Abstract
The environmental burden of disease is the mortality and morbidity attributable to exposures of air pollution and other stressors. The inequality metrics used in cumulative impact and environmental justice studies can be incorporated into environmental burden studies to better understand the health disparities of ambient air pollutant exposures. This study examines the diseases and health disparities attributable to air pollutants for the Detroit urban area. We apportion this burden to various groups of emission sources and pollutants, and show how the burden is distributed among demographic and socioeconomic subgroups. The analysis uses spatially-resolved estimates of exposures, baseline health rates, age-stratified populations, and demographic characteristics that serve as proxies for increased vulnerability, e.g., race/ethnicity and income. Based on current levels, exposures to fine particulate matter (PM2.5), ozone (O3), sulfur dioxide (SO2), and nitrogen dioxide (NO2) are responsible for more than 10,000 disability-adjusted life years (DALYs) per year, causing an annual monetized health impact of $6.5 billion. This burden is mainly driven by PM2.5 and O3 exposures, which cause 660 premature deaths each year among the 945,000 individuals in the study area. NO2 exposures, largely from traffic, are important for respiratory outcomes among older adults and children with asthma, e.g., 46% of air-pollution related asthma hospitalizations are due to NO2 exposures. Based on quantitative inequality metrics, the greatest inequality of health burdens results from industrial and traffic emissions. These metrics also show disproportionate burdens among Hispanic/Latino populations due to industrial emissions, and among low income populations due to traffic emissions. Attributable health burdens are a function of exposures, susceptibility and vulnerability (e.g., baseline incidence rates), and population density. Because of these dependencies, inequality metrics should be calculated using the attributable health burden when feasible to avoid potentially underestimating inequality. Quantitative health impact and inequality analyses can inform health and environmental justice evaluations, providing important information to decision makers for prioritizing strategies to address exposures at the local level.
Highlights
IntroductionCumulative impact analyses aim to understand the way social and environmental factors combine to increase adverse health risks and impacts across a population [1]
PM2.5 exposures are dominated by regional sources, which contributed an average of
Excludes more highly burdened groups in need more highly burdened groups in. These analyses suggest the need for small spatial units (i.e., for small spatial units that can capture exposure gradients, and study areas large census blocks) that can capture exposure gradients, and study areas large enough to capture the full enough to capture the full distribution of health impacts
Summary
Cumulative impact analyses aim to understand the way social and environmental factors combine to increase adverse health risks and impacts across a population [1]. This information can identify areas where social and environmental stressors together create environmental justice (EJ) concerns, such as disproportionate impacts and health disparities among low income communities and communities of color [2], often with the goal of helping disadvantaged groups gain access to the resources needed to. Res. Public Health 2017, 14, 1243; doi:10.3390/ijerph14101243 www.mdpi.com/journal/ijerph
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