Burden and future trends of facial fractures in China: a global perspective with machine learning projections to 2036

Facial fractures are among the most common types of fractures, potentially resulting in severe facial deformities, functional impairments, and even life-threatening complications. This study aims to evaluate the burden of facial fractures in China within a global context and provide a scientific foundation for the development of relevant healthcare policies. Using Global Burden of Disease (GBD) 2021 data, this study assessed China’s facial fracture burden, analyzing its distribution by age and sex. It examined 32-year trends and used time-series machine learning models to project the burden until 2036. The age-period-cohort (APC) model evaluated age, period, and birth cohort effects. Additionally, in a global context, the study explored socioeconomic influences through cross-country inequality and frontier analyses, identifying China’s relative global position. In 2021, China reported 1,194,145 (95% CI: 909,426 to 1,571,247) new facial fracture cases and 291,005 (95% CI: 251,615 to 340,269) total cases. The burden was higher in males, with 20–24 and 85–94 age groups at highest risk. From 1990 to 2021, the burden continued to rise, and projections suggest this trend may persist until 2036. While disparities among socio-demographic index (SDI) groups are narrowing, a mismatch between economic growth and healthcare development in China remains. China bears a higher burden of facial fractures compared to the global average, highlighting the need for targeted preventive and control measures for high-risk populations to effectively reduce the disease burden.

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Publication Details

Journal
BMC Oral Health
Published
2025-10-22
DOI
https://doi.org/10.1186/s12903-025-07076-x
Primary Topic
Facial Trauma and Fracture Management
Type
article
Field-Weighted Citation Impact
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Burden and future trends of facial fractures in China: a global perspective with machine learning projections to 2036

Yuyang Wang, Lu Fan, Xuanli Zhao, Yueyuan Yu
BMC Oral Health
Facial Trauma and Fracture Management
article

Burden and future trends of facial fractures in China: a global perspective with machine learning projections to 2036

Yuyang Wang, Lu Fan, Xuanli Zhao, Yueyuan Yu
article en

Abstract

Facial fractures are among the most common types of fractures, potentially resulting in severe facial deformities, functional impairments, and even life-threatening complications. This study aims to evaluate the burden of facial fractures in China within a global context and provide a scientific foundation for the development of relevant healthcare policies. Using Global Burden of Disease (GBD) 2021 data, this study assessed China’s facial fracture burden, analyzing its distribution by age and sex. It examined 32-year trends and used time-series machine learning models to project the burden until 2036. The age-period-cohort (APC) model evaluated age, period, and birth cohort effects. Additionally, in a global context, the study explored socioeconomic influences through cross-country inequality and frontier analyses, identifying China’s relative global position. In 2021, China reported 1,194,145 (95% CI: 909,426 to 1,571,247) new facial fracture cases and 291,005 (95% CI: 251,615 to 340,269) total cases. The burden was higher in males, with 20–24 and 85–94 age groups at highest risk. From 1990 to 2021, the burden continued to rise, and projections suggest this trend may persist until 2036. While disparities among socio-demographic index (SDI) groups are narrowing, a mismatch between economic growth and healthcare development in China remains. China bears a higher burden of facial fractures compared to the global average, highlighting the need for targeted preventive and control measures for high-risk populations to effectively reduce the disease burden.

BMC Oral HealthVol. 25(1)
Zhejiang Chinese Medical University (CN)
Openalex Percentile: Top 53%
Facial Trauma and Fracture Management
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Burden and future trends of facial fractures in China: a global perspective with machine learning projections to 2036 — Yuyang Wang, Lu Fan, et al. · BMC Oral Health (2025) | TGRS Research Map | TGRS