The map below shows majority race by area in Lavon Beach Estates, 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 Lavon Beach Estates racial diversity and diversity scores. Click here to scroll to diversity data.
WhiteHispanicBlackAsianMultiple/Other
Majority race by area
The majority race in Lavon Beach Estates overall is white, making up 76.8% of residents. The next most-common racial group is hispanic at 15.1%. There are more white people in the northeast areas of the city. People who identify as hispanic 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 |
Lavon Beach Estates, TX Population |
|---|---|
White |
76.8% |
Hispanic |
15.1% |
Black |
4.2% |
Asian |
0.5% |
Native American |
0.0% |
Other |
3.5% |
Racial Distribution Key
White
Hispanic
Black
Asian
Native American
Other
Self-Identified Race |
Lavon Beach Estates, TX Population |
|---|---|
White |
76.8% |
Hispanic |
15.1% |
Black |
4.2% |
Asian |
0.5% |
Native American |
0.0% |
Other |
3.5% |
Diversity and Diversity Scores for Lavon Beach Estates, TX
The map below shows diversity in Lavon Beach Estates. 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.
Diversity Score
Diverse
Moderately diverse
No diversity
Lavon Beach Estates Diversity Score
80
With a diversity score of 80 out of 100, Lavon Beach Estates is much more diverse than other US cities. The most diverse area within Lavon Beach Estates's proper boundaries is to the east of the city. The least diverse areas are located in the northeast parts of Lavon Beach Estates.
Data Sources: U.S. Census, proprietary data mapping and analysis. Special thanks to the University of Virginia.
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