Demographics details for Kimberly, AL vs Whitehall, WI
Population Overview
Compare main population characteristics in Kimberly, AL vs Whitehall, WI.
| Data | Kimberly | Whitehall |
|---|---|---|
| Population | 4,191 | 1,632 |
| Median Age | 36.8 years | 36.8 years |
| Median Income | $107,670 | $56,894 |
| Married Families | 50.0% | 30.0% |
| Poverty Level | 4% | 7% |
| Unemployment Rate | 2.5 | 3.6 |
Population Comparison: Kimberly vs Whitehall
- In Kimberly, the population is higher at 4,191, compared to 1,632 in Whitehall.
- The median age is the same in both Kimberly and Whitehall at 36.8 years.
- Kimberly has a higher median income of $107,670 compared to $56,894 in Whitehall.
- A higher percentage of married families is found in Kimberly at 50.0% compared to 30.0% in Whitehall.
- The poverty level is higher in Whitehall at 7%, compared to 4% in Kimberly.
- Whitehall has a higher unemployment rate at 3.6% compared to 2.5% in Kimberly.
Demographics
Demographics Kimberly vs Whitehall provide insight into the diversity of the communities to compare.
| Demographic | Kimberly | Whitehall |
|---|---|---|
| Black | 4 | 1 |
| White | 88 | 83 |
| Asian | 5 | Data is updating |
| Hispanic | Data is updating | 12 |
| Two or More Races | 1 | 3 |
| American Indian | 2 | 1 |
Demographics Comparison: Kimberly vs Whitehall
- A higher percentage of Black residents are in Kimberly at 4% compared to 1% in Whitehall.
- Kimberly has a higher percentage of White residents at 88% compared to 83% in Whitehall.
- The Asian population is larger in Kimberly at 5% compared to 0% in Whitehall.
- Whitehall has a higher percentage of Hispanic residents at 12%, compared to 0% in Kimberly.
- The percentage of residents identifying as two or more races is higher in Whitehall at 3%, compared to 1% in Kimberly.
- A greater percentage of American Indian residents live in Kimberly at 2% compared to 1% in Whitehall.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Kimberly | Whitehall |
|---|---|---|
| Mental Health Not Good | 17.3% | 15.2% |
| Physical Health Not Good | 10.4% | 10.3% |
| Depression | 24.8% | 24.0% |
| Smoking | 15.2% | 16.7% |
| Binge Drinking | 18.1% | 24.4% |
| Obesity | 33.4% | 34.9% |
| Disability Percentage | 10.0% | 15.0% |
Health Statistics Comparison: Kimberly vs Whitehall
- More residents in Kimberly report poor mental health at 17.3% compared to 15.2% in Whitehall.
- Depression is more prevalent in Kimberly at 24.8% compared to 24.0% in Whitehall.
- Whitehall has a higher smoking rate at 16.7% compared to 15.2% in Kimberly.
- More residents engage in binge drinking in Whitehall at 24.4% compared to 18.1% in Kimberly.
- Whitehall has higher obesity rates at 34.9% compared to 33.4% in Kimberly.
- There is a higher percentage of disabled individuals in Whitehall at 15.0% compared to 10.0% in Kimberly.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Kimberly | Whitehall |
|---|---|---|
| No Schooling | 0.6% (24) | 0.4% (7) |
| High School Diploma | 9.8% (411) | 24.4% (398) |
| Less than High School | 6.0% (252) | 15.7% (256) |
| Bachelor's Degree and Higher | 18.3% (765) | 8.6% (141) |
Education Levels Comparison: Kimberly vs Whitehall
- A higher percentage of residents in Kimberly have no formal schooling at 0.6% compared to 0.4% in Whitehall.
- In Whitehall, the rate of residents with high school diplomas is higher at 24.4% compared to 9.8% in Kimberly.
- The percentage of residents with less than a high school education is higher in Whitehall at 15.7%, compared to 6.0% in Kimberly.
- A higher percentage of residents in Kimberly hold a bachelor's degree or higher at 18.3% compared to 8.6% in Whitehall.
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.