Demographics details for Piqua, OH vs Columbia, MO
Population Overview
Compare main population characteristics in Piqua, OH vs Columbia, MO.
| Data | Piqua | Columbia |
|---|---|---|
| Population | 20,607 | 128,555 |
| Median Age | 37.9 years | 28.8 years |
| Median Income | $55,379 | $60,455 |
| Married Families | 35.0% | 32.0% |
| Poverty Level | 10% | 19% |
| Unemployment Rate | 4.5 | 3.8 |
Population Comparison: Piqua vs Columbia
- The population in Columbia is higher at 128,555, compared to 20,607 in Piqua.
- Residents in Piqua have a higher median age of 37.9 years compared to 28.8 years in Columbia.
- Columbia has a higher median income of $60,455, compared to $55,379 in Piqua.
- A higher percentage of married families is found in Piqua at 35.0% compared to 32.0% in Columbia.
- The poverty level is higher in Columbia at 19%, compared to 10% in Piqua.
- The unemployment rate in Piqua is higher at 4.5%, compared to 3.8% in Columbia.
Demographics
Demographics Piqua vs Columbia provide insight into the diversity of the communities to compare.
| Demographic | Piqua | Columbia |
|---|---|---|
| Black | 2 | 11 |
| White | 92 | 73 |
| Asian | 1 | 6 |
| Hispanic | 1 | 4 |
| Two or More Races | 4 | 6 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Piqua vs Columbia
- In Columbia, the percentage of Black residents is higher at 11% compared to 2% in Piqua.
- Piqua has a higher percentage of White residents at 92% compared to 73% in Columbia.
- In Columbia, the Asian population stands at 6%, greater than 1% in Piqua.
- Columbia has a higher percentage of Hispanic residents at 4%, compared to 1% in Piqua.
- The percentage of residents identifying as two or more races is higher in Columbia at 6%, compared to 4% in Piqua.
- The percentage of American Indian residents is the same in both Piqua and Columbia at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Piqua | Columbia |
|---|---|---|
| Mental Health Not Good | 18.8% | 16.7% |
| Physical Health Not Good | 13.1% | 11.4% |
| Depression | 23.9% | 25.3% |
| Smoking | 23.2% | 16.3% |
| Binge Drinking | 17.2% | 17.7% |
| Obesity | 42.0% | 33.5% |
| Disability Percentage | 14.0% | 11.0% |
Health Statistics Comparison: Piqua vs Columbia
- More residents in Piqua report poor mental health at 18.8% compared to 16.7% in Columbia.
- Higher depression rates are seen in Columbia at 25.3% versus 23.9% in Piqua.
- Smoking is more prevalent in Piqua at 23.2% compared to 16.3% in Columbia.
- More residents engage in binge drinking in Columbia at 17.7% compared to 17.2% in Piqua.
- Obesity rates are higher in Piqua at 42.0% compared to 33.5% in Columbia.
- Disability percentages are higher in Piqua at 14.0% compared to 11.0% in Columbia.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Piqua | Columbia |
|---|---|---|
| No Schooling | 0.5% (109) | 0.7% (845) |
| High School Diploma | 24.5% (5,047) | 7.8% (9,965) |
| Less than High School | 13.5% (2,775) | 4.2% (5,383) |
| Bachelor's Degree and Higher | 8.9% (1,835) | 30.5% (39,270) |
Education Levels Comparison: Piqua vs Columbia
- In Columbia, a larger percentage of residents lack formal schooling at 0.7% compared to 0.5% in Piqua.
- A higher percentage of residents in Piqua hold a high school diploma at 24.5% compared to 7.8% in Columbia.
- More residents in Piqua have less than a high school education at 13.5% compared to 4.2% in Columbia.
- In Columbia, a larger share of residents have a bachelor's degree or higher at 30.5% compared to 8.9% in Piqua.
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.