基于医疗大数据的空气污染类疾病信息分析研究

Information Analysis of Air Pollution Diseases Based on Medical Big Data

世界卫生组织表示,空气污染为造成全球疾病负担的一项重要因素,能够导致心血管疾病、呼吸系统疾病等各种疾病的发生,空气污染问题已经成为公共卫生领域关注的重点问题,对基于医疗大数据的空气污染类疾病信息进行分析。利用半参数广义相加的泊松回归模型,在控制时间、长期趋势、气象因素等一些复杂条件的基础上,对2012年1月1日至2016年12月31日,某市空气中SO2、PM10和NO2等一些主要空气污染物的监测浓度值与呼吸系统疾病(肺炎以及支气管炎与哮喘)住院人数的相关性进行研究,研究结果表明,空气颗粒物PM10对患病率的影响相对于气态污染物SO2、NO2更为严重。

The World Health Organization says air pollution is an important factor in the global disease burden,leading to cardiovascular,respiratory and other diseases. Air pollution has become a key issue in the field of public health. The information of air pollution diseases based on medical big data is analyzed. The Poisson regression model with semi-parametric generalized addition is used to control time and long-term trend. Based on some complicated conditions such as meteorological factors,the concentration of some major air pollutants,such as SO2,PM10 and NO2,in the air of a certain city from January 1,2012 to December 31,2016 was monitored. A study of the correlation between degrees and the number of hospitalizations for respiratory diseases（pneumonia,bronchitis and asthma） showed that,Air particulate matter（PM10） and NO2 significantly increased the content of PM10 in patients with bronchitis and showed a significant positive correlation with the incidence of asthma,and with the increase of the concentrations of SO2、N_（10） and NO2,there was a significant positive correlation between the content of PM10 and the incidence of asthma. The risk of cardiovascular and cerebrovascular death was increased by 0. 3 and 0. 30. 2. PM10 effect reached the maximum after 1 day,showing linear no threshold. The effect of air particulate PM10 on the morbidity was relative to that of gaseous pollutant SO2、NO2 is more serious. In order to reduce the incidence of many kinds of diseases and reduce the inducing factors,we should actively call for the protection of the environment and the improvement of air quality.