Age-period-cohort analysis and prediction of tuberculosis trends in China-based on the Global Burden of Disease 2021 data.

ABSTRACT:

Background

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.

Methods

Annual Percent Change (APC), Average Annual Percent Change (AAPC) and 95% confidence interval (CI) 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.

Results

In 2021, it is estimated that

SUBMITTER: Chen Z 

PROVIDER: S-EPMC11868063 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature