Demographics details for Columbus, OH vs Bigfork, MN
Population Overview
Compare main population characteristics in Columbus, OH vs Bigfork, MN.
| Data | Columbus | Bigfork |
|---|---|---|
| Population | 907,971 | 403 |
| Median Age | 32.7 years | 66.3 years |
| Median Income | $62,994 | $33,750 |
| Married Families | 29.0% | 31.0% |
| Poverty Level | 14% | 9% |
| Unemployment Rate | 5.0 | 3.5 |
Population Comparison: Columbus vs Bigfork
- In Columbus, the population is higher at 907,971, compared to 403 in Bigfork.
- The median age in Bigfork is higher at 66.3 years, compared to 32.7 years in Columbus.
- Columbus has a higher median income of $62,994 compared to $33,750 in Bigfork.
- In Bigfork, the percentage of married families is higher at 31.0%, compared to 29.0% in Columbus.
- Columbus has a higher poverty level at 14% compared to 9% in Bigfork.
- The unemployment rate in Columbus is higher at 5.0%, compared to 3.5% in Bigfork.
Demographics
Demographics Columbus vs Bigfork provide insight into the diversity of the communities to compare.
| Demographic | Columbus | Bigfork |
|---|---|---|
| Black | 29 | 1 |
| White | 51 | 93 |
| Asian | 6 | Data is updating |
| Hispanic | 7 | 2 |
| Two or More Races | 7 | 1 |
| American Indian | Data is updating | 3 |
Demographics Comparison: Columbus vs Bigfork
- A higher percentage of Black residents are in Columbus at 29% compared to 1% in Bigfork.
- The percentage of White residents is higher in Bigfork at 93% compared to 51% in Columbus.
- The Asian population is larger in Columbus at 6% compared to 0% in Bigfork.
- The Hispanic community is larger in Columbus at 7% compared to 2% in Bigfork.
- More residents identify as two or more races in Columbus at 7% compared to 1% in Bigfork.
- In Bigfork, the percentage of American Indian residents is higher at 3%, compared to 0% in Columbus.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Columbus | Bigfork |
|---|---|---|
| Mental Health Not Good | 18.4% | 16.0% |
| Physical Health Not Good | 12.2% | 10.4% |
| Depression | 23.9% | 24.3% |
| Smoking | 19.6% | 21.9% |
| Binge Drinking | 17.7% | 18.4% |
| Obesity | 38.0% | 41.6% |
| Disability Percentage | 11.0% | 23.0% |
Health Statistics Comparison: Columbus vs Bigfork
- More residents in Columbus report poor mental health at 18.4% compared to 16.0% in Bigfork.
- Higher depression rates are seen in Bigfork at 24.3% versus 23.9% in Columbus.
- Bigfork has a higher smoking rate at 21.9% compared to 19.6% in Columbus.
- More residents engage in binge drinking in Bigfork at 18.4% compared to 17.7% in Columbus.
- Bigfork has higher obesity rates at 41.6% compared to 38.0% in Columbus.
- There is a higher percentage of disabled individuals in Bigfork at 23.0% compared to 11.0% in Columbus.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Columbus | Bigfork |
|---|---|---|
| No Schooling | 1.4% (12,592) | 0.0% (Data is updating) |
| High School Diploma | 14.4% (130,716) | 26.6% (107) |
| Less than High School | 9.7% (87,770) | 9.7% (39) |
| Bachelor's Degree and Higher | 25.2% (229,071) | 8.2% (33) |
Education Levels Comparison: Columbus vs Bigfork
- A higher percentage of residents in Columbus have no formal schooling at 1.4% compared to 0.0% in Bigfork.
- In Bigfork, the rate of residents with high school diplomas is higher at 26.6% compared to 14.4% in Columbus.
- Both cities report the same percentage of residents with less than a high school education at 9.7%.
- A higher percentage of residents in Columbus hold a bachelor's degree or higher at 25.2% compared to 8.2% in Bigfork.
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.