The map below shows majority race by area in Maryland Point, 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 Maryland Point racial diversity and diversity scores. Click here to scroll to diversity data.
WhiteHispanicBlackAsianMultiple/Other
Majority race by area
The majority race in Maryland Point overall is white, making up 68.0% of residents. The next most-common racial group is black at 21.8%. There are more white people in the east areas of the city. People who identify as black are most likely to be living in the east 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 Maryland Point
Self-Identified Race |
Maryland Point, MD Population |
|---|---|
White |
68.0% |
Hispanic |
0.6% |
Black |
21.8% |
Asian |
0.4% |
Native American |
0.0% |
Other |
9.2% |
Diversity and Diversity Scores for Maryland Point, MD
The map below shows diversity in Maryland Point. 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.
Less diverse
More diverse
Colorblind friendly
off
Maryland Point Diversity Score
48.1
More diverse than 81% of US cities
Maryland Point has a diversity score of 48.1: 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. Maryland Point is much more diverse than other US cities, more diverse than 81% of them.
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.