Evidence map›Paper›PMID 36578816›Full record

ArticleJournal of transport & health2018

Latent analysis of Complete Streets and traffic safety along an urban corridor.

Kara E MacLeod, Rebecca L Sanders, Ashleigh Griffin, Jill F Cooper, David R Ragland

Abstract read
In one paragraph

Article in Journal of transport & health, 2018. 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

5 authors.

Kara E MacLeodSafe Transportation Research & Education Center University of California, Berkeley 2614 Dwight Way #7374 Berkeley, CA 94720 U.S.A.
Rebecca L SandersSafe Transportation Research & Education Center University of California, Berkeley 2614 Dwight Way #7374 Berkeley, CA 94720 U.S.A.
Ashleigh GriffinSafe Transportation Research & Education Center University of California, Berkeley 2614 Dwight Way #7374 Berkeley, CA 94720 U.S.A.
Jill F CooperSafe Transportation Research & Education Center University of California, Berkeley 2614 Dwight Way #7374 Berkeley, CA 94720 U.S.A.
David R RaglandSafe Transportation Research & Education Center University of California, Berkeley 2614 Dwight Way #7374 Berkeley, CA 94720 U.S.A.

Funding

TREND &STRUCTURE OF ALCOHOL DEPENDENCE--GENERAL POPULATION 1990 SURVEY DATAP50AA005595 · NIAAA · WESTERN CONSORTIUM FOR PUBLIC HEALTH · PI KERR, WILLIAM C. · 1985 to 2025
$34.1M
GRADUATE RESEARCH TRAINING ON ALCOHOL PROBLEMST32AA007240 · NIAAA · UNIVERSITY OF CALIFORNIA BERKELEY · PI William C. Kerr · 1985 to 2026
$7.5M
NIAAA NIH HHS P50 AA005595NIAAA NIH HHS T32 AA007240
6 · The paper itself

Abstract

backgroundTo evaluate Complete Street implementations that covary, the present paper aims to: 1) explore the development of typologies of intersections; and 2) examine how these typologies relate to traffic safety.

methodsThe study site is a five-mile segment in Los Angeles County, California. Multiple indicators of environmental features were collected in 2012 and were included in a latent analysis. Latent classes were then analyzed as a predictor of the number of pedestrian injuries/fatalities and injuries/fatalities for all modes in separate models using negative binomial regression and controlling for exposures. Injuries/fatalities represent the most recent 3 years of crash data available surrounding the environmental data collection (2009-2014). We also examined the role of alcohol.

resultsFor a relatively short segment of an urban corridor, we identified two distinct classes of intersections. One class was more complete with respect to pedestrian features but was also associated with indicators of increased potential conflict and was predictive of higher overall injuries/fatalities for all modes. This class also had higher pedestrian volumes but was not predictive of higher pedestrian injuries/fatalities in the final models. The alcohol involvement in crash injuries at these locations did not differ by intersection class but was positively associated with injuries/fatalities for all modes and with severe/fatal injuries for pedestrians in the final models.

conclusionsIdentifying typologies can be used to understand the combination of features and prioritize locations for treatment. While Complete Streets may help counter pedestrian injury trends, the efforts captured in this data are insufficient for municipalities aiming for Vision Zero. Ideally, future research can examine these intersections after the implementation of additional improvements in order to isolate treatment effects. These findings suggest additional intersection countermeasures are needed, in addition to efforts to address social problems such as alcohol use and traffic safety.

Indexed as

Complete Streetspedestrian safetytraffic safetytypologiesvehicle conflictVision Zero

Identifiers

PMID36578816
PMCPMC9794175

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.