Demographics details for Virginia beach, VA vs Lena, MS
Population Overview
Compare main population characteristics in Virginia beach, VA vs Lena, MS.
| Data | Virginia beach | Lena |
|---|---|---|
| Population | 455,618 | 155 |
| Median Age | 37.1 years | 45.1 years |
| Median Income | $87,544 | $85,000 |
| Married Families | 42.0% | 25.0% |
| Poverty Level | 10% | 10% |
| Unemployment Rate | 2.8 | 5.0 |
Population Comparison: Virginia beach vs Lena
- In Virginia beach, the population is higher at 455,618, compared to 155 in Lena.
- The median age in Lena is higher at 45.1 years, compared to 37.1 years in Virginia beach.
- Virginia beach has a higher median income of $87,544 compared to $85,000 in Lena.
- A higher percentage of married families is found in Virginia beach at 42.0% compared to 25.0% in Lena.
- The poverty level is identical in both Virginia beach and Lena at 10%.
- Lena has a higher unemployment rate at 5.0% compared to 2.8% in Virginia beach.
Demographics
Demographics Virginia beach vs Lena provide insight into the diversity of the communities to compare.
| Demographic | Virginia beach | Lena |
|---|---|---|
| Black | 19 | 3 |
| White | 56 | 95 |
| Asian | 7 | Data is updating |
| Hispanic | 9 | 1 |
| Two or More Races | 9 | 1 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Virginia beach vs Lena
- A higher percentage of Black residents are in Virginia beach at 19% compared to 3% in Lena.
- The percentage of White residents is higher in Lena at 95% compared to 56% in Virginia beach.
- The Asian population is larger in Virginia beach at 7% compared to 0% in Lena.
- The Hispanic community is larger in Virginia beach at 9% compared to 1% in Lena.
- More residents identify as two or more races in Virginia beach at 9% compared to 1% in Lena.
- The percentage of American Indian residents is the same in both Virginia beach and Lena at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Virginia beach | Lena |
|---|---|---|
| Mental Health Not Good | 14.5% | 19.0% |
| Physical Health Not Good | 9.3% | 14.7% |
| Depression | 20.4% | 24.7% |
| Smoking | 13.7% | 25.1% |
| Binge Drinking | 16.8% | 15.2% |
| Obesity | 31.5% | 40.6% |
| Disability Percentage | 11.0% | 10.0% |
Health Statistics Comparison: Virginia beach vs Lena
- In Lena, a higher percentage report poor mental health at 19.0% compared to 14.5% in Virginia beach.
- Higher depression rates are seen in Lena at 24.7% versus 20.4% in Virginia beach.
- Lena has a higher smoking rate at 25.1% compared to 13.7% in Virginia beach.
- Binge drinking is more common in Virginia beach at 16.8% compared to 15.2% in Lena.
- Lena has higher obesity rates at 40.6% compared to 31.5% in Virginia beach.
- Disability percentages are higher in Virginia beach at 11.0% compared to 10.0% in Lena.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Virginia beach | Lena |
|---|---|---|
| No Schooling | 0.6% (2,931) | 0.0% (Data is updating) |
| High School Diploma | 11.8% (53,968) | 8.4% (13) |
| Less than High School | 6.0% (27,564) | 5.2% (8) |
| Bachelor's Degree and Higher | 27.6% (125,790) | 14.8% (23) |
Education Levels Comparison: Virginia beach vs Lena
- A higher percentage of residents in Virginia beach have no formal schooling at 0.6% compared to 0.0% in Lena.
- A higher percentage of residents in Virginia beach hold a high school diploma at 11.8% compared to 8.4% in Lena.
- More residents in Virginia beach have less than a high school education at 6.0% compared to 5.2% in Lena.
- A higher percentage of residents in Virginia beach hold a bachelor's degree or higher at 27.6% compared to 14.8% in Lena.
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.