.

Objective

The objective of this study was to assess the performance of one of the least expensive mobile phones on the market to track people's travel-activity pattern.

Methods

Adults living and working in Barcelona (72/162 bicycle commuters) carried simultaneously a mobile phone and a Global Positioning System (GPS) tracker and filled in a travel-activity diary (TAD) for 1 week (N=162). The CalFit app for mobile phones was used to log participants’ geographical location and physical activity. The geographical location data were assigned to different microenvironments (home, work or school, in transit, others) with a newly developed spatiotemporal map-matching algorithm. The tracking performance of the mobile phones was compared with that of the GPS trackers using chi-square test and Kruskal-Wallis rank sum test. The minute agreement across all microenvironments between the TAD and the algorithm was compared using the Gwet agreement coefficient (AC1).

Results

The mobile phone acquired locations for 905 (29.2%) more trips reported in travel diaries than the GPS tracker (P<.001) and had a median accuracy of 25 m. Subjects spent on average 57.9%, 19.9%, 9.0%, and 13.2% of time at home, work, in transit, and other places, respectively, according to the TAD and 57.5%, 18.8%, 11.6%, and 12.1%, respectively, according to the map-matching algorithm. The overall minute agreement between both methods was high (AC1 .811, 95% CI .810-.812).

Conclusions

The use of mobile phones running the CalFit app provides better information on which microenvironments people spend their time in than previous approaches based only on GPS trackers. The improvements of mobile phone technology in microenvironment determination are because the mobile phones are faster at identifying first locations and capable of getting location in challenging environments thanks to the combination of assisted-GPS technology and network positioning systems. Moreover, collecting location information from mobile phones, which are already carried by individuals, allows monitoring more people with a cheaper and less burdensome method than deploying GPS trackers.

"Spatial Energetics": Integrating Data From GPS, Accelerometry, and GIS to Address Obesity and Inactivity

To address the current obesity and inactivity epidemics, public health researchers have attempted to identify spatial factors that influence physical inactivity and obesity. Technologic and methodologic developments have led to a revolutionary ability to examine dynamic, high-resolution measures of temporally matched location and behavior data through GPS, accelerometry, and GIS. These advances allow the investigation of spatial energetics, high-spatiotemporal resolution data on location and time-matched energetics, to examine how environmental characteristics, space, and time are linked to activity-related health behaviors with far more robust and detailed data than in previous work. Although the transdisciplinary field of spatial energetics demonstrates promise to provide novel insights on how individuals and populations interact with their environment, there remain significant conceptual, technical, analytical, and ethical challenges stemming from the complex data streams that spatial energetics research generates. First, it is essential to better understand what spatial energetics data represent, the relevant spatial context of analysis for these data, and if spatial energetics can establish causality for development of spatially relevant interventions. Second, there are significant technical problems for analysis of voluminous and complex data that may require development of spatially aware scalable computational infrastructures. Third, the field must come to agreement on appropriate statistical methodologies to account for multiple observations per person. Finally, these challenges must be considered within the context of maintaining participant privacy and security. This article describes gaps in current practice and understanding and suggests solutions to move this promising area of research forward.

Quantifying spatial misclassification in exposure to noise complaints among low-income housing residents across New York City neighborhoods: a Global Positioning System (GPS) study

PURPOSE

To examine if there was spatial misclassification in exposure to neighborhood noise complaints among a sample of low-income housing residents in New York City, comparing home-based spatial buffers and Global Positioning System (GPS) daily path buffers.

METHODS

Data came from the community-based NYC Low-Income Housing, Neighborhoods and Health Study, where GPS tracking of the sample was conducted for a week (analytic n = 102). We created a GPS daily path buffer (a buffering zone drawn around GPS tracks) of 200 m and 400 m. We also used home-based buffers of 200 m and 400 m. Using these "neighborhoods" (or exposure areas), we calculated neighborhood exposure to noisy events from 311 complaints data (analytic n = 143,967). Friedman tests (to compare overall differences in neighborhood definitions) were applied.

RESULTS

There were differences in neighborhood noise complaints according to the selected neighborhood definitions (P < .05). For example, the mean neighborhood noise complaint count was 1196 per square kilometer for the 400-m home-based and 812 per square kilometer for the 400-m activity space buffer, illustrating how neighborhood definition influences the estimates of exposure to neighborhood noise complaints.

CONCLUSIONS

These analyses suggest that, whenever appropriate, GPS neighborhood definitions can be used in spatial epidemiology research in spatially mobile populations to understand people's lived experience.

Spatio-temporal determinants of mental health and well-being: advances in geographically-explicit ecological momentary assessment (GEMA)

PURPOSE

Overview of geographically explicit momentary assessment research, applied to the study of mental health and well-being, which allows for cross-validation, extension, and enrichment of research on place and health.

METHODS

Building on the historical foundations of both ecological momentary assessment and geographic momentary assessment research, this review explores their emerging synergy into a more generalized and powerful research framework.

RESULTS

Geographically explicit momentary assessment methods are rapidly advancing across a number of complimentary literatures that intersect but have not yet converged. Key contributions from these areas reveal tremendous potential for transdisciplinary and translational science.

CONCLUSIONS

Mobile communication devices are revolutionizing research on mental health and well-being by physically linking momentary experience sampling to objective measures of socio-ecological context in time and place. Methodological standards are not well-established and will be required for transdisciplinary collaboration and scientific inference moving forward.

Feasibility and Acceptability of Global Positioning System (GPS) Methods to Study the Spatial Contexts of Substance Use and Sexual Risk Behaviors among Young Men Who Have Sex with Men in New York City: A P18 Cohort Sub-Study

Background

No global positioning system (GPS) technology study has been conducted among a sample of young gay, bisexual, and other men who have sex with men (YMSM). As such, the purpose of this study was to evaluate the feasibility and acceptability of using GPS methods to understand the spatial context of substance use and sexual risk behaviors among a sample of YMSM in New York City, a high-risk population.

Methods

Data came from a subsample of the ongoing P18 Cohort Study (n = 75). GPS feasibility and acceptability among participants was measured with: 1) a pre- and post-survey and 2) adherence to the GPS protocol which included returning the GPS device, self-report of charging and carrying the GPS device as well as objective data analyzed from the GPS devices. Analyses of the feasibility surveys were treated as repeated measures as each participant had a pre- and post-feasibility survey. When comparing the similar GPS survey items asked at baseline and at follow-up, we present percentages and associated p-values based on chi-square statistics.

Results

Participants reported high ratings of pre-GPS acceptability, ease of use, and low levels of wear-related concerns in addition to few concerns related to safety, loss, or appearance, which were maintained after baseline GPS feasibility data collection. The GPS return rate was 100%. Most participants charged and carried the GPS device on most days. Of the total of 75 participants with GPS data, 75 (100%) have at least one hour of GPS data for one day and 63 (84%) had at least one hour on all 7 days.

Conclusions

Results from this pilot study demonstrate that utilizing GPS methods among YMSM is feasible and acceptable. GPS devices may be used in spatial epidemiology research in YMSM populations to understand place-based determinants of health such as substance use and sexual risk behaviors.

Mapping Multi-Day GPS Data: A Cartographic Study in NYC

Multi-day GPS data is increasingly being used in research-including in the field of spatial epidemiology. We present several maps as ways to present multi-day GPS data. Data come from the NYC Low-Income Housing, Neighborhoods and Health Study (n=120). Participants wore a QStarz BT-Q1000XT GPS device for about a week (mean: 7.44, SD= 2.15). Our maps show various ways to visualize multi-day GPS data; these data are presented by overall GPS data, by weekday/weekend and by day of the week. We discuss implications for each of the maps.

Assessing opportunities for physical activity in the built environment of children: interrelation between kernel density and neighborhood scale

BACKGROUND

Built environment studies provide broad evidence that urban characteristics influence physical activity (PA). However, findings are still difficult to compare, due to inconsistent measures assessing urban point characteristics and varying definitions of spatial scale. Both were found to influence the strength of the association between the built environment and PA.

METHODS

We simultaneously evaluated the effect of kernel approaches and network-distances to investigate the association between urban characteristics and physical activity depending on spatial scale and intensity measure. We assessed urban measures of point characteristics such as intersections, public transit stations, and public open spaces in ego-centered network-dependent neighborhoods based on geographical data of one German study region of the IDEFICS study. We calculated point intensities using the simple intensity and kernel approaches based on fixed bandwidths, cross-validated bandwidths including isotropic and anisotropic kernel functions and considering adaptive bandwidths that adjust for residential density. We distinguished six network-distances from 500 m up to 2 km to calculate each intensity measure. A log-gamma regression model was used to investigate the effect of each urban measure on moderate-to-vigorous physical activity (MVPA) of 400 2- to 9.9-year old children who participated in the IDEFICS study. Models were stratified by sex and age groups, i.e. pre-school children (2 to <6 years) and school children (6-9.9 years), and were adjusted for age, body mass index (BMI), education and safety concerns of parents, season and valid weartime of accelerometers.

RESULTS

Association between intensity measures and MVPA strongly differed by network-distance, with stronger effects found for larger network-distances. Simple intensity revealed smaller effect estimates and smaller goodness-of-fit compared to kernel approaches. Smallest variation in effect estimates over network-distances was found for kernel intensity measures based on isotropic and anisotropic cross-validated bandwidth selection.

CONCLUSION

We found a strong variation in the association between the built environment and PA of children based on the choice of intensity measure and network-distance. Kernel intensity measures provided stable results over various scales and improved the assessment compared to the simple intensity measure. Considering different spatial scales and kernel intensity methods might reduce methodological limitations in assessing opportunities for PA in the built environment.