代謝症候群患者與一般民眾生活品質預測因子之探討

A Comparison of Life Quality between Patients with and without Metabolic Syndrome

10.6142/VGHN.29.2.187

劉嘉瑋(Chia-Wei Liu)；馬維芬(Wei-Fen Ma)；周守民(Shieu-Ming Chou)；陳清助(Ching-Chu Chen)；劉秋松(Chiu-Shong Liu)

代謝症候群 ； 健康促進生活型態 ； 生活品質 ； metabolic syndrome ； health promotion lifestyle ； quality of life

榮總護理

29卷2期（2012 / 06 / 01）

187 - 197

繁體中文

代謝症候群患者生活品質直接影響其尋求健康行為的維護，文獻中卻缺少對其生活品質影響因子的了解，而無法針對病人需求提供適當介入性措施。本研究目的在探討並比較代謝症候群患者與一般民眾的生活品質之預測因子之差異。採橫斷性研究設計，以立意取樣，在中部某醫學中心家醫科門診進行收案，採結構式問卷與直接儀器測量來收集資料，含自編式的基本資料與生理代謝表現表、健康促進生活型態中文簡式量表及臺灣版世界衛生組織生活品質問卷，以SPSS19.0版統計軟體進行統計與分析。結果共收案182位，代謝症候群患者與一般民眾各91人。代謝症候群患者生活品質得分較一般民眾低（t= 5.208, p=.026）。自我實現、人際支持、身體質量指數及年齡等四個變項為代謝症候群患者生活品質有意義的預測因子，能共同解釋代謝症候群者整體生活品質變異量為73.4%；壓力管理、營養、運動、身體質量指數、舒張壓及教育程度為有可預測一般民眾的生活品質之因子。代謝症候群患者與一般民眾在生活品質的預測上有明顯之差異，研究結果可協助醫療人員在提供照護時，針對代謝症候群患者與一般民眾要有不同之健康資訊，以利改善其生活品質。

Background: For patients with metabolic syndrome, seeking health behaviors are influenced by individuals' perceived quality of life. However, fewer studies in literature focused on predictors of quality of life for people with metabolic syndrome. Therefore, nurses cannot provide suitable intervention strategies to help those patients with metabolic syndrome based on their needs. Purpose: The purpose of this study was to explore and compare the factors that influenced quality of life between general populations and patients with metabolic syndrome. Methods: A cross-sectional design with purposive sampling was used for this study. Study samples were recruited from family medicine clinics at a medical center in Taichung, Taiwan. Structured questionnaire and direct objective measures were used to collect data, including Demographic Inventory, Metabolic Parameters Scale, Health Promotion Lifestyle Scale, and WHOQOL- Brief. Statistics were performed using SPSS 19.0. Results: A total of 182 people (91 general populations and 91 patients with metabolic syndrome) were recruited. Results showed that the average score of Quality Lifestyle Scale for patients with metabolic syndrome was lower than that for the general populations (t= 5.208, p=.026). A variance of 73.4% explained that self-actualization, interpersonal support, body mass index, and age were significant predictors in predicting the quality of life for people with metabolic syndrome. In addition, stress management, nutrition, exercise, body mass index, diastolic pressure, and education levels were significant factors in predicting the quality of life for the general populations. Conclusions/Implications for practice: Findings of this study may facilitate medical staff's understanding of the factors that influenced quality of life for people with metabolic syndrome versus those in the general populations. This enabled medical staff to provide different interventions for improving the patients' quality of life.