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Assessing the timing and the duration of exposure to air pollution on cardiometabolic biomarkers in patients suspected of coronary artery disease

  • Kexin Zhu
  • , Zhihui Hou
  • , Conghong Huang
  • , Muwu Xu
  • , Lina Mu
  • , Guan Yu
  • , Joel D. Kaufman
  • , Meng Wang
  • , Bin Lu
  • SUNY Buffalo
  • Chinese Academy of Medical Sciences
  • Nanjing Agricultural University
  • University of Pittsburgh
  • University of Washington

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Air pollution can affect cardiometabolic biomarkers in susceptible populations, but the most important exposure window (lag days) and exposure duration (length of averaging period) are not well understood. We investigated air pollution exposure across different time intervals on ten cardiometabolic biomarkers in 1550 patients suspected of coronary artery disease. Daily residential PM2.5 and NO2 were estimated using satellite-based spatiotemporal models and assigned to participants for up to one year before the blood collection. Distributed lag models and generalized linear models were used to examine the single-day-effects by variable lags and cumulative effects of exposures averaged over different periods before the blood draw. In single-day-effect models, PM2.5 was associated with lower apolipoprotein A (ApoA) in the first 22 lag days with the effect peaking on the first lag day; PM2.5 was also associated with elevated high-sensitivity C-reactive protein (hs-CRP) with significant exposure windows observed after the first 5 lag days. For the cumulative effects, short- and medium-term exposure was associated with lower ApoA (up to 30wk-average) and higher hs-CRP (up to 8wk-average), triglycerides and glucose (up to 6 d-average), but the associations were attenuated to null over the long term. The impacts of air pollution on inflammation, lipid, and glucose metabolism differ by the exposure timing and durations, which can inform our understanding of the cascade of underlying mechanisms among susceptible patients.

Original languageEnglish
Article number116334
JournalEnvironmental Research
Volume232
DOIs
StatePublished - Sep 1 2023

Keywords

  • Air pollution
  • Cardiometabolic biomarkers
  • Distributed lag models
  • Exposure duration

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