陆隽文, 姚雪梅, 钟若诗, 王小兰, 郭慧宁, 谢大明, 汪颖霞, 张鹏, 王婷婷. 上海社区老年人脑卒中患病风险的病例对照研究[J]. 上海预防医学, 2023, 35(2): 137-141. DOI: 10.19428/j.cnki.sjpm.2023.22319
引用本文: 陆隽文, 姚雪梅, 钟若诗, 王小兰, 郭慧宁, 谢大明, 汪颖霞, 张鹏, 王婷婷. 上海社区老年人脑卒中患病风险的病例对照研究[J]. 上海预防医学, 2023, 35(2): 137-141. DOI: 10.19428/j.cnki.sjpm.2023.22319
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LU Junwen, YAO Xuemei, ZHONG Ruoshi, WANG Xiaolan, GUO Huining, XIE Daming, WANG Yingxia, ZHANG Peng, WANG Tingting. A case-control study on the risk of stroke in the elderly in Shanghai community[J]. Shanghai Journal of Preventive Medicine, 2023, 35(2): 137-141. DOI: 10.19428/j.cnki.sjpm.2023.22319
Citation: LU Junwen, YAO Xuemei, ZHONG Ruoshi, WANG Xiaolan, GUO Huining, XIE Daming, WANG Yingxia, ZHANG Peng, WANG Tingting. A case-control study on the risk of stroke in the elderly in Shanghai community[J]. Shanghai Journal of Preventive Medicine, 2023, 35(2): 137-141. DOI: 10.19428/j.cnki.sjpm.2023.22319
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上海社区老年人脑卒中患病风险的病例对照研究

A case-control study on the risk of stroke in the elderly in Shanghai community

    摘要
  • 摘要:
    目的 探究脑卒中患病危险因素，为预防脑卒中的发生和进行健康管理提供参考依据。
    方法 2022年2月—2022年3月，以随机抽样法选取上海4个社区患有脑卒中、年龄≥60岁社区居民为病例组（n=100），并选取非脑卒中居民为对照组（n=100）。以调查问卷形式记录并比较所有研究对象的年龄、体重指数（BMI）、血脂及血压相关指标、家族史、生活习惯、情绪与睡眠情况等。经受试者工作特征（ROC）曲线分析预测上海社区老年人脑卒中患病的价值。采用logistic模型分析脑卒中发病的影响因素。
    结果 病例组BMI、高血压、心脏病、糖尿病、短暂性脑缺血发作（TIA）、血脂异常、脑卒中家族史、吸烟、运动缺乏或仅轻体力劳动、收缩压（SBP）、舒张压（DBP）、三酰甘油（TG）水平显著高于对照组（均P<0.05），HDL⁃C水平明显低于对照组（P<0.05）。经ROC分析BMI、SBP、DBP、TG、高密度脂蛋白胆固醇（HDL⁃C）预测脑卒中患病有意义（均P<0.05）。Logistic回归分析结果显示BMI≥23.820 kg·m-2、心脏病、糖尿病、TIA、血脂异常、脑卒中家族史、吸烟、运动缺乏或仅轻体力劳动、SBP≥139.535 mmHg、DBP≥89.605 mmHg、TG≥1.565 mmol·L-1、HDL⁃C≤1.105 mmol·L-1是脑卒中患病的危险因素（均P<0.05）。
    结论 包括血脂及血压等相关指标的身体健康状况与部分病症家族史、生活习惯等可能是上海社区老年人脑卒中患病的重要危险因素。针对以上因素采取预防干预措施具有重要的临床意义。

     

    Abstract:
    Objective To explore the risk factors of stroke， and to provide reference for the prevention and health management of stroke.
    Methods From February 2022 to March 2022， four community residents over 60 years old with stroke in Shanghai were randomly selected as the case group （n=100）， and non-stroke residents were selected as the control group （n=100）. The survey was in the form of questionnaires to record and compare the age， body mass index （BMI）， blood lipids， blood pressure-related indicators， family history of other diseases， living habits， mood and sleep conditions of all subjects. The value of predicting the incidence of stroke among the elderly in Shanghai community was analyzed by receiver operating characteristic （ROC）， and the influencing factors of stroke were analyzed by logistic model.
    Results BMI， hypertension， heart disease， diabetes， transient ischemic attack （TIA）， dyslipidemia， family history of stroke， smoking， lack of exercise or only light physical labor， SBP， DBP， TG levels were significantly higher in the case group （P<0.05）. The level of HDL-C was significantly lower than that in the control group （P<0.05）. BMI， SBP， DBP， TG， HDL-C predicted the incidence of stroke by ROC analysis （P<0.05）. Logistic regression analysis showed that BMI≥23.820 kg·m-2， heart disease， diabetes， TIA， dyslipidemia， family history of stroke， smoking， lack of exercise or only light physical labor， SBP≥139.535 mmHg， DBP≥89.605 mmHg， TG≥1.565 mmol·L-1 and HDL-C≤1.105 mmol·L-1 were risk factors for stroke （P<0.05）.
    Conclusion Physical health status including blood lipids and blood pressure， family history of certain diseases， and living habits could be important risk factors for stroke in the elderly in Shanghai community. Preventive intervention measures for the above factors have important clinical significance.

     

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