研究背景與目的
慢性腎臟病是臺灣重要慢性疾病之一，也是我國疾病負擔第一名。在2018年因腎臟疾病就醫人數達36萬4,000人，需要接受腹膜透析或血液透析治療人數更高達到9萬人，其中接受透析患者中有一半為工作年齡，65歲以下。過去研究指出在工作年齡期間接受透析治療，工作容易產生變動甚至離開職場。美國研究顯示若勞動人口若接受透析，其失業率是一般族群的7倍，約有38%慢性腎病病患者在透析前就已經處於無業狀態，在進入透析後相較於透析前有受僱者，透析前無就業者其透析後失業率和死亡率較高。當患者進入透析治療造成勞動變動是無可避免，改善和維持患者勞動狀態才是重要問題。因此，本研究目的主要想了解我國透析前一年有受僱工作者進入透析前後勞動變動與無透析患者之差異以及探討影響因透析前有受僱透析者轉變為無業或死亡的風險因素。
研究方法
本研究使用衛生福利部全民健康保險資料庫和勞動部勞工保險資料庫兩大資料庫進行研究分析。透析樣本部分是以2006-2010年25歲到64歲患有慢性腎病且新接受透析個案為透析樣本母體共14,609人，由母體中挑選出在透析前一年有工作者為透析樣本共3,320人。針對透析樣本與前一年同樣有受僱工作之對照樣本以性別、年齡、都市化程度為條件以1：1之頻率配對進行匹配，最終研究樣本共6,640人。追蹤期間為透析前一年至透析開始後追蹤五年，本研究期間為2005/1/1至2015/12/31。研究設計共分為兩部分，第一部份探討透析組與對照組差異。使用描述性統計分析分別描述受僱透析樣本與對照樣本之基本特性分布情形以百分比、平均數、標準差呈現，連續變項以獨立T檢定進行分析，若為類別變項則以卡方檢定進行分析，並估算勞動變動情形與各行業別工作年數損失、存活年數損失。第二部分針對透析樣本使用Cox回歸模型分別探討透析前不同行業進入透析後轉變為死亡、無業風險。使用SAS 9.4統計軟體進行分析、Tableau Public 2020.2繪圖。
研究結果
男性透析樣本追蹤五年離開受僱工作比例是對照樣本3.4倍，女性透析樣本追蹤五年離開受僱工作比例是對照樣本2.8倍。整體上，透析樣本追蹤五年平均存活時間較對照樣本少5個月。在死亡風險因素探討發現年齡較大55-64、男性、居住在東部、CCI共病指數>=3死亡風險為較高。在無業風險因素部分以年齡為55-64、性別男性、投保薪資較低(低於20,000元)、CCI共病指數>=3、電力及燃氣供應業、支援服務業、製造業、運輸及倉儲業、醫療保健及社會工作服務業、批發及零售業轉變為無業風險較高。
研究結論
整體上，透析樣本追蹤五年平均存活時間較對照樣本少5個月，而工作年數損失約3年，很大比例轉向無業離開勞動市場。因轉變為無業而離開勞動市場以年齡較大、性別為男性、共病問題較嚴重、社經地位較低如：低投保金額、高工時或高勞動力行業別等風險較高。本研究針對我國各行業別進行分析透析患者離開勞動市場因素，並比較各行業別間差異，希望藉由研究結果可提供政府一個政策之方向，以改善高工時高勞動力行業之勞動條件，並給予透析勞工或健康狀況不佳勞工一個友善工作環境。

關鍵字：透析、末期腎臟病、存活分析、工作年數、勞動狀態

Chronic kidney disease is one of the major chronic diseases in Taiwan The nearly half chronic kidney disease patient incident dialysis in working age. In working-age people with dialysis will be employment status changes, even exit from paid employment. This study examines the dialysis people and the nondialysis people's change of employment status before and after dialysis, risk factors for unempolyed, death, and their association with industrial. This study uses National health insurance and Labor insurance from 2006 to 2015, selected 3,320 patients between the ages of 25 and 64 years old with incident dialysis and 1:1 ratio matching control samples. This study estimated the loss of paid employment working life expectancy and loss of life expectancy and risk factors for job loss, death, and their association with industrial about dialysis samples by Cox proportional hazard model. Compared with samples who were nondialysis, dialysis loss 1.54 years of paid employment working year and loss 5 months survey year. This study findings male sex, age 55 to 64, lower payroll bracket, higher CCI, hight working time and hight physical work were significantly associated with the risk of changing to an unemployed. This study assessed dialysis and the nondialysis’s change of employment status, risk factors for unempolyed, death, and their association with industrial. That can provide the government to take as a reference and improve and maintain the working environment for the employee with dialysis.

Key words: Dialysis, End-Stage Renal Disease, Survival Analysis, Working Life Expectancy, Employed Status

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