Evidence map›Paper›PMID 21673858›Full record

ArticleBulletin of the World Health Organization2011

Effect on road traffic injuries of criminalizing road traffic offences: a time-series study.

Ana M Novoa, Katherine Pérez, Elena Santamariña-Rubio, Carme Borrell

Abstract read
In one paragraph

Article in Bulletin of the World Health Organization, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Ana M NovoaAgència de Salut Pública de Barcelona, Pl Lesseps 1, 08023 Barcelona, Spain .
Katherine Pérez
Elena Santamariña-Rubio
Carme Borrell

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo determine the effect of criminalizing some traffic behaviours, after the reform of the Spanish penal code in 2007, on the number of drivers involved in injury collisions and of people injured in traffic collisions in Spain.

methodsThis study followed an interrupted times-series design in which the number of drivers involved in injury collisions and of people injured in traffic collisions in Spain before and after the criminalization of offences were compared. The data on road traffic injuries in 2000-2009 were obtained from the road traffic collision database of the General Traffic Directorate. The dependent variables were stratified by sex, age, injury severity, type of road user, road type and time of collision. Quasi-Poisson regression models were fitted with adjustments for time trend, seasonality, previous interventions and national fuel consumption.

findingsThe overall number of male drivers involved in injury collisions dropped (relative risk, RR: 0.93; 95% confidence interval, CI: 0.89-0.97) after the reform of the penal code, but among women no change was observed (RR: 0.99; 95% CI: 0.95-1.03). In addition, 13 891 men (P < 0.01) were prevented from being injured. Larger reductions were observed among young male drivers and among male motorcycle or moped riders than among the drivers of other vehicles.

conclusionThe findings suggest that criminalizing certain traffic behaviours can improve road safety by reducing both the number of drivers involved in injury collisions and the number of people injured in such collisions.

Indexed as

Accidents, TrafficAdolescentAdultAgedAutomobilesConfidence IntervalsCrimeDatabases, FactualFemaleHumansMaleMiddle AgedPoisson DistributionPublic HealthRiskSafety

Identifiers

PMID21673858
PMCPMC3099552

What OpenQuestion holds

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Registered trials

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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.