Demographics details for Marietta, GA vs White swan, WA
Population Overview
Compare main population characteristics in Marietta, GA vs White swan, WA.
| Data | Marietta | White swan |
|---|---|---|
| Population | 62,602 | 561 |
| Median Age | 35.2 years | 24.5 years |
| Median Income | $67,589 | $51,667 |
| Married Families | 31.0% | 13.0% |
| Poverty Level | 11% | 12% |
| Unemployment Rate | 3.5 | 8.2 |
Population Comparison: Marietta vs White swan
- In Marietta, the population is higher at 62,602, compared to 561 in White swan.
- Residents in Marietta have a higher median age of 35.2 years compared to 24.5 years in White swan.
- Marietta has a higher median income of $67,589 compared to $51,667 in White swan.
- A higher percentage of married families is found in Marietta at 31.0% compared to 13.0% in White swan.
- The poverty level is higher in White swan at 12%, compared to 11% in Marietta.
- White swan has a higher unemployment rate at 8.2% compared to 3.5% in Marietta.
Demographics
Demographics Marietta vs White swan provide insight into the diversity of the communities to compare.
| Demographic | Marietta | White swan |
|---|---|---|
| Black | 30 | Data is updating |
| White | 41 | -6 |
| Asian | 2 | Data is updating |
| Hispanic | 18 | 26 |
| Two or More Races | 8 | 10 |
| American Indian | 1 | 70 |
Demographics Comparison: Marietta vs White swan
- A higher percentage of Black residents are in Marietta at 30% compared to 0% in White swan.
- Marietta has a higher percentage of White residents at 41% compared to -6% in White swan.
- The Asian population is larger in Marietta at 2% compared to 0% in White swan.
- White swan has a higher percentage of Hispanic residents at 26%, compared to 18% in Marietta.
- The percentage of residents identifying as two or more races is higher in White swan at 10%, compared to 8% in Marietta.
- In White swan, the percentage of American Indian residents is higher at 70%, compared to 1% in Marietta.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Marietta | White swan |
|---|---|---|
| Mental Health Not Good | 15.1% | 22.0% |
| Physical Health Not Good | 11.1% | 18.1% |
| Depression | 18.1% | 24.7% |
| Smoking | 14.5% | 26.0% |
| Binge Drinking | 14.5% | 15.8% |
| Obesity | 32.3% | 43.8% |
| Disability Percentage | 9.0% | 21.0% |
Health Statistics Comparison: Marietta vs White swan
- In White swan, a higher percentage report poor mental health at 22.0% compared to 15.1% in Marietta.
- Higher depression rates are seen in White swan at 24.7% versus 18.1% in Marietta.
- White swan has a higher smoking rate at 26.0% compared to 14.5% in Marietta.
- More residents engage in binge drinking in White swan at 15.8% compared to 14.5% in Marietta.
- White swan has higher obesity rates at 43.8% compared to 32.3% in Marietta.
- There is a higher percentage of disabled individuals in White swan at 21.0% compared to 9.0% in Marietta.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Marietta | White swan |
|---|---|---|
| No Schooling | 1.8% (1,148) | 0.0% (Data is updating) |
| High School Diploma | 10.0% (6,250) | 16.4% (92) |
| Less than High School | 13.1% (8,224) | 24.8% (139) |
| Bachelor's Degree and Higher | 29.9% (18,706) | 0.9% (5) |
Education Levels Comparison: Marietta vs White swan
- A higher percentage of residents in Marietta have no formal schooling at 1.8% compared to 0.0% in White swan.
- In White swan, the rate of residents with high school diplomas is higher at 16.4% compared to 10.0% in Marietta.
- The percentage of residents with less than a high school education is higher in White swan at 24.8%, compared to 13.1% in Marietta.
- A higher percentage of residents in Marietta hold a bachelor's degree or higher at 29.9% compared to 0.9% in White swan.
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.