Alcohol‐involved motor vehicle crashes and the size and duration of random breath testing checkpoints

Abstract

Objective: Sobriety checkpoints have strong empirical and theoretical support as an intervention to reduce alcohol-involved motor vehicle crashes. The purpose of this study was to examine whether checkpoint size (the number of police officers) and checkpoint duration (the amount of time in operation) affect associations between individual checkpoints and subsequent alcohol-related crash incidence.Method: Queensland Police Service provided latitude-longitude coordinates and date and time data for all breath tests that occurred in Brisbane, Australia, from January 2012 to June 2018. We applied hierarchical cluster analysis to the latitude-longitude coordinates for breath tests, identifying checkpoints as clusters of ≥25 breath tests conducted by ≥3 breath testing devices over a duration of 3 to 8 hours. Generalized linear autoregressive moving average (GLARMA) models related counts of alcoholinvolved motor vehicle crashes to the number of checkpoints conducted per week, as well as 1 week prior and 2 weeks prior.Results: A total of 3420 alcohol-related crashes occurred and 2069 checkpoints were conducted in Brisbane over the 6.5-year (339-week) study period. On average, checkpoints included a mean of 266.0 breath tests (SD = 216.3), 16.4 devices (SD = 13.7), and were 286.3 minutes in duration (SD = 104.2). Each 10 additional checkpoints were associated with a 12% decrease in crash incidence at a lag of 1 week (IRR = 0.88; 95%CI: 0.80, 0.97). We detected no differential associations according to checkpoint size or duration.Conclusions: Sobriety checkpoints are associated with fewer alcohol-related motor vehicle crashes for around 1 week. Checkpoint size and duration do not appear to affect this relationship.

The geography of sobriety checkpoints and alcohol‐impaired driving

“…Previous research has detected that these associations decay temporally over approximately 1 week [22,23], and that smaller checkpoints staffed by fewer law enforcement officers have similar effects compared to larger checkpoints staffed by more officers [34]. Here we add that they also decay spatially within local areas that approximate the geographic extent within which individuals' travel during routine activities.…”

“…In Queensland, there are 528 SA2 areas, which have a mean land area of 3276.8 km 2 (SD = 18 559.0 km 2 ) and a mean population of 8883.5 (SD = 55 018.3); and 84 SA3 areas, which have a mean land area of 20 597.3 km 2 (SD = 81 496.9 km 2 ) and a mean population of 57 201.6 (SD = 29 521.6). Following our previous findings [22,23], we partitioned these polygons into weeks, from 5:00 AM Tuesday to 4:59 AM on the following Tuesday, because this time typically has very low activity for sobriety checkpoints and alcohol-impaired driving [25]. Data were available for 338 weeks beginning at 5:00 AM Tuesday 3 January 2012 and ending at 4:59 AM Tuesday 26 June 2018.…”

“…Data are released for the Australian census within nested geographies at the statistical area level 1 through level 4 (SA1-SA4), the state level and the national level. Based on our prior research [9,22,23,27], we assessed that the theoretically plausible areas level over which individual checkpoints could be associated with alcohol-impaired driving were the SA2 level (typically one or more suburbs with resident population of 3000-25 000) and SA3 level (typically regional areas with resident population of 30 000-130 000). In Queensland, there are 528 SA2 areas, which have a mean land area of 3276.8 km 2 (SD = 18 559.0 km 2 ) and a mean population of 8883.5 (SD = 55 018.3); and 84 SA3 areas, which have a mean land area of 20 597.3 km 2 (SD = 81 496.9 km 2 ) and a mean population of 57 201.6 (SD = 29 521.6).…”

“…Guiding theory [21] and our prior observations of cities [22,23] suggest that sobriety checkpoints may affect alcohol-impaired driving for approximately 1 week after the checkpoint date. Thus, in addition to measuring associations for spatially adjacent units, we also measured associations for temporally lagged units.…”

“…Just as the effects of individual checkpoints decay over time, they are also likely to decay over geographic space. Prior studies have detected associations between individual checkpoints and impaired driving outcomes within areas as small as 3.2 km around checkpoint sites [26] and as large as the full extent of cities such as Los Angeles and Brisbane [22,23]; but no studies have sought to identify the precise spatial scale over which these associations occur, and the optimal spatial location for checkpoints is not clear. Given these gaps in knowledge, the aim of this study was to identify the geographic extent over which individual sobriety checkpoints affect alcohol-impaired driving.…”