The map below shows majority race by area in Glastonbury, as self-identified on the US census. Darker shades indicate a larger racial majority in that neighborhood. This page also contains data and maps on Glastonbury racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Glastonbury overall is white, making up 71.4% of residents. The next most-common racial group is hispanic at 13.0%. There are more white people in the southwest areas of the city. People who identify as hispanic are most likely to be living in the southeast places. The data below shows how many people identify themselves as each of the following races, which most Americans base on their family's national origin:
Race in Glastonbury
Self-Identified Race |
Glastonbury, CT Population |
|---|---|
White |
71.4% |
Hispanic |
13.0% |
Black |
1.8% |
Asian |
10.4% |
Native American |
0.1% |
Other |
3.3% |
Diversity and Diversity Scores for Glastonbury, CT
The map below shows diversity in Glastonbury. Areas in green are more diverse, while areas in red are much less diverse. Diversity, in this case, means a mixture of people with different race and ethnicity living close to one another. For example, all-black and all-white areas in the city would both be considered lacking diversity.
Glastonbury Diversity Score
46.1
More diverse than 79% of US cities
Glastonbury has a diversity score of 46.1: the chance, in percent, that two residents picked at random belong to different racial or ethnic groups, from ACS race counts. A place where everyone shares one group scores 0, and an even mix of the six groups in the chart above scores the maximum, 83.3. Glastonbury is more diverse than other US cities, more diverse than 79% of them. Within Glastonbury's proper boundaries, the most diverse area is central Glastonbury, and the least diverse areas are in southwest Glastonbury.
Source: BestNeighborhood calculations from the U.S. Census Bureau, American Community Survey (ACS) 2020-2024 5-year estimates (race and Hispanic origin); proprietary data mapping and analysis. Special thanks to the University of Virginia.