摘要
目的:了解内蒙古部分地区高血压的患病现状,从个体及区县水平探讨患病的影响因素。方法:本研究为横断面调查,使用ArcMap 10.2软件绘制疾病空间分布地图,影响因素分析采用χ~2检验、多水平模型。结果:内蒙古中部呼和浩特市回民区和赛罕区患病率均较高,分别为37.4%、30.0%;西部鄂尔多斯市达拉特旗、包头市东河区以及阿拉善盟阿拉善右旗患病率较高,分别为29.1%、26.9%、26.3%;影响因素的多水平模型分析结果显示,个体水平中,年龄、女性(OR=1.182)、超重肥胖(OR=2.280)、其他民族(OR=1.315)、距最近医疗机构>5公里(OR=1.351)是影响高血压患病的独立因素;区县水平中,经济水平(GDP)较高地区高血压患病较严重。结论:内蒙古部分地区高血压患病情况较严重,应重点关注超重肥胖、距医疗机构较远人群,加强对经济较好地区居民的吸烟及体重管理。
Objective：To understand the prevalence of hypertension in some areas of Inner Mongolia,and explore the influencing factors of the disease from individual and district-level.Methods：A cross-sectional study was conducted.ArcMap 10.2 software was used to map the spatial distribution of disease,and the influencing factor analysis adopted the χ~2 test and the multi-level model.Results：The prevalence of hypertension in the part of central and western Inner Mongolia was high.The prevalence rates in the Huimin District and Saihan District of Hohhot,central Inner Mongolia,at 37.4% and 30.0%,respectively;while in the Western Region,the prevalence rates were 29.1%,26.9%,and 26.3% respectively in Dalad Banner,Donghe District,and Alashan Youqi;The multi-level analysis of the influencing factors shows that,age,women（OR=1.182）,overweight and obesity（OR=2.280）,other ethnic groups（OR=1.315）,from the nearest medical institutions 5 km（OR=1.351）in the individual level are independent factor that affects the prevalence of hypertension.At the district/county level,hypertension is more severe in areas with higher levels of GDP.Conclusion：The prevalence of hypertension in some areas of Inner Mongolia is more serious.We should focus on overweight,obesity,and people who are farther away from the nearest medical institution,and strengthen the management of smoking and weight for residents in better-developed regions.
作者
刘丹
王学梅
杜茂林
梁丹艳
王瑞琪
贾璐
南茜
宋瑞儿
张东雪
LIU Dan;WANG Xue-Mei;DU Mao-Lin(Inner Mongolia Medical university,Hohhot 010110 China)
出处
《疾病监测与控制》
2018年第2期85-91,111,共8页
Journal of Diseases Monitor and Control
基金
内蒙古自治区2017年研究生科研创新项目
关键词
高血压
空间分布
多水平模型
影响因素
hypertension
spatial distribution
multi-level model
influencing factors
