School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Faculty of Medicine, Laval University, Quebec City, Quebec, Canada.
PLoS One. 2022 Jul 6;17(7):e0266521. doi: 10.1371/journal.pone.0266521. eCollection 2022.
Spatiotemporal modelling techniques allow one to predict injury across time and space. However, such methods have been underutilised in injury studies. This study demonstrates the use of statistical spatiotemporal modelling in identifying areas of significantly high injury risk, and areas witnessing significantly increasing risk over time.
We performed a retrospective review of hospitalised major trauma patients from the Victorian State Trauma Registry, Australia, between 2007 and 2019. Geographical locations of injury events were mapped to the 79 local government areas (LGAs) in the state. We employed Bayesian spatiotemporal models to quantify spatial and temporal patterns, and analysed the results across a range of geographical remoteness and socioeconomic levels.
There were 31,317 major trauma patients included. For major trauma overall, we observed substantial spatial variation in injury incidence and a significant 2.1% increase in injury incidence per year. Area-specific risk of injury by motor vehicle collision was higher in regional areas relative to metropolitan areas, while risk of injury by low fall was higher in metropolitan areas. Significant temporal increases were observed in injury by low fall, and the greatest increases were observed in the most disadvantaged LGAs.
These findings can be used to inform injury prevention initiatives, which could be designed to target areas with relatively high injury risk and with significantly increasing injury risk over time. Our finding that the greatest year-on-year increases in injury incidence were observed in the most disadvantaged areas highlights the need for a greater emphasis on reducing inequities in injury.
时空建模技术可用于预测时间和空间上的伤害。然而，此类方法在伤害研究中并未得到充分利用。本研究展示了统计时空建模在识别高伤害风险区域和随着时间推移风险显著增加区域方面的应用。
我们对澳大利亚维多利亚州创伤登记处 2007 年至 2019 年期间的住院重大创伤患者进行了回顾性研究。伤害事件的地理位置被映射到该州的 79 个地方政府区域（LGA）。我们采用贝叶斯时空模型来量化空间和时间模式，并在一系列地理偏远程度和社会经济水平上分析结果。
共纳入 31317 例重大创伤患者。对于整体重大创伤，我们观察到伤害发生率存在显著的空间差异，且每年伤害发生率呈 2.1%的显著增长。与大都市地区相比，区域地区的机动车碰撞致伤风险较高，而大都市地区的低坠伤风险较高。低坠伤的伤害风险呈显著上升趋势，在最弱势群体 LGA 中观察到的增幅最大。
这些发现可用于为伤害预防计划提供信息，这些计划可以针对具有相对较高伤害风险和随着时间推移风险显著增加的区域设计。我们发现，伤害发生率的年同比增幅最大的是最弱势群体的地区，这凸显了需要更加重视减少伤害方面的不平等。
