The map below shows majority race by area in Mount Laguna, 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 Mount Laguna racial diversity and diversity scores. Click here to scroll to diversity data.
The majority race in Mount Laguna overall is white, making up 75.4% of residents. The next most-common racial group is hispanic at 17.3%. There are more white people in the east 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 Mount Laguna
Self-Identified Race |
Mount Laguna, CA Population |
|---|---|
White |
75.4% |
Hispanic |
17.3% |
Black |
1.3% |
Asian |
0.4% |
Native American |
0.0% |
Other |
5.6% |
Diversity and Diversity Scores for Mount Laguna, CA
The map below shows diversity in Mount Laguna. 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.
Mount Laguna Diversity Score
39.8
More diverse than 73% of US cities
Mount Laguna has a diversity score of 39.8: 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. Mount Laguna is more diverse than other US cities, more diverse than 73% of them. Within Mount Laguna's proper boundaries, the most diverse area is central Mount Laguna, and the least diverse areas are in east Mount Laguna.
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.