Demographics details for Mountain view, AR vs Berlin, NJ
Population Overview
Compare main population characteristics in Mountain view, AR vs Berlin, NJ.
| Data | Mountain view | Berlin |
|---|---|---|
| Population | 2,915 | 7,506 |
| Median Age | 55.5 years | 40.4 years |
| Median Income | $23,458 | $98,706 |
| Married Families | 25.0% | 37.0% |
| Poverty Level | 17% | 5% |
| Unemployment Rate | 4.8 | 3.2 |
Population Comparison: Mountain view vs Berlin
- The population in Berlin is higher at 7,506, compared to 2,915 in Mountain view.
- Residents in Mountain view have a higher median age of 55.5 years compared to 40.4 years in Berlin.
- Berlin has a higher median income of $98,706, compared to $23,458 in Mountain view.
- In Berlin, the percentage of married families is higher at 37.0%, compared to 25.0% in Mountain view.
- Mountain view has a higher poverty level at 17% compared to 5% in Berlin.
- The unemployment rate in Mountain view is higher at 4.8%, compared to 3.2% in Berlin.
Demographics
Demographics Mountain view vs Berlin provide insight into the diversity of the communities to compare.
| Demographic | Mountain view | Berlin |
|---|---|---|
| Black | 1 | 12 |
| White | 89 | 76 |
| Asian | 1 | 1 |
| Hispanic | 8 | 5 |
| Two or More Races | 1 | 6 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Mountain view vs Berlin
- In Berlin, the percentage of Black residents is higher at 12% compared to 1% in Mountain view.
- Mountain view has a higher percentage of White residents at 89% compared to 76% in Berlin.
- Both Mountain view and Berlin have the same percentage of Asian residents at 1%.
- The Hispanic community is larger in Mountain view at 8% compared to 5% in Berlin.
- The percentage of residents identifying as two or more races is higher in Berlin at 6%, compared to 1% in Mountain view.
- The percentage of American Indian residents is the same in both Mountain view and Berlin at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Mountain view | Berlin |
|---|---|---|
| Mental Health Not Good | 22.6% | 15.9% |
| Physical Health Not Good | 16.7% | 9.9% |
| Depression | 31.9% | 23.8% |
| Smoking | 26.6% | 14.6% |
| Binge Drinking | 14.9% | 19.5% |
| Obesity | 41.1% | 28.0% |
| Disability Percentage | 36.0% | 13.0% |
Health Statistics Comparison: Mountain view vs Berlin
- More residents in Mountain view report poor mental health at 22.6% compared to 15.9% in Berlin.
- Depression is more prevalent in Mountain view at 31.9% compared to 23.8% in Berlin.
- Smoking is more prevalent in Mountain view at 26.6% compared to 14.6% in Berlin.
- More residents engage in binge drinking in Berlin at 19.5% compared to 14.9% in Mountain view.
- Obesity rates are higher in Mountain view at 41.1% compared to 28.0% in Berlin.
- Disability percentages are higher in Mountain view at 36.0% compared to 13.0% in Berlin.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Mountain view | Berlin |
|---|---|---|
| No Schooling | 2.4% (70) | 0.4% (27) |
| High School Diploma | 17.8% (520) | 17.0% (1,279) |
| Less than High School | 15.9% (464) | 8.2% (612) |
| Bachelor's Degree and Higher | 11.3% (329) | 22.7% (1,706) |
Education Levels Comparison: Mountain view vs Berlin
- A higher percentage of residents in Mountain view have no formal schooling at 2.4% compared to 0.4% in Berlin.
- A higher percentage of residents in Mountain view hold a high school diploma at 17.8% compared to 17.0% in Berlin.
- More residents in Mountain view have less than a high school education at 15.9% 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 11.3% in Mountain view.
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.