P3420Is there an association between Saharan dust events and acute coronary syndrome incidence?

Abstract Background Asian dust and air pollution have been recently recognized as triggers in the incidence of acute myocardial infarction. The inflow of dust from the Sahara into Spain causes an increase in particulate matter (PM) levels in the atmosphere. The proximity to the Western Coast of Morocco and the Sahara Desert promotes the seasonality arrival of natural PM on the Canary Islands (Spain), leading to high concentrations of PM with an aerodynamic diameter over 10μm (PM10). The association of dust transport from the Sahara to the Atlantic Ocean and Mediterranean areas over the incidence of acute coronary syndromes (ACS), is unknown. Purpose The aim of the present study was to elucidate whether Saharan dust events in the dust belt - Canary Islands - is associated with the incidence of ACS. Methods We retrospectively collected data of hospitalizations due to ACS in 2416 consecutive patients from a tertiary care hospital in Tenerife (Canary Islands–Spain), from December 2012 to December 2017. Taking advantage of Canary Islands location, we characterized the Saharan dust events using PMx measurements and dust modeling. Concentrations of PM10 and reactive gases are measured in the Air Quality Network of the Canary Islands by using the European reference method. We applied the time-stratified case crossover design to examine the association between Saharan dust events and the incidence of ACS. This design allows us to adjust for individual confounders, season, time trend and the day of week. Using conditional Poisson regression models, we estimated the impact of PM10 Saharan dust events on the incidence of ACS. Because the effects of Saharan dust events could persist over the course of a few days, we examined the lag effect from Day 0 to Day 5. Results The occurrence of Saharan dust events observed 0–5 days before the ACS was not significantly associated with the incidence of ACS. PM10 (μg/m3) effect was: lag 0 (IRR: 0.999, 95% CI: 0.977–1.022), lag 1 (IRR: 1.025, 95% CI: 0.988–1.063), lag 2 (IRR: 0.98, 95% CI: 0.928–1.042), lag 3 (IRR: 0.976, 95% CI: 0.944–1.011), lag 4 (IRR: 0.996, 95% CI: 0.983–1.008) and lag 5 (IRR: 0.996, 95% CI: 0.984–1.007). (Figure 1) Poisson regression model of PM10 Conclusions This negative study, the first to assess the impact of Saharan dust events as a potential trigger in the onset of ACS, shows that African dust is unlikely to be associated with the incidence of ACS.