Emergency Department Visits Resulting From
Intentional Injury In and Out of School
WHAT’S KNOWN ON THIS SUBJECT: Injuries sustained by children
in the school setting have a significant public health impact.
A concerning subgroup of school injuries are due to intentional
and violent etiologies. Several studies have identified a need for
further research to understand intentional school-based injuries.
WHAT THIS STUDY ADDS: This study discusses national estimates
and trends over time and risk factors of intentional injury–related
emergency department visits due to injuries sustained in the
school setting.
abstract
BACKGROUND AND OBJECTIVE: Previous studies have reported concerning numbers of injuries to children in the school setting. The objective was to understand temporal and demographic trends in intentional
injuries in the school setting and to compare these with intentional injuries outside the school setting.
METHODS: Data from the National Electronic Injury Surveillance System–
All Injury Program from 2001 to 2008 were analyzed to assess emergency
department visits (EDVs) after an intentional injury.
RESULTS: There were an estimated 7 397 301 total EDVs due to injuries
sustained at school from 2001 to 2008. Of these, an estimated 736 014
(10%) were reported as intentional (range: 8.5%–10.7% for the study
time period). The overall risk of an EDV after an intentional injury in
school was 2.33 (95% confidence interval [CI]: 1.93–2.82) when compared with an EDV after an intentional injury outside the school
setting. For intentional injury–related EDVs originating in the school
setting, multivariate regression identified several demographic risk
factors: 10- to 14-year-old (odds ratio [OR]: 1.58; 95% CI: 1.10–2.27) and
15- to 19-year-old (OR: 1.69; 95% CI: 1.01–2.82) age group, black (OR:
4.14; 95% CI: 2.94–5.83) and American Indian (OR: 2.48; 95% CI: 2.06–
2.99) race, and Hispanic ethnicity (OR: 3.67; 95% CI: 2.02–6.69). The
odds of hospitalization resulting from intentional injury–related EDV
compared with unintentional injury–related EDVs was 2.01 (95% CI:
1.50–2.69) in the school setting. These odds were found to be 5.85
(95% CI: 4.76–7.19) in the outside school setting.
CONCLUSIONS: The findings of this study suggest a need for additional
prevention strategies addressing school-based intentional injuries.
Pediatrics 2014;133:254–261
254
AMANULLAH et al
AUTHORS: Siraj Amanullah, MD, MPH,a,b,c Julia A.
Heneghan, MD,c,d Dale W. Steele, MD, MS,a,b Michael J.
Mello, MD, MPH,a,c and James G. Linakis, PhD, MDa,b,c
Departments of aEmergency Medicine and bPediatrics, Alpert
Medical School of Brown University, Providence, Rhode Island;
cInjury Prevention Center, Rhode Island Hospital, Providence,
Rhode Island; and dDepartment of Pediatrics, Rainbow Babies
and Children’s Hospital, University Hospitals Case Medical Center,
Cleveland, Ohio
KEY WORDS
injury, emergency department, school, bullying
ABBREVIATIONS
CI—confidence interval
ED—emergency department
EDV—emergency department visit
NEISS—National Electronic Injury Surveillance System
NEISS-AIP—National Electronic Injury Surveillance System–All
Injury Program
OR—odds ratio
Drs Amanullah and Linakis conceptualized and designed the
study, carried out the initial analysis, and drafted the initial
manuscript; Drs Heneghan, Steele, and Mello helped in the
design of the study, analysis, and reviewed and revised the
manuscript; and all authors approved the final manuscript as
submitted.
www.pediatrics.org/cgi/doi/10.1542/peds.2013-2155
doi:10.1542/peds.2013-2155
Accepted for publication Nov 15, 2013
Address correspondence to Siraj Amanullah, MD, MPH, 593 Eddy
St, Department of Emergency Medicine, Claverick Building,
Second Floor, Providence, RI 02903. E-mail:
[email protected]
PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).
Copyright © 2014 by the American Academy of Pediatrics
FINANCIAL DISCLOSURE: The authors have indicated they have
no financial relationships relevant to this article to disclose.
FUNDING: No external funding.
POTENTIAL CONFLICT OF INTEREST: The authors have indicated
they have no potential conflicts of interest to disclose.
ARTICLE
American children spend ∼180 days
each year at school, making it the most
common place other than their home
where they spend time.1–3 Consequently, it is perhaps unsurprising that
they sustain an estimated 10% to 25%
of all injuries in the school setting.1,4,5
Whereas most injuries in this setting
are documented to be the result of
unintentional mechanisms, including
sports or other physical activity,4–13
a concerning subgroup of school injuries are due to intentional and violent
etiologies, with 10% to 17% of school
injuries resulting from intentional
mechanisms.4–6 Additionally, results
from the Youth Risk Behavior Surveillance System for 2011 indicate that
20.1% of youth nationwide reported
being bullied on school property.14
A number of studies have shown significant health-related issues, including
an increase in risk-taking behaviors, poor
school performance, and absenteeism
related to bullying and violence.15–23 As
a consequence, there have been numerous efforts to reduce injuries in the
school setting, including increased supervision of physical activities, improving student:teacher ratio, teaching
students how to deescalate bullying,
adding safety officers, teaching school
staff how to address violence, and extra
activities for students such as music
and arts classes to avoid unstructured
or unsupervised time in school.2,10,22,24
Pediatric intentional and unintentional
injuries have been thoroughly discussed
in the literature,20,25–30 and several studies have identified a need for further
research to understand intentional
school-based injuries.1–7,10,24,25,31–33 With
the increasing awareness of physical
and mental health issues associated
with intentional injuries resulting from
interpersonal violence and bullying in
children, it is important to examine the
overall trend for such injuries in the
school setting to tailor appropriate measures for safety and prevention.1,6,24,31,32
PEDIATRICS Volume 133, Number 2, February 2014
Therefore, the goal of this study was to
examine the national demographic and
temporal trends of intentional injuries in
the school setting. Our specific objective
was to compare emergency department
visits (EDVs) for intentional injuries sustained in the school setting to EDVs
resulting from intentional injuries sustained outside of the school setting to
better guide preventive efforts.
METHODS
Study Design
This was a retrospective cohort study
using data from the National Electronic
Injury Surveillance System (NEISS)–All
Injury Program (NEISS-AIP) from January
1, 2001, through December 31, 2008.
The study was classified as exempt by
the Rhode Island Hospital Committee
on the Protection of Human Subjects.
Study Setting and Population
Data from NEISS-AIP were obtained at
www.icpsr.umich.edu/icpsrweb/ICPSR/
series/00198. NEISS-AIP is a database
of EDVs for injury reported by 66 hospitals (of the 100 NEISS database hospitals) selected from throughout the
United States. Sampling is performed
to derive a stratified probability sample of the 5000 hospitals in the United
States with emergency departments
(EDs) that have at least 6 beds and are
operational 24 hours per day. A sampling weight is assigned to each case
on the basis of the inverse probability
of selection to provide national estimates. NEISS-AIP is operated by the US
Consumer Product Safety Commission
in collaboration with the National
Center for Injury Prevention and
Control, Centers for Disease Control
and Prevention.34 A NEISS-trained researcher at each institution is responsible for reviewing the chart and
entering data related to each injury
visit, including the patient’s age,
gender, race, and ethnicity; the date of
the injury; the location where the injury
occurred in the community; the body
part to which the injury occurred; the
intent and perpetrator (if intentional);
the patient’s diagnosis and disposition;
and a detailed account of the injury
event as gleaned from the medical
records. Trained quality assurance
coders at the NEISS center code from
the narrative and provide the “cause of
injury.” Data values with ,20 records,
with weighted estimates ,1200, or
with a coefficient of variation .30%
are considered by NEISS to be unstable
and were interpreted accordingly when
making decisions about variable recoding and regression modeling.
Measurements
Our study examined nonfatal injuryrelated EDVs from January 2001
through December 2008. The injuryrelated EDV rate was calculated by
using the average census for the age
group from the US census data over the
study time period (http://www.census.
gov/popest/data/historical/2000s/vintage_2008/). Intent of injury is recorded as “intentional” or “unintentional/
unknown” in the data set and was
used as such for this study. NEISS-AIP
defines intentional injuries as “an injury [that] was caused by an act carried out on purpose by oneself or by
another person(s), with the goal of
injuring or killing”.35 Unintentional
injuries were defined as those due
to “not deliberate means.” Because
NEISS data are not intended to capture
all deaths related to injuries, EDVs
associated with fatality or “dead
on arrival” were excluded from our
analysis.
The location of injury was identified as
“school setting” when documented as
“school,” whereas injuries that occurred in any location other than
school were coded as “outside school
setting.” Those EDVs where the location
was unknown were excluded from the
analysis. Visits by patients between the
255
ages of 5 and 19 years were included in
the analysis. Age was categorized into 3
groups: 5 to 9 years, 10 to 14 years, and
15 to 19 years, which approximate the
traditional elementary, middle, and
high school age groups, respectively.
NEISS coding for race and ethnicity
defines “white” as non-Hispanic, “black”
as both non-Hispanic and Hispanic
black, and “Hispanic” as “Hispanics for
all races other than black.” Although it
is noted by NEISS-AIP that ∼17% of the
race/ethnicity data are missing for the
overall data set, these data were found
to be missing for 7% for our study
sample.
Diagnosis at discharge was restricted
to the top 5 categories and “other.” We
created a “traumatic brain injury”
category for the diagnoses of concussion and fracture or internal injury when “head” was the injured
body part.5,36 All other diagnoses
were left as originally coded in the
NEISS-AIP database. Immediate cause
of injury was also restricted to the
top 5 causes and “other.” Disposition
was recoded as follows: “discharged”
(those patients who were “treated and
released”), “hospitalized/transferred/
observed” (those patients who were
“treated and transferred”, “hospitalized,” or “held for observation”), and
“other” (those patients who “left without being seen/left against medical advice,” or whose disposition was not
specified or was “unknown”).
Statistical Analysis
Data were analyzed with SAS (version
9.3; SAS Institute, Inc, Cary, NC) by using
the SURVEYFREQ and SURVEYLOGISTIC
procedures. A specific weighting factor
was assigned to each NEISS hospital related to the inverse probability of selection, permitting generalization of the data
to the national population. The probability
value for statistical significance was set
at an a level of 0.05. National estimates,
frequencies, and 95% confidence intervals (CIs) were calculated on the basis of
the sample weights and clusters. Tests
for trend for intentional injuries over
time were performed by using PROC
SURVEYLOGISTIC with treatment year
scored as a linear sequence. Separate
multivariable logistic regression models
were fit to the in-school and out-of-school
data to model the probability of an intentional injury–related EDV, adjusted for
gender, age, race, and ethnicity.
RESULTS
During the study time period (2001–
2008), NEISS-AIP data identified an estimated 44 721 462 injury-related EDVs for
youth 5 to 19 years of age where the location of injury was known. Of these, an
estimated 7 397 301 (12.5%) injuries occurred in the school setting (an average
of 924 662 EDVs per year). This finding
represents an annualized injury-related
EDV rate of 45 per 1000 children in the
school setting, based on the average
2001–2008 US census (census mean =
20 480 716 for 5–19 years of age).
There were a total of 736 014 (average =
92 001 per year) intentional injury–
related EDVs from the school setting,
with an annual rate of 4.5 per 1000 children. For the “outside school” setting,
the total number of intentional injury–
related EDVs was 2 293 922 from 2001 to
2008 (average = 286 740 per year), with
an annual rate of 14 per 1000 children.
For the unintentional injuries, the annual
rate of EDVs was found to be 41 per 1000
children in the school setting (average =
832 660 per year) and 214 per 1000 children in the “outside school” setting (average = 4 378 770 per year) for the study
time period. The proportion of EDVs due
to intentional injury at school varied over
time, from 10.7% of all injuries in 2001–
2002 to 8.5% of all injuries in 2007–2008
(Table 1, Fig 1). A test for trend revealed
a decreasing trend for intentional injuries inside school (Ptrend = .046) but not
for outside school (Ptrend = .462).
The demographic characteristics for
patients with intentional injury–related
EDVs from both in-school and out-ofthe-school settings are summarized
in Table 2. The odds for an EDV due to an
intentional injury (with reference to
unintentional injury) in the school setting compared with outside the school
setting were found to be 1.76 (95% CI:
1.45–2.12) in the univariate logistic
models. Male gender and the 10- to
14-year age group were identified
as risk factors for intentional injury–
related EDVs in the school setting and
female gender and the 15- to 19-year
age group were identified as risk
TABLE 1 School Injury–Related EDVs in the 5- to 19-Year-Old Age Group
NEISS Data Years
2001–2002
2003–2004
2005–2006
2007–2008
School Setting, n (% of Total
Injury-Related EDVs; 95% CI)
Intentional Injury–
Related EDVs
Unintentional Injury–
Related EDVs
Intentional Injury–
Related EDVs
Unintentional Injury–
Related EDVs
198 670 (10.7; 6.1–15.3)
203 763 (10.8; 7.7–13.9)
183 692 (9.8; 6.4–13.2)
149 889 (8.5; 6.3–10.6)
1 660 545 (89.3; 84.7–93.4)
1 689 123 (89.2; 86.1–92.3)
1 697 234 (90.2; 86.8–93.6)
1 614 385 (91.5; 89.4–93.7)
601 585 (6.4; 4.2–8.6)
595 923 (6.3; 5.0–7.5)
599 987 (6.2; 4.6–7.8)
496 427 (5.7; 4.9–6.4)
8 776 813 (93.6; 91.4–95.8)
8 892 491 (93.7; 92.3–95.0)
9 091 675 (93.8; 92.2–95.4)
8 269 184 (94.3; 93.6–95.1)
Estimated frequencies are presented as 2-year totals.
256
AMANULLAH et al
Outside-School Setting, n (% of Total
Injury-Related EDVs; 95% CI)
ARTICLE
school setting. Black race and Hispanic
ethnicity were both found to confer
higher risks for the school setting when
compared with the outside-school setting (Table 4).
FIGURE 1
Estimated numbers (with 95% CIs) of intentional injury–related EDVs for inside-school and outsideschool settings for children aged 5 to 19 years old (2-year totals). Tests for trend for intentional injuries
over time revealed a decreasing trend for intentional injuries inside the school (Ptrend = .046) but not
for outside of the school (Ptrend = .462) setting.
factors for intentional injury–related
EDVs in the outside school setting (Table 3). Patients of black and American
Indian race and of Hispanic ethnicity
were also found to have higher risk of
intentional injury–related EDVs in both
settings when compared with unintentional injuries (Table 3).
For intentional injury–related EDVs
from the school setting (Table 4), various demographic risk factors were
identified as follows: 10- to 14-year and
15- to 19-year age groups, black and
American Indian race, and Hispanic
ethnicity (odds ratio [OR]: 3.67; 95%
CI: 2.02–6.69). When contrasting the 2
settings (Table 4), girls were less likely
to have an intentional injury–related
EDV compared with boys in the school
setting but were more likely than boys
to have an intentional injury–related
EDV in the outside-school setting. The
risk of an intentional injury–related
EDV was found to be lower for the 15- to
19-year age group in the school setting
when compared with the outside
TABLE 2 Demographic Characteristics of Children With Intentional Injury–Related EDVs in the
School and Outside-School Settings
Variable
Gender
Male
Female
Age
5–9 years
10–14 years
15–19 years
Race
White
Black
Asian
American Indian
Other
Not specified
Ethnicity
Hispanic
Non-Hispanic
School Setting, % (95% CI)
Outside-School Setting, % (95% CI)
67.9 (66.5–69.4)
32.1 (30.6–33.5)
54.9 (52.5–57.3)
45.1 (42.7–47.5)
16.8 (9.4–24.2)
48.5 (45.8–51.3)
34.7 (24.9–44.5)
8.7 (6.3–11.1)
22.7 (20.4–24.9)
68.6 (64.1–73.1)
32.4 (18.5–46.3)
35.1 (5.8–23.5)
0.9 (0.1–1.9)
2.3 (0–6.4)
14.7 (0–29.5)
14.6 (4.9–24.2)
38.4 (25.7–51.0)
29.5 (19.6–39.4)
0.6 (0.1–1.2)
2.9 (0–7.9)
11.4 (1.4–21.4)
17.2 (7.6–26.9)
16.5 (0–34.1)
83.5 (65.9–100)
13.0 (0.7–25.4)
87.0 (74.6–99.3)
Data source: NEISS (2001–2008)34
PEDIATRICS Volume 133, Number 2, February 2014
A description of the EDVs is presented in
Table 5 for the 2 settings. Fractures
were identified more often in the school
setting, whereas lacerations were
identified more often in the outsideschool setting. The proportion of injuries due to traumatic brain injury was
higher in the school setting compared
with the outside-school setting. Poisoning was identified as 1 of the top 5
diagnoses for the outside-school setting. Conversely, strain/sprain was
common in the school setting but
comparatively not as common outside
of school. The proportion of EDVs due to
assault as an immediate cause was
higher in the school setting, and those
due to self (intentional self-harm) or
legal intervention were more common
in the outside-school setting.
With regard to disposition, the overall
risk of hospitalization (hospitalized/
transferred/observed) in all settings was
4.91 (95% CI: 4.03–5.97) for any intentional injury–related EDV compared
with an unintentional injury–related
EDV. The likelihood of hospitalization
after an intentional injury–related
EDV (versus an unintentional injury–
related EDV) was lower for the school
setting (OR: 2.01; 95% CI: 1.50–2.69)
when compared with outside the school
setting (OR: 5.85; 95% CI: 4.76–7.19)
(Table 3).
DISCUSSION
Despite increased emphasis on safety
at school and evidence of a decreasing
trend, children aged 5 to 19 years still
experienced a substantial number of
intentional injuries at school over the
time period studied. A recent study
has also noted that ED utilization by
pediatric patients due to violence (not
limited to a specific setting) has not
257
TABLE 3 Univariate Logistic Models for Intentional Injury–Related EDVs Compared With
additional interventions to enhance
safety at school.
Unintentional Injury–Related EDVs for Inside- and Outside-School Settings
Variable
Inside-School Setting
OR
Age
5–9 years
10–14 years
15–19 years
Gender
Male
Female
Race
White
Black
Asian
American Indian
Other
Ethnicity
Non-Hispanic
Hispanic
Top 5 diagnosis
Contusion/abrasion
Laceration
Fracture
Traumatic brain injury
Strain/sprain
Poisoning
Other/unknown
Disposition
Discharged
Hospitalized/transferred/observed
Other
Outside-School Setting
95% CI
OR
95% CI
1.44
1.38
1.0 (reference)
0.98–2.13
0.71–2.68
2.23
5.34
1.0 (reference)
1.87–2.66
3.94–7.23
0.77
1.0 (reference)
0.73–0.83
1.24
1.0 (reference)
1.11–1.37
3.86
1.32
2.24
3.72
1.0 (reference)
2.89–5.15
0.55–3.17
1.85–2.71
2.12–6.51
2.75
0.80
2.14
2.49
1.0 (reference)
2.02–3.75
0.62–1.04
1.89–2.43
1.67–3.70
2.35
1.0 (reference)
1.51–3.65
1.88
1.0 (reference)
1.42–2.48
0.71
0.33
1.02
0.13
—
0.90
1.0 (reference)
0.62–0.82
0.26–0.41
0.85–1.22
0.11–0.15
—
0.68–1.20
0.70
0.37
0.97
—
5.01
0.48
1.0 (reference)
0.65–0.76
0.32–0.43
0.75–1.26
—
3.07–8.17
0.42–0.55
2.01
2.10
1.0 (reference)
1.5–2.69
1.3–3.4
5.85
2.66
1.0 (reference)
4.76–7.19
1.87–3.78
Data source: NEISS (2001–2008)34
changed.29 Additionally, our study has
shown that the proportion of injury
visits originating from school that are
intentional continues to be higher
than for those suffered out of the
school setting, suggesting the need for
TABLE 4 Separate Multivariable Logistic Models for Predictors of Intentional Injury–Related EDVs
Compared With Unintentional Injury–Related EDVs in the 2 Settings
Inside-School Settinga
Variable
OR
Age
5–9 years
10–14 years
15–19 years
Gender
Male
Female
Race
White
Black
Asian
American Indian
Other
Ethnicity
Non-Hispanic
Hispanic
95% CI
AMANULLAH et al
OR
95% CI
1.58
1.69
1.0 (reference)
1.10–2.27
1.01–2.82
2.38
5.87
1.0 (reference)
2.06–2.74
4.69–7.34
0.80
1.0 (reference)
0.76–0.86
1.26
1.0 (reference)
1.13–1.40
4.14
1.43
2.48
1.14
1.0 (reference)
2.94–5.83
0.59–3.44
2.06–2.99
0.99–1.32
3.00
0.87
2.40
0.92
1.0 (reference)
2.04–4.43
0.70–1.09
2.13–2.71
0.8–1.06
3.67
1.0 (reference)
2.02–6.69
3.27
1.0 (reference)
2.05–5.23
Data source: NEISS (2001–2008)34
Multivariable logistic models adjusted for age, gender, race and ethnicity.
a Weighted n = 5 931 550.
b Weighted n = 30 028 406.
258
Outside-School Settingb
This study identified a gender disparity
in intentional injury–related EDVs for
the 2 settings, with boys more likely to
have intentional injury–related EDVs
when originating in the school setting
and girls more likely in the outsideschool setting. This gender difference
is interesting, especially because previous studies have identified male
gender to be a risk factor for injuries in
a variety of settings.6,11,12,14,21,26 Further
research is needed to understand why
this disparity exists.
Another important finding from this
study is that middle school–aged children (10- to 14-year-old group) carry
a significant burden of intentional
injury–related EDVs in the school setting. This is in contrast to the out-ofschool setting where high school–aged
students (15- to 19-year-old group) were
found to have the highest burden. This
distribution persisted through the
study time period and was consistent
with our earlier study.5
Previous studies have documented that
African American race and Hispanic
ethnicity are associated with increased
likelihood of bullying and its associated
mentaland physicalhealth impacts.18,19,21
Our study also suggests that racial disparity persists for the risk of intentional
injury–related EDVs. In addition to students of black race and Hispanic ethnicity, American Indian youth were found
to be high risk. Interestingly, these demographic risks are much higher in the
school setting compared with the outsideschool setting. This finding suggests the
need for developing interventions that
meet the needs of these populations.
Of note, there is no information in
NEISS-AIP regarding the racial and
ethnic background of perpetrators or
of the overall racial/ethnic composition
of the school where an injury occurred,
thus limiting understanding of the racial disparity phenomenon.
ARTICLE
TABLE 5 Characteristics of EDVs Related to Intentional Injury in the School and Outside-School
Settings
Variable
Top 5 diagnosis
Contusion/abrasion
Laceration
Poisoning
Fracture
Traumatic brain injury
Strain/sprain
Other/unknown
Primary body part affected
Head/neck
Upper trunk
Lower trunk
Arm/hand
Leg/foot
Other
Intent
Assault
Self
Legal intervention
Perpetrator
Friend/acquaintance
Multiple perpetrators
Parent
Spouse/partner
Other relative
Unrelated caregiver
Official authorities
Stranger
Others
Top 5 immediate cause of injury
Struck by/against
Fall
Cut/pierce
Other bite/sting
Poisoning
Firearms/gunshot
Other/unknown
Disposition
Discharged
Hospitalized/transferred/observed
Other
School Setting,
% (95% CI)
Outside-School
Setting, % (95% CI)
39.8 (36.3–43.3)
15.7 (14.3-17.1)
—
11.6 (8.8–14.4)
10.2 (7.9–12.6)
6.9 (6.0–7.8)
15.8 (14.3–17.1)
29.0 (26.3–31.8)
20.3 (18.7–21.9)
12.9 (8.9–16.9)
7.3 (6.3–8.4)
7.0 (5.1–8.9)
—
23.5 (19.9–27.1)
60.1 (58.3–61.9)
6.2 (5.8–6.7)
5.0 (4.0–5.9)
20.8 (19.5–22.0)
5.0 (4.3–5.7)
2.9 (2.0–3.8)
45.0 (41.3–48.6)
6.3 (5.8–6.9)
9.3 (8.0–10.7)
18.7 (17.7–19.8)
4.8 (4.1–5.5)
15.9 (12.5–19.3)
95.8 (94.3–97.2)
3.3 (1.7–4.9)
0.9 (0.7–1.2)
79.2 (73.7–84.7)
18.5 (13.1–24.0)
2.3 (1.9–2.6)
86.0 (84.6–87.4)
9.7 (8.1–11.4)
0.1a (0.1–0.3)
0.2a (0.1–0.3)
0.2 (0.1–0.3)
0.1a (0–0.1)
0.1a (0–0.1)
0.3 (0.1–0.5)
3.3 (2.8–3.8)
21.1 (16.6–25.7)
22.2 (16.6–25.7)
13.2 (11.8–14.5)
9.4 (7.8–11.1)
22.8 (19.6–25.8)
0.4 (0.3–0.5)
0.1a (0.0–0.1)
4.5 (3.1–6.0)
6.3 (5.5–7.1)
79.1 (76.6–81.5)
10.4 (9.0–11.8)
3.8 (2.9–4.7)
3.1 (1.9–4.3)
1.2 (0.5–1.9)
—b
2.4 (1.8–3.1)
65.4 (60.7–70.2)
4.0 (3.6–4.5)
9.2 (8.4–10.0)
—
9.8 (6.7–12.9)
2.6 (0.9–4.2)
9.0 (7.9–10.0)
96.4 (95.5–97.2)
3.1 (2.4–3.8)
0.5 (0.3–0.7)
84.4 (81.7–87.0)
14.7 (11.9–17.6)
0.9 (0.5–1.3)
Data source: NEISS (2001–2008)34
a National estimates ,20 actual cases or 1200 estimated cases may not be statistically stable.
b Fire arms/Gunshot (not among top 5 immediate cause of injury) in ‘school setting’ = 0.08% a (95% CI: 0.01%–0.14%).
When considering the types of injuries
sustained due to intentional mechanisms, it is important to note that the
risk of sustaining traumatic brain
injuries was similar to that of sustaining abrasions/contusions. The head
and neck region was also found to be
the most common body region affected,
followed by the upper extremities. This
finding is in contrast to earlier studies
that documented upper extremity to be
the most frequently affected body part
PEDIATRICS Volume 133, Number 2, February 2014
in all school injuries.4,7 Possibly related
to this phenomenon, most of the intentional injuries in our study sample
were reported to be to the result of
assault, and ∼90% reported the perpetrator to be either a friend or an
acquaintance in the school setting.
Other studies have shown that a bullied victim frequently knew the bully
and that the incident usually involved
a past disagreement.28 When considering the perpetrators, it is notable
that 10% of the EDVs were reportedly
due to multiple perpetrators in the
school setting. Intentional injuries and
violence have immense mental health
effects on the victims, and studies have
reported that victims may be involved
with future violence, either as victims
or as perpetrators.21,22 With the knowledge that intentional injuries continue
to be a significant problem in the school
setting, and in light of the limited information that these data offer regarding perpetrators, it is clear that
more work needs to be done to understand the victim-bully relationship to
design preventive efforts.
The risk of hospitalization in our study
was found to be higher for intentional
versus unintentional injury–related
EDVs in either setting. If being hospitalized is a proxy for sustaining a serious injury, these data document that
children sustained more serious injuries resulting in hospitalization when
the injury was intentionally inflicted
compared with unintentional injuries.
This finding further emphasizes the
importance of the problem and need
for preventive efforts.
This study was limited in terms of its
ability to completely capture the full
range of injuries suffered by children,
both in and out of the school environment. Because the NEISS-AIP data
source is predicated on the injury
resulting in an EDV, it does not include
patients who were directly admitted to
a hospital. This limitation also points
toward the inherent selection bias dependent on the sampling design and
a caregiver’s decision to seek medical
care in the ED. For example, studies
have shown that there may be overreferral to the ED from school after an
injury.9 Additionally, care may have
been sought at a primary care office,
urgent care center, or other medical
provider, and those visits would not
have been captured here. Another
limitation is the data’s wide CIs that
259
result from national estimates that
are based on a restricted sample of
66 hospitals. It is also important to note
that NEISS data do not code for the
acuity of a visit and do not report data
on fatalities in the school setting, which
may limit understanding of the most
serious injuries.
Although the NEISS-AIP database collects information on a wide range of
patients, it lacks the granularity that
would be necessary to more fully answer questions one might have about
an individual injury. This, in turn,
makes it difficult to ascertain the
specific circumstances under which
each of the injuries occurred. A
plethora of characteristics related to
the school environment, including the
physical environment and location of
a school, supervision provided while in
the school environment, demographic
characteristics of perpetrators, and
many others, all may have an effect on
the occurrence of an individual intentional injury. Precise detail about
the intentional injury event can assist
in developing preventive strategies
especially related to using the principles of the Haddon Matrix.37
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CONCLUSIONS
There are substantial numbers of intentional injury–related EDVs from
the school setting. Our study identifies age, gender, and racial and ethnic
disparities associated with schoolbased intentional injuries, emphasizing the need for the development
of culturally appropriate preventive
strategies.
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FANTASY FOOTBALL: I was recently emailing with one of my advisees when she
confessed that she was feeling stressed. As she is a fourth year medical student
preparing to interview for a highly competitive residency position, I offered some
words of wisdom on the application process and the strength of her application.
She responded that her stress was not because of her upcoming interviews but
because it was draft night for her fantasy football league.
Fantasy football is a game in which fans create imaginary teams selected from
players in the National Football League. Fans score points and compete against
each other based on the statistical performance of their selected players. This
creates intense interest in games across the nation. It turns out that fantasy
football is incredibly popular – so popular that even football stadiums have to
account for a fan’s desire to keep track of his or her players.
As reported in The New York Times (Sports: September 14, 2013), the days when
fans could only see their local football team play by attending a game in person
are long gone. With high-definition TV, high-speed internet connections, and round
the clock programming, fans can see almost any game any time and track how
well their local and fantasy teams are doing from the comfort of home. Recognizing the popularity of fantasy football, stadiums are now being outfitted with
lounges packed with TV screens showing all the games being played, high-speed
internet connections, comfortable chairs, air conditioning, and easy access to
food and drink. Fans dispirited by the play of the home team can wander into the
lounge and root for their fantasy football players. Lounges in some stadiums are
so popular that bouncers are employed to control access and crowding.
While it seems a bit odd to purchase a ticket essentially to spend the afternoon in
a sports bar, the teams are trying to battle flagging attendance and create a great
game-day experience. As for my advisee, she does not attend the games in person,
preferring to keep track of the New England Patriots and her fantasy team by
smartphone. And, she told me that she had a very successful draft.
Noted by WVR, MD
PEDIATRICS Volume 133, Number 2, February 2014
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