Demographics details for Richland, MS vs Everest, KS
Population Overview
Compare main population characteristics in Richland, MS vs Everest, KS.
| Data | Richland | Everest |
|---|---|---|
| Population | 7,297 | 258 |
| Median Age | 37.1 years | 34.5 years |
| Median Income | $54,753 | $44,375 |
| Married Families | 40.0% | 50.0% |
| Poverty Level | 12% | 11% |
| Unemployment Rate | 4.2 | 3.5 |
Population Comparison: Richland vs Everest
- In Richland, the population is higher at 7,297, compared to 258 in Everest.
- Residents in Richland have a higher median age of 37.1 years compared to 34.5 years in Everest.
- Richland has a higher median income of $54,753 compared to $44,375 in Everest.
- In Everest, the percentage of married families is higher at 50.0%, compared to 40.0% in Richland.
- Richland has a higher poverty level at 12% compared to 11% in Everest.
- The unemployment rate in Richland is higher at 4.2%, compared to 3.5% in Everest.
Demographics
Demographics Richland vs Everest provide insight into the diversity of the communities to compare.
| Demographic | Richland | Everest |
|---|---|---|
| Black | 19 | 2 |
| White | 74 | 90 |
| Asian | 2 | Data is updating |
| Hispanic | 3 | Data is updating |
| Two or More Races | 2 | 6 |
| American Indian | Data is updating | 2 |
Demographics Comparison: Richland vs Everest
- A higher percentage of Black residents are in Richland at 19% compared to 2% in Everest.
- The percentage of White residents is higher in Everest at 90% compared to 74% in Richland.
- The Asian population is larger in Richland at 2% compared to 0% in Everest.
- The Hispanic community is larger in Richland at 3% 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 Richland.
- In Everest, the percentage of American Indian residents is higher at 2%, compared to 0% in Richland.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Richland | Everest |
|---|---|---|
| Mental Health Not Good | 16.9% | 17.3% |
| Physical Health Not Good | 11.7% | 11.2% |
| Depression | 23.4% | 22.4% |
| Smoking | 19.3% | 20.4% |
| Binge Drinking | 14.2% | 19.1% |
| Obesity | 37.4% | 37.8% |
| Disability Percentage | 13.0% | 50.0% |
Health Statistics Comparison: Richland vs Everest
- In Everest, a higher percentage report poor mental health at 17.3% compared to 16.9% in Richland.
- Depression is more prevalent in Richland at 23.4% compared to 22.4% in Everest.
- Everest has a higher smoking rate at 20.4% compared to 19.3% in Richland.
- More residents engage in binge drinking in Everest at 19.1% compared to 14.2% in Richland.
- Everest has higher obesity rates at 37.8% compared to 37.4% in Richland.
- There is a higher percentage of disabled individuals in Everest at 50.0% compared to 13.0% in Richland.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Richland | Everest |
|---|---|---|
| No Schooling | 1.7% (122) | 0.0% (Data is updating) |
| High School Diploma | 12.6% (916) | 26.4% (68) |
| Less than High School | 10.0% (732) | 17.8% (46) |
| Bachelor's Degree and Higher | 16.1% (1,175) | 36.8% (95) |
Education Levels Comparison: Richland vs Everest
- A higher percentage of residents in Richland have no formal schooling at 1.7% compared to 0.0% in Everest.
- In Everest, the rate of residents with high school diplomas is higher at 26.4% compared to 12.6% in Richland.
- The percentage of residents with less than a high school education is higher in Everest at 17.8%, compared to 10.0% in Richland.
- In Everest, a larger share of residents have a bachelor's degree or higher at 36.8% compared to 16.1% in Richland.
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.