Demographics details for Cocoa beach, FL vs Peru, IN
Population Overview
Compare main population characteristics in Cocoa beach, FL vs Peru, IN.
| Data | Cocoa beach | Peru |
|---|---|---|
| Population | 11,341 | 10,828 |
| Median Age | 58.6 years | 41.3 years |
| Median Income | $80,880 | $44,665 |
| Married Families | 50.0% | 34.0% |
| Poverty Level | 7% | 15% |
| Unemployment Rate | 3.5 | 3.2 |
Population Comparison: Cocoa beach vs Peru
- In Cocoa beach, the population is higher at 11,341, compared to 10,828 in Peru.
- Residents in Cocoa beach have a higher median age of 58.6 years compared to 41.3 years in Peru.
- Cocoa beach has a higher median income of $80,880 compared to $44,665 in Peru.
- A higher percentage of married families is found in Cocoa beach at 50.0% compared to 34.0% in Peru.
- The poverty level is higher in Peru at 15%, compared to 7% in Cocoa beach.
- The unemployment rate in Cocoa beach is higher at 3.5%, compared to 3.2% in Peru.
Demographics
Demographics Cocoa beach vs Peru provide insight into the diversity of the communities to compare.
| Demographic | Cocoa beach | Peru |
|---|---|---|
| Black | 1 | 5 |
| White | 85 | 84 |
| Asian | 1 | Data is updating |
| Hispanic | 7 | 4 |
| Two or More Races | 6 | 7 |
| American Indian | Data is updating | Data is updating |
Demographics Comparison: Cocoa beach vs Peru
- In Peru, the percentage of Black residents is higher at 5% compared to 1% in Cocoa beach.
- Cocoa beach has a higher percentage of White residents at 85% compared to 84% in Peru.
- The Asian population is larger in Cocoa beach at 1% compared to 0% in Peru.
- The Hispanic community is larger in Cocoa beach at 7% compared to 4% in Peru.
- The percentage of residents identifying as two or more races is higher in Peru at 7%, compared to 6% in Cocoa beach.
- The percentage of American Indian residents is the same in both Cocoa beach and Peru at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Cocoa beach | Peru |
|---|---|---|
| Mental Health Not Good | 14.6% | 20.1% |
| Physical Health Not Good | 8.7% | 14.3% |
| Depression | 19.5% | 28.8% |
| Smoking | 14.5% | 25.7% |
| Binge Drinking | 17.9% | 16.2% |
| Obesity | 29.4% | 39.3% |
| Disability Percentage | 19.0% | 21.0% |
Health Statistics Comparison: Cocoa beach vs Peru
- In Peru, a higher percentage report poor mental health at 20.1% compared to 14.6% in Cocoa beach.
- Higher depression rates are seen in Peru at 28.8% versus 19.5% in Cocoa beach.
- Peru has a higher smoking rate at 25.7% compared to 14.5% in Cocoa beach.
- Binge drinking is more common in Cocoa beach at 17.9% compared to 16.2% in Peru.
- Peru has higher obesity rates at 39.3% compared to 29.4% in Cocoa beach.
- There is a higher percentage of disabled individuals in Peru at 21.0% compared to 19.0% in Cocoa beach.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Cocoa beach | Peru |
|---|---|---|
| No Schooling | 0.4% (48) | 1.3% (137) |
| High School Diploma | 11.7% (1,326) | 24.4% (2,642) |
| Less than High School | 4.7% (532) | 17.5% (1,900) |
| Bachelor's Degree and Higher | 43.6% (4,948) | 10.1% (1,098) |
Education Levels Comparison: Cocoa beach vs Peru
- In Peru, a larger percentage of residents lack formal schooling at 1.3% compared to 0.4% in Cocoa beach.
- In Peru, the rate of residents with high school diplomas is higher at 24.4% compared to 11.7% in Cocoa beach.
- The percentage of residents with less than a high school education is higher in Peru at 17.5%, compared to 4.7% in Cocoa beach.
- A higher percentage of residents in Cocoa beach hold a bachelor's degree or higher at 43.6% compared to 10.1% in Peru.
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.