Demographics details for Tyler, TX vs Mount union, PA
Population Overview
Compare main population characteristics in Tyler, TX vs Mount union, PA.
| Data | Tyler | Mount union |
|---|---|---|
| Population | 109,286 | 2,267 |
| Median Age | 34.9 years | 34.8 years |
| Median Income | $63,056 | $38,382 |
| Married Families | 35.0% | 25.0% |
| Poverty Level | 12% | 12% |
| Unemployment Rate | 4.2 | 4.2 |
Population Comparison: Tyler vs Mount union
- In Tyler, the population is higher at 109,286, compared to 2,267 in Mount union.
- Residents in Tyler have a higher median age of 34.9 years compared to 34.8 years in Mount union.
- Tyler has a higher median income of $63,056 compared to $38,382 in Mount union.
- A higher percentage of married families is found in Tyler at 35.0% compared to 25.0% in Mount union.
- The poverty level is identical in both Tyler and Mount union at 12%.
- The unemployment rate is the same in both Tyler and Mount union at 4.2%.
Demographics
Demographics Tyler vs Mount union provide insight into the diversity of the communities to compare.
| Demographic | Tyler | Mount union |
|---|---|---|
| Black | 23 | 8 |
| White | 46 | 87 |
| Asian | 3 | Data is updating |
| Hispanic | 21 | 1 |
| Two or More Races | 6 | 4 |
| American Indian | 1 | Data is updating |
Demographics Comparison: Tyler vs Mount union
- A higher percentage of Black residents are in Tyler at 23% compared to 8% in Mount union.
- The percentage of White residents is higher in Mount union at 87% compared to 46% in Tyler.
- The Asian population is larger in Tyler at 3% compared to 0% in Mount union.
- The Hispanic community is larger in Tyler at 21% compared to 1% in Mount union.
- More residents identify as two or more races in Tyler at 6% compared to 4% in Mount union.
- A greater percentage of American Indian residents live in Tyler at 1% compared to 0% in Mount union.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Tyler | Mount union |
|---|---|---|
| Mental Health Not Good | 18.0% | 20.7% |
| Physical Health Not Good | 12.5% | 15.3% |
| Depression | 22.9% | 25.6% |
| Smoking | 18.0% | 26.4% |
| Binge Drinking | 16.8% | 16.4% |
| Obesity | 37.5% | 43.0% |
| Disability Percentage | 11.0% | 20.0% |
Health Statistics Comparison: Tyler vs Mount union
- In Mount union, a higher percentage report poor mental health at 20.7% compared to 18.0% in Tyler.
- Higher depression rates are seen in Mount union at 25.6% versus 22.9% in Tyler.
- Mount union has a higher smoking rate at 26.4% compared to 18.0% in Tyler.
- Binge drinking is more common in Tyler at 16.8% compared to 16.4% in Mount union.
- Mount union has higher obesity rates at 43.0% compared to 37.5% in Tyler.
- There is a higher percentage of disabled individuals in Mount union at 20.0% compared to 11.0% in Tyler.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Tyler | Mount union |
|---|---|---|
| No Schooling | 0.9% (1,016) | 1.9% (43) |
| High School Diploma | 11.0% (12,027) | 28.5% (646) |
| Less than High School | 13.4% (14,636) | 16.3% (370) |
| Bachelor's Degree and Higher | 19.4% (21,157) | 6.3% (142) |
Education Levels Comparison: Tyler vs Mount union
- In Mount union, a larger percentage of residents lack formal schooling at 1.9% compared to 0.9% in Tyler.
- In Mount union, the rate of residents with high school diplomas is higher at 28.5% compared to 11.0% in Tyler.
- The percentage of residents with less than a high school education is higher in Mount union at 16.3%, compared to 13.4% in Tyler.
- A higher percentage of residents in Tyler hold a bachelor's degree or higher at 19.4% compared to 6.3% in Mount union.
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.