中老年人血压变化轨迹与冠心病发病的关系
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  • 英文篇名:Association between trajectory of blood pressure and risk of coronary heart disease in middle aged and elderly population
  • 作者:林伟强 ; 王春霞 ; 李明卓 ; 孙秀彬 ; 刘言训 ; 薛付忠 ; 袁中尚
  • 英文作者:LIN Weiqiang;WANG Chunxia;LI Mingzhuo;SUN Xiubin;LIU Yanxun;XUE Fuzhong;YUAN Zhongshang;Department of Biostatistics, School of Public Health, Shandong University;Cheeloo Research Center for Biomedical Big Data, Shandong University;Health Management Center of Affiliated Hospital of Jining Medical University;
  • 关键词:血压 ; 冠心病 ; 群组化轨迹模型 ; Cox比例风险模型 ; 队列
  • 英文关键词:Blood pressure;;Coronary heart disease;;Group-based trajectory model;;Cox proportional hazard regression;;Cohort
  • 中文刊名:SDYB
  • 英文刊名:Journal of Shandong University(Health Sciences)
  • 机构:山东大学公共卫生学院生物统计学系;山东大学齐鲁生物医学大数据研究中心;济宁医学院附属医院健康管理中心;
  • 出版日期:2019-03-26 18:25
  • 出版单位:山东大学学报(医学版)
  • 年:2019
  • 期:v.57;No.320
  • 基金:国家自然科学基金(81673272,81872712,81573259);; 山东大学青年学者未来计划(2016WLJH23)
  • 语种:中文;
  • 页:SDYB201904020
  • 页数:7
  • CN:04
  • ISSN:37-1390/R
  • 分类号:112-118
摘要
目的探索血压随年龄变化的轨迹与冠心病发病的关系。方法以健康体检纵向数据管理队列为基础,应用群组化轨迹模型(GBTM)分别建立研究对象的收缩压和舒张压血压变化轨迹发展模型,依据其轨迹发展模型分别对收缩压和舒张压两个子队列人群进行轨迹分组;进而应用Cox回归模型分析子队列中不同轨迹变化组与冠心病发生的关联。结果收缩压和舒张压子队列分别包含1 215例和1 345例,随访期间两个子队列分别新发冠心病78例和86例。根据GBTM轨迹发展模型,可将收缩压子队列分为收缩压低水平上升组、中水平上升组和高水平快速上升组;舒张压子队列可分为舒张压低水平下降组和高水平下降组。对收缩压子队列和舒张压子队列分别进行Cox回归分析显示,调整可能的混杂因素(年龄、性别、收缩压、舒张压、吸烟、饮酒、体质量指数、空腹血糖、第1年体检、血脂异常等)后,收缩压子队列中,收缩压高水平快速上升组的冠心病发病风险是低水平上升组的冠心病发病风险的2.23倍(95%CI:1.13~4.40);舒张压子队列中,舒张压高水平下降组的冠心病发病风险是低水平下降组冠心病发病风险的0.96倍(95%CI:0.54~1.71)。进一步调整基线收缩压和舒张压水平后,收缩压子队列中,收缩压高水平快速上升组的冠心病发病风险是低水平上升组的冠心病发病风险的3.19倍(95%CI:1.31~7.80);舒张压子队列中,舒张压高水平下降组的冠心病发病风险是低水平下降组冠心病发病风险的1.04倍(95%CI:0.56~1.93)。而舒张压高水平下降组和低水平下降组组间冠心病发病水平差异无统计学意义(HR=1.03,95%CI:0.56~1.89)。结论血压水平随年龄的变化轨迹与冠心病发生有关,且不受包含基线血压水平在内的其他代谢因素的影响。
        Objective To investigate the relationship between trajectory of blood pressure and the incidence of coronary heart disease(CHD). Methods Based on the longitudinal data from health management cohort, the trajectories of systolic blood pressure(SBP) and diastolic blood pressure(DBP) were constructed with the group-based trajectory model(GBTM). After that, the subjects were classified according to the trajectories of SBP and DBP. The association between CHD risk and trajectories of blood pressure was analyzed with Cox regression model. Results The subcohorts of SBP and DBP included 1 215 and 1 345 participants, respectively, with 78 and 86 new CHD cases during the follow-up. The subcohort of SBP was divided into low-growth, intermediate-growth and high-growth groups. The subcohort of DBP was divided into low-drop and high-drop groups. Cox regression was again used to investigate the association between the trajectories and CHD risk, and the confounding factors were adjusted, including age, gender, SBP, DBP, smoking, drinking, body mass index(BMI), fasting plasma glucose(FPG), first-year medical examination and dyslipidemia. For the SBP subcohort, the CHD risk of the high-growth group was 2.23 times of that of the low-growth group(95%CI: 1.13-4.40). For the DBP subcohort, the CHD risk of the high-drop group was 0.96 times of that of the low-drop group(95%CI: 0.54-1.71). When the baseline SBP and DBP levels were further adjusted, for the SBP subcohort, the CHD risk of the high-growth group was 3.19 times of that of the low-growth group(95%CI: 1.31-7.80); for the DBP subcohort, the CHD risk of the high-drop group was 1.04 times of that of the low-drop group(95%CI: 0.56-1.93). There was no statistically significant difference between the two DBP groups(HR=1.03, 95%CI: 0.56-1.89). Conclusion The longitudinal trajectory of blood pressure is related to CHD risk, and such relation is independent of other metabolic factors such as baseline blood pressure level.
引文
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