Demographics details for Big sky, MT vs Oceanside, CA
Population Overview
Compare main population characteristics in Big sky, MT vs Oceanside, CA.
| Data | Big sky | Oceanside |
|---|---|---|
| Population | 2,825 | 172,199 |
| Median Age | 37.2 years | 37.5 years |
| Median Income | $94,176 | $86,701 |
| Married Families | 43.0% | 41.0% |
| Poverty Level | 5% | 9% |
| Unemployment Rate | 3.5 | 4.6 |
Population Comparison: Big sky vs Oceanside
- The population in Oceanside is higher at 172,199, compared to 2,825 in Big sky.
- The median age in Oceanside is higher at 37.5 years, compared to 37.2 years in Big sky.
- Big sky has a higher median income of $94,176 compared to $86,701 in Oceanside.
- A higher percentage of married families is found in Big sky at 43.0% compared to 41.0% in Oceanside.
- The poverty level is higher in Oceanside at 9%, compared to 5% in Big sky.
- Oceanside has a higher unemployment rate at 4.6% compared to 3.5% in Big sky.
Demographics
Demographics Big sky vs Oceanside provide insight into the diversity of the communities to compare.
| Demographic | Big sky | Oceanside |
|---|---|---|
| Black | Data is updating | 4 |
| White | 85 | 31 |
| Asian | Data is updating | 7 |
| Hispanic | 12 | 38 |
| Two or More Races | 2 | 19 |
| American Indian | 1 | 1 |
Demographics Comparison: Big sky vs Oceanside
- In Oceanside, the percentage of Black residents is higher at 4% compared to 0% in Big sky.
- Big sky has a higher percentage of White residents at 85% compared to 31% in Oceanside.
- In Oceanside, the Asian population stands at 7%, greater than 0% in Big sky.
- Oceanside has a higher percentage of Hispanic residents at 38%, compared to 12% in Big sky.
- The percentage of residents identifying as two or more races is higher in Oceanside at 19%, compared to 2% in Big sky.
- The percentage of American Indian residents is the same in both Big sky and Oceanside at 1%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Big sky | Oceanside |
|---|---|---|
| Mental Health Not Good | 12.8% | 16.2% |
| Physical Health Not Good | 8.0% | 10.9% |
| Depression | 20.6% | 17.9% |
| Smoking | 10.7% | 11.7% |
| Binge Drinking | 24.3% | 18.9% |
| Obesity | 24.1% | 25.0% |
| Disability Percentage | 5.0% | 12.0% |
Health Statistics Comparison: Big sky vs Oceanside
- In Oceanside, a higher percentage report poor mental health at 16.2% compared to 12.8% in Big sky.
- Depression is more prevalent in Big sky at 20.6% compared to 17.9% in Oceanside.
- Oceanside has a higher smoking rate at 11.7% compared to 10.7% in Big sky.
- Binge drinking is more common in Big sky at 24.3% compared to 18.9% in Oceanside.
- Oceanside has higher obesity rates at 25.0% compared to 24.1% in Big sky.
- There is a higher percentage of disabled individuals in Oceanside at 12.0% compared to 5.0% in Big sky.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Big sky | Oceanside |
|---|---|---|
| No Schooling | 0.0% (Data is updating) | 1.7% (2,927) |
| High School Diploma | 10.1% (284) | 12.0% (20,662) |
| Less than High School | 4.2% (118) | 17.7% (30,528) |
| Bachelor's Degree and Higher | 44.6% (1,261) | 23.5% (40,490) |
Education Levels Comparison: Big sky vs Oceanside
- In Oceanside, a larger percentage of residents lack formal schooling at 1.7% compared to 0.0% in Big sky.
- In Oceanside, the rate of residents with high school diplomas is higher at 12.0% compared to 10.1% in Big sky.
- The percentage of residents with less than a high school education is higher in Oceanside at 17.7%, compared to 4.2% in Big sky.
- A higher percentage of residents in Big sky hold a bachelor's degree or higher at 44.6% compared to 23.5% in Oceanside.
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.