Children And Education
Education Levels of Adults by Race/Ethnicity

Increasing





Education Levels of Adults, by Race/Ethnicity, 2017-21

What does this measure?

The number of residents with a particular level of education in a region, expressed as a percentage of all residents 25 and older, broken down by race and ethnicity.

Why is this important?

An educated population makes a more attractive workforce and is better prepared to instruct the next generation of residents. High educational attainment represents a region's investment in human capital and preparation for long-term growth. There are persistent gaps in academic achievement among students of different races, ethnicities and incomes, and this is likely reflected in levels of educational attainment.

How does our county compare?

In 2017-21, the share of Lancaster County residents who held a bachelor's degree or higher was highest among Asians, at 44%, followed by whites, 30%, African Americans, 19%, and Hispanics, 18%. At the state level, a higher share of Asians (57%), and whites (34%) had college degrees than in Lancaster, while rates among African Americans (20%), and Hispanic residents (19%) were similar. The share of people with a Bachelor's degree in the United States was also higher than Lancaster County among all groups, with the exception of Hispanics which was on par with Lancaster.

In the City of Lancaster, a similar share of whites (32%) had college degrees compared to Lancaster County as a whole, while a smaller share of Asians (27%), African Americans (16%) and Hispanics (13%) in the city had degrees.

Since 2000, the share of residents without a high school degree declined among all racial and ethnic groups in Lancaster County, ranging from an 21 percentage-point drop among Hispanics to a 9-point drop among whites. All groups had increases in their share of residents who had attended some college or earned an associate's degree.

Among neighboring counties in 2017-21, while racial and ethnic disparities persisted, Chester County had larger shares of all groups with at least a bachelor's degree compared to Lancaster. Chester had higher percentages of Asians (86%), African American (27%), Hispanics (26%) and whites (56%) with college degrees. Lebanon and York had a smaller share of residents with college degrees than Lancaster for all racial groups, with the exception of African Americans with rates similar to Lancaster.

Why do these disparities exist?

There are a variety of factors believed to contribute to disparities in educational attainment. School systems in the United States are highly segregated, and students of color disproportionately attend schools with high proportions of low-income students who may not have benefited from early learning opportunities at the same rate as other students. Schools also have different levels of resources ranging from qualified/experienced teachers to advanced courses to facilities and technology, and schools with large Black and Latino populations often have lower levels. In addition, teachers across all school systems tend to be disproportionately white, and teaching practices and curriculum may not be culturally relevant to students of color. Low staff expectations at racially and economically segregated schools also contribute disparities in educational attainment. The accumulation of inequities leads to lower graduation rates and college matriculation, with college affordability acting as another barrier. When Black and Latino students enter higher education institutions, they are less likely to attain a college a degree given weaker academic preparation and financial hardship.

Notes about the data

Adults are people 25 and older. The multi-year figures are from the Census Bureau's American Community Survey. The bureau combined five years of responses to the survey to provide estimates for smaller geographic areas and increase the precision of its estimates. However, because the information came from a survey, the samples responding to the survey were not always large enough to produce reliable results, especially in small geographic areas. CGR has noted on data tables the estimates with relatively large margins of error. Estimates with three asterisks have the largest margins, plus or minus 50% or more of the estimate. Two asterisks mean plus or minus 35%-50%, and one asterisk means plus or minus 20%-35%. For all estimates, the confidence level is 90%, meaning there is 90% probability the true value (if the whole population were surveyed) would be within the margin of error (or confidence interval). The survey provides data on characteristics of the population that used to be collected only during the decennial census. Data for this indicator are released annually in December.


Education Levels of Adults, by Race/Ethnicity, 2017-21
AsianBlack or African AmericanHispanicWhite
Pennsylvania13%30%23%24%
Lancaster County17%*28%24%22%
Lancaster City8%***29%22%24%
Lancaster County Boroughs
Christiana borough0%***33%***0%***27%*
Columbia borough0%***26%***10%***22%
Denver township17%***0%***47%***25%*
East Petersburg borough0%***36%***41%***30%*
Elizabethtown borough0%***25%***38%***27%*
Ephrata borough42%***23%***20%***26%
Lititz borough0%***0%***13%***27%
Manheim boroughN/A***N/A***94%***20%*
Marietta borough0%***28%***35%***27%*
Millersville borough18%***14%***3%***20%*
Mount Joy borough36%***21%***19%***29%
Mountville borough100%***0%***0%***19%*
New Holland borough0%***43%***32%***30%*
Quarryville borough0%***0%***30%***29%
Strasburg boroughN/A***100%***27%***18%*
Terre Hill borough0%***N/A***0%***21%**
Adamstown borough62%***46%***0%***22%*
Akron borough0%***100%***66%***30%
Lancaster County Townships
West Lampeter township24%***57%***4%***20%
Bart townshipN/A***N/A***0%***15%*
Brecknock township0%***N/A***0%***19%*
Caernarvon township0%***36%***N/A***16%*
Clay townshipN/A***0%***49%***22%*
Colerain townshipN/A***0%***N/A***19%*
Conestoga township23%***0%***20%***25%*
Conoy townshipN/A***N/A***0%***25%*
Drumore townshipN/A***N/A***0%***18%*
Earl township38%***N/A***0%***14%*
East Cocalico township0%***51%***7%***18%
East Donegal townshipN/A***0%***11%***27%
East Drumore township0%***0%***100%***22%*
East Earl township41%***0%***0%***14%*
East Hempfield township20%***27%***40%**22%
East Lampeter township13%***27%***32%*20%
Eden townshipN/A***0%***N/A***13%*
Elizabeth township37%***N/A***100%***17%*
Ephrata township21%***68%***37%***23%*
Fulton townshipN/A***0%***0%***21%*
Lancaster township11%***30%***24%**20%
Leacock townshipN/A***N/A***N/A***16%*
Little Britain townshipN/A***0%***N/A***15%**
Manheim township19%***26%***17%**20%
Manor township31%***22%***34%***20%
Martic townshipN/A***0%***50%***22%*
Mount Joy township0%***0%***15%***23%
Paradise townshipN/A***44%***24%***16%*
Penn township0%***0%***0%***21%*
Pequea township63%***0%***43%***29%*
Providence township28%***N/A***100%***19%*
Rapho township0%***71%***37%***25%
Sadsbury townshipN/A***0%***10%***25%*
Salisbury township27%***11%***43%***14%*
Strasburg townshipN/A***N/A***N/A***15%*
Upper Leacock township30%***58%***6%***19%*
Warwick township39%***9%***42%***24%
West Cocalico townshipN/A***43%***41%***19%*
West Donegal townshipN/A***36%***38%***27%*
West Earl township29%***N/A***51%***26%*
West Hempfield township0%***16%***17%***22%
Lebanon County17%**31%*23%23%
York County25%*28%24%26%
Berks County18%*38%23%25%
Chester County5%*27%19%20%
Cumberland County13%32%28%23%
Dauphin County17%*28%24%26%

Source: U.S. Census Bureau
Notes: Adults are people 25 and older. Multiyear results are from rolling American Community Survey. * Margin of error between 20% & 35% of estimate; ** margin of error between 35% & 50%; *** margin of error greater than 50%. The Census Bureau asks people to identify their race (white, African-American, etc.) separate from their ethnicity (Hispanic or non-Hispanic). So the totals for these categories cannot be added together, as people show up in both a racial and ethnic group.




Number of Adults, by Education Level and Race/Ethnicity, 2017-21
AsianBlack or African AmericanHispanicWhite
Pennsylvania39,242275,343127,2191,795,491
Lancaster County1,439*3,6467,71972,160
Lancaster City85***1,5922,9455,274
Lancaster County Boroughs
Christiana borough0***9***0***170*
Columbia borough0***156***118***1,432
Denver township14***0***89***599*
East Petersburg borough0***58***145***866*
Elizabethtown borough0***75***61***1,845*
Ephrata borough10***47***129***2,217
Lititz borough0***0***26***1,725
Manheim borough0***0***72***648*
Marietta borough0***30***36***447*
Millersville borough67***43***14***564*
Mount Joy borough17***44***58***1,614
Mountville borough37***0***0***408*
New Holland borough0***40***132***1,152*
Quarryville borough0***0***25***464
Strasburg borough0***22***31***385*
Terre Hill borough0***0***0***140**
Adamstown borough24***19***0***310*
Akron borough0***16***107***878
Lancaster County Townships
West Lampeter township63***218***14***2,311
Bart township0***0***0***250*
Brecknock township0***0***0***932*
Caernarvon township0***5***0***461*
Clay township0***0***64***976*
Colerain township0***0***0***423*
Conestoga township14***0***29***646*
Conoy township0***0***0***601*
Drumore township0***0***0***253*
Earl township12***0***0***635*
East Cocalico township0***18***41***1,220
East Donegal township0***0***14***1,506
East Drumore township0***0***26***573*
East Earl township30***0***0***626*
East Hempfield township162***143***562**3,928
East Lampeter township78***179***484*1,838
Eden township0***0***0***158*
Elizabeth township43***0***13***445*
Ephrata township11***69***101***1,619*
Fulton township0***0***0***328*
Lancaster township79***267***591**2,038
Leacock township0***0***0***477*
Little Britain township0***0***0***431**
Manheim township281***168***423**5,560
Manor township147***109***437***2,707
Martic township0***0***20***722*
Mount Joy township0***0***63***1,630
Paradise township0***27***50***478*
Penn township0***0***0***1,441*
Pequea township36***0***113***1,077*
Providence township21***0***20***857*
Rapho township0***30***50***2,106
Sadsbury township0***0***10***440*
Salisbury township8***14***89***876*
Strasburg township0***0***0***389*
Upper Leacock township69***130***24***912*
Warwick township69***21***168***2,958
West Cocalico township0***26***39***875*
West Donegal township0***18***34***1,759*
West Earl township62***0***146***1,201*
West Hempfield township0***53***106***2,381
Lebanon County230**608*2,35519,554
York County1,065*4,5014,56173,311
Berks County758*4,94411,35159,546
Chester County1,165*4,8664,03760,953
Cumberland County1,0711,9551,73537,317
Dauphin County1,562*9,0973,47837,253

Source: U.S. Census Bureau
Notes: Adults are people 25 and older. Multiyear results are from rolling American Community Survey. * Margin of error between 20% & 35% of estimate; ** margin of error between 35% & 50%; *** margin of error greater than 50%. The Census Bureau asks people to identify their race (white, African-American, etc.) separate from their ethnicity (Hispanic or non-Hispanic). So the totals for these categories cannot be added together, as people show up in both a racial and ethnic group.




INDICATORS TREND
Prekindergarten Participation Increasing
Student Performance on Grade 3 English Not Applicable
Student Performance on Grade 8 Math Not Applicable
High School Cohort Graduation Rate Increasing
Per-Student Spending Maintaining
Students Receiving Special Education Services Increasing
Rate of Foster Care Admissions Maintaining
Disengaged Youth Maintaining
Single-Parent Families by Race/Ethnicity Not Applicable
Plans of High School Graduates Not Applicable
Enrollment in Local Colleges Decreasing
College Graduation Rates Decreasing
Brain Drain/Gain Increasing
Education Levels of Adults by Race/Ethnicity Not Applicable
Average Charitable Giving Maintaining
Voter Registration Rate Not Applicable
Voter Participation Rate Increasing
Age of Housing Stock Not Applicable
Violent Crime Rate Maintaining
Incarceration Rate Decreasing
Incarceration Rate by Race/Ethnicity Not Applicable
Population Density Increasing
Air Quality Decreasing
Water Use Decreasing
Waterways Impaired by Pollution Not Applicable
Change in Population Increasing
Change in Population by Age and Gender Not Applicable
Population by Age Not Applicable
Population by Race/Ethnicity Not Applicable
People with Disabilities Maintaining
Foreign-Born Population Increasing
Language Diversity Increasing
Change in Total Jobs Increasing
Change in Employment by Sector Not Applicable
Sector Share of Total Jobs Not Applicable
Workers by Occupation Not Applicable
Change in Labor Force Maintaining
People Entering/Leaving County/Region for Work Not Applicable
Average Salary by Sector Not Applicable
Change in Average Salary Since 2000 Increasing
Female to Male Earnings Ratio Maintaining
Employer Size Not Applicable
Change in Number of Businesses by Sector Increasing
Change in Total Agricultural Sales Increasing
Spending for Local Government Maintaining
Spending for School Districts Maintaining
Children Living in Poverty Decreasing
Children in Poverty by Race/Ethnicity Not Applicable
People Living in Poverty Decreasing
People Living in Poverty, by Race/Ethnicity Not Applicable
Veterans Living in Poverty Maintaining
Working Poor Decreasing
Median Household Income by Household Type Not Applicable
Median Household Income Maintaining
Median Household Income, by Race/Ethnicity Not Applicable
Living Wage Not Applicable
Unemployment Rate by Race/Ethnicity Not Applicable
Households Receiving SNAP by Race/Ethnicity Not Applicable
Household Receiving Temporary Assistance Maintaining
Students Eligible for Free/Reduced Price Lunch Increasing
Median Home Value Maintaining
Occupied Housing Units Maintaining
Homeownership Rate, by Race/Ethnicity Not Applicable
Cost of Homeownership by Race/Ethnicity Not Applicable
Median Rent Maintaining
Cost of Renting Increasing
Households Without Vehicles Maintaining
Means of Transportation to Work, by Race/Ethnicity Not Applicable
People Without Health Insurance Increasing
Early Prenatal Care by Mother's Race/Ethnicity Not Applicable
Health Status Decreasing
Prevalence of Mental Illness Maintaining
Adults Who are Overweight or Obese Not Applicable
Mortality Rates Decreasing
Mortality Rate, by Race/Ethnicity Increasing
Fatal Drug Overdoses Increasing
Cancer Incidence Decreasing
Households With Internet Access Increasing
High-Tech Jobs Increasing
STEM Graduates Increasing
Science and Engineering Research and Development Maintaining
Single-Parent Families by Race/Ethnicity Not Applicable
Education Levels of Adults by Race/Ethnicity Not Applicable
Incarceration Rate by Race/Ethnicity Not Applicable
Population by Race/Ethnicity Not Applicable
Children in Poverty by Race/Ethnicity Not Applicable
People Living in Poverty, by Race/Ethnicity Not Applicable
Median Household Income, by Race/Ethnicity Not Applicable
Unemployment Rate by Race/Ethnicity Not Applicable
Households Receiving SNAP by Race/Ethnicity Not Applicable
Homeownership Rate, by Race/Ethnicity Not Applicable
Cost of Homeownership by Race/Ethnicity Not Applicable
Early Prenatal Care by Mother's Race/Ethnicity Not Applicable


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