exposure, disease and risk

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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 Centre at Lund University. Common aim for all cases. Estimate human exposure to possibly harmful environmental factors. - PowerPoint PPT Presentation

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Page 1: Exposure, Disease and Risk

Karin Larsson

Page 2: Exposure, Disease and Risk

Exposure, Disease and Risk.

Presentation of some case studies using geographical information systems (GIS)

Occupational and Environmental Medicin &

GIS Centreat

Lund University

Page 3: Exposure, Disease and Risk

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.

Page 4: Exposure, Disease and Risk

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.

Page 5: Exposure, Disease and Risk

Case 1: Developing a methodology for risk assessment of exposure to air pollution.

Study areaScania in Southern SwedenAreal extent: appr. 10 000 km2

Population: appr. 1.1 milj

Page 6: Exposure, Disease and Risk

• 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).

Page 7: Exposure, Disease and Risk

Dispersion model

Concentration NO2

Location of population on residential coordinate

Population and concentration

Exposure

Page 8: Exposure, Disease and Risk

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

Page 9: Exposure, Disease and Risk

Exposure differences inside and outside cities (>15 000 people)

Towns: 543 500

Countryside: 591 500

Page 10: Exposure, Disease and Risk

• 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.

Page 11: Exposure, Disease and Risk
Page 12: Exposure, Disease and Risk

Case 2: Association between air pollution and self reported airway nuisance

Study areaVäxjö town and municipality in South

SwedenAreal extent:

town: appr. 28 km2

municipality: appr. 1 700 km2

Population: town: appr. 50 000municipality: appr. 74 000

Page 13: Exposure, Disease and Risk

• 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).

Page 14: Exposure, Disease and Risk
Page 15: Exposure, Disease and Risk

• 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.

Page 16: Exposure, Disease and Risk
Page 17: Exposure, Disease and Risk

Case 3: Development of a methodology for estimation of health effects associated with exposure to radon, NO2 and noise

Study areaScania in Southern SwedenAreal extent: appr. 10 000 km2

Population: appr. 1.1 milj

Page 18: Exposure, Disease and Risk

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).

Page 19: Exposure, Disease and Risk

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

Page 20: Exposure, Disease and Risk

Noise: 40 dBA from different transport sources

Estimated risk areas for ground radon occurance based on rocks and soils

Page 21: Exposure, Disease and Risk

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).

Page 22: Exposure, Disease and Risk

• 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.

Page 23: Exposure, Disease and Risk

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

Page 24: Exposure, Disease and Risk

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.