Demographics details for Clinton, SC vs Chester, MA
Population Overview
Compare main population characteristics in Clinton, SC vs Chester, MA.
| Data | Clinton | Chester |
|---|---|---|
| Population | 7,554 | 1,337 |
| Median Age | 35.4 years | 41.0 years |
| Median Income | $38,350 | $78,889 |
| Married Families | 19.0% | 64.0% |
| Poverty Level | 18% | 4% |
| Unemployment Rate | 4.5 | 3.3 |
Population Comparison: Clinton vs Chester
- In Clinton, the population is higher at 7,554, compared to 1,337 in Chester.
- The median age in Chester is higher at 41.0 years, compared to 35.4 years in Clinton.
- Chester has a higher median income of $78,889, compared to $38,350 in Clinton.
- In Chester, the percentage of married families is higher at 64.0%, compared to 19.0% in Clinton.
- Clinton has a higher poverty level at 18% compared to 4% in Chester.
- The unemployment rate in Clinton is higher at 4.5%, compared to 3.3% in Chester.
Demographics
Demographics Clinton vs Chester provide insight into the diversity of the communities to compare.
| Demographic | Clinton | Chester |
|---|---|---|
| Black | 38 | Data is updating |
| White | 55 | 100 |
| Asian | 2 | Data is updating |
| Hispanic | 1 | Data is updating |
| Two or More Races | 4 | Data is updating |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Clinton vs Chester
- A higher percentage of Black residents are in Clinton at 38% compared to 0% in Chester.
- The percentage of White residents is higher in Chester at 100% compared to 55% in Clinton.
- The Asian population is larger in Clinton at 2% compared to 0% in Chester.
- The Hispanic community is larger in Clinton at 1% compared to 0% in Chester.
- More residents identify as two or more races in Clinton at 4% compared to 0% in Chester.
- The percentage of American Indian residents is the same in both Clinton and Chester at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Clinton | Chester |
|---|---|---|
| Mental Health Not Good | 19.1% | Data is updating% |
| Physical Health Not Good | 14.0% | Data is updating% |
| Depression | 23.7% | Data is updating% |
| Smoking | 22.0% | Data is updating% |
| Binge Drinking | 15.8% | Data is updating% |
| Obesity | 44.9% | Data is updating% |
| Disability Percentage | 17.0% | Data is updating% |
Health Statistics Comparison: Clinton vs Chester
- More residents in Clinton report poor mental health at 19.1% compared to 0.0% in Chester.
- Depression is more prevalent in Clinton at 23.7% compared to 0.0% in Chester.
- Smoking is more prevalent in Clinton at 22.0% compared to 0.0% in Chester.
- Binge drinking is more common in Clinton at 15.8% compared to 0.0% in Chester.
- Obesity rates are higher in Clinton at 44.9% compared to 0.0% in Chester.
- Disability percentages are higher in Clinton at 17.0% compared to 0.0% in Chester.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Clinton | Chester |
|---|---|---|
| No Schooling | 1.0% (74) | 0.0% (Data is updating) |
| High School Diploma | 19.3% (1,460) | 0.0% (Data is updating) |
| Less than High School | 15.6% (1,177) | 0.0% (Data is updating) |
| Bachelor's Degree and Higher | 17.3% (1,310) | 0.0% (Data is updating) |
Education Levels Comparison: Clinton vs Chester
- A higher percentage of residents in Clinton have no formal schooling at 1.0% compared to 0.0% in Chester.
- A higher percentage of residents in Clinton hold a high school diploma at 19.3% compared to 0.0% in Chester.
- More residents in Clinton have less than a high school education at 15.6% compared to 0.0% in Chester.
- A higher percentage of residents in Clinton hold a bachelor's degree or higher at 17.3% compared to 0.0% in Chester.
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.