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|Title: ||探索台灣的季節性疾病與 氣候的相關性;Discovering relationship among climate and seasonal diseases in Taiwan|
|Keywords: ||季節性疾病;氣候;相關性;Seasonal diseases;Climate;Relationship|
|Issue Date: ||2015-09-23 11:30:19 (UTC+8)|
;It has been reported that environment factors may be related to several diseases in recent years, especially weather. The diseases which are related to the weather are called seasonal diseases. In this study, we expect to identify some new seasonal diseases in Taiwan through the diagnostic data from Cathay General Hospital in Taipei. Also, we collect the climate data from Central Weather Bureau′s website in Taiwan because these climate factors in Taiwan are different to what Europe and US have. We expect to construct a disease network database through diagnostic data and climate data (includes air temperature, relative humidity, hours of sunshine, and days of rain). In the disease network, we defined and calculated the correlation coefficients between the cases of illness and the climate data, then we can inferred the relation of both categories.
In our results, we found that many diseases were correlating with air temperature, such as acute sinusitis (ICD9-461) and acute upper respiratory infections of multiple or unspecified sites (ICD9-465), they were both negatively related. For relative humidity, internal derangement of knee (ICD9-717) and other diseases of upper respiratory tract (ICD9-478) were also negatively related. In addition, benign neoplasm of other parts of digestive system (ICD9-211) and contact dermatitis and other eczema (ICD9-692) were correlated with either hours of sunshine or days of rain. We also analyzed to investigate whether different sex and ages affected occurrence of diseases. For air temperature, other and unspecified disorders of back (ICD9-724) was not related with younger group (ages less than 20) in female; however, it was not related with older group (ages more than 60) in male.
At last, we obtain the correlations of diseases through this analysis, and then we hope to construct a special and dynamic disease network, which may show the correlations between different diseases and external factors, then profile the occurring pattern of diseases.
|Appears in Collections:||[系統生物與生物資訊研究所] 博碩士論文|
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