Demographics details for Pinola, MS vs Oceanside, CA
Population Overview
Compare main population characteristics in Pinola, MS vs Oceanside, CA.
| Data | Pinola | Oceanside |
|---|---|---|
| Population | 540 | 172,199 |
| Median Age | 36.0 years | 37.5 years |
| Median Income | $45,000 | $86,701 |
| Married Families | 60.0% | 41.0% |
| Poverty Level | 15% | 9% |
| Unemployment Rate | 5.0 | 4.6 |
Population Comparison: Pinola vs Oceanside
- The population in Oceanside is higher at 172,199, compared to 540 in Pinola.
- The median age in Oceanside is higher at 37.5 years, compared to 36.0 years in Pinola.
- Oceanside has a higher median income of $86,701, compared to $45,000 in Pinola.
- A higher percentage of married families is found in Pinola at 60.0% compared to 41.0% in Oceanside.
- Pinola has a higher poverty level at 15% compared to 9% in Oceanside.
- The unemployment rate in Pinola is higher at 5.0%, compared to 4.6% in Oceanside.
Demographics
Demographics Pinola vs Oceanside provide insight into the diversity of the communities to compare.
| Demographic | Pinola | Oceanside |
|---|---|---|
| Black | 20 | 4 |
| White | 75 | 31 |
| Asian | 2 | 7 |
| Hispanic | 3 | 38 |
| Two or More Races | Data is updating | 19 |
| American Indian | Data is updating | 1 |
Demographics Comparison: Pinola vs Oceanside
- A higher percentage of Black residents are in Pinola at 20% compared to 4% in Oceanside.
- Pinola has a higher percentage of White residents at 75% compared to 31% in Oceanside.
- In Oceanside, the Asian population stands at 7%, greater than 2% in Pinola.
- Oceanside has a higher percentage of Hispanic residents at 38%, compared to 3% in Pinola.
- The percentage of residents identifying as two or more races is higher in Oceanside at 19%, compared to 0% in Pinola.
- In Oceanside, the percentage of American Indian residents is higher at 1%, compared to 0% in Pinola.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Pinola | Oceanside |
|---|---|---|
| Mental Health Not Good | Data is updating% | 16.2% |
| Physical Health Not Good | Data is updating% | 10.9% |
| Depression | Data is updating% | 17.9% |
| Smoking | Data is updating% | 11.7% |
| Binge Drinking | Data is updating% | 18.9% |
| Obesity | Data is updating% | 25.0% |
| Disability Percentage | Data is updating% | 12.0% |
Health Statistics Comparison: Pinola vs Oceanside
- In Oceanside, a higher percentage report poor mental health at 16.2% compared to 0.0% in Pinola.
- Higher depression rates are seen in Oceanside at 17.9% versus 0.0% in Pinola.
- Oceanside has a higher smoking rate at 11.7% compared to 0.0% in Pinola.
- More residents engage in binge drinking in Oceanside at 18.9% compared to 0.0% in Pinola.
- Oceanside has higher obesity rates at 25.0% compared to 0.0% in Pinola.
- There is a higher percentage of disabled individuals in Oceanside at 12.0% compared to 0.0% in Pinola.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Pinola | Oceanside |
|---|---|---|
| No Schooling | 0.0% (Data is updating) | 1.7% (2,927) |
| High School Diploma | 0.0% (Data is updating) | 12.0% (20,662) |
| Less than High School | 0.0% (Data is updating) | 17.7% (30,528) |
| Bachelor's Degree and Higher | 0.0% (Data is updating) | 23.5% (40,490) |
Education Levels Comparison: Pinola vs Oceanside
- In Oceanside, a larger percentage of residents lack formal schooling at 1.7% compared to 0.0% in Pinola.
- In Oceanside, the rate of residents with high school diplomas is higher at 12.0% compared to 0.0% in Pinola.
- The percentage of residents with less than a high school education is higher in Oceanside at 17.7%, compared to 0.0% in Pinola.
- In Oceanside, a larger share of residents have a bachelor's degree or higher at 23.5% compared to 0.0% in Pinola.
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.