Global Geographies of Injustice in Traffic-Related Air Pollution Exposure

Havard et al1 have added new evidence to the environmental justice debate with a substantial and well-conducted study from Strasbourg, France. Their study combined advanced dispersion modeling of traffic-related air pollution, a deprivation index, and thoughtful spatial autocorrelation analysis to demonstrate for the first time in France what has been seen elsewhere: Socially disadvantaged groups bear a higher burden of pollution exposure than other groups in society. Put in global context, the findings from this study fit within a consistent pattern. Even in economically advanced countries with many income and social equalization programs, air pollution and other environmental risks remain unequally distributed. Even in countries viewed as egalitarian with high life expectancies and good access to health care (ie, Sweden, Canada, and now France), the socially disadvantaged suffer greater environmental exposures and risks. The concept of environmental “justice” or “equity” emerged in the United States through the 1980s with landmark studies by the United Church of Christ and the General Accounting Office.2 In practice, the concept translates into qualitative and quantitative empirical analyses investigating whether socioeconomic position or racial/ethnic status is linked to exposure to environmental contaminants and other potential sources of health effects such as psycho-social stress. Environmental justice research takes on a political dimension, implying that the poor and minorities have not only been left behind in sharing the benefits of economic development, but they must also bear a disproportionate burden of the external costs of that development.3 Thus, environmental justice encompasses issues of fairness in regulations, landuse planning, and other environmental protection and economic decisions.4 Much of the earlier research focused on point sources of toxic pollution.4–7 Early debates emphasized 2 major issues. One is whether the methods for assessing spatial inequities were adequate.8 The other is whether unequal exposure by social or racial group was proof of intentional discrimination, or rather a “natural” outcome of housing market processes such that persons of lower income are drawn to lower-rent areas with higher pollution.9 Methodologic advances of the kind displayed in the Havard et al study—with better exposure characterization, a deprivation index representing multiple dimensions, and spatial autocorrelation analysis—have done much to demonstrate that the results of environmental justice studies are not due to poor methods. There is still controversy as to whether deprived communities are specifically targeted when decisions on the placement of hazardous waste facilities (for example) are being made, or whether the association is the outcome of devalued (and thus more affordable) housing near such exposures. Some studies4,10 have emphasized the role of manufacturing employment as a contributor to exposure inequalities, which suggests an element of individual selection of residential location (albeit with a high probability of an income-constrained choice set). The question of intent cannot be resolved through cross-sectional studies but must be examined historically. Pastor et al11 showed that over a 30-year period, hazardous waste facilities were consistently placed in minority neighborhoods, rather than minority groups moving in after the facility had depressed local rents. Answering the question of intent will necessitate more studies with a longitudinal perspective. More recently, researchers such as Havard et al are examining the social distribution of traffic pollution. This body of literature is still relatively small. Apelberg et al12 analyzed associations between the U.S. Environmental Protection Agency's (EPA's) National Air Toxics Assessment models and census tract socioeconomic data in Maryland, USA. Cancer risk for road-source emissions was higher in low-income and racial minority tracts. Green et al13 found that elementary schools in socially disadvantaged parts of California were more likely to be exposed to high levels of traffic. Other studies from southern California used emissions inventories and EPA data to show that transportation sources of pollution were most important for lifetime cancer risk, particularly among racial minorities.12 Evidence of unequal distributions of traffic pollution by race and socioeconomic position has also been found outside the United States, although the results are more mixed. Pearce et al14 used atmospheric dispersion modeling to detect a relationship between traffic pollution and disadvantaged social groups in New Zealand. In England, Brainard et al15 found that carbon monoxide and nitrogen dioxide (markers of traffic pollution) related strongly to racial/ethnic minority status and to social deprivation. Air pollution from dust resuspension, such as street cleaning and maintenance, have also been shown to be related to socioeconomic position in England.16 In Sweden, Chaix et al17 reported higher levels of NO2 for children living in poorer housing and neighborhoods. A Canadian study reported that lower socioeconomic position in Toronto was related to air pollution exposures, although there were exceptions that contrasted with the US literature.18 For example, racial minority groups tended to be less exposed in Toronto than other groups, probably due to its role as a gateway city for highly educated immigrants. Dwelling values also took an unexpected positive sign, which may have been partly explained by the dense urban structure of the downtown area and the relatively high traffic and land rents in this district. These subtle differences highlight the need to examine the specific intricacies of place. Still, these minor differences do not diminish the overall pattern of low socioeconomic position and higher exposure to air pollution from traffic. To the extent this association exists, it has important implications for the interpretation of epidemiologic findings. First, social health inequalities persist in many places and at many scales. Although the determinants remain only partially understood,19 environmental risks likely contribute.20 Epidemiologists interested in explaining social disparities need to consider prima facie environmental exposures as an important confounder or effect modifier—something that is rarely seen in the social epidemiology literature. Second, because more disadvantaged groups often experience more intensive environmental exposures, researchers interested in assessing the effects of environmental risk factors need to consider whether the observed health effects are larger in deprived groups than in the general population. As Havard et al echo from earlier studies,4 groups with lower socioeconomic position may have both higher exposure and greater susceptibility to its deleterious effects due to poor nutrition, higher occupational exposure, and a raft of other challenges, social and environmental. Similarly, other risks may be modified by the air pollution burden. For example, poor nutrition may have heightened impact on health in individuals and communities exposed to higher air pollution. Havard et al have illustrated the need to assess residual autocorrelation in studies relying on a spatial exposure gradient. Failure to do so may lead to biased and inefficient estimates. These findings are not new,21 but their study stands as one of the better recent attempts to grapple with the issue. Understanding and interpreting epidemiologic findings on social or environmental risk factors consequently requires researchers 1) to recognize that exposure inequalities exist, 2) to assess inequalities in their statistical models that account explicitly for autocorrelation, and 3) to ensure their results are appropriately tempered with the knowledge of the complex temporal interplay between socioeconomic position and environmental exposures. Looking to the future, environmental justice research needs to go beyond the single pollutant or facility-type assessments of exposure. Multiple or cumulative exposures probably bear on disadvantaged populations, with possible synergistic effects. For example, noise and air pollution from traffic probably disproportionately affect disadvantaged populations. Likewise, beneficial exposures such as access to healthy food or parks follow social gradients.22 Assessing cumulative exposures and their related health effects is the next big challenge for epidemiologists interested in the geographies of injustice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.