USING GIS FOR EXPOSURE

ASSESSMENTJ.R. NUCKOLS, PhD

COLORADO STATE UNIVERSITY, FORT COLLINS, COLORADO, USA

http://ehasl.cvmbs.colostate.edu

GOALS

• FUNDAMENTAL PRINCIPLES– GEOSPATIAL SCIENCE

– HEALTH SCIENCE

– ENVIRONMENTAL SCIENCE

• EXPOSURE ASSESSMENT PROCESS - ENVIRONMENTAL EPIDEMIOLOGY

• STATE OF THE SCIENCE – GIS AND ENVIRONMENTAL EPIDEMIOLOGY

FUNDAMENTALS• GEOSPATIAL SCIENCE

– SCALE– RESOLUTION– VALIDATION

• ENVIRONMENTAL SCIENCE– GEOPHYSICAL PLAUSIBILITY– MEAUREMENT DATA– ALGORITHMS – VALIDATION

• EPIDEMIOLOGY– BIOLOGICAL PLAUSIBILITY– CONFOUNDING FACTORS– STATISTICAL POWER

ENVIRONMENTAL = SPATIAL

ENVIRONMENTAL EPIDEMIOLOGY: Evaluates associations between environmental

exposures and health outcomes, with the purpose of further understanding the etiology of disease

COMMON SPATIAL FACTORSEPIDEMIOLOGY

CONTAMINANT OF INTEREST

STUDY POPULATIONDEMOGRAPHICS

INCIDENCE OF DISEASE

EXPOSURE ASSMT

SOURCE ID

SYSTEM BOUNDARYFATE/TRANSPORT

EXPOSURE METRIC

GIS-Based Exposure Assessment:

Agricultural Chemicals

and

Childhood Cancer

Principal Co-Investigators:

Dr. Mary H. Ward, NCI-OEB

Dr. Peggy Reynolds, CDHS-EHIB

Mr. Robert Guiner, CDHS-EHIB

Mr. Ryan Miller, USDA-APHIS

Funding: USDHHS-NIH-NCI grants RO3 CA83071, RO1CA71745, and RO1CA92683, andUSDHHS-NIH-NCI Occupational and Environmental Epidemiology Branch.

San Francicso

Sacramento

Fresno

Kilometers

0 400200

STATE OF CALIFORNIA, USA

The Problem… landscape trends

Highly integrated landscapes…

…with multiple applications to many fields.

Complex landscapes = Complex Processes …

… Pesticide Use Patterns are Complex

… Variable application method• Aerial• Ground• Orchard Blast• Fumigation• Chemgation

… Variable in time and space

CONTAMINANT OF INTEREST

SOURCE IDENTIFICATION

Selection of Pesticides

• 850 Pesticides in California Pesticide Use Reporting Database

• Prioritized Study Pesticides based on:– Carcenogenicity– Transportability– Use in our study area

• 6 Pesticides in initial study, Approx 30 will be analyzed in validation study

0 25 5012.5

Kilometers

Pounds of Chemicals Applied

1 - 250

251 - 500

501 - 750

751 - 1000

1001 - 20000

California Pesticide Use Reporting DatabaseFresno, Madera, Kings, and Tulare Counties

Fresno

STUDY POPULATION

FATE/TRANSPORT

CPUR Expossure Metric

Section A Section B

1,400 lbs - Methyl BromideApplied to Grapes

CASE/CONTROL RESIDENCE

0 25 5012.5

Kilometers

California Department of Water Resources DatabaseFresno, Madera, Kings, and Tulare Counties

Row and Field Crops

RiceOrchards

Urban Land

PastureSurface Water

Vineyards

Fresno

Grain and Hay Crops

CDWR Metric

Section A Section B

1,400 lbs - Methyl BromideApplied to Grapes

Vineyard

Spatial Refinement of Pesticide Use Data

Residences

1

10

100

1000

Ave

rag

e P

esti

cid

e U

se (

lbs/

sq m

ile)

Trifualin Simazine Propargite Dicofol MethylBromide

Chemical

Predicted Pesticide Use Within Exposure Zone

CPUR Metric

CDWR Metric

0.4

1,230

0

50

100

150

200

250

Nu

mb

er

Trifuralin Simazine Propargite Dicofol MethylBromide

Chemical

Study Population Classified as Exposed(Total N = 577)

CPUR Metric

CDWR Metric

0

10

20

30

40

50

60

70

80

90

100

Per

cen

t o

f S

tud

y P

op

ula

tio

n

Low Medium High

Exposure Class

Exposure Classification

CPURCDWR

EPIDEMIOLOGICAL RISK

EXPOSURE METRIC

SENSITVITY AND SPECIFICITY OF THE PUR EXPOSURE METRIC USING THE CDWR METRIC AS THE “GOLD STANDARD”

Trifuralin Simazine Propargite DicofolMethyl

Bromide

Sensitivity 100% 100% 100% 100% 100%

Specificity 78% 72% 68% 87% 74%

Prevalence 2.1% 0.3% 3.8% 2.4% 2.1%

Non-differential exposure misclassificationExample: 2% exposure prevalence, true RR = 2

1.0 0.8 0.6 0.4 0.2

1.0 2.00 1.99 1.98 1.98 1.97

0.8 1.09 1.07 1.05 1.02 1.00

0.6 1.05 1.03 1.02 1.00

0.4 1.03 1.02 1.00

0.2 1.02 1.00

Sp

ecif

icit

y

Sensitivity

Source: Norell SE, 1987

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LIN N

LEE

SAC

TAMA

ID A

SIOUXCLAY

IOWAPOLK

LYON

CASS

KOSSUTH

PAGE

JASPER

ADAIR

BENTON JONES

STORY

DAVIS

CLAYTONFAYETTE

CEDAR

CLINTON

BOONE

PLYMOUTH

MONON A

FLOYD

DALLASSHELBY

BUTLER

MILLS

O'BRIEN

WOODBU RYWEBSTER

WAYNE

HARD IN

WRIGHT

MARION

SCOTT

GREENE

KEOKUK

TAYLOR

JACKSON

GUTH RIEHARRISON

WARREN

UNION LU CAS HEN RY

JOHNSON

DUBUQUE

CRAW FOR D CARR OLL

MADISON

ADAMS

GRUND Y

FRANKLIN

CALHOUN

MAHASKA

LOUISA

HANC OCK

POTTAWATTAMIE

EMMET

DECATU R

ALLAMAKEE

HAMILTON

WINNESHIEKWORTH

CLARKE

FREMONT

MARSHALL

DELAWARE

HOWARD

CHER OKEEBREMER

PALO ALTO

BUCHAN AN

RINGGOLD

POWESHIEK

MONROE

MITCHELL

WAPELLO

AUDU BON

BUENA VISTA

BLACK HAWK

VAN BUREN

OSCEOLA

WASHINGTON

CHICKASAW

POCAHONTAS

APPANOOSE

HUMBOLDT

MUSCATIN E

CERR O GORDO

JEFFERSON

DICKIN SON

DES MOIN ES

WINNEBAGO

MONTGOMERY

Path 26 Row 31Path 27 Row 31

Residence Locations

Residence Locations#S 237 in the study area#S 407 not in the study area

Outline of Landsat Scene

IOWA NHL STUDY: Satellite image boundaries & residences (from Ward et al., 2003)

750 m

500

250100

OR = 11.0

OR = 3.5

OR = 2.8

OR = 1.6**Not statistically significantRef: Ward et al. (2003)

Odds Ratio (OR) of detecting ≥ 1 of 9 herbicides in house dustResidences with vs without corn or soybean fields in buffer

N = 112 residences

Residence

SCORECARD• GEOSPATIAL SCIENCE

– SCALE– RESOLUTION– VALIDATION

• ENVIRONMENTAL SCIENCE– GEOPHYSICAL PLAUSIBILITY– MEAUREMENT DATA– ALGORITHMS – VALIDATION

• EPIDEMIOLOGY– BIOLOGICAL PLAUSIBILITY– CONFOUNDING FACTORS– STATISTICAL POWER

STATE OF THE SCIENCE

• EDUCATIONAL OPPORTUNITIES

• INSTITUTIONAL SUPPORT

• RESEARCH

INSTITUTIONAL SUPPORT IN THE USA

• PROGRAMS– Agency for Toxic Substances and Disease Registry– National Cancer Institute– Unites States Environmental Protection Agency– Centers for Disease Control and Prevention

• ISSUES– FEASIBILITY– COST– IMPLEMENTATION

PROPOSED RESEARCH INITIATIVES

• MORE CASE STUDIES / METHODS DEVEL AND VALIDATION

• ROLE OF SPATIAL ANALYSIS AND STATISTICS

• UNCERTAINTY IN EXPOSURE ASSESSMENT

• RETROSPECTIVE ANALYSIS – INCORPORATING TEMPORAL ASPECT

• LONG TERM STUDY SITES

• Understanding ecological phenomena over long temporal and large spatial scales.

• Create a legacy of well-designed and documented long-term experiments.

• Conducting major synthetic and theoretical efforts.

• Providing information for the identification

and solution of ecological problems.

NSF Long Term Ecological Research Network

International LTER NetworkCurrently 21 Countries Actively Contribute

Proposed NCI Geographic-Based Surveillance Project

DiseaseIncidence

EcologicalInformation

Understanding Long Term Influence of

Environmental Factors.

CONCLUSIONS

• USE OF GIS IS FEASIBLE FOR EXPOSURE ASSESSMENT– USE OF GIS CAN IMPROVE EXPOSURE

ASSESSMENT

• INTERDISCIPLINARY APPROACH ESSENTIAL – MUST CONSIDER FUNDAMENTALS OF EACH

SCIENTIFIC DISCIPLINE

• NEED EXPANDED EDUCATIONAL AND INSTITUTIONAL SUPPORT