The map below shows majority race by area in White Marsh, 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 White Marsh racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in White Marsh overall is white, making up 55.5% of residents. The next most-common racial group is black at 19.7%. 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 south 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 White Marsh
Self-Identified Race |
White Marsh, MD Population |
|---|---|
White |
55.5% |
Hispanic |
8.8% |
Black |
19.7% |
Asian |
10.9% |
Native American |
0.0% |
Other |
5.1% |
Diversity and Diversity Scores for White Marsh, MD
The map below shows diversity in White Marsh. 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.
White Marsh Diversity Score
63.1
More diverse than 96% of US cities
White Marsh has a diversity score of 63.1: 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. White Marsh is much more diverse than other US cities, more diverse than 96% of them. Within White Marsh's proper boundaries, the most diverse area is south White Marsh, and the least diverse areas are in east White Marsh.
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.