Demographics details for Jefferson, SD vs Santa clara, CA
Population Overview
Compare main population characteristics in Jefferson, SD vs Santa clara, CA.
| Data | Jefferson | Santa clara |
|---|---|---|
| Population | 457 | 126,930 |
| Median Age | 37.1 years | 34.5 years |
| Median Income | $77,601 | $165,352 |
| Married Families | 59.0% | 45.0% |
| Poverty Level | 5% | 8% |
| Unemployment Rate | 2.3 | 3.9 |
Population Comparison: Jefferson vs Santa clara
- The population in Santa clara is higher at 126,930, compared to 457 in Jefferson.
- Residents in Jefferson have a higher median age of 37.1 years compared to 34.5 years in Santa clara.
- Santa clara has a higher median income of $165,352, compared to $77,601 in Jefferson.
- A higher percentage of married families is found in Jefferson at 59.0% compared to 45.0% in Santa clara.
- The poverty level is higher in Santa clara at 8%, compared to 5% in Jefferson.
- Santa clara has a higher unemployment rate at 3.9% compared to 2.3% in Jefferson.
Demographics
Demographics Jefferson vs Santa clara provide insight into the diversity of the communities to compare.
| Demographic | Jefferson | Santa clara |
|---|---|---|
| Black | Data is updating | 2 |
| White | 85 | 27 |
| Asian | Data is updating | 48 |
| Hispanic | 6 | 15 |
| Two or More Races | 4 | 8 |
| American Indian | 5 | Data is updating |
Demographics Comparison: Jefferson vs Santa clara
- In Santa clara, the percentage of Black residents is higher at 2% compared to 0% in Jefferson.
- Jefferson has a higher percentage of White residents at 85% compared to 27% in Santa clara.
- In Santa clara, the Asian population stands at 48%, greater than 0% in Jefferson.
- Santa clara has a higher percentage of Hispanic residents at 15%, compared to 6% in Jefferson.
- The percentage of residents identifying as two or more races is higher in Santa clara at 8%, compared to 4% in Jefferson.
- A greater percentage of American Indian residents live in Jefferson at 5% compared to 0% in Santa clara.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Jefferson | Santa clara |
|---|---|---|
| Mental Health Not Good | 12.5% | 12.0% |
| Physical Health Not Good | 8.2% | 7.4% |
| Depression | 16.7% | 14.2% |
| Smoking | 14.5% | 7.1% |
| Binge Drinking | 20.4% | 13.9% |
| Obesity | 38.6% | 18.6% |
| Disability Percentage | 14.0% | 7.0% |
Health Statistics Comparison: Jefferson vs Santa clara
- More residents in Jefferson report poor mental health at 12.5% compared to 12.0% in Santa clara.
- Depression is more prevalent in Jefferson at 16.7% compared to 14.2% in Santa clara.
- Smoking is more prevalent in Jefferson at 14.5% compared to 7.1% in Santa clara.
- Binge drinking is more common in Jefferson at 20.4% compared to 13.9% in Santa clara.
- Obesity rates are higher in Jefferson at 38.6% compared to 18.6% in Santa clara.
- Disability percentages are higher in Jefferson at 14.0% compared to 7.0% in Santa clara.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Jefferson | Santa clara |
|---|---|---|
| No Schooling | 0.0% (Data is updating) | 0.9% (1,134) |
| High School Diploma | 22.3% (102) | 7.3% (9,232) |
| Less than High School | 7.9% (36) | 7.1% (8,967) |
| Bachelor's Degree and Higher | 23.0% (105) | 46.5% (58,962) |
Education Levels Comparison: Jefferson vs Santa clara
- In Santa clara, a larger percentage of residents lack formal schooling at 0.9% compared to 0.0% in Jefferson.
- A higher percentage of residents in Jefferson hold a high school diploma at 22.3% compared to 7.3% in Santa clara.
- More residents in Jefferson have less than a high school education at 7.9% compared to 7.1% in Santa clara.
- In Santa clara, a larger share of residents have a bachelor's degree or higher at 46.5% compared to 23.0% in Jefferson.
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.