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Exposure, Disease and Risk.

Exposure, Disease and Risk. Presentation of some case studies using geographical information systems (GIS) Occupational and Environmental Medicin & GIS Centre at Lund University. Common aim for all cases. Estimate human exposure to possibly harmful environmental factors.

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Exposure, Disease and Risk.

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  1. Karin Larsson

  2. Exposure, Disease and Risk. Presentation of some case studies using geographical information systems (GIS) Occupational and Environmental Medicin &GIS CentreatLund University

  3. 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.

  4. 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.

  5. 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

  6. 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).

  7. Dispersion model Concentration NO2 Population and concentration Exposure Location of population on residential coordinate

  8. 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 Data requirement

  9. Exposure differences inside and outside cities (>15 000 people) Towns: 543 500 Countryside: 591 500

  10. 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.

  11. 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 km2municipality: appr. 1 700 km2 Population: town: appr. 50 000municipality: appr. 74 000

  12. 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).

  13. 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.

  14. 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

  15. 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).

  16. 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 Data requirement

  17. Noise: 40 dBA from different transport sources Estimated risk areas for ground radon occurance based on rocks and soils

  18. 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).

  19. 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.

  20. ”Case” 4: Rapid Inquiry Facility (RIF) in Scania

  21. 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.

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