Demographics details for White pigeon, MI vs Buda, TX
Population Overview
Compare main population characteristics in White pigeon, MI vs Buda, TX.
| Data | White pigeon | Buda |
|---|---|---|
| Population | 1,728 | 16,086 |
| Median Age | 39.3 years | 36.8 years |
| Median Income | $46,750 | $105,378 |
| Married Families | 29.0% | 44.0% |
| Poverty Level | 14% | 5% |
| Unemployment Rate | 4.5 | 3.2 |
Population Comparison: White pigeon vs Buda
- The population in Buda is higher at 16,086, compared to 1,728 in White pigeon.
- Residents in White pigeon have a higher median age of 39.3 years compared to 36.8 years in Buda.
- Buda has a higher median income of $105,378, compared to $46,750 in White pigeon.
- In Buda, the percentage of married families is higher at 44.0%, compared to 29.0% in White pigeon.
- White pigeon has a higher poverty level at 14% compared to 5% in Buda.
- The unemployment rate in White pigeon is higher at 4.5%, compared to 3.2% in Buda.
Demographics
Demographics White pigeon vs Buda provide insight into the diversity of the communities to compare.
| Demographic | White pigeon | Buda |
|---|---|---|
| Black | Data is updating | 1 |
| White | 94 | 59 |
| Asian | Data is updating | Data is updating |
| Hispanic | 5 | 30 |
| Two or More Races | 1 | 10 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: White pigeon vs Buda
- In Buda, the percentage of Black residents is higher at 1% compared to 0% in White pigeon.
- White pigeon has a higher percentage of White residents at 94% compared to 59% in Buda.
- Both White pigeon and Buda have the same percentage of Asian residents at 0%.
- Buda has a higher percentage of Hispanic residents at 30%, compared to 5% in White pigeon.
- The percentage of residents identifying as two or more races is higher in Buda at 10%, compared to 1% in White pigeon.
- The percentage of American Indian residents is the same in both White pigeon and Buda at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | White pigeon | Buda |
|---|---|---|
| Mental Health Not Good | 19.2% | 14.6% |
| Physical Health Not Good | 12.8% | 8.8% |
| Depression | 26.5% | 20.5% |
| Smoking | 22.3% | 11.4% |
| Binge Drinking | 17.5% | 20.1% |
| Obesity | 39.0% | 27.5% |
| Disability Percentage | 26.0% | 8.0% |
Health Statistics Comparison: White pigeon vs Buda
- More residents in White pigeon report poor mental health at 19.2% compared to 14.6% in Buda.
- Depression is more prevalent in White pigeon at 26.5% compared to 20.5% in Buda.
- Smoking is more prevalent in White pigeon at 22.3% compared to 11.4% in Buda.
- More residents engage in binge drinking in Buda at 20.1% compared to 17.5% in White pigeon.
- Obesity rates are higher in White pigeon at 39.0% compared to 27.5% in Buda.
- Disability percentages are higher in White pigeon at 26.0% compared to 8.0% in Buda.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | White pigeon | Buda |
|---|---|---|
| No Schooling | 1.7% (30) | 0.3% (49) |
| High School Diploma | 23.1% (400) | 10.4% (1,668) |
| Less than High School | 20.4% (353) | 3.3% (532) |
| Bachelor's Degree and Higher | 7.2% (125) | 30.8% (4,960) |
Education Levels Comparison: White pigeon vs Buda
- A higher percentage of residents in White pigeon have no formal schooling at 1.7% compared to 0.3% in Buda.
- A higher percentage of residents in White pigeon hold a high school diploma at 23.1% compared to 10.4% in Buda.
- More residents in White pigeon have less than a high school education at 20.4% compared to 3.3% in Buda.
- In Buda, a larger share of residents have a bachelor's degree or higher at 30.8% compared to 7.2% in White pigeon.
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.