Demographics details for Groom, TX vs Martinsburg, WV
Population Overview
Compare main population characteristics in Groom, TX vs Martinsburg, WV.
| Data | Groom | Martinsburg |
|---|---|---|
| Population | 548 | 18,953 |
| Median Age | 46.0 years | 36.4 years |
| Median Income | $51,944 | $55,240 |
| Married Families | 39.0% | 29.0% |
| Poverty Level | 12% | 8% |
| Unemployment Rate | 3.5 | 4.5 |
Population Comparison: Groom vs Martinsburg
- The population in Martinsburg is higher at 18,953, compared to 548 in Groom.
- Residents in Groom have a higher median age of 46.0 years compared to 36.4 years in Martinsburg.
- Martinsburg has a higher median income of $55,240, compared to $51,944 in Groom.
- A higher percentage of married families is found in Groom at 39.0% compared to 29.0% in Martinsburg.
- Groom has a higher poverty level at 12% compared to 8% in Martinsburg.
- Martinsburg has a higher unemployment rate at 4.5% compared to 3.5% in Groom.
Demographics
Demographics Groom vs Martinsburg provide insight into the diversity of the communities to compare.
| Demographic | Groom | Martinsburg |
|---|---|---|
| Black | Data is updating | 13 |
| White | 96 | 69 |
| Asian | Data is updating | 1 |
| Hispanic | 3 | 6 |
| Two or More Races | 1 | 11 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Groom vs Martinsburg
- In Martinsburg, the percentage of Black residents is higher at 13% compared to 0% in Groom.
- Groom has a higher percentage of White residents at 96% compared to 69% in Martinsburg.
- In Martinsburg, the Asian population stands at 1%, greater than 0% in Groom.
- Martinsburg has a higher percentage of Hispanic residents at 6%, compared to 3% in Groom.
- The percentage of residents identifying as two or more races is higher in Martinsburg at 11%, compared to 1% in Groom.
- The percentage of American Indian residents is the same in both Groom and Martinsburg at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Groom | Martinsburg |
|---|---|---|
| Mental Health Not Good | 17.3% | 21.8% |
| Physical Health Not Good | 10.6% | 15.8% |
| Depression | 25.1% | 27.7% |
| Smoking | 16.4% | 24.7% |
| Binge Drinking | 20.3% | 12.6% |
| Obesity | 34.7% | 43.0% |
| Disability Percentage | 11.0% | 17.0% |
Health Statistics Comparison: Groom vs Martinsburg
- In Martinsburg, a higher percentage report poor mental health at 21.8% compared to 17.3% in Groom.
- Higher depression rates are seen in Martinsburg at 27.7% versus 25.1% in Groom.
- Martinsburg has a higher smoking rate at 24.7% compared to 16.4% in Groom.
- Binge drinking is more common in Groom at 20.3% compared to 12.6% in Martinsburg.
- Martinsburg has higher obesity rates at 43.0% compared to 34.7% in Groom.
- There is a higher percentage of disabled individuals in Martinsburg at 17.0% compared to 11.0% in Groom.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Groom | Martinsburg |
|---|---|---|
| No Schooling | 0.7% (4) | 0.8% (144) |
| High School Diploma | 22.3% (122) | 16.7% (3,171) |
| Less than High School | 10.9% (60) | 13.5% (2,556) |
| Bachelor's Degree and Higher | 10.9% (60) | 16.2% (3,077) |
Education Levels Comparison: Groom vs Martinsburg
- In Martinsburg, a larger percentage of residents lack formal schooling at 0.8% compared to 0.7% in Groom.
- A higher percentage of residents in Groom hold a high school diploma at 22.3% compared to 16.7% in Martinsburg.
- The percentage of residents with less than a high school education is higher in Martinsburg at 13.5%, compared to 10.9% in Groom.
- In Martinsburg, a larger share of residents have a bachelor's degree or higher at 16.2% compared to 10.9% in Groom.
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.