U.S. Department of Commerce

Economics and Statistics Administration

U.S. CENSUS BUREAU

School-Aged Children With 

Disabilities in U.S. Metropolitan 

Statistical Areas: 2010

American Community Survey Briefs

ACSBR/10-12

By

Matthew W. Brault

Issued November 2011

INTRODUCTION

Of the 53.9 million school-aged children (aged 5 to 17) in the U.S. civilian noninstitutionalized population, 

about 2.8 million (5.2 percent) were 

reported to have a disability in 2010.1

For many of these children, the kinds 

of disabilities they experience may 

require special approaches to providing 

education or other accommodations.

In 1975, Congress enacted the Education 

for All Handicapped Children Act, which 

required all public schools that accept 

federal funds to provide equal access to 

education for children with physical and 

mental disabilities.2 Congress reauthorized the act in 1990, expanded certain 

programs, and renamed it the Individuals 

with Disabilities Education Act (IDEA).3

In 2004, Congress amended the law and 

further clarified its intended purpose that 

states provide a free appropriate public 

education for all students aged 3 to 21, 

including children with disabilities.4

IDEA defines a “child with a disability” as 

any child who has:

“mental retardation, hearing 

impairments (including deafness), 

speech or language impairments, 

visual impairments (including 

blindness), serious emotional 

disturbance [...], orthopedic 

1 S1810. Disability Characteristics, 

<factfinder2.census.gov/bkmk/table/1.0/en

/ACS/10_1YR/S1810>. 2 PL 94-142.

3 PL 101-476.

4 PL 108-4460. For information, see the 

Department of Education’s IDEA Web site: 

<http://idea.ed.gov/>.

impairments, autism, traumatic 

brain injury, other health impairments, or specific learning 

disabilities; and who, by reason 

thereof, needs special education 

and related services.”5

Before a child is deemed eligible for special education services under IDEA, the 

child must be evaluated to determine his 

or her disability status and educational 

needs.6 For each child who is determined 

5 20 U.S.C. §1401(3)(A).

6 20 U.S.C. §1414.

ACS DISABILITY CONCEPTS

With a disability—having vision, 

hearing, cognitive, ambulatory, selfcare, or independent living difficulty

Vision difficulty—blindness or 

serious difficulty seeing even 

when wearing glasses

Hearing difficulty—deafness or 

serious difficulty hearing

Cognitive difficulty—serious difficulty concentrating, remembering, 

or making decisions

Ambulatory difficulty—serious 

difficulty walking or climbing stairs

Self-care difficulty—difficulty 

bathing or dressing

Independent living difficulty—

having difficulty going outside the 

home to shop or visit a doctor’s 

office (status determined for the 

population 15 years and over)
2 U.S. Census Bureau

to have a disability under this act, 

an Individualized Education Program (IEP) is written to guide the 

provision of services.

The American Community Survey 

(ACS) captures core concepts of 

disability that may be useful for 

understanding the population of 

children for whom special education services may be necessary. 

While this measure of disability 

covers elements of physical and 

mental impairment, the ACS does 

not identify children who have been 

evaluated for or qualify under the 

statutory definition of a disability 

in IDEA. This report presents data 

on the disability status and public 

school enrollment of children aged 

5 to 17 who do not yet have a 

high school diploma or equivalent. 

These estimates are presented for 

the civilian noninstitutionalized 

population in the United States, 

states, and metropolitan statistical areas using data from the 2010 

ACS. This population excludes children in institutions such as juvenile 

correctional facilities, noncorrectional group homes for juveniles, 

and residential schools for people 

with disabilities.7

7 2010 ACS/PRCS Group Quarters 

Definitions, <www.census.gov/acs

/www/Downloads/data_documentation

/GroupDefinitions/2010GQ_Definitions.pdf>.

NATION

While the federal government 

may set certain policies, state 

and local governments share the 

primary authority over funding and 

establishing rules and curricula 

for public education. Local control 

over education allows for policies 

to be tailored to the characteristics of the communities they 

serve. One such characteristic is 

the concentration of population in 

metro areas, which provides children with more schooling options 

like private, charter, and magnet 

schools. While education is predominantly a local issue, aggregating this population to the national 

Figure 1. 

Disability Status and Type for School-Aged Children Inside and Outside Metro Areas 

in the United States: 2010

Source: U.S. Census Bureau, 2010 American Community Survey.

Disability Type

Percent

0

1

2

3

4

5

6

7

8

Children inside metro areas

Children outside metro areas

Self-care

difficulty

Ambulatory 

difficulty

Cognitive 

difficulty

Vision 

difficulty

Hearing 

difficulty

With a disability 

(total)
U.S. Census Bureau 3

level can highlight commonalities 

across states and metro areas.

About 5.0 percent of school-aged 

children living in metro areas 

across the United States had a disability (Figure 1, Table 2), compared 

with 6.3 percent of children living 

outside metro areas. Children, both 

inside and outside metro areas, 

were more likely to experience cognitive difficulties than other disability types (Figure 1). Approximately, 

3.8 percent of children in metro 

areas had a cognitive difficulty 

while 4.8 percent of children outside metro areas had a cognitive 

difficulty.8 Children living outside 

metro areas were also more likely 

to have hearing, vision, and ambulatory difficulties than children in 

metro areas. Because respondents 

in the ACS could report more than 

one type of disability, cognitive 

difficulties often accompanied 

other types of reported difficulties. 

More than one-third of children 

reporting vision, hearing, ambulatory, or self-care difficulties also 

reported a cognitive difficulty.

Of the school-aged children in 

metro areas who had a disability, 89.4 percent were enrolled in 

public schools, 7.3 percent were 

enrolled in private schools, and 

8 The percentage of children outside 

metro areas with a cognitive difficulty was not 

statistically different from the percentage of 

children inside metro areas with a disability.

3.3 percent were not enrolled in 

school (Table 1). Comparably, 86.2 

of children without disabilities 

were enrolled in public schools, 

11.0 percent enrolled in private 

schools, and 2.8 percent were not 

enrolled in school. By disability 

type, 89.7 percent of children with 

cognitive difficulties, 89.5 percent 

of children with vision difficulties, 

and 88.4 percent of children with 

hearing difficulties were enrolled 

in public schools.9 Children with 

ambulatory and self-care difficulties were less likely to be enrolled 

in public schools than children 

with other disability types with 

86.5 percent and 86.0 percent of 

children enrolled, respectively.10

Children with vision difficulties 

were among the least likely to be 

enrolled in private schools (6.3 percent), while children with self-care 

difficulties were among the most 

likely to get private education.11

9 The public school enrollment rate for 

children with vision difficulties was not statistically different from the rates for children 

with hearing difficulties, children with cognitive difficulties, or children with disabilities 

overall. 10 The public school enrollment rate for 

children with ambulatory difficulties was not 

statistically different from the rate for children with self-care difficulties. 11 The private school enrollment rate 

for children with vision difficulties was not 

statistically different from the private school 

enrollment rates for children with ambulatory 

difficulties and for children with cognitive 

difficulties. The private school enrollment rate 

for children with self-care difficulties was not 

statistically different from the private school 

Children with each of the disability 

types were less likely to attend a 

private school than children with 

no disability. Overall, children with 

ambulatory difficulties were more 

likely to not be enrolled in school 

than children with hearing, vision, 

cognitive, or self-care difficulties.

STATES

While the ranges of disability rates 

appear similar, from about 3.5 

percent to 8.4 percent, the relative ranking of rates for children 

in metro areas was different from 

those for children living outside 

metro areas (Table 2). Some states 

were not included in the range of 

disability rates for children living 

outside metro areas.12 For instance, 

the District of Columbia was among 

the highest state-level geographies for metro area disability 

rates but, for obvious reasons, 

does not have an estimate for 

children living outside metro areas. 

Fourteen states—Alabama, Arizona, 

California, Florida, Georgia, Illinois, 

Maine, Missouri, New Mexico, New 

enrollment rate for children with hearing 

difficulties. 12 New Jersey, Rhode Island, and the 

District of Columbia do not contain any 

population living outside metro areas 

and thus are not included. The estimate 

for children living outside metro areas in 

Massachusetts is not included is because the 

total population for this aggregate area was 

below the 65,000 population threshold for 

publication of geographies with 1-year 

ACS data.

Table 1. 

School Enrollment of School-Aged Children1 Living in Metro Areas by Disability Type

Disability type

Percentage

enrolled in

public school

Margin of 

error (±)2

Percentage

enrolled in

private school

Margin of 

error (±)2

Percentage

not enrolled

in school

Margin of 

error (±)2

Children with a disability: . . . . . . . . . . . . . . . . . . . 89.4 0.4 7.3 0.3 3.3 0.2

Hearing difficulty . . . . . . . . . . . . . . . . . . . . . . . 88.4 1.0 7.7 0.8 3.9 0.7

Vision difficulty . . . . . . . . . . . . . . . . . . . . . . . . . 89.5 1.0 6.3 0.8 4.3 0.7

Cognitive difficulty . . . . . . . . . . . . . . . . . . . . . . 89.7 0.5 7.0 0.3 3.3 0.2

Ambulatory difficulty . . . . . . . . . . . . . . . . . . . . . 86.5 1.3 6.8 0.8 6.7 0.9

Self-care difficulty . . . . . . . . . . . . . . . . . . . . . . . 86.0 1.0 8.8 0.7 5.2 0.7

Children with no disability . . . . . . . . . . . . . . . . . . 86.2 0.1 11.0 0.1 2.8 0.1

1

 “School-Aged Children” is defined as children aged 5 to 17 who have yet to receive a high school diploma or equivalent.

2

 Data are based on a sample and are subject to sampling variability. A margin of error is a measure of an estimate’s variability. The larger the margin of error 

in relation to the size of the estimate, the less reliable the estimate. This number when added to and subtracted from the estimate forms the 90 percent confidence 

interval. For information on the source and accuracy of these estimates, including standard errors, margins of error, and confidence intervals, see <www.census

.gov/acs/www/Downloads/data_documentation/Accuracy/ACS_Accuracy_of_Data_2010.pdf>.

Source: U.S. Census Bureau, 2010 American Community Survey.
4 U.S. Census Bureau

Table 2. 

Disability Status of School-Aged Children1 in States by Metro Status: 2010

Area

In metro areas Outside metro areas

All 

children

Margin of 

error (±)2

Percent with 

a disability

Margin of 

error (±)2

All 

children

Margin of 

error (±)2

Percent with 

a disability

Margin of 

error (±)2

 United States . . . . . . . . 45,042,788 24,254 5 .0 0 .1 8,454,357 18,392 6 .3 0 .2

Alabama . . . . . . . . . . . . . . . . . . . 583,988 3,118 6 .2 0 .6 234,462 2,992 7 .6 1 .1

Alaska . . . . . . . . . . . . . . . . . . . . . 88,947 1,305 4 .4 1 .2 43,842 672 3 .9 1 .2

Arizona . . . . . . . . . . . . . . . . . . . . 1,075,496 2,015 4 .3 0 .3 92,443 1,113 6 .2 1 .7

Arkansas . . . . . . . . . . . . . . . . . . . 315,201 2,455 7 .1 0 .8 196,559 2,454 7 .6 0 .9

California . . . . . . . . . . . . . . . . . . . 6,569,837 4,985 3 .9 0 .1 127,831 2,391 5 .7 1 .4

Colorado . . . . . . . . . . . . . . . . . . . 766,812 2,631 4 .3 0 .5 111,157 1,584 4 .5 0 .8

Connecticut . . . . . . . . . . . . . . . . . 556,488 1,396 4 .6 0 .5 51,303 481 3 .9 1 .2

Delaware . . . . . . . . . . . . . . . . . . . 120,274 735 5 .4 1 .4 28,777 277 5 .6 2 .0

District of Columbia3 . . . . . . . . . . 67,759 515 8 .4 2 .3 (X) (X) (X) (X)

Florida . . . . . . . . . . . . . . . . . . . . . 2,745,960 5,327 4 .9 0 .2 152,540 5,287 7 .5 1 .2

Georgia . . . . . . . . . . . . . . . . . . . . 1,473,905 5,612 5 .0 0 .4 323,467 3,616 6 .7 0 .9

Hawaii . . . . . . . . . . . . . . . . . . . . . 147,325 666 5 .1 1 .1 66,184 934 4 .8 1 .8

Idaho . . . . . . . . . . . . . . . . . . . . . . 207,019 2,380 5 .2 0 .7 99,324 2,201 6 .6 1 .6

Illinois . . . . . . . . . . . . . . . . . . . . . . 2,006,661 3,127 4 .1 0 .2 268,116 2,755 6 .4 0 .8

Indiana . . . . . . . . . . . . . . . . . . . . . 911,634 3,477 5 .6 0 .4 252,583 2,695 5 .9 0 .7

Iowa . . . . . . . . . . . . . . . . . . . . . . . 292,456 2,161 4 .7 0 .7 226,474 2,602 5 .1 0 .7

Kansas . . . . . . . . . . . . . . . . . . . . . 360,161 2,537 4 .8 0 .7 158,073 2,421 5 .4 0 .8

Kentucky . . . . . . . . . . . . . . . . . . . 432,050 3,672 6 .6 0 .6 302,880 3,388 7 .4 0 .9

Louisiana . . . . . . . . . . . . . . . . . . . 584,542 5,251 7 .3 0 .7 208,886 2,591 7 .1 0 .9

Maine . . . . . . . . . . . . . . . . . . . . . . 120,220 1,212 6 .4 1 .3 83,187 909 9 .3 1 .7

Maryland . . . . . . . . . . . . . . . . . . . 922,626 2,274 4 .9 0 .4 50,819 1,290 6 .3 1 .8

Massachusetts3 . . . . . . . . . . . . . . 1,036,885 2,138 5 .5 0 .4 (X) (X) (X) (X)

Michigan . . . . . . . . . . . . . . . . . . . 1,426,266 2,488 6 .2 0 .4 298,496 1,968 6 .8 0 .6

Minnesota . . . . . . . . . . . . . . . . . . 697,439 2,178 4 .8 0 .4 223,053 1,818 5 .3 0 .6

Mississippi . . . . . . . . . . . . . . . . . . 247,411 3,135 6 .7 1 .0 291,299 3,091 6 .6 0 .9

Missouri . . . . . . . . . . . . . . . . . . . . 768,698 3,711 5 .6 0 .5 252,627 3,009 6 .7 0 .8

Montana . . . . . . . . . . . . . . . . . . . . 53,855 1,141 5 .3 1 .6 104,926 1,386 5 .3 1 .3

Nebraska . . . . . . . . . . . . . . . . . . . 191,411 1,095 5 .4 1 .0 133,857 1,815 4 .0 0 .8

Nevada . . . . . . . . . . . . . . . . . . . . 425,955 1,571 4 .0 0 .6 47,401 1,382 3 .9 1 .3

New Hampshire . . . . . . . . . . . . . . 140,113 1,039 5 .6 1 .2 75,158 760 7 .8 1 .9

New Jersey3 . . . . . . . . . . . . . . . . . 1,506,500 3,124 4 .5 0 .3 (X) (X) (X) (X)

New Mexico . . . . . . . . . . . . . . . . . 243,685 1,467 3 .6 0 .7 127,047 2,094 5 .4 1 .2

New York . . . . . . . . . . . . . . . . . . . 2,868,880 3,746 4 .3 0 .2 248,035 2,027 7 .0 0 .7

North Carolina . . . . . . . . . . . . . . . 1,162,642 3,644 4 .9 0 .3 475,925 3,407 7 .7 0 .7

North Dakota . . . . . . . . . . . . . . . . 48,602 899 3 .5 1 .4 56,652 648 4 .7 1 .4

Ohio . . . . . . . . . . . . . . . . . . . . . . . 1,594,723 3,409 6 .4 0 .3 392,832 2,677 6 .5 0 .6

Oklahoma . . . . . . . . . . . . . . . . . . 430,087 1,889 5 .7 0 .6 230,824 3,115 6 .1 0 .7

Oregon . . . . . . . . . . . . . . . . . . . . . 489,264 2,126 5 .8 0 .8 135,477 1,606 6 .0 1 .0

Pennsylvania . . . . . . . . . . . . . . . . 1,723,461 2,844 6 .2 0 .3 316,539 1,765 7 .6 0 .6

Rhode Island3 . . . . . . . . . . . . . . . 164,935 1,220 7 .1 1 .1 (X) (X) (X) (X)

South Carolina . . . . . . . . . . . . . . . 593,980 3,306 4 .6 0 .5 177,785 2,818 5 .6 1 .0

South Dakota . . . . . . . . . . . . . . . . 64,970 1,090 4 .1 1 .1 77,796 1,208 4 .4 1 .4

Tennessee . . . . . . . . . . . . . . . . . . 797,486 4,127 5 .5 0 .5 280,784 3,298 7 .9 1 .0

Texas . . . . . . . . . . . . . . . . . . . . . . 4,373,967 5,207 5 .5 0 .2 543,455 4,418 5 .9 0 .6

Utah . . . . . . . . . . . . . . . . . . . . . . . 533,438 2,012 3 .6 0 .4 70,581 1,624 4 .3 1 .3

Vermont . . . . . . . . . . . . . . . . . . . . 32,408 478 5 .2 2 .1 64,289 984 8 .3 1 .5

Virginia . . . . . . . . . . . . . . . . . . . . . 1,163,110 4,627 4 .3 0 .3 171,294 3,286 5 .0 1 .0

Washington . . . . . . . . . . . . . . . . . 1,006,416 2,766 4 .8 0 .4 130,887 1,992 5 .8 1 .0

West Virginia . . . . . . . . . . . . . . . . 157,942 2,313 7 .8 1 .3 123,245 2,093 6 .9 1 .2

Wisconsin . . . . . . . . . . . . . . . . . . 721,268 2,101 5 .5 0 .5 254,407 1,768 4 .3 0 .4

Wyoming . . . . . . . . . . . . . . . . . . . 27,630 768 6 .1 3 .0 67,105 1,383 4 .3 1 .8

Puerto Rico . . . . . . . . . . . . . . . . . 621,601 2,440 9 .8 0 .7 38,722 1,366 9 .1 2 .1

(X) Not applicable . 

1

 “School-Aged Children” is defined as children aged 5 to 17 who have yet to receive a high school diploma or equivalent .

2

 Data are based on a sample and are subject to sampling variability . A margin of error is a measure of an estimate’s variability . The larger the margin of error 

in relation to the size of the estimate, the less reliable the estimate . This number when added to and subtracted from the estimate forms the 90 percent confidence 

interval . For information on the source and accuracy of these estimates, including standard errors, margins of error, and confidence intervals, see <www .census 

 .gov/acs/www/Downloads/data_documentation/Accuracy/ACS_Accuracy_of_Data_2010 .pdf> .

3

 New Jersey, Rhode Island, and the District of Columbia have no population living outside metropolitan areas . The population of Massachusetts living outside 

metropolitan areas is below the 65,000 cutoff for the publication of geographies in the 1-year ACS .

Sources: U .S . Census Bureau, 2010 American Community Survey, 2010 Puerto Rico Community Survey .
U.S. Census Bureau 5

York, North Carolina, Pennsylvania, 

Tennessee, and Vermont—had 

lower disability rates for children 

living in metro areas compared 

with those living outside metro 

areas. Nebraska and Wisconsin 

were the only states with statistically greater disability rates among 

children in metro areas compared 

to those outside metro areas. 

Across states, the percentage of 

metro area children with disabilities 

who were enrolled in public schools 

ranged from 76.5 percent to nearly 

100 percent. As shown in Figure 

2, states with public enrollment 

rates towards the lower end of the 

distribution tended to concentrate 

in the eastern part of the United 

States. States with public school 

enrollment rates at the upper end 

of the distribution were mostly in 

the western parts of the country. 

Six states—Florida, Hawaii, Illinois, 

Louisiana, Maryland, and Ohio—

and the District of Columbia had 

public school enrollment rates less 

than the national estimate while 

12 states—Arkansas, California, 

Connecticut, Kansas, Minnesota, 

Montana, North Dakota, Oklahoma, 

Rhode Island, Texas, Virginia, and 

Wyoming—had enrollment rates 

above the national estimate.

METRO AREAS

While school districts are the 

primary administrative entity with 

local jurisdiction over education 

policies, metro areas may serve 

as local markets for education. 

Families often can choose where to 

reside inside a metro area so that 

their children can attend schools in 

specific districts or can select from 

private school options in districts 

outside of their own.13 With school 

choice initiatives, a child living in 

one school district can attend a 

public school in a nearby district.

Rates of disability among schoolaged children for metropolitan 

statistical areas ranged from 1.2 

percent to 13.0 percent, while 

among those enrolled in public 

schools, the disability rates ranged 

from 1.4 percent to 14.6 percent. 

Metro areas with higher rates of 

child disability were predominantly 

13 Cullen, Julie B. and Steven G. Rivkin, 

“The Role of Special Education in School 

Choice,” in Caroline M. Hoxby (ed.) The 

Economics of School Choice, University of 

Chicago Press, Chicago, 2003, pp. 67–106.

Figure 2.

Percentage of School-Aged Children With Disabilities Living in 

Metro Areas Who Were Enrolled in Public Schools

U.S. estimate: 89.4 percent

Percentage

Greater than 93.0

89.4 to 93.0

85.0 to 89.3

Less than 85.0

*Significantly different 

from U.S. estimate

Sources: U.S. Census Bureau, 2010 American Community Survey,

2010 Puerto Rico Community Survey.

MT*

AK

NM

OR MN*

KS*

SD

ND*

MO

WA

FL*

IL* IN

WI NY

PA

MI

OH*

IA

ME

MA 

CT* 

AZ

NV

TX*

CA CO

WY*

UT

ID

NE

OK*

GA

AR*

AL

NC

MS

LA*

TN

KY

VA*

SC

WV

RI* 

DE 

MD* 

NJ 

HI*

VT NH

PR*

DC *
6 U.S. Census Bureau 0 200 mi 0 400 km 0 300 km 0 160 mi 0 300 mi 0 600 km 

Figure 3. Disability Rate for Children in Metropolitan Statistical Areas: 2010 (Children 5 to 17 years who have yet to receive a High School Degree or its equivalent. For inf

on confidentiality protection, sampling error, nonsampling error, and definitions, see www.census.gov/acs/www/Downloads/data_documentation/Accuracy/ACS_Accuracy_of_Data_

Metropolitan statistical areas defined by the Office of Management and Budget as of December 2009. Source: U.S. Census Bureau, 2010 American Community Survey. 
U.S. Census Bureau 7

in the eastern half of the United 

States, as shown in Figure 3. In 

305 of the 366 metropolitan areas, 

children with cognitive difficulties made up more than half of 

children with disabilities overall.

Among the 50 largest metropolitan 

statistical areas, the Columbus, 

OH Metro Area had one of the 

highest child disability rates at 

7.2 percent (Table 3).14 The rate 

for the San Jose-Sunnyvale-Santa 

Clara, CA Metro Area was among 

the lowest child disability rates 

at 2.8 percent.15 In all 50 metro 

areas, cognitive difficulty was 

the dominant type of disability; 

over one-half of children with 

disabilities reported this type of 

difficulty in every geography. 

Disability rates among public 

school children in the 50 largest metropolitan statistical areas 

ranged from 3.0 percent to 7.5 percent. In 27 of the 50 largest metro 

areas, disability was more common 

among public school children than 

among children overall (Table 3). 

For example, the rate of disability 

14 The child disability rate for the 

Columbus, OH Metro Area was not 

statistically different from the rates for the 

Birmingham-Hoover, AL; Cleveland-ElyriaMentor, OH; Detroit-Warren-Livonia, MI; 

Louisville/Jefferson County, KY-IN; Memphis, 

TN-MS-AR; Milwaukee-Waukesha-West 

Allis, WI; New Orleans-Metairie-Kenner, LA; 

Pittsburgh, PA; Providence-New Bedford-Fall 

River, RI-MA; and San Antonio-New Braunfels, 

TX Metro Areas. 15 The child disability rate for the San JoseSunnyvale-Santa Clara, CA Metro Area was 

not statistically different from the rates for 

the Salt Lake City, UT; San Diego-CarlsbadSan Marcos, CA; and San Francisco-OaklandFremont, CA Metro Areas.

among public school children in 

the New Orleans-Metairie-Kenner, 

LA Metro Area was 1.0 percentage point higher than the rate of 

disability among all children.

MORE INFORMATION

For more information about disability in the United States, 

go to the U.S. Census Bureau 

Web site on Disability at 

<www.census.gov/hhes/www

/disability/disability.html> or 

contact the Health and Disability 

Statistics Branch of the Census 

Bureau at 301-763-9112 or e-mail 

<matthew.w.brault@census.gov>.

SOURCE & ACCURACY

Data presented in this report are 

based on people and households 

that responded to the ACS in 2010. 

The resulting estimates are 

representative of the civilian 

noninstitutionalized population. All 

comparisons presented in this 

report have taken sampling error 

into account and are significant at 

the 90 percent confidence level 

unless otherwise noted. Due to 

rounding, some details may not 

sum to totals. For information on 

sampling and estimation methods, 

confidentiality protection, and 

sampling and nonsampling errors, 

please see the “ACS Accuracy of the 

Data” document located at 

<www.census.gov/acs/www

/Downloads/data_documentation

/Accuracy/ACS_Accuracy_of

_Data_2010.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 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>.
8 U.S. Census Bureau

Table 3. 

Disability Rates Among All School-Aged Children1 and Those Enrolled in Public Schools for the 

50 Largest Metro Areas: 2010

Metro area

All school-aged children Children enrolled in public schools Difference 

between the 

disability 

rates for all 

children and 

public school 

children

Percent 

with a 

disability

Margin 

of error 

(±)2

Percent 

with 

cognitive 

difficulty

Margin 

of error 

(±)2

Percent 

with a 

disability

Margin 

of error 

(±)2

Percent 

with 

cognitive 

difficulty

Margin 

of error 

(±)2

Atlanta-Sandy Springs-Marietta, GA . . . . . . . . . . . . . . . . . 4 .2 0 .4 3 .1 0 .3 4 .4 0 .4 3 .2 0 .4 –0 .1

Austin-Round Rock-San Marcos, TX . . . . . . . . . . . . . . . . . 5 .2 1 .0 3 .9 0 .9 5 .3 1 .0 4 .0 0 .9 –0 .1

Baltimore-Towson, MD . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 .3 0 .6 4 .0 0 .6 5 .7 0 .7 4 .2 0 .6 *–0 .3

Birmingham-Hoover, AL . . . . . . . . . . . . . . . . . . . . . . . . . . 6 .7 1 .0 4 .7 0 .9 7 .0 1 .1 4 .9 1 .0 –0 .3

Boston-Cambridge-Quincy, MA-NH . . . . . . . . . . . . . . . . . . 4 .5 0 .5 3 .5 0 .4 4 .6 0 .5 3 .6 0 .4 –0 .1

Buffalo-Niagara Falls, NY . . . . . . . . . . . . . . . . . . . . . . . . . 5 .7 1 .0 4 .3 0 .9 6 .1 1 .1 4 .7 1 .0 *–0 .4

Charlotte-Gastonia-Rock Hill, NC-SC . . . . . . . . . . . . . . . . 4 .3 0 .7 3 .4 0 .6 4 .1 0 .7 3 .1 0 .6 0 .3

Chicago-Joliet-Naperville, IL-IN-WI . . . . . . . . . . . . . . . . . . 3 .8 0 .3 2 .8 0 .2 3 .8 0 .3 2 .9 0 .2 –

Cincinnati-Middletown, OH-KY-IN . . . . . . . . . . . . . . . . . . . 5 .1 0 .7 3 .7 0 .5 5 .7 0 .7 4 .0 0 .6 *–0 .6

Cleveland-Elyria-Mentor, OH . . . . . . . . . . . . . . . . . . . . . . . 5 .9 0 .7 4 .8 0 .6 6 .2 0 .8 5 .0 0 .7 *–0 .3

Columbus, OH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 .2 0 .9 6 .1 0 .8 7 .4 1 .1 6 .4 0 .9 –0 .2

Dallas-Fort Worth-Arlington, TX . . . . . . . . . . . . . . . . . . . . . 4 .6 0 .4 3 .4 0 .3 4 .8 0 .4 3 .4 0 .3 *–0 .2

Denver-Aurora-Broomfield, CO . . . . . . . . . . . . . . . . . . . . . 4 .1 0 .6 2 .8 0 .5 4 .1 0 .6 2 .8 0 .5 –

Detroit-Warren-Livonia, MI . . . . . . . . . . . . . . . . . . . . . . . . . 6 .6 0 .6 5 .0 0 .5 6 .7 0 .7 5 .1 0 .6 –0 .1

Hartford-West Hartford-East Hartford, CT . . . . . . . . . . . . . 4 .8 0 .9 3 .7 0 .8 5 .1 1 .0 3 .9 0 .8 *–0 .3

Houston-Sugar Land-Baytown, TX . . . . . . . . . . . . . . . . . . 4 .6 0 .3 3 .2 0 .3 4 .6 0 .4 3 .2 0 .3 –

Indianapolis-Carmel, IN . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 .0 0 .7 3 .7 0 .6 5 .3 0 .8 4 .0 0 .7 *–0 .3

Jacksonville, FL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 .8 0 .9 4 .4 0 .8 6 .1 1 .0 4 .7 0 .9 *–0 .3

Kansas City, MO-KS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 .2 0 .6 3 .2 0 .5 4 .5 0 .7 3 .4 0 .5 *–0 .3

Las Vegas-Paradise, NV . . . . . . . . . . . . . . . . . . . . . . . . . . 3 .8 0 .6 3 .0 0 .6 3 .8 0 .6 3 .0 0 .6 –

Los Angeles-Long Beach-Santa Ana, CA . . . . . . . . . . . . . 3 .5 0 .2 2 .4 0 .2 3 .6 0 .2 2 .5 0 .2 *–0 .1

Louisville/Jefferson County, KY-IN . . . . . . . . . . . . . . . . . . . 6 .5 0 .9 5 .4 0 .8 7 .2 1 .0 6 .0 0 .9 *–0 .6

Memphis, TN-MS-AR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 .4 1 .1 4 .9 1 .0 6 .8 1 .3 5 .2 1 .2 –0 .4

Miami-Fort Lauderdale-Pompano Beach, FL . . . . . . . . . . . 4 .4 0 .4 3 .3 0 .4 4 .5 0 .4 3 .3 0 .4 –0 .1

Milwaukee-Waukesha-West Allis, WI . . . . . . . . . . . . . . . . . 6 .1 1 .0 5 .0 0 .9 6 .7 1 .1 5 .4 1 .1 *–0 .5

Minneapolis-St . Paul-Bloomington, MN-WI . . . . . . . . . . . . 4 .8 0 .5 3 .8 0 .4 5 .3 0 .5 4 .2 0 .5 *–0 .5

Nashville-Davidson–Murfreesboro–Franklin, TN . . . . . . . . 4 .2 0 .7 3 .4 0 .7 4 .5 0 .8 3 .6 0 .8 *–0 .3

New Orleans-Metairie-Kenner, LA . . . . . . . . . . . . . . . . . . . 5 .8 1 .1 4 .6 0 .9 6 .9 1 .3 5 .4 1 .1 *–1 .0

New York-Northern New Jersey-Long Island, NY-NJ-PA . . 3 .8 0 .2 2 .8 0 .1 4 .0 0 .2 2 .9 0 .2 *–0 .2

Oklahoma City, OK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 .7 0 .8 3 .6 0 .7 4 .9 0 .8 3 .7 0 .7 *–0 .3

Orlando-Kissimmee-Sanford, FL . . . . . . . . . . . . . . . . . . . . 5 .8 0 .7 4 .6 0 .7 5 .9 0 .8 4 .8 0 .7 –0 .1

Philadelphia-Camden-Wilmington, PA-NJ-DE-MD . . . . . . 5 .4 0 .4 4 .0 0 .4 5 .8 0 .4 4 .3 0 .4 *–0 .4

Phoenix-Mesa-Glendale, AZ . . . . . . . . . . . . . . . . . . . . . . . 4 .0 0 .4 2 .9 0 .3 4 .1 0 .4 3 .0 0 .4 –

Pittsburgh, PA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 .6 0 .7 5 .5 0 .7 6 .8 0 .7 5 .7 0 .7 –0 .2

Portland-Vancouver-Hillsboro, OR-WA . . . . . . . . . . . . . . . 5 .5 0 .8 4 .2 0 .7 5 .9 1 .0 4 .6 0 .8 *–0 .3

Providence-New Bedford-Fall River, RI-MA . . . . . . . . . . . . 6 .8 0 .9 5 .6 0 .9 7 .5 1 .1 6 .2 1 .1 *–0 .7

Raleigh-Cary, NC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 .1 0 .8 3 .6 0 .7 4 .5 0 .9 3 .9 0 .8 *–0 .3

Richmond, VA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 .4 0 .9 4 .1 0 .8 5 .9 1 .0 4 .6 0 .9 *–0 .5

Riverside-San Bernardino-Ontario, CA . . . . . . . . . . . . . . . 4 .1 0 .4 2 .8 0 .3 4 .0 0 .4 2 .8 0 .3 0 .1

Sacramento–Arden-Arcade–Roseville, CA . . . . . . . . . . . . 5 .7 0 .9 4 .4 0 .8 5 .5 0 .9 4 .3 0 .8 0 .2

St . Louis, MO-IL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 .7 0 .7 4 .2 0 .6 6 .2 0 .8 4 .6 0 .7 *–0 .4

Salt Lake City, UT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 .6 0 .7 2 .9 0 .6 3 .7 0 .8 3 .0 0 .7 –0 .1

San Antonio-New Braunfels, TX . . . . . . . . . . . . . . . . . . . . 6 .5 0 .7 4 .8 0 .6 6 .7 0 .8 5 .0 0 .7 –0 .2

San Diego-Carlsbad-San Marcos, CA . . . . . . . . . . . . . . . . 3 .3 0 .4 2 .3 0 .4 3 .3 0 .5 2 .4 0 .4 –0 .1

San Francisco-Oakland-Fremont, CA . . . . . . . . . . . . . . . . 3 .3 0 .4 2 .4 0 .4 3 .5 0 .5 2 .4 0 .4 *–0 .2

San Jose-Sunnyvale-Santa Clara, CA . . . . . . . . . . . . . . . . 2 .8 0 .6 1 .8 0 .4 3 .0 0 .7 2 .0 0 .5 *–0 .2

Seattle-Tacoma-Bellevue, WA . . . . . . . . . . . . . . . . . . . . . . 4 .1 0 .4 2 .8 0 .3 4 .4 0 .5 3 .0 0 .4 *–0 .3

Tampa-St . Petersburg-Clearwater, FL . . . . . . . . . . . . . . . . 4 .0 0 .6 3 .1 0 .5 3 .8 0 .6 3 .0 0 .6 0 .2

Virginia Beach-Norfolk-Newport News, VA-NC . . . . . . . . . 5 .0 0 .7 4 .2 0 .7 5 .3 0 .8 4 .5 0 .8 *–0 .3

Washington-Arlington-Alexandria, DC-VA-MD-WV . . . . . . 3 .8 0 .4 2 .8 0 .3 3 .9 0 .4 3 .0 0 .3 –0 .1

– Represents or rounds to zero .

* Statistically different from zero at the 90 percent confidence level . 

1

 “School-Aged Children” is defined as people aged 5 to 17 without a high school degree or equivalent .

2

 Data are based on a sample and are subject to sampling variability . A margin of error is a measure of an estimate’s variability . The larger the margin of error in relation to 

the size of the estimate, the less reliable the estimate . This number when added to and subtracted from the estimate forms the 90 percent confidence interval . For information 

on the source and accuracy of these estimates, including standard errors, margins of error, and confidence intervals, see <www .census .gov/acs/www/Downloads/data 

_documentation/Accuracy/ACS_Accuracy_of_Data_2010 .pdf> .

Source: U .S . Census Bureau, 2010 American Community Survey .