Demographics details for Baltimore, MD vs Dighton, MA
Population Overview
Compare main population characteristics in Baltimore, MD vs Dighton, MA.
| Data | Baltimore | Dighton |
|---|---|---|
| Population | 569,931 | 7,891 |
| Median Age | 36.0 years | 42.0 years |
| Median Income | $58,349 | $77,750 |
| Married Families | 23.0% | 64.0% |
| Poverty Level | 16% | 5% |
| Unemployment Rate | 4.3 | 3.5 |
Population Comparison: Baltimore vs Dighton
- In Baltimore, the population is higher at 569,931, compared to 7,891 in Dighton.
- The median age in Dighton is higher at 42.0 years, compared to 36.0 years in Baltimore.
- Dighton has a higher median income of $77,750, compared to $58,349 in Baltimore.
- In Dighton, the percentage of married families is higher at 64.0%, compared to 23.0% in Baltimore.
- Baltimore has a higher poverty level at 16% compared to 5% in Dighton.
- The unemployment rate in Baltimore is higher at 4.3%, compared to 3.5% in Dighton.
Demographics
Demographics Baltimore vs Dighton provide insight into the diversity of the communities to compare.
| Demographic | Baltimore | Dighton |
|---|---|---|
| Black | 63 | Data is updating |
| White | 23 | 96 |
| Asian | 3 | 1 |
| Hispanic | 6 | 2 |
| Two or More Races | 5 | 1 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Baltimore vs Dighton
- A higher percentage of Black residents are in Baltimore at 63% compared to 0% in Dighton.
- The percentage of White residents is higher in Dighton at 96% compared to 23% in Baltimore.
- The Asian population is larger in Baltimore at 3% compared to 1% in Dighton.
- The Hispanic community is larger in Baltimore at 6% compared to 2% in Dighton.
- More residents identify as two or more races in Baltimore at 5% compared to 1% in Dighton.
- The percentage of American Indian residents is the same in both Baltimore and Dighton at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Baltimore | Dighton |
|---|---|---|
| Mental Health Not Good | 17.9% | Data is updating% |
| Physical Health Not Good | 12.3% | Data is updating% |
| Depression | 20.2% | Data is updating% |
| Smoking | 19.8% | Data is updating% |
| Binge Drinking | 15.4% | Data is updating% |
| Obesity | 37.1% | Data is updating% |
| Disability Percentage | 16.0% | Data is updating% |
Health Statistics Comparison: Baltimore vs Dighton
- More residents in Baltimore report poor mental health at 17.9% compared to 0.0% in Dighton.
- Depression is more prevalent in Baltimore at 20.2% compared to 0.0% in Dighton.
- Smoking is more prevalent in Baltimore at 19.8% compared to 0.0% in Dighton.
- Binge drinking is more common in Baltimore at 15.4% compared to 0.0% in Dighton.
- Obesity rates are higher in Baltimore at 37.1% compared to 0.0% in Dighton.
- Disability percentages are higher in Baltimore at 16.0% compared to 0.0% in Dighton.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Baltimore | Dighton |
|---|---|---|
| No Schooling | 1.2% (6,683) | 0.0% (Data is updating) |
| High School Diploma | 16.8% (95,744) | 0.0% (Data is updating) |
| Less than High School | 11.9% (67,970) | 0.0% (Data is updating) |
| Bachelor's Degree and Higher | 25.1% (143,174) | 0.0% (Data is updating) |
Education Levels Comparison: Baltimore vs Dighton
- A higher percentage of residents in Baltimore have no formal schooling at 1.2% compared to 0.0% in Dighton.
- A higher percentage of residents in Baltimore hold a high school diploma at 16.8% compared to 0.0% in Dighton.
- More residents in Baltimore have less than a high school education at 11.9% compared to 0.0% in Dighton.
- A higher percentage of residents in Baltimore hold a bachelor's degree or higher at 25.1% compared to 0.0% in Dighton.
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.