Evidence mapPaperPMID 40862126Full record

ArticleFrontiers in endocrinology2025

The global incidence rate of type 2 diabetes related chronic kidney disease and predictions by Bayesian age-period-cohort analysis: findings from the Global Burden of Disease Study 2019.

Junpu Yu, Fanhui Luo, Yiwen Zhang, Jingli Yang, Shuxia Yu, Nan Li, Aimin Yang, Li Ma, Jinsheng Li

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Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Junpu Yu *School of Public Health, Lanzhou University, Lanzhou, Gansu, China.
Fanhui Luo *School of Public Health, Lanzhou University, Lanzhou, Gansu, China.
Yiwen ZhangSchool of Public Health, Lanzhou University, Lanzhou, Gansu, China.
Jingli YangSchool of Public Health, Lanzhou University, Lanzhou, Gansu, China.
Shuxia YuSchool of Public Health, Lanzhou University, Lanzhou, Gansu, China.
Nan LiSchool of Public Health, Lanzhou University, Lanzhou, Gansu, China.
Aimin YangDepartment of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, Hong Kong SAR, China.
Li MaSchool of Public Health, Lanzhou University, Lanzhou, Gansu, China.
Jinsheng LiDepartment of Medical Administration, Gansu Provincial Maternity and Child-care Hospital, Lanzhou, Gansu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: To evaluate the spatial-temporal changes in the incidence of type 2 diabetes related chronic kidney disease (CKD-T2DM) from 1990 to 2019, categorized by age and sex in 21 regions with different socio-demographic indexes (SDI), and to predict the incidence rate between 2020 and 2030. Methods: Data on the burden of CKD-T2DM were obtained from the Global Burden of Disease Study 2019. Age-standardized incidence rates (ASIR) were estimated by sex, age, region, SDI, and specifically in China. The trends of ASIR were assessed using Joinpoint model to calculate the average annual percentage changes (AAPCs) and their 95% confidence intervals. Prediction was conducted using the Bayesian age-period-cohort (BAPC) model. Result: In 2019, the ASIR of global CKD-T2DM increased with age in both sexes, and was highest in the older 75 age group. The ASIR of CKD-T2DM in males was higher than those in females. Overall, the global ASIR of CKD-T2DM increased from 1990 to 2019 in both sexes and all age groups. The most significant increase was observed in the 15-49 age group [males: AAPC=1.42, 95%CI:(1.35-1.49); females: AAPC=1.18,95%CI:(1.13-1.23)]. Besides, the upward trends in ASIR of CKD-T2DM were observed in most SDI regions and GBD regions. The changing trends in ASIR of CKD-T2DM in China were similar to the global trends. Finally, the predicted ASIR was also found to be increased globally and also in China in both sex from 2020 to 2030. Conclusion: The global CKD-T2DM incidence rates increased from 1990 to 2019 in both sexes, most regions and in China., and also increased globally between 2020 and 2030. Therefore, it is important to input more medical resources and establish prevention strategies for the increasing trends of CKD-T2DM.

Indexed as

Diabetes Mellitus, Type 2Global Burden of DiseaseRenal Insufficiency, ChronicAdolescentAdultAgedAged, 80 and overAge FactorsBayes TheoremChinaCohort StudiesFemaleHumansIncidenceMaleMiddle AgedBayesian age-period-cohort modelchronic kidney diseaseincidencesociodemographic indextype 2 diabetes

Identifiers

PMID40862126
PMCPMC12375498

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.