Disparities in physical activity resource availability in six US regions.

OBJECTIVE: We conducted an ecological study to determine physical activity resource availability overall and by sociodemographic groups in parts of six states (CA, IL, MD, MN, NC, NY). METHODS: Data on parks and recreational facilities were collected from 3 sources in 2009-2012. Three measures characterized park and recreational facility availability at the census tract level: presence of ≥1 resource, number of resources, and resource kernel density. Associations between resource availability and census tract characteristics (predominant racial/ethnic group, median income, and proportion of children and older adults) were estimated using linear, binomial, and zero-inflated negative binomial regression in 2014. Pooled and stratified analyses were conducted. RESULTS: The study included 7139 census tracts, comprising 9.5% of the 2010 US population. Overall the availability of parks and recreational facilities was lower in predominantly minority relative to non-Hispanic white census tracts. Low-income census tracts and those with a higher proportion of children had an equal or greater availability of park resources but fewer recreational facilities. Stratification revealed substantial variation in resource availability by site. CONCLUSION: The availability of physical activity resources varied by sociodemographic characteristics and across regions. Improved knowledge of resource distribution can inform strategies to provide equitable access to parks and recreational facilities.

Changes in the built environment and changes in the amount of walking over time: longitudinal results from the multi-ethnic study of atherosclerosis.

Lack of longitudinal research hinders causal inference on the association between the built environment and walking. In the present study, we used data from 6,027 adults in the Multi-Ethnic Study of Atherosclerosis who were 45-84 years of age at baseline to investigate the association of neighborhood built environment with trends in the amount of walking between 2000 and 2012. Walking for transportation and walking for leisure were assessed at baseline and at 3 follow-up visits (median follow-up = 9.15 years). Time-varying built environment measures (measures of population density, land use, number of destinations, bus access, and street connectivity) were created using geographic information systems. We used linear mixed models to estimate the associations between baseline levels of and a change in each built environment feature and a change in the frequency of walking. After adjustment for potential confounders, we found that higher baseline levels of population density, area zoned for retail, social destinations, walking destinations, and street connectivity were associated with greater increases in walking for transportation over time. Higher baseline levels of land zoned for residential use and distance to buses were associated with less pronounced increases (or decreases) in walking for transportation over time. Increases in the number of social destinations, the number of walking destinations, and street connectivity over time were associated with greater increases in walking for transportation. Higher baseline levels of both land zoned for retail and walking destinations were associated with greater increases in leisure walking, but no changes in built environment features were associated with leisure walking. The creation of mixed-use, dense developments may encourage adults to incorporate walking for transportation into their everyday lives.

Geostatistical exploration of spatial variation of summertime temperatures in the Detroit metropolitan region.

BACKGROUND: Because of the warming climate urban temperature patterns have been receiving increased attention. Temperature within urban areas can vary depending on land cover, meteorological and other factors. High resolution satellite data can be used to understand this intra-urban variability, although they have been primarily studied to characterize urban heat islands at a larger spatial scale. OBJECTIVE: This study examined whether satellite-derived impervious surface and meteorological conditions from multiple sites can improve characterization of spatial variability of temperature within an urban area. METHODS: Temperature was measured at 17 outdoor sites throughout the Detroit metropolitan area during the summer of 2008. Kriging and linear regression were applied to daily temperatures and secondary information, including impervious surface and distance-to-water. Performance of models in predicting measured temperatures was evaluated by cross-validation. Variograms derived from several scenarios were compared to determine whether high-resolution impervious surface information could capture fine-scale spatial structure of temperature in the study area. RESULTS: Temperatures measured at the sites were significantly different from each other, and all kriging techniques generally performed better than the two linear regression models. Impervious surface values and distance-to-water generally improved predictions slightly. Restricting models to days with lake breezes and with less cloud cover also somewhat improved the predictions. In addition, incorporating high-resolution impervious surface information into cokriging or universal kriging enhanced the ability to characterize fine-scale spatial structure of temperature. CONCLUSIONS: Meteorological and satellite-derived data can better characterize spatial variability in temperature across a metropolitan region. The data sources and methods we used can be applied in epidemiological studies and public health interventions to protect vulnerable populations from extreme heat events.

A Geospatial Analysis of Access to Ethnic Food Retailers in Two Michigan Cities: Investigating the Importance of Outlet Type within Active Travel Neighborhoods.

To date, the research that examines food accessibility has tended to ignore ethnic food outlets. This void leaves us with a limited understanding of how such food stores may, or may not, impact food security. The study discussed herein addressed this by conducting a geospatial assessment of ethnic food outlet accessibility in two U.S. cities: Flint and Grand Rapids, Michigan. We used Geographic Information Systems (GIS) tools to create a revealed accessibility index for each food outlet, and used the index to determine access within active travel service areas. We utilized an ordinary least squares regression (OLS), and two local models: spatial autoregression (SAR) and geographically weighted regression (GWR) to enhance our understanding of global and localized relationships between outlet accessibility and type (while controlling for known covariates). The results show that the local models outperformed (R2 max = 0.938) the OLS model. The study found that there was reduced access to ethnic restaurants in all service areas of Grand Rapids. However, in Flint, we observed this association in the bicycling areas only. Also notable were the influences that demographic characteristics had on access in each city. Ultimately, the findings tell us that nuanced planning and policy approaches are needed in order to promote greater access to ethnic food outlets and reduce overall food insecurity.

Spatial variation in teens' crash rate reduction following the implementation of a graduated driver licensing program in Michigan.

Motor vehicle crashes are a leading cause of injury, and teen drivers contribute disproportionately to that burden. Graduated Driver Licensing (GDL) programs are effective at reducing teen crash risk, but teen crash rates remain high. Between-state variation in the teen crash rate reduction following GDL implementation has been documented, but this is the first study to examine small-area variation in such a reduction. Fusing together crash data from the Michigan State Police, census data, and organizational data (alcohol outlet, movie theatre, and school locations), we analyzed spatial correlates of teen injury crash, and place-based features that modified the injury crash rate difference following GDL implementation. Specifically, using census-based units, we estimated changes in injury crash rates among teens using negative binomial regression controlling for spatial autocorrelation, and tested whether any measured spatial characteristics modified the crash rate change in the pre versus post GDL periods. There was a substantial reduction in teen crashes after GDL implementation (RR = 0.66, 95%CI: [0.65, 0.67]), and this effect was robust across gender and time-of-day (light/dark). We found evidence that this reduction varied across space; areas with more alcohol outlets corresponded to a larger daytime crash rate reduction post-GDL, while areas near schools corresponded to a smaller daytime crash rate reduction. Concentrations of movie theatres corresponded to larger post-GDL crash rate reductions after dark. Maximizing the substantial successes of GDL programs requires understanding why crash rate reductions were larger in some areas following GDL implementation, and harnessing that understanding to improve its effectiveness across a state, focusing on identifying priorities for improving driver training (e.g., by parents and driver educators), law enforcement, and future policy changes to current GDL laws.

An assessment of child passenger safety levels of service in Michigan.

Objective: The purpose of this article was to assess the match between child passenger safety resources (child passenger safety technicians [CPSTs], car seat checks, and child restraint system [CRS] distribution programs) and the child population in Michigan by utilizing geographic information systems approaches and to analyze the impact of Michigan's CPSTs on child passenger safety behaviors on departure from a seat check. Methods: Data were collected from administrative sources and a survey of CPSTs to determine the number and location of child passenger safety resources and children in Michigan. The main analyses used data from 2014. The child population ≤4 years old per county and per traffic safety region was determined from census data. CPST and car seat check locations were determined from a list from the Michigan Office of Highway Safety Planning (Mi-OHSP) and a survey of CPSTs who coordinate seat checks. Summary sheets from Mi-OHSP served as the data source for CRSs distributed through their occupant protection program. Data from child passenger safety checklists completed with seat checks were obtained from Safe Kids Michigan. Addresses were geocoded using Google Maps Geocoding API and then mapped at the county level using ArcGIS Desktop 10.3.1. Descriptive statistics were calculated and levels of service were determined at the county and regional levels. Results: In 2014, there were 570,929 children ≤4 years old in Michigan and 979 CPSTs who worked at 209 known seat check locations. An average of 6,854 seats was checked per year through Safe Kids Michigan Coalitions. All but 3 regions met an intermediate service level for seat check locations by offering one or more per 5,000 children ≤4 years old. There was at least one CPST in 80 of 83 counties (median 5; interquartile range, 2, 10.5). Assuming that an average Michigan CPST provides 10 h of service each year, all but 2 regions reached an intermediate service level of at least one technician hour per 90 children ≤4 years old. Fewer regions reached a basic level of service for the number of seat checks. Almost half (49.5%) of Safe Kids Michigan seat checks resulted in a change in child passenger safety behaviors. Conclusions: Child passenger safety resources in Michigan are not evenly distributed yet most regions and counties meet intermediate levels of service. Reallocating resources to areas that are providing basic levels of service could help reduce disparities in child passenger safety behaviors.

Availability of recreational resources in minority and low socioeconomic status areas.

BACKGROUND: Differences in availability of recreational resources may contribute to racial and socioeconomic status (SES) disparities in physical activity. Variations in the location and density of recreational resources were examined by SES and racial composition of neighborhoods. METHODS: Densities of resources available in recreational facilities and parks were estimated for census tracts between April 2003 and June 2004 in North Carolina, New York, and Maryland using kernel estimation. The probability of not having a facility or park was modeled by tract racial composition and SES, adjusting for population and area, using binomial regression in 2006. Mean densities of tract resources were modeled by SES and racial composition using linear regression. RESULTS: Minority neighborhoods were significantly more likely than white neighborhoods not to have recreational facilities (relative probability [RP]=3.27 [95% CI=2.11-5.07] and 8.60 [95% CI=4.48-16.51], for black and Hispanic neighborhoods, respectively). Low-income neighborhoods were 4.5 times more likely to not have facilities than high-income areas (95% CI=2.87-7.12). Parks were more equitably distributed. Most resources located in recreational facilities required a fee and were less dense in minority and low-income areas. Those located inside parks were usually free to use, sports-related, and denser in poor and minority neighborhoods. CONCLUSIONS: Recreational facilities and the resources they offer are not equitably distributed. The presence of parks in poor and minority areas suggest that improving the types and quality of resources in parks could be an important strategy to increase physical activity and reduce racial/ethnic and socioeconomic disparities.

Availability of recreational resources and physical activity in adults.

OBJECTIVES: Using data from a large cohort of adults aged 45 to 84 years-old, we investigated whether availability of recreational resources is related to physical activity levels. METHODS: Data from a multiethnic sample of 2723 adult residents of New York City, NY; Baltimore, Md; and Forsyth County, NC, were linked to data on locations of recreational resources. We measured the availability (density) of resources within 0.5 (0.8 km), 1, 2, and 5 miles of each participant's residence and used binomial regression to investigate associations of density with physical activity. RESULTS: After adjustment for potential confounders, individuals in the tertile of participants residing in areas with the highest density of resources were more likely to report physical activity during a typical week than were individuals in the lowest tertile. Associations between availability of recreational resources and physical activity levels were not present for the smallest area assessed (0.5 miles) but were present for areas ranging from 1 to 5 miles. These associations were slightly stronger among minority and low-income residents. CONCLUSIONS: Availability of resources may be 1 of several environmental factors that influence individuals' physical activity behaviors.

How much are built environments changing, and where?: Patterns of change by neighborhood sociodemographic characteristics across seven U.S. metropolitan areas.

Investments in neighborhood built environments could increase physical activity and overall health. Disproportionate distribution of these changes in advantaged neighborhoods could inflate health disparities. Little information exists on where changes are occurring. This paper aims to 1) identify changes in the built environment in neighborhoods and 2) investigate associations between high levels of change and sociodemographic characteristics. Using Geographic Information Systems, neighborhood land-use, local destinations (for walking, social engagement, and physical activity), and sociodemographics were characterized in 2000 and 2010 for seven U.S. cities. Linear and change on change models estimated associations of built environment changes with baseline (2000) and change (2010-2000) in sociodemographics. Spatial patterns were assessed using Global Moran's I to measure overall clustering of change and Local Moran's I to identify statistically significant clusters of high increases surrounded by high increases (HH). Sociodemographic characteristics were compared between HH cluster and other tracts using Analysis of Variance (ANOVA). We observed small land-use changes but increases in the destination types. Greater increases in destinations were associated with higher percentage non-Hispanic whites, percentage households with no vehicle, and median household income. Associations were present for both baseline sociodemographics and changes over time. Greater increases in destinations were associated with lower baseline percentage over 65 but higher increases in percentage over 65 between 2000 and 2010. Global Moran's indicated changes were spatially clustered. HH cluster tracts started with a higher percentage non-Hispanic whites and higher percentage of households without vehicles. Between 2000 and 2010, HH cluster tracts experienced increases in percent non-Hispanic white, greater increases in median household income, and larger decreases in percent of households without a vehicle. Changes in the built environment are occurring in neighborhoods across a diverse set of U.S. metropolitan areas, but are patterned such that they may lead to increased health disparities over time.

Built environment change and change in BMI and waist circumference: Multi-ethnic Study of Atherosclerosis.

OBJECTIVE: To examine longitudinal associations of the neighborhood built environment with objectively measured body mass index (BMI) and waist circumference (WC) in a geographically and racial/ethnically diverse group of adults. METHODS: This study used data from 5,506 adult participants in the Multi-Ethnic Study of Atherosclerosis, aged 45-84 years in 2000 (baseline). BMI and WC were assessed at baseline and four follow-up visits (median follow-up 9.1 years). Time-varying built environment measures (population density, land-use, destinations, bus access, and street characteristics) were created using Geographic Information Systems. Principal components analysis was used to derive composite scores for three built environment factors. Fixed-effects models, tightly controlling for all time-invariant characteristics, estimated associations between change in the built environment, and change in BMI and WC. RESULTS: Increases in the intensity of development (higher density of walking destinations and population density, and lower percent residential) were associated with less pronounced increases or decreases over time in BMI and WC. Changes in connected retail centers (higher percent retail, higher street connectivity) and public transportation (distance to bus) were not associated with changes in BMI or WC. CONCLUSIONS: Longitudinal changes in the built environment, particularly increased density, are associated with decreases in BMI and WC.

Discrete land uses and transportation walking in two U.S. cities: the Multi-Ethnic Study of Atherosclerosis.

This study examines associations of disaggregate land uses with self-reported walking for transportation among participants of the Multi-Ethnic Study of Atherosclerosis (MESA) in Forsyth County, NC and New York, NY. Network distance to each use (in miles), intensity (number of uses per 1/2-mile network buffer) of each use and diversity (number of different uses per 1/2-mile network buffer) of uses were calculated using Geographic Information Systems (GIS). Associations with odds of meeting recommended physical activity levels (150min/week) were examined after controlling for individual- and census-tract-level covariates. Greater distance to and lower intensity of pedestrian-oriented uses, specifically those for social interactions, were associated with lower odds of meeting recommendations in NY. Results suggest that land uses linked to social interactions may be useful for encouraging increased transportation walking.

Validating satellite-derived land surface temperature with in situ measurements: a public health perspective.

BACKGROUND: Land surface temperature (LST) and percent surface imperviousness (SI), both derived from satellite imagery, have been used to characterize the urban heat island effect, a phenomenon in which urban areas are warmer than non-urban areas. OBJECTIVES: We aimed to assess the correlations between LSTs and SI images with actual temperature readings from a ground-based network of outdoor monitors. METHODS: We evaluated the relationships among a) LST calculated from a 2009 summertime satellite image of the Detroit metropolitan region, Michigan; b) SI from the 2006 National Land Cover Data Set; and c) ground-based temperature measurements monitored during the same time period at 19 residences throughout the Detroit metropolitan region. Associations between these ground-based temperatures and the average LSTs and SI at different radii around the point of the ground-based temperature measurement were evaluated at different time intervals. Spearman correlation coefficients and corresponding p-values were calculated. RESULTS: Satellite-derived LST and SI values were significantly correlated with 24-hr average and August monthly average ground temperatures at all but two of the radii examined (100 m for LST and 0 m for SI). Correlations were also significant for temperatures measured between 0400 and 0500 hours for SI, except at 0 m, but not LST. Statistically significant correlations ranging from 0.49 to 0.91 were observed between LST and SI. CONCLUSIONS: Both SI and LST could be used to better understand spatial variation in heat exposures over longer time frames but are less useful for estimating shorter-term, actual temperature exposures, which can be useful for public health preparedness during extreme heat events.

A spatial analysis of health-related resources in three diverse metropolitan areas.

Few studies have investigated the spatial clustering of multiple health-related resources. We constructed 0.5 mile kernel densities of resources for census areas in New York City, NY (n=819 block groups), Baltimore, MD (n=737), and Winston-Salem, NC (n=169). Three of the four resource densities (supermarkets/produce stores, retail areas, and recreational facilities) tended to be correlated with each other, whereas park density was less consistently and sometimes negatively correlated with others. Blacks were more likely to live in block groups with multiple low resource densities. Spatial regression models showed that block groups with higher proportions of black residents tended to have lower supermarket/produce, retail, and recreational facility densities, although these associations did not always achieve statistical significance. A measure that combined local and neighboring block group racial composition was often a stronger predictor of resources than the local measure alone. Overall, our results from three diverse U.S. cities show that health-related resources are not randomly distributed across space and that disadvantage in multiple domains often clusters with residential racial patterning.

US local action on heat and health: are we prepared for climate change?

OBJECTIVES: Global climate change is increasing the frequency of heat waves, hot weather, and temperature variability, which contribute to mortality and illness. Baseline information on local efforts to reduce heat vulnerability, including public advisories; minimizing greenhouse gas emissions; and mitigating urban heat islands, is lacking. METHODS: We designed a survey about local government programs to prevent health problems and reduce heat exposure during heatwaves and administered it to 285 US communities. RESULTS: Of 70 respondents, 26 indicated that excessive heat events are a significant issue for the local government; 30 had established preventive programs. Local government leadership and public health impacts of heat were cited most frequently as extremely important determinants of preventive programs, followed by implementation costs, economic impacts of hot weather, and greenhouse gas emissions mitigation. Cool paving materials and vegetated roofs were common heat mitigation strategies. Fact sheets and case studies were desired guidance for protecting communities during hot weather. CONCLUSIONS: New partnerships and financial resources are needed to support more widespread local action to prevent adverse health consequences of climate change and promote environmental sustainability.

Land use, residential density, and walking. The multi-ethnic study of atherosclerosis.

BACKGROUND: The neighborhood environment may play a role in encouraging sedentary patterns, especially for middle-aged and older adults. PURPOSE: The aim of this study was to examine the associations between walking and neighborhood population density, retail availability, and land-use distribution using data from a cohort of adults aged 45 to 84 years. METHODS: Data from a multi-ethnic sample of 5529 adult residents of Baltimore MD, Chicago IL, Forsyth County NC, Los Angeles CA, New York NY, and St. Paul MN enrolled in the Multi-Ethnic Study of Atherosclerosis in 2000-2002 were linked to secondary land-use and population data. Participant reports of access to destinations and stores and objective measures of the percentage of land area in parcels devoted to retail land uses, the population divided by land area in parcels, and the mixture of uses for areas within 200 m of each participant's residence were examined. Multinomial logistic regression was used to investigate associations of self-reported and objective neighborhood characteristics with walking. All analyses were conducted in 2008 and 2009. RESULTS: After adjustment for individual-level characteristics and neighborhood connectivity, it was found that higher density, greater land area devoted to retail uses, and self-reported proximity of destinations and ease of walking to places were each related to walking. In models including all land-use measures, population density was positively associated with walking to places and with walking for exercise for more than 90 minutes/week, both relative to no walking. Availability of retail was associated with walking to places relative to not walking, and having a more proportional mix of land uses was associated with walking for exercise for more than 90 minutes/week, while self-reported ease of access to places was related to higher levels of exercise walking, both relative to not walking. CONCLUSIONS: Residential density and the presence of retail uses are related to various walking behaviors. Efforts to increase walking may benefit from attention to the intensity and type of land development.

Mapping community determinants of heat vulnerability.

BACKGROUND: The evidence that heat waves can result in both increased deaths and illness is substantial, and concern over this issue is rising because of climate change. Adverse health impacts from heat waves can be avoided, and epidemiologic studies have identified specific population and community characteristics that mark vulnerability to heat waves. OBJECTIVES: We situated vulnerability to heat in geographic space and identified potential areas for intervention and further research. METHODS: We mapped and analyzed 10 vulnerability factors for heat-related morbidity/mortality in the United States: six demographic characteristics and two household air conditioning variables from the U.S. Census Bureau, vegetation cover from satellite images, and diabetes prevalence from a national survey. We performed a factor analysis of these 10 variables and assigned values of increasing vulnerability for the four resulting factors to each of 39,794 census tracts. We added the four factor scores to obtain a cumulative heat vulnerability index value. RESULTS: Four factors explained > 75% of the total variance in the original 10 vulnerability variables: a) social/environmental vulnerability (combined education/poverty/race/green space), b) social isolation, c) air conditioning prevalence, and d) proportion elderly/diabetes. We found substantial spatial variability of heat vulnerability nationally, with generally higher vulnerability in the Northeast and Pacific Coast and the lowest in the Southeast. In urban areas, inner cities showed the highest vulnerability to heat. CONCLUSIONS: These methods provide a template for making local and regional heat vulnerability maps. After validation using health outcome data, interventions can be targeted at the most vulnerable populations.

Comparing Perception-Based and Geographic Information System (GIS)-based characterizations of the local food environment.

Measuring features of the local food environment has been a major challenge in studying the effect of the environment on diet. This study examined associations between alternate ways of characterizing the local food environment by comparing Geographic Information System (GIS)-derived densities of various types of stores to perception-based measures of the availability of healthy foods. Survey questions rating the availability of produce and low-fat products in neighborhoods were aggregated into a healthy food availability score for 5,774 residents of North Carolina, Maryland, and New York. Densities of supermarkets and smaller stores per square mile were computed for 1 mile around each respondent's residence using kernel estimation. The number of different store types in the area was used to measure variety in the food environment. Linear regression was used to examine associations of store densities and variety with reported availability. Respondents living in areas with lower densities of supermarkets rated the selection and availability of produce and low-fat foods 17% lower than those in areas with the highest densities of supermarkets (95% CL, -18.8, -15.1). In areas without supermarkets, low densities of smaller stores and less store variety were associated with worse perceived availability of healthy foods only in North Carolina (8.8% lower availability, 95% CL, -13.8, -3.4 for lowest vs. highest small-store density; 10.5% lower 95% CL, -16.0, -4.7 for least vs. most store variety). In contrast, higher smaller store densities and more variety were associated with worse perceived healthy food availability in Maryland. Perception- and GIS-based characterizations of the environment are associated but are not identical. Combinations of different types of measures may yield more valid measures of the environment.