You are here:
Estimating Personal Exposures from Ambient Air Pollution Measures - Using Meta-Analysis to Assess Measurement Error
Citation:
Holliday, K., C. Avery, C. Poole, K. McGraw, R. Williams, D. Liao, R. Smith, AND E. Whitsel. Estimating Personal Exposures from Ambient Air Pollution Measures - Using Meta-Analysis to Assess Measurement Error. EPIDEMIOLOGY. Lippincott Williams & Wilkins, Philadelphia, PA, 25(1):35-36, (2014).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA′s mission to protect human health and the environment. HEASD′s research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA′s strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
Although ambient concentrations of particulate matter ≤ 10μm (PM10) are often used as proxies for total personal exposure, correlation (r) between ambient and personal PM10 concentrations varies. Factors underlying this variation and its effect on health outcome-PM exposure relationships remain poorly understood. The authors therefore conducted a systematic review of literature examining r, including fifteen studies (1990-2009) of 342 participants in five countries. The median (range) of r was 0.46 (0.13,0.72). There was little evidence of funnel plot asymmetry, but substantial heterogeneity of r, which increased 0.05 (95% confidence interval [CI]: 0.01,0.09) per 10µg/m3 increase in mean ambient PM10 concentration.
URLs/Downloads:
PM10_EPID_ACCEPTED FINAL FINAL.PDF (PDF, NA pp, 2126.648 KB, about PDF)Epidemiology
