{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T21:27:55Z","timestamp":1789248475844,"version":"build-2803163510"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,2,14]],"date-time":"2025-02-14T00:00:00Z","timestamp":1739491200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>This study explores the epidemic trend of tuberculosis (TB) in China from 1990 to 2021, analyzes its relationship with age-period-cohort factors from 1992 to 2021, and predicts the development trend of TB in China from 2022 to 2046.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Annual Percent Change (APC), Average Annual Percent Change (AAPC) and 95% confidence interval (<jats:italic>CI<\/jats:italic>) were calculated by Joinpoint regression model to describe the epidemic trend of TB in China. The Age-Period-Cohort (APC) model was used to explore the effects of age, period and cohort effects on the trend of TB incidence rate, mortality and DALYs rate. APC model and Bayesian Age-Period-Cohort (BAPC) model were used to predict the epidemic trend of TB in China from 2022 to 2046.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In 2021, it is estimated that there are 617,700 incidence cases of TB, 37,300 deaths and 1,375,500 DALYs cases in China, and the corresponding number of male cases is higher than that of female cases. From 1990 to 2021, the number of TB incidence, deaths and DALYs, as well as ASIR, ASDR and ASR of DALYs in China decreased year by year. The AAPC of ASIR, ASDR and ASR of DALYs were \u22123.33, \u22127.28% and \u22126.77%, respectively, all <jats:italic>p<\/jats:italic> &amp;lt;\u202f0.05, indicating that the overall trend showed a significant decrease. With the increase of age, the incidence rate of TB first decreased, then increased and then decreased, while the mortality and DALYs rate first decreased rapidly and then decreased slowly, and both reached the highest value in the &amp;lt;5\u202fyears age group. The period effect showed that the risk of the total population, male and female population decreased overall. The cohort effect showed that the risk of TB incidence rate, mortality and DALYs rate decreased significantly. The ASIR, ASDR and ASR of DALYs of TB in China are predicted to decrease year by year from 2022 to 2046. The BAPC model predicts that the number of incidence, deaths and DALYs will reach 177,100,077,000 and 181,700 in 2046, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The APC model shows that the earlier the contemporary people are born, the older the age, the higher the risk of disease. APC and BAPC models predict that the ASR of TB in China will decrease year by year, but men and the older adult are still at high risk of TB burden in China. It is recommended to strengthen the screening of TB patients in key populations, especially in the older adult.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpubh.2025.1512514","type":"journal-article","created":{"date-parts":[[2025,2,14]],"date-time":"2025-02-14T06:58:46Z","timestamp":1739516326000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Age-period-cohort analysis and prediction of tuberculosis trends in China\u2014based on the Global Burden of Disease 2021 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