Introduction

This report draws on data from the 2017 National Household Travel Survey, which provides a snapshot of the travel patterns of both able-bodied and disabled individuals in the United States.1 We focused on the travel of disabled people, specifically their use of public transportation. Public transit is an important resource for many people, but disability status and other factors could affect an individual’s ability to use this service. We wanted to examine who has access to this resource, so we looked at the effects of travel accommodations on the use of public transit and questioned the effects of lifestyle factors like household income and size.

Data Visualization

Data Visualization 1

These histograms show public transit use by disabled individuals, based on the duration of disability. Those without disabilities were removed from the dataset because their overwhelming numbers threw off the scale of the plot. The overall shape of each plot is similar, indicating similar use of public transit by disabled people across disability types. The plots show strong positive skew, with the highest bar at zero, indicating that most people with disabilities are not using public transit at all. However, the spread shows that individuals with disabilities are using public transit in a variety of ways - some ride rarely and some ride many times a day. The proportion of people with a lifelong disability that did not use public transit was lower than other categories, indicating that those with lifelong disabilities may rely on public transit more, or may have had more time to learn to navigate transit systems.

Data visualization 2

This series of plots explores the relationship between public transit use and travel accommodations. The first plot shows that disabled people without travel accommodations are less likely to use public transit overall, since the median count is higher among those with accommodations across all types of disability. This indicates that accommodations do allow greater traveling ability for those with disabilities. The next plots explore the use of specific accommodations. Those using walkers are overall more likely to use public transit than those without, although the disparity lessens the longer the disability is experienced. Those with electric wheelchairs are overall less likely to use public transit than those without, but those with manual wheelchairs are slightly more likely to use public transit. This could be due to the difficulty of loading a heavy electric wheelchair onto a bus or train, while manual wheelchairs are generally lighter and can often be folded.

Data visualization 3

This column chart shows the relationship between disabled people’s public transit use and their average household income and employment status. The dataset is for this visualization as well as visualization #4 is also composed entirely of people with disabilities. The graph illuminates that those who make $35,000 annually are more likely to use public transit than those who make more (I also compared this distribution to the household income breakdown of the full dataset, and this observation remains true). Additionally, unemployed people are proportionally more likely to use public transit than their employed counterparts. Employment, income, and transportation options are all tightly linked and mutually contingent, and using public transit is almost always more accessible and affordable than private car ownership or ride-sharing. This visualization, with its pronounced positive skew, offers a possible reinforcement of these social conditions.

Data visualization 4

This plot also shows public transit use by household income, this time illustrating differences in transit use by household structure. While we already know that those on the lower end of the income spectrum (<$35,000 per year) constitute the majority of the public transit trip count, this graph shows that those who live alone use public transit more than those who do not. Once again, this opens a window into a couple tightly intertwined contextual variables–income, household structure–that impact how often disabled people rely on public transport. Living alone, without shared funds, often limits economic stability and upward mobility. Also, non-driving disabled people who live alone do not have the support of family/roommates to transport them. These variables, which make up the backdrop of living conditions, influence how people with disabilities can travel and engage with their communities.

Summary

Summarize the key takeaway from your analysis: The data that we used to create our visualizations was pulled from an NHTS repository constructed about travel disabilities; participants were asked if they “have a medical condition that makes it difficult to travel outside of home.” This sort of data collection, based on self-reporting, comes with the risk of underrepresentation. The phrasing of the question is highly loaded and important. For example, the term “medical” might lead those without officially diagnosed disabilities to misrepresent the extent of their travel difficulties. The phrase “medical condition,” often used to refer to chronic physical injury/disability, might influence how those who experience more psychological or other invisibilized forms of disability choose to respond.

One implication of this data is the importance of accommodations to enable individuals with disabilities to utilize public transportation. The first visualization shows that disabled people are not using public transit in large numbers. This could be due to difficulty accessing or navigating public transit because of a disability. The next series of graphs shows that accommodations do appear to enable people to use public transit in greater numbers. However, a larger accommodation like an electric wheelchair made use less likely. Improved access to accommodations and improved access for all types of accommodations would likely make accessing public transit easier for people with disabilities.

  1. Henly, M., & Brucker, D. L. (2019). Transportation patterns demonstrate inequalities in community participation for working-age Americans with disabilities. Transportation Research Part A: Policy and Practice, 130, 93–106. https://doi.org/10.1016/j.tra.2019.09.042 .↩︎