北京大学学报(医学版) ›› 2016, Vol. 48 ›› Issue (3): 478-482. doi: 10.3969/j.issn.1671-167X.2016.03.018

• 论著 • 上一篇    下一篇

城镇化水平与慢性病及健康相关行为的关联分析

刘国峰1,孙美平1,王智勇2,简伟研1△   

  1. (1.北京大学公共卫生学院卫生政策与管理系,北京100191; 2. 中国社会科学院人口与劳动经济研究所,北京100028)
  • 出版日期:2016-06-18 发布日期:2016-06-18
  • 通讯作者: 简伟研 E-mail:jianweiyan@bjmu.edu.cn

Association analysis between urbanization and non-communicable diseases and health-related behavior

LIU Guo-feng1, SUN Mei-ping1, WANG Zhi-yong2, JIAN Wei-yan1△   

  1. (1.Department of Health Policy and Management, Peking University School of Public Health, Beijing 100191, China; 2. The Institute of Population and Labor Economics, Chinese Academy of Social Sciences, Beijing 100028,China)
  • Online:2016-06-18 Published:2016-06-18
  • Contact: JIAN Wei-yan E-mail:jianweiyan@bjmu.edu.cn

摘要:

目的:探究中国不同城镇化水平与慢性病的关系,为城镇化过程中相关卫生政策的设计提供依据。方法: 通过2011年中国健康与养老追踪调查(China Health and Retirement Longitudinal Study, CHARLS)获得健康相关数据,利用多阶段抽样方法,调查覆盖150个区县,样本有全国代表性;利用地理信息系统(geoinformation system, GIS)方法计算出各个地区面积,结合第六次人口普查数据计算出各个地区的人口密度作为城镇化水平的代理变量。采用Logistic模型分析不同城镇化水平对高血压、糖尿病、吸烟、饮酒、超重、肥胖的影响。结果: 上海市、深圳市城镇化水平最高,人口密度超过3 000人/平方公里。整体而言,中国西北地区的城镇化水平明显低于东南地区,沿海地区的城镇化水平普遍高于内陆地区。高血压患病率随着城镇化水平的提高而增加,但是差异无统计学意义。糖尿病患病率呈现先上升后下降的趋势。饮酒率、超重率和肥胖率在城镇化水平较低时呈上升趋势,之后经历下降过程,拐点数值分别依次是737、1 186、1 353人/平方公里;而人群吸烟率经历先下降后上升的变化,拐点为1 029人/平方公里。结论: 不同城镇化水平对慢性病患病率、健康相关行为及超重、肥胖的影响不同。城镇化水平较低时可能对健康产生负向影响,而较高水平时可能由于卫生服务可及性、环境改善等原因又会提高居民的健康状况。决策者在城镇化水平的不同时期要侧重关注居民的不同健康问题,包括环境污染的影响、卫生资源配置、卫生服务可及性等,尽量减少或者避免城镇化对慢性病的负面影响,以应对慢性病带来的威胁。

关键词: 都市化, 慢性病, 健康知识, 态度, 实践, 中国

Abstract:

Objective: To explore the association between different urbanization levels and non-communicable diseases (NCDs) in China and provide suggestions on designing relevant health policies in the urbanization process. Methods: We obtained health-related data from China Health and Retirement Longitudinal Study (CHARLS) 2011. This study used multistage sampling in design stage and covered 150 districts/counties, representative at the levels of the country. Geo-information system (GIS) method was used to get district areas data, and in combination with the Sixth National Census population data, we computed the population density which was regarded as the proxy variable of urbanization level in every city. The Logistic model was used to explore the effect of urbanization level on hypertension, diabetes, smoking, drinking, overweight and obesity.  Results: Compared with other cities in China, Shanghai and Shenzhen, with the population density of more than 3 000 people per km2, were the cities with highest urbanization level. From the map of urbanization distribution across China, it was found that the urbanization levels of the northwestern districts were lower than those of the southeastern and coastal districts. The hypertension rate increased with the development of urbanization but there was no statistical significance. The proportion of patients with diabetes went up first and then saw a decrease trend in the process of urbanization. Drinking rate, overweight rate and obesity rate had similar trends, falling to their lowest point when urbanization level equaled 737,1 186 and 1 353 people per km2 respectively and then ex-perienced upward trends. By contrast, smoking rate declined first and then went up (the turning point was 1 029 people per km2). Conclusion: Different urbanization levels have different effects on NCDs, health-related behavior, overweight and obesity. Low urbanization level may create negative impact on health while high level can pose positive effect and increase people’s health condition possibly due to the improvement of health care accessibility and the quality of living environment. Policy-makers should specially focus on different residents’health problems in different periods of urbanization, such as the impact of environmental pollution, health resources’ allocation and accessibility of health services. It is necessary to reduce or avoid the negative effect of urbanization on NCDs during the local development process to face the NCDs’ threat.

Key words: Urbanization, Chronic disease, Health knowledge, attitudes, practice, China

中图分类号: 

  • R19
[1] 靖婷,江华,李婷,申倩倩,叶兰,曾银丹,梁文欣,冯罡,司徒文佑,张玉梅. 中国西部5城市中老年人血清25羟基维生素D与握力的相关性[J]. 北京大学学报(医学版), 2024, 56(3): 448-455.
[2] 王清波,傅虹桥. 中国卫生筹资转型的主要特征与历史沿革[J]. 北京大学学报(医学版), 2024, 56(3): 462-470.
[3] 闫晓晋,刘云飞,马宁,党佳佳,张京舒,钟盼亮,胡佩瑾,宋逸,马军. 《中国儿童发展纲要(2011-2020年)》实施期间中小学生营养不良率变化及其政策效应分析[J]. 北京大学学报(医学版), 2023, 55(4): 593-599.
[4] 祝春素,连至炜,崔一民. 中国中老年人抑郁和慢性病的关联[J]. 北京大学学报(医学版), 2023, 55(4): 606-611.
[5] 王婷,李乔晟,刘皓冉,简伟研. 人格特征、城乡差异与抑郁症状变化的关系[J]. 北京大学学报(医学版), 2023, 55(3): 385-391.
[6] 邓佳慧,黄筱琳,刘晓星,孙杰,陆林. 中国睡眠医学的过去、现在和未来[J]. 北京大学学报(医学版), 2023, 55(3): 567-封三.
[7] 曹瑞洁,姚中强,焦朋清,崔立刚. 不同分类标准对中国大动脉炎的诊断效能比较[J]. 北京大学学报(医学版), 2022, 54(6): 1128-1133.
[8] 梁喆,范芳芳,张岩,秦献辉,李建平,霍勇. 中国高血压人群中H型高血压的比率和特征及与美国人群的比较[J]. 北京大学学报(医学版), 2022, 54(5): 1028-1037.
[9] 陆林,刘晓星,袁凯. 中国脑科学计划进展[J]. 北京大学学报(医学版), 2022, 54(5): 791-795.
[10] 方伟岗,田新霞,解云涛. 基因多态性对中国汉族女性乳腺癌遗传易感性的影响[J]. 北京大学学报(医学版), 2022, 54(5): 822-828.
[11] 刘小璇,段晓慧,张朔,孙阿萍,张英爽,樊东升. 中国人群遗传性周围神经病的致病基因分布[J]. 北京大学学报(医学版), 2022, 54(5): 874-883.
[12] 张力,龚继芳,潘宏铭,白玉贤,刘天舒,程颖,陈亚池,黄佳莹,许婷婷,葛飞娇,许婉玲,施佳,胡夕春,沈琳. 阿替利珠单抗治疗中国晚期实体瘤患者的开放标签Ⅰ期临床试验[J]. 北京大学学报(医学版), 2022, 54(5): 971-980.
[13] 刘光奇,庞元捷,吴疆,吕敏,于孟轲,李雨橦,黄旸木. 2013—2019年流感季北京市住院老年人流感疫苗接种趋势分析[J]. 北京大学学报(医学版), 2022, 54(3): 505-510.
[14] 许颖,次仁央金. 高原红细胞增多症与消化性溃疡出血的关系[J]. 北京大学学报(医学版), 2022, 54(1): 161-165.
[15] 敖英芳. 我国运动医学发展与北京冬奥会和健康中国建设[J]. 北京大学学报(医学版), 2021, 53(5): 823-827.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!