Demographics details for Paterson, NJ vs Charlotte, TN
Population Overview
Compare main population characteristics in Paterson, NJ vs Charlotte, TN.
| Data | Paterson | Charlotte |
|---|---|---|
| Population | 156,661 | 1,674 |
| Median Age | 33.1 years | 36.8 years |
| Median Income | $52,092 | $57,188 |
| Married Families | 27.0% | 46.0% |
| Poverty Level | 18% | 14% |
| Unemployment Rate | 8.8 | 4.3 |
Population Comparison: Paterson vs Charlotte
- In Paterson, the population is higher at 156,661, compared to 1,674 in Charlotte.
- The median age in Charlotte is higher at 36.8 years, compared to 33.1 years in Paterson.
- Charlotte has a higher median income of $57,188, compared to $52,092 in Paterson.
- In Charlotte, the percentage of married families is higher at 46.0%, compared to 27.0% in Paterson.
- Paterson has a higher poverty level at 18% compared to 14% in Charlotte.
- The unemployment rate in Paterson is higher at 8.8%, compared to 4.3% in Charlotte.
Demographics
Demographics Paterson vs Charlotte provide insight into the diversity of the communities to compare.
| Demographic | Paterson | Charlotte |
|---|---|---|
| Black | 25 | 6 |
| White | Data is updating | 82 |
| Asian | 5 | Data is updating |
| Hispanic | 64 | 4 |
| Two or More Races | 17 | 6 |
| American Indian | Data is updating | 2 |
Demographics Comparison: Paterson vs Charlotte
- A higher percentage of Black residents are in Paterson at 25% compared to 6% in Charlotte.
- The percentage of White residents is higher in Charlotte at 82% compared to 0% in Paterson.
- The Asian population is larger in Paterson at 5% compared to 0% in Charlotte.
- The Hispanic community is larger in Paterson at 64% compared to 4% in Charlotte.
- More residents identify as two or more races in Paterson at 17% compared to 6% in Charlotte.
- In Charlotte, the percentage of American Indian residents is higher at 2%, compared to 0% in Paterson.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Paterson | Charlotte |
|---|---|---|
| Mental Health Not Good | 17.5% | 20.3% |
| Physical Health Not Good | 15.1% | 14.7% |
| Depression | 16.5% | 28.8% |
| Smoking | 17.7% | 25.3% |
| Binge Drinking | 13.9% | 16.0% |
| Obesity | 38.0% | 38.9% |
| Disability Percentage | 7.0% | 27.0% |
Health Statistics Comparison: Paterson vs Charlotte
- In Charlotte, a higher percentage report poor mental health at 20.3% compared to 17.5% in Paterson.
- Higher depression rates are seen in Charlotte at 28.8% versus 16.5% in Paterson.
- Charlotte has a higher smoking rate at 25.3% compared to 17.7% in Paterson.
- More residents engage in binge drinking in Charlotte at 16.0% compared to 13.9% in Paterson.
- Charlotte has higher obesity rates at 38.9% compared to 38.0% in Paterson.
- There is a higher percentage of disabled individuals in Charlotte at 27.0% compared to 7.0% in Paterson.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Paterson | Charlotte |
|---|---|---|
| No Schooling | 2.1% (3,278) | 0.4% (6) |
| High School Diploma | 25.1% (39,354) | 25.3% (424) |
| Less than High School | 26.1% (40,961) | 26.0% (436) |
| Bachelor's Degree and Higher | 7.9% (12,450) | 9.9% (166) |
Education Levels Comparison: Paterson vs Charlotte
- A higher percentage of residents in Paterson have no formal schooling at 2.1% compared to 0.4% in Charlotte.
- In Charlotte, the rate of residents with high school diplomas is higher at 25.3% compared to 25.1% in Paterson.
- More residents in Paterson have less than a high school education at 26.1% compared to 26.0% in Charlotte.
- In Charlotte, a larger share of residents have a bachelor's degree or higher at 9.9% compared to 7.9% in Paterson.
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.