Demographics details for Marshall, AR vs Loma linda, CA
Population Overview
Compare main population characteristics in Marshall, AR vs Loma linda, CA.
| Data | Marshall | Loma linda |
|---|---|---|
| Population | 1,339 | 25,129 |
| Median Age | 52.3 years | 37.8 years |
| Median Income | $28,290 | $70,685 |
| Married Families | 33.0% | 40.0% |
| Poverty Level | 16% | 10% |
| Unemployment Rate | 4.2 | 3.7 |
Population Comparison: Marshall vs Loma linda
- The population in Loma linda is higher at 25,129, compared to 1,339 in Marshall.
- Residents in Marshall have a higher median age of 52.3 years compared to 37.8 years in Loma linda.
- Loma linda has a higher median income of $70,685, compared to $28,290 in Marshall.
- In Loma linda, the percentage of married families is higher at 40.0%, compared to 33.0% in Marshall.
- Marshall has a higher poverty level at 16% compared to 10% in Loma linda.
- The unemployment rate in Marshall is higher at 4.2%, compared to 3.7% in Loma linda.
Demographics
Demographics Marshall vs Loma linda provide insight into the diversity of the communities to compare.
| Demographic | Marshall | Loma linda |
|---|---|---|
| Black | Data is updating | 6 |
| White | 84 | 28 |
| Asian | Data is updating | 26 |
| Hispanic | 3 | 28 |
| Two or More Races | 12 | 11 |
| American Indian | 1 | 1 |
Demographics Comparison: Marshall vs Loma linda
- In Loma linda, the percentage of Black residents is higher at 6% compared to 0% in Marshall.
- Marshall has a higher percentage of White residents at 84% compared to 28% in Loma linda.
- In Loma linda, the Asian population stands at 26%, greater than 0% in Marshall.
- Loma linda has a higher percentage of Hispanic residents at 28%, compared to 3% in Marshall.
- More residents identify as two or more races in Marshall at 12% compared to 11% in Loma linda.
- The percentage of American Indian residents is the same in both Marshall and Loma linda at 1%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Marshall | Loma linda |
|---|---|---|
| Mental Health Not Good | 21.7% | 15.1% |
| Physical Health Not Good | 16.2% | 10.2% |
| Depression | 29.8% | 16.5% |
| Smoking | 27.2% | 11.1% |
| Binge Drinking | 14.7% | 13.9% |
| Obesity | 39.2% | 31.7% |
| Disability Percentage | 30.0% | 13.0% |
Health Statistics Comparison: Marshall vs Loma linda
- More residents in Marshall report poor mental health at 21.7% compared to 15.1% in Loma linda.
- Depression is more prevalent in Marshall at 29.8% compared to 16.5% in Loma linda.
- Smoking is more prevalent in Marshall at 27.2% compared to 11.1% in Loma linda.
- Binge drinking is more common in Marshall at 14.7% compared to 13.9% in Loma linda.
- Obesity rates are higher in Marshall at 39.2% compared to 31.7% in Loma linda.
- Disability percentages are higher in Marshall at 30.0% compared to 13.0% in Loma linda.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Marshall | Loma linda |
|---|---|---|
| No Schooling | 0.9% (12) | 1.6% (401) |
| High School Diploma | 27.9% (373) | 9.5% (2,397) |
| Less than High School | 32.4% (434) | 13.1% (3,304) |
| Bachelor's Degree and Higher | 11.7% (156) | 35.4% (8,904) |
Education Levels Comparison: Marshall vs Loma linda
- In Loma linda, a larger percentage of residents lack formal schooling at 1.6% compared to 0.9% in Marshall.
- A higher percentage of residents in Marshall hold a high school diploma at 27.9% compared to 9.5% in Loma linda.
- More residents in Marshall have less than a high school education at 32.4% compared to 13.1% in Loma linda.
- In Loma linda, a larger share of residents have a bachelor's degree or higher at 35.4% compared to 11.7% in Marshall.
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.