Demographics details for White house, TN vs Waterproof, LA
Population Overview
Compare main population characteristics in White house, TN vs Waterproof, LA.
| Data | White house | Waterproof |
|---|---|---|
| Population | 14,516 | 499 |
| Median Age | 36.5 years | 37.0 years |
| Median Income | $85,404 | $21,953 |
| Married Families | 46.0% | 9.0% |
| Poverty Level | 7% | 30% |
| Unemployment Rate | 3.4 | 5.0 |
Population Comparison: White house vs Waterproof
- In White house, the population is higher at 14,516, compared to 499 in Waterproof.
- The median age in Waterproof is higher at 37.0 years, compared to 36.5 years in White house.
- White house has a higher median income of $85,404 compared to $21,953 in Waterproof.
- A higher percentage of married families is found in White house at 46.0% compared to 9.0% in Waterproof.
- The poverty level is higher in Waterproof at 30%, compared to 7% in White house.
- Waterproof has a higher unemployment rate at 5.0% compared to 3.4% in White house.
Demographics
Demographics White house vs Waterproof provide insight into the diversity of the communities to compare.
| Demographic | White house | Waterproof |
|---|---|---|
| Black | 2 | 103 |
| White | 87 | -12 |
| Asian | 1 | 7 |
| Hispanic | 4 | Data is updating |
| Two or More Races | 6 | 2 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: White house vs Waterproof
- In Waterproof, the percentage of Black residents is higher at 103% compared to 2% in White house.
- White house has a higher percentage of White residents at 87% compared to -12% in Waterproof.
- In Waterproof, the Asian population stands at 7%, greater than 1% in White house.
- The Hispanic community is larger in White house at 4% compared to 0% in Waterproof.
- More residents identify as two or more races in White house at 6% compared to 2% in Waterproof.
- The percentage of American Indian residents is the same in both White house and Waterproof at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | White house | Waterproof |
|---|---|---|
| Mental Health Not Good | 17.5% | 24.5% |
| Physical Health Not Good | 11.0% | 20.0% |
| Depression | 27.6% | 25.1% |
| Smoking | 17.7% | 33.7% |
| Binge Drinking | 16.7% | 11.8% |
| Obesity | 32.5% | 53.1% |
| Disability Percentage | 11.0% | 22.0% |
Health Statistics Comparison: White house vs Waterproof
- In Waterproof, a higher percentage report poor mental health at 24.5% compared to 17.5% in White house.
- Depression is more prevalent in White house at 27.6% compared to 25.1% in Waterproof.
- Waterproof has a higher smoking rate at 33.7% compared to 17.7% in White house.
- Binge drinking is more common in White house at 16.7% compared to 11.8% in Waterproof.
- Waterproof has higher obesity rates at 53.1% compared to 32.5% in White house.
- There is a higher percentage of disabled individuals in Waterproof at 22.0% compared to 11.0% in White house.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | White house | Waterproof |
|---|---|---|
| No Schooling | 0.2% (30) | 0.0% (Data is updating) |
| High School Diploma | 18.0% (2,617) | 27.7% (138) |
| Less than High School | 12.4% (1,794) | 10.6% (53) |
| Bachelor's Degree and Higher | 15.4% (2,235) | 12.8% (64) |
Education Levels Comparison: White house vs Waterproof
- A higher percentage of residents in White house have no formal schooling at 0.2% compared to 0.0% in Waterproof.
- In Waterproof, the rate of residents with high school diplomas is higher at 27.7% compared to 18.0% in White house.
- More residents in White house have less than a high school education at 12.4% compared to 10.6% in Waterproof.
- A higher percentage of residents in White house hold a bachelor's degree or higher at 15.4% compared to 12.8% in Waterproof.
Crime and Safety
Understanding crime rates and safety measures is crucial for assessing the livability of a city or town. Crime levels can vary significantly from one neighborhood to another, influenced by various factors such as population density and local amenities. For instance, areas with high foot traffic, like train stations, might experience different crime dynamics compared to quieter residential neighborhoods. Evaluating these patterns helps in making informed decisions about safety and community well-being.