The map below shows majority race by area in Green Level, 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 Green Level racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Green Level overall is white, making up 33.4% of residents. The next most-common racial group is hispanic at 29.8%. There are more white people in the northwest areas of the city. People who identify as hispanic are most likely to be living in the central 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 Green Level
Self-Identified Race |
Green Level, NC Population |
|---|---|
White |
33.4% |
Hispanic |
29.8% |
Black |
28.0% |
Asian |
0.6% |
Native American |
0.0% |
Other |
8.2% |
Diversity and Diversity Scores for Green Level, NC
The map below shows diversity in Green Level. 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.
Green Level Diversity Score
71.4
More diverse than 99% of US cities
Green Level has a diversity score of 71.4: 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. Green Level is much more diverse than other US cities, more diverse than 99% of them. Within Green Level's proper boundaries, the most diverse area is north Green Level, and the least diverse areas are in northwest Green Level.
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.