Evidence map›Paper›PMID 37095075›Full record

ArticleAlcohol, clinical & experimental research2023

Trends in alcohol-impaired crashes in California, 2016 to 2021: A time series analysis for alcohol involvement and crash distribution among demographic subgroups.

Christina A Mehranbod, Ariana N Gobaud, Charles C Branas, Qixuan Chen, Daniel P Giovenco, David K Humphreys, Andrew G Rundle, Brady R Bushover, Christopher N Morrison

Abstract read
In one paragraph

Article in Alcohol, clinical & experimental research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Christina A MehranbodDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.ORCID https://orcid.org/0000-0003-1235-3252
Ariana N GobaudDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.
Charles C BranasDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.
Qixuan ChenDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York, USA.
Daniel P GiovencoDepartment of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, New York, USA.
David K HumphreysDepartment of Social Policy and Intervention, University of Oxford, Oxford, UK.
Andrew G RundleDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.
Brady R BushoverDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.
Christopher N MorrisonDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA.ORCID https://orcid.org/0000-0001-6522-6420

Funding

Substance Abuse Epidemiology Training Program (SAETP) at Columbia UniversityT32DA031099 · NIDA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI DEBORAH S HASIN, Silvia Saboia Martins · 2012 to 2026
$6.1M
Impacts of Subsidized Ridesharing on Drunk Driving, Alcohol Consumption, and MobilityR01AA029112 · NIAAA · YALE UNIVERSITY · PI MORRISON, CHRISTOPHER NEIL · 2021 to 2025
$3.1M
Influences Of In-Person Social Networks, Digital Social Networks And Neighborhoods On Adolescent Alcohol ConsumptionK01AA026327 · NIAAA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MORRISON, CHRISTOPHER NEIL · 2018 to 2022
$903k
NIAAA NIH HHS K01 AA026327NIAAA NIH HHS K01AA026327NIAAA NIH HHS R01 AA029112NIAAA NIH HHS R01AA029112NIDA NIH HHS T32 DA031099NIDA NIH HHS T32DA031099
6 · The paper itself

Abstract

backgroundIn 2020, the COVID-19 pandemic and control measures changed alcohol consumption in the United States (US) and globally. Before the pandemic, alcohol-impaired crashes contributed to approximately one-third of all road traffic crash injuries and fatalities nationally. We examined the impact of the COVID-19 pandemic on crashes and examined differences in alcohol-involved crashes across various subgroups.

methodsThe University of California Berkeley Transportation Injury Mapping Systems provided information on all crashes reported to the California Highway Patrol from January 1, 2016 through December 31, 2021. Using autoregressive integrated moving average (ARIMA) models applied to weekly time series data, we estimated the effect of California's first mandatory statewide shelter-in-place order (March 19, 2020) on crashes per 100,000 population. We also examined crash subgroups according to crash severity, sex, race/ethnicity, age, and alcohol involvement.

resultsIn California, the mean crash rate per week before the pandemic (January 1, 2016-March 18, 2020) was 9.5 crashes per 100,000 population, and 10.3% of those were alcohol-involved. After the initiation of the COVID-19 stay-at-home order, the percentage of crashes that were alcohol-involved rose to 12.7%. Overall, the crash rate across California decreased significantly (-4.6 crashes per 100,000; 95% CI: -5.3, -3.9), including across all examined subgroups, with the greatest decrease among the least severe crashes. However, there was a 2.3% absolute increase in the proportion of crashes that were alcohol-involved (0.02 crashes per 100,000; 95% CI: 0.02, 0.03).

conclusionsThe initiation of a COVID-19 stay-at-home ordinance in California was associated with a substantial decrease in overall crash rates. While crashes have returned to pre-pandemic levels, alcohol-involved crashes remain elevated. The initiation of the stay-at-home order significantly increased alcohol-impaired driving, which has remained elevated.

Indexed as

alcohol-impaired drivingcrashespandemic

Identifiers

PMID37095075
PMCPMC10858975

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.