Demographics details for Ocean city, NJ vs Wilson, NC
Population Overview
Compare main population characteristics in Ocean city, NJ vs Wilson, NC.
| Data | Ocean city | Wilson |
|---|---|---|
| Population | 11,303 | 47,606 |
| Median Age | 56.9 years | 38.8 years |
| Median Income | $98,576 | $46,891 |
| Married Families | 53.0% | 32.0% |
| Poverty Level | Data is updating | 17% |
| Unemployment Rate | 3.2 | 7.1 |
Population Comparison: Ocean city vs Wilson
- The population in Wilson is higher at 47,606, compared to 11,303 in Ocean city.
- Residents in Ocean city have a higher median age of 56.9 years compared to 38.8 years in Wilson.
- Ocean city has a higher median income of $98,576 compared to $46,891 in Wilson.
- A higher percentage of married families is found in Ocean city at 53.0% compared to 32.0% in Wilson.
- The poverty level is higher in Wilson at 17%, compared to 0% in Ocean city.
- Wilson has a higher unemployment rate at 7.1% compared to 3.2% in Ocean city.
Demographics
Demographics Ocean city vs Wilson provide insight into the diversity of the communities to compare.
| Demographic | Ocean city | Wilson |
|---|---|---|
| Black | 3 | 50 |
| White | 86 | 33 |
| Asian | Data is updating | 1 |
| Hispanic | 8 | 12 |
| Two or More Races | 3 | 4 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Ocean city vs Wilson
- In Wilson, the percentage of Black residents is higher at 50% compared to 3% in Ocean city.
- Ocean city has a higher percentage of White residents at 86% compared to 33% in Wilson.
- In Wilson, the Asian population stands at 1%, greater than 0% in Ocean city.
- Wilson has a higher percentage of Hispanic residents at 12%, compared to 8% in Ocean city.
- The percentage of residents identifying as two or more races is higher in Wilson at 4%, compared to 3% in Ocean city.
- The percentage of American Indian residents is the same in both Ocean city and Wilson at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Ocean city | Wilson |
|---|---|---|
| Mental Health Not Good | 14.0% | 18.0% |
| Physical Health Not Good | 8.7% | 13.9% |
| Depression | 21.8% | 22.2% |
| Smoking | 11.9% | 21.4% |
| Binge Drinking | 20.3% | 14.8% |
| Obesity | 29.8% | 39.4% |
| Disability Percentage | 14.0% | 14.0% |
Health Statistics Comparison: Ocean city vs Wilson
- In Wilson, a higher percentage report poor mental health at 18.0% compared to 14.0% in Ocean city.
- Higher depression rates are seen in Wilson at 22.2% versus 21.8% in Ocean city.
- Wilson has a higher smoking rate at 21.4% compared to 11.9% in Ocean city.
- Binge drinking is more common in Ocean city at 20.3% compared to 14.8% in Wilson.
- Wilson has higher obesity rates at 39.4% compared to 29.8% in Ocean city.
- Disability percentages are the same in both Ocean city and Wilson at 14.0%.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Ocean city | Wilson |
|---|---|---|
| No Schooling | 0.4% (50) | 1.3% (630) |
| High School Diploma | 16.9% (1,907) | 19.5% (9,264) |
| Less than High School | 6.0% (676) | 15.2% (7,224) |
| Bachelor's Degree and Higher | 43.6% (4,926) | 15.0% (7,125) |
Education Levels Comparison: Ocean city vs Wilson
- In Wilson, a larger percentage of residents lack formal schooling at 1.3% compared to 0.4% in Ocean city.
- In Wilson, the rate of residents with high school diplomas is higher at 19.5% compared to 16.9% in Ocean city.
- The percentage of residents with less than a high school education is higher in Wilson at 15.2%, compared to 6.0% in Ocean city.
- A higher percentage of residents in Ocean city hold a bachelor's degree or higher at 43.6% compared to 15.0% in Wilson.
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.