Racial or ethnic minority groups and low-income communities have poorer health outcomes than others. They are more frequently exposed to multiple environmental hazards and social stressors, including poverty, poor housing quality, and social inequality. Researchers are grappling with how best to characterize the cumulative effects of these hazards and stressors in order to help regulators and decision makers craft more-effective policies to address health and environmental disparities. In this article we synthesize the existing scientific evidence regarding the cumulative health implications of higher rates of exposure to environmental hazards, along with individual biological susceptibility and social vulnerability. We conclude that current environmental policy, which is focused narrowly on pollutants and their sources, should be broadened to take into account the cumulative impact of exposures and vulnerabilities encountered by people who live in neighborhoods consisting largely of racial or ethnic minorities or people of low socioeconomic status.

Previous research shows poorer birth outcomes for racial and ethnic minorities and for persons with low socioeconomic status (SES). We evaluated whether mothers in groups at higher risk for poor birth outcomes live in areas of higher air pollution and whether higher exposure to air pollution contributes to poor birth outcomes. An index representing long-term exposure to criteria air pollutants was matched with birth certificate data at the county level for the United States in 1998-1999. We used linear regression to estimate associations between the air pollution index and maternal race and educational attainment, a marker for SES of the mother, controlling for age, parity, marital status, and region of the country. Then we used logistic regression models both to estimate likelihood of living in counties with the highest levels of air pollution for different racial groups and by educational attainment, adjusting for other maternal risk factors, and to estimate the effect of living in counties with higher levels of air pollution on preterm delivery and births small for gestational age (SGA). Hispanic, African-American, and Asian/Pacific Islander mothers experienced higher mean levels of air pollution and were more than twice as likely to live in the most polluted counties compared with white mothers after controlling for maternal risk factors, region, and educational status [Hispanic mothers: adjusted odds ratio (AOR) = 4.66; 95% confidence interval (95% CI), 1.92-11.32; African-American mothers: AOR = 2.58; 95% CI, 1.00-6.62; Asian/Pacific Islander mothers: AOR = 2.82; 95% CI, 1.07-7.39]. Educational attainment was not associated with living in counties with highest levels of the air pollution index (AOR = 0.95; 95% CI, 0.40-2.26) after adjusting for maternal risk factors, region of the country, and race/ethnicity. There was a small increase in the odds of preterm delivery (AOR = 1.05; 95% CI, 0.99-1.12) but not SGA (AOR = 0.96; 95% CI, 0.86-1.07) in a county with high air pollution. Additional risk of residing in areas with poor air quality may exacerbate health problems of infants and children already at increased risk for poor health.

Researchers in environmental justice contend that lowincome communities and communities of color face greater impacts from environmental hazards. This is also of concern for policy makers. In this context, our paper has two principal objectives. First, we propose a method for creating an index capable of summarizing racial-ethnic and socioeconomic inequalities from the impact of cumulative environmental hazards. Second, we apply the index to Los Angeles County to illustrate the potential applications and complexities of its implementation. Individual environmental inequality indices are calculated based on unequal shares of environmental hazards for racial-ethnic groups and socioeconomic positions. The illustrated hazards include ambient concentrations of particulate matter, nitrogen dioxide, and estimates of cancer risk associated with modeled estimates for diesel particulate matter. The cumulative environmental hazard inequality index (CEHII) then combines individual environmental hazards, using either a multiplicative or an additive model. Significant but modest inequalities exist for both individual and cumulative environmental hazards in Los Angeles. The highest level of inequality among racial-ethnic and socioeconomic groups occurs when a multiplicative model is used to estimate cumulative hazard. The CEHII provides a generalized framework that incorporates environmental hazards and socioeconomic characteristics to assess inequalities in cumulative environmental risks.

BackgroundThe field of risk assessment has focused on protecting the health of individual people or populations of wildlife from single risks, mostly from chemical exposure. The U.S. Environmental Protection Agency recently began to address multiple risks to communities in the “Framework for Cumulative Risk Assessment” [EPA/630/P02/001F. Washington DC:Risk Assessment Forum, U.S. Environmental Protection Agency (2003)].Simultaneously, several reports concluded that some individuals and groups are more vulnerable to environmental risks than the general population. However, vulnerability has received little specific attention in the risk assessment literature.ObjectiveOur objective is to examine the issue of vulnerability in cumulative risk assessment and present a conceptual framework rather than a comprehensive review of the literature. In this article we consider similarities between ecologic and human communities and the factors that make communities vulnerable to environmental risks.DiscussionThe literature provides substantial evidence on single environmental factors and simple conditions that increase vulnerability or reduce resilience for humans and ecologic systems. This observation is especially true for individual people and populations of wildlife. Little research directly addresses the topic of vulnerability in cumulative risk situations, especially at the community level. The community level of organization has not been adequately considered as an end point in either human or ecologic risk assessment. Furthermore, current information on human risk does not completely explain the level of response in cumulative risk conditions. Ecologic risk situations are similarly more complex and unpredictable for cases of cumulative risk.ConclusionsPsychosocial conditions and responses are the principal missing element for humans. We propose a model for including psychologic and social factors as an integral component of cumulative risk assessment.