一般人群健康相关生命质量的预测因素

Predictors of health-related quality of life in the general population

目的应用简明健康状况调查问卷（SF-36）评价中国一般人群的健康相关生命质量（HRQoL），研究其健康相关生命质量的预测因素。方法利用我国江苏、安徽、甘肃、青海、福建、北京、吉林、江西、河南9省市一般人群健康状况横断面现场调查的大样本数据，随机抽取性别、年龄结构与2005年全国1％人口抽样调查样本数据基本一致的8448例，组成代表中国一般人群的样本。通过社会人口学变量以及行为和健康相关特征变量的单因素分析，探讨HRQoL得分与社会人口学特征以及行为和健康相关因素的关系；应用多元逐步回归分析法研究HRQoL的预测因素。结果中国一般人群总体生命质量、生理和心理领域生命质量的得分分别为（78．18±15．88）分、（79．36±17．00）分和（77．00±17．42）分，SF-36各维度得分的变化趋势接近于中国香港地区常模的评价结果。单因素分析显示：HRQoL的减损与性别、年龄、婚姻状况、文化程度、职业、睡眠时间、运动习惯、体质指数、既往慢性疾病史均有关。多元逐步回归分析的结果显示：SF-36各维度有意义的预测因素不同，8个维度前6位有意义的预测因素有12个指标。其中年龄增高、低水平运动、既往慢性疾病史、农民、无职业者、学生、女性、睡眠时间少、体质量过低是HRQoL降低的预测因素，已婚、高文化程度是HRQoL的保护因素。结论年龄、性别、婚姻状况、文化程度、职业、睡眠时间、运动习惯、体质指数和既往慢性疾病史是HRQoL有意义的预测因素。

Objective To evaluate health-related quality of life （HRQoL） in the general population in China and research on the predictive factors of HRQoL by using the short form 36 item （SF-36） questionnaire. Methods Using large sample data of health status cross-section survey from general population of nine provinces and municipalities （Jiangsu, Anhui, Gansu, Qinghai, Fujian, Beijing, Jilin, Jiangxi and He＇ nan） from December 2005 to January 2007,8448 samples in accord with sample data from 1% nationwide population survey in 2005 were randomly selected with sex and age structures, which could representative the general population of China. The relationship between HRQoL score and socio-demographie characteristics, behavior and health-related factors were studied by using variables single factor analysis, and found out the predictive factors of HRQoL by using multiple stepwise regression analysis. Results All sub-scales scores were similar trend of change between Chinese general population and Hong Kong general norm. Single factor analysis showed that the decreasing of HRQoL score was related with sex, age, marital status, education level, occupation, sleep time, exercise habit, body mass index and past history of chronic disease. Multiple stepwise regression analysis showed that there were differences among significant predictive factors of each domain of SF-36 ; in all eight domains, the first six significant predictive factors have twelve indexes. Among them, the predictive factors of age increase, low-level exercises, past history of chronic disease, farmers, inoccupation people, students, women, less sleep time and low weight leaded to the decrement in HRQoL score, married and higher education were protective factors for HRQoL. Conclusion Age, sex, marital status, education level, occupation, sleep time, exercise habit, body mass index and past history of chronic disease were the predictive factors for HRQoL.