For the past decade, understanding of the health effects of the air pollution mixture has been a top priority, following recommendations that the nation should begin the shift from a one-pollutant-at-a-time perspective to a multipollutant perspective. Yet challenges remain substantial: designing studies that systematically investigate a range of pollutants and their potential independent, synergistic, and antagonistic effects is difficult, and made more difficult by a lack of available statistical techniques to allow consideration of the effects of more than a few pollutants at a time.
Ambient air consists of multiple pollutants from diverse sources, both natural and man-made
It’s difficult to find out which components or sources of the mixture lead to adverse effects
Advanced statistical methods to disentangle effects of multiple pollutants
Studies of large populations to provide insight into effects below the current air quality standards
Statistical Methods. HEI has been involved in several areas of multipollutant research. Recently, three studies were completed that developed and evaluated statisticial methods to disentangle the effects of multiple pollutants in the ambient mixture (see RFA 09-1, Methods to Investigate the Effects of Multiple Air Pollution Constituents).
Health Effects at Low Concentrations. Levels of ambient air pollution have declined significantly over the last decades in North America, Europe, and in other high-income regions. Nonetheless, recent epidemiologic studies report adverse health effects even at these lower levels of exposure. In order to inform future risk assessment and regulation, it is important to know whether adverse effects continue to be observed as levels of air pollution decline still further, and what the shape of the exposure-response function is at those low levels; these issues currently represent the major remaining uncertainties in air quality standards decisions. HEI recently funded three studies that will evaluate large populations in North America and Europe to delve into this important question (see RFA 14-3, Assessing Health Effects of Long-term Exposure to Low Levels of Ambient Air Pollution).
This study will investigate mortality effects of low levels of air pollution in Canada using Canadian Census data from about 6 million people. The shape of the exposure-response function will be characterized using newly developed flexible non-linear exposure-response functions. See also this Program Summary of HEI's research program on low levels of air pollution.
This study will examine health effects of low levels of air pollution in the US using data from about ~56 million people enrolled in Medicare and Medicaid. In addition, they will develop new causal modeling methods to characterize the shape of the exposure-response function. See also this Program Summary of HEI's research program on low levels of air pollution.