探討空氣汙染與氣候對呼吸道疾病就診人次之衝擊-以台中市為例

Abstract

由於空氣汙染及天氣的變化會增加人們感染呼吸道疾病的風險，環境污染與氣候變遷是現今備受各國政府關切的議題；近年來的中外文獻指出，地理環境的差異，不同年齡族群的差異及性別的差異，對於氣象的變化與空氣汙染所造成的健康衝擊程度皆會有所不同。因此，本研究的主要目的是以空氣品質不佳之台中市為例，依照該市市民不同性別與不同年齡層來建構呼吸道疾病就醫人次的預測模型，並利用變化情境的方式來探究暴露於過量的空氣汙染濃度與極劇的天氣變化而導致感染呼吸道疾病之風險。本研究共分成兩個階段進行：第一階段是利用逐步迴歸分析法分別找出影響幼年男性、幼年女性、青壯年男性、青壯年女性、老年男性、老年女性等子群呼吸道疾病就醫人次的關鍵氣象與空氣汙染因子；第二階段則是將影響幼年男性、幼年女性、青壯年男性、青壯年女性、老年男性、老年女性等子群就醫人次之關鍵氣象與空氣汙染因子，利用自組性演算法分別建構呼吸道疾病就醫人次的預測模型，並利用建構完成的各就醫人次預測模型進行壓力測試。本研究最後證明了所建構的青壯年男性、青壯年女性、老年男性、老年女性呼吸道疾病就醫人次預測模型正確可行。壓力測試的分析結果則顯示，不論性別，幼年族群主要會因氣溫、非甲烷碳氫化合物下降而導致呼吸道疾病的就醫風險增加；青壯年族群主要會因氣溫下降或懸浮微粒增加而導致呼吸道疾病的就醫風險增加；而老年族群主要會因氣溫下降或臭氧、懸浮微粒增加而導致呼吸道疾病的就醫風險增加。此外，幼年與青壯年男性比女性受到氣象與空氣汙染因子影響而導致感染呼吸道疾病之風險更大。

Since the air pollution and weather can affect the risk of respiratory infection, the environmental pollution and the climate change issues are now concerned by worldwide. Past studies have pointed out that the differences in geographical, age groups and gender affected the extent of causing the risk of respiratory disease which are mainly determined by the changes in meteorological and air pollution. Therefore, the main objective of this study is to utilize Taichung city as a case study to construct various prediction models of respiratory disease outpatient according to gender and age variables. This study also explored the impacts of the excessive air pollution concentration and the dramatic weather changes on the risk of respiratory infections by simulated scenarios. The work of this study is divided into two stages. In the first stage, stepwise regression is utilized to find the key meteorological and air pollutants for male child, female child, young male, young female, elder male, and elder female on respiratory disease outpatient, respectively. In the second stage, GMDH is utilized to construct the prediction models of respiratory disease outpatient using the significant meteorological and air pollution factors obtained in the first stage for male child, female child, young male, young female, elder male, and elder female, respectively. Finally, the prediction models of respiratory disease outpatient are employed to conduct the stress test. The results indicated that the prediction models of respiratory disease outpatient for young male, young female, elder male, and elder female are quite accurate. The scenarios prediction of the stress test showed that the temperature, NMHC decline would increase the risk of respiratory disease for children mainly; temperature drops or PM10 increases would increase the risk of respiratory disease for young people mainly; temperature drops or ozone and PM10 increase would increase the risk of respiratory disease for elder people mainly. Besides, for children and young people, the risk of respiratory disease caused by meteorological and air pollution factor is higher for male than that for female.