高科技職場員工健康促進介入性方案對代謝症候群員工之影響

Effects on Metabolic Syndrome of an Employee Health Promotion Intervention Program in a High-tech Industry

10.3966/207010632013060039002

劉美蘭(Mei-Lan Liu)；陳俊瑜(Chun-Yu Chen)；徐儆暉(Jin-Huei Hsu)

介入性健康促進方案 ； 代謝症候群 ； 健康促進生活型態 ； Health promoting lifestyles ； Health promotion intervention program ； Metabolic syndrome

健康促進與衛生教育學報

39期（2013 / 06 / 01）

27 - 52

繁體中文

本研究的主要目的是在探討於某高科技職場內實施介入性健康促進方案對代謝症候群員工的影響，以內湖科學園區某高科技公司1,300位員工為研究對象，於該公司對僱用勞工實施定期健康檢查時蒐集資料，了解員工健康促進生活型態與代謝症候群的關聯性，總計有效回收問卷共1,100份，回收率達84.6%。之後，再招募有意願參與方案的員工共98位，並依其意願分成實驗組33人與對照組的人，進行介入性健康促進方案之實驗。介入性健康促進方案之執行時間共12週，方案結束後，進行體重、體脂及代謝症候群各項指標追蹤，並分析所得之各項數據，進而推論此介入性健康促進方案對代謝症候群員工的影響情形。依據本研究所提出之研究架構、研究目的，以及調查分析之結果，歸納、整理並提出研究結論如下：一、該高科技職場代謝症候群盛行率為8.6%，且盛行率除了與性別、年齡顯著相關外，與工作職等亦有顯著關聯性。二、對代謝症候群之預測力達到顯著水準的是性別、年齡及健康促進生活型態中的健康責任、社會支持兩面向。三、實驗組實施介入性健康促進方案後，其健康促進生活型態均有改善，且呈顯著差異。四、實驗組實施介入性健康促進方案後，對代謝症候群之各項指標除收縮壓外，其餘各項相關指標均具有改善之效益。

The primary purpose of this study was to explore the effects of implementing health promotion intervention program on metabolic syndrome from in a high-tech industry. Targeting 1300 employees of a high-tech company in Taipei Neihu Technology Park, data was collected during the company's periodic employee health checkups, aiming to understand the correlation and prediction of metabolic syndrome regarding employees' health promoting lifestyles. An experiment of health promotion intervention program was conducted, and 98 employees willing to participate in the experiment were recruited and divided into experimental group and control group based on their inclination. The execution time of the health promotion intervention program totaled twelve weeks; indexes of body weight, body fat, and metabolic syndrome were tracked after the program, and the obtained data were analyzed. Then the effects of health promotion intervention program on employee metabolic syndrome were inferred based on the analysis. Based on the proposed research structure, purpose, and the analytical results of this study, our integrated compilation and induction had led to the conclusions as follows: 1. The rate of metabolic syndrome prevalence in the high-tech industry was 8.6%. The rate of prevalence was not only significantly correlated with gender and age, but also with work grade. 2. The factors that attain significant level of prediction for metabolic syndrome were gender, age, and the two dimensions (health responsibility and social support) within health promoting lifestyles. 3. The entire experimental group experienced improvement on health promoting lifestyles after the health promotion intervention program was implemented, and the variance was significant. 4. After implementing the health promotion intervention program for the experimental group, all the indexes related to metabolic syndrome except systolic pressure were benefited with improvements.

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