Spatiotemporal Analysis of the Prevalence and Pattern of Multimorbidity in Older Chinese Adults
BackgroundMultimorbidity presents an enormous problem to societal and healthcare utilization under the context of aging population in low- and middle-income countries (LMICs). Currently, systematic studies on the profile of multimorbidity and its characteristics among Chinese elderly are lacking. We...
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Frontiers Media S.A.
2022-01-01
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| Series: | Frontiers in Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2021.806616/full |
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| author | Shimin Chen Shengshu Wang Wangping Jia Ke Han Yang Song Shaohua Liu Xuehang Li Miao Liu Yao He |
| author_facet | Shimin Chen Shengshu Wang Wangping Jia Ke Han Yang Song Shaohua Liu Xuehang Li Miao Liu Yao He |
| author_sort | Shimin Chen |
| collection | DOAJ |
| description | BackgroundMultimorbidity presents an enormous problem to societal and healthcare utilization under the context of aging population in low- and middle-income countries (LMICs). Currently, systematic studies on the profile of multimorbidity and its characteristics among Chinese elderly are lacking. We described the temporal and spatial trends in the prevalence of multimorbidity and explored chronological changes of comorbidity patterns in a large elderly population survey.MethodsData were extracted from the Chinese Longitudinal Healthy Longevity Study (CLHLS) conducted between 1998 and 2018 in a random selection of half of the counties and city districts. All the elderly aged 65 and older were included in the survey of eight waves. We used 13 investigated chronic diseases to measure the prevalence of multimorbidity by means of geography, subpopulation, and chronological changes. The patterns of multimorbidity were assessed by computing the value of relative risk (RR indicates the likelihood of certain diseases to be associated with multimorbidity) and the observed-to-expected ratio (O/E indicates the likelihood of the coexistence of a multimorbidity combination).ResultsFrom 1998 to 2018, the prevalence of multimorbidity went from 15.60 to 30.76%, increasing in the fluctuation across the survey of eight waves (pfor trend = 0.020). Increasing trends were observed similarly in a different gender group (pmale = 0.009; pfemale = 0.004) and age groups among female participants (p~80 = 0.009; p81−90 = 0.004; p91−100 = 0.035; p101~ = 0.018). The gap in the prevalence of multimorbidity between the north and the south was getting narrow across the survey of eight waves. Hypertension was the highest prevalent chronic condition while diabetes was most likely to coexist with other chronic conditions in the CLHLS survey. The most frequently occurring clusters were hypertension and heart disease, hypertension and cataract, and hypertension and chronic lung disease. And, the cancer, TB, and Parkinson's disease cluster took the domination of O/E rankings over time, which had a higher probability of coexistence in all the multimorbidity combinations.ConclusionsThe prevalence of multimorbidity has been increasing nationwide, and more attention should be paid to a rapid growth in the southern part of China. It demands the effective diagnosis and treatment adopted to the highly prevalent comorbidities, and strategies and measures were adjusted to strongly relevant clusters. |
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| institution | Directory Open Access Journal |
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| spelling | doaj.art-f7693753838d472f91666b053778c3b12022-12-21T21:20:21ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2022-01-01810.3389/fmed.2021.806616806616Spatiotemporal Analysis of the Prevalence and Pattern of Multimorbidity in Older Chinese AdultsShimin Chen0Shengshu Wang1Wangping Jia2Ke Han3Yang Song4Shaohua Liu5Xuehang Li6Miao Liu7Yao He8Institute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Disease, Chinese People's Liberation Army Medical School, Second Medical Center of Chinese People's Liberation Army General Hospital, Beijing, ChinaInstitute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Disease, Chinese People's Liberation Army Medical School, Second Medical Center of Chinese People's Liberation Army General Hospital, Beijing, ChinaSchool of Non-commissioned Officer, Army Medical University, Hebei, ChinaDepartment of Gastroenterology, Chinese People's Liberation Army Medical School, First Medical Center of Chinese People's Liberation Army General Hospital, Beijing, ChinaInstitute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Disease, Chinese People's Liberation Army Medical School, Second Medical Center of Chinese People's Liberation Army General Hospital, Beijing, ChinaInstitute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Disease, Chinese People's Liberation Army Medical School, Second Medical Center of Chinese People's Liberation Army General Hospital, Beijing, ChinaInstitute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Disease, Chinese People's Liberation Army Medical School, Second Medical Center of Chinese People's Liberation Army General Hospital, Beijing, ChinaDepartment of Statistics and Epidemiology, Graduate School, Chinese People's Liberation Army Medical School, Chinese People's Liberation Army General Hospital, Beijing, ChinaInstitute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatric Disease, Chinese People's Liberation Army Medical School, Second Medical Center of Chinese People's Liberation Army General Hospital, Beijing, ChinaBackgroundMultimorbidity presents an enormous problem to societal and healthcare utilization under the context of aging population in low- and middle-income countries (LMICs). Currently, systematic studies on the profile of multimorbidity and its characteristics among Chinese elderly are lacking. We described the temporal and spatial trends in the prevalence of multimorbidity and explored chronological changes of comorbidity patterns in a large elderly population survey.MethodsData were extracted from the Chinese Longitudinal Healthy Longevity Study (CLHLS) conducted between 1998 and 2018 in a random selection of half of the counties and city districts. All the elderly aged 65 and older were included in the survey of eight waves. We used 13 investigated chronic diseases to measure the prevalence of multimorbidity by means of geography, subpopulation, and chronological changes. The patterns of multimorbidity were assessed by computing the value of relative risk (RR indicates the likelihood of certain diseases to be associated with multimorbidity) and the observed-to-expected ratio (O/E indicates the likelihood of the coexistence of a multimorbidity combination).ResultsFrom 1998 to 2018, the prevalence of multimorbidity went from 15.60 to 30.76%, increasing in the fluctuation across the survey of eight waves (pfor trend = 0.020). Increasing trends were observed similarly in a different gender group (pmale = 0.009; pfemale = 0.004) and age groups among female participants (p~80 = 0.009; p81−90 = 0.004; p91−100 = 0.035; p101~ = 0.018). The gap in the prevalence of multimorbidity between the north and the south was getting narrow across the survey of eight waves. Hypertension was the highest prevalent chronic condition while diabetes was most likely to coexist with other chronic conditions in the CLHLS survey. The most frequently occurring clusters were hypertension and heart disease, hypertension and cataract, and hypertension and chronic lung disease. And, the cancer, TB, and Parkinson's disease cluster took the domination of O/E rankings over time, which had a higher probability of coexistence in all the multimorbidity combinations.ConclusionsThe prevalence of multimorbidity has been increasing nationwide, and more attention should be paid to a rapid growth in the southern part of China. It demands the effective diagnosis and treatment adopted to the highly prevalent comorbidities, and strategies and measures were adjusted to strongly relevant clusters.https://www.frontiersin.org/articles/10.3389/fmed.2021.806616/fullmultimorbiditypatternprevalenceolder adultsLMICs |
| spellingShingle | Shimin Chen Shengshu Wang Wangping Jia Ke Han Yang Song Shaohua Liu Xuehang Li Miao Liu Yao He Spatiotemporal Analysis of the Prevalence and Pattern of Multimorbidity in Older Chinese Adults Frontiers in Medicine multimorbidity pattern prevalence older adults LMICs |
| title | Spatiotemporal Analysis of the Prevalence and Pattern of Multimorbidity in Older Chinese Adults |
| title_full | Spatiotemporal Analysis of the Prevalence and Pattern of Multimorbidity in Older Chinese Adults |
| title_fullStr | Spatiotemporal Analysis of the Prevalence and Pattern of Multimorbidity in Older Chinese Adults |
| title_full_unstemmed | Spatiotemporal Analysis of the Prevalence and Pattern of Multimorbidity in Older Chinese Adults |
| title_short | Spatiotemporal Analysis of the Prevalence and Pattern of Multimorbidity in Older Chinese Adults |
| title_sort | spatiotemporal analysis of the prevalence and pattern of multimorbidity in older chinese adults |
| topic | multimorbidity pattern prevalence older adults LMICs |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2021.806616/full |
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