Demographics details for Dublin, CA vs Mount pleasant, SC
Population Overview
Compare main population characteristics in Dublin, CA vs Mount pleasant, SC.
| Data | Dublin | Mount pleasant |
|---|---|---|
| Population | 72,060 | 94,545 |
| Median Age | 37.1 years | 42.4 years |
| Median Income | $191,039 | $115,167 |
| Married Families | 47.0% | 47.0% |
| Poverty Level | 5% | 5% |
| Unemployment Rate | 4.3 | 3.2 |
Population Comparison: Dublin vs Mount pleasant
- The population in Mount pleasant is higher at 94,545, compared to 72,060 in Dublin.
- The median age in Mount pleasant is higher at 42.4 years, compared to 37.1 years in Dublin.
- Dublin has a higher median income of $191,039 compared to $115,167 in Mount pleasant.
- The percentage of married families is the same in both Dublin and Mount pleasant at 47.0%.
- The poverty level is identical in both Dublin and Mount pleasant at 5%.
- The unemployment rate in Dublin is higher at 4.3%, compared to 3.2% in Mount pleasant.
Demographics
Demographics Dublin vs Mount pleasant provide insight into the diversity of the communities to compare.
| Demographic | Dublin | Mount pleasant |
|---|---|---|
| Black | 4 | 4 |
| White | 23 | 90 |
| Asian | 53 | 2 |
| Hispanic | 10 | 2 |
| Two or More Races | 9 | 2 |
| American Indian | 1 | Data is updating |
Demographics Comparison: Dublin vs Mount pleasant
- The percentage of Black residents is the same in both Dublin and Mount pleasant at 4%.
- The percentage of White residents is higher in Mount pleasant at 90% compared to 23% in Dublin.
- The Asian population is larger in Dublin at 53% compared to 2% in Mount pleasant.
- The Hispanic community is larger in Dublin at 10% compared to 2% in Mount pleasant.
- More residents identify as two or more races in Dublin at 9% compared to 2% in Mount pleasant.
- A greater percentage of American Indian residents live in Dublin at 1% compared to 0% in Mount pleasant.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Dublin | Mount pleasant |
|---|---|---|
| Mental Health Not Good | 12.8% | 13.7% |
| Physical Health Not Good | 7.3% | 7.6% |
| Depression | 16.2% | 19.5% |
| Smoking | 7.4% | 9.8% |
| Binge Drinking | 16.8% | 25.5% |
| Obesity | 23.6% | 26.9% |
| Disability Percentage | 6.0% | 6.0% |
Health Statistics Comparison: Dublin vs Mount pleasant
- In Mount pleasant, a higher percentage report poor mental health at 13.7% compared to 12.8% in Dublin.
- Higher depression rates are seen in Mount pleasant at 19.5% versus 16.2% in Dublin.
- Mount pleasant has a higher smoking rate at 9.8% compared to 7.4% in Dublin.
- More residents engage in binge drinking in Mount pleasant at 25.5% compared to 16.8% in Dublin.
- Mount pleasant has higher obesity rates at 26.9% compared to 23.6% in Dublin.
- Disability percentages are the same in both Dublin and Mount pleasant at 6.0%.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Dublin | Mount pleasant |
|---|---|---|
| No Schooling | 0.6% (461) | 0.3% (259) |
| High School Diploma | 5.9% (4,230) | 5.8% (5,499) |
| Less than High School | 4.3% (3,081) | 2.7% (2,577) |
| Bachelor's Degree and Higher | 46.5% (33,513) | 46.2% (43,679) |
Education Levels Comparison: Dublin vs Mount pleasant
- A higher percentage of residents in Dublin have no formal schooling at 0.6% compared to 0.3% in Mount pleasant.
- A higher percentage of residents in Dublin hold a high school diploma at 5.9% compared to 5.8% in Mount pleasant.
- More residents in Dublin have less than a high school education at 4.3% compared to 2.7% in Mount pleasant.
- A higher percentage of residents in Dublin hold a bachelor's degree or higher at 46.5% compared to 46.2% in Mount pleasant.
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.