背景:在COVID-19大流行期间实施了几项公共卫生措施。然而,对环境暴露对哮喘儿童肺功能的实时评估知之甚少。因此,我们开发了一个手机应用程序,用于捕获大流行期间环境空气污染的实时日常动态变化。我们的目标是探索封锁前之间环境空气污染物的变化,封锁,和封锁,并分析污染物与螨致敏和季节变化介导的PEF之间的关系。
方法:一项前瞻性队列研究于2016年1月至2022年2月在511名哮喘儿童中进行。用于记录日常环境空气污染的智能手机应用程序,颗粒物(PM2.5,PM10)Ozon(O3),二氧化氮(NO2),一氧化碳(CO),二氧化硫(SO2),平均温度,和相对湿度,通过链接到基于全球定位系统(GPS)的软件,从附近的77个空气监测站进行测量和连接。污染物对呼气峰流速仪(PEF)和哮喘的影响的结果由每位患者或护理人员的电话中的智能峰流速仪进行实时评估。
结果:封锁(5月19日,2021年7月27日2021年)与2021年调整后,除SO2以外的所有环境空气污染物水平下降有关。在滞后0(测量PEF的同一天),NO2和SO2不断与PEF水平降低相关。滞后1(测量PEF前一天),和滞后2(测量PEF前两天。仅在单一空气污染物模型的分层分析中,对螨虫敏感的儿童中,CO的浓度与PEF相关。根据季节,与其他季节相比,春季与所有污染物暴露中PEF的降低具有更高的相关性。
结论:使用我们开发的智能手机应用程序,我们确定了NO2,CO,在COVID-19封锁前后,PM10高于封锁期间。我们的智能手机应用程序可能有助于收集个人空气污染数据和肺功能,特别是对于哮喘患者,并可能指导预防哮喘发作。它为COVID时代及以后的个性化护理提供了一种新模式。
BACKGROUND: Several public health measures were implemented during the COVID-19 pandemic. However, little is known about the real-time assessment of environmental exposure on the pulmonary function of asthmatic children. Therefore, we developed a mobile phone application for capturing real-time day-to-day dynamic changes in ambient air pollution during the pandemic. We aim to explore the change in ambient air pollutants between pre-lockdown, lockdowns, and lockdowns and analyze the association between pollutants and PEF mediated by mite sensitization and seasonal change.
METHODS: A prospective cohort study was conducted among 511 asthmatic children from January 2016 to February 2022. Smartphone-app used to record daily ambient air pollution, particulate matter (PM2.5, PM10) Ozon (O3), nitrogen dioxide (NO2), Carbon Monoxide (CO), sulfur dioxide (SO2), average temperature, and relative humidity, which measured and connected from 77 nearby air monitoring stations by linking to Global Positioning System (GPS)-based software. The outcome of pollutants\' effect on peak expiratory flow meter (PEF) and asthma is measured by a smart peak flow meter from each patient or caregiver\'s phone for real-time assessment.
RESULTS: The lockdown (May 19th, 2021, to July 27th, 2021) was associated with decreased levels of all ambient air pollutants aside from SO2 after adjusting for 2021. NO2 and SO2 were constantly associated with decreased levels of PEF across lag 0 (same day when the PEF was measured), lag 1 (one day before PEF was measured), and lag 2 (two days prior when the PEF was measured. Concentrations of CO were associated with PEF only in children who were sensitized to mites in lag 0, lag 1, and lag 2 in the stratification analysis for a single air pollutant model. Based on the season, spring has a higher association with the decrease of PEF in all pollutant exposure than other seasons.
CONCLUSIONS: Using our developed smartphone apps, we identified that NO2, CO, and PM10 were higher at the pre-and post-COVID-19 lockdowns than during the lockdown. Our smartphone apps may help collect personal air pollution data and lung function, especially for asthmatic patients, and may guide protection against asthma attacks. It provides a new model for individualized care in the COVID era and beyond.