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    Home » Trend analysis and prediction of injury incidence in China from 1990 to 2019 based on Bayesian age-period-cohort model
    Injuries

    Trend analysis and prediction of injury incidence in China from 1990 to 2019 based on Bayesian age-period-cohort model

    TECHBy TECHMarch 28, 2026No Comments2 Mins Read
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    Trend analysis and prediction of injury incidence in China from 1990 to 2019 based on Bayesian age-period-cohort model
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    Background

    Injury is a major challenge to global public health. Analysing the trend of injury incidence in China from 1990 to 2019 and predicting future trends in incidence can provide a theoretical basis for injury prevention and control in China.

    Methods

    We collected age-standardised incidence rates of injuries in China from 1990 to 2019 from the Global Burden of Disease 2019 study. We analysed trends using joinpoint regression and age–period–cohort models. A prediction study was conducted using the Bayesian age-period-cohort model.

    Results

    From 1990 to 2019, there was an increasing trend in transport injuries, a decreasing trend in unintentional injuries and a decreasing trend in self-harm and interpersonal violence. The high-risk age for transport injuries, unintentional injuries and self-harm and interpersonal violence were 20–69 years (relative risk (RR)>1), ≤14 and ≥80 years (RR>1) and 20–24 years (RR=2.311, 95% CI 2.296 to 2.326), respectively. Projections indicate that by 2030, the incidence of transport and unintentional injuries will increase, whereas the incidence of self-harm and interpersonal violence will decrease.

    Conclusion

    The age group with the highest risk of transport injuries, unintentional injuries and self-harm and interpersonal violence were the 20–69 years, ≤ 14 and ≥80 years and 20–24 years age groups, respectively. Transport injuries and unintentional injuries will increase in 2020–2030, while self-harm and interpersonal violence will decrease. These can serve as a basis for developing measures to prevent and manage the impact of injuries.

    ageperiodcohort Analysis Based Bayesian China incidence Injury model prediction trend
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