Demographics details for New hope, PA vs Baltimore, MD
Population Overview
Compare main population characteristics in New hope, PA vs Baltimore, MD.
| Data | New hope | Baltimore |
|---|---|---|
| Population | 2,632 | 569,931 |
| Median Age | 56.8 years | 36.0 years |
| Median Income | $117,143 | $58,349 |
| Married Families | 48.0% | 23.0% |
| Poverty Level | 6% | 16% |
| Unemployment Rate | 3.5 | 4.3 |
Population Comparison: New hope vs Baltimore
- The population in Baltimore is higher at 569,931, compared to 2,632 in New hope.
- Residents in New hope have a higher median age of 56.8 years compared to 36.0 years in Baltimore.
- New hope has a higher median income of $117,143 compared to $58,349 in Baltimore.
- A higher percentage of married families is found in New hope at 48.0% compared to 23.0% in Baltimore.
- The poverty level is higher in Baltimore at 16%, compared to 6% in New hope.
- Baltimore has a higher unemployment rate at 4.3% compared to 3.5% in New hope.
Demographics
Demographics New hope vs Baltimore provide insight into the diversity of the communities to compare.
| Demographic | New hope | Baltimore |
|---|---|---|
| Black | Data is updating | 63 |
| White | 82 | 23 |
| Asian | 3 | 3 |
| Hispanic | 9 | 6 |
| Two or More Races | 6 | 5 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: New hope vs Baltimore
- In Baltimore, the percentage of Black residents is higher at 63% compared to 0% in New hope.
- New hope has a higher percentage of White residents at 82% compared to 23% in Baltimore.
- Both New hope and Baltimore have the same percentage of Asian residents at 3%.
- The Hispanic community is larger in New hope at 9% compared to 6% in Baltimore.
- More residents identify as two or more races in New hope at 6% compared to 5% in Baltimore.
- The percentage of American Indian residents is the same in both New hope and Baltimore at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | New hope | Baltimore |
|---|---|---|
| Mental Health Not Good | 13.5% | 17.9% |
| Physical Health Not Good | 8.0% | 12.3% |
| Depression | 21.5% | 20.2% |
| Smoking | 12.0% | 19.8% |
| Binge Drinking | 20.2% | 15.4% |
| Obesity | 30.3% | 37.1% |
| Disability Percentage | 8.0% | 16.0% |
Health Statistics Comparison: New hope vs Baltimore
- In Baltimore, a higher percentage report poor mental health at 17.9% compared to 13.5% in New hope.
- Depression is more prevalent in New hope at 21.5% compared to 20.2% in Baltimore.
- Baltimore has a higher smoking rate at 19.8% compared to 12.0% in New hope.
- Binge drinking is more common in New hope at 20.2% compared to 15.4% in Baltimore.
- Baltimore has higher obesity rates at 37.1% compared to 30.3% in New hope.
- There is a higher percentage of disabled individuals in Baltimore at 16.0% compared to 8.0% in New hope.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | New hope | Baltimore |
|---|---|---|
| No Schooling | 0.0% (Data is updating) | 1.2% (6,683) |
| High School Diploma | 9.8% (259) | 16.8% (95,744) |
| Less than High School | 11.5% (303) | 11.9% (67,970) |
| Bachelor's Degree and Higher | 55.5% (1,462) | 25.1% (143,174) |
Education Levels Comparison: New hope vs Baltimore
- In Baltimore, a larger percentage of residents lack formal schooling at 1.2% compared to 0.0% in New hope.
- In Baltimore, the rate of residents with high school diplomas is higher at 16.8% compared to 9.8% in New hope.
- The percentage of residents with less than a high school education is higher in Baltimore at 11.9%, compared to 11.5% in New hope.
- A higher percentage of residents in New hope hold a bachelor's degree or higher at 55.5% compared to 25.1% in Baltimore.
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.