The map below shows majority race by area in La Cienega, 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 La Cienega racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in La Cienega overall is hispanic, making up 75.1% of residents. The next most-common racial group is white at 23.4%. There are more hispanic people in the central areas of the city. People who identify as white 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 La Cienega
Self-Identified Race |
La Cienega, NM Population |
|---|---|
White |
23.4% |
Hispanic |
75.1% |
Black |
0.0% |
Asian |
0.5% |
Native American |
0.1% |
Other |
0.9% |
Diversity and Diversity Scores for La Cienega, NM
The map below shows diversity in La Cienega. 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.
La Cienega Diversity Score
38.2
More diverse than 71% of US cities
La Cienega has a diversity score of 38.2: 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. La Cienega is more diverse than other US cities, more diverse than 71% of them. Within La Cienega's proper boundaries, the most diverse area is southeast La Cienega, and the least diverse areas are in central La Cienega.
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.