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Population cohort study to evaluate the health effects of environmental and occupational exposures in industrial sites Francesca Mataloni Roma 15/10/2012
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Epidemiological studies in industrial areas and contaminated sites Multiple sources and exposure to multiple substances Different pathways: soil, water, air, food Variable time of contamination Size of exposed group Socioeconomic status and environmental justice Occupational exposures Difficulties in data collection Environmental worries and media attention
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Study design in environmental epidemiology Long-term effects –Ecological studies (municipalities, small area statistics) –Cross-sectional (biomonitoring) –Cohort studies –Case-controls Short-term effects –Time series or case-crossover –Panel studies
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Study design - Environment and Health t1t1 Study area definition Municipality data Geocoding procedure Dispersion model (footprint) Follow-up Population cohort Epidemiological evaluation Exposure-response relationship Pollution source Socioeconomic level t0t0 MeteorologyOther pollution sources Orography Environmental monitoring Occupational history
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Case study: Taranto Taranto Ilva steel plant Background Vigotti (2007) Graziano (2009) Marinaccio (2011) MISA SISTI EPIAIR SENTIERI
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Air quality in Taranto European Pollutant Release and Transfer Register
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Study area and objective cohort study design to evaluate the relationship between PM10 from industry and mortality and hospitalization Court investigation report delivered on March 2012
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Methods Cohort of residents in Taranto, Massafra and Statte (1998-2010) Mortality (1998-2008) and hospitalization (1998-2010) PM 10 concentration from industry Municipality data Regional Health database v Lagrangian particle model (2004)
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Methods Occupational history amount of contributions paid; length of working period; worker task (blue-collar or white-collar workers); company where the activity was performed. INPS (National Social Insurance Agency) Since 1974
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1 st model: exposure= PM 10 industrial origin (10µg/m 3 ) Statistical analysis Outcomes: cause-specific mortality and hospitalization 2 nd model: exposure= Occupation (workers in steel, naval confounders= age, calendar period, SES, occupation Hazard Ratio Cox proportional model and mechanical construction factories vs others). confounders= age, calendar period, SES
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Geocoding of the cohort
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PM 10 from dispersion model
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Socioeconomic level % population with educational level <= primary school, % active population unemployed or looking for their first job, % rented houses, % single parent families, population density.
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Results Cohort
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Results PM 10 industrial origin (10µg/m 3 )
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Results occupation (mortality)
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Results occupation (hospitalization)
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Conclusions Being exposed to PM 10 and working in steel factories were associated with increased mortality/morbidity levels
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Points for further discussion (1/2) Other study design except for cohort approach? Quality of dispersion modelling vs other exposure assessment? Other individual confounders Reporting and communication when the media alarm is so high
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Points for further discussion (2/2) Reporting and communication when the media alarm is so high
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