|Before the Air Pollution Control Act of 1955, air pollution was not considered a national environmental problem. (Photo credit: Wikipedia)|
Identifying exposure disparities in air pollution epidemiology specific to adverse birth outcomes (4 page pdf, Laura A Geer, Environmental Research Letters, Oct. 8, 2014)
Today we review a short research note that pointed out that almost half of the population of the USA live in areas with higher air pollution levels than standards allow. At the same time, standard reference air quality monitors tend to be located in high pollution areas and also in areas where certain sectors of the population live, some of whom are more vulnerable to those impacts- such as pregnant women with low incomes. Unless these biases are taken into account, general conclusions drawn may exaggerate the impacts. This suggests both more care in monitor siting and allowance for bias in population exposure.
“More than 147 million people in the US live in areas where pollutant levels are above regulatory limits and pose a risk to health. Most of the vast network of air pollutant monitors in the US are located in places with higher pollution levels…Vulnerable populations are more likely to reside near air pollutant sources, and thus near pollutant monitors placed in higher pollution level zones.”
"Specific area-level or neighborhood-level factors that set up for disproportionate air pollution exposure to socioeconomically disadvantaged populations include proximity to traffic and roads, crowding, poor infrastructure, hindered access to transportation and services (e.g., supermarkets and health care),…”
“In large epidemiologic studies linking air pollution from stationary monitors with health outcomes, it is especially important to accurately classify maternal pollutant exposure status.” “Another measurement consideration is the distance of the individual study participant from pollutant monitors, encompassing the issue of selection of buffer size.”
“selection of exposure assessment method comes with tradeoffs in accurate exposure classification, sample size, and population characteristics, ultimately impacting the generalizability of the study“