Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA; Yale Center on Climate Change and Health, Yale School of Public Health, 60 College Street, New Haven, CT, 06520-8034, USA.
China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China.
Environ Pollut. 2021 Nov 15;289:117858. doi: 10.1016/j.envpol.2021.117858. Epub 2021 Jul 29.
Evidence on the relationship between particulate matter air pollution and urinary system disease (UD) is scarce. This study aims to evaluate the associations between short-term exposures to PM and PM and risk of daily UD inpatient hospital admissions through the emergency room (ER-admissions) in Beijing. We obtained 41,203 weekday UD ER-admissions for secondary and tertiary hospitals in all 16 districts in Beijing during 2013-2018 from the Beijing Municipal Health Commission Information Center and obtained district-level air pollution concentrations based on 35 fixed monitoring stations in Beijing. We conducted a two-stage time-series analysis, with district-specific generalized linear models for each of Beijing's 16 districts, followed by random effects meta-analysis to obtain pooled risk estimates. We evaluated lagged and cumulative associations up to 30 days. In single-pollutant models, for both PM and PM, cumulative exposure averaged over the day of admission and the previous 10 days (lag 0-10 days) showed the strongest association, with per interquartile range increases of PM or PM concentrations associated with a 7.5 % (95 % confidence interval [CI]: 3.0 %-12.2 %) or 6.0 % (95 % CI: 1.1 %-11.2 %) increased risk of daily UD hospital admissions, respectively. The risk estimates were robust to adjustment for co-pollutants and to a variety of sensitivity analyses. However, due to the strong correlation between PM and PM concentrations, we were unable to disentangle the respective relationships between these two exposures and UD risk. In this study, we found that short-term exposures to PM and PM are risk factors for UD morbidity and that cumulative exposure to PM pollution over a period of one to two weeks (i.e., 11 days) could be more important for UD risk than transient exposure during each of the respective single days.
关于颗粒物空气污染与泌尿系统疾病(UD)之间关系的证据很少。本研究旨在评估短期暴露于 PM 和 PM 与北京市二级和三级医院所有 16 个区通过急诊(ER-入院)每日 UD 住院入院风险之间的关联。我们从北京市卫生健康委员会信息中心获得了 2013-2018 年期间北京市所有 16 个区的 41,203 个工作日 UD ER 入院数据,并根据北京市 35 个固定监测站获得了区级空气污染浓度数据。我们进行了两阶段时间序列分析,为北京市的 16 个区中的每个区分别使用特定于区的广义线性模型,然后进行随机效应荟萃分析以获得汇总风险估计值。我们评估了滞后和累积效应,最长可达 30 天。在单污染物模型中,对于 PM 和 PM,入院当天和前 10 天(滞后 0-10 天)的累积暴露平均显示出最强的关联,PM 或 PM 浓度每增加一个四分位间距与每日 UD 住院入院风险增加 7.5%(95%置信区间 [CI]:3.0%-12.2%)或 6.0%(95%CI:1.1%-11.2%)相关。风险估计值在调整了共污染物和各种敏感性分析后仍然稳健。然而,由于 PM 和 PM 浓度之间存在很强的相关性,我们无法区分这两种暴露与 UD 风险之间的各自关系。在这项研究中,我们发现短期暴露于 PM 和 PM 是 UD 发病率的危险因素,并且在一到两周(即 11 天)的时间内对 PM 污染的累积暴露比在各自的每一天的短暂暴露对 UD 风险更为重要。