Long-term exposure to air pollutants is recognized as a risk factor for cardiovascular disease (CVD); exposure to ambient fine particulates (PM2.5) is considered among the top ten global risk factors for premature death and morbidity primarily due to CVD effects. Public health action on a national and global level still requires better information on the nature of the association between pollutants and CVD: Is there a threshold for exposure, below which effects do not occur? Is the effect linear or does it follow a more biologically likely function? This proposal addresses these critical questions with two approaches: 1) pooling high-quality cohort studies; and 2) analyzing health system records based on electronic health records (EHR). The former approach is the epidemiological standard while the latter represents the ?big data? future. The combination and comparison of these two approaches in the same research program affords a unique opportunity to address another key public health question: Can ?big data? provide the same answer as traditional cohort approaches? This proposal addresses low-level air pollution health effects using state-of-the-art exposure assessment, fine- scale hybrid modeling of concentrations (PM2.5, oxides of nitrogen, and ozone) and advanced statistical methods. The cohorts permit optimal minimization of bias due to confounding and misclassification by pooling information from a set of well-established cohorts in the US totaling nearly one million participants, each with appropriate outcome, home address, and individual level covariate detail. The consortium cohorts feature geographic and exposure diversity. This project will also study one unusually well-characterized large-scale integrated health delivery system, Kaiser Permanente Northern California, with detailed EHR on more than 4.7 million members. Results of this study will provide critically important knowledge to guide policy in the United States and globally. Further, this proposal will directly compare traditional cohort and new ?big data? approaches for answering complex epidemiological research questions, allowing for better understanding of the ability of ?big data? to replace and/or supplement traditional approaches.

Public Health Relevance

Air pollution contributes to the development of heart disease, but questions remain about the nature of this relationship?especially at the lower concentrations now experienced in the United States. Better understanding will help in the development of cost-effective policies to protect public health and reduce health inequality. The proposed research will address these questions and compare the results using two sources: 1) established epidemiological cohorts and 2) electronic health records.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Research Project (R01)
Project #
5R01ES027696-02
Application #
9564119
Study Section
Cancer, Heart, and Sleep Epidemiology A Study Section (CHSA)
Program Officer
Joubert, Bonnie
Project Start
2017-09-15
Project End
2021-06-30
Budget Start
2018-07-01
Budget End
2019-06-30
Support Year
2
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Washington
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195
Hazlehurst, Marnie F; Spalt, Elizabeth W; Nicholas, Tyler P et al. (2018) Contribution of the in-vehicle microenvironment to individual ambient-source nitrogen dioxide exposure: the Multi-Ethnic Study of Atherosclerosis and Air Pollution. J Expo Sci Environ Epidemiol 28:371-380
Honda, Trenton; Eliot, Melissa N; Eaton, Charles B et al. (2017) Long-term exposure to residential ambient fine and coarse particulate matter and incident hypertension in post-menopausal women. Environ Int 105:79-85