Demographics details for Patoka, IL vs Deerfield beach, FL
Population Overview
Compare main population characteristics in Patoka, IL vs Deerfield beach, FL.
Data | Patoka | Deerfield beach |
---|---|---|
Population | 512 | 86,772 |
Median Age | 39.2 years | 43.5 years |
Median Income | $69,091 | $53,741 |
Married Families | 54.0% | 35.0% |
Poverty Level | 10% | 12% |
Unemployment Rate | 5.0 | 3.2 |
Population Comparison: Patoka vs Deerfield beach
- The population in Deerfield beach is higher at 86,772, compared to 512 in Patoka.
- The median age in Deerfield beach is higher at 43.5 years, compared to 39.2 years in Patoka.
- Patoka has a higher median income of $69,091 compared to $53,741 in Deerfield beach.
- A higher percentage of married families is found in Patoka at 54.0% compared to 35.0% in Deerfield beach.
- The poverty level is higher in Deerfield beach at 12%, compared to 10% in Patoka.
- The unemployment rate in Patoka is higher at 5.0%, compared to 3.2% in Deerfield beach.
Demographics
Demographics Patoka vs Deerfield beach provide insight into the diversity of the communities to compare.
Demographic | Patoka | Deerfield beach |
---|---|---|
Black | Data is updating | 24 |
White | 98 | 33 |
Asian | 1 | 2 |
Hispanic | Data is updating | 24 |
Two or More Races | 1 | 17 |
American Indian | Data is updating | Data is updating |
Demographics Comparison: Patoka vs Deerfield beach
- In Deerfield beach, the percentage of Black residents is higher at 24% compared to 0% in Patoka.
- Patoka has a higher percentage of White residents at 98% compared to 33% in Deerfield beach.
- In Deerfield beach, the Asian population stands at 2%, greater than 1% in Patoka.
- Deerfield beach has a higher percentage of Hispanic residents at 24%, compared to 0% in Patoka.
- The percentage of residents identifying as two or more races is higher in Deerfield beach at 17%, compared to 1% in Patoka.
- The percentage of American Indian residents is the same in both Patoka and Deerfield beach at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
Health Metric | Patoka | Deerfield beach |
---|---|---|
Mental Health Not Good | 16.8% | 16.6% |
Physical Health Not Good | 11.2% | 11.6% |
Depression | 23.2% | 18.5% |
Smoking | 17.8% | 19.8% |
Binge Drinking | 18.6% | 15.1% |
Obesity | 37.4% | 30.3% |
Disability Percentage | 21.0% | 14.0% |
Health Statistics Comparison: Patoka vs Deerfield beach
- More residents in Patoka report poor mental health at 16.8% compared to 16.6% in Deerfield beach.
- Depression is more prevalent in Patoka at 23.2% compared to 18.5% in Deerfield beach.
- Deerfield beach has a higher smoking rate at 19.8% compared to 17.8% in Patoka.
- Binge drinking is more common in Patoka at 18.6% compared to 15.1% in Deerfield beach.
- Obesity rates are higher in Patoka at 37.4% compared to 30.3% in Deerfield beach.
- Disability percentages are higher in Patoka at 21.0% compared to 14.0% in Deerfield beach.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
Education Level | Patoka | Deerfield beach |
---|---|---|
No Schooling | 0.6% (3) | 1.8% (1,563) |
High School Diploma | 32.8% (168) | 18.7% (16,205) |
Less than High School | 6.6% (34) | 18.3% (15,908) |
Bachelor's Degree and Higher | 11.1% (57) | 20.3% (17,606) |
Education Levels Comparison: Patoka vs Deerfield beach
- In Deerfield beach, a larger percentage of residents lack formal schooling at 1.8% compared to 0.6% in Patoka.
- A higher percentage of residents in Patoka hold a high school diploma at 32.8% compared to 18.7% in Deerfield beach.
- The percentage of residents with less than a high school education is higher in Deerfield beach at 18.3%, compared to 6.6% in Patoka.
- In Deerfield beach, a larger share of residents have a bachelor's degree or higher at 20.3% compared to 11.1% in Patoka.
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.