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Study On The Correlation Between Meteorological Factors Or Air Pollution And Stroke Occurrence Of Guangzhou City

Posted on:2010-02-10Degree:MasterType:Thesis
Country:ChinaCandidate:L Y LiangFull Text:PDF
GTID:2144360302960168Subject:Emergency Medicine
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Background and ObjectiveStroke is the third leading cause of death and the leading cause of severe long-term disability in developed countries. Many studies have shown an association between meteorological factors, air pollution and stroke. However, the conclusions are not the same and even more some studies shown contradiction. The evidence is conflicting partly due to variation in the populations and in climatic conditions between studies. To evaluate the association between meteorological factors, air pollutants and the occurrence of acute stroke and work out a meteorological formula for predicting the onset of stroke for the residents of Guangzhou city.MethodsThe daily stroke data was obtained from Guangzhou"120"register during Aug 1, 2006 to Oct 22, 2007. The daily meteorological parameters (including atmospheric pressure, minimum and mean relative humidity, maximum, minimum and mean temperatures, difference in temperature, wind speed, rainfall, sunshine hours) and air pollution levels for SO2, NO2 and Particulate matter of Guangzhou were obtained from Guangdong meteorological department during Aug 1, 2006 to Oct 22, 2007. I investigated the presence of seasonality and circadian variations in the incidence of stroke with compose rate and chi-square test. I used correlation analysis and multiple regression techniques through statistical software SPSS For Windows 13.0 to explore the daily and weekly effects of meteorological parameters or air pollution levels. At last, I try to confirm the main factor and work out the meteorological formula for predicting the onset of strokeResults1. The findings of this study confirmed the presence of circadian variation in the incidence of stroke in Guangzhou city. The higher number of stroke occurred during 8am12am, showing a peak in 10am. The lower number of stroke cases were during 22pm 6am.2. Incidence of stroke has seasonal difference in Guangzhou city. I noted a higher occurrence of stroke during winter and spring months than in summer and autumn months. The lower occurrence of stroke was observed from August to November.3. Correlation analysis suggested that daily stroke occurrence in Guangzhou was negatively correlated with mean, maximum, minimum temperatures, mean dew point temperature and positively correlated with mean atmospheric pressure, NO2 and Particulate matter of the same day.4. No associations were found between the daily stroke occurrence and the daily difference in temperature, relative humidity, wind speed, sunshine hours, rainfall and SO2.5. More significant associations were found between the weekly stroke occurrence in Guangzhou and temperature, atmospheric pressure but not with air pollutant.6. The formula for predicting daily onset of stroke is YD = (19.815-0.230×daily minimum temperature)×1.00008n (n are the days from August1, 2006). The formula has some vale on predicting the onset of stroke.7.The formula for predicting weekly onset of stroke is YW = (141.451-1.760×daily minimum temperature)×1.00057n (n are the weeks from August1, 2006). It has significance in statistics.Conclusions1. The findings of this study confirm the presence of circadian variation in the incidence of stroke in Guangzhou city. The higher number of stroke occurred in the morning, showing a peak in 10am. The lower number of stroke cases were from the midnight to the early morning of the last day.2. Incidence of stroke has seasonal difference in Guangzhou city, higher during winter and spring months and lower in summer and autumn months.3. The occurrence of stroke in Guangzhou city was correlated with meteorological parameters, especially the daily minimum temperature. And the correlation was not significant between with air pollution.The formula for predicting the onset of stroke is: YD= (19.815-0.230×daily minimum temperature)×1.00008n (n are the days from August 1, 2006) YW= (141.451-1.760×daily minimum temperature)×1.00057n (n are the weeks from August 1, 2006).
Keywords/Search Tags:Stroke, meteorological factor, pollution, predict
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