Race, Diversity, and Ethnicity in Miramar, CA

The map below shows majority race by area in Miramar, 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 Miramar racial diversity and diversity scores. Click here to scroll to diversity data.

Miramar, CA map of race and ethnicity
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White
Hispanic
Black
Asian
Multiple/Other
WhiteHispanicBlackAsianMultiple/Other
Majority race by area

The majority race in Miramar overall is white, making up 55.0% of residents. The next most-common racial group is hispanic at 33.2%. 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 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 Miramar
Race
Miramar, CA Population
White
55.0%
Hispanic
33.2%
Black
0.3%
Asian
10.4%
Native American
0.1%
Other
1.0%
 

Racial Distribution Key

White
Hispanic
Black
Asian
Native American
Other
 
Self-Identified Race
Miramar, CA Population
White
55.0%
Hispanic
33.2%
Black
0.3%
Asian
10.4%
Native American
0.1%
Other
1.0%
   

Diversity and Diversity Scores for Miramar, CA

The map below shows diversity in Miramar. 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.

Miramar, CA map of race and ethnicity
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Diversity Score

Diverse
Moderately diverse
No diversity
 

Miramar Diversity Score

91

With a diversity score of 91 out of 100, Miramar is much more diverse than other US cities. The most diverse area within Miramar's proper boundaries is to the central of the city. The least diverse areas are located in the central parts of Miramar.

Data Sources: U.S. Census, proprietary data mapping and analysis. Special thanks to the University of Virginia.

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