Demographics details for Everest, KS vs Santa clarita, CA
Population Overview
Compare main population characteristics in Everest, KS vs Santa clarita, CA.
| Data | Everest | Santa clarita |
|---|---|---|
| Population | 258 | 221,345 |
| Median Age | 34.5 years | 37.3 years |
| Median Income | $44,375 | $116,186 |
| Married Families | 50.0% | 43.0% |
| Poverty Level | 11% | 8% |
| Unemployment Rate | 3.5 | 5.7 |
Population Comparison: Everest vs Santa clarita
- The population in Santa clarita is higher at 221,345, compared to 258 in Everest.
- The median age in Santa clarita is higher at 37.3 years, compared to 34.5 years in Everest.
- Santa clarita has a higher median income of $116,186, compared to $44,375 in Everest.
- A higher percentage of married families is found in Everest at 50.0% compared to 43.0% in Santa clarita.
- Everest has a higher poverty level at 11% compared to 8% in Santa clarita.
- Santa clarita has a higher unemployment rate at 5.7% compared to 3.5% in Everest.
Demographics
Demographics Everest vs Santa clarita provide insight into the diversity of the communities to compare.
| Demographic | Everest | Santa clarita |
|---|---|---|
| Black | 2 | 4 |
| White | 90 | 30 |
| Asian | Data is updating | 11 |
| Hispanic | Data is updating | 37 |
| Two or More Races | 6 | 17 |
| American Indian | 2 | 1 |
Demographics Comparison: Everest vs Santa clarita
- In Santa clarita, the percentage of Black residents is higher at 4% compared to 2% in Everest.
- Everest has a higher percentage of White residents at 90% compared to 30% in Santa clarita.
- In Santa clarita, the Asian population stands at 11%, greater than 0% in Everest.
- Santa clarita has a higher percentage of Hispanic residents at 37%, compared to 0% in Everest.
- The percentage of residents identifying as two or more races is higher in Santa clarita at 17%, compared to 6% in Everest.
- A greater percentage of American Indian residents live in Everest at 2% compared to 1% in Santa clarita.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Everest | Santa clarita |
|---|---|---|
| Mental Health Not Good | 17.3% | 14.7% |
| Physical Health Not Good | 11.2% | 9.6% |
| Depression | 22.4% | 16.8% |
| Smoking | 20.4% | 9.7% |
| Binge Drinking | 19.1% | 17.1% |
| Obesity | 37.8% | 26.2% |
| Disability Percentage | 50.0% | 10.0% |
Health Statistics Comparison: Everest vs Santa clarita
- More residents in Everest report poor mental health at 17.3% compared to 14.7% in Santa clarita.
- Depression is more prevalent in Everest at 22.4% compared to 16.8% in Santa clarita.
- Smoking is more prevalent in Everest at 20.4% compared to 9.7% in Santa clarita.
- Binge drinking is more common in Everest at 19.1% compared to 17.1% in Santa clarita.
- Obesity rates are higher in Everest at 37.8% compared to 26.2% in Santa clarita.
- Disability percentages are higher in Everest at 50.0% compared to 10.0% in Santa clarita.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Everest | Santa clarita |
|---|---|---|
| No Schooling | 0.0% (Data is updating) | 1.4% (3,097) |
| High School Diploma | 26.4% (68) | 10.7% (23,725) |
| Less than High School | 17.8% (46) | 11.7% (25,882) |
| Bachelor's Degree and Higher | 36.8% (95) | 26.1% (57,684) |
Education Levels Comparison: Everest vs Santa clarita
- In Santa clarita, a larger percentage of residents lack formal schooling at 1.4% compared to 0.0% in Everest.
- A higher percentage of residents in Everest hold a high school diploma at 26.4% compared to 10.7% in Santa clarita.
- More residents in Everest have less than a high school education at 17.8% compared to 11.7% in Santa clarita.
- A higher percentage of residents in Everest hold a bachelor's degree or higher at 36.8% compared to 26.1% in Santa clarita.
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.