Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2026 Apr 11.
Published in final edited form as: Subst Use Misuse. 2025 Apr 11;60(8):1117–1125. doi: 10.1080/10826084.2025.2487974

Association of Substance Use with Types of Assault-Related Injury Among Black Men in Baltimore, Maryland

L A Marineau 1, N A Perrin 1, R M Johnson 2, M Uzzi 2, K A Alexander 1, N A Irvin 3, P Thurman 4,5, J C Campbell 1
PMCID: PMC12166359  NIHMSID: NIHMS2070961  PMID: 40219643

Abstract

Background.

Black men in Baltimore, Maryland experience high rates of assault-related injuries, and the association between substance use and assault-related injury is unclear. The purpose of this study is to examine substance use in association with types of assault-related injury (blunt force, stabbing, and firearm).

Methods.

Black men aged 18-34 admitted to a large trauma center in Baltimore, Maryland with an assault-related injury and toxicology screen between 2013-2017 (N=1922) were included. We conducted multinomial logistic regression analyses to investigate associations between recent substance use, comorbid diagnoses, and types of assault-related injury.

Results.

Cannabis was more frequently detected (42.5%), followed by alcohol (24.4%), opioids (22.3%), and cocaine (3.6%). Over one quarter of men screened positive for multiple substances (25.8%). Men who screened positive for alcohol use were 134% more likely to have been stabbed vs. shot and 54% more likely to have been beaten (i.e., blunt force assault) vs. shot. Men who screened positive for cannabis had a 32% lower risk of experiencing a stabbing compared to firearm assault, and 50% lower risk of experiencing a blunt force compared to firearm assault.

Conclusion.

Among Black men who received care for an assault-related injury, those who were shot were more likely to have screened positive for cannabis and less likely to have screened positive for alcohol. Socio-contextual factors and acute intoxication effects may explain why differing substance types were associated with different types of assault injury. Future research should examine environmental and social contexts of substance use types among assault-injured men.

Keywords: substance use, assault-related injury, firearm assault, stabbing assault, blunt force assault

Introduction

Black men in cities across the U.S., including Baltimore, Maryland, experience the highest rates of assault-related injuries compared to other racial and gender groups, likely because of structural factors and social inequities (Baltimore Police Department, 2023; CDC, 2021). Firearms are used in the majority of homicides and nonfatal assaults among Black men. In 2020, 94% of homicides in Baltimore city were caused by firearms and there were more than 700 non-fatal shootings (Baltimore Police Department, 2023).

Stabbing and blunt force assault-related injuries also cause significant harm, although they are less lethal than firearm assault-related injuries (Cook, 2018; Nygaard et al., 2018). Studies examining recurrent assault-related injuries among samples that include majority Black and majority male hospitalized participants from different regions of the U.S. found 17-27% and 15-60% experienced stabbing and blunt force assault-related injuries, respectively (Laytin et al., 2018; Nygaard et al., 2018; Richardson et al., 2016). There is also evidence suggesting people who experience stabbing and blunt force assault-related injuries are at higher risk for being violently reinjured compared to people who experienced a firearm assault (Nygaard et al., 2018; Pino et al., 2022). However, people who experience firearm assaults are more likely to be re-assaulted by a firearm and their injuries become more severe with each subsequent firearm assault (Nygaard et al., 2018; Pino et al., 2022). Thus, there is a need to better understand individual-level factors related to types of assault-related injury (e.g., blunt force, stabbing, firearm) among Black men.

Substance use and violence victimization

The association between substance use and violence victimization is well established in the literature (Buss et al., 1995; Carter et al., 2020; Cunningham et al., 2009; Duke et al., 2018; Hohl et al., 2017; Lau et al., 2023; Stoddard et al., 2015). A moderate body of evidence has demonstrated a high prevalence of substance use detected by toxicology screen among assault-injured people who present to a hospital (Lau et al., 2023; Laytin et al., 2018). One systematic review found substances (alcohol or other drugs) were detected by toxicology measures in at least 40% of patients presenting to a hospital with assault-related injuries (Lau et al., 2023). Many of these studies have samples that are majority Black and majority men; however, few have disaggregated data by gender and race or restricted their samples to Black men. This limits our understanding of how substance use is related to assault-related injuries among Black men, a population that experiences the highest burden of community violence (CDC, 2021).

Among the few studies that examined risk for assault-related injury among samples with majority Black men, investigators used varied measures for substance use, and they often combined all substance types into one category like “drug use” or “substance use”, making it difficult to discern if certain drug types are more strongly associated with assault-related injury than others. There is also mixed evidence demonstrating an association between substance use and assault-related injuries among Black men. History of drug and alcohol use has been found to be associated with firearm assault-related injuries (Carter et al., 2015; Hohl et al., 2017; Kongkaewpaisan et al., 2020), and detection of alcohol or other drugs by toxicology screen was associated with a 53% increased risk for repeat assault in one study (Nygaard et al., 2018). However, at least two studies that measured substance use near the time of injury by toxicology screen or survey did not find an association with firearm assault or recurrent violent injury (Hohl et al., 2017; Richardson et al., 2016), and one study found a protective effect between alcohol use disorder diagnosis and firearm assault among a sample of Black men (Lovelady et al., 2022). Two studies that defined substance use as a diagnosis (ICD-9-CM) from hospital-based data did not report an association with firearm and recurrent firearm assault-related injuries (Mills et al., 2018; Pear et al., 2020).

Among research examining the relationship between specific substances and violence victimization, the association between alcohol use and assault-related injury has the strongest supporting evidence. In hospital settings, alcohol screening is more common compared to other drugs (London & Battistella, 2007) and the prevalence of alcohol detected by toxicology is higher than other substances among assault-injured patients (Lau et al., 2023). Few studies examining the substance use-violence relationship measured other substances using toxicology screen among assault-injured people who present to a hospital or emergency department. Instead, more studies have used self-reported drug use measures via survey or interview to examine specific drug types. Among these studies, cannabis was the most common drug identified among assault-injured people ranging from 32.1-96.7% (varies based on sample characteristics), and it was associated with 2.1-7.41 greater odds of assault-related injury. Cocaine was associated with 2.7-3.1 greater odds of assault-related injury (Coupet Jr et al., 2022).

Mental health symptomatology and violence victimization

There is mixed evidence about associations between mental health symptoms or mental illness and assault-related injury. One study found an association (RR 1.39, 95% CI 1.13, 1.71) between self-reported PTSD symptoms and firearm violence (Carter et al., 2015); and Kaufman et al. (2016) found any mental health visits to be associated with recurrent assault-related injury (Kaufman et al., 2016). Additionally, Cunningham and colleagues (2009) found self-reported poor mental health to be predictive of past year non-partner assault among a sample of emergency department patients after adjusting for demographic factors and substance use (Cunningham et al., 2009). At least two studies did not find an association between several mental-health related diagnoses from hospital-based data (psychoses, depression/anxiety, impulse-control/conduct disorder, affective disorders, psychotic disorders, any mental health disorder) using ICD-9-CM codes and firearm assault-related injuries (Mills et al., 2018; Pear et al., 2020).

The current study

Many questions remain, limiting a clearer understanding of drug use and drug use disorders among Black men who have experienced assault-related injuries. First, there is little specification of different drugs or drug use disorders, and many studies include a single category for drugs. Given the multiple differences across drug types in their psychopharmacological effects, harms, and legal status, clarification is needed. Second, few studies have examined associations between substance use and types of assault-related injury (blunt force, stabbing, firearm). It is unclear whether specific substance types differentially increase the risk for different types of assault-related injuries. Considering types of assault may help practitioners better understand the context of substance use. Finally, there have been many differences in sampling and methods, for instance self-report versus ICD-9-CM codes.

The purpose of this study is to examine substance use types in association with types of assault-related injury, including those caused by blunt force, stabbing, and firearms. The rationale for our focus on Black men in Baltimore relates to their high rates of assault-related injuries. This study was guided by an adaptation of the Integrated Biopsychosocial Conceptualization of the Alcohol-Aggression Relationship (Chermack & Giancola, 1997). This adaptation considers how developmental influences (e.g., childhood experiences) and proximal influences (e.g., alcohol/other drug use, psychological, and contextual influences) relate to experiences of violence (Chermack & Giancola, 1997). This study focuses on the associations of proximal influences (alcohol or other drug use and comorbid mental health diagnoses) with violent injury hospitalizations.

Methods

Study sample

The study sample comes from the R Adams Cowley Shock Trauma Center at the University of Maryland Medical Center that treats more than 5,000 patients annually, comprising almost one-quarter of all trauma patients in Maryland (MIEMSS, 2024). We included data from Black men aged 18 to 34 years who were admitted with an assault-related injury (blunt force, stabbing, firearm) and had a documented toxicology screen between January 1, 2013 and December 31, 2017 (N=1922). The Johns Hopkins Medicine Institutional Review Board (protocol # IRB00277316) approved this study.

Measures

All variables were obtained from the trauma registry data bank from the time of presentation to the trauma center for an initial assault-related injury. The dataset included age, insurance status (private payer, public payer, unknown), diagnosis codes for assault-related injury, urine and blood toxicology reports, diagnosis codes for mental health and substance use disorder diagnoses, injury severity, and length of hospital stay. If a patient had multiple assaults during the period of our data collection, we only included data from the initial assault.

Types of Assault.

We examined three types of assault-related injuries, including: [1] blunt force trauma (beaten with a blunt object or bodily force), [2] stabbing (penetrated, cut, or pierced with a knife or sharp object), and [3] firearm injuries. The main type of assault was designated for each patient in the trauma registry, therefore no patient had more than one type of assault documented. The three types of assault were based on the International Statistical Classification of Disease (ICD-9-CM & ICD-10-CM) codes for external causes of injury or e-codes. Data from 2015 forward were based on ICD-10-CM codes (Blunt force: Y00, Y04; Stabbing: X99; Firearm: X93, X94, X95); whereas data from 2013 to 2015 were based on ICD-9-CM codes (Blunt force: E960.0, E968.2; Stabbing: E966; Firearm: E965.0-E965.4) (Hedegaard et al., 2020; World Health Organization, 1978; World Health Organization, 2004).

Evidence of substance use at presentation to hospital.

Recent substance use was measured using urine and blood toxicology reports from the time of presentation to the trauma center for an assault-related injury. Blood alcohol concentration and urine toxicology screens are routinely collected on all trauma patients at admission as part of their initial trauma work-up. Blood alcohol concentrations (BAC) were recorded at 10 mg/dL and higher. We examined two alcohol use variables: 1) BAC was measured as a continuous variable, 2) alcohol use indicated whether alcohol was present or not on the BAC. Drugs assessed include: opioids other than methadone (including heroin, fentanyl, and prescription opioids), methadone, amphetamines (includes methamphetamines, phenmetrazine, mephentermine, and dextroamphetamine), barbiturates, benzodiazepines, cannabis, cocaine, and phencyclidine (PCP). The presence of all other substances determined from urine samples using enzyme immunoassay techniques; they were designated as present or not based on whether the substance was detected on the toxicology screen. We classified patients who had two or more substances detected (including alcohol and other drugs) as engaged in polysubstance use.

Mental health and substance use diagnoses.

Few mental health and substance use disorder diagnoses were available from the trauma registry data bank. We obtained ICD-9-CM diagnosis codes for alcohol use dependence or disorder (ICD-9-CM: 303.9), non-intravenous drug use disorder (ICD-9-CM: 304.9), intravenous drug use disorder (ICD-9-CM: 304.9), unspecified drug dependence or disorder (ICD-9-CM: 304.9), depression (ICD-9-CM: 311), and bipolar affective disorder (ICD-9-CM: 296.7). From these ICD-9-CM codes we created three binary variables: 1) alcohol use disorder diagnosis, 2) drug use disorder diagnosis (combined non-intravenous, intravenous, and unspecified drug use dependence or disorders), and 3) mental health diagnosis (combined depression and bipolar affective disorder). ICD-9-CM codes for attention deficit disorder/ attention deficit hyperactive disorder, history of psychiatric disorder, and schizophrenia not included in this analysis due to small cell counts. ICD-9-CM codes for post-traumatic stress disorder or post-traumatic stress symptoms were not available in the data.

Injury severity.

Injury severity score (ISS) and hospital length of stay (LOS) were collected. ISS is a measure used to assess the overall severity of traumatic injuries and can be used to predict outcomes in trauma patients. It is an anatomical scoring system that provides a standardized overall score of injury severity for patients who sustain multiple injuries. The score is calculated by rating the most severe injury from six body systems (head or neck, face, chest, abdomen or pelvic contents, extremities or pelvic girdle, external) and ranges from 0 to 75 (Baker et al., 1974). An ISS of 16 or greater is generally regarded as a major trauma (Boyd et al., 1987). LOS was measured by the number of days between hospital admission and discharge. Longer stays are associated with more severe injuries.

Statistical Analyses

Missing data in all study variables was minimal. Bivariate analyses of demographics, recent substance use, comorbid diagnoses, and injury severity by assault type were performed using chi-square and analysis of variance (ANOVA). ISS and LOS were examined descriptively by type of assault but were not included in the regression models described below. The rationale is that neither ISS nor LOS are not predictors of assault; rather they are outcomes of assault that vary by assault type.

We used multinomial logistic regression analysis to estimate associations between recent substance use, comorbid diagnoses, and type of assault (N=1922). First, we used bivariate multinomial logistic regression to examine associations. Variables that were statistically significant at p<0.05 in the bivariate models were added to the multivariable multinomial logistic regression model. Relative risk ratios were estimated for all regression models. All tests were two-tailed, and Stata version 18.0 was used for all analyses (StataCorp, 2023).

Results

The distributions of characteristics for the sample are reported in Table 1. Cell counts for amphetamines, barbiturates, benzodiazepines, PCP, and methadone were too small to include in all analyses, therefore we only examined alcohol, cannabis, opioids, cocaine, and polysubstance use (any combination of all drugs screened for and alcohol). Fifty-two percent of men experienced a firearm assault, 28% a stabbing assault, and 20% a blunt force assault. The mean age was 25.3 years (S.D.=4.6). Men who experienced blunt force and stabbing assaults were about one year older than men who experienced a firearm assault (25.6 & 25.8 years compared to 24.8 years respectively, p<0.001). Men who experienced a firearm assault were more likely to have public payer insurance (e.g., Medicare, Medicaid, other government program) (40.1% firearm vs. 32.2% stabbing & 30.4% blunt force, p=0.002), higher injury severity scores (12.0 vs 7.5 & 6.3, p<0.001), and longer length of hospital stay (5.2 days vs. 2.5 & 1.4 days, p<0.001) than men who experienced a stabbing or blunt force assault. Firearm assaults resulted in more fatalities compared to stabbing or blunt force assaults (9.1% vs. 1.7% & 0.3%, p<0.001).

Table 1.

Characteristics at initial assault by mechanism of injury among Black men in Baltimore, MD

Characteristics at initial assault related injury Total
(N=1922)		 Mechanism of Assault-Related Injury p-value (Chi-
square (X2),
ANOVA)
Firearm
(n=991, 52%)		 Stabbing
(n=543, 28%)		 Blunt force
(n=388, 20%)
Age in years, mean (SD) 25.3 (4.6) 24.8 (4.5) 25.8 (4.5) 25.6 (4.6) <0.001 (F=9.3)
Insurance status, % (n) 0.002 (X2=17.1)
  Public payer (Medicare, Medicaid, other government programs) 35.9% (690) 40.1% (397) 32.2% (175) 30.4% (118) -
  Private payer 5.9% (114) 6.1% (60) 5.3% (29) 6.4% (25) -
  Unknown 58.2% (1118) 53.9% (534) 62.4% (339) 63.1% (245) -
Injury Severity Score (range 0-75), mean (SD) 9.6 (10.9) 12.0 (13.1) 7.5 (8.4) 6.3 (4.6) <0.001 (F=53.6)
Length of Stay, mean days (SD) 3.7 (7.9) 5.2 (10.2) 2.5 (4.3) 1.4 (2.5) <0.001 (F=41.2)
Fatal assault (patient deceased at initial presentation), % (n) 5.2% (100) 9.1% (90) 1.7% (9) 0.3% (1) <0.001 (X2=63.3)
Toxicology Screen (at time of admission)
  Alcohol, % (n) 24.4% (469) 16.2% (161) 36.6% (199) 28.1% (109) <0.001 (X2=82.7)
    Blood alcohol concentration, mg/dL, mean (SD) (range) 137.0 (94.0) (10-463) 101.6 (70.3) (10-328) 149.8 (92.8) (11-434) 166.1 (110.2) (11-463) <0.001 (F=20.0)
  Cannabis, % (n) 42.5% (816) 46.8% (464) 38.1% (207) 37.4% (145) <0.001 (X2=16.0)
  Opioids, % (n) 22.3% (429) 22.3% (221) 17.7% (96) 28.9% (112) <0.001 (X2=16.3)
  Cocaine, % (n) 3.6% (70) 3.2% (32) 4.0% (22) 4.1% (16) 0.607 (X2=1.0)
  Polysubstance (≥2 substances: alcohol or drugs), % (n) 25.8% (496) 23.2% (230) 26.7% (145) 31.2% (121) 0.008 (X2=9.6)
Mental Health or Substance Use Disorder Diagnosis, % (n)
  Mental health diagnosis (Depression, Bipolar affective disorder) 4.7% (90) 1.8% (18) 6.4% (35) 9.5% (37) <0.001 (X2=42.5)
  Drug use disorder diagnosis 13.7% (264) 14.2% (141) 13.3% (72) 13.1% (51) 0.810 (X2=0.4)
  Alcohol use disorder diagnosis 2.2% (42) 0.8% (8) 3.3% (18) 4.1% (16) <0.001 (X2=18.9)
Open in a new tab

Cannabis was the most common substance detected among the full sample (42.5%), followed by alcohol (24.4%), opioids (22.3%), and cocaine (3.6%). Over one quarter of the sample had polysubstance use (25.8%). Among men who had polysubstance use, the most common combination of substance types were cannabis and opioids (n=215, 43%), cannabis and alcohol (n=124, 25%), cannabis, opioids, and alcohol (n=28, 6%), and opioids and alcohol (n=26, 5%). Men who experienced stabbing and blunt force assaults were more likely to have alcohol detected on toxicology screen (36.6% & 28.1% vs 16.2%, p<0.001), more likely to have two or more substances detected (26.7% & 31.2% vs. 23.2%, p=0.008), and less likely to have cannabis detected (38.1% & 37.4% vs 46.8%, p<0.001) than men who experienced a firearm assault. Men who experienced a stabbing or blunt force assault were also more likely to have a mental health diagnosis (6.4% & 9.5% vs 1.8%, p<0.001) and alcohol use disorder diagnosis (3.3% & 4.1% vs 0.8%, p<0.001) than men who experienced a firearm assault.

The results from the bivariate regression models are reported in Table 2. The final multivariable multinomial logistic regression model is reported in Table 3. In the final regression model (model 3), men who had alcohol detected had a 134% greater risk of experiencing a stabbing assault compared to a firearm assault, and a 54% greater risk of experiencing a blunt force assault compared to a firearm assault (RRR 2.34, 95% CI 1.75, 3.14 & RRR 1.54, 95% CI 1.10, 2.15 respectively). Men who had cannabis detected had a 32% lower risk of experiencing a stabbing assault compared to firearm assault, and a 50% lower risk of experiencing a blunt force assault compared to firearm assault (RRR 0.68, 95% CI 0.51, 0.90 & RRR 0.50, 95% CI 0.36, 0.70 respectively). Men who had two or more substances detected (alcohol or other drugs) had a 75% greater risk of experiencing a blunt force assault compared to a firearm assault (RRR 1.75, 95% CI 1.11, 2.76). Men who had a recorded mental health diagnosis had a 256% greater risk for experiencing a stabbing assault compared to a firearm assault, and a 415% greater risk of experiencing a blunt force assault compared to a firearm assault (RRR 3.56, 95% CI 1.98, 6.42 & RRR 5.15, 95% CI 2.87, 9.24 respectively). Men who had a recorded alcohol use disorder diagnosis had a 149% greater risk of experiencing a stabbing assault compared to a firearm assault, and a 240% greater risk of experiencing a blunt force assault compared to a firearm assault (RRR 2.49, 95% CI 1.05, 5.94 & RRR 3.40, 95% CI 1.39, 8.31 respectively).

Table 2.

Bivariate multinomial logistic regression between individual characteristics and mechanism of assault-related injury among Black men in Baltimore, Maryland

*Stabbing assault
(n=543)		 *Blunt force assault
(n=388)
Individual Characteristics RRR (95% CI) p-value RRR (95% CI) p-value
Age 1.05 (1.02, 1.07) <0.001 1.04 (1.00, 1.06) 0.007
Insurance
  Public Pay REF REF
  Private Pay 1.09 (0.68, 1.77) 0.705 1.40 (0.84, 2.33) 0.194
  Unknown 1.44 (1.15, 1.80) 0.001 1.54 (1.19, 1.99) 0.001
Toxicology Screen (at time of admission)
  Alcohol 2.98 (2.34, 3.80) <0.001 2.01 (1.52, 2.66) <0.001
  Cannabis 0.70 (0.56, 0.87) 0.001 0.68 (0.53, 0.86) 0.002
  Opioid 0.75 (0.57, 0.98) 0.033 1.41 (1.08, 1.84) 0.011
  Cocaine 1.26 (0.73, 2.20) 0.404 1.29 (0.70, 2.38) 0.416
  Polysubstance (≥ 2 substances: alcohol or drugs) 1.20 (0.95, 1.53) 0.128 1.50 (1.15, 1.94) 0.002
Mental Health or Substance Use Disorder Diagnosis
  Mental health diagnosis 3.72 (2.09, 6.64) <0.001 5.70 (3.20, 10.13) <0.001
  Alcohol use disorder diagnosis 4.21 (1.82, 9.75) 0.001 5.28 (2.24, 12.45) <0.001
  Drug use disorder diagnosis 0.92 (0.68, 1.25) 0.600 0.91 (0.65, 1.29) 0.601
Open in a new tab
*

Reference category is firearm assault (n=991)

Table 3.

Multivariable multinomial logistic regression between individual characteristics and mechanism of assault-related injury among Black men in Baltimore, Maryland

*Stabbing assault (n=543) *Blunt force assault (n=388)
Model 3
Individual Characteristics RRR (95% CI) p-value RRR (95% CI) p-value
Age 1.02 (0.99, 1.04) 0.104 1.02 (0.99, 1.04) 0.250
Toxicology Screen (at time of admission)
  Alcohol 2.34 (1.75, 3.14) <0.001 1.54 (1.10, 2.15) 0.011
  Cannabis 0.68 (0.51, 0.90) 0.007 0.50 (0.36, 0.70) <0.001
  Opioid 0.75 (0.52, 1.07) 0.110 1.22 (0.84, 1.77) 0.282
  Polysubstance (≥ 2 substances) 1.38 (0.91, 2.07) 0.125 1.75 (1.11, 2.76) 0.016
Mental Health or Substance Use Disorder Diagnosis
  Mental health diagnosis 3.56 (1.98, 6.42) <0.001 5.15 (2.87, 9.24) <0.001
  Alcohol use disorder diagnosis 2.49 (1.05, 5.94) 0.039 3.40 (1.39, 8.31) 0.007
Open in a new tab
*

Reference category is firearm assault (n=991)

Discussion

The purpose of this study is to examine substance use in association with types of assault, including those caused by blunt force, stabbing, and firearm. To our knowledge, this is the only study that has examined the association of specific substance types with types of assault-related injuries among a large sample of Black men. This is important because understanding the relationship between specific substance types and types of assault-related injury can better inform targeted substance use and violence interventions by alerting practitioners to the most salient substance types that should be addressed.

Consistent with existing research (Braga et al., 2021), we found firearm assault injuries to be more severe and result in longer hospital stays than stabbing or blunt force assault-related injuries. Firearms are more lethal weapons than knives or blunt objects. Similar to the Cook and colleagues (2018) study where crime victims who sustained firearm assault injuries were more than seven times likely to die compared to crime victims who sustained stabbing assault-related injuries, the men in our study who experienced firearm assault injuries were six times more likely to die than those who experienced stabbing assault-related injuries (Cook, 2018). We also found differences in the substances used prior to experiencing an assault-related injury to be associated with differing types of assault-related injury among Black men in this sample. Experiencing a stabbing assault compared to firearm assault was associated with alcohol use; experiencing a blunt force assault compared to firearm assault was associated with alcohol and polysubstance use; and experiencing a firearm assault compared to stabbing and blunt force assaults was associated with cannabis use. In summary, the men who experienced firearm assault in our study were significantly less likely to be using substances except for cannabis than those who experienced a stabbing or blunt force assault.

We found experiencing a firearm assault compared to stabbing and blunt force assaults to be associated with cannabis use. A recent systematic review examining drug use among assault-injured people presenting to an emergency department found cannabis use resulted in 2.71-7.41 greater odds of experiencing any assault-related injury (type of assault not differentiated) and was the most common drug detected (Coupet Jr et al., 2022). Similar to our findings, Carter and colleagues (2017) found cannabis use doubled the risk for experiencing a firearm conflict compared to non-firearm conflict. This study differs from ours because their outcome included both firearm aggression and victimization compared to non-firearm aggression and victimization (Carter et al., 2017), and we focused only on victimization. One likely explanation for our results is cannabis use is a response to chronic exposures to community violence and is commonly used as a coping mechanism to manage emotional distress (Reboussin et al., 2015). Cannabis use does not cause firearm assault-related injuries but can be a result of coping with living in toxic neighborhood environments. It is also a commonly used recreational substance in all kinds of living situations used by 22% of all Americans in 2022 (SAMHSA, 2023). Our findings of 42.5% of the overall sample and 46.8% of those experiencing firearm assault using cannabis is considerably higher than the national estimates of cannabis use.

Firearm violence occurs in communities that experience the most disadvantage, reflecting structural and social inequities (Kravitz-Wirtz et al., 2022; Semenza et al., 2023), and high rates of community firearm violence lead to worsened overall community health (Semenza et al., 2023). People who have experienced previous violence victimization or trauma may use cannabis for coping or self-medication (Maniglio, 2015; Rich & Grey, 2005), and cannabis may be more likely to be used in contexts associated with higher risks, especially among people who live in areas with chronic exposures to community violence. Other potential mechanisms explaining the relationship between cannabis use and experiencing an assault-related injury are varied and unclear. There is evidence showing cannabis use is associated with non-partner conflict, aggression, and increased hostility and impulse control, (Ansell et al., 2015; Carter et al., 2020; Maniglio, 2015; Schoeler et al., 2016) and there may be a dose-response where chronic, more frequent use is associated with use of violence, especially for persistent heavy users (Dellazizzo et al., 2020).

In 2014, possession of small amounts of cannabis (< 10 grams) was decriminalized in Maryland (Zirkin & Kittleman, 2014). Following this (2015-2017), there was an overall decrease in cannabis-related arrests for Maryland residents, but cannabis-related arrests in Baltimore were primarily and disproportionately among Black Baltimore residents (96%) (McLeod et al., 2018). These findings are consistent with data from other states that have legalized cannabis, indicating racist and discriminatory targeting of Black people persists after enacting policies about legalization or decriminalization of cannabis possession (Edwards et al., 2020). This indicates over-policing and hyper-surveillance in Black Baltimore communities (McLeod et al., 2018) and provides important context for this study because the study period was from 2013 to 2017. Despite these disparities in cannabis-related arrests, recent multi-state data has shown that cannabis use has not increased significantly from its approximate 14.8% use following recreational cannabis legalization among Black people, but it has increased among non-Hispanic White people aged 21 years and older (Martins et al., 2021). Drug law enforcement has been shown to increase violence related to illicit drug markets in urban Black communities (Werb et al., 2011). Over-policing in Black communities also contributes to inequities in criminal legal system involvement and sentencing, leading to harmful social and economic effects, and other traumas (Johnson & Bennett, 2017; Lanni, 2022).

We found alcohol use was associated with stabbing and blunt force assault compared to firearm assault-related injuries. Prior research has found a strong relationship between alcohol use and experiencing an assault-related injury, including firearm assault, but few studies have also distinguished between stabbing and blunt force assault-related injuries. Also, in contrast to our study, most studies included a non-assault comparison group (Branas et al., 2009; Duke et al., 2018; Hohl et al., 2017; Lau et al., 2023; Stoddard et al., 2015). One study examined types of penetrating (firearm and stabbing) assault-related injury among a hospital-based sample that was majority Black and majority male (Pino et al., 2022). Consistent with our alcohol use findings, they found people who experienced stabbing assault-related injuries were more likely to have an existing diagnosis of alcohol use disorder compared to people who experienced a firearm assault-related injury (Pino et al., 2022).

We found polysubstance use was associated with an increased risk for blunt force assault-related injuries compared to firearm assault-related injuries. Stoddard and colleagues (2020) found polysubstance use among adolescents and young adults to be associated with experiences of high, chronic peer violence, but not serious assault-related injuries requiring hospitalization (Stoddard et al., 2020).

In our bivariate multinomial logistic regressions, we found opioid use increased the risk of experiencing a blunt force assault compared to firearm assault and decreased the risk of experiencing a stabbing assault compared to firearm assault, but these associations lost significance in the multivariable models after adjusting for demographics and mental health and alcohol use disorders. Few studies have examined the relationship between opioid use and assault-related injury, but Cunningham and colleagues (2009) found self-reported prescription drug misuse (includes opioids and sedatives) increased the odds of experiencing past-year non-partner violence victimization among a sample of adults presenting to an urban emergency department in Flint, MI (Cunningham et al., 2009).

We did not find significant associations between cocaine use and types of assault-related injury. This conflicts with existing research examining non-partner victimization. Cocaine had strong associations with non-partner victimization in at least two studies; however, neither study measured whether the victimization resulted in serious injury requiring hospitalization, and these studies compared victimization to non-victimization (Cunningham et al., 2009; Stoddard et al., 2015).

We found men with a mental health diagnosis had an increased risk of experiencing a stabbing and blunt force assault compared to firearm assault. Few known studies have examined mental health diagnoses by types of assault. Similar to our results, Pino and colleagues (2022) found stab wound victims to be more likely to have a preexisting mental health diagnosis compared to gunshot wound victims among people presenting to Boston Medical Center with penetrating (stabbing and firearm) assault-related injuries (Pino et al., 2022). We relied on ICD-9-CM codes for mental health diagnosis and were only able to include depression and bipolar affective disorder due to limitations in the dataset. We were not able to examine post-traumatic stress disorder. There is evidence that post-traumatic stress disorder and post-traumatic stress symptoms are important risk factors for firearm assault-related injury. Carter and colleagues (2015) found self-reported PTSD symptoms to be associated with firearm violence (Carter et al., 2015). There is strong evidence that exposure to interpersonal firearm violence is associated with worsened mental health, including post-traumatic stress disorder (Abba-Aji et al., 2024). Rich and Gray (2005) describe how post-traumatic stress symptoms can lead to cannabis use for coping after experiencing an assault injury (Rich & Grey, 2005).

Limitations

Limitations of this study should be noted. Our sample came from the state-designated PARC located in Baltimore, Maryland, and results cannot be generalized to other populations. We used cross-sectional data and the temporal relationship between substance use and type of assault-related injury is unclear. Additionally, we are only studying associations between substance use and type of assault-related injury and we cannot determine causation. There are inherent limitations to using data from a trauma registry, including missing and incomplete data. However, because we restricted our sample to men who had documented toxicology screens at presentation to the hospital, we had complete data for our substance use predictors. There is a possibility that patients received prescription opioids (e.g., fentanyl) prior to collecting blood and urine specimens for the toxicology screens. Patients are often treated for pain upon arrival to the trauma resuscitation unit while they are being assessed. However, we do not believe this will differ based on type of assault. Additionally, we were unable to account for prescription pain medications patients may have been taking prior to presentation the STC due to the dataset not including medications prescribed prior to admission, or medications administered during hospitalization.

There are also limitations with using blood and urine toxicology screens. Testing positive for substances only means the substance was detected at the time of the test but does not mean the person was impaired with the substance at the time of their assault. Some substances remain detectable long after their effects end (Mukherji et al., 2023; Sharma et al., 2012). Toxicology screens cannot provide information about when the substance was used. Alcohol and other drugs have varying half-lives and are metabolized differently depending on multiple factors like age, frequency of use, dosage, hydration status, size, liver function, etc. (Mukherji et al., 2023). For instance, cannabis has a particularly long half-life and can be detected weeks after acute use, especially among people who use it chronically (Sharma et al., 2012). Additionally, urine toxicology screens can result in false positive and false negative results (Mukherji et al., 2023). Toxicology screens, however, can give an indication of current drug use, which provides better understanding of the relationships between substance types and types of assault-related injury.

This study has multiple strengths. It has a large sample size and includes an objective measure for substance use (toxicology screens). Our findings add to the literature examining the relationship between substance use types and types of assault-related injury among Black men, a population that is disproportionately affected by violence.

Conclusion

Given the alarming statistics of injury and death for Black men from violent assault, violence prevention interventions are urgently needed. These violence prevention interventions must also address substance use. Detection of a substance by toxicology screen can drive initiation of further diagnostic work-up for substance use disorders and substance use education and further counseling or treatment if needed. There are racial disparities in access to treatment for substance use disorders. Among Black men who needed drug or alcohol use treatment between 2015-2019, only 19.8 % and 14.8% received it, respectively (Center for Behavioral Health Statistics and Quality, 2021). U.S. counties with higher proportions of Black residents are less likely to have outpatient substance use disorder treatment facilities that accept any insurance (Cummings et al., 2014). Additionally, the COVID-19 pandemic worsened access to substance use treatment in communities of color (Kariisa et al., 2022a; Kariisa et al., 2022b).

Type of assault may help practitioners better understand the context of substance use. Future research should examine neighborhood factors like violent crime, policing patterns, illicit drug market activity, and alcohol outlet density to examine their relationships with substance use types and types of assault related injury. Understanding the neighborhood context of substance use types among assault-injured men will better inform policy, and violence intervention and substance use treatment programs. The social circumstances under which different substance types are used and their relationships with different assault types should also be examined to better contextualize the substance use experiences of people with violent injuries. Future research should also examine relationships between substance types, substance use disorders, substance use severity, and recurrent assault-related injury to better understand if certain substance types and severity of use increase the risk for recurrent assault or homicide. This will better inform targeted substance use screening and treatment among violence intervention programs.

Acknowledgments

This work was supported by the National Institute on Drug Abuse [F31DA053029] and partially supported by the Intramural Research Program of the National Institutes of Health, National Institute on Minority Health and Health Disparities.

Footnotes

The authors report there are no competing interests to declare.

References

  1. Abba-Aji M, Koya SF, Abdalla SM, Ettman CK, Cohen GH, & Galea S (2024). The mental health consequences of interpersonal gun violence: A systematic review. SSM - Mental Health, 5, 100302. 10.1016/j.ssmmh.2024.100302 [DOI] [Google Scholar]
  2. Albrecht JS, Afshar M, Stein DM, & Smith GS (2018). Association of Alcohol With Mortality After Traumatic Brain Injury. American Journal of Epidemiology, 187(2), 233–241. 10.1093/aje/kwx254 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Ansell EB, Laws HB, Roche MJ, & Sinha R (2015). Effects of marijuana use on impulsivity and hostility in daily life. Drug and Alcohol Dependence, 148, 136–142. 10.1016/j.drugalcdep.2014.12.029 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Baker SP, OʼNeill B, Haddon W, & Long WB (1974). THE INJURY SEVERITY SCORE: A METHOD FOR DESCRIBING PATIENTS WITH MULTIPLE INJURIES AND EVALUATING EMERGENCY CARE. The Journal of Trauma: Injury, Infection, and Critical Care, 14(3), 187–196. 10.1097/00005373-197403000-00001 [DOI] [PubMed] [Google Scholar]
  5. Baltimore Police Department. (2023, Open Baltimore DataStats. https://www.baltimorepolice.org/crime-stats/open-data. Retrieved July 8, 2023, from https://www.baltimorepolice.org/crime-stats/open-data
  6. Boyd CR, Tolson MA, & Copes WS (1987). Evaluating trauma care: the TRISS method. Trauma Score and the Injury Severity Score. The Journal of Trauma, 27(4), 370–378. https://www.ncbi.nlm.nih.gov/pubmed/3106646 [PubMed] [Google Scholar]
  7. Braga AA, Griffiths E, Sheppard K, & Douglas S (2021). Firearm Instrumentality: Do Guns Make Violent Situations More Lethal? Annual Review of Criminology, 4(1), 147–164. 10.1146/annurev-criminol-061020-021528 [DOI] [Google Scholar]
  8. Branas CC, Elliott MR, Richmond TS, Culhane DP, & Wiebe DJ (2009). Alcohol Consumption, Alcohol Outlets, and the Risk of Being Assaulted With a Gun. Alcoholism, Clinical and Experimental Research, 33(5), 906–915. 10.1111/j.1530-0277.2009.00912.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Buss TF, Abdu R, & Walker JR (1995). Alcohol, drugs, and urban violence in a small city trauma center. Journal of Substance Abuse Treatment, 12(2), 75–83. 10.1016/0740-5472(94)00086-7 [DOI] [PubMed] [Google Scholar]
  10. Carter PM, Cranford JA, Buu A, Walton MA, Zimmerman MA, Goldstick J, Ngo Q, & Cunningham RM (2020). Daily patterns of substance use and violence among a high-risk urban emerging adult sample: Results from the Flint Youth Injury Study. Addictive Behaviors, 101, 106127. 10.1016/j.addbeh.2019.106127 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Carter PM, Walton MA, Goldstick J, Epstein-Ngo Q, Zimmerman MA, Mercado MC, Williams AG, & Cunningham RM (2017). Violent firearm-related conflicts among high-risk youth: An event-level and daily calendar analysis. Preventive Medicine, , 112–119. 10.1016/j.ypmed.2017.07.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Carter PM, Walton MA, Roehler DR, Goldstick J, Zimmerman MA, Blow FC, & Cunningham RM (2015). Firearm Violence Among High-Risk Emergency Department Youth After an Assault Injury. Pediatrics (Evanston), 135(5), 805–815. 10.1542/peds.2014-3572 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. CDC. (2021, WISQARS (Web-based Injury Statistics Query and Reporting System). Retrieved Mar 23, 2021, from https://www.cdc.gov/injury/wisqars/index.html
  14. Center for Behavioral Health Statistics and Quality. (2021). Racial/ethnic differences in substance use, substance use disorders, and substance use treatment utilization among people aged 12 or older (2015-2019) (Publication No. PEP21-07-01-001). (). Rockville, MD: Substance Abuse and Mental Health Services Administration. https://www.samhsa.gov/data/ [Google Scholar]
  15. Chermack ST, & Giancola PR (1997). The relation between alcohol and aggression: an integrated biopsychosocial conceptualization. Clinical psychology review, 17(6), 621–649. 10.1016/s0272-7358(97)00038-x [DOI] [PubMed] [Google Scholar]
  16. Cook PJ (2018). Gun Markets. Annual Review of Criminology, 1(1), 359–377. 10.1146/annurev-criminol-032317-092149 [DOI] [Google Scholar]
  17. Coupet E Jr, Dodington J, Brackett A, & Vaca F (2022). United States Emergency Department Screening for Drug Use Among Assault-Injured Individuals: A Systematic Review. The Western Journal of Emergency Medicine, 23(4), 443–450. 10.5811/westjem.2022.5.55475 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Cummings JR, Wen H, Ko M, & Druss BG (2014). Race/Ethnicity and Geographic Access to Medicaid Substance Use Disorder Treatment Facilities in the United States. JAMA Psychiatry (Chicago, Ill.), 71(2), 190–196. 10.1001/jamapsychiatry.2013.3575 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Cunningham RM, Murray R, Walton MA, Chermack ST, Wojnar M, Wozniak P, Booth BM, & Blow FC (2009). Prevalence of Past Year Assault among Inner-City ED Patients 10.1016/j.annemergmed.2009.01.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Dellazizzo L, Potvin S, Athanassiou M, & Dumais A (2020). Violence and Cannabis Use: A Focused Review of a Forgotten Aspect in the Era of Liberalizing Cannabis. Frontiers in Psychiatry, 11, 567887. 10.3389/fpsyt.2020.567887 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Duke AA, Smith KMZ, Oberleitner LMS, Westphal A, & McKee SA (2018). Alcohol, Drugs, and Violence: A Meta-Meta-Analysis. Psychology of Violence, 8(2), 238–249. 10.1037/vio0000106 [DOI] [Google Scholar]
  22. Edwards E, Greytak E, Madubuonwu B, Sanchez T, Beiers S, Resing C, Fernandez P, & Galai S (2020). A Tale of Two Countries: Racially Targeted Arrests in the Era of Marijuana Reform. American Civil Liberties Union. (). https://www.aclu.org/sites/default/files/field_document/tale_of_two_countries_racially_targeted_arrests_in_the_era_of_marijuana_reform_revised_7.1.20_0.pdf [Google Scholar]
  23. Hedegaard H, Johnson RL, Garnett MF, & Thomas KE (2020). The 2020 International Classification of Diseases, 10th Revision, Clinical Modification Injury Diagnosis Framework for Categorizing Injuries by Body Region and Nature of Injury . National Health Statistics Reports, (150), 1–27. https://www.ncbi.nlm.nih.gov/pubmed/33395385 [PubMed] [Google Scholar]
  24. Hohl BC, Wiley S, Wiebe DJ, Culyba AJ, Drake R, & Branas CC (2017). Association of Drug and Alcohol Use With Adolescent Firearm Homicide at Individual, Family, and Neighborhood Levels. JAMA Internal Medicine, 177(3), 317–324. 10.1001/jamainternmed.2016.8180 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Johnson LT, & Bennett JZ (2017). Drug markets, violence, and the need to incorporate the role of race. Sociology Compass, 11(1), e12441. 10.1111/soc4.12441 [DOI] [Google Scholar]
  26. Kariisa M, Davis NL, Kumar S, Seth P, Mattson CL, Chowdhury F, & Jones CM (2022a). Vital Signs: Drug Overdose Deaths, by Selected Sociodemographic and Social Determinants of Health Characteristics — 25 States and the District of Columbia, 2019-2020. MMWR. Morbidity and Mortality Weekly Report, 71(29), 940–947. 10.15585/mmwr.mm7129e2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Kariisa M, Seth P, & Jones CM (2022b). Increases in Disparities in US Drug Overdose Deaths by Race and Ethnicity: Opportunities for Clinicians and Health Systems. JAMA : The Journal of the American Medical Association, 328(5), 421–422. 10.1001/jama.2022.12240 [DOI] [PubMed] [Google Scholar]
  28. Kaufman E, MD, Rising Kristin, MD, MS, Wiebe DJ, PhD, Ebler DJ, MD, Crandall Marie L., MD, MPH, & Delgado M. Kit, MD, MS. (2016). Recurrent violent injury: magnitude, risk factors, and opportunities for intervention from a statewide analysis. American Journal of Emergency Medicine, 34(9), 1823–1830. 10.1016/j.ajem.2016.06.051 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Kongkaewpaisan N, El Hechi M, El Moheb M, Orlas CP, Ortega G, Mendoza MA, Parks J, Saillant NN, Kaafarani HMA, & Mendoza AE (2020). No place like home: A national study on firearm-related injuries in the American household. The American Journal of Surgery, 220(6), 1599–1604. 10.1016/j.amjsurg.2020.04.030 [DOI] [PubMed] [Google Scholar]
  30. Kravitz-Wirtz N, Bruns A, Aubel AJ, Zhang X, & Buggs SA (2022). Inequities in Community Exposure to Deadly Gun Violence by Race/Ethnicity, Poverty, and Neighborhood Disadvantage among Youth in Large US Cities. Journal of Urban Health, 99(4), 610–625. 10.1007/s11524-022-00656-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Lanni A. (2022). Community-Based and Restorative-Justice Interventions to Reduce Over-Policing. American Journal of Law and Equality, 2, 69–84. 10.1162/ajle_a_00040 [DOI] [Google Scholar]
  32. Lau G, Ang JY, Kim N, Gabbe BJ, Mitra B, Dietze PM, Reeder S, Scott D, & Beck B (2023). Prevalence of Alcohol and Other Drug Use in Patients Presenting to Hospital for Violence-Related Injuries: A Systematic Review. SAGE Publications. 10.1177/15248380221150951 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Laytin AD, Shumway M, Boccellari A, Juillard CJ, & Dicker RA (2018). ANOTHER “LETHAL TRIAD”—RISK FACTORS FOR VIOLENT INJURY AND LONG-TERM MORTALITY AMONG ADULT VICTIMS OF VIOLENT INJURY. The Journal of Emergency Medicine, 54(5), 711–718. 10.1016/j.jemermed.2017.12.060 [DOI] [PubMed] [Google Scholar]
  34. London JA, & Battistella FD (2007). Testing for Substance Use in Trauma Patients: Are We Doing Enough? Archives of Surgery (Chicago. 1960), 142(7), 633–638. 10.1001/archsurg.142.7.633 [DOI] [PubMed] [Google Scholar]
  35. Lovelady NN, Zaller ND, Stewart MK, Cheney AM, Porter A III, & Haynes TF (2022). Characterizing Firearm Assault Injury Among Young Black Men Using Arkansas Hospital Discharge Data. Journal of Interpersonal Violence, 37(13-14), NP12609–NP12633. 10.1177/0886260521997947 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Maniglio R. (2015). Association between peer victimization in adolescence and cannabis use: A systematic review. Aggression and Violent Behavior, 25, 252–258. 10.1016/j.avb.2015.09.002 [DOI] [Google Scholar]
  37. Martins SS, Segura LE, Levy NS, Mauro PM, Mauro CM, Philbin MM, & Hasin DS (2021). Racial and Ethnic Differences in Cannabis Use Following Legalization in US States With Medical Cannabis Laws. JAMA Network Open, 4(9), e2127002. 10.1001/jamanetworkopen.2021.27002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. McLeod E, Friedman A, & Soderberg B (2018, Dec 28,). Structural Racism and Cannabis: Black Baltimoreans still disproportionately arrested for weed after decriminalization. Baltimore Fishbowl https://baltimorefishbowl.com/stories/structural-racism-and-cannabis-black-baltimoreans-still-disproportionately-arrested-for-weed-after-decriminalization/ [Google Scholar]
  39. Maryland Institute for Emergency Medical Services Systems (MIEMSS). (2024). 2023-2023 Annual report. Retrieved December 10, 2024, from https://miemss.org/home/Portals/0/Docs/AnnualReports/Annual-Report-2024.pdf
  40. Mills BM, Nurius PS, Matsueda RL, Rivara FP, & Rowhani-Rahbar A (2018). Prior Arrest, Substance Use, Mental Disorder, and Intent-Specific Firearm Injury. American Journal of Preventive Medicine, 55(3), 298–307. 10.1016/j.amepre.2018.04.041 [DOI] [PubMed] [Google Scholar]
  41. Mukherji P, Azhar Y & Sharma S (2023, Toxicology Screening . https://www.ncbi.nlm.nih.gov/books/NBK499901/. Retrieved September 15, 2023, from https://www.ncbi.nlm.nih.gov/books/NBK499901/ [Google Scholar]
  42. Nygaard R, Nygaard R, Marek A, Marek A, Daly S, Daly S, Van Camp J, & Van Camp J (2018). Violent trauma recidivism: Does all violence escalate? European Journal of Trauma and Emergency Surgery, 44(6), 851–858. 10.1007/s00068-017-0787-5 [DOI] [PubMed] [Google Scholar]
  43. Pear VA, McCort CD, Kravitz-Wirtz N, Shev AB, Rowhani-Rahbar A, & Wintemute GJ (2020). Risk factors for assaultive reinjury and death following a nonfatal firearm assault injury: A population-based retrospective cohort study. Preventive Medicine, 139, 106198. 10.1016/j.ypmed.2020.106198 [DOI] [PubMed] [Google Scholar]
  44. Pino EC, Fontin F, James TL, & Dugan E (2022). Mechanism of penetrating injury mediates the risk of long-term adverse outcomes for survivors of violent trauma. The Journal of Trauma and Acute Care Surgery, 92(3), 511–519. 10.1097/TA.0000000000003364 [DOI] [PubMed] [Google Scholar]
  45. Reboussin BA, Green KM, Milam AJ, Furr-Holden DM, Johnson RM, & Ialongo NS (2015). The role of neighborhood in urban black adolescent marijuana use. Drug and Alcohol Dependence, 154, 69–75. 10.1016/j.drugalcdep.2015.06.029 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Rich JA, & Grey CM (2005). Pathways to Recurrent Trauma Among Young Black Men: Traumatic Stress, Substance Use, and the “Code of the Street”. American Journal of Public Health, 95(5), 816. 10.2105/AJPH.2004.044560 [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Richardson JB, St Vil C, Sharpe T, Wagner M, & Cooper C (2016). Risk factors for recurrent violent injury among black men. Journal of Surgical Research, 204(1), 261–266. 10.1016/j.jss.2016.04.027 [DOI] [PubMed] [Google Scholar]
  48. SAMHSA. (2023). Results from the 2022 National Survey on Drug Use and Health (HHS Publication No. PEP23-07-01-006, NSDUH Series H-58). ().Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. https://www.samhsa.gov/data/report/2022-nsduh-annual-national-report [Google Scholar]
  49. Schoeler T, Theobald D, Pingault J -., Farrington DP, Jennings WG, Piquero AR, Coid JW, & Bhattacharyya S (2016). Continuity of cannabis use and violent offending over the life course. Psychological Medicine, 46(8), 1663–1677. 10.1017/S0033291715003001 [DOI] [PubMed] [Google Scholar]
  50. Semenza DC, Stansfield R, Silver IA, & Savage B (2023). Reciprocal Neighborhood Dynamics in Gun Violence Exposure, Community Health, and Concentrated Disadvantage in One Hundred US Cities. Journal of Urban Health, 10.1007/s11524-023-00796-x [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Sharma P, Murthy P, & Bharath MMS (2012). Chemistry, metabolism, and toxicology of cannabis: clinical implications. Iranian Journal of Psychiatry, 7(4), 149–156. https://www.ncbi.nlm.nih.gov/pubmed/23408483 [PMC free article] [PubMed] [Google Scholar]
  52. StataCorp, L. (2023). STATA 18.0 [computer software]
  53. Stoddard SA, Meier-Austic E, Epstein-Ngo Q, Walton M, Carter PM, Heinze JE, Zimmerman MA, & Cunningham R (2020). Substance use and mental health predictors of patterns of non-partner youth violence among high-risk urban youth. Drug and Alcohol Dependence, 213, 108117. 10.1016/j.drugalcdep.2020.108117 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Stoddard SA, Epstein-Ngo Q, Walton MA, Zimmerman MA, Chermack ST, Blow FC, Booth BM, & Cunningham RM (2015). Substance Use and Violence Among Youth: A Daily Calendar Analysis. Substance use & Misuse, 50(3), 328–339. 10.3109/10826084.2014.980953 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Werb D, Rowell G, Guyatt G, Kerr T, Montaner J, & Wood E (2011). Effect of drug law enforcement on drug market violence: A systematic review. The International Journal of Drug Policy, 22(2), 87–94. 10.1016/j.drugpo.2011.02.002 [DOI] [PubMed] [Google Scholar]
  56. World Health Organization. (1978). International classification of diseases : [9th] ninth revision, basic tabulation list with alphabetic index. World Health Organization. [Google Scholar]
  57. World Health Organization. (2004). ICD-10 : international statistical classification of diseases and related health problems (10th revision, 2nd ed ed.). World Health Organization. [Google Scholar]
  58. Criminal Law - Possession of Marijuana - Civil Offense , (2014).

RESOURCES