Population cohort study to evaluate the health effects of environmental and occupational exposures in industrial sites Francesca Mataloni Roma 15/10/2012

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

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

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

Case study: Taranto Taranto Ilva steel plant Background Vigotti (2007) Graziano (2009) Marinaccio (2011) MISA SISTI EPIAIR SENTIERI

Air quality in Taranto European Pollutant Release and Transfer Register

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

Methods Cohort of residents in Taranto, Massafra and Statte ( ) Mortality ( ) and hospitalization ( ) PM 10 concentration from industry Municipality data Regional Health database v Lagrangian particle model (2004)

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

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

Geocoding of the cohort

PM 10 from dispersion model

Socioeconomic level % population with educational level <= primary school, % active population unemployed or looking for their first job, % rented houses, % single parent families, population density.

Results Cohort

Results PM 10 industrial origin (10µg/m 3 )

Results occupation (mortality)

Results occupation (hospitalization)

Conclusions Being exposed to PM 10 and working in steel factories were associated with increased mortality/morbidity levels

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

Points for further discussion (2/2) Reporting and communication when the media alarm is so high