Number 39 n April 20, 2011

Wireless Substitution: State-level Estimates From
 

the National Health Interview Survey,
 

January 2007–June 2010
 by Stephen J. Blumberg, Ph.D., and Julian V. Luke, Division of Health Interview Statistics,
 

National Center for Health Statistics; Nadarajasundaram Ganesh, Ph.D., and Michael E. Davern, Ph.D.,
 

NORC at the University of Chicago; and Michel H. Boudreaux, M.S., and Karen Soderberg, M.S.,
 

State Health Access Data Assistance Center, University of Minnesota
 

Abstract

Objectives—This report presents state-level estimates of the percentage of

adults and children living in households that did not have a landline telephone

but did have at least one wireless telephone. National estimates for the 12-month

time period from July 2009 through June 2010 indicate that 23.9% of adults and

27.5% of children were living in these wireless-only households. Estimates are

also presented for selected U.S. counties and groups of counties, for other

household telephone service use categories (e.g., those that had only landlines

and those that had landlines yet received all or almost all calls on wireless

telephones), and for 12-month time periods since January–December 2007.

Methods—Small-area statistical modeling techniques were used to estimate

the prevalence of adults and children living in households with various household

telephone service types for 93 disjoint geographic areas that make up the entire

United States. This modeling was based on January 2007–June 2010 data from

the National Health Interview Survey, 2006–2009 data from the American

Community Survey, and auxiliary information on the number of listed telephone

lines per capita in 2007–2010.

Results—The prevalence of wireless-only adults and children varied

substantially across states. State-level estimates for July 2009–June 2010 ranged

from 12.8% (Rhode Island and New Jersey) to 35.2% (Arkansas) of adults and

from 12.6% (Connecticut and New Jersey) to 46.2% (Arkansas) of children. For

adults, the magnitude of the increase from 2007 to 2010 was lowest in New

Jersey (7.2 percentage points) and highest in Arkansas (14.5 percentage points).

Keywords: cell phones • telephone surveys • noncoverage • small domain

estimation

Introduction

The prevalence and use of wireless

telephones (also known as cellular

telephones, cell phones, or mobile

phones) has changed substantially over

the past decade. Today, an everincreasing number of adults have chosen

to use wireless telephones rather than

landline telephones to make and receive

calls. As of the first half of 2010, more

than one in four American households

(26.6%) had only wireless telephones—

an eightfold increase over just 6

years (1). The prevalence of such

‘‘wireless-only’’ households now

markedly exceeds the prevalence of

households with only landline

telephones (12.9%), and this difference

is expected to grow.

The increasing prevalence of

wireless-only households has

implications for telephone surveys.

Many health surveys, political polls, and

other research studies are conducted

using random-digit-dial (RDD)

telephone surveys. Until recently, these

surveys did not include wireless

telephone numbers in their samples.

Now, despite operational challenges,

most major survey research organizations include wireless telephone

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES 

Centers for Disease Control and Prevention 

National Center for Health Statistics 
Page 2 National Health Statistics Reports n Number 39 n April 20, 2011

numbers when conducting RDD

telephone surveys. If they did not, the

exclusion of households with only

wireless telephones (along with the

2.0% of households that have no

telephone service) could bias

results (2–4).

Best practices for conducting

surveys by calling wireless telephones

are not yet known, but substantial

research has been conducted to address

the known operational challenges (5).

Statistical challenges also exist when

combining samples of wireless-only

households with samples of landline

households from RDD surveys. To

ensure that each sample is appropriately

represented in the final data set and

appropriately weighted in the final

analyses, reliable estimates of the

prevalence of wireless-only households

are needed (5). Moreover, if the persons

interviewed on their wireless telephones

are not screened to exclude persons who

also have landlines, reliable estimates of

the prevalence of landline and wireless

telephone service use may be required

to address the probability that an

individual could be in both samples (5).

The National Health Interview

Survey (NHIS) is the most widely cited

source for data on the ownership and

use of wireless telephones. Every 6

months, the Centers for Disease Control

and Prevention’s (CDC) National Center

for Health Statistics (NCHS) releases a

report with the most up-to-date

estimates available from the federal

government concerning the size and

characteristics of the wireless-only

population (1). That report, published as

part of the NHIS Early Release

Program, presents national and regional

estimates.

Many RDD telephone surveys are

designed to collect data and produce

results at the state or local level,

including several surveys conducted by

CDC (e.g., the Behavioral Risk Factor

Surveillance System, the National

Immunization Survey, and the State and

Local Area Integrated Telephone

Survey). For such surveys to effectively

combine samples of wireless-only

households with samples of landline

households, state-level estimates of the

prevalence of wireless-only households

are needed. Direct state-level estimates

of this prevalence have not been

available from NHIS data because the

sample size of NHIS is insufficient for

direct, reliable annual estimates for most

states. However, in March 2009 NCHS

released the results of statistically

modeled estimates of the prevalence of

wireless-only adults at the state level,

using data from the 2007 NHIS and the

2008 Current Population Survey’s

Annual Social and Economic

Supplement (6). Those estimates were

the first state-level estimates of the size

of this population available from the

federal government.

In this report, we update those

original 2007 estimates. We present

results of modeled estimates of the

prevalence of wireless-only adults and

wireless-only children at the state level,

using data from the 2007–2010 NHIS

and the 2006–2009 American

Community Survey (ACS), along with

auxiliary information on the number of

listed telephone lines per capita. By

incorporating data from multiple

sources, the modeled estimates presented

here take advantage of the unique

strengths of each data set.

This report also expands on the

original 2007 estimates in three

important ways. First, it includes

estimates for 42 additional substate

geographic areas in the United States.

Second, it includes estimates not only

for July 2009–June 2010, but also for

12-month time periods from January

2007 through June 2010. Third, it

includes estimates not only for persons

living in wireless-only households, but

also for additional household telephone

service use categories. Estimates are

presented for adults and children living

in wireless-mostly households (defined

as households that have landlines yet

receive all or almost all calls on

wireless telephones), dual-use

households (which receive significant

amounts of calls on both landlines and

wireless telephones), landline-mostly

households (which have wireless

telephones yet receive all or almost all

calls on landlines), and landline-only

households.

Methods

Small-area statistical modeling

techniques were used to combine NHIS

data collected from within specific

geographies (states and some counties)

with auxiliary data that are representative of those geographies to

produce model-based estimates.

Specifically, we used a combination of

direct survey estimates from the

2007–2010 NHIS, direct survey

estimates from the 2006–2009 ACS, and

auxiliary information on the number of

listed telephone lines per capita in

2007–2010. The small-area model was

used to derive estimates of the

proportion of people who lived in

households that were wireless-only,

wireless-mostly, dual-use, landlinemostly, and landline-only for the

following seven 6-month periods:

January–June 2007, July–December

2007, January–June 2008, July–

December 2008, January–June 2009,

July–December 2009, and January–

June 2010.

Estimates were derived for adults

and children for 93 nonoverlapping

areas that make up the entire United

States. Twenty-six of these areas were

states, and one was the District of

Columbia; others areas consisted of

selected counties, groups of counties, or

the balance of the state population

excluding the selected counties. No

areas crossed state lines, and every

location in the United States was part of

one (and only one) of the 93 areas.

Areas considered for inclusion in this

report included urban areas that receive

federal Section 317 immunization grants

and other substate areas that are strata

for CDC’s National Immunization

Survey (7). Areas were selected for this

report on the basis of available survey

sample sizes and the stability of the

modeled estimates.

For each telephone category, the

6-month estimates for all 93 small areas

were modeled jointly. That is, all

6-month periods were modeled together

in a single model rather than separately

as seven models (one for each 6-month

period). Separate small-area models

were fitted for each telephone service

use category (e.g., wireless-only,
Greater than or equal to 30% 

25% to less than 30% 

20% to less than 25% 

Less than 20% 

DATA SOURCES: CDC/NCHS, National Health Interview Survey, January 2007–2010; U.S. Census Bureau, American Community Survey, 2006–2009; and infoUSA.com consumer database, 

2007–2010. Estimates were calculated by NORC at the University of Chicago. 

Figure 1. State-level comparisons of the percentage of adults living in wireless-only households, using modeled estimates: United States,

July 2009–June 2010

National Health Statistics Reports n Number 39 n April 20, 2011 Page 3

dual-use) and by age group (adults or

children). The model-based estimates for

each telephone service use category,

small area, and 6-month period were

derived using a standard small-area

modeling and estimation approach

known as ‘‘empirical best linear

unbiased prediction’’ (8–10). The

model-based estimates were a weighted

combination of three distinct sets of

estimates: (a) the direct estimate from

NHIS for the small area during the

6-month period of interest, (b) a

synthetic estimate derived from a

regression model involving ACS and

other auxiliary data for the small area

during the 6-month period of interest,

and (c) ‘‘adjusted direct estimates’’ from

NHIS for the small area during all

6-month periods other than the 6-month

period of interest. By using estimates

from all seven 6-month periods, the

model-based estimate allows for

‘‘borrowing strength’’ across time. When

these three distinct sets of estimates

were combined, the weights associated

with each set reflected the relative

precision of each estimate.

Although model-based estimates

were produced for every small area and

6-month period, consecutive 6-month

period estimates were combined to

produce 12-month estimates. The

small-area estimates for 12-month

periods were obtained by averaging two

consecutive 6-month estimates. This

helped to reduce the variability of the

estimates. Then, the 12-month smallarea estimates for each phone category

were adjusted so that they agreed with

the national direct estimates from NHIS

for the corresponding phone category

and year. The 12-month estimates were

further adjusted so that they agreed with

the 2008 or 2009 ACS estimate for the

population with a telephone (either

landline or wireless) for each small area.

For states with multiple small areas,

12-month state-level estimates were

obtained by appropriately weighting the

12-month small-area estimates by

population size.

Further detail regarding this

estimation methodology is available in

the Technical Notes section.

Estimates for Adults

and Children Living

in Wireless-only

Households

Results from the small-area

modeling strategy showed great

variation in the prevalence of adults

living in wireless-only households

across states (Figures 1 and 2).

Estimates for July 2009–June 2010

ranged from a high of 35.2% in

Arkansas to a low of 12.8% in Rhode

Island and New Jersey (Table 1). Other

states in which the prevalence of

wireless-only adults was relatively high
(exceeding 31%) were Mississippi

(35.1%), Texas (32.5%), North Dakota

(32.3%), Idaho (31.7%), and Kentucky

(31.5%). Several other states in the

Northeast region joined Rhode Island

and New Jersey with prevalence rates

below 17%, including Connecticut

(13.6%), New Hampshire (16.0%),

Pennsylvania (16.5%), Delaware

(16.5%), and Massachusetts (16.8%).

Prevalence rates were also relatively low

in South Dakota (15.6%).

Similarly, results showed great

variation in the prevalence of wirelessonly children across states, ranging from

a high of 46.2% in Arkansas to a low of

12.6% in Connecticut and New Jersey

(Table 2). Other states with a high

prevalence of wireless-only children

included Mississippi (41.9%), North

Dakota (39.7%), New Mexico (38.9%),

and Idaho (37.3%). Other states with a

low prevalence of wireless-only children

included New Hampshire (15.0%),

Massachusetts (15.1%), Rhode Island

(15.8%), and New York (16.6%).

Table 1 also provides the modeled

estimates of the prevalence of wirelessonly adults for each 12-month time

period from January 2007 through June

2010. Nationally, the prevalence of

wireless-only adults increased from

13.6% to 23.9%, an absolute increase of

10.3 percentage points. As expected, the

values increased in every state from

2007 to 2010, and the increase in

prevalence was statistically significant in

every state. The absolute increase from

2007 to 2010 ranged from a high of

14.5 percentage points in Arkansas to a

low of 7.2 percentage points in New

Jersey. Other states with a larger-thanaverage increase in the prevalence of

wireless-only adults included Mississippi

(14.1) and North Dakota (13.0). Other

states with a smaller-than-average

increase included New York (7.3),

Pennsylvania (7.5), Rhode Island (7.5),

and Utah (7.6). Table 2 can be used to

produce similar estimates of change

over time for children living in wirelessonly households.

Estimates for Adults

Living in Households

With Wireless

Telephones

Table 3 presents modeled estimates

for July 2009–June 2010 for the

prevalence of adults living in

households with various telephone

service types, including but not limited

to wireless-only status. Estimates are

presented for adults living in wirelessmostly households, landline-mostly

State

Percent

0

5

10

15

20

25

30

AR

MS

TX

ND

ID

KY

ORCO

NE

OK

AZ

MI

IA

KS

TN

FL

NM

LA

GA

WA

SC

OH

WI

AL

NC

MN

IN

UT

IL

NV

ME

MO

WY

HI

VA

WV

VT

AK

MT

MD

CANY

MA

DE

PA

NH

SD

CT

NJ

RI

35

40

DATA SOURCES: CDC/NCHS, National Health Interview Survey, January 2007–2010; U.S. Census Bureau, American Community Survey, 2006–2009; and infoUSA.com consumer database,

2007–2010. Estimates were calculated by NORC at the University of Chicago.

Figure 2. Modeled state-level estimates of the percentage of adults living in wireless-only households: United States, July 2009–June 2010

Page 4 National Health Statistics Reports n Number 39 n April 20, 2011
National Health Statistics Reports n Number 39 n April 20, 2011 Page 5

households, dual-use households, and

landline-only households. These results

can be used to obtain the prevalence of

adults living in households with any

wireless telephones (regardless of

whether the wireless telephones are the

only telephones). Estimates ranged from

a high of 91.8% in Iowa to a low of

47.9% in South Dakota. Other states

exceeding 90% included Utah (90.9%),

Colorado (90.7%), Kansas (90.7%),

Minnesota (90.3%), and Delaware

(90.3%). Other states below 70%

included Montana (60.6%), Wyoming

(63.3%), and Nevada (66.2%).

Table 3 can also be used to look at

the prevalence of adults living in

households that receive all or almost all

calls on wireless telephones, regardless

of whether the households have landline

telephones. Both wireless-only and

wireless-mostly adults are in this group.

Estimates of the prevalence of adults

living in households where wireless

telephones are the primary means of

receiving calls ranged from 52.8% in

Texas to 24.9% in South Dakota. Other

states exceeding 47% included Arkansas

(50.9%), Mississippi (49.8%), Arizona

(48.1%), and Nebraska (47.3%). Other

states below 30% included Connecticut

(28.2%), New Hampshire (29.4%), and

Rhode Island (29.6%).

Table 4 presents modeled estimates

for July 2009–June 2010 for the

prevalence of children living in

households with various telephone

service types. The table can be used to

calculate estimates for children similar

to those for adults described above.

Discussion

Because of the limited availability

of reliable and updated state-level

prevalence estimates for the wirelessonly population, survey researchers

interested in combining state-level

samples of wireless-only households

with samples of landline households

have relied on national or regional

estimates of the relative sizes of these

two populations (5). Similarly,

telecommunications companies seeking

greater understanding of conditions in

state and local markets have relied on

regional estimates of the prevalence of

wireless-only persons (11). The results

in this report clearly show that, for

many states, national and regional

estimates are not sufficiently accurate

for these purposes.

Results from the small-area

statistical models show great state-level

variation in the prevalence of wirelessonly adults, even within regions. The

range of prevalence exceeded

10 percentage points in the Northeast

region, 13 percentage points in the West

region, 16 percentage points in the

Midwest region, and 18 percentage

points in the South region. In fact, in

the Midwest region, the state with the

lowest prevalence (South Dakota,

15.6%) borders the state with the

highest prevalence (North Dakota,

32.3%). Wider ranges within regions

were observed for estimates of the

prevalence of wireless-only children.

Survey researchers and

telecommunications companies

interested in local areas may question

whether state-level prevalence estimates

are sufficiently specific. This report

includes estimates for 42 counties or

groups of counties, selected from a list

of immunization-policy-relevant areas

on the basis of available survey sample

sizes and the stability of the modeled

estimates. Most of these substate areas

are major metropolitan cities, and

national estimates suggest that adults

living in metropolitan areas are more

likely to live in wireless-only

households than are adults living in

nonmetropolitan areas. The mean of the

42 substate-area estimates of the

prevalence of wireless-only adults

(26.7%) was greater than the mean of

the ‘‘rest of state’’ estimates for those 24

states (23.5%). However, for the

majority of the substate areas, the

prevalence of wireless-only adults did

not differ significantly from the area’s

corresponding state-level prevalence

estimate. Exceptions included Orange

County (Orlando, Florida), Cook County

(Chicago, Illinois), Madison/St. Clair

counties (Metro East St. Louis, Illinois),

Marion County (Indianapolis, Indiana),

Suffolk County (Boston, Massachusetts),

Wayne County (Detroit, Michigan),

Essex County (Newark, New Jersey),

Allegheny County (Pittsburgh,

Pennsylvania), Davidson County

(Nashville, Tennessee), Dallas County

(Dallas, Texas), and King County

(Seattle, Washington), where the

prevalence of wireless-only adults

significantly exceeded the corresponding

state-level prevalence.

Prevalence estimates are included

not only for July 2009–June 2010, but

also for 12-month time periods from

January 2007 through June 2010. The

statistical model based on 31⁄2 years of

data—and therefore larger sample sizes

in each geographic area—is more stable

than a model based on only a single

year of data. Estimates from the more

stable model are presumed to be more

reliable. Thus, we presume that the

estimates for 2007 presented in this

report are more reliable than the

estimates for 2007 presented in our

previous report (6). Modeled estimates

for January 2007–June 2009 for

household telephone service use

categories other than wireless-only have

not been included in this report but are

available upon request.

The estimates developed for this

report are based on data from 2007

through 2010. The number of American

homes with only wireless telephones

continues to grow (1), and it is very

likely that the current prevalence rates

of wireless-only adults and children are

greater than the estimates presented

here. Researchers may find that the rates

of growth presented in Tables 1 and 2

for states and substate areas are useful

for predicting current or future

prevalence rates.

Finally, the state and substate

estimates presented here may differ

from estimates produced by other

sources. For example, Arbitron, Inc.,

released Fall 2009 estimates of the

prevalence of wireless-only households

in local radio markets (12). Their

estimates are based largely on survey

responses received from mailed

screening questionnaires, which may be

subject to various nonresponse biases.

The estimates presented here are less

likely to be biased by survey

nonresponse (due to the high NHIS

response rates), but are more likely to

be biased by the focus here on

demographic characteristics in the
Page 6	 National Health Statistics Reports n Number 39 n April 20, 2011

statistical model. Arbitron’s estimates

reveal higher wireless-only prevalence

estimates in areas with college campuses

or military bases; the statistical models

here did not include any community

characteristics. The NHIS sample also

does not include active-duty military

personnel. Survey nonresponse, sample

characteristics, and model selection

should all be considered when

evaluating or comparing small-area

estimates, including those presented

here.

References

1.	 Blumberg SJ, Luke JV. Wireless

substitution: Early release of

estimates based on data from the

National Health Interview Survey,

January–June 2010. National Center

for Health Statistics. December 2010.

Available from: http://www.cdc.gov/

nchs/nhis.htm.

2.	 Blumberg SJ, Luke JV. Coverage

bias in traditional telephone surveys

of low-income and young adults.

Public Opin Q 71(5):734–49. 2007.

3.	 Blumberg SJ, Luke JV, Cynamon

ML. Reevaluating the need for

concern regarding noncoverage bias

in landline surveys. Am J Public

Health 99(10):1806–10. 2009.

4.	 Blumberg SJ, Luke JV, Cynamon

ML, Frankel MR. Recent trends in

household telephone coverage in the

United States. In: Lepkowski JM,

Tucker C, Brick JM, et al., eds.

Advances in telephone survey

methodology: 56–86. Hoboken, NJ:

John Wiley & Sons. 2007.

5.	 AAPOR Cell Phone Task Force. New

considerations for survey researchers

when planning and conducting RDD

telephone surveys in the U.S. with

respondents reached via cell phone

numbers [online]. American

Association for Public Opinion

Research. 2010. Available from:

http://aapor.org/cell_phone_
 

task_force.htm.
 

6.	 Blumberg SJ, Luke JV, Davidson G,

et al. Wireless substitution: Statelevel estimates from the National

Health Interview Survey, January–

December 2007. National health

statistics reports; no 14. Hyattsville,

MD: National Center for Health

Statistics. 2009. Available from:

http://www.cdc.gov/nchs/data/nhsr/

nhsr014.pdf.

7.	 CDC. National Immunization Survey:

A user’s guide for the 2008 publicuse data file. 2009. Available from:

ftp://ftp.cdc.gov/pub/

Health_Statistics/NCHS/

Dataset_Documentation/NIS/

NISPUF08_DUG.pdf.

8.	 Jiang J, Lahiri P. Mixed model

prediction and small area estimation

(with discussion). Test 15(1):1–96.

2006.

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Hoboken, NJ: John Wiley & Sons.

2003.

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estimation by combining time-series

and cross-section data. Can J Stat

22(4):511–28. 1994.

11. Petitions of Qwest Corporation for

forbearance pursuant to 47 U.S.C.

§160(c) in the Denver, MinneapolisSt. Paul, Phoenix, and Seattle

metropolitan statistical areas. WC

Docket No. 07–97, Memorandum

Opinion and Order, FCC 08–174.

Federal Communications

Commission. July 25, 2008.

Available from: http://hraunfoss.

fcc.gov/edocs_public/attachmatch/

FCC-08-174A1.pdf.

12. Arbitron, Inc. Cell-phone-only

household penetration in Arbitron

radio metro areas. 2009. Available

from: http://www.arbitron.com/

downloads/cell_phone_penetration

_map.pdf.

13. Jiang J, Lahiri P, Wan S-M, Wu C-H.

Jackknifing in the Fay-Herriot model

with an example. In: Statistical

policy working paper 33:

Proceedings of the Seminar on

Funding Opportunity in Survey

Research; 98–104. Washington, DC:

Federal Committee on Statistical

Methodology, Office of Management

and Budget. 2001.

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Wald and likelihood ratio joint

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National Health Statistics Reports n Number 39 n April 20, 2011 Page 7

Table 1. Modeled estimates (with standard errors) of the percentage of adults aged 18 and over living in wireless-only households, by

selected geographic areas and time period: United States, January 2007–June 2010

Jan–Dec Jul 2007– Jan–Dec Jul 2008– Jan–Dec Jul 2009–

Geographic area 2007 Jun 2008 2008 Jun 2009 2009 Jun 2010

Percent (standard error)

Alabama................... 13.1 (1.3) 15.0 (1.3) 17.9 (1.5) 20.6 (1.6) 22.7 (1.6) 25.3 (1.6)

Jefferson County ............ 13.6 (2.1) 15.8 (2.2) 17.8 (2.3) 19.7 (2.5) 22.6 (2.5) 24.3 (2.4)

Rest of Alabama ............ 13.0 (1.4) 14.9 (1.5) 17.9 (1.7) 20.7 (1.8) 22.7 (1.8) 25.4 (1.8)

Alaska .................... 10.8 (2.4) 13.2 (2.5) 15.2 (2.6) 17.9 (2.8) 20.2 (3.0) 19.9 (2.9)

Arizona ................... 17.2 (1.3) 18.5 (1.4) 20.4 (1.4) 23.8 (1.5) 27.2 (1.5) 29.4 (1.5)

Maricopa County ............ 17.1 (1.6) 18.1 (1.7) 20.0 (1.7) 23.6 (1.9) 27.6 (1.9) 30.3 (1.9)

Rest of Arizona ............. 17.3 (2.2) 19.2 (2.3) 21.0 (2.4) 24.0 (2.6) 26.6 (2.5) 28.2 (2.5)

Arkansas .................. 20.7 (2.1) 23.0 (2.1) 25.5 (2.2) 30.7 (2.3) 33.5 (2.3) 35.2 (2.3)

California .................. 8.9 (0.5) 10.5 (0.5) 12.5 (0.6) 14.9 (0.6) 16.3 (0.6) 18.2 (0.6)

Alameda County ............ 9.6 (1.5) 11.5 (1.6) 13.6 (1.7) 14.5 (1.8) 15.3 (1.8) 17.4 (1.9)

Fresno County ............. 14.2 (1.9) 15.0 (1.9) 15.3 (1.9) 17.2 (1.9) 19.9 (2.0) 21.5 (2.2)

Los Angeles County .......... 7.1 (0.8) 8.6 (0.8) 10.6 (0.9) 14.1 (1.1) 16.1 (1.0) 17.0 (1.0)

Northern Counties1 ........... 8.0 (1.6) 9.5 (1.7) 10.3 (1.7) 12.6 (1.9) 16.0 (2.1) 18.1 (2.2)

San Bernardino County ........ 8.7 (1.5) 10.3 (1.6) 12.4 (1.7) 14.1 (1.8) 15.5 (1.8) 18.1 (1.8)

San Diego County ........... 7.3 (1.2) 8.7 (1.2) 10.5 (1.3) 13.1 (1.5) 16.2 (1.5) 18.4 (1.6)

Santa Clara County .......... 9.3 (1.4) 9.7 (1.4) 10.1 (1.5) 12.4 (1.7) 15.5 (1.8) 17.7 (1.8)

Rest of California ............ 10.1 (0.8) 11.7 (0.9) 14.1 (1.0) 16.3 (1.1) 16.5 (1.0) 18.8 (0.9)

Colorado .................. 20.4 (1.6) 23.1 (1.7) 25.7 (1.7) 27.5 (1.7) 29.0 (1.7) 30.4 (1.6)

City of Denver Counties2 ....... 26.1 (2.9) 28.6 (3.0) 30.4 (3.0) 31.2 (2.9) 31.6 (2.8) 33.6 (2.8)

Rest of Colorado ............ 16.8 (1.8) 19.6 (1.9) 22.7 (2.0) 25.1 (2.1) 27.4 (2.0) 28.4 (1.9)

Connecticut ................. 5.6 (1.0) 6.7 (1.1) 8.2 (1.2) 9.7 (1.3) 12.1 (1.4) 13.6 (1.4)

Delaware .................. 6.9 (1.7) 8.1 (1.8) 10.3 (2.1) 13.4 (2.4) 15.6 (2.5) 16.5 (2.5)

District of Columbia ............ 13.8 (2.8) 15.9 (2.9) 18.5 (3.1) 21.9 (3.2) 24.9 (3.2) 27.7 (3.4)

Florida . . . . . . . . . . . . . . . . . . . . 15.2 (0.9) 17.6 (0.9) 20.4 (1.0) 22.9 (1.1) 24.9 (1.0) 27.3 (1.0)

Dade County .............. 14.6 (1.5) 17.2 (1.6) 20.5 (1.7) 22.9 (1.8) 24.7 (1.8) 27.1 (1.7)

Duval County .............. 17.9 (2.5) 21.2 (2.6) 24.3 (2.7) 25.8 (2.8) 26.9 (2.7) 29.3 (2.6)

Orange County ............. 19.7 (2.4) 22.4 (2.5) 25.3 (2.7) 28.1 (2.8) 31.3 (2.7) 34.1 (2.7)

Rest of Florida ............. 14.8 (1.1) 17.1 (1.1) 19.7 (1.2) 22.4 (1.3) 24.3 (1.3) 26.7 (1.2)

Georgia ................... 14.7 (1.2) 16.6 (1.2) 19.4 (1.3) 21.6 (1.4) 23.4 (1.4) 26.5 (1.4)

Fulton/DeKalb Counties ........ 16.7 (2.1) 19.9 (2.3) 24.2 (2.5) 25.4 (2.5) 26.2 (2.5) 30.3 (2.5)

Rest of Georgia ............. 14.2 (1.4) 15.9 (1.4) 18.2 (1.5) 20.7 (1.6) 22.8 (1.6) 25.7 (1.6)

Hawaii .................... 9.3 (1.4) 10.5 (1.5) 12.6 (1.6) 15.6 (1.7) 19.7 (1.9) 21.8 (1.9)

Idaho..................... 19.6 (2.3) 21.2 (2.4) 23.5 (2.5) 27.4 (2.7) 30.5 (2.7) 31.7 (2.6)

Illinois .................... 14.8 (1.1) 16.0 (1.1) 18.1 (1.2) 20.5 (1.2) 22.3 (1.2) 24.4 (1.2)

Cook County............... 17.8 (1.5) 19.0 (1.6) 22.5 (1.7) 26.0 (1.8) 27.6 (1.7) 29.7 (1.7)

Madison/St. Clair Counties ...... 15.7 (2.5) 19.5 (2.7) 23.1 (3.0) 24.4 (3.0) 26.0 (3.0) 31.5 (3.1)

Rest of Illinois .............. 13.9 (1.4) 14.9 (1.4) 16.5 (1.5) 18.6 (1.5) 20.4 (1.5) 22.3 (1.5)

Indiana. . . . . . . . . . . . . . . . . . . . 14.1 (1.2) 15.1 (1.2) 17.2 (1.3) 21.1 (1.5) 24.1 (1.4) 25.2 (1.4)

Lake County ............... 8.3 (2.3) 11.7 (2.5) 14.6 (2.8) 15.5 (2.9) 16.6 (2.9) 18.7 (3.1)

Marion County.............. 21.1 (2.6) 22.6 (2.7) 24.9 (2.7) 28.9 (2.9) 32.8 (3.0) 33.5 (2.9)

Rest of Indiana ............. 13.5 (1.4) 14.1 (1.4) 16.2 (1.6) 20.3 (1.7) 23.3 (1.7) 24.4 (1.7)

Iowa . . . . . . . . . . . . . . . . . . . . . 19.7 (2.1) 22.0 (2.1) 24.2 (2.2) 25.7 (2.3) 27.7 (2.2) 29.2 (2.1)

Kansas ................... 17.2 (1.7) 20.0 (1.7) 22.1 (1.8) 24.1 (1.8) 26.7 (1.9) 28.7 (1.8)

Johnson/Wyandotte Counties .... 7.5 (1.7) 10.1 (1.9) 13.7 (2.2) 16.1 (2.4) 18.1 (2.5) 21.2 (2.6)

Rest of Kansas ............. 20.4 (2.1) 23.2 (2.2) 24.8 (2.2) 26.7 (2.3) 29.5 (2.3) 31.1 (2.2)

Kentucky .................. 21.7 (2.0) 24.0 (2.1) 26.6 (2.1) 28.4 (2.1) 30.2 (2.1) 31.5 (2.1)

Louisiana .................. 14.1 (1.5) 15.5 (1.6) 17.1 (1.7) 20.3 (1.9) 24.2 (1.8) 26.8 (1.8)

Maine .................... 14.2 (2.1) 15.9 (2.2) 18.0 (2.2) 20.5 (2.4) 22.5 (2.3) 22.9 (2.4)

Maryland .................. 9.8 (1.1) 10.7 (1.1) 11.6 (1.2) 14.4 (1.3) 16.6 (1.3) 18.4 (1.4)

Baltimore City . . . . . . . . . . . . . . 14.1 (2.4) 14.4 (2.4) 15.2 (2.5) 19.4 (2.7) 23.1 (2.8) 23.7 (2.8)

Rest of Maryland ............ 9.2 (1.2) 10.2 (1.3) 11.1 (1.3) 13.7 (1.4) 15.8 (1.4) 17.7 (1.5)

Massachusetts ............... 7.9 (0.9) 9.4 (1.0) 11.5 (1.1) 13.5 (1.2) 16.0 (1.2) 16.8 (1.2)

Suffolk County.............. 16.4 (2.5) 19.8 (2.8) 22.3 (3.0) 22.6 (2.9) 23.1 (2.8) 25.2 (2.8)

Rest of Massachusetts ........ 7.0 (1.0) 8.3 (1.1) 10.3 (1.2) 12.5 (1.3) 15.2 (1.3) 15.8 (1.3)

Michigan. . . . . . . . . . . . . . . . . . . 16.9 (1.2) 18.7 (1.3) 21.0 (1.3) 23.4 (1.4) 26.7 (1.3) 29.2 (1.3)

Wayne County.............. 19.1 (2.2) 22.1 (2.2) 25.2 (2.2) 28.1 (2.4) 30.6 (2.5) 34.9 (2.4)

Rest of Michigan ............ 16.7 (1.3) 18.4 (1.4) 20.7 (1.4) 23.1 (1.5) 26.3 (1.5) 28.6 (1.4)

Minnesota.................. 15.8 (1.3) 18.6 (1.3) 21.0 (1.4) 22.4 (1.4) 24.1 (1.4) 25.2 (1.4)

Twin Cities Counties3 ......... 17.1 (1.7) 20.3 (1.8) 23.0 (1.9) 24.2 (1.9) 25.4 (1.9) 26.1 (1.8)

Rest of Minnesota ........... 14.4 (1.8) 16.7 (1.9) 18.8 (2.0) 20.4 (2.1) 22.7 (2.1) 24.3 (2.1)

Mississippi ................. 21.0 (1.9) 25.0 (2.0) 28.2 (2.0) 30.3 (2.1) 33.2 (2.0) 35.1 (2.0)

See footnotes at end of table.
Page 8 National Health Statistics Reports n Number 39 n April 20, 2011

Table 1. Modeled estimates (with standard errors) of the percentage of adults aged 18 and over living in wireless-only households, by

selected geographic areas and time period: United States, January 2007–June 2010—Con.

Jan–Dec Jul 2007– Jan–Dec Jul 2008– Jan–Dec Jul 2009–

Geographic area 2007 Jun 2008 2008 Jun 2009 2009 Jun 2010

Percent (standard error)

Missouri ................... 10.1 (1.1) 12.5 (1.2) 15.0 (1.3) 17.6 (1.4) 21.0 (1.5) 22.4 (1.5)

St. Louis County/City ......... 13.9 (2.0) 17.2 (2.1) 19.5 (2.2) 22.9 (2.4) 26.7 (2.4) 26.9 (2.3)

Rest of Missouri............. 9.0 (1.3) 11.0 (1.4) 13.6 (1.6) 16.1 (1.7) 19.4 (1.7) 21.1 (1.8)

Montana................... 9.5 (2.0) 11.3 (2.1) 14.0 (2.3) 16.6 (2.5) 18.5 (2.5) 19.4 (2.6)

Nebraska .................. 19.0 (2.2) 21.1 (2.3) 23.5 (2.4) 27.9 (2.6) 29.9 (2.5) 30.4 (2.4)

Nevada ................... 11.6 (1.4) 12.6 (1.4) 14.3 (1.5) 18.1 (1.7) 22.3 (1.8) 24.2 (1.8)

Clark County............... 11.5 (1.6) 11.8 (1.6) 12.9 (1.7) 17.1 (2.0) 21.8 (2.1) 24.1 (2.1)

Rest of Nevada ............. 12.1 (2.3) 14.3 (2.6) 17.7 (2.8) 20.8 (3.0) 23.6 (3.1) 24.6 (3.2)

New Hampshire .............. 7.2 (1.5) 8.3 (1.6) 9.4 (1.7) 13.0 (1.9) 15.8 (2.0) 16.0 (2.0)

New Jersey ................. 5.6 (0.8) 6.6 (0.9) 8.0 (0.9) 9.7 (1.0) 11.4 (1.0) 12.8 (1.0)

Essex County .............. 7.1 (2.0) 12.0 (2.3) 18.4 (2.9) 21.2 (3.0) 23.9 (3.1) 26.5 (3.0)

Rest of New Jersey .......... 5.5 (0.8) 6.5 (0.9) 7.7 (0.9) 9.3 (1.1) 11.0 (1.1) 12.4 (1.1)

New Mexico ................ 17.2 (1.7) 18.4 (1.7) 20.2 (1.8) 23.5 (1.9) 26.3 (1.9) 27.2 (1.8)

Southern Counties4 .......... 19.4 (2.5) 20.3 (2.6) 21.2 (2.7) 25.5 (2.9) 28.3 (2.9) 29.3 (2.9)

Rest of New Mexico .......... 16.5 (2.1) 17.7 (2.1) 19.9 (2.2) 22.7 (2.3) 25.6 (2.3) 26.3 (2.2)

New York .................. 9.8 (0.8) 10.6 (0.8) 11.9 (0.8) 13.9 (0.9) 15.4 (0.9) 17.0 (0.9)

City of New York Counties5...... 9.5 (1.0) 10.5 (1.0) 13.0 (1.1) 15.2 (1.3) 16.9 (1.2) 19.1 (1.3)

Rest of New York ............ 9.9 (1.1) 10.7 (1.2) 11.1 (1.2) 12.9 (1.3) 14.4 (1.3) 15.4 (1.3)

North Carolina ............... 15.1 (1.2) 17.5 (1.3) 19.8 (1.3) 21.8 (1.4) 23.7 (1.3) 25.2 (1.3)

North Dakota ................ 19.2 (2.9) 20.6 (2.9) 22.7 (3.1) 27.5 (3.3) 31.8 (3.4) 32.3 (3.4)

Ohio ..................... 14.3 (1.0) 16.4 (1.1) 18.2 (1.1) 20.6 (1.2) 23.2 (1.1) 25.6 (1.1)

Cuyahoga County ........... 9.1 (1.5) 10.6 (1.6) 12.7 (1.7) 16.6 (1.9) 19.6 (2.0) 21.4 (2.0)

Franklin County ............. 18.7 (2.5) 20.5 (2.6) 22.5 (2.6) 25.4 (2.7) 28.2 (2.8) 30.6 (2.8)

Rest of Ohio ............... 14.5 (1.2) 16.7 (1.3) 18.5 (1.3) 20.6 (1.4) 23.0 (1.4) 25.6 (1.4)

Oklahoma .................. 21.3 (1.9) 23.5 (2.0) 23.9 (2.0) 25.6 (2.0) 28.6 (2.0) 30.1 (2.0)

Oregon ................... 18.5 (1.9) 19.6 (2.0) 21.5 (2.0) 24.2 (2.2) 27.6 (2.2) 30.6 (2.2)

Pennsylvania ................ 9.0 (0.8) 10.2 (0.9) 11.7 (0.9) 13.8 (1.0) 15.4 (1.0) 16.5 (1.0)

Allegheny County............ 16.6 (2.8) 18.2 (2.9) 19.8 (3.0) 22.3 (3.1) 23.6 (3.1) 25.0 (3.1)

Philadelphia County .......... 7.9 (1.7) 10.4 (1.9) 13.0 (2.1) 14.8 (2.2) 16.5 (2.2) 18.4 (2.2)

Rest of Pennsylvania ......... 8.2 (1.0) 9.1 (1.0) 10.5 (1.1) 12.6 (1.2) 14.2 (1.2) 15.1 (1.1)

Rhode Island ................ 5.3 (1.3) 5.8 (1.4) 6.3 (1.4) 9.4 (1.7) 11.9 (1.9) 12.8 (1.9)

South Carolina ............... 15.4 (1.6) 17.1 (1.6) 19.3 (1.7) 21.1 (1.8) 22.8 (1.7) 25.8 (1.7)

South Dakota................ 7.7 (1.7) 9.0 (1.9) 11.1 (2.1) 12.5 (2.1) 14.0 (2.3) 15.6 (2.4)

Tennessee ................. 18.6 (1.4) 20.5 (1.5) 22.1 (1.5) 24.4 (1.5) 25.6 (1.5) 27.9 (1.5)

Davidson County ............ 25.2 (3.4) 27.0 (3.4) 28.3 (3.4) 30.4 (3.5) 33.4 (3.4) 37.5 (3.5)

Shelby County.............. 24.0 (3.0) 25.8 (3.1) 27.5 (3.1) 30.2 (3.0) 32.4 (3.0) 32.9 (2.9)

Rest of Tennessee ........... 16.7 (1.7) 18.6 (1.7) 20.3 (1.8) 22.6 (1.9) 23.2 (1.8) 25.7 (1.8)

Texas .................... 19.9 (0.9) 22.6 (0.9) 24.5 (1.0) 27.2 (1.0) 30.0 (1.0) 32.5 (1.0)

Bexar County .............. 17.9 (2.0) 19.4 (2.1) 21.7 (2.2) 24.9 (2.3) 27.0 (2.3) 29.1 (2.2)

Dallas County .............. 27.0 (2.2) 30.3 (2.3) 33.1 (2.3) 36.5 (2.4) 40.7 (2.4) 43.2 (2.3)

El Paso County ............. 19.8 (2.4) 20.0 (2.4) 22.0 (2.6) 27.6 (2.9) 31.0 (2.8) 32.8 (2.7)

Harris County .............. 20.1 (1.5) 23.7 (1.6) 27.4 (1.7) 29.4 (1.8) 31.0 (1.7) 32.4 (1.6)

Rest of Texas .............. 19.1 (1.1) 21.9 (1.2) 23.3 (1.3) 25.8 (1.3) 28.6 (1.3) 31.3 (1.3)

Utah ..................... 16.8 (2.1) 17.7 (2.2) 18.5 (2.2) 20.0 (2.2) 21.6 (2.2) 24.4 (2.3)

Vermont ................... 8.2 (1.9) 10.5 (2.1) 13.8 (2.4) 17.0 (2.6) 20.4 (2.8) 20.3 (2.8)

Virginia ................... 11.7 (1.2) 14.1 (1.3) 16.7 (1.4) 19.7 (1.5) 20.6 (1.5) 21.2 (1.4)

Washington ................. 15.3 (1.1) 16.8 (1.2) 18.1 (1.2) 20.9 (1.3) 23.6 (1.3) 26.4 (1.3)

Eastern Counties6 ........... 20.1 (2.4) 21.1 (2.3) 22.5 (2.3) 24.1 (2.3) 25.3 (2.4) 28.6 (2.5)

King County ............... 21.5 (2.3) 23.3 (2.3) 24.6 (2.4) 27.4 (2.4) 29.7 (2.3) 31.8 (2.3)

Western Counties7 ........... 9.5 (1.8) 10.1 (1.8) 11.5 (1.9) 14.8 (2.1) 17.5 (2.2) 20.4 (2.3)

Rest of Washington .......... 12.4 (1.9) 14.2 (2.0) 15.4 (2.1) 18.4 (2.3) 21.7 (2.4) 25.0 (2.5)

West Virginia ................ 10.4 (1.8) 12.3 (1.9) 14.2 (2.0) 16.0 (2.2) 18.5 (2.3) 20.5 (2.3)

Wisconsin .................. 13.4 (1.4) 14.5 (1.4) 16.4 (1.5) 19.8 (1.6) 22.5 (1.6) 25.3 (1.6)

Milwaukee County ........... 16.2 (2.1) 18.4 (2.2) 20.2 (2.4) 23.4 (2.5) 27.3 (2.6) 30.7 (2.7)

Rest of Wisconsin ........... 12.9 (1.5) 13.8 (1.6) 15.7 (1.7) 19.1 (1.8) 21.6 (1.8) 24.2 (1.8)

Wyoming .................. 14.1 (2.1) 14.9 (2.2) 16.0 (2.4) 19.8 (2.5) 20.9 (2.6) 22.3 (2.6)

1Includes Del Norte, Siskiyou, Modoc, Lassen, Shasta, Trinity, Humboldt, Mendocino, Tehama, Plumas, Butte, Glenn, Colusa, Lake, and Sierra. 2Includes Denver, Adams, Arapahoe, and Douglas. 3Includes Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington. 4Includes Chaves, Lea, Eddy, Lincoln, Socorro, Catron, Sierra, Curry, Roosevelt, De Baca, Dona Ana, Otero, Luna, Grant, and Hidalgo. 5Includes Queens, Kings, Richmond, New York, and Bronx. 6Includes Asotin, Columbia, Garfield, Whitman, Adams, Walla Walla, Stevens, Ferry, Lincoln, Chelan, Douglas, Okanogan, Benton, Franklin, Grant, Kittitas, Klickitat, and Pend Oreille.

7Includes Kitsap, Whatcom, Thurston, Skagit, Island, Cowlitz, Mason, Clallam, Jefferson, Grays Harbor, Lewis, Pacific, San Juan, Skamania, and Wahkiahum.
National Health Statistics Reports n Number 39 n April 20, 2011 Page 9

Table 2. Modeled estimates (with standard errors) of the percentage of children under age 18 years living in wireless-only households,

by selected geographic areas and time period: United States, January 2007–June 2010

Jan–Dec Jul 2007– Jan–Dec Jul 2008– Jan–Dec Jul 2009–

Geographic area 2007 Jun 2008 2008 Jun 2009 2009 Jun 2010

Percent (standard error)

Alabama................... 13.5 (2.2) 18.3 (2.5) 22.6 (2.8) 22.4 (2.8) 24.7 (2.7) 30.9 (2.8)

Jefferson County ............ 18.1 (4.0) 23.4 (4.3) 24.6 (4.4) 24.6 (4.5) 29.5 (4.5) 33.1 (4.3)

Rest of Alabama ............ 12.7 (2.5) 17.5 (2.8) 22.2 (3.2) 22.1 (3.2) 23.9 (3.0) 30.5 (3.1)

Alaska .................... *7.2 (3.1) *11.5 (3.8) 13.4 (3.9) 14.3 (4.2) 19.1 (4.7) 21.0 (4.9)

Arizona ................... 19.5 (2.1) 20.2 (2.1) 21.2 (2.2) 25.1 (2.4) 30.7 (2.4) 34.8 (2.4)

Maricopa County ............ 18.4 (2.5) 18.4 (2.5) 20.0 (2.6) 24.8 (2.8) 31.3 (2.9) 35.5 (3.1)

Rest of Arizona ............. 21.4 (3.7) 23.4 (3.8) 23.2 (3.8) 25.6 (4.1) 29.8 (3.9) 33.6 (3.7)

Arkansas .................. 28.2 (3.9) 32.2 (3.9) 33.3 (3.7) 37.1 (3.8) 41.6 (3.7) 46.2 (3.8)

California .................. 7.7 (0.7) 10.1 (0.8) 12.5 (0.9) 14.8 (1.0) 16.5 (0.9) 19.7 (0.9)

Alameda County ............ *5.1 (1.8) 7.8 (2.2) 9.9 (2.4) 9.6 (2.5) 11.5 (2.6) 15.4 (2.8)

Fresno County ............. 13.5 (2.7) 13.5 (2.7) 14.1 (2.8) 19.0 (3.3) 24.4 (3.6) 27.8 (3.8)

Los Angeles County .......... 6.4 (1.1) 7.9 (1.2) 9.2 (1.3) 12.4 (1.6) 14.5 (1.5) 17.4 (1.5)

Northern Counties1 ........... *7.6 (2.3) 9.4 (2.5) 9.7 (2.5) 13.1 (2.7) 19.8 (3.3) 22.9 (3.5)

San Bernardino County ........ 9.4 (2.4) 11.2 (2.5) 13.6 (2.7) 14.9 (2.8) 18.1 (2.8) 22.5 (3.0)

San Diego County ........... 7.0 (1.9) 7.6 (2.0) 8.7 (2.1) 10.9 (2.3) 16.1 (2.5) 18.6 (2.5)

Santa Clara County .......... 7.6 (2.0) 10.0 (2.2) 9.1 (2.1) 10.6 (2.3) 14.8 (2.6) 17.5 (2.7)

Rest of California ............ 8.3 (1.2) 11.9 (1.5) 15.6 (1.6) 17.7 (1.8) 17.5 (1.6) 20.7 (1.5)

Colorado .................. 18.6 (2.5) 21.5 (2.7) 22.6 (2.7) 22.7 (2.7) 27.4 (2.6) 31.1 (2.6)

City of Denver Counties2 ....... 23.2 (4.7) 26.9 (4.9) 28.8 (5.0) 28.1 (5.0) 31.4 (4.8) 36.0 (4.7)

Rest of Colorado ............ 15.2 (2.7) 17.7 (2.8) 18.1 (2.8) 18.7 (2.8) 24.5 (2.8) 27.5 (2.8)

Connecticut ................. *3.7 (1.3) *4.3 (1.4) 6.3 (1.7) 7.5 (1.9) 10.1 (2.1) 12.6 (2.2)

Delaware .................. *6.6 (2.7) *8.8 (3.1) *10.9 (3.5) 13.3 (3.8) 16.8 (4.1) 20.1 (4.3)

District of Columbia ............ *10.5 (4.8) *12.6 (5.1) *15.8 (5.5) *19.3 (6.0) 25.0 (6.4) 30.3 (7.0)

Florida . . . . . . . . . . . . . . . . . . . . 16.2 (1.5) 19.3 (1.5) 22.3 (1.6) 25.1 (1.8) 30.5 (1.7) 34.2 (1.6)

Dade County .............. 16.1 (2.6) 19.1 (2.7) 24.1 (3.0) 25.3 (3.0) 28.9 (2.9) 35.2 (3.0)

Duval County .............. 19.3 (3.9) 21.9 (4.2) 23.4 (4.2) 25.2 (4.3) 27.4 (4.1) 32.0 (4.0)

Orange County ............. 18.4 (3.9) 22.8 (4.0) 27.0 (4.4) 27.6 (4.5) 33.8 (4.4) 39.5 (4.3)

Rest of Florida ............. 15.8 (1.8) 18.8 (1.9) 21.5 (2.0) 24.8 (2.3) 30.7 (2.2) 33.7 (2.1)

Georgia ................... 17.2 (2.1) 19.9 (2.2) 22.7 (2.2) 25.1 (2.4) 27.8 (2.3) 33.5 (2.3)

Fulton/DeKalb Counties ........ 15.7 (3.5) 19.6 (3.7) 22.1 (4.0) 20.0 (3.8) 22.4 (3.9) 29.8 (4.0)

Rest of Georgia ............. 17.5 (2.4) 20.0 (2.5) 22.8 (2.5) 26.1 (2.7) 28.8 (2.7) 34.2 (2.6)

Hawaii .................... *7.5 (2.3) 11.1 (2.6) 14.6 (3.0) 16.1 (3.3) 20.4 (3.5) 23.6 (3.4)

Idaho..................... 23.1 (3.9) 25.1 (4.0) 26.2 (4.1) 31.8 (4.5) 33.8 (4.1) 37.3 (3.9)

Illinois .................... 13.1 (1.8) 15.4 (1.9) 17.9 (1.9) 19.5 (2.1) 22.4 (2.0) 27.4 (2.1)

Cook County............... 13.5 (2.2) 16.9 (2.5) 21.6 (2.9) 22.1 (2.9) 23.9 (2.7) 29.0 (2.7)

Madison/St. Clair Counties ...... 12.8 (3.6) 19.4 (4.3) 22.9 (4.6) 22.7 (4.7) 28.7 (4.9) 38.0 (5.3)

Rest of Illinois .............. 13.0 (2.3) 14.7 (2.4) 16.6 (2.4) 18.5 (2.6) 21.6 (2.6) 26.3 (2.6)

Indiana. . . . . . . . . . . . . . . . . . . . 15.3 (2.0) 16.3 (2.1) 17.9 (2.2) 22.4 (2.5) 27.8 (2.5) 31.2 (2.4)

Lake County ............... 17.5 (4.8) 23.3 (5.1) 25.6 (5.3) 26.3 (5.6) 29.7 (5.4) 35.1 (5.7)

Marion County.............. 18.3 (3.9) 20.2 (4.1) 22.7 (4.3) 25.3 (4.4) 32.4 (4.8) 36.7 (4.7)

Rest of Indiana ............. 14.5 (2.5) 14.9 (2.5) 16.1 (2.6) 21.4 (3.0) 26.7 (3.0) 29.7 (2.9)

Iowa . . . . . . . . . . . . . . . . . . . . . 14.3 (3.0) 17.1 (3.0) 17.7 (3.1) 19.2 (3.3) 24.6 (3.3) 29.8 (3.2)

Kansas ................... 18.2 (2.7) 22.3 (2.9) 24.8 (3.0) 26.9 (3.1) 31.1 (3.1) 34.8 (2.9)

Johnson/Wyandotte Counties .... *5.4 (2.3) *8.8 (2.8) 12.8 (3.3) 14.6 (3.5) 17.4 (3.8) 23.0 (4.1)

Rest of Kansas ............. 22.7 (3.5) 27.0 (3.7) 29.1 (3.9) 31.3 (4.0) 35.9 (3.8) 39.0 (3.7)

Kentucky .................. 22.4 (3.1) 24.3 (3.2) 29.1 (3.4) 29.3 (3.3) 30.9 (3.2) 34.9 (3.2)

Louisiana .................. 17.1 (2.6) 19.0 (2.7) 22.4 (2.9) 26.7 (3.2) 31.1 (2.9) 34.4 (3.0)

Maine .................... *4.8 (2.0) 10.5 (2.9) 15.4 (3.6) 16.4 (3.8) 19.4 (3.7) 21.6 (3.8)

Maryland .................. 6.0 (1.4) 6.9 (1.5) 8.6 (1.7) 11.4 (2.0) 15.0 (2.1) 18.0 (2.2)

Baltimore City . . . . . . . . . . . . . . 11.7 (3.3) 13.6 (3.5) 15.3 (3.7) 18.0 (3.9) 22.3 (4.2) 27.4 (4.5)

Rest of Maryland ............ 5.3 (1.5) 6.0 (1.6) 7.8 (1.9) 10.6 (2.2) 14.1 (2.3) 16.8 (2.4)

Massachusetts ............... 5.3 (1.3) 6.7 (1.4) 8.5 (1.5) 9.8 (1.8) 12.7 (1.9) 15.1 (2.0)

Suffolk County.............. 15.1 (4.5) 20.1 (5.3) 21.3 (5.7) 22.0 (5.5) 25.5 (5.6) 28.1 (5.7)

Rest of Massachusetts ........ 4.4 (1.3) 5.5 (1.4) 7.3 (1.6) 8.7 (1.8) 11.6 (2.0) 14.1 (2.1)

Michigan. . . . . . . . . . . . . . . . . . . 15.3 (2.0) 18.0 (2.1) 22.0 (2.3) 25.4 (2.5) 30.6 (2.5) 35.6 (2.4)

Wayne County.............. 22.9 (4.1) 27.7 (3.9) 30.2 (4.0) 32.9 (4.3) 38.6 (4.5) 42.9 (4.2)

Rest of Michigan ............ 14.5 (2.2) 17.0 (2.3) 21.2 (2.5) 24.7 (2.7) 29.7 (2.7) 34.7 (2.6)

Minnesota.................. 8.7 (1.6) 13.1 (1.9) 16.1 (2.0) 17.8 (2.2) 20.8 (2.3) 23.5 (2.3)

Twin Cities Counties3 ......... 7.2 (2.0) 12.2 (2.4) 16.3 (2.7) 17.6 (2.8) 19.5 (2.9) 21.0 (2.9)

Rest of Minnesota ........... 10.5 (2.6) 14.2 (3.0) 15.8 (3.1) 17.9 (3.4) 22.4 (3.5) 26.5 (3.6)

Mississippi ................. 20.9 (3.3) 26.5 (3.4) 31.2 (3.6) 32.9 (3.7) 36.0 (3.4) 41.9 (3.3)

See footnotes at end of table.
Page 10 National Health Statistics Reports n Number 39 n April 20, 2011

Table 2. Modeled estimates (with standard errors) of the percentage of children under age 18 years living in wireless-only households,

by selected geographic areas and time period: United States, January 2007–June 2010—Con.

Jan–Dec Jul 2007– Jan–Dec Jul 2008– Jan–Dec Jul 2009–

Geographic area 2007 Jun 2008 2008 Jun 2009 2009 Jun 2010

Percent (standard error)

Missouri ................... 8.9 (1.9) 11.3 (2.0) 16.1 (2.4) 18.7 (2.6) 22.2 (2.6) 26.5 (2.7)

St. Louis County/City ......... *8.1 (2.5) 10.8 (2.8) 14.4 (3.2) 16.1 (3.3) 19.2 (3.3) 22.9 (3.5)

Rest of Missouri............. 9.1 (2.3) 11.5 (2.5) 16.6 (2.9) 19.5 (3.2) 23.1 (3.1) 27.5 (3.3)

Montana................... 13.4 (3.5) 18.3 (3.9) 23.9 (4.3) 26.1 (4.5) 30.7 (4.6) 35.1 (4.5)

Nebraska .................. 15.5 (3.4) 19.1 (3.6) 21.7 (3.7) 26.8 (4.1) 28.0 (3.8) 29.5 (3.7)

Nevada ................... 8.6 (1.9) 11.0 (2.1) 13.5 (2.3) 17.3 (2.7) 22.9 (2.9) 26.8 (3.0)

Clark County............... *6.5 (2.1) 8.1 (2.2) 10.1 (2.4) 14.0 (3.0) 20.3 (3.4) 24.9 (3.5)

Rest of Nevada ............. 14.2 (4.2) 18.6 (4.9) 23.1 (5.3) 26.5 (5.4) 29.9 (5.5) 32.2 (5.7)

New Hampshire .............. *4.4 (1.9) *7.0 (2.4) *7.3 (2.5) *7.7 (2.6) 11.3 (2.9) 15.0 (3.3)

New Jersey ................. 5.0 (1.2) 6.8 (1.4) 8.1 (1.5) 8.8 (1.6) 10.3 (1.5) 12.6 (1.6)

Essex County .............. *2.9 (1.9) *6.4 (2.5) 11.6 (3.4) 14.5 (3.7) 21.5 (4.4) 26.9 (4.7)

Rest of New Jersey .......... 5.1 (1.2) 6.9 (1.4) 8.0 (1.5) 8.6 (1.6) 9.9 (1.6) 12.1 (1.7)

New Mexico ................ 21.7 (3.0) 23.6 (3.0) 26.2 (3.1) 28.9 (3.2) 34.5 (3.1) 38.9 (3.0)

Southern Counties4 .......... 31.1 (5.1) 32.6 (5.2) 33.4 (5.3) 41.7 (5.8) 44.1 (5.6) 46.0 (5.6)

Rest of New Mexico .......... 18.0 (3.6) 20.1 (3.5) 23.2 (3.7) 23.6 (3.7) 30.6 (3.7) 36.0 (3.5)

New York .................. 6.5 (1.0) 7.2 (1.0) 8.5 (1.1) 9.9 (1.2) 12.5 (1.3) 16.6 (1.4)

City of New York Counties5...... 7.0 (1.4) 8.6 (1.5) 10.0 (1.7) 12.1 (1.9) 14.6 (1.9) 19.1 (2.1)

Rest of New York ............ 6.1 (1.4) 6.3 (1.4) 7.3 (1.5) 8.1 (1.6) 10.9 (1.7) 14.9 (1.9)

North Carolina ............... 16.0 (2.2) 19.7 (2.3) 22.9 (2.4) 24.5 (2.5) 26.7 (2.4) 31.4 (2.3)

North Dakota ................ 19.4 (4.7) 20.1 (4.6) 22.7 (4.9) 31.0 (5.8) 38.8 (5.9) 39.7 (5.9)

Ohio ..................... 12.8 (1.7) 16.0 (1.9) 17.2 (2.0) 18.7 (2.1) 24.3 (2.1) 28.8 (2.1)

Cuyahoga County ........... *8.0 (2.4) 12.1 (2.8) 13.3 (2.8) 15.1 (2.9) 22.3 (3.3) 28.3 (3.6)

Franklin County ............. 12.3 (2.9) 17.7 (3.3) 15.4 (3.0) 14.0 (3.0) 20.8 (3.5) 25.7 (3.7)

Rest of Ohio ............... 13.6 (2.2) 16.3 (2.3) 18.0 (2.5) 19.8 (2.6) 25.1 (2.6) 29.3 (2.6)

Oklahoma .................. 21.9 (3.3) 26.9 (3.5) 26.3 (3.4) 27.2 (3.5) 31.7 (3.4) 35.2 (3.5)

Oregon ................... 19.0 (3.1) 20.3 (3.2) 22.8 (3.4) 25.1 (3.5) 29.6 (3.5) 36.1 (3.6)

Pennsylvania ................ 8.4 (1.4) 10.3 (1.4) 10.4 (1.5) 12.4 (1.6) 15.5 (1.6) 18.2 (1.7)

Allegheny County............ *14.0 (4.4) 15.0 (4.2) 15.3 (4.2) 18.1 (4.6) 21.8 (4.8) 24.4 (5.1)

Philadelphia County .......... *7.0 (2.5) 11.5 (3.1) 13.4 (3.3) 13.8 (3.4) 17.8 (3.7) 23.1 (4.0)

Rest of Pennsylvania ......... 7.9 (1.6) 9.5 (1.7) 9.3 (1.7) 11.5 (1.9) 14.4 (1.9) 16.7 (1.9)

Rhode Island ................ *5.8 (2.1) *7.2 (2.4) *6.4 (2.2) 8.9 (2.6) 13.0 (2.9) 15.8 (3.1)

South Carolina ............... 18.6 (3.0) 20.6 (3.0) 21.5 (3.0) 23.4 (3.2) 28.1 (3.2) 33.6 (3.2)

South Dakota................ *6.9 (2.6) *8.8 (2.9) *9.6 (3.1) *10.5 (3.2) 15.1 (4.0) 20.5 (4.8)

Tennessee ................. 21.8 (2.4) 25.6 (2.5) 28.1 (2.6) 29.2 (2.6) 30.8 (2.4) 36.3 (2.5)

Davidson County ............ 23.0 (5.7) 25.6 (5.4) 27.0 (5.4) 28.4 (5.5) 35.2 (5.6) 38.9 (5.5)

Shelby County.............. 26.7 (5.1) 28.1 (5.1) 28.5 (5.0) 30.5 (4.7) 34.1 (4.6) 39.0 (4.9)

Rest of Tennessee ........... 20.5 (2.9) 25.0 (3.1) 28.2 (3.2) 29.0 (3.3) 29.5 (3.0) 35.4 (3.1)

Texas .................... 21.4 (1.3) 25.8 (1.5) 27.5 (1.5) 29.2 (1.6) 33.3 (1.5) 36.5 (1.5)

Bexar County .............. 23.3 (3.5) 22.2 (3.4) 27.0 (3.6) 35.6 (4.2) 38.4 (3.9) 37.8 (3.6)

Dallas County .............. 24.1 (3.3) 28.6 (3.6) 33.1 (3.5) 34.2 (3.5) 37.5 (3.4) 42.8 (3.2)

El Paso County ............. 24.2 (4.1) 26.0 (4.1) 26.7 (4.1) 32.9 (4.4) 35.7 (4.0) 36.7 (3.9)

Harris County .............. 22.0 (2.5) 26.1 (2.7) 31.5 (3.0) 33.3 (3.2) 34.3 (2.8) 38.0 (2.6)

Rest of Texas .............. 20.6 (1.7) 25.7 (1.9) 26.3 (2.0) 27.2 (2.1) 31.9 (1.9) 35.3 (1.9)

Utah ..................... 14.4 (2.8) 15.6 (2.9) 15.3 (2.8) 16.2 (2.8) 21.4 (3.1) 25.9 (3.4)

Vermont ................... *3.1 (2.0) *6.0 (2.9) *9.9 (3.8) *10.5 (3.6) 16.1 (4.3) 19.8 (4.8)

Virginia ................... 8.5 (1.7) 11.2 (1.8) 13.2 (2.0) 15.9 (2.2) 19.4 (2.2) 20.1 (2.1)

Washington ................. 11.4 (1.6) 12.9 (1.6) 14.0 (1.7) 17.1 (1.9) 22.3 (2.0) 27.0 (2.1)

Eastern Counties6 ........... 19.7 (3.5) 20.2 (3.4) 23.4 (3.5) 25.1 (3.3) 28.6 (3.5) 34.4 (4.0)

King County ............... 10.1 (2.8) 11.3 (2.8) 12.4 (2.9) 16.5 (3.3) 20.2 (3.3) 22.9 (3.3)

Western Counties7 ........... *9.5 (2.9) 10.1 (2.9) 11.1 (3.1) 14.1 (3.3) 19.1 (3.6) 24.4 (4.1)

Rest of Washington .......... 10.7 (2.7) 13.2 (2.9) 13.6 (2.9) 16.6 (3.3) 23.1 (3.7) 28.4 (3.8)

West Virginia ................ 11.2 (3.0) 14.3 (3.3) 16.5 (3.4) 18.6 (3.6) 22.2 (3.8) 26.6 (3.9)

Wisconsin .................. 13.2 (2.3) 13.9 (2.3) 16.0 (2.4) 19.0 (2.6) 22.8 (2.6) 28.6 (2.8)

Milwaukee County ........... 13.6 (3.3) 15.9 (3.6) 18.0 (3.8) 20.4 (3.9) 26.7 (4.2) 35.3 (4.6)

Rest of Wisconsin ........... 13.1 (2.7) 13.4 (2.7) 15.5 (2.7) 18.6 (3.0) 22.0 (3.1) 27.1 (3.2)

Wyoming .................. *9.9 (3.4) *11.6 (3.5) 13.4 (3.8) 16.8 (4.0) 20.2 (4.4) 23.2 (4.5)

* Estimate has a relative standard error greater than 30% and does not meet National Center for Health Statistics standards for reliability or precision.
 1Includes Del Norte, Siskiyou, Modoc, Lassen, Shasta, Trinity, Humboldt, Mendocino, Tehama, Plumas, Butte, Glenn, Colusa, Lake, and Sierra.
 2Includes Denver, Adams, Arapahoe, and Douglas.
 3Includes Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington.
 4Includes Chaves, Lea, Eddy, Lincoln, Socorro, Catron, Sierra, Curry, Roosevelt, De Baca, Dona Ana, Otero, Luna, Grant, and Hidalgo.
 5Includes Queens, Kings, Richmond, New York, and Bronx.
 6Includes Asotin, Columbia, Garfield, Whitman, Adams, Walla Walla, Stevens, Ferry, Lincoln, Chelan, Douglas, Okanogan, Benton, Franklin, Grant, Kittitas, Klickitat, and Pend Oreille.
 

7Includes Kitsap, Whatcom, Thurston, Skagit, Island, Cowlitz, Mason, Clallam, Jefferson, Grays Harbor, Lewis, Pacific, San Juan, Skamania, and Wahkiahum.
 
National Health Statistics Reports n Number 39 n April 20, 2011 Page 11

Table 3. Modeled estimates (with standard errors) of the percent distribution of household telephone status for adults aged 18 years and

over, by selected geographic areas: United States, July 2009–June 2010

No

Wireless- Landline- Landline­ telephone

Geographic area Wireless-only mostly Dual-use mostly only service1 Total

Percent (standard error)

Alabama................... 25.3 (1.6) 18.4 (1.4) 29.8 (2.0) 15.1 (1.6) 9.5 (1.3) 1.9 100.0

Jefferson County ............ 24.3 (2.4) 18.9 (2.2) 32.8 (3.2) 14.4 (2.3) 8.7 (1.9) 0.9 100.0

Rest of Alabama ............ 25.4 (1.8) 18.4 (1.6) 29.3 (2.3) 15.2 (1.8) 9.7 (1.4) 2.0 100.0

Alaska .................... 19.9 (2.9) 20.4 (2.8) 22.2 (3.7) 19.7 (3.3) 16.3 (3.3) 1.6 100.0

Arizona ................... 29.4 (1.5) 18.7 (1.3) 25.4 (1.8) 11.9 (1.3) 11.7 (1.3) 2.9 100.0

Maricopa County ............ 30.3 (1.9) 20.3 (1.7) 27.4 (2.3) 9.9 (1.5) 8.9 (1.4) 3.1 100.0

Rest of Arizona ............. 28.2 (2.5) 16.1 (1.9) 22.4 (2.7) 14.9 (2.3) 15.9 (2.4) 2.5 100.0

Arkansas .................. 35.2 (2.3) 15.7 (1.7) 20.0 (2.3) 11.4 (1.8) 15.7 (2.0) 2.1 100.0

California .................. 18.2 (0.6) 20.8 (0.6) 33.5 (0.7) 14.8 (0.6) 11.5 (0.5) 1.3 100.0

Alameda County ............ 17.4 (1.9) 22.5 (2.0) 34.3 (2.9) 16.3 (2.2) 8.8 (1.7) 0.7 100.0

Fresno County ............. 21.5 (2.2) 9.0 (1.5) 29.4 (3.0) 19.0 (2.5) 19.5 (2.5) 1.7 100.0

Los Angeles County .......... 17.0 (1.0) 20.0 (1.1) 38.1 (1.4) 10.4 (0.9) 12.8 (1.0) 1.6 100.0

Northern Counties2 ........... 18.1 (2.2) 14.9 (1.9) 21.8 (2.9) 23.7 (2.9) 20.3 (2.7) 1.3 100.0

San Bernardino County ........ 18.1 (1.8) 20.4 (1.9) 38.0 (2.8) 12.2 (1.8) 10.2 (1.7) 1.1 100.0

San Diego County ........... 18.4 (1.6) 18.8 (1.6) 34.3 (2.3) 16.9 (1.8) 10.7 (1.4) 0.9 100.0

Santa Clara County .......... 17.7 (1.8) 24.2 (2.0) 34.5 (2.8) 13.1 (1.9) 9.8 (1.7) 0.6 100.0

Rest of California ............ 18.8 (0.9) 22.1 (1.0) 30.9 (1.2) 16.5 (1.0) 10.4 (0.8) 1.2 100.0

Colorado .................. 30.4 (1.6) 15.7 (1.2) 29.7 (1.9) 15.0 (1.5) 7.5 (1.1) 1.7 100.0

City of Denver Counties3 ....... 33.6 (2.8) 16.0 (2.1) 27.1 (3.1) 14.7 (2.4) 7.3 (1.8) 1.3 100.0

Rest of Colorado ............ 28.4 (1.9) 15.4 (1.5) 31.3 (2.4) 15.1 (1.8) 7.7 (1.3) 2.0 100.0

Connecticut ................. 13.6 (1.4) 14.6 (1.4) 32.5 (2.3) 21.8 (2.0) 16.7 (1.8) 0.8 100.0

Delaware .................. 16.5 (2.5) 17.7 (2.5) 28.4 (3.8) 27.6 (3.6) 8.5 (2.3) 1.2 100.0

District of Columbia ............ 27.7 (3.4) 16.3 (2.8) 30.0 (4.0) 12.6 (2.8) 10.7 (2.7) 2.7 100.0

Florida .................... 27.3 (1.0) 16.5 (0.8) 29.5 (1.1) 12.5 (0.8) 12.2 (0.8) 1.8 100.0

Dade County .............. 27.1 (1.7) 19.7 (1.5) 32.0 (2.2) 7.4 (1.2) 11.9 (1.5) 1.9 100.0

Duval County .............. 29.3 (2.6) 15.9 (2.0) 26.8 (3.0) 13.2 (2.2) 12.4 (2.2) 2.3 100.0

Orange County ............. 34.1 (2.7) 17.5 (2.1) 28.9 (3.1) 8.9 (1.9) 8.6 (1.9) 2.0 100.0

Rest of Florida ............. 26.7 (1.2) 15.9 (1.0) 29.3 (1.4) 13.7 (1.1) 12.6 (1.0) 1.8 100.0

Georgia ................... 26.5 (1.4) 19.0 (1.2) 26.4 (1.6) 13.4 (1.2) 12.4 (1.2) 2.2 100.0

Fulton/DeKalb Counties ........ 30.3 (2.5) 21.2 (2.2) 26.4 (2.9) 12.0 (2.1) 8.0 (1.8) 2.1 100.0

Rest of Georgia ............. 25.7 (1.6) 18.4 (1.4) 26.4 (1.9) 13.7 (1.4) 13.4 (1.4) 2.3 100.0

Hawaii .................... 21.8 (1.9) 17.5 (1.8) 32.4 (2.7) 18.1 (2.2) 8.3 (1.5) 1.8 100.0

Idaho..................... 31.7 (2.6) 15.1 (1.9) 24.5 (2.9) 18.0 (2.5) 9.5 (1.9) 1.2 100.0

Illinois .................... 24.4 (1.2) 17.6 (1.0) 30.4 (1.5) 16.8 (1.2) 9.3 (0.9) 1.5 100.0

Cook County............... 29.7 (1.7) 18.6 (1.4) 29.1 (2.0) 13.6 (1.5) 7.0 (1.1) 2.0 100.0

Madison/St. Clair Counties ...... 31.5 (3.1) 14.8 (2.3) 28.3 (3.6) 12.9 (2.5) 10.8 (2.5) 1.7 100.0

Rest of Illinois .............. 22.3 (1.5) 17.4 (1.3) 30.9 (1.9) 18.0 (1.6) 10.0 (1.2) 1.4 100.0

Indiana. . . . . . . . . . . . . . . . . . . . 25.2 (1.4) 15.1 (1.1) 28.5 (1.8) 14.2 (1.3) 15.0 (1.4) 2.1 100.0

Lake County ............... 18.7 (3.1) 16.8 (2.8) 23.3 (4.1) 19.2 (3.7) 20.7 (4.1) 1.3 100.0

Marion County.............. 33.5 (2.9) 16.1 (2.1) 25.2 (3.2) 16.2 (2.7) 7.2 (1.9) 1.9 100.0

Rest of Indiana ............. 24.4 (1.7) 14.7 (1.4) 29.5 (2.1) 13.4 (1.6) 15.8 (1.7) 2.2 100.0

Iowa ..................... 29.2 (2.1) 16.5 (1.7) 29.1 (2.6) 16.9 (2.1) 7.0 (1.4) 1.3 100.0

Kansas ................... 28.7 (1.8) 12.8 (1.3) 31.4 (2.2) 17.9 (1.8) 7.8 (1.2) 1.4 100.0

Johnson/Wyandotte Counties .... 21.2 (2.6) 13.0 (2.0) 43.3 (3.9) 12.7 (2.5) 8.6 (2.1) 1.2 100.0

Rest of Kansas ............. 31.1 (2.2) 12.7 (1.6) 27.6 (2.6) 19.5 (2.3) 7.6 (1.5) 1.5 100.0

Kentucky .................. 31.5 (2.1) 13.8 (1.5) 19.0 (2.2) 20.7 (2.2) 12.8 (1.8) 2.2 100.0

Louisiana .................. 26.8 (1.8) 16.2 (1.5) 34.4 (2.4) 9.4 (1.4) 10.7 (1.5) 2.6 100.0

Maine .................... 22.9 (2.4) 11.4 (1.7) 19.7 (2.7) 31.9 (3.1) 13.2 (2.3) 0.9 100.0

Maryland .................. 18.4 (1.4) 21.2 (1.4) 29.6 (1.9) 20.4 (1.7) 9.2 (1.2) 1.2 100.0

Baltimore City .............. 23.7 (2.8) 19.8 (2.6) 30.3 (3.7) 13.5 (2.6) 9.7 (2.4) 3.0 100.0

Rest of Maryland ............ 17.7 (1.5) 21.4 (1.6) 29.5 (2.1) 21.3 (1.9) 9.2 (1.3) 0.9 100.0

Massachusetts ............... 16.8 (1.2) 14.7 (1.2) 34.7 (1.9) 21.6 (1.6) 11.2 (1.2) 1.0 100.0

Suffolk County.............. 25.2 (2.8) 9.3 (1.9) 30.3 (3.6) 15.5 (2.8) 18.1 (3.0) 1.7 100.0

Rest of Massachusetts ........ 15.8 (1.3) 15.3 (1.3) 35.2 (2.0) 22.3 (1.8) 10.4 (1.3) 0.9 100.0

Michigan. . . . . . . . . . . . . . . . . . . 29.2 (1.3) 15.3 (1.1) 24.7 (1.5) 19.9 (1.3) 9.1 (0.9) 1.8 100.0

Wayne County.............. 34.9 (2.4) 13.3 (1.7) 24.4 (2.6) 15.5 (2.1) 10.0 (1.8) 2.0 100.0

Rest of Michigan ............ 28.6 (1.4) 15.5 (1.1) 24.8 (1.6) 20.3 (1.5) 9.0 (1.0) 1.7 100.0

Minnesota.................. 25.2 (1.4) 16.1 (1.2) 32.5 (1.8) 16.4 (1.4) 8.7 (1.1) 1.0 100.0

Twin Cities Counties4 ......... 26.1 (1.8) 16.8 (1.5) 35.6 (2.4) 15.0 (1.8) 5.7 (1.1) 0.9 100.0

Rest of Minnesota ........... 24.3 (2.1) 15.3 (1.7) 28.9 (2.7) 18.2 (2.3) 12.1 (1.9) 1.2 100.0

Mississippi ................. 35.1 (2.0) 14.7 (1.4) 25.8 (2.1) 13.7 (1.7) 8.7 (1.3) 2.0 100.0

See footnotes at end of table.
Page 12 National Health Statistics Reports n Number 39 n April 20, 2011

Table 3. Modeled estimates (with standard errors) of the percent distribution of household telephone status for adults aged 18 years and

over, by selected geographic areas: United States, July 2009–June 2010—Con.

No

Wireless- Landline- Landline­ telephone

Geographic area Wireless-only mostly Dual-use mostly only service1 Total

Percent (standard error)

Missouri ................... 22.4 (1.5) 15.5 (1.3) 30.0 (2.0) 16.4 (1.6) 13.8 (1.5) 1.9 100.0

St. Louis County/City ......... 26.9 (2.3) 12.4 (1.7) 30.4 (2.9) 17.4 (2.4) 11.1 (2.0) 1.9 100.0

Rest of Missouri............. 21.1 (1.8) 16.5 (1.6) 29.9 (2.4) 16.1 (1.9) 14.6 (1.8) 1.8 100.0

Montana................... 19.4 (2.6) 13.7 (2.1) 16.9 (2.9) 10.6 (2.3) 37.0 (3.8) 2.3 100.0

Nebraska .................. 30.4 (2.4) 16.9 (1.9) 24.3 (2.7) 16.1 (2.2) 11.1 (1.9) 1.3 100.0

Nevada ................... 24.2 (1.8) 14.6 (1.4) 17.7 (1.9) 9.7 (1.4) 32.0 (2.2) 1.8 100.0

Clark County............... 24.1 (2.1) 10.4 (1.5) 15.3 (2.1) 8.2 (1.6) 40.2 (2.8) 1.8 100.0

Rest of Nevada ............. 24.6 (3.2) 25.1 (3.0) 23.7 (3.8) 13.5 (2.9) 11.3 (2.9) 1.8 100.0

New Hampshire .............. 16.0 (2.0) 13.4 (1.8) 31.0 (3.1) 27.8 (3.0) 10.6 (2.0) 1.3 100.0

New Jersey ................. 12.8 (1.0) 21.8 (1.3) 36.0 (1.8) 18.2 (1.4) 9.6 (1.0) 1.5 100.0

Essex County .............. 26.5 (3.0) 13.3 (2.3) 30.0 (3.7) *2.9 (1.4) 25.6 (3.6) 1.7 100.0

Rest of New Jersey .......... 12.4 (1.1) 22.1 (1.3) 36.2 (1.8) 18.7 (1.5) 9.1 (1.1) 1.5 100.0

New Mexico ................ 27.2 (1.8) 11.7 (1.3) 27.8 (2.2) 10.4 (1.5) 19.1 (1.9) 4.0 100.0

Southern Counties5 .......... 29.3 (2.9) 9.3 (1.8) 25.6 (3.5) 10.5 (2.4) 22.6 (3.3) 2.6 100.0

Rest of New Mexico .......... 26.3 (2.2) 12.5 (1.6) 28.6 (2.6) 10.3 (1.8) 17.7 (2.2) 4.5 100.0

New York .................. 17.0 (0.9) 13.5 (0.8) 32.7 (1.3) 17.9 (1.1) 16.8 (1.0) 2.0 100.0

City of New York Counties6...... 19.1 (1.3) 14.7 (1.1) 31.6 (1.7) 10.1 (1.1) 21.6 (1.5) 2.9 100.0

Rest of New York ............ 15.4 (1.3) 12.6 (1.1) 33.6 (1.9) 23.8 (1.7) 13.2 (1.4) 1.4 100.0

North Carolina ............... 25.2 (1.3) 16.1 (1.1) 24.6 (1.5) 19.9 (1.3) 12.4 (1.1) 1.8 100.0

North Dakota ................ 32.3 (3.4) 9.5 (2.0) 26.1 (3.8) 12.5 (2.7) 18.3 (3.4) 1.3 100.0

Ohio ..................... 25.6 (1.1) 17.2 (1.0) 25.7 (1.3) 20.2 (1.2) 9.1 (0.8) 2.1 100.0

Cuyahoga County ........... 21.4 (2.0) 18.7 (1.8) 23.8 (2.5) 20.2 (2.3) 14.6 (2.0) 1.3 100.0

Franklin County ............. 30.6 (2.8) 17.3 (2.2) 28.9 (3.4) 16.9 (2.7) *3.9 (1.4) 2.4 100.0

Rest of Ohio ............... 25.6 (1.4) 17.0 (1.2) 25.6 (1.6) 20.6 (1.4) 9.0 (1.0) 2.2 100.0

Oklahoma .................. 30.1 (2.0) 17.0 (1.6) 30.4 (2.5) 12.5 (1.7) 8.3 (1.4) 1.8 100.0

Oregon ................... 30.6 (2.2) 15.0 (1.7) 18.1 (2.3) 22.4 (2.4) 12.2 (1.9) 1.7 100.0

Pennsylvania ................ 16.5 (1.0) 16.5 (1.0) 32.0 (1.4) 23.4 (1.3) 10.4 (0.9) 1.3 100.0

Allegheny County............ 25.0 (3.1) 14.7 (2.5) 26.2 (3.9) 20.7 (3.4) 12.3 (2.9) 1.0 100.0

Philadelphia County .......... 18.4 (2.2) 27.1 (2.5) 25.5 (3.0) 16.3 (2.5) 9.2 (1.9) 3.5 100.0

Rest of Pennsylvania ......... 15.1 (1.1) 15.1 (1.1) 33.7 (1.7) 24.8 (1.5) 10.3 (1.1) 1.0 100.0

Rhode Island ................ 12.8 (1.9) 16.8 (2.0) 27.8 (3.1) 23.2 (2.8) 17.8 (2.6) 1.5 100.0

South Carolina ............... 25.8 (1.7) 18.5 (1.5) 26.5 (2.1) 15.9 (1.7) 11.0 (1.4) 2.3 100.0

South Dakota................ 15.6 (2.4) 9.3 (1.8) 14.3 (2.8) 8.6 (2.2) 50.8 (4.0) 1.3 100.0

Tennessee ................. 27.9 (1.5) 17.1 (1.2) 27.6 (1.8) 16.3 (1.5) 9.4 (1.2) 1.8 100.0

Davidson County ............ 37.5 (3.5) 15.4 (2.4) 22.6 (3.6) 15.8 (2.9) *7.4 (2.2) 1.3 100.0

Shelby County.............. 32.9 (2.9) 17.7 (2.3) 27.3 (3.4) 10.8 (2.3) 9.3 (2.2) 2.1 100.0

Rest of Tennessee ........... 25.7 (1.8) 17.2 (1.5) 28.3 (2.2) 17.3 (1.8) 9.7 (1.4) 1.8 100.0

Texas .................... 32.5 (1.0) 20.3 (0.8) 24.0 (1.0) 12.5 (0.8) 9.0 (0.6) 1.8 100.0

Bexar County .............. 29.1 (2.2) 17.7 (1.8) 32.9 (2.7) 7.1 (1.5) 11.5 (1.8) 1.6 100.0

Dallas County .............. 43.2 (2.3) 17.7 (1.7) 16.9 (2.1) 10.9 (1.7) 9.4 (1.6) 1.9 100.0

El Paso County ............. 32.8 (2.7) 14.8 (2.0) 17.5 (2.7) 8.1 (1.9) 23.3 (2.9) 3.4 100.0

Harris County .............. 32.4 (1.6) 22.1 (1.4) 19.5 (1.5) 14.4 (1.4) 9.6 (1.1) 1.9 100.0

Rest of Texas .............. 31.3 (1.3) 20.9 (1.1) 25.0 (1.3) 13.1 (1.0) 8.0 (0.8) 1.7 100.0

Utah ..................... 24.4 (2.3) 13.9 (1.8) 35.3 (3.2) 17.2 (2.5) 7.7 (1.7) 1.4 100.0

Vermont ................... 20.3 (2.8) 15.2 (2.4) 21.0 (3.5) 27.8 (3.8) 13.9 (3.0) 1.8 100.0

Virginia ................... 21.2 (1.4) 17.9 (1.3) 30.5 (1.9) 18.6 (1.6) 10.0 (1.2) 1.8 100.0

Washington ................. 26.4 (1.3) 17.2 (1.1) 26.7 (1.6) 18.7 (1.4) 9.6 (1.0) 1.4 100.0

Eastern Counties7 ........... 28.6 (2.5) 19.8 (2.2) 20.7 (2.8) 15.0 (2.4) 14.3 (2.4) 1.6 100.0

King County ............... 31.8 (2.3) 16.5 (1.8) 28.8 (2.7) 14.9 (2.1) 6.9 (1.5) 1.1 100.0

Western Counties8 ........... 20.4 (2.3) 15.9 (2.0) 27.2 (3.1) 22.4 (2.8) 13.1 (2.3) 1.0 100.0

Rest of Washington .......... 25.0 (2.5) 17.7 (2.1) 26.5 (3.1) 20.6 (2.8) 8.3 (1.9) 1.8 100.0

West Virginia ................ 20.5 (2.3) 13.4 (1.9) 22.7 (2.9) 20.4 (2.7) 20.3 (2.7) 2.7 100.0

Wisconsin .................. 25.3 (1.6) 10.4 (1.1) 25.1 (1.9) 20.8 (1.8) 17.2 (1.6) 1.3 100.0

Milwaukee County ........... 30.7 (2.7) 5.0 (1.2) 32.6 (3.4) 9.6 (2.0) 21.0 (2.9) 1.1 100.0

Rest of Wisconsin ........... 24.2 (1.8) 11.5 (1.3) 23.6 (2.2) 23.0 (2.1) 16.5 (1.8) 1.3 100.0

Wyoming ................. 22.3 (2.6) 13.1 (2.0) 22.0 (3.2) 5.9 (1.7) 35.5 (3.6) 1.2 100.0

* Estimate has a relative standard error greater than 30% and does not meet National Center for Health Statistics standards for reliability or precision. 1The proportion of adults living in households with no telephone service was not modeled. Other proportions were adjusted so that this estimate agreed with the 2009 American Community Survey
 

estimate for this proportion. 2Includes Del Norte, Siskiyou, Modoc, Lassen, Shasta, Trinity, Humboldt, Mendocino, Tehama, Plumas, Butte, Glenn, Colusa, Lake, and Sierra. 3Includes Denver, Adams, Arapahoe, and Douglas. 4Includes Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington. 5Includes Chaves, Lea, Eddy, Lincoln, Socorro, Catron, Sierra, Curry, Roosevelt, De Baca, Dona Ana, Otero, Luna, Grant, and Hidalgo. 6Includes Queens, Kings, Richmond, New York, and Bronx. 7Includes Asotin, Columbia, Garfield, Whitman, Adams, Walla Walla, Stevens, Ferry, Lincoln, Chelan, Douglas, Okanogan, Benton, Franklin, Grant, Kittitas, Klickitat, and Pend Oreille.
 8Includes Kitsap, Whatcom, Thurston, Skagit, Island, Cowlitz, Mason, Clallam, Jefferson, Grays Harbor, Lewis, Pacific, San Juan, Skamania, and Wahkiahum.
 
National Health Statistics Reports n Number 39 n April 20, 2011 Page 13

Table 4. Modeled estimates (with standard errors) of the percent distribution of household telephone status by selected geographic

areas, for children under age 18 years: United States, July 2009–June 2010

Wireless- Wireless- Landline- Landline- No teleGeographic area only mostly Dual-use mostly only phone service1 Total

Percent (standard error)

Alabama ................... 30.9 (2.8) 21.7 (2.4) 30.3 (3.0) 10.9 (2.1) *4.1 (1.4) 2.2 100.0

Jefferson County............. 33.1 (4.3) 24.6 (3.7) 34.2 (4.8) *4.0 (2.0) *3.3 (2.0) 0.8 100.0

Rest of Alabama............. 30.5 (3.1) 21.2 (2.6) 29.7 (3.4) 12.1 (2.5) *4.2 (1.6) 2.4 100.0

Alaska .................... 21.0 (4.9) 23.5 (4.6) 20.4 (5.5) 19.6 (5.4) *14.6 (5.4) 0.8 100.0

Arizona.................... 34.8 (2.4) 22.8 (2.0) 25.8 (2.4) 6.3 (1.3) 7.5 (1.5) 2.9 100.0

Maricopa County ............ 35.5 (3.1) 24.3 (2.7) 26.3 (3.1) *4.2 (1.4) 6.7 (1.9) 3.1 100.0

Rest of Arizona ............. 33.6 (3.7) 20.2 (2.9) 25.0 (3.6) 9.9 (2.5) 9.0 (2.6) 2.5 100.0

Arkansas .................. 46.2 (3.8) 21.8 (3.0) 16.8 (3.1) *6.3 (2.1) *6.1 (2.2) 2.7 100.0

California .................. 19.7 (0.9) 23.0 (0.9) 34.4 (1.1) 11.4 (0.8) 10.1 (0.7) 1.4 100.0

Alameda County............. 15.4 (2.8) 24.5 (3.2) 39.8 (4.2) 13.7 (3.0) *6.1 (2.2) 0.4 100.0

Fresno County .............. 27.8 (3.8) 13.4 (2.7) 22.0 (3.9) 15.7 (3.4) 19.4 (4.1) 1.7 100.0

Los Angeles County........... 17.4 (1.5) 21.0 (1.6) 38.3 (2.1) 9.4 (1.3) 12.1 (1.4) 1.8 100.0

Northern Counties2 ........... 22.9 (3.5) 17.5 (3.0) 24.2 (4.0) 17.8 (3.6) 16.4 (3.7) 1.3 100.0

San Bernardino County......... 22.5 (3.0) 23.0 (3.0) 33.5 (3.6) 11.7 (2.5) 7.9 (2.2) 1.4 100.0

San Diego County............ 18.6 (2.5) 18.5 (2.4) 37.4 (3.4) 15.2 (2.6) 9.5 (2.2) 0.8 100.0

Santa Clara County ........... 17.5 (2.7) 21.3 (2.8) 44.8 (3.8) 7.5 (2.0) 7.9 (2.2) 1.0 100.0

Rest of California ............ 20.7 (1.5) 25.9 (1.6) 31.5 (1.8) 11.4 (1.3) 9.1 (1.2) 1.5 100.0

Colorado................... 31.1 (2.6) 18.9 (2.0) 36.2 (2.9) 8.6 (1.6) *3.9 (1.2) 1.4 100.0

City of Denver Counties3 ........ 36.0 (4.7) 21.4 (3.6) 33.6 (5.1) *4.7 (2.3) *3.5 (2.2) 0.9 100.0

Rest of Colorado ............ 27.5 (2.8) 17.0 (2.3) 38.1 (3.3) 11.4 (2.2) *4.3 (1.5) 1.8 100.0

Connecticut ................. 12.6 (2.2) 18.1 (2.5) 38.0 (3.6) 19.5 (2.9) 11.2 (2.5) 0.5 100.0

Delaware .................. 20.1 (4.3) 23.3 (4.0) 33.7 (5.7) 15.7 (4.4) *5.7 (3.2) 1.4 100.0

District of Columbia ............ 30.3 (7.0) 22.8 (6.4) 35.2 (8.1) *6.5 (4.0) *3.0 (3.2) 2.1 100.0

Florida .................... 34.2 (1.6) 21.6 (1.4) 29.7 (1.7) 5.4 (0.9) 6.9 (1.0) 2.2 100.0

Dade County ............... 35.2 (3.0) 21.7 (2.5) 32.1 (3.2) *3.3 (1.2) *5.3 (1.6) 2.4 100.0

Duval County............... 32.0 (4.0) 19.5 (3.2) 27.9 (4.3) *6.5 (2.4) 12.2 (3.4) 1.8 100.0

Orange County.............. 39.5 (4.3) 21.2 (3.3) 30.4 (4.5) *4.5 (2.0) *2.9 (1.8) 1.6 100.0

Rest of Florida .............. 33.7 (2.1) 21.8 (1.8) 29.3 (2.1) 5.8 (1.1) 7.1 (1.2) 2.2 100.0

Georgia ................... 33.5 (2.3) 21.8 (1.9) 24.2 (2.2) 9.3 (1.6) 9.0 (1.6) 2.2 100.0

Fulton/DeKalb Counties ........ 29.8 (4.0) 24.5 (3.5) 33.7 (4.6) *3.2 (1.7) *6.5 (2.7) 2.3 100.0

Rest of Georgia ............. 34.2 (2.6) 21.2 (2.2) 22.3 (2.5) 10.5 (1.8) 9.5 (1.8) 2.2 100.0

Hawaii .................... 23.6 (3.4) 28.0 (3.6) 35.8 (4.3) *7.8 (2.4) *2.6 (1.6) 2.2 100.0

Idaho ..................... 37.3 (3.9) 19.7 (3.0) 27.0 (3.9) 12.0 (2.9) *2.9 (1.6) 1.2 100.0

Illinois .................... 27.4 (2.1) 21.0 (1.9) 32.8 (2.3) 12.0 (1.7) 5.3 (1.2) 1.5 100.0

Cook County ............... 29.0 (2.7) 19.0 (2.3) 33.5 (3.0) 9.1 (1.9) 6.9 (1.7) 2.5 100.0

Madison/St. Clair Counties ....... 38.0 (5.3) 16.1 (3.5) 34.4 (5.7) *8.1 (3.3) *1.9 (1.8) 1.4 100.0

Rest of Illinois .............. 26.3 (2.6) 21.9 (2.4) 32.5 (3.0) 13.1 (2.2) 5.0 (1.5) 1.2 100.0

Indiana.................... 31.2 (2.4) 17.9 (1.9) 30.4 (2.7) 8.9 (1.6) 8.9 (1.8) 2.7 100.0

Lake County ............... 35.1 (5.7) 21.3 (4.3) 25.1 (5.8) *12.3 (4.4) *5.3 (3.4) 0.8 100.0

Marion County .............. 36.7 (4.7) 18.2 (3.4) 26.0 (4.8) 14.8 (3.9) *3.5 (2.2) 0.7 100.0

Rest of Indiana.............. 29.7 (2.9) 17.4 (2.3) 31.7 (3.2) 7.5 (1.9) 10.3 (2.3) 3.3 100.0

Iowa ..................... 29.8 (3.2) 19.4 (2.7) 37.5 (3.7) 8.4 (2.2) *3.8 (1.6) 1.1 100.0

Kansas.................... 34.8 (2.9) 14.2 (2.0) 36.2 (3.2) 10.4 (2.1) *3.3 (1.3) 1.1 100.0

Johnson/Wyandotte Counties ..... 23.0 (4.1) 14.4 (3.2) 53.9 (5.9) *4.5 (2.3) *3.5 (2.3) 0.7 100.0

Rest of Kansas ............. 39.0 (3.7) 14.1 (2.5) 30.0 (3.8) 12.4 (2.7) *3.2 (1.6) 1.3 100.0

Kentucky................... 34.9 (3.2) 19.7 (2.5) 18.0 (2.8) 17.2 (2.8) 7.2 (2.0) 2.9 100.0

Louisiana .................. 34.4 (3.0) 19.7 (2.5) 32.6 (3.3) 5.7 (1.7) *4.7 (1.6) 2.9 100.0

Maine .................... 21.6 (3.8) 17.1 (3.2) 28.7 (4.7) 22.1 (4.4) *9.8 (3.4) 0.6 100.0

Maryland................... 18.0 (2.2) 25.2 (2.4) 35.8 (3.1) 16.6 (2.4) *3.3 (1.2) 1.1 100.0

Baltimore City .............. 27.4 (4.5) 21.7 (4.0) 31.4 (5.3) *9.2 (3.3) *7.4 (3.4) 3.0 100.0

Rest of Maryland ............ 16.8 (2.4) 25.6 (2.7) 36.3 (3.3) 17.5 (2.7) *2.9 (1.2) 0.9 100.0

Massachusetts ............... 15.1 (2.0) 18.2 (2.1) 43.7 (3.0) 14.9 (2.2) 7.4 (1.7) 0.7 100.0

Suffolk County .............. 28.1 (5.7) *12.5 (4.3) 35.7 (7.2) *10.6 (4.6) *12.6 (5.5) 0.5 100.0

Rest of Massachusetts ......... 14.1 (2.1) 18.7 (2.2) 44.3 (3.2) 15.3 (2.4) 7.0 (1.7) 0.7 100.0

Michigan ................... 35.6 (2.4) 19.2 (1.9) 25.2 (2.4) 13.2 (1.9) 5.2 (1.2) 1.7 100.0

Wayne County .............. 42.9 (4.2) 15.5 (2.9) 22.1 (3.9) *8.2 (2.5) *9.4 (3.0) 2.0 100.0

Rest of Michigan............. 34.7 (2.6) 19.6 (2.1) 25.5 (2.6) 13.8 (2.1) 4.7 (1.3) 1.7 100.0

Minnesota .................. 23.5 (2.3) 19.0 (2.0) 37.8 (2.9) 14.8 (2.1) *4.1 (1.3) 0.8 100.0

Twin Cities Counties4 .......... 21.0 (2.9) 17.1 (2.5) 40.1 (3.8) 16.9 (3.0) *4.4 (1.7) 0.5 100.0

Rest of Minnesota ............ 26.5 (3.6) 21.4 (3.1) 34.9 (4.3) 12.3 (3.0) *3.8 (1.9) 1.2 100.0

Mississippi. . . . . . . . . . . . . . . . . . 41.9 (3.3) 19.2 (2.5) 24.1 (3.1) 9.2 (2.1) *2.6 (1.2) 3.0 100.0

See footnotes at end of table.
Page 14 National Health Statistics Reports n Number 39 n April 20, 2011

Table 4. Modeled estimates (with standard errors) of the percent distribution of household telephone status by selected geographic

areas, for children under age 18 years: United States, July 2009–June 2010—Con.

Wireless- Wireless- Landline- Landline- No teleGeographic area only mostly Dual-use mostly only phone service1 Total

Percent (standard error)

Missouri ................... 26.5 (2.7) 18.8 (2.3) 29.9 (3.0) 13.1 (2.2) 9.3 (2.1) 2.3 100.0

St. Louis County/City .......... 22.9 (3.5) 17.3 (3.0) 36.0 (4.5) 16.5 (3.5) *4.8 (2.2) 2.4 100.0

Rest of Missouri ............. 27.5 (3.3) 19.3 (2.7) 28.2 (3.6) 12.2 (2.7) 10.6 (2.7) 2.3 100.0

Montana ................... 35.1 (4.5) 18.1 (3.3) 11.4 (3.3) *5.5 (2.4) 27.0 (5.2) 3.0 100.0

Nebraska .................. 29.5 (3.7) 17.1 (2.8) 35.8 (4.3) 8.7 (2.5) *7.8 (2.6) 1.1 100.0

Nevada ................... 26.8 (3.0) 17.6 (2.3) 17.6 (2.8) 6.8 (1.9) 29.3 (3.7) 1.9 100.0

Clark County ............... 24.9 (3.5) 13.8 (2.6) 14.3 (3.1) *7.4 (2.3) 38.0 (4.8) 1.7 100.0

Rest of Nevada ............. 32.2 (5.7) 28.1 (4.7) 26.7 (6.1) *5.2 (3.0) *5.5 (3.6) 2.4 100.0

New Hampshire .............. 15.0 (3.3) 15.3 (3.0) 41.1 (5.0) 24.7 (4.5) *2.3 (1.7) 1.5 100.0

New Jersey ................. 12.6 (1.6) 25.4 (2.1) 42.7 (2.6) 12.2 (1.8) 5.6 (1.2) 1.5 100.0

Essex County .............. 26.9 (4.7) 15.3 (3.7) 34.3 (5.5) *0.0 (0.1) 22.2 (5.4) 1.3 100.0

Rest of New Jersey ........... 12.1 (1.7) 25.8 (2.2) 43.0 (2.7) 12.7 (1.8) 5.0 (1.2) 1.5 100.0

New Mexico................. 38.9 (3.0) 18.6 (2.2) 24.2 (2.8) 5.5 (1.6) 8.9 (2.1) 4.0 100.0

Southern Counties5 ............ 46.0 (5.6) 20.3 (4.0) 15.6 (4.4) *3.6 (2.3) *11.3 (4.4) 3.2 100.0

Rest of New Mexico........... 36.0 (3.5) 17.8 (2.7) 27.7 (3.5) *6.3 (2.0) 7.9 (2.3) 4.4 100.0

New York .................. 16.6 (1.4) 15.4 (1.3) 40.9 (2.0) 14.4 (1.5) 10.7 (1.3) 1.9 100.0

City of New York Counties6 ...... 19.1 (2.1) 15.9 (1.9) 38.3 (2.8) 9.1 (1.7) 14.9 (2.1) 2.7 100.0

Rest of New York ............ 14.9 (1.9) 15.0 (1.8) 42.9 (2.8) 18.4 (2.2) 7.5 (1.6) 1.4 100.0

North Carolina ............... 31.4 (2.3) 21.2 (2.0) 26.6 (2.4) 12.0 (1.8) 6.8 (1.4) 2.0 100.0

North Dakota ................ 39.7 (5.9) 12.4 (3.5) 37.0 (6.7) *7.0 (3.4) *3.4 (2.8) 0.6 100.0

Ohio ..................... 28.8 (2.1) 19.3 (1.8) 28.5 (2.3) 15.5 (1.8) 5.2 (1.2) 2.7 100.0

Cuyahoga County ............ 28.3 (3.6) 22.2 (3.1) 21.4 (3.6) 22.2 (3.7) 5.3 (2.1) 0.6 100.0

Franklin County ............. 25.7 (3.7) 19.4 (3.1) 38.1 (4.6) 13.4 (3.3) *1.3 (1.2) 2.0 100.0

Rest of Ohio ............... 29.3 (2.6) 18.9 (2.1) 28.2 (2.7) 14.8 (2.2) 5.7 (1.5) 3.1 100.0

Oklahoma .................. 35.2 (3.5) 19.9 (2.8) 30.4 (3.7) *6.1 (1.9) *7.1 (2.3) 1.3 100.0

Oregon.................... 36.1 (3.6) 16.1 (2.6) 23.1 (3.4) 16.6 (3.1) *7.0 (2.2) 1.1 100.0

Pennsylvania ................ 18.2 (1.7) 21.5 (1.7) 36.4 (2.2) 16.5 (1.8) 5.7 (1.1) 1.7 100.0

Allegheny County ............ 24.4 (5.1) 22.5 (4.5) 34.0 (6.5) *16.7 (5.1) *1.4 (1.8) 1.0 100.0

Philadelphia County ........... 23.1 (4.0) 32.1 (4.1) 20.6 (4.2) 16.2 (3.9) *5.6 (2.6) 2.5 100.0

Rest of Pennsylvania .......... 16.7 (1.9) 19.6 (2.0) 39.4 (2.6) 16.6 (2.1) 6.2 (1.4) 1.6 100.0

Rhode Island ................ 15.8 (3.1) 20.1 (3.2) 30.6 (4.4) 18.3 (3.7) 13.9 (3.6) 1.3 100.0

South Carolina ............... 33.6 (3.2) 24.3 (2.8) 21.8 (3.0) 9.4 (2.2) 7.9 (2.1) 3.0 100.0

South Dakota ................ 20.5 (4.8) 14.2 (3.6) 20.8 (5.6) *4.5 (2.8) 39.1 (8.0) 0.9 100.0

Tennessee.................. 36.3 (2.5) 21.0 (2.0) 27.1 (2.5) 9.7 (1.7) *4.0 (1.2) 1.9 100.0

Davidson County ............ 38.9 (5.5) 25.4 (4.3) 29.8 (5.6) *3.4 (2.2) *1.6 (1.7) 0.9 100.0

Shelby County .............. 39.0 (4.9) 23.1 (3.9) 27.6 (5.0) *5.1 (2.5) *3.5 (2.3) 1.6 100.0

Rest of Tennessee ........... 35.4 (3.1) 20.0 (2.5) 26.6 (3.1) 11.6 (2.3) *4.4 (1.5) 2.1 100.0

Texas..................... 36.5 (1.5) 22.9 (1.3) 24.0 (1.4) 8.0 (0.9) 6.7 (0.8) 1.9 100.0

Bexar County .............. 37.8 (3.6) 21.2 (2.8) 30.8 (3.7) *3.9 (1.6) *5.1 (1.9) 1.1 100.0

Dallas County .............. 42.8 (3.2) 18.8 (2.5) 19.0 (2.8) 8.3 (2.0) 8.5 (2.1) 2.6 100.0

El Paso County ............. 36.7 (3.9) 16.4 (2.9) 18.2 (3.4) *5.4 (2.1) 18.8 (3.7) 4.4 100.0

Harris County .............. 38.0 (2.6) 22.8 (2.2) 17.7 (2.1) 8.8 (1.6) 10.6 (1.8) 2.2 100.0

Rest of Texas .............. 35.3 (1.9) 24.0 (1.7) 25.0 (1.8) 8.4 (1.2) 5.6 (1.0) 1.8 100.0

Utah ..................... 25.9 (3.4) 17.6 (2.8) 39.9 (4.3) 10.5 (2.7) *5.2 (2.1) 0.8 100.0

Vermont ................... 19.8 (4.8) 17.5 (4.0) 19.2 (5.2) 32.7 (6.4) *9.9 (4.3) 1.0 100.0

Virginia.................... 20.1 (2.1) 20.6 (2.0) 38.8 (2.7) 14.5 (2.0) 3.8 (1.1) 2.1 100.0

Washington ................. 27.0 (2.1) 20.6 (1.8) 30.8 (2.4) 12.7 (1.7) 7.7 (1.5) 1.3 100.0

Eastern Counties7 ............ 34.4 (4.0) 23.3 (3.3) 14.5 (3.2) 11.0 (2.9) 15.3 (3.6) 1.4 100.0

King County ............... 22.9 (3.3) 18.1 (2.8) 40.4 (4.2) 12.6 (2.8) *5.2 (2.0) 0.8 100.0

Western Counties8 ........... 24.4 (4.1) 21.8 (3.6) 28.0 (4.8) 17.2 (4.1) *7.3 (3.0) 1.3 100.0

Rest of Washington ........... 28.4 (3.8) 20.7 (3.2) 31.0 (4.4) 11.1 (3.0) *7.2 (2.7) 1.6 100.0

West Virginia ................ 26.6 (3.9) 17.4 (3.1) 26.9 (4.4) 15.5 (3.7) *10.8 (3.5) 2.7 100.0

Wisconsin .................. 28.6 (2.8) 15.4 (2.1) 31.7 (3.1) 15.1 (2.5) 8.0 (1.9) 1.3 100.0

Milwaukee County............ 35.3 (4.6) 9.4 (2.6) 31.6 (4.9) *10.1 (3.2) *12.2 (3.7) 1.3 100.0

Rest of Wisconsin ............ 27.1 (3.2) 16.7 (2.6) 31.7 (3.7) 16.2 (2.9) *7.0 (2.1) 1.3 100.0

Wyoming .................. 23.2 (4.5) 19.6 (3.8) 27.5 (5.4) *6.2 (2.9) 22.8 (5.7) 0.7 100.0

0.0 Quantity more than zero but less than 0.05.

* Estimate has a relative standard error greater than 30% and does not meet National Center for Health Statistics standards for reliability or precision. 1The proportion of children living in households with no telephone service was not modeled. Other proportions were adjusted so that this estimate agreed with the 2009 American Community
 

Survey estimate for this proportion. 2Includes Del Norte, Siskiyou, Modoc, Lassen, Shasta, Trinity, Humboldt, Mendocino, Tehama, Plumas, Butte, Glenn, Colusa, Lake, and Sierra. 3Includes Denver, Adams, Arapahoe, and Douglas. 4Includes Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington. 5Includes Chaves, Lea, Eddy, Lincoln, Socorro, Catron, Sierra, Curry, Roosevelt, De Baca, Dona Ana, Otero, Luna, Grant, and Hidalgo. 6Includes Queens, Kings, Richmond, New York, and Bronx. 7Includes Asotin, Columbia, Garfield, Whitman, Adams, Walla Walla, Stevens, Ferry, Lincoln, Chelan, Douglas, Okanogan, Benton, Franklin, Grant, Kittitas, Klickitat, and Pend Oreille. 8Includes Kitsap, Whatcom, Thurston, Skagit, Island, Cowlitz, Mason, Clallam, Jefferson, Grays Harbor, Lewis, Pacific, San Juan, Skamania, and Wahkiahum.
 
National Health Statistics Reports n Number 39 n April 20, 2011 Page 15

Technical Notes

Survey data sources

The estimates presented in this

report are based on National Health

Interview Survey (NHIS) data collected

from January 2007 through June 2010

and on American Community Survey

(ACS) data collected from 2006 through

2009. NHIS is a multipurpose health

survey conducted by the Centers for

Disease Control and Prevention’s (CDC)

National Center for Health Statistics

(NCHS). ACS is a multipurpose survey

conducted by the U.S. Census Bureau to

produce estimates of demographic,

social, economic, and housing

characteristics.

NHIS is an annual multistage

probability household survey of a large

sample of households drawn from the

civilian noninstitutionalized household

population of the United States. This

face-to-face survey interview is

administered by trained field

representatives from the U.S. Census

Bureau. NHIS interviews are conducted

continuously throughout the year to

collect information on health status,

health-related behaviors, and health care

utilization. The survey also includes

information about household telephones

and whether anyone in the household

has a wireless telephone.

The sample for NHIS is stratified

by state, which allows use of NHIS data

in statistical models that produce

state-level estimates. However, for most

states, the limited number of sampling

strata and small sample sizes preclude

reliable direct state-level estimates.

Household telephone status information

was obtained for 75,408 persons in

2007, for 74,014 persons in 2008, for

88,374 persons in 2009, and for 46,014

persons in January–June 2010. Fewer

than 0.5% of persons with completed

NHIS family-level interviews had

missing data for household telephone

status.

NHIS was used to derive the direct

estimates for each telephone service use

category by age group (adult or child),

small area, and 6-month period. These

estimates were the dependent variables

in each statistical model. Also, NHIS

was the source for the national estimates

used for raking the model-based

estimates for each telephone service use

category by age group and year.

ACS is a multistage probability

survey that provides data on households

and group quarters. Here we use a

subset of the full ACS sample—

the civilian noninstitutionalized

population—to represent a population

similar to that sampled for NHIS.

Data are collected continuously

through a combination of mailed,

telephone, and face-to-face interviews.

ACS is both nationally and state-level

representative and has included

approximately 2 million housing units

per year since 2006.

ACS data are released for calendar

years rather than for 6-month periods.

Moreover, 2010 ACS data will not be

released until Fall 2011. Therefore, ACS

data for 2006 were used in models for

both 6-month periods of 2007 (i.e.,

January–June 2007 and July–December

2007). Similarly, ACS data for 2007

were used in models for both 6-month

periods of 2008; ACS data for 2008

were used in models for both 6-month

periods of 2009; and ACS data for 2009

were used in models for the 6-month

period January–June 2010. Moreover,

the 2008 and 2009 ACS were the

sources for the proportion of adults or

children living in households with any

telephone service (landline or wireless).

These ACS estimates were used as

benchmarking totals when raking the

model-based estimates.

NHIS and ACS sampling weights

adjust for the probability of selection of

each household, and they are adjusted

for nonresponse. The results in this

report are based on weighted estimates.

R software (http://www.r-project.org)

was used to derive the model-based

estimates and standard errors. Design

effects were included in the models to

account for the complex survey

designs.

Auxiliary data sources

The two-sample estimation model

used in our previous report (6)

incorporated auxiliary data on the

number of wireless telephone

subscriptions per state. These data

were obtained from the Federal

Communications Commission’s

Automated Reporting Management

Information System database. The major

wireless telecommunications companies

are no longer required to update this

database with data for every state, and

relevant data from 2006 and 2007 did

not prove to be a significant covariate in

any of the models.

Instead, the numbers of listed

telephone lines for 2007–2010 were

obtained from a consumer database

compiled by infoUSA.com, Inc. This

database is updated bimonthly with

information from 37 sources, including

postal delivery sequence files, National

Change of Address lists, utility company

records, and more than 4,000 White

Pages directories. These data were

available for each calendar year rather

than each 6-month period. Therefore,

annual data on listed telephone lines

were used in models for both 6-month

periods of that calendar year. We

divided the count of listed telephone

lines by the number of civilian

noninstitutionalized persons.

Definitions

For each family contacted by NHIS,

one adult family member is asked

whether ‘‘you or anyone in your family

has a working cellular telephone.’’ A

family can be an individual or a group

of two or more related persons living

together in the same housing unit (a

‘‘household’’). Thus, a family can

consist of only one person, and more

than one family can live in a household

(including, for example, a household

where there are multiple single-person

families, as when unrelated roommates

are living together).

To produce the statistics for this

report, families are identified as

‘‘wireless families’’ if anyone in the

family had a working cellular telephone

at the time of interview. This person (or

persons) could be a civilian adult, a

member of the military, or a child.

Households are identified as ‘‘wirelessonly’’ if they include at least one

wireless family and if there are no

working landline telephones inside the
Page 16 National Health Statistics Reports n Number 39 n April 20, 2011

household. To determine whether there

was a working landline telephone inside

the household, survey respondents were

asked if there was ‘‘at least one phone

inside your home that is currently

working and is not a cell phone.’’

Household telephone status (rather

than family telephone status) is used

because most telephone surveys draw

samples of households rather than

families. Adults and children are

identified as wireless-only if they live in

a wireless-only household. Individual

ownership or use of wireless telephones

is not determined. A similar approach is

used to identify adults and children

living in landline-only households and

in households with both landline and

wireless telephones.

NHIS includes an additional

question for persons living in families

with both landline and wireless

telephones. The respondent for the

family is asked to consider all of the

telephone calls his or her family

receives and to report whether ‘‘all or

almost all calls are received on cell

phones, some are received on cell

phones and some on regular phones, or

very few or none are received on cell

phones.’’ This question permits the

identification of persons living in

‘‘wireless-mostly’’ households (defined

as households with both landline and

cellular telephones in which all families

receive all or almost all calls on cell

phones) and ‘‘landline-mostly’’

households (defined as households with

both landline and cellular telephones in

which all families receive all or almost

all calls on landline telephones).

‘‘Dual-use’’ households are those with

both landline and cellular telephones

that are neither wireless-mostly or

landline-mostly. That is, they receive

some calls on cell phones and some on

landline telephones.

Small-area model

This section describes in detail the

small-area model and the derivation of

the model-based estimates and standard

errors for the proportion of adults living

in households that were wireless-only

(WO), wireless-mostly (WM), dual-use

(DU), landline-mostly (LM), and

landline-only (LO). Derivation of the

estimates and standard errors for the

proportion of children living in

households that are WO, WM, DU, LM,

and LO is similar to the derivation

given below and is not repeated here.

NHIS was used to obtain direct

estimates of adults living in households

that were WO, WM, DU, LO, and LM

for the following 6-month periods:

January–June 2007, July–December

2007, January–June 2008, July–

December 2008, January–June 2009,

July–December 2009, and January–June

2010. Direct estimates were derived for

93 small areas that form a mutually

exclusive and exhaustive partition of the

United States. Twenty-six of these small

areas were states; others were selected

counties, groups of counties, or the

balance of the state population

excluding the selected counties. No

areas crossed state lines, and every

location in the United States was part of

one (and only one) of the 93 areas. See

Tables I and II for a list of the small

areas and the direct estimates of adults

living in households that were WO

or LO.

Typically when modeling

proportions, the direct estimates are

transformed using an arcsine

transformation (9,13). The arcsine

transformation preserves the bounds of 0

and 1 for proportions. In equation form,

the transformed direct estimate for WO

is

WO WO = 2sin–1 y ' , it zit

where zWO

it is the direct estimate for the

proportion of adults living in households

that are WO, i denotes the small areas

(i = 1,...,93), and t denotes the 6-month

periods (t = 1,...,7).

The small-area model is a crosssectional and time-series model (9,10).

The transformed direct estimate for

small area i and 6-month period t is

given by

WO

yit = μ + x'

it + + u + e (1) t i it it ,

where μt is the intercept term for

6-month period t; xit is a vector of

covariates for small area i and 6-month

period t; and β is a vector that has the

same number of entries as the number

of covariates in the vector xit. The vi

values are random effects that capture

the small-area-specific effect not

captured by the regression component

(μt + xit' β); uit is a small-area-by-time

random effect; and eit is the sampling

error associated with the transformed

direct estimate. Standard distributional

assumptions of normality with mean

zero and unknown variance were

assumed for the small-area-specific

random effects, and the small-area-bytime effects were assumed to follow a

first-order autoregressive model. The

regression parameters (coefficients β)

are assumed to be time-invariant, and it

is only the intercept term and the

random effects that capture the variation

in the small-area parameters over time.

The sampling errors were assumed to be

normally distributed with mean zero and

with sampling variance estimated using

a Taylor series method.

The set of possible covariates were

the demographic estimates from ACS

and the number of listed telephone lines

per capita. The demographic estimates

were calculated from ACS for each of

the 93 small areas. The dependent

variables were calculated at the person

level for each small area (e.g.,

proportion of adults in WO households),

and demographic estimates were

calculated at the person level for each

small area (e.g., proportion of persons

living in one-person households). Area

definitions from ACS and NHIS

matched precisely for all but five areas:

Suffolk County (Boston, Massachusetts),

Essex County (Newark, New Jersey),

Wayne County (Detroit, Michigan),

Cook County (Chicago, Illinois), and

Harris County (Houston, Texas). Minor

differences in these definitions were not

expected to bias the model-based

estimates. All the covariates were

standardized (by subtracting the mean

and then dividing by the standard

deviation) prior to fitting the models.

Among the set of possible

covariates, the best set of covariates was

selected using an Akaike information

criterion (AIC). In particular, AIC was

used to select the best set of covariates

for a person-level (i.e., total population)

model, and then these selected

covariates were used for the adult and
National Health Statistics Reports n Number 39 n April 20, 2011 Page 17

Table I. Direct estimates (with standard errors) of the percentage of adults aged 18 years and over living in wireless-only households, by

selected geographic areas and time period: United States, January 2007–June 2010

Jan–Jun Jul–Dec Jan–Jun Jul–Dec Jan–Jun Jul–Dec Jan–Jun

Geographic area 2007 2007 2008 2008 2009 2009 2010

Percent (standard error)

Alabama

Jefferson County ............ 7.2 (3.7) 23.7 (4.7) 12.5 (4.2) 15.3 (6.8) 9.6 (1.9) 33.7 (3.0) 21.6 (6.9)

Rest of Alabama ............ 10.9 (5.1) 12.8 (3.8) 13.0 (3.4) 23.3 (2.9) 18.7 (5.4) 25.1 (4.0) 27.0 (7.0)

Alaska .................... 2.3 (3.2) 21.2 (5.2) 14.8 (10.3) 12.3 (6.5) 14.5 (14.7) 15.7 (2.8) 16.8 (10.6)

Arizona

Maricopa County ............ 15.6 (3.7) 16.2 (3.2) 16.1 (3.8) 23.1 (5.9) 22.7 (4.9) 37.6 (7.9) 30.6 (1.7)

Rest of Arizona ............. 17.9 (3.9) 22.1 (3.3) 22.3 (8.8) 22.3 (2.8) 33.0 (9.4) 25.1 (4.6) 24.0 (11.7)

Arkansas .................. 17.1 (4.6) 25.1 (6.5) 18.6 (4.4) 26.8 (7.8) 44.4 (1.9) 28.4 (3.5) 38.6 (5.5)

California

Alameda County ............ 8.8 (3.4) 6.2 (1.4) 17.1 (3.7) 11.9 (7.9) 13.7 (4.2) 12.3 (2.1) 20.4 (3.7)

Fresno County ............. 17.2 (5.7) 19.7 (2.3) 20.4 (7.7) 14.7 (2.6) 13.9 (2.7) 14.7 (4.0) 13.8 (1.0)

Los Angeles County .......... 4.5 (0.9) 8.1 (1.1) 7.8 (1.6) 13.0 (2.7) 16.9 (1.6) 17.1 (1.4) 17.6 (0.9)

Northern Counties1 ........... 4.0 (2.0) 2.6 (2.8) 14.5 (3.3) 0.8 (0.6) 16.7 (2.9) 14.8 (8.6) 25.9 (9.3)

San Bernardino County ........ 4.7 (2.2) 4.4 (2.0) 19.2 (10.1) 22.6 (2.4) 11.8 (4.0) 15.6 (3.5) 15.5 (1.3)

San Diego County ........... 5.5 (2.5) 6.6 (2.3) 7.3 (2.5) 11.4 (1.9) 11.6 (4.3) 21.3 (5.6) 17.8 (3.0)

Santa Clara County .......... 7.5 (2.2) 7.2 (3.8) 9.8 (3.5) 5.7 (2.7) 13.2 (3.1) 19.9 (4.5) 20.5 (3.7)

Rest of California ............ 8.3 (1.2) 10.9 (1.1) 11.9 (1.3) 17.3 (2.3) 16.1 (2.0) 15.6 (1.3) 22.4 (1.5)

Colorado

City of Denver Counties2 ....... 27.9 (8.0) 40.2 (3.9) 36.8 (8.2) 24.1 (10.0) 38.9 (3.7) 22.8 (3.1) 40.9 (6.8)

Rest of Colorado ............ 12.4 (0.7) 17.9 (5.3) 20.0 (1.7) 27.5 (9.5) 24.7 (1.5) 32.8 (4.4) 24.9 (2.5)

Connecticut ................. 7.8 (2.9) 2.7 (1.3) 11.4 (5.1) 5.5 (2.2) 10.3 (3.4) 12.8 (2.8) 15.1 (2.8)

Delaware .................. 2.3 (2.2) 7.3 (3.0) 0.6 (0.7) 26.6 (21.5) 10.0 (0.1) 18.0 (9.1) 12.5 (3.3)

District of Columbia ............ 30.4 (3.6) 17.9 (9.9) 11.5 (5.6) – 13.8 (5.3) 13.0 (3.4) 36.0 (7.5)

Florida

Dade County .............. 13.7 (2.8) 8.7 (1.2) 26.0 (5.6) 21.8 (5.4) 30.4 (3.0) 22.3 (0.5) 32.0 (6.0)

Duval County .............. 13.7 (2.9) 42.6 (16.8) 18.3 (6.5) 21.1 (1.4) 29.9 (1.5) 33.9 (8.6) 22.3 (1.6)

Orange County ............. 19.9 (8.9) 19.2 (4.5) 27.9 (5.4) 25.9 (10.6) 25.0 (5.2) 39.1 (6.0) 31.8 (0.9)

Rest of Florida ............. 12.6 (2.2) 16.9 (2.2) 17.6 (2.3) 23.0 (2.5) 21.9 (4.0) 25.8 (2.0) 27.9 (3.3)

Georgia

Fulton/DeKalb Counties ........ 16.8 (2.4) 8.8 (1.6) 24.8 (2.5) 27.6 (6.7) 18.4 (6.4) 23.3 (1.4) 41.7 (3.3)

Rest of Georgia ............. 10.8 (2.5) 17.7 (2.8) 13.1 (2.1) 23.4 (3.4) 16.8 (2.9) 26.0 (2.3) 26.3 (2.7)

Hawaii .................... 12.6 (8.2) 4.6 (4.7) 10.8 (2.5) 9.0 (0.6) 19.4 (5.5) 29.2 (4.6) 25.9 (4.3)

Idaho..................... 26.4 (4.2) 15.4 (7.5) 22.9 (5.9) 15.9 (7.2) 48.1 (4.5) 27.3 (8.6) 34.6 (5.9)

Illinois

Cook County............... 14.8 (3.2) 15.6 (1.6) 16.5 (2.5) 33.7 (7.6) 27.4 (6.0) 30.0 (4.2) 28.2 (3.0)

Madison/St. Clair Counties ...... 6.6 (8.6) 19.1 (0.9) 28.8 (10.0) 30.9 (7.0) 1.5 (2.0) 27.5 (0.8) 45.0 (6.9)

Rest of Illinois .............. 14.2 (3.1) 17.4 (3.7) 13.8 (3.0) 21.0 (3.5) 15.2 (4.0) 21.8 (2.1) 20.9 (2.5)

Indiana

Lake County ............... 2.7 (2.6) 26.2 (3.8) 18.2 (11.9) – – 9.7 (3.3) 25.4 (10.8)

Marion County.............. 20.6 (3.7) 18.1 (8.9) 18.2 (1.9) 26.9 (13.2) 30.1 (9.9) 44.8 (5.3) 23.2 (5.0)

Rest of Indiana ............. 14.5 (1.9) 10.5 (4.5) 11.2 (3.3) 14.9 (2.0) 26.6 (6.6) 23.7 (2.6) 26.8 (4.4)

Iowa ..................... 24.1 (6.9) 18.3 (5.5) 28.9 (7.5) 27.5 (8.8) 19.6 (5.9) 25.3 (5.7) 30.1 (5.0)

Kansas

Johnson/Wyandotte Counties .... 3.4 (2.1) 0.6 (0.8) 5.6 (3.0) 15.3 (3.5) 14.5 (3.9) 16.0 (2.3) 38.2 (7.1)

Rest of Kansas ............. 17.8 (3.3) 20.3 (2.3) 32.8 (4.4) 19.2 (10.1) 30.2 (5.3) 30.9 (5.5) 31.7 (9.8)

Kentucky .................. 21.7 (5.0) 23.7 (6.0) 23.8 (5.8) 28.3 (4.4) 27.4 (5.8) 34.4 (4.1) 29.4 (6.2)

Louisiana .................. 14.0 (3.9) 12.7 (4.3) 17.5 (2.7) 13.7 (2.2) 22.7 (2.4) 26.7 (3.8) 28.7 (4.6)

Maine .................... 19.1 (8.7) 11.7 (2.6) 20.1 (5.4) 17.7 (9.1) 30.9 (8.3) 20.9 (9.9) 17.1 (5.7)

Maryland

Baltimore City . . . . . . . . . . . . . . 18.4 (8.6) 6.7 (3.8) 11.1 (3.1) 6.9 (6.1) 35.7 (5.5) 24.2 (2.5) 17.4 (2.3)

Rest of Maryland ............ 6.7 (2.4) 11.1 (3.6) 8.9 (2.1) 11.6 (2.2) 16.9 (5.2) 15.9 (2.2) 19.9 (3.7)

Massachusetts

Suffolk County.............. 15.2 (2.0) 27.7 (7.9) 35.8 (6.5) 7.0 (5.3) 19.5 (5.8) 19.7 (9.7) 26.9 (5.2)

Rest of Massachusetts ........ 9.2 (2.9) 4.9 (1.9) 9.7 (2.6) 8.2 (1.3) 16.6 (5.4) 16.7 (1.4) 16.2 (3.1)

Michigan

Wayne County.............. 16.1 (2.5) 18.7 (2.8) 29.3 (6.5) 34.2 (3.4) 26.8 (4.7) 25.3 (9.5) 45.2 (4.6)

Rest of Michigan ............ 15.6 (3.8) 18.1 (3.4) 19.0 (3.4) 23.9 (2.3) 21.5 (2.8) 31.5 (2.6) 26.6 (2.0)

Minnesota

Twin Cities Counties3 ......... 15.5 (2.6) 23.1 (8.6) 24.7 (4.8) 26.5 (2.8) 24.1 (1.5) 26.6 (4.3) 20.7 (2.5)

Rest of Minnesota ........... 13.8 (3.2) 11.9 (3.8) 23.4 (3.4) 14.8 (0.6) 21.8 (7.9) 24.4 (4.7) 25.5 (7.8)

Mississippi ................. 17.0 (6.5) 20.6 (5.0) 31.8 (6.5) 26.7 (3.6) 29.9 (5.7) 34.8 (2.4) 39.3 (4.6)

See footnotes at end of table.
Page 18 National Health Statistics Reports n Number 39 n April 20, 2011

Table I. Direct estimates (with standard errors) of the percentage of adults aged 18 years and over living in wireless-only households, by

selected geographic areas and time period: United States, January 2007–June 2010—Con.

Jan–Jun Jul–Dec Jan–Jun Jul–Dec Jan–Jun Jul–Dec Jan–Jun

Geographic area 2007 2007 2008 2008 2009 2009 2010

Percent (standard error)

Missouri

St. Louis County/City ......... 13.5 (3.0) 14.9 (6.5) 31.2 (13.1) 12.6 (4.8) 31.1 (1.2) 25.9 (1.9) 20.5 (7.0)

Rest of Missouri............. 6.5 (1.4) 6.9 (3.1) 10.5 (1.4) 11.9 (2.6) 14.2 (2.7) 26.0 (4.9) 18.4 (3.0)

Montana................... 3.0 (0.6) 3.1 (0.2) 8.1 (2.9) 26.3 (4.7) 16.7 (1.2) 23.5 (0.5) 18.4 (2.2)

Nebraska .................. 14.7 (4.0) 28.4 (5.2) 13.7 (3.7) 28.4 (11.1) 43.1 (5.6) 25.3 (3.4) 31.6 (7.3)

Nevada

Clark County............... 11.8 (0.8) 4.1 (3.0) 10.6 (3.9) 9.5 (3.3) 18.5 (2.9) 26.9 (4.7) 25.0 (0.4) 
 

Rest of Nevada ............. 7.7 (4.3) 6.3 (1.0) 5.8 (5.8) 20.2 (1.9) 21.6 (5.0) 33.7 (11.1) 8.5 (5.7)

New Hampshire .............. 3.4 (2.8) 16.4 (2.2) 6.7 (4.0) 15.3 (3.9) 17.7 (7.7) 9.5 (1.1) 19.2 (5.2)

New Jersey

Essex County .............. 5.7 (2.0) 2.3 (2.4) 11.1 (5.5) 19.7 (9.1) 22.4 (14.2) 28.8 (9.6) 27.2 (4.4) 
 

Rest of New Jersey .......... 6.0 (0.7) 6.1 (2.0) 7.3 (1.8) 8.1 (1.9) 10.2 (0.8) 11.4 (1.4) 11.6 (2.1) 
 

New Mexico

Southern Counties4 .......... 15.6 (3.0) 35.3 (6.1) 10.2 (2.3) 15.7 (1.4) 42.7 (7.6) 21.8 (4.7) 31.5 (6.6)

Rest of New Mexico .......... 24.1 (5.5) 6.3 (1.8) 22.3 (13.2) 14.8 (7.3) 31.6 (8.7) 28.7 (5.7) 21.9 (3.1)

New York

City of New York Counties5...... 11.1 (1.3) 8.8 (1.4) 10.1 (1.7) 14.1 (2.6) 14.8 (1.4) 17.6 (2.2) 20.3 (1.2)

Rest of New York ............ 11.6 (3.4) 15.8 (5.8) 10.1 (1.8) 10.5 (2.5) 12.7 (3.4) 12.7 (2.3) 14.4 (2.9)

North Carolina . . . . . . . . . . . . . . . 15.1 (2.5) 14.3 (2.3) 21.1 (2.7) 19.5 (4.7) 23.4 (2.6) 22.3 (2.3) 25.9 (2.1)

North Dakota ................ 18.0 (9.9) 8.9 (5.1) 14.7 (8.2) 13.8 (2.0) 38.3 (16.5) 39.4 (14.5) 48.5 (12.5)

Ohio

Cuyahoga County ........... 6.0 (1.5) 7.9 (3.2) 8.2 (2.0) 17.3 (3.7) 21.0 (4.9) 18.7 (2.4) 21.7 (3.6) 
 

Franklin County ............. 23.9 (12.6) 8.3 (0.5) 26.0 (8.7) 17.1 (3.5) 30.0 (4.7) 22.0 (5.3) 40.3 (3.9) 
 

Rest of Ohio ............... 13.6 (2.8) 15.5 (2.7) 18.8 (2.5) 16.2 (4.2) 22.5 (2.7) 22.9 (2.1) 28.6 (2.6) 
 

Oklahoma .................. 18.7 (2.4) 35.2 (6.2) 24.0 (2.9) 18.9 (9.1) 23.0 (6.7) 32.9 (3.9) 26.2 (4.3)

Oregon ................... 19.1 (5.7) 16.0 (4.7) 18.0 (5.3) 24.3 (10.2) 20.8 (6.6) 35.7 (8.0) 31.4 (7.5)

Pennsylvania

Allegheny County............ 3.2 (1.8) 37.6 (7.9) 9.4 (5.2) 51.3 (36.5) 23.5 (0.9) 32.3 (7.8) 22.5 (3.7) 
 

Philadelphia County .......... 4.6 (2.2) 14.0 (4.8) 7.7 (6.2) 6.3 (2.7) 14.4 (5.3) 19.3 (6.7) 19.3 (3.7) 
 

Rest of Pennsylvania ......... 8.0 (2.1) 8.2 (1.7) 9.8 (1.5) 11.6 (2.3) 14.4 (2.8) 14.2 (2.4) 15.0 (1.5) 
 

Rhode Island ................ 1.6 (0.4) 6.9 (4.4) 1.2 (0.9) 5.4 (3.2) 26.8 (6.3) 13.6 (3.0) 11.0 (3.5)

South Carolina ............... 18.1 (3.4) 18.7 (3.8) 17.6 (2.1) 22.4 (3.9) 15.3 (3.2) 21.1 (4.1) 29.7 (5.8)

South Dakota................ 10.7 (1.2) 3.3 (2.4) 10.4 (0.0) 10.8 (5.3) 2.9 (0.7) 14.6 (4.7) 5.4 (0.9)

Tennessee

Davidson County ............ 23.5 (14.6) 27.2 (5.7) 34.5 (2.8) 13.4 (7.4) 24.8 (5.6) 51.5 (8.1) 28.8 (2.1) 
 

Shelby County.............. 24.0 (10.1) 41.5 (13.3) 15.5 (2.6) 27.1 (10.0) 36.1 (9.5) 42.9 (20.9) 26.6 (1.6) 
 

Rest of Tennessee ........... 14.8 (3.2) 19.6 (4.3) 18.9 (2.5) 20.8 (5.9) 25.2 (4.4) 17.6 (2.9) 34.4 (4.8) 
 

Texas
 

Bexar County .............. 21.3 (10.7) 13.3 (5.5) 18.3 (4.1) 17.6 (2.1) 33.3 (7.1) 23.3 (4.2) 34.7 (1.7) 
 

Dallas County .............. 28.3 (9.6) 20.1 (4.1) 40.7 (5.9) 27.4 (5.5) 41.6 (8.0) 40.1 (3.4) 51.1 (2.5) 
 

El Paso County ............. 19.0 (5.0) 4.1 (2.4) 15.5 (1.9) 30.9 (10.2) 42.3 (6.3) 24.6 (1.8) 50.1 (3.3) 
 

Harris County .............. 19.1 (2.3) 19.0 (2.2) 28.5 (2.5) 28.5 (6.8) 31.3 (2.1) 28.9 (3.4) 32.9 (3.0) 
 

Rest of Texas .............. 16.1 (1.8) 20.7 (2.2) 23.5 (1.9) 22.3 (2.6) 28.5 (2.0) 29.0 (1.9) 34.1 (1.4) 
 

Utah ..................... 21.1 (2.8) 23.4 (4.4) 15.2 (3.7) 16.9 (1.4) 17.7 (2.1) 21.7 (3.8) 23.5 (2.8)

Vermont ................... 3.7 (2.6) 2.9 (2.1) 5.6 (3.7) 16.6 (6.2) 22.0 (5.8) 34.2 (8.8) 18.0 (0.1)

Virginia ................... 10.9 (1.7) 11.2 (3.3) 16.8 (3.4) 17.6 (5.0) 27.3 (6.5) 15.7 (2.3) 22.6 (3.0)

Washington

Eastern Counties6 ........... 30.9 (7.1) 16.7 (3.1) 18.0 (1.3) 14.3 (1.9) 25.2 (1.7) 12.2 (1.9) 49.2 (14.3) 
 

King County ............... 16.0 (6.5) 30.8 (9.0) 26.0 (6.0) 33.8 (7.0) 20.5 (8.0) 30.2 (7.0) 34.9 (5.9) 
 

Western Counties7 ........... 7.1 (3.9) 15.2 (5.1) 1.0 (0.9) 15.6 (3.6) 15.8 (4.0) 23.0 (7.2) 18.3 (2.8) 
 

Rest of Washington .......... 6.0 (4.4) 17.0 (4.6) 14.3 (2.8) 10.4 (1.9) 20.4 (7.4) 25.4 (8.1) 28.9 (6.0) 
 

West Virginia . . . . . . . . . . . . . . . . 11.1 (8.0) 7.9 (5.7) 17.6 (3.4) 8.3 (1.1) 10.8 (4.0) 20.0 (4.6) 16.0 (3.7) 
 

Wisconsin

Milwaukee County ........... 12.0 (1.7) 23.2 (6.4) 18.1 (8.9) 14.8 (9.3) 19.7 (6.8) 32.8 (3.9) 32.1 (5.3)

Rest of Wisconsin ........... 11.2 (3.0) 18.7 (4.6) 8.5 (2.3) 22.7 (6.1) 16.1 (3.1) 23.7 (4.5) 26.4 (3.2)

Wyoming .................. 9.6 (4.5) 21.0 (1.8) 13.1 (7.9) 29.3 (4.3) 29.6 (4.6) 4.5 (1.1) 14.0 (2.6) 
 

– Quantity zero.
 1Includes Del Norte, Siskiyou, Modoc, Lassen, Shasta, Trinity, Humboldt, Mendocino, Tehama, Plumas, Butte, Glenn, Colusa, Lake, and Sierra.
 2Includes Denver, Adams, Arapahoe, and Douglas.
 3Includes Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington.
 4Includes Chaves, Lea, Eddy, Lincoln, Socorro, Catron, Sierra, Curry, Roosevelt, De Baca, Dona Ana, Otero, Luna, Grant, and Hidalgo.
 5Includes Queens, Kings, Richmond, New York, and Bronx.
 6Includes Asotin, Columbia, Garfield, Whitman, Adams, Walla Walla, Stevens, Ferry, Lincoln, Chelan, Douglas, Okanogan, Benton, Franklin, Grant, Kittitas, Klickitat, and Pend Oreille.
 

7Includes Kitsap, Whatcom, Thurston, Skagit, Island, Cowlitz, Mason, Clallam, Jefferson, Grays Harbor, Lewis, Pacific, San Juan, Skamania, and Wahkiahum.
 
National Health Statistics Reports n Number 39 n April 20, 2011 Page 19

Table II. Direct estimates (with standard errors) of the percentage of adults aged 18 years and over living in landline-only households, by

selected geographic areas and time period: United States, January 2007–June 2010

Jan–Jun Jul–Dec Jan–Jun Jul–Dec Jan–Jun Jul–Dec Jan–Jun

Geographic area 2007 2007 2008 2008 2009 2009 2010

Percent (standard error)

Alabama

Jefferson County ............ 21.3 (10.3) 20.1 (3.9) 8.1 (1.5) 11.0 (6.9) 22.1 (2.0) 6.8 (3.0) 9.0 (2.2)

Rest of Alabama ............ 13.5 (1.9) 22.1 (3.7) 13.8 (4.1) 14.6 (1.6) 5.1 (1.5) 14.5 (1.9) 6.5 (1.6)

Alaska .................... 21.6 (8.3) 14.0 (6.2) 27.0 (6.5) 19.0 (11.9) 17.7 (6.6) 16.8 (4.4) 20.1 (5.8) 
 

Arizona

Maricopa County ............ 16.5 (3.2) 20.6 (1.1) 17.7 (2.8) 17.3 (4.2) 10.6 (3.1) 9.7 (3.1) 6.2 (1.9)

Rest of Arizona ............. 18.4 (0.8) 19.2 (5.3) 14.2 (3.0) 13.3 (1.4) 9.7 (2.4) 14.8 (3.9) 25.8 (12.7)

Arkansas .................. 20.8 (4.1) 30.8 (5.2) 15.1 (3.9) 13.8 (2.5) 14.4 (2.5) 22.4 (4.5) 12.5 (1.5) 
 

California
 

Alameda County ............ 20.6 (4.8) 11.9 (1.7) 14.0 (2.4) 5.2 (4.9) 11.7 (3.5) 6.8 (1.0) 11.6 (4.6) 
 

Fresno County ............. 28.2 (3.7) 38.7 (6.1) 21.6 (5.4) 25.3 (5.8) 15.4 (0.9) 17.9 (2.6) 26.5 (2.0) 
 

Los Angeles County .......... 23.8 (2.9) 16.8 (2.3) 14.6 (2.1) 19.2 (2.5) 11.3 (2.1) 13.8 (1.6) 12.4 (0.8) 
 

Northern Counties1 ........... 31.7 (9.0) 37.9 (1.8) 40.4 (5.3) 25.6 (1.2) 27.1 (3.0) 20.1 (2.2) 12.1 (3.1) 
 

San Bernardino County ........ 28.2 (5.7) 22.0 (5.6) 31.3 (8.4) 11.6 (2.4) 8.4 (1.6) 9.0 (1.6) 10.2 (3.3) 
 

San Diego County ........... 16.4 (2.2) 11.3 (1.8) 13.8 (4.9) 11.7 (3.4) 17.0 (2.1) 10.2 (1.9) 11.7 (0.9) 
 

Santa Clara County .......... 12.8 (1.9) 9.5 (3.3) 13.8 (5.1) 19.2 (6.8) 14.8 (4.8) 7.2 (1.9) 12.1 (2.8) 
 

Rest of California ............ 22.6 (2.3) 17.6 (1.5) 18.5 (1.8) 10.0 (1.5) 13.4 (2.0) 10.8 (1.4) 10.1 (1.1) 
 

Colorado

City of Denver Counties2 ....... 19.9 (2.0) 16.4 (4.9) 11.1 (5.2) 9.5 (3.4) 8.8 (7.2) 7.6 (4.6) 4.5 (1.3)

Rest of Colorado ............ 15.3 (3.2) 14.5 (2.4) 10.7 (1.9) 8.6 (2.9) 3.5 (1.2) 8.2 (1.7) 9.2 (2.2)

Connecticut ................. 17.8 (5.5) 23.0 (2.7) 16.7 (3.9) 18.9 (4.8) 22.8 (3.3) 18.5 (2.0) 17.2 (1.1)

Delaware .................. 11.9 (5.2) 31.8 (4.3) 10.6 (3.0) 9.3 (2.2) – 15.9 (8.6) 9.1 (6.9)

District of Columbia ............ 16.8 (1.3) 22.3 (18.0) 8.5 (6.6) 19.2 (0.3) 11.7 (5.4) 18.6 (3.2) 5.6 (4.6)

Florida

Dade County .............. 15.2 (3.0) 12.8 (1.7) 21.9 (4.5) 11.6 (3.5) 7.1 (2.7) 15.0 (3.0) 10.9 (1.0) 
 

Duval County .............. 20.6 (6.9) 11.1 (4.6) 11.7 (9.7) 18.4 (5.4) 36.2 (2.9) 13.4 (3.6) 8.4 (0.4) 
 

Orange County ............. 20.2 (9.5) 14.0 (13.3) 10.7 (2.4) 4.2 (4.9) 11.7 (1.4) 7.0 (1.9) 13.0 (3.9) 
 

Rest of Florida ............. 21.8 (2.0) 13.8 (1.7) 18.0 (2.8) 10.5 (1.6) 14.4 (2.2) 14.2 (1.5) 11.9 (1.7) 
 

Georgia

Fulton/DeKalb Counties ........ 11.4 (2.1) 6.0 (2.6) 16.3 (2.7) 8.9 (3.5) 16.2 (4.7) 11.2 (3.1) 7.4 (0.6)

Rest of Georgia ............. 27.7 (4.6) 19.0 (5.6) 23.3 (4.8) 14.0 (1.1) 11.4 (2.8) 13.0 (1.8) 15.0 (3.4)

Hawaii .................... 23.7 (4.0) 18.8 (3.7) 18.3 (1.0) 13.3 (5.8) 13.3 (2.3) 5.7 (1.5) 5.8 (2.6)

Idaho..................... 10.1 (6.1) 23.1 (1.6) 10.3 (1.8) 10.6 (6.1) 10.0 (4.8) 14.0 (3.0) 6.9 (1.6)

Illinois

Cook County............... 16.3 (2.2) 12.0 (3.4) 15.2 (2.1) 7.6 (1.9) 8.1 (1.8) 7.8 (2.2) 7.0 (0.8)

Madison/St. Clair Counties ...... 27.2 (4.5) 18.9 (9.5) 7.6 (5.4) 7.3 (3.6) 12.7 (4.6) 11.7 (4.3) 10.2 (3.8)

Rest of Illinois .............. 14.4 (3.9) 22.5 (5.4) 18.9 (4.0) 12.6 (2.0) 13.1 (2.2) 9.9 (2.6) 10.0 (1.5)

Indiana

Lake County ............... 15.6 (6.1) 55.9 (3.9) 22.4 (5.9) 72.6 (22.6) 23.7 (9.2) 11.2 (8.0) 42.3 (9.7)

Marion County.............. 20.7 (2.7) 15.2 (1.6) 12.1 (2.5) 13.8 (5.5) 18.2 (8.7) 4.1 (1.6) 2.5 (0.6)

Rest of Indiana ............. 32.3 (3.0) 26.8 (4.3) 35.6 (3.1) 20.8 (2.2) 10.5 (2.8) 18.5 (3.6) 12.4 (3.2)

Iowa ..................... 20.6 (5.3) 10.8 (4.3) 7.9 (1.5) 7.8 (1.3) 9.2 (2.7) 7.4 (2.2) 5.9 (1.1) 
 

Kansas

Johnson/Wyandotte Counties .... 12.0 (12.2) 21.0 (6.3) 36.6 (4.1) 7.1 (3.7) 18.9 (4.6) 10.4 (3.7) 1.6 (1.2)

Rest of Kansas ............. 16.1 (3.8) 8.7 (3.0) 10.5 (2.4) 6.7 (0.3) 13.0 (2.7) 8.9 (3.3) 5.7 (0.8)

Kentucky .................. 29.8 (6.7) 18.4 (5.8) 16.7 (3.2) 17.0 (5.8) 12.1 (3.6) 12.1 (4.4) 13.8 (3.2)

Louisiana .................. 16.5 (2.6) 17.3 (4.6) 11.5 (4.2) 11.7 (2.2) 6.7 (1.8) 10.7 (2.0) 14.2 (5.3)

Maine .................... 29.4 (6.8) 18.4 (4.5) 15.4 (2.5) 7.1 (4.2) 19.2 (6.9) 12.3 (3.9) 15.0 (2.4)

Maryland

Baltimore City .............. 22.7 (5.1) 14.9 (8.6) 23.7 (4.8) 34.3 (14.9) 15.2 (2.0) 5.8 (2.3) 6.8 (3.5) 
 

Rest of Maryland ............ 15.0 (2.7) 20.4 (4.0) 11.7 (1.6) 10.8 (1.3) 6.2 (1.8) 12.0 (4.4) 8.5 (2.7) 
 

Massachusetts

Suffolk County.............. 26.9 (0.8) 43.9 (2.6) 12.6 (2.1) 40.3 (2.9) 15.0 (7.4) 26.9 (6.1) 14.5 (4.0)

Rest of Massachusetts ........ 20.2 (2.5) 18.4 (1.9) 15.0 (3.2) 20.5 (3.7) 10.6 (2.3) 10.7 (1.9) 9.8 (1.4)

Michigan

Wayne County.............. 20.1 (5.8) 17.1 (5.0) 15.3 (4.2) 15.9 (2.1) 10.7 (6.7) 11.2 (2.7) 8.6 (2.7)

Rest of Michigan ............ 17.8 (1.9) 14.8 (2.9) 13.1 (1.4) 11.4 (1.6) 13.1 (2.4) 11.0 (1.8) 7.0 (1.1)

Minnesota

Twin Cities Counties3 ......... 11.4 (1.6) 11.1 (1.6) 6.5 (1.3) 11.3 (4.9) 5.3 (1.0) 9.9 (2.1) 3.6 (0.6)

Rest of Minnesota ........... 17.2 (3.3) 24.3 (10.5) 14.2 (3.9) 11.6 (4.3) 9.0 (4.2) 13.1 (1.2) 13.4 (3.0)

Mississippi ................. 26.2 (7.7) 35.0 (4.8) 12.0 (3.6) 16.6 (2.5) 16.1 (3.7) 7.1 (1.9) 7.4 (1.9) 
 

See footnotes at end of table.
Page 20 National Health Statistics Reports n Number 39 n April 20, 2011

Table II. Direct estimates (with standard errors) of the percentage of adults aged 18 years and over living in landline-only households, by

selected geographic areas and time period: United States, January 2007–June 2010—Con.

Jan–Jun Jul–Dec Jan–Jun Jul–Dec Jan–Jun Jul–Dec Jan–Jun

Geographic area 2007 2007 2008 2008 2009 2009 2010

Percent (standard error)
 

Missouri
 

St. Louis County/City ......... 19.2 (7.9) 13.0 (8.6) 22.9 (11.3) 19.9 (8.1) 12.4 (4.4) 9.6 (3.2) 11.4 (1.9) 
 

Rest of Missouri............. 34.5 (6.8) 27.8 (5.6) 33.6 (6.9) 25.2 (3.6) 15.9 (4.6) 12.9 (3.9) 11.0 (2.8) 
 

Montana................... 55.5 (12.5) 60.4 (3.9) 60.7 (17.3) 40.7 (14.0) 21.0 (16.7) 42.4 (8.2) 45.0 (18.3) 
 

Nebraska .................. 17.0 (7.6) 6.5 (3.8) 10.7 (2.9) 21.3 (10.5) 7.2 (1.5) 19.4 (3.2) 7.5 (4.9) 
 

Nevada
 

Clark County............... 58.8 (5.8) 56.3 (9.2) 58.1 (10.1) 51.2 (16.9) 69.2 (1.8) 47.2 (5.9) 22.6 (0.6) 
 

Rest of Nevada ............. 46.8 (18.2) 17.0 (5.1) 25.1 (10.5) 15.7 (8.5) 8.3 (1.9) 2.9 (2.6) 15.0 (2.8) 
 

New Hampshire .............. 29.4 (1.1) 26.8 (6.1) 9.1 (3.4) 14.3 (7.6) 10.4 (4.6) 14.4 (4.6) 6.3 (0.9) 
 

New Jersey
 

Essex County .............. 74.3 (9.6) 56.5 (16.1) 79.9 (5.3) 31.7 (6.1) 22.2 (10.0) 19.4 (4.9) 12.2 (5.8) 
 

Rest of New Jersey .......... 12.8 (2.7) 12.7 (1.5) 10.8 (1.7) 11.3 (2.2) 10.5 (1.3) 10.1 (1.6) 9.1 (2.3) 
 

New Mexico
 

Southern Counties4 .......... 47.5 (10.8) 4.7 (2.9) 38.3 (2.9) 24.4 (1.9) 21.2 (4.6) 27.4 (0.7) 23.6 (6.4) 
 

Rest of New Mexico .......... 24.3 (1.9) 24.7 (2.2) 23.4 (12.6) 21.1 (5.3) 35.7 (14.1) 10.6 (1.7) 22.2 (2.4) 
 

New York
 

City of New York Counties5...... 32.8 (5.0) 29.9 (4.5) 32.8 (4.6) 25.9 (2.6) 25.3 (2.2) 23.5 (3.1) 18.8 (1.2) 
 

Rest of New York ............ 22.8 (2.4) 24.1 (3.3) 24.1 (2.5) 26.7 (5.6) 27.1 (2.8) 11.0 (1.5) 12.4 (1.8) 
 

North Carolina . . . . . . . . . . . . . . . 22.9 (2.3) 21.7 (3.8) 18.7 (1.6) 16.9 (2.2) 15.4 (1.5) 11.6 (2.0) 13.4 (1.7) 
 

North Dakota ................ 26.6 (18.0) 37.3 (14.6) 26.8 (11.4) 34.4 (0.6) 13.4 (11.0) 14.9 (5.2) 17.6 (0.8) 
 

Ohio
 

Cuyahoga County ........... 22.6 (3.8) 14.3 (4.2) 27.7 (12.2) 20.3 (5.4) 16.1 (4.2) 15.8 (2.6) 11.7 (2.4) 
 

Franklin County ............. 14.0 (5.6) 6.7 (5.5) 1.1 (0.9) 7.3 (6.9) 16.1 (2.2) 8.4 (2.2) – 
 

Rest of Ohio ............... 23.2 (2.0) 19.1 (1.8) 14.1 (2.2) 11.4 (1.2) 11.7 (1.7) 12.0 (1.9) 5.8 (1.1) 
 

Oklahoma .................. 12.3 (1.7) 8.0 (1.7) 16.8 (2.6) 16.7 (4.7) 11.7 (2.1) 9.5 (2.9) 6.7 (1.9) 
 

Oregon ................... 17.0 (3.0) 19.1 (1.1) 20.2 (5.4) 10.9 (4.0) 14.9 (3.5) 10.3 (0.6) 14.1 (3.3) 
 

Pennsylvania
 

Allegheny County............ 42.1 (5.5) 11.5 (1.2) 16.8 (2.5) 5.1 (3.2) 17.6 (4.1) 9.4 (1.8) 18.4 (5.9) 
 

Philadelphia County .......... 16.4 (5.1) 36.3 (3.3) 26.5 (8.6) 18.2 (3.4) 6.7 (2.8) 9.0 (4.8) 5.3 (1.6) 
 

Rest of Pennsylvania ......... 19.5 (1.8) 22.5 (3.8) 16.7 (2.3) 21.0 (4.2) 12.7 (1.5) 11.2 (2.3) 8.7 (1.4) 
 

Rhode Island ................ 15.4 (2.1) 21.9 (9.0) 23.1 (7.7) 28.6 (1.9) 8.8 (4.1) 19.5 (6.6) 22.9 (4.0) 
 

South Carolina ............... 17.4 (3.7) 21.7 (2.9) 13.9 (2.5) 8.2 (4.3) 10.1 (1.6) 14.9 (4.2) 10.1 (2.2) 
 

South Dakota................ 79.8 (4.7) 78.8 (7.4) 84.4 (0.1) 59.1 (14.0) 77.3 (4.9) 53.8 (10.8) 29.0 (16.5) 
 

Tennessee
 

Davidson County ............ 7.4 (4.1) 6.7 (3.4) 6.3 (2.7) 35.3 (22.8) 9.5 (2.9) 5.3 (4.5) 7.4 (2.8) 
 

Shelby County.............. 15.5 (3.0) 12.5 (5.9) 21.9 (6.7) 10.2 (2.4) 22.6 (0.7) 2.6 (2.3) 9.5 (1.0) 
 

Rest of Tennessee ........... 18.6 (5.4) 19.1 (4.0) 13.1 (3.2) 16.5 (3.3) 12.4 (3.1) 10.9 (2.0) 8.1 (3.2) 
 

Texas
 

Bexar County .............. 22.3 (1.7) 7.8 (4.9) 10.8 (1.1) 9.1 (4.2) 20.4 (1.0) 11.6 (2.9) 11.9 (1.4) 
 

Dallas County .............. 13.0 (3.4) 9.9 (3.5) 5.5 (1.5) 11.9 (4.7) 8.3 (2.6) 15.1 (3.2) 8.0 (2.9) 
 

El Paso County ............. 9.3 (4.8) 29.6 (9.8) 21.2 (3.0) 29.0 (17.0) 23.4 (2.6) 26.9 (9.2) 29.3 (1.6) 
 

Harris County .............. 13.4 (1.5) 13.6 (1.4) 14.9 (2.9) 13.4 (4.3) 2.8 (1.1) 11.7 (1.6) 10.0 (1.3) 
 

Rest of Texas .............. 13.9 (2.1) 13.8 (2.4) 12.9 (1.4) 11.2 (1.2) 9.2 (2.1) 9.1 (1.0) 6.8 (1.1) 
 

Utah ..................... 9.7 (3.3) 8.8 (2.6) 14.0 (4.1) 9.8 (4.1) 7.0 (0.3) 6.5 (1.5) 12.9 (2.0) 
 

Vermont ................... 20.6 (1.4) 22.3 (4.8) 19.4 (9.3) 5.1 (0.6) 3.9 (2.8) 23.0 (7.2) 14.0 (1.5) 
 

Virginia ................... 17.5 (3.4) 17.3 (2.5) 19.5 (3.7) 14.8 (3.0) 13.2 (2.6) 11.4 (1.5) 8.6 (1.0) 
 

Washington
 

Eastern Counties6 ........... 40.7 (8.5) 10.2 (0.2) 11.7 (5.5) 11.3 (1.9) 13.2 (2.0) 11.0 (2.7) 17.2 (4.4) 
 

King County ............... 13.1 (2.1) 9.7 (3.4) 5.3 (1.6) 15.9 (1.7) 10.4 (3.1) 9.1 (3.0) 5.1 (1.0) 
 

Western Counties7 ........... 20.5 (2.6) 6.2 (5.2) 16.0 (3.8) 20.8 (3.4) 11.1 (6.8) 12.8 (4.7) 13.2 (2.2) 
 

Rest of Washington .......... 8.6 (1.3) 8.9 (5.0) 18.9 (3.5) 9.1 (5.4) 12.4 (3.2) 5.8 (3.6) 7.5 (2.9) 
 

West Virginia . . . . . . . . . . . . . . . . 33.9 (6.2) 29.2 (6.3) 21.9 (3.6) 23.4 (9.9) 19.4 (3.2) 28.5 (13.1) 13.5 (6.9) 
 

Wisconsin
 

Milwaukee County ........... 37.7 (2.5) 23.3 (12.3) 28.8 (6.1) 14.8 (4.9) 35.1 (6.5) 14.8 (3.1) 25.2 (5.3) 
 

Rest of Wisconsin ........... 34.0 (5.0) 32.5 (6.3) 27.9 (5.0) 16.2 (6.5) 14.9 (1.9) 16.3 (2.1) 15.8 (2.2) 
 

Wyoming .................. 27.7 (4.4) 45.5 (1.0) 48.3 (6.1) 29.7 (0.6) 29.6 (3.1) 55.0 (14.0) 39.0 (2.1) 
 

– Quantity zero.
 1Includes Del Norte, Siskiyou, Modoc, Lassen, Shasta, Trinity, Humboldt, Mendocino, Tehama, Plumas, Butte, Glenn, Colusa, Lake, and Sierra.
 2Includes Denver, Adams, Arapahoe, and Douglas.
 3Includes Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington.
 4Includes Chaves, Lea, Eddy, Lincoln, Socorro, Catron, Sierra, Curry, Roosevelt, De Baca, Dona Ana, Otero, Luna, Grant, and Hidalgo.
 5Includes Queens, Kings, Richmond, New York, and Bronx.
 6Includes Asotin, Columbia, Garfield, Whitman, Adams, Walla Walla, Stevens, Ferry, Lincoln, Chelan, Douglas, Okanogan, Benton, Franklin, Grant, Kittitas, Klickitat, and Pend Oreille.
 7Includes Kitsap, Whatcom, Thurston, Skagit, Island, Cowlitz, Mason, Clallam, Jefferson, Grays Harbor, Lewis, Pacific, San Juan, Skamania, and Wahkiahum.
 
National Health Statistics Reports n Number 39 n April 20, 2011 Page 21

child models. Model selection using

AIC involves selecting the model that

minimizes twice the difference between

the number of parameters in the model

and the maximized value of the log

likelihood function. Because this

criterion was used to select covariates

for the person-level model, in some of

the adult or child models some of the

covariates were not statistically

significant at conventional alpha levels.

However, for ease of interpretation, we

used the same set of covariates for the

adult and child models. Tables III and

IV present the best set of covariates for

each of the phone categories.

Model-based estimate for the

proportion of adults in

wireless-only households

The parameter of interest in the

model given by Eqn 1 is the true but

unknown value for the arcsinetransformed proportion of adults living

in wireless-only households for a given

small area and 6-month period, and it

can be expressed as the sum of a

small-area/6-month-period mean, the

small-area effect, and the small-area-bytime effect.

The model-based estimate used in

estimating the proportion of adults

living in wireless-only households was

derived using a best linear unbiased

prediction (BLUP) approach (see

reference 10, p. 516). Because the

BLUP depends on unknown variance

components, an empirical model-based

estimate, referred to as the empirical

BLUP (EBLUP), is obtained by

substituting the maximum likelihood

estimate for the unknown variance

components in the BLUP.

The 12-month estimates for the

arcsine-transformed proportion of adults

living in wireless-only households was

obtained by a simple average of the

consecutive 6-month-period estimates.

The 12-month model-based estimate for

the proportion of adults living in

wireless-only households in each small

area was then obtained by backtransforming the previously mentioned

annual estimate. A more direct approach

could have been to model the annual

12-month direct estimates instead of

modeling 6-month direct estimates, but

model-based moving averages were

desired for overlapping 12-month

periods to smooth out short-term

fluctuations and highlight longer-term

trends. Hence, we needed to combine

successive 6-month model-based

estimates.

The model given by Eqn 1 was also

fitted for the proportion of adults living

in WM, DU, LM, and LO households.

Similar to fitting the model for adults

living in WO households, the best set of

covariates was selected for each of the

models for WM, DU, LM, and LO, and

the unknown parameters in each model

were estimated by the maximum

likelihood estimator. Table V presents R2

statistics that reflect the relative fit of

each model. These statistics estimate the

proportion of variability in the data that

is accounted for by the statistical

models, including the covariates and

random effects (14). Models for adults

fit better than models for children,

perhaps because covariates were initially

selected for a person-level (i.e., total

population) model that included more

adults than children. The WO and LO

models fit better than the WM, DU, and

LM models, perhaps because decisions

to own only a wireless or landline

telephone are more strongly related to

the covariates than are decisions to use

one or the other when both are owned.

The 12-month model-based estimate

for the proportion of adults living in

households that are WM, DU, LM, or

LO was derived using methodology

similar to the derivation of the 12-month

estimate for adults living in households

that are WO. Next, the set of 12-month

estimates for WO, WM, DU, LM, and

LO for every small area and time period

were raked such that for the

corresponding time period, the raked

estimates agreed with the NHIS

national-level direct estimate for WO,

WM, DU, LM, and LO. Also, for each

small area, the raked estimates for

January–December 2007, July 2007–

June 2008, January–December 2008,

and July 2008–June 2009 agreed with

the 2008 ACS estimate for the

proportion of adults living in households

with a telephone (landline or cell

phone), and the raked estimates for

January–December 2009 and July

2009–June 2010 agreed with the 2009

ACS estimate for the proportion of

adults living in households with a

telephone. These raked estimates are the

final published small-area-level

estimates.

For states with multiple small areas,

in order to derive state-level estimates

for proportion of adults in WO, WM,

DU, LM, and LO households, the raked

small-area-level estimates were

appropriately weighted by the number of

adults. For example, if a state consists

of two small areas, the state-level

proportion of adults in WO households

was obtained by multiplying the number

of adults in each small area and the

raked small-area estimate for the

proportion of adults in WO households,

then summing this product across the

two small areas, and finally dividing the

sum by the state-level total for number

of adults. These estimates are the final

published state-level estimates.

Variance estimation

An estimate for the variance of the

EBLUP for each small area/6-month

period was derived using equation 5.2 of

reference 10 (p. 518). However, because

the final model-based estimate involved

combining successive 6-month periods,

back-transformation, and raking, the

initial estimate for the variance was then

adjusted to take into account each of

these steps.

We recognize that Eqn 1 could have

been extended to a multivariate model

that would include all telephone service

use categories (WO, WM, DU, LM, and

LO) and age groups. This approach

would have produced more-efficient

estimates by using the dependence of

the random effects. That is, the

multivariate model would have produced

estimates with smaller standard errors

compared with the estimates produced

using Eqn 1, but this approach would

have been computationally more

demanding.
Page 22 National Health Statistics Reports n Number 39 n April 20, 2011

Table III. Estimated regression coefficients (with standard errors) for models predicting the percentage of adults living in households with

various telephone statuses: United States, January 2007–June 2010

Predictor1 Wireless-only Wireless-mostly Dual-use Landline-mostly Landline-only

Intercept Coefficient (standard error)

Jan–Jun 2007.............................. 0.685 (0.022) 0.713 (0.018) 1.169 (0.018) 0.859 (0.018) 0.967 (0.022)
 

Jul–Dec 2007 .............................. 0.724 (0.022) 0.752 (0.019) 1.148 (0.019) 0.828 (0.019) 0.920 (0.023)
 

Jan–Jun 2008.............................. 0.780 (0.022) 0.767 (0.018) 1.121 (0.018) 0.829 (0.017) 0.889 (0.022)
 

Jul–Dec 2008 .............................. 0.835 (0.023) 0.792 (0.019) 1.116 (0.019) 0.843 (0.018) 0.819 (0.023)
 

Jan–Jun 2009.............................. 0.916 (0.022) 0.838 (0.019) 1.117 (0.019) 0.799 (0.018) 0.768 (0.023)
 

Jul–Dec 2009 .............................. 0.962 (0.021) 0.845 (0.018) 1.114 (0.017) 0.785 (0.016) 0.751 (0.022)
 

Jan–Jun 2010.............................. 0.998 (0.024) 0.850 (0.018) 1.087 (0.020) 0.772 (0.018) 0.704 (0.023)
 

Household size

One person ............................... 0.098 (0.027) . . .† – 0.062 (0.021) . . .† . . .†
 

Two persons............................... 0.149 (0.022) . . . – 0.086 (0.022) . . . . . .
 

Three persons ............................. 0.034 (0.011) ... . . .† ... ... 
 

Four persons .............................. . . .† 0.053 (0.013) . . . . . . – 0.038 (0.015)
 

Five persons .............................. ... 0.054 (0.015) . . . . . . . . .
 

Six persons ............................... ... ... ... 0.052 (0.020) . . .
 

Race or ethnicity of household members

All are Hispanic............................. ... ... ... – 0.079 (0.017) . . .
 

All are black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... ... 0.050 (0.019) . . . – 0.125 (0.036)
 

All are white . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... – 0.075 (0.017) . . . . . . . . .
 

Age of household members2

All adults are under 31 ........................ ... ... 0.054 (0.017) – 0.114 (0.029) . . .
 

At least one adult is 65 or over ................... – 0.081 (0.018) . . . 0.063 (0.022) . . . . . .
 

Education of most educated adult household member3

Less than high school diploma ................... ... ... ... 0.063 (0.018) . . .
 

Some college .............................. ... ... – 0.039 (0.018) . . . . . .
 

College degree or higher ....................... ... ... ... ... – 0.113 (0.026)
 

Employment status of household members4

All adults are attending school.................... ... ... ... 0.045 (0.017) – 0.042 (0.019)
 

Household composition5

One or more adults and one or more children . . . . . . . . . . ... – 0.140 (0.040) . . . . . . . . .

One or more adults and one or more children (squared).... . . . – 0.044 (0.013) . . . . . . . . .

Two or more adults and one or more children . . . . . . . . . . 0.129 (0.032) 0.111 (0.039) . . . 0.122 (0.037) . . .

Two or more adults and one or more children (squared).... . . . 0.032 (0.014) . . . . . . . . .

No children ............................... ... ... ... 0.142 (0.035) . . .
 

All adults are male . . . . . . . . . . . . . . . . . . . . . . . . . . . ... 0.051 (0.019) . . . . . . . . .
 

All adults are female ......................... ... ... ... ... 0.112 (0.041)
 

Home ownership

Rented .................................. ... – 0.078 (0.019) . . . – 0.132 (0.024) 0.062 (0.024)

Rented and all household members are under age 31 ..... . . . . . . . . . 0.100 (0.031) . . .

Poverty status of individuals6

Less than 200% of poverty (all persons) ............. ... ... – 0.405 (0.144) . . . . . .

200%–399% of poverty (all persons)................ ... ... – 0.170 (0.078) . . . . . .

Less than 200% of poverty (adults, aged 18 and over)..... 0.068 (0.013) . . . 0.300 (0.131) . . . . . .

200%–399% of poverty (adults, aged 18 and over) ....... ... ... 0.143 (0.075) . . . . . .

Less than 200% of poverty (children, aged 0–17 years) .... . . . 0.046 (0.018) . . . . . . – 0.099 (0.031)

Listed telephones

Listed telephone numbers per capita................ – 0.054 (0.014) . . . . . . . . . . . .
 

See footnotes at end of table.
National Health Statistics Reports n Number 39 n April 20, 2011 Page 23

Table III. Estimated regression coefficients (with standard errors) for models predicting the percentage of adults living in households with

various telephone statuses: United States, January 2007–June 2010—Con.

Predictor1 Wireless-only Wireless-mostly Dual-use Landline-mostly Landline-only

Census region7 Coefficient (standard error)

Northeast .............................. . . . . . . . . . 0.133 (0.035) . . .
 

Midwest ............................... 0.099 (0.031) – 0.065 (0.026) . . . . . . . . .
 

South ................................ 0.081 (0.031) . . . . . . . . . . . .
 

. . . Category not applicable.

† Here, not applicable means the coefficient was not statistically significant in the person-level model, and therefore the covariate was not retained in this model.
 1Except for the intercepts, poverty status, census region, and listed telephones, all predictors refer to the proportion of persons in the geographic area who live in households with the specified
 

characteristic. The linear terms of all covariates were considered. The square term of a covariate was considered only if the linear term was also included in the model. A square term of a covariate is

indicated by (squared). 2The proportion of persons living in households where all adults were between ages 31 and 44, and the proportion of persons living in households where all adults were between ages 45 and 64, were

not statistically significant in any model. 3The proportion of persons living in households where the education of the most educated adult was a high school diploma was not statistically significant in any model. 4The proportion of persons living in households where at least one adult was employed was not statistically significant in any model. 5The proportion of persons living in households with one adult and one or more children, the proportion of persons living in households with no related adults, the proportion of persons living in

households with related adults, and the proportion of persons living in households with more than one family in the household were not statistically significant in any model.
 6The proportion of persons at or above 400% of poverty, the proportion of adults at or above 400% of poverty, the proportion of children at 200%–399% of poverty, and the proportion of children at or
 

above 400% of poverty were not statistically significant in any model.
 

7Indicator for the West region was not statistically significant in any model.

Comparison of state-level

adult wireless-only

estimates for 2007

The modeling approach used in this

report is distinct from that used in the

previous report (6). In the previous

report, a two-sample strategy was used

to estimate the prevalence of adults

living in wireless-only households for

the year 2007. That approach involved

using the national sample of NHIS data

to fit a multinomial logistic regression

model with state-level fixed effects.

Then, the fitted NHIS model was

applied to the CPS microdata to obtain

predicted probabilities for each person

in the data set. The average predicted

probability within the state was used for

the model-based estimate of adults

living in wireless-only households. Next,

NHIS was used to derive state-level

direct estimates for adults living in

wireless-only households. Finally, a

blended estimate was derived by

combining the state-level, model-based

estimate and the state-level direct

estimate. The two sets of estimates were

combined based on the relative precision

of each estimate.

The approach used in the present

report involves modeling the direct

estimates for each small-area/6-month

period instead of modeling individual

observations. The approach used in the

previous report involved blending the

model-based estimate with the direct

estimate; the final estimate under that

approach is no longer consistent under

the model. The current approach derives

an ‘‘optimal’’ estimate under a model,

which also automatically is a weighted

combination of the direct estimate, a

regression estimate, and ‘‘adjusted direct

estimates.’’ This approach allows the

model-based estimate to incorporate the

direct estimate for the small-area/6­

month period of interest, and also, the

adjusted direct estimates for other

6-month periods. That is, the current

approach allows for ‘‘borrowing

strength’’ across time. In comparison,

using the modeling approach in the

previous report, there is no obvious

method for blending the direct estimate,

the model-based estimate, and the direct

estimates for 6-month periods other than

the 6-month period of interest, because

the direct estimates for other 6-month

periods need to be ‘‘adjusted’’ prior to

blending. (An adjustment is necessary to

ensure that the direct estimates for other

6-month periods are unbiased for the

small-area/6-month period of interest.)

Also, the approach used in the

current report allows for the production

of accurate standard errors when

combining estimates for consecutive

6-month periods and when combining

estimates for multiple small areas in a

state. Using the approach in the previous

report, we would not be able to produce

accurate standard errors when

combining estimates because the

correlation among the blended estimates

cannot be estimated.

We compared the modeled statelevel estimates and confidence intervals

of the percentage of adults living in

wireless-only households for January–

December 2007 using the current model

(Table 1) and the previous report’s

model (6). The estimates differ (data not

shown); however, the largest differences

are associated with estimates that have

wide confidence intervals. For example,

the 2007 adult wireless-only estimate for

the District of Columbia changed from

25.4% (using the approach in the

previous report) to 13.8%, but the

confidence interval associated with the

estimate using the current model is

significantly narrower. There are several

states (e.g., Iowa, Kentucky, Nebraska,

New Mexico, North Dakota, Oklahoma)

for which significantly narrower

confidence intervals are obtained using

the current model. In part, this occurs

because the process of borrowing

strength across time helps to moderate

the impact of any outlier estimates.

Direct estimates for a specific 6-month

period that are unusually high or

unusually low have less impact on the

final 12-month state-level estimate when

they are considered in a model that

incorporates six other 6-month time

periods. Examples of these outlier

estimates can be seen in Table I for

several areas in 2007. For example, the

direct estimates for the District of
Page 24 National Health Statistics Reports n Number 39 n April 20, 2011

Columbia for January–June 2007 and

for Oklahoma for July–December 2007

were substantially higher than for any

other 6-month time period for those

areas.

For some states (e.g., Delaware,

Hawaii, Idaho, Maine, Montana, South

Dakota, Vermont, Wyoming), the current

model gives a wider confidence interval.

We believe that some of the confidence

intervals associated with the estimates

from the model used in the previous

report had unrealistically narrow

confidence intervals (e.g., Vermont).

This may have occurred because, for the

model used in the previous year,

‘‘widest plausible intervals’’ were

constructed as a proxy for confidence

intervals. We believe that the confidence

intervals associated with the estimates

using the current model are more

accurate. These confidence intervals

have coverage probability approximately

equal to the nominal level of 95%.

Table IV. Estimated regression coefficients (with standard errors) for models predicting the percentage of children living in households

with various telephone status: United States, January 2007–June 2010

Predictor1 Wireless-only Wireless-mostly Dual-use Landline-mostly Landline-only

Intercept Coefficient (standard error)

Jan–Jun 2007.............................. 0.608 (0.029) 0.745 (0.024) 1.278 (0.027) 0.767 (0.027) 0.823 (0.028)

Jul–Dec 2007 .............................. 0.666 (0.030) 0.802 (0.026) 1.223 (0.028) 0.747 (0.029) 0.740 (0.029)

Jan–Jun 2008.............................. 0.763 (0.030) 0.835 (0.025) 1.203 (0.027) 0.712 (0.027) 0.688 (0.028)

Jul–Dec 2008 .............................. 0.781 (0.031) 0.858 (0.026) 1.198 (0.029) 0.703 (0.029) 0.643 (0.030)

Jan–Jun 2009.............................. 0.872 (0.031) 0.915 (0.027) 1.190 (0.028) 0.660 (0.028) 0.569 (0.029)

Jul–Dec 2009 .............................. 0.994 (0.028) 0.926 (0.024) 1.165 (0.025) 0.609 (0.026) 0.563 (0.027)

Jan–Jun 2010.............................. 1.022 (0.032) 0.942 (0.025) 1.106 (0.029) 0.602 (0.028) 0.511 (0.029)

Household size

One person ............................... 0.061 (0.039) . . .† – 0.068 (0.029) . . .† . . .†

Two persons............................... 0.138 (0.028) . . . – 0.083 (0.031) . . . . . .

Three persons ............................. 0.022 (0.017) . . . . . .† . . . . . .

Four persons .............................. . . .† 0.052 (0.018) . . . . . . – 0.030 (0.021)

Five persons .............................. . . . 0.072 (0.022) . . . . . . . . .

Six persons ............................... . . . . . . . . . 0.067 (0.030) . . .

Race or ethnicity of household members

All are Hispanic............................. . . . . . . . . . – 0.105 (0.026) . . .

All are black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.067 (0.025) . . . – 0.134 (0.044)

All are white . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . – 0.081 (0.022) . . . . . . . . .

Age of household members2

All adults are under 31 ........................ . . . . . . 0.054 (0.024) – 0.145 (0.043) . . .

At least one adult is 65 or over ................... – 0.033 (0.023) . . . 0.061 (0.031) . . . . . .

Education of most educated adult

household member3

Less than high school diploma ................... . . . . . . . . . 0.098 (0.027) . . .

Some college .............................. . . . . . . – 0.035 (0.024) . . . . . .

College degree or higher ....................... . . . . . . . . . . . . – 0.118 (0.032)

Employment status of household members4

All adults are going to school .................... . . . . . . . . . 0.064 (0.026) – 0.085 (0.025)

Household composition5

One or more adults and one or more children . . . . . . . . . . . . . – 0.202 (0.053) . . . . . . . . .

One or more adults and one or more children

(squared) ............................... . . . – 0.061 (0.018) . . . . . . . . .

Two or more adults and one or more children . . . . . . . . . . 0.124 (0.045) 0.144 (0.052) . . . 0.194 (0.055) . . .

Two or more adults and one or more children

(squared) ............................... . . . 0.050 (0.019) . . . . . . . . .

No children ............................... . . . . . . . . . 0.198 (0.052) . . .

All adults are male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.045 (0.024) . . . . . . . . .

All adults are female.......................... . . . . . . . . . . . . 0.119 (0.053)

See footnotes at end of table.
National Health Statistics Reports n Number 39 n April 20, 2011 Page 25

Table IV. Estimated regression coefficients (with standard errors) for models predicting the percentage of children living in households

with various telephone status: United States, January 2007–June 2010—Con.

Predictor1 Wireless-only Wireless-mostly Dual-use Landline-mostly Landline-only

Home ownership Coefficient (standard error)

Rented .................................. . . . – 0.118 (0.024) . . . – 0.147 (0.036) 0.117 (0.027)

Rented and all household members are under

age 31 ................................. . . . . . . . . . 0.113 (0.047) . . .

Poverty status of individuals6

Less than 200% of poverty (all persons) ............. . . . . . . – 0.660 (0.204) . . . . . .

200%–399% of poverty (all persons)................ . . . . . . – 0.259 (0.116) . . . . . . 

Less than 200% of poverty (adults, aged 18 and over)..... 0.113 (0.016) . . . 0.477 (0.186) . . . . . .

200%–399% of poverty (adults, aged 18 and over) ....... . . . . . . 0.227 (0.112) . . . . . . 

Less than 200% of poverty (children, aged 0–17 years) .... . . . 0.084 (0.023) . . . . . . – 0.095 (0.039)

Listed telephones

Listed telephone numbers per capita................ – 0.070 (0.019) . . . . . . . . . . . .

Census region7

Northeast ................................ . . . . . . . . . 0.170 (0.053) . . .

Midwest ................................. 0.105 (0.038) – 0.094 (0.031) . . . . . . . . .

South ................................... 0.150 (0.037) . . . . . . . . . . . .

. . . Category not applicable

† Here, not applicable means the coefficient was not statistically significant in the person-level model, and therefore the covariate was not retained in this model.
 1Except for the intercepts, poverty status, census region, and listed telephones, all predictors refer to the proportion of persons in the geographic area who live in households with the specified
 

characteristic. The linear terms of all covariates were considered. The square term of a covariate was considered only if the linear term was also included in the model. A square term of a

covariate is indicated by (squared). 2The proportion of persons living in households where all adults were between ages 31 and 44, and the proportion of persons living in households where all adults were between ages 45 and 64,

were not statistically significant in any model. 3The proportion of persons living in households where the education of the most educated adult was a high school diploma was not statistically significant in any model. 4 The proportion of persons living in households where at least one adult is employed was not statistically significant in any model. 5The proportion of persons living in households with one adult and one or more children, the proportion of persons living in households with no related adults, the proportion of persons living in

households with related adults, and the proportion of persons living in households with more than one family in the household were not statistically significant in any model. 6The proportion of persons at or above 400% of poverty, the proportion of adults at or above 400% of poverty, the proportion of children at 200%–399% of poverty, and the proportion of children at
 

or above 400% of poverty were not statistically significant in any model.
 7Indicator for the West region was not statistically significant in any model.
 
Page 26 National Health Statistics Reports n Number 39 n April 20, 2011

Table V. Goodness-of-fit (R2) statistics for models predicting the percentage of persons living in households with various household

telephone status, by age: United States, January 2007–June 2010

Dependent variable Wireless-only Wireless-mostly Dual-use Landline-mostly Landline-only

Percentage of adults ........... 0.85 0.56 0.71 0.77 0.88

Percentage of children .......... 0.76 0.31 0.64 0.57 0.64
National Health Statistics Reports n Number 39 n April 20, 2011 Page 27
Page 28 National Health Statistics Reports n Number 39 n April 20, 2011

Acknowledgments

NCHS thanks NORC’s Center for Excellence in Survey Research and SHADAC at the University of Minnesota for providing resources that

supported this research. The authors are solely responsible for the content of this report. Nadarajasundaram Ganesh was the primary author of

the Technical Notes section and developed the statistical models. We thank Marketing Systems Group for providing the auxiliary data on listed

telephone numbers, the staff of the NCHS Research Data Center for their assistance, and Avi Singh (NORC at the University of Chicago) for

his comments on an earlier version of the Technical Notes.

Suggested citation

Blumberg SJ, Luke JV, Ganesh N, et al.

Wireless substitution: State-level estimates

from the National Health Interview Survey,

January 2007–June 2010. National health

statistics reports; no 39. Hyattsville, MD:

National Center for Health Statistics. 2011.

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