Trends and levels of the global, regional, and national burden of injuries from 1990 to 2021: findings from the global burden of disease study 2021

Jiaqi Lou; Ziyi Xiang; Xiaoyu Zhu; Youfen Fan; Jingyao Song; Shengyong Cui; Jiliang Li; Guoying Jin; Neng Huang; Xin Le

doi:10.1080/07853890.2025.2537917

. 2025 Jul 31;57(1):2537917. doi: 10.1080/07853890.2025.2537917

Trends and levels of the global, regional, and national burden of injuries from 1990 to 2021: findings from the global burden of disease study 2021

Jiaqi Lou ^a,^#, Ziyi Xiang ^b,^#, Xiaoyu Zhu ^c,^#, Youfen Fan ^a,^#, Jingyao Song ^d, Shengyong Cui ^a, Jiliang Li ^a, Guoying Jin ^a, Neng Huang ^a, Xin Le ^a,^✉

PMCID: PMC12315186 PMID: 40744902

Abstract

Background/Objectives

Injuries remain a major global public health challenge. This study aimed to analyze the global, regional, and national burden of injuries from 1990 to 2021 and project future trends to 2046, addressing a gap in long-term trend analyses and projections accounting for demographic shifts.

Patients/Materials and Methods

We conducted an observational analysis using data from the Global Burden of Disease (GBD) Study 2021, covering 204 countries and territories. We extracted data on injury incidence, prevalence, mortality, and disability-adjusted life years (DALYs). Age-standardized rates (ASRs) were calculated. Temporal trends (1990–2021) were assessed using estimated annual percentage change (EAPC). Future burden (2022–2046) was projected using statistical modeling.

Results

Globally, while absolute numbers of injury incidence, prevalence, deaths, and DALYs increased from 1990 to 2021, all corresponding ASRs declined significantly (EAPC: incidence – 0.96%, prevalence – 0.73%, mortality – 1.55%, and DALYs – 1.75%). Males consistently bore a greater burden than females (mortality ratio male:female = 2.41). Marked disparities existed: mortality rates in low Socio-demographic Index (SDI) regions were 2.5 times higher than in high SDI regions. Afghanistan, the Central African Republic, and Lesotho had the highest national mortality rates; Singapore, Spain, and Italy the lowest. Projections indicate rising absolute cases but declining ASRs through 2046.

Conclusion

Despite declining ASRs, the increasing absolute injury burden necessitates intensified prevention efforts. Targeted interventions are crucial to address persistent geographic, demographic (especially males), and socioeconomic (low SDI regions) disparities.

Keywords: Global burden of disease (GBD), injuries, Disease burden, Disability-Adjusted life years (DALYs), Age-Standardized rates (ASRs), Age-Period-Cohort (APC), autoregressive Integrated moving average (ARIMA), trend

1. Background

In medical science, “injury” refers to physical harm resulting from the harmful transfer of energy or substances between an individual and their environment. Injuries are generally categorized as either unintentional—such as those caused by road traffic accidents, falls, or burns—or intentional, including those resulting from self-harm, violence, or war [1]. According to the World Health Organization (WHO), injuries constitute a significant global public health concern and are the fifth leading cause of mortality worldwide, following malignancies, cardiovascular and cerebrovascular diseases, respiratory conditions, and myocardial infarction [2]. In 2019, injuries accounted for nearly 500,000 deaths annually in the European Region—equivalent to one death per minute and over 5% of all deaths in the region [3]. Globally, injuries are responsible for approximately 5 million deaths each year. Marked disparities exist in injury-related mortality and disability between developed and developing regions. In 2019, low- and middle-income countries (LMICs) accounted for nearly 90% of all injury-related deaths. Road traffic injuries alone caused 1.35 million deaths annually, primarily affecting individuals aged 5–29 years [4]. In contrast, high-income countries (HICs) reported drowning mortality rates 3.4 times lower than those in LMICs [5]. Age-specific patterns are also evident: in the European Region, adults aged 60 and older have the highest injury-related mortality rates, while injuries account for nearly half of all deaths among individuals aged 15–29 [4]. In the United States, youth violence-related injuries generate an annual economic burden of $122 billion [6]. Many high-income countries have successfully reduced injury incidence through comprehensive safety education and environmental interventions. For instance, Sweden’s “Vision Zero” road safety initiative has significantly lowered traffic fatalities through infrastructure redesign, speed regulation, and vehicle safety enhancements [7]. In drowning prevention, the WHO’s 2021 Global Drowning Prevention Resolution provides a comprehensive framework and practical roadmap to guide national strategies [8]. Japan has implemented earthquake-resistant building codes and early warning systems, substantially reducing injury-related mortality during natural disasters [9]. In the United States, household disaster preparedness is actively promoted through measures such as emergency kits, food and water reserves, and alternative communication plans, all aimed at strengthening residents’ disaster response capabilities [10,11].

The term disease burden refers to the impact of illness, disability, and premature death on population health and socioeconomic development. Quantifying disease burden enables the evaluation of health losses attributable to various diseases and risk factors, providing a foundation for identifying major health threats and prioritizing public health interventions [4]. A key indicator used in this quantification is Disability-Adjusted Life Years (DALYs), which aggregate Years of Life Lost (YLL) due to premature mortality and Years Lived with Disability (YLD) [5]. According to the Global Burden of Disease (GBD) study, global injury-related deaths increased from 4.26 million in 1990 to 4.48 million in 2017. However, during the same period, the age-standardized mortality rate decreased from 1079 to 738 per 100,000 population, indicating a relative decline in the burden of injuries despite ongoing global population growth and aging [12]. While existing databases such as GBD offer valuable insights into injury-related outcomes, they often lack long-term trend analyses and future projections that account for demographic transitions and socioeconomic developments. To address this gap, our study extends the existing literature by analyzing trends in injury burden from 1990 to 2021 and, uniquely, projecting these trends through 2046. This dual approach captures both historical dynamics and future patterns, offering policymakers critical, evidence-based forecasts for long-term planning and resource allocation. Furthermore, by presenting both absolute figures and age-standardized rates, our analysis disentangles the influence of demographic changes—such as population growth and aging—on injury burden. By adopting a comprehensive temporal lens, this study provides a nuanced understanding of the evolving global injury burden, supporting the development of targeted, data-driven prevention and control strategies tailored to regional and demographic contexts.

2. Methods

2.1. Data sources and extraction

This study utilized data from the Global Burden of Disease (GBD) 2021 database (https://ghdx.healthdata.org/gbd-2021), a widely recognized and authoritative resource offering extensive estimates on health outcomes related to a broad spectrum of diseases, injuries, and risk factors [13–15]. As a flagship initiative in global epidemiology, the GBD 2021 Study represents the most comprehensive and methodologically rigorous assessment to date, covering 371 diseases and injuries, 88 key risk factors, and data from 204 countries and territories [13–15].

The Human Research Ethics Committee of Ningbo No.2 Hospital granted exemption from ethics approval and waived the requirement for informed consent for this study, as it exclusively utilized publicly available, de-identified data. Furthermore, this research was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki.

For this analysis, we focused specifically on the “Injuries” category within the GBD dataset. Data extraction was conducted using the following parameters: (1) Cause of death or injury, selected under the “GBD Estimate” option; (2) Incidence, prevalence, DALYs, and mortality under the Measure option; and (3) both number (absolute values in the population) and rate (per 100,000 population) under the Metric option. The study period spanned from 1990 to 2021, enabling a robust and comprehensive assessment of long-term trends in injury burden.

The GBD Study employs a rigorous data collection methodology that integrates diverse sources, including population-based surveys, vital registration systems, hospital discharge records, and peer-reviewed literature, thereby establishing a comprehensive and robust evidence base [16,17]. Injuries are classified in the GBD framework into several major categories: transport injuries; unintentional injuries (such as falls, fires, heat and hot substances, natural disasters, mechanical forces, and contact with venomous animals and plants); self-harm and interpersonal violence; and collective violence and legal interventions. For this study, we extracted data on incidence, prevalence, mortality, and DALYs related to injuries, with detailed stratification by age, sex, and geographic region.

2.2. Disease definition and classification

According to the GBD 2021 classification system, diseases and injuries are organized into a four-level hierarchical structure. At the first level, they are broadly categorized into communicable, maternal, neonatal, and nutritional diseases; non-communicable diseases; and injuries. Injuries are coded based on the International Classification of Diseases, 10th Revision (ICD-10). The GBD 2021 framework identifies 29 specific non-fatal injury causes, including transport injuries, falls, drowning, self-harm, interpersonal violence, and animal contact (with sexual violence treated separately within the GBD methodology).

Injury incidence was defined using ICD-9 codes E000–E999 and ICD-10 chapters V through Y, while morbidity estimation was based on ICD-10 chapters S and T and ICD-9 codes 800–999. Additionally, the analysis incorporated fatal discontinuities—defined as abrupt and unexpected spikes in mortality that deviate from expected trends. These included deaths resulting from state actor violence (e.g. police conflicts and executions), armed conflict and terrorism, and exposure to forces of nature.

2.3. Burden estimation methodology

Under the GBD 2021 framework, burden estimation was performed using DisMod-MR, a Bayesian meta-regression tool regarded as the gold standard for modeling disease burden across different sexes, age groups, geographies, and time periods [18,19]. The estimation process involved rigorous data quality control, with systematic biases addressed through cross-validation procedures using adjustment factors generated by the MR-BRT (meta-regression—Bayesian, regularized, trimmed) tool [18,19]. In line with established GBD methodology, both excess mortality and remission rates were conservatively assumed to be zero in the DisMod-MR model to ensure consistency and methodological robustness [16,19].

2.4. Statistical analysis

To detail our methodological approach, we first conducted a comprehensive analysis of the global incidence, prevalence, mortality, and disability-adjusted life years (DALYs) attributable to injuries in 2021, alongside their respective age-standardized rates (ASRs) [20]. This analysis was stratified by age group, sex, Socio-Demographic Index (SDI) regions, GBD super-regions, and individual countries, thereby providing a multidimensional understanding of the global injury burden.

We then explored temporal trends in the injury burden from 1990 to 2021, both globally and across the aforementioned stratifications. A linear regression model was employed to calculate the Estimated Annual Percentage Change (EAPC), which served as the basis for a subsequent hierarchical cluster analysis [21]. This clustering analysis enabled the identification of regional patterns and grouped the 54 GBD regions into four distinct trend categories: those with a significant increase, a minor increase, a stable or minor decrease, and a significant decrease in burden over time. To assess future trends, we projected the global injury burden from 2022 to 2046 using two complementary statistical approaches: the Age-Period-Cohort (APC) model and the Autoregressive Integrated Moving Average (ARIMA) model [22].

All statistical tests were conducted using a significance threshold of p < 0.05. Analyses were performed using R software (version 4.0.2), which was also utilized for database construction, data integration, and statistical computations, ensuring both the accuracy and reproducibility of the results.

3. Results

3.1. Global burden of injuries

In 2021, there were 607,789,604 incident cases of injury worldwide, reflecting an increase from 554,872,072 cases in 1990. Despite this absolute rise, the age-standardized incidence rate (ASIR) declined from 10,264.62 to 7705.75 per 100,000 population (EAPC: −0.96%, 95% CI: −1.00 to −0.92). A similar trend was observed in prevalence: the number of prevalent injury cases rose from 1,030,712,875 in 1990 to 1,456,350,420 in 2021, while the age-standardized prevalence rate (ASPR) decreased from 21,445.74 to 17,531.20 per 100,000 population (EAPC: −0.73%, 95% CI: −0.76 to −0.70).

For mortality, although the absolute number of deaths rose from 4,185,780 in 1990 to 4,343,698 in 2021, the age-standardized mortality rate (ASMR) experienced a marked decline, falling from 84.86 to 53.66 per 100,000 population (EAPC: −1.55%, 95% CI: −1.67 to −1.43). Likewise, the burden of injuries measured in DALYs decreased both in absolute numbers (from 278,725,498 to 247,843,924) and in age-standardized rates (from 5221.14 to 3101.29 per 100,000 population; EAPC: −1.75%, 95% CI: −1.87 to −1.64). Significant gender disparities were observed across all metrics. Males exhibited higher rates than females in incidence (9240.23 vs. 6,101.04 per 100,000), prevalence (19,469.12 vs. 15,614.65 per 100,000), mortality (76.33 vs. 31.68 per 100,000), and DALYs (4274.42 vs. 1,915.82 per 100,000). The male-to-female ratio was particularly pronounced for mortality (2.41) and DALYs (2.23). (Table 1, Figures 1, S1, and S2)

Table 1.

Incidence, prevalence, deaths, and disability-adjusted life years (DALYs) of injuries and their estimated annual percentage changes (EAPCs) from 1990 to 2021, stratified by sex and age groups.

	Incidence (95% Ul)					prevalence (95% Ul)					Death (95% Ul)					DALYs (95% Ul)
	1990		2021		EAPC (95% CI)	1990		2021		EAPC (95% CI)	1990		2021		EAPC (95% CI)	1990		2021		EAPC (95% CI)
	Number	ASR	Number	ASR	EAPC (95% CI)	Number	ASR	Number	ASR	EAPC (95% CI)	Number	ASR	Number	ASR	EAPC (95% CI)	Number	ASR	Number	ASR	EAPC (95% CI)
Global	554872072 (520239997-592107015)	10264.62 (9647.3-10944.94)	607789604 (574661712-644552987)	7705.75 (7271.61-8171.19)	−0.96 (-1 to −0.92)	1030712875 (980087458-1086397210)	21445.74 (20428.04-22536.24)	1456350420 (1385784930-1535575907)	17531.2 (16677.62-18485.66)	−0.73 (-0.76 to -0.7)	4185780 (3974301-4373502)	84.86 (80.77-88.56)	4343698 (3984365-4631455)	53.66 (49.18-57.28)	−1.55 (-1.67 to −1.43)	278725498 (262114155-298335835)	5221.14 (4898.12-5617.65)	247843924 (226826042-272347784)	3101.29 (2839.62-3408.68)	−1.75 (-1.87 to −1.64)
Sex
Female	206296712 (192720806-220728987)	7748.53 (7253.71-8272.83)	241536635 (227019750-258048940)	6101.04 (5720.99-6517.85)	−0.82 (-0.87 to −0.77)	454215595 (431259253-482858117)	18600.22 (17702.92-19664.17)	659887942 (626207235-699380173)	15614.65 (14799.02-16552.27)	−0.66 (-0.69 to −0.62)	1341532 (1240245-1418673)	54.14 (49.81-57.21)	1341233 (1189014-1460392)	31.68 (27.96-34.53)	−1.8 (-1.93 to −1.66)	92440215 (85100637-100736554)	3483.33 (3206.67-3816.24)	77069874 (68189581-86579634)	1915.82 (1700.54-2143.15)	−2.01 (-2.15 to −1.88)
Male	348575360 (326639487-371744791)	12662.94 (11886.94-13476.97)	366252969 (345806132-388346253)	9240.23 (8719.52-9797.86)	−1.05 (-1.08 to −1.01)	576497280 (548985608-604435769)	24309.91 (23188.91-25422.16)	796462477 (757035396-836992129)	19469.12 (18518.91-20452.38)	−0.78 (-0.81 to −0.75)	2844248 (2689990-2986573)	116.58 (110.42-122.38)	3002465 (2774333-3211181)	76.33 (70.54-81.56)	−1.43 (-1.56 to −1.31)	186285284 (175573632-199033803)	6937.09 (6531.06-7440.54)	170774050 (158019392-186766835)	4274.42 (3950.99-4677.63)	−1.62 (-1.74 to −1.51)
Age
<5 years	60049363 (54344811-67063079)	9686.35 (8766.17-10817.71)	38735921 (34846500-43263991)	5885.38 (5294.44-6573.36)	−1.68 (-1.8 to −1.57)	12627047 (11633874-13651596)	2036.82 (1876.62-2202.09)	7994636 (7287722-8661668)	1214.67 (1107.27-1316.02)	−1.81 (-1.91 to −1.71)	620974 (542723-696813)	100.17 (87.54-112.4)	199926 (144395-257478)	30.38 (21.94-39.12)	−3.65 (-3.83 to −3.46)	55302570 (48432131-61867415)	8920.66 (7812.42-9979.61)	17993435 (13140645-23031679)	2733.85 (1996.54-3499.34)	−3.62 (-3.8 to −3.43)
5-9 years	56661337 (47555782-67671390)	9710.09 (8149.66-11596.89)	45587208 (38239234-54353399)	6635.18 (5565.68-7911.09)	−1.13 (-1.21 to −1.05)	30533942 (27569621-34139633)	5232.62 (4724.62-5850.53)	24512483 (21942283-27471765)	3567.77 (3193.68-3998.49)	−1.24 (-1.3 to −1.19)	222243 (200209-244219)	38.09 (34.31-41.85)	93553 (81492-105535)	13.62 (11.86-15.36)	−3.14 (-3.37 to −2.91)	19654744 (17771571-21514373)	3368.25 (3045.52-3686.93)	8583861 (7630448-9554623)	1249.37 (1110.6-1390.67)	−3.04 (-3.26 to −2.82)
10-14 years	54100087 (44200638-64318794)	10099.28 (8251.27-12006.88)	48246172 (39670864-57034436)	7237.26 (5950.9-8555.56)	−1.1 (-1.16 to −1.04)	46054183 (41255838-51429165)	8597.29 (7701.54-9600.68)	41899345 (37108062-47610225)	6285.19 (5566.47-7141.86)	−1.08 (-1.12 to −1.04)	154060 (142858-164211)	28.76 (26.67-30.65)	93849 (83134-103010)	14.08 (12.47-15.45)	−2.14 (-2.36 to −1.92)	13703784 (12744940-14775125)	2558.19 (2379.2-2758.19)	8623711 (7857353-9488583)	1293.62 (1178.66-1423.35)	−2.07 (-2.27 to −1.87)
15-19 years	65524767 (56663676-75877580)	12614.9 (10908.96-14608.04)	56850035 (49290882-65491413)	9110.88 (7899.43-10495.76)	−1.06 (-1.15 to −0.97)	70858392 (63497266-80093506)	13641.74 (12224.57-15419.69)	64721327 (57133874-74713856)	10372.34 (9156.36-11973.76)	−0.95 (-0.99 to −0.91)	332705 (317161-347418)	64.05 (61.06-66.89)	242864 (225923-258602)	38.92 (36.21-41.44)	−1.56 (-1.93 to −1.2)	26695998 (25397687-28216925)	5139.54 (4889.59-5432.35)	19601258 (18381973-21114771)	3141.33 (2945.92-3383.89)	−1.56 (-1.9 to −1.23)
20-24 years	64313738 (56639707-74306456)	13069.56 (11510.08-15100.24)	57659905 (50840333-66533621)	9655.72 (8513.71-11141.71)	−1.08 (-1.14 to −1.01)	88734427 (79599339-99742964)	18032.23 (16175.84-20269.34)	84160885 (74181506-96454577)	14093.57 (12422.42-16152.27)	−0.85 (-0.89 to −0.81)	380651 (363128-395785)	77.35 (73.79-80.43)	313307 (295977-329886)	52.47 (49.56-55.24)	−1.34 (-1.57 to −1.12)	29100652 (27693404-30519016)	5913.71 (5627.74-6201.94)	23857459 (22574137-25490575)	3995.17 (3780.26-4268.65)	−1.36 (-1.56 to −1.16)
25-29 years	53119213 (46320690-62966377)	12001.1 (10465.12-14225.84)	52055049 (45310822-60733113)	8847.74 (7701.43-10322.74)	−0.99 (-1.05 to −0.94)	94143009 (85653947-103842278)	21269.5 (19351.59-23460.84)	98980656 (88933256-111052670)	16823.62 (15115.88-18875.49)	−0.81 (-0.84 to −0.77)	321886 (307653-332561)	72.72 (69.51-75.13)	294284 (277745-308817)	50.02 (47.21-52.49)	−1.29 (-1.46 to −1.13)	23903553 (22620400-25309273)	5400.47 (5110.57-5718.06)	21700580 (20439259-23161678)	3688.42 (3474.04-3936.76)	−1.32 (-1.47 to −1.18)
30-34 years	43447422 (36652395-50474946)	11272.67 (9509.67-13096)	49806759 (42300824-57690372)	8239.6 (6997.88-9543.8)	−1.04 (-1.09 to −0.98)	94441638 (87330324-102747826)	24503.41 (22658.34-26658.49)	119256468 (108309364-132471561)	19728.76 (17917.77-21914.96)	−0.78 (-0.81 to −0.75)	284222 (272004-293926)	73.74 (70.57-76.26)	296316 (280270-311726)	49.02 (46.37-51.57)	−1.43 (-1.58 to −1.28)	20187811 (18957494-21631593)	5237.84 (4918.63-5612.44)	21136594 (19701955-22742167)	3496.66 (3259.32-3762.27)	−1.43 (-1.55 to −1.3)
35-39 years	36261171 (30674261-43077708)	10294.32 (8708.23-12229.49)	43846120 (37320468-51458271)	7817.57 (6654.08-9174.79)	−1.04 (-1.13 to −0.95)	94061210 (87653341-101408945)	26703.39 (24884.23-28789.36)	122774085 (113080124-134617514)	21890.09 (20161.7-24001.72)	−0.74 (-0.78 to −0.71)	275845 (261684-288132)	78.31 (74.29-81.8)	284915 (265388-301557)	50.8 (47.32-53.77)	−1.57 (-1.72 to −1.43)	18452410 (17154079-19916499)	5238.52 (4869.94-5654.17)	19423222 (17849812-21206765)	3463.08 (3182.54-3781.07)	−1.51 (-1.63 to −1.4)
40-44 years	27163386 (22876304-32262172)	9481.72 (7985.26-11261.51)	35849848 (30599499-41815940)	7166.38 (6116.83-8359)	−1.06 (-1.15 to −0.98)	82678477 (76706991-88166620)	28859.96 (26775.54-30775.66)	118452798 (108503910-128176746)	23678.68 (21689.9-25622.5)	−0.75 (-0.79 to −0.71)	229566 (217260-240039)	80.13 (75.84-83.79)	270362 (250628-287660)	54.05 (50.1-57.5)	−1.6 (-1.76 to −1.43)	14547199 (13398403-15894366)	5077.88 (4676.88-5548.13)	17380695 (15867122-19170917)	3474.4 (3171.83-3832.26)	−1.52 (-1.65 to −1.38)
45-49 years	20040723 (16898656-23769485)	8630.97 (7277.77-10236.84)	31780623 (26821728-37355106)	6711.79 (5664.51-7889.07)	−0.95 (-1.02 to −0.88)	70779811 (66432359-75665756)	30482.85 (28610.53-32587.09)	119252284 (110867688-129218928)	25185.03 (23414.28-27289.9)	−0.73 (-0.78 to − to −0.68)	192284 (181849-200895)	82.81 (78.32-86.52)	256094 (237247-273691)	54.08 (50.1-57.8)	−1.53 (-1.71 to −1.34)	11388288 (10368780-12568908)	4904.61 (4465.54-5413.07)	15615423 (14107057-17409670)	3297.84 (2979.29-3676.77)	−1.44 (-1.59 to −1.29)
50-54 years	17759923 (14996455-21050633)	8354.8 (7054.78-9902.85)	29028054 (24792747-34146707)	6524.29 (5572.37-7674.75)	−0.8 (-0.86 to −0.75)	70517779 (66867209-74301775)	33173.68 (31456.34-34953.79)	118945010 (111630934-126969400)	26733.84 (25089.95-28537.39)	−0.75 (-0.79 to −0.71)	201002 (190016-210447)	94.56 (89.39-99)	259266 (238027-278207)	58.27 (53.5-62.53)	−1.69 (-1.88 to −1.51)	10902886 (9877218-12117912)	5129.05 (4646.54-5700.63)	14678954 (13103175-16548594)	3299.21 (2945.04-3719.43)	−1.54 (-1.67 to −1.41)
55-59 years	14510424 (12559266-17218341)	7835 (6781.46-9297.16)	25628464 (22208179-30083098)	6476.28 (5611.98-7601.96)	−0.56 (-0.59 to −0.53)	64765114 (61659524-67859768)	34970.37 (33293.49-36641.35)	113584688 (107249662-120584667)	28702.72 (27101.86-30471.6)	−0.71 (-0.74 to −0.68)	185694 (174244-194694)	100.27 (94.08-105.13)	258212 (234851-277170)	65.25 (59.35-70.04)	−1.53 (-1.66 to −1.4)	9217922 (8277994-10341086)	4977.28 (4469.76-5583.74)	13376148 (11869497-15171432)	3380.14 (2999.41-3833.8)	−1.39 (-1.48 to −1.29)
60-64 years	12133113 (10507656-14158625)	7554.43 (6542.37-8815.57)	21459987 (18451261-24645381)	6705.24 (5765.16-7700.53)	−0.34 (-0.39 to −0.3)	60976302 (58271251-63641245)	37965.63 (36281.38-39624.9)	100768328 (95615041-105799605)	31485.39 (29875.23-33057.43)	−0.69 (-0.74 to −0.64)	170806 (161668-178873)	106.35 (100.66-111.37)	232133 (212465-246640)	72.53 (66.39-77.06)	−1.41 (-1.54 to −1.28)	7779751 (6882261-8835924)	4843.9 (4285.1-5501.5)	10995439 (9715745-12572935)	3435.56 (3035.72-3928.45)	−1.27 (-1.36 to −1.18)
65-69 years	9107107 (7824604-10677429)	7367.65 (6330.1-8638.04)	18688738 (15935953-21942271)	6775.16 (5777.2-7954.65)	−0.18 (-0.22 to −0.14)	49792052 (47575308-52246999)	40281.75 (38488.4-42267.8)	94402769 (89240538-99824665)	34223.47 (32352.03-36189.05)	−0.63 (-0.65 to −0.6)	151690 (141288-159347)	122.72 (114.3-128.91)	241896 (220175-258251)	87.69 (79.82-93.62)	−1.23 (-1.4 to −1.06)	6022230 (5285409-6849767)	4871.98 (4275.89-5541.46)	9997326 (8698172-11526581)	3624.29 (3153.31-4178.69)	−1.1 (-1.21 to −0.98)
70-74 years	6718115 (5629165-7816678)	7935.3 (6649.05-9232.9)	15706286 (13179127-18355875)	7630.37 (6402.63-8917.58)	−0.12 (-0.16 to −0.07)	36181066 (34566576-38034907)	42736.32 (40829.32-44926.04)	78810028 (74366744-83937323)	38287.18 (36128.56-40778.1)	−0.49 (-0.54 to −0.44)	131734 (121244-139149)	155.6 (143.21-164.36)	236969 (213004-253366)	115.12 (103.48-123.09)	−1.02 (-1.16 to −0.88)	4342202 (3827783-4969689)	5128.92 (4521.3-5870.09)	8265906 (7150239-9560597)	4015.71 (3473.7-4644.69)	−0.88 (-0.98 to −0.79)
75-79 years	6052861 (5155037-7011297)	9833.17 (8374.61-11390.2)	12619743 (10780549-14618333)	9568.79 (8174.24-11084.2)	−0.04 (-0.1-0.03)	30192183 (28661072-31794018)	49048.71 (46561.34-51650.97)	57043924 (53415104-60829908)	43252.97 (40501.46-46123.66)	−0.4 (-0.44 to −0.36)	126073 (117071-132488)	204.81 (190.19-215.23)	215913 (194622-231923)	163.71 (147.57-175.85)	−0.81 (-0.9 to −0.71)	3492906 (3039266-4019138)	5674.4 (4937.44-6529.29)	6116706 (5236885-7078759)	4637.93 (3970.81-5367.4)	−0.7 (-0.77 to −0.64)
80-84 years	4467753 (3812359-5203447)	12629.36 (10776.7-14709.01)	11257604 (9593190-13105369)	12853.63 (10953.25-14963.36)	0.05 (0.01-0.1)	19977427 (18720574-21251758)	56471.81 (52918.96-60074.07)	45517502 (42015319-49193208)	51970.67 (47971.97-56167.49)	−0.3 (-0.32 to −0.27)	99998 (91408-106048)	282.67 (258.39-299.77)	208837 (180723-226795)	238.44 (206.34-258.95)	−0.49 (-0.58 to −0.41)	2288508 (1979673-2655431)	6469.11 (5596.1-7506.32)	4854273 (4137126-5676531)	5542.48 (4723.66-6481.31)	−0.48 (-0.53 to −0.43)
85-89 years	2420701 (2034507-2931914)	16019.38 (13463.68-19402.42)	7786677 (6541213-9377024)	17030.56 (14306.55-20508.87)	0.13 (0.03-0.22)	9625370 (9074669-10208552)	63697.46 (60053.11-67556.76)	28386873 (26267358-30494020)	62086.09 (57450.41-66694.72)	−0.11 (-0.15 to −0.07)	67935 (59861-73320)	449.57 (396.14-485.21)	185228 (154600-205802)	405.12 (338.13-450.12)	−0.22 (-0.33 to −0.11)	1208733 (1045511-1401331)	7998.99 (6918.84-9273.54)	3318997 (2845878-3883412)	7259.11 (6224.34-8493.57)	−0.26 (-0.31 to −0.21)
90-94 years	813130 (700536-965679)	18975.37 (16347.86-22535.28)	3808835 (3330580-4394162)	21291.05 (18617.65-24562.97)	0.35 (0.24-0.46)	3015390 (2849423-3175890)	70367.75 (66494.71-74113.22)	12695230 (11883308-13403575)	70965.2 (66426.63-74924.79)	0 (-0.04-0.04)	28082 (23938-30819)	655.34 (558.62-719.2)	112757 (88999-126567)	630.3 (497.5-707.5)	0.1 (-0.01-0.2)	419992 (363319-487986)	9801.02 (8478.48-11387.74)	1689013 (1433342-1985591)	9441.43 (8012.25-11099.27)	0.01 (-0.05-0.08)
95+ years	207737 (164096-271148)	20404.7 (16118.07-26633.08)	1387575 (1132776-1725097)	25458.65 (20783.71-31651.36)	0.59 (0.44-0.74)	758057 (725668-795032)	74458.97 (71277.65-78090.78)	4191099 (4010218-4391298)	76896.55 (73577.82-80569.71)	0.04 (-0.01-0.09)	8329 (6687-9399)	818.15 (656.79-923.16)	47018 (35902-53895)	862.67 (658.72-988.85)	0.33 (0.24-0.42)	113360 (97224-132553)	11134.58 (9549.63-13019.79)	634923 (533283-748030)	11649.3 (9784.46-13724.55)	0.21 (0.18-0.25)

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Figure 1. — Numbers and age-standardized rates of injury-related incidence, prevalence, deaths, and disability-adjusted life years (DALYs) for both sexes in 2021. The figure presents detailed data on incidence (new cases and age-standardized incidence rates), prevalence (existing cases and age-standardized prevalence rates), deaths (number and age-standardized death rates), and DALYs (disability-adjusted life years and age-standardized DALY rates), with emphasis on differences between male and female populations.

3.2. Age-Specific injury burden patterns

Analysis by age group revealed distinct patterns in the injury burden. In terms of incidence in 2021, the highest age-standardized incidence rates (ASIRs) were observed among individuals aged 90–94 years (21,291.05 per 100,000) and those aged 95 years and above (25,458.65), while the lowest ASIRs were recorded among children aged <5 years (5,885.38) and 5–9 years (6635.18). Regarding prevalence, the highest age-standardized prevalence rates (ASPRs) were also found in the 95+ years (76,896.55 per 100,000) and 90–94 years (70,965.20) age groups, whereas the lowest ASPRs were observed among those aged <5 years (1,214.67) and 5–9 years (3,567.77). In terms of mortality, the highest age-standardized mortality rates (ASMRs) occurred in the 95+ years (862.67 per 100,000) and 90–94 years (630.30) age groups, with the lowest rates seen in the 5–9 years (13.62) and 10–14 years (14.08) age groups. For DALYs, the highest age-standardized rates were among those aged 95+ years (11,649.30 per 100,000) and 90–94 years (9,441.43), while the lowest were among children aged 5–9 years (1,249.37) and 10–14 years (1,293.62). Notably, the Estimated Annual Percentage Change (EAPC) for all indicators demonstrated a declining trend across most age groups. The most pronounced decreases were found in the youngest age groups, with EAPCs for incidence, mortality, and DALYs in the <5 years group being −1.68, −3.65, and −3.62, respectively. In contrast, the oldest age groups often exhibited stable or increasing trends. For instance, the 95+ years group showed a positive EAPC for mortality (0.33) and DALYs (0.21) (Table 1, Figures 2, and S3)

Figure 2. — Numbers and age-standardized rates of injury-related incidence, prevalence, deaths, and DALYs across different age groups in 2021. The figure provides detailed data on incidence (new cases and age-standardized incidence rates), prevalence (existing cases and age-standardized prevalence rates), deaths (number and age-standardized death rates), and DALYs (disability-adjusted life years and age-standardized DALY rates), highlighting variations among different age groups.

3.3. Socio-demographic index regional patterns

Analysis across Socio-Demographic Index (SDI) quintiles revealed clear and consistent gradients in the injury burden. In 2021, regions with higher SDI levels generally reported higher ASIRs and ASPRs, while regions with lower SDI levels experienced significantly higher mortality and DALY burdens. Specifically, the High SDI region recorded the highest ASIR at 12,676.57 per 100,000, followed by High-middle, Middle, Low-middle, and Low SDI regions in descending order. A similar trend was observed for ASPR, with the High SDI region reaching 21,100.73 per 100,000. In contrast, mortality and DALY burdens were inversely associated with SDI levels. The Low SDI region exhibited the highest ASMR at 88.69 per 100,000—more than twice that of the High SDI region (35.39). The same pattern was evident in age-standardized DALY rates, with the Low SDI region at 4357.93 compared to 2263.82 per 100,000 in the High SDI region. These disparities suggest considerable differences in injury outcomes linked to socio-economic development.

Temporal trend analysis showed that all SDI regions experienced declines in ASRs from 1990 to 2021, with Low-middle and Low SDI regions exhibiting the slowest reductions in ASMR and DALYs. Detailed data are presented in Tables S1, S3, S5, S7, and Figures S4–S5.

3.4. Global burden of disease regional variations

Marked disparities in injury burden were observed across the 21 Global Burden of Disease (GBD) regions in 2021. Australasia recorded the highest age-standardized incidence rate (ASIR) at 26,096.64 per 100,000. Conversely, Western Africa had the lowest ASIR (4,786.13 per 100,000). Australasia also had the highest age-standardized prevalence rate (ASPR) at 33,009.36 per 100,000, whereas Western Africa reported the lowest (11,650.97 per 100,000). The highest age-standardized mortality rate (ASMR) was seen in the Central African Republic (173.44 per 100,000), while the lowest was in Singapore (13.43 per 100,000). Similarly, the Central African Republic exhibited the highest age-standardized DALY rate (9,268.91 per 100,000), compared to the lowest in Singapore (1,280.59 per 100,000). Detailed data are available in Table S1, S3, S5, S7, and Figure S6.

3.5. World Bank regional patterns of injury burden

Significant disparities in injury burden were evident across World Bank income groups in 2021. High-income regions reported the highest ASIR (13,292.37 per 100,000), while lower-middle-income regions had the lowest (6,093.98 per 100,000). A similar pattern was observed for ASPR, with high-income regions reaching 21,785.78 per 100,000 and lower-middle-income regions at the bottom (14,755.57 per 100,000). In contrast, low-income regions experienced the highest ASMR (85.74 per 100,000), while high-income regions recorded the lowest ASMR (35.28 per 100,000). The DALY rate followed the same pattern: highest in low-income regions (4526.37 per 100,000) and lowest in high-income regions (2290.19 per 100,000). Comprehensive data are presented in Tables S1, S3, S5, S7, and Figure S6.

3.6. Country-level variations in injury burden

At the national level, considerable heterogeneity in injury burden was observed across 204 countries and territories in 2021. Australia recorded the highest ASIR (25,252.16 per 100,000), while Bangladesh had the lowest (4025.16 per 100,000). For ASPR, Slovenia had the highest rate (36,025.08 per 100,000), in contrast to Indonesia, which had the lowest (12,167.50 per 100,000). The highest ASMR was observed in Afghanistan (211.87 per 100,000), while Singapore reported the lowest (13.43 per 100,000). Regarding DALYs, the Central African Republic bore the highest burden (9268.91 per 100,000), whereas Singapore had the lowest (1280.59 per 100,000). Detailed country-level statistics and trend estimates are provided in Tables S2, S4, S6, S8, and Figures S7–S8.

3.7. Future trends in global injury burden

Based on predictive analyses utilizing both the Age-Period-Cohort (APC) and Autoregressive Integrated Moving Average (ARIMA) models, the global injury burden is projected to undergo substantial changes from 2022 to 2046. According to the APC model, although the absolute number of injury incidence cases is expected to increase—from 249,152,844 to 299,706,055 for females, and from 377,551,755 to 414,577,361 for males—the age-standardized incidence rates (ASIRs) are projected to decline from 6193.66 to 5994.18 per 100,000 for females and from 9369.95 to 8910.73 per 100,000 for males. Similarly, the number of prevalent cases is expected to rise—from 669,926,710 to 865,471,202 for females and from 808,794,014 to 1,005,288,778 for males—while the age-standardized prevalence rates (ASPRs) will decrease from 15,501.45 to 14,653.59 per 100,000 for females and from 19,326.15 to 18,009.95 per 100,000 for males. Regarding mortality, the APC model forecasts a rise in absolute deaths—from 1,415,269 to 1,873,510 among females and from 3,131,708 to 3,574,183 among males—accompanied by a decrease in age-standardized mortality rates (ASMRs), from 32.80 to 28.18 per 100,000 for females and from 77.80 to 66.27 per 100,000 for males. Trends in DALYs follow a similar pattern, with increasing absolute numbers but declining age-standardized rates. The ARIMA model predicts even steeper decreases in age-standardized rates across all metrics, particularly for females. For example, the ASMR is projected to decline sharply from 30.82 to 12.83 per 100,000, and the age-standardized DALY rate from 1824.53 to 542.03 per 100,000. These projections reflect a continuing demographic transition in the global injury burden, where population growth and aging contribute to rising absolute numbers, while improvements in prevention and treatment drive declines in age-standardized rates. Notably, males are expected to bear a consistently higher burden across all metrics throughout the forecast period. (See Table 2, Figures 3, and 4).

Table 2.

Predicted global numbers and age-standardized rates of incidence, prevalence, deaths, and DALYs related to injuries by sex from 2022 to 2046.

		APC model								ARIMA model
Year	Sex	Age-standardized incidence rate	Number of incidence cases	Age-standardized prevalence rate	Number of prevalence cases	Age-standardized deaths rate	Number of deaths cases	Age-standardized DALYs rate	Number of DALYs cases	Age-standardized incidence rate	Number of incidence cases	Age-standardized prevalence rate	Number of prevalence cases	Age-standardized deaths rate	Number of deaths cases	Age-standardized DALYs rate	Number of DALYs cases
2022	Female	6193.66	249152844	15501.45	669926710.2	32.8	1415268.978	1992.43	81573190.5	6012.809115	241818442.3	15544.37796	665974731.1	30.82177008	1371776.495	1824.527397	76845956.77
2023	Female	6190.93	251708299.3	15447.42	677854124.1	32.63	1431686.888	1987.94	82282388.68	5973.496539	243263621.6	15444.78699	670998769.1	30.05880354	1371776.495	1782.842272	76131636.16
2024	Female	6188.19	254299774.3	15393.39	685917335.8	32.45	1449639.045	1983.44	82996002.62	5905.454787	244010752.8	15336.41093	676276263.6	29.28483828	1371776.495	1722.90941	75559273.9
2025	Female	6177	256593532	15344.14	694266461.7	32.19	1465305.857	1969.8	83402266.84	5854.285204	245176728	15229.69884	682262653.6	28.59496732	1371776.495	1673.094842	74986911.64
2026	Female	6165.81	258848711	15294.88	702551621.6	31.93	1480501.747	1956.16	83783298.82	5793.206877	246091387.7	15127.95357	688829943	27.8154776	1371776.495	1625.181537	74414549.38
2027	Female	6154.62	261047923.7	15245.63	710692871.3	31.66	1494650.225	1942.53	84129908.4	5737.94779	247156842.1	15030.76104	695655446.7	27.06610419	1371776.495	1571.488144	73842187.12
2028	Female	6143.44	263241991	15196.38	718842404.6	31.4	1509081.668	1928.89	84461727.52	5679.27116	248131816.4	14936.4739	702480228.4	26.31303408	1371776.495	1506.231838	73269824.86
2029	Female	6132.25	265464489.4	15147.12	727113182.4	31.13	1524762.716	1915.25	84793439.12	5622.601596	249161080.8	14843.53138	709192098.1	25.57528085	1371776.495	1458.563963	72697462.6
2030	Female	6122.81	267745098.6	15109.21	735896011.9	30.92	1543187.535	1904.65	85242740.33	5564.753316	250157769.9	14750.91705	715794213.6	24.81813614	1371776.495	1403.171731	72125100.34
2031	Female	6113.36	269989404.4	15071.31	744584404.8	30.71	1561498.982	1894.05	85670813.82	5507.597276	251174004.9	14658.14872	722338405.8	24.06939152	1371776.495	1352.537703	71552738.08
2032	Female	6103.92	272173775	15033.4	753100770.2	30.49	1579183.033	1883.45	86068653.63	5450.034695	252178512	14565.09933	728873827.7	23.31927598	1371776.495	1299.19402	70980375.82
2033	Female	6094.48	274340198.3	14995.49	761488387.6	30.28	1597268.936	1872.85	86451817.15	5392.710869	253190056.1	14471.81436	735425871.2	22.57195468	1371776.495	1242.134942	70408013.56
2034	Female	6085.04	276521826.1	14957.58	769920916.5	30.07	1616554.441	1862.25	86833697.17	5335.246826	254197377.8	14378.38791	741997928.6	21.82054907	1371776.495	1186.527984	69835651.3
2035	Female	6077.25	278743636.7	14930.99	778833821.9	29.9	1638853.079	1854.46	87331457.29	5277.865131	255207233	14284.9011	748582273	21.07131798	1371776.495	1135.466064	69263289.04
2036	Female	6069.46	280912611.1	14904.4	787580775	29.74	1660948.742	1846.68	87806134.83	5220.435074	256215568.1	14191.40361	755169897.7	20.32161695	1371776.495	1081.339309	68690926.78
2037	Female	6061.67	283001083.1	14877.81	796073102.9	29.58	1682219.261	1838.89	88247111.03	5163.033418	257224815.2	14097.91728	761755380.7	19.57243799	1371776.495	1028.41292	68118564.52
2038	Female	6053.88	285053569.6	14851.21	804391351	29.41	1703693.479	1831.1	88671056.1	5105.615083	258233515.1	14004.44647	768337350.5	18.82241729	1371776.495	973.3828359	67546202.26
2039	Female	6046.09	287101448.1	14824.62	812663519	29.25	1726141.557	1823.31	89090020.28	5048.206544	259242543.4	13910.98769	774916826.3	18.07293055	1371776.495	918.2618071	66973840
2040	Female	6038.67	289103058.7	14800.19	820877021.3	29.1	1749000.848	1816.25	89512957.94	4990.792252	260251374.7	13817.53571	781495397.5	17.32329689	1371776.495	864.9463272	66401477.75
2041	Female	6031.25	291032056.2	14775.75	828858983.4	28.94	1771179.657	1809.19	89905969.35	4933.381338	261260324.1	13724.08638	788074170.8	16.57376586	1371776.495	812.030733	65829115.49
2042	Female	6023.84	292860496	14751.32	836538500.5	28.79	1791983.029	1802.14	90257923.58	4875.96844	262269202.7	13630.63728	794653534.1	15.82406418	1371776.495	757.9132512	65256753.23
2043	Female	6016.42	294637532.2	14726.89	844004763	28.64	1812425.944	1795.08	90586724.01	4818.556708	263278123.8	13537.18746	801233384.8	15.07448845	1371776.495	703.9206832	64684390.97
2044	Female	6009.01	296389776.4	14702.45	851367913.7	28.49	1833296.269	1788.02	90902831.99	4761.144291	264287019.3	13443.7368	807813454.1	14.32487016	1371776.495	649.3137874	64112028.71
2045	Female	6001.59	298087933	14678.02	858548130.4	28.33	1853863.953	1780.96	91195745.91	4703.732276	265295930.2	13350.28553	814393524.8	13.57527356	1371776.495	595.3990122	63539666.45
2046	Female	5994.18	299706055.4	14653.59	865471202.4	28.18	1873509.665	1773.91	91456264.16	4646.320025	266304831.9	13256.83394	820973501.9	12.82564271	1371776.495	542.0303361	62967304.19
2022	Male	9369.95	377551755.3	19326.15	808794014	77.8	3131708.319	4399.76	179293789.2	9129.816474	366252969.3	19251.27872	799729436.7	75.79846599	3049154.375	4180.558686	173664610.5
2023	Male	9354.37	380229119.6	19238.98	817188974	77.02	3142899.922	4371.78	179850082.9	9019.406359	366252969.3	18968.21156	801658551.4	74.41414987	3067711.571	4082.863362	173664610.5
2024	Male	9338.8	382857204.7	19151.81	825610879.8	76.23	3154447.446	4343.8	180345860.4	8908.996245	366252969.3	18697.97178	808537229.1	73.02983375	3075087.318	4003.575932	173664610.5
2025	Male	9312.04	385014518	19074.98	834458024.4	75.47	3168020.844	4307.83	180569667.3	8798.586131	366252969.3	18485.08326	815415906.8	71.64551763	3078018.884	3915.416546	173664610.5
2026	Male	9285.28	387077890.9	18998.15	843126841.5	74.7	3180080.706	4271.85	180723681.1	8688.176017	366252969.3	18332.00575	822294584.5	70.26120151	3079184.065	3826.500743	173664610.5
2027	Male	9258.52	389041991.8	18921.32	851537760.8	73.94	3189974.064	4235.88	180801334.4	8577.765902	366252969.3	18212.90847	829173262.2	68.87688539	3079647.178	3740.693511	173664610.5
2028	Male	9231.77	390928692.8	18844.49	859828807.5	73.17	3199129.7	4199.9	180815112.6	8467.355788	366252969.3	18095.53363	836051939.9	67.49256927	3079831.247	3653.421141	173664610.5
2029	Male	9205.01	392748121.3	18767.65	868108438.4	72.41	3208509.816	4163.93	180771480.2	8356.945674	366252969.3	17958.26114	842930617.7	66.10825315	3079904.407	3566.002994	173664610.5
2030	Male	9183.36	394691676	18709.19	877110899.9	71.88	3228611.495	4139.36	181192323.5	8246.53556	366252969.3	17796.25152	849809295.4	64.72393703	3079933.485	3479.109579	173664610.5
2031	Male	9161.72	396534127.1	18650.72	885913975.5	71.36	3247619.534	4114.8	181549787.3	8136.125445	366252969.3	17617.7199	856687973.1	63.33962091	3079945.042	3391.974345	173664610.5
2032	Male	9140.08	398284603.6	18592.25	894466065.6	70.83	3265079.429	4090.24	181847329.3	8025.715331	366252969.3	17435.54541	863566650.8	61.95530479	3079949.636	3304.811505	173664610.5
2033	Male	9118.43	399886976.9	18533.78	902773159.8	70.31	3281536.991	4065.68	182053391.6	7915.305217	366252969.3	17259.71472	870445328.5	60.57098867	3079951.462	3217.737205	173664610.5
2034	Male	9096.79	401406751.5	18475.31	911021454.7	69.78	3298222.735	4041.12	182203509.4	7804.895103	366252969.3	17093.76855	877324006.2	59.18667254	3079952.188	3130.623016	173664610.5
2035	Male	9079.63	403026264.4	18434.92	920007370.2	69.47	3325421.936	4026.82	182798188.7	7694.484988	366252969.3	16935.46196	884202683.9	57.80235642	3079952.476	3043.50367	173664610.5
2036	Male	9062.47	404537094.7	18394.54	928773367	69.17	3351617.354	4012.53	183335864.6	7584.074874	366252969.3	16779.84306	891081361.6	56.4180403	3079952.591	2956.399258	173664610.5
2037	Male	9045.31	405936475	18354.15	937263573.3	68.86	3376230.893	3998.23	183814144.9	7473.66476	366252969.3	16622.48206	897960039.3	55.03372418	3079952.636	2869.28827	173664610.5
2038	Male	9028.15	407225496.1	18313.76	945533635.8	68.55	3400252.19	3983.94	184235046.8	7363.254646	366252969.3	16461.31703	904838717	53.64940806	3079952.654	2782.17633	173664610.5
2039	Male	9010.99	408417755.2	18273.37	953711019.4	68.24	3424494.446	3969.64	184604472.5	7252.844531	366252969.3	16296.76039	911717394.7	52.26509194	3079952.661	2695.066907	173664610.5
2040	Male	8996.67	409634660.4	18235.74	961832959.3	67.96	3449674.922	3956.83	184999090.4	7142.434417	366252969.3	16130.63326	918596072.4	50.88077582	3079952.664	2607.956401	173664610.5
2041	Male	8982.35	410732563.4	18198.11	969694145.4	67.68	3473491.502	3944.02	185331690	7032.024303	366252969.3	15964.83159	925474750.2	49.4964597	3079952.665	2520.845721	173664610.5
2042	Male	8968.02	411703879.3	18160.48	977247484.3	67.4	3495303.087	3931.21	185597297.7	6921.614189	366252969.3	15800.43048	932353427.9	48.11214358	3079952.666	2433.735465	173664610.5
2043	Male	8953.7	412582632	18122.84	984538739.1	67.11	3516044.389	3918.4	185809857.2	6811.204074	366252969.3	15637.48214	939232105.6	46.72782746	3079952.666	2346.62503	173664610.5
2044	Male	8939.38	413359148.1	18085.21	991683967.1	66.83	3536465.098	3905.59	185967101.8	6700.79396	366252969.3	15475.35427	946110783.3	45.34351134	3079952.666	2259.514564	173664610.5
2045	Male	8925.06	414025668.3	18047.58	998620475.2	66.55	3555994.642	3892.77	186065943.4	6590.383846	366252969.3	15313.26245	952989461	43.95919521	3079952.666	2172.40417	173664610.5
2046	Male	8910.73	414577360.7	18009.95	1005288778	66.27	3574183.115	3879.96	186105529.9	6479.973732	366252969.3	15150.6836	959868138.7	42.57487909	3079952.666	2085.293746	173664610.5

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Figure 3. — Predicted injury-related numbers (bars) and age-standardized rates (trend lines per 100,000 population) of incidence, prevalence, deaths, and DALYs by sex globally from 2022 to 2046, using the age-period-cohort (APC) model. The figure displays age-standardized incidence rates, prevalence rates, death rates, and DALY rates for both males and females across the forecast period.

Figure 4. — Predicted injury-related numbers (bars) and age-standardized rates (trend lines per 100,000 population) of incidence, prevalence, deaths, and DALYs by sex globally from 2022 to 2046, using the autoregressive integrated moving average (ARIMA) model. The figure shows age-standardized incidence rates, prevalence rates, death rates, and DALY rates for both males and females over the prediction period.

4. Discussion

4.1. Main findings and key results

This study aimed to analyze the global burden of injuries from 1990 to 2021 and project future trends through 2046. Our comprehensive assessment revealed several key findings. While the absolute numbers of injury-related incidence, prevalence, deaths, and DALYs have increased over the past three decades, age-standardized rates for all metrics have declined significantly. This trend suggests that although population growth and aging have led to a greater absolute burden, the risk per individual has decreased, likely due to advancements in healthcare systems and injury prevention strategies [23–26].

4.2. Gender disparities in injury burden

Our gender-specific analysis revealed that males consistently experience a greater injury burden than females across all metrics, with male-to-female ratios of 2.41 for mortality and 2.23 for DALYs. This finding aligns with previous studies indicating that males are more likely to engage in high-risk behaviors and occupations, resulting in higher injury rates [15,20,27]. These disparities emphasize the importance of gender-specific prevention strategies that address behaviors more commonly associated with injury risk in males. This is particularly critical for the working-age population, which is especially susceptible to certain types of injuries [28]. Public health interventions should incorporate these gender differences when developing educational campaigns and implementing safety regulations.

4.3. Age-related variations in injury risk

Age-based analysis revealed distinct patterns in the global injury burden. The highest age-standardized incidence rates were observed among individuals aged 90–94 and those aged 95 and older, whereas the lowest rates were found in children under 5 years old and those aged 5–9. Similar trends were noted for prevalence, mortality, and DALYs, with the oldest age groups experiencing a substantially higher burden across all metrics. This age-related distribution may be partly explained by socioeconomic factors [29], indicating that injury risk fluctuates significantly across different life stages. The markedly higher burden among older adults underscores the need for specialized medical services targeting this vulnerable demographic, whose diminished physical resilience may hinder full recovery following injury [30,31]. Future research should explore strategies to mitigate the influence of socioeconomic disparities on injury risk through targeted community-based resource allocation and tailored healthcare services for disadvantaged populations.

4.4. Socio-demographic index regional patterns

At the regional level, our analysis revealed substantial variation in injury burden, reflecting disparities in healthcare infrastructure, socioeconomic development, and other key determinants. Regions with a low Socio-Demographic Index (SDI) exhibited the highest age-standardized mortality rates (88.69 per 100,000) and DALY rates (4357.93 per 100,000), nearly 2.5 times higher than those in high SDI regions (35.39 and 2263.82 per 100,000, respectively). This striking disparity highlights the urgent need for international collaboration and equitable resource distribution to alleviate the injury burden in low SDI regions [32,33]. The inverse relationship between age-standardized DALY rates and SDI quintiles identified in this study is consistent with findings from the GBD 2019 analysis [27], reinforcing the pivotal role of socioeconomic development in reducing injury-related health outcomes.

4.5. Global burden of disease regional and country-level variations

Country-level analysis across 204 countries and territories revealed significant heterogeneity in injury burden. Nations such as Afghanistan, the Central African Republic, and Lesotho reported the highest age-standardized mortality rates, while countries like Singapore, Spain, and Italy recorded the lowest. These findings are consistent with previous research by Wang et al. [25], further highlighting differences in country-specific injury risk profiles and healthcare system responsiveness. The observed disparities underscore the need for global policymakers to consider local contexts when designing and implementing injury prevention strategies [34]. These country-level variations may be partially attributable to differences in urbanization processes. Rapid urban expansion is often associated with elevated injury risk, particularly due to increases in traffic accidents and occupational hazards [35,36]. In contrast, countries with lower injury burdens have typically implemented robust safety measures. High-income countries, for instance, have established well-developed trauma care systems integrated with public health infrastructure—features that are often lacking in low- and middle-income countries [37]. This suggests that future research should focus on urban planning and occupational safety regulations aimed at minimizing injury risks, especially in rapidly urbanizing areas of the developing world.

4.6. Future trends and climate change impacts

Our projections indicate a rising trend in the absolute numbers of incidence, prevalence, mortality, and DALYs from 2022 to 2046, despite ongoing declines in age-standardized rates. This underscores the necessity for sustained and enhanced efforts in injury prevention and medical treatment strategies. Emerging evidence highlights that environmental changes, notably climate change and natural disasters, exert significant influence on injury rates [38,39]. Research has shown that rising temperatures are correlated with increased rates of injury-related hospitalizations, with the heat-attributable fraction of all injuries rising slightly from 23.2% in the 2000s to 23.6% in the 2010s [28].

Climate change contributes to a growing injury burden that varies by geographic region, injury type, and demographic group [40]. These findings imply that future injury prevention strategies must incorporate climate adaptation measures. Studies indicate that extreme weather events associated with climate change—including heatwaves, floods, and storms—are linked to diverse injury mechanisms, ranging from drowning to transport-related incidents [39,41]. Future research should focus on enhancing infrastructure resilience, developing effective early warning systems, and promoting community preparedness to reduce injury burdens amid environmental challenges.

4.7. Strengths and limitations

This analysis offers critical insights into the global burden of injuries, identifying particularly vulnerable populations and regions. However, several limitations warrant consideration. The quality and completeness of data depend heavily on national surveillance and reporting systems, with some countries lacking adequate infrastructure or exhibiting underreporting due to stigma or cultural factors [42,43]. Moreover, substantial variability exists in injury classification and reporting across data sources, complicating data comparison and interpretation [44,45]. The GBD study relies on statistical modeling to estimate disease burdens where direct data are unavailable. Although these models are invaluable, they inherently introduce uncertainty and may be biased by the quality and representativeness of underlying data [44,46]. Additionally, GBD estimates may not fully capture the long-term consequences of injuries, such as chronic disability, mental health sequelae, and reductions in quality of life, which remain difficult to quantify [47]. Finally, despite comprehensive injury data, the GBD dataset often lacks detailed information on modifiable risk factors critical for designing targeted prevention interventions.

4.8. Conclusion and recommendations

In conclusion, this study underscores the substantial global health burden imposed by injuries and highlights the imperative for strengthened preventive measures, particularly among vulnerable demographic groups and severely impacted regions. To mitigate this burden, it is essential to adopt and refine injury prevention and management strategies tailored to the specific regional and demographic contexts [48]. Key elements include building resilient health systems, implementing comprehensive educational initiatives, advancing appropriate safety regulations, and fostering enhanced international collaboration.

Efforts should prioritize reducing absolute case numbers while continuing to lower age-standardized rates [49]. Prevention programs must target high-risk populations defined by gender, age, and socioeconomic status. Regional and context-specific approaches are crucial for risk mitigation and case management, with some areas requiring interventions focused on injury types disproportionately prevalent locally [50]. Given the ongoing influence of climate change on injury patterns worldwide [51], integrated strategies addressing both injury prevention and climate adaptation will become increasingly vital for effective public health planning and policy development.

Supplementary Material

Supplemental Material

IANN_A_2537917_SM8166.zip^{(9.5MB, zip)}

Acknowledgements

We would like to extend our gratitude to all members of the Global Burden of Disease Collaborative Network and the Institute for Health Metrics and Evaluation (IHME) for their invaluable contributions. All authors have read and approved the final work.

Glossary

Abbreviations

APC: Annual percentage change
ARIMA: Autoregressive integrated moving average
ASDR: Age-Standardized Deaths Rate
ASDAR: Age-Standardized DALYs Rate
ASIR: Age-Standardized Incidence Rate
ASR: Age-standardized rates
CI: Confidence interval
DALYs: Disability-adjusted life years
DW: Disability Weight
EAPC: Estimated annual percentage change
GBD: Global Burden of Disease
SDI: Socio-demographic Index
YLD: Years Lived with Disability
YLL: Years of Life Loss
UI: Uncertainty Intervals

Funding Statement

This work was supported by the HwaMei Reasearch Foundation of the Ningbo No.2 Hospital (Grant No.2022HMKY48 and No.2023HMZD07), the Medical Scientific Reasearch Foundation of Zhejiang Province (Grant No. 2021KY1004, No. 2023RC081, No. 2025KY1395 and No.2022KY1134), the Project of NINGBO Leading Medical & Health Discipline (2022-F17), the Ningbo Top Medical and Health Research Program (No.2023030615), the Zhejiang Clinovation Pride (CXTD202502004), Research and development of efficient hemostatic materials (2024001), the Zhu Xiu Shan Talent Project of Ningbo No.2 Hospital (Project Number: 2023HMYQ25), and the Ningbo Health Youth Technical Backbone Talent Development Program (2024RC-QN-02). Funders played no role in the study design, execution or manuscript writing.

Ethics statement

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The datasets generated and analyzed in this study are publicly accessible through the Global Burden of Disease (GBD) Data Tool repository at http://ghdx.healthdata.org/gbd-results-tool. This platform offers open access to the GBD database, with no permissions required and no additional consent needed from the Institute for Health Metrics and Evaluation (IHME) for data usage. While most data utilized in this study are available via the GBD Data Tool, certain datasets may be withheld due to ethical, privacy, or security considerations. For specific data inquiries or requests, please contact the corresponding author, Xin Le, who will assist in facilitating access in accordance with Taylor & Francis’s Share upon Reasonable Request policy.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Material

IANN_A_2537917_SM8166.zip^{(9.5MB, zip)}

Data Availability Statement

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PERMALINK

Trends and levels of the global, regional, and national burden of injuries from 1990 to 2021: findings from the global burden of disease study 2021

Jiaqi Lou

Ziyi Xiang

Xiaoyu Zhu

Youfen Fan

Jingyao Song

Shengyong Cui

Jiliang Li

Guoying Jin

Neng Huang

Xin Le

Roles

Abstract

Background/Objectives

Patients/Materials and Methods

Results

Conclusion

1. Background

2. Methods

2.1. Data sources and extraction

2.2. Disease definition and classification

2.3. Burden estimation methodology

2.4. Statistical analysis

3. Results

3.1. Global burden of injuries

Table 1.

Figure 1.

3.2. Age-Specific injury burden patterns

Figure 2.

3.3. Socio-demographic index regional patterns

3.4. Global burden of disease regional variations

3.5. World Bank regional patterns of injury burden

3.6. Country-level variations in injury burden

3.7. Future trends in global injury burden

Table 2.

Figure 3.

Figure 4.

4. Discussion

4.1. Main findings and key results

4.2. Gender disparities in injury burden

4.3. Age-related variations in injury risk

4.4. Socio-demographic index regional patterns

4.5. Global burden of disease regional and country-level variations

4.6. Future trends and climate change impacts

4.7. Strengths and limitations

4.8. Conclusion and recommendations

Supplementary Material

Acknowledgements

Glossary

Abbreviations

Funding Statement

Ethics statement

Disclosure statement

Data availability statement

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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