空氣污染物與自殺：斷面時序分析

Air Pollutants and Suicide Rate: A Cross-sectional Time Series Analysis

目的：近來的研究發現了空氣污染物與自殺的關係，但先前的研究並未將其他重要的因 子列入考慮。本研究之目的在於以斷面時序分析 (cross-sectional time series analysis) 探討空污 物濃度與自殺的關係，並同時考慮其他重要的因子。 方法：作者收集了台灣 1994-2009 年度 自殺死亡率、社經參數、氣象資料，以及五種空污物濃度二氧化硫 (SO2)，二氧化氮 (NO2)， 臭氧 (O3)，一氧化碳 (CO)，粒徑 10 微米以下之粒狀污染物 (PM10)，然後以斷面時序法分析 上述資料。 結果：隨機效果模式被選為最後模式。它指出無配偶人口是自殺死亡的最顯著的 因素 (z = 4.27, p < 0.001)。PM10 也扮演重要的角色 (z = 2.56, p < 0.05)，而 SO2、NO2、O3、 CO 則不顯著。 結論：結果顯示 PM10 是自殺的可能危險因子。本研究之發現以提供一更長 時期且更寬廣斷面分布，並同時考慮更多潛在的干擾因子而彌補了先前的研究。

Objectives: Recently, studies have shown a positive relationship between air pollutants and suicide. But, the previous studies did not take other significant fac-tors into consideration. The present study was intended to explore the relationship between the air pollutant concentrations and suicide rate by cross-sectional time series analysis considering other significant factors simultaneously. Methods: I gathered the annual suicide rates, socioeconomic parameters, meteorological data, and concentrations of five air pollutants -- sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), particulate matter (PM10) -- in Taiwan during 1994-2009. Then, I did a pooled cross-sectional time series analysis. Results: Random effect model was identified as the final model, indicating the spouseless population having the most significant risk factor for suicide (z = 4.27, p < 0.001). PM10 was also found to play a significant rôle in suicide (z = 2.56, p < 0.05); while SO2, NO2, O3, and CO were found to be nonsignificant. Conclusion: The results identify PM10 as a possible risk factor for suicide. The present findings complement previous studies by providing the viewpoint from a longer aspect as well as a broader cross-sectional distribution, with the consideration of some more potential confounders.