Central Clinical Hospital MSWiA in Warsaw, Wołoska 137, 02-507, Warsaw, Poland.
University of Humanities and Economics in Łodz, Satellite Campus in Warsaw, ul. Wolność 2a, 01-018, Warsaw, Poland.
Environ Sci Pollut Res Int. 2020 Jul;27(19):24582-24590. doi: 10.1007/s11356-020-08542-5. Epub 2020 Apr 30.
Very few publications have compared different study designs investigating the short-term effects of air pollutants on healthcare visits and hospitalizations for respiratory tract diseases. This study describes, using two different study designs (a case-crossover design and a time-series analysis), the association of air pollutants and respiratory disease hospitalizations. The study has been conducted on 5 cities in Poland on a timeline of almost 4 years. DLNM and regression models were both used for the assessment of the short-term effects of air pollution peaks on respiratory hospitalizations. Both case-crossover and time-series studies equally revealed a positive association between air pollution peaks and hospitalization occurrences. Results were provided in the form of percentage increase of a respiratory visit/hospitalization, for each 10-μg/m increment in single pollutant level for both study designs. The most significant estimated % increases of hospitalizations linked to increase of 10 μg/m of pollutant have been recorded in general with particulate matter, with highest values for 24 h PM in Warsaw (6.4%, case-crossover; 4.5%, time series, respectively) and in Białystok (5.6%, case-crossover; 4.5%, time series, respectively). The case-crossover analysis results have shown a larger CI in comparison to the results of the time-series analysis, while the lag days were easier to identify with the case-crossover design. The trends and the overlap of the results occurring from both methods are good and show applicability of both study designs to air pollution effects on short-term hospitalizations.
很少有出版物比较过不同的研究设计,这些研究设计旨在调查短期空气污染物对呼吸道疾病就诊和住院的影响。本研究使用两种不同的研究设计(病例交叉设计和时间序列分析)描述了空气污染物与呼吸道疾病住院之间的关联。该研究在波兰的 5 个城市进行,时间跨度近 4 年。DLNM 和回归模型均用于评估空气污染高峰期对呼吸道住院的短期影响。病例交叉和时间序列研究都同样揭示了空气污染高峰期与住院发生之间存在正相关关系。结果以两种研究设计中每种污染物水平增加 10μg/m 时呼吸道就诊/住院的百分比增加的形式提供。与污染物增加 10μg/m 相关的住院百分比的最高估计增幅是与颗粒物有关,在华沙(病例交叉 6.4%,时间序列 4.5%)和比亚韦斯托克(病例交叉 5.6%,时间序列 4.5%)记录的最高值。与时间序列分析相比,病例交叉分析的结果显示出更大的置信区间,而病例交叉设计更容易识别滞后天数。两种方法的结果趋势和重叠良好,表明这两种研究设计都适用于空气污染对短期住院的影响。