Demographics details for Chester, CT vs Mount pocono, PA

Population Overview

Compare main population characteristics in Chester, CT vs Mount pocono, PA.

Data Chester Mount pocono
Population 3,994 3,071
Median Age 43.0 years 38.5 years
Median Income $102,500 $81,127
Married Families 64.0% 30.0%
Poverty Level 5% 10%
Unemployment Rate 2.1 4.8

Population Comparison: Chester vs Mount pocono

  • In Chester, the population is higher at 3,994, compared to 3,071 in Mount pocono.
  • Residents in Chester have a higher median age of 43.0 years compared to 38.5 years in Mount pocono.
  • Chester has a higher median income of $102,500 compared to $81,127 in Mount pocono.
  • A higher percentage of married families is found in Chester at 64.0% compared to 30.0% in Mount pocono.
  • The poverty level is higher in Mount pocono at 10%, compared to 5% in Chester.
  • Mount pocono has a higher unemployment rate at 4.8% compared to 2.1% in Chester.

Demographics

Demographics Chester vs Mount pocono provide insight into the diversity of the communities to compare.

Demographic Chester Mount pocono
Black 1 16
White 87 41
Asian Data is updating 6
Hispanic 5 33
Two or More Races 3 4
American Indian Data is updating Data is updating

Demographics Comparison: Chester vs Mount pocono

  • In Mount pocono, the percentage of Black residents is higher at 16% compared to 1% in Chester.
  • Chester has a higher percentage of White residents at 87% compared to 41% in Mount pocono.
  • In Mount pocono, the Asian population stands at 6%, greater than 0% in Chester.
  • Mount pocono has a higher percentage of Hispanic residents at 33%, compared to 5% in Chester.
  • The percentage of residents identifying as two or more races is higher in Mount pocono at 4%, compared to 3% in Chester.
  • The percentage of American Indian residents is the same in both Chester and Mount pocono at 0%.

Health Statistics

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

Health Metric Chester Mount pocono
Mental Health Not Good Data is updating% 16.1%
Physical Health Not Good Data is updating% 11.8%
Depression Data is updating% 20.1%
Smoking Data is updating% 18.1%
Binge Drinking Data is updating% 16.1%
Obesity Data is updating% 34.3%
Disability Percentage Data is updating% 13.0%

Health Statistics Comparison: Chester vs Mount pocono

  • In Mount pocono, a higher percentage report poor mental health at 16.1% compared to 0.0% in Chester.
  • Higher depression rates are seen in Mount pocono at 20.1% versus 0.0% in Chester.
  • Mount pocono has a higher smoking rate at 18.1% compared to 0.0% in Chester.
  • More residents engage in binge drinking in Mount pocono at 16.1% compared to 0.0% in Chester.
  • Mount pocono has higher obesity rates at 34.3% compared to 0.0% in Chester.
  • There is a higher percentage of disabled individuals in Mount pocono at 13.0% compared to 0.0% in Chester.

Education Levels

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

Education Level Chester Mount pocono
No Schooling 0.0% (Data is updating) 3.2% (98)
High School Diploma 0.0% (Data is updating) 27.4% (842)
Less than High School 0.0% (Data is updating) 18.1% (555)
Bachelor's Degree and Higher 0.0% (Data is updating) 15.9% (488)

Education Levels Comparison: Chester vs Mount pocono

  • In Mount pocono, a larger percentage of residents lack formal schooling at 3.2% compared to 0.0% in Chester.
  • In Mount pocono, the rate of residents with high school diplomas is higher at 27.4% compared to 0.0% in Chester.
  • The percentage of residents with less than a high school education is higher in Mount pocono at 18.1%, compared to 0.0% in Chester.
  • In Mount pocono, a larger share of residents have a bachelor's degree or higher at 15.9% compared to 0.0% in Chester.

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.