Demographics details for Princeton, NJ vs Baltimore, MD
Population Overview
Compare main population characteristics in Princeton, NJ vs Baltimore, MD.
| Data | Princeton | Baltimore |
|---|---|---|
| Population | 30,377 | 569,931 |
| Median Age | 28.6 years | 36.0 years |
| Median Income | $176,695 | $58,349 |
| Married Families | 37.0% | 23.0% |
| Poverty Level | 4% | 16% |
| Unemployment Rate | 3.5 | 4.3 |
Population Comparison: Princeton vs Baltimore
- The population in Baltimore is higher at 569,931, compared to 30,377 in Princeton.
- The median age in Baltimore is higher at 36.0 years, compared to 28.6 years in Princeton.
- Princeton has a higher median income of $176,695 compared to $58,349 in Baltimore.
- A higher percentage of married families is found in Princeton at 37.0% compared to 23.0% in Baltimore.
- The poverty level is higher in Baltimore at 16%, compared to 4% in Princeton.
- Baltimore has a higher unemployment rate at 4.3% compared to 3.5% in Princeton.
Demographics
Demographics Princeton vs Baltimore provide insight into the diversity of the communities to compare.
| Demographic | Princeton | Baltimore |
|---|---|---|
| Black | 8 | 63 |
| White | 60 | 23 |
| Asian | 19 | 3 |
| Hispanic | 6 | 6 |
| Two or More Races | 6 | 5 |
| American Indian | 1 | Data is updating |
Demographics Comparison: Princeton vs Baltimore
- In Baltimore, the percentage of Black residents is higher at 63% compared to 8% in Princeton.
- Princeton has a higher percentage of White residents at 60% compared to 23% in Baltimore.
- The Asian population is larger in Princeton at 19% compared to 3% in Baltimore.
- The percentage of Hispanic residents is the same in both Princeton and Baltimore at 6%.
- More residents identify as two or more races in Princeton at 6% compared to 5% in Baltimore.
- A greater percentage of American Indian residents live in Princeton at 1% compared to 0% in Baltimore.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Princeton | Baltimore |
|---|---|---|
| Mental Health Not Good | 12.1% | 17.9% |
| Physical Health Not Good | 7.2% | 12.3% |
| Depression | 18.9% | 20.2% |
| Smoking | 8.8% | 19.8% |
| Binge Drinking | 16.6% | 15.4% |
| Obesity | 19.4% | 37.1% |
| Disability Percentage | 6.0% | 16.0% |
Health Statistics Comparison: Princeton vs Baltimore
- In Baltimore, a higher percentage report poor mental health at 17.9% compared to 12.1% in Princeton.
- Higher depression rates are seen in Baltimore at 20.2% versus 18.9% in Princeton.
- Baltimore has a higher smoking rate at 19.8% compared to 8.8% in Princeton.
- Binge drinking is more common in Princeton at 16.6% compared to 15.4% in Baltimore.
- Baltimore has higher obesity rates at 37.1% compared to 19.4% in Princeton.
- There is a higher percentage of disabled individuals in Baltimore at 16.0% compared to 6.0% in Princeton.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Princeton | Baltimore |
|---|---|---|
| No Schooling | 0.2% (52) | 1.2% (6,683) |
| High School Diploma | 2.6% (777) | 16.8% (95,744) |
| Less than High School | 1.8% (559) | 11.9% (67,970) |
| Bachelor's Degree and Higher | 47.6% (14,457) | 25.1% (143,174) |
Education Levels Comparison: Princeton vs Baltimore
- In Baltimore, a larger percentage of residents lack formal schooling at 1.2% compared to 0.2% in Princeton.
- In Baltimore, the rate of residents with high school diplomas is higher at 16.8% compared to 2.6% in Princeton.
- The percentage of residents with less than a high school education is higher in Baltimore at 11.9%, compared to 1.8% in Princeton.
- A higher percentage of residents in Princeton hold a bachelor's degree or higher at 47.6% 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.