Liu Cong, Tai Meihui, Hu Jialu, Zhu Xinlei, Wang Weidong, Guo Yutao, Kan Haidong, Chen Renjie
School of Public Health, Shanghai Institute of Infectious Disease and Biosecurity, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China.
Pulmonary Vessel and Thrombotic Disease, Sixth Medical Center, Chinese PLA General Hospital, Beijing, 100048, China.
NPJ Digit Med. 2023 Mar 14;6(1):42. doi: 10.1038/s41746-023-00788-w.
Few studies have examined the link between short-term exposure to air pollutants and atrial fibrillation (AF) episodes. This study aims to examine the association of hourly criteria air pollutants with AF episodes. We employ a smart device-based photoplethysmography technology to screen AF from 2018 to 2021. Hourly concentrations of six criteria air pollutants are matched to the onset hour of AF for each participant. We adopt a time-stratified case-crossover design to capture the acute effects of air pollutants on AF episodes, using conditional logistic regression models. Subgroup analyses are conducted by age, gender, and season. A total of 11,906 episodes of AF are identified in 2976 participants from 288 Chinese cities. Generally, the strongest associations of air pollutants are present at lag 18-24 h, with positive and linear exposure-response relationships. For an interquartile range increase in inhalable particles, fine particles, nitrogen dioxide, and carbon monoxide, the odds ratio (OR) of AF is 1.19 [95% confidential interval (CI): 1.03, 1.37], 1.38 (95%CI: 1.14, 1.67), 1.60 (95%CI: 1.16, 2.20) and 1.48 (95%CI: 1.19, 1.84), respectively. The estimates are robust to the adjustment of co-pollutants, and they are larger in females, older people, and in cold seasons. There are insignificant associations for sulfur dioxide and ozone. This nationwide case-crossover study demonstrates robust evidence of significant associations between hourly exposure to air pollutants and the onset of AF episodes, which underscores the importance of ongoing efforts to further improve air quality as an effective target for AF prevention.
很少有研究探讨短期暴露于空气污染物与房颤（AF）发作之间的联系。本研究旨在检验每小时的标准空气污染物与AF发作之间的关联。我们采用基于智能设备的光电容积脉搏波描记术技术，在2018年至2021年期间筛查AF。将六种标准空气污染物的每小时浓度与每位参与者AF发作的小时数进行匹配。我们采用时间分层病例交叉设计，使用条件逻辑回归模型来捕捉空气污染物对AF发作的急性影响。按年龄、性别和季节进行亚组分析。在来自中国288个城市的2976名参与者中，共识别出11906次AF发作。一般来说，空气污染物的最强关联出现在滞后18 - 24小时，具有正的线性暴露 - 反应关系。对于可吸入颗粒物、细颗粒物、二氧化氮和一氧化碳的四分位数间距增加，AF的优势比（OR）分别为1.19 [95%置信区间（CI）：1.03, 1.37]、1.38（95%CI：1.14, 1.67）、1.60（95%CI：1.16, 2.20）和1.48（95%CI：1.19, 1.84）。这些估计值在调整共污染物后具有稳健性，并且在女性、老年人和寒冷季节中更大。二氧化硫和臭氧的关联不显著。这项全国性的病例交叉研究证明了每小时暴露于空气污染物与AF发作之间存在显著关联的有力证据，这凸显了持续努力进一步改善空气质量作为预防AF的有效目标的重要性。
