Demographics details for Forest, MS vs Warrensburg, MO
Population Overview
Compare main population characteristics in Forest, MS vs Warrensburg, MO.
| Data | Forest | Warrensburg |
|---|---|---|
| Population | 5,330 | 19,458 |
| Median Age | 36.4 years | 24.4 years |
| Median Income | $50,093 | $54,535 |
| Married Families | 35.0% | 27.0% |
| Poverty Level | 18% | 14% |
| Unemployment Rate | 4.5 | 3.5 |
Population Comparison: Forest vs Warrensburg
- The population in Warrensburg is higher at 19,458, compared to 5,330 in Forest.
- Residents in Forest have a higher median age of 36.4 years compared to 24.4 years in Warrensburg.
- Warrensburg has a higher median income of $54,535, compared to $50,093 in Forest.
- A higher percentage of married families is found in Forest at 35.0% compared to 27.0% in Warrensburg.
- Forest has a higher poverty level at 18% compared to 14% in Warrensburg.
- The unemployment rate in Forest is higher at 4.5%, compared to 3.5% in Warrensburg.
Demographics
Demographics Forest vs Warrensburg provide insight into the diversity of the communities to compare.
| Demographic | Forest | Warrensburg |
|---|---|---|
| Black | 43 | 4 |
| White | 24 | 80 |
| Asian | Data is updating | 3 |
| Hispanic | 30 | 6 |
| Two or More Races | 3 | 7 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Forest vs Warrensburg
- A higher percentage of Black residents are in Forest at 43% compared to 4% in Warrensburg.
- The percentage of White residents is higher in Warrensburg at 80% compared to 24% in Forest.
- In Warrensburg, the Asian population stands at 3%, greater than 0% in Forest.
- The Hispanic community is larger in Forest at 30% compared to 6% in Warrensburg.
- The percentage of residents identifying as two or more races is higher in Warrensburg at 7%, compared to 3% in Forest.
- The percentage of American Indian residents is the same in both Forest and Warrensburg at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Forest | Warrensburg |
|---|---|---|
| Mental Health Not Good | 18.9% | 18.4% |
| Physical Health Not Good | 16.8% | 12.7% |
| Depression | 21.2% | 24.3% |
| Smoking | 26.1% | 20.8% |
| Binge Drinking | 11.8% | 16.8% |
| Obesity | 45.7% | 37.2% |
| Disability Percentage | 20.0% | 11.0% |
Health Statistics Comparison: Forest vs Warrensburg
- More residents in Forest report poor mental health at 18.9% compared to 18.4% in Warrensburg.
- Higher depression rates are seen in Warrensburg at 24.3% versus 21.2% in Forest.
- Smoking is more prevalent in Forest at 26.1% compared to 20.8% in Warrensburg.
- More residents engage in binge drinking in Warrensburg at 16.8% compared to 11.8% in Forest.
- Obesity rates are higher in Forest at 45.7% compared to 37.2% in Warrensburg.
- Disability percentages are higher in Forest at 20.0% compared to 11.0% in Warrensburg.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Forest | Warrensburg |
|---|---|---|
| No Schooling | 4.4% (232) | 0.8% (150) |
| High School Diploma | 10.5% (557) | 9.7% (1,895) |
| Less than High School | 33.4% (1,779) | 6.0% (1,174) |
| Bachelor's Degree and Higher | 8.5% (455) | 18.4% (3,573) |
Education Levels Comparison: Forest vs Warrensburg
- A higher percentage of residents in Forest have no formal schooling at 4.4% compared to 0.8% in Warrensburg.
- A higher percentage of residents in Forest hold a high school diploma at 10.5% compared to 9.7% in Warrensburg.
- More residents in Forest have less than a high school education at 33.4% compared to 6.0% in Warrensburg.
- In Warrensburg, a larger share of residents have a bachelor's degree or higher at 18.4% compared to 8.5% in Forest.
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.