Explore the impact of demographic factors on the ridership of public transit (light rail and subway(T)) in the Boston area.
By Becca Flach, Camille Kawabata, Sally Lee, Sherry Li, Noah Woosley
Published Apr. 25, 2024
In the bustling, hectic cityscape of Boston, public transit should be the network that connects everyone. Instead of acting as the great connector, the rapid transit lines in Boston perpetuate racial and class divides. This works directly against the United Nation’s Sustainable Development Goals, specifically target 11.2; “By 2030, provide access to safe, affordable, accessible and sustainable transport systems for all, improving road safety, notably by expanding public transport, with special attention to the needs of those in vulnerable situations, women, children, persons with disabilities and older persons”.
Suffolk County is composed of four cities:
Within the four cities above, we used a block group, the smallest geographic unit that the census uses with 250-550 houses for each unit, to analyze our census and compare it to the ridership data.
One of the key demographic factors we hypothesized to impact transit usage is income level. We assumed that lower-income individuals may heavily rely on public transportation due to limited access to private vehicles or the high cost of car ownership.
Race is another important demographic factor that influences public transit usage patterns. In Boston, as in many other cities, we assumed that there would be disparities in transit access and usage among the differential racial and ethnic groups. We expected to see variations in transit ridership based on racial demographics, with certain communities showing higher levels of public transit usage compared to others.
To measure public transit usage, we used the data published by the MBTA about the number of entries to each gated station. We combined this with census data by finding which station was closest to each census block. Using the population, income, and demographic information for each census block group, we investigated the relationship between transit usage and demographic factors.
Figure 1: choropleth map depicting the percentage of the population that uses either the light rail or subway to get to work in Suffolk County in 2016 and 2022 with the station locations overlaid.