Demographics details for Ohiopyle, PA vs Baltimore, MD
Population Overview
Compare main population characteristics in Ohiopyle, PA vs Baltimore, MD.
| Data | Ohiopyle | Baltimore |
|---|---|---|
| Population | 36 | 569,931 |
| Median Age | 53.2 years | 36.0 years |
| Median Income | $38,000 | $58,349 |
| Married Families | 81.0% | 23.0% |
| Poverty Level | Data is updating | 16% |
| Unemployment Rate | 3.2 | 4.3 |
Population Comparison: Ohiopyle vs Baltimore
- The population in Baltimore is higher at 569,931, compared to 36 in Ohiopyle.
- Residents in Ohiopyle have a higher median age of 53.2 years compared to 36.0 years in Baltimore.
- Baltimore has a higher median income of $58,349, compared to $38,000 in Ohiopyle.
- A higher percentage of married families is found in Ohiopyle at 81.0% compared to 23.0% in Baltimore.
- The poverty level is higher in Baltimore at 16%, compared to 0% in Ohiopyle.
- Baltimore has a higher unemployment rate at 4.3% compared to 3.2% in Ohiopyle.
Demographics
Demographics Ohiopyle vs Baltimore provide insight into the diversity of the communities to compare.
| Demographic | Ohiopyle | Baltimore |
|---|---|---|
| Black | Data is updating | 63 |
| White | 100 | 23 |
| Asian | Data is updating | 3 |
| Hispanic | Data is updating | 6 |
| Two or More Races | Data is updating | 5 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Ohiopyle vs Baltimore
- In Baltimore, the percentage of Black residents is higher at 63% compared to 0% in Ohiopyle.
- Ohiopyle has a higher percentage of White residents at 100% compared to 23% in Baltimore.
- In Baltimore, the Asian population stands at 3%, greater than 0% in Ohiopyle.
- Baltimore has a higher percentage of Hispanic residents at 6%, compared to 0% in Ohiopyle.
- The percentage of residents identifying as two or more races is higher in Baltimore at 5%, compared to 0% in Ohiopyle.
- The percentage of American Indian residents is the same in both Ohiopyle and Baltimore at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Ohiopyle | Baltimore |
|---|---|---|
| Mental Health Not Good | 18.7% | 17.9% |
| Physical Health Not Good | 13.1% | 12.3% |
| Depression | 25.2% | 20.2% |
| Smoking | 23.2% | 19.8% |
| Binge Drinking | 18.8% | 15.4% |
| Obesity | 36.5% | 37.1% |
| Disability Percentage | 44.0% | 16.0% |
Health Statistics Comparison: Ohiopyle vs Baltimore
- More residents in Ohiopyle report poor mental health at 18.7% compared to 17.9% in Baltimore.
- Depression is more prevalent in Ohiopyle at 25.2% compared to 20.2% in Baltimore.
- Smoking is more prevalent in Ohiopyle at 23.2% compared to 19.8% in Baltimore.
- Binge drinking is more common in Ohiopyle at 18.8% compared to 15.4% in Baltimore.
- Baltimore has higher obesity rates at 37.1% compared to 36.5% in Ohiopyle.
- Disability percentages are higher in Ohiopyle at 44.0% compared to 16.0% in Baltimore.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Ohiopyle | Baltimore |
|---|---|---|
| No Schooling | 27.8% (10) | 1.2% (6,683) |
| High School Diploma | 30.6% (11) | 16.8% (95,744) |
| Less than High School | 55.6% (20) | 11.9% (67,970) |
| Bachelor's Degree and Higher | 25.0% (9) | 25.1% (143,174) |
Education Levels Comparison: Ohiopyle vs Baltimore
- A higher percentage of residents in Ohiopyle have no formal schooling at 27.8% compared to 1.2% in Baltimore.
- A higher percentage of residents in Ohiopyle hold a high school diploma at 30.6% compared to 16.8% in Baltimore.
- More residents in Ohiopyle have less than a high school education at 55.6% compared to 11.9% in Baltimore.
- In Baltimore, a larger share of residents have a bachelor's degree or higher at 25.1% compared to 25.0% in Ohiopyle.
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.