Estimating personal exposures from ambient air pollution measures: Using meta-analysis to assess measurement error

Katelyn M. Holliday, Christy L. Avery, Charles Poole, Kathleen McGraw, Ronald Williams, Duanping Liao, Richard L. Smith, Eric A. Whitsel

Research output: Contribution to journalReview articlepeer-review

18 Scopus citations


BACKGROUND:: Although ambient concentrations of particulate matter ≤10 μm (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. METHODS:: We conducted a random-effects meta-analysis to estimate effects of study, participant, and environmental factors on r; used the estimates to impute personal exposure from ambient PM10 concentrations among 4,012 nonsmoking, participants with diabetes in the Women's Health Initiative clinical trial; and then estimated the associations of ambient and imputed personal PM10 concentrations with electrocardiographic measures, such as heart rate variability. RESULTS:: We identified 15 studies (in years 1990-2009) of 342 participants in five countries. The median r was 0.46 (range = 0.13 to 0.72). There was little evidence of funnel plot asymmetry but substantial heterogeneity of r, which increased 0.05 (95% confidence interval = 0.01 to 0.09) per 10 μg/m increase in mean ambient PM10 concentration. Substituting imputed personal exposure for ambient PM10 concentrations shifted mean percent changes in electrocardiographic measures per 10 μg/m increase in exposure away from the null and decreased their precision, for example, -2.0% (-4.6% to 0.7%) versus -7.9% (-15.9% to 0.9%), for the standard deviation of normal-to-normal RR interval duration. CONCLUSIONS:: Analogous distributions and heterogeneity of r in extant meta-analyses of ambient and personal PM2.5 concentrations suggest that observed shifts in mean percent change and decreases in precision may be generalizable across particle size.

Original languageEnglish (US)
Pages (from-to)35-43
Number of pages9
Issue number1
StatePublished - Jan 2014

All Science Journal Classification (ASJC) codes

  • Epidemiology


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