Department of Orthopaedics, Wuhan Fourth Hospital, Qiaokou, Wuhan, 430000, China.
Department of Epidemiology, School of Public Health, Key Laboratory of Coal Environmental Pathogenicity and Prevention, Shanxi Medical University, Ministry Education, Taiyuan, 030001, China.
BMC Public Health. 2024 Nov 14;24(1):3162. doi: 10.1186/s12889-024-20675-7.
Bone fractures are a global public health issue and a major source of significant illness and financial hardship. However, to date, there is limited research on patella, tibia or fibula, or ankle fractures (FPTFA) disease burden.
Using the framework of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we conducted temporal trends of disease burden, effects of sex and socio-demographic index (SDI) on age standardized prevalence rate (ASPR) and age-period-cohort model. Machine learning models were built to predict the ASPR of FPTFA in 2035.
In 1990 and 2019, the top three of all fractures with the highest ASPR was FPTFA. Globally, in 2019, there were 13529.45 million (95%UI: 11811.02, 15642.25), 9198.67 million (95%UI: 8518.9, 10009.91) and 77.54 million (95%UI: 34.09, 149.9) prevalent cases of fracture attributable to fall, transport injury and mechanical external force, respectively. The number of fracture prevalence and years lived with disability (YLDs), and ASPR were higher in males than in females. From 1990 to 2019, most of GBD regions showed a downward trend in average annual percent change (AAPC) of ASPR attributable to transport injuries, High-income Asia Pacific had the highest decline (AAPC= -1.81%, 95%CI: -1.89% to -1.74%). However, an upward trend in East Asia was observed (AAPC = 1.60%, 95%CI: 1.48-1.73%). With increasing SDI, the ASPR for FPTFA attributed to the fall and mechanical external force slowly increased and then turned downward, especially in high-income and high-SDI countries. The longitudinal age curve suggested that the attributed rate was increased for the three sites of lower limb fractures. The best predictive models for FPTFA caused by falls, transport injuries and mechanical external force were autoregressive integrated moving average model (ARIMA) (0,2,1), ARIMA (2,0,1) and ARIMA (0,2,2), with R of 0.96, 0.78 and 0.94, respectively. By 2035, ASPR for the fall-related FPTFA will continue to rise rapidly, whereas the ASPR of the transport injury-related FPTFA will gradually decrease.
FPTFA attributed to the falls is the dominant type and the burden and trends of the fall-related FPTFA are substantial. Fall prevention and access to treatment are crucial for reducing FPTFA burden.
骨折是一个全球性的公共卫生问题，也是导致严重疾病和经济困难的主要原因。然而，迄今为止，有关髌骨、胫骨或腓骨或踝关节骨折（FPTFA）疾病负担的研究有限。
我们使用 2019 年全球疾病、伤害和危险因素研究（GBD）的框架，对疾病负担的时间趋势、性别和社会人口指数（SDI）对年龄标准化患病率（ASPR）的影响以及年龄-时期-队列模型进行了研究。我们还建立了机器学习模型来预测 2035 年 FPTFA 的 ASPR。
1990 年和 2019 年，所有骨折中 ASPR 最高的前三种都是 FPTFA。在全球范围内，2019 年，归因于跌倒、交通伤害和机械外力的骨折分别有 13529.45 亿例（95%UI：11811.02，15642.25）、9198.67 亿例（95%UI：8518.9，10009.91）和 77.54 万例（95%UI：34.09，149.9）。骨折患病率、残疾生存年（YLDs）和 ASPR 男性均高于女性。1990 年至 2019 年，大多数 GBD 地区归因于交通伤害的 ASPR 的平均年百分比变化（AAPC）呈下降趋势，亚太高收入地区的降幅最大（AAPC=-1.81%，95%CI：-1.89%至-1.74%）。然而，东亚呈上升趋势（AAPC=1.60%，95%CI：1.48-1.73%）。随着 SDI 的增加，归因于跌倒和机械外力的 FPTFA 的 ASPR 先缓慢上升，然后下降，特别是在高收入和高 SDI 国家。纵向年龄曲线表明，下肢三个部位的骨折发生率都有所增加。跌倒、交通伤害和机械外力导致的 FPTFA 的最佳预测模型分别为自回归积分移动平均模型（ARIMA）（0，2，1）、ARIMA（2，0，1）和 ARIMA（0，2，2），预测值分别为 0.96、0.78 和 0.94。到 2035 年，归因于跌倒的 FPTFA 的 ASPR 将继续快速上升，而归因于交通伤害的 FPTFA 的 ASPR 将逐渐下降。
跌倒相关的 FPTFA 是主要类型，跌倒相关 FPTFA 的负担和趋势很大。预防跌倒和获得治疗对于降低 FPTFA 的负担至关重要。
