Demographics details for Goleta, CA vs Mount union, PA
Population Overview
Compare main population characteristics in Goleta, CA vs Mount union, PA.
| Data | Goleta | Mount union |
|---|---|---|
| Population | 32,432 | 2,267 |
| Median Age | 35.0 years | 34.8 years |
| Median Income | $113,889 | $38,382 |
| Married Families | 37.0% | 25.0% |
| Poverty Level | 8% | 12% |
| Unemployment Rate | 3.2 | 4.2 |
Population Comparison: Goleta vs Mount union
- In Goleta, the population is higher at 32,432, compared to 2,267 in Mount union.
- Residents in Goleta have a higher median age of 35.0 years compared to 34.8 years in Mount union.
- Goleta has a higher median income of $113,889 compared to $38,382 in Mount union.
- A higher percentage of married families is found in Goleta at 37.0% compared to 25.0% in Mount union.
- The poverty level is higher in Mount union at 12%, compared to 8% in Goleta.
- Mount union has a higher unemployment rate at 4.2% compared to 3.2% in Goleta.
Demographics
Demographics Goleta vs Mount union provide insight into the diversity of the communities to compare.
| Demographic | Goleta | Mount union |
|---|---|---|
| Black | 3 | 8 |
| White | 34 | 87 |
| Asian | 11 | Data is updating |
| Hispanic | 37 | 1 |
| Two or More Races | 14 | 4 |
| American Indian | 1 | Data is updating |
Demographics Comparison: Goleta vs Mount union
- In Mount union, the percentage of Black residents is higher at 8% compared to 3% in Goleta.
- The percentage of White residents is higher in Mount union at 87% compared to 34% in Goleta.
- The Asian population is larger in Goleta at 11% compared to 0% in Mount union.
- The Hispanic community is larger in Goleta at 37% compared to 1% in Mount union.
- More residents identify as two or more races in Goleta at 14% compared to 4% in Mount union.
- A greater percentage of American Indian residents live in Goleta at 1% compared to 0% in Mount union.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Goleta | Mount union |
|---|---|---|
| Mental Health Not Good | 13.9% | 20.7% |
| Physical Health Not Good | 9.2% | 15.3% |
| Depression | 18.1% | 25.6% |
| Smoking | 9.8% | 26.4% |
| Binge Drinking | 17.0% | 16.4% |
| Obesity | 26.7% | 43.0% |
| Disability Percentage | 8.0% | 20.0% |
Health Statistics Comparison: Goleta vs Mount union
- In Mount union, a higher percentage report poor mental health at 20.7% compared to 13.9% in Goleta.
- Higher depression rates are seen in Mount union at 25.6% versus 18.1% in Goleta.
- Mount union has a higher smoking rate at 26.4% compared to 9.8% in Goleta.
- Binge drinking is more common in Goleta at 17.0% compared to 16.4% in Mount union.
- Mount union has higher obesity rates at 43.0% compared to 26.7% in Goleta.
- There is a higher percentage of disabled individuals in Mount union at 20.0% compared to 8.0% in Goleta.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Goleta | Mount union |
|---|---|---|
| No Schooling | 2.6% (836) | 1.9% (43) |
| High School Diploma | 7.0% (2,263) | 28.5% (646) |
| Less than High School | 15.7% (5,090) | 16.3% (370) |
| Bachelor's Degree and Higher | 32.6% (10,582) | 6.3% (142) |
Education Levels Comparison: Goleta vs Mount union
- A higher percentage of residents in Goleta have no formal schooling at 2.6% compared to 1.9% in Mount union.
- In Mount union, the rate of residents with high school diplomas is higher at 28.5% compared to 7.0% in Goleta.
- The percentage of residents with less than a high school education is higher in Mount union at 16.3%, compared to 15.7% in Goleta.
- A higher percentage of residents in Goleta hold a bachelor's degree or higher at 32.6% 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.