Demographics details for Blue island, IL vs Helper, UT

Population Overview

Compare main population characteristics in Blue island, IL vs Helper, UT.

Data Blue island Helper
Population 23,706 2,131
Median Age 33.0 years 43.2 years
Median Income $63,000 $59,323
Married Families 38.0% 61.0%
Poverty Level 17% 11%
Unemployment Rate 5.3 2.5

Population Comparison: Blue island vs Helper

  • In Blue island, the population is higher at 23,706, compared to 2,131 in Helper.
  • The median age in Helper is higher at 43.2 years, compared to 33.0 years in Blue island.
  • Blue island has a higher median income of $63,000 compared to $59,323 in Helper.
  • In Helper, the percentage of married families is higher at 61.0%, compared to 38.0% in Blue island.
  • Blue island has a higher poverty level at 17% compared to 11% in Helper.
  • The unemployment rate in Blue island is higher at 5.3%, compared to 2.5% in Helper.

Demographics

Demographics Blue island vs Helper provide insight into the diversity of the communities to compare.

Demographic Blue island Helper
Black 60 Data is updating
White 20 85
Asian 10 Data is updating
Hispanic 10 10
Two or More Races 5 5
American Indian Data is updating Data is updating

Demographics Comparison: Blue island vs Helper

  • A higher percentage of Black residents are in Blue island at 60% compared to 0% in Helper.
  • The percentage of White residents is higher in Helper at 85% compared to 20% in Blue island.
  • The Asian population is larger in Blue island at 10% compared to 0% in Helper.
  • The percentage of Hispanic residents is the same in both Blue island and Helper at 10%.
  • Both Blue island and Helper have the same percentage of residents identifying as two or more races at 5%.
  • The percentage of American Indian residents is the same in both Blue island and Helper at 0%.

Health Statistics

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

Health Metric Blue island Helper
Mental Health Not Good Data is updating% 17.1%
Physical Health Not Good Data is updating% 11.4%
Depression Data is updating% 25.3%
Smoking Data is updating% 11.5%
Binge Drinking Data is updating% 14.2%
Obesity Data is updating% 36.9%
Disability Percentage Data is updating% 26.0%

Health Statistics Comparison: Blue island vs Helper

  • In Helper, a higher percentage report poor mental health at 17.1% compared to 0.0% in Blue island.
  • Higher depression rates are seen in Helper at 25.3% versus 0.0% in Blue island.
  • Helper has a higher smoking rate at 11.5% compared to 0.0% in Blue island.
  • More residents engage in binge drinking in Helper at 14.2% compared to 0.0% in Blue island.
  • Helper has higher obesity rates at 36.9% compared to 0.0% in Blue island.
  • There is a higher percentage of disabled individuals in Helper at 26.0% compared to 0.0% in Blue island.

Education Levels

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

Education Level Blue island Helper
No Schooling 0.0% (Data is updating) 0.0% (Data is updating)
High School Diploma 0.0% (Data is updating) 23.4% (499)
Less than High School 0.0% (Data is updating) 8.7% (185)
Bachelor's Degree and Higher 0.0% (Data is updating) 18.7% (399)

Education Levels Comparison: Blue island vs Helper

  • The percentage of residents with no formal schooling is the same in both Blue island and Helper at 0.0%.
  • In Helper, the rate of residents with high school diplomas is higher at 23.4% compared to 0.0% in Blue island.
  • The percentage of residents with less than a high school education is higher in Helper at 8.7%, compared to 0.0% in Blue island.
  • In Helper, a larger share of residents have a bachelor's degree or higher at 18.7% compared to 0.0% in Blue island.

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.