Demographics details for Everest, KS vs Sanborn, NY
Population Overview
Compare main population characteristics in Everest, KS vs Sanborn, NY.
Data | Everest | Sanborn |
---|---|---|
Population | 258 | 1,499 |
Median Age | 34.5 years | 35.2 years |
Median Income | $44,375 | $75,109 |
Married Families | 50.0% | 34.0% |
Poverty Level | 11% | 9% |
Unemployment Rate | 3.5 | 4.5 |
Population Comparison: Everest vs Sanborn
- The population in Sanborn is higher at 1,499, compared to 258 in Everest.
- The median age in Sanborn is higher at 35.2 years, compared to 34.5 years in Everest.
- Sanborn has a higher median income of $75,109, compared to $44,375 in Everest.
- A higher percentage of married families is found in Everest at 50.0% compared to 34.0% in Sanborn.
- Everest has a higher poverty level at 11% compared to 9% in Sanborn.
- Sanborn has a higher unemployment rate at 4.5% compared to 3.5% in Everest.
Demographics
Demographics Everest vs Sanborn provide insight into the diversity of the communities to compare.
Demographic | Everest | Sanborn |
---|---|---|
Black | 2 | 1 |
White | 90 | 94 |
Asian | Data is updating | Data is updating |
Hispanic | Data is updating | 1 |
Two or More Races | 6 | 4 |
American Indian | 2 | Data is updating |
Demographics Comparison: Everest vs Sanborn
- A higher percentage of Black residents are in Everest at 2% compared to 1% in Sanborn.
- The percentage of White residents is higher in Sanborn at 94% compared to 90% in Everest.
- Both Everest and Sanborn have the same percentage of Asian residents at 0%.
- Sanborn 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 4% in Sanborn.
- A greater percentage of American Indian residents live in Everest at 2% compared to 0% in Sanborn.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
Health Metric | Everest | Sanborn |
---|---|---|
Mental Health Not Good | 17.3% | 15.5% |
Physical Health Not Good | 11.2% | 9.4% |
Depression | 22.4% | 24.9% |
Smoking | 20.4% | 17.7% |
Binge Drinking | 19.1% | 20.0% |
Obesity | 37.8% | 32.9% |
Disability Percentage | 50.0% | 9.0% |
Health Statistics Comparison: Everest vs Sanborn
- More residents in Everest report poor mental health at 17.3% compared to 15.5% in Sanborn.
- Higher depression rates are seen in Sanborn at 24.9% versus 22.4% in Everest.
- Smoking is more prevalent in Everest at 20.4% compared to 17.7% in Sanborn.
- More residents engage in binge drinking in Sanborn at 20.0% compared to 19.1% in Everest.
- Obesity rates are higher in Everest at 37.8% compared to 32.9% in Sanborn.
- Disability percentages are higher in Everest at 50.0% compared to 9.0% in Sanborn.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
Education Level | Everest | Sanborn |
---|---|---|
No Schooling | 0.0% (Data is updating) | 3.9% (58) |
High School Diploma | 26.4% (68) | 19.6% (294) |
Less than High School | 17.8% (46) | 16.0% (240) |
Bachelor's Degree and Higher | 36.8% (95) | 13.9% (209) |
Education Levels Comparison: Everest vs Sanborn
- In Sanborn, a larger percentage of residents lack formal schooling at 3.9% compared to 0.0% in Everest.
- A higher percentage of residents in Everest hold a high school diploma at 26.4% compared to 19.6% in Sanborn.
- More residents in Everest have less than a high school education at 17.8% compared to 16.0% in Sanborn.
- A higher percentage of residents in Everest hold a bachelor's degree or higher at 36.8% compared to 13.9% in Sanborn.
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.