Chinese General Practice ›› 2024, Vol. 27 ›› Issue (28): 3520-3528.DOI: 10.12114/j.issn.1007-9572.2023.0611

• Article • Previous Articles     Next Articles

Effects of Chronic Disease Prevalence and Comorbidity Patterns on SRH Status in Middle-aged and Elderly Populations in Rural Areas

  

  1. School of Public Health, Xinjiang Medical University, Urumqi 830054, China
  • Received:2023-12-14 Revised:2024-05-11 Published:2024-10-05 Online:2024-07-16
  • Contact: GULIBAHAER Kadeer

农村地区中老年人群慢性病患病及共病模式对SRH状况的影响研究

  

  1. 830054 新疆维吾尔自治区乌鲁木齐市,新疆医科大学公共卫生学院
  • 通讯作者: 古丽巴哈尔·卡德尔
  • 作者简介:

    作者贡献:

    苏比努尔·艾外都力、古丽巴哈尔·卡德尔负责本研究的设计,并确定研究的可行性;苏比努尔·艾外都力、木开达斯·塔西、吕宇娟、卡迪尔亚·那斯尔、苏比德·阿力木江等人负责数据收集;苏比努尔·艾外都力负责数据整理、统计学分析,并对分析结果进行解释;苏比努尔·艾外都力、古丽巴哈尔·卡德尔负责核对结果;苏比努尔·艾外都力负责论文起草、初步撰写;古丽巴哈尔·卡德尔负责文章的质量控制及审校。

  • 基金资助:
    国家社会科学基金资助项目(17BRK030)

Abstract:

Background

With the acceleration of China's aging population, the prevalence of chronic diseases and comorbidity patterns pose significant challenges to global health. There is a close relationship between the prevalence of chronic diseases and individuals' self-related health (SRH) status. However, there is limited research on the prevalence of chronic diseases and comorbidity patterns among middle-aged and elderly populations in rural areas of Xinjiang, China, and their impact on SRH status.

Objective

To understand the prevalence of chronic diseases and comorbidity patterns among middle-aged and elderly populations in rural areas of Xinjiang and to explore the impact of chronic diseases and comorbidity patterns on SRH status, providing effective reference for improving the health level of this population.

Methods

The data for this study were derived from the survey database of the National Social Science Foundation project (17BRK030) from 2016 to 2019. A questionnaire survey was conducted on the demographic characteristics, chronic disease status, and self-rated health status of male and female heads of households. Ordered logistics regression analysis was used to screen the influencing factors of SRH status. SOM network training analysis and partial least squares method were employed to evaluate the interrelationships among 14 chronic diseases and the degree of their impact on SRH status.

Results

A total of 3 400 middle-aged and elderly individuals were surveyed. Residents' SRH status varied significantly by geographical distribution, gender, age, education level, occupation, marital status, illness or disability, and chronic disease status (P<0.05). Geographical region as southern Xinjiang, education level of primary school below, and presence of chronic diseases were identified as risk factors for SRH status (P<0.05). Being male, aged 45-59 years, occupation as pastoralists, staff of government or public institutions, or technical workers, being divorced, and having illness or disability were identified as protective factors for SRH status. The prevalence of chronic diseases among middle-aged and elderly populations in rural areas of Xinjiang was 36.47%. The top three diseases were hypertension (17.47%), arthritis or rheumatism (8.62%), and heart disease (5.68%). The comorbidity rate of chronic diseases was 8.09%, with hypertension (6.12%), arthritis or rheumatism (5.18%), and heart disease (4.71%) being the top three comorbid diseases. The predominant comorbidity pattern was the co-occurrence of two chronic diseases (78.18%). The most common comorbidity pattern among individuals with two chronic diseases was hypertension combined with heart disease, and among those with three chronic diseases was hypertension combined with heart disease and arthritis or rheumatism. The impact of chronic disease status on SRH status revealed that individuals with chronic diseases had significantly lower SRH status than those without chronic diseases, and individuals with two or more chronic diseases had lower SRH status than those with one chronic disease.

Conclusion

The prevalence of chronic diseases and comorbidity among middle-aged and elderly populations in rural areas of Xinjiang is high. Chronic respiratory diseases, arthritis or rheumatism, heart disease, anemia, and other chronic diseases have a significant impact on SRH status. Therefore, it is necessary to further strengthen the construction of chronic disease service systems, improve the health records of middle-aged and elderly individuals, establish specialized clinics for chronic disease comorbidity to detect and control the comorbidity of chronic diseases among middle-aged and elderly populations. Additionally, efforts should be made to enhance health education for middle-aged and elderly groups, increase awareness of chronic diseases, and promote active and healthy lifestyles to improve the health level and quality of life of middle-aged and elderly populations.

Key words: Multiple chronic conditions, Rural population, Chronic disease comorbidity patterns, Self-related health status, Middle aged, Aged, Root cause analysis

摘要:

背景

随着我国人口老龄化速度的加快,慢性病患病及共病模式给全球卫生事业带来重大挑战,慢性病患病与人群的个人自评健康(SRH)状况之间关联紧密。然而,目前对新疆维吾尔自治区农村地区中老年人群慢性病患病及共病模式现状,以及对SRH状况的影响相关研究甚少。

目的

了解新疆维吾尔自治区农村地区中老年群体慢性病患病及共病模式的现状,探讨慢性病患病及共病模式对SRH状况的影响,为提升农村中老年群体健康水平提供有效参考依据。

方法

本研究数据来源于2016—2019年国家社会科学基金项目(17BRK030)的调研数据库;对家庭中男女主事者的一般人口学特征、患慢性病情况、SRH状况进行问卷调查。采用有序Logistics回归分析筛查SRH状况的影响因素,采用自组织映射(SOM)网络训练分析和偏最小二乘法,评估14种慢性病之间的相互关联性和各类慢性病对SRH状况的影响程度。

结果

共调查3 400名中老年人。不同疆域分布、性别、年龄、文化程度、职业、婚姻状况、患病或伤残情况、患慢性病情况居民SRH状况比较,差异有统计学意义(P<0.05)。其中疆域为南疆、文化程度为小学以下、患有慢性病是SRH状况的危险因素(P<0.05);性别为男性,年龄为45~59岁,职业为牧民、机关或事业单位员工、技术工人,婚姻状况为离异,患病或伤残情况是SRH状况的保护因素(P<0.05);新疆维吾尔自治区农村地区中老年群体慢性病患病率为36.47%,其中患病率排在前三位的疾病分别是高血压(17.47%)、关节炎或风湿病(8.62%)、心脏病(5.68%);慢性病共病率为8.09%,共病患病率排在前三位的疾病分别是高血压(6.12%)、关节炎或风湿病(5.18%)、心脏病(4.71%);共病模式主要以患2种慢性病为主(78.18%);患2种慢性病共病模式主要以高血压+心脏病为主,患3种慢性病患病模式主要以高血压+心脏病+关节炎或风湿病为主;患慢性病情况对SRH状况的影响结果显示,患慢性病患者SRH状况明显低于未患慢性病人群,患2种及以上慢性病患者的SRH状况低于患1种慢性病患者。

结论

新疆维吾尔自治区农村地区中老年人群的慢性病患病及共病情况较高,慢性呼吸系统疾病、关节炎或风湿病、心脏病、贫血等慢性疾病对SRH状况的影响比较明显,因此需进一步加强慢性病服务系统的建设,完善中老年健康档案,设立慢性病共病专科门诊来检测并控制中老年人群慢性病共病情况;另外,应加强对中老年群体的健康教育,提升对慢性病的认识,并提倡积极健康的生活方式,从而提高中老年人群的健康水平和生活质量。

关键词: 慢性病共病, 农村人口, 慢性病共病模式, 自评健康状况, 中年人, 老年人, 影响因素分析

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