中国全科医学 ›› 2024, Vol. 27 ›› Issue (10): 1179-1185.DOI: 10.12114/j.issn.1007-9572.2023.0686

• 论著 • 上一篇    下一篇

中国≥45岁人群健康体检服务利用情况:一项基于CHARLS 2018的全国横断面调查

高川1, 李庆印1, 柯丹丹2, 周俞余3, 张宇扬1, 何仲1,*()   

  1. 1.100037 北京市,中国医学科学院阜外医院护理研究室
    2.100005 北京市,北京协和医学院人文和社会科学学院
    3.100005 北京市,中国医学科学院北京协和医院
  • 收稿日期:2023-04-10 修回日期:2023-11-15 出版日期:2024-04-05 发布日期:2024-01-25
  • 通讯作者: 何仲

  • 作者贡献:高川负责研究设计、数据分析和论文撰写;李庆印提供论文修改指导意见;柯丹丹负责论文细节修改和论文图表制作;周俞余负责论文修改和润色;张宇扬负责论文修改和润色;何仲负责提供研究整体思路和修改论文,对文章整体负责。

The Utilization of Health Checkup Services among People Aged 45 and above in China: a National Cross-sectional Survey Based on CHARLS 2018

GAO Chuan1, LI Qingyin1, KE Dandan2, ZHOU Yuyu3, ZHANG Yuyang1, HE Zhong1,*()   

  1. 1. Fuwai Hospital, Chinese Academy of Medical Science, Beijing 100037, China
    2. College of Humanities and Social Sciences, Peking Union Medical College, Beijing 100005, China
    3. Peking Union Medical College Hospital, Chinese Academy of Medical Science, Beijing 100005, China
  • Received:2023-04-10 Revised:2023-11-15 Published:2024-04-05 Online:2024-01-25
  • Contact: HE Zhong

摘要: 背景 居民门诊和住院的医疗卫生服务利用情况及影响因素的研究已经十分成熟,然而分析我国居民预防性就医及健康体检服务利用情况的相关研究却较少。目的 了解我国≥45岁人群健康体检服务利用情况,并分析其影响因素。方法 利用2018年《中国健康与养老追踪调查》(CHARLS)的数据,选取≥45岁人群,统计其2015—2018年参加体检率和体检项目数。采用零膨胀负二项回归(Zinb)模型,分析居民参加体检项目数的影响因素。结果 本研究共纳入17 203例居民,平均年龄(62.4±10.0)岁,参加体检率为47.73%(8 211/17 203)。体检参加率排名前三位的分别是新疆维吾尔自治区(96.47%)、上海市(83.67%)和北京市(82.05%),排名后三位的分别为辽宁省(35.41%)、青海省(36.55%)和福建省(36.94%)。8 211例参加过常规体检的人群平均年龄(64.1±9.9)岁,人均参加体检项目中位数为9(5,12)项。体检项目数排名前三位的分别为北京市(14项)、上海市(14项)和新疆维吾尔自治区(13项),排名后三位的分别为甘肃省(7项)、安徽省(7项)和辽宁省(7.5项)。非参数检验显示,城镇居民体检项目数高于农村(10项与8项),东部高于中部(10项与8项)、西部(10项与9项)及东北部(10项与8项),西部高于中部(9项与8项)(P<0.001)。Zinb模型显示,经济区域(中部、西部、东北部)、居住地类型(城镇地区)、性别(女性)、年龄(60岁及以上)、文化程度(初中及以上)、健康状况(共患病)和基本医疗保险类型(职工医疗保险)是居民参加体检项目数的影响因素(P<0.001)。按照城镇和农村进行亚组分析,结果显示经济区域(中部、西部、东北部)、年龄(60岁及以上)、文化程度(初中及以上)是城镇和农村居民参加体检项目数的共同影响因素(P<0.05)。除此之外,对于城镇地区居民而言,已婚是其参加体检项目数的影响因素(P<0.001);对于农村地区居民而言,男性、共病、具有职工医疗保险是其参加体检项目数的影响因素(P<0.001)。结论 我国≥45岁人群健康体检服务利用率较低,城镇地区、东部地区健康体检服务更多,年龄和文化程度是居民利用健康体检服务的影响因素,婚姻状况是城镇地区居民利用健康体检服务的影响因素,性别、健康状态和基本医疗保险类型是农村地区居民利用健康体检服务的影响因素。未来应进一步提高居民健康体检服务的利用率,并分城乡和地域制定不同的政策措施。

关键词: 中年人, 老年人, 体格检查, 预防卫生服务, 健康体检, 影响因素分析

Abstract:

Background

Research on the utilization of outpatient and inpatient health services and its influencing factors has been well established, but there are few studies on the utilization of preventive medical services such as health checkup by residents in China.

Objective

To investigate the utilization of health checkup in Chinese residents aged 45 years and above and analyze its influencing factors.

Methods

Using data from the 2018 China Health and Retirement Longitudinal Study (CHARLS), the population aged≥45 years was selected to calculate the rate of participation in health checkup and the number of health checkup items from 2015 to 2018. Zero-inflation negative binomial regression was used to analyze the influencing factors of the number of health checkup items attended by residents.

Results

A total of 17 203 samples were included in this study, with an average age of (62.4±10.0), and the participation rate of 47.73% (8 21/17 203). The top three in participation rate in health checkup were Xinjiang Uygur Autonomous Region (96.47%), Shanghai (83.67%) and Beijing (82.05%), while the bottom three were Liaoning Province (35.41%), Qinghai Province (36.55%) and Fujian Province (36.94%). Among the 8 211 people who had participated in health checkup, the average age was (64.1±9.9) years old, and the median number of health checkup items per capita was 9 (5, 12). The top three in the number of health checkup items were Beijing Municipality (14 items), Shanghai Municipality (14 items) city and Xinjiang Uygur Autonomous Region (13 items), and the bottom three were Gansu Province (7 items), Anhui Province (7 items) and Liaoning Province (7.5 items). Non-parametric test showed that the number of health checkup items in urban residents was significantly higher than that in rural areas (10 items vs. 8 items), the eastern region was significantly higher than the central (10 items vs. 8 items), western (10 items vs. 8 items) and northeast (10 items vs. 8 items) region, the western region was significantly higher than the central region (9 items vs. 8 items) (P<0.001). The Zinb model showed that economic region (central, western, and northeastern), type of residence (urban area), gender (female), age (60 years and above), education level (junior high school and above), health status (comorbidity), and type of basic health insurance (employee health insurance) were the factors influencing the number of health checkup items attended by residents (P<0.001). Subgroup analysis according to urban and rural areas showed that economic region (central, western, and northeastern), age (60 and above), and education level (junior high school and above) were the common influencing factors on the number of health checkup items attended by urban and rural residents (P<0.05). In addition, for residents of urban areas, being married was an influential factor in the number of health checkup items attended (P<0.001) ; for residents of rural areas, being male, comorbidity, and employee health insurance were the factors influencing the number of health checkup items attended (P<0.001) .

Conclusion

The people aged 45 years and above in China have a low utilization rate of health checkup services, health check-up services are more available in urban and eastern areas. Age and education level are the influencing factors of utilization of health checkup services. Marital status is the influencing factor of utilization of health checkup services in urban, gender, health status and type of basic medical insurance are the influencing factors of the utilization of health checkup services in rural. In the future, the utilization of health checkup services should be further improved, different policies and measures should be formulated according to urban and rural areas, as well as geographical regions.

Key words: Middle aged, Aged, Physical examination, Preventive health services, Health checkup, Root cause analysis