Demographics details for Elm city, NC vs Greenbelt, MD
Population Overview
Compare main population characteristics in Elm city, NC vs Greenbelt, MD.
| Data | Elm city | Greenbelt |
|---|---|---|
| Population | 1,204 | 24,360 |
| Median Age | 48.0 years | 37.2 years |
| Median Income | $48,125 | $82,019 |
| Married Families | 43.0% | 30.0% |
| Poverty Level | 15% | 9% |
| Unemployment Rate | 5.1 | 6.5 |
Population Comparison: Elm city vs Greenbelt
- The population in Greenbelt is higher at 24,360, compared to 1,204 in Elm city.
- Residents in Elm city have a higher median age of 48.0 years compared to 37.2 years in Greenbelt.
- Greenbelt has a higher median income of $82,019, compared to $48,125 in Elm city.
- A higher percentage of married families is found in Elm city at 43.0% compared to 30.0% in Greenbelt.
- Elm city has a higher poverty level at 15% compared to 9% in Greenbelt.
- Greenbelt has a higher unemployment rate at 6.5% compared to 5.1% in Elm city.
Demographics
Demographics Elm city vs Greenbelt provide insight into the diversity of the communities to compare.
| Demographic | Elm city | Greenbelt |
|---|---|---|
| Black | 60 | 48 |
| White | 25 | 17 |
| Asian | 3 | 12 |
| Hispanic | 11 | 16 |
| Two or More Races | 1 | 6 |
| American Indian | Data is updating | 1 |
Demographics Comparison: Elm city vs Greenbelt
- A higher percentage of Black residents are in Elm city at 60% compared to 48% in Greenbelt.
- Elm city has a higher percentage of White residents at 25% compared to 17% in Greenbelt.
- In Greenbelt, the Asian population stands at 12%, greater than 3% in Elm city.
- Greenbelt has a higher percentage of Hispanic residents at 16%, compared to 11% in Elm city.
- The percentage of residents identifying as two or more races is higher in Greenbelt at 6%, compared to 1% in Elm city.
- In Greenbelt, the percentage of American Indian residents is higher at 1%, compared to 0% in Elm city.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Elm city | Greenbelt |
|---|---|---|
| Mental Health Not Good | 16.8% | 12.9% |
| Physical Health Not Good | 12.0% | 8.1% |
| Depression | 21.2% | 13.0% |
| Smoking | 18.8% | 9.8% |
| Binge Drinking | 15.7% | 12.3% |
| Obesity | 37.9% | 36.0% |
| Disability Percentage | 19.0% | 10.0% |
Health Statistics Comparison: Elm city vs Greenbelt
- More residents in Elm city report poor mental health at 16.8% compared to 12.9% in Greenbelt.
- Depression is more prevalent in Elm city at 21.2% compared to 13.0% in Greenbelt.
- Smoking is more prevalent in Elm city at 18.8% compared to 9.8% in Greenbelt.
- Binge drinking is more common in Elm city at 15.7% compared to 12.3% in Greenbelt.
- Obesity rates are higher in Elm city at 37.9% compared to 36.0% in Greenbelt.
- Disability percentages are higher in Elm city at 19.0% compared to 10.0% in Greenbelt.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Elm city | Greenbelt |
|---|---|---|
| No Schooling | 0.7% (8) | 2.2% (530) |
| High School Diploma | 24.1% (290) | 9.0% (2,195) |
| Less than High School | 15.1% (182) | 11.4% (2,766) |
| Bachelor's Degree and Higher | 11.5% (139) | 32.2% (7,832) |
Education Levels Comparison: Elm city vs Greenbelt
- In Greenbelt, a larger percentage of residents lack formal schooling at 2.2% compared to 0.7% in Elm city.
- A higher percentage of residents in Elm city hold a high school diploma at 24.1% compared to 9.0% in Greenbelt.
- More residents in Elm city have less than a high school education at 15.1% compared to 11.4% in Greenbelt.
- In Greenbelt, a larger share of residents have a bachelor's degree or higher at 32.2% compared to 11.5% in Elm city.
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.