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

Bowen Zhu; Yimei Wang; Weiran Zhou; Shi Jin; Ziyan Shen; Han Zhang; Xiaoyan Zhang; Xiaoqiang Ding; Yang Li

doi:10.3389/fpubh.2022.1008598

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

Front Public Health. 2022 Oct 12:10:1008598. doi: 10.3389/fpubh.2022.1008598. eCollection 2022.

Authors

Bowen Zhu^{1

2

3}, Yimei Wang^{1

2

3}, Weiran Zhou^{1

2

3}, Shi Jin^{1

2

3}, Ziyan Shen^{1

2

3}, Han Zhang^{1

2

3}, Xiaoyan Zhang^{1

2

3}, Xiaoqiang Ding^{1

2

3}, Yang Li^{1

2

3}

Affiliations

¹ Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China.
² Shanghai Medical Center of Kidney, Shanghai, China.
³ Shanghai Key Laboratory of Kidney and Blood Purification, Shanghai, China.

Abstract

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.

Keywords: ARIMA model; age-period-cohort analysis; epidemiology; gout; hyperuricemia; joinpoint regression.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aged
Aged, 80 and over
China / epidemiology
Cohort Studies
Female
Gout* / epidemiology
Humans
Male
Prevalence