Demographics details for Montgomery village, MD vs Boyle, MS

Population Overview

Compare main population characteristics in Montgomery village, MD vs Boyle, MS.

Data Montgomery village Boyle
Population 34,748 499
Median Age 36.8 years 36.7 years
Median Income $91,703 $33,750
Married Families 38.0% 25.0%
Poverty Level 7% 20%
Unemployment Rate 4.2 4.5

Population Comparison: Montgomery village vs Boyle

  • In Montgomery village, the population is higher at 34,748, compared to 499 in Boyle.
  • Residents in Montgomery village have a higher median age of 36.8 years compared to 36.7 years in Boyle.
  • Montgomery village has a higher median income of $91,703 compared to $33,750 in Boyle.
  • A higher percentage of married families is found in Montgomery village at 38.0% compared to 25.0% in Boyle.
  • The poverty level is higher in Boyle at 20%, compared to 7% in Montgomery village.
  • Boyle has a higher unemployment rate at 4.5% compared to 4.2% in Montgomery village.

Demographics

Demographics Montgomery village vs Boyle provide insight into the diversity of the communities to compare.

Demographic Montgomery village Boyle
Black 23 50
White 19 50
Asian 13 Data is updating
Hispanic 35 Data is updating
Two or More Races 10 Data is updating
American Indian Data is updating Data is updating

Demographics Comparison: Montgomery village vs Boyle

  • In Boyle, the percentage of Black residents is higher at 50% compared to 23% in Montgomery village.
  • The percentage of White residents is higher in Boyle at 50% compared to 19% in Montgomery village.
  • The Asian population is larger in Montgomery village at 13% compared to 0% in Boyle.
  • The Hispanic community is larger in Montgomery village at 35% compared to 0% in Boyle.
  • More residents identify as two or more races in Montgomery village at 10% compared to 0% in Boyle.
  • The percentage of American Indian residents is the same in both Montgomery village and Boyle at 0%.

Health Statistics

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

Health Metric Montgomery village Boyle
Mental Health Not Good 14.5% 17.4%
Physical Health Not Good 9.0% 13.3%
Depression 18.9% 20.4%
Smoking 11.3% 20.5%
Binge Drinking 12.1% 13.0%
Obesity 27.8% 41.3%
Disability Percentage 10.0% 48.0%

Health Statistics Comparison: Montgomery village vs Boyle

  • In Boyle, a higher percentage report poor mental health at 17.4% compared to 14.5% in Montgomery village.
  • Higher depression rates are seen in Boyle at 20.4% versus 18.9% in Montgomery village.
  • Boyle has a higher smoking rate at 20.5% compared to 11.3% in Montgomery village.
  • More residents engage in binge drinking in Boyle at 13.0% compared to 12.1% in Montgomery village.
  • Boyle has higher obesity rates at 41.3% compared to 27.8% in Montgomery village.
  • There is a higher percentage of disabled individuals in Boyle at 48.0% compared to 10.0% in Montgomery village.

Education Levels

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

Education Level Montgomery village Boyle
No Schooling 2.7% (955) 0.0% (Data is updating)
High School Diploma 12.2% (4,244) 16.2% (81)
Less than High School 14.3% (4,958) 17.0% (85)
Bachelor's Degree and Higher 28.9% (10,032) 41.7% (208)

Education Levels Comparison: Montgomery village vs Boyle

  • A higher percentage of residents in Montgomery village have no formal schooling at 2.7% compared to 0.0% in Boyle.
  • In Boyle, the rate of residents with high school diplomas is higher at 16.2% compared to 12.2% in Montgomery village.
  • The percentage of residents with less than a high school education is higher in Boyle at 17.0%, compared to 14.3% in Montgomery village.
  • In Boyle, a larger share of residents have a bachelor's degree or higher at 41.7% compared to 28.9% in Montgomery village.

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.