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Trend dynamics of gout prevalence among the Chinese population, 1990-2019: A joinpoint and age-period-cohort analysis

BACKGROUND: The burden of gout is increasing worldwide, which places a heavy burden on society and healthcare systems. This study investigates the independent effects of age, period, and cohort on the gout prevalence from 1990 to 2019 in China, compares these effects by gender and then predicts the...

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Autores principales: Zhu, Bowen, Wang, Yimei, Zhou, Weiran, Jin, Shi, Shen, Ziyan, Zhang, Han, Zhang, Xiaoyan, Ding, Xiaoqiang, Li, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9602928/
https://www.ncbi.nlm.nih.gov/pubmed/36311630
http://dx.doi.org/10.3389/fpubh.2022.1008598
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author Zhu, Bowen
Wang, Yimei
Zhou, Weiran
Jin, Shi
Shen, Ziyan
Zhang, Han
Zhang, Xiaoyan
Ding, Xiaoqiang
Li, Yang
author_facet Zhu, Bowen
Wang, Yimei
Zhou, Weiran
Jin, Shi
Shen, Ziyan
Zhang, Han
Zhang, Xiaoyan
Ding, Xiaoqiang
Li, Yang
author_sort Zhu, Bowen
collection PubMed
description BACKGROUND: The burden of gout is increasing worldwide, which places a heavy burden on society and healthcare systems. This study investigates the independent effects of age, period, and cohort on the gout prevalence from 1990 to 2019 in China, compares these effects by gender and then predicts the future burden of gout over the next decade. METHODS: The data were obtained from the Global Burden of Disease (GBD) study in 2019. Joinpoint regression model was employed to calculate the annual percentage change (APC) in gout prevalence, and the age-period-cohort analysis was utilized to estimate the independent effects of age, period, and cohort. ARIMA model was extended to predict the gout epidemic in 2020–2029. RESULTS: In 2019, there were 16.2 million cases of gout in China, with an age-standardized prevalence rate (ASPR) of 12.3‰ and 3.9‰ in men and women, respectively. During 1990–2019, the ASPR of gout was increasing significantly, with an average APC of 0.9%. The periods of 2014–2017 and 2001–2005 were “joinpoint” for men and women (APC: 6.3 and 5.6%). The age-period-cohort analyses revealed that the relative risk (RR) of developing gout increased with age, peaking at 70–74 years in men (RR(age(70−74)) = 162.9) and 75–79 years in women (RR(age(75−79))=142.3). The period effect trended upward, with a more rapid increase in women (RR(period(2019)) = 2.31) than men (RR(period(2019)) = 2.23). The cohort effect generally peaked in the earlier cohort born in 1905–1909 for both sexes. Gout prevalence showed a strong positive correlation with the consumption of meat and aquatic products (r(meat) = 0.966, r(aquaticproducts) = 0.953). Within 2029, the ASPR of gout was projected to be 11.7‰ and 4.0‰ in men and women, respectively. CONCLUSION: The prevalence of gout is increasing at an alarming rate in China; thus, it is necessary to provide targeted health education, regular screening, and accessible urate-lowering therapy healthcare to prevent and protect against gout in China, particularly in older women.
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spelling pubmed-96029282022-10-27 Trend dynamics of gout prevalence among the Chinese population, 1990-2019: A joinpoint and age-period-cohort analysis Zhu, Bowen Wang, Yimei Zhou, Weiran Jin, Shi Shen, Ziyan Zhang, Han Zhang, Xiaoyan Ding, Xiaoqiang Li, Yang Front Public Health Public Health BACKGROUND: The burden of gout is increasing worldwide, which places a heavy burden on society and healthcare systems. This study investigates the independent effects of age, period, and cohort on the gout prevalence from 1990 to 2019 in China, compares these effects by gender and then predicts the future burden of gout over the next decade. METHODS: The data were obtained from the Global Burden of Disease (GBD) study in 2019. Joinpoint regression model was employed to calculate the annual percentage change (APC) in gout prevalence, and the age-period-cohort analysis was utilized to estimate the independent effects of age, period, and cohort. ARIMA model was extended to predict the gout epidemic in 2020–2029. RESULTS: In 2019, there were 16.2 million cases of gout in China, with an age-standardized prevalence rate (ASPR) of 12.3‰ and 3.9‰ in men and women, respectively. During 1990–2019, the ASPR of gout was increasing significantly, with an average APC of 0.9%. The periods of 2014–2017 and 2001–2005 were “joinpoint” for men and women (APC: 6.3 and 5.6%). The age-period-cohort analyses revealed that the relative risk (RR) of developing gout increased with age, peaking at 70–74 years in men (RR(age(70−74)) = 162.9) and 75–79 years in women (RR(age(75−79))=142.3). The period effect trended upward, with a more rapid increase in women (RR(period(2019)) = 2.31) than men (RR(period(2019)) = 2.23). The cohort effect generally peaked in the earlier cohort born in 1905–1909 for both sexes. Gout prevalence showed a strong positive correlation with the consumption of meat and aquatic products (r(meat) = 0.966, r(aquaticproducts) = 0.953). Within 2029, the ASPR of gout was projected to be 11.7‰ and 4.0‰ in men and women, respectively. CONCLUSION: The prevalence of gout is increasing at an alarming rate in China; thus, it is necessary to provide targeted health education, regular screening, and accessible urate-lowering therapy healthcare to prevent and protect against gout in China, particularly in older women. Frontiers Media S.A. 2022-10-12 /pmc/articles/PMC9602928/ /pubmed/36311630 http://dx.doi.org/10.3389/fpubh.2022.1008598 Text en Copyright © 2022 Zhu, Wang, Zhou, Jin, Shen, Zhang, Zhang, Ding and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Zhu, Bowen
Wang, Yimei
Zhou, Weiran
Jin, Shi
Shen, Ziyan
Zhang, Han
Zhang, Xiaoyan
Ding, Xiaoqiang
Li, Yang
Trend dynamics of gout prevalence among the Chinese population, 1990-2019: A joinpoint and age-period-cohort analysis
title Trend dynamics of gout prevalence among the Chinese population, 1990-2019: A joinpoint and age-period-cohort analysis
title_full Trend dynamics of gout prevalence among the Chinese population, 1990-2019: A joinpoint and age-period-cohort analysis
title_fullStr Trend dynamics of gout prevalence among the Chinese population, 1990-2019: A joinpoint and age-period-cohort analysis
title_full_unstemmed Trend dynamics of gout prevalence among the Chinese population, 1990-2019: A joinpoint and age-period-cohort analysis
title_short Trend dynamics of gout prevalence among the Chinese population, 1990-2019: A joinpoint and age-period-cohort analysis
title_sort trend dynamics of gout prevalence among the chinese population, 1990-2019: a joinpoint and age-period-cohort analysis
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9602928/
https://www.ncbi.nlm.nih.gov/pubmed/36311630
http://dx.doi.org/10.3389/fpubh.2022.1008598
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