Alcohol Consumption and 15 Causes of Fatal Injuries: A Systematic Review and Meta-Analysis

Hillel R. Alpert; Megan E. Slater; Young-Hee Yoon; Chiung M. Chen; Nancy Winstanley; Marissa B. Esser

doi:10.1016/j.amepre.2022.03.025

Review Article| Volume 63, ISSUE 2, P286-300, August 01, 2022

Alcohol Consumption and 15 Causes of Fatal Injuries: A Systematic Review and Meta-Analysis

Hillel R. Alpert, ScD, ScM
Hillel R. Alpert
Correspondence
Address correspondence to: Hillel R. Alpert, ScD, ScM, CSR, Incorporated, 22375 Broderick Drive, Suite 220, Sterling VA 20166.
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Affiliations
CSR, Incorporated, Sterling, Virginia
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Megan E. Slater, PhD, MPH
Megan E. Slater
Affiliations
CSR, Incorporated, Sterling, Virginia
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Young-Hee Yoon, PhD, MA
Young-Hee Yoon
Affiliations
CSR, Incorporated, Sterling, Virginia
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Chiung M. Chen, MA, BS
Chiung M. Chen
Affiliations
CSR, Incorporated, Sterling, Virginia
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Nancy Winstanley, MLS, BA
Nancy Winstanley
Affiliations
CSR, Incorporated, Sterling, Virginia
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Marissa B. Esser, PhD, MPH
Marissa B. Esser
Affiliations
Division of Population Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
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Published:May 15, 2022DOI:https://doi.org/10.1016/j.amepre.2022.03.025

Introduction

The proportion of fatal nontraffic injuries that involve high levels of alcohol use or alcohol intoxication was assessed by cause of injury to generate alcohol-attributable fractions. Updated alcohol-attributable fractions can contribute to improved estimates of the public health impact of excessive alcohol use.

Methods

Peer-reviewed and gray literature for 1995–2019 on 15 causes of fatal nontraffic injuries in the U.S., Canada, or Mexico were systematically reviewed, and state data systems were queried for available estimates of fatalities with recorded blood alcohol concentration levels and proportions of decedents with blood alcohol concentrations ≥0.10 g/dL by cause of injury. For each injury cause, alcohol-attributable fractions across studies were synthesized by meta-analysis of single proportions using generalized linear mixed models.

Results

In total, 60 published studies and 40 additional population-level data points from 6 state data systems were included. The meta-analyzed alcohol-attributable fractions by cause of injury are as follows: air-space transport (0.03), aspiration (0.24), child maltreatment (0.09), drowning (0.31), fall injuries (0.37), fire injuries (0.34), firearm injuries (0.24), homicide (0.29), hypothermia (0.29), motor vehicle nontraffic crashes (0.42), occupational and machine injuries (0.08), other road vehicle crashes (railroad trespasser injuries) (0.63), poisoning (not alcohol) (0.20), suicide (0.21), and water transport (0.27), yielding an overall median alcohol-attributable fraction of 0.27.

Discussion

Excessive alcohol use is associated with substantial proportions of violent and nonviolent injury deaths. These findings can improve the data used for estimating alcohol-attributable injury deaths and inform the planning and implementation of evidence-based strategies (e.g., increasing alcohol taxes, regulating alcohol outlet density) to prevent them.

INTRODUCTION

Excessive alcohol use is a leading cause of preventable death in the U.S.

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It is a risk factor for both unintentional and intentional injuries.

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Binge drinking (i.e., the consumption of 4 or more drinks for women or 5 or more drinks for men on an occasion or in about a 2-hour period, which generally raises one's blood alcohol concentration [BAC] level to 0.08 g/dL or higher) is associated with an increase in the likelihood of fatal injuries.

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Alcohol-attributable fractions (AAFs) measure the contribution of alcohol use to a given health outcome or cause of death and are important for estimating alcohol-related morbidity and mortality. Direct estimates of AAFs (i.e., the proportion of persons dying from a particular alcohol-attributable condition that had a BAC above a specified level) are often used to measure the contribution of alcohol to acute causes of death, such as injuries. With approximately 10,000 deaths from alcohol-impaired driving recorded each year, AAFs for fatal motor vehicle crashes are well monitored in the U.S. relative to those of other causes of alcohol-related injuries, and such data are accessible from the Fatality Analysis Reporting System.

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The purpose of this systematic review and meta-analysis is to assess the proportion of fatal nontraffic injuries that involve high levels of alcohol (BAC ≥0.10 g/dL or indications of alcohol intoxication) by cause of injury. The results from this meta-analysis can improve the data used for estimating alcohol-attributable deaths from nontraffic injuries, such as in data systems that rely on AAFs (e.g., the Centers for Disease Control and Prevention's [CDC] Alcohol-Related Disease Impact [ARDI] application). The findings from this study could also inform the planning and implementation of evidence-based population-level strategies

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METHODS

A total of 15 mutually exclusive acute causes of death from alcohol-attributable nontraffic-related injuries were included in this systematic review and meta-analysis: air-space transport, aspiration, child maltreatment, drowning, poisoning (not alcohol), fall injuries, fire injuries, firearm injuries, homicide, hypothermia, motor vehicle nontraffic crashes, other road vehicle crashes, occupational and machine injuries, suicide, and water transport. These categories align with the acute causes of death from partially alcohol-attributable nontraffic-related injuries that are used in CDC's ARDI application

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The CDC's ARDI application is a comprehensive tool for estimating state and national alcohol-attributable deaths and years of potential life lost for nearly 60 causes of alcohol-related death. Data on alcohol-related deaths from chronic conditions were not included in this study nor were injuries that are fully alcohol attributable (e.g., alcohol poisoning). Fully alcohol-attributable deaths (AAF=1.0) are those that would not occur in the absence of alcohol; therefore, no estimation is required. Because annual AAFs for fatal motor vehicle traffic crashes are available from the Fatality Analysis Reporting System,

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Search Strategy

For each of the 15 causes of fatal nontraffic injuries, published studies in peer-reviewed journals, government reports (e.g., medical examiners’ reports), and other gray literature were systematically reviewed to identify studies, reports, and data systems that independently assessed alcohol involvement. Boolean algorithms were submitted to literature search engines that index relevant published studies, including PubMed, ScienceDirect, Web of Science, Cochrane Central, Embase, SCOPUS, CINAHL, Google Scholar, and Epistomonikos. Gray literature was also searched to capture data from sources that might not otherwise be available in the peer-reviewed literature (Appendix 2, available online),

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including proceedings of professional association meetings, coroners’ and medical examiners’ reports, and U.S. federal and state government and Canadian reports.

State health surveillance systems, vital death records, and medical examiner/coroner offices have traditionally been the primary sources of data underlying fatal injury AAFs. Therefore, between January 2020 and August 2020, emails were sent to health departments or medical examiner government offices in 20 states that have centralized medical examiner systems or an epidemiologist working on alcohol. Each was provided with a table specifying the 15 causes of fatal injuries and the cause-specific ICD-10 codes. Recent 5 years of data were requested to calculate the number of fatalities with a valid BAC test result and the number of decedents with BAC ≥0.10 g/dL, by cause of injury.

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scanning reference lists and authors’ names of primary sources identified as well as citations to studies ascertained through Web of Science to ensure literature saturation. This approach can be particularly effective in systematic reviews of multidisciplinary areas such as alcohol involvement in fatal injuries because primary sources may reference other reports with relevant data or additional literature from other fields. The International Classification of Diseases, Ninth Revision and ICD-10 codes from CDC's ARDI application were used to identify literature on the 15 types of injuries.

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Inclusion criteria consisted of studies and reports on any of the 15 causes of fatal nontraffic injuries published from 1995 through 2019 or data from state systems during this period; involving human subjects; based in the U.S., Canada, or Mexico; and written in English. The search started with 1995, being the final year of reports included in the previous comprehensive meta-analysis on alcohol-related nontraffic injuries.

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Studies were primarily sought that reported direct AAF estimates or included data to directly assess AAFs (i.e., the proportion of persons that died of a particular injury with BAC ≥0.10 g/dL at the time of injury among those who had a valid BAC test). In other words, AAF is an estimate of the percentage of deaths that are attributed to alcohol. Consistent with CDC's ARDI application, 0.10 g/dL was used as the threshold for determining alcohol involvement instead of 0.08 g/dL (a common threshold level for acute intoxication). Injury fatalities can be due to many nonalcohol-related factors, and the higher BAC threshold provides a greater level of assurance for a death being attributable to alcohol.

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BAC measurements are typically, although not always, obtained during injury death investigations conducted by medical examiners, coroners, or other government officials (e.g., forensic toxicology laboratories). These measurements are often included in state and local health surveillance and vital death records systems. Studies in which the AAF was equal to zero were included if selection bias was not suspected. A minimum sample size of at least 5 decedents with BAC test results per cause of death was required for inclusion.

Upon completion of comprehensive full-text reviews, minimal studies with suitable BAC data were identified for 7 fatal injury causes (aspiration, child maltreatment, fall injuries, homicide, hypothermia, occupational and machine injuries, and other road vehicle crashes). Therefore, the inclusion criteria were broadened for these to include descriptions of alcohol intoxication that would approximate BAC ≥0.10 g/dL (i.e., alcohol intoxication, alcohol impaired, inebriated, under the influence, drunk, or alcohol was a factor). This broader approach aligns with the seminal English and Holman meta-analysis on alcohol and numerous related outcomes.

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Because our study reports AAFs by cause of injury, AAFs for the 7 causes mentioned earlier can be viewed separately from AAFs for the other causes. Appendix 1 (available online) provides further details on study inclusion by cause of death.

All citations identified in the systematic literature reviews were compiled and managed in an EndNote reference management database after initial screening for eligibility by a bibliographic research librarian (NW) on the basis of cause of injury, location, and presence of BAC information. Before data abstraction, 2 investigators closely examined the full-text reports for specificity and linkage of BAC information with fatal injuries, minimum sample size requirements, the remaining eligibility criteria, and any redundancies among reports. Each eligible source was compared with the remaining reports with respect to dates, places of data collection, and populations sampled to exclude duplicates. When the same underlying data were reported by >1 source, the source with the largest number of decedents was included.

Data abstraction forms were developed to collect the following information from each published report: report information (e.g., data source type, funding source); study eligibility (e.g., causes of death, BAC or alcohol intoxication data); study setting; population characteristics; methodology, including study design, sampling frame, selection criteria, fatal injury data sources, and BAC sources and timing; effect size, including the numbers of decedents, BAC tests, BAC test results ≥0.10 g/dL, and missing or unreported BAC tests; and risk of bias assessment.

The risk of bias assessment for individual studies was adapted from the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach.

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The GRADE approach uses specific evaluation criteria to identify the subset of studies likely to yield the most accurate approximation of the effect size of alcohol on each cause of death. It allows for optimal objectivity and clear communication of any subjective judgments. Consistent with this approach, 2 primary investigators with formal epidemiologic training and experience evaluating quality and risk of bias in research (HRA and CMC) independently performed data abstraction and evaluation. Discrepancies were adjudicated by a third epidemiologist investigator (MES), and any remaining issues were discussed and resolved among all investigators before analysis. Calibration exercises were held using clear instructions with explicit evaluation criteria, and a structured approach was employed to ensure transparency.

The potential study-level biases (selection bias, imprecision, missing data, external validity, and reporting bias) relevant to measures of direct AAF estimates (i.e., incidence and proportions) for fatal nontraffic injuries were evaluated following the PRISMA statement and GRADE recommendations.

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Evaluation of nonpeer-reviewed data considered internal consistency, reliability, and face validity of the sources. The risk of bias score was increased by 1 point for each type of bias judged to potentially influence the accuracy or precision of the AAF significantly. Points were summed for an overall rating of each study. Published studies that met inclusion criteria were selected for analysis if they had a risk of bias score not >3. In the absence of suitably defined data, emails were sent to authors of 8 potentially eligible studies requesting clarification of reported BAC data or other important missing information or to resolve observed inconsistencies.

Data abstracted included the numerator and denominator of the study-level AAF for each cause of death. The numerator was defined as the number of deaths where the decedent (or offender in homicide and child maltreatment cases) either had BAC ≥0.10 g/dL or was reported to be alcohol intoxicated. The denominator was defined as the number of deaths where the decedent (or offender) had either a valid BAC test result or a descriptive indication of alcohol involvement. For each cause of death, AAFs across studies were synthesized by meta-analysis of single proportions using generalized linear mixed models. Generalized linear mixed model was used rather than alternative methods (e.g., standard inverse variance methods such as Freeman‒Tukey double arcsine transformation) because it avoids potential problems with back transformations by considering the binomial structure of AAF data.

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RESULTS

The data in this meta-analysis were sourced from a total of 60 published studies (Figure 1) and 6 state data and surveillance systems (Colorado, Michigan, Minnesota, North Carolina, Utah, and Virginia) that provided data for 40 AAF estimates. Overall, data were included from 28 U.S. states, 5 national-level U.S. studies, and 6 Canadian studies. Characteristics of individual data sources, including study-level AAFs used for calculating the meta-analyzed AAFs, are presented in Table 1.

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).

Figure 1Flowchart of selection of studies for inclusion in the meta-analysis.
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Figure 2Meta-analysis of AAFs for 15 causes of fatal nontraffic injuries.
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^an: the total number of studies and data from states included for a given cause of fatal injury.
^bBAC ≥0.10 g/dL: the number of deaths where the involved decedent (or offender in homicide and child maltreatment cases) had BAC ≥0.10 g/dL or were reported to be alcohol intoxicated.
^cTested: the number of deaths where the involved decedent (or offender in homicide and child maltreatment cases) had either valid BAC test results or valid measures of alcohol involvement.
^dI²: a statistic that describes the percentage of variation across studies that is because of heterogeneity rather than chance.
AAF, alcohol-attributable fraction; BAC, blood alcohol concentration.
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Table 1Study Characteristics and Risk of Bias Scores for 15 Causes of Fatal Nontraffic Injuries

Studies by cause of death	Dates of injuries	Geographical location	BAC ≥0.10g/dL	BAC tests (n)	Alcohol-attributable fraction	Risk of bias score ^a State data systems were not assigned a risk of bias score.
Air-space transport
Botch and Johnson (2009) ³³ Botch SR, Johnson RD. Toxicological findings of pilots involved in aviation accidents operated under Title 14 CFR, Part 135. Washington, DC: Office of Aerospace Medicine, Federal Aviation Administration. https://apps.dtic.mil/sti/pdfs/ADA506749.pdf. Published 2009. Accessed May 5, 2022. Google Scholar ^, ^b Cases are from separate, nonoverlapping samples in Botch et al. reports.	1997–2007	U.S.	1	139	0.01	2
Botch and Johnson (2008) ³⁴ Botch SR, Johnson RD. Alcohol-related aviation accidents involving pilots with previous alcohol offenses. Washington, DC: Office of Aerospace Medicine, Federal Aviation Administration. https://libraryonline.erau.edu/online-full-text/faa-aviation-medicine-reports/AM08-22.pdf. Published 2008. Accessed May 5, 2022. Google Scholar ^, ^b Cases are from separate, nonoverlapping samples in Botch et al. reports.	2000–2007	U.S.	8	215	0.04	2
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Virginia data system	2014–2018	Virginia	0	17	0.00	NA
Utah data system	2014–2018	Utah	0	13	0.00	NA
Aspiration
Boghossian et al. (2010) ³⁶ Boghossian E Tambuscio S Sauvageau A. Nonchemical suffocation deaths in forensic setting: a 6-year retrospective study of environmental suffocation, smothering, choking, and traumatic/positional asphyxia. J Forensic Sci. 2010; 55: 646-651https://doi.org/10.1111/j.1556-4029.2010.01351.x Crossref PubMed Scopus (24) Google Scholar ^, ^c Data were based on descriptive reports of alcohol intoxication, drunkenness, or alcohol being a factor involved in the fatalities.	2000–2005	Quebec, Canada	2	11	0.18	1
Virginia data system	2014–2018	Virginia	4	50	0.08	NA
Utah data system	2014–2018	Utah	5	26	0.19	NA
North Carolina data system	2014–2019	North Carolina	15	21	0.71	NA
Child maltreatment
Colorado CFPS (2021) ³⁷ Colorado child fatality prevention system data dashboard. Colorado Department of Public Health and Environment. https://cohealthviz.dphe.state.co.us/t/PSDVIP-MHPPUBLIC/views/CFPSDashboardFinalLocal/Story1?iframeSizedToWindow=true&:embed=y&:showAppBanner=false&:display_count=no&:showVizHome=no. Accessed May 5, 2022. Google Scholar ^, ^c Data were based on descriptive reports of alcohol intoxication, drunkenness, or alcohol being a factor involved in the fatalities.	2009–2018	Colorado	41	452	0.09	2
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Drowning
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Browne et al. (2003) ⁴² Browne ML Lewis-Michl EL Stark AD. Unintentional drownings among New York State residents, 1988-1994. Public Health Rep. 2003; 118: 448-458https://doi.org/10.1093/phr/118.5.448 Crossref PubMed Google Scholar	1988–1994	New York	58	178	0.33	2
Canadian Red Cross society (2006) ⁴³ Canadian Red Cross Society Drownings and other water-related injuries in Canada: 10 years of research, Module 1 overview. Canadian Red Cross Society, Ottawa, Canada2021 https://www.redcross.ca/training-and-certification/swimming-and-water-safety-tips-and-resources/drowning-research Google Scholar	1991–2000	Canada	583	1,500	0.39	0
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Utah data system	2014–2018	Utah	11	130	0.08	NA
Virginia data system	2014–2018	Virginia	83	346	0.24	NA
Minnesota data system	2014–2018	Minnesota	49	136	0.36	NA
North Carolina data system	2014–2019	North Carolina	131	230	0.57	NA
Fall injuries
Virginia data system	2014–2018	Virginia	89	760	0.12	NA
North Carolina data system	2014–2019	North Carolina	116	159	0.73	NA
Fire injuries
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Tridata Corporation (1999) ⁴⁶ Tridata Corporation. Establishing a Relationship Between Alcohol and Casualties of Fire. Arlington, VA: Federal Emergency Management Agency, United States Fire Administration National Fire Data Center. https://www.sustainable-design.ie/fire/alcoholfire.pdf. Published October 1999. Accessed May 5, 2022. Google Scholar	1993–1996	Minnesota	67	255	0.26	2
U.S. Fire administration (2003) ⁴⁷ U.S. Department of Homeland Security/Federal Emergency Management Agency. Case study: contribution of alcohol to fire fatalities in Minnesota. Topical Fire Research Series. Vol. 3-Issue 4. Washington, DC: U.S. Department of Homeland Security/Federal Emergency Management Agency. https://nfa.usfa.fema.gov/downloads/pdf/statistics/v3i4.pdf. July 2003. Accessed May 5, 2022. Google Scholar	1996–2002	Minnesota	113	374	0.30	0
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Utah data system	2014–2018	Utah	5	40	0.12	NA
Virginia data system	2014–2018	Virginia	51	338	0.15	NA
North Carolina data system	2014–2019	North Carolina	80	100	0.80	NA
Firearm injuries
Cherry et al. (2001) ⁵⁰ Cherry D Runyan C Butts J. A population based study of unintentional firearm fatalities. Inj Prev. 2001; 7: 62-65https://doi.org/10.1136/ip.7.1.62 Crossref PubMed Scopus (16) Google Scholar	1985–1994	North Carolina	55	351	0.16	0
Collins (2010) ⁵¹ Collins KA. Adolescent Russian roulette deaths. Am J Forensic Med Pathol. 2010; 31: 4-6https://doi.org/10.1097/PAF.0b013e3181c6849f Crossref PubMed Scopus (4) Google Scholar	1987–2006	South Carolina	2	7	0.29	2
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Minnesota data system	2015–2018	Minnesota	1	17	0.06	NA
Virginia data system	2014–2018	Virginia	7	67	0.10	NA
Colorado data system	2014–2018	Colorado	10	42	0.24	NA
Utah data system	2014–2018	Utah	9	30	0.30	NA
North Carolina data system	2014–2019	North Carolina	11	19	0.58	NA
Homicide
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Utah data system	2014–2018	Utah	6	39	0.15	NA
Hypothermia
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Utah data system	2014–2018	Utah	13	55	0.24	NA
Virginia data system	2014–2018	Virginia	26	101	0.26	NA
North Carolina data system	2014–2019	North Carolina	11	21	0.52	NA
Motor vehicle nontraffic crashes
Minnesota DNR (2002–2010) ⁵⁸ Incident (accident) reports. Minnesota Department of Natural Resources. https://www.dnr.state.mn.us/enforcement/incidentreports/index.html?__cf_chl_captcha_tk__=d75424ba4d2e1c70b375583390bef6fccc0f677d-1618131130-0-AeZxhJIZ3GwnN8Li8Fzo0OnztKNCpkvJp5hwVJcvj6u5a1BhhNUO-BWaZWJMovu2ICPEqUIk_pPUXEAcuUK9ABFhkY7f3CsoOJyVmfKTQNH5iQX-. Accessed May 5, 2022. Google Scholar	2002–2010	Minnesota	44	166	0.27	1
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Minnesota DNR (2001–2015) ⁵⁸ Incident (accident) reports. Minnesota Department of Natural Resources. https://www.dnr.state.mn.us/enforcement/incidentreports/index.html?__cf_chl_captcha_tk__=d75424ba4d2e1c70b375583390bef6fccc0f677d-1618131130-0-AeZxhJIZ3GwnN8Li8Fzo0OnztKNCpkvJp5hwVJcvj6u5a1BhhNUO-BWaZWJMovu2ICPEqUIk_pPUXEAcuUK9ABFhkY7f3CsoOJyVmfKTQNH5iQX-. Accessed May 5, 2022. Google Scholar	2001–2015	Minnesota	81	165	0.49	1
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Occupational and machine injuries
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Utah data system	2014–2018	Utah	1	5	0.20	NA
North Carolina data system	2014–2019	North Carolina	3	7	0.43	NA
Other road vehicle crashes (railroad trespasser injuries)
North American Management (2013) ⁶⁸ North American Management. Rail Trespasser Fatalities: Demographic and Behavioral Profiles. Washington, DC: U.S. Department of Transportation, Federal Railroad Administration. https://railroads.dot.gov/sites/fra.dot.gov/files/fra_net/3315/RailTrespasserFatalitiesDemograph62013.pdf. Published 2013. Accessed June 3, 2021. Google Scholar ^, ^c Data were based on descriptive reports of alcohol intoxication, drunkenness, or alcohol being a factor involved in the fatalities.	2005–2010	U.S.	470	940	0.50	1
CDC (1999) ⁶⁹ Centers for Disease Control and Prevention (CDC) Injuries among railroad trespassers–Georgia, 1990-1996. MMWR Morb Mortal Wkly Rep. 1999; 48: 537-541 PubMed Google Scholar	1990–1996	Georgia	40	78	0.51	2
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North Carolina data system	2014–2019	North Carolina	33	48	0.69	NA
Poisoning (not alcohol)
Przepyszny and Jenkins (2007) ⁷¹ Przepyszny LM Jenkins AJ. The prevalence of drugs in carbon monoxide-related deaths: a retrospective study, 2000-2003. Am J Forensic Med Pathol. 2007; 28: 242-248https://doi.org/10.1097/01.paf.0000257417.26383.e4 Crossref PubMed Scopus (18) Google Scholar	2000–2003	Cuyahoga County, Ohio	19	84	0.23	1
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Utah data system	2014–2018	Utah	170	1,719	0.10	NA
Michigan data system	2017–2018	Michigan	475	4,081	0.12	NA
Virginia data system	2014–2018	Virginia	668	5,576	0.12	NA
Minnesota data system	2019	Minnesota	60	500	0.12	NA
North Carolina data system	2014–2019	North Carolina	1,126	2,388	0.47	NA
Suicide
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Utah data system	2014–2017	Utah	485	2,416	0.20	NA
Virginia data system	2014–2018	Virginia	493	2,417	0.20	NA
Minnesota data system	2015–2018	Minnesota	588	2,490	0.24	NA
Colorado data system	2014–2018	Colorado	1,038	4,221	0.25	NA
Michigan data system	2014–2018	Michigan	962	3,645	0.26	NA
North Carolina data system	2014–2019	North Carolina	1,249	1,886	0.66	NA
Water transport
New York State OPRHP (2013–2019) ⁸⁶ Boating resources. Recreational boating reports. New York State Office of Parks, Recreation & Historic Preservation. https://parks.ny.gov/recreation/boating/resources.aspx. Accessed May 5, 2022. Google Scholar	2013–2019	New York	14	83	0.17	2
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Virginia data system	2014–2018	Virginia	3	7	0.43	NA
Minnesota data system	2014–2018	Minnesota	20	45	0.44	NA

a State data systems were not assigned a risk of bias score.

b Cases are from separate, nonoverlapping samples in Botch et al. reports.

c Data were based on descriptive reports of alcohol intoxication, drunkenness, or alcohol being a factor involved in the fatalities.

d Cases are from separate, nonoverlapping samples (including snowmobiles and all-terrain vehicles) in the Wisconsin Department of Natural Resources motor vehicle nontraffic crash reports.

e States included were Alaska, Colorado, Georgia, Kentucky, Maryland, Massachusetts, New Jersey, New Mexico, North Carolina, Oklahoma, Oregon, Rhode Island, South Carolina, Utah, Virginia, and Wisconsin.BAC, blood alcohol concentration; CFPS, Child Fatality Prevention System; DNR, Department of Natural Resources; NA, not applicable; OPRHP, Office of Parks, Recreation and Historic Preservation; SCFAC, State Child Fatality Advisory Committee.

Open table in a new tab

The meta-analysis results for the 15 causes of fatal nontraffic injuries are summarized in Figure 2, including AAFs and associated 95% CIs. In alphabetical order, the AAFs were air-space transport (0.03), aspiration (0.24), child maltreatment (0.09), drowning (0.31), fall injuries (0.37), fire injuries (0.34), firearm injuries (0.24), homicide (0.29), hypothermia (0.29), motor vehicle nontraffic crashes (0.42), occupational and machine injuries (0.08), other road vehicle crashes (railroad trespasser injuries) (0.63), poisoning (not alcohol) (0.20), suicide (0.21), and water transport (0.27). The AAF for each cause of death can be interpreted as the percentage of deaths attributable to alcohol among those with known BAC levels or intoxication status. For example, 24% of 553 firearm injury deaths with known BAC levels were attributable to alcohol. Overall, cause-specific analyses yielded a median AAF of 0.27. Study heterogeneity, based on I², varied by cause of death, ranging from 0% for air-space transport and child maltreatment to 100% for fall injuries and poisoning (not alcohol) (Appendix 3, available online). In sensitivity analysis, no statistically significant differences (based on overlapping 95% CIs) were observed between AAFs derived with and without the inclusion of Canadian data (Appendix 4, available online).

DISCUSSION

This study is the most current and comprehensive systematic review and meta-analysis assessing involvement of excessive alcohol use in deaths from 15 causes of fatal nontraffic injuries. The study shows that excessive drinking was associated with more than one quarter of violent and nonviolent injury deaths. For example, the findings show that almost 1 in 4 unintentional firearm injury deaths, 1 in 3 homicides, 1 in 5 poisonings (not alcohol), and 1 in 5 suicides involved alcohol, with a BAC ≥0.10 g/dL or a descriptive indication of alcohol intoxication. The mechanisms by which excessive drinking might lead to these deaths could include the effects of alcohol and impaired brain function resulting in poor judgment; slow decision making and reaction time; reduced perception and response to hazards; loss of balance and motor skills; and through behavioral effects, such as increased risk taking, reduced inhibitions, reduced processing of communications, and increased aggression.

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AAF estimates were determined in this study using the direct method, which is based on the proportion of deaths from a given cause of injury due to alcohol. This method has advantages compared with approaches for estimating alcohol-related injury fatalities that are not based on individual causes of death. For example, applying continuous distributions that consider the prevalence of alcohol use and the RR of dying from a given injury to the estimated number of deaths from that injury generally involves aggregating alcohol-attributable injuries into broad categories (e.g., road injuries, other unintentional injuries, intentional injuries).

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Shield K
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This is because limited cause-specific data are available to inform risk functions. Others have indicated that a systematic review of data from medical examiners' and coroners’ reports on the contribution of alcohol to injury deaths, such as those used in this study, might be more accurate than estimates generated from continuous risk functions.

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Unlike other studies on alcohol-related homicides that rely on BAC among victims, a strength of this study is that it uniquely considered alcohol intoxication among homicide offenders.

⁹⁶

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Cooper SE
et al.

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Offender BACs for homicides and child maltreatment are typically not collected by state data and surveillance systems. Sources of homicide and maltreatment data in this study used either offender BAC or alternatively observer or self-reports of alcohol intoxication among offenders.

Most of the poisoning (not alcohol) deaths in this study were from drug overdose fatalities that involved a BAC ≥0.10 g/dL. However, the AAF of 0.20 may underestimate the role of alcohol in drug overdose deaths because alcohol can contribute to overdoses at low levels, particularly when combined with substances such as opioids or benzodiazepines.

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Singh AK.

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Dasgupta A.

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White AM
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¹⁰⁰

Castle IJ
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Alcohol testing rates among decedents vary by decedents’ characteristics (e.g., race/ethnicity), cause of death, and state of residence.

¹⁰⁰

Castle IJ
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State variation in underreporting of alcohol involvement on death certificates: motor vehicle traffic crash fatalities as an example.

^,

¹⁰¹

Greene N
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State-level data in this study were from 28 states, including 6 state surveillance systems. Additional states did not provide data from their surveillance systems for reasons provided such as labor intensiveness and insufficient resources during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (coronavirus disease 2019 [COVID-19]) pandemic. The inclusion of data from only some state data systems potentially introduces biases in the AAFs owing to socioeconomic, demographic, policy environment, or social norm differences among states regarding drinking.

Because AAFs in this meta-analysis were calculated as a percentage among decedents tested for alcohol, the estimates might be high if decedents who were not tested for alcohol had consistently lower BAC levels. Testing rates, procedures for conducting postmortem BAC tests, and timing of alcohol testing (relative to both the time since alcohol was consumed and time after death) likely varied across states,

¹⁰¹

Greene N
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Esser MB.

Alcohol testing and alcohol involvement among violent deaths by state, 2014-2016.

although most potential systematic biases in BAC testing (e.g., lag between death and BAC test) likely led to conservative AAF estimates.

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Chrystoja BR
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¹⁰¹

Greene N
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¹⁰²

Greene N
Esser MB
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Auman KM
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Lauerman MH.

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^,

¹⁰⁴

Quintas MJ
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Variability exists in AAFs from individual sources within causes of death. Some relatively extreme values might have contributed to the nonstatistically significant differences observed between random-effects and fixed-effect estimates for certain causes. These could also be partially explained by factors such as differences in alcohol use by sex, age, race/ethnicity, or location. However, sufficient data were not available to estimate AAFs by decedents’ characteristics, and observed variation in AAFs by location across individual sources improves generalizability.

The sensitivity analyses suggest that biases did not result from inclusion of Canadian data, although the AAFs in this meta-analysis might not reflect those that would be obtained from meta-analyses of exclusively Canadian data. The U.S. and Canada are comparable on several indicators of population-level alcohol consumption (e.g., per capita alcohol consumption, prevalence of heavy episodic drinking),

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although they may differ in other relevant aspects (e.g., implementation and enforcement of alcohol control policies). These AAFs also might not be generalizable to Mexico because only studies in English were searched.

There were some limitations because of the data available for certain causes of death. Deaths from poisonings have the potential for misclassification of intent (suicide versus unintentional) and for unobserved heterogeneity.

¹⁰⁶

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Caine ED
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et al.

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For deaths from homicide and child maltreatment, BAC data among offenders are potentially limited because the offenders are often not apprehended immediately at the time of injury. Given the sensitive nature of child maltreatment deaths, further data on alcohol involvement in these deaths may be discovered from restricted sources, such as the National Child Death Review Case Reporting System.

For fall injuries, the AAF estimate was based on the data of >900 decedents, although high study heterogeneity between the 2 data sources and the wide 95% CIs suggest some uncertainty around the estimate. The extent to which excessive alcohol use contributes to deaths from falls might vary by age group. More data pertaining to the age distribution of decedents would be needed to differentially estimate alcohol-related falls among younger and older people. Nevertheless, falls contribute to a substantial number of deaths each year, especially among older adults,

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Fatal injuries from other road vehicle crashes involve pedestrians or occupants who collide with or fall from pedal cycles, other nonmotor vehicles, or railway trains; however, the available studies of alcohol involvement in these deaths pertained solely to scenarios involving railroad trespassers (i.e., persons on railroad property whose presence was prohibited or unlawful). One of these studies documented that alcohol intoxication was the most frequently reported factor associated with these deaths,

⁷⁰

Pelletier A.

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as when people walk across railroad tracks while being intoxicated.

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The AAF for these circumstances might not be applicable to different situations of other road vehicle crash deaths.

Available data regarding air-space transport were limited to pilot fatalities. Data reported in one of the studies on aviation-related crashes suggests that the number of aviation passenger deaths per crash did not differ between crashes involving and not involving alcohol.

¹⁰⁹

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Characteristics of alcohol-related fatal general aviation crashes.

The AAF for this cause of death may therefore be appropriate for estimating the total number of alcohol-attributable deaths among persons who die from air-space transport injuries.

Despite these limitations, the findings in this meta-analysis have public health implications. Effective population-level approaches for preventing excessive drinking include those recommended by the Community Preventive Services Task Force, such as strategies to decrease the availability of and access to alcohol or to increase alcohol prices.

¹¹⁰

Middleton JC
Hahn RA
Kuzara JL
et al.

Effectiveness of policies maintaining or restricting days of alcohol sales on excessive alcohol consumption and related harms.

^,

¹¹¹

Campbell CA
Hahn RA
Elder R
et al.

The effectiveness of limiting alcohol outlet density as a means of reducing excessive alcohol consumption and alcohol-related harms.

^,

¹¹²

Elder RW
Lawrence B
Ferguson A
et al.

The effectiveness of tax policy interventions for reducing excessive alcohol consumption and related harms.

In addition to reducing the number and concentration of alcohol outlets, having dram shop liability laws to hold retailers accountable for harms incurred by service to intoxicated or underage patrons could also reduce alcohol-attributable injury deaths.

¹¹¹

Campbell CA
Hahn RA
Elder R
et al.

The effectiveness of limiting alcohol outlet density as a means of reducing excessive alcohol consumption and alcohol-related harms.

^,

¹¹³

Rammohan V
Hahn RA
Elder R
et al.

Effects of dram shop liability and enhanced overservice law enforcement initiatives on excessive alcohol consumption and related harms: two community guide systematic reviews.

These population-level alcohol policies have been found to be associated with reductions in several causes of death, including homicides,

¹¹⁴

Naimi TS
Xuan Z
Coleman SM
et al.

Alcohol policies and alcohol-involved homicide victimization in the United States.

suicides,

¹¹⁵

Coleman SM
Lira MC
Blanchette J
Heeren TC
Naimi TS.

Alcohol policies, firearm policies, and suicide in the United States: a lagged cross-sectional study.

and pedestrian injuries.

¹¹⁶

Nesoff ED
Milam AJ
Branas CC
Martins SS
Knowlton AR
Furr-Holden DM.

Alcohol outlets, neighborhood retail environments, and pedestrian injury risk.

Screening and brief interventions to reduce excessive alcohol use might also reduce alcohol-related injuries if delivered face to face in clinical settings or using electronic devices in a variety of settings (e.g., healthcare facilities, universities, workplaces).

¹¹⁷

O'Connor EA
Perdue LA
Senger CA
et al.

Screening and behavioral counseling interventions to reduce unhealthy alcohol use in adolescents and adults: updated evidence report and systematic review for the U.S. Preventive Services Task Force.

^,

¹¹⁸

Tansil KA
Esser MB
Sandhu P
et al.

Alcohol electronic screening and brief intervention: a Community Guide systematic review.

CONCLUSIONS

The results of this meta-analysis show that a median of 27% of fatalities from nontraffic injuries are attributable to excessive alcohol use, which is a preventable risk behavior. The updated AAFs in this meta-analysis are fundamental for improving the estimates of alcohol-attributable deaths (as in CDC's ARDI application) and for calculating the economic burden of excessive drinking. Such data are essential for establishing public health priorities. Future research would benefit from more routine and widespread data collection on alcohol involvement in nontraffic fatal injuries, particularly those where previous investigation has been lacking. Our findings underscore the importance of implementing and enforcing evidence-based strategies for preventing excessive drinking and designing and encouraging safer community environments.

ACKNOWLEDGMENTS

The authors thank the Colorado Department of Public Health and Environment, Michigan Department of Health and Human Services, Minnesota Department of Health, North Carolina Office of the Chief Medical Examiner, Utah Department of Health, and Virginia Office of the Chief Medical Examiner for state-level fatality and blood alcohol concentration data.

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention (CDC).

This study was supported by CDC of HHS, as part of a financial assistance award totaling $219,325.27 with 100% funded by CDC/HHS.

No financial disclosures were reported by the authors of this paper.

CRediT AUTHOR STATEMENT

Marissa B. Esser: Conceptualization, Writing - review and editing. Megan E. Slater: Methodology, Investigation, Writing - review and editing. Young-Hee Yoon: Methodology, Investigation. Chiung M. Chen: Formal analysis, Methodology, Investigation, Writing - review and editing. Hillel R. Alpert: Investigation, Methodology, Writing - original draft, Writing - review and editing. Nancy Winstanley: Investigation.

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Published online: May 15, 2022

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Alcohol Consumption and 15 Causes of Fatal Injuries: A Systematic Review and Meta-Analysis

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