| 张玲,朱立强,伍亚舟,刘宏红,易东.重庆社区居民糖尿病相关危险因素定量评价标准[J].Chinese journal of Epidemiology,2008,29(7):656-660 |
| 重庆社区居民糖尿病相关危险因素定量评价标准 |
| Analysis and quantitative assessment on the risks of diabetes at the community level in Chongqing |
| Received:December 24, 2007 |
| DOI： |
| KeyWord: 糖尿病 危险因素 评估模型 logistic回归分析 |
| English Key Word: Diabetes mellitus Risk factor Appraisal mode Logistic regression |
| FundProject:重庆市科技计划软课题资助项(200706) |
| Author Name | Affiliation | E-mail | | ZHANG Ling | The Department of Health Statistics, the Third Military Medical University, Chongqing 400038, China | | | ZHU Li-qiang | The Department of Health Statistics, the Third Military Medical University, Chongqing 400038, China | | | WU Ya-zhou | The Department of Health Statistics, the Third Military Medical University, Chongqing 400038, China | | | LIU Hong-hon | 沙坪坝区疾病预防控制中心 | | | YI Dong | The Department of Health Statistics, the Third Military Medical University, Chongqing 400038, China | yd_house@hotmail.com |
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| Abstract: |
| 目的 探讨重庆市16岁以上社区居民糖尿病相关危险因素,制定危险因素的定量评价模型,为预测个体糖尿病的患病危险奠定基础。方法 采用病例对照研究的方法,从重庆市沙坪坝、 小龙坎、天星桥、渝碚路、磁器口 5个社区中以1:2的比例抽取糖尿病患者1981例,健康人群3962例 进行回顾性柯查,利用logistic回归方法分析,得出各危险因素与糖尿病的OR值,运用统计模型将不 同暴露水平的危险因素转化成危险分数。结果 得到不同性别、年龄、行为、疾病以及家族史的个体 在不同情况下的危险分数,男性为高脂血症史(14.995)、冠心病(6.689)、高血压家族史(4.005)、吸烟 (3.111)等13个危险因素进人主效应模型;女性为高脂血症史(12.426)、高血压家族史(3.986)、脑卒 中史(2.714)、嗜甜食(1.244)等15个危险因素。根据个体情况得到组合危险分数,从而预测该个体 的糖尿病发病危险。结论 改变不良的生活方式以及个人疾病的积极治疗和控制,能有效降低糖尿 病的发病率;而根据危险因素建立的危险分数评估模型是健康教育的有力依据,也是当前开展社区卫 生服务的重要方法。 |
| English Abstract: |
| Objective To investigate the correlation risk factors of diabetes over 16-year-olds at the community level in Chongqing and to set a quantitative criteria for determining risk for diabetes and to identify persons having potential risk. Methods 1981 cases with 1:2 matched controls were chosen from five communities in Chongqing including Shapingba，Xiaolongkan，Tianxingqiao，Yubei Road, Ciqikou，which were interviewed with a uniformed questionnaire. The risk factors of diabetes mellitus were analyzed with logistic regression, and to calculate the odds ratios of risk factors for diabetes. Different levels of risk exposure factors were converted into a risk scores, using statistical models. Results An individual health risk appraisal model of diabetes was established, applicable to individuals of different sex, age, health behavior,disease,and family history, for men，13 risk factors including hyperlipidemia (14. 995), coronary heart disease (6.689)，family history of hypertension (4.005)，smoking (3.111) etc. while for women， hyperlipidemia (12.426),family history of hypertension (3.986),stroke (2.714)，liking sweets (1.244), about 15 risk factors, were entering the main effect model. The related risk scores were added to obtain a combined risk score to predict the individual’s risk of diabetes in the future. Conclusion The incidence of diabetes could be effectively reduced by changing the unhealthy lifestyle and curing the patient with the disease. Evidence was provided to persuade people change their unhealthy lifestyles and behaviors through health education. The results could also be used in community to improve their health services. |
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