Number 70 n December 18, 2013

Wireless Substitution: State-level Estimates From
 

the National Health Interview Survey, 2012
 by Stephen J. Blumberg, Ph.D., National Center for Health Statistics;
 

Nadarajasundaram Ganesh, Ph.D., NORC at the University of Chicago;
 

Julian V. Luke, National Center for Health Statistics; and
 

Gilbert Gonzales, M.H.A., State Health Access Data Assistance Center, University of Minnesota
 

Abstract

Objectives—This report updates subnational estimates of the percentage of

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

have at least one wireless telephone (i.e., wireless-only households). State-level

estimates for 2012 are presented, along with estimates 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 one earlier 12-month period

(July 2011–June 2012).

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 United

States. This modeling was based on 2007–2012 data from the National Health

Interview Survey, 2006–2011 data from the American Community Survey, and

auxiliary information on the number of listed telephone lines per capita in

2007–2012.

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

substantially across states. State-level estimates for 2012 ranged from 19.4%

(New Jersey) to 52.3% (Idaho) of adults and from 20.6% (New Jersey) to 63.4%

(Mississippi) of children.

Keywords: cell phones • telephone surveys • small domain estimation

Introduction

The 

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

prevalence and use of wireless

calls. As of the second half of 2012,

nearly two in every five American

households (38.2%) had only wireless

telephones (1). The prevalence of such

‘‘wireless-only’’ households markedly

exceeds the prevalence of households

with only landline telephones (8.6%), as

it has since 2009, and this difference is

expected to grow.

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

(http://www.cdc.gov/nchs/nhis/

releases.htm), presents both national and

regional estimates.

Direct state-level estimates of this

prevalence were not available previously

from NHIS data because the NHIS

sample size was insufficient for direct,

reliable annual estimates for most states.

However, in April 2011 NCHS released

the results of statistically modeled

estimates of the prevalence of wirelessonly adults and children at the state

level, using data from NHIS and the

U.S. Census Bureau’s American

Community Survey (ACS), along with

auxiliary information on the number of

listed telephone lines per capita (2).

Those estimates for 12-month periods

from January 2007 through June 2010

were the first multiyear state-level

estimates of the size of this population

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 70 n December 18, 2013

available from the federal government.

In October 2012, those estimates were

updated through December 2011 (3).

In this report, the estimates are

further updated through December 2012.

Estimates are presented for adults and

children living in wireless-only

households, 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

numbers 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

The methods employed to produce

the estimates for this report were

identical to those used for the estimates

published in 2011 and 2012 (2,3).

Small-area statistical modeling

techniques were used to combine

NHIS data collected within specific

geographies (states and some counties)

with auxiliary data that are representative

of those geographies, to produce

model-based estimates. Specifically, a

combination of direct survey estimates

from the 2007–2012 NHIS and the

2006–2011 ACS, and auxiliary

information on the number of listed

telephone lines per capita in 2007–2012,

were used. 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 twelve

6-month periods: January–June and

July–December in each year from 2007

through 2012.

Selection of small areas

Estimates were derived separately

for adults (aged 18 and over) and

children (under age 18) for 93

nonoverlapping areas that make up the

United States. Twenty-six of these areas

were states and one was the District of

Columbia; other 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 were urban areas that receive

federal Section 317 immunization

grants, and other substate areas that are

strata for CDC’s National Immunization

Survey (4). Areas were selected based

on the available survey sample sizes and

the stability of the modeled estimates.

Production of model-based

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 12 models (one for each 6-month

period). Separate small-area models

were fitted for each telephone service

use category (e.g., wireless-only,

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’’ (5–7). 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

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

twelve 6-month periods, the modelbased 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.

Model-based estimates were

produced for every small area and

6-month period, and consecutive

6-month estimates were combined to

produce 12-month estimates. The

small-area estimates for 12-month

periods were obtained by averaging the

two consecutive 6-month estimates. This

helped to reduce the variability of the

estimates. The 12-month small-area

estimates for each telephone category

were then adjusted to agree with the

national direct estimates from NHIS for

the corresponding telephone category

and year. The 12-month estimates were

further adjusted to agree with annual

ACS estimates for the population

without telephone service (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.

Model-based estimates were

produced for 2007–2012. Because the

models now included full-year data from

2012, the estimates for 2007–2011

differed from the estimates previously

reported (3) that were based on models

that did not include data from 2012. The

differences in the estimates for 2007–

2011 were generally small (e.g., for the

prevalence of wireless-only adults,

mean = –0.01, interquartile range = 0.5).

Therefore, the updated estimates for

2007–2011 are not presented here.

Instead, this report includes estimates

for July 2011–June 2012 and January–

December 2012 only.

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. Estimates for 2012 ranged

from a high of 52.3% in Idaho to a low

of 19.4% in New Jersey (Table 1). Other

states in which the prevalence of

wireless-only adults was relatively high

(exceeding 45%) were Mississippi

(49.4%), Arkansas (49.0%), and Utah

(46.6%). Several other states in the

northeast joined New Jersey with

prevalence rates below 25%, including
National Health Statistics Reports n Number 70 n December 18, 2013	 Page 3

Connecticut (20.6%), Delaware (23.3%),

New York (23.5%), Massachusetts

(24.1%), and Rhode Island (24.9%).

Similarly, results showed great

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

a high of 63.4% in Mississippi to a low

of 20.6% in New Jersey (Table 1). Other

states with a high prevalence of

wireless-only children included Idaho

(62.2%), Arkansas (59.8%), Missouri

(55.2%), and South Carolina (54.5%).

Other states with a low prevalence of

wireless-only children included Vermont

(24.5%), Connecticut (25.4%), Alaska

(25.7%), and Massachusetts (26.7%).

Estimates for Adults

and Children Living in

Households With

Wireless Telephones

Table 2 presents modeled estimates

for 2012 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 wireless-mostly households, landlinemostly 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 94.1%

in Utah to a low of 80.8% in West

Virginia. Two-thirds of the states (33

total) exceeded 90%, with Maryland

(93.8%), New Hampshire (93.6%),

Minnesota (93.6%), and Illinois (93.0%)

joining Utah with the highest rates.

Along with West Virginia, states with

the lowest rates included New Mexico

(81.1%) and North Dakota (82.6%).

Table 2 can also be used to examine

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 64.1% in

Arkansas to 39.4% in Connecticut.

Thirty-two states had rates of primary

wireless use exceeding 50%, with Texas

(63.0%), Idaho (62.7%), and Mississippi

(62.0%) joining Arkansas at the top end.

Other states at the low end included

Massachusetts (41.1%), New York

(41.2%), West Virginia (41.3%), and

Vermont (41.3%).

Table 3 presents modeled estimates

for 2012 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 as

described above.

Implications of Findings

The increasing prevalence of

wireless-only households has

implications for random-digit-dial

(RDD) telephone surveys. Historically,

such surveys did not include wireless

telephone numbers in their samples.

Now, despite operational challenges (8),

most major RDD telephone surveys

include wireless telephone numbers

(9,10). If they did not, the exclusion of

households with only wireless

telephones (along with the 2.1% of

households that have no telephone

service) could bias results (11).

Statistical challenges exist when

samples of wireless-only households are

combined 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 and current estimates

of the prevalence of wireless-only

households are needed (8). Moreover,

if the persons interviewed on their

wireless telephones are not screened to

exclude those who also have landlines,

reliable and current estimates of the

prevalence of landline and wireless

telephone service use may be required

in order to address the probability that

an individual could be in both

samples (8).

This report presents survey

researchers with the most up-to-date

estimates available from the federal

government concerning the prevalence

of landline and wireless telephone

service use in each state.

Telecommunications companies may

also find these estimates useful for

understanding changing conditions in

state and local markets.

References

1.	 Blumberg SJ, Luke JV. Wireless

substitution: Early release of

estimates based on data from the

National Health Interview Survey,

July–December 2012. National

Center for Health Statistics. June

2013. Available from: http://

www.cdc.gov/nchs/nhis.htm.

2.	 Blumberg SJ, Luke JV, Ganesh N,

et al. Wireless substitution: Statelevel 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. Available from:

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

nhsr039.pdf.

3.	 Blumberg SJ, Luke JV, Ganesh N,

et al. Wireless substitution: Statelevel estimates from the National

Health Interview Survey, 2010–2011.

National health statistics reports;

no 61. Hyattsville, MD: National

Center for Health Statistics. 2012.

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

nchs/data/nhsr/nhsr061.pdf.

4.	 CDC. National Immunization Survey:

A user’s guide for the 2010 publicuse data file. 2011. Available from:

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

Health_Statistics/NCHS/
 

Dataset_Documentation/NIS/
 

NISPUF10_DUG.PDF.
 

5.	 Jiang J, Lahiri P. Mixed model

prediction and small area estimation

(with discussion). Test 15(1):1–96.

2006.

6.	 Rao JNK. Small area estimation.

Hoboken, NJ: Wiley-Interscience.

2003.

7.	 Rao JNK, Yu M. Small area

estimation by combining time-series

and cross-sectional data. Can J Stat

22(4):511–28. 1994.

8.	 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. Deerfield, IL: American

Association for Public Opinion
Page 4	 National Health Statistics Reports n Number 70 n December 18, 2013

Research. 2010. Available from:

http://aapor.org/cell_phone_task_

force.htm.

9.	 CDC. Methodologic changes in the

Behavioral Risk Factor Surveillance

System in 2011 and potential effects

on prevalence estimates. MMWR

61(22):410–3. 2012. Available from:

http://www.cdc.gov/mmwr/preview/

mmwrhtml/mm6122a3.htm?s_cid=

mm6122a3_w.

10. CDC. Announcement: Addition of

households with only cellular

telephone service to the National

Immunization Survey, 2011. MMWR

61(34):685. 2012. Available from:

http://www.cdc.gov/mmwr/preview/

mmwrhtml/mm6134a5.htm?s_cid=

mm6134a5_w.

11. Blumberg SJ, Luke JV. Reevaluating

the need for concern regarding

noncoverage bias in landline surveys.

Am J Public Health 99(10):1806–10.

2009.
National Health Statistics Reports n Number 70 n December 18, 2013 Page 5

Table 1. Modeled estimates (with standard errors) of the percentage of persons living in wireless-only households, by selected

geographic areas, age, and period: United States, 2011–2012

Adults aged 18 and over Children under age 18

July 2011– January– July 2011– January–

Geographic area June 2012 December 2012 June 2012 December 2012

Percent (standard error)

Alabama ....................... 34.4 (1.9) 36.4 (2.0) 46.8 (3.1) 49.6 (3.2)

Jefferson County ................. 40.8 (2.7) 41.7 (2.8) 55.7 (4.4) 55.2 (4.4)

Rest of Alabama ................. 33.4 (2.1) 35.5 (2.3) 45.4 (3.5) 48.7 (3.7)

Alaska ......................... 30.2 (2.8) 31.6 (2.7) 22.8 (3.8) 25.7 (3.7)

Arizona ........................ 39.4 (1.8) 41.2 (1.9) 45.8 (2.6) 49.9 (2.7)

Maricopa County ................. 42.7 (2.4) 44.6 (2.6) 48.1 (3.5) 52.0 (3.7)

Rest of Arizona .................. 34.6 (2.6) 36.1 (2.7) 42.1 (3.8) 46.3 (3.9)

Arkansas ....................... 45.7 (2.1) 49.0 (2.1) 56.6 (3.3) 59.8 (3.1)

California ....................... 30.1 (0.7) 32.6 (0.8) 33.8 (1.1) 38.2 (1.2)

Alameda County ................. 31.4 (2.6) 34.2 (2.9) 34.3 (4.1) 37.0 (4.3)

Fresno County .................. 31.8 (2.8) 33.8 (2.9) 31.6 (3.7) 36.1 (3.6)

Los Angeles County ............... 30.2 (1.5) 31.7 (1.6) 33.7 (2.1) 36.7 (2.2)

Northern counties1 ................ 27.0 (2.7) 30.5 (3.0) 32.0 (4.1) 38.2 (4.4)

San Bernardino County ............. 33.7 (2.5) 38.9 (2.7) 38.0 (3.5) 45.8 (3.9)

San Diego County ................ 23.5 (1.8) 26.6 (2.0) 23.1 (2.7) 29.5 (3.0)

Santa Clara County ............... 30.9 (2.4) 31.4 (2.5) 32.8 (3.6) 34.9 (3.7)

Rest of California................. 30.8 (1.2) 33.6 (1.3) 35.4 (1.9) 40.0 (2.0)

Colorado ....................... 39.9 (1.9) 41.7 (2.0) 42.2 (2.7) 45.1 (2.8)

City of Denver counties2 ............ 35.2 (2.4) 37.8 (2.7) 41.7 (3.6) 46.3 (3.9)

Rest of Colorado ................. 42.9 (2.6) 44.3 (2.7) 42.6 (3.8) 44.2 (3.8)

Connecticut...................... 19.1 (1.7) 20.6 (1.7) 21.2 (2.4) 25.4 (2.6)

Delaware ....................... 23.0 (2.1) 23.3 (1.9) 24.5 (3.5) 26.8 (3.3)

District of Columbia................. 44.4 (2.9) 46.0 (2.6) 43.7 (4.9) 42.2 (4.4)

Florida. . . . . . . . . . . . . . . . . . . . . . . . . 37.1 (1.2) 39.7 (1.2) 45.6 (1.8) 49.2 (1.8)

Miami-Dade County ............... 36.6 (3.0) 37.6 (3.1) 48.8 (4.6) 53.2 (4.6)

Duval County ................... 43.5 (2.2) 44.4 (2.3) 52.8 (3.2) 54.2 (3.3)

Orange County .................. 43.9 (3.2) 46.5 (3.2) 49.1 (4.8) 51.4 (4.6)

Rest of Florida .................. 35.4 (1.5) 38.4 (1.5) 43.7 (2.3) 47.7 (2.3)

Georgia ........................ 34.3 (1.6) 37.0 (1.7) 41.3 (2.4) 45.9 (2.4)

Fulton/DeKalb counties ............. 40.7 (2.9) 41.8 (3.0) 46.8 (4.5) 48.8 (4.4)

Rest of Georgia.................. 33.0 (1.8) 36.0 (1.9) 40.3 (2.7) 45.4 (2.7)

Hawaii ......................... 29.2 (2.1) 31.6 (2.2) 38.8 (3.9) 43.8 (3.9)

Idaho ......................... 49.7 (2.0) 52.3 (1.9) 58.3 (2.9) 62.2 (2.6)

Illinois ......................... 35.2 (1.4) 38.0 (1.5) 39.7 (2.2) 42.4 (2.3)

Cook County ................... 39.7 (2.0) 42.2 (2.1) 41.1 (3.1) 42.3 (3.2)

Madison/St. Clair counties ........... 35.1 (3.5) 36.5 (3.6) 43.8 (5.7) 45.6 (5.5)

Rest of Illinois................... 33.9 (1.8) 36.8 (2.0) 39.1 (2.7) 42.2 (2.9)

Indiana ........................ 33.4 (1.6) 36.1 (1.8) 43.3 (2.7) 46.3 (2.9)

Lake County.................... 30.3 (2.8) 33.1 (3.0) 41.3 (5.0) 44.5 (5.2)

Marion County .................. 41.5 (3.3) 44.9 (3.3) 51.0 (5.1) 52.8 (4.7)

Rest of Indiana .................. 32.3 (2.0) 34.8 (2.2) 42.0 (3.2) 45.3 (3.5)

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . 40.1 (2.0) 42.2 (2.1) 41.3 (3.2) 45.4 (3.2)

Kansas ........................ 40.0 (1.8) 42.3 (1.9) 48.6 (2.8) 52.5 (2.7)

Johnson/Wyandotte counties ......... 31.1 (3.1) 35.0 (3.3) 33.7 (4.4) 41.5 (4.8)

Rest of Kansas .................. 42.9 (2.2) 44.8 (2.2) 53.8 (3.4) 56.4 (3.2)

Kentucky ....................... 35.3 (2.2) 37.0 (2.2) 47.1 (3.2) 52.5 (3.2)

Louisiana ....................... 34.0 (2.1) 36.2 (2.2) 42.8 (3.1) 45.1 (3.1)

Maine . . . . . . . . . . . . . . . . . . . . . . . . . 33.0 (2.4) 35.0 (2.3) 38.6 (3.6) 41.6 (3.3)

Maryland . . . . . . . . . . . . . . . . . . . . . . . 27.9 (1.5) 29.4 (1.6) 31.1 (2.3) 33.6 (2.4)

Baltimore City . . . . . . . . . . . . . . . . . . . 37.2 (3.1) 39.6 (3.2) 46.7 (5.0) 51.8 (5.3)

Prince George’s County............. § § § §

Rest of Maryland ................. 26.2 (1.9) 27.6 (2.0) 28.0 (2.8) 30.0 (3.0)

Massachusetts.................... 22.3 (1.5) 24.1 (1.6) 23.7 (2.4) 26.7 (2.7)

Suffolk County .................. 35.1 (3.4) 37.5 (3.6) 41.9 (6.4) 48.9 (6.8)

Rest of Massachusetts ............. 20.9 (1.6) 22.6 (1.7) 22.2 (2.6) 24.9 (2.8)

Michigan ....................... 37.5 (1.6) 39.5 (1.7) 42.7 (2.5) 44.2 (2.6)

Wayne County .................. 43.5 (2.6) 46.6 (2.8) 54.5 (4.2) 59.6 (4.1)

Rest of Michigan ................. 37.0 (1.8) 39.0 (1.9) 41.7 (2.7) 42.9 (2.8)

See footnotes at end of table.
Page 6 National Health Statistics Reports n Number 70 n December 18, 2013

Table 1. Modeled estimates (with standard errors) of the percentage of persons living in wireless-only households, by selected

geographic areas, age, and period: United States, 2011–2012—Con.

Adults aged 18 and over Children under age 18

July 2011– January– July 2011– January–

Geographic area June 2012 December 2012 June 2012 December 2012

Percent (standard error)

Minnesota ...................... 34.4 (1.6) 35.7 (1.7) 33.0 (2.5) 36.7 (2.6)

Twin Cities counties3 .............. 35.6 (2.1) 36.7 (2.3) 33.7 (3.5) 37.0 (3.7)

Rest of Minnesota ................ 33.1 (2.3) 34.6 (2.5) 32.2 (3.4) 36.3 (3.7)

Mississippi . . . . . . . . . . . . . . . . . . . . . . 45.6 (2.0) 49.4 (1.9) 59.0 (3.2) 63.4 (3.0)

Missouri ........................ 38.1 (1.8) 41.4 (2.0) 49.8 (2.8) 55.2 (3.0)

St. Louis County/City .............. 34.2 (2.9) 38.1 (3.2) 32.4 (4.3) 39.2 (4.8)

Rest of Missouri ................. 39.3 (2.1) 42.4 (2.4) 54.5 (3.4) 59.4 (3.5)

Montana ....................... § § § §

Nebraska ....................... 37.4 (2.0) 37.5 (2.0) 40.5 (3.3) 43.7 (3.2)

Nevada ........................ 36.0 (1.8) 38.9 (1.8) 37.9 (2.8) 41.7 (2.8)

Clark County ................... 37.2 (2.2) 40.7 (2.2) 36.3 (3.3) 40.6 (3.4)

Rest of Nevada .................. 33.1 (2.9) 34.4 (2.9) 42.2 (5.0) 44.6 (5.0)

New Hampshire ................... 25.4 (2.0) 26.7 (1.9) 29.3 (3.6) 30.3 (3.2)

New Jersey. . . . . . . . . . . . . . . . . . . . . . 17.8 (1.3) 19.4 (1.4) 19.8 (2.1) 20.6 (2.2)

Essex County ................... 35.9 (3.4) 40.2 (3.7) 29.9 (4.4) 38.2 (5.0)

Rest of New Jersey ............... 17.2 (1.3) 18.8 (1.5) 19.4 (2.2) 19.9 (2.3)

New Mexico ..................... 35.8 (2.0) 36.8 (2.0) 50.7 (3.3) 53.4 (3.3)

Southern counties4

................ 38.1 (2.8) 40.1 (3.0) 56.1 (4.4) 59.1 (4.6)

Rest of New Mexico ............... 35.0 (2.5) 35.6 (2.5) 48.6 (4.2) 51.2 (4.1)

New York . . . . . . . . . . . . . . . . . . . . . . . 21.4 (1.1) 23.5 (1.2) 23.2 (1.7) 26.8 (1.9)

City of New York counties5 ........... 26.0 (1.5) 29.4 (1.6) 25.7 (2.4) 29.8 (2.7)

Rest of New York................. 18.0 (1.5) 19.1 (1.6) 21.5 (2.3) 24.7 (2.6)

North Carolina . . . . . . . . . . . . . . . . . . . . 34.3 (1.7) 34.7 (1.7) 46.3 (2.6) 47.1 (2.6)

North Dakota..................... 39.9 (1.8) 40.2 (1.7) 44.9 (3.5) 50.0 (3.2)

Ohio . . . . . . . . . . . . . . . . . . . . . . . . . . 35.5 (1.3) 36.8 (1.4) 41.2 (2.2) 44.7 (2.4)

Cuyahoga County ................ 34.3 (2.9) 38.1 (3.2) 31.1 (4.0) 37.0 (4.2)

Franklin County.................. 40.9 (3.7) 41.8 (3.7) 43.9 (4.4) 43.1 (4.5)

Rest of Ohio.................... 34.9 (1.6) 35.9 (1.7) 42.2 (2.7) 46.0 (2.9)

Oklahoma....................... 37.1 (2.0) 39.0 (2.0) 46.1 (3.2) 50.9 (3.4)

Oregon ........................ 37.2 (2.1) 36.8 (2.2) 38.6 (3.4) 41.5 (3.4)

Pennsylvania..................... 25.0 (1.2) 26.2 (1.3) 29.9 (2.1) 31.4 (2.1)

Allegheny County ................ 39.4 (3.2) 40.4 (3.4) 42.0 (5.2) 43.9 (5.4)

Philadelphia County ............... 33.5 (2.6) 37.8 (2.9) 40.8 (4.2) 46.8 (4.4)

Rest of Pennsylvania .............. 21.8 (1.4) 22.7 (1.6) 26.9 (2.5) 27.6 (2.5)

Rhode Island..................... 19.5 (1.7) 24.9 (1.8) 25.5 (3.4) 34.8 (3.4)

South Carolina.................... 37.0 (1.9) 39.0 (2.1) 48.3 (3.2) 54.5 (3.3)

South Dakota .................... § § § §

Tennessee ...................... 35.9 (1.6) 37.8 (1.7) 47.3 (2.6) 52.3 (2.6)

Davidson County ................. 48.0 (3.5) 51.2 (3.6) 55.5 (5.2) 61.8 (5.4)

Shelby County .................. 43.2 (3.2) 46.2 (3.3) 49.4 (4.8) 54.1 (4.7)

Rest of Tennessee ................ 32.9 (2.0) 34.5 (2.1) 45.8 (3.2) 50.7 (3.3)

Texas ......................... 42.6 (1.1) 44.5 (1.2) 51.9 (1.7) 54.2 (1.7)

Bexar County ................... 41.4 (2.3) 42.6 (2.5) 52.1 (3.6) 57.0 (3.9)

Dallas County ................... 55.0 (2.6) 56.5 (2.6) 63.0 (3.6) 65.9 (3.6)

El Paso County .................. § § § §

Harris County ................... 44.1 (2.0) 47.0 (2.1) 49.2 (2.8) 54.8 (2.9)

Rest of Texas ................... 40.9 (1.5) 42.9 (1.6) 50.4 (2.2) 52.0 (2.2)

Utah . . . . . . . . . . . . . . . . . . . . . . . . . . 42.3 (2.0) 46.6 (1.9) 43.8 (2.8) 48.5 (2.6)

Vermont ........................ 29.0 (2.1) 29.9 (1.9) 22.6 (3.5) 24.5 (3.2)

Virginia ........................ 30.1 (1.8) 32.0 (1.9) 32.2 (2.5) 36.2 (2.7)

Washington...................... 37.3 (1.5) 39.4 (1.6) 37.5 (2.1) 41.8 (2.2)

Eastern counties6 ................ 32.1 (2.2) 34.2 (2.4) 40.7 (3.6) 44.2 (3.7)

King County .................... 45.3 (2.8) 46.0 (2.9) 38.6 (4.0) 41.0 (4.0)

Rest of Washington ............... 34.6 (2.3) 37.6 (2.4) 35.4 (3.1) 41.1 (3.4)

West Virginia. . . . . . . . . . . . . . . . . . . . . 27.3 (2.4) 30.2 (2.4) 36.1 (3.6) 42.7 (3.6)

Wisconsin....................... 35.2 (1.8) 39.0 (2.0) 38.0 (2.8) 44.5 (3.0)

Milwaukee County ................ § § § §

Rest of Wisconsin ................ 32.9 (2.1) 36.6 (2.2) 34.8 (3.2) 41.0 (3.5)

Wyoming ....................... § § § §

§ Model-based estimates for Maryland-Prince George’s County, Montana, South Dakota, Texas-El Paso County, Wisconsin-Milwaukee County, and Wyoming are not reported because, for at least

one telephone service use category, direct estimates from the National Health Information Survey were more than double or less than one-half the synthetic estimate. These differences between

two components of the model-based estimates suggest that the direct estimates for these areas may be biased. Biased estimates violate a key model-based estimation assumption.
National Health Statistics Reports n Number 70 n December 18, 2013 Page 7

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

Yakima.

NOTE: Estimates were calculated by NORC at the University of Chicago.

SOURCES: CDC/NCHS, National Health Interview Survey, 2007–2012; U.S. Census Bureau, American Community Survey, 2006–2011; and infoUSA.com consumer database, 2007–2012.
Page 8 National Health Statistics Reports n Number 70 n December 18, 2013

Table 2. Modeled estimates (with standard errors) of the percent distribution of household telephone status for adults aged 18 and over,

by selected geographic areas: United States, 2012

No

Wireless- Wireless- Landline- Landline­ telephone

Geographic area only mostly Dual-use mostly only service1 Total

Percent (standard error)

Alabama ....................... 36.4 (2.0) 16.0 (1.5) 21.6 (1.9) 16.3 (1.6) 7.8 (1.3) 2.0 100.0

Jefferson County ................. 41.7 (2.8) 17.6 (2.1) 20.7 (2.5) 12.1 (1.8) 6.5 (1.6) 1.5 100.0

Rest of Alabama ................. 35.5 (2.3) 15.7 (1.7) 21.7 (2.1) 17.0 (1.8) 8.0 (1.4) 2.0 100.0

Alaska ......................... 31.6 (2.7) 17.7 (2.2) 30.3 (2.9) 12.2 (1.9) 6.6 (1.6) 1.6 100.0

Arizona ........................ 41.2 (1.9) 16.4 (1.4) 18.8 (1.6) 10.7 (1.1) 10.8 (1.4) 2.1 100.0

Maricopa County ................. 44.6 (2.6) 17.1 (1.9) 18.8 (2.2) 6.0 (1.2) 11.8 (1.9) 1.8 100.0

Rest of Arizona .................. 36.1 (2.7) 15.5 (2.0) 18.9 (2.4) 17.6 (2.1) 9.4 (1.9) 2.6 100.0

Arkansas ....................... 49.0 (2.1) 15.1 (1.5) 15.8 (1.6) 10.9 (1.3) 6.7 (1.1) 2.4 100.0

California ....................... 32.6 (0.8) 21.5 (0.7) 25.6 (0.8) 11.3 (0.5) 7.4 (0.5) 1.5 100.0

Alameda County ................. 34.2 (2.9) 17.6 (2.3) 30.1 (3.1) 10.6 (1.8) 6.3 (1.7) 1.2 100.0

Fresno County .................. 33.8 (2.9) 9.6 (1.8) 32.1 (3.1) 10.8 (1.9) 12.3 (2.3) 1.3 100.0

Los Angeles County ............... 31.7 (1.6) 22.9 (1.4) 26.6 (1.5) 9.8 (1.0) 7.5 (0.9) 1.4 100.0

Northern counties2 ................ 30.5 (3.0) 15.2 (2.3) 23.6 (3.1) 19.2 (2.5) 10.1 (2.3) 1.4 100.0

San Bernardino County ............. 38.9 (2.7) 22.5 (2.3) 23.6 (2.6) 9.8 (1.6) *3.9 (1.2) 1.2 100.0

San Diego County ................ 26.6 (2.0) 21.1 (1.8) 32.0 (2.3) 9.4 (1.3) 8.3 (1.4) 2.6 100.0

Santa Clara County ............... 31.4 (2.5) 21.2 (2.2) 27.9 (2.7) 9.3 (1.6) 9.0 (1.8) 1.1 100.0

Rest of California................. 33.6 (1.3) 22.1 (1.1) 23.3 (1.2) 12.5 (0.9) 7.1 (0.7) 1.4 100.0

Colorado ....................... 41.7 (2.0) 16.9 (1.5) 20.9 (1.8) 11.9 (1.3) 6.7 (1.1) 1.8 100.0

City of Denver counties3 ............ 37.8 (2.7) 19.0 (2.1) 23.5 (2.6) 12.0 (1.8) 6.1 (1.5) 1.7 100.0

Rest of Colorado ................. 44.3 (2.7) 15.6 (2.0) 19.3 (2.4) 11.8 (1.8) 7.1 (1.6) 1.9 100.0

Connecticut...................... 20.6 (1.7) 18.8 (1.6) 32.0 (2.1) 18.5 (1.6) 9.0 (1.3) 1.1 100.0

Delaware ....................... 23.3 (1.9) 22.5 (1.9) 30.0 (2.2) 17.1 (1.7) 6.0 (1.1) 1.2 100.0

District of Columbia................. 46.0 (2.6) 18.3 (2.1) 17.3 (2.1) 9.1 (1.5) 6.6 (1.4) 2.6 100.0

Florida. . . . . . . . . . . . . . . . . . . . . . . . . 39.7 (1.2) 17.2 (0.9) 22.6 (1.1) 11.5 (0.8) 6.5 (0.7) 2.5 100.0

Miami-Dade County ............... 37.6 (3.1) 13.0 (2.1) 27.8 (3.2) 11.9 (2.1) 7.1 (2.0) 2.6 100.0

Duval County ................... 44.4 (2.3) 18.8 (1.8) 19.9 (2.0) 6.4 (1.1) 6.5 (1.3) 4.0 100.0

Orange County .................. 46.5 (3.2) 22.2 (2.7) 18.7 (2.8) 6.2 (1.6) *4.5 (1.6) 1.9 100.0

Rest of Florida .................. 38.4 (1.5) 16.7 (1.2) 23.1 (1.4) 12.9 (1.1) 6.6 (0.8) 2.3 100.0

Georgia ........................ 37.0 (1.7) 22.8 (1.4) 20.2 (1.5) 11.0 (1.1) 6.4 (0.9) 2.6 100.0

Fulton/DeKalb counties ............. 41.8 (3.0) 21.6 (2.5) 21.3 (2.8) 9.0 (1.8) *4.2 (1.4) 2.1 100.0

Rest of Georgia.................. 36.0 (1.9) 23.1 (1.7) 20.0 (1.7) 11.4 (1.3) 6.8 (1.1) 2.7 100.0

Hawaii ......................... 31.6 (2.2) 19.6 (1.8) 28.9 (2.2) 11.6 (1.5) 6.5 (1.2) 1.7 100.0

Idaho ......................... 52.3 (1.9) 10.4 (1.1) 17.5 (1.5) 12.3 (1.2) 4.9 (0.9) 2.7 100.0

Illinois ......................... 38.0 (1.5) 17.5 (1.2) 24.3 (1.5) 13.2 (1.1) 5.5 (0.8) 1.6 100.0

Cook County ................... 42.2 (2.1) 14.9 (1.5) 24.2 (2.0) 10.4 (1.3) 6.3 (1.1) 2.0 100.0

Madison/St. Clair counties ........... 36.5 (3.6) 17.5 (2.8) 25.3 (3.7) 13.7 (2.5) *5.4 (2.1) 1.6 100.0

Rest of Illinois................... 36.8 (2.0) 18.2 (1.6) 24.3 (1.9) 14.0 (1.4) 5.2 (1.0) 1.4 100.0

Indiana ........................ 36.1 (1.8) 15.4 (1.4) 20.9 (1.6) 15.5 (1.3) 9.5 (1.2) 2.7 100.0

Lake County.................... 33.1 (3.0) 15.1 (2.2) 23.5 (2.9) 16.8 (2.3) 10.1 (2.2) 1.4 100.0

Marion County .................. 44.9 (3.3) 8.8 (1.9) 16.5 (2.7) 16.8 (2.5) 9.0 (2.2) 3.9 100.0

Rest of Indiana .................. 34.8 (2.2) 16.6 (1.7) 21.4 (2.0) 15.1 (1.6) 9.5 (1.5) 2.6 100.0

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . 42.2 (2.1) 18.4 (1.6) 19.4 (1.8) 11.9 (1.4) 5.7 (1.1) 2.3 100.0

Kansas ........................ 42.3 (1.9) 13.5 (1.3) 23.2 (1.7) 11.0 (1.2) 8.3 (1.2) 1.7 100.0

Johnson/Wyandotte counties ......... 35.0 (3.3) 14.2 (2.4) 31.8 (3.5) 10.8 (2.1) *6.6 (2.0) 1.7 100.0

Rest of Kansas .................. 44.8 (2.2) 13.3 (1.5) 20.3 (1.9) 11.0 (1.4) 8.8 (1.4) 1.7 100.0

Kentucky ....................... 37.0 (2.2) 15.3 (1.7) 19.7 (2.0) 16.6 (1.7) 9.1 (1.5) 2.4 100.0

Louisiana ....................... 36.2 (2.2) 16.5 (1.7) 26.4 (2.2) 11.9 (1.5) 7.1 (1.3) 1.9 100.0

Maine . . . . . . . . . . . . . . . . . . . . . . . . . 35.0 (2.3) 13.4 (1.6) 21.0 (2.1) 22.6 (2.0) 6.8 (1.3) 1.3 100.0

Maryland . . . . . . . . . . . . . . . . . . . . . . . 29.4 (1.6) 18.1 (1.4) 28.4 (1.7) 17.8 (1.4) 4.6 (0.8) 1.6 100.0

Baltimore City . . . . . . . . . . . . . . . . . . . 39.6 (3.2) 11.7 (2.1) 23.4 (3.1) 12.1 (2.2) 9.4 (2.3) 3.8 100.0

Prince George’s County............. § § § § § § §

Rest of Maryland ................. 27.6 (2.0) 17.9 (1.7) 30.3 (2.2) 19.0 (1.8) 3.8 (1.0) 1.4 100.0

Massachusetts.................... 24.1 (1.6) 17.0 (1.4) 34.3 (2.0) 15.0 (1.4) 8.4 (1.2) 1.1 100.0

Suffolk County .................. 37.5 (3.6) 17.5 (2.8) 19.8 (3.4) 12.2 (2.5) 11.2 (2.8) 1.6 100.0

Rest of Massachusetts ............. 22.6 (1.7) 16.9 (1.6) 36.0 (2.1) 15.4 (1.5) 8.1 (1.2) 1.1 100.0

Michigan ....................... 39.5 (1.7) 14.4 (1.2) 21.6 (1.6) 15.8 (1.3) 6.5 (1.0) 2.2 100.0

Wayne County .................. 46.6 (2.8) 16.9 (2.1) 16.8 (2.4) 9.4 (1.6) 5.8 (1.5) 4.6 100.0

Rest of Michigan ................. 39.0 (1.9) 14.2 (1.3) 21.9 (1.7) 16.3 (1.4) 6.6 (1.0) 2.1 100.0

Minnesota ...................... 35.7 (1.7) 17.5 (1.3) 26.5 (1.7) 13.8 (1.2) 5.0 (0.9) 1.4 100.0

Twin Cities counties4 .............. 36.7 (2.3) 18.3 (1.8) 27.9 (2.3) 12.5 (1.6) 3.2 (0.9) 1.3 100.0

Rest of Minnesota ................ 34.6 (2.5) 16.6 (1.9) 24.9 (2.5) 15.3 (1.9) 7.2 (1.5) 1.4 100.0

See footnotes at end of table.
National Health Statistics Reports n Number 70 n December 18, 2013 Page 9

Table 2. Modeled estimates (with standard errors) of the percent distribution of household telephone status for adults aged 18 and over,

by selected geographic areas: United States, 2012—Con.

No

Wireless- Wireless- Landline- Landline­ telephone

Geographic area only mostly Dual-use mostly only service1 Total

Percent (standard error)

Mississippi ...................... 49.4 (1.9) 12.6 (1.3) 16.0 (1.5) 14.2 (1.3) 5.8 (1.0) 2.1 100.0

Missouri ........................ 41.4 (2.0) 15.8 (1.4) 20.6 (1.7) 14.1 (1.4) 5.9 (1.0) 2.1 100.0

St. Louis County/City .............. 38.1 (3.2) 15.4 (2.3) 25.1 (3.2) 13.4 (2.2) 6.4 (1.9) 1.5 100.0

Rest of Missouri ................. 42.4 (2.4) 15.9 (1.7) 19.3 (2.0) 14.3 (1.7) 5.7 (1.2) 2.3 100.0

Montana ....................... § § § § § § §

Nebraska ....................... 37.5 (2.0) 15.3 (1.5) 25.0 (1.9) 12.9 (1.4) 7.7 (1.2) 1.6 100.0

Nevada ........................ 38.9 (1.8) 21.2 (1.5) 19.9 (1.6) 9.4 (1.0) 9.1 (1.2) 1.5 100.0

Clark County ................... 40.7 (2.2) 21.6 (1.9) 19.8 (1.9) 7.9 (1.2) 8.6 (1.4) 1.5 100.0

Rest of Nevada .................. 34.4 (2.9) 20.1 (2.4) 20.1 (2.6) 13.0 (2.0) 10.5 (2.1) 1.7 100.0

New Hampshire ................... 26.7 (1.9) 17.5 (1.6) 31.8 (2.1) 17.6 (1.6) 5.2 (1.0) 1.2 100.0

New Jersey. . . . . . . . . . . . . . . . . . . . . . 19.4 (1.4) 25.7 (1.6) 31.1 (1.8) 15.2 (1.3) 6.9 (1.0) 1.6 100.0

Essex County ................... 40.2 (3.7) 14.8 (2.6) 30.9 (3.9) *3.3 (1.3) 8.2 (2.4) 2.5 100.0

Rest of New Jersey ............... 18.8 (1.5) 26.0 (1.6) 31.1 (1.8) 15.5 (1.3) 6.9 (1.0) 1.6 100.0

New Mexico ..................... 36.8 (2.0) 13.2 (1.4) 21.7 (1.9) 9.4 (1.2) 15.1 (1.7) 3.8 100.0

Southern counties5

................ 40.1 (3.0) 9.4 (1.7) 22.7 (2.8) 9.2 (1.8) 15.3 (2.5) 3.3 100.0

Rest of New Mexico ............... 35.6 (2.5) 14.6 (1.8) 21.4 (2.3) 9.4 (1.5) 15.1 (2.1) 4.0 100.0

New York ....................... 23.5 (1.2) 17.7 (1.1) 30.9 (1.4) 16.5 (1.1) 9.4 (0.9) 2.0 100.0

City of New York counties6 ........... 29.4 (1.6) 16.7 (1.3) 30.3 (1.7) 10.2 (1.1) 10.6 (1.2) 2.7 100.0

Rest of New York................. 19.1 (1.6) 18.4 (1.6) 31.3 (2.0) 21.3 (1.7) 8.6 (1.3) 1.4 100.0

North Carolina .................... 34.7 (1.7) 12.7 (1.2) 26.2 (1.7) 17.2 (1.4) 7.6 (1.0) 1.7 100.0

North Dakota..................... 40.2 (1.7) 10.8 (1.1) 23.2 (1.5) 8.4 (1.0) 15.6 (1.3) 1.7 100.0

Ohio .......................... 36.8 (1.4) 16.1 (1.1) 24.0 (1.3) 15.8 (1.1) 5.3 (0.7) 2.1 100.0

Cuyahoga County ................ 38.1 (3.2) 18.4 (2.5) 19.3 (2.9) 16.2 (2.4) 6.1 (1.8) 1.9 100.0

Franklin County.................. 41.8 (3.7) 17.1 (2.8) 25.4 (3.8) 10.7 (2.4) † 2.4 100.0

Rest of Ohio.................... 35.9 (1.7) 15.6 (1.3) 24.4 (1.6) 16.4 (1.3) 5.5 (0.8) 2.1 100.0

Oklahoma....................... 39.0 (2.0) 19.2 (1.6) 21.2 (1.8) 11.3 (1.3) 7.6 (1.2) 1.8 100.0

Oregon ........................ 36.8 (2.2) 16.1 (1.7) 19.7 (1.9) 16.4 (1.7) 9.2 (1.4) 1.8 100.0

Pennsylvania..................... 26.2 (1.3) 18.7 (1.2) 26.4 (1.4) 18.4 (1.2) 8.7 (0.9) 1.5 100.0

Allegheny County ................ 40.4 (3.4) 12.6 (2.3) 24.5 (3.3) 14.4 (2.4) *6.8 (2.0) 1.4 100.0

Philadelphia County ............... 37.8 (2.9) 18.1 (2.2) 21.8 (2.7) 13.0 (2.0) 6.6 (1.7) 2.7 100.0

Rest of Pennsylvania .............. 22.7 (1.6) 19.5 (1.5) 27.4 (1.7) 19.7 (1.5) 9.3 (1.2) 1.4 100.0

Rhode Island..................... 24.9 (1.8) 22.0 (1.7) 28.5 (1.9) 15.9 (1.5) 6.9 (1.1) 1.7 100.0

South Carolina.................... 39.0 (2.1) 16.3 (1.5) 18.7 (1.8) 16.0 (1.5) 8.0 (1.2) 2.0 100.0

South Dakota .................... § § § § § § §

Tennessee ...................... 37.8 (1.7) 16.7 (1.3) 24.6 (1.7) 13.3 (1.2) 5.4 (0.9) 2.1 100.0

Davidson County ................. 51.2 (3.6) 16.5 (2.6) 16.1 (3.0) 10.4 (2.2) *4.1 (1.7) 1.7 100.0

Shelby County .................. 46.2 (3.3) 17.9 (2.5) 19.7 (2.9) 8.7 (1.8) *5.6 (1.8) 1.9 100.0

Rest of Tennessee ................ 34.5 (2.1) 16.5 (1.6) 26.7 (2.1) 14.6 (1.6) 5.6 (1.1) 2.2 100.0

Texas ......................... 44.5 (1.2) 18.5 (0.9) 18.0 (1.0) 9.4 (0.7) 7.5 (0.6) 2.0 100.0

Bexar County ................... 42.6 (2.5) 16.1 (1.9) 17.7 (2.1) 5.8 (1.2) 16.0 (2.1) 1.7 100.0

Dallas County ................... 56.5 (2.6) 16.4 (1.9) 13.1 (1.9) 7.1 (1.3) 5.2 (1.3) 1.8 100.0

El Paso County .................. § § § § § § §

Harris County ................... 47.0 (2.1) 20.7 (1.7) 16.4 (1.7) 9.7 (1.3) 3.7 (0.9) 2.5 100.0

Rest of Texas ................... 42.9 (1.6) 19.0 (1.2) 19.3 (1.3) 10.2 (1.0) 6.7 (0.8) 1.9 100.0

Utah .......................... 46.6 (1.9) 15.2 (1.3) 22.1 (1.6) 10.2 (1.1) 4.1 (0.8) 1.8 100.0

Vermont ........................ 29.9 (1.9) 11.5 (1.3) 23.9 (1.8) 22.4 (1.7) 11.1 (1.4) 1.2 100.0

Virginia ........................ 32.0 (1.9) 22.1 (1.7) 24.0 (1.9) 14.6 (1.4) 5.3 (1.0) 1.9 100.0

Washington...................... 39.4 (1.6) 17.4 (1.2) 22.1 (1.5) 13.4 (1.1) 6.3 (0.9) 1.4 100.0

Eastern counties7 ................ 34.2 (2.4) 19.4 (2.0) 22.8 (2.3) 15.8 (1.9) 6.2 (1.4) 1.7 100.0

King County .................... 46.0 (2.9) 16.9 (2.2) 21.0 (2.6) 9.8 (1.7) *4.7 (1.4) 1.5 100.0

Rest of Washington ............... 37.6 (2.4) 16.7 (1.9) 22.5 (2.3) 14.6 (1.8) 7.4 (1.5) 1.2 100.0

West Virginia..................... 30.2 (2.4) 11.1 (1.6) 14.6 (1.9) 24.8 (2.2) 16.7 (2.1) 2.5 100.0

Wisconsin....................... 39.0 (2.0) 11.3 (1.3) 20.2 (1.7) 18.0 (1.6) 9.8 (1.3) 1.7 100.0

Milwaukee County ................ § § § § § § §

Rest of Wisconsin ................ 36.6 (2.2) 11.9 (1.5) 20.3 (2.0) 19.5 (1.8) 10.1 (1.5) 1.5 100.0

Wyoming ....................... § § § § § § §

* Estimate has a relative standard error greater than 30% and less than or equal to 50% and is considered unreliable.

§ Model-based estimates for Maryland-Prince George’s County, Montana, South Dakota, Texas-El Paso County, Wisconsin-Milwaukee County, and Wyoming are not reported because, for at least

one telephone service use category, direct estimates from the National Health Information Survey were more than double or less than one-half the synthetic estimate. These differences between

two components of the model-based estimates suggest that the direct estimates for these areas may be biased. Biased estimates violate a key model-based estimation assumption.

† Estimate has a relative standard error greater than 50% and is not shown.

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 2011 American Community Survey

estimate for this proportion.

2Includes Butte, Colusa, Del Norte, Glenn, Humboldt, Lake, Lassen, Mendocino, Modoc, Plumas, Shasta, Sierra, Siskiyou, Tehama, and Trinity.
Page 10 National Health Statistics Reports n Number 70 n December 18, 2013

3Includes Adams, Arapahoe, Denver, and Douglas. 4Includes Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington. 5Includes Catron, Chaves, Curry, De Baca, Dona Ana, Eddy, Grant, Hidalgo, Lea, Lincoln, Luna, Otero, Roosevelt, Sierra, and Socorro. 6Includes Bronx, Kings, New York, Queens, and Richmond. 7Includes Adams, Asotin, Benton, Chelan, Columbia, Douglas, Ferry, Franklin, Garfield, Grant, Kittitas, Klickitat, Lincoln, Okanogan, Pend Oreille, Spokane, Stevens, Walla Walla, Whitman, and

Yakima.

NOTE: Estimates were calculated by NORC at the University of Chicago.

SOURCES: CDC/NCHS, National Health Interview Survey, 2007–2012; U.S. Census Bureau, American Community Survey, 2006–2011; and infoUSA.com consumer database, 2007–2012.
National Health Statistics Reports n Number 70 n December 18, 2013 Page 11

Table 3. Modeled estimates (with standard errors) of the percent distribution of household telephone status for children under age 18, by

selected geographic areas: United States, 2012

No

Wireless- Wireless- Landline- Landline­ telephone

Geographic area only mostly Dual-use mostly only service1 Total

Percent (standard error)

Alabama ....................... 49.6 (3.2) 19.8 (2.7) 18.5 (2.9) 6.6 (1.6) *3.5 (1.5) 2.1 100.0

Jefferson County ................. 55.2 (4.4) 20.3 (3.7) 16.4 (3.7) † † 1.4 100.0

Rest of Alabama ................. 48.7 (3.7) 19.7 (3.1) 18.8 (3.3) 7.2 (1.9) *3.5 (1.6) 2.2 100.0

Alaska ......................... 25.7 (3.7) 27.6 (3.9) 30.6 (4.2) 10.1 (2.6) *5.1 (2.1) 0.9 100.0

Arizona ........................ 49.9 (2.7) 19.7 (2.3) 16.3 (2.3) 3.7 (0.9) 8.4 (1.9) 2.0 100.0

Maricopa County ................. 52.0 (3.7) 18.6 (3.0) 15.7 (3.0) † 10.9 (2.8) 1.6 100.0

Rest of Arizona .................. 46.3 (3.9) 21.4 (3.5) 17.4 (3.4) 7.8 (2.0) *4.2 (2.0) 2.8 100.0

Arkansas ....................... 59.8 (3.1) 16.3 (2.5) 14.1 (2.5) *4.1 (1.3) *3.0 (1.3) 2.8 100.0

California ....................... 38.2 (1.2) 22.9 (1.1) 24.1 (1.1) 7.4 (0.6) 6.0 (0.6) 1.4 100.0

Alameda County ................. 37.0 (4.3) 22.7 (4.0) 34.2 (4.9) *4.9 (1.8) † 0.7 100.0

Fresno County .................. 36.1 (3.6) 11.5 (2.5) 28.3 (3.8) 8.1 (2.1) 14.7 (3.3) 1.3 100.0

Los Angeles County ............... 36.7 (2.2) 24.4 (2.0) 23.5 (2.0) 7.2 (1.2) 6.5 (1.3) 1.6 100.0

Northern counties2 ................ 38.2 (4.4) 18.3 (3.8) 25.8 (4.6) 8.6 (2.4) *7.6 (3.1) 1.5 100.0

San Bernardino County ............. 45.8 (3.9) 22.9 (3.5) 19.8 (3.5) 6.9 (1.9) *3.4 (1.7) 1.1 100.0

San Diego County ................ 29.5 (3.0) 23.4 (2.9) 28.4 (3.3) 8.2 (1.8) 8.2 (2.1) 2.3 100.0

Santa Clara County ............... 34.9 (3.7) 24.1 (3.5) 31.7 (4.1) *3.9 (1.5) *4.6 (2.0) 0.7 100.0

Rest of California................. 40.0 (2.0) 22.9 (1.7) 22.2 (1.7) 7.9 (1.1) 5.6 (1.0) 1.3 100.0

Colorado ....................... 45.1 (2.8) 21.1 (2.4) 23.7 (2.6) 6.1 (1.3) *2.2 (1.0) 1.9 100.0

City of Denver counties3 ............ 46.3 (3.9) 20.2 (3.3) 24.5 (3.7) *5.5 (1.7) † 1.4 100.0

Rest of Colorado ................. 44.2 (3.8) 21.7 (3.3) 23.1 (3.6) 6.5 (1.9) † 2.2 100.0

Connecticut...................... 25.4 (2.6) 20.6 (2.5) 32.9 (3.0) 11.8 (1.9) 8.4 (1.9) 0.8 100.0

Delaware ....................... 26.8 (3.3) 28.5 (3.5) 35.5 (3.9) 5.9 (1.8) † 1.2 100.0

District of Columbia................. 42.2 (4.4) 19.4 (3.7) 25.3 (4.0) *3.8 (1.7) *7.2 (2.6) 2.2 100.0

Florida. . . . . . . . . . . . . . . . . . . . . . . . . 49.2 (1.8) 21.1 (1.6) 21.4 (1.6) 2.6 (0.6) 2.7 (0.7) 3.1 100.0

Miami-Dade County ............... 53.2 (4.6) 18.3 (3.8) 21.1 (4.3) † † 2.9 100.0

Duval County ................... 54.2 (3.3) 18.6 (2.8) 18.6 (2.9) *1.9 (0.9) † 5.7 100.0

Orange County .................. 51.4 (4.6) 23.3 (4.2) 21.1 (4.4) † † 1.7 100.0

Rest of Florida .................. 47.7 (2.3) 21.5 (2.0) 22.0 (2.1) 3.0 (0.8) 3.0 (0.9) 2.7 100.0

Georgia ........................ 45.9 (2.4) 24.6 (2.2) 18.7 (2.0) 3.9 (1.0) 3.8 (1.1) 3.0 100.0

Fulton/DeKalb counties ............. 48.8 (4.4) 25.1 (4.1) 22.8 (4.3) † † 2.1 100.0

Rest of Georgia.................. 45.4 (2.7) 24.5 (2.5) 18.0 (2.3) 4.5 (1.1) 4.4 (1.3) 3.2 100.0

Hawaii ......................... 43.8 (3.9) 18.6 (3.2) 28.6 (3.9) *3.7 (1.4) *3.5 (1.7) 1.7 100.0

Idaho ......................... 62.2 (2.6) 9.1 (1.6) 17.8 (2.2) 7.0 (1.4) † 2.7 100.0

Illinois ......................... 42.4 (2.3) 21.3 (2.0) 26.5 (2.2) 5.9 (1.1) *2.3 (0.8) 1.6 100.0

Cook County ................... 42.3 (3.2) 16.2 (2.5) 32.4 (3.3) *4.1 (1.3) *2.5 (1.2) 2.4 100.0

Madison/St. Clair counties ........... 45.6 (5.5) 21.4 (4.7) 25.9 (5.6) *5.8 (2.4) † 1.2 100.0

Rest of Illinois................... 42.2 (2.9) 22.7 (2.6) 25.0 (2.8) 6.4 (1.4) *2.3 (1.0) 1.4 100.0

Indiana ........................ 46.3 (2.9) 16.0 (2.2) 19.5 (2.5) 6.5 (1.4) 8.3 (1.9) 3.4 100.0

Lake County.................... 44.5 (5.2) 18.9 (4.2) 21.0 (4.8) *5.5 (2.3) *8.0 (3.6) 2.1 100.0

Marion County .................. 52.8 (4.7) 11.0 (3.1) 21.0 (4.3) *5.2 (2.0) *5.9 (2.8) 4.1 100.0

Rest of Indiana .................. 45.3 (3.5) 16.6 (2.8) 19.1 (3.1) 6.9 (1.7) 8.7 (2.4) 3.4 100.0

Iowa . . . . . . . . . . . . . . . . . . . . . . . . . . 45.4 (3.2) 27.5 (3.0) 18.0 (2.7) *3.3 (1.1) *2.7 (1.2) 3.0 100.0

Kansas ........................ 52.5 (2.7) 15.9 (2.1) 21.9 (2.4) 5.2 (1.2) *3.2 (1.1) 1.4 100.0

Johnson/Wyandotte counties ......... 41.5 (4.8) 17.6 (3.9) 32.9 (5.2) *5.0 (2.0) † 1.1 100.0

Rest of Kansas .................. 56.4 (3.2) 15.3 (2.4) 18.0 (2.7) 5.3 (1.4) *3.6 (1.4) 1.4 100.0

Kentucky ....................... 52.5 (3.2) 16.2 (2.5) 14.6 (2.5) 9.4 (1.8) *4.3 (1.5) 3.0 100.0

Louisiana ....................... 45.1 (3.1) 21.5 (2.7) 24.4 (3.0) 4.8 (1.3) † 2.2 100.0

Maine . . . . . . . . . . . . . . . . . . . . . . . . . 41.6 (3.3) 17.9 (2.7) 21.8 (3.0) 16.1 (2.5) † 0.6 100.0

Maryland . . . . . . . . . . . . . . . . . . . . . . . 33.6 (2.4) 22.7 (2.3) 30.6 (2.7) 9.7 (1.6) † 2.1 100.0

Baltimore City . . . . . . . . . . . . . . . . . . . 51.8 (5.3) 12.5 (3.6) 22.0 (4.9) *6.7 (2.5) † 5.4 100.0

Prince George’s County............. § § § § § § §

Rest of Maryland ................. 30.0 (3.0) 23.3 (2.9) 32.8 (3.4) 10.6 (2.0) † 1.9 100.0

Massachusetts.................... 26.7 (2.7) 22.3 (2.7) 37.9 (3.3) 8.6 (1.7) *3.3 (1.3) 1.2 100.0

Suffolk County .................. 48.9 (6.8) 22.0 (5.8) *20.2 (6.1) † † 2.8 100.0

Rest of Massachusetts ............. 24.9 (2.8) 22.3 (2.9) 39.4 (3.5) 8.9 (1.8) *3.4 (1.4) 1.1 100.0

Michigan ....................... 44.2 (2.6) 18.6 (2.2) 23.5 (2.5) 8.1 (1.5) *3.2 (1.1) 2.3 100.0

Wayne County .................. 59.6 (4.1) 19.5 (3.7) 12.4 (3.4) *2.8 (1.3) † 3.5 100.0

Rest of Michigan ................. 42.9 (2.8) 18.6 (2.3) 24.5 (2.7) 8.6 (1.6) *3.3 (1.2) 2.2 100.0

Minnesota ...................... 36.7 (2.6) 22.5 (2.4) 30.0 (2.8) 8.3 (1.5) † 1.2 100.0

Twin Cities counties4 .............. 37.0 (3.7) 19.9 (3.2) 33.1 (4.0) 9.0 (2.1) † 0.8 100.0

Rest of Minnesota ................ 36.3 (3.7) 25.7 (3.6) 26.1 (3.8) 7.4 (2.0) † 1.5 100.0

See footnotes at end of table.
Page 12 National Health Statistics Reports n Number 70 n December 18, 2013

Table 3. Modeled estimates (with standard errors) of the percent distribution of household telephone status for children under age 18, by

selected geographic areas: United States, 2012—Con.

No

Wireless- Wireless- Landline- Landline­ telephone

Geographic area only mostly Dual-use mostly only service1 Total

Percent (standard error)

Mississippi ...................... 63.4 (3.0) 15.4 (2.4) 11.3 (2.2) 5.5 (1.4) *2.5 (1.1) 1.9 100.0

Missouri ........................ 55.2 (3.0) 17.8 (2.4) 16.4 (2.4) 5.9 (1.4) *2.3 (1.1) 2.5 100.0

St. Louis County/City .............. 39.2 (4.8) 22.9 (4.4) 28.6 (5.1) *6.5 (2.3) † 2.1 100.0

Rest of Missouri ................. 59.4 (3.5) 16.5 (2.8) 13.1 (2.6) 5.8 (1.6) † 2.5 100.0

Montana ....................... § § § § § § §

Nebraska ....................... 43.7 (3.2) 19.7 (2.7) 26.8 (3.2) 5.8 (1.5) *2.4 (1.2) 1.6 100.0

Nevada ........................ 41.7 (2.8) 27.2 (2.6) 20.8 (2.5) 4.0 (1.1) *4.7 (1.4) 1.7 100.0

Clark County ................... 40.6 (3.4) 25.0 (3.1) 22.9 (3.1) *4.0 (1.3) *6.1 (1.9) 1.5 100.0

Rest of Nevada .................. 44.6 (5.0) 33.5 (4.8) 15.0 (3.9) *3.9 (1.9) † 2.2 100.0

New Hampshire ................... 30.3 (3.2) 23.4 (3.1) 32.7 (3.6) 9.8 (2.1) † 1.2 100.0

New Jersey. . . . . . . . . . . . . . . . . . . . . . 20.6 (2.2) 31.2 (2.7) 33.2 (2.9) 8.5 (1.6) 4.8 (1.4) 1.7 100.0

Essex County ................... 38.2 (5.0) 20.4 (4.3) 33.1 (5.5) † † 4.3 100.0

Rest of New Jersey ............... 19.9 (2.3) 31.6 (2.8) 33.2 (3.0) 8.8 (1.6) *4.8 (1.5) 1.6 100.0

New Mexico ..................... 53.4 (3.3) 15.2 (2.5) 18.7 (2.8) *2.7 (1.1) *5.1 (1.8) 4.8 100.0

Southern counties5

................ 59.1 (4.6) 10.4 (2.9) 20.7 (4.3) † † 4.5 100.0

Rest of New Mexico ............... 51.2 (4.1) 17.1 (3.2) 17.9 (3.5) *3.4 (1.5) *5.5 (2.3) 5.0 100.0

New York ....................... 26.8 (1.9) 21.0 (1.8) 34.5 (2.2) 10.7 (1.3) 4.9 (1.1) 2.0 100.0

City of New York counties6 ........... 29.8 (2.7) 20.3 (2.5) 34.7 (3.0) 7.3 (1.5) 5.3 (1.5) 2.7 100.0

Rest of New York................. 24.7 (2.6) 21.6 (2.5) 34.3 (3.1) 13.1 (2.0) *4.7 (1.4) 1.6 100.0

North Carolina .................... 47.1 (2.6) 17.8 (2.1) 23.2 (2.4) 6.9 (1.3) *3.4 (1.1) 1.6 100.0

North Dakota..................... 50.0 (3.2) 16.3 (2.4) 25.2 (2.9) † 6.8 (1.8) 1.5 100.0

Ohio .......................... 44.7 (2.4) 18.1 (1.9) 22.8 (2.2) 8.5 (1.3) *2.9 (1.0) 3.0 100.0

Cuyahoga County ................ 37.0 (4.2) 20.5 (3.8) 25.5 (4.4) 14.2 (3.0) † 2.5 100.0

Franklin County.................. 43.1 (4.5) 19.7 (3.8) 28.5 (4.7) *5.4 (2.0) † 1.6 100.0

Rest of Ohio.................... 46.0 (2.9) 17.5 (2.3) 21.7 (2.6) 8.2 (1.6) *3.4 (1.2) 3.2 100.0

Oklahoma....................... 50.9 (3.4) 24.8 (3.0) 15.1 (2.6) *3.3 (1.2) *4.6 (1.6) 1.3 100.0

Oregon ........................ 41.5 (3.4) 21.4 (3.0) 22.3 (3.2) 7.2 (1.8) *5.7 (1.9) 1.9 100.0

Pennsylvania..................... 31.4 (2.1) 24.6 (2.1) 29.9 (2.4) 8.5 (1.3) 3.6 (1.0) 2.1 100.0

Allegheny County ................ 43.9 (5.4) 21.7 (4.7) 28.6 (5.6) *4.7 (2.2) † 0.9 100.0

Philadelphia County ............... 46.8 (4.4) 17.1 (3.4) 22.3 (4.1) 8.5 (2.3) † 2.7 100.0

Rest of Pennsylvania .............. 27.6 (2.5) 26.1 (2.6) 31.2 (2.8) 8.9 (1.6) *4.1 (1.3) 2.2 100.0

Rhode Island..................... 34.8 (3.4) 27.9 (3.3) 25.4 (3.4) 6.5 (1.8) *3.4 (1.5) 1.9 100.0

South Carolina.................... 54.5 (3.3) 19.0 (2.7) 16.2 (2.6) 5.8 (1.5) *2.5 (1.2) 2.1 100.0

South Dakota .................... § § § § § § §

Tennessee ...................... 52.3 (2.6) 18.1 (2.1) 20.6 (2.4) 5.9 (1.3) † 2.3 100.0

Davidson County ................. 61.8 (5.4) 17.6 (4.2) 17.5 (4.6) † † 2.1 100.0

Shelby County .................. 54.1 (4.7) 22.4 (4.2) 16.8 (4.0) † † 1.4 100.0

Rest of Tennessee ................ 50.7 (3.3) 17.2 (2.6) 21.8 (3.0) 7.2 (1.7) † 2.5 100.0

Texas ......................... 54.2 (1.7) 21.6 (1.5) 14.7 (1.3) 4.1 (0.7) 3.4 (0.7) 2.1 100.0

Bexar County ................... 57.0 (3.9) 18.4 (3.2) 16.4 (3.2) † *5.9 (2.2) 1.6 100.0

Dallas County ................... 65.9 (3.6) 17.6 (3.0) 10.7 (2.6) *3.6 (1.4) † 2.0 100.0

El Paso County .................. § § § § § § §

Harris County ................... 54.8 (2.9) 22.6 (2.5) 13.5 (2.1) 4.7 (1.2) *2.1 (1.0) 2.4 100.0

Rest of Texas ................... 52.0 (2.2) 22.8 (1.9) 15.3 (1.7) 4.6 (0.9) 3.4 (0.9) 1.9 100.0

Utah .......................... 48.5 (2.6) 19.7 (2.1) 23.5 (2.3) 4.5 (1.0) *1.9 (0.8) 1.9 100.0

Vermont ........................ 24.5 (3.2) 13.5 (2.6) 32.8 (3.7) 20.7 (3.0) 8.2 (2.3) 0.2 100.0

Virginia ........................ 36.2 (2.7) 24.3 (2.5) 27.6 (2.7) 6.9 (1.4) *3.1 (1.1) 2.0 100.0

Washington...................... 41.8 (2.2) 20.6 (1.9) 23.9 (2.1) 7.8 (1.2) 4.6 (1.2) 1.3 100.0

Eastern counties7 ................ 44.2 (3.7) 23.4 (3.3) 21.5 (3.4) 7.2 (1.9) † 1.8 100.0

King County .................... 41.0 (4.0) 19.3 (3.5) 31.9 (4.4) *4.7 (1.7) † 1.4 100.0

Rest of Washington ............... 41.1 (3.4) 19.9 (3.0) 20.7 (3.2) 9.8 (2.0) 7.5 (2.2) 1.0 100.0

West Virginia..................... 42.7 (3.6) 11.9 (2.4) 13.9 (2.7) 18.6 (2.8) 10.0 (2.5) 2.9 100.0

Wisconsin....................... 44.5 (3.0) 17.4 (2.5) 24.3 (3.0) 8.6 (1.7) *2.6 (1.2) 2.7 100.0

Milwaukee County ................ § § § § § § §

Rest of Wisconsin ................ 41.0 (3.5) 18.5 (2.9) 25.6 (3.5) 9.9 (2.1) † 2.5 100.0

Wyoming ....................... § § § § § § §

* Estimate has a relative standard error greater than 30% and less than or equal to 50% and is considered unreliable.

† Estimate has a relative standard error greater than 50% and is not shown.

§ Model-based estimates for Maryland-Prince George’s County, Montana, South Dakota, Texas-El Paso County, Wisconsin-Milwaukee County, and Wyoming are not reported because, for at least

one telephone service use category, direct estimates from the National Health Information Survey were more than double or less than one-half the synthetic estimate. These differences between

two components of the model-based estimates suggest that the direct estimates for these areas may be biased. Biased estimates violate a key model-based estimation assumption. 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 2011 American Community

Survey estimate for this proportion.
National Health Statistics Reports n Number 70 n December 18, 2013 Page 13

2Includes Butte, Colusa, Del Norte, Glenn, Humboldt, Lake, Lassen, Mendocino, Modoc, Plumas, Shasta, Sierra, Siskiyou, Tehama, and Trinity. 3Includes Adams, Arapahoe, Denver, and Douglas. 4Includes Anoka, Carver, Dakota, Hennepin, Ramsey, Scott, and Washington. 5Includes Catron, Chaves, Curry, De Baca, Dona Ana, Eddy, Grant, Hidalgo, Lea, Lincoln, Luna, Otero, Roosevelt, Sierra, and Socorro. 6Includes Bronx, Kings, New York, Queens, and Richmond. 7Includes Adams, Asotin, Benton, Chelan, Columbia, Douglas, Ferry, Franklin, Garfield, Grant, Kittitas, Klickitat, Lincoln, Okanogan, Pend Oreille, Spokane, Stevens, Walla Walla, Whitman, and

Yakima.

NOTE: Estimates were calculated by NORC at the University of Chicago.

SOURCES: CDC/NCHS, National Health Interview Survey, 2007–2012; U.S. Census Bureau, American Community Survey, 2006–2011; and infoUSA.com consumer database, 2007–2012.
Page 14 National Health Statistics Reports n Number 70 n December 18, 2013

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 December

2012, and on American Community

Survey (ACS) data collected from 2006

through 2011. 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.

National Health Interview Survey

NHIS is a 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 interview survey is

administered by trained field

representatives from the U.S. Census

Bureau, under contract to NCHS. NHIS

interviews are conducted continuously

throughout the year to collect

information that is used to assess

progress toward meeting national health

objectives. Survey content includes

health status, health risk factors,

health-related behaviors, health care

access, and health care utilization. NHIS

also includes questions about

demographic and socioeconomic

characteristics, household telephones,

and whether anyone in the household

has a wireless telephone.

The sample for NHIS is stratified

by state, which allows NHIS data to be

used 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 75,150 persons in

2007, for 73,749 persons in 2008, for

88,053 persons in 2009, for 89,620

persons in 2010, for 101,449 persons in

2011, and for 107,723 persons in 2012.

Fewer than 0.5% of persons with

completed NHIS family-level interviews

had missing data for household

telephone status.

NHIS was used to derive direct

estimates for each telephone service use

category by age group (adults aged 18

and over or children under age 18),

small area, and 6-month period. These

estimates were the dependent variables

in the statistical models. 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.

American Community Survey

ACS is a multistage probability

survey that provides data on households

and group quarters. In this report, a

subset of the full ACS sample—the

civilian noninstitutionalized

population—is used 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 staterepresentative 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, 2012 ACS data will not be

released until Fall 2013. 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; data for 2008 were

used in models for 2009; data for 2009

were used in models for 2010; data for

2010 were used in models for 2011; and

data for 2011 were used in models for

2012. Moreover, ACS was the source

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.

Auxiliary data source

The numbers of listed telephone

lines within each state for 2007–2012

were obtained from a consumer database

compiled by infoUSA.com (Infogroup,

Papillion, NE). 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 the

selected calendar year. The count of

listed telephone lines was divided by the

number of civilian noninstitutionalized

persons and, because these proportions

were available at the state level only, the

same state-specific proportion was used

in the model for each small area in the

state.

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.’’ An

NHIS 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

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
National Health Statistics Reports n Number 70 n December 18, 2013 Page 15

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 the 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 telephones, 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 ‘‘landlinemostly’’ 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 wirelessmostly nor landline-mostly. That is, they

receive some calls on cell phones and

some on landline telephones.

Small-area model

Detailed descriptions of the

small-area model and the derivation of

the model-based estimates and standard

errors are provided elsewhere (2). As

noted above, 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

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.

NHIS and ACS sampling weights

adjust for the probability of selection of

each household, and 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.

The approach used to create the

model-based estimates can produce

substantially biased prevalence estimates

and unstable variance estimates when

the direct estimate from NHIS is based

on small sample sizes, when that sample

is drawn from only a few geographic

areas, and when those few geographic

areas are not representative of the state

or county of interest. To identify

potentially problematic model-based

estimates, the person-level prevalence

ratio of the direct survey estimate to the

synthetic regression-based estimate was

examined for each telephone service use

category and for each small area. Ratios

were computed across all 6-month

periods. If the ratios for any telephone

service use category were greater than

two or less than one-half, then all

model-based estimates for that reporting

area were suppressed from Tables 1–3 in

this report. This occurred for six small

areas: Maryland-Prince George’s

County, Montana, South Dakota,

Texas-El Paso County, WisconsinMilwaukee County, and Wyoming. For

these areas, the synthetic estimates

derived from the regression model are

presented in the Table below.

Table. Synthetic regression-based estimates (with standard errors) of the percent

selected geographic areas where model-based estimates are not reported: United

distribution of

States, 2012

household telephone status, by age, for

Age and geographic area

WirelessonlyWirelessmostly Dual-useLandlinemostlyLandlineonly

No

telephone

service1 Total

Adults aged 18 and over

Maryland-Prince George’s County ..........

Montana ..........................

South Dakota .......................

Texas-El Paso County .................

Wisconsin-Milwaukee County .............

Wyoming .........................

Children under age 18

Maryland-Prince George’s County ..........

Montana ..........................

South Dakota .......................

Texas-El Paso County .................

Wisconsin-Milwaukee County .............

Wyoming .........................

32.2

39.9

38.6

43.8

44.1

39.3

35.6

49.7

46.2

55.9

51.5

47.3

(5.7)

(6.1)

(5.9)

(6.3)

(6.1)

(6.1)

(7.5)

(8.1)

(7.7)

(7.4)

(8.1)

(8.0)

21.3

16.9

15.1

14.3

13.7

15.7

24.8

22.9

19.3

*15.2

*16.4

21.0

(4.3)

(3.8)

(3.6)

(3.7)

(3.5)

(3.7)

(6.4)

(6.2)

(5.6)

(5.0)

(5.4)

(5.9)

29.6

17.7

21.8

23.2

20.8

19.8

31.2

*15.6

22.3

*17.7

*21.1

*17.9

Percent

(6.0)

(4.9)

(5.1)

(5.5)

(5.1)

(5.1)

(7.8)

(6.0)

(6.5)

(6.0)

(6.6)

(6.3)

(standard error)

13.3 (3.6)

14.7 (3.8)

13.9 (3.7)

†

*9.7 (3.2)

13.3 (3.7)

†

†

†

†

†

†

†

†

†

†

†

†

†

†

†

†

†

†

1.0

2.4

2.0

3.8

2.4

2.1

1.0

2.5

2.5

5.2

3.4

1.7

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

† Estimate has a relative standard error greater than 50% and is not shown.

* Estimate has a relative standard error greater than 30% and less than or equal to 50% and is considered unreliable. 1The proportion of persons living in households with no telephone service was not modeled. Other proportions were adjusted so that this estimate agreed with the 2011 American Community

Survey estimate for this proportion.

NOTES: Model-based estimates for these six areas are not reported in the main-text tables because the direct National Health Interview Survey estimates (a component of the model-based

estimates) may be biased. This table presents synthetic estimates (another component of the model-based estimates) for these areas. These synthetic estimates are the best available estimates

for these areas but should be used with caution because they are generally less reliable than the model-based estimates reported for other geographic areas. Estimates were calculated by NORC

at the University of Chicago.

SOURCES: U.S. Census Bureau, American Community Survey, 2006–2011; and infoUSA.com consumer database, 2007–2012.
U.S. DEPARTMENT OF

HEALTH & HUMAN SERVICES

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Acknowledgments

NCHS thanks NORC at the University of Chicago and the State Health Access Data Assistance Center (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 developed the statistical models. The authors thank Marketing Systems Group for providing the auxiliary data on

listed telephone numbers, and the staff of the NCHS Research Data Center for their assistance.

Suggested citation

Blumberg SJ, Ganesh N, Luke JV, Gonzales

G. Wireless substitution: State-level estimates

from the National Health Interview Survey,

2012. National health statistics reports; no 70.

Hyattsville, MD: National Center for Health

Statistics. 2013.

Copyright information

All material appearing in this report is in the

public domain and may be reproduced or

copied without permission; citation as to

source, however, is appreciated.

National Center for Health Statistics

Charles J. Rothwell, M.S., Director
 

Jennifer H. Madans, Ph.D., Associate Director
 

for Science
 

Division of Health Interview Statictics

Jane F. Gentleman, Ph.D., Director

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DHHS Publication No. 2014–1250 • CS243817