Li Huichu, Bai Hongjian, Yang Changyuan, Chen Renjie, Wang Cuicui, Zhao Zhuohui, Kan Haidong
School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China.
The First People's Hospital of Yancheng, Jiangsu Province, China.
J Epidemiol. 2017 Dec;27(12):584-589. doi: 10.1016/j.je.2017.01.002. Epub 2017 Jun 20.
Epidemiological studies have shown the associations of ambient temperature and particulate matter (PM) air pollution with respiratory morbidity and mortality. However, the underlying mechanisms have not been well characterized. The aim of this study is to investigate the associations of temperature and fine and coarse PM with fractional exhaled nitric oxide (FeNO), a well-established biomarker of respiratory inflammation.
We conducted a longitudinal panel study involving six repeated FeNO tests among 33 type 2 diabetes mellitus patients from April to June 2013 in Shanghai, China. Hourly temperature and PM concentrations were obtained from a nearby fixed-site monitoring station. We then explored the associations between temperature, PM, and FeNO using linear mixed-effect models incorporated with distributed lag nonlinear models for the lagged and nonlinear associations. The interactions between temperature and PM were evaluated using stratification analyses.
We found that both low and high temperature, as well as increased fine and coarse PM, were significantly associated with FeNO. The cumulative relative risk of FeNO was 1.75% (95% confidence interval [CI], 1.04-2.94) comparing 15 °C to the referent temperature (24 °C) over lags 0-9 days. A 10 μg/m increase in fine and coarse PM concentrations were associated with 1.18% (95% CI, 0.18-2.20) and 1.85% (95% CI, 0.62-3.09) FeNO in lag 0-1 days, respectively. PM had stronger effects on cool days than on warm days.
This study suggested low ambient temperature, fine PM, and coarse PM might elevate the levels of respiratory inflammation. Our findings may help understand the epidemiological evidence linking temperature, particulate air pollution, and respiratory health.
流行病学研究表明,环境温度和颗粒物(PM)空气污染与呼吸道疾病的发病率和死亡率有关。然而,其潜在机制尚未得到充分阐明。本研究的目的是调查温度以及细颗粒物和粗颗粒物与呼出一氧化氮分数(FeNO)之间的关联,FeNO是一种公认的呼吸道炎症生物标志物。
我们于2013年4月至6月在中国上海对33名2型糖尿病患者进行了一项纵向队列研究,其中包括6次重复的FeNO检测。每小时的温度和PM浓度数据来自附近的固定监测站。然后,我们使用线性混合效应模型结合分布滞后非线性模型来探讨温度、PM和FeNO之间的滞后和非线性关联。通过分层分析评估温度和PM之间的相互作用。
我们发现,低温和高温以及细颗粒物和粗颗粒物的增加均与FeNO显著相关。在0 - 9天的滞后时间内,将15°C与参考温度(24°C)相比,FeNO的累积相对风险为1.75%(95%置信区间[CI],1.04 - 2.94)。在滞后0 - 1天,细颗粒物和粗颗粒物浓度每增加10μg/m³,分别与FeNO增加1.18%(95% CI,0.18 - 2.20)和1.85%(95% CI,0.62 - 3.09)相关。PM在凉爽天气比在温暖天气的影响更强。
本研究表明,低环境温度、细颗粒物和粗颗粒物可能会升高呼吸道炎症水平。我们的研究结果可能有助于理解将温度、颗粒物空气污染和呼吸道健康联系起来的流行病学证据。