Demographics details for Mountain home, AR vs Milan, OH
Population Overview
Compare main population characteristics in Mountain home, AR vs Milan, OH.
| Data | Mountain home | Milan |
|---|---|---|
| Population | 13,150 | 1,359 |
| Median Age | 41.8 years | 40.1 years |
| Median Income | $42,281 | $90,145 |
| Married Families | 38.0% | 51.0% |
| Poverty Level | 14% | 5% |
| Unemployment Rate | 3.5 | 3.5 |
Population Comparison: Mountain home vs Milan
- In Mountain home, the population is higher at 13,150, compared to 1,359 in Milan.
- Residents in Mountain home have a higher median age of 41.8 years compared to 40.1 years in Milan.
- Milan has a higher median income of $90,145, compared to $42,281 in Mountain home.
- In Milan, the percentage of married families is higher at 51.0%, compared to 38.0% in Mountain home.
- Mountain home has a higher poverty level at 14% compared to 5% in Milan.
- The unemployment rate is the same in both Mountain home and Milan at 3.5%.
Demographics
Demographics Mountain home vs Milan provide insight into the diversity of the communities to compare.
| Demographic | Mountain home | Milan |
|---|---|---|
| Black | Data is updating | 2 |
| White | 90 | 94 |
| Asian | 1 | Data is updating |
| Hispanic | 4 | 2 |
| Two or More Races | 4 | 2 |
| American Indian | 1 | Data is updating |
Demographics Comparison: Mountain home vs Milan
- In Milan, the percentage of Black residents is higher at 2% compared to 0% in Mountain home.
- The percentage of White residents is higher in Milan at 94% compared to 90% in Mountain home.
- The Asian population is larger in Mountain home at 1% compared to 0% in Milan.
- The Hispanic community is larger in Mountain home at 4% compared to 2% in Milan.
- More residents identify as two or more races in Mountain home at 4% compared to 2% in Milan.
- A greater percentage of American Indian residents live in Mountain home at 1% compared to 0% in Milan.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Mountain home | Milan |
|---|---|---|
| Mental Health Not Good | 19.2% | 16.5% |
| Physical Health Not Good | 12.9% | 10.6% |
| Depression | 28.5% | 24.1% |
| Smoking | 21.1% | 19.3% |
| Binge Drinking | 16.3% | 21.0% |
| Obesity | 34.3% | 39.2% |
| Disability Percentage | 22.0% | 13.0% |
Health Statistics Comparison: Mountain home vs Milan
- More residents in Mountain home report poor mental health at 19.2% compared to 16.5% in Milan.
- Depression is more prevalent in Mountain home at 28.5% compared to 24.1% in Milan.
- Smoking is more prevalent in Mountain home at 21.1% compared to 19.3% in Milan.
- More residents engage in binge drinking in Milan at 21.0% compared to 16.3% in Mountain home.
- Milan has higher obesity rates at 39.2% compared to 34.3% in Mountain home.
- Disability percentages are higher in Mountain home at 22.0% compared to 13.0% in Milan.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Mountain home | Milan |
|---|---|---|
| No Schooling | 0.7% (87) | 0.0% (Data is updating) |
| High School Diploma | 16.9% (2,225) | 30.7% (417) |
| Less than High School | 14.2% (1,870) | 4.0% (54) |
| Bachelor's Degree and Higher | 15.0% (1,973) | 18.3% (249) |
Education Levels Comparison: Mountain home vs Milan
- A higher percentage of residents in Mountain home have no formal schooling at 0.7% compared to 0.0% in Milan.
- In Milan, the rate of residents with high school diplomas is higher at 30.7% compared to 16.9% in Mountain home.
- More residents in Mountain home have less than a high school education at 14.2% compared to 4.0% in Milan.
- In Milan, a larger share of residents have a bachelor's degree or higher at 18.3% compared to 15.0% in Mountain home.
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.