U.S. Department of Commerce

Economics and Statistics Administration

U.S. CENSUS BUREAU

census.gov

The Geographic Concentration of High-Income 

Households: 2007–2011

American Community Survey Briefs

Issued February 2013

ACSBR/11-23

By Charles Adam Bee 

Two questions present themselves when considering 

the geographic concentration of high-income households. First, where do most high-income households 

live? Second, where are the highest concentrations of 

high-income households? This brief answers the first 

question by estimating the number of high-income 

households in each area. This brief answers the second 

question by presenting estimates of the proportions 

of households that are among the top 5 percent.

This brief is based on data from the American 

Community Survey pooled across survey 

years 2007 through 2011, referring to income 

received from January 2006 to November 2011.1

During this period, the top 5 percent of households received at least $191,469 per year.2

Figure 1 depicts the number of high-income households in each county, while Figure 2 maps the 

number of all households in each county. These 

figures illustrate that, like the general population, most high-income households lived in highpopulation counties, especially along the coasts.3

We are interested not only in where most high-income 

households lived, but also in which places had the 

highest concentrations of high-income households. 

Figure 3 illustrates the proportion of households 

within each county that were among the top 5 

1 All income data are adjusted for inflation to 2011 dollars.

2 Source: 2007–2011 American Community Survey 5-Year Estimates, Base Table B19080: Household Income Quintile Upper Limits. 3 The correlation between the number of high-income households 

in each county and the number of other households was 0.88.

percent of U.S. households with respect to income. 

This map highlights how the geographic distribution of high-income households differed from that of 

other households. Some sparsely populated areas, for 

example, may have low absolute numbers of highincome households (relative to other counties), and 

yet have high concentrations of such households.

Inspection of Figure 3 suggests that high-concentration 

counties are especially prevalent in the coastal areas

as well. The Pacific, Middle Atlantic, and New 

England divisions had high proportions of counties with high concentrations of high-income 

households. In contrast, the East South Central 

division’s counties tended to have unusually low 

concentrations of high-income households.

Table 1 presents proportions of households that were 

in the top 5 percent of the national distribution for 

each of the 50 most populous metropolitan statistical 

areas (MSAs). This table suggests that high-population 

areas often had high-income households not only in 

large numbers, but also in high concentrations. These 

50 most populous metropolitan areas contained 51.9 

percent of all U.S. households, and 71.9 percent of the 

top 5 percent of households. Within MSAs, the central 

cities had lower concentrations than the suburbs, as 

4.9 percent of households in the central city were 

among the top 5 percent, compared to 6.1 percent 

of those within MSAs but outside central cities.4

4 Among households residing outside MSAs, 1.9 percent were in 

the top 5 percent.
2 U.S. Census Bureau Number of High-Income Households for Each County in the United States: 2007–2011 Figure 1. Source: U.S. Census Bureau, 2007–2011 American Community Survey. Note: The term "county" refers to a county or statistically equivalent entity. 0 100 Miles 0 100 Miles 0 500 Miles Number of households by county107–251 252–883 43–106 884 or more Less than 43
U.S. Census Bureau 

3

Number of Households for Each County in the United States: 2007–2011Figure 2.

Source: U.S. Census Bureau, 2007–2011 American Community Survey.

Note: The term "county" refers to a county or statistically equivalent entity.

0 100 Miles

0 100 Miles

0 500 Miles

Number of households 

by county

7,248–14,074

14,075–34,586

3,534–7,247

Less than 3,534

34,587 or more
4 U.S. Census Bureau Fi Concentration of High-Income Households for Each County in the United States: 2007–2011 gure 3. 0 100 Miles 0 100 Miles 0 500 Miles Concentration by county1.559% to 2.159% 2.160% to 3.247% 1.012% to 1.558% Less than 1.012% Pacific Pacific Pacific WEST Mountain West South Central West North Central East North Central Middle Atlantic East South Central South Atlantic New England MIDWEST NORTHEAST SOUTH CENSUS REGION 3. Census Division 248% or more Source: U.S. Census Bureau, 2007–2011 American Community Survey. Note: The term "county" refers to a county or statistically equivalent entity. Each category contains approximately 629 counties ranked by concentration of high-income households.
U.S. Census Bureau 5

Table 1.

Concentration of High-Income Households in the 50 Most Populous Metropolitan 

Statistical Areas: 2007–2011

(For information on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/acs/www/)

Rank Population 

Metropolitan statistical area

Percentage of 

MSA households 

among top

5 percent

1 19,015,900 New York-Northern New Jersey-Long Island, NY-NJ-PA . . . . . . . . . . . . . . . . . . . 10.0

2 12,944,801 Los Angeles-Long Beach-Santa Ana, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.9

3 9,504,753 Chicago-Joliet-Naperville, IL-IN-WI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.8

4 6,526,548 Dallas-Fort Worth-Arlington, TX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1

5 6,086,538 Houston-Sugar Land-Baytown, TX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.8

6 5,992,414 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD . . . . . . . . . . . . . . . . . . . . . . . . 6.9

7 5,703,948 Washington-Arlington-Alexandria, DC-VA-MD-WV . . . . . . . . . . . . . . . . . . . . . . . 14.1

8 5,670,125 Miami-Fort Lauderdale-Pompano Beach, FL . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3

9 5,359,205 Atlanta-Sandy Springs-Marietta, GA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.9

10 4,591,112 Boston-Cambridge-Quincy, MA-NH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.7

11 4,391,037 San Francisco-Oakland-Fremont, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.0

12 4,304,997 Riverside-San Bernardino-Ontario, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4

13 4,285,832 Detroit-Warren-Livonia, MI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3

14 4,263,236 Phoenix-Mesa-Glendale, AZ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6

15 3,500,026 Seattle-Tacoma-Bellevue, WA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1

16 3,318,486 Minneapolis-St. Paul-Bloomington, MN-WI ............................... 6.4

17 3,140,069 San Diego-Carlsbad-San Marcos, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3

18 2,824,724 Tampa-St. Petersburg-Clearwater, FL ................................... 3.6

19 2,817,355 St. Louis, MO-IL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3

20 2,729,110 Baltimore-Towson, MD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.0

21 2,599,504 Denver-Aurora-Broomfield, CO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3

22 2,359,746 Pittsburgh, PA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.8

23 2,262,605 Portland-Vancouver-Hillsboro, OR-WA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7

24 2,194,927 San Antonio-New Braunfels, TX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9

25 2,176,235 Sacramento—Arden-Arcade—Roseville, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5

26 2,171,360 Orlando-Kissimmee-Sanford, FL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9

27 2,138,038 Cincinnati-Middletown, OH-KY-IN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4

28 2,068,283 Cleveland-Elyria-Mentor, OH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7

29 2,052,676 Kansas City, MO-KS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4

30 1,969,975 Las Vegas-Paradise, NV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1

31 1,865,450 San Jose-Sunnyvale-Santa Clara, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9

32 1,858,464 Columbus, OH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5

33 1,795,472 Charlotte-Gastonia-Rock Hill, NC-SC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4

34 1,783,519 Austin-Round Rock-San Marcos, TX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3

35 1,778,568 Indianapolis-Carmel, IN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4

36 1,679,894 Virginia Beach-Norfolk-Newport News, VA-NC . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.0

37 1,617,142 Nashville-Davidson—Murfreesboro—Franklin, TN . . . . . . . . . . . . . . . . . . . . . . . . 4.6

38 1,600,224 Providence-New Bedford-Fall River, RI-MA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7

39 1,562,216 Milwaukee-Waukesha-West Allis, WI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3

40 1,360,251 Jacksonville, FL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1

41 1,325,605 Memphis, TN-MS-AR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9

42 1,294,849 Louisville/Jefferson County, KY-IN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5

43 1,278,053 Oklahoma City, OK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5

44 1,269,380 Richmond, VA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3

45 1,213,255 Hartford-West Hartford-East Hartford, CT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4

46 1,191,089 New Orleans-Metairie-Kenner, LA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3

47 1,163,515 Raleigh-Cary, NC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.0

48 1,145,905 Salt Lake City, UT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4

49 1,134,039 Buffalo-Niagara Falls, NY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2

50 1,132,264 Birmingham-Hoover, AL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2

Note: Population estimates are as of July 1, 2011.

Sources: High-income concentrations are from the 2007–2011 American Community Surveys, and populations are from “Annual Estimates of the Population of 

Metropolitan and Micropolitan Statistical Areas: April 1, 2010 to July 1, 2011.”
6 U.S. Census Bureau

Table 2 lists 25 metropolitan statistical areas with high concentrations of households among the top 

5 percent. Bridgeport-StamfordNorwalk, CT, had the highest 

concentration of high-income 

households, with 17.9 percent of 

households falling in the top 5 

percent of the national distribution.

Table 3 lists 25 MSAs with low 

concentrations of high-income 

households out of the 366 MSAs. 

Coincidentally, two of the lowest 

MSAs were both named Danville. In 

Danville, IL, and Danville, VA, 1.1 

percent of each county’s households were among the top 5 percent of U.S. households by income.5

SOURCE AND ACCURACY

The data presented in this report 

are based on the ACS sample 

interviewed in years 2007 through 

2011. The estimates based on this 

5 The estimated proportions for Danville, 

VA, and Danville, IL, were not statistically 

significantly different at the 90 percent confidence level. The estimated proportion for 

Danville, VA, is also not statistically significantly different from the third-, fourth-, and 

seventh-lowest estimates. The estimate for 

Danville, IL, is not statistically significantly 

different from any of the seven lowest estimated proportions.

sample approximate the actual 

values and represent the entire 

household and group quarters 

population. Sampling error is the 

difference between an estimate 

based on a sample and the corresponding value that would be 

obtained if the estimate were based 

on the entire population (as from a 

census). Measures of the sampling 

errors are provided in the form of 

margins of error for all estimates 

included in this report. All comparative statements in this report have 

undergone statistical testing, and 

comparisons are significant at the 

90 percent level unless otherwise 

noted. In addition to sampling 

error, nonsampling error may be 

introduced during any of the operations used to collect and process 

survey data such as editing, reviewing, or keying data from questionnaires. For more information on 

sampling and estimation methods, 

confidentiality protection, and 

sampling and nonsampling errors, 

please see the 2011 ACS Accuracy 

of the Data document located at 

<www.census.gov/acs

/www/Downloads/data

_documentation/Accuracy/ACS

_Accuracy_of_Data_2011.pdf>.

What Is the American Community Survey?

The American Community Survey (ACS) is a nationwide survey 

designed to provide communities with reliable and timely demographic, 

social, economic, and housing data for the nation, states, congressional districts, counties, places, and other localities every year. It has an 

annual sample size of about 3.3 million addresses across the United 

States and Puerto Rico and includes both housing units and group 

quarters (e.g., nursing facilities and prisons). The ACS is conducted 

in every county throughout the nation, and every municipio in Puerto 

Rico, where it is called the Puerto Rico Community Survey. Beginning 

in 2006, ACS data for 2005 were released for geographic areas with 

populations of 65,000 and greater. For information on the ACS sample 

design and other topics, visit <www.census.gov/acs/www>.
U.S. Census Bureau 7

Table 2.

Concentrations of High-Income Households in the Highest-Concentration Metropolitan 

Statistical Areas: 2007–2011

(For information on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/acs/www/)

Rank

Metropolitan statistical area

Percentage of

MSA households 

among top

5 percent

1 Bridgeport-Stamford-Norwalk, CT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17.9

2 San Jose-Sunnyvale-Santa Clara, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15.9

3 Washington-Arlington-Alexandria, DC-VA-MD-WV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.1

4 San Francisco-Oakland-Fremont, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.0

5 Trenton-Ewing, NJ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.6

6 New York-Northern New Jersey-Long Island, NY-NJ-PA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.0

7 Oxnard-Thousand Oaks-Ventura, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.7

8 Boston-Cambridge-Quincy, MA-NH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.7

9 Boulder, CO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4

10 Napa, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3

11 Santa Cruz-Watsonville, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.0

12 Naples-Marco Island, FL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.8

13 Baltimore-Towson, MD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.0

14 Midland, TX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.9

15 Los Angeles-Long Beach-Santa Ana, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.9

16 Santa Barbara-Santa Maria-Goleta, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4

17 Hartford-West Hartford-East Hartford, CT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4

18 San Diego-Carlsbad-San Marcos, CA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3

19 Seattle-Tacoma-Bellevue, WA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1

20 Honolulu, HI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.0

21 Philadelphia-Camden-Wilmington, PA-NJ-DE-MD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.9

22 Anchorage, AK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.9

23 Santa Rosa-Petaluma, CA............................................................ 6.8

24 Houston-Sugar Land-Baytown, TX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.8

25 Chicago-Joliet-Naperville, IL-IN-WI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.8

Sources: 2007–2011 American Community Surveys.

Table 3.

Concentrations of High-Income Households in the Lowest-Concentration Metropolitan 

Statistical Areas: 2007–2011

(For information on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/acs/www/)

Rank

Metropolitan statistical area

Percentage of

MSA households 

among top

5 percent

342 Owensboro, KY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7

343 Lake Havasu City-Kingman, AZ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7

344 Morristown, TN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7

345 Lewiston-Auburn, ME . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6

346 Jacksonville, NC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6

347 Bay City, MI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6

348 Williamsport, PA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6

349 Youngstown-Warren-Boardman, OH-PA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6

350 Springfield, OH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5

351 Pocatello, ID . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5

352 Goldsboro, NC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5

353 Clarksville, TN-KY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5

354 Johnstown, PA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4

355 Wheeling, WV-OH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4

356 Sumter, SC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4

357 Cumberland, MD-WV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4

358 Gadsden, AL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4

359 Mansfield, OH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4

360 Hinesville-Fort Stewart, GA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3

361 Anderson, IN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3

362 Muskegon-Norton Shores, MI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3

363 Steubenville-Weirton, OH-WV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3

364 Pine Bluff, AR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2

365 Danville, IL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1

366 Danville, VA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1

Sources: 2007–2011 American Community Surveys.