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Karin Larsson
Exposure, Disease and Risk.
Presentation of some case studies using geographical information systems (GIS)
Occupational and Environmental Medicin &
GIS Centreat
Lund University
Common aim for all cases
• Estimate human exposure to possibly harmful environmental factors.
• Investigate relationships between exposure and health effects.
• Improve risk assessment for health effects caused by environmental factors.
Methodology• Model the spatial and temporal variation of
possibly harmful environmental factors.
• Integrate these model results with population data to estimate exposure.
• Link exposure to data on health to evaluate these relationships.
• Employ different methods for sampling of environmental and health data.
• Employ different statistical methods for evaluating relationships and risk.
Case 1: Developing a methodology for risk assessment of exposure to air pollution.
Study area
Scania in Southern Sweden
Areal extent: appr. 10 000 km2
Population: appr. 1.1 milj
• Emission database is built for the region.
• Meteorological dispersion models are used to estimate concentration of air pollutants (particles and NO2) in time and space.
• GIS is used to link concentrations to the population’s residential coordinates, i.e. static population (step 1).
• GIS is used to link concentrations to the population’s location in time and space, i.e. dynamic population (step 2).
Dispersion model
Concentration NO2
Location of population on residential coordinate
Population and concentration
Exposure
Data requirement• NO2 and particles:
– Traffic information
– Industrial activities
– Energy production, heating
• Specific particle sources:– Emissions generated by wind
• agricultural land• ocean
– Traffic• whirls of dust around roads
caused by cars
– Diffuse industrial sources• industries• agriculture activities
• Meteorological parameters
Exposure differences inside and outside cities (>15 000 people)
Towns: 543 500
Countryside: 591 500
• Exposure estimates will be connected with records on ICD-10 diagnoses of airway diseases registered in indoor- and outdoor patient care.
• Exposure levels for symptomatic patients may be compared to other groups.
• Structured selection of cases and referents for case-referent studies is facilitated.
Case 2: Association between air pollution and self reported airway nuisance
Study area
Växjö town and municipality in South Sweden
Areal extent: town: appr. 28 km2
municipality: appr. 1 700 km2
Population: town: appr. 50 000municipality: appr. 74 000
• Meteorological dispersion models are used to estimate concentration of air pollutants (particles and NO2) in time and space.
• Intensive campain for detailed mesurements of air pollution is performed during 3 months.
• GIS is used to link concentrations to a static population (step 1).
• GIS is used to link concentrations to a dynamic population (step 2).
• Diaries and questionnaries are filled out by 120 randomly selected persons to report nuisance from airways during the campaign period.
• Statistical analyses for estimation of association between air pollution and nuisance.
Case 3: Development of a methodology for estimation of health effects associated with exposure to radon, NO2 and noise
Study area
Scania in Southern Sweden
Areal extent: appr. 10 000 km2
Population: appr. 1.1 milj
Estimate exposure by using GIS.
• Emission data inventory and collection: radon and noice.
• Use of dispersion models: air pollutants and noise.
• Use of maps and measurement data: ground emitted radon.
• Link concentrations to a static population (step 1).
• Link concentrations to a dynamic population (step 2).
Data requirement
• Noise:
– Traffic information
– Industrial activities
– Shooting ranges
– Motor sport facilities
• Radon:
– Ground radon inventories
– Ground radon measurements
– Indoor radon measurements• relevant building
characteristics
• Topography
• Ground conditions (soft/hard)
• Noise protection measures
Noise: 40 dBA from different transport sources
Estimated risk areas for ground radon occurance based on rocks and soils
Estimation of health effects
• Using risk data from literature (Step 1).
• Perform structured case-referent studies on diseases related to: noise – increased blood pressureradon – lung cancerparticles and nitrogen dioxide – airway diseases(Step 2).
• Evaluate trends of exposure and health effects by making calculations for different years.
• Use the methodology for estimating effects of different scenarios for planning purposes.
• Develop a methodology to be used by the County Council for monitoring and taking measures to reach environmental objectives concerning health.
”Case” 4: Rapid Inquiry Facility (RIF) in Scania
In who’s interest?
• Governmental agencies at all levels for planning, monitoring and follow up of health status and effects.
• Energy agencies.• Environmental protection agencies.• EU.• Research community. • Companies.