Pedestrian safety disparities in lower-income areas

Are we failing our lower-income communities?

Hafez Alavi’s recent PHD thesis on Pedestrian Safety got Lewis Martin thinking. One of the key variables it identifies as influencing higher pedestrian risk was lower social economic areas. But that is in Australia – do we have the same problem in New Zealand?

Unfortunately, the answer seems to be a resounding yes.

Analysis of New Zealand crash data in conjunction with population density data and income data shows that there are much higher pedestrian crash rates in low-income areas, as shown in the graph below. Here we can see that pedestrian crash rates per population are highest in the lowest income areas and lowest in the highest income areas. 

pedestrian sign
Pedestrian crashes graph
Figure 1: NZ Pedestrian Crash Risk for various median incomes - Injury crashes

The results do not look any better if we focus on deaths and serious injuries. Pedestrian death and serious injury rates per population are almost two times higher in the lowest income areas compared with the most affluent areas.

So why does this trend exist? As always with transportation problems, the answer is not a simple one. Some reasons include:

  1. There are normally higher levels of car ownership in higher income communities.[1] This likely results in less walking and thus less exposure for pedestrians.
  2. Lower income communities often have older vehicles without the pedestrian safety technologies present in new vehicles.

However, these reasons likely only act to blur the main reason for this disparity – road design. Affluent residential areas normally have higher quality infrastructure features, such as better footpaths, more speed calming treatments, safe pedestrian crossings and the like. This again is due to multiple reasons. Developers have to follow stricter rules when it comes to building new metaproperty development than local governments do when it comes to retrofitting existing environments. To add to this, once these environments are built and require maintenance, local governments generally replace like for like. This means that “better” environments get “better” infrastructure and “poorer” environments get “poorer” infrastructure.

The affluent population also have louder voices. In my experience working for a local government authority, the louder voice of the more affluent areas of the city, was not lost on me. And these are often the people who have connections with politicians and have better access to smart phones, computers and other technologies and education that helps them understand how the system works and how to use that to their advantage.

Bring all this together and what do you get? Vibrant, well designed and safe communities in affluent areas and dreary, outdated and higher risk road environments in lower income communities.

So what is the solution? Well unfortunately, there is no single answer to this complex issue. Further work is required to fully understand the causes of and inter-dependencies of this issue. However, there are some recommendations I am comfortable making. These include:

  1. Safer infrastructure for lower income communities – perhaps we need to look at our maintenance practices and move away from replacing like for like, when this is disadvantaging lower income communities.
  2. Develop tools to predict pedestrian risk – we need tools to help us understand locations of highest pedestrian risk. Historical crashes alone do not cut it, as we know there is risk on sections of the network where there have been no previous crashes. This helps road safety practitioners and decision makers be data-led and rely less on potentially biased community input.
  3. Better communication with lower income communities – not everyone knows how to get in contact with their local government. This means that local government needs to do everything they can to contact these communities and hear their concerns.

These issues are not isolated to road safety, in fact they are much broader than even transportation, touching on all aspects in our country. As road safety professionals we have a responsibility to reduce risk across all communities and must avoid being swayed by the loudest voices by taking a data-led approach.