The map below shows majority race by area in Old Moses, 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 Old Moses racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Old Moses overall is white, making up 57.1% of residents. The next most-common racial group is hispanic at 30.4%. There are more white people in the central 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 Old Moses
Self-Identified Race |
Old Moses, NM Population |
|---|---|
White |
57.1% |
Hispanic |
30.4% |
Black |
3.4% |
Asian |
0.0% |
Native American |
6.3% |
Other |
2.8% |
Diversity and Diversity Scores for Old Moses, NM
The map below shows diversity in Old Moses. 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.
Old Moses Diversity Score
57.5
More diverse than 92% of US cities
Old Moses has a diversity score of 57.5: 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. Old Moses is much more diverse than other US cities, more diverse than 92% of them. Within Old Moses's proper boundaries, the most diverse area is northwest Old Moses, and the least diverse areas are in central Old Moses.
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.