The map below shows majority race by area in Maple Shade, 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 Maple Shade racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Maple Shade overall is white, making up 61.9% of residents. The next most-common racial group is hispanic at 16.4%. There are more white people in the north areas of the city. People who identify as hispanic are most likely to be living in the northeast 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 Maple Shade
Self-Identified Race |
Maple Shade, NJ Population |
|---|---|
White |
61.9% |
Hispanic |
16.4% |
Black |
6.8% |
Asian |
8.7% |
Native American |
0.0% |
Other |
6.2% |
Diversity and Diversity Scores for Maple Shade, NJ
The map below shows diversity in Maple Shade. 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.
Maple Shade Diversity Score
57.4
More diverse than 92% of US cities
Maple Shade has a diversity score of 57.4: 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. Maple Shade is much more diverse than other US cities, more diverse than 92% of them. Within Maple Shade's proper boundaries, the most diverse area is east Maple Shade, and the least diverse areas are in north Maple Shade.
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.