Demographics details for Pittsburg, KS vs Flower mound, TX
Population Overview
Compare main population characteristics in Pittsburg, KS vs Flower mound, TX.
| Data | Pittsburg | Flower mound |
|---|---|---|
| Population | 20,658 | 78,486 |
| Median Age | 25.7 years | 42.6 years |
| Median Income | $42,371 | $154,471 |
| Married Families | 28.0% | 51.0% |
| Poverty Level | 23% | 4% |
| Unemployment Rate | 3.1 | 3.7 |
Population Comparison: Pittsburg vs Flower mound
- The population in Flower mound is higher at 78,486, compared to 20,658 in Pittsburg.
- The median age in Flower mound is higher at 42.6 years, compared to 25.7 years in Pittsburg.
- Flower mound has a higher median income of $154,471, compared to $42,371 in Pittsburg.
- In Flower mound, the percentage of married families is higher at 51.0%, compared to 28.0% in Pittsburg.
- Pittsburg has a higher poverty level at 23% compared to 4% in Flower mound.
- Flower mound has a higher unemployment rate at 3.7% compared to 3.1% in Pittsburg.
Demographics
Demographics Pittsburg vs Flower mound provide insight into the diversity of the communities to compare.
| Demographic | Pittsburg | Flower mound |
|---|---|---|
| Black | 3 | 3 |
| White | 78 | 66 |
| Asian | 3 | 13 |
| Hispanic | 11 | 11 |
| Two or More Races | 5 | 7 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Pittsburg vs Flower mound
- The percentage of Black residents is the same in both Pittsburg and Flower mound at 3%.
- Pittsburg has a higher percentage of White residents at 78% compared to 66% in Flower mound.
- In Flower mound, the Asian population stands at 13%, greater than 3% in Pittsburg.
- The percentage of Hispanic residents is the same in both Pittsburg and Flower mound at 11%.
- The percentage of residents identifying as two or more races is higher in Flower mound at 7%, compared to 5% in Pittsburg.
- The percentage of American Indian residents is the same in both Pittsburg and Flower mound at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Pittsburg | Flower mound |
|---|---|---|
| Mental Health Not Good | 19.3% | 13.3% |
| Physical Health Not Good | 12.5% | 7.7% |
| Depression | 25.0% | 21.1% |
| Smoking | 23.9% | 9.5% |
| Binge Drinking | 19.7% | 19.7% |
| Obesity | 43.5% | 28.5% |
| Disability Percentage | 16.0% | 6.0% |
Health Statistics Comparison: Pittsburg vs Flower mound
- More residents in Pittsburg report poor mental health at 19.3% compared to 13.3% in Flower mound.
- Depression is more prevalent in Pittsburg at 25.0% compared to 21.1% in Flower mound.
- Smoking is more prevalent in Pittsburg at 23.9% compared to 9.5% in Flower mound.
- Binge drinking rates are similar in both Pittsburg and Flower mound at 19.7%.
- Obesity rates are higher in Pittsburg at 43.5% compared to 28.5% in Flower mound.
- Disability percentages are higher in Pittsburg at 16.0% compared to 6.0% in Flower mound.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Pittsburg | Flower mound |
|---|---|---|
| No Schooling | 0.7% (150) | 0.7% (519) |
| High School Diploma | 13.0% (2,686) | 6.2% (4,886) |
| Less than High School | 5.9% (1,222) | 2.7% (2,090) |
| Bachelor's Degree and Higher | 17.2% (3,562) | 42.3% (33,161) |
Education Levels Comparison: Pittsburg vs Flower mound
- The percentage of residents with no formal schooling is the same in both Pittsburg and Flower mound at 0.7%.
- A higher percentage of residents in Pittsburg hold a high school diploma at 13.0% compared to 6.2% in Flower mound.
- More residents in Pittsburg have less than a high school education at 5.9% compared to 2.7% in Flower mound.
- In Flower mound, a larger share of residents have a bachelor's degree or higher at 42.3% compared to 17.2% in Pittsburg.
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.