Karin Larsson. Exposure, Disease and Risk. Presentation of some case studies using geographical...
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![Page 1: Karin Larsson. Exposure, Disease and Risk. Presentation of some case studies using geographical information systems (GIS) Occupational and Environmental.](https://reader034.fdocuments.in/reader034/viewer/2022051210/5517ead1550346c6568b490e/html5/thumbnails/1.jpg)
Karin Larsson
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Exposure, Disease and Risk.
Presentation of some case studies using geographical information systems (GIS)
Occupational and Environmental Medicin &
GIS Centreat
Lund University
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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.
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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.
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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
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• 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).
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Dispersion model
Concentration NO2
Location of population on residential coordinate
Population and concentration
Exposure
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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
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Exposure differences inside and outside cities (>15 000 people)
Towns: 543 500
Countryside: 591 500
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• 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.
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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
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• 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).
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• 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.
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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
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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).
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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
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Noise: 40 dBA from different transport sources
Estimated risk areas for ground radon occurance based on rocks and soils
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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).
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• 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.
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”Case” 4: Rapid Inquiry Facility (RIF) in Scania
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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.