Demographics details for Dayton, OH vs Mount olive, MS
Population Overview
Compare main population characteristics in Dayton, OH vs Mount olive, MS.
| Data | Dayton | Mount olive |
|---|---|---|
| Population | 135,944 | 878 |
| Median Age | 34.0 years | 31.7 years |
| Median Income | $41,443 | $53,947 |
| Married Families | 21.0% | 49.0% |
| Poverty Level | 18% | 18% |
| Unemployment Rate | 6.8 | 6.5 |
Population Comparison: Dayton vs Mount olive
- In Dayton, the population is higher at 135,944, compared to 878 in Mount olive.
- Residents in Dayton have a higher median age of 34.0 years compared to 31.7 years in Mount olive.
- Mount olive has a higher median income of $53,947, compared to $41,443 in Dayton.
- In Mount olive, the percentage of married families is higher at 49.0%, compared to 21.0% in Dayton.
- The poverty level is identical in both Dayton and Mount olive at 18%.
- The unemployment rate in Dayton is higher at 6.8%, compared to 6.5% in Mount olive.
Demographics
Demographics Dayton vs Mount olive provide insight into the diversity of the communities to compare.
| Demographic | Dayton | Mount olive |
|---|---|---|
| Black | 38 | 120 |
| White | 50 | 145 |
| Asian | 1 | 2 |
| Hispanic | 5 | Data is updating |
| Two or More Races | 6 | Data is updating |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Dayton vs Mount olive
- In Mount olive, the percentage of Black residents is higher at 120% compared to 38% in Dayton.
- The percentage of White residents is higher in Mount olive at 145% compared to 50% in Dayton.
- In Mount olive, the Asian population stands at 2%, greater than 1% in Dayton.
- The Hispanic community is larger in Dayton at 5% compared to 0% in Mount olive.
- More residents identify as two or more races in Dayton at 6% compared to 0% in Mount olive.
- The percentage of American Indian residents is the same in both Dayton and Mount olive at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Dayton | Mount olive |
|---|---|---|
| Mental Health Not Good | 21.9% | 17.8% |
| Physical Health Not Good | 16.5% | 13.3% |
| Depression | 26.5% | 21.5% |
| Smoking | 26.0% | 21.3% |
| Binge Drinking | 15.2% | 13.0% |
| Obesity | 47.6% | 43.6% |
| Disability Percentage | 18.0% | 27.0% |
Health Statistics Comparison: Dayton vs Mount olive
- More residents in Dayton report poor mental health at 21.9% compared to 17.8% in Mount olive.
- Depression is more prevalent in Dayton at 26.5% compared to 21.5% in Mount olive.
- Smoking is more prevalent in Dayton at 26.0% compared to 21.3% in Mount olive.
- Binge drinking is more common in Dayton at 15.2% compared to 13.0% in Mount olive.
- Obesity rates are higher in Dayton at 47.6% compared to 43.6% in Mount olive.
- There is a higher percentage of disabled individuals in Mount olive at 27.0% compared to 18.0% in Dayton.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Dayton | Mount olive |
|---|---|---|
| No Schooling | 0.9% (1,157) | 2.3% (20) |
| High School Diploma | 16.3% (22,101) | 23.9% (210) |
| Less than High School | 13.9% (18,900) | 14.9% (131) |
| Bachelor's Degree and Higher | 12.7% (17,260) | 13.0% (114) |
Education Levels Comparison: Dayton vs Mount olive
- In Mount olive, a larger percentage of residents lack formal schooling at 2.3% compared to 0.9% in Dayton.
- In Mount olive, the rate of residents with high school diplomas is higher at 23.9% compared to 16.3% in Dayton.
- The percentage of residents with less than a high school education is higher in Mount olive at 14.9%, compared to 13.9% in Dayton.
- In Mount olive, a larger share of residents have a bachelor's degree or higher at 13.0% compared to 12.7% in Dayton.
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.