You are here

Health effects of air pollution components, noise and socioeconomic status (“HERMES”)

Principal Investigator: 
,

Danish Cancer Society Research Center, Copenhagen, Denmark

This study will assess myocardial infarction, stroke, diabetes, and biomarkers related to cardiovascular disease and diabetes in three large Danish cohorts.  The investigators will estimate exposure to several pollutants and transportation noise and evaluate the roles of socioeconomic status, green space, physical activity, diet, and stress.

Funded under
Status: 
Ongoing
Abstract

Exposure to Air Pollution and Risk for Cardiometabolic Disease: Effects of Register-Based and Questionnaire-Based Adjustment

Ole Raaschou-Nielsen1,4, Mette Sørensen1,2, Ulla Arthur Hvidtfeldt1, Aslak Harbo Poulsen1, Lau Caspar Thygesen3, Lise M. Frohn4, Matthias Ketzel4,5, Jesper H. Christensen4, Jørgen Brandt4, Jibran Khan4

1Danish Cancer Society Research Center, Copenhagen, Denmark; 2Roskilde University, Roskilde, Denmark; 3University of Southern Denmark, Copenhagen, Denmark; 4Aarhus University, Roskilde, Denmark; 5University of Surrey, Guildford, U.K.

Background. Recent studies on air pollution and disease have been based on millions of participants within a region or country, relying entirely on register-based confounder adjustment. We aimed to investigate the effects of increasing adjustment for register- and questionnaire-based covariates on the association between air pollution and cardiometabolic diseases.

Methods. In a population-based cohort of 217,213 eligible participants randomly selected across Denmark in 2010 and 2013, we identified 2,516 myocardial infarction (MI) cases, 3,034 stroke cases and 5,165 type 2 diabetes cases. Based on historical address-information, we calculated 5-year time-weighted exposure to PM2.5 and NO2 modeled with a validated air pollution model. We used Cox proportional hazards models to calculate hazard ratios (HR) with increasing adjustment for a number of individual- and area-level register-based covariates as well as lifestyle covariates assessed through questionnaires.

Results. We found that a 5 µg/m3 higher PM2.5 was associated with HRs (95% CI) for MI, stroke and diabetes of, respectively, 1.47 (1.10–1.95), 1.36 (1.05–1.77) and 1.28 (1.05–1.57) in the fully adjusted models. For MI and diabetes, adjustment for either individual-level, area-level or lifestyle covariates, or combinations of these resulted in marked increases in HRs, whereas for stroke, adjustment only changed HRs slightly. Further adjustment for lifestyle, in models with full register-based individual- and area-level adjustment, resulted in only minor changes in HRs for all three diseases. 

Conclusions. Our findings suggest that studies on air pollution and cardiometabolic disease based on administrative cohorts without lifestyle information can produce reliable results if a broad register-based adjustment strategy is applied.