Demographics details for Upland, CA vs Montgomery village, MD

Population Overview

Compare main population characteristics in Upland, CA vs Montgomery village, MD.

Data Upland Montgomery village
Population 78,841 34,748
Median Age 37.1 years 36.8 years
Median Income $93,994 $91,703
Married Families 38.0% 38.0%
Poverty Level 9% 7%
Unemployment Rate 4.4 4.2

Population Comparison: Upland vs Montgomery village

  • In Upland, the population is higher at 78,841, compared to 34,748 in Montgomery village.
  • Residents in Upland have a higher median age of 37.1 years compared to 36.8 years in Montgomery village.
  • Upland has a higher median income of $93,994 compared to $91,703 in Montgomery village.
  • The percentage of married families is the same in both Upland and Montgomery village at 38.0%.
  • Upland has a higher poverty level at 9% compared to 7% in Montgomery village.
  • The unemployment rate in Upland is higher at 4.4%, compared to 4.2% in Montgomery village.

Demographics

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

Demographic Upland Montgomery village
Black 7 23
White 22 19
Asian 10 13
Hispanic 44 35
Two or More Races 16 10
American Indian 1 Data is updating

Demographics Comparison: Upland vs Montgomery village

  • In Montgomery village, the percentage of Black residents is higher at 23% compared to 7% in Upland.
  • Upland has a higher percentage of White residents at 22% compared to 19% in Montgomery village.
  • In Montgomery village, the Asian population stands at 13%, greater than 10% in Upland.
  • The Hispanic community is larger in Upland at 44% compared to 35% in Montgomery village.
  • More residents identify as two or more races in Upland at 16% compared to 10% in Montgomery village.
  • A greater percentage of American Indian residents live in Upland at 1% compared to 0% in Montgomery village.

Health Statistics

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

Health Metric Upland Montgomery village
Mental Health Not Good 15.5% 14.5%
Physical Health Not Good 10.4% 9.0%
Depression 17.8% 18.9%
Smoking 10.8% 11.3%
Binge Drinking 16.3% 12.1%
Obesity 34.9% 27.8%
Disability Percentage 12.0% 10.0%

Health Statistics Comparison: Upland vs Montgomery village

  • More residents in Upland report poor mental health at 15.5% compared to 14.5% in Montgomery village.
  • Higher depression rates are seen in Montgomery village at 18.9% versus 17.8% in Upland.
  • Montgomery village has a higher smoking rate at 11.3% compared to 10.8% in Upland.
  • Binge drinking is more common in Upland at 16.3% compared to 12.1% in Montgomery village.
  • Obesity rates are higher in Upland at 34.9% compared to 27.8% in Montgomery village.
  • Disability percentages are higher in Upland at 12.0% 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 Upland Montgomery village
No Schooling 1.3% (1,036) 2.7% (955)
High School Diploma 14.1% (11,080) 12.2% (4,244)
Less than High School 12.3% (9,718) 14.3% (4,958)
Bachelor's Degree and Higher 23.2% (18,252) 28.9% (10,032)

Education Levels Comparison: Upland vs Montgomery village

  • In Montgomery village, a larger percentage of residents lack formal schooling at 2.7% compared to 1.3% in Upland.
  • A higher percentage of residents in Upland hold a high school diploma at 14.1% compared to 12.2% in Montgomery village.
  • The percentage of residents with less than a high school education is higher in Montgomery village at 14.3%, compared to 12.3% in Upland.
  • In Montgomery village, a larger share of residents have a bachelor's degree or higher at 28.9% compared to 23.2% in Upland.

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.