Demographics details for Catlettsburg, KY vs Mount olive, MS
Population Overview
Compare main population characteristics in Catlettsburg, KY vs Mount olive, MS.
Data | Catlettsburg | Mount olive |
---|---|---|
Population | 1,746 | 878 |
Median Age | 48.0 years | 31.7 years |
Median Income | $33,047 | $53,947 |
Married Families | 28.0% | 49.0% |
Poverty Level | 12% | 18% |
Unemployment Rate | 5.0 | 6.5 |
Population Comparison: Catlettsburg vs Mount olive
- In Catlettsburg, the population is higher at 1,746, compared to 878 in Mount olive.
- Residents in Catlettsburg have a higher median age of 48.0 years compared to 31.7 years in Mount olive.
- Mount olive has a higher median income of $53,947, compared to $33,047 in Catlettsburg.
- In Mount olive, the percentage of married families is higher at 49.0%, compared to 28.0% in Catlettsburg.
- The poverty level is higher in Mount olive at 18%, compared to 12% in Catlettsburg.
- Mount olive has a higher unemployment rate at 6.5% compared to 5.0% in Catlettsburg.
Demographics
Demographics Catlettsburg vs Mount olive provide insight into the diversity of the communities to compare.
Demographic | Catlettsburg | Mount olive |
---|---|---|
Black | 5 | 120 |
White | 90 | 145 |
Asian | Data is updating | 2 |
Hispanic | 1 | Data is updating |
Two or More Races | 4 | Data is updating |
American Indian | Data is updating | Data is updating |
Demographics Comparison: Catlettsburg vs Mount olive
- In Mount olive, the percentage of Black residents is higher at 120% compared to 5% in Catlettsburg.
- The percentage of White residents is higher in Mount olive at 145% compared to 90% in Catlettsburg.
- In Mount olive, the Asian population stands at 2%, greater than 0% in Catlettsburg.
- The Hispanic community is larger in Catlettsburg at 1% compared to 0% in Mount olive.
- More residents identify as two or more races in Catlettsburg at 4% compared to 0% in Mount olive.
- The percentage of American Indian residents is the same in both Catlettsburg and Mount olive at 0%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
Health Metric | Catlettsburg | Mount olive |
---|---|---|
Mental Health Not Good | 22.4% | 17.8% |
Physical Health Not Good | 18.0% | 13.3% |
Depression | 32.9% | 21.5% |
Smoking | 29.0% | 21.3% |
Binge Drinking | 13.5% | 13.0% |
Obesity | 42.8% | 43.6% |
Disability Percentage | 32.0% | 27.0% |
Health Statistics Comparison: Catlettsburg vs Mount olive
- More residents in Catlettsburg report poor mental health at 22.4% compared to 17.8% in Mount olive.
- Depression is more prevalent in Catlettsburg at 32.9% compared to 21.5% in Mount olive.
- Smoking is more prevalent in Catlettsburg at 29.0% compared to 21.3% in Mount olive.
- Binge drinking is more common in Catlettsburg at 13.5% compared to 13.0% in Mount olive.
- Mount olive has higher obesity rates at 43.6% compared to 42.8% in Catlettsburg.
- Disability percentages are higher in Catlettsburg at 32.0% compared to 27.0% in Mount olive.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
Education Level | Catlettsburg | Mount olive |
---|---|---|
No Schooling | 2.9% (50) | 2.3% (20) |
High School Diploma | 28.8% (502) | 23.9% (210) |
Less than High School | 33.4% (584) | 14.9% (131) |
Bachelor's Degree and Higher | 4.6% (80) | 13.0% (114) |
Education Levels Comparison: Catlettsburg vs Mount olive
- A higher percentage of residents in Catlettsburg have no formal schooling at 2.9% compared to 2.3% in Mount olive.
- A higher percentage of residents in Catlettsburg hold a high school diploma at 28.8% compared to 23.9% in Mount olive.
- More residents in Catlettsburg have less than a high school education at 33.4% compared to 14.9% in Mount olive.
- In Mount olive, a larger share of residents have a bachelor's degree or higher at 13.0% compared to 4.6% in Catlettsburg.
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.