Using Distributed Lag Non-Linear Models to Estimate Exposure Lag-Response Associations between Long-Term Air Pollution Exposure and Incidence of Cardiovascular Disease.
Hedi Katre KriitEva M AnderssonHanne Krage CarlsenNiklas AnderssonPetter L S LjungmanGöran PershagenDavid SegerssonKristina EnerothLars GidhagenMårten SpannePeter MolnàrPatrik WennbergAnnika RosengrenDebora RizzutoKarin LeanderDiego Yacamán-MéndezPatrik K E MagnussonBertil ForsbergLeo StockfeltJohan Nilsson SommarPublished in: International journal of environmental research and public health (2022)
Long-term air pollution exposure increases the risk for cardiovascular disease, but little is known about the temporal relationships between exposure and health outcomes. This study aims to estimate the exposure-lag response between air pollution exposure and risk for ischemic heart disease (IHD) and stroke incidence by applying distributed lag non-linear models (DLNMs). Annual mean concentrations of particles with aerodynamic diameter less than 2.5 µm (PM 2.5 ) and black carbon (BC) were estimated for participants in five Swedish cohorts using dispersion models. Simultaneous estimates of exposure lags 1-10 years using DLNMs were compared with separate year specific (single lag) estimates and estimates for lag 1-5- and 6-10-years using moving average exposure. The DLNM estimated no exposure lag-response between PM 2.5 total, BC, and IHD. However, for PM 2.5 from local sources, a 20% risk increase per 1 µg/m 3 for 1-year lag was estimated. A risk increase for stroke was suggested in relation to lags 2-4-year PM 2.5 and BC, and also lags 8-9-years BC. No associations were shown in single lag models. Increased risk estimates for stroke in relation to lag 1-5- and 6-10-years BC moving averages were observed. Estimates generally supported a greater contribution to increased risk from exposure windows closer in time to incident IHD and incident stroke.