Demographics details for Martinsburg, WV vs Ohiopyle, PA
Population Overview
Compare main population characteristics in Martinsburg, WV vs Ohiopyle, PA.
| Data | Martinsburg | Ohiopyle |
|---|---|---|
| Population | 18,953 | 36 |
| Median Age | 36.4 years | 53.2 years |
| Median Income | $55,240 | $38,000 |
| Married Families | 29.0% | 81.0% |
| Poverty Level | 8% | Data is updating |
| Unemployment Rate | 4.5 | 3.2 |
Population Comparison: Martinsburg vs Ohiopyle
- In Martinsburg, the population is higher at 18,953, compared to 36 in Ohiopyle.
- The median age in Ohiopyle is higher at 53.2 years, compared to 36.4 years in Martinsburg.
- Martinsburg has a higher median income of $55,240 compared to $38,000 in Ohiopyle.
- In Ohiopyle, the percentage of married families is higher at 81.0%, compared to 29.0% in Martinsburg.
- Martinsburg has a higher poverty level at 8% compared to 0% in Ohiopyle.
- The unemployment rate in Martinsburg is higher at 4.5%, compared to 3.2% in Ohiopyle.
Demographics
Demographics Martinsburg vs Ohiopyle provide insight into the diversity of the communities to compare.
| Demographic | Martinsburg | Ohiopyle |
|---|---|---|
| Black | 13 | Data is updating |
| White | 69 | 100 |
| Asian | 1 | Data is updating |
| Hispanic | 6 | Data is updating |
| Two or More Races | 11 | Data is updating |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Martinsburg vs Ohiopyle
- A higher percentage of Black residents are in Martinsburg at 13% compared to 0% in Ohiopyle.
- The percentage of White residents is higher in Ohiopyle at 100% compared to 69% in Martinsburg.
- The Asian population is larger in Martinsburg at 1% compared to 0% in Ohiopyle.
- The Hispanic community is larger in Martinsburg at 6% compared to 0% in Ohiopyle.
- More residents identify as two or more races in Martinsburg at 11% compared to 0% in Ohiopyle.
- The percentage of American Indian residents is the same in both Martinsburg and Ohiopyle at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Martinsburg | Ohiopyle |
|---|---|---|
| Mental Health Not Good | 21.8% | 18.7% |
| Physical Health Not Good | 15.8% | 13.1% |
| Depression | 27.7% | 25.2% |
| Smoking | 24.7% | 23.2% |
| Binge Drinking | 12.6% | 18.8% |
| Obesity | 43.0% | 36.5% |
| Disability Percentage | 17.0% | 44.0% |
Health Statistics Comparison: Martinsburg vs Ohiopyle
- More residents in Martinsburg report poor mental health at 21.8% compared to 18.7% in Ohiopyle.
- Depression is more prevalent in Martinsburg at 27.7% compared to 25.2% in Ohiopyle.
- Smoking is more prevalent in Martinsburg at 24.7% compared to 23.2% in Ohiopyle.
- More residents engage in binge drinking in Ohiopyle at 18.8% compared to 12.6% in Martinsburg.
- Obesity rates are higher in Martinsburg at 43.0% compared to 36.5% in Ohiopyle.
- There is a higher percentage of disabled individuals in Ohiopyle at 44.0% compared to 17.0% in Martinsburg.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Martinsburg | Ohiopyle |
|---|---|---|
| No Schooling | 0.8% (144) | 27.8% (10) |
| High School Diploma | 16.7% (3,171) | 30.6% (11) |
| Less than High School | 13.5% (2,556) | 55.6% (20) |
| Bachelor's Degree and Higher | 16.2% (3,077) | 25.0% (9) |
Education Levels Comparison: Martinsburg vs Ohiopyle
- In Ohiopyle, a larger percentage of residents lack formal schooling at 27.8% compared to 0.8% in Martinsburg.
- In Ohiopyle, the rate of residents with high school diplomas is higher at 30.6% compared to 16.7% in Martinsburg.
- The percentage of residents with less than a high school education is higher in Ohiopyle at 55.6%, compared to 13.5% in Martinsburg.
- In Ohiopyle, a larger share of residents have a bachelor's degree or higher at 25.0% compared to 16.2% in Martinsburg.
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.