The Association Between ADHD in Adolescence and Injury in Early Adulthood in Israel: A Nationwide Historical Cohort Study

Abstract

Objective:

To examine the association between late adolescence ADHD and the risk of serious injury in early adulthood.

Method:

A nationwide cohort study utilizing data from the Military Health Examinations Database for potential military recruits (age 16.5–18 years), cross-referenced with the Israeli National Trauma Registry (2008–2020). Individuals with and without ADHD (mild/severe) were compared for early adulthood injury risk using Cox models.

Results:

This study compared 76,403 participants with mild ADHD (18.76%) and 330,792 without (81.24%), alongside 2,835 severe ADHD participants (1.11%) versus 252,626 without (98.89%). Adjusted hazard ratios for injury-related hospitalization were 1.27 (95% CI [1.17, 1.37]) for mild ADHD and 1.40 (95% CI [1.09, 1.79]) for severe ADHD, compared to non-ADHD.

Conclusions:

Adolescents with ADHD, regardless of severity, had a significantly higher risk of hospitalization due to injury that persists into early adulthood, underscoring the importance of recognizing ADHD as an injury risk and incorporating it into injury prevention strategies.

Keywords

ADHD adolescence young adult injury trauma

Background

Attention-deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder that affects individuals across the lifespan, with an estimated global prevalence of around 5% to 10% in children and 2% to 5% in adults(Fayyad et al., 2017; Polanczyk et al., 2014). In the United States, it is estimated that between 8.8% and 11.0% of children aged 4 to 17 years are diagnosed with ADHD (Visser et al., 2014). In Israel, the estimated prevalence is even higher, amounting to 14.4% among children aged 5 to 17 years (Davidovitch et al., 2017). In contrast, the prevalence among adults is reported to be lower, with ADHD affecting approximately 4.3% of the adult population in the U.S. (London & Landes, 2021). This difference is thought to result, at least partly, from under-diagnosis in the adult population, with the diagnostic tools being different from those used for children. In the last few decades, there has been a substantial increase in the diagnosis and treatment of ADHD in Israel, with the consumption of ADHD medications more than doubling between 2005 and 2012 (Ponizovsky et al., 2014).

In addition to difficulties in social, academic, or occupational functioning, one concern related to ADHD is the increased risk of injuries among individuals with this condition. In 2017, a total of 1,845 Israelis died due to trauma, accounting for 54.8% of deaths between ages 18 and 24 years and 26.1% between 24 and 45 years (Israeli Central Bureau of Statistics, 2019). Additional severe toll is taken in the form of injury and disability.

Several studies have examined the relationship between ADHD and injury risk, with evidence suggesting that individuals with ADHD are more prone to experiencing injuries compared to those without the disorder (Chang et al., 2014; Dalsgaard et al., 2015; Guy et al., 2016; Lindemann et al., 2017; Merrill et al., 2009; Shem-Tov et al., 2019; Sun et al., 2019). This association is well described in children and adolescents, including a meta-analysis (Ruiz-Goikoetxea et al., 2018).

The increased risk of injury translates to increased mortality, specifically unnatural mortality, in individuals with ADHD (Dalsgaard et al., 2015). The contribution of other psychiatric comorbidities to this increased mortality was also described (Sun et al., 2019). This phenomenon can be partially explained by the fact that individuals with ADHD are prone to risky behavior patterns (Shoham et al., 2021), particularly hazardous driving patterns (Bron et al., 2018). ADHD has also been proven to be a risk factor for anti-social behavior and substance abuse, and subsequently to criminal behavior, with staggeringly higher rates of arrests, convictions, and incarcerations (Mannuzza et al., 2008).

It is worth mentioning that, in the case of ADHD, providing appropriate treatment is considered effective in improving outcomes (Ruiz-Goikoetxea et al., 2018; Shaw et al., 2012). This underscores the value of considering and adopting relevant policy changes, as suggested by Ornoy and Spivak (2019), who calculated a possible Benefit to Cost ratio of up to 7.02 for screening and treating ADHD in Israeli primary school students.

Most previous studies focused on specific types of injuries and did not examine the overall injury risk and outcomes in individuals with ADHD. The age ranges, and effect size also varied across the studies, apart from the differences in study settings and methodologies. Most of these studies examine the pediatric population even though ADHD often continues to affect the adult’s life. Understanding the association between ADHD and injury is essential for developing targeted interventions to reduce the risk of injury in individuals with ADHD. In this study, two large nationwide databases were cross-referenced to create a large cohort of ADHD adolescents and controls, intending to examine:

1) The effect of ADHD in adolescence on the risk of hospitalization in early adulthood due to injury (any injury, by injury severity, and injury mechanism).

2) The effect of ADHD on injury-related in-hospital mortality and utilization of critical hospital resources (hospital length of stay, admission to intensive care unit and need for surgical intervention).

Methods

Study Design and Data Source

A historical cohort study was conducted based on cross-referencing the data from the Military Health Examinations Database (MHED) in the Israel Defense Forces (IDF), representing the exposure variable, with the data from the Israeli National Trauma Registry (INTR), representing the outcome variables, recorded between 2008 and 2020.

Medical fitness for duty is determined and logged for all potential recruits for military service (as defined in the Israel Security Service Law) and recorded as an ordinal measure termed the “Medical Profile” (Knesset – Israeli Parliament, 1986). All potential recruits undergo medical assessment and are assigned a profile during their initial assessment in the recruitment office, regardless of whether they are eventually recruited or exempt from service. The data are based on a self-reporting questionnaire, physical examination, urinalysis, and medical information provided by the potential recruit. Further examinations and referral to specialist assessment and outpatient testing are performed as necessary. Medical and psychiatric diagnoses are compiled into diagnostic codes, which are assigned a severity level. The diagnostic code with the highest degree of severity determines the final medical profile and dictates the potential recruit’s fitness for service, specifically for combat or combat-adjacent service.

The INTR is an extensive database of hospitalized trauma patients, providing broad geographic and demographic coverage in the country (Israel National Center for Trauma & Emergency Medicine Research, 2016). Most of the trauma centers in Israel participated in the INTR, including all six level I trauma centers, which cover more than 90% of all national trauma cases and 98% of the severe cases. The INTR includes all hospitalized trauma patients classified based on an International Classification of Diseases, Ninth Revision, Classification Modification (ICD-9-CM) diagnosis code of 800-959.9, including deaths in the Emergency Department (ED) and transfers. The INTR does not include patients who died at the scene of the event or on the way to the hospital, were discharged following treatment in the ED, or were admitted 72 hr or more following the injury. Injuries resulting from poisoning, drowning, or suffocation also are not included in the registry. In order to avoid duplicate entries for transferred patients, their most recent hospitalization data were used. Trained trauma registrars record data reported in the registry at each trauma center under the supervision of a trauma director and trauma coordinator. Electronic files are transferred to the INTR at the National Center for Trauma and Emergency Medicine Research, where extensive logical tests and quality assurance are carried out to ensure their reliability and completeness prior to data analysis. Unclear, erroneous, or missing data are referred back to the trauma centers for clarification or completion, leading to a missing data rate of less than 0.5% of entries.

This research received the approval of the Institutional Review Boards from the Sheba Medical Center (Number 5138-18-SMC) and the headquarters of IDF Chief Medical Officer (Number 2263-2021).

Inclusion and Exclusion Criteria

For assessment of the association of mild ADHD with the risk of injury, individuals who attended the recruitment office between 2015 (when the diagnostic code for mild ADHD was first introduced) and 2020 were included. For severe ADHD, individuals who attended the recruitment office between 2008 and 2020 were included. Individuals who were outside the usual age margins for reporting to the recruitment office (16.5–18 years) were excluded, as they represent special populations outside the scope of this study and shift the distribution of follow-up ages in the study. For quality assurance purposes, individuals for whom the age of birth in the MHED was not in accordance with the reported age and date of injury in the INTR, were excluded. This study conducted separate comparisons for severe ADHD and mild ADHD. Of note, individuals with severe ADHD, as defined in our study by their “military medical profile,“ are exempt from combat duty assignment, whereas those with mild ADHD may be assigned any duty, depending on other co-existing medical conditions. To compare individuals with severe ADHD to controls with similar risk exposure regarding the nature of military service, individuals with severe ADHD were only compared to controls with similar medical profiles unfit for combat service. Mild ADHD does not affect the overall medical profile; thus, these individuals were compared to all other recruits.

Outcomes

The diagnostic code for attention-deficit hyperactivity disorder was an exposure variable, and this study’s primary outcome was the risk of overall traumatic injury resulting in hospitalization. Only injuries that occurred later than the report to the recruitment office were sought when cross-referencing the databases. The study participants were followed whether admitted to a hospital or not due to injury in one of the hospitals included in the INTR during 2008 to 2020. Severe and critical injury (Injury Severity Score [ISS] 16-75), injury mechanism, mortality, and utilization of hospital resources (hospital length of stay [LOS], admission to intensive care unit [ICU] and need for surgical intervention) were the secondary outcomes.

The data measured included age, gender, socioeconomic status (SES), ADHD, neuropsychiatric comorbidities, hospital admission due to injury, injury mechanism, injury severity score (ISS), utilization of critical hospital resources and disposition at hospital discharge (in-hospital mortality, referred for rehabilitation service). Age in years was compared as mean (standard deviation) and median (interquartile range). Socioeconomic status, determined by the place of living, was categorized as low (lower 30%), middle (30%–70%) and high (highest 30%) (Central Bureau of Statistics, 2019). Mechanism of injury was classified into motor vehicle collision (MVC), fall, burn/fire, other unintentional (which included unintentional struck from object/person, cuts/piercing, injury from a machine, unintentional firearm injuries and others), intentional and unidentified mechanism. Injury severity score was grouped into four categories (1–8, 9–14, 16–24, and 25–75) (Rozenfeld et al., 2014), which were then grouped into two categories (1–14 and 16–75) in the model estimating the risk of severe and critical injury (ISS 16-75). Relevant comorbidities (substance abuse disorder and impulse control disorders) were obtained from the MHED based on their diagnostic codes.

Statistical Analysis

Data analysis was performed using R version 4.3.1 (R Core Team, Vienna, Austria). Descriptive data were compared using Chi-square test or Fisher’s exact test as appropriate for categorical variables, Student’s t-test or Man-Whitney test for continuous variables with and without normal distribution, respectively. The incidence rates for hospitalization due to any injury, specific injury mechanisms and severe injury (ISS 16-75) were calculated as cumulative number of events divided by cumulative person-years. Kaplan-Meir analysis was performed to assess the cumulative incidence of injuries leading to hospitalization as a function of ADHD diagnosis.

Cox Proportional Hazards Regression models were performed to estimate the influence of ADHD on the risk of any injury and the risk of specific injury mechanisms and severe and critical injury (ISS16-75) while controlling for possible confounding factors. Interactions and multi-collinearity between the independent variables were tested using variance inflation factor (VIF) for their influence on the dependent variables.

Descriptive data values were reported as percentages for the categorical variables, as mean (standard deviation) and median (interquartile range) for the continuous variables. Incidence rates were displayed as cases per 100,000 person-years with the corresponding 95% confidence intervals (CI). Results from the Cox Proportional Hazards models were presented as hazard ratios (HR), with the corresponding 95% CI. A p-value < .05 was considered statistically significant.

The manuscript was composed in accordance with the Strengthening the reporting of observational studies in epidemiology (STROBE) statement (von Elm et al., 2007).

Results

A flow chart showing the study exclusion process is displayed in Figure 1. Seventy-six thousand four hundred three individuals with mild ADHD were compared with 330,792 individuals without ADHD in the years 2015 to 2020, and 2,835 individuals with severe ADHD were compared with 252,626 individuals without severe ADHD in the years 2008 to 2020. Their baseline characteristics are detailed in Table 1. When comparing individuals with mild or severe ADHD to their respective control groups, significant differences were observed in terms of gender, age (mean and median), and SES (Table 1).

Figure 1.

Flow diagram of the study’s process inclusion, exclusion and division to comparison groups for (A) mild ADHD and (B) severe ADHD.

Table 1.

Baseline Characteristics for Adolescents and Young Adults With ADHD Compared With a Cohort Without ADHD.

Variables		Participants with and without mild ADHD (N₁ = 407,195)^a			Participants with and without severe ADHD (N₂ = 255,461)^a
Variables		Mild ADHD (18.76%)	No ADHD (81.24%)	p-Value	Severe ADHD (1.05%)	No ADHD (98.95%)	p-Value
Age in years	Median (IQR)	16.97 (16.78–17.23)	16.92 (16.75–17.15)	<.001	17.17 (16.96–17.47)	17.07 (16.88–17.33)	<.001
Age in years	Mean (SD)	17.03 (0.34)	16.99 (0.32)	<.001	17.23 (0.35)	17.12 (0.33)	<.001
Gender (%)	Male	62.5	54.8	<.001	73.9	50.2	<.001
SES (%)	Low	2.0	3.6	<.001	3.2	3.7	<.05
	Middle	71.1	74.1		72.6	74.0
	High	26.9	22.3		24.3	22.3
Comorbidity (n, %)	Impulse control disorder	28 (0.04)	91 (0.03)	NS	7 (0.25)	164 (0.06)	<.001
Comorbidity (n, %)	Substance abuse disorder	167 (0.22)	453 (0.14)	<.001	12 (0.42)	1,004 (0.40)	NS

Note. IQR = interquartile range; % = percentage; SES = socioeconomic status; ADHD = attention deficit/hyperactivity disorder; NS = non-significant (p-value ≥ .05).

It is important to note that mild ADHD and severe ADHD are exclusive diagnoses, and as a result, their effects were evaluated independently from the N₁ and N₂ populations, respectively.

In the mild ADHD group, the incidence rate of injury-related hospitalization was 182.0 (95% CI [169.8, 194.8]) per 100,000 Person Years (PY) compared to 140.8 (95% CI [135.6, 146.1]) per 100,000 in the non-ADHD group (17.5 (95% CI [13.9, 21.7]) and 13.8 (95% CI [12.2, 15.5]), respectively for severe injuries (ISS ≥ 16)), while in the severe ADHD group, the incidence rate was 167.5 (95% CI [129.0, 213.8]) per 100,000 PY compared to 107.6 (95% CI [104.2, 111.1]) per 100,000 PY (10.3 (95% CI [2.8, 26.4]) and 11.5 (95% CI [10.4, 12.7])), respectively for severe injuries), see Table 2.

Table 2.

Incidence Rates and Cox Proportional Hazard Ratios for Overall Injury, Severe and Critical Injury (ISS16+) and Specific Injury Mechanisms Among Adolescents and Young Adults With and Without ADHD.^d

Outcome variables	ADHD status^a	n	Person-years	Incidence rate per 100,000 person-years (95% CI)	Unadjusted HR (95% CI)	Adjusted HR^c (95% CI)
Overall injury^e	Mild ADHD	828	455,038	182.0 [169.8, 194.8]	1.29 [1.20, 1.40]*	1.27 [1.17, 1.37]*
	No ADHD	2,779	1,973,746	140.8 [135.6, 146.1]	Ref.	Ref.
	Severe ADHD	64	38,219	167.5 [129.0, 213.8]	1.55 [1.21, 1.99]*	1.39 [1.09, 1.78]**
	No ADHD	3,686	3,425,384	107.6 [104.2, 111.1]	Ref.	Ref.
ISS16-75^e	Mild ADHD	80	458,088	17.5 [13.9, 21.7]	1.27 [0.99, 1.62]	1.24 [0.97, 1.60]
	No ADHD	274	1,983,730	13.8 [12.2, 15.5]	Ref.	Ref.
	Severe ADHD	4	38,799	10.3 [2.8, 26.4]	0.90 [0.34, 2.40]	0.76 [0.28, 2.04]
	No ADHD	399	3,456,770	11.5 [10.4, 12.7]	Ref.	Ref.
MVC^e	Mild ADHD	406	456,731.9	88.9 [80.5, 98.0]	1.42 [1.27, 1.59]*	1.40 [1.25, 1.57]*
MVC^e	No ADHD	1,242	1,979,714	62.7 [59.3, 66.3]	Ref.	Ref.
Fall	Mild ADHD	135	457,855.9	29.5 [24.7, 34.9]	1.03 [0.85, 1.24]	1.02 [0.84, 1.23]
Fall	No ADHD	570	1,982,468	28.6 [26.4, 31.2]	Ref.	Ref.
Burn/Fire	Mild ADHD	21	458,335.6	4.6 [2.8, 7.0]	1.07 [0.66, 1.73]	1.13 [0.70, 1.82]
Burn/Fire	No ADHD	85	1,984,447	4.3 [3.4, 5.3]	Ref.	Ref.
Other Unintentional^b,e	Mild ADHD	194	457,675.2	42.4 [36.6, 48.8]	1.31 [1.11, 1.54]**	1.24 [1.06, 1.46]**
Other Unintentional^b,e	No ADHD	643	1,982,315	32.4 [30.0, 35.0]	Ref.	Ref.
Intentional	Mild ADHD	71	458,113.3	15.5 [12.1, 19.6]	1.33 [1.02, 1.73]***	1.31 [1.00, 1.71]
Intentional	No ADHD	232	1,983,838	11.7 [10.2, 13.3]	Ref.	Ref.

Note. ADHD = attention deficit/hyperactivity disorder; ISS = injury severity score; n = number of hospitalized cases for injury; MVC = motor vehicle collision; HR = hazard ratio; CI = confidence interval; Ref. = reference group.

The mild ADHD cohort constituted 76,403 participants (18.76%) and the group without ADHD constituted 330,792 participants (81.24%) for each analysis. In contrast, the severe ADHD group composed 2,835 participants (1.11%) and was compared with 252,626 individuals without ADHD (98.89%).

Unintentional other included unintentional struck from object/person, cuts/piercing, injury from machine and others.

Adjusted for gender and socioeconomic status (classified into low, middle and high), impulse control disorder, and substance abuse disorder.

It is important to note that mild ADHD and severe ADHD are exclusive diagnoses, and as a result, their effects were evaluated independently from different populations, N₁ = 407,195 and N₂ = 255,461, respectively.

The incidence rates are significantly different between the comparison groups.

p < .001. **p < .01. ***p < .05.

In the Cox proportional hazard regression, adjustments were made for gender, socio-economic status and comorbidity with impulse control or substance abuse disorders. Multi-collinearity was ruled out by VIF calculation (1.00). Both mild (unadjusted HR: 1.29, 95% CI [1.20, 1.40]; adjusted HR: 1.27, 95% CI [1.17, 1.37]) and severe (unadjusted HR: 1.55, 95% CI [1.21, 1.99]; adjusted HR: 1.39, 95% CI [1.09, 1.78]) ADHD were associated with an increased risk for injury-related hospitalization (Table 2). This association became less apparent and was non-significant when examining the risk for more severe injuries (ISS16-75): Unadjusted HR = 1.27 (95% CI [0.99, 1.62]); adjusted HR = 1.24 (95% CI [0.97, 1.60]) for mild ADHD and unadjusted HR = 0.90 (95% CI [0.34, 2.40]); adjusted HR = 0.76 (95% CI [0.28, 2.04]) for severe ADHD (Table 2). This is most likely due to the decreased overall incidence of these injuries.

Table 2 also displays the incidence rates and the results of the Cox proportional hazard model for specific injury mechanisms. It was only performed for the mild ADHD population due to the small overall number of injuries in the severe ADHD group. A statistically significant association was found between mild ADHD, motor vehicle collisions, and other unintentional injuries.

Figure 2 displays the Kaplan-Meyer curves of cumulative injury-related hospitalizations of individuals with mild and severe ADHD compared to the relevant control groups.

Figure 2.

Kaplan-Meyer curves showing the cumulative risk of injury for individuals with (A) mild and (B) severe ADHD comparing to their respective controls.

Amongst the participants hospitalized due to injuries, no significant differences were found concerning mortality, intensive care unit admission, need for surgery, length of stay, and need for rehabilitation. These results are displayed in Table 3.

Table 3.

In-Hospital Mortality and Hospital Resource Use Characteristics Among Adolescents and Young Adults Hospitalized for Injury by ADHD.

Variables	Participants with and without mild ADHD (N₁ = 3,607)^a			Participants with and without severe ADHD (N₂ = 3,750)^a
Variables	Mild ADHD (n = 828; 22.96%)	No ADHD (2,779; 77.04%)	p-Value	Severe ADHD (n = 64, 1.71%)	No ADHD (n = 3,686; 98.29%)	p-Value
Mortality	11 (1.3)	22 (0.8)	NS	0 (0)	30 (0.8)	NS
ICU admission	59 (7.1)	196 (7.1)	NS	6 (9.4)	276 (7.5)	NS
Surgery	275 (33.2)	973 (35.0)	NS	29 (45.3)	1,292 (35.1)	NS
LOS > 7 days	108 (13.0)	379 (13.6)	NS	12 (18.8)	581 (15.8)	NS
LOS > 14 days	30 (3.6)	142 (5.1)	NS	6 (9.4)	238 (6.5)	NS
Discharge to a rehabilitation facility	30 (3.6)	97 (3.5)	NS	2 (3.1)	174 (4.7)	NS

Note. ADHD = attention deficit/hyperactivity disorder; NS = non-significant (p-value ≥ .05).

It is important to note that mild ADHD and severe ADHD are exclusive diagnoses, and as a result, their effects were evaluated independently from the N₁ and N₂ populations, respectively.

Discussion

The findings of this study indicate that a diagnosis of ADHD among young adults, regardless of its severity, is associated with an increased risk of injury that requires hospital admission.

This finding is consistent with the results of previous studies that have also suggested an association between ADHD and an increased risk of injury, including the magnitude of the effect. A systematic review and meta-analysis conducted by Ruiz-Goikoetxea et al. (2018) showed an association between ADHD and increased risk of injuries in children and adolescents, with pooled odds ratios ranging between 1.39 and 1.53. Chang et al. (2014) have demonstrated a similar association in adolescents and young adults with ADHD, specifically with injury-associated hospitalization following transport accidents, with hazard ratios of 1.45 to 1.47. Another study by Shem-Tov et al. (2019), following a cohort of children and adolescents, found a hazard ratio of 1.63. This consistency across multiple studies strengthens the evidence supporting this association.

The population of this study is unique as the majority of this cohort was recruited for military service for 2 to 3 years within the follow-up period. Since a diagnosis of severe ADHD precludes the participants from combat service, severe ADHD may have a protective effect due to decreased risk exposure. To prevent that bias, we compared participants with severe ADHD to controls with similar medical profiles which have similar limitations to their service assignments.

While not statistically significant, there was a borderline tendency toward a higher likelihood of severe and critical injuries (ISS16-75) in individuals with mild ADHD. However, no significant association was observed between severe ADHD and the risk of severe and critical injuries. This difference is most likely related to fewer injury events among individuals with severe ADHD. Additionally, it may be related to the exemption from combat service granted to individuals with severe ADHD.

ADHD is known to be associated with substance abuse (Dalsgaard et al., 2014) and impulse control disorders (Barkley & Brown, 2008), which in turn may lead to an increased risk of injury. This study demonstrates the increased risk of injury associated with ADHD, even when adjusting to these comorbidities. The association of ADHD with an increased risk of injury was demonstrated both for intentional and unintentional injuries. This is particularly important as it may guide potential preventive interventions. Injury outcomes were similar between trauma casualties with and without ADHD, as well as hospital resources utilization, which assists in quantifying the burden associated with the excess injuries associated with ADHD and can aid with future cost analyses.

Given that the injury data were ascertained from a nationwide registry and considering that there are no military hospitals in Israel, it is pertinent to note that hospitalization records encompass injuries incurred both during and outside of military service. Hence, it is plausible that a portion of the injuries occurred among subjects during their military tenure and as part of their military duties. However, our dataset does not include explicit information on whether injuries occurred during military service. Given the variable nature of military service duration, coupled with reserve service following discharge, reliably estimating the proportion of injuries during military service becomes challenging. To address the potential contribution of injuries occurring during military service, we conducted an additional analysis examining the interaction between medical profiles fit for combat service and mild ADHD, revealing no significant interaction between the two.

Due to variations in elligibilty for combat duty and the delayed introduction of a diagnostic code for mild ADHD to IDF medical guidelines, this study did not directly compare the risk of injury between individuals with mild and severe ADHD. Nonetheless, it is plausible that individuals with mild ADHD may be more prone to injuries than those with severe ADHD. This potential difference could be attributed to the tendency of individuals with mild ADHD to underestimate their condition, leading to lower medication adherence and increased vulnerability to injuries, given the effectiveness of proper treatment in improving outcomes (Ruiz-Goikoetxea et al., 2018; Shaw et al., 2012). An even more important factor might be their increased risk exposure due to possible enlistment for combat duty, which introduces additional risks such as combat injuries, firearm and machinery accidents, etc. This is reflected by the association between a fit for combat service medical profile and the increased risk for trauma-related hospitalization in the multivariable model.

This study has several limitations. First, the retrospective nature of the study prevents any conclusions regarding causality. However, in this cohort, the diagnosis preceded the injury in all cases by design. Second, the nature of the INTR database rules out trauma casualties who died before arriving at the hospital, which may lead to underestimating the effect. In addition, this study did not include minor injuries that did not arrive or were discharged from the emergency department. Third, no documentation regarding medical treatment was available in the database. Instead, the diagnostic code assigned represents the severity of symptoms and functional level, with or without medical therapy. Fourth, while data regarding injury types and circumstances are available, the small numbers in the subgroups limit the ability to draw conclusions regarding differences in injury patterns associated with ADHD. Fifth, due to the late introduction of a diagnostic code for mild ADHD, follow-up time for these individuals was significantly shorter. However, the abundance of this diagnosis allowed for a clear demonstration of association. Lastly, this study was conducted entirely in Israel, and includes some specific features (e.g., mandatory military service) that may affect its generalizability.

In conclusion, this study demonstrates that diagnosis of ADHD, both mild and severe, in late adolescence is associated with an increased risk for serious injury in early adulthood. This supports the need for developing preventive strategies aimed for this population, through early detection, treatment, education and more. Larger cohorts may allow for better characterization of injury circumstances and patterns.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by THE ISRAEL SCIENCE FOUNDATION (Grant No. 2808/21).

ORCID iDs

Abebe Tiruneh

Ofer Almog

Author Biographies

Abebe Tiruneh, MD, MPH, is a senior researcher at the Israel National Center for Trauma and Emergency Medicine Research, Gertner Institute for Epidemiology and Health Policy Research. Dr. Abebe’s research interest includes exploring causes and risk factors, health outcomes, disparities and interventions related to injuries and violence, as well as their impact on the utilization of health resources.

Irina Radomislensky, BSc, Work as statistician in the Center for Trauma and Emergency Medicine Research, The Gertner Institute for Health Policy and Epidemiology, since 2008. She received her BSc (1999) from Bar Ilan university, faculty of mathematics, statistics and computer science. A list of his scientific publications can be found at: https://pubmed.ncbi.nlm.nih.gov/?term=radomislensky+i&sort=pubdate

Amir Shlaifer, MD, MHA, MBA. He received his MD (2004) from the Hebrew University and Hadassah Faculty of Medicine in Jerusalem, Israel. He served as a combat physician in various assignments and his current position is chief surgeon of the Israel Defense Forces’ Northern Command. He is a certified Orthopedic surgeon. In his previous position, he served as the head of the medical evaluation branch in the IDF Medical Corps and was responsible for determining the IDF’s medical evaluation policy for military service and the medical evaluation process for those designated for military service, carried out in the recruitment bureaus before recruitment and for serving soldiers. A list of his publications is available at: https://pubmed.ncbi.nlm.nih.gov/?term=Shlaifer%2C+Amir%5BAuthor%5D&sort=

Tomer Talmy, is a physician and medical officer of the Israel Defense Forces Trauma and Combat Medicine Branch. Dr. Talmy’s main research interest include the prehospital management and critical care of trauma patients, along With the long-term impact of traumatic injuries among military personnel.

Ofer Almog, is the head of the IDF-MC Trauma and Combat Medicine Branch. He is a board certified anesthesiologist and a lecturer at the Department of Military Medicine, Faculty of Medicine, Hebrew University of Jerusalem, Israel. His current research interest is prehospital and battlefield trauma management.

Jacob Rotschield, is a psychiatrist in the IDF and since 2021 serves as the head of the occupational health branch. He earned an MD from Tel Aviv University and completed a clinical residency in psychiatry at the Shalvata Mental Health Center, Israel. His primary previous roles in the IDF were battalion surgeon of the 101st airborne battalion, chief of medicine at the Flotilla 13 unit of the Israeli navy, Adjutant to the chief northern command surgeon and Division surgeon of the 91st division. In 2017 he earned and MHA from the Bar-Ilan University and in 2000 he completed the Jungian Analytic Psychology Program at the Kibbutzim College of Education, Technology and the Arts. He currently studies toward a certification in psychogeriatrics at the Tel Aviv University.

Eldad Katorza, MD, MSc, MBA, Director of the Gertner Institute for Epidemiology & Health Policy Research at Sheba Medical Center, and Director of Arrow Program for Medical Research Education. Prof. Katorza is a specialist in Fetal Imaging & MRI, and serves as senior physician at the OB/GYN and Diagnostic Imaging Divisions, and head of the multidisciplinary team at the Fetal Neurology Clinic at Sheba Medical Center. He received his MD (2002) from the Faculty of Medicine, Ben-Gurion University of the Negev including an MA in clinical research. He went on to complete a residency in Obstetrics and Gynecology (2008) at Sheba Medical Center and a fellowship in Fetal MRI and Imaging of the fetal central nervous system and brain at the Hôpital Armand Trousseau, Paris. Prof. Katorza holds an MBA (2018) from Coller School of Management, Tel Aviv University. He went on to complete a residency in Medical Management (2022) at Sheba Medical & the Israeli Ministry of Health. A list of his scientific publications can be found at: https://pubmed.ncbi.nlm.nih.gov/?term=katorza+e&sort=date

Avi Benov MD, MHA, MBA, Deputy to the Surgeon General. COL Benov graduated from the Ben-Gurion University Medical School in 2002 and was commissioned as a Lieutenant in the Medical Corps of the Israel Defense Forces 2003. He was appointed as a medical officer of a Paratroopers battalion and later became the Paratroopers Brigade’s chief medical officer until 2007, a position he held during the Second Lebanon War. In2007, COL Benov was appointed a medical officer in the Israeli Air Force special operation unit. He also served as a flight surgeon and a medical commander in the Israeli Air Force. Between 2014 and 2016, COL Benov served as Deputy to the Head of the Trauma & Combat Medicine Branch, including during Operation “Protective Edge” in Gaza, and as a fellow at the USA Institute of Surgical Research, San Antonio, TX. COL Benov helped with the implementation of the IDF’s Strategic Force Generation plan, focusing on the elimination of preventable death. This plan is known as “My Brother’s Keeper.” In 2019, he was appointed Head of the Trauma & Combat Medicine Branch and continued his work on preventable death. COL Benov is a board-certified general surgeon and an ATLS instructor who served as the Israeli Defense Forces Liaison to the Committee on Tactical Combat Casualty Care and as a member of the board of the Israeli Trauma Association. COL Benov is a Senior lecturer of Surgery at the Faculty of Medicine in the Galilee (Bar-Ilan University) and a winner of numerous citations, such as the Minister of Health Excellence Award, The Presidential Medal, Israel National Emergency Medical Service (Magen David Adom)–Medal of Distinguished Service, IDF-Medical Corps, Surgeon General’s Excellence Award (3 times). COL Benov is an expert in pre-hospital trauma care and military medicine and an active researcher who has published over 80 articles in leading journals. COL Benov is a graduate of the Maoz leadership program (an Israeli government program aimed at developing the next generation of national leadership, including executive management training at the Harvard Business School. He also holds two second degrees in management: Master of Health Administration (2012) from Ben-Gurion University and Master of Business Administration (2023) from Tel Aviv University (with honors). COL Benov took a leading part in several humanitarian rescue missions the IDF Medical Corps performed worldwide, including the Israeli humanitarian aid mission to the Syrian civil war victims as the IDF Surgical team leader and the IDF humanitarian mission for the earthquake casualties in Turkey (2023). Since 2012, he has served as a flight surgeon in the Airborne Search & Rescue Unit (unit 669) and has participated in numerous operations and medical evacuations. He takes particular pride in remaining operational even these days.

Guy Avital, MD, A Combat Physician in the Israel Defense Forces and a resident in the Division of Anesthesia, Critical Care and Pain Medicine, Tel-Aviv Sourasky Medical Center. He received his MD (2011) from the Hebrew University and Hadassah Faculty of Medicine in Jerusalem, Israel. He served as a combat physician in various assignments and has begun his anesthesiology residency in the Tel-Aviv Sourasky Medical Center. In 2020-2021 he served as the deputy of the Trauma & Combat Medicine Branch in the IDF Surgeon General’s headquarters, and in 2021-2022 was assigned to the United States Army Institute of Surgical Research as part of the Engineers and Scientists Exchange Program (ESEP). A list of his publications is available at:

References

Barkley

R. A.

Brown

T. E.

(2008). Unrecognized attention-deficit/hyperactivity disorder in adults presenting with other psychiatric disorders. CNS Spectrums, 13(11), 977–984. https://doi.org/10.1017/S1092852900014036

Bron

T. I.

Bijlenga

Breuk

Michielsen

Beekman

A. T. F.

Kooij

J. J. S.

(2018). Risk factors for adverse driving outcomes in Dutch adults with ADHD and controls. Accident Analysis and Prevention, 111, 338–344. https://doi.org/10.1016/j.aap.2017.12.011

Central Bureau of Statistics. (2019). Characterization and Classification of Geographical Units by the Socio-Economic Level of the Population. Author.

Chang

Lichtenstein

D’Onofrio

B. M.

Sjölander

Larsson

(2014). Serious transport accidents in adults with attention-deficit/hyperactivity disorder and the effect of medication a population-based study. JAMA Psychiatry, 71(3), 319–325. https://doi.org/10.1001/jamapsychiatry.2013.4174

Dalsgaard

Mortensen

P. B.

Frydenberg

Thomsen

P. H.

(2014). ADHD, stimulant treatment in childhood and subsequent substance abuse in adulthood - a naturalistic long-term follow-up study. Addictive Behaviors, 39(1), 325–328.

Dalsgaard

Østergaard

S. D.

Leckman

J. F.

Mortensen

P. B.

Pedersen

M. G.

(2015). Mortality in children, adolescents, and adults with attention deficit hyperactivity disorder: A nationwide cohort study. Lancet, 385(9983), 2190–2196. https://doi.org/10.1016/S0140-6736(14)61684-6

Davidovitch

Koren

Fund

Shrem

Porath

(2017). Challenges in defining the rates of ADHD diagnosis and treatment: Trends over the last decade. BMC Pediatrics, 17(1), 218. https://doi.org/10.1186/s12887-017-0971-0

Fayyad

Sampson

N. A.

Hwang

Adamowski

Aguilar-Gaxiola

Al-Hamzawi

Andrade

L. H.

Borges

de Girolamo

Florescu

Gureje

Haro

J. M.

Karam

E. G.

Lee

Navarro-Mateu

O’Neill

Pennell

B. E.

Piazza

. . . Kessler

R. C.

(2017). The descriptive epidemiology of DSM-IV adult ADHD in the World Health Organization world mental health surveys. Attention Deficit and Hyperactivity Disorders, 9(1), 47–65. https://doi.org/10.1007/s12402-016-0208-3

Guy

J. A.

Knight

L. M.

Wang

Jerrell

J. M.

(2016). Factors associated with musculoskeletal injuries in children and adolescents with attention-deficit/hyperactivity disorder. Primary Care Companion for CNS Disorders, 18(3), 18. https://doi.org/10.4088/PCC.16m01937

10.

Israeli Central Bureau of Statistics. (2019). Causes of Death in Israel 2017. CBS Publications. https://www.cbs.gov.il/he/mediarelease/DocLib/2019/380/05_19_380b.pdf (Hebrew)

11.

Israel National Center for Trauma & Emergency Medicine Research. (2016). Trauma Injuries in Israel 2010–2015, National Report (Hebrew). Author.

12.

Knesset – Israeli Parliament. (1986). Low of Security Service (Combined Version) (Hebrew). Author.

13.

Lindemann

Langner

Banaschewski

Garbe

Mikolajczyk

R. T.

(2017). The risk of hospitalizations with injury diagnoses in a matched cohort of children and adolescents with and without attention deficit/hyperactivity disorder in Germany: A database study. Frontiers in Pediatrics, 5(220), 1–9. https://doi.org/10.3389/fped.2017.00220

14.

London

A. S.

Landes

S. D.

(2021). Cohort change in the prevalence of ADHD among U.S. adults: Evidence of a gender-specific historical period effect. Journal of Attention Disorders, 25(6), 771–782. https://doi.org/10.1177/1087054719855689

15.

Mannuzza

Klein

R. G.

Moulton

J. L.

(2008). Lifetime criminality among boys with attention deficit hyperactivity disorder: A prospective follow-up study into adulthood using official arrest records. Psychiatry Research, 160(3), 237–246. https://doi.org/10.1016/j.psychres.2007.11.003

16.

Merrill

R. M.

Lyon

J. L.

Baker

R. K.

Gren

L. H.

(2009). Attention deficit hyperactivity disorder and increased risk of injury. Advances in Medical Sciences, 54(1), 20–26. https://doi.org/10.2478/v10039-009-0022-7

17.

Ornoy

Spivak

(2019). Cost effectiveness of optimal treatment of ADHD in Israel: A suggestion for national policy. Health Economics Review, 9(1), 24. https://doi.org/10.1186/s13561-019-0240-z

18.

Polanczyk

G. V.

Willcutt

E. G.

Salum

G. A.

Kieling

Rohde

L. A.

(2014). ADHD prevalence estimates across three decades: An updated systematic review and meta-regression analysis. International Journal of Epidemiology, 43(2), 434–442. https://doi.org/10.1093/ije/dyt261

19.

Ponizovsky

A. M.

Marom

Fitoussi

(2014). Trends in attention deficit hyperactivity disorder drugs consumption, Israel, 2005-2012. Pharmacoepidemiology and Drug Safety, 23, 534–538. https://doi.org/10.1002/pds.3604

20.

Rozenfeld

Radomislensky

Freedman

Givon

Novikov

Peleg

(2014). ISS groups: Are we speaking the same language? Injury Prevention, 20(5), 330–335. https://doi.org/10.1136/injuryprev-2013-041042

21.

Ruiz-Goikoetxea

Cortese

Aznarez-Sanado

Magallón

Alvarez Zallo

Luis

E. O.

de Castro-Manglano

Soutullo

Arrondo

(2018). Risk of unintentional injuries in children and adolescents with ADHD and the impact of ADHD medications: A systematic review and meta-analysis. Neuroscience and Biobehavioral Reviews, 84, 63–71. https://doi.org/10.1016/j.neubiorev.2017.11.007

22.

Shaw

Hodgkins

Caci

Young

Kahle

Woods

A. G.

Arnold

L. E.

(2012). A systematic review and analysis of long-term outcomes in attention deficit hyperactivity disorder: Effects of treatment and non-treatment. BMC Medicine, 10, 99. Published online 2012. https://doi.org/10.1186/1741-7015-10-99

23.

Shem-Tov

Chodick

Weitzman

Koren

(2019). The association between Attention-deficit hyperactivity disorder, injuries, and methylphenidate. Global Pediatric Health, 6, 1–8. https://doi.org/10.1177/2333794X19845920

24.

Shoham

Sonuga-Barke

Yaniv

Pollak

(2021). ADHD is associated with a widespread pattern of risky behavior across activity domains. Journal of Attention Disorders, 25(7), 989–1000. https://doi.org/10.1177/1087054719875786

25.

Sun

Kuja-Halkola

Faraone

S. V.

D’Onofrio

B. M.

Dalsgaard

Chang

Larsson

(2019). Association of psychiatric comorbidity with the risk of premature death among children and adults with attention-deficit/hyperactivity disorder. JAMA Psychiatry, 76(11), 1141–1149. https://doi.org/10.1001/jamapsychiatry.2019.1944

26.

Visser

S. N.

Danielson

M. L.

Bitsko

R. H.

Holbrook

J. R.

Kogan

M. D.

Ghandour

R. M.

Perou

Blumberg

S. J.

(2014). Trends in the parent-report of health care provider-diagnosed and medicated attention-deficit/hyperactivity disorder: United States, 2003-2011. Journal of the American Academy of Child and Adolescent Psychiatry, 53(1), 34–46.e2. https://doi.org/10.1016/j.jaac.2013.09.001

27.

von Elm

Altman

D. G.

Egger

Pocock

S. J.

Gøtzsche

P. C.

Vandenbroucke

J. P

. (2007). The strengthening the reporting of observational studies in Epidemiology (STROBE) statement: Guidelines for reporting observational studies. Lancet, 370(9596), 1453–1457. https://doi.org/10.1016/S0140-6736(07)61602-X