Critical Issues of Exposure Assessment for Human Health Studies of Air Pollution

1. Critical Issues of Exposure Assessment for Human Health Studies of Air Pollution SAMSI September 15, 2009 Michelle L. Bell Yale University

2. Outline • Basic health effects model • Methods of measuring exposure • Key challenges in assessing exposure • Spatial misalignment • Multiple pollutant exposures • Special case of particulate matter • Current and upcoming approaches to estimating exposure • Other challenges

3. Exposure Assessment for Studies of Air Pollution and Health • Basic health effects model • Methods of measuring exposure • Key challenges in assessing exposure • Spatial misalignment • Multiple pollutant exposures • Special case of particulate matter • Current and upcoming approaches to estimating exposure • Other challenges

4. Example Air Pollution and Health Effects Model • Time-series model / Acute exposure • Community-aggregated health data • Community-aggregated exposure data

5. Example Air Pollution and Health Effects Model Estimated Air Pollution Exposure

6. Exposure Assessment for Studies of Air Pollution and Health • Basic health effects model • Methods of measuring exposure • Key challenges in assessing exposure • Spatial misalignment • Multiple pollutant exposures • Special case of particulate matter • Current and upcoming approaches to estimating exposure • Other challenges

7. Traditional Approaches to Exposure Assessment • Use of ambient monitors + cost-effective + can provide large sample size • not present in all times or locations of interest • locations based on regulatory, not scientific, purposes • obscures between-person differences • Personal monitors + individualized data • short timeframe • small population • logistical concerns Source: Louisville, KY government Jiang and Bell EHP 2008

8. Traditional Approaches to Exposure Assessment • Use of ambient monitors + cost-effective + can provide large sample size • not present in all times or locations of interest • locations based on regulatory, not scientific, purposes • obscures between-person differences • Personal monitors + individualized data + measure pollutant characteristics of interest • short timeframe and small population • logistical concerns and expensive

9. Exposure Assessment for Studies of Air Pollution and Health • Basic health effects model • Methods of measuring exposure • Key challenges in assessing exposure • Spatial misalignment • Multiple pollutant exposures • Special case of particulate matter • Current and upcoming approaches to estimating exposure • Other challenges

10. Spatial Misalignment • Spatially heterogeneity in the concentration surface field • Mismatch between data used to estimate exposure and actual subjects’ locations

11. Correlation of PM2.5 components by distance Peng and Bell Biostatistics Accepted

12. Spatial Disconnect in Data Pollution data measured at a single or multiple fixed locations Health data aggregated over a spatial area Weather data measured at a single or multiple fixed locations, that likely differ from the pollution monitor locations

13. Error Model Pollution data measured at a single or multiple fixed locations True pollution level over a spatial area Peng and Bell Biostatistics Accepted

14. Spatial Misalignment Adjustment • Monitor average ( ) good proxy for true value ( xt) with good monitor coverage and/or low spatial heterogeneity • Spatial misalignment adjustments useful when: • Pollutant very spatially heterogeneous (e.g., EC) • Poor monitor coverage within area of interest, but monitors elsewhere

15. Multi-Pollutant Concepts • Physiologically we respond to a complex mixture of air pollutants • Many studies focus on the effects of a single pollutant • Additional pollutants typically considered with respect to confounding, not complex effects • Air pollution policy set for single pollutants • Based on single pollutant science

16. SO2 PM Pb NOx CO VOCs Major Air Pollution Emissions Sources Industrial Sources Diesel Domestic Sources Gasoline Power Generation VEHICLE SOURCES STATIONARY SOURCES

17. Particulate Matter • What is represented by an exposure estimate for PM? • Only pollutant regulated without regard to chemical form • May vary in: • Size • Shape • Chemical structure • Water content • Acidity • Age • Etc.

18. Different chemical components by PM size Different sources by PM size

19. <1.0 mg/m3 1.0 to 2.5 2.5 to 4.0 4.0 to 5.5 >5.5 PM as a Pollutant Mixture PM2.5 sulfate (2000-2002) Bell et al. EHP 2007

20. Spring Winter Fall Summer <2 mg/m3 2 to 3 Seasonal sulfate PM2.5 averages for 187 U.S. counties, 2000-2005 3 to 4 4 to 5 >5 Bell et al. EHP 2007

21. PM2.5 and Medicare Hospital Admissions 3 2 1 0 -1 West East -2 % Change in Hospital Admissions per 10 mg/m3 PM2.5 Ischemic Heart Disease Heart Failure Heart Rhythm Respiratory Infection COPD Peripheral Vascular Disease Cerebrovascular Disease Dominici et al. JAMA 2006

22. Allow Temporal Variation in Effect Estimates Based on Variation in Exposure

23. Season Interaction Model • Allows different effect estimates by season Harmonic Model • Allows effect estimates to differ throughout the year Bell et al. Am J Epidemiol 2008

24. Seasonal Variation in PM Total Mass Health Effect Estimates % increase in CVD hospitalizations per 10 mg/m3 L0 PM2.5 Day of the year Bell et al. Am J Epidemiol 2008

25. Exposure Assessment for Studies of Air Pollution and Health • Basic health effects model • Methods of measuring exposure • Key challenges in assessing exposure • Spatial misalignment • Multiple pollutant exposures • Special case of particulate matter • Current and upcoming approaches to estimating exposure • Other challenges

26. Domain 1 Domain 2 Domain 3 Domain 4 Example: Air Quality Modeling to Estimate Exposure • CMAQ / MM5 • Aug 15 – 18, 1995 • 2,168 cells with 4 km horizontal resolution • 8 monitors for ozone Bell Environ Int 2006

27. Bell and Ellis J Air Waste Manage Assoc 2003

28. > 180 170 to 180 160 to 170 150 to 160 140 to 150 130 to 140 120 to 130 110 to 120 100 to 110 <100 County-level Exposure Estimates 1-Hour max O3 (ppb) Monitor in county Modeling estimates Spatial interpolation of monitors Bell Environ Int 2006

29. 180+ 170 to 180 160 to 170 150 to 160 140 to 150 130 to 140 120 to 130 110 to 120 100 to 110 <100 Modeling estimates Individual-Level Exposure Estimates 1-Hour max O3 (ppb) Nearest monitor Bell Environ Int 2006

30. < 50 51 to 75 75 to 150 151 to 250 251 to 500 501 to 1000 >1001 Ozone monitors in Georgia 2000 Persons / Sq. Mile

31. Example: Traffic Modeling to Estimate Exposure Holford et al. Statistics in Medicine Accepted

32. Estimated NO2 (traffic) Levels for New Haven County Area (2002) Holford et al. Statistics in Medicine Accepted

33. Exposure Assessment for Studies of Air Pollution and Health • Basic health effects model • Methods of measuring exposure • Key challenges in assessing exposure • Spatial misalignment • Multiple pollutant exposures • Special case of particulate matter • Current and upcoming approaches to estimating exposure • Other challenges

34. Other Challenges • Other factors affecting certainty of monitor values • Detection limits of monitors • Measurement error (see co-located monitors) • Other factors that affect exposure and variation of exposure • Movement through the community • Indoor/outdoor activity patterns • Behaviors and activities (e.g., AC, jogging) • Differences between exposure and dose

35. Thank you • Key Collaborators • Francesca Dominici, Harvard University • Roger D. Peng, Johns Hopkins University • Keita Ebisu, Yale University • Sponsors • National Institute for Environmental Health Sciences (NIEHS) • Health Effects Institute • U.S. Environmental Protection Agency-sponsored Johns Hopkins Particulate Matter Research Center