Temporal trends in prevalence and mortality for chronic kidney disease in China from 1990 to 2019: an analysis of the Global Burden of Disease Study 2019

Yang Li; Yichun Ning; Bo Shen; Yiqin Shi; Nana Song; Yi Fang; Xiaoqiang Ding

doi:10.1093/ckj/sfac218

Temporal trends in prevalence and mortality for chronic kidney disease in China from 1990 to 2019: an analysis of the Global Burden of Disease Study 2019

Clin Kidney J. 2022 Oct 10;16(2):312-321. doi: 10.1093/ckj/sfac218. eCollection 2023 Feb.

Authors

Yang Li^{1

2

3}, Yichun Ning^{1

2

3}, Bo Shen^{1

2

3}, Yiqin Shi^{1

2

3}, Nana Song^{1

2

3}, Yi Fang^{1

2

3}, Xiaoqiang Ding^{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: This study aimed to characterize the temporal trends of chronic kidney disease (CKD) burden in China during 1990-2019, evaluate their age, period and cohort effects, and predict the disease burden for the next 10 years.

Methods: Data were obtained from the Global Burden of Disease (GBD) 2019 study. Join-point regression model was used to estimate the average annual percentage change (AAPC) of CKD prevalence and mortality, and the age-period-cohort analysis was used to estimate the age, period and cohort effects. We extended the autoregressive integrated moving average (ARIMA) model to predict the disease burden of CKD in 2020-2029.

Results: In 2019, there were 150.5 million cases of (10.6%) and 196 726 deaths from (13.8 per 100 000 general population) CKD in China. Between 1990 and 2019, the prevalence and mortality rate of CKD increased significantly from 6.7% to 10.6%, and from 8.3/100 000 to 13.8/100 000. The AAPC was estimated as 1.6% and 1.8%, respectively. Females had a higher CKD prevalence of CKD but a lower mortality rate. Setting the mean level of age, period and cohort as reference groups, the risk of developing CKD increased with age [RR_age(15-19) = 0.18 to RR_age(85-89) = 2.45]. The cohort risk was significantly higher in the early birth cohort [RR_{cohort(1905-1909)} = 1.56]. In contrast, the increase in age-specific CKD mortality rate after 60-64 years was exponential [RR_age(60-64) = 1.24]. The cohort-based mortality risk remained high prior to the 1945-1949 birth cohorts (RR_cohort ranging from 1.69 to 1.89) and then declined in the 2000-2004 birth cohort [RR_{cohort(2000-2004)} = 0.22]. The CKD prevalence and mortality are projected to rise to 11.7% and 17.1 per 100 000, respectively, by 2029.

Conclusions: To reduce the disease burden of CKD, a comprehensive strategy that includes risk factors prevention at the primary care level, CKD screening among the elderly and high-risk population, and access to high-quality medical services is required.

Keywords: ARIMA model; age-period-cohort analysis; chronic kidney disease; disease burden; join-point regression.