It is not surprising that in wealthier communities, which, for most of the country, means suburban areas with low density and a street network that is not amenable to walking or cycling, there are fewer pedestrian injuries and deaths. If no one is walking, there are relatively few accidents involving walkers. This is not a sign that the community is safer for walkers, but that there is consensus that walking is a dangerous activity.
I would be more interested in comparing socioeconomic groups by type of community in terms of walkability, road speed, etc. One might find very different data in Brooklyn than in Oklahoma City.--On Mon, Apr 23, 2012 at 9:14 AM, David Levinger <david@mobilityeducation.org> wrote:Speed is one of the prime factors, so it surprised me that it's not mentioned in these articles.Wealthier residential communities are able to muster the political will to implement different speed norms. And, of course one of the top priorities for neighborhood selection is "less traffic."
-DavidOf interest, relation of low income neighborhoods and traffic crashes.
Marc Brenman
mbrenman001@comcast.net
Traffic injuries much more common in poor areas, study finds
LA Times
By Karen Kaplan, Los Angeles Times/For the Booster Shots blog
April 19, 2012, 1:47 p.m.
Here’s another way that rich people are different – they experience far fewer traffic accidents in their neighborhoods, according to a new study.
This isn’t exactly a shocking conclusion. There are an estimated 40,000 road deaths in the U.S. each year, and many studies have found that these are more likely to involve low-income people in low-income areas.
But there’s nothing about being poor that should make a person inherently more vulnerable to being hurt in a car crash. As researchers from Montreal explained in their study, “deaths and injuries result from the transfer of a motor vehicle’s kinetic energy at a rate that exceeds the human body’s protective capacity.”
So what is it about poor neighborhoods that explains the heightened risk? To find out, the researchers gathered information on all road traffic injuries on the Island of Montreal between 1999 and 2003. (The island is served by a single ambulance company, which provided records for the study.) The researchers focused on 19,568 accident victims who got hurt at 17,498 intersections, all of which were located in census tracts with at least some residents. Intersections that straddled multiple census tracts, were adjacent to highway on-ramps or were in purely industrial or commercial areas were not included in the analysis.
Then the researchers took all of those intersections and sorted them into five categories based on the average household income for the census tract in which they were located. The main comparisons were between the 20% of intersections in the poorest census tracts and the 20% of intersections in the wealthiest census tracts. Here’s some of what they found:
* Population density in the poorest census tracts was 2.7 times higher than in the wealthiest census tracts.
* Average traffic at intersections in the poorest neighborhoods was 2.4 times greater than in the richest neighborhoods.
* 30% of the intersections in the poorest neighborhoods included a major traffic artery, compared with only 11.5% of intersections in the richest neighborhoods.
* The number of four-way intersections in the poorest census tracts was nearly twice as high as in the wealthiest census tracts. Collisions involving injuries are more common at four-way intersections than at three-way intersections.
The net effect of these (and other) factors was not good for motorists, cyclists or pedestrians in the lowest-income areas. The researchers found that the number of pedestrians injured in the poorest census tracts was 6.3 times higher than in the richest census tracts. People riding in cars were also more vulnerable in the poorest areas – the number of injured motor vehicle occupants was 4.3 times greater in poor areas than in rich ones. The story was similar for cyclists – the number of injuries was 3.9 times higher in poor areas than in rich ones.
The researchers calculated that for every 1,000 additional vehicles that pass through an intersection each day, the number of people injured in cars rose by 7%, the number of injured pedestrians rose by 6%, and the number of injured cyclist rose by 5%. Since poorer neighborhoods had more traffic, they also had more injuries.
“We found that environmental factors associated with a greater risk of crashes” – the number of people exposed to crashes, the total volume of traffic, and the geometry of roads and intersections – “were more frequent in the poorest neighborhoods,” the study authors wrote. These three factors accounted for “a substantial portion” of the difference between the poorest versus the richest neighborhoods, they added.
“It should be underscored that poverty per se does not produce RTIs [road traffic injuries] – exposure to moving vehicles does,” they wrote.
The results were published online Thursday by the American Journal of Public Health. The full study is behind a pay wall, but you can read an abstract here.
Patrick Morency, Lise Gauvin, Céline Plante, Michel Fournier, and Catherine Morency. (2012). Neighborhood Social Inequalities in Road Traffic Injuries: The Influence of Traffic Volume and Road Design. American Journal of Public Health. e-View Ahead of Print.
doi: 10.2105/AJPH.2011.300528
Accepted on: Oct 13, 2011
Neighborhood Social Inequalities in Road Traffic Injuries: The Influence of Traffic Volume and Road Design
Patrick Morency, MD, PhD, Lise Gauvin, PhD, Céline Plante, MSc, Michel Fournier, MA, and Catherine Morency, PhD
Patrick Morency, Céline Plante, and Michel Fournier are with the Direction de santé publique de Montréal, Montréal, Québec, Canada. Patrick Morency and Lise Gauvin are with the Centre de Recherche du Centre Hospitalier de l'Université de Montréal and the Département de médecine sociale et préventive de l'Université de Montréal, Montréal, Québec, Canada. Catherine Morency is with the Département des génies civil, géologique et des mines, École Polytechnique de Montréal, and the Centre interuniversitaire de recherche sur les réseaux d'entreprise, la logistique et le transport, Montréal, Québec, Canada.
Correspondence should be sent to Patrick Morency, MD, PhD, Direction de santé publique de Montréal, 1301 Sherbrooke Est, Montréal (Québec) H2L 1M3, Canada (e-mail: pmorency@santepub-mtl.qc.ca). Reprints can be ordered at http://www.ajph.org by clicking the “Reprints” link.
Contributors
P. Morency conceptualized the study and led the writing. L. Gauvin conceptualized and supervised the study. C. Plante and M. Fournier contributed to the analyses. C. Morency assisted with the data collection and analyses. All authors contributed to the writing of the article.
Objectives. We examined the extent to which differential traffic volume and road geometry can explain social inequalities in pedestrian, cyclist, and motor vehicle occupant injuries across wealthy and poor urban areas.
Methods. We performed a multilevel observational study of all road users injured over 5 years (n = 19 568) at intersections (n = 17 498) in a large urban area (Island of Montreal, Canada). We considered intersection-level (traffic estimates, major roads, number of legs) and area-level (population density, commuting travel modes, household income) characteristics in multilevel Poisson regressions that nested intersections in 506 census tracts.
Results. There were significantly more injured pedestrians, cyclists, and motor vehicle occupants at intersections in the poorest than in the richest areas. Controlling for traffic volume, intersection geometry, and pedestrian and cyclist volumes greatly attenuated the event rate ratios between intersections in the poorest and richest areas for injured pedestrians (−70%), cyclists (−44%), and motor vehicle occupants (−44%).
Conclusions. Roadway environment can explain a substantial portion of the excess rate of road traffic injuries in the poorest urban areas. (Am J Public Health. Published online ahead of print April 19, 2012: e1-e8. doi:10.2105/AJPH.2011.300528)
Read More: http://ajph.aphapublications.org/doi/abs/10.2105/AJPH.2011.300528
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