Demographics details for Falling waters, WV vs Trexlertown, PA

Population Overview

Compare main population characteristics in Falling waters, WV vs Trexlertown, PA.

Data Falling waters Trexlertown
Population 2,150 1,885
Median Age 32.2 years 34.6 years
Median Income $84,038 $93,472
Married Families 29.0% 50.0%
Poverty Level 9% 4%
Unemployment Rate 3.5 3.5

Population Comparison: Falling waters vs Trexlertown

  • In Falling waters, the population is higher at 2,150, compared to 1,885 in Trexlertown.
  • The median age in Trexlertown is higher at 34.6 years, compared to 32.2 years in Falling waters.
  • Trexlertown has a higher median income of $93,472, compared to $84,038 in Falling waters.
  • In Trexlertown, the percentage of married families is higher at 50.0%, compared to 29.0% in Falling waters.
  • Falling waters has a higher poverty level at 9% compared to 4% in Trexlertown.
  • The unemployment rate is the same in both Falling waters and Trexlertown at 3.5%.

Demographics

Demographics Falling waters vs Trexlertown provide insight into the diversity of the communities to compare.

Demographic Falling waters Trexlertown
Black 6 18
White 92 65
Asian Data is updating 11
Hispanic Data is updating 5
Two or More Races 2 1
American Indian Data is updating Data is updating

Demographics Comparison: Falling waters vs Trexlertown

  • In Trexlertown, the percentage of Black residents is higher at 18% compared to 6% in Falling waters.
  • Falling waters has a higher percentage of White residents at 92% compared to 65% in Trexlertown.
  • In Trexlertown, the Asian population stands at 11%, greater than 0% in Falling waters.
  • Trexlertown has a higher percentage of Hispanic residents at 5%, compared to 0% in Falling waters.
  • More residents identify as two or more races in Falling waters at 2% compared to 1% in Trexlertown.
  • The percentage of American Indian residents is the same in both Falling waters and Trexlertown at 0%.

Health Statistics

The health statistics provide insights into prevalent health conditions in two communities.

Health Metric Falling waters Trexlertown
Mental Health Not Good 18.5% 13.5%
Physical Health Not Good 11.9% 8.2%
Depression 25.7% 19.9%
Smoking 18.7% 12.3%
Binge Drinking 15.2% 19.4%
Obesity 37.6% 28.2%
Disability Percentage 24.0% 3.0%

Health Statistics Comparison: Falling waters vs Trexlertown

  • More residents in Falling waters report poor mental health at 18.5% compared to 13.5% in Trexlertown.
  • Depression is more prevalent in Falling waters at 25.7% compared to 19.9% in Trexlertown.
  • Smoking is more prevalent in Falling waters at 18.7% compared to 12.3% in Trexlertown.
  • More residents engage in binge drinking in Trexlertown at 19.4% compared to 15.2% in Falling waters.
  • Obesity rates are higher in Falling waters at 37.6% compared to 28.2% in Trexlertown.
  • Disability percentages are higher in Falling waters at 24.0% compared to 3.0% in Trexlertown.

Education Levels

The educational attainment in the area helps gauge the workforce's skill level and economic potential.

Education Level Falling waters Trexlertown
No Schooling 0.0% (Data is updating) 0.0% (Data is updating)
High School Diploma 22.4% (482) 18.4% (347)
Less than High School 4.7% (102) 4.0% (76)
Bachelor's Degree and Higher 11.0% (237) 41.2% (776)

Education Levels Comparison: Falling waters vs Trexlertown

  • The percentage of residents with no formal schooling is the same in both Falling waters and Trexlertown at 0.0%.
  • A higher percentage of residents in Falling waters hold a high school diploma at 22.4% compared to 18.4% in Trexlertown.
  • More residents in Falling waters have less than a high school education at 4.7% compared to 4.0% in Trexlertown.
  • In Trexlertown, a larger share of residents have a bachelor's degree or higher at 41.2% compared to 11.0% in Falling waters.

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.