Demographics details for Deerfield beach, FL vs Winona, MN
Population Overview
Compare main population characteristics in Deerfield beach, FL vs Winona, MN.
| Data | Deerfield beach | Winona |
|---|---|---|
| Population | 86,772 | 25,842 |
| Median Age | 43.5 years | 30.7 years |
| Median Income | $53,741 | $52,500 |
| Married Families | 35.0% | 28.0% |
| Poverty Level | 12% | 12% |
| Unemployment Rate | 3.2 | 3.6 |
Population Comparison: Deerfield beach vs Winona
- In Deerfield beach, the population is higher at 86,772, compared to 25,842 in Winona.
- Residents in Deerfield beach have a higher median age of 43.5 years compared to 30.7 years in Winona.
- Deerfield beach has a higher median income of $53,741 compared to $52,500 in Winona.
- A higher percentage of married families is found in Deerfield beach at 35.0% compared to 28.0% in Winona.
- The poverty level is identical in both Deerfield beach and Winona at 12%.
- Winona has a higher unemployment rate at 3.6% compared to 3.2% in Deerfield beach.
Demographics
Demographics Deerfield beach vs Winona provide insight into the diversity of the communities to compare.
| Demographic | Deerfield beach | Winona |
|---|---|---|
| Black | 24 | 2 |
| White | 33 | 88 |
| Asian | 2 | 2 |
| Hispanic | 24 | 4 |
| Two or More Races | 17 | 3 |
| American Indian | Data is updating | 1 |
Demographics Comparison: Deerfield beach vs Winona
- A higher percentage of Black residents are in Deerfield beach at 24% compared to 2% in Winona.
- The percentage of White residents is higher in Winona at 88% compared to 33% in Deerfield beach.
- Both Deerfield beach and Winona have the same percentage of Asian residents at 2%.
- The Hispanic community is larger in Deerfield beach at 24% compared to 4% in Winona.
- More residents identify as two or more races in Deerfield beach at 17% compared to 3% in Winona.
- In Winona, the percentage of American Indian residents is higher at 1%, compared to 0% in Deerfield beach.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Deerfield beach | Winona |
|---|---|---|
| Mental Health Not Good | 16.6% | 16.1% |
| Physical Health Not Good | 11.6% | 10.1% |
| Depression | 18.5% | 24.4% |
| Smoking | 19.8% | 18.5% |
| Binge Drinking | 15.1% | 19.8% |
| Obesity | 30.3% | 40.0% |
| Disability Percentage | 14.0% | 10.0% |
Health Statistics Comparison: Deerfield beach vs Winona
- More residents in Deerfield beach report poor mental health at 16.6% compared to 16.1% in Winona.
- Higher depression rates are seen in Winona at 24.4% versus 18.5% in Deerfield beach.
- Smoking is more prevalent in Deerfield beach at 19.8% compared to 18.5% in Winona.
- More residents engage in binge drinking in Winona at 19.8% compared to 15.1% in Deerfield beach.
- Winona has higher obesity rates at 40.0% compared to 30.3% in Deerfield beach.
- Disability percentages are higher in Deerfield beach at 14.0% compared to 10.0% in Winona.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Deerfield beach | Winona |
|---|---|---|
| No Schooling | 1.8% (1,563) | 0.6% (144) |
| High School Diploma | 18.7% (16,205) | 14.2% (3,665) |
| Less than High School | 18.3% (15,908) | 7.1% (1,840) |
| Bachelor's Degree and Higher | 20.3% (17,606) | 19.8% (5,111) |
Education Levels Comparison: Deerfield beach vs Winona
- A higher percentage of residents in Deerfield beach have no formal schooling at 1.8% compared to 0.6% in Winona.
- A higher percentage of residents in Deerfield beach hold a high school diploma at 18.7% compared to 14.2% in Winona.
- More residents in Deerfield beach have less than a high school education at 18.3% compared to 7.1% in Winona.
- A higher percentage of residents in Deerfield beach hold a bachelor's degree or higher at 20.3% compared to 19.8% in Winona.
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.