Using primary and routinely collected data to determine prevalence and patterns of multimorbidity in rural China: a representative cross-sectional study of 6474 Chinese adultsResearch in context
Summary: 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. Thi...
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2025-01-01
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| Series: | The Lancet Regional Health. Western Pacific |
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| author | Xinyi Zhang Tingzhuo Liu Zhifang Li Jiajuan Yang Huinan Hou Tianyou Hao Pei Zhang Chi Hu Mingjia Bao Pengpeng Ye Shangzhi Xiong Wei Tian Guangcan Yan Jing Zhang Yue Wang Wei Jiang Anqi Ge Yonghui Pan Devarsetty Praveen David Peiris Xiaoqi Feng Ding Ding Lijing L. Yan Xiaolin Xu Hanbin Zhang Yongchen Wang Wenjing Tian Maoyi Tian |
| author_facet | Xinyi Zhang Tingzhuo Liu Zhifang Li Jiajuan Yang Huinan Hou Tianyou Hao Pei Zhang Chi Hu Mingjia Bao Pengpeng Ye Shangzhi Xiong Wei Tian Guangcan Yan Jing Zhang Yue Wang Wei Jiang Anqi Ge Yonghui Pan Devarsetty Praveen David Peiris Xiaoqi Feng Ding Ding Lijing L. Yan Xiaolin Xu Hanbin Zhang Yongchen Wang Wenjing Tian Maoyi Tian |
| author_sort | Xinyi Zhang |
| collection | DOAJ |
| description | Summary: 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). |
| format | Article |
| id | doaj-art-eea2b91f59a54b739e08cf9594afecc5 |
| institution | Kabale University |
| issn | 2666-6065 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | The Lancet Regional Health. Western Pacific |
| spelling | doaj-art-eea2b91f59a54b739e08cf9594afecc52024-12-28T05:22:54ZengElsevierThe Lancet Regional Health. Western Pacific2666-60652025-01-0154101272Using primary and routinely collected data to determine prevalence and patterns of multimorbidity in rural China: a representative cross-sectional study of 6474 Chinese adultsResearch in contextXinyi Zhang0Tingzhuo Liu1Zhifang Li2Jiajuan Yang3Huinan Hou4Tianyou Hao5Pei Zhang6Chi Hu7Mingjia Bao8Pengpeng Ye9Shangzhi Xiong10Wei Tian11Guangcan Yan12Jing Zhang13Yue Wang14Wei Jiang15Anqi Ge16Yonghui Pan17Devarsetty Praveen18David Peiris19Xiaoqi Feng20Ding Ding21Lijing L. Yan22Xiaolin Xu23Hanbin Zhang24Yongchen Wang25Wenjing Tian26Maoyi Tian27School of Public Health, Harbin Medical University, Harbin, ChinaSchool of Public Health, Harbin Medical University, Harbin, ChinaSchool of Public Health, Changzhi Medical College, Changzhi, ChinaYichang Centre for Disease Control and Prevention, Yichang, ChinaJiamusi Centre for Disease Control and Prevention, Jiamusi, ChinaHeping Hospital Affiliated to Changzhi Medical College, Changzhi, ChinaYichang Centre for Disease Control and Prevention, Yichang, ChinaYichang Centre for Disease Control and Prevention, Yichang, ChinaHeilongjiang Provincial Centre for Disease Control and Prevention, Harbin, ChinaNational Centre for Non-communicable Disease Control and Prevention, Chinese Centre for Diseases Control and Prevention, Beijing, ChinaThe George Institute for Global Health, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia; Global Health Research Centre, Duke Kunshan University, Kunshan, ChinaSchool of Public Health, Harbin Medical University, Harbin, ChinaSchool of Public Health, Harbin Medical University, Harbin, ChinaSchool of Public Health, Harbin Medical University, Harbin, ChinaSchool of Public Health, Harbin Medical University, Harbin, ChinaNational Centre for Non-communicable Disease Control and Prevention, Chinese Centre for Diseases Control and Prevention, Beijing, ChinaSchool of Public Health, Harbin Medical University, Harbin, ChinaDivision of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, ChinaThe George Institute for Global Health, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia; The George Institute for Global Health, India, Hyderabad, India; Prasanna School of Public Health, Manipal Academy of Higher Education, Manipal, IndiaThe George Institute for Global Health, Faculty of Medicine and Health, University of New South Wales, Sydney, AustraliaSchool of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, AustraliaSydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, AustraliaGlobal Health Research Centre, Duke Kunshan University, Kunshan, ChinaSchool of Public Health, Zhejiang University, Hangzhou, ChinaEuropean Centre for Environment and Human Health, University of Exeter, United Kingdom; Environmental Research Group, MRC Centre for Environment and Health, Faculty of Medicine, Imperial College London, UKDivision of General Practice, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; Corresponding author. Division of General Practice, The Second Affiliated Hospital of Harbin Medical University, Harbin Medical University, 246 Xuefu Road, Harbin, China.School of Public Health, Harbin Medical University, Harbin, China; Corresponding author. School of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, China.School of Public Health, Harbin Medical University, Harbin, China; Division of General Practice, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; Corresponding author. School of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, China.Summary: 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).http://www.sciencedirect.com/science/article/pii/S2666606524002669MultimorbidityRoutinely collected dataChina |
| spellingShingle | Xinyi Zhang Tingzhuo Liu Zhifang Li Jiajuan Yang Huinan Hou Tianyou Hao Pei Zhang Chi Hu Mingjia Bao Pengpeng Ye Shangzhi Xiong Wei Tian Guangcan Yan Jing Zhang Yue Wang Wei Jiang Anqi Ge Yonghui Pan Devarsetty Praveen David Peiris Xiaoqi Feng Ding Ding Lijing L. Yan Xiaolin Xu Hanbin Zhang Yongchen Wang Wenjing Tian Maoyi Tian Using primary and routinely collected data to determine prevalence and patterns of multimorbidity in rural China: a representative cross-sectional study of 6474 Chinese adultsResearch in context The Lancet Regional Health. Western Pacific Multimorbidity Routinely collected data China |
| title | Using primary and routinely collected data to determine prevalence and patterns of multimorbidity in rural China: a representative cross-sectional study of 6474 Chinese adultsResearch in context |
| title_full | Using primary and routinely collected data to determine prevalence and patterns of multimorbidity in rural China: a representative cross-sectional study of 6474 Chinese adultsResearch in context |
| title_fullStr | Using primary and routinely collected data to determine prevalence and patterns of multimorbidity in rural China: a representative cross-sectional study of 6474 Chinese adultsResearch in context |
| title_full_unstemmed | Using primary and routinely collected data to determine prevalence and patterns of multimorbidity in rural China: a representative cross-sectional study of 6474 Chinese adultsResearch in context |
| title_short | Using primary and routinely collected data to determine prevalence and patterns of multimorbidity in rural China: a representative cross-sectional study of 6474 Chinese adultsResearch in context |
| title_sort | using primary and routinely collected data to determine prevalence and patterns of multimorbidity in rural china a representative cross sectional study of 6474 chinese adultsresearch in context |
| topic | Multimorbidity Routinely collected data China |
| url | http://www.sciencedirect.com/science/article/pii/S2666606524002669 |
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