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. 2023 Mar 30;10(4):651. doi: 10.3390/children10040651

Fractures in Children Due to Firearm Activity

Randall T Loder 1,*, Taylor Luster 2
Editor: Johannes Mayr
PMCID: PMC10136767  PMID: 37189900

Abstract

The purpose of this study was to investigate fracture patterns due to pediatric firearm injuries. The data used was from the US Firearm Injury Surveillance Study 1993–2019. Over these 27 years, there were 19,033 children with fractures due to firearm activity with an average age of 12.2 years; 85.2% were boys and the firearm was a powder type in 64.7%. The finger was the most common fracture location, while the tibia/fibula was the most common location for those admitted to the hospital. Children ≤ 5 years of age sustained more skull/face fractures; most spine fractures occurred in the 11–15-year age group. The injury was self-inflicted in 65.2% of the non-powder and 30.6% of the powder group. The injury intent was an assault in 50.0% of the powder and 3.7% of the non-powder firearm group. Powder firearms accounted for the majority of the fractures in the ≤5 and 11–15 year-olds, non-powder firearms accounted for the majority of the fractures in the 6–10 year-olds. Injuries occurring at home decreased with increasing age; there was an increase in hospital admissions over time. In conclusion, our findings support the need for safe storage of firearms in the home away from children. This data will be helpful to assess any changes in prevalence or demographics with future firearm legislation or other prevention programs. The increasing acuity of firearm-associated injuries seen in this study is detrimental to the child, impacts familial wellbeing, and results in significant financial costs to society.

Keywords: firearm, fracture, children, demographics, spine, extremity, hospital admission

1. Introduction

Injuries due to firearms are a significant health burden [1,2,3]. Deaths attributed to firearms in the US population are equivalent to those from motor vehicle crashes and falls [2]. Additionally, firearm injuries result in significant societal costs, including both financial damage and loss of human life/work [3,4,5]. These injuries do not occur solely in adults, but also in children [6,7,8,9]. Pediatric firearm injuries result in significant costs to society [6,10,11,12]. Deleterious firearm injuries in children also result in emotional trauma for families due to the loss or injury of a child, financial burden [6,7,8,9], and rehabilitation costs, as 8.4% of children with firearm injuries are discharged to a rehabilitation facility [13].

Pediatric orthopaedists are often called upon to care for a child with a fracture arising from a firearm injury [14]. There are several studies regarding firearm injury fracture patterns and associated demographics in children [14,15,16,17,18,19,20,21,22,23,24]. These studies, although informative, are limited in scope by various parameters. For example, some studies only include a certain geographic area [16,19,20,23,24,25], only those admitted to the hospital [14,19,20,24], short time periods [16,17,23,25], or difficult fractures [15,26]. Most are either limited to powder firearms [14,15,16,17,19,20,23,24,25] or non-powder firearms [18] and very few studies mention spine fractures [14,19]. The difference between powder and non-powder firearms is the source of the energy used to project the bullet out of the gun. Powder firearms use the gases from the explosion of the gunpowder, while non-powder firearms use compressed air or other gases. One study covers an entire nation, albeit a small one (Jamaica) [17].

It was the purpose of this study to concentrate on the demographics and fracture patterns of injuries due to firearms in children over a quarter of a century using a national emergency department (ED) visit the database. This will include both those treated and released as well as admitted to the hospital, all areas of the country, and both powder and non-powder firearms. The strength of this study is that it will provide a large overview of pediatric fractures from injuries due to firearm activity, be useful as baseline data for future studies regarding these injuries, and perhaps serve as a guide for injury prevention programs.

2. Materials and Methods

2.1. Data Source

The data for this study was obtained from the Inter-University Consortium for Political and Social Research Firearm Injury Surveillance Study 1993–2020 (ICPSR 38574) (https://www.icpsr.umich.edu/web/NACJD/studies/38574, accessed on 18 December 2022) collected by the National Electronic Injury Surveillance System (NEISS). The NEISS, a branch of the US Consumer Product Safety Commission, collects data from a probability sample of hospitals in the United States and its territories that have at least six beds and an ED. The sample contains five strata, four based on size (the total number of emergency room visits reported by the hospital and are small, medium, large, and very large) and one stratum consisting of children’s hospitals. There are ~100 hospitals in the NEISS, and this number varies slightly from year to year. Patient information is collected daily from each NEISS hospital for every patient treated in the ED due to an injury associated. The ICPSR data set consists of any patient seeking care in the ED for firearm-related injury, regardless of activity involved during the injury (e.g., hunting, committing a crime, suicide, assault), and whether the patient had been shot by the firearm or injured in some other way (e.g., a skull/face fracture from being pistol-whipped, a clavicle fracture from a rifle recoil, etc.). Further details regarding the acquisition of the ICPSR/NEISS data and guidelines for use of such data can be accessed from their respective websites (ICPSR—www.icpsr.umich.edu, NEISS—www.cpsc.gov/library/neiss.html, accessed on 18 December 2022). This study of publicly available de-identified data was considered exempt by our local Institutional Review Board.

The data from 1993 through 2020 was downloaded from the ICPSR website; however, due to changes in injury patterns associated with the COVID pandemic, those data from the year 2020 were excluded [27,28,29,30,31,32], including firearm injuries [33,34,35]. The data includes age, sex, race, type of firearm, the perpetrator of the injury (e.g., self, stranger, etc.), intent of injury (unintentional, assault, suicide, law enforcement), anatomic location of the injury, incident locale (home, street/highway, etc.), disposition from the ED, involvement of drugs/crime/fight/argument in the incident, and was the patient shot or not with the firearm. Race was classified as White, Black, Amerindian (Hispanic and Native American), and Asian [36]. We limited our study to those 15 years or younger. The 16-year-old age limit was used as most patients ≥ 16 years of age demonstrate adult fracture patterns and 16 is when the transition into adult activities, such as driving, begins.

Fractures were identified using two different methods. The first method was to identify fractures using the NEISS diagnosis code of 57, the code for a fracture. As the most serious injury is used to determine the diagnosis by the NEISS, many patients sustained fractures along with more serious injuries, such as a pneumothorax. In order to identify additional fractures, the database column CMTX was utilized; this column is a description of the event where patient identification has been purged by the CDC and CPSC. The database was searched for other fractures using the FIND command in Microsoft Excel™ (Microsoft® Office 365 Apps for enterprise) using the terms fx and frac. To further search for spinal injuries the database was searched using the terms spinal, verte, paral (for paralyzed), spine, cervical, thoracic, parapl and quadri (for paraplegia and quadriplegia), and each vertebral level (e.g., C1, C-1) from C1 through S4. The anatomic location of the fracture was then determined and ranked from the most serious to least serious when there was more than one fracture. Fractures of the spine were classified as the most severe, followed by the skull, pelvis, sternum/ribs, and, finally, the long bones of the appendicular skeleton beginning from proximal to distal respectively. The fracture locations were condensed into 5 major groups: spine, upper extremity, lower extremity (including the pelvis), skull/face, and rib(s).

Patients were separated into 3 groups by age (≤5, 6 through 10, and 11 through 15 years). The 27 years covered in this study were separated into 3 equal groups of 9 years (1993 through 2001, 2002 through 2010, and 2010 through 2019). Finally, we wished to study differences in fracture patterns by assessing if the shooting was a drive-by shooting or not; drive-by shootings were found by searching the database using the FIND command for the terms driveb, drive-by, drive-b, driveth, drive th, and drive-th.

2.2. Statistical Analysis

Statistical analyses were performed with SUDAAN 11.0.01™ software (RTI International, Research Triangle Park, North Carolina, 2013) which accounts for the weighted, stratified nature of the data, giving an estimated number of ED visits, along with 95% confidence intervals (CI) of the estimate N denoted by brackets [ ]. When the actual number of patients (n) is <20, the estimated number (N) becomes unstable and should be interpreted with caution; thus, we report both the n and N. Analyses between groups of continuous data were performed with the t-test (2 groups) or ANOVA (3 or more groups). Differences between groups of categorical data were analyzed by the χ2 test. For all analyses a p < 0.05 was considered statistically significant.

3. Results

Over the 27-year period of 1993 through 2019, there were 111,796 actual ED visits for injuries due to firearms, resulting in an estimated 3,359,809 [2,956,755, 3,744,864] ED visits after appropriate statistical analysis using the weighted data. Of these 3.36 million ED visits, an estimated 434,458 [356,526, 526,747] (13.0%) were in those <16 years of age. Of these 434,458 ED patients an estimated 19,033 [15,814, 22,852] (4.4%) sustained fractures. Therefore, these 19,033 ED visits comprise this study. From here on, only the estimated number (N) will be given in the manuscript text and used in the figures; both the actual (n) and estimated number (N) of ED visits are given in the Tables.

The average was 12.2 years; 85.2% were boys and the firearm was a powder type in 64.7%. All the data for the many different variables are given in Table 1.

Table 1.

Demographics of the 19,033 patients.

n N L95%CI U95%CI %
All 711 19,033 14,321 25,200 -
Age (average in years) 12.2 [11.7, 12.6]
Fracture location
Spine 39 717 416 1221 3.8
Upper extremity 292 9209 7612 10,823 48.4
Lower extremity 251 5982 4952 7118 31.5
Skull/face 114 2894 2137 3857 15.2
Rib 13 209 110 397 1.1
Number of fractures per patient
1 695 18,640 18,245 18,834 98.0
2 13 365 173 760 1.9
3 1 6 0 42 0.0
Sex
Male 586 16,203 15,578 16,731 85.2
Female 124 2825 2297 3450 14.8
Race
White 214 8215 7032 9364 54.9
Black 270 4883 3584 6389 32.6
Amerindian 60 1809 933 3314 12.1
Asian 2 70 9 502 0.5
Firearm type
Powder 536 12,314 10,662 13,801 64.7
Non-powder 175 6719 5232 8371 35.3
Shot
Yes 617 15,376 14,378 16,203 80.8
No 94 3657 2830 4655 19.2
Drive by shooting 0 0 0.0
Yes 43 705 447 1100 3.7
No 668 18,328 17,933 18,586 96.3
Disposition from ED
Release 385 13,272 11,267 15,334 68.7
Admit 321 5631 3889 7987 29.1
Death 3 100 21 485 0.5
Who caused the injury
Unknown 207 4533 3624 5586 23.8
Stranger 91 1494 967 2273 7.8
Self 214 8148 6926 9419 42.8
Friend/acquaintance 58 1577 1146 2149 8.3
Other relative 54 1299 876 1907 6.8
Other/not seen 86 1906 1338 2678 10.0
Injury intent
Unknown 37 985 560 1707 5.2
Unintentional 328 11,417 9977 12,771 60.0
Assault 336 6401 5097 7851 33.6
Suicide 4 157 34 689 0.8
Law enforcement 6 73 27 194 0.4
Incident locale
Unknown 242 7190 5959 8502 37.8
Home/apt 272 7256 6001 8599 38.1
School/recreation 43 1298 862 1930 6.8
Street/highway 96 1867 1256 2727 9.8
Other property 57 1310 847 1997 6.9
Farm 1 112 15 797 0.6
Year span
1993–2001 180 7027 5383 8848 36.9
2002–2010 252 6108 4762 7630 32.1
2011–2019 279 5898 4604 7370 31.0
Hospital size
Small 64 5154 3493 7238 27.1
Medium 56 3485 2033 5632 18.3
Large 98 5226 2630 8982 27.5
Very large 227 3671 2282 5620 19.3
Children 266 1497 744 2893 7.9
Argument
Unknown 306 7408 204,300 7321 69.5
Yes 29 691 405 1165 3.6
No 376 10,934 9606 12,208 57.4
Crime
Unknown 290 6993 5836 8237 36.7
Yes 83 1208 700 2044 6.3
No 338 10,832 9505 12,109 56.9
Drugs
Unknown 319 7665 6344 9064 40.3
Yes 17 398 188 830 2.1
No 375 10,970 9610 12,272 57.6
Fight
Unknown 283 6606 5055 8350 34.7
Yes 34 705 390 1260 3.7
No 394 11,722 10,217 13,118 61.6
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n = actual number, N = estimated number, L95%CI is the lower 95% confidence limit for N, U95%CI is the upper confidence limit for N.

There were 19,370 fractures in these 19,033 patients. The exact number of fractures was known in 19,011 patients and was 1 in 18,640 (98.05%), 2 in 365 (1.92%), and 3 in 6 (0.03%). The detailed anatomic distributions for all patients as well as two separate groups of those released from the ED and those admitted to the hospital are shown in Table 2.

Table 2.

Anatomic distribution of 19,370 fractures in 19,033 patients.

All Patients Released from ED Admitted to Hospital
Bone n N %N N N% N N%
Finger 157 6043 31.4% 5875 43.6% 168 2.9%
Face 70 2127 11.1% 1291 9.6% 836 14.5%
Foot 51 1394 7.2% 1186 8.8% 208 3.6%
Toe 33 1348 7.0% 1253 9.3% 95 1.6%
Tibia/fibula 75 1301 6.8% 316 2.3% 985 17.1%
Hand 46 1208 6.3% 1013 7.5% 195 3.4%
Femur 57 1036 5.4% 215 1.6% 821 14.2%
Forearm 37 844 4.4% 432 3.2% 412 7.1%
Skull 45 741 3.9% 217 1.6% 524 9.1%
Humerus 30 658 3.4% 476 3.5% 182 3.2%
Ankle 15 479 2.5% 374 2.8% 105 1.8%
Knee 12 399 2.1% 230 1.7% 169 2.9%
Scapula/shoulder 15 386 2.0% 168 1.2% 218 3.8%
Cervical spine 7 246 1.3% 120 0.9% 126 2.2%
Thoracic spine 15 219 1.1% 6 0.0% 213 3.7%
Rib 14 215 1.1% 65 0.5% 150 2.6%
Lumbar spine 12 168 0.9% 18 0.1% 150 2.6%
Clavicle 5 159 0.8% 143 1.1% 16 0.3%
Sacrococcygeal spine 5 84 0.4% 18 0.1% 66 1.1%
Wrist 7 81 0.4% 37 0.3% 44 0.8%
Pelvis 7 59 0.3% 6 0.0% 53 0.9%
Elbow 4 23 0.1% 11 0.1% 12 0.2%
Hip 2 22 0.1% 0 0.0% 22 0.4%
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n = actual number, N = estimated number of ED visits.

The finger was the most common fracture location for patients both overall and released from the ED. The tibia/fibula was the most common fracture location for those admitted to the hospital. For those released from the ED, the upper extremity was the most common location (61%) (Figure 1a) and for those admitted to the hospital, it was the lower extremity (45%) (Figure 1b).

Figure 1.

Figure 1

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Fracture distribution by major anatomic location: (a) for those patients treated and released from the ED; (b) for those patients admitted to the hospital from the ED.

There were very few Asian children, children with isolated rib fractures and those having more than one fracture. Thus, we excluded Asian children, those with an isolated rib fracture, and those with more than one fracture. All the subsequent analyses were performed with these exclusions.

3.1. Analyses by Fracture Group

Notable differences (Table 3) include children ≤ 5 years of age sustained more skull/face fractures (Figure 2a). Most spine fractures, while rare, occurred in the 11–15-year age group. Fractures of the upper extremity accounted for 58.6% of all the fractures in the 6–10 age group. Nearly all spine fractures (98%) were associated with powder firearms (Figure 2b). Patients with lower extremity fractures were more commonly admitted to the hospital compared to those with upper extremity fractures; the few deaths occurred exclusively in those with fractures to the skull/face (Figure 2c). While most of the patients sustained a gunshot wound (i.e., were shot), nearly all of those with spine fractures were shot, while 39% of those with skull/face fractures were not shot (Figure 2d). Other statistically significant differences existed by race, perpetrator, incident locale, and injury intent.

Table 3.

Analyses by fracture location.

Spine Upper Extremity Lower Extremity Skull/Face Rib p Value p Value ^
Variable n N L95%CI U95%CI % n N L95%CI U95%CI % n N L95%CI U95%CI % n N L95%CI U95%CI % n N L95%CI U95%CI %
All 39 717 416 1221 4.0 292 9209 7612 10,823 12.8 251 5982 4952 7118 31.5 114 2894 2137 3857 15.2 13 209 110 397 1.1 - -
Age (average in years) 11.6 [10.7, 12.5] 13.8 [12.2, 15.4] 12.7 [11.8, 13.6] 11.6 [10.7, 12.5] 13.8 [12.2, 15.4] 0.005
Age group (years)
≤5 2 21 4 97 3 26 743 445 1212 8.1 16 429 141 1187 7.2 19 438 211 834 15.1 1 15 2 86 7 0.041 0.12
6 to 10 3 46 10 182 6 50 1802 1260 2504 19.6 27 633 398 982 10.6 17 336 178 603 11.6 0 0 0 0 0
11 to 15 34 650 518 698 91 216 6664 5980 7250 72.4 208 4920 4318 5337 82.2 78 2120 1827 2357 73.3 12 194 123 207 93
Sex
Male 33 596 481 660 84 250 8149 7609 8523 88.5 203 5142 4762 5418 86.0 87 2118 1714 2422 73.2 12 193 120 207 92 0.51 0.39
Female 5 116 52 231 16 42 1060 686 1600 11.5 48 840 564 1220 14.0 27 776 472 1180 26.8 1 16 2 89 8
Race
White 5 133 37 330 23 114 4896 4134 5551 67.3 51 1808 1414 2236 39.1 40 1283 958 1584 56.9 4 95 38 131 66 0.003 0.0007
Black 19 277 90 479 47 97 1901 1335 2602 26.1 116 2131 1460 2834 46.1 31 504 291 810 22.3 5 48 12 105 34
Amerindian 5 179 79 325 30 22 474 240 908 6.5 19 687 294 1432 14.9 14 469 190 968 20.8 0 0 0 0 0
Firearm Type
Powder 37 705 666 714 98 168 4275 3460 5112 46.4 225 4841 4058 5354 80.9 92 2267 1841 2553 78.3 12 204 174 208 98 <10−4 0.0004
Non-powder 2 12 3 51 2 124 4934 4097 5749 53.6 26 1141 628 1924 19.1 22 627 341 1053 21.7 1 5 1 35 2
Shot
Yes 38 701 602 715 98 238 6954 6238 7543 75.5 243 5720 5316 5883 95.6 83 1770 1376 2119 61.2 13 209 2 5 100 0.0001 <10−4
No 1 16 2 115 2 54 2255 1666 2971 24.5 8 262 99 666 4.4 31 1124 775 1518 38.8 0 0 0 0 0
Drive by shooting
Yes 7 63 22 162 9 14 272 110 659 3.0 20 295 137 617 4.9 1 60 12 281 2.1 1 15 2 86 7 0.67 0.53
No 32 654 555 695 91 278 8937 8551 9099 97.0 231 5687 5365 5845 95.1 113 2834 2613 2882 97.9 12 194 123 207 93
Disposition from ED
Release 6 162 44 405 23 220 8007 7347 8457 86.9 112 3525 2887 4116 59.1 42 1508 995 2004 52.4 4 65 23 130 31 0.0001 0.0001
Admit 33 555 312 673 77 72 1202 752 1862 13.1 138 2442 1851 3080 40.9 68 1271 755 1834 44.1 9 144 79 186 69
Death 0 0 0 0 0 0 0 0 0 0.0 0 0 0.0 3 100 20 444 3.5 0 0 0
Who caused the injury
Unknown 16 361 207 514 50 62 1658 1213 2221 18.0 79 1452 1004 2018 24.3 40 877 584 1238 30.3 9 168 110 196 80 <10−4 <10−4
Stranger 7 50 14 155 7 30 392 227 666 4.3 44 910 505 1548 15.2 8 132 41 402 4.6 1 5 1 35 2
Self 2 21 4 98 3 128 5184 4338 5991 56.3 63 2259 1667 2919 37.8 21 684 479 943 23.6 0 0 0 0 0
Friend/acquaintance 4 90 33 214 13 16 525 280 961 5.7 20 634 363 1069 10.6 17 323 127 739 11.2 1 5 1 35 2
Other relative 3 58 14 202 8 19 475 222 984 5.2 11 244 100 574 4.1 20 506 308 792 17.5 1 16 3 72 8
Other/not seen 7 137 72 240 19 36 899 541 1456 9.8 34 483 246 912 8.1 8 372 133 902 12.9 1 15 2 86 7
Injury intent
Unknown 2 12 3 48 2 19 588 314 1072 6.4 13 264 112 599 4.4 3 121 31 432 4.2 0 0 0 0 0 <10− <10−4
Unintentional 6 111 48 228 15 177 6747 5994 7377 73.3 93 3168 2408 3905 53.0 50 1370 899 1858 47.3 2 21 5 69 10
Assault 30 578 474 645 81 93 1839 1244 2625 20.0 143 2528 1845 3264 42.3 57 1246 901 1615 43.1 11 188 140 204 90
Suicide 0 0 0 0 0 0 0 0 0 0.0 0 0 0 0 0.0 4 157 41 542 5.4 0 0 0 0 0
Law enforcement 1 16 2 105 2 3 35 10 116 0.4 2 22 5 102 0.4 0 0 0 0 0.0 0 0 0 0 0
Incident locale
Unknown 15 254 136 404 35 99 3603 2789 4488 39.1 78 1879 1345 2511 31.4 44 1324 945 1720 45.7 5 113 53 168 54 0.003 0.002
Home/apt 11 218 153 297 30 127 3802 3020 4636 41.3 83 2162 1415 3040 36.1 46 1014 764 1296 35.0 4 55 22 109 26
School/recreation 1 6 1 46 1 18 712 387 1270 7.7 14 302 166 540 5.0 8 258 88 677 8.9 2 20 4 83 10
Street/highway 5 140 51 312 20 32 468 271 797 5.1 49 1080 720 1567 18.1 10 179 69 438 6.2 0 0 0 0 0
Other property 7 99 44 203 14 16 624 288 1294 6.8 27 559 328 925 9.3 6 119 49 276 4.1 2 21 5 69 10
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n = actual number, N = estimated number, L95%CI is the lower 95% confidence limit for N, U95%CI is the upper confidence limit for N. ^ p value excluding the rib group.

Figure 2.

Figure 2

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Differences between the four major fracture locations (spine, upper extremity, lower extremity, and skull/face: (a) by age group (p = 0.041); (b) by firearm type (p < 10−4); (c) by ED disposition (p = 0.0001); (d) by being shot or not (p < 10−4).

3.2. Analyses by Powder vs. Non-Powder Firearms

In addition to the differences described above by fracture location and firearm type, there were notable differences by sex, race, disposition from the ED, perpetrator of the injury, injury intent, incident locale, and age groups (Table 4).

Table 4.

Analyses by firearm type.

Powder Non-Powder
Variable n N L95%CI U95%CI % n N L95%CI U95%CI % p Value
All 536 12,314 10,662 13,801 64.7 175 6719 5242 8382 35.3 -
Age (average in years) 12.5 [11.9, 13.1] 11.7 [11.1, 12.2] 0.58
Age group (years)
≤5 years 53 1299 803 2047 10.5 12 352 76 335 5.2 0.012
6 to 10 56 1241 896 1698 10.1 41 1576 408 815 23.5
11 to 15 427 9774 9006 10,402 79.4 122 4791 703 892 71.3
Sex
Male 425 10,012 9410 10,512 81.3 161 6191 5702 6456 92.1 0.0024
Female 110 2297 1797 2899 67.0 14 528 263 1017 7.9
Race
White 124 4336 3510 5195 45.7 90 3879 3166 4436 71.6 0.0005
Black 288 3740 2593 5032 39.4 32 1143 665 1832 21.1
Amerindian 44 1413 803 2366 14.9 16 396 145 998 7.3
Fracture location
Spine 37 705 429 1140 5.8 2 12 3 45 0.2 <10−4
Upper extremity 168 4275 3327 5330 35.4 124 4934 4179 5528 73.5
Lower extremity 225 4841 4070 5655 40.0 26 1141 648 1891 17.0
Head/face 92 2267 1677 3005 18.8 22 627 330 1142 9.3
Shot
Yes 476 10,070 9244 10,712 81.8 141 5306 2830 4655 79.0 0.59
No 60 2244 1603 3070 18.2 34 1413 2830 4655 21.0
Drive by shooting 0 0 0.0 0 0 0.0
Yes 42 627 399 975 5.1 1 78 11 538 1.2 0.022
No 494 11,687 11,339 11,915 94.9 174 6641 6181 6708 98.8
Disposition from the ED
Released 233 6953 5669 8200 56.5 152 6319 2830 4655 94.0 <10−4
Admitted 298 5231 3987 6583 42.5 23 400 2830 4655 6.0
Died 3 100 14 309 0.8 0 0 2830 4655 0.0
Who caused the injury
Unknown 181 3602 2890 4408 29.3 26 931 556 1498 13.9 <10−4
Stranger 90 1416 909 2154 11.5 1 78 11 538 1.2
Self 106 3765 3045 4571 30.6 108 4383 3758 4938 65.2
Friend/acquaintance 42 1176 815 1672 5.0 16 401 186 834 6.0
Other relative 38 857 549 1319 7.0 16 442 237 802 6.6
Other/not seen 79 1498 1058 2088 12.2 7 408 183 873 6.1
Injury intent
Unknown 26 504 249 1001 4.1 11 481 225 983 7.2 <10−4
Unintentional 173 5436 4536 6368 44.1 155 5981 5476 6297 89.0
Assault 328 6151 5269 7034 50.0 8 250 101 600 3.7
Suicide 3 150 33 659 1.2 1 7 1 51 0.1
Law enforcement 6 73 28 191 0.6 0 0 0 0 0.0
Incident locale
Unknown 173 4422 5371 3553 36.2 69 2768 2057 3538 41.2 <10−4
Home/apt 177 3788 3010 4665 31.0 95 3468 2755 4171 51.6
School/recreation 40 1206 772 1844 9.9 3 92 19 421 1.4
Street/highway 93 1812 1300 2481 14.9 3 55 14 216 0.8
Other property 52 974 638 1464 8.0 5 3336 123 868 49.7
Year group
1993 to 2001 109 3942 2756 5352 32.0 71 3085 2377 3819 45.9 0.006
2002 to 2010 187 3604 2601 4804 29.3 65 2504 1835 3255 37.3
2011 to 2019 240 4768 3670 5969 38.7 39 1130 707 1734 16.8
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n = actual number, N = estimated number, L95%CI is the lower 95% confidence limit for N, U95%CI is the upper confidence limit for N.

Boys comprised 81.3% of the powder and 92.1% of the non-powder firearm groups (p = 0.0024). White children accounted for 45.7% of the powder and 71.6% of the non-powder firearm group (p = 0.0005) (Figure 3a). Of those patients with fractures due to powder firearms, 42.5% were admitted to the hospital, while only 6.0% of those due to non-powder firearms were admitted (p < 10−4). The injury was self-inflicted in 65.2% of the non-powder and 30.6% of the powder group (Figure 3b) (p < 10−4). The injury intent was an assault in 50.0% of the powder and 3.7% of the non-powder firearm group (Figure 3c) (p < 10−4). While the injuries occurred at schools or places of recreation in only 6.8% of all the patients (Table 1), those fractures which occurred at schools or places of recreation were due to powder firearms in 92.9% (Figure 3d) (p < 10−4). Although there was minimal difference in the average age between the two groups (12.5 years—powder, 11.7 years—non-powder, p = 0.58), there was a significant difference between the three age groups. Powder firearms accounted for the majority of the fractures in the ≤5 and 11–15 yea-olds, non-powder firearms accounted for the majority of the fractures in the 6–10-year-old group (Figure 3e) (p = 0.006). No differences were observed in the patient being shot or not shot by firearm type.

Figure 3.

Figure 3

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Differences between powder and non-powder firearms: (a) by race (p = 0.0005); (b) by perpetrator of the injury (p < 10−4); (c) by injury intent (p < 10−4); (d) by incident locale (p < 10−4); (e) by age group (p = 0.006).

3.3. Analyses by Being Shot or Not Shot

In addition to the differences by major fracture, groups noted above, there were notable differences by incident locale and disposition from the ED (Table 5).

Table 5.

Analyses by being shot or not.

Shot Not Shot p Value
Variable n N L95%CI U95%CI % n N L95%CI U95%CI %
All 617 15,376 14,378 16,203 80.8 94 3657 2830 4655 19.2 -
Age (average in years) 11.5 [11.3, 11.6] 10.5 [10.1, 10.8] <10−4
Sex
Male 516 13,278 12,676 13,762 86.4 70 2925 2480 3231 80.0 0.27
Female 100 2093 1609 2695 13.6 24 732 426 1177 20.0
Race
White 168 6164 5167 7154 51.2 46 2051 1587 2396 71.7 0.036
Black 255 4389 3108 5851 36.4 15 494 266 853 17.3
Amerindian 48 1494 772 2726 12.4 12 315 132 687 11.0
Firearm type
Powder 476 10,070 8534 11,421 65.5 60 2244 1769 2667 61.4 0.59
Non-powder 141 5306 3955 6842 34.5 34 1413 990 1888 38.6
Drive by shooting
Yes 43 705 452 1090 4.6 0 0 0 0 0.0 <10−4
No 574 14,671 14,286 14,924 95.4 94 3657 2830 4655 100.0
Disposition from ED
Release 298 9830 8049 11,390 64.1 87 3442 2988 3594 94.1 <10−4
Admit 314 5416 3846 7239 35.3 7 215 63 669 5.9
Death 3 100 20 477 0.7 0 0 0 0 0.0
Fracture location
Spine 38 701 406 1195 4.6 1 16 2 116 0.4 <10−4
Upper extremity 238 6954 5658 8287 45.9 54 2255 1721 2722 61.7
Lower extremity 243 5720 4798 6705 37.8 8 262 102 628 7.2
Skull/face 83 1770 1213 2537 11.7 31 1124 721 1627 30.7
Who caused 617 15,376 0 0 100.0 94 3657 0 0 100.0
Unknown 185 3866 3089 4763 25.1 22 667 397 1062 18.2 0.18
Stranger 84 1366 864 2117 8.9 7 128 41 381 3.5
Self 170 6151 5139 7222 40.0 44 1997 1526 2446 54.6
Friend/acquaintance 53 1292 906 1822 5.0 5 285 106 707 7.8
Other relative 44 1076 689 1656 7.0 10 223 88 535 6.1
Other/not seen 81 1625 1147 2271 10.6 5 281 112 658 7.7
Injury intent
Unknown 36 951 533 1655 6.2 1 34 5 225 0.9 0.0005
Unintentional 268 8635 7417 9802 56.2 60 2782 2320 3121 76.1
Assault 304 5565 4427 6809 36.2 32 836 507 1290 22.9
Suicide 4 157 35 675 1.0 0 0 0 0 0.0
Law enforcement 5 68 0 191 0.4 1 5 1 37 0.1
Incident locale
Unknown 203 5572 4573 6741 36.2 39 1618 1168 2095 44.2 <10−4
Home/apt 242 6200 5086 7477 40.3 30 1056 660 1566 28.9
School/recreation 24 476 277 824 3.1 19 822 472 1323 22.5
Street/highway 91 1775 1244 2526 11.5 5 92 26 312 2.5
Other property 56 1241 823 1871 8.1 1 69 11 418 1.9
Age group (years)
≤5 56 1337 836 2093 8.7 9 314 138 674 8.6 0.95
6 to 10 87 2215 1691 2866 14.4 10 602 277 1175 16.5
11 to 15 474 11,824 10,969 12,556 76.9 75 2741 2191 3134 75.0
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n = actual number, N = estimated number, L95%CI is the lower 95% confidence limit for N, U95%CI is the upper confidence limit for N.

Children who sustained injuries at schools and recreational facilities were less likely to be shot compared to other places (Figure 4a). Examples would be a clavicle fracture sustained from a rifle recoil while doing target practice, or a nasal fracture to a participant in marching band/color guard activities. All deaths and nearly all of those admitted to the hospital had been shot (Figure 4b), while 26% of those released from the ED were not shot (p < 10−4) and experienced injury from the firearm in a different way. There were no differences between those shot or not shot by firearm type or perpetrator of the injury; however, there were differences by race and injury intent. White children comprised 71.7% of those not shot and 51.2% of those shot (p = 0.036); the injury was unintentional in 76.1% of the shot group and 56.2% of the shot group (p = 0.0005).

Figure 4.

Figure 4

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Differences between being shot or not. (a) By incident locale (p < 10−4); (b) by disposition from the ED (p < 10−4).

3.4. Analyses by Disposition from the ED

In addition to the differences by fracture location, firearm type, and being shot or injured in another way, those admitted to the hospital from the ED (Table 6) were less commonly White (Figure 5a), less frequently injured themselves (Figure 5b), and more commonly injured due to an assault (Figure 5c). The rate of hospital admissions increased over time (p = 0.004) (Figure 5d).

Table 6.

Analyses by disposition from the ED.

Variable Released Admitted p Value
n N L95%CI U95%CI % n N L95%CI U95%CI %
All 385 13,272 11,060 15,077 70.2 321 5631 3826 7843 29.8 -
Age (average in years) 12.1 [11.8, 12.7] 12.6 [11.9, 13.2] 0.29
Age group (years)
≤5 33 1145 691 1851 8.6 29 406 53 170 7.2 0.74
6 to 10 51 2067 1449 2884 15.6 46 750 171 340 13.3
11 to 15 301 10,060 9131 10,837 75.8 246 4475 1791 2100 79.5
Sex
Male 329 11,490 10,874 11,967 86.6 253 4598 4346 4810 81.7 0.12
Female 56 1782 1305 2398 67.0 1028 23 655 816 0.4
Race
White 141 6254 5183 7239 60.2 72 1945 1274 2670 43.9 0.011
Black 127 3091 2358 3941 29.8 141 1708 766 2893 38.6
Amerindian 30 1036 530 1930 10.0 30 773 398 1380 17.5
Firearm Type
Powder 233 6953 5853 8035 52.4 298 5231 4936 5407 92.9 <10−4
Non-powder 152 6319 5237 7419 47.6 23 400 224 695 7.1
Shot
Yes 298 9830 8992 10,554 74.1 314 5416 2830 4655 96.3 <10−4
No 87 3442 2718 4280 25.9 7 215 2830 4655 3.8
Drive by shooting
Yes 17 399 186 841 3.0 26 396 199 465 7.0 0.15
No 368 12,873 12,431 13,086 97.0 295 5325 5166 5432 94.6
Fracture location
Spine 6 162 44 591 1.2 33 555 391 777 10.1 0.0001
Upper extremity 220 8007 7017 8935 60.6 72 1202 906 1562 22.0
Lower extremity 112 3525 2660 4549 26.7 138 2442 2029 2869 44.6
Skull/face 42 1508 1051 2128 11.4 68 1271 889 1754 23.2
Who caused the injury
Unknown 97 2723 2037 3568 20.5 108 1780 1391 2220 31.6 0.0006
Stranger 40 934 518 1644 7.0 51 560 264 1119 9.9
Self 161 6922 5903 7927 52.2 50 1126 746 1636 20.0
Friend/acquaintance 26 901 549 1453 5.0 32 676 427 1041 12.0
Other relative 25 758 435 1297 5.7 29 541 361 798 9.6
Other/not seen 35 958 617 1465 7.2 51 948 677 1299 16.8
Injury intent
Unknown 25 844 466 1492 6.4 12 141 52 368 2.5 <10−4
Unintentional 222 9195 8148 10,111 69.3 103 2122 1636 2657 37.7
Assault 137 3228 2357 4293 24.3 197 3143 2593 3669 55.8
Suicide 0 0 0 0 0.0 4 157 47 499 2.8
Law enforcement 1 5 1 37 0.0 5 68 23 199 1.2
Incident locale
Unknown 142 5256 4210 6376 39.9 98 1904 1473 2389 33.8 0.02
Home/apt 148 5189 4177 6275 39.4 121 1967 1519 2468 34.9
School/recreation 31 1104 697 1715 8.4 12 194 111 334 3.4
Street/highway 40 762 455 1255 5.8 56 1105 849 1415 19.6
Other property 23 849 458 1532 6.5 34 461 338 622 8.2
Year group
1993 to 2001 132 5692 1597 6891 42.9 48 1335 856 1971 23.7 0.004
2002 to 2010 132 4251 3331 5290 32.0 118 1826 1265 2493 32.4
2011 to 2019 121 3329 2483 4348 25.1 155 2470 1879 3094 43.9
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n = actual number, N = estimated number, L95%CI is the lower 95% confidence limit for N, U95%CI is the upper confidence limit for N.

Figure 5.

Figure 5

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Differences by disposition from the ED: (a) by race (p = 0.011); (b) by perpetrator of the injury (p = 0.0006); (c) by intent of the injury (p < 10−4); (d) by year time span (p = 0.004).

3.5. Analyses by Age Groups and Drive-by Shootings

In addition to the difference by firearm type previously noted, the percentage of injuries occurring at home decreased with increasing age (63.3% < 5 years, 54.5% 6 to 10 years, and 32.4% 11 to 15 years of age) (Figure 6). No other significant differences existed between the different age groups. Regarding those injured in drive-by shootings, differences existed by race, firearm type, and perpetrator of the injury. Drive-by shooting patients were 11.2% White, 62.5% Black, and 26.3% Amerindian; non-drive-by shooting patients were 57.0% White, 31.5% Black, and 11.5% Amerindian (p = 0.008). The involved firearm was a powder firearm in 88.9% of the drive-by and 63.8% of the non-drive-by patients (p = 0.022). The perpetrator was unknown in 55.8%, a stranger in 21.3%, and not seen in 23.1% of the drive-by shootings; the perpetrator in the non-drive-by shootings was unknown in 23.1%, a stranger in 7.2%, themselves in 44.6%, a friend/acquaintance in 8.6%, another relative in 7.1%, and not seen in 9.3% (p = 0.008).

Figure 6.

Figure 6

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Differences in age group by incident locale (p = 0.037). Note the decreasing number of cases occurring at home with increasing age.

3.6. Variations by Time

A noticeable increase in ED visits on Saturday and Sunday was observed (Figure 7a). No pattern by month (Figure 7b) or year (Figure 7c) was present.

Figure 7.

Figure 7

Figure 7

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Temporal variability in the number of ED visits for fractures in children < 16 years old: (a) by day of the week. Note the increased number of ED visits on the weekend); (b) by month. Note that there is no apparent pattern. There was no change by month upon linear regression analysis: r2 = 0.057, p = 0.45. Additionally, cosinor analysis [37,38] demonstrated no rhythmic pattern as seen in many other pediatric non-firearm injuries [39,40,41]; (c) by year from 1993 through 2019. There was no change over time upon linear regression analysis: r2 = 0.05, p = 0.26.

4. Discussion

The findings in this study are both similar and different to other studies in the literature. As most of the studies regarding fractures in children due to firearms are due to powder firearms, we have compared our findings to the other studies (Table 7). The percentage of boys was strikingly similar for all studies; it ranged from 78 to 91% and was 81% in this series. Most of the series demonstrated more lower extremity fractures than upper extremity fractures. Of the three studies that included spine fractures, the 5.5% in this study and the 2% in that of Naranje et al. [19] are similar, in contrast to the 18.9% in the study of Blumberg et al. [14]. We have no explanation for this finding, except that only inpatients were included in the Blumberg series [14] and they included those 16 through 20 years of age. It has been shown in a previous study that those with firearm-associated spine injuries are much more common in the 15-to-34 year-old age group [42]. Carillo et al. [43] studied 19 patients with spinal cord injury secondary to gunshot wounds. The average age was 17 years with a range of 14–19 years. The fact that we excluded those over 15 years of age likely explains some of the differences between this study and that of Blumberg et al. [14].

Table 7.

Compilation of the literature regarding firearm-associated fractures in children.

Study Year Location Number of Patients with Fractures Inpatient or Outpatient % Male Age Limit (years) % UE % LE % Spine
Present 2023 Entire USA 12,314 Both 81 <16 42.5 52.0 5.5
Blumberg et al. [14] 2018 Entire USA 2814 IP 91 <21 30.3 59.1 18.9
Naranje et al. [19] 2016 Birmingham, AL and Memphis, TN 49 IP 84 <19 22 76 2
Perkins [20] 2016 Charlotte, NC 44 IP 78 <18 41 59 -
Washington et al. [25] 1995 Los Angeles, CA 29 IP 81 <18 55 44 -
Victoroff et al. [23] 1994 Washington, DC 23 IP 83 <19 48 52 -
Stucky et al. [24] 1991 Detroit, MI 44 IP 83 <18 50 50 -
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UE = upper extremity, LE = lower extremity.

The most fractured bone in this study was the finger, likely due to the inclusion of both those patients released from the ED and non-powder firearms. When looking at only those admitted to the hospital (Table 2), the most common fracture involved the tibia/fibula (17.1%) followed by the femur (14.2%). In the only other large study, that of [14], the most common fractured bone was the femur (21.2%), followed by the spine as discussed above at 18.9%, and then the tibia/fibula at 15.0%. Again, these differences are likely due to the inclusion of those children from 16 through 21 years of age in the Blumberg study [14]. Nevertheless, the numbers in this study respectively for the tibia/fibula (17.1%) and femur (14.2%) are similar to the 15.0% and 21.2% respectively for the Blumberg study [14]. In the much smaller series of 58 gunshot fractures by Naranje et al. [19] both the femur and tibia/fibula each accounted for 19% of the fractures, again very similar to the numbers in this study.

We noted that powder firearms were responsible for the majority of the fractures in the ≤5 and 11–16-year-old groups (78.7% and 67.1%) but only 44.1% for the non-powder firearm group (Figure 3e) and that the majority (63.3%) of those in the ≤5-year-old group occurred at home (Figure 6). This confirms and supports the need for firearms in the home to be safely stored and locked and away from children [44,45,46]. It has been estimated that even in 2020 that 4.6 million US children live in homes with at least one loaded and unlocked firearm [47]. The issue of gun ownership is very emotional in the US population, and in a recent study [48] gun owners with children were more likely than those without children to feel that guns make them feel more valuable to their families. Thus, acknowledging parental motivations for gun ownership is a pivotal educational component toward firearm injury prevention. However, the initial analyses did not uncover if this particular group in this study was injured unintentionally by the child or others. We, therefore, performed detailed analyses of the perpetrator and incident locale by the three age groups. In the ≤5-year-old age group, 90.8% of the fractures were self-inflicted and occurred at home; this number was 29.6% for the 6–10 and 18.4% for the 11–15 year old age groups (p < 10−4). Therefore, it can be concluded that young children are exceptionally vulnerable to accidental dislodging of an unlocked and loaded gun left at home, furthermore, emphasizing the importance of gun safety around young children.

Another interesting finding was that those injured in schools or recreational facilities had the second highest prevalence of fractures due to powder firearms (92.9%) (Figure 3d) but the least likely (36.7% compared to the overall study 80.8%) to be shot (Figure 4a). This is most likely due to the fact that, in schools, powder-type firearms are often used in color guard or other sanctioned activities. In a recent study, 43.9% of injuries due to firearms in schools occurred in the sanctioned guard or drill activities [49]. While there is understandably significant concern regarding school mass shootings in the US, only ~37% of the patients with fractures due to school-related firearm encounters were shot. Of the 1298 patients injured at schools or recreational facilities, 696 were at schools and 602 at recreational facilities. There was no difference in the number of those injured by powder and non-powder firearms between the school and recreational facilities.

Regarding temporal factors, the patients with fractures were more likely to be injured on the weekend than on the weekday. This is understandable as school-aged children are occupied during the weekdays, reducing access to firearm activities. Tatebe et al. [50] noted that there was an increase in pediatric firearm injuries overall in Chicago. However, we noted no variation by month in this select group of children with fractures due to firearm injuries. A previous US study of temporal variation in firearm injuries [51] using an earlier version of the Research Firearm Injury Surveillance Study 1993–2008 noted a peak in September, but with many exceptions. Thus, fractures due to firearm injuries in children are likely another one of these exceptions.

The United States has the highest rate of pediatric firearm-related injuries, specifically 10–35 times higher than other high-income countries [50]. With pediatric firearm-related fractures increasing from 1993–2019, it is important that national prevention strategies are implemented to prevent further increases in childhood morbidity and mortality relating to firearms. Tatebe et al. [50] found that 43.6% of all firearm-associated injuries occurred outside of school hours, thus providing family support, early childhood education and scheduled after-school activities could minimize the time that children are exposed to firearms. Additionally, it has been proposed [50] that access to unsecured loaded weapons needs to be minimized with increased emphasis on education regarding firearm handling.

A more interesting finding was that over time, the percentage of children admitted to the hospital for firearm-associated fractures increased (Figure 5d), in spite of the very well-known emphasis to not admit patients to the hospital in the US, where hospital admission is typically reserved for very serious injuries and/or those needing immediate surgical treatment. If hospital admission is used as an indication of injury severity, then this is a very concerning trend. If, however, it reflects perhaps more aggressive fracture fixation, then perhaps this trend could be explained. However, the vast majority of the upper extremity and many of the lower extremity fractures in children due to firearms can be treated non-operatively, with the major exception perhaps being the femur and less so the tibia/fibula. There has certainly been an increase in operative pediatric femur fracture treatment from 1993 to 2019 and, to a lesser extent, other long bone fractures [52,53,54,55]. This may explain the trend seen here.

We compared the patterns of fractures in those associated with powder and non-powder firearms. The literature regarding non-powder firearms (i.e., BB guns, air-powered rifles) primarily focuses on overall injury patterns and does not specifically study fracture patterns. A recent study [18] used the NEISS database and excluded powder firearm injuries, while we used the Firearm Injury Surveillance Study, which is also a NEISS database, but incorporates all firearms, both powder and non-powder. In the study by Jones et al. [18] from 1990–2016, the rate of non-powder firearm injuries decreased by 47.8%, boys accounted for 87.1% of the children; BB guns accounted for 80.8% of the injuries, followed by pellet guns (15.5%), paintball guns (3.0%), and airsoft guns (0.6%). However, there was little mention of fractures with most of the focus on ocular injuries; nonetheless, fractures were most commonly associated with hospital admission. Details of fracture anatomic location were not given. In this study, 73.5% of the fractures due to non-powder firearms occurred in the upper extremity (Table 4). Of these 4934 upper extremity fractures due to non-powder firearms, 4485 (90.9%) involved the finger, 362 (7.3%) the hand, with the remaining 87 from the wrist proximal. A similar pattern was seen in the lower extremity; of the 1313 lower extremity fractures due to non-powder firearms, 820 (62.5%) involved the toes and 311 (23.7%) the foot, with the remaining 10 (0.8%) the tibia/fibula.

There are certain limitations of the study. First is the accuracy of the NEISS data. However, previous studies [56,57], including those involving firearms, have demonstrated over 90% accuracy of NEISS data. Second, it studies only patients seen in EDs and thus those visiting urgent care centers or other outpatient clinics are not captured in this data. However, we suspect that any serious firearm injury would be seen in an ED. Third, regional-specific analyses could not be carried out due to the de-identified nature of each hospital in the NEISS sample. It would be very interesting to study differences by region [58], especially those having stricter gun control laws compared to others, but unfortunately, that is not possible due to the de-identified status of each NEISS hospital. Fourth, the number of fractures reported is likely less than the actual number for several reasons. Potential error could stem from the clerks entering the data into the comments section and inadvertently forgetting to mention a fracture when in actuality there was a fracture. In addition, a very seriously injured person coming into the ED with a major trauma likely had fractures that were overlooked and not mentioned, especially if the patient was in extremis and/or died in the ED. An additional reason is that many of the serious head injuries with brain damage from the gunshot wound would have had an open skull fracture, but it was not so coded, it was missed. The same would be for a patient with a hemo/pneumothorax, likely having a rib(s) fracture. As this is an ED-focused database, we have no information on the length of stay for those admitted to the hospital. Finally, we can not differentiate between the injuries sustained during routine recreational use (e.g., hunting, target practice) or self defense during a perceived or actual assault due to how this database is catalogued.

A major strength of this study is that it is a national picture of pediatric fracture patterns due to firearms over a quarter of a century. It encompasses both rural and urban areas, all races, both boys and girls, and especially studies the outcome of the ED visit—treated and released, admitted, or expired while in the hospital. While these are national estimates and may not be locally applicable, they can give healthcare providers, especially ED providers, orthopaedic surgeons, and health facility administrators important information about these events. This data will also be helpful in analyzing any changes in prevalence or demographics with any future firearm legislation, for or against gun control.

Finally, what are the financial costs of this particular group of patients? The average cost of an ED visit in the US in 2020 was $1150 (https://consumerhealthratings.com/how-much-does-er-visit-cost/, accessed on 18 December 2022). The average cost for a pediatric inpatient hospital admission in US$ 2016 was $7800 (https://consumerhealthratings.com/healthcare_category/inpatient-average-cost-typical-prices-ballpark/, accessed on 18 December 2022), or $8493 for 2020 dollars using the US Consumer Price Index inflation index calculator (https://www.bls.gov/data/inflation_calculator.html, accessed on 18 December 2022). The cost for a fatality in a US ED is unknown but assuming it is equal to a hospital admission, in this study there were 13,272 children seen in US EDs for fractures due to firearm activity and released after treatment; 5671 admitted to the hospital; and 100 fatalities. This gives an estimated cost of (13,272 × $1150) + (8493 × $5631) + (100 × $5631), or $63.9 million. This is a conservative estimate, as it does not include costs for follow-up visits from an ED (which is crucial for fracture care), associated charges for imaging (cost of the radiographs, interpretation fees from the radiologist),prophylactic antibiotics, nor costs to the parents/family/society for time lost regarding employment, childcare and other issues. Finally, the estimate for pediatric hospital admission of $7800 ($8493 in 2020$) is likely very low for this particular scenario, as admissions to the hospital for pediatric orthopaedic surgical care are likely much higher than this $7800. What these actual numbers are is difficult to know. The important point is that pediatric fractures arising from firearm activity are a significant financial burden to everyone.

5. Conclusions

Many of the findings in this study are sobering. The increase in hospital admissions over time for firearm-associated fractures, especially in view of hospital admissions becoming more difficult to justify in the US, is concerning. If a hospital admission is a proxy of injury severity, then firearm associated fracture injuries are becoming more severe. Growing acuity of firearm-associated injuries is detrimental to the child, but also greatly impacts familial wellbeing, societal functioning, and the US-health care system financial state.

Author Contributions

Conceptualization, R.T.L.; Methodology, R.T.L.; Investigation, R.T.L. and T.L.; Data curation, T.L.; Writing—original draft, R.T.L. and T.L.; Writing—review & editing, R.T.L. and T.L. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

This study of publicly available de-identified data was considered exempt by our local Institutional Review Board.

Informed Consent Statement

Not applicable as noted above.

Data Availability Statement

This data is freely to anyone online at the Inter-University Consortium for Political and Social Research Firearm Injury Surveillance Study 1993–2020 (ICPSR 38574) (https://www.icpsr.umich.edu/web/NACJD/studies/38574, accessed on 18 December 2022).

Conflicts of Interest

The authors declare no conflict of interest.

Funding Statement

This research received no external funding.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

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Associated Data

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

Data Availability Statement

This data is freely to anyone online at the Inter-University Consortium for Political and Social Research Firearm Injury Surveillance Study 1993–2020 (ICPSR 38574) (https://www.icpsr.umich.edu/web/NACJD/studies/38574, accessed on 18 December 2022).

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