Background: The LIFE MED HISS project aims at setting up a surveillance system on the long term effects of air pollution on health, using data from National Health Interview Surveys and other currently available sources of information in most European countries. Few studies assessed the long term effect of air pollution on hospital admissions in European cohorts.
Objective: The objective of this paper is to estimate the long term effect of fine particulate matter (PM2.5) and nitrogen dioxide (NO) on first-ever (incident) cause-specific hospitalizations in Italy.
Methods: We used data from the Italian Longitudinal Study (ILS), a cohort study based on the 1999-2000 National Health Interview Survey (NHIS), followed up for hospitalization (2001-2008) at individual level. The survey contains information on crucial potential confounders: occupational/educational/marital status, body mass index (BMI), smoking habit and physical activity. Annual mean exposure to PM2.5 and NO was assigned starting from simulated gridded data at spatial resolution of 4 × 4 km firstly integrated with data from monitoring stations and then up-scaled at municipality level. Statistical analyses were conducted using Cox proportional hazard models with robust variance estimator.
Results: For each cause of hospitalization we estimated the hazard ratios (HRs) adjusted for confounders with 95% Confidence Interval (CI) related to a 10 μg/m increase in pollutants. For PM2.5 and NO, respectively, we found positive associations for circulatory system diseases [1.05(1.03-1.06); 1.05(1.03-1.07)], myocardial infarction [1.15(1.12-1.18); 1.15(1.12-1.18)], lung cancer [1.18(1.10-1.26); 1.20(1.12-1.28)], kidney cancer [1.24(1.11-1.29); 1.20(1.07-1.33)], all cancers (but lung) [1.06(1.04-1.08); 1.06(1.04-1.08)] and Low Respiratory Tract Infections (LRTI) [1.07 (1.04-1.11); 1.05 (1.02-1.08)].
Discussion: Our results add new evidence on the effects of air pollution on first-ever (incident) hospitalizations, both in urban and rural areas. We demonstrated the feasibility of a low-cost monitoring system based on available data.
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