建立跨資料庫時間序列分析決策支援系統─以氣候變化對心血管疾
病影響為例
A cross-database time series analysis decision support system-
Studying the relationship between climate change and cardiovascular disease
中文摘要
近年來，隨著台灣地區人口年齡結構的老化，心血管疾病對國人的健康威脅日與 俱增。在許多不同國家及氣候型態不同的地區都曾有文獻報告指出此類型疾病的 發生率與死亡率皆會隨著季節及環境溫度變動而有所變化。
台灣地處亞熱帶又為海島型氣候因此受到周圍氣候影響相當大，且台灣地形屬南 北狹長可能同時間南北呈現不同之氣後狀態如南熱北冷等或北部降雨南部放晴 等現象，若只針對單一縣市區域做研究可能會稍嫌說服力不足。
本研究目的在探討國人心血管疾病之發作與大氣溫度變化與相關氣象因子之關 聯性。資料來源為全民健康保險資料庫西元 2000 年至西元 2002 年間所有相關案 例與對應年度的氣象觀測資料為研究對象，並將收集之資料分成各縣市別探討疾 病的發作是否會隨著環境溫度變化而有所不同，分析病患就醫人次與各氣象因子 間的關係。本研究利用迴歸分析找出各氣象因子對就醫人次的相對危險性後，再 利用時間序列中的 VAR 模型作進一步分析探討，最後建立 Web 介面系統依縣市 別將所有分析資訊作整合呈現，期待讓使用者藉由 Web 點選的方式得知心血管 疾病族群就醫人次與各氣象因子間的關係。
英文摘要
In the recent years, because of the ageing problem in the population structure of Taiwan, the threat of the cardiovascular illness for Taiwanese people is constantly increasing. In the literature reports of many countries with different climate conditions have pointed out that the occurrence and mortality of such illness do tend to be
different according to the change of the seasons and the surrounding temperature.
Taiwan is situated in the subtropical zone, and its type of climate is sea-island, therefore, it is affected a great deal by its surrounding climate. The Taiwanese terrain is both long and narrow at its north and south ends, and so the climate condition of both ends can be different at any given one time. For example, the north can be cold while the south is experiencing hot weather, or the north is raining while the south is having a sunny day. For this very own reason, if the research is only done to one county or city alone, the strength of persuasion can be deemed a little low.
The purpose of this research is to investigate the Taiwanese people’s cardiovascular illness and the relatedness between the relative climate factors and the change in the atmospheric temperature. The source of information is the research database of the National Health Insurance from year 2000 to 2002. From this database, any related case with its climate observation data in the corresponding year is chosen as the research subject. The collected data is also divided according to different counties and cities, and whether the occurrence of the illness is related to the change in the
surrounding climate factors is discussed individually. The relationship between the number of people seeking medical advice and each different climate factors is also analyzed. Regression analysis is used in this research to figure out the related risk of each climate factors to the number of people seeking medical advice. And after that, VAR model in the time series is then used to further analysis. Finally, a Web interface system is created according to different counties and cities, and the analyzed
information is displayed in integral. All is done with the expectation of utilizing the point-and-click technique in the Web interface from the users to allow the
understanding of the relationship between the number of people having cardiovascular illness seeking medical advice and each different climate factors.
