工作壓力與健康之研究： 1. 工作相關因子與心血管疾病風險研究：教育程度的角色 2. 軟體工程師的睡眠對疲勞與生活品質影響之研究

Abstract

1. 工作相關因子與心血管疾病風險研究：教育程度的角色 心血管疾病是台灣地區重要的死亡原因之一，已知的危險因子只能解釋30-40%的疾病，近來研究顯示工作壓力與心血管疾病可能有關，但之間的關係仍不清楚。本研究為橫斷性研究，探討工作相關因子與心血管疾病的關係。我們收集239名參加醫院健檢男性之理學及生化檢查值，以問卷測量工作中活動量、輪班、工時、工作類別、睡眠品質等資料，另以「Need for Recovery Scale」衡量疲勞程度。Framingham Risk Score (FRS) 被廣泛使用在冠狀動脈心臟病的風險評估，所以本研究依照FRS將個案分為心血管疾病低危險群 (10Year CHD Risk <5%) 及高危險群 (Risk >5%)。另外，社經地位為重要的心血管疾病危險因子，所以將個案依教育程度分為低學歷組(高中以下)及高學歷組(大專以上)。分析發現 : 在工作類別部分，以管理專業階層為對照組，高學歷組中白領階級及自營業具有較高的心血管疾病危險對比值，低學歷組則相反 ; 而在工時部份，低學歷組中高危險群之工時高於低危險群，高學歷組中則相反。此外，疲勞程度及睡眠品質在兩組間亦有差異。研究結果顯示心血管疾病與工作型態之相關受到社經地位的影響，要釐清工作相關因子與心血管疾病的關係需要進一步研究。 2. 軟體工程師的睡眠對疲勞與生活品質影響之研究 軟體工程師是一群具有高學歷、高專業技能的專業人員，會努力工作以反映個人價值，對工作過度投入並注重績效，同時享受工作帶來的成就感，但也因此經常超時工作，犧牲個人的休息及睡眠，其工作特性，不容易以工時來界定或探討，睡眠可能比較能反映其工作壓力，過去研究指出睡眠時數與生活品質有關，工時比較無關。工作壓力可導致疲勞並影響生活品質，本研究進一步探討工時、睡眠品質對軟體工程師疲勞程度與生活品質之影響，以橫斷式研究，針對239名某高科技公司軟體工程師 (男性佔73%，平均年齡32歲，70%未婚) 進行問卷調查研究。睡眠品質以匹茲堡睡眠品質量表指標 (Pittsburgh Sleep Quality Index) 測量，包括主觀的睡眠品質、睡眠潛伏期、睡眠困擾、白天功能及使用安眠藥等，工作疲勞程度以疲勞恢復問卷 (Need for Recovery) 中文版問卷進行評估，生活品質採用台灣版世界衛生組織生活品質問卷 (WHOQOL-BREF) 進行研究。結果發現，員工平均每週工作時間為48.4小時，工作日平均睡眠時間6.6小時，休假日平均睡眠時間8.5小時，疲勞程度平均分數為41分，男性員工在生活品質生理、心理、社會關係及環境四大範疇平均得分為13.8+/-1.8, 12.8+/-2.1, 13.5+/-1.8 和 13.5+/-1.6；女性員工為14.4+/-2.1, 13.3+/-2.2, 13.6+/-2.1 和 13.6+/-2.0。睡眠品質指標越差(主觀感覺較差、睡眠潛伏期長、有睡眠困擾、會影響白天功能及有使用安眠藥)，則疲勞程度顯著較高，而生活品質在不同性別及範疇(社會及環境範疇較不一致)分數均顯著較低，工時則與疲勞程度及生活品質較無相關。研究結果顯示對軟體工程師而言，尤其是女性，睡眠比工時更能夠反應工作壓力及其影響，不過限於研究對象人數較少，工作、睡眠、疲勞程度與生活品質之間的複雜關係需要進一步研究。

1. Education as a possible modifying factor on the relationship between work-related factors and cardiovascular risk The association between cardiovascular diseases (CVD) and work-related factors has been studied with inconsistent results. We conducted a cross-sectional study to further investigate the relationship between several work-related factors and cardiovascular risk. A total of 239 men who received health examination in one medical center were enrolled and their basic data, physical examination results and biochemical values were collected. We used questionnaires to measure work-related factors including occupational categories, work hours, activity at work and sleep quality. We divided our subjects into low (10 Year CHD Risk<5%) and high (>5%) risk groups by Framingham Risk Score (FRS), which has been used to represent the risk of coronary heart disease. Since socioeconomic status (SES) is an important risk factor for CVD, the analysis on the association between cardiovascular risk and work-related factors was further stratified by the variable of education. In the high education group, white collar workers had higher cardiovascular risk than managers/professionals (OR=3.2, p<0.05), while the self-employed workers did not have higher OR. In the low education group, OR for cardiovascular risk were lower for all job categories as compared to managers/professionals. High risk group had longer work hours than low risk group in the low education group, while the trend was opposite in the high education group. Further, the cardiovascular risk for activity at work and sleep quality were different between high and low education groups. Our results suggest the relationship between work-related factors and CVD may be modified by education level. 2. Association of Sleep with Fatigue and Quality of Life in Software Engineers Software engineers are knowledge workers of professional skills with high education level. They are over-commitment to work and put their leisure and sleep time to work. The work characteristic of software engineers is not easy to be investigated only by working time. Sleep seems a better indicator to reflect work stress. Work stress can lead to fatigue and influence quality of life (QOL). Previous studies have indicated sleeping hours is related to QOL. To investigate the impact of sleep quality on fatigue status and QOL in software engineers, we conducted a cross-sectional study on 239 workers (male workers：73%, average age：32 years old, 70% single) in an information-technology (IT) company. The psychophysical outcome of fatigue status was assessed using the Need for Recovery questionnaire (NFR). Quality of sleep was directly asked using the indicators of Pittsburgh Sleep Quality Index (PSQI) including subjective sleep quality, sleep latency, sleep disturbance, use of sleep medication, day-time dysfunction and sleep duration. QOL was estimated by World Health Organization quality of life instrument (WHOQOL-BREF). Results revealed sleep quality was significantly related with fatigue status and QOL. Poor sleep quality was associated with high fatigue status and low QOL scores. Working time was weak related to fatigue and QOL. Our findings suggest that work hours and sleep quality representing work stress were associated with the fatigue status and QOL of software engineers. Sleep quality may be a better indicator for work stress and its influence than working time. To maintain the lower fatigue status and higher quality of life, it may be necessary to monitor their sleep quality in addition to their working time. Further studies are needed to clarify the relationships of work stress, work hours, sleep, fatigue and QOL.