Demographics details for Washington, IN vs Everest, KS
Population Overview
Compare main population characteristics in Washington, IN vs Everest, KS.
| Data | Washington | Everest |
|---|---|---|
| Population | 12,171 | 258 |
| Median Age | 37.0 years | 34.5 years |
| Median Income | $48,255 | $44,375 |
| Married Families | 38.0% | 50.0% |
| Poverty Level | 12% | 11% |
| Unemployment Rate | 3.2 | 3.5 |
Population Comparison: Washington vs Everest
- In Washington, the population is higher at 12,171, compared to 258 in Everest.
- Residents in Washington have a higher median age of 37.0 years compared to 34.5 years in Everest.
- Washington has a higher median income of $48,255 compared to $44,375 in Everest.
- In Everest, the percentage of married families is higher at 50.0%, compared to 38.0% in Washington.
- Washington has a higher poverty level at 12% compared to 11% in Everest.
- Everest has a higher unemployment rate at 3.5% compared to 3.2% in Washington.
Demographics
Demographics Washington vs Everest provide insight into the diversity of the communities to compare.
| Demographic | Washington | Everest |
|---|---|---|
| Black | 4 | 2 |
| White | 76 | 90 |
| Asian | Data is updating | Data is updating |
| Hispanic | 12 | Data is updating |
| Two or More Races | 8 | 6 |
| American Indian | Data is updating | 2 |
Demographics Comparison: Washington vs Everest
- A higher percentage of Black residents are in Washington at 4% compared to 2% in Everest.
- The percentage of White residents is higher in Everest at 90% compared to 76% in Washington.
- Both Washington and Everest have the same percentage of Asian residents at 0%.
- The Hispanic community is larger in Washington at 12% compared to 0% in Everest.
- More residents identify as two or more races in Washington at 8% compared to 6% in Everest.
- In Everest, the percentage of American Indian residents is higher at 2%, compared to 0% in Washington.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Washington | Everest |
|---|---|---|
| Mental Health Not Good | 18.7% | 17.3% |
| Physical Health Not Good | 13.5% | 11.2% |
| Depression | 27.6% | 22.4% |
| Smoking | 23.3% | 20.4% |
| Binge Drinking | 16.3% | 19.1% |
| Obesity | 36.4% | 37.8% |
| Disability Percentage | 16.0% | 50.0% |
Health Statistics Comparison: Washington vs Everest
- More residents in Washington report poor mental health at 18.7% compared to 17.3% in Everest.
- Depression is more prevalent in Washington at 27.6% compared to 22.4% in Everest.
- Smoking is more prevalent in Washington at 23.3% compared to 20.4% in Everest.
- More residents engage in binge drinking in Everest at 19.1% compared to 16.3% in Washington.
- Everest has higher obesity rates at 37.8% compared to 36.4% in Washington.
- There is a higher percentage of disabled individuals in Everest at 50.0% compared to 16.0% in Washington.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Washington | Everest |
|---|---|---|
| No Schooling | 1.3% (163) | 0.0% (Data is updating) |
| High School Diploma | 22.8% (2,771) | 26.4% (68) |
| Less than High School | 20.2% (2,460) | 17.8% (46) |
| Bachelor's Degree and Higher | 9.3% (1,129) | 36.8% (95) |
Education Levels Comparison: Washington vs Everest
- A higher percentage of residents in Washington have no formal schooling at 1.3% compared to 0.0% in Everest.
- In Everest, the rate of residents with high school diplomas is higher at 26.4% compared to 22.8% in Washington.
- More residents in Washington have less than a high school education at 20.2% compared to 17.8% in Everest.
- In Everest, a larger share of residents have a bachelor's degree or higher at 36.8% compared to 9.3% in Washington.
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.