Demographics details for Mount olive, MS vs Banning, CA
Population Overview
Compare main population characteristics in Mount olive, MS vs Banning, CA.
| Data | Mount olive | Banning |
|---|---|---|
| Population | 878 | 30,683 |
| Median Age | 31.7 years | 42.8 years |
| Median Income | $53,947 | $54,083 |
| Married Families | 49.0% | 35.0% |
| Poverty Level | 18% | 14% |
| Unemployment Rate | 6.5 | 6.5 |
Population Comparison: Mount olive vs Banning
- The population in Banning is higher at 30,683, compared to 878 in Mount olive.
- The median age in Banning is higher at 42.8 years, compared to 31.7 years in Mount olive.
- Banning has a higher median income of $54,083, compared to $53,947 in Mount olive.
- A higher percentage of married families is found in Mount olive at 49.0% compared to 35.0% in Banning.
- Mount olive has a higher poverty level at 18% compared to 14% in Banning.
- The unemployment rate is the same in both Mount olive and Banning at 6.5%.
Demographics
Demographics Mount olive vs Banning provide insight into the diversity of the communities to compare.
| Demographic | Mount olive | Banning |
|---|---|---|
| Black | 120 | 7 |
| White | 145 | 21 |
| Asian | 2 | 5 |
| Hispanic | Data is updating | 48 |
| Two or More Races | Data is updating | 17 |
| American Indian | Data is updating | 2 |
Demographics Comparison: Mount olive vs Banning
- A higher percentage of Black residents are in Mount olive at 120% compared to 7% in Banning.
- Mount olive has a higher percentage of White residents at 145% compared to 21% in Banning.
- In Banning, the Asian population stands at 5%, greater than 2% in Mount olive.
- Banning has a higher percentage of Hispanic residents at 48%, compared to 0% in Mount olive.
- The percentage of residents identifying as two or more races is higher in Banning at 17%, compared to 0% in Mount olive.
- In Banning, the percentage of American Indian residents is higher at 2%, compared to 0% in Mount olive.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Mount olive | Banning |
|---|---|---|
| Mental Health Not Good | 17.8% | 18.1% |
| Physical Health Not Good | 13.3% | 13.9% |
| Depression | 21.5% | 18.5% |
| Smoking | 21.3% | 17.2% |
| Binge Drinking | 13.0% | 15.2% |
| Obesity | 43.6% | 39.1% |
| Disability Percentage | 27.0% | 20.0% |
Health Statistics Comparison: Mount olive vs Banning
- In Banning, a higher percentage report poor mental health at 18.1% compared to 17.8% in Mount olive.
- Depression is more prevalent in Mount olive at 21.5% compared to 18.5% in Banning.
- Smoking is more prevalent in Mount olive at 21.3% compared to 17.2% in Banning.
- More residents engage in binge drinking in Banning at 15.2% compared to 13.0% in Mount olive.
- Obesity rates are higher in Mount olive at 43.6% compared to 39.1% in Banning.
- Disability percentages are higher in Mount olive at 27.0% compared to 20.0% in Banning.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Mount olive | Banning |
|---|---|---|
| No Schooling | 2.3% (20) | 2.4% (749) |
| High School Diploma | 23.9% (210) | 18.4% (5,655) |
| Less than High School | 14.9% (131) | 21.9% (6,720) |
| Bachelor's Degree and Higher | 13.0% (114) | 11.4% (3,495) |
Education Levels Comparison: Mount olive vs Banning
- In Banning, a larger percentage of residents lack formal schooling at 2.4% compared to 2.3% in Mount olive.
- A higher percentage of residents in Mount olive hold a high school diploma at 23.9% compared to 18.4% in Banning.
- The percentage of residents with less than a high school education is higher in Banning at 21.9%, compared to 14.9% in Mount olive.
- A higher percentage of residents in Mount olive hold a bachelor's degree or higher at 13.0% compared to 11.4% in Banning.
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.