@article{ref1,
title="Trend analysis and prediction of injury incidence in China from 1990 to 2019 based on Bayesian age-period-cohort model",
journal="Injury prevention",
year="2024",
author="Meng, Yuanjie and Wang, Chaocai and Liu, Yan",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="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. <br><br>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. <br><br>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. <br><br>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.<p /> <p>Language: en</p>",
language="en",
issn="1353-8047",
doi="10.1136/ip-2024-045303",
url="http://dx.doi.org/10.1136/ip-2024-045303"
}