Dab W, Medina S, Quénel P, Le Moullec Y, Le Tertre A, Thelot B, Monteil C, Lameloise P, Pirard P, Momas I, Ferry R, Festy B
Ecole Nationale de Santé Publique and Service des Etudes Médicales EDF-GDF, Saint-Maurice, France.
J Epidemiol Community Health. 1996 Apr;50 Suppl 1(Suppl 1):s42-6. doi: 10.1136/jech.50.suppl_1.s42.
To quantify the short term respiratory health effects of ambient air pollution in the Paris area.
Time series analysis of daily pollution levels using Poisson regression.
Paris, 1987-92.
Air pollution was monitored by measurement of black smoke (BS) (15 monitoring stations), sulphur dioxide (SO2), nitrogen dioxide (NO2), particulate matter less than 13 microns in diameter (PM13), and ozone (O3) (4 stations). Daily mortality and general admissions to public hospitals due to respiratory causes were considered. The statistical analysis was based on a time series procedure using linear regression modelling followed by a Poisson regression. Meterological variables, epidemics of influenza A and B, and strikes of medical staff were included in the models. The mean daily concentration of PM13 and daily 1 hour maximum of SO2 significantly affected daily mortality from respiratory causes. An increase in the concentration of PM13 of 100 micrograms/m3 above its 5th centile value increased the risk of respiratory death by 17%. PM13 and BS were also associated with hospital admissions due to all respiratory diseases (4.1% increased risk when the BS level exceeded its 5th centile value by 100 micrograms/m3). SO2 levels consistently influenced hospital admissions for all respiratory diseases, chronic obstructive pulmonary disease, and asthma. Asthma was also correlated with NO2 levels.
These results indicate that even though the relative risk is weak in areas with low levels of pollution, ambient air pollution, and especially particulate matter and SO2, nonetheless require attention because of the number of people exposed and the existence of high risk groups.
量化巴黎地区环境空气污染对短期呼吸健康的影响。
使用泊松回归对每日污染水平进行时间序列分析。
巴黎,1987 - 1992年。
通过测量黑烟(BS)(15个监测站)、二氧化硫(SO₂)、二氧化氮(NO₂)、直径小于13微米的颗粒物(PM13)和臭氧(O₃)(4个站)来监测空气污染。考虑了每日死亡率以及因呼吸道疾病入住公立医院的情况。统计分析基于一种时间序列程序,先使用线性回归建模,然后进行泊松回归。模型中纳入了气象变量、甲型和乙型流感流行情况以及医务人员罢工情况。PM13的日均浓度和SO₂的每日1小时最大值对因呼吸道疾病导致的每日死亡率有显著影响。PM13浓度比其第5百分位数增加100微克/立方米会使呼吸道死亡风险增加17%。PM13和BS也与所有呼吸道疾病导致的住院情况相关(当BS水平超过其第5百分位数100微克/立方米时,风险增加4.1%)。SO₂水平一直影响所有呼吸道疾病、慢性阻塞性肺疾病和哮喘的住院情况。哮喘也与NO₂水平相关。
这些结果表明,尽管在污染水平较低的地区相对风险较弱,但由于暴露人群数量以及高危人群的存在,环境空气污染,尤其是颗粒物和SO₂,仍然需要引起关注。