Demographics details for Southold, NY vs Everest, KS
Population Overview
Compare main population characteristics in Southold, NY vs Everest, KS.
| Data | Southold | Everest |
|---|---|---|
| Population | 22,125 | 258 |
| Median Age | 47.0 years | 34.5 years |
| Median Income | $92,839 | $44,375 |
| Married Families | 65.0% | 50.0% |
| Poverty Level | 5% | 11% |
| Unemployment Rate | 3.0 | 3.5 |
Population Comparison: Southold vs Everest
- In Southold, the population is higher at 22,125, compared to 258 in Everest.
- Residents in Southold have a higher median age of 47.0 years compared to 34.5 years in Everest.
- Southold has a higher median income of $92,839 compared to $44,375 in Everest.
- A higher percentage of married families is found in Southold at 65.0% compared to 50.0% in Everest.
- The poverty level is higher in Everest at 11%, compared to 5% in Southold.
- Everest has a higher unemployment rate at 3.5% compared to 3.0% in Southold.
Demographics
Demographics Southold vs Everest provide insight into the diversity of the communities to compare.
| Demographic | Southold | Everest |
|---|---|---|
| Black | 2 | 2 |
| White | 90 | 90 |
| Asian | 1 | Data is updating |
| Hispanic | 5 | Data is updating |
| Two or More Races | 2 | 6 |
| American Indian | Data is updating | 2 |
Demographics Comparison: Southold vs Everest
- The percentage of Black residents is the same in both Southold and Everest at 2%.
- The percentage of White residents is the same in both Southold and Everest at 90%.
- The Asian population is larger in Southold at 1% compared to 0% in Everest.
- The Hispanic community is larger in Southold at 5% compared to 0% in Everest.
- The percentage of residents identifying as two or more races is higher in Everest at 6%, compared to 2% in Southold.
- In Everest, the percentage of American Indian residents is higher at 2%, compared to 0% in Southold.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Southold | Everest |
|---|---|---|
| Mental Health Not Good | Data is updating% | 17.3% |
| Physical Health Not Good | Data is updating% | 11.2% |
| Depression | Data is updating% | 22.4% |
| Smoking | Data is updating% | 20.4% |
| Binge Drinking | Data is updating% | 19.1% |
| Obesity | Data is updating% | 37.8% |
| Disability Percentage | Data is updating% | 50.0% |
Health Statistics Comparison: Southold vs Everest
- In Everest, a higher percentage report poor mental health at 17.3% compared to 0.0% in Southold.
- Higher depression rates are seen in Everest at 22.4% versus 0.0% in Southold.
- Everest has a higher smoking rate at 20.4% compared to 0.0% in Southold.
- More residents engage in binge drinking in Everest at 19.1% compared to 0.0% in Southold.
- Everest has higher obesity rates at 37.8% compared to 0.0% in Southold.
- There is a higher percentage of disabled individuals in Everest at 50.0% compared to 0.0% in Southold.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Southold | Everest |
|---|---|---|
| No Schooling | 0.0% (Data is updating) | 0.0% (Data is updating) |
| High School Diploma | 0.0% (Data is updating) | 26.4% (68) |
| Less than High School | 0.0% (Data is updating) | 17.8% (46) |
| Bachelor's Degree and Higher | 0.0% (Data is updating) | 36.8% (95) |
Education Levels Comparison: Southold vs Everest
- The percentage of residents with no formal schooling is the same in both Southold and Everest at 0.0%.
- In Everest, the rate of residents with high school diplomas is higher at 26.4% compared to 0.0% in Southold.
- The percentage of residents with less than a high school education is higher in Everest at 17.8%, compared to 0.0% in Southold.
- In Everest, a larger share of residents have a bachelor's degree or higher at 36.8% compared to 0.0% in Southold.
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.