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<p>Air pollution is a significant risk factor for atrial fibrillation (AF), a condition marked by sudden and transient episodes. Accurately capturing these short-term associations requires precise exposure assessment. However, conventional methods utilizing residential addresses alone do not account for personal mobility and rapid fluctuations in pollutant levels, leading to exposure misclassification. To improve exposure precision, we developed a novel method that integrates GPS-tracked mobility data with intracardiac device monitoring to examine short-term associations between ambient air pollutants and atrial fibrillation (AF) episodes. We applied a time-stratified case-crossover design combined with distributed lag nonlinear models (DLNMs) to evaluate associations between short-term exposure to air pollutants, including particulate matter ≤ 2.5&#xa0;µm and ≤ 10&#xa0;µm in diameter (PM<sub>2.5</sub> and PM<sub>10</sub>), nitrogen dioxide (NO<sub>2</sub>), ozone (O<sub>3</sub>), and sulfur dioxide (SO<sub>2</sub>), and AF episodes. AF episodes were ascertained through intracardiac devices (pacemakers and defibrillators) equipped for continuous recording arrhythmic events. Exposure estimates derived from GPS-based mobility data were compared to those based on participants’ residential addresses. An increase by interquartile range of exposure within 1&#xa0;day before event showed higher odds ratios (ORs) for AF with GPS-based estimates, particularly for PM<sub>2.5</sub> (OR: 1.26, 95% CI: 0.81, 1.96) and NO<sub>2</sub> (OR: 1.22, 95% CI: 0.94, 1.57), compared to residential methods (PM<sub>2.5</sub> OR: 1.07, 95% CI: 0.53, 2.14; NO<sub>2</sub> OR: 1.01, 95% CI: 0.65, 1.55). Participants younger than 70&#xa0;years old demonstrated stronger associations using GPS-based methods. Similarly, higher effect estimates were observed among current smokers, while differences between exposure models were less pronounced in non-smokers. GPS-enhanced, real-time pollutant exposure demonstrates feasibility and may improve accuracy by capturing dynamic exposure patterns. The results suggest potential advantages of GPS-based approach in identifying vulnerable populations, but larger studies are needed to confirm is superiority in environmental health research.</p>

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Integrating GPS-based exposure assessment and intracardiac device monitoring to link air pollution and atrial fibrillation

  • 期刊论文

  • 发表日期：

    2025年9月1日

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  • Shaked Yarza,
  • Louise Henriques,
  • Victor Novack,
  • Batia Sarov,
  • Lena Novack

摘要

Air pollution is a significant risk factor for atrial fibrillation (AF), a condition marked by sudden and transient episodes. Accurately capturing these short-term associations requires precise exposure assessment. However, conventional methods utilizing residential addresses alone do not account for personal mobility and rapid fluctuations in pollutant levels, leading to exposure misclassification. To improve exposure precision, we developed a novel method that integrates GPS-tracked mobility data with intracardiac device monitoring to examine short-term associations between ambient air pollutants and atrial fibrillation (AF) episodes. We applied a time-stratified case-crossover design combined with distributed lag nonlinear models (DLNMs) to evaluate associations between short-term exposure to air pollutants, including particulate matter ≤ 2.5 µm and ≤ 10 µm in diameter (PM2.5 and PM10), nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2), and AF episodes. AF episodes were ascertained through intracardiac devices (pacemakers and defibrillators) equipped for continuous recording arrhythmic events. Exposure estimates derived from GPS-based mobility data were compared to those based on participants’ residential addresses. An increase by interquartile range of exposure within 1 day before event showed higher odds ratios (ORs) for AF with GPS-based estimates, particularly for PM2.5 (OR: 1.26, 95% CI: 0.81, 1.96) and NO2 (OR: 1.22, 95% CI: 0.94, 1.57), compared to residential methods (PM2.5 OR: 1.07, 95% CI: 0.53, 2.14; NO2 OR: 1.01, 95% CI: 0.65, 1.55). Participants younger than 70 years old demonstrated stronger associations using GPS-based methods. Similarly, higher effect estimates were observed among current smokers, while differences between exposure models were less pronounced in non-smokers. GPS-enhanced, real-time pollutant exposure demonstrates feasibility and may improve accuracy by capturing dynamic exposure patterns. The results suggest potential advantages of GPS-based approach in identifying vulnerable populations, but larger studies are needed to confirm is superiority in environmental health research.