摘要
目的探索2019年淄博市各镇(街道)脑卒中报告病例的时空分布特征,为脑卒中防控策略提供参考。方法收集淄博市2019年脑卒中报告病例数据,应用空间自相关分析、圆分布法和扫描统计量探索脑卒中的时空分布特征。结果淄博市2019年脑卒中报告病例共18469例,粗发病率为407.65/10万,其中,男性粗发病率(464.90/10万)高于女性(350.03/10万);随着年龄增长,脑卒中粗发病率呈增长趋势;发病类型以缺血性脑卒中(84.06%)为主;空间上,病例主要分布在沂源县、张店区和淄川区;时间上,病例主要分布在1月至5月初和8月末至11月。结论脑卒中在空间和时间上的分布不同,各疾病预防控制部门可因地制宜,有针对性地加强对脑卒中的预防和干预,以期有效地降低脑卒中的发病率。
Objective To explore the spatio-temporal distribution characteristics of stroke in various towns(subdistricts)in Zibo City in 2019,so as to provide references for the preventive and control strategies.Methods The data of stroke cases in Zibo City in 2019 were collected.The spatial autocorrelation analysis,circular distribution method and scan statistics were used to explore the spatio-temporal distribution characteristics of stroke.Results The total number of stroke cases was 18,469,with a crude incidence rate of 407.65/100,000.The crude incidence rate of men(464.90/100,000)was higher than that of women(350.03/100,000),and showed an increasing trend with the increase of age.The main type of disease was ischemic stroke(84.06%).In terms of space,cases were mainly distributed in Yiyuan County,Zhangdian District and Zichuan District.In terms of time,cases mainly occurred from January to early May and from the end of August to November.Conclusion The distribution of stroke cases is different in space and time.Various disease prevention and control departments can strengthen the prevention and intervention of stroke according to local conditions,so as to effectively reduce the incidence of stroke.
作者
房启迪
杨淑霞
齐畅
程传龙
韩闯
刘盈
崔峰
李秀君
FANG Qidi;YANG Shuxia;QI Chang;CHENG Chuanlong;HAN Chuang;LIU Ying;CUI Feng;LI Xiujun(Department of Biostatistics,School of Public Health,Cheeloo College of Medicine,Shandong University,Jinan 250012,Shandong,China;Zibo Center for Disease Control and Prevention,Zibo 255026,Shandong,China)
出处
《山东大学学报(医学版)》
CAS
北大核心
2022年第2期81-88,共8页
Journal of Shandong University:Health Sciences
基金
国家自然科学基金(81673238)
国家重点研发计划(2019YFC1200500,2019YFC1200502)
关键词
脑卒中
空间自相关
圆分布
扫描统计量
Stroke
Spatial autocorrelation
Circular distribution method
Scan statistics