The map below shows majority race by area in New Mexico, 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 New Mexico racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in New Mexico overall is hispanic, making up 48.6% of residents. The next most-common racial group is white at 36.0%. There are more hispanic people in the south areas of the state. People who identify as white 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 New Mexico
Self-Identified Race |
New Mexico Population |
|---|---|
White |
36.0% |
Hispanic |
48.6% |
Black |
1.8% |
Asian |
1.7% |
Native American |
8.1% |
Other |
3.7% |
Diversity and Diversity Scores for New Mexico
The map below shows diversity in New Mexico. 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 state would both be considered lacking diversity.
New Mexico Diversity Score
62.6
More diverse than 80% of US states
New Mexico has a diversity score of 62.6: 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. New Mexico is much more diverse than other US states, more diverse than 80% of them. Within New Mexico's proper boundaries, the most diverse area is west New Mexico, and the least diverse areas are in south New Mexico.
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.