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利用原始数据和常规收集的数据确定中国农村地区的多病共存患病率及模式:一项对6474名中国成年人的代表性横断面研究

Using primary and routinely collected data to determine prevalence and patterns of multimorbidity in rural China: a representative cross-sectional study of 6474 Chinese adults.

作者信息

Zhang Xinyi, Liu Tingzhuo, Li Zhifang, Yang Jiajuan, Hou Huinan, Hao Tianyou, Zhang Pei, Hu Chi, Bao Mingjia, Ye Pengpeng, Xiong Shangzhi, Tian Wei, Yan Guangcan, Zhang Jing, Wang Yue, Jiang Wei, Ge Anqi, Pan Yonghui, Praveen Devarsetty, Peiris David, Feng Xiaoqi, Ding Ding, Yan Lijing L, Xu Xiaolin, Zhang Hanbin, Wang Yongchen, Tian Wenjing, Tian Maoyi

机构信息

School of Public Health, Harbin Medical University, Harbin, China.

School of Public Health, Changzhi Medical College, Changzhi, China.

出版信息

Lancet Reg Health West Pac. 2024 Dec 26;54:101272. doi: 10.1016/j.lanwpc.2024.101272. eCollection 2025 Jan.

Abstract

BACKGROUND

In China, rising chronic diseases has coincided with the increasing burden of multimorbidity, particularly for vulnerable populations. Limited primary data are available to understand the prevalence and patterns of multimorbidity, especially in resource-limited rural areas. This study aims to conduct robust evaluations of the prevalence and patterns of multimorbidity among rural adults in China, and to compare the differences in prevalence and patterns when using primary data alone versus in combination with routinely collected data.

METHODS

This cross-sectional study was conducted in three provinces in China, with two counties per province and 40 villages per county, resulted in a total of 240 villages. Participants were randomly selected and stratified by sex and age in each village. Multimorbidity, defined as the coexistence of two or more diseases in same individual, was assessed through data collection involving primary data (face-to-face questionnaire, physical examination and fasting blood sample collection) and routinely collected data (health insurance claims, hospital electronic records and infectious disease surveillance system). Multimorbidity prevalence and patterns were compared based on 1) primary data alone and 2) primary data complemented by routinely collected data.

FINDINGS

A total of 6474 individuals participated in this study (50.9% women, mean age 57.1). Combining routinely collected data with the primary data increased the prevalence of all single disease conditions. Multimorbidity prevalence rose from 35.7% with primary data alone to 44.4% with the addition of routinely collected data. The top three dyad multimorbidity patterns (hypertension with heart disease, stroke, or chronic digestive diseases) remained consistent between the two ascertainment methods, while triad pattern rankings had a substantial shift. According to blood pressure measurements, over 40% of participants had elevated blood pressure and may have undiagnosed hypertension. Over 20% may have undiagnosed mental health disorders base on the questionnaires, and nearly 10% with undiagnosed chronic kidney disease as indicated by blood testing.

INTERPRETATION

The utilisation of primary data combined with routinely collected data provided a robust estimation of multimorbidity burden in three rural regions in China. Yet, the prevalence may still have been underestimated due to inaccuracies in self-reported data and underdiagnosis of diseases. Future research should incorporate routinely collected data for more robust epidemiological evidence of multimorbidity.

FUNDING

Harbin Medical University Leading Talent Grant (31021220002) and National Natural Science Foundation of China (72074065 and 72474063).

摘要

背景

在中国,慢性病的增加与多重疾病负担的加重同时出现,尤其是对弱势群体而言。目前可用于了解多重疾病患病率和模式的原始数据有限,特别是在资源有限的农村地区。本研究旨在对中国农村成年人的多重疾病患病率和模式进行有力评估,并比较单独使用原始数据与结合常规收集数据时患病率和模式的差异。

方法

本横断面研究在中国的三个省份进行,每个省份两个县,每个县40个村庄,共240个村庄。在每个村庄中,参与者按性别和年龄进行随机选择和分层。多重疾病定义为同一个体中两种或更多种疾病并存,通过收集原始数据(面对面问卷调查、体格检查和空腹血样采集)和常规收集数据(医疗保险理赔、医院电子记录和传染病监测系统)进行评估。基于以下两种情况比较多重疾病的患病率和模式:1)仅使用原始数据;2)由常规收集数据补充的原始数据。

结果

共有6474人参与本研究(女性占50.9%,平均年龄57.1岁)。将常规收集的数据与原始数据相结合提高了所有单一疾病状况的患病率。多重疾病患病率从仅使用原始数据时的35.7%上升到加上常规收集数据后的44.4%。两种确定方法中,二元组多重疾病的前三种模式(高血压合并心脏病、中风或慢性消化系统疾病)保持一致,而三元组模式的排名有很大变化。根据血压测量,超过40%的参与者血压升高,可能患有未确诊的高血压。根据问卷调查,超过20%的人可能患有未确诊的心理健康障碍,血液检测显示近10%的人患有未确诊的慢性肾脏病。

解读

结合使用原始数据和常规收集的数据,为中国三个农村地区的多重疾病负担提供了有力估计。然而,由于自我报告数据的不准确和疾病的诊断不足,患病率可能仍被低估。未来的研究应纳入常规收集的数据,以获得更有力的多重疾病流行病学证据。

资助

哈尔滨医科大学领军人才资助(31021220002)以及中国国家自然科学基金(72074065和72474063)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/412a/11741085/d5b170b900f8/gr1.jpg

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