Demographics details for Oxford, MS vs Sugar land, TX
Population Overview
Compare main population characteristics in Oxford, MS vs Sugar land, TX.
| Data | Oxford | Sugar land |
|---|---|---|
| Population | 26,437 | 109,414 |
| Median Age | 27.7 years | 42.5 years |
| Median Income | $56,784 | $132,247 |
| Married Families | 28.0% | 52.0% |
| Poverty Level | 18% | 6% |
| Unemployment Rate | 2.7 | 4.0 |
Population Comparison: Oxford vs Sugar land
- The population in Sugar land is higher at 109,414, compared to 26,437 in Oxford.
- The median age in Sugar land is higher at 42.5 years, compared to 27.7 years in Oxford.
- Sugar land has a higher median income of $132,247, compared to $56,784 in Oxford.
- In Sugar land, the percentage of married families is higher at 52.0%, compared to 28.0% in Oxford.
- Oxford has a higher poverty level at 18% compared to 6% in Sugar land.
- Sugar land has a higher unemployment rate at 4.0% compared to 2.7% in Oxford.
Demographics
Demographics Oxford vs Sugar land provide insight into the diversity of the communities to compare.
| Demographic | Oxford | Sugar land |
|---|---|---|
| Black | 25 | 7 |
| White | 68 | 33 |
| Asian | 3 | 39 |
| Hispanic | 2 | 13 |
| Two or More Races | 2 | 8 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Oxford vs Sugar land
- A higher percentage of Black residents are in Oxford at 25% compared to 7% in Sugar land.
- Oxford has a higher percentage of White residents at 68% compared to 33% in Sugar land.
- In Sugar land, the Asian population stands at 39%, greater than 3% in Oxford.
- Sugar land has a higher percentage of Hispanic residents at 13%, compared to 2% in Oxford.
- The percentage of residents identifying as two or more races is higher in Sugar land at 8%, compared to 2% in Oxford.
- The percentage of American Indian residents is the same in both Oxford and Sugar land at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Oxford | Sugar land |
|---|---|---|
| Mental Health Not Good | 15.1% | 12.5% |
| Physical Health Not Good | 10.6% | 7.4% |
| Depression | 21.3% | 16.9% |
| Smoking | 15.2% | 9.6% |
| Binge Drinking | 14.9% | 16.0% |
| Obesity | 35.0% | 25.0% |
| Disability Percentage | 8.0% | 7.0% |
Health Statistics Comparison: Oxford vs Sugar land
- More residents in Oxford report poor mental health at 15.1% compared to 12.5% in Sugar land.
- Depression is more prevalent in Oxford at 21.3% compared to 16.9% in Sugar land.
- Smoking is more prevalent in Oxford at 15.2% compared to 9.6% in Sugar land.
- More residents engage in binge drinking in Sugar land at 16.0% compared to 14.9% in Oxford.
- Obesity rates are higher in Oxford at 35.0% compared to 25.0% in Sugar land.
- Disability percentages are higher in Oxford at 8.0% compared to 7.0% in Sugar land.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Oxford | Sugar land |
|---|---|---|
| No Schooling | 0.4% (114) | 1.2% (1,314) |
| High School Diploma | 7.0% (1,862) | 7.3% (7,972) |
| Less than High School | 5.5% (1,444) | 4.3% (4,753) |
| Bachelor's Degree and Higher | 33.0% (8,735) | 42.8% (46,851) |
Education Levels Comparison: Oxford vs Sugar land
- In Sugar land, a larger percentage of residents lack formal schooling at 1.2% compared to 0.4% in Oxford.
- In Sugar land, the rate of residents with high school diplomas is higher at 7.3% compared to 7.0% in Oxford.
- More residents in Oxford have less than a high school education at 5.5% compared to 4.3% in Sugar land.
- In Sugar land, a larger share of residents have a bachelor's degree or higher at 42.8% compared to 33.0% 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.