Demographics details for Everest, KS vs Old forge, NY
Population Overview
Compare main population characteristics in Everest, KS vs Old forge, NY.
| Data | Everest | Old forge |
|---|---|---|
| Population | 258 | 756 |
| Median Age | 34.5 years | 45.0 years |
| Median Income | $44,375 | $60,000 |
| Married Families | 50.0% | 55.0% |
| Poverty Level | 11% | 12% |
| Unemployment Rate | 3.5 | 4.5 |
Population Comparison: Everest vs Old forge
- The population in Old forge is higher at 756, compared to 258 in Everest.
- The median age in Old forge is higher at 45.0 years, compared to 34.5 years in Everest.
- Old forge has a higher median income of $60,000, compared to $44,375 in Everest.
- In Old forge, the percentage of married families is higher at 55.0%, compared to 50.0% in Everest.
- The poverty level is higher in Old forge at 12%, compared to 11% in Everest.
- Old forge has a higher unemployment rate at 4.5% compared to 3.5% in Everest.
Demographics
Demographics Everest vs Old forge provide insight into the diversity of the communities to compare.
| Demographic | Everest | Old forge |
|---|---|---|
| Black | 2 | Data is updating |
| White | 90 | 98 |
| Asian | Data is updating | 1 |
| Hispanic | Data is updating | 1 |
| Two or More Races | 6 | Data is updating |
| American Indian | 2 | Data is updating |
Demographics Comparison: Everest vs Old forge
- A higher percentage of Black residents are in Everest at 2% compared to 0% in Old forge.
- The percentage of White residents is higher in Old forge at 98% compared to 90% in Everest.
- In Old forge, the Asian population stands at 1%, greater than 0% in Everest.
- Old forge has a higher percentage of Hispanic residents at 1%, compared to 0% in Everest.
- More residents identify as two or more races in Everest at 6% compared to 0% in Old forge.
- A greater percentage of American Indian residents live in Everest at 2% compared to 0% in Old forge.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Everest | Old forge |
|---|---|---|
| Mental Health Not Good | 17.3% | Data is updating% |
| Physical Health Not Good | 11.2% | Data is updating% |
| Depression | 22.4% | Data is updating% |
| Smoking | 20.4% | Data is updating% |
| Binge Drinking | 19.1% | Data is updating% |
| Obesity | 37.8% | Data is updating% |
| Disability Percentage | 50.0% | Data is updating% |
Health Statistics Comparison: Everest vs Old forge
- More residents in Everest report poor mental health at 17.3% compared to 0.0% in Old forge.
- Depression is more prevalent in Everest at 22.4% compared to 0.0% in Old forge.
- Smoking is more prevalent in Everest at 20.4% compared to 0.0% in Old forge.
- Binge drinking is more common in Everest at 19.1% compared to 0.0% in Old forge.
- Obesity rates are higher in Everest at 37.8% compared to 0.0% in Old forge.
- Disability percentages are higher in Everest at 50.0% compared to 0.0% in Old forge.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Everest | Old forge |
|---|---|---|
| No Schooling | 0.0% (Data is updating) | 0.0% (Data is updating) |
| High School Diploma | 26.4% (68) | 0.0% (Data is updating) |
| Less than High School | 17.8% (46) | 0.0% (Data is updating) |
| Bachelor's Degree and Higher | 36.8% (95) | 0.0% (Data is updating) |
Education Levels Comparison: Everest vs Old forge
- The percentage of residents with no formal schooling is the same in both Everest and Old forge at 0.0%.
- A higher percentage of residents in Everest hold a high school diploma at 26.4% compared to 0.0% in Old forge.
- More residents in Everest have less than a high school education at 17.8% compared to 0.0% in Old forge.
- A higher percentage of residents in Everest hold a bachelor's degree or higher at 36.8% compared to 0.0% in Old forge.
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.