Research on Medical-Meteorological Model of Common Diseases Impacted by Meteorological Condition in Nanjing
|School||Nanjing University of Information Engineering|
|Keywords||meteorological factors chronic obstructive pulmonary coronary heart disease cerebral infraction stepwise regression forecasting models|
The influences of climate change and atmospheric pollution on human health have become one of the focus of attention of the whole society. many studies have shown that changes in meteorological elements have significant impacts on the respiratory, cardiovascular and cerebrovascular diseases, besides, the seasonal distribution trends among different inducers of the same disease are various.So it’s practically significant for the prevention and cure of disease to investigate the relationship between meteorological elements and respiratory, and cardiovascular and cerebrovascular disease. In this article, Nanjing’s temperature trends, the correlation of chronic obstructive pulmonary disease (COPD), coronary heart disease (CHD), and cerebral infarction (CI) incidence with meteorological factors were analyzed by using the meteorological data from1951to2010in Nanjing. Meanwhile, the prediction model for the three common meteorological disease incidence trends were set up, the main conclusions are as follows:(1) The temperature in60years during1951to2010in Nanjing presents a rising trend, low-temperature increases more quickly than the high-temperature, and the temperature difference ratio presents a decreasing trend.In addition, temperature changes during the quarter, each quarter temperatures were uptrend, spring temperatures rise quickly, its warming trend is most obvious, followed by winter and autumn. Summer is also warming, but its trend is least obvious.(2) COPD occurrence presents an ascendant trend in the recent10years, which the male occurrence was three times higher than that of women, and the peak of COPD occurrence appears in about80-year-old. Meteorological factors played a comprehensive effect on the occurrence of COPD. The weather featured as high-pressure, low-temperature, small wind speed and low humidity was most easily lead to COPD. For the whole year, the incidence of COPD is largest from the late autumn to midwinter, following by spring and the least in summer, this paper established the forecasting model of COPD, the accuracy of which could preferably meet the requirements of operational meteorological service to reduce the occurrence of COPD. The acute exacerbation of chronic obstructive pulmonary disease was closely related to meteorological condition, especial attention should be taken for the middle and old age people.(3)The incidences of coronary heart disease and cerebral infarction disease have increased year by year in the past10years, mostly happened in elderly patients, with the peak of age segment mainly in60-75year-old. Male patients account for about67%, women account for about33%. Coronary heart disease frequently occurred in November, December and March and April of Spring. Cerebral infarction occurred mainly in the seasonal transition month of March, July, September, November and so on. When the summer daily maximum temperature above35℃or so, number of coronary heart disease (CHD) morbidity increases with temperature rise; When the minimum temperature is lower than0℃in winter days, coronary heart disease incidence and less as the temperature decreases. When the summer day when the highest temperature is higher than33℃or so, cerebral infarction incidence increases with temperature rise; When winter, the lowest temperature is less than1℃, the male cerebral infarction incidence and less as the temperature decreases. Women cerebral infarction incidence trend is not obvious. Multivariate analysis found that there have significant correlations of coronary heart disease, cerebral infarction with the temperature of that day and the former three days, pressure, minimum relative humidity, precipitation, API index the disease prediction model of coronary heart disease and cerebral infarction among four seasons were derived by the stepwise regression analysis of diseases number and meteorological elements according different seasons.almost all model grading predictions’ accuracy rate are over90%,which have a practical value to reduce the incidence of the disease.