Demographics details for Baltimore, MD vs Moody, AL
Population Overview
Compare main population characteristics in Baltimore, MD vs Moody, AL.
Data | Baltimore | Moody |
---|---|---|
Population | 569,931 | 13,587 |
Median Age | 36.0 years | 41.5 years |
Median Income | $58,349 | $77,680 |
Married Families | 23.0% | 41.0% |
Poverty Level | 16% | 9% |
Unemployment Rate | 4.3 | 3.5 |
Population Comparison: Baltimore vs Moody
- In Baltimore, the population is higher at 569,931, compared to 13,587 in Moody.
- The median age in Moody is higher at 41.5 years, compared to 36.0 years in Baltimore.
- Moody has a higher median income of $77,680, compared to $58,349 in Baltimore.
- In Moody, the percentage of married families is higher at 41.0%, compared to 23.0% in Baltimore.
- Baltimore has a higher poverty level at 16% compared to 9% in Moody.
- The unemployment rate in Baltimore is higher at 4.3%, compared to 3.5% in Moody.
Demographics
Demographics Baltimore vs Moody provide insight into the diversity of the communities to compare.
Demographic | Baltimore | Moody |
---|---|---|
Black | 63 | 8 |
White | 23 | 83 |
Asian | 3 | Data is updating |
Hispanic | 6 | 3 |
Two or More Races | 5 | 5 |
American Indian | Data is updating | 1 |
Demographics Comparison: Baltimore vs Moody
- A higher percentage of Black residents are in Baltimore at 63% compared to 8% in Moody.
- The percentage of White residents is higher in Moody at 83% compared to 23% in Baltimore.
- The Asian population is larger in Baltimore at 3% compared to 0% in Moody.
- The Hispanic community is larger in Baltimore at 6% compared to 3% in Moody.
- Both Baltimore and Moody have the same percentage of residents identifying as two or more races at 5%.
- In Moody, the percentage of American Indian residents is higher at 1%, compared to 0% in Baltimore.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
Health Metric | Baltimore | Moody |
---|---|---|
Mental Health Not Good | 17.9% | 17.7% |
Physical Health Not Good | 12.3% | 11.1% |
Depression | 20.2% | 23.6% |
Smoking | 19.8% | 16.5% |
Binge Drinking | 15.4% | 16.1% |
Obesity | 37.1% | 37.6% |
Disability Percentage | 16.0% | 14.0% |
Health Statistics Comparison: Baltimore vs Moody
- More residents in Baltimore report poor mental health at 17.9% compared to 17.7% in Moody.
- Higher depression rates are seen in Moody at 23.6% versus 20.2% in Baltimore.
- Smoking is more prevalent in Baltimore at 19.8% compared to 16.5% in Moody.
- More residents engage in binge drinking in Moody at 16.1% compared to 15.4% in Baltimore.
- Moody has higher obesity rates at 37.6% compared to 37.1% in Baltimore.
- Disability percentages are higher in Baltimore at 16.0% compared to 14.0% in Moody.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
Education Level | Baltimore | Moody |
---|---|---|
No Schooling | 1.2% (6,683) | 0.9% (119) |
High School Diploma | 16.8% (95,744) | 21.0% (2,850) |
Less than High School | 11.9% (67,970) | 8.3% (1,131) |
Bachelor's Degree and Higher | 25.1% (143,174) | 16.8% (2,283) |
Education Levels Comparison: Baltimore vs Moody
- A higher percentage of residents in Baltimore have no formal schooling at 1.2% compared to 0.9% in Moody.
- In Moody, the rate of residents with high school diplomas is higher at 21.0% compared to 16.8% in Baltimore.
- More residents in Baltimore have less than a high school education at 11.9% compared to 8.3% in Moody.
- A higher percentage of residents in Baltimore hold a bachelor's degree or higher at 25.1% compared to 16.8% in Moody.
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.