Demographics details for Marshall, CA vs Swanton, OH
Population Overview
Compare main population characteristics in Marshall, CA vs Swanton, OH.
| Data | Marshall | Swanton |
|---|---|---|
| Population | 533 | 3,861 |
| Median Age | 42.0 years | 39.1 years |
| Median Income | $90,000 | $67,367 |
| Married Families | 60.0% | 38.0% |
| Poverty Level | 5% | 8% |
| Unemployment Rate | 3.0 | 3.5 |
Population Comparison: Marshall vs Swanton
- The population in Swanton is higher at 3,861, compared to 533 in Marshall.
- Residents in Marshall have a higher median age of 42.0 years compared to 39.1 years in Swanton.
- Marshall has a higher median income of $90,000 compared to $67,367 in Swanton.
- A higher percentage of married families is found in Marshall at 60.0% compared to 38.0% in Swanton.
- The poverty level is higher in Swanton at 8%, compared to 5% in Marshall.
- Swanton has a higher unemployment rate at 3.5% compared to 3.0% in Marshall.
Demographics
Demographics Marshall vs Swanton provide insight into the diversity of the communities to compare.
| Demographic | Marshall | Swanton |
|---|---|---|
| Black | Data is updating | Data is updating |
| White | 90 | 90 |
| Asian | 2 | 3 |
| Hispanic | 5 | 4 |
| Two or More Races | 3 | 3 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Marshall vs Swanton
- The percentage of Black residents is the same in both Marshall and Swanton at 0%.
- The percentage of White residents is the same in both Marshall and Swanton at 90%.
- In Swanton, the Asian population stands at 3%, greater than 2% in Marshall.
- The Hispanic community is larger in Marshall at 5% compared to 4% in Swanton.
- Both Marshall and Swanton have the same percentage of residents identifying as two or more races at 3%.
- The percentage of American Indian residents is the same in both Marshall and Swanton at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Marshall | Swanton |
|---|---|---|
| Mental Health Not Good | Data is updating% | 16.8% |
| Physical Health Not Good | Data is updating% | 10.7% |
| Depression | Data is updating% | 23.9% |
| Smoking | Data is updating% | 18.4% |
| Binge Drinking | Data is updating% | 18.4% |
| Obesity | Data is updating% | 40.2% |
| Disability Percentage | Data is updating% | 16.0% |
Health Statistics Comparison: Marshall vs Swanton
- In Swanton, a higher percentage report poor mental health at 16.8% compared to 0.0% in Marshall.
- Higher depression rates are seen in Swanton at 23.9% versus 0.0% in Marshall.
- Swanton has a higher smoking rate at 18.4% compared to 0.0% in Marshall.
- More residents engage in binge drinking in Swanton at 18.4% compared to 0.0% in Marshall.
- Swanton has higher obesity rates at 40.2% compared to 0.0% in Marshall.
- There is a higher percentage of disabled individuals in Swanton at 16.0% compared to 0.0% in Marshall.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Marshall | Swanton |
|---|---|---|
| No Schooling | 0.0% (Data is updating) | 0.5% (18) |
| High School Diploma | 0.0% (Data is updating) | 22.8% (880) |
| Less than High School | 0.0% (Data is updating) | 12.4% (480) |
| Bachelor's Degree and Higher | 0.0% (Data is updating) | 12.4% (480) |
Education Levels Comparison: Marshall vs Swanton
- In Swanton, a larger percentage of residents lack formal schooling at 0.5% compared to 0.0% in Marshall.
- In Swanton, the rate of residents with high school diplomas is higher at 22.8% compared to 0.0% in Marshall.
- The percentage of residents with less than a high school education is higher in Swanton at 12.4%, compared to 0.0% in Marshall.
- In Swanton, a larger share of residents have a bachelor's degree or higher at 12.4% compared to 0.0% in Marshall.
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.