Speed kills? Quantifying the association between police traffic stops, types of stops, and motor vehicle collisions

Allison Gasnick; Anuja L Sarode; Avanti Badrinathan; Vanessa P Ho; Daniel J Tisch; Christopher W Towe

doi:10.1016/j.injury.2023.111241

Speed kills? Quantifying the association between police traffic stops, types of stops, and motor vehicle collisions

Injury. 2024 Feb;55(2):111241. doi: 10.1016/j.injury.2023.111241. Epub 2023 Nov 29.

Authors

Allison Gasnick¹, Anuja L Sarode², Avanti Badrinathan³, Vanessa P Ho⁴, Daniel J Tisch⁵, Christopher W Towe⁶

Affiliations

¹ Case Western Reserve University School of Medicine, Cleveland, OH, United States.
² Research in Surgical Outcomes and Effectiveness, University Hospitals Cleveland Medical Center (UH-RISES), Cleveland, OH, United States.
³ Department of Surgery, University Hospitals Cleveland Medical Center, 11100 Euclid Avenue, Cleveland, OH 44106-5011, United States.
⁴ Division of Trauma, Critical Care, Burns, and Acute Care Surgery, MetroHealth Medical Center, Cleveland, OH, United States; Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States.
⁵ Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States.
⁶ Department of Surgery, University Hospitals Cleveland Medical Center, 11100 Euclid Avenue, Cleveland, OH 44106-5011, United States. Electronic address: christopher.towe@uhhospitals.org.

PMID: 38041924
DOI: 10.1016/j.injury.2023.111241

Abstract

Background: Motor vehicle crashes (MVCs) are a leading cause of traumatic death and injury. Police traffic stops (PTS) are a common approach to enforcing motor vehicle laws intended to prevent MVCs. However, it is unclear which types of PTS are most effective. This study examined the relationship of PTS subtypes among municipal police patrols on non-interstate roads and MVCs and MVC-related deaths.

Methods: PTS subtype data were characterized from six North Carolina cities: Charlotte, Durham, Fayetteville, Greensboro, Raleigh, and Winston-Salem. The primary outcomes of this study were yearly non-interstate MVC and MVC-related death rates per 100 population. The data were analyzed as balanced time-series cross-sectional data. The statistical analysis accounted for time-dependent and city-dependent confounding. We used a two-way fixed effects model to analyze the relationship between PTS and MVC or MVC-related deaths. We also utilized the difference in difference (DID) analysis to analyze if the reduction of PTS following a 2012 policing administrative change in Fayetteville had an association with MVC or MVC-related deaths.

Results: We found no significant overall association between non-interstate PTS and MVCs (Coeff: -0.00006; p = 0.43) or MVC-related deaths (Coeff: -0.00011; p = 0.15). Panel regression suggested no significant relationship between MVCs and MVC-related deaths and PTS related to driving while impaired (p = 0.36), safe movement violation (p = 0.43), or seatbelt violations (p = 0.17). However, speed limit violations (Coeff: -0.00025; p = 0.032) and stop-light/sign violations (Coeff: -0.00147; p = 0.017) related to PTS significantly reduced MVC-related deaths. The DID regression showed no significant impact on MVCs (p = 0.924) or MVC-related deaths (0.706) before and after the police reform period.

Conclusions: The evidence regarding the absence of an overall association and any association with most PTS subtypes suggest that PTS are not effective for MVC death prevention. Policymakers may proceed with exploring modifications to policing efforts without detriments to public safety as defined by MVC and MVC-related deaths.

Level of evidence: Retrospective epidemiological study, level IV.

Keywords: Injury prevention; Motor vehicle crash; Motor vehicle related deaths; Police traffic stops.

MeSH terms

Accidents, Traffic* / prevention & control
Cross-Sectional Studies
Humans
Motor Vehicles
Police*
Retrospective Studies