Demographics details for Oxford, MS vs Cornelia, GA
Population Overview
Compare main population characteristics in Oxford, MS vs Cornelia, GA.
Data | Oxford | Cornelia |
---|---|---|
Population | 26,437 | 5,004 |
Median Age | 27.7 years | 30.4 years |
Median Income | $56,784 | $46,211 |
Married Families | 28.0% | 32.0% |
Poverty Level | 18% | 12% |
Unemployment Rate | 2.7 | 3.5 |
Population Comparison: Oxford vs Cornelia
- In Oxford, the population is higher at 26,437, compared to 5,004 in Cornelia.
- The median age in Cornelia is higher at 30.4 years, compared to 27.7 years in Oxford.
- Oxford has a higher median income of $56,784 compared to $46,211 in Cornelia.
- In Cornelia, the percentage of married families is higher at 32.0%, compared to 28.0% in Oxford.
- Oxford has a higher poverty level at 18% compared to 12% in Cornelia.
- Cornelia has a higher unemployment rate at 3.5% compared to 2.7% in Oxford.
Demographics
Demographics Oxford vs Cornelia provide insight into the diversity of the communities to compare.
Demographic | Oxford | Cornelia |
---|---|---|
Black | 25 | 9 |
White | 68 | 43 |
Asian | 3 | 3 |
Hispanic | 2 | 32 |
Two or More Races | 2 | 13 |
American Indian | Data is updating | Data is updating |
Demographics Comparison: Oxford vs Cornelia
- A higher percentage of Black residents are in Oxford at 25% compared to 9% in Cornelia.
- Oxford has a higher percentage of White residents at 68% compared to 43% in Cornelia.
- Both Oxford and Cornelia have the same percentage of Asian residents at 3%.
- Cornelia has a higher percentage of Hispanic residents at 32%, compared to 2% in Oxford.
- The percentage of residents identifying as two or more races is higher in Cornelia at 13%, compared to 2% in Oxford.
- The percentage of American Indian residents is the same in both Oxford and Cornelia at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
Health Metric | Oxford | Cornelia |
---|---|---|
Mental Health Not Good | 15.1% | 18.2% |
Physical Health Not Good | 10.6% | 14.7% |
Depression | 21.3% | 22.4% |
Smoking | 15.2% | 20.2% |
Binge Drinking | 14.9% | 14.4% |
Obesity | 35.0% | 34.6% |
Disability Percentage | 8.0% | 13.0% |
Health Statistics Comparison: Oxford vs Cornelia
- In Cornelia, a higher percentage report poor mental health at 18.2% compared to 15.1% in Oxford.
- Higher depression rates are seen in Cornelia at 22.4% versus 21.3% in Oxford.
- Cornelia has a higher smoking rate at 20.2% compared to 15.2% in Oxford.
- Binge drinking is more common in Oxford at 14.9% compared to 14.4% in Cornelia.
- Obesity rates are higher in Oxford at 35.0% compared to 34.6% in Cornelia.
- There is a higher percentage of disabled individuals in Cornelia at 13.0% compared to 8.0% in Oxford.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
Education Level | Oxford | Cornelia |
---|---|---|
No Schooling | 0.4% (114) | 3.6% (179) |
High School Diploma | 7.0% (1,862) | 9.5% (473) |
Less than High School | 5.5% (1,444) | 35.8% (1,790) |
Bachelor's Degree and Higher | 33.0% (8,735) | 12.5% (625) |
Education Levels Comparison: Oxford vs Cornelia
- In Cornelia, a larger percentage of residents lack formal schooling at 3.6% compared to 0.4% in Oxford.
- In Cornelia, the rate of residents with high school diplomas is higher at 9.5% compared to 7.0% in Oxford.
- The percentage of residents with less than a high school education is higher in Cornelia at 35.8%, compared to 5.5% in Oxford.
- A higher percentage of residents in Oxford hold a bachelor's degree or higher at 33.0% compared to 12.5% in Cornelia.
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.