| Objective：Particulate matter (PM) is a mixture of solid or liquid particles in the air.Particulate matter is Usually divided into three categories according to it’saerodynamic diameter: coarse PM (PM with an average aerodynamic diameterbetween2.5and10micrometers),PM2.5(PM with an average aerodynamicdiameter less than2.5micrometers), and ultrafine PM (PM with an averageaerodynamic diameter less than or equal to0.1micrometers).Pneumonia is a common respiratory disease. Many epidemiologic studiesfound positive associations between particulate matter and hospital admissionsfor pneumonia. These studies were almost all done in North America, and theimpact of particulate matter on hospital admissions for pneumonia is less welldocumented in Asia. There is no records about this in China. Becauseparticles show considerable heterogeneity over space and season, the effect ofparticles is likely to vary. So, it is very important to detect associationsbetween particulate matter and hospital admissions for pneumonia in China.This study was undertaken to examine the association between levels ofambient particulate matter (PM10/PM2.5) and hospital admissions forpneumonia among people residing in Shijiazhuang,2013,using case-crossoverdesign.Methods：1This study was carried out in the nine hospitals in Shi Jiazhuang, China.Patients were included in the study carried out between January1st,2013andDecember31st,2013if they were pneumonia. The records for pneumoniaadmissions were collected, including sex, age, residential address,complications and so on. 2Data on air pollutants were provided by Shi Jiazhuang EnvironmentalMonitoring Center. Six pollutants were monitored including inhalableparticulate matter(PM10), fine particulate matter(PM2.5), sulfur dioxide(SO2),nitrogen dioxide(NO2), carbon monoxide(CO) and ozone(O3). For each day,hourly air pollution data were obtained, the24h average levels of thesepollutants were computed. Daily information on mean temperature wasprovided by the center of meteorological agency in Shi Jiazhuang city.3We used a case-crossover design, which was proposed as a method forassessing the effects of transient exposures of air pollutants on the subsequentrisk of disease event, to assess the risk of pneumonia admissions based onexposure to various pollutants. To assess pollution exposure, same-day (lag0)average exposures and lagged intervals extending from1to5days (lag1-lag5)before the case or control event were obtained. The event day is termed lag0,and the day before the event day is lag1. The day before lag1is lag2, and soforth. The associations between hospital admissions for pneumonia and levelsof pollutants were estimated using the odds ratio (OR) and their95%confidence intervals (CI) which were produced using conditional logisticregression with weights equal to the number of hospital admissions on thatday. Both single-pollutant models and multi-pollutant models were fitted witha different combination of pollutants to assess the stability of the effect of PM.Stratified analyses of exposure based on the average exposure at lag0to lag5based on age, gender, season and underlying disease was undertaken toevaluate effect modification. All statistical analyses were performed usingthe SPSS13.0package, All statistical tests were two-sided. Values ofP<0.05were considered statistically significant.Results：1During the study period,2253pneumonia admissions were recorded.The majority were men (53%) and older (55%). And65.96%of thepneumonia admissions were combined diabetes, hypertensive, heart disease,and12.16%of pneumonia admissions with Chronic lung disease.2The average level The data of air pollutants reveals that the mean annual concentration of PM2.5,PM10,SO2,NO2,CO and O3were (156.43±118.60)μg/m3,(311.26±162.94) μg/m3,(106.44±86.84) μg/m3,(68.77±28.69) μg/m3,(2.04±1.74) mg/m3and (96.25±67.99) μg/m3.The mean annual concentrationaverage level of PM2.5,PM10,SO2and NO2were significantly higher comparedwith current WHO criterion and Chinese national secondary standard. PM2.5and PM10were the main pollutants in Shi Jiazhuang..3For the single-pollutant model, pneumonia admissions were positivelyassociated with higher PM levels, After adjusted for daily average temperaturefactor, A10μg/m3increase in PM10was associated with a0.5%increase inhospital admissions for pneumonia at lad5. A10μg/m3increase in PM2.5wasassociated with a1.1%increase in hospital admissions for pneumonia at lag0.4For multi-pollutant models, the effect of a PM2.5remained significantafter each of the other four pollutants was included in the model. The effect ofa PM10remained significant after O3and NO2was included in the model.However, the effects of PM10were significantly negative after adjusted forSO2and CO.5We also considered effect modified by age, sex, season, and underlyingdisease. Increase in PM2.5was associated with increase in hospital admissionsfor pneumonia, and a larger association was seen in male, youngers andadmissions without underlying disease and without chronic lung disease. Andthe effect was significantly on warm days. However, the associated with PM10was significantly in male, olders and admissions without chronic lung disease.Conclusion：There was positive association between atmosphere particulate matter(PM2.5/PM10)and hospital admissions for pneumonia in Shi Jiazhuang. Theeffect of PM2.5was stronger than that of PM10. There was a tendency for theeffect of PM2.5on pneumonia admissions to be higher for males, younger than60years and for persons without underlying disease and chronic lungdiseases，this effects were significantly in warm seasons. However，there waslarger effects of PM10for males, older than60years and for persons without chronic lung diseases，this effects were significantly in cold seasons. |
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