Demographics details for Ontario, CA vs Forest, MS
Population Overview
Compare main population characteristics in Ontario, CA vs Forest, MS.
| Data | Ontario | Forest |
|---|---|---|
| Population | 184,705 | 5,330 |
| Median Age | 34.3 years | 36.4 years |
| Median Income | $67,659 | $50,093 |
| Married Families | 30.5% | 35.0% |
| Poverty Level | 14% | 18% |
| Unemployment Rate | 5.1 | 4.5 |
Population Comparison: Ontario vs Forest
- In Ontario, the population is higher at 184,705, compared to 5,330 in Forest.
- The median age in Forest is higher at 36.4 years, compared to 34.3 years in Ontario.
- Ontario has a higher median income of $67,659 compared to $50,093 in Forest.
- In Forest, the percentage of married families is higher at 35.0%, compared to 30.5% in Ontario.
- The poverty level is higher in Forest at 18%, compared to 14% in Ontario.
- The unemployment rate in Ontario is higher at 5.1%, compared to 4.5% in Forest.
Demographics
Demographics Ontario vs Forest provide insight into the diversity of the communities to compare.
| Demographic | Ontario | Forest |
|---|---|---|
| Black | 8.5 | 43 |
| White | 36.2 | 24 |
| Asian | 6.0 | Data is updating |
| Hispanic | 44.5 | 30 |
| Two or More Races | 4.8 | 3 |
| American Indian | 0.5 | Data is updating |
Demographics Comparison: Ontario vs Forest
- In Forest, the percentage of Black residents is higher at 43% compared to 8.5% in Ontario.
- Ontario has a higher percentage of White residents at 36.2% compared to 24% in Forest.
- The Asian population is larger in Ontario at 6.0% compared to 0% in Forest.
- The Hispanic community is larger in Ontario at 44.5% compared to 30% in Forest.
- More residents identify as two or more races in Ontario at 4.8% compared to 3% in Forest.
- A greater percentage of American Indian residents live in Ontario at 0.5% compared to 0% in Forest.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Ontario | Forest |
|---|---|---|
| Mental Health Not Good | Data is updating% | 18.9% |
| Physical Health Not Good | Data is updating% | 16.8% |
| Depression | Data is updating% | 21.2% |
| Smoking | Data is updating% | 26.1% |
| Binge Drinking | Data is updating% | 11.8% |
| Obesity | Data is updating% | 45.7% |
| Disability Percentage | Data is updating% | 20.0% |
Health Statistics Comparison: Ontario vs Forest
- In Forest, a higher percentage report poor mental health at 18.9% compared to 0.0% in Ontario.
- Higher depression rates are seen in Forest at 21.2% versus 0.0% in Ontario.
- Forest has a higher smoking rate at 26.1% compared to 0.0% in Ontario.
- More residents engage in binge drinking in Forest at 11.8% compared to 0.0% in Ontario.
- Forest has higher obesity rates at 45.7% compared to 0.0% in Ontario.
- There is a higher percentage of disabled individuals in Forest at 20.0% compared to 0.0% in Ontario.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Ontario | Forest |
|---|---|---|
| No Schooling | 0.0% (Data is updating) | 4.4% (232) |
| High School Diploma | 0.0% (Data is updating) | 10.5% (557) |
| Less than High School | 0.0% (Data is updating) | 33.4% (1,779) |
| Bachelor's Degree and Higher | 0.0% (Data is updating) | 8.5% (455) |
Education Levels Comparison: Ontario vs Forest
- In Forest, a larger percentage of residents lack formal schooling at 4.4% compared to 0.0% in Ontario.
- In Forest, the rate of residents with high school diplomas is higher at 10.5% compared to 0.0% in Ontario.
- The percentage of residents with less than a high school education is higher in Forest at 33.4%, compared to 0.0% in Ontario.
- In Forest, a larger share of residents have a bachelor's degree or higher at 8.5% compared to 0.0% in Ontario.
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.