目標：工作者的身心健康問題除了影響工作表現，還可能導致病假、抱病上班等「健康生產力減損」的後果，影響企業的營運效能。本研究運用職場員工「減效出席」（presenteeism）現象（指身心負荷過重或有症狀/疾病，卻仍勉強上班）和病假天數，建立「潛在健康生產力損失模型」（potential health-related productivity loss model），估算企業因員工健康問題所損失的人力成本，並分析影響因素。方法：資料來源為某健診機構企業健檢客戶在2017年2月至9月間收集的326份問卷，另納入政府勞動統計數據估算潛在健康生產力損失經濟價值。結果：在各種身心症狀中，感冒、頭痛、肌肉骨骼、消化、皮膚、情緒、睡眠問題和減效出席關聯性較高，有無這些症狀者健康生產力損失也有顯著差異。在納入主計處報告的薪資和工時參數後，換算調查對象之潛在健康生產力損失平均為2,038.84元/月。多元線性迴歸分析顯示，職場員工的年齡、工作個人生活衝突、疾病和身心不適症狀數量，和潛在健康生產力損失經濟價值有正向關係。結論：藉由本研究建立的推估模型，可成為健康促進介入方案投入/成效的評估指標，另對於因健康和壓力問題造成的減效出席風險因素，也提供企業做為提供職業健康服務的實證依據，作為職場健康問題改善優先次序的參考。
Objectives: Workers' physical and mental health problems negatively affect their work performance as well as their employers' daily business operations; coming to work sick lowers productivity and sick leave increases labor costs. In this article, we establish a “potential healthrelated productivity loss model” that uses the concept of “presenteeism” (the psychological tendency to feel obligated to be present at work despite experiencing physical or psychological stress overload or suffering from symptoms of an illness) and days of sick leave to estimate labor costs incurred by a company because of employee health conditions and analyze influencing factors. Methods: Data were obtained from 326 questionnaires collected by corporate health check clients of a health management institution between February and September 2017. Government labor statistics were also included in the model and were used together with questionnaire data to estimate potential health productivity losses. Results: Close correlations were identified between sickness presenteeism and symptoms of physical/psychological discomfort related to common colds; headaches; musculoskeletal conditions; digestive disorders; and skin, mood, and sleep problems. Potential health productivity loss was significant among workers with these symptoms compared with the productivity of workers without these health conditions. After including the salary and working hour parameters reported by the Taiwan Directorate General of Budget, Accounting and Statistics, the mean potential health productivity loss of the survey respondents was calculated to be NT$2,038.84 per month. The results of the multiple linear regression analysis indicated that employees' age, degree of work and life conflict, and number of illnesses and physical/mental symptoms were positively related to the monetary value of potential health productivity loss. Conclusions: The estimation model established in this study can be used as an indicator to evaluate the cost/benefit of workplace health promotion intervention programs, and empirical evidence concerning presenteeism-related risk factors can encourage companies to provide occupational health services and prioritize health promotion.