Enforcement uniquely predicts reductions in alcohol-impaired crash fatalities.

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Enforcement uniquely predicts reductions in alcohol-impaired crash fatalities.

Addiction. 2016 Mar;111(3):448-53

Authors: Yao J, Johnson MB, Tippetts S


BACKGROUND AND AIMS: Alcohol-impaired driving contributes to more than 10 000 fatalities in the United States each year. This research estimated the unique effect of enforcement intensity on reductions in alcohol-impaired fatal crashes.

DESIGN: We collected data from 30 states (including the District of Columbia) that experienced the greatest changes in alcohol-impaired fatal crashes from 1996 to 2006. Mixed-model regression was used to examine the extent to which year-over-year changes in the intensity of impaired driving enforcement predicted year-over-year reductions of drivers killed in alcohol-involved fatal crashes.

SETTING: Data from 30 states were obtained online.

PARTICIPANTS: Aggregate state-level data from a total of 279 state-year combinations were analyzed.

MEASURES: Our dependent measure was the ratio of drivers involved in fatal crashes with blood alcohol concentrations (BACs) ≥ 0.08 g/dl over drivers involved in fatal crashes with BACs = 0.00 g/dl. Per capita driving under the influence (DUI) arrests and traffic enforcement funding were the primary predictors. Covariates were estimated vehicle miles traveled (VMT); the proportional distributions of gender and racial/ethnic; geographic distribution; the proportion of drivers aged 21-34 years; median family income; and education level.

FINDINGS: Analysis revealed that DUI arrests per capita uniquely and significantly predicted reductions in the ratio of fatal crashes (β = -0.753, t(238)  = 2.1, P < 0.05) after controlling the covariates. Exploratory analysis suggests the increase in arrest rates was associated with stronger reductions in urban versus rural settings.

CONCLUSIONS: Drunk driving enforcement intensity uniquely contributes to reductions in alcohol-impaired crash fatalities after controlling for other factors.

PMID: 26451697 [PubMed - in process]