Air pollution and kidney function using electronic health records

These data include electronic health records of a random sample of patients at the University of North Carolina healthcare system. In addition, we linked these data to results of hybrid air pollution models generated by a team at Harvard University. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: Enquiries regarding access to electronic health records data can be submitted at https://tracs.unc.edu/. Format: These data include electronic medical records, which include sensitive information that cannot be released. In addition, we included results of propietary air pollution models generated by our colleagues at Harvard University. This dataset is associated with the following publication: Dillon, D., C. Ward-Caviness, A. Kshirsagar, J. Moyer, J. Schwartz, Q. Di, and A. Weaver. Associations between long-term exposure to air pollution and kidney function utilizing electronic healthcare records: a cross-sectional study. ENVIRONMENTAL HEALTH. Academic Press Incorporated, Orlando, FL, USA, 23(43): 1322, (2024).

[
  "020:00"
]

{
  "fn": "Anne Weaver",
  "hasEmail": "mailto:weaver.anne@epa.gov"
}

[]

[
  "Ozone",
  "air pollution",
  "chronic kidney disease",
  "nitrogen dioxide",
  "particulate matter (PM)"
]

[
  "020:000"
]

{
  "name": "U.S. EPA Office of Research and Development (ORD)",
  "subOrganizationOf": {
    "name": "U.S. Environmental Protection Agency",
    "subOrganizationOf": {
      "name": "U.S. Government"
    }
  }
}

[
  "https://doi.org/10.1186/s12940-024-01080-4",
  "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11036746"
]