Demographics details for White house, TN vs Berlin, NJ
Population Overview
Compare main population characteristics in White house, TN vs Berlin, NJ.
| Data | White house | Berlin |
|---|---|---|
| Population | 14,516 | 7,506 |
| Median Age | 36.5 years | 40.4 years |
| Median Income | $85,404 | $98,706 |
| Married Families | 46.0% | 37.0% |
| Poverty Level | 7% | 5% |
| Unemployment Rate | 3.4 | 3.2 |
Population Comparison: White house vs Berlin
- In White house, the population is higher at 14,516, compared to 7,506 in Berlin.
- The median age in Berlin is higher at 40.4 years, compared to 36.5 years in White house.
- Berlin has a higher median income of $98,706, compared to $85,404 in White house.
- A higher percentage of married families is found in White house at 46.0% compared to 37.0% in Berlin.
- White house has a higher poverty level at 7% compared to 5% in Berlin.
- The unemployment rate in White house is higher at 3.4%, compared to 3.2% in Berlin.
Demographics
Demographics White house vs Berlin provide insight into the diversity of the communities to compare.
| Demographic | White house | Berlin |
|---|---|---|
| Black | 2 | 12 |
| White | 87 | 76 |
| Asian | 1 | 1 |
| Hispanic | 4 | 5 |
| Two or More Races | 6 | 6 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: White house vs Berlin
- In Berlin, the percentage of Black residents is higher at 12% compared to 2% in White house.
- White house has a higher percentage of White residents at 87% compared to 76% in Berlin.
- Both White house and Berlin have the same percentage of Asian residents at 1%.
- Berlin has a higher percentage of Hispanic residents at 5%, compared to 4% in White house.
- Both White house and Berlin have the same percentage of residents identifying as two or more races at 6%.
- The percentage of American Indian residents is the same in both White house and Berlin at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | White house | Berlin |
|---|---|---|
| Mental Health Not Good | 17.5% | 15.9% |
| Physical Health Not Good | 11.0% | 9.9% |
| Depression | 27.6% | 23.8% |
| Smoking | 17.7% | 14.6% |
| Binge Drinking | 16.7% | 19.5% |
| Obesity | 32.5% | 28.0% |
| Disability Percentage | 11.0% | 13.0% |
Health Statistics Comparison: White house vs Berlin
- More residents in White house report poor mental health at 17.5% compared to 15.9% in Berlin.
- Depression is more prevalent in White house at 27.6% compared to 23.8% in Berlin.
- Smoking is more prevalent in White house at 17.7% compared to 14.6% in Berlin.
- More residents engage in binge drinking in Berlin at 19.5% compared to 16.7% in White house.
- Obesity rates are higher in White house at 32.5% compared to 28.0% in Berlin.
- There is a higher percentage of disabled individuals in Berlin at 13.0% 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 | Berlin |
|---|---|---|
| No Schooling | 0.2% (30) | 0.4% (27) |
| High School Diploma | 18.0% (2,617) | 17.0% (1,279) |
| Less than High School | 12.4% (1,794) | 8.2% (612) |
| Bachelor's Degree and Higher | 15.4% (2,235) | 22.7% (1,706) |
Education Levels Comparison: White house vs Berlin
- In Berlin, a larger percentage of residents lack formal schooling at 0.4% compared to 0.2% in White house.
- A higher percentage of residents in White house hold a high school diploma at 18.0% compared to 17.0% in Berlin.
- More residents in White house have less than a high school education at 12.4% compared to 8.2% in Berlin.
- In Berlin, a larger share of residents have a bachelor's degree or higher at 22.7% compared to 15.4% in White house.
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.