2022 年9 期 第30 卷
论著![查看全文 查看全文](/Areas/201911120101/Content/img/icon_html.png)
![PDF下载 PDF下载](/Areas/201911120101/Content/img/icon_pdf.png)
深圳市大气污染物与肺源性脓毒症关系的时间分层病例交叉研究
Relationship between Air Pollutants and Pulmonary Sepsis in Shenzhen:a Time-Stratified Case-Crossover Study
作者:陈璟,史菲
- 单位:
- 518001广东省深圳市人民医院急诊科重症监护室
- 单位(英文):
- Department of Emergency Intensive Care Unit, Shenzhen People's Hospital, Shenzhen 518001, China
- 关键词:
- 脓毒症;空气污染物;深圳市;病例交叉研究
- 关键词(英文):
- Sepsis; Air pollutants; Shenzhen; Case-crossover study
- 中图分类号:
- R 631
- DOI:
- 10.12114/j.issn.1008-5971.2022.00.249
- 基金项目:
- 广东省卫生健康适宜技术推广项目(202006181142034974)
摘要:
目的 分析深圳市大气污染物与肺源性脓毒症的关系。方法 本研究为时间分层病例交叉研究。选取2018—2020年深圳市人民医院收治的肺源性脓毒症患者336例为研究对象。收集患者临床资料,获取每例患者发病当天(记为Lag0)及发病前第1~7天(滞后1~7 d,记为Lag1~Lag7)的深圳市区大气污染物〔空气颗粒物(PM)1、PM2.5、PM10、二氧化氮(NO2)、二氧化硫(SO2)、一氧化碳(CO)、臭氧(O3)〕浓度;整理2018-01-01至2020-12-31深圳市区日均大气污染物浓度、气象资料(温度、相对湿度)。两变量间的相关性分析采用Spearman秩相关分析;肺源性脓毒症影响因素分析采用单因素、多因素条件Logistic回归分析,并根据OR 值最大原则确定大气污染物的最佳滞后期。结果 Spearman秩相关分析结果显示,日均PM2.5与日均PM1呈强正相关,日均PM10与日均PM1、PM2.5呈强正相关(P <0.05)。单因素条件Logistic回归分析结果显示,Lag6时PM1及Lag4、Lag5、Lag6时O3是肺源性脓毒症的影响因素(P <0.05),且滞后6 d是PM1、O3的最佳滞后期。多因素条件Logistic回归分析结果显示,在分别控制了PM2.5、PM10的影响后,PM1对肺源性脓毒症发病的影响有所减弱(P <0.05)。结论 深圳市大气污染物中的PM1及O3升高可导致肺源性脓毒症发病风险升高,且滞后6 d是其最佳滞后期,此外,PM2.5、PM10可使PM1对肺源性脓毒症发病的影响减弱。
英文摘要:
Objective To analyze the relationship between air pollutants and pulmonary sepsis in Shenzhen. Methods This was a time-stratified case-crossover study. A total of 336 patients with pulmonary sepsis treated in Shenzhen People'sHospital from 2018 to 2020 were selected as the research objects. The clinical data of the patients were collected. The air pollutantconcentrations [particulate matter (PM) 1, PM2.5, PM10, nitrogen dioxide (NO2) , sulfur dioxide (SO2) , carbon monoxide (CO) , ozone(O3) ] in Shenzhen urban area were obtained on the day of onset of each patient (denoted as Lag0) and 1 to 7 days before the onsetof the disease (lag of 1 to 7 days, denoted as Lag1 to Lag7) . The daily average air pollutant concentrations and meteorologicaldata (temperature, relative humidity) in Shenzhen from 2018-01-01 to 2020-12-31 were sorted out. The correlation between thetwo variables was analyzed by Spearman rank correlation analysis. The influencing factors of pulmonary sepsis were analyzed byunivariate and multivariate conditional Logistic regression analysis, and the optimal lag period of air pollutants was determinedaccording to the principle of maximum OR value. Results The results of Spearman rank correlation analysis showed thatthe daily average PM2.5 was strongly positively correlated with the daily average PM1, and the daily average PM10 was stronglypositively correlated with the daily average PM1 and PM2.5 (P < 0.05) . Univariate conditional Logistic regression analysis showedthat PM1 at Lag6 and O3 at Lag4, Lag5, and Lag6 were the influencing factors of pulmonary sepsis (P < 0.05) , and a lag of 6 d wasthe best lag period for PM1 and O3. Multivariate conditional Logistic regression analysis showed that after controlling for the effectsof PM2.5 and PM10, the effect of PM1 on the incidence of pulmonary sepsis was weakened (P < 0.05) . Conclusion The increaseof PM1 and O3 in air pollutants in Shenzhen can lead to an increased risk of pulmonary sepsis, and a lag of 6 d is the optimal lagperiod. In addition, PM2.5 and PM10 can attenuate the effect of PM1 on the pathogenesis of pulmonary sepsis.
参考文献: