This is a small community in a single neighborhood.
As throughout the site, some neighborhood-level data are reserved for subscribers.
What do we mean by a neighborhood?
NeighborhoodScout® uses the official government designation for neighborhoods - the census tract.
Census tracts are small, relatively permanent subdivisions of a county that are defined by the U.S. Census Bureau in conjunction with local authorities all across the country to define real neighborhoods that are bounded to contain areas with homogeneous population characteristics (including economic status, lifestyle, and living conditions). Census tracts usually have 4,000 persons, but can range between 1,500 and 8,000 persons. This is the most fine-grained area for which detailed information is made available from the government, to protect the individual privacy of each of us. Because census tracts are based on population, they vary in size depending on the density of settlement. In urban areas, they are small, and in rural areas they can cover an entire small town or even a few small towns in very rural areas.
Since census tracts are subdivisions of a county, we did a spatial overlay of the census tracts onto city and town boundaries using a geographic information system to properly assign each census tract to its appropriate city or town. Then we named each census tract to the local colloquially recognized neighborhood name for that spot (e.g., Boston, MA (Dorchester). If there was not a name available, we named the census tract by the largest street intersection in the census tract (e.g., Worcester, MA (Lincoln St/Plantation St)
Why we don't use Zip Codes as neighborhoods
Zip codes were developed by the Postal Service for the purpose of delivering mail, but were never intended to define coherent neighborhoods. In addition, Zip Codes can have as many as 10 distinctly different census tracts contained within them. When distinct census tracts are blended together in a single Zip Code, the data reflects their average conditions and often gives a false sense of the area. The result is that potentially great matching neighborhoods can be missed, and erroneous matches can also be produced and delivered to you.
Using census tracts makes great matches possible, and helps people find the areas that are best for them and their families. Because we are committed to providing the highest possible quality and finding the neighborhoods that best meet your criteria, we use census tracts. And, as always, we show you the actual street map of the neighborhood so you know exactly where your best matching neighborhood is located.
What is a Condition Alert?
A condition alert is a condition in the neighborhood that triggers an alert. NeighborhoodScout contains condition alerts to highlight conditions that are extreme, whether good or bad. This helps answer crucial questions about the state of the neighborhood being evaluated, such as:
What are the risks of violent crime here?
Is the risk of home break-ins or other property crimes increasing?
Does real estate here hold its value?
Are the trends in local vacancies or unemployment concerning?
...and dozens more.
Information at a glance that you need to know to invest, appraise or finance a property.
Mount Union is a very small borough located in the state of Pennsylvania. With a population of 2,257 people and just one neighborhood, Mount Union is the 598th largest community in Pennsylvania.
Occupations and Workforce
Because occupations involving physical labor dominate the local economy, Mount Union is generally considered to be a blue-collar town. 38.10% of the Mount Union workforce is employed in blue-collar occupations, compared to the national average of 27.7%. Overall, Mount Union is a borough of service providers, professionals, and production and manufacturing workers. There are especially a lot of people living in Mount Union who work in business and financial occupations (8.45%), healthcare suport services (7.86%), and healthcare (7.02%).
Setting & Lifestyle
In Mount Union, however, the average commute to work is quite long. On average, people spend 30.67 minutes each day getting to work, which is significantly higher than the national average.
Demographics
The citizens of Mount Union have a very low rate of college education: just 9.77% of people over 25 have a bachelor's degree or advanced degree, compared to a national average of 21.84% for all cities.
The per capita income in Mount Union in 2022 was $22,687, which is low income relative to Pennsylvania and the nation. This equates to an annual income of $90,748 for a family of four. However, Mount Union contains both very wealthy and poor people as well. Mount Union also has one of the higher rates of people living in poverty in the nation, with 32.25% of its population below the federal poverty line.
Mount Union is a somewhat ethnically-diverse borough. The people who call Mount Union home describe themselves as belonging to a variety of racial and ethnic groups. The greatest number of Mount Union residents report their race to be White, followed by Black or African-American. Important ancestries of people in Mount Union include German, Irish, Italian, English, and Hungarian.
The most common language spoken in Mount Union is English. Other important languages spoken here include Italian and Polish.
Notable & Unique Neighborhood Characteristics
When you see a neighborhood for the first time, the most important thing is often the way it looks, like its homes and its setting. Some places look the same, but they only reveal their true character after living in them for a while because they contain a unique mix of occupational or cultural groups. This neighborhood is very unique in some important ways, according to NeighborhoodScout's exclusive exploration and analysis.
Diversity
Did you know that the neighborhood has more Hungarian ancestry people living in it than nearly any neighborhood in America? It's true! In fact, 3.0% of this neighborhood's residents have Hungarian ancestry.
is also pretty special linguistically. Significantly, 6.4% of its residents five years old and above primarily speak Italian at home. While this may seem like a small percentage, it is higher than 95.2% of the neighborhoods in America.
The Neighbors
How wealthy a neighborhood is, from very wealthy, to middle income, to low income is very formative with regard to the personality and character of a neighborhood. Equally important is the rate of people, particularly children, who live below the federal poverty line. In some wealthy gated communities, the areas immediately surrounding can have high rates of childhood poverty, which indicates other social issues. NeighborhoodScout's analysis reveals both aspects of income and poverty for this neighborhood.
The neighbors in the neighborhood in Mount Union are low income, making it among the lowest income neighborhoods in America. NeighborhoodScout's research shows that this neighborhood has an income lower than 91.7% of U.S. neighborhoods. With 50.7% of the children here below the federal poverty line, this neighborhood has a higher rate of childhood poverty than 94.2% of U.S. neighborhoods.
The old saying "you are what you eat" is true. But it is also true that you are what you do for a living. The types of occupations your neighbors have shape their character, and together as a group, their collective occupations shape the culture of a place.
In the neighborhood, 38.1% of the working population is employed in manufacturing and laborer occupations. The second most important occupational group in this neighborhood is executive, management, and professional occupations, with 30.0% of the residents employed. Other residents here are employed in sales and service jobs, from major sales accounts, to working in fast food restaurants (20.1%), and 11.8% in clerical, assistant, and tech support occupations.
Languages
The most common language spoken in the neighborhood is English, spoken by 98.1% of households. Some people also speak Italian (6.4%).
Ethnicity / Ancestry
Culture is shared learned behavior. We learn it from our parents, their parents, our houses of worship, and much of our culture – our learned behavior – comes from our ancestors. That is why ancestry and ethnicity can be so interesting and important to understand: places with concentrations of people of one or more ancestries often express those shared learned behaviors and this gives each neighborhood its own culture. Even different neighborhoods in the same city can have drastically different cultures.
In the neighborhood in Mount Union, PA, residents most commonly identify their ethnicity or ancestry as German (18.7%). There are also a number of people of Irish ancestry (12.5%), and residents who report Italian roots (12.2%), and some of the residents are also of English ancestry (5.9%), along with some Hungarian ancestry residents (3.0%), among others.
Getting to Work
How you get to work – car, bus, train or other means – and how much of your day it takes to do so is a large quality of life and financial issue. Especially with gasoline prices rising and expected to continue doing so, the length and means of one's commute can be a financial burden. Some neighborhoods are physically located so that many residents have to drive in their own car, others are set up so many walk to work, or can take a train, bus, or bike. The greatest number of commuters in neighborhood spend between 15 and 30 minutes commuting one-way to work (30.3% of working residents), which is shorter than the time spent commuting to work for most Americans.
Here most residents (77.8%) drive alone in a private automobile to get to work. In addition, quite a number also carpool with coworkers, friends, or neighbors to get to work (11.7%) and 7.5% of residents also hop out the door and walk to work for their daily commute. In a neighborhood like this, as in most of the nation, many residents find owning a car useful for getting to work.
SCOUT’s patented match algorithm identifies the most similar neighborhoods to a subject location, and quantifies the similarity to the subject location. This allows analysts to identify the most similar neighborhoods in a local market area for appraisals, investments, and research.
The algorithm uses 273 neighborhood conditions, identifies the dominant dimensions underlying the conditions and calculates the similarity. This captures the true culture and character of locations, economic conditions, and trends.
The closer to 100% means the locations are nearly identical. 80% is a very good, but not excellent match, and so forth.
