The Effect Of Ambient Particulate Matter(PM_2.5/PM₁₀) On Hospital Admissions For Lower Respiratory Tract Infection: A Case-crossover Study In Shi Jiazhuang, China

Objective : Many epidemiologic studies found positive associations between particulate matter and human health. Particulate matter(PM10,PM with an average aerodynamic diameter less than or equal to 10 micrometers) is usually divided into three categories: coarse PM(PM with an average aerodynamic diameter between 2.5 and 10 micrometers), PM2.5(PM with an average aerodynamic diameter less than 2.5 micrometers), and ultrafine PM(PM with an average aerodynamic diameter less than or equal to 0. 1 micrometers). PM2.5 has a larger surface area, adsorbed more harmful substances such as pathogenic microorganisms. It can be reached at all levels of bronchioles and deposits on the alveolar. So PM2.5 has greater toxicity to human body[1-2].Lower Respiratory Tract Infection is one of the common causes of respiratory diseases in hospital, including community-acquired pneumonia, acute exacerbation of chronic obstructive pulmonary disease, bronchiectasis acute aggravating period[3]. Many abroad studies found positive associations between particulate matter and hospital admissions for respiratory diseases[4-6]. Since January 1, 2013 in China,PM2.5 monitoring data been monitored and published. There is no study in China. Particles show considerable heterogeneity over space and season, the effect of particles is vary different. So, it is very important to research the associations between particulate matter and hospital admissions for lower respiratory tract infection in China.This study explore the association between ambient particulate matter(PM2.5/PM10) levels and hospital admissions for lower respiratory tract infection in Shijiazhuang,2013,using case-crossover design. Methods:Methods:1 This study was carried out in the nine hospitals in Shi Jiazhuang, China. Patients were included in the study carried out that if they were lower respiratory tract infection and city residents, between January 1st, 2013 and December 31 st, 2013. The records for lower respiratory tract infection admissions were collected, including sex, age, complications and so on.2 Air pollutants data were provided by Shi Jiazhuang Environmental Monitoring Center. Six pollutants were monitored including inhalable particulate matter(PM10), fine particulate matter(PM2.5), nitrogen dioxide(NO2), sulfur dioxide(SO2), carbon monoxide(CO) and ozone(O3). For each day, the 24 h average levels of these pollutants were computed. The daily mean temperature information was provided by the center of meteorological agency in Shi Jiazhuang city.3 We used a case-crossover design, as a method for assessing the effects of transient exposures of air pollutants on the subsequent risk of disease event, to assess the risk of lower respiratory tract infection admissions based on exposured to various pollutants. To assess pollution exposure, lag 0(the same-day) average exposures and lagged intervals extending from lag 1-lag5(1 to 5 days) before the case or control event were obtained. The event day is termed lag 0, and the day before the event day is lag 1 and so forth. The associations between hospital admissions for lower respiratory tract infection and levels of pollutants were estimated using the odds ratio(OR) and 95% confidence intervals(CI) which were produced using conditional logistic regression with weights equal to the number of hospital admissions. Single-pollutant models and multi-pollutant models were fitted with combination of pollutants to assess the stability of the effect of PM. Stratified analyses of exposure was undertaken to evaluate effect modification based on age, gender, season and underlying disease. All statistical analyses were performed using the SPSS17.0 package. All statistical tests were two-sided and values of P<0.05 were considered statistically significant.Results:1 During the study period, 3126 lower respiratory tract infection admissions were recorded. The majority were male(54.22%) and older(59.15%). And 69.35% of the lower respiratory tract infection admissions were combined underlying disease, and 51.22% of lower respiratory tract infection admissions in warm season.2 The 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. PM2.5 and PM10 were the main pollutants in Shi Jiazhuang.3 For the single-pollutant model, lower respiratory tract infection admissions were positively associated with higher PM level, after adjusted for daily average temperature factor. A 10μg/m3 increase in PM2.5 was associated with a 1.0% increase in hospital admissions for lower respiratory tract infection at lag 0. A 10μg/m3 increase in PM10 was associated with a 0.6% increase in hospital admissions for lower respiratory tract infection at lag5.4 For multi-pollutant models, the effect of a PM2.5 remained significant after NO2、SO2、O3、NO2+SO2、NO2+O3、SO2+O3、NO2+SO2+O3、CO+NO2+SO2、CO+NO2+SO2+O3 was included in the model. The effect of a PM10 remained significant after NO2、NO2+O3、CO、O3、NO2+SO2、CO+NO2+SO2、CO+NO2+O3、NO2+SO2+O3、CO+NO2+SO2+O3 was included in the model.5 We considered effect modified by age, sex, season, and underlying disease. Increase in PM2.5 was associated with increase in hospital admissions for lower respiratory tract infection, and a larger association was seen in male, youngers and admissions without underlying disease. And the effect was significantly on cold days. However, the associated with PM10 was significantly in female, olders and admissions with underlying disease.Conclusion:There was positive association between atmosphere particulate matter(PM2.5/PM10)and hospital admissions for lower respiratory tract infection in Shi Jiazhuang. The effect of PM2.5 was stronger than that of PM10. There was a tendency for the effect of PM2.5 on lower respiratory tract infection admissions to be higher for male, younger than 60 years and for persons without underlying disease,this effects were significantly in cold seasons. However,there was larger effects of PM10 for female, older than 60 years and for persons with underlying disease, this effects were significantly in cold seasons.