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Every five years, the Greater Golden Horseshoe Area (of southern Ontario) conducts something called a Transportation Tomorrow Survey. And I am told that it is the most comprehensive travel survey conducted anywhere in the world. So let's look at some of the data. The last survey was completed in 2022 and a mapping of the data was prepared by the School of Cities at the University of Toronto.
Population density:
Percentage of trips by walking:
Percentage of trips by bicycle:
Percentage of trips by public transit:
Percentage of trips by car:
Percentage of residents with a driver's license:
Percentage of households without a car:
Average trips by distance:
Once again, these maps remind us that the starkest contrast is between active and non-active forms of mobility. In other words, we have a central core where many, and sometimes most people (>50%) walk to where they need to go, and then there's absolutely everywhere else in the region where most people drive (>50%) and, in some cases, where people drive almost exclusively (>90%). Public transit ridership is more dispersed, but it's really only dominant in Toronto, and not in any of the suburbs.
Perhaps the only reasonably uniform finding is that average trip distances tend to be relatively short (<10 km) no matter where you live.
Maps from the School of Cities at the University of Toronto; cover photo by Juan Rojas on Unsplash
Richard Florida and Patrick Adler recently looked at the geography of gyms across the United States. They analyzed 17 different fitness chains, over 10,000 gyms, and nearly 5,000 zip codes. Full article over here at CityLab.
The findings probably won’t surprise you, but it’s still interesting to see some of the data. Gyms and fitness studios tend to concentrate themselves in affluent neighborhoods with a high number of college graduates.
The median household income of the average zip code with a gym or fitness studio is $72,720. This is compared to $56,694 for all zip codes. And when it comes to zip codes with an Equinox, SoulCycle, The Bar Method, or Town Sports Clubs, the median income jumps to over $100,000.
According to a recent study in the New York Times, the average age of a first-time mother in Manhattan is 31.1 years old. In San Francisco County, the number is nearly 32. And in the US as a whole, it was 26.3 in 2016.
This is what the national distribution looked like in 1980:
And this is what it looked like in 2016:
Perhaps not surprisingly, the biggest factor influencing the age of a first-time mother is education. Becoming educated and building a career takes time. First-time mothers tend to be older in big cities (particularly on the coasts) compared to rural areas.
The concern that researchers have with all of this is that it is symptomatic of growing inequality. Scrolling over the NY Times’ map, it would appear that there’s nearly a 10 year gap between the coasts and many parts of the country.
On the one hand you have people who are finishing high school and having kids fairly soon after. And on the other hand, you have people going to college, establishing their career, and waiting, in some cases a decade, to have kids.
This is significant because it can create a virtuous circle (excerpt from article):
“A college degree is increasingly essential to earning a middle-class wage, and older parents have more years to earn money to invest in violin lessons, math tutoring and college savings accounts — all of which can set children on very different paths.”
Unequal childhoods can lead to unequal outcomes.
Images: New York Times
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