Demographics details for Green, OH vs Montgomery, NY
Population Overview
Compare main population characteristics in Green, OH vs Montgomery, NY.
| Data | Green | Montgomery |
|---|---|---|
| Population | 27,269 | 49,623 |
| Median Age | 41.1 years | 40.6 years |
| Median Income | $90,419 | $58,033 |
| Married Families | 45.0% | 34.0% |
| Poverty Level | 4% | 10% |
| Unemployment Rate | 4.7 | 4.2 |
Population Comparison: Green vs Montgomery
- The population in Montgomery is higher at 49,623, compared to 27,269 in Green.
- Residents in Green have a higher median age of 41.1 years compared to 40.6 years in Montgomery.
- Green has a higher median income of $90,419 compared to $58,033 in Montgomery.
- A higher percentage of married families is found in Green at 45.0% compared to 34.0% in Montgomery.
- The poverty level is higher in Montgomery at 10%, compared to 4% in Green.
- The unemployment rate in Green is higher at 4.7%, compared to 4.2% in Montgomery.
Demographics
Demographics Green vs Montgomery provide insight into the diversity of the communities to compare.
| Demographic | Green | Montgomery |
|---|---|---|
| Black | 1 | 3 |
| White | 94 | 74 |
| Asian | 1 | 1 |
| Hispanic | 1 | 15 |
| Two or More Races | 3 | 6 |
| American Indian | Data is updating | 1 |
Demographics Comparison: Green vs Montgomery
- In Montgomery, the percentage of Black residents is higher at 3% compared to 1% in Green.
- Green has a higher percentage of White residents at 94% compared to 74% in Montgomery.
- Both Green and Montgomery have the same percentage of Asian residents at 1%.
- Montgomery has a higher percentage of Hispanic residents at 15%, compared to 1% in Green.
- The percentage of residents identifying as two or more races is higher in Montgomery at 6%, compared to 3% in Green.
- In Montgomery, the percentage of American Indian residents is higher at 1%, compared to 0% in Green.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Green | Montgomery |
|---|---|---|
| Mental Health Not Good | 16.6% | 16.7% |
| Physical Health Not Good | 10.5% | 12.3% |
| Depression | 24.7% | 23.2% |
| Smoking | 17.4% | 20.4% |
| Binge Drinking | 19.1% | 17.8% |
| Obesity | 40.2% | 35.8% |
| Disability Percentage | 9.0% | 16.0% |
Health Statistics Comparison: Green vs Montgomery
- In Montgomery, a higher percentage report poor mental health at 16.7% compared to 16.6% in Green.
- Depression is more prevalent in Green at 24.7% compared to 23.2% in Montgomery.
- Montgomery has a higher smoking rate at 20.4% compared to 17.4% in Green.
- Binge drinking is more common in Green at 19.1% compared to 17.8% in Montgomery.
- Obesity rates are higher in Green at 40.2% compared to 35.8% in Montgomery.
- There is a higher percentage of disabled individuals in Montgomery at 16.0% compared to 9.0% in Green.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Green | Montgomery |
|---|---|---|
| No Schooling | 0.2% (46) | 1.1% (540) |
| High School Diploma | 16.6% (4,514) | 20.6% (10,235) |
| Less than High School | 3.0% (828) | 14.9% (7,375) |
| Bachelor's Degree and Higher | 29.3% (7,977) | 13.7% (6,785) |
Education Levels Comparison: Green vs Montgomery
- In Montgomery, a larger percentage of residents lack formal schooling at 1.1% compared to 0.2% in Green.
- In Montgomery, the rate of residents with high school diplomas is higher at 20.6% compared to 16.6% in Green.
- The percentage of residents with less than a high school education is higher in Montgomery at 14.9%, compared to 3.0% in Green.
- A higher percentage of residents in Green hold a bachelor's degree or higher at 29.3% compared to 13.7% in Montgomery.
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.