Demographics details for Oakland park, FL vs Tea, SD
Population Overview
Compare main population characteristics in Oakland park, FL vs Tea, SD.
Data | Oakland park | Tea |
---|---|---|
Population | 43,824 | 6,918 |
Median Age | 39.1 years | 30.2 years |
Median Income | $64,989 | $99,153 |
Married Families | 30.0% | 39.0% |
Poverty Level | 14% | 6% |
Unemployment Rate | 3.1 | 2.5 |
Population Comparison: Oakland park vs Tea
- In Oakland park, the population is higher at 43,824, compared to 6,918 in Tea.
- Residents in Oakland park have a higher median age of 39.1 years compared to 30.2 years in Tea.
- Tea has a higher median income of $99,153, compared to $64,989 in Oakland park.
- In Tea, the percentage of married families is higher at 39.0%, compared to 30.0% in Oakland park.
- Oakland park has a higher poverty level at 14% compared to 6% in Tea.
- The unemployment rate in Oakland park is higher at 3.1%, compared to 2.5% in Tea.
Demographics
Demographics Oakland park vs Tea provide insight into the diversity of the communities to compare.
Demographic | Oakland park | Tea |
---|---|---|
Black | 29 | 2 |
White | 20 | 95 |
Asian | 2 | 1 |
Hispanic | 32 | Data is updating |
Two or More Races | 17 | 2 |
American Indian | Data is updating | Data is updating |
Demographics Comparison: Oakland park vs Tea
- A higher percentage of Black residents are in Oakland park at 29% compared to 2% in Tea.
- The percentage of White residents is higher in Tea at 95% compared to 20% in Oakland park.
- The Asian population is larger in Oakland park at 2% compared to 1% in Tea.
- The Hispanic community is larger in Oakland park at 32% compared to 0% in Tea.
- More residents identify as two or more races in Oakland park at 17% compared to 2% in Tea.
- The percentage of American Indian residents is the same in both Oakland park and Tea at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
Health Metric | Oakland park | Tea |
---|---|---|
Mental Health Not Good | 16.3% | 11.3% |
Physical Health Not Good | 12.2% | 7.7% |
Depression | 17.8% | 16.6% |
Smoking | 20.1% | 12.6% |
Binge Drinking | 15.0% | 21.6% |
Obesity | 31.1% | 34.5% |
Disability Percentage | 11.0% | 4.0% |
Health Statistics Comparison: Oakland park vs Tea
- More residents in Oakland park report poor mental health at 16.3% compared to 11.3% in Tea.
- Depression is more prevalent in Oakland park at 17.8% compared to 16.6% in Tea.
- Smoking is more prevalent in Oakland park at 20.1% compared to 12.6% in Tea.
- More residents engage in binge drinking in Tea at 21.6% compared to 15.0% in Oakland park.
- Tea has higher obesity rates at 34.5% compared to 31.1% in Oakland park.
- Disability percentages are higher in Oakland park at 11.0% compared to 4.0% in Tea.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
Education Level | Oakland park | Tea |
---|---|---|
No Schooling | 1.4% (596) | 0.1% (10) |
High School Diploma | 19.8% (8,695) | 7.8% (537) |
Less than High School | 16.2% (7,092) | 1.6% (108) |
Bachelor's Degree and Higher | 20.7% (9,073) | 19.9% (1,378) |
Education Levels Comparison: Oakland park vs Tea
- A higher percentage of residents in Oakland park have no formal schooling at 1.4% compared to 0.1% in Tea.
- A higher percentage of residents in Oakland park hold a high school diploma at 19.8% compared to 7.8% in Tea.
- More residents in Oakland park have less than a high school education at 16.2% compared to 1.6% in Tea.
- A higher percentage of residents in Oakland park hold a bachelor's degree or higher at 20.7% compared to 19.9% in Tea.
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.