Experimental, animal, and human studies have shown that ultrafine particles (particulate matter with diameter < 0.1 μm; UFPs) exposure caused oxidative stress, atherosclerotic plaque formation, inflammation, reduced coronary circulation, and autonomic imbalance, all associated with cardiovascular diseases (CVD). To date, sparse epidemiological evidence suggests associations of UFPs with CVD, yet no studies adjusted for road traffic noise, which shares the main source with UFPs and is a risk factor for CVD. Other gaps in knowledge include a general lack of studies on long-term exposure to UFPs and all cause-specific mortality and morbidity due to dementia, diabetes, and respiratory diseases (RD), all of which have been linked so far to long-term exposure to particulate matter ≤ 2.5 μm (PM2.5). In line with the HEI strategy on Complex Questions for the Air Pollution Mixture, the aim of the proposed research is to conduct a comprehensive study of health effects related to long-term exposure to UFPs in Copenhagen, Denmark. We hypothesize that long-term exposure to UFPs increases the risk of mortality and morbidity due to CVD, RD, including lung cancer, diabetes, and dementia, independent from other air pollutants and road traffic noise. We will define a new, population based COpenhagen Ultrafine Particles and Health (COUPH) cohort by including people who were residing in the Copenhagen area defined by the Google Air View car routes measurement campaign from 2018-2020, and who were 30 years or older in 2010. We will include the entire populations of municipalities of Copenhagen and Frederiksberg, and a part of surrounding municipalities resulting in ~650,000, who will be linked to the national registries to extract individuallevel data on income, education, employment, marital status, country of birth, and neighborhood-level (parish) mean income, % unemployment, and % with low education, incidence rates of lung cancer, chronic obstructive pulmonary disease (COPD), and diabetes, in year 2010.
Data on mortality and incidence of CVD, RD, lung cancer, diabetes, and dementia until 2020 will be extracted from nationwide health registries. The main source for exposure will be Google Air View data where exposure to UFPs, nitrogen dioxide (NO2), and black carbon (BC) will be estimated at COUPH subjects' addresses in 2010 by land-use regression (LUR) models based on measurement campaign in Greater Copenhagen area (November 2018- March 2020). Additionally, data on PM2.5 from the European-wide hybrid LUR model will be used. We will use Cox proportional hazard models with age as an underlying time to examine the associations of long-term exposure to UFPs and other pollutants with the mortality and incidence of CVD, RD, diabetes, and dementia.
In order to estimate the independent effects of UFPs, we will apply Bayesian kernel machine regression (BKMR) approach to identify the individual components of the mixture (UFPs, PM2.5, NO2, BC) responsible for health effects. We will adjust for conventional air pollutants (PM2.5, NO2, and BC) and road traffic noise. The project benefits from objective incidence definition for a number of diseases as well as detailed data on individual and neighborhood levels of socio-economic status (SES), all from uniquely available Danish national registries with high validity and 100% coverage. Given the fact that air pollution is a global modifiable risk factor of health, the findings of this research may have significant implications for global public and environmental health.