Disease and Health Inequalities Attributable to Air Pollutant Exposure in Detroit, Michigan

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.

Health and Environmental Justice Implications of Retiring Two Coal‐Fired Power Plants in the Southern Front Range Region of Colorado

“…Because the concentration curves are sensitive to the study boundaries (Martenies et al, 2017), we focused on inequality within the southern Front Range region of the state, as this area is more densely populated than the state as a whole.…”

Clearing the Air: The Impacts of Ambient Air Pollution on Environmental Equity

“…The most common use of air quality models is the use of atmospheric dispersion models. Some studies have used AERMOD (Chaix et al, 2017;Cohan, Wu, & Dabdub, 2011;Maroko, 2012;Martenies, Milando, Williams, & Batterman, 2017;Poorfakhraei, Tayarani, & Rowangould, 2017;Pratt, Vadali, Kvale, & Ellickson, 2015;Tayarani, Poorfakhraei, Nadafianshahamabadi, & Rowangould, 2016), and some other less common dispersion models are used as well (Fan, Lam, & Yu, 2012;Havard, Deguen, Zmirou-Navier, Schillinger, & Bard, 2009;Levy, Greco, Melly, & Mukhi, 2009). Even fewer studies have used Chemical Transport Models (CTMs).…”

“…While it has mostly been applied to examining inequalities in health care delivery across income groups (Arokiasamy & Pradhan, 2011;Costa Font, Hernandez-Quevedo, & McGuire, 2011;Kakwani, Wagstaff, & van Doorslaer, 1997;Wagstaff, 2002), the concentration curve was recently applied in environmental justice literature as well (Koolman & van Doorslaer, 2004;Martenies et al, 2017;Sarabia & Jorda, 2013;Su et al, 2009;Walker, Mitchell, Fairburn, & Smith, 2005). One of the first applications by Walker et al (2005) used the Concentration Curve to examine whether industrial pollution sites in England were clustered in areas of lower socio-economic status.…”

“…The Concentration Curve has also been applied beyond exposures to examine the inequality in health burden faced by different subgroups of the population. Recently, Martenies et al (2017) examined the inequality in mortality and morbidity attributable to NO2, PM2.5, O3, and SO2 in Detroit. They found an annual monetized health impact of $6.5 billion, and that the environmental burden of disease was largely driven by PM2.5 and O3 exposures.…”

“…In environmental inequality literature, transfers are desirable away from the most exposed (at the higher end of the distribution), so a typical value of 0.75 is selected for the inequality aversion parameter. (Clark et al, 2014;Fann et al, 2011;Levy, Greco, et al, 2009;Marshall et al, 2014;Martenies et al, 2017).…”