GIS using in Epidemiology and Risk Assessment

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GIS using in Epidemiology and Risk Assessment
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Content

• GIS and Epidemiology
• GIS and Risk Assessment
• Examples

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John Snow (1813-1858)

• GP based in Soho section of London
• Insight into communication of cholera by water

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Health Risk Assessment- Modified from Health
Risk Assessment, Dr. Bill Hartley

• 2006/05/09

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ENHS 762 Health Risk Assessment, Dr. Bill Hartley
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Basic Concepts and Definitions

• Risk Assessment
• The scientific estimation (qualitative or
  quantitative) of hazard which is obtained by
  combining the results of an exposure assessment
  with the results of the toxicity assessment for
  the subject chemical.

Modified from Health Risk Assessment, Dr. Bill
Hartley
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Basic Concepts and Definitions

• Risk Management
• The judgment and analysis that combine the
  scientific results of a risk assessment with
  economic, political, legal and social factors to
  produce a decision about environmental action.

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Basic Concepts and Definitions

• Risk Communication
• Communication of risk assessment/management
  information to the public, reporters, and
  state/local officials.

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What is Risk?

• the likelihood of injury, disease, or death
• What is Environmental Risk?
• The likelihood of injury, disease, or death
  resulting from human exposure to a potential
  environmental hazard

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Comparative Risks of Death
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Comparative Risks Pesticides
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Risk

• Subjective
• Not a risk-free world
• Uncertainty complexity
• Probabilistic
• Benchmarks
• Product of probability consequence

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Risk Assessment
dose-response assessment
hazard identification
risk characterization
exposure assessment
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Risk Management and Risk Assessment Working
Together

• Risk Assessment

• Risk Management

dose-response assessment
regulatory decision
hazard identification
risk characterization
control options
exposure assessment
non-risk analyses
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Non-risk Analyses
economics
regulatory decision
risk characterization
politics
control options
statutory legal considerations
non-risk analyses
social factors
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Risk Management and Risk Assessment working
together

• Risk Assessment

Risk Management
dose-response assessment
hazard identification
regulatory decision
risk characterization
exposure assessment
control options
non-risk analyses
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The Components of Risk Assessment

• Hazard Identification
• Dose-Response Evaluation
• Human Exposure Evaluation
• Risk Characterization

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Component 1 Hazard Identification
?

• Agent

Effect
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Human Evidence

• Sufficient
• Limited
• Inadequate
• No Data
• No evidence

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Advantages Uncertainties of Animal Data
Dolly
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Weigh All the Evidence
Human Evidence
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Hazard Identification

• Review analyze toxicity data
• Weigh the evidence that a substance causes
  various toxic effects
• Evaluate whether toxic effects in one setting
  will occur in other settings

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Component 2 Dose-Response Assessment
?
Dose
Response
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Dose-Response

• Dancing with proper limitations is a salutary
  exercise, but when violent and long continued in
  a crowded room it is extremely pernicious, and
  has hurried many young people to the grave.
• A.
  Murray, M.D. 1826

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Sources of Toxicity Data

• Human Studies
• Case reports
• Epidemiological studies
• retrospective
• prospective
• case-control

• Animal Studies
• General toxicity studies
• acute sub-chronic
• sub-acute chronic
• Specialized toxicity studies
• teratology
• genotoxicity
• developmental
• male/female reproductive
• cancer
• endocrine disruption

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Animal Data
Approximate Oral LD50 in rats for a group of
well-known chemicals Chemical
LD50(mg/kg) Sucrose (table sugar) 29,700 Ethyl
alcohol 14,000 Sodium chloride 3,000
(table salt) Vitamin A 2,000 Aspirin
1,000 Chloroform 800 Copper Sulfate
300 Caffeine 192 Phenobarbital
162 DDT 113 Nicotine 53
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Dose-Response Evaluation

• Threshold

• Non-
• Threshold

Cancer
Organ Damage
No effect
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Dose-Response Evaluation
Threshold-Systemic Toxicity (Non-cancer)
responding
MFO Slim
Fatty Change
Decreased Dye Clearance
Mortality
Dose (mg/kg)
mixed function oxidase
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Dose-Response Evaluation
Non-threshold--Cancer
Performed to estimate the incidence of the
adverse effect as a function of the magnitude of
human exposure to a substance
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Dose-Response Curve
Non-Threshold--Cancer
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Dose-Response Curve
Non-Threshold--Cancer
Observable range
Response
Range of inference
0
Dose
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Dose-Response Evaluation

• All substances are poisons there is none which
  is not a poison. The right dose differentiates a
  poison and a remedy. Paracelsus
  (1495-1541)

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Dose-Two types of measurement

• Type I
• Measurement of the amount of the substance in the
  medium (air, diet, etc.) in which it is present
  or administered.
• NOT DOSE

• Type II
• Measurement of the amount absorbed by the
  subject, whether human or animal.
• DOSE

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Dose

• Example
• Chemical HC-BAD is present in drinking water at a
  concentration of 10mg/L (Type I measurement)
• What is the dose (DAILY) for an adult (Type II)?
• Exposure Assumptions Body weight 70kg (150
  lbs)
• Water consumption 2L water/day

by convention
or .29mg/kg ? day
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Component 3 Exposure Assessment

• ?

Agent
People
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Exposure Issues Assumptions

• Extent frequency of human exposure
• how much?
• how often?
• how certain?
• Number of people exposed
• Degree of absorption by various routes of
  exposure
• Use of average or typical individual
• Use of high risk groups

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Routes of Exposure

• Ingestion (Drinking, Food)
• Skin Absorption (Water, Soil)
• Inhalation
• Total Dose is equal to the sum of the doses from
  the above routes ( pathways)

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Estimation of exposure levels

• Direct
• Measure the actual concentration of chemical in
  the air, water or food used by an individual.
• Measure the actual amount of air, water or food
  used by the individual.
• Calculate the actual dose to the individual.

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Estimation of exposure levels

• Reconstructive
• Measure the level of the chemical, its
  metabolites, or some other chemical-specific
  change (biomarker) in the body.
• Based on toxicokinectic models, calculate the
  dose to the individual from the level of the
  biomarker.

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Estimation of exposure levels

• Predictive
• Measure or calculate the concentration of
  chemical in environmental media around the
  source.
• Estimate human contact with the media.
• Estimate the resulting dose to the average person.

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Component 4 Risk Characterization
Hazard Identification
Risk Characterization
Dose-Response
Exposure
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Risk Assessment Issues
Hazard Animal data Identification
Epidemiological Studies
Weight of Evidence Dose-Response
Extrapolation from high to low Assessment
dose Extrapolation from
animals to humans Exposure
Assessment Modeling vs. monitoring vs.
biological monitoring Risk Characterization
Qualitative or quantitative
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Quantitative Analysis of Cancer Risk

• In Air (mg/kg-day)-1 -gt ? (mg/m3)-1
• -gt Unit from (kg-day/mg) to (m3/mg)
• Exposure Assumption (adult only)
• Respiratory rate 20 m3/day
• Body weight 70 kg
• Absorption rate 100

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Quantitative Analysis of Cancer Risk

• In Drinking water (mg/kg-day)-1 -gt ? (ug/L)-1
• -gt Unit from (kg-day/mg) to (L/ug)
• Exposure Assumption (adult only)
• Drinking water 2 L/day
• Body weight 70 kg
• Absorption rate 100

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Risk Analysis (Systematic and Cancer)

• Step 1. Dose Calculation
• Child and Adult
• Step 2. Margin of Exposure (MOE) (Threshold
  model NOAEL/LOAEL with UFs and MF)
• Children and Adults
• Step 3. Cancer risk (No child cancer model yet,
  Non-threshold model currently)
• Cancer Potency Factor (q1) dose (adult only)
• Cancer Risk (no unit) (mg/kg-day)-1
  (mg/kg-day)
• Unit Risk Concentration
• Cancer Risk (no unit) (mg/m3)-1 (mg/m3) (air)
• or (ug/L)-1 (ug/L) (drinking water)
• (General speaking, acceptable cancer risk 10-4
  10-6)
• Step 4. Size of population (estimate how many
  excess cancer cases will be caused by exposure to
  chemical in drinking water and/or air
  (life-time))
• Step 5. Fact Sheet for public (systematic and
  cancer)

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Key Variables in Exposure Assessment

• Population

Visitors/Trespassers
Current and Future Residents
Workers
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Sensitive Groups
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Key Variables in Exposure Assessment

• Location
• On-site
• Off-site

Outside
Inside
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ENHS 762 Health Risk Assessment, Dr. Bill Hartley
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Key Variables in Exposure Assessment

• Exposure Medium

Food
Air
Soil/sediments
House dust
Surface Ground Water
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Key Variables in Exposure Assessment

• Duration
• acute
• sub-chronic
• chronic
• lifetime

• Exposure Route
• oral
• inhalation
• dermal

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ENHS 762 Health Risk Assessment, Dr. Bill Hartley
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Estimation of Exposure Levels

• Direct
• Measure the actual concentration of chemical in
  the air, water or food used by an individual.
• Measure the actual amount of air, water or food
  used by the individual.
• Calculate the actual dose to the individual.

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ENHS 762 Health Risk Assessment, Dr. Bill Hartley
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Estimation of Exposure Levels

• Reconstructive
• Measure the level of the chemical, its
  metabolites, or some other chemical-specific
  change (biomarker) in the body.
• Based on Toxicokinetic models, calculate the dose
  to the individual from the level of the biomarker.

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ENHS 762 Health Risk Assessment, Dr. Bill Hartley
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Estimation of Exposure Levels

• Predictive
• Measure or calculate the concentration of
  chemical in environmental media around the
  source.
• Estimate human contact with the media.
• Estimate the resulting dose to the average person.

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ENHS 762 Health Risk Assessment, Dr. Bill Hartley
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Identify Major Uncertainty Factors in Risk
Estimates

• Assumptions variables that contribute most to
  uncertainty in risk estimates
• Site specific factors monitoring data quality,
  likelihood of exposure scenarios occurring,
  chemicals not included in risk estimates, key
  assumptions for contaminant transport fate
  models
• Toxicity values weight of evidence, adjustment
  factors, dose additivity/extrapolation, less than
  lifetime cancer risk estimates

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ENHS 762 Health Risk Assessment, Dr. Bill Hartley
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Evaluate Uncertainty Factors

• Identify data gaps default values
• Provide distributions for parameter values, where
  possible
• Statistical treatment of uncertainty possible in
  very few situations
• A qualitative evaluation of uncertainty factors
  is typical
• Describe impacts (bias) on risk estimates
  (direction order of magnitude)
• Qualify risk estimates for risk management
  decisions

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ENHS 762 Health Risk Assessment, Dr. Bill Hartley
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GIS and Risk AssessmentA Fruitful Combination

• Results from evaluations of human health risks
  associated with environmental contamination are
  traditionally presented non-spatially.
• Because of the expense associated with sampling
  and analysis, samples of environmental
  contaminants are often taken from relatively few
  spatial locations, such as test wells.
• Moreover, in many cases, the environmental
  gradient of contamination is known to be
  anisotropic due to directional forces like
  groundwater flow or wind.
• In an effort to avoid presenting misleading
  information, non-spatial tabular reporting of
  single values, such as increased incidence of
  human cancer, has become the widely-accepted
  convention for communication of human health risk
  results.

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GIS and Risk AssessmentA Fruitful Combination

• Ultimately, interpolation of contaminant data
  which are rare in space and time is necessary for
  full evaluation of human risks.
• We present an alternative spatial format for the
  communication of contamination and risk an array
  of maps which we call a 'Map Spreadsheet.' The
  Map Spreadsheet is analogous to a data
  spreadsheet, except that each cell is a spatially
  co-registered interpolated map of contaminant
  concentration.
• Columns and rows in the Map Spreadsheet could
  represent alternative ingestion pathways,
  chemical classes and/or species of contaminants,
  or years through time.
• The viewer of a Map Spreadsheet obtains a
  perspective of the combined risk from exposure to
  multiple contaminants, as well as an idea of the
  heterogeneity of contamination across space.

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The Spatial Nature of Risk

• Environmental risk professionals typically report
  risk as single values or tables of values. Often,
  separate numbers are calculated and reported for
  different pathways, each of which are considered
  independently.
• Yet it is clear that risk assessments have an
  important spatial component. Risk evaluations are
  generated by reference to specific environmental
  data collected from specific locations.
• We argue that the presentation of risk benefits
  greatly from a spatial approach, and that the
  marriage of GIS and risk analysis is a sensible
  one. Although difficulties and problems certainly
  exist in the spatial analysis of risk, we suggest
  that it is a better - and more conservative -
  strategy to openly present these details and
  assumptions spatially rather than allowing them
  to remain implicit. Risk professionals will not
  mislead by presenting maps - they mislead by not
  presenting maps.

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Maps with Icons

• This series of maps shows the spatial
  relationships bewteen chemical concentrations in
  a series of test wells and a manufacturing
  facility, a series of buried pipelines, and a
  group of holding ponds. Concentration data are
  presented spatially for 1,1-dichloroethene,
  trichloroethene, and vinyl chloride in this
  K-1420 industrial area. Although we chose to plot
  each contaminant on separate maps, the icons
  could have been combined on a single map, and
  differentiated by the shape of the icons used.
• Only slightly more sophisticated is the plotting
  not of simple contaminant concentrations, but of
  risk due to the contamination at that
  concentration. In this map of total human health
  risk due to vinyl chloride contamination, human
  risk values calculated for the water ingestion
  pathway are mapped directly. Mapped units are in
  terms of likelihood of excess'' human cancers.

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Map and Chart Hybrids

• The combination of charts with maps allows for
  the inclusion of additional information regarding
  contaminants. The simple maps above presented a
  static snapshot of contamination no information
  was included about the way that contaminant
  concentrations changed through time (figure
  left).
• All maps to this point have shown total
  contamination or risk. By plotting size-dependent
  pie diagrams at sampled locations, we can
  communicate not only the total but the proportion
  of total contamination or risk contributed by
  each of several contaminants. This map of the
  X-10 area shows proportional human health risk by
  all pathways posed by test well concentrations.
  The size of each pie reflects total relative
  human health risk in terms of increased incidence
  of human cancer, while the color and proportion
  of each pie slice indicate each contaminants'
  contributions. The locations of each data point
  are maintained, so that the spatial distribution
  of the test wells and their proximity to
  prominent features is obvious. (figure right)

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GIS and Risk AssessmentA Fruitful Combination (
CONCLUSIONS )

• It is clearly not sufficient to report risk
  non-spatially. Risk is an inherently spatial
  phenomenon. A risk map should be considered the
  ultimate product of any risk investigation, and
  should be the first resource sought for any risk
  decision or evaluation. GIS techniques can be
  central to these important and critical processes
  of risk identification, quantification, and
  evaluation.

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Case Study I An investigation of the association
between traffic exposure and thediagnosis of
asthma in children

• Gordian ME, Haneuse S, Wakefield J.
• J Expo Sci Environ Epidemiol. 2006
  Jan16(1)49-55.
• ??????? ??
• ??????

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Introduction

• Several studies have indicated that children who
  live near traffic have greater symptoms and
  increased hospitalizations for asthma (Edwards et
  al., 1994, Brauer et al., 2002).
• The severity of asthma symptoms is also
  associated with ambient benzene concentrations
  (Thompson et al., 2001 Delfino et al., 2003).

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Objective

• This paper reports the results of a study that
  investigated the association between a
  traffic-density related measure of exposure and
  the prevalence of diagnosed asthma among school
  children5 to 7 years of age in Anchorage, Alaska
  (an area with high ambient benzene
  concentrations), adjusting for gender, parental
  asthma, a smoker in the home, and family income.

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Exposure Assessment

• Traffic counts on roadways were obtained from the
  Alaska Department of Transportation and the city
  Planning Office.
• We used the GIS to map the coordinates of the
  nearest cross streets to each childs home.
• We calculated a traffic exposure variable by
  drawing a 100-m buffer zone around each
  intersection of interest.

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Materials Methods

• All the road segments that fell within the 100-m
  buffer were multiplied by the traffic count of
  that road at that point and then summed to create
  a measure of traffic exposure.
• A total of 1106 surveys were received. The
  overall return rate by school for surveys was
  75, with a range of 5492 across schools.

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Statistical Analysis

• We used logistic regression to model the lifetime
  probability of being diagnosed with asthma, as a
  function of the traffic count in vehicle-meters
  (vm), and additional confounder and precision
  variables that were known to be associated with
  diagnosis of asthma.

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Conclusion

• We have evidence of a weak association between
  asthma prevalence in children 57 years of age
  exposed to traffic in an area where the primary
  air pollutants are VOCs and coarse fraction
  particulate matter(2.5µm lt PM lt 10µm).
• Children without genetic predisposition to asthma
  appear to be most at risk.
• More epidemiological studies are needed regarding
  the effects of traffic pollutants, especially
  VOCs.

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Case Study II Cancer Risk Near a Polluted River
in Finland

• Verkasalo PK, Kokki E, Pukkala E, Vartiainen T,
  Kiviranta H, Penttinen A, Pekkanen J.
• Environ Health Perspect. 2004112(9)1026-31.
• ??????? ??
• ??????

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PCDD/Fs

• The surface sediment levels of PCDD/Fs are
  between 0.5 and 350 ng/g in dry weight as toxic
  equivalents and thus are among the highest
  sediment levels observed worldwide.
• The most toxic congener, 2,3,7,8-tetrachlorodibenz
  o-p-dioxin (2,3,7,8-TCDD), has also been
  classified by the International Agency for
  Research on Cancer (IARC) as carcinogenic to
  humans in 1997.
• Overall, the strongest epidemiologic evidence for
  the carcinogenicity of 2,3,7,8-TCDD is for all
  cancers combined rather than for any specific
  site.

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• In this study we investigated cancer risk in
  people living near the River Kymijoki (lt 20.0
  km).
• We assumed that PCDD/Fs are mobilized from the
  river surface sediments and reach nearby
  residents via the food chain (e.g., by
  consumption of locally caught fish).
• We hypothesized that cancer risk increases with
  decreasing distance to the river. Furthermore, we
  hypothesized that farmers show a higher risk than
  most other people.

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Materials and Methods Small-Area Statistics on
Health System

• The SMASH system has previously been used to
  investigate cancer risk near geographically
  defined exposure sources in Finland.
• Data include population counts by age, sex,
  socioeconomic status (SES), and location
  coordinate of residence for 1980 and all cancer
  cases from 1981 to 2000.
• The original data sets were linked using personal
  identification numbers unique to every resident
  in Finland. The data were available in 500 m
  500 m grid squares and were further aggregated
  according to our hypothesis on geographic
  reference to the river.

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Small-Area Statistics on Health System

• A total of 27 cancers were selected to be
  studied. They were classified traditionally
  according to the ICD-7(WHO1995).
• Basal cell carcinomas (BCCs) of the skin were not
  included in the total numbers because there are
  large variations in the BCC rates by hospital
  catchment area, suggesting that many cases may
  remain undetected.

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Exposure Assessment

• The study population was defined as all people
  (farmers in particular) living within 20.0 km
  from the River Kymijoki (i.e., in a 500 m 500 m
  grid square at least partially located within
  20.0 km from the river shoreline) on 31 December
  1980.
• The study area was divided into nine subareas
  according to increasing distance to the river
  downstream from the factory producing Ky-5 (lt 1.0
  km 1.04.9 km 5.019.9 km), and according to
  increasing distance to the sea (lt 20.0 km
  20.039.9 km 40.059.9 km) (Figure 1).

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Statistical Analyses

• We estimated reference incidence rates separately
  for total Finnish population and Finnish farmers,
  dividing the number of new cases of cancer by the
  population at risk in 1980, by sex, age, time
  period, and SES (in analyses of all people but
  not farmers).
• For the study area, we calculated expected
  numbers of cancers as the number of subjects
  multiplied by reference incidence rate for that
  cancer by sex, age, time period, SES, distance to
  sea, and distance to river.

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Statistical Analyses

• For distance to river comparisons, we used
  Poisson regression main-effect models for the
  observed numbers of cases in 3 3 contingency
  tables, where the classification is based on
  distance to river (three categories) and distance
  to sea (three categories).

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Conclusions

• This study cannot exclude the possibility that
  residence near the River Kymijoki may have
  contributed to a subtle increase in the risk of
  total cancer, especially among farmers.
• This study can provide only first approximations
  of risks and tell only a little about causality.

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Case Study III ??GIS???????

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• -??????????

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??GIS???????

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  ??????????,?????????????????,????????????????

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??GIS???????

• ???????????????DEP(Department of Environmental
  Protection)?the Department of Health(DOH)?the
  Department of Agriculture(PDA)??????????????????,?
  ????????????????(database)?,??????????????????WN
  ????????????????,?????????????????DEP
  ????????????????????????,?????????????????

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??GIS???????

• ???????????????????????,???ESRI
  ????????????????????????????????????????????????(C
  ampag)??????(handhelds)???????(Global Positioning
  System)?ESRI ???????(information
  mappingsoftware)ArcPad,??????????????????(Web)???,
  ???????????????????????????????????

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??GIS???????
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??GIS???????

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  ???????,???????????????????????

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??GIS???????