Mobilizing for Community Benefits to Assess Health and Promote Environmental Justice near the Gordie Howe International Bridge.

Transportation infrastructure decisions contribute to social, economic, and health inequities in the U.S. Health Impact Assessments (HIAs) may improve understanding of potential strategies to mitigate adverse effects on quality of life from planned developments. We use the Gordie Howe International Bridge (GHIB), currently under construction in southwest Detroit, MI, as a case study to examine 15 years of community mobilization, which resulted in community benefits that included an HIA. We describe community engagement processes, household survey methods, and select findings of the baseline HIA, with a focus on their application to inform recommendations to promote quality of life. Baseline HIA results indicated significantly higher self-reported asthma rates among children living within 500 feet of trucking routes. Residents reported substantial economic (e.g., decreased home values), health (e.g., adverse outcomes, lack of health care access), and environmental (e.g., air pollution) concerns related to the GHIB. We discuss specific recommendations, based on HIA results, to reduce adverse impacts of the GHIB. These recommendations will inform ongoing community benefits negotiations. This case study provides lessons for community, academic, and government partners conducting HIAs, especially during building and operation of major infrastructure, and discusses their potential role in improving community engagement opportunities towards environmental justice.

Mapping Modeled Exposure of Wildland Fire Smoke for Human Health Studies in California.

Wildland fire smoke exposure affects a broad proportion of the U.S. population and is increasing due to climate change, settlement patterns and fire seclusion. Significant public health questions surrounding its effects remain, including the impact on cardiovascular disease and maternal health. Using atmospheric chemical transport modeling, we examined general air quality with and without wildland fire smoke PM2.5. The 24-h average concentration of PM2.5 from all sources in 12-km gridded output from all sources in California (2007-2013) was 4.91 µg/m3. The average concentration of fire-PM2.5 in California by year was 1.22 µg/m3 (~25% of total PM2.5). The fire-PM2.5 daily mean was estimated at 4.40 µg/m3 in a high fire year (2008). Based on the model-derived fire-PM2.5 data, 97.4% of California's population lived in a county that experienced at least one episode of high smoke exposure ("smokewave") from 2007-2013. Photochemical model predictions of wildfire impacts on daily average PM2.5 carbon (organic and elemental) compared to rural monitors in California compared well for most years but tended to over-estimate wildfire impacts for 2008 (2.0 µg/m3 bias) and 2013 (1.6 µg/m3 bias) while underestimating for 2009 (-2.1 µg/m3 bias). The modeling system isolated wildfire and PM2.5 from other sources at monitored and unmonitored locations, which is important for understanding population exposure in health studies. Further work is needed to refine model predictions of wildland fire impacts on air quality in order to increase confidence in the model for future assessments. Atmospheric modeling can be a useful tool to assess broad geographic scale exposure for epidemiologic studies and to examine scenario-based health impacts.

MI-Environment: Geospatial patterns and inequality of relative heat stress vulnerability in Michigan.

Heat stress causes morbidity and mortality and is increasing with climate change. Heat stress can pose particular challenges in northern regions not well adapted to heat. To assist decision makers, we identified the relative vulnerability of census tracts within Michigan to factors that increase exposure to heat stress or reflect susceptibilities in the population based on a California heat vulnerability index. In the MI-Environment assessment, we used a Geographic Information System (GIS) to combine future ensemble climate model projections to create a total of 9 geospatial and demographic variables. As part of a broader planned cumulative environmental exposure assessment, the statewide heat vulnerability index (HVI) maps display the location and relative magnitude of exposure on three metrics: built environment (Place), future expected long-term temperature averages (Temperature), and population susceptibility (People). We observed varied and distinct patterns for each of the three component indices. We assessed how equitably those exposures are distributed by racial and socioeconomic factors. This analysis showed that each of the component indices and the aggregate HVI are disproportionately distributed along racial and socioeconomic lines in Michigan. Census tracts with higher percentages of people of color had larger exposure to HVI factors with a deviation from equity of -0.115 [95% CI -0.108, -0.122]. Similarly, for census tracts with higher percentage of people experiencing poverty, the deviation from equity was -0.101 [95% CI -0.094, -0.107]. The MI-Environment visualization tool can help communities prepare for climate change and resolve inequities by identifying census tracts with the most vulnerable residents and highest potential exposures.

Independent and Joint Contributions of Fine Particulate Matter Exposure and Population Vulnerability to Mortality in the Detroit Metropolitan Area.

Fine particulate matter is associated with adverse health outcomes. Exposure to fine particulate matter may disproportionately affect urban communities with larger numbers of vulnerable residents. We used multilevel logistic regression models to estimate the joint effects of fine particulate matter (PM2.5) and population vulnerabilities on cardiopulmonary mortality (CPM). We estimated the health benefits of reductions in PM2.5 across census tracts in the Detroit metropolitan area with varying levels of population vulnerability, using cluster-specific odds ratios scaled to reflect PM2.5-attributable cardiopulmonary risk. PM2.5 and population vulnerability were independently associated with odds of CPM. Odds of CPM and the number of deaths attributable to PM2.5 were greatest in census tracts with both high PM2.5 exposures and population vulnerability. Reducing PM2.5 in census tracts with high PM2.5 would lead to an estimated 18% annual reduction in PM2.5-attributable CPM. Between 78⁻79% of those reductions in CPM would occur within census tracts with high population vulnerabilities. These health benefits of reductions in PM2.5 occurred at levels below current U.S. reference concentrations. Focusing efforts to reduce PM2.5 in the Detroit metropolitan area in census tracts with currently high levels would also lead to greater benefits for residents of census tracts with high population vulnerabilities.

Multidirectional Translation of Environmental Health Science in Community Settings: The Case of Oxidative Stress Pathways.

BACKGROUND: Translation of environmental health science in vulnerable communities is particularly important to promote public health and reduce health inequities. METHODS: We describe a structured, multidirectional process used to develop a suite of health promotion tools (e.g., fact sheets, video, maps) documenting patterning of local air pollution sources and availability of antioxidant-rich foods in Detroit, Michigan as factors that jointly affect oxidative stress (OS). OS underlies many pathological processes associated with air pollution, including asthma, metabolic syndrome, cancer, diabetes, and obesity. This translational effort involved a 2-year dialogue among representatives from community-based and environmental organizations, health service providers, and academic researchers. RESULTS: This dialogue led to development of tools, as well as new opportunities to inform related policies and research. CONCLUSIONS: Through this example, we highlight how collaborative partnerships can enhance multidirectional dialogue to inform translation of environmental health science by promoting consideration of multilevel risk factors, local priorities and context, and diverse audiences.

RACE AND THE DISTRIBUTION OF SOCIAL AND PHYSICAL ENVIRONMENTAL RISK: A Case Example from the Detroit Metropolitan Area.

Since W. E. B. Du Bois documented the physical and social environments of Philadelphia's predominantly African American Seventh Ward over a century ago, there has been continued interest in understanding the distribution of social and physical environments by racial make-up of communities. Characterization of these environments allows for documentation of inequities, identifies communities which encounter heightened risk, and can inform action to promote health equity. In this paper, we apply and extend Du Bois's approach to examine the contemporary distribution of physical environmental exposures, health risks, and social vulnerabilities in the Detroit metropolitan area, one of the most racially-segregated areas in the United States. We begin by mapping the proximity of sensitive populations to hazardous land uses, their exposure to air pollutants and associated health risks, and social vulnerabilities, as well as cumulative risk (combined proximity, exposure, and vulnerability), across Census tracts. Next, we assess, quantitatively, the extent to which communities of color experience excess burdens of environmental exposures and associated health risks, economic and age-related vulnerabilities, and cumulative risk. The results, depicted in maps presented in the paper, suggest that Census tracts with greater proportions of people of color disproportionately encounter physical environmental exposures, socioeconomic vulnerabilities, and combined risk. Quantitative tests of inequality confirm these distributions, with statistically greater exposures, vulnerabilities, and cumulative risk in Census tracts with larger proportions of people of color. Together, these findings identify communities that experience disproportionate cumulative risk in the Detroit metropolitan area and quantify the inequitable distribution of risk by Census tract relative to the proportion of people of color. They identify clear opportunities for prioritizing communities for legislative, regulatory, policy, and local actions to promote environmental justice and health equity.

Inter-rater reliability of the food environment audit for diverse neighborhoods (FEAD-N).

Studies have shown that neighborhood food environments are important influences on dietary intake and may contribute to health disparities. While instruments with high reliability have been developed to assess food availability, price, and quality, few measures to assess items associated with the physical and social features of food stores have been developed. Yet, recent qualitative studies have documented aspects associated with such features of urban food stores that are barriers to food acquisition. We assessed the reliability of measures to assess multiple components of the food environment-including physical and social store features--in three geographically distinct and diverse communities in Detroit, Michigan, using the Food Environment Audit for Diverse Neighborhoods (FEAD-N). Using the FEAD-N, four trained observers conducted observations of 167 food stores over a 10-week period between October and December 2008. To assess inter-rater reliability, two trained observers independently visited, on the same day, a random subset of 44 food stores. Kappa statistics and percent agreement were used to evaluate inter-rater reliability. Overall, the instrument had mostly high inter-rater reliability with more than 75% of items with kappa scores between 0.80 and 1.00, indicating almost perfect reliability. More than half of the physical store features and 47% of the social store features had almost perfect reliability and about 37% and 47%, respectively, had substantial reliability. Measuring factors associated with the physical and social environment of food stores with mostly high reliability is feasible. Systematic documentation of the physical and social features of food stores using objective measures may promote a more comprehensive understanding of how neighborhood food environments influence health.