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Critical Issues of Exposure Assessment for Human Health Studies of Air Pollution. SAMSI September 15, 2009. Michelle L. Bell Yale University. Outline. Basic health effects model Methods of measuring exposure Key challenges in assessing exposure Spatial misalignment

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Critical issues of exposure assessment for human health studies of air pollution

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

SAMSI

September 15, 2009

Michelle L. Bell

Yale University


Outline
Outline Studies of Air Pollution

  • 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
Exposure Assessment for Studies of Air Pollution and Health Studies of Air Pollution

  • 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 Studies of Air Pollution

  • Time-series model / Acute exposure

  • Community-aggregated health data

  • Community-aggregated exposure data


Example Air Pollution and Health Effects Model Studies of Air Pollution

Estimated Air Pollution Exposure


Exposure assessment for studies of air pollution and health1
Exposure Assessment for Studies of Air Pollution and Health Studies of Air Pollution

  • 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


Traditional approaches to exposure assessment
Traditional Approaches to Exposure Assessment Studies of Air Pollution

  • 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


Traditional approaches to exposure assessment1
Traditional Approaches to Exposure Assessment Studies of Air Pollution

  • 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 health2
Exposure Assessment for Studies of Air Pollution and Health Studies of Air Pollution

  • 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
Spatial Misalignment Studies of Air Pollution

  • 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
Correlation of PM Studies of Air Pollution2.5 components by distance

Peng and Bell Biostatistics Accepted


Spatial disconnect in data
Spatial Disconnect in Data Studies of Air Pollution

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


Error model
Error Model Studies of Air Pollution

Pollution data measured at a single or multiple fixed locations

True pollution level over a spatial area

Peng and Bell Biostatistics Accepted


Spatial misalignment adjustment
Spatial Misalignment Adjustment Studies of Air Pollution

  • 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


Multi pollutant concepts
Multi-Pollutant Concepts Studies of Air Pollution

  • 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

SO Studies of Air Pollution2

PM

Pb

NOx

CO

VOCs

Major Air Pollution Emissions Sources

Industrial Sources

Diesel

Domestic Sources

Gasoline

Power

Generation

VEHICLE

SOURCES

STATIONARY

SOURCES


Particulate matter
Particulate Matter Studies of Air Pollution

  • 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 Studies of Air Pollution

Different sources by PM size


<1.0 Studies of Air Pollutionmg/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


Spring Studies of Air Pollution

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


Pm 2 5 and medicare hospital admissions
PM Studies of Air Pollution2.5 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



Season interaction model
Season Interaction Model Variation in Exposure

  • 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 Variation in Exposure

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


Exposure assessment for studies of air pollution and health3
Exposure Assessment for Studies of Air Pollution and Health Variation in Exposure

  • 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

Domain 1 Variation in Exposure

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


Bell and Ellis Variation in ExposureJ Air Waste Manage Assoc 2003


> 180 Variation in Exposure

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


180+ Variation in Exposure

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


Ozone monitors in georgia 2000

< Variation in Exposure 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


Example traffic modeling to estimate exposure
Example: Traffic Modeling to Estimate Exposure Variation in Exposure

Holford et al. Statistics in Medicine Accepted


Estimated no 2 traffic levels for new haven county area 2002
Estimated NO Variation in Exposure2 (traffic) Levels for New Haven County Area (2002)

Holford et al. Statistics in Medicine Accepted


Exposure assessment for studies of air pollution and health4
Exposure Assessment for Studies of Air Pollution and Health Variation in Exposure

  • 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 Challenges Variation in Exposure

  • 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
Thank you Variation in Exposure

  • 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


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