Lombardy, the most populated and industrialized Italian region, was the epicentre of the first wave (March and April 2020) of COVID-19 in Italy and it is among the most air polluted areas of Europe. We carried out an ecological study to assess the association between long-term exposure to particulate matter (PM) and nitrogen dioxide (NO2) on COVID-19 incidence and all-cause mortality after accounting for demographic, socioeconomic and meteorological variables. The study was based on publicly available data. Multivariable negative binomial mixed regression models were fitted, and results were reported in terms of incidence rate ratios (IRRs) and standardized mortality ratios (SMR). The effect of winter temperature and humidity was modelled through restricted cubic spline. Data from 1439 municipalities out of 1507 (95%) were included in the analyses, leading to a total of 61,377 COVID-19 cases and 40,401 deaths from all-causes collected from February 20th to April 16th and from March 1st to April 30th, 2020, respectively. Several demographic and socioeconomic variables resulted significantly associated with COVID-19 incidence and all-cause mortality in a multivariable fashion. An increase in average winter temperature was associated with a nonlinear decrease in COVID-19 incidence and all-cause mortality, while an opposite trend emerged for the absolute humidity. An increase of 10 μg/m3 in the mean annual concentrations of PM2.5 and PM10 over the previous years was associated with a 58% and 34% increase in COVID-19 incidence rate, respectively. Similarly, a 10 μg/m3 increase of annual mean PM2.5 concentration was associated with a 23% increase in all-cause mortality. An inverse association was found between NO2 levels and COVID-19 incidence and all-cause mortality. Our ecological study showed that exposure to PM was significantly associated with the COVID-19 incidence and excess mortality during the first wave of the outbreak in Lombardy, Italy.
Keywords: COVID-19; Ecological study; Excess mortality; Incidence; Risk factors.
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