氣候變遷對人類疾病網路造成衝擊;Climate change impacts on human disease network

NCUIR > college of Health Sciences and Technology > Institute of Systems Biology and Bioinformatics > Electronic Thesis & Dissertation > Item 987654321/74215

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/74215

Title:	氣候變遷對人類疾病網路造成衝擊;Climate change impacts on human disease network
Authors:	吳孟賢;Wu, Meng-Hsien
Contributors:	系統生物與生物資訊研究所
Keywords:	氣候變遷;人類疾病網路;climate change;human disease network
Date:	2017-07-14
Issue Date:	2017-10-27 13:16:47 (UTC+8)
Publisher:	國立中央大學
Abstract:	過去100年內，全球氣溫逐漸升高，尤以近30年來，升高幅度越趨快速。氣候改變將對人體造成影響，而疾病的發生率也隨著氣候而改變。透過前人的研究，我們已知許多疾病的發生與環境氣溫或季節改變呈現相關性，稱為疾病的氣溫相關性或疾病的季節性。在此，我們利用國泰醫院與壢新醫院的看診資料，探討疾病對氣溫的關聯性與疾病網路對氣溫的關聯性。兩醫院的急診與門診資料皆顯現出許多高氣溫關聯度的疾病，此結果可與許多前人的研究相互驗證。最重要的是，我們發現了許多疾病，其一階關聯網路之複雜度與年均溫或季均溫呈現高度相關性；而這些疾病大多並非季節性疾病。不同於以往的研究，我們發現了隱性的季節性疾病。這樣的隱性季節性疾病並非透過氣溫影響患者的發病率，而是影響共病症或併發症的發生。最後，我們試著對照兩間醫院的資料；我們的結果顯示兩間醫院的診斷碼多數不同。然而，若非直接對照診斷碼，而是對照類似疾病群組，則將兩醫院的資料合併討論是可能的。;The changes in global climate have led to the rising of temperature over the past 100 years, especially in the past 30 years. Climate change affects human body and the morbidities of diseases. According to former researches, prevalence of many diseases correlate with ambient temperature or seasons. We call those diseases temperature correlated diseases or seasonal diseases. Here, we used clinical data from Cathay General Hospital (CGH) and Landseed Hospital (LSH) to discuss the correlations between diseases and temperature, and between disease network and temperature. In both emergency room cases and all clinical data, the data from two hospitals showed high temperature correlation in many diseases. These results agreed with numerous former researches. The most important thing is that we found some diseases whose first order disease network changed with temperature. The connectivity among diseases in the network changed with either annual mean temperature or seasonal mean temperature. Most of those diseases do not correlate with temperature, but the network around them do. Different from other studies, we discovered the invisible temperature-correlated diseases. Finally, we tried to map the diagnosis from two hospitals. Most of the diagnosis from the two hospitals are different from each other, but it is possible to map them together.
Appears in Collections:	[Institute of Systems Biology and Bioinformatics] Electronic Thesis & Dissertation

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	428	View/Open

社群 sharing

Loading...