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

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Presentation transcript:

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

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

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

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

Example Air Pollution and Health Effects Model Estimated Air Pollution Exposure

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

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 Traditional Approaches to Exposure Assessment Source: Louisville, KY government Jiang and Bell EHP 2008

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

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

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

Correlation of PM 2.5 components by distance Peng and Bell Biostatistics Accepted

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

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

Spatial Misalignment Adjustment Monitor average ( ) good proxy for true value ( x t ) 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

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

Major Air Pollution Emissions Sources Industrial Sources Domestic Sources Power Generation SO 2 PbNO x CO PMVOCs Diesel Gasoline STATIONARY SOURCES VEHICLE SOURCES

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.

Different chemical components by PM size Different sources by PM size

<1.0  g/m to to to 5.5 >5.5 PM as a Pollutant Mixture PM 2.5 sulfate ( ) Bell et al. EHP 2007

Seasonal sulfate PM 2.5 averages for 187 U.S. counties, Winter Spring Summer Fall <2  g/m 3 2 to 3 4 to 5 >5 3 to 4 Bell et al. EHP 2007

% Change in Hospital Admissions per 10  g/m 3 PM 2.5 West East Respiratory Infection COPD Heart Failure Heart Rhythm Ischemic Heart Disease Peripheral Vascular Disease Cerebrovascular Disease Dominici et al. JAMA 2006 PM 2.5 and Medicare Hospital Admissions

Allow Temporal Variation in Effect Estimates Based on Variation in Exposure

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

Seasonal Variation in PM Total Mass Health Effect Estimates Bell et al. Am J Epidemiol 2008 % increase in CVD hospitalizations per 10  g/m 3 L0 PM 2.5 Day of the year

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

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

Bell and Ellis J Air Waste Manage Assoc 2003

<100 > to to to to to to to to 110 Modeling estimates Monitor in county Spatial interpolation of monitors 1-Hour max O 3 (ppb) County-level Exposure Estimates Bell Environ Int 2006

< to to to to to to to to Hour max O 3 (ppb) Modeling estimates Nearest monitor Individual-Level Exposure Estimates Bell Environ Int 2006

Ozone monitors in Georgia 2000 < to to to to to 1000 >1001 Persons / Sq. Mile

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

Estimated NO 2 (traffic) Levels for New Haven County Area (2002) Holford et al. Statistics in Medicine Accepted

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

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

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