The Journal of Practical Medicine ›› 2026, Vol. 42 ›› Issue (17): 3083-3091.doi: 10.3969/j.issn.1006-5725.2026.17.006

• Chronic Disease Control • Previous Articles     Next Articles

Forecasting oral disease burden to 2041: Joinpoint and Bayesian Age-Period-Cohort modeling of GBD data

Yuzhuo Hei1, Jirong Yang2, Peixian Xiong2, Huisheng Feng2, Sai Zhang1, Yuyao Liu1, Zheng Chen1, Hong Ai1()   

  1. 1. Department of Stomatology,the Third Affiliated Hospital of Sun Yat?sen University,Guangzhou 510630,Guangdong,Chin
    2. Department of Anesthesiology,the Third Affiliated Hospital of Sun Yat?sen University,Guangzhou 510630,Guangdong,China
  • Received:2026-04-20 Online:2026-09-10 Published:2026-10-10
  • Contact: Hong Ai
  • About author:

    Hei Yuzhuo, Yang Jirong, and Xiong Peixian conceived and designed the study, analyzed and interpreted the data, and drafted and critically revised the manuscript. Feng Huisheng acquired the data, interpreted the results, and drafted the manuscript. Zhang Sai and Liu Yuyao analyzed and interpreted the data, and revised the manuscript. Chen Zheng and Ai Hong conceived and designed the study, interpreted the results, and revised the manuscript. All authors read and approved the final manuscript as submitted.

Abstract:

Objective This study aims to project the global burden of oral diseases through 2041, so as to fill this critical research gap. Methods We extracted data on the incidence, prevalence, and years lived with disability (YLDs) of oral diseases covering the period 1990—2021 from the Global Burden of Disease (GBD) database. Joinpoint regression analysis was performed to identify statistically significant temporal trends in oral disease burden, and a Bayesian age-period-cohort (BAPC) model was applied to project the future global oral disease burden for 2022—2041, adjusting for demographic covariates including population aging. Results From 1990 to 2021, the global age-standardized incidence, prevalence, and years lived with disability (YLD) rates for oral diseases remained relatively stable, despite substantial absolute increases in total case counts: incidence increased by 36%, prevalence by 52%, and YLDs by 81%. Joinpoint regression analysis revealed significant heterogeneity in trends across disease subtypes: the age-standardized incidence of permanent tooth caries followed a sustained upward trajectory, while that of deciduous tooth caries declined overall. Periodontal disease showed a gradual decreasing trend accompanied by stage-specific fluctuations, and edentulism reversed to an upward trend after 2015. Sex-stratified analyses showed broadly consistent trends between sexes; however, age-standardized incidence rates increased moderately in males, while remaining stable with a slight decrease in females. Further stratification by region and sociodemographic index (SDI) identified pronounced disparities: the African region experienced the largest absolute increase in incident cases (+113.6%), and China observed a marked increase in age-standardized incidence (estimated annual percentage change [EAPC], +0.71%), while Pakistan, Nigeria, and India exhibited downward trends. In addition, high-SDI regions recorded the fastest growth in YLD rates. BAPC projections predict a significant further increase in the above indicators by 2041, particularly for age-standardized incidence, which is projected to rise from 48,600 to 60 700 per 100 000 population, with older adults bearing a disproportionate burden of disease. Conclusions Our joinpoint regression analysis detected minimal historical improvement in global oral disease prevalence and incidence trends, indicating that currently deployed oral health strategies are insufficient to reverse the current disease burden trajectory. Projections from the BAPC model further demonstrate that without intensified population-level preventive measures and strengthened primary oral healthcare systems, the global burden of oral diseases will see a substantial increase by 2030, posing a major barrier to achieving the World Health Organization (WHO)’s 2030 global oral health targets.

Key words: oral disease burden, Joinpoint regression, Bayesian Age-Period-Cohort analysis, global burden of disease, disease projection

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