Bayer-Oglesby, Lucy

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Bayer-Oglesby
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Lucy
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Bayer-Oglesby, Lucy

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2000 - 20072
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Thema: exposure assessment ×

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  • Vorschaubild
    Publikation
    Characterization of source-specific air pollution exposure for a large population-based Swiss cohort (SAPALDIA)
    (National Institute of Environmental Health Sciences, 2007) Liu, L.-J. Sally; Curjuric, Ivan; Keidel, Dirk; Heldstab, Jürg; Künzli, Nino; Bayer-Oglesby, Lucy; Ackermann-Liebrich, Ursula; Schindler, Christian [in: Environmental Health Perspectives]
    Background: Although the dispersion model approach has been used in some epidemiologic studies to examine health effects of traffic-specific air pollution, no study has evaluated the model predictions vigorously. Methods: We evaluated total and traffic-specific particulate matter < 10 and < 2.5 microm in aero-dynamic diameter (PM(10), PM(2.5)), nitrogren dioxide, and nitrogen oxide concentrations predicted by Gaussian dispersion models against fixed-site measurements at different locations, including traffic-impacted, urban-background, and alpine settings between and across cities. The model predictions were then used to estimate individual subjects' historical and cumulative exposures with a temporal trend model. Results: Modeled PM(10) and NO(2) predicted at least 55% and 72% of the variability of the measured PM(10) and NO(2), respectively. Traffic-specific pollution estimates correlated with the NO(x) measurements (R(2) >or=0.77) for background sites but not for traffic sites. Regional background PM(10) accounted for most PM(10) mass in all cities. Whereas traffic PM(10) accounted for < 20% of the total PM(10), it varied significantly within cities. The modeling error for PM(10) was similar within and between cities. Traffic NO(x) accounted for the majority of NO(x) mass in urban areas, whereas background NO(x) accounted for the majority of NO(x) in rural areas. The within-city NO(2) modeling error was larger than that between cities. Conclusions: The dispersion model predicted well the total PM(10), NO(x), and NO(2) and traffic-specific pollution at background sites. However, the model underpredicted traffic NO(x) and NO(2) at traffic sites and needs refinement to reflect local conditions. The dispersion model predictions for PM(10) are suitable for examining individual exposures and health effects within and between cities.
    01A - Beitrag in wissenschaftlicher Zeitschrift
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    Publikation
    Personal exposure assessment studies may suffer from exposure-relevant selection bias
    (Nature, 27.07.2000) Bayer-Oglesby, Lucy; Rotko, Tuulia; Krütli, Pius; Boudet, Céline; Kruize, Hanneke; Jantunen, Matti; Künzli, Nino [in: Journal of Exposure Science & Environmental Epidemiology]
    We evaluated exposure-relevant selection bias within the framework of a study on personal air pollution exposure, using traffic data as exposure proxy. Based on random samples of 3000 (Basel) and 2532 (Helsinki) persons, 50 and 250 subjects, respectively, were recruited for direct monitoring and 250 (Basel, Helsinki) for indirect monitoring. In Basel, participants of direct monitoring as compared to non-participants were more likely to live at streets with low traffic volume (49% below 1st quartile vs. 27%). Adjusted for sex, age and nationality, an increase of 100 cars per hour was associated with 14% less participation (odds ratio (OR): 0.861; 95% CI: 0.731, 1.007). Although in Helsinki, traffic volume was neither significantly related to participation in direct nor indirect monitoring, the point estimates indicate a tendency to decreased participation with increasing traffic intensity at home. We conclude that selection bias regarding exposure-relevant characteristics is likely to occur when recruiting participants for studies including demanding personal exposure assessment. Correction for factors routinely collected may not fully account for exposure-relevant bias. This is of particular importance when using exposure data for modelling population exposure distributions, whereas in epidemiological studies, a reduced range of exposure must not a priori distort the exposure-response relationship.
    01A - Beitrag in wissenschaftlicher Zeitschrift