Global, Regional, and National Prevalence of Gout From 1990 to 2019: Age-Period-Cohort Analysis With Future Burden Prediction

Gout is a common and debilitating condition that is associated with significant morbidity and mortality. Despite advances in medical treatment, the global burden of gout continues to increase, particularly in high-sociodemographic index (SDI) regions. To address the aforementioned issue, we used age...

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Published inJMIR public health and surveillance Vol. 9; p. e45943
Main Authors He, Qiyu, Mok, Tsz-Ngai, Sin, Tat-Hang, Yin, Jiaying, Li, Sicun, Yin, Yiyue, Ming, Wai-Kit, Feng, Bin
Format Journal Article
LanguageEnglish
Published Canada JMIR Publications 07.06.2023
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Abstract Gout is a common and debilitating condition that is associated with significant morbidity and mortality. Despite advances in medical treatment, the global burden of gout continues to increase, particularly in high-sociodemographic index (SDI) regions. To address the aforementioned issue, we used age-period-cohort (APC) modeling to analyze global trends in gout incidence and prevalence from 1990 to 2019. Data were extracted from the Global Burden of Disease Study 2019 to assess all-age prevalence and age-standardized prevalence rates, as well as years lived with disability rates, for 204 countries and territories. APC effects were also examined in relation to gout prevalence. Future burden prediction was carried out using the Nordpred APC prediction of future incidence cases and the Bayesian APC model. The global gout incidence has increased by 63.44% over the past 2 decades, with a corresponding increase of 51.12% in global years lived with disability. The sex ratio remained consistent at 3:1 (male to female), but the global gout incidence increased in both sexes over time. Notably, the prevalence and incidence of gout were the highest in high-SDI regions (95% uncertainty interval 14.19-20.62), with a growth rate of 94.3%. Gout prevalence increases steadily with age, and the prevalence increases rapidly in high-SDI quantiles for the period effect. Finally, the cohort effect showed that gout prevalence increases steadily, with the risk of morbidity increasing in younger birth cohorts. The prediction model suggests that the gout incidence rate will continue to increase globally. Our study provides important insights into the global burden of gout and highlights the need for effective management and prophylaxis of this condition. The APC model used in our analysis provides a novel approach to understanding the complex trends in gout prevalence and incidence, and our findings can inform the development of targeted interventions to address this growing health issue.
AbstractList Background:Gout is a common and debilitating condition that is associated with significant morbidity and mortality. Despite advances in medical treatment, the global burden of gout continues to increase, particularly in high–sociodemographic index (SDI) regions.Objective:To address the aforementioned issue, we used age-period-cohort (APC) modeling to analyze global trends in gout incidence and prevalence from 1990 to 2019.Methods:Data were extracted from the Global Burden of Disease Study 2019 to assess all-age prevalence and age-standardized prevalence rates, as well as years lived with disability rates, for 204 countries and territories. APC effects were also examined in relation to gout prevalence. Future burden prediction was carried out using the Nordpred APC prediction of future incidence cases and the Bayesian APC model.Results:The global gout incidence has increased by 63.44% over the past 2 decades, with a corresponding increase of 51.12% in global years lived with disability. The sex ratio remained consistent at 3:1 (male to female), but the global gout incidence increased in both sexes over time. Notably, the prevalence and incidence of gout were the highest in high-SDI regions (95% uncertainty interval 14.19-20.62), with a growth rate of 94.3%. Gout prevalence increases steadily with age, and the prevalence increases rapidly in high-SDI quantiles for the period effect. Finally, the cohort effect showed that gout prevalence increases steadily, with the risk of morbidity increasing in younger birth cohorts. The prediction model suggests that the gout incidence rate will continue to increase globally.Conclusions:Our study provides important insights into the global burden of gout and highlights the need for effective management and prophylaxis of this condition. The APC model used in our analysis provides a novel approach to understanding the complex trends in gout prevalence and incidence, and our findings can inform the development of targeted interventions to address this growing health issue.
Gout is a common and debilitating condition that is associated with significant morbidity and mortality. Despite advances in medical treatment, the global burden of gout continues to increase, particularly in high-sociodemographic index (SDI) regions.BACKGROUNDGout is a common and debilitating condition that is associated with significant morbidity and mortality. Despite advances in medical treatment, the global burden of gout continues to increase, particularly in high-sociodemographic index (SDI) regions.To address the aforementioned issue, we used age-period-cohort (APC) modeling to analyze global trends in gout incidence and prevalence from 1990 to 2019.OBJECTIVETo address the aforementioned issue, we used age-period-cohort (APC) modeling to analyze global trends in gout incidence and prevalence from 1990 to 2019.Data were extracted from the Global Burden of Disease Study 2019 to assess all-age prevalence and age-standardized prevalence rates, as well as years lived with disability rates, for 204 countries and territories. APC effects were also examined in relation to gout prevalence. Future burden prediction was carried out using the Nordpred APC prediction of future incidence cases and the Bayesian APC model.METHODSData were extracted from the Global Burden of Disease Study 2019 to assess all-age prevalence and age-standardized prevalence rates, as well as years lived with disability rates, for 204 countries and territories. APC effects were also examined in relation to gout prevalence. Future burden prediction was carried out using the Nordpred APC prediction of future incidence cases and the Bayesian APC model.The global gout incidence has increased by 63.44% over the past 2 decades, with a corresponding increase of 51.12% in global years lived with disability. The sex ratio remained consistent at 3:1 (male to female), but the global gout incidence increased in both sexes over time. Notably, the prevalence and incidence of gout were the highest in high-SDI regions (95% uncertainty interval 14.19-20.62), with a growth rate of 94.3%. Gout prevalence increases steadily with age, and the prevalence increases rapidly in high-SDI quantiles for the period effect. Finally, the cohort effect showed that gout prevalence increases steadily, with the risk of morbidity increasing in younger birth cohorts. The prediction model suggests that the gout incidence rate will continue to increase globally.RESULTSThe global gout incidence has increased by 63.44% over the past 2 decades, with a corresponding increase of 51.12% in global years lived with disability. The sex ratio remained consistent at 3:1 (male to female), but the global gout incidence increased in both sexes over time. Notably, the prevalence and incidence of gout were the highest in high-SDI regions (95% uncertainty interval 14.19-20.62), with a growth rate of 94.3%. Gout prevalence increases steadily with age, and the prevalence increases rapidly in high-SDI quantiles for the period effect. Finally, the cohort effect showed that gout prevalence increases steadily, with the risk of morbidity increasing in younger birth cohorts. The prediction model suggests that the gout incidence rate will continue to increase globally.Our study provides important insights into the global burden of gout and highlights the need for effective management and prophylaxis of this condition. The APC model used in our analysis provides a novel approach to understanding the complex trends in gout prevalence and incidence, and our findings can inform the development of targeted interventions to address this growing health issue.CONCLUSIONSOur study provides important insights into the global burden of gout and highlights the need for effective management and prophylaxis of this condition. The APC model used in our analysis provides a novel approach to understanding the complex trends in gout prevalence and incidence, and our findings can inform the development of targeted interventions to address this growing health issue.
BackgroundGout is a common and debilitating condition that is associated with significant morbidity and mortality. Despite advances in medical treatment, the global burden of gout continues to increase, particularly in high–sociodemographic index (SDI) regions. ObjectiveTo address the aforementioned issue, we used age-period-cohort (APC) modeling to analyze global trends in gout incidence and prevalence from 1990 to 2019. MethodsData were extracted from the Global Burden of Disease Study 2019 to assess all-age prevalence and age-standardized prevalence rates, as well as years lived with disability rates, for 204 countries and territories. APC effects were also examined in relation to gout prevalence. Future burden prediction was carried out using the Nordpred APC prediction of future incidence cases and the Bayesian APC model. ResultsThe global gout incidence has increased by 63.44% over the past 2 decades, with a corresponding increase of 51.12% in global years lived with disability. The sex ratio remained consistent at 3:1 (male to female), but the global gout incidence increased in both sexes over time. Notably, the prevalence and incidence of gout were the highest in high-SDI regions (95% uncertainty interval 14.19-20.62), with a growth rate of 94.3%. Gout prevalence increases steadily with age, and the prevalence increases rapidly in high-SDI quantiles for the period effect. Finally, the cohort effect showed that gout prevalence increases steadily, with the risk of morbidity increasing in younger birth cohorts. The prediction model suggests that the gout incidence rate will continue to increase globally. ConclusionsOur study provides important insights into the global burden of gout and highlights the need for effective management and prophylaxis of this condition. The APC model used in our analysis provides a novel approach to understanding the complex trends in gout prevalence and incidence, and our findings can inform the development of targeted interventions to address this growing health issue.
Gout is a common and debilitating condition that is associated with significant morbidity and mortality. Despite advances in medical treatment, the global burden of gout continues to increase, particularly in high-sociodemographic index (SDI) regions. To address the aforementioned issue, we used age-period-cohort (APC) modeling to analyze global trends in gout incidence and prevalence from 1990 to 2019. Data were extracted from the Global Burden of Disease Study 2019 to assess all-age prevalence and age-standardized prevalence rates, as well as years lived with disability rates, for 204 countries and territories. APC effects were also examined in relation to gout prevalence. Future burden prediction was carried out using the Nordpred APC prediction of future incidence cases and the Bayesian APC model. The global gout incidence has increased by 63.44% over the past 2 decades, with a corresponding increase of 51.12% in global years lived with disability. The sex ratio remained consistent at 3:1 (male to female), but the global gout incidence increased in both sexes over time. Notably, the prevalence and incidence of gout were the highest in high-SDI regions (95% uncertainty interval 14.19-20.62), with a growth rate of 94.3%. Gout prevalence increases steadily with age, and the prevalence increases rapidly in high-SDI quantiles for the period effect. Finally, the cohort effect showed that gout prevalence increases steadily, with the risk of morbidity increasing in younger birth cohorts. The prediction model suggests that the gout incidence rate will continue to increase globally. Our study provides important insights into the global burden of gout and highlights the need for effective management and prophylaxis of this condition. The APC model used in our analysis provides a novel approach to understanding the complex trends in gout prevalence and incidence, and our findings can inform the development of targeted interventions to address this growing health issue.
Author Mok, Tsz-Ngai
Feng, Bin
Sin, Tat-Hang
Yin, Yiyue
Yin, Jiaying
Li, Sicun
He, Qiyu
Ming, Wai-Kit
AuthorAffiliation 2 Department of Infectious Diseases and Public Health Jockey Club College of Veterinary Medicine and Life Sciences City University of Hong Kong Hong Kong Hong Kong
6 School of Humanities and Communication Guangdong University of Finance and Economics Guangzhou China
4 Department of Surgery Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
3 Department of Orthopedic Surgery and Sports Medicine Center The First Affiliated Hospital and The First Clinical College Jinan University Guangzhou China
7 Department of Biostatistics College of Science City University of Hong Kong Hong Kong Hong Kong
5 School of Public Health University of Hong Kong Hong Kong Hong Kong
9 Department of Orthopedic Surgery Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
8 School of Public Policy and Management Tsinghua University Beijing China
1 State Key Laboratory of Cardiovascular
AuthorAffiliation_xml – name: 2 Department of Infectious Diseases and Public Health Jockey Club College of Veterinary Medicine and Life Sciences City University of Hong Kong Hong Kong Hong Kong
– name: 3 Department of Orthopedic Surgery and Sports Medicine Center The First Affiliated Hospital and The First Clinical College Jinan University Guangzhou China
– name: 9 Department of Orthopedic Surgery Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
– name: 4 Department of Surgery Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China
– name: 5 School of Public Health University of Hong Kong Hong Kong Hong Kong
– name: 7 Department of Biostatistics College of Science City University of Hong Kong Hong Kong Hong Kong
– name: 6 School of Humanities and Communication Guangdong University of Finance and Economics Guangzhou China
– name: 1 State Key Laboratory of Cardiovascular Disease, Fuwai Hospital National Center for Cardiovascular Diseases Chinese Academy of Medical Sciences, Peking Union Medical College Bejing China
– name: 8 School of Public Policy and Management Tsinghua University Beijing China
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/37285198$$D View this record in MEDLINE/PubMed
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ContentType Journal Article
Copyright Qiyu He, Tsz-Ngai Mok, Tat-Hang Sin, Jiaying Yin, Sicun Li, Yiyue Yin, Wai-Kit Ming, Bin Feng. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 07.06.2023.
2023. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Qiyu He, Tsz-Ngai Mok, Tat-Hang Sin, Jiaying Yin, Sicun Li, Yiyue Yin, Wai-Kit Ming, Bin Feng. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 07.06.2023. 2023
Copyright_xml – notice: Qiyu He, Tsz-Ngai Mok, Tat-Hang Sin, Jiaying Yin, Sicun Li, Yiyue Yin, Wai-Kit Ming, Bin Feng. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 07.06.2023.
– notice: 2023. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
– notice: Qiyu He, Tsz-Ngai Mok, Tat-Hang Sin, Jiaying Yin, Sicun Li, Yiyue Yin, Wai-Kit Ming, Bin Feng. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 07.06.2023. 2023
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Keywords prevalence
age-period-cohort analysis
gout
prediction
Global Burden of Disease Study 2019
Bayesian age-period-cohort analysis
Norped age-period-cohort analysis
Language English
License Qiyu He, Tsz-Ngai Mok, Tat-Hang Sin, Jiaying Yin, Sicun Li, Yiyue Yin, Wai-Kit Ming, Bin Feng. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 07.06.2023.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on https://publichealth.jmir.org, as well as this copyright and license information must be included.
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Snippet Gout is a common and debilitating condition that is associated with significant morbidity and mortality. Despite advances in medical treatment, the global...
Background:Gout is a common and debilitating condition that is associated with significant morbidity and mortality. Despite advances in medical treatment, the...
BackgroundGout is a common and debilitating condition that is associated with significant morbidity and mortality. Despite advances in medical treatment, the...
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SubjectTerms Age
Bayes Theorem
Cohort Studies
Disease
Epidemiology
Female
Gout - epidemiology
Health care delivery
Humans
Male
Medical treatment
Morbidity
Mortality
Original Paper
Prediction models
Prevalence
Prophylaxis
Public health
Quality of life
Quality-Adjusted Life Years
Review boards
Rheumatism
Sex ratio
Trends
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Title Global, Regional, and National Prevalence of Gout From 1990 to 2019: Age-Period-Cohort Analysis With Future Burden Prediction
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