Demographics details for Palatka, FL vs Mount pleasant, SC
Population Overview
Compare main population characteristics in Palatka, FL vs Mount pleasant, SC.
| Data | Palatka | Mount pleasant |
|---|---|---|
| Population | 10,574 | 94,545 |
| Median Age | 39.9 years | 42.4 years |
| Median Income | $30,945 | $115,167 |
| Married Families | 18.0% | 47.0% |
| Poverty Level | 22% | 5% |
| Unemployment Rate | 5.5 | 3.2 |
Population Comparison: Palatka vs Mount pleasant
- The population in Mount pleasant is higher at 94,545, compared to 10,574 in Palatka.
- The median age in Mount pleasant is higher at 42.4 years, compared to 39.9 years in Palatka.
- Mount pleasant has a higher median income of $115,167, compared to $30,945 in Palatka.
- In Mount pleasant, the percentage of married families is higher at 47.0%, compared to 18.0% in Palatka.
- Palatka has a higher poverty level at 22% compared to 5% in Mount pleasant.
- The unemployment rate in Palatka is higher at 5.5%, compared to 3.2% in Mount pleasant.
Demographics
Demographics Palatka vs Mount pleasant provide insight into the diversity of the communities to compare.
| Demographic | Palatka | Mount pleasant |
|---|---|---|
| Black | 40 | 4 |
| White | 43 | 90 |
| Asian | 1 | 2 |
| Hispanic | 8 | 2 |
| Two or More Races | 7 | 2 |
| American Indian | 1 | Data is updating |
Demographics Comparison: Palatka vs Mount pleasant
- A higher percentage of Black residents are in Palatka at 40% compared to 4% in Mount pleasant.
- The percentage of White residents is higher in Mount pleasant at 90% compared to 43% in Palatka.
- In Mount pleasant, the Asian population stands at 2%, greater than 1% in Palatka.
- The Hispanic community is larger in Palatka at 8% compared to 2% in Mount pleasant.
- More residents identify as two or more races in Palatka at 7% compared to 2% in Mount pleasant.
- A greater percentage of American Indian residents live in Palatka at 1% compared to 0% in Mount pleasant.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Palatka | Mount pleasant |
|---|---|---|
| Mental Health Not Good | 19.4% | 13.7% |
| Physical Health Not Good | 16.4% | 7.6% |
| Depression | 20.5% | 19.5% |
| Smoking | 29.4% | 9.8% |
| Binge Drinking | 14.2% | 25.5% |
| Obesity | 40.8% | 26.9% |
| Disability Percentage | 21.0% | 6.0% |
Health Statistics Comparison: Palatka vs Mount pleasant
- More residents in Palatka report poor mental health at 19.4% compared to 13.7% in Mount pleasant.
- Depression is more prevalent in Palatka at 20.5% compared to 19.5% in Mount pleasant.
- Smoking is more prevalent in Palatka at 29.4% compared to 9.8% in Mount pleasant.
- More residents engage in binge drinking in Mount pleasant at 25.5% compared to 14.2% in Palatka.
- Obesity rates are higher in Palatka at 40.8% compared to 26.9% in Mount pleasant.
- Disability percentages are higher in Palatka at 21.0% compared to 6.0% in Mount pleasant.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Palatka | Mount pleasant |
|---|---|---|
| No Schooling | 1.0% (111) | 0.3% (259) |
| High School Diploma | 20.0% (2,118) | 5.8% (5,499) |
| Less than High School | 22.0% (2,324) | 2.7% (2,577) |
| Bachelor's Degree and Higher | 8.0% (841) | 46.2% (43,679) |
Education Levels Comparison: Palatka vs Mount pleasant
- A higher percentage of residents in Palatka have no formal schooling at 1.0% compared to 0.3% in Mount pleasant.
- A higher percentage of residents in Palatka hold a high school diploma at 20.0% compared to 5.8% in Mount pleasant.
- More residents in Palatka have less than a high school education at 22.0% compared to 2.7% in Mount pleasant.
- In Mount pleasant, a larger share of residents have a bachelor's degree or higher at 46.2% compared to 8.0% in Palatka.
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.