4.7 Article

The effect of adjustment to register-based and questionnaire-based covariates on the association between air pollution and cardiometabolic disease

Journal

ENVIRONMENTAL RESEARCH
Volume 203, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.envres.2021.111886

Keywords

Air pollution; Cardiometabolic disease; Cohort study; Confounders

Funding

  1. United States Environmental Protection Agency (EPA) [R-82811201]

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The study investigates the impact of increasing adjustment for register-and questionnaire-based covariates on the association between air pollution and cardiometabolic diseases. Results show a significant association between air pollution and myocardial infarction, stroke, and type 2 diabetes, with little impact on risk estimates from subsequent lifestyle adjustment after adjusting for socioeconomic variables.
Objective: 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 246,766 eligible participants randomly selected across Denmark in 2010 and 2013 and followed up until December 31, 2017, we identified 3,247 myocardial infarction (MI) cases, 4,166 stroke cases and 6,366 type 2 diabetes cases. Based on historical address-information, we calculated 5-year time-weighted exposure to PM2.5 and NO2 modelled using a validated air pollution model. We used Cox pro-portional 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 mu g/m(3) higher PM2.5 was associated with HRs (95% CI) for MI, stroke and diabetes, of respectively, 1.18 (0.91-1.52), 1.11 (0.88-1.40) and 1.24 (1.03-1.50) in the fully adjusted models. For all three diseases, adjustment for either individual-level, area-level or lifestyle covariates, or combinations of these resulted in higher HRs compared to HRs adjusted only for age, sex and calendar-year, most marked for MI and diabetes. 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 in studies of air pollution and cardiometabolic disease, which use an adjustment strategy with a broad range of register-based socioeconomic variables, there is no effect on risk estimates from subsequent lifestyle adjustment.

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