Demographics details for Cornelia, GA vs Mount pleasant, SC
Population Overview
Compare main population characteristics in Cornelia, GA vs Mount pleasant, SC.
| Data | Cornelia | Mount pleasant |
|---|---|---|
| Population | 5,004 | 94,545 |
| Median Age | 30.4 years | 42.4 years |
| Median Income | $46,211 | $115,167 |
| Married Families | 32.0% | 47.0% |
| Poverty Level | 12% | 5% |
| Unemployment Rate | 3.5 | 3.2 |
Population Comparison: Cornelia vs Mount pleasant
- The population in Mount pleasant is higher at 94,545, compared to 5,004 in Cornelia.
- The median age in Mount pleasant is higher at 42.4 years, compared to 30.4 years in Cornelia.
- Mount pleasant has a higher median income of $115,167, compared to $46,211 in Cornelia.
- In Mount pleasant, the percentage of married families is higher at 47.0%, compared to 32.0% in Cornelia.
- Cornelia has a higher poverty level at 12% compared to 5% in Mount pleasant.
- The unemployment rate in Cornelia is higher at 3.5%, compared to 3.2% in Mount pleasant.
Demographics
Demographics Cornelia vs Mount pleasant provide insight into the diversity of the communities to compare.
| Demographic | Cornelia | Mount pleasant |
|---|---|---|
| Black | 9 | 4 |
| White | 43 | 90 |
| Asian | 3 | 2 |
| Hispanic | 32 | 2 |
| Two or More Races | 13 | 2 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Cornelia vs Mount pleasant
- A higher percentage of Black residents are in Cornelia at 9% compared to 4% in Mount pleasant.
- The percentage of White residents is higher in Mount pleasant at 90% compared to 43% in Cornelia.
- The Asian population is larger in Cornelia at 3% compared to 2% in Mount pleasant.
- The Hispanic community is larger in Cornelia at 32% compared to 2% in Mount pleasant.
- More residents identify as two or more races in Cornelia at 13% compared to 2% in Mount pleasant.
- The percentage of American Indian residents is the same in both Cornelia and Mount pleasant at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Cornelia | Mount pleasant |
|---|---|---|
| Mental Health Not Good | 18.2% | 13.7% |
| Physical Health Not Good | 14.7% | 7.6% |
| Depression | 22.4% | 19.5% |
| Smoking | 20.2% | 9.8% |
| Binge Drinking | 14.4% | 25.5% |
| Obesity | 34.6% | 26.9% |
| Disability Percentage | 13.0% | 6.0% |
Health Statistics Comparison: Cornelia vs Mount pleasant
- More residents in Cornelia report poor mental health at 18.2% compared to 13.7% in Mount pleasant.
- Depression is more prevalent in Cornelia at 22.4% compared to 19.5% in Mount pleasant.
- Smoking is more prevalent in Cornelia at 20.2% compared to 9.8% in Mount pleasant.
- More residents engage in binge drinking in Mount pleasant at 25.5% compared to 14.4% in Cornelia.
- Obesity rates are higher in Cornelia at 34.6% compared to 26.9% in Mount pleasant.
- Disability percentages are higher in Cornelia at 13.0% 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 | Cornelia | Mount pleasant |
|---|---|---|
| No Schooling | 3.6% (179) | 0.3% (259) |
| High School Diploma | 9.5% (473) | 5.8% (5,499) |
| Less than High School | 35.8% (1,790) | 2.7% (2,577) |
| Bachelor's Degree and Higher | 12.5% (625) | 46.2% (43,679) |
Education Levels Comparison: Cornelia vs Mount pleasant
- A higher percentage of residents in Cornelia have no formal schooling at 3.6% compared to 0.3% in Mount pleasant.
- A higher percentage of residents in Cornelia hold a high school diploma at 9.5% compared to 5.8% in Mount pleasant.
- More residents in Cornelia have less than a high school education at 35.8% 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 12.5% in Cornelia.
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.