Demographics details for Berlin, NJ vs Seneca, MO
Population Overview
Compare main population characteristics in Berlin, NJ vs Seneca, MO.
| Data | Berlin | Seneca |
|---|---|---|
| Population | 7,506 | 2,284 |
| Median Age | 40.4 years | 35.3 years |
| Median Income | $98,706 | $42,279 |
| Married Families | 37.0% | 37.0% |
| Poverty Level | 5% | Data is updating |
| Unemployment Rate | 3.2 | 3.1 |
Population Comparison: Berlin vs Seneca
- In Berlin, the population is higher at 7,506, compared to 2,284 in Seneca.
- Residents in Berlin have a higher median age of 40.4 years compared to 35.3 years in Seneca.
- Berlin has a higher median income of $98,706 compared to $42,279 in Seneca.
- The percentage of married families is the same in both Berlin and Seneca at 37.0%.
- Berlin has a higher poverty level at 5% compared to 0% in Seneca.
- The unemployment rate in Berlin is higher at 3.2%, compared to 3.1% in Seneca.
Demographics
Demographics Berlin vs Seneca provide insight into the diversity of the communities to compare.
| Demographic | Berlin | Seneca |
|---|---|---|
| Black | 12 | Data is updating |
| White | 76 | 87 |
| Asian | 1 | Data is updating |
| Hispanic | 5 | 3 |
| Two or More Races | 6 | 7 |
| American Indian | Data is updating | 3 |
Demographics Comparison: Berlin vs Seneca
- A higher percentage of Black residents are in Berlin at 12% compared to 0% in Seneca.
- The percentage of White residents is higher in Seneca at 87% compared to 76% in Berlin.
- The Asian population is larger in Berlin at 1% compared to 0% in Seneca.
- The Hispanic community is larger in Berlin at 5% compared to 3% in Seneca.
- The percentage of residents identifying as two or more races is higher in Seneca at 7%, compared to 6% in Berlin.
- In Seneca, the percentage of American Indian residents is higher at 3%, compared to 0% in Berlin.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Berlin | Seneca |
|---|---|---|
| Mental Health Not Good | 15.9% | 19.3% |
| Physical Health Not Good | 9.9% | 14.1% |
| Depression | 23.8% | 27.1% |
| Smoking | 14.6% | 24.5% |
| Binge Drinking | 19.5% | 16.7% |
| Obesity | 28.0% | 42.3% |
| Disability Percentage | 13.0% | 20.0% |
Health Statistics Comparison: Berlin vs Seneca
- In Seneca, a higher percentage report poor mental health at 19.3% compared to 15.9% in Berlin.
- Higher depression rates are seen in Seneca at 27.1% versus 23.8% in Berlin.
- Seneca has a higher smoking rate at 24.5% compared to 14.6% in Berlin.
- Binge drinking is more common in Berlin at 19.5% compared to 16.7% in Seneca.
- Seneca has higher obesity rates at 42.3% compared to 28.0% in Berlin.
- There is a higher percentage of disabled individuals in Seneca at 20.0% 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 | Berlin | Seneca |
|---|---|---|
| No Schooling | 0.4% (27) | 0.1% (3) |
| High School Diploma | 17.0% (1,279) | 18.0% (411) |
| Less than High School | 8.2% (612) | 14.9% (340) |
| Bachelor's Degree and Higher | 22.7% (1,706) | 7.4% (170) |
Education Levels Comparison: Berlin vs Seneca
- A higher percentage of residents in Berlin have no formal schooling at 0.4% compared to 0.1% in Seneca.
- In Seneca, the rate of residents with high school diplomas is higher at 18.0% compared to 17.0% in Berlin.
- The percentage of residents with less than a high school education is higher in Seneca at 14.9%, compared to 8.2% in Berlin.
- A higher percentage of residents in Berlin hold a bachelor's degree or higher at 22.7% compared to 7.4% in Seneca.
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.