Demographics details for Mobile, AL vs Oxford, NC
Population Overview
Compare main population characteristics in Mobile, AL vs Oxford, NC.
| Data | Mobile | Oxford |
|---|---|---|
| Population | 183,289 | 8,771 |
| Median Age | 37.6 years | 43.1 years |
| Median Income | $48,524 | $42,016 |
| Married Families | 30.0% | 29.0% |
| Poverty Level | 21% | 12% |
| Unemployment Rate | 3.9 | 4.1 |
Population Comparison: Mobile vs Oxford
- In Mobile, the population is higher at 183,289, compared to 8,771 in Oxford.
- The median age in Oxford is higher at 43.1 years, compared to 37.6 years in Mobile.
- Mobile has a higher median income of $48,524 compared to $42,016 in Oxford.
- A higher percentage of married families is found in Mobile at 30.0% compared to 29.0% in Oxford.
- Mobile has a higher poverty level at 21% compared to 12% in Oxford.
- Oxford has a higher unemployment rate at 4.1% compared to 3.9% in Mobile.
Demographics
Demographics Mobile vs Oxford provide insight into the diversity of the communities to compare.
| Demographic | Mobile | Oxford |
|---|---|---|
| Black | 54 | 55 |
| White | 38 | 31 |
| Asian | 2 | 1 |
| Hispanic | 3 | 6 |
| Two or More Races | 3 | 7 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Mobile vs Oxford
- In Oxford, the percentage of Black residents is higher at 55% compared to 54% in Mobile.
- Mobile has a higher percentage of White residents at 38% compared to 31% in Oxford.
- The Asian population is larger in Mobile at 2% compared to 1% in Oxford.
- Oxford has a higher percentage of Hispanic residents at 6%, compared to 3% in Mobile.
- The percentage of residents identifying as two or more races is higher in Oxford at 7%, compared to 3% in Mobile.
- The percentage of American Indian residents is the same in both Mobile and Oxford at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Mobile | Oxford |
|---|---|---|
| Mental Health Not Good | 19.3% | 17.7% |
| Physical Health Not Good | 13.5% | 13.3% |
| Depression | 21.7% | 22.8% |
| Smoking | 18.6% | 20.8% |
| Binge Drinking | 15.1% | 14.8% |
| Obesity | 42.0% | 45.0% |
| Disability Percentage | 13.0% | 15.0% |
Health Statistics Comparison: Mobile vs Oxford
- More residents in Mobile report poor mental health at 19.3% compared to 17.7% in Oxford.
- Higher depression rates are seen in Oxford at 22.8% versus 21.7% in Mobile.
- Oxford has a higher smoking rate at 20.8% compared to 18.6% in Mobile.
- Binge drinking is more common in Mobile at 15.1% compared to 14.8% in Oxford.
- Oxford has higher obesity rates at 45.0% compared to 42.0% in Mobile.
- There is a higher percentage of disabled individuals in Oxford at 15.0% compared to 13.0% in Mobile.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Mobile | Oxford |
|---|---|---|
| No Schooling | 0.7% (1,270) | 2.9% (256) |
| High School Diploma | 18.4% (33,785) | 15.8% (1,386) |
| Less than High School | 9.4% (17,177) | 11.2% (980) |
| Bachelor's Degree and Higher | 20.9% (38,346) | 16.6% (1,457) |
Education Levels Comparison: Mobile vs Oxford
- In Oxford, a larger percentage of residents lack formal schooling at 2.9% compared to 0.7% in Mobile.
- A higher percentage of residents in Mobile hold a high school diploma at 18.4% compared to 15.8% in Oxford.
- The percentage of residents with less than a high school education is higher in Oxford at 11.2%, compared to 9.4% in Mobile.
- A higher percentage of residents in Mobile hold a bachelor's degree or higher at 20.9% compared to 16.6% in Oxford.
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.