National Center for Health 

Statistics Data Presentation 

Standards for Proportions 

Vital and Health StatisticsSeries 2, Number 175 August 2017 
 

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Parker JD, Talih M, Malec DJ, et al. National Center for Health Statistics Data 

Presentation Standards for Proportions. National Center for Health Statistics. Vital 

Health Stat 2(175). 2017. 

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Names: National Center for Health Statistics (U.S.), issuing body. 

Title: National Center for Health Statistics Data Presentation Standards for 

 Proportions. 

Other titles: Vital and health statistics. Series 2, Data evaluation and 

 methods research ; no. 175. | DHHS publication ; no. (PHS) 2017-1375.

 0276-4733 

Description: Hyattsville, Maryland : U.S. Department of Health and Human 

 Services, Centers for Disease Control and Prevention, National Center for 

 Health Statistics, August 2017. | Series: Vital and health statistics.

 Series 2, Data evaluation and methods research ; number 175 | Series: DHHS 

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Identifiers: LCCN 2017033531 | ISBN 0840606826 (pbk. : alk. paper) 

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Vital and Health Statistics
 

Series 2, Number 175 

National Center for Health 

Statistics Data Presentation 

Standards for Proportions 

Data Evaluation and Methods Research 

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES 

Centers for Disease Control and Prevention 

National Center for Health Statistics 

Hyattsville, Maryland 

August 2017 

DHHS Publication No. 2017–1375 
 

 

National Center for Health Statistics 

Charles J. Rothwell, M.S., M.B.A., Director 

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

Division of Research and Methodology 

Charles J. Rothwell, M.S., M.B.A., Acting Director 

Donald J. Malec, Ph.D., Associate Director for Science 

Office of Analysis and Epidemiology 

Irma E. Arispe, Ph.D., Director 

Makram Talih, Ph.D., Associate Director for Science 

Division of Health and Nutrition Examination Surveys 

Kathryn S. Porter, M.D., M.S., Director 

Ryne Paulose-Ram, Ph.D., Associate Director for Science 

Division of Health Interview Statistics 

Marcie L. Cynamon, Director 

Stephen J. Blumberg, Ph.D., Associate Director for Science 

Division of Health Care Statistics 

Denys T. Lau, Ph.D., Acting Director 

Alexander Strashny, Ph.D., Associate Director for Science 

Division of Vital Statistics 

Delton Atkinson, M.P.H., M.P.H., P.M.P., Director 

Hanyu Ni, Ph.D., M.P.H., Associate Director for Science 
Contents
 

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv 

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1 

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1 

NCHS Data Presentation Standards for Proportions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2 

Sample Size. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2 

Confidence Intervals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3 

Degrees of Freedom . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4 

Complementary Proportions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4 

Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5 

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6 

Appendix I. Figure. Implementation of NCHS Data Presentation Standards for Proportions . . . . . . . . . . . . . . . . . . . . .7 

Appendix II. Examples of the Application of NCHS Data Presentation Standards for Proportions . . . . . . . . . . . . . . . . . .8 

Text Table 

NCHS Data Presentation Standards for Proportions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2 

Appendix Tables 

I. Percentage of children aged 8–17 years with elevated and normal or borderline blood pressure, by race and 

Hispanic origin: United States, 2013–2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8 

II. Percentage of adults aged 60 and over who are overweight, by sex and race and Hispanic origin: 

United States, 2013–2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9 

III. Percentage of adults aged 18 and over with hearing difficulties, by race and Hispanic origin and 

family income: United States, 2013 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 

IV. Percentage of ambulatory care visits, by setting type according to diagnosis: United States, 2009–2010 . . . . . . . . . . 11 

V. Percentage of fathers aged 15–44 with children under age 5 years who live with their children, 

by how often they played with their children in the last 4 weeks and father’s age: United States, 2006–2010. . . . . . . . 12 

VI. Proportion of triplet and higher-order multiple births, by age and race and Hispanic origin of mother for 

mothers aged 15–19 and 40–54: United States, 2015 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 

iii 
Acknowledgments 

The authors would like to 

acknowledge the contribution of Cynthia 

A. Reuben, NCHS Office of Analysis and 

Epidemiology and the contributions of 

the following people who participated in 

sessions on this topic in 2015 at the Joint 

Statistical Meetings and the National 

Center for Health Statistics (NCHS) 

National Conference on Health Statistics: 

Michael Davern, NORC at the University 

of Chicago; Jennifer Madans, NCHS 

Associate Director for Science; Virginia 

Lesser, Oregon State University; Ron 

Jarmin, U.S. Census Bureau; and Arthur 

Hughes, Substance Abuse and Mental 

Health Services Administration. This 

report was edited and produced by the 

NCHS Office of Information Services, 

Information Design and Publishing Staff: 

Jen Hurlburt edited the report, typesetting 

was done by Erik L. Richardson 

(contractor), and graphics were produced 

by Dorothy M. Day. 

iv 
Abstract 

Background 

The National Center for Health 

Statistics (NCHS) disseminates 

information on a broad range of 

health topics through diverse 

publications. These publications 

must rely on clear and transparent 

presentation standards that can 

be broadly and efficiently applied. 

Standards are particularly important 

for large, cross-cutting reports where 

estimates cannot be individually 

evaluated and indicators of precision 

cannot be included alongside the 

estimates. 

Objective 

This report describes the NCHS 

Data Presentation Standards for 

Proportions. 

Results 

The multistep NCHS Data 

Presentation Standards for 

Proportions are based on a minimum 

denominator sample size and on 

the absolute and relative widths of 

a confidence interval calculated 

using the Clopper-Pearson method. 

Proportions (usually multiplied by 

100 and expressed as percentages) 

are the most commonly reported 

estimates in NCHS reports. 

Conclusions 

The NCHS Data Presentation 

Standards for Proportions will be 

applied to all NCHS publications. 

Using these Standards, some 

estimates will be identified as 

unreliable and suppressed and 

some estimates will be flagged for 

statistical review. For reports where 

estimates are evaluated individually, a 

particular proportion not meeting the 

NCHS Data Presentation Standards 

could be identified as unreliable 

but not be suppressed if it can be 

interpreted appropriately in the 

context of subject-specific factors 

and report objectives. 

Keywords: confidence interval • 

sample size • degrees of freedom • 

health surveys • vital statistics 

National Center for Health 

Statistics Data Presentation 

Standards for Proportions
 by the Data Suppression Workgroup: Jennifer D. Parker, Ph.D., 

Division of Research and Methodology; Makram Talih, Ph.D., Office 

of Analysis and Epidemiology; Donald J. Malec, Ph.D., Division of 

Research and Methodology; Vladislav Beresovsky, Ph.D., Division of 

Research and Methodology; Margaret Carroll, M.S.P.H., Division of 

Health and Nutrition Examination Surveys; Joe Fred Gonzalez, Jr., 

M.S., Division of Research and Methodology; Brady E. Hamilton, 

Ph.D., Division of Vital Statistics; Deborah D. Ingram, Ph.D., Office 

of Analysis and Epidemiology; Kenneth Kochanek, M.A., Division of 

Vital Statistics; Frances McCarty, M.Ed., Ph.D., Division of Research 

and Methodology; Chris Moriarity, Ph.D., Division of Health Interview 

Statistics; Iris Shimizu, Ph.D., Division of Research and Methodology; 

Alexander Strashny, Ph.D., Division of Health Care Statistics; and 

Brian W. Ward, Ph.D., Division of Health Care Statistics 

Introduction
 

The National Center for Health 

Statistics (NCHS) collects, analyzes, 

and disseminates information on a broad 

range of health topics through diverse 

publications, databases, and tables. Some 

data products present information based 

on a single data system, while others 

summarize information from many data 

systems. These reports and data products 

may include estimates on a wide range 

of topics or focus on a particular health 

outcome. Furthermore, data products may 

include estimates based on data sources 

outside of NCHS. However, many of 

these reports do not display supporting 

information about an estimate to provide 

the reader with information about the 

estimate’s reliability, such as its standard 

error (SE) or confidence interval (CI), 

due to space and format constraints. As 

a result, reports must rely on clear and 

transparent presentation criteria that can 

be broadly and efficiently implemented. 

Statistical standards for data 

presentation vary across agencies, 

data systems, and data products (1). 

Differences among standards can be, 

in part, attributed to each data system’s 

unique features and constraints. 

Standards also change over time, due 

to changes in the purpose and scope of 

the data’s use, the feasibility of users 

carefully reviewing published estimates, 

the ability to provide explanatory text 

discussing the precision of the published 

estimates, and advances in statistical 

methodology. 

This report describes the NCHS Data 

Presentation Standards for Proportions. 

Proportions (usually multiplied by 100 

and expressed as percentages) are the 

most commonly reported estimates 

in NCHS reports. For many NCHS 

reports, an automated rule is needed 

to determine whether or not estimates 

are sufficiently stable for publication. 

The multistep NCHS Data Presentation 

Standards for Proportions are based on 

a minimum denominator sample size 

and on criteria based on the absolute and 

relative widths of a CI calculated using 

the Clopper-Pearson method (2,3). The 

next section provides details about the 

Standards and their implementation. For 

all NCHS data products, the Standards 

will be applied and departures from the 

Standards will be justified. A flow chart 

Page 1 
Page 2  Series 2, No. 175 

describing the Standards and examples of 

their implementation are provided in the 

appendices. 

NCHS Data 

Presentation Standards 

for Proportions 

The Table summarizes the NCHS 

Data Presentation Standards for 

Proportions, and Appendix I shows the 

process used to implement the Standards. 

When applying the NCHS Data 

Presentation Standards for Proportions, 

estimates identified as unreliable will 

be suppressed. Other estimates will 

be flagged for statistical review by the 

clearance official. Flagged estimates may 

be suppressed or presented, depending 

on the outcome of the review. To ease 

production of large reports, the decision 

process for flagged estimates could 

be automated at the discretion of the 

clearance official, with the suppression of 

all flagged estimates. When an estimate 

is flagged or suppressed, a footnote 

indicating the reason the estimate has 

been flagged or suppressed should be 

provided in the publication. 

The NCHS Data Presentation 

Standards for Proportions will be applied 

to all NCHS reports and data systems. 

Importantly, the Standards presented 

in this report apply to estimates that 

are known to meet all confidentiality 

requirements, or in the case of vital 

statistics, meet all agreements between 

NCHS and the states. Like other 

statistical agencies, NCHS may restrict 

access to certain data or estimates to 

protect the confidentiality of survey 

participants (4,5). 

Departures from the Standards 

should be justified. In reports in which 

estimates are evaluated individually, 

a particular estimate not meeting 

the Standards could be identified as 

unreliable but not be suppressed if it 

can be interpreted appropriately in 

the context of subject-specific factors 

and report objectives. Currently such 

reports include, but are not limited to, 

Data Briefs, National Health Statistics 

Reports, multi-agency reports such as 

Table. NCHS Data Presentation Standards for Proportions 

Statistic Standard 

Sample size Estimated proportions should be based on a minimum 

denominator sample size and effective denominator sample 

size (when applicable) of 30. Estimates with either a 

denominator sample size or an effective denominator sample 

size (when applicable) less than 30 should be suppressed. 

If the number of events is 0 (or its complement1

), then the 

denominator sample size should be used to obtain confidence 

intervals. If all other criteria are met for presentation, an 

estimate based on 0 events (or its complement1

) should 

be flagged for statistical review by the clearance official. 

The review could result in either the presentation or the 

suppression of the proportion. 

Confidence interval If the sample size criterion is met, calculate a 95% two-sided 

confidence interval using the Clopper-Pearson method, or the 

Korn-Graubard method for complex surveys, and obtain its 

width. 

Small absolute confidence interval width If the absolute confidence interval width is greater than 0.00 

and less than or equal to 0.05, then the proportion can be 

presented if the number of events is greater than 0 and the 

degrees of freedom criterion (below) is met. If the number of 

events is 0 (or its complement1

) or the degrees of freedom 

criterion is not met, then the estimate should be flagged for 

statistical review by the clearance official. The review could 

result in either the presentation or the suppression of the 

proportion. 

Large absolute confidence interval width If the absolute confidence interval width is greater than or equal 

to 0.30, then the proportion should be suppressed. 

Relative confidence interval width If the absolute confidence interval width is between 0.05 and 

0.30 and the relative confidence interval width is more than 

130%, then the proportion should be suppressed. 

Relative confidence interval width If the absolute confidence interval width is between 0.05 and 

0.30 and the relative confidence interval width is less than 

or equal to 130%, then the proportion can be presented if 

the degrees of freedom criterion below is met. If the degrees 

of freedom criterion is not met, then the estimate should 

be flagged for statistical review by the clearance official. 

The review could result in either the presentation or the 

suppression of the proportion. 

Degrees of freedom When applicable for complex surveys, if the sample size and 

confidence interval criteria are met for presentation and the 

degrees of freedom are fewer than 8, then the proportion 

should be flagged for statistical review by the clearance 

official. This review may result in either the presentation or the 

suppression of the proportion. 

Complementary proportions If all criteria are met for presenting the proportion but not for its 

complement1

, then the proportion should be shown. A footnote 

indicating that the complement of the proportion may be 

unreliable should be provided. 

1

The complement of a proportion p is (1 – p). The complement of the number of events in the numerator for p is the number of 

events in the numerator for (1 – p). 

America’s Children and Older Americans, 

and journal articles authored by NCHS 

staff members. For such reports, the 

analyst(s) should provide justification 

for including the estimate in the report 

to the clearance official(s) and a final 

determination will be made jointly by 

the analyst(s) and clearance official(s) 

on a case-by-case basis. If the final 

determination is to present an estimate, 

a footnote or appropriate language in the 

report indicating that the estimate does 

not meet the NCHS Data Presentation 

Standards should be provided. 

The specific components of the 

NCHS Data Presentation Standards for 

Proportions are described more fully in 

the following sections. 

Sample Size 

The sample size (denominator) is 

an important indicator of an estimate’s 

precision. The variance of a proportion 

is directly related to the sample size 

and, with large samples, applying the 

normal approximation to the binomial 

distribution for proportions can be useful 

for many analyses (6). 

For vital statistics, the sample size 

for a proportion is the number of births 

(or deaths) in the denominator. For an 
Series 2, No. 175  Page 3 

estimate from a complex survey, the 

effective sample size, ne, is defined as 

the sample size, n, divided by the design 

effect (7). One approach used to calculate 

ne for estimated proportions from a 

complex sample survey is: 

where, in this case, the design effect is:
	

Documentation for specific surveys 

should be consulted when calculating 

design effects, as approaches can differ 

among surveys and for specific analytic 

purposes. 

If the number of numerator events 

is 0 or equal to the denominator (the 

complement of 0 events), the estimated 

proportion will be 0 or 1, respectively. 

As a result, the estimated variance of the 

proportion will be 0, and the effective 

sample size will be undefined. In these 

cases, the sample size should be used to 

determine whether the minimum sample 

size criterion is met, and it should also 

be used for CIs and other computations 

that include the effective sample size. 

Because observing no events or events 

for everyone in a category can provide 

important information (e.g., in the context 

of rare health outcomes or conditions), 

estimates based on 0 events (or the 

complement) that meet absolute CI and 

degrees of freedom criteria should be 

flagged and considered for presentation 

after statistical review by a clearance 

official to confirm the validity of the point 

and interval estimates. 

For complex sample surveys, due 

to sampling design and variability, 

there may be cases where the effective 

sample size is greater than the sample 

size. When the effective sample size is 

greater than the sample size, the sample 

size should be used to determine whether 

the minimum sample size criterion is 

met, and it should also be used for CIs 

and other computations that include the 

effective sample size. 

Standard 

●		 Estimated proportions should be based 

on a minimum denominator sample 

size and effective denominator sample 

size (when applicable) of 30. Estimates 

with either a denominator sample size 

or an effective denominator sample 

size (when applicable) less than 30 

should be suppressed. 

●		 If the number of numerator events 

is 0 (or its complement), then the 

denominator sample size should be 

used to obtain confidence intervals. 

If all other criteria are met for 

presentation, an estimate based on 0 

events (or its complement) should be 

flagged for statistical review by the 

clearance official. The review could 

result in either the presentation or the 

suppression of the proportion. 

Confidence Intervals 

The NCHS Data Presentation 

Standards for Proportions are based on the 

evaluation of absolute and relative 95% 

CI widths. CIs provide a way to assess 

an estimate’s precision, and technical 

definitions are available in many standard 

statistical texts, including Bickel and 

Doksum (8) and Casela and Berger (9). 

More generally, under repeated sampling, if 

a proportion and its 95% CI are estimated 

from each sample, the true value of the 

proportion is expected to be contained in 

95% of the calculated intervals. A handful 

of methods to calculate CIs for proportions 

are available and the expectation of 95% 

coverage may not be attained for some 

intervals or under some conditions. 

Methods used to calculate a CI lead to 

undercoverage if the true proportion is 

contained in fewer than the expected 

number of intervals (e.g., less than 95%). 

Conversely, methods are considered 

conservative if the true proportion is 

contained in more than the expected 

number of intervals. 

The Clopper-Pearson CI (2) [adapted 

for complex surveys by Korn and Graubard 

(3) when applicable] should be used to 

determine whether or not the CI of a 

proportion meets the presentation criteria. 

For the purposes of setting thresholds 

for the Standards, the determinations of 

small and large in the context of absolute 

and relative CI widths for estimated 

proportions are based on the 95% twosided Clopper-Pearson CI. The ClopperPearson CI is known to perform well for 

estimated proportions with few events 

in the numerator. For complex sample 

surveys, the calculation of the ClopperPearson CI using the approach of Korn and 

Graubard incorporates information from 

the survey design, including the effective 

sample size and, when appropriate, the 

degrees of freedom. Finally, the coverage 

of a 95% Clopper-Pearson CI is generally 

conservative, meaning that the ClopperPearson CI includes the true proportion 

more than 95% of the time. Other intervals 

have been shown to have poorer coverage, 

meaning that a 95% CI includes the true 

proportion less than 95% of the time 

(10–12). 

In particular, the commonly used 

Wald CI [p ± 1.96 × SE(p) for a two-sided 

95% CI] is known to perform poorly 

for proportions (10–12). In addition to 

sometimes producing negative lower 

bounds for small proportions or upper 

bounds greater than 1 for large proportions, 

the Wald CI does not always produce 

adequate coverage. In other words, 

published simulation studies demonstrate 

that the true proportion is contained within 

a 95% Wald CI in less than 95% of the 

simulated CIs, with greater undercoverage 

for smaller and larger proportions. 

From a calculated CI, the absolute 

CI width is obtained by subtracting the 

value of the lower confidence limit from 

the value of the upper confidence limit. 

The relative CI width is calculated as the 

absolute CI width divided by the proportion 

and multiplied by 100%. Past practice 

for many surveys has been to evaluate 

relative standard errors (RSEs), which 

are calculated by dividing the SE by the 

proportion and multiplying by 100%. 

However, when dividing the SE by very 

small proportions, the RSE can be too 

conservative, and when dividing the SE 

by very large proportions, the RSE can be 

too liberal. Because the relative CI width is 

calculated in a similar manner, this property 

of the RSE also applies to the relative 

CI width. The NCHS Data Presentation 

Standards for Proportions rely on both the 

relative and absolute CI widths to reduce 

the impact of this property. 
 

 

Page 4  Series 2, No. 175 

For complex sample surveys, default 

calculations from survey software 

may not be appropriate or feasible for 

all situations, including age-adjusted 

estimates, estimates based on multiple 

imputation, estimates for subgroups 

represented in only a subset of primary 

sampling units (PSUs) (e.g., some 

racial and ethnic groups and regionspecific estimates), and when calculating 

annual or survey cycle estimates using 

a multiyear or multicycle data file. In 

these instances, the relevant information 

should be extracted and the CIs directly 

calculated. 

Standard 

●		 If the sample size criterion is met, 

calculate a 95% two-sided confidence 

interval using the Clopper-Pearson 

method (2), or the Korn-Graubard 

method (3) for complex sample 

surveys, and obtain the width of the 

confidence interval. 

○		 If the absolute confidence 

interval width is greater than 

0.00 and less than or equal to 

0.05, then the proportion can be 

presented if the number of events 

is greater than 0 and the degrees 

of freedom criterion (described 

in the next section) is met. If 

the number of events is 0 (or 

the complement) or the degrees 

of freedom criterion is not met, 

then the estimate should be 

flagged and statistically reviewed 

by the clearance official. This 

review may result in either the 

presentation or the suppression of 

the proportion. 

○		 If the absolute confidence 

interval width is greater than or 

equal to 0.30, then the proportion 

should be suppressed. 

○		 If the absolute confidence 

interval width is between 

0.05 and 0.30 and the relative 

confidence interval width is more 

than 130%, then the proportion 

should be suppressed. 

○		 If the absolute confidence 

interval width is between 

0.05 and 0.30 and the relative 

confidence interval width is 

less than or equal to 130%, 

then if the degrees of freedom 

criterion described in the next 

section is met, the proportion 

can be presented. If the degrees 

of freedom criterion is not met, 

then the estimate should be 

flagged and statistically reviewed 

by the clearance official. This 

review may result in either the 

presentation or the suppression of 

the proportion. 

Degrees of Freedom 

For complex sample surveys, the 

precision of the estimated SE is inversely 

related to the square root of the degrees 

of freedom. Using SEs with low precision 

to assess estimated proportions may lead 

to poor measures of effective sample size 

and CI widths. Under certain conditions, 

the variance estimate has an approximate 

chi-squared distribution, and the RSE of 

the SE obtained from a complex sample 

survey can be approximated as

 . From this 

expression, estimated proportions based 

on fewer than 8 degrees of freedom have 

an RSE of 50% or higher. 

As one rule of thumb, the degrees of 

freedom can be calculated as the number 

of PSUs minus the number of strata. This 

calculation is used in most NCHS surveys 

and implemented in survey software, 

although specific calculations can vary 

across packages. However, default 

calculations of degrees of freedom from 

survey software may not be appropriate 

for subgroups represented in only a subset 

of PSUs (e.g., some racial and ethnic 

groups and region-specific estimates) and 

when calculating annual or survey cycle 

estimates using a multiyear or multicycle 

data file. In these instances, the relevant 

information should be extracted and the 

degrees of freedom directly calculated to 

assess estimate precision. The calculation 

of degrees of freedom as a measure of 

precision for the SE may not be applicable 

for all surveys (see survey-specific 

documentation) and does not apply to 

vital statistics. For additional information 

on degrees of freedom, see Korn and 

Graubard (13) and Valliant and Rust (14). 

Standard 

●		 When applicable for complex 

surveys, if the sample size and CI 

criteria are met for presentation and 

the degrees of freedom are fewer 

than 8, then the proportion should be 

flagged for statistical review by the 

clearance official. This review may 

result in either the presentation or the 

suppression of the proportion. 

Complementary 

Proportions 

The SE and width of the CI for the 

complement of a proportion (1 – p) are 

the same as those for the proportion, 

p. As described in previous sections, 

relative measures for the smaller 

proportion are much larger than for its 

larger complement. Consequently, there 

is a range of proportions where the CI 

criteria will yield conflicting assessments 

of reliability. For these proportions, the 

relative CI width may indicate that a 

small proportion is unreliable but that its 

complement is not. 

For a given health indicator or 

publication, the larger proportion may 

be the most salient measure, while for 

others, the smaller proportion may be 

the most important. Typically, both 

proportions are not shown (e.g., only 

the proportion with health insurance 

would be shown, not both the proportion 

with and the proportion without health 

insurance). Given that the complement 

of the presented proportion can be 

determined by subtraction, consideration 

of the precision of the complement 

is important. For some publications, 

the practice has been to suppress both 

proportions if one of the proportions is 

identified as unreliable. However, this 

practice may lead to the suppression of 

important information. 

Standard 

●		 If all criteria are met for presenting 

the proportion but not for its 

complement, then the proportion 

should be shown. A footnote 

indicating that the complement of the 

proportion may be unreliable should 

be provided. 
Discussion
 

The NCHS Data Presentation 

Standards for Proportions will be applied 

to all NCHS publications. Using these 

Standards, some estimates will be 

identified as unreliable and suppressed 

and some estimates will be flagged for 

statistical review. There are two scenarios 

where the estimates will be flagged for 

statistical review by a clearance official: 

a) when the number of events is 0 (or its 

complement, equal to the denominator); 

and b) for estimates from sample surveys 

with fewer than 8 degrees of freedom. 

Statistical review by a clearance official 

of flagged estimates will consider the 

recommendation of the analyst(s) and 

factors such as the estimate’s sample size, 

CI, and degrees of freedom; the report’s 

objectives and format (including the 

ability to present CIs or other measures 

of precision); and the other estimates in 

the report to determine whether to present 

or suppress the estimate. In some large 

reports, this process may be automated 

to ease the production process, with all 

flagged estimates suppressed without 

review. 

When the NCHS Data Presentation 

Standards for Proportions are used for 

shorter, more focused reports, specific 

estimates that do not meet the standards 

may be reported after being evaluated 

individually by the analyst(s) and 

clearance official(s). Some estimates 

identified as unreliable based on the 

Standards may be important and can be 

interpreted appropriately in the context of 

measures of precision and other subjectspecific information. In these cases, the 

estimate could be presented. Because 

report objectives and subject-specific 

factors vary widely, justification for 

presenting an unreliable estimate should 

be provided by the analyst(s) and final 

determination should be made by the 

analyst(s) and clearance official(s) on a 

case-by-case basis. In all publications, 

unreliable estimates, whether presented 

or suppressed, should be identified with a 

footnote. 

Many NCHS data products include 

SEs so that data users can assess the 

precision of the point estimates. As stated 

previously, measures derived solely 

from the SE (e.g., Wald CI and RSE) 

can perform poorly for proportions. 

Consequently, whenever space permits, 

appropriate CIs should be provided, 

rather than just SEs. 

Age-adjusted estimates are often 

produced for national statistics. Age 

adjustment allows for a comparison 

of outcomes between two groups with 

differing age distributions, as many health 

outcomes are highly correlated with age 

(15,16). These estimates can be handled 

in a similar manner as unadjusted 

estimates. There may be instances in 

which the age-adjusted estimates will 

not meet the presentation criteria but the 

crude estimate would, or vice versa. In 

these cases, the estimate that meets the 

presentation criteria will be shown, and 

the one that does not will be suppressed. 

If CIs for age-adjusted estimates are not 

readily obtained from survey software, 

the relevant information can be extracted 

and the CIs can be directly calculated. 

For the NCHS Data Presentation 

Standards for Proportions, there is 

no minimum number of events (i.e., 

numerator size). For the calculation of 

the Clopper-Pearson CI, a minimum 

numerator is not needed. A numerator 

with few events may provide useful 

information for some purposes. Although 

observing no events (or its complement, 

observing events for all records in 

the category) can provide important 

information (e.g., in the context of 

subgroup-specific analyses of rare [or 

prevalent] health outcomes), an estimate 

based on 0 events (or its complement) 

should be flagged for statistical review 

to confirm the validity of the point and 

interval estimates. In addition, inferences 

based on the normal approximation, 

including statistical comparisons of 

proportions between subgroups, require 

a minimum number of events. Finally, 

some estimates based on restricted data 

or vital statistics may require a minimum 

number of events to decrease disclosure 

risks, and reporting of these estimates 

may be based on different criteria (e.g., 

confidentiality). 

Although most estimates produced 

in NCHS reports are proportions, other 

estimates, such as rates, percentiles, and 

Series 2, No. 175  Page 5 

means are also regularly reported. Death 

rates, for example, are calculated as the 

number of events reported in a calendar 

year divided by the corresponding census 

population estimate at the midpoint of 

the calendar year. The NCHS Standards 

were not developed to apply to these 

estimators. Although the principles 

considered by the workgroup for 

proportions can be considered for other 

estimators, including the evaluation of 

effective sample size and CIs to guide 

decisions, no specific thresholds for 

these estimators are provided by these 

Standards. Rates calculated from vital 

statistics will continue to use the criterion 

of requiring 20 or more events for 

reporting. In addition to precision, there 

are other statistical issues, not addressed 

here, that affect the quality of the 

estimates, including measurement error 

and survey nonresponse (17). 

The NCHS Data Presentation 

Standards for Proportions can be 

considered in planning analytic studies 

or table shells for reports. Collapsing 

subgroups and aggregating years leads 

to estimates with less uncertainty and 

might be more appropriate for a specific 

report than disaggregated estimates, even 

when minimum presentation guidelines 

are met. Other items to be considered 

may include the intended use of the 

estimate, the amount and structure of 

supporting information about uncertainty 

that can be conveyed, and the availability 

of corresponding estimates for other 

subgroups or other time periods. 

References 

1.	 Klein RJ, Proctor SE, Boudreault 

MA, Turczyn KM. Healthy People 

2010 criteria for data suppression. 

Statistical Notes, no 24. Hyattsville, 

MD: National Center for Health 

Statistics. 2002. 

2.	 Clopper CJ, Pearson ES. The use 

of confidence or fiducial limits 

illustrated in the case of the 

binomial. Biometrika 26(4):404–13. 

1934. 
Page 6  Series 2, No. 175 

3.	 Korn EL, Graubard BI. Confidence 

intervals for proportions with small 

expected number of positive counts 

estimated from survey data. Surv 

Methodol 24(2):193–201. 1998. 

4.	 National Center for Health 

Statistics. NCHS staff manual on 

confidentiality. Available from: 

https://www.cdc.gov/nchs/data/misc/ 

staffmanual2004.pdf. 

5.	 National Center for Health Statistics 

Research Data Center. Disclosure 

manual: Preventing disclosure: 

Rules for researchers. Available 

from: https://www.cdc.gov/rdc/data/ 

b4/disclosuremanual.pdf. 

6.	 Johnson NL, Kotz S, Kemp AW. 

Univariate discrete distributions. 

2nd edition. New York: John Wiley 

& Sons, Inc. 114. 1992. 

7.	 Kish L. Survey sampling. New York: 

John Wiley & Sons, Inc. 1965. 

8.	 Bickel PJ, Doksum KA. 

Mathematical statistics: Basic ideas 

and selected topics, Volume 1, 

Second Edition. Chapman & Hall/ 

CRC. 2015. 

9.	 Casella G, Berger RL. Statistical 

inference. 2nd edition. Cengage 

Learning. 2001. 

10.	 Dean N, Pagano M. Evaluating 

confidence interval methods for 

binomial proportions in clustered 

surveys. J Surv Stat Methodol 

3(4):484–503. 2015. 

11.	 Brown LD, Cai TT, Dasgupta A. 

Interval estimation for a binomial 

proportion. Stat Sci 16(2):101–17. 

2001. 

12.	 Newcombe RG. Two-sided 

confidence intervals for the single 

proportion: Comparison of seven 

methods. Stat Med 17(8):857–72. 

1998. 

13.	 Korn EL, Graubard BI. Chapter 

5: Additional issues in variance 

estimation. In: Korn EL, Graubard 

BI. Analysis of health surveys. New 

York, NY: John Wiley & Sons, Inc. 

192–234. 1999. 

14.	 Valliant R, Rust KF. Degrees of 

freedom approximations and rulesof-thumb. J Off Stat 26(4):585–602. 

2010. 

15.	 Anderson RN, Rosenberg HM. 

Age standardization of death rates: 

Implementation of the year 2000 

standard. National vital statistics 

reports; vol 47 no 3. Hyattsville, 

MD: National Center for Health 

Statistics. 1998. 

16.	 National Center for Health Statistics. 

Health, United States, 2015: With 

special feature on racial and ethnic 

health disparities. Hyattsville, MD. 

2016. Available from: https://www. 

cdc.gov/nchs/data/hus/hus15.pdf. 

17.	 Groves RM, Fowler Jr FJ, Couper 

MP, Lepkowski JM, Singer E, 

Tourangeau R. Survey methodology. 

Hoboken, NJ: John Wiley & Sons. 

2004. 

18.	 National Center for Health Statistics. 

National Health and Nutrition 

Examination Survey. Available 

from: https://www.cdc.gov/nchs/ 

nhanes.htm. 

19.	 National Center for Health Statistics. 

National Health Interview Survey. 

Available from: https://www.cdc. 

gov/nchs/nhis.htm. 

20. Parsons VL, Moriarity C, Jonas K, 

et al. Design and estimation for the 

National Health Interview Survey, 

2006–2015. National Center for 

Health Statistics. Vital Health Stat 

2(165). 2014. 

21.	 National Center for Health Statistics. 

Health, United States, 2014: With 

special feature on adults aged 55–64. 

Hyattsville, MD. 2015. Available 

from: https://www.cdc.gov/nchs/ 

data/hus/hus14.pdf. 

22.	 National Center for Health Statistics. 

National Ambulatory Medical Care 

Survey. Available from: 

https://www.cdc.gov/nchs/ahcd/ 

about_ahcd.htm#NAMCSNAMCES. 

23. National Center for Health Statistics. 

National Ambulatory Medical Care 

Survey: 2012 state and national 

summary tables. Available from: 

https://www.cdc.gov/nchs/data/ahcd/ 

namcs_summary/2012_namcs_web_ 

tables.pdf. 

24. National Center for Health Statistics. 

National Survey of Family Growth. 

Available from: https://www.cdc. 

gov/nchs/nsfg.htm. 

25.	 Jones J, Mosher WD. Fathers’ 

involvement with their children: 

United States, 2006–2010. National 

health statistics reports; no 71. 

Hyattsville, MD: National Center for 

Health Statistics. 2013. 

26. National Center for Health Statistics. 

The public use natality file—2015 

update. 2016. Available from: ftp:// 

ftp.cdc.gov/pub/Health_Statistics/ 

NCHS/Dataset_Documentation/ 

DVS/natality/UserGuide2015.pdf. 

27.	 Martin JA, Hamilton BE, Osterman 

MJK, et al. Births: Final data 

for 2015. National vital statistics 

reports; vol 66 no 1. Hyattsville, 

MD: National Center for Health 

Statistics. 2017. Available from: 

https://www.cdc.gov/nchs/data/nvsr/ 

nvsr66/nvsr66_01.pdf. 
Series 2, No. 175  Page 7 

Appendix I. Figure. Implementation of NCHS Data Presentation 

Standards for Proportions 

 

SOURCE: NCHS, 2017. 
 

Page 8  Series 2, No. 175 

Appendix II. Examples of the Application of NCHS Data Presentation 

Standards for Proportions 

This appendix describes National 

Center for Health Statistics (NCHS) 

data sets and provides examples of the 

application of the NCHS Presentation 

Standards using excerpts of previously 

published tables or new tabulations. 

Shown in these examples are: the 

sample size, the effective sample 

size (when applicable), the estimated 

proportion, the standard error (SE) of 

the proportion, the upper and lower 

bounds of the two-sided 95% ClopperPearson (or Korn-Graubard when 

applicable) confidence interval (CI), the 

absolute CI width, the relative CI width, 

and, if appropriate, the degrees of 

freedom and the number of events in the 

numerator. Because survey estimates 

with high relative standard errors 

[RSE = 100% × (SE/Estimate)] have 

been marked as potentially unreliable 

or suppressed in previous NCHS 

publications, the implications of the 

Standards are compared with decisions 

based on the RSE > 30% criterion 

for survey estimates. Estimates in the 

Appendix II tables are for illustration 

only and should not be used as the 

source for subject-specific information. 

National Health and 

Nutrition Examination 

Survey 

The National Health and Nutrition 

Examination Survey (NHANES) 

is a program of studies designed to 

assess the health and nutritional status 

of adults and children in the United 

States. Currently, the survey examines 

a nationally representative sample of 

about 5,000 participants each year. These 

participants are located in counties across 

the country, 15 of which are included in 

the sample each year. Data are released 

in 2-year cycles. The NHANES interview 

includes demographic, socioeconomic, 

dietary, and health-related questions. 

The examination component consists 

of medical, dental, and physiological 

measurements, as well as laboratory tests 

administered by highly trained medical 

personnel (18). 

Table I shows the percentage of 

children aged 8–17 years with elevated 

blood pressure, a relatively rare outcome 

for children, by race and Hispanic origin 

using the 2013–2014 NHANES data. 

Percentage estimates for elevated blood 

pressure range from 0.5% among nonHispanic white children to 2.5% among 

Hispanic children. For illustration, the 

complements of these percentages, the 

percentages with normal or borderline 

elevated blood pressure, are also shown. 

●		 All sample sizes and effective 

samples sizes are 30 or higher. 

●		 Absolute CI widths for elevated high 

blood pressure for non-Hispanic 

white and Hispanic children are less 

than 5 percentage points, so these 

estimates can be presented if the 

number of events is not 0 (or equal to 

the denominator) and there are 8 or 

more degrees of freedom. 

●		 Absolute CI widths for elevated 

high blood pressure for nonHispanic black and Asian children 

are between 5 and 30 percentage 

Table I. Percentage of children aged 8–17 years with elevated and normal or borderline blood pressure, by race and Hispanic origin: 

United States, 2013–2014 

Standard Relative 

Race and Hispanic origin 

and blood pressure 

Sample 

size 

Effective 

sample size1 

Percent 

estimate 

error of 

percent 

standard 

error 2 

Lower 

bound3 

Upper 

bound3 

Absolute 

CI width4 

Relative 

CI width5 

Degrees of 

freedom 

Non-Hispanic white, 

elevated . . . . . . . . . . . . . . . . 460 8

583.0 0.5 0.29 58.0 0.1 1.6 1.6 320.0 15 

Non-Hispanic white, 

normal or borderline . . . . . . . 460 8

583.0 99.5 0.29 0.3 98.4 99.9 1.6 1.6 15 

Non-Hispanic black, 

elevated . . . . . . . . . . . . . . . . 447 145.3 6

2.0 1.17 58.5 0.3 6.4 6.1 305.0 13 

Non-Hispanic black, 

normal or borderline . . . . . . . 447 145.3 7

98.0 1.17 1.2 93.6 99.7 6.1 6.2 13 

Non-Hispanic Asian, 

elevated . . . . . . . . . . . . . . . . 164 124.8 6

0.9 0.83 92.2 0.0 5.1 5.1 566.7 13 

Non-Hispanic Asian, 

normal or borderline . . . . . . . 164 124.8 7

99.1 0.83 0.8 94.9 100.0 5.1 5.2 13 

Hispanic, elevated . . . . . . . . . 589 8

946.8 2.5 0.51 20.4 1.4 4.1 2.7 108.0 15 

Hispanic, normal or 

borderline . . . . . . . . . . . . . . . 589 8

946.8 97.5 0.51 0.5 95.9 98.6 2.7 2.8 15 

1

Sample size divided by the design effect. It is calculated in this table using this formula:
 

2

Standard error divided by the estimated percent multiplied by 100%.
 

3

Lower and upper confidence bounds were computed using the Korn-Graubard method.
 

4

Difference between the upper and lower confidence bounds.
 

5

Absolute width divided by the estimated percent multiplied by 100%.
 

6

Relative CI width is greater than 130%. Estimate would be suppressed.
 

7

Estimate would have a footnote indicating its complement is suppressed.
 

8

Effective sample size is greater than sample size. Sample size used in CI calculations.
 

 

NOTES: CI is confidence interval. Percent estimate and its lower and upper confidence bounds are equal to the proportion estimate and its lower and upper confidence bounds, respectively, multiplied 

by 100. Standard error of percent and absolute CI width are expressed in percentage points. Numbers in the table are subject to rounding. 

SOURCE: NCHS, National Health and Nutrition Examination Survey. 
 

Series 2, No. 175  Page 9 

points, so the relative CI width 

should be examined. 

●		 Relative CI widths for elevated high 

blood pressure for non-Hispanic 

black and non-Hispanic Asian 

children are greater than 130%, so 

these estimates would be suppressed. 

●		 The number of events is greater than 

0 (and not equal to the denominator) 

and there are more than 8 degrees 

of freedom for all estimates, so 

estimates that have met all other 

sample size and CI criteria would be 

presented. 

●		 If the outcome of interest is the 

complement (normal or borderline 

high blood pressure), the absolute 

CI widths are the same. However, 

the relative CI widths for nonHispanic black and non-Hispanic 

Asian children are less than 130%, 

so these estimates would be 

presented with a note indicating 

that their complements do not meet 

presentation standards. 

●		 Estimates of elevated blood pressure 

for non-Hispanic white children would 

be presented using the NCHS Data 

Presentation Standards for Proportions 

but would have been suppressed or 

identified as unreliable based on the 

RSE > 30% criterion. 

Table II shows the prevalence of 

overweight among adults aged 60 and 

over by sex and race and Hispanic 

origin using NHANES 2013–2014 data. 

Prevalence estimates for these subgroups 

range from around 25% for non-Hispanic 

black and Asian women to more than 

50% for Hispanic men. 

●		 All sample sizes and effective 

sample sizes are 30 or higher. 

●		 Absolute CI widths for men in each 

race and Hispanic-origin group and 

for Hispanic, non-Hispanic white, 

and non-Hispanic black women are 

between 5 and 30 percentage points, 

so the relative CI width would be 

examined. 

●		 The relative CI widths for men in 

each race and Hispanic-origin group 

and for Hispanic, non-Hispanic 

white, and non-Hispanic black 

women are all less than 130%, so 

the percentages could be presented 

if the degrees of freedom are 8 or 

greater. 

●		 The absolute CI width for nonHispanic Asian women is 30.6 

percentage points, indicating that 

the percentage would be suppressed. 

●		 The number of events for all 

estimates is greater than 0 (and not 

equal to the denominator). 

●		 The degrees of freedom for nonHispanic Asian men and women are 

7, indicating that these estimates 

would be flagged for statistical 

review by the clearance official. 

●		 The RSE for all subgroups is less 

than 30%. Under the RSE > 30% 

suppression criterion, all estimates 

would have been presented, whereas 

using the NCHS Data Presentation 

Standards for Proportions, the 

percentage for non-Hispanic Asian 

women would be suppressed. 

National Health Interview 

Survey 

First fielded in 1957, the main 

objective of the National Health 

Interview Survey (NHIS) is to monitor 

the health of the U.S. population through 

the collection and analysis of data on a 

broad range of health topics (19). NHIS 

is conducted continuously throughout the 

calendar year, collecting data from the 

civilian noninstitutionalized population 

of the United States. Each year, a 

representative sample of households 

across the country is selected for NHIS 

using a multistage cluster sample design. 

Parsons et al. (2014) contains more 

information on the design and estimation 

methods for 2006–2015 (20). 

Table II. Percentage of adults aged 60 and over who are overweight, by sex and race and Hispanic origin: United States, 2013–2014 

Effective Standard Relative 

Sex and race and Hispanic origin

 Sample 

size 

sample 

size1 

Percent 

estimate 

error of 

percent 

standard 

error 2 

Lower 

bound 3 

Upper 

bound3 

Absolute 

CI width4 

Relative 

CI width5 

Degrees of 

freedom 

Men 

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 124.3 52.2 4.49 8.6 42.0 61.5 19.5 37.4 11 

Non-Hispanic white. . . . . . . . . . . . . . . . . . . 384 246.2 38.6 3.10 8.0 32.0 47.1 15.2 39.3 15 

Non-Hispanic black. . . . . . . . . . . . . . . . . . . 195 6

240.7 34.9 3.06 8.8 27.6 45.2 17.6 50.5 12 

Non-Hispanic Asian . . . . . . . . . . . . . . . . . . 74 6

108.8 747.8 4.79 10.0 33.8 62.6 28.7 60.1 7 

Women 

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 152.1 36.1 3.89 10.8 27.7 47.7 20.1 55.6 12 

Non-Hispanic white. . . . . . . . . . . . . . . . . . . 466 296.8 34.3 2.76 8.0 28.4 42.3 13.8 40.4 15 

Non-Hispanic black. . . . . . . . . . . . . . . . . . . 175 6

236.5 25.1 2.83 11.3 18.2 36.5 18.3 72.8 12 

Non-Hispanic Asian . . . . . . . . . . . . . . . . . . 82 6

107.9 825.0 4.16 16.6 14.6 45.2 30.6 122.4 7 

1

Sample size divided by the design effect. It is calculated in this table using this formula:
 .
 2

Standard error divided by the estimated percent multiplied by 100%.
 

3

Lower and upper confidence bounds were computed using the Korn-Graubard method.
 

4

Difference between the upper and lower confidence bounds.
 

5

Absolute width divided by the estimated percent multiplied by 100%.
 

6

Effective sample size is greater than sample size. Sample size used for CI calculations.
 

7

Degrees of freedom fewer than 8. Estimate would be flagged for statistical review by the clearance official and may be presented or suppressed.
 

8

Absolute CI width is greater than or equal to 30. Estimate would be suppressed.
 

NOTES: CI is confidence interval. Overweight is defined as a body mass index (BMI) of at least 25 but less than 30 kilograms per square meter. BMI is calculated as weight (kilograms) divided by 

height squared (meters). Percent estimate and its lower and upper confidence bounds are equal to the proportion estimate and its lower and upper confidence bounds, respectively, multiplied by 100. 

Standard error of percent and absolute CI width are expressed in percentage points. Numbers in the table are subject to rounding. 

SOURCE: NCHS, National Health and Nutrition Examination Survey. 
 

Page 10 Series 2, No. 175 

Table III illustrates the application 

of the presentation standards using an 

excerpt of data from the 2013 NHIS, 

showing hearing difficulty among adults 

by race and Hispanic origin and family 

income relative to the federal poverty 

level (FPL). Percentage estimates range 

from 0.47% among non-Hispanic black 

adults with incomes 400% of the FPL 

and higher to 3.2% among non-Hispanic 

white adults with incomes below the 

FPL. NHIS guidelines do not recommend 

calculating degrees of freedom using 

variance units available on the data 

file (https://www.cdc.gov/nchs/data/ 

nhis/2006var.pdf). For national estimates, 

the degrees of freedom are assumed to be 

large enough for a normal approximation. 

Table III is based on Table 49 in 

Health, United States, 2014 (21). 

●		 All sample sizes and effective 

sample sizes are 30 or higher. 

●		 All absolute CI widths are less 

than 5 percentage points, so all 

percentages should be presented 

if the number of events is greater 

than 0 (and not equal to the 

denominator). 

●		 The numbers of events are all 

greater than 0 (and not equal to the 

denominator), so percentages that 

meet all other sample size and CI 

criteria for presentation would be 

presented. 

●		 The RSE for several subgroups, 

including Hispanic adults with 

incomes below the FPL, 200%–399% 

of the FPL, and 400% of the FPL or 

higher and non-Hispanic black adults 

with incomes 200%–399% of the 

FPL and 400% of the FPL or higher 

is greater than 30%. Percentages for 

these subgroups would have been 

suppressed or identified as unreliable 

using the RSE > 30% criterion 

but would be presented using the 

NCHS Data Presentation Standards 

for Proportions. 

National Ambulatory Medical 

Care Survey and National 

Hospital Ambulatory Medical 

Care Survey 

The National Ambulatory Medical 

Care Survey (NAMCS) is an annual, 

nationally representative survey 

of visits to nonfederal office-based 

physicians (excluding pathologists, 

anesthesiologists, and radiologists) and to 

community health centers. The sampling 

frames for physicians are constructed 

from the master files of the American 

Medical Association and the American 

Osteopathic Association; the sampling 

frames for community health centers 

are obtained from the federal Health 

Resources and Services Administration 

and the Indian Health Service. NAMCS 

data were collected on approximately 

32,000 and 31,000 visits to officebased physician practices in samples 

of geographic primary sampling units 

(PSUs) in 2009 and 2010, respectively. 

The National Hospital Ambulatory 

Medical Care Survey (NHAMCS) 

is a nationally representative survey 

of nonfederal general and short-stay 

hospitals that is conducted annually. 

NHAMCS uses a multistage probability 

design with samples of geographic 

PSUs, hospitals within PSUs, and 

patient visits within emergency and 

outpatient departments. NHAMCS data 

were collected on approximately 35,000 

emergency department visits in both 

2009 and 2010 and on approximately 

34,000 and 35,000 outpatient department 

visits in 2009 and 2010, respectively. 

Table III. Percentage of adults aged 18 and over with hearing difficulties, by race and Hispanic origin and family income: United States, 2013 

Effective Standard Relative 

Race and Hispanic origin and 

family income (percentage of FPL)

 Sample 

size 

sample 

size1 

Percent 

estimate 

error of 

percent 

standard 

error 2 

Lower 

bound3 

Upper 

bound3 

Absolute 

CI width4 

Relative 

CI width5 

Hispanic 

Under 100% . . . . . . . . . . . . . . . . . . . . . 1,675 559.3 1.43 0.50 35.2 0.62 2.79 2.18 152.7 

100%–199% . . . . . . . . . . . . . . . . . . . . . 1,744 1,061.7 1.55 0.38 24.4 0.90 2.49 1.59 102.6 

200%–399% . . . . . . . . . . . . . . . . . . . . . 1,621 586.8 1.10 0.43 39.1 0.42 2.32 1.90 172.0 

400% and higher . . . . . . . . . . . . . . . . . 903 516.1 0.80 0.39 49.1 0.22 2.00 1.78 223.6 

Non-Hispanic white 

Under 100% . . . . . . . . . . . . . . . . . . . . . 2,468 1,514.3 3.21 0.45 14.1 2.38 4.22 1.85 57.5 

100%–199% . . . . . . . . . . . . . . . . . . . . . 3,650 3,167.7 2.86 0.30 10.3 2.31 3.51 1.19 41.7 

200%–399% . . . . . . . . . . . . . . . . . . . . . 6,419 4,713.9 2.36 0.22 9.4 1.95 2.84 0.89 37.7 

400% and higher . . . . . . . . . . . . . . . . . 8,020 4,909.4 1.78 0.19 10.5 1.43 2.19 0.76 42.7 

Non-Hispanic black 

Under 100% . . . . . . . . . . . . . . . . . . . . . 1,470 912.8 1.36 0.38 28.2 0.72 2.35 1.63 119.6 

100%–199% . . . . . . . . . . . . . . . . . . . . . 1,367 6

1,421.8 1.11 0.28 25.0 0.63 1.83 1.20 107.4 

200%–399% . . . . . . . . . . . . . . . . . . . . . 1,375 1,143.7 0.71 0.25 35.0 0.31 1.38 1.08 152.2 

400% and higher . . . . . . . . . . . . . . . . . 940 6

1,301.5 0.47 0.19 40.3 0.14 1.15 1.01 214.9 

1

Sample size divided by the design effect. It is calculated in this table using this formula:
 .
 2

Standard error divided by the estimated percent multiplied by 100%.
 

3

Lower and upper confidence bounds were computed using the Korn-Graubard method.
 

4

Difference between the upper and lower confidence bounds.
 

5

Absolute width divided by the estimated percent multiplied by 100%.
 

6

Effective sample size is greater than the sample size. Sample size is used in CI calculations.
 

NOTES: FPL is federal poverty level. CI is confidence interval. Percent estimate and its lower and upper confidence bounds are equal to the proportion estimate and its lower and upper confidence 

bounds, respectively, multiplied by 100. Standard error of percent and absolute CI width are expressed in percentage points. This table is based on Health, United States, 2014 Table 49. Numbers in the 

table are subject to rounding. 

SOURCE: NCHS, National Health Interview Survey. 
 

 

Series 2, No. 175  Page 11 

More details about the designs of 

NAMCS and NHAMCS are available 

elsewhere (22,23). 

Table IV shows the percent 

distribution of ambulatory care visits 

by setting type according to diagnosis 

group for two conditions: a) malignant 

neoplasms of the colon and rectum and 

b) malignant neoplasm of the breast. As 

these are percent distributions, the sum 

of the values across all settings is 100%, 

and the values range from less than 1% to 

more than 50%. As a result, if one value 

is suppressed among the setting types, it 

may be inferred from those shown. These 

data are an extract of a larger table found 

at: https://www.cdc.gov/nchs/data/ahcd/ 

combined_tables/2009-2010_combined_ 

web_table01.pdf. For this table, data 

for visits to office-based practices of 

physicians in primary care, surgical 

specialties, and medical specialties 

were obtained from the 2009–2010 

NAMCS, and data for visits to outpatient 

departments and emergency departments 

were obtained from the 2009–2010 

NHAMCS. 

●		 Design effects (not shown) for many 

estimates are large. Effective sample 

sizes for the percentage of malignant 

neoplasms of colon and rectum 

visits and percentage of malignant 

neoplasm of breast visits to primary 

care offices are less than 30, so these 

estimates would be suppressed. 

●		 Absolute CI widths for the 

percentage of malignant neoplasms 

of colon and rectum visits and the 

percentage of malignant neoplasm 

of breast visits to emergency 

departments are less than 5 

percentage points, so these estimates 

could be presented if the number of 

events is not 0 (and not equal to the 

denominators) and the other criteria 

for presentation are met. 

●		 Absolute CI widths for the 

percentage of malignant neoplasms 

of colon and rectum visits and the 

percentage of malignant neoplasm 

of breast visits in medical specialty 

physician offices are greater than 30 

percentage points, so these estimates 

would be suppressed. 

●		 Degrees of freedom are all greater 

than 8 and the numbers of events are 

all greater than 0 (and not equal to 

the denominator), so estimates that 

meet all other sample size and CI 

criteria for presentation would be 

presented. 

●		 The RSE for the percentage of 

malignant neoplasms of colon and 

rectum visits made to emergency 

departments is greater than 30%, 

so this estimate would have been 

suppressed or identified as unreliable 

using the RSE > 30% criterion 

but would be presented using 

the NCHS Data Standards for 

Proportions. 

●		 The RSEs for the percentage of 

malignant neoplasms of colon and 

rectum visits and the percentage 

of malignant neoplasm of breast 

visits in medical specialty physician 

offices are each less than 30%, so 

these estimates would have been 

presented using the RSE > 30% 

suppression criterion but would be 

suppressed using the NCHS Data 

Standards for Proportions. 

National Survey of Family 

Growth 

The primary purpose of the National 

Survey of Family Growth (NSFG) 

is to produce national estimates of: 

factors affecting pregnancy, including 

sexual activity, contraceptive use, and 

infertility; medical care associated with 

contraception, infertility, and childbirth; 

factors affecting marriage, divorce, 

cohabitation, and family building; 

adoption and caring for nonbiological 

children; fathers’ involvement with their 

children; use of sexual and reproductive 

Table IV. Percentage of ambulatory care visits, by setting type according to diagnosis: United States, 2009–2010 

Effective Standard Relative 

Diagnosis and setting type

 Sample 

size 

sample 

size1 

Percent 

estimate 

error of 

percent 

standard 

error 2 

Lower 

bound3 

Upper 

bound3 

Absolute 

CI width4 

Relative 

CI width5 

Degrees of 

freedom 

Malignant neoplasms of colon and rectum 

Primary care office . . . . . . . . . . . . . . . . . . . . 411 22.4 6

12.4 6.6 56.2 2.4 33.0 30.6 247.7 52 

Surgical specialty office . . . . . . . . . . . . . . . . 411 68.1 17.3 4.6 26.5 9.2 28.4 19.2 110.6 52 

Medical specialty office. . . . . . . . . . . . . . . . . 411 37.5 7

53.4 8.2 15.3 36.5 69.8 33.3 62.4 52 

Hospital outpatient department . . . . . . . . . . 411 64.4 16.3 4.6 28.2 8.3 27.6 19.3 118.3 52 

Hospital emergency department. . . . . . . . . . 411 8

416.7 0.6 0.4 64.3 0.1 1.9 1.8 311.2 52 

Malignant neoplasm of breast 

Primary care office . . . . . . . . . . . . . . . . . . . . 1,006 22.3 6

10.4 6.5 62.0 1.6 30.7 29.1 278.8 77 

Surgical specialty office . . . . . . . . . . . . . . . . 1,006 97.8 19.4 4.0 20.6 12.1 28.6 16.5 85.3 77 

Medical specialty office. . . . . . . . . . . . . . . . . 1,006 42.4 7

54.2 7.6 14.1 38.2 69.6 31.4 57.9 77 

Hospital outpatient department . . . . . . . . . . 1,006 71.4 15.8 4.3 27.4 8.2 26.3 18.1 114.8 77 

Hospital emergency department. . . . . . . . . . 1,006 57.7 0.2 0.1 27.4 0.0 0.8 0.7 316.8 77 

1

Sample size divided by the design effect. It is calculated in this table using this formula: . 2

Standard error divided by the estimated percent multiplied by 100%. 

3

Lower and upper confidence bounds were computed using the Korn-Graubard method. 

4

Difference between the upper and lower confidence bounds. 

5

Absolute width divided by the estimated percent multiplied by 100%. 

6

Effective sample size is less than 30. Estimate would be suppressed. 

7

Absolute CI width is greater than or equal to 30. Estimate would be suppressed. 

8

Effective sample size is greater than sample size. Sample size used in CI calculations. 

NOTES: CI is confidence interval. Percent estimate and its lower and upper confidence bounds are equal to the proportion estimate and its lower and upper confidence bounds, respectively, multiplied 

by 100. Standard error of percent and absolute CI width are expressed in percentage points. Numbers in the table are subject to rounding. 

SOURCES: NCHS, National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey. 
 

 

Page 12  Series 2, No. 175 

health services; and men’s and women’s points for all outcomes, so the relative 

attitudes about sex, childbearing, and CI width would be examined for these 

marriage. Since NSFG began in 1973, groups. 

there have been nine data file releases. ● The relative CI widths for fathers aged 

The most current release of data for 15–24 are greater than 130% for all 

2013–2015 contains information on more outcomes, so these estimates would 

than 10,000 persons aged 15–44, with be suppressed. 

oversamples of non-Hispanic black and ● Degrees of freedom are all greater 

Hispanic adults and teenagers. See the than 8 and the numbers of events 

survey’s website for more information are all greater than 0 (and not equal 

and results from NSFG (24). to the denominator), so percentages 

Table V shows the percentage of that meet all other sample size and 

fathers who live with their children by CI criteria for presentation would be 

how often they played with their children presented. 

in the past 4 weeks and father’s age (25). ● The RSE > 30% for fathers aged 

Percentage estimates in this table range 35–44 for all outcomes indicates that 

from 0.04% for fathers aged 35–44 who these percentages would have been 

never play with their children to 4.04% suppressed or identified as unreliable 

of fathers aged 15–24 who play with their using the RSE > 30% criterion. 

children once a week or less, including These percentages would be presented 

never. The number of events (numerators) using the NCHS Data Presentation 

for these estimates ranged from 1 to 29. Standards for Proportions. 

● All sample sizes and effective sample ● The RSE > 30% for fathers aged 

sizes are 30 or higher. 15–24 for all outcomes indicates 

● The absolute CI width is less than 5 that these estimates would have 

percentage points for all estimates been suppressed or identified as 

for fathers aged 25–34 and 35–44, unreliable using the RSE > 30% 

indicating that these estimates could criterion. These percentages would 

be presented if the number of events is be suppressed using the NCHS 

greater than 0 and degrees of freedom Data Presentation Standards for 

are 8 or more. Proportions. 

● The absolute CI width for fathers aged 

15–24 is between 5 and 30 percentage 

Vital Statistics 

NCHS’ Division of Vital Statistics 

(DVS) provides the official statistics for 

the United States on births and deaths, 

including fetal deaths. These statistics 

are based on information collected 

from the 57 independent registration 

jurisdictions where the events occurred 

(26). Vital statistics birth data contain 

information on characteristics of the 

parents and infant, including: race and 

Hispanic origin of mother and father, age 

of mother and father, live-birth order, 

marital status of mother, gestational 

age, birthweight, and plurality of birth. 

Mortality data include information on 

cause of death, sex, race and Hispanic 

origin, and educational attainment of the 

decedent, among other characteristics. 

Data files on births and deaths are 

released annually. 

Prior to the implementation of the 

NCHS Data Standards for Proportions, 

when displaying vital statistics data 

in standard NCHS reports, an asterisk 

had been shown in place of any derived 

statistic based on fewer than 20 events 

(26). The new reporting standards apply 

to proportions, used mostly to describe 

various indicators from the birth data 

(e.g., percentage low birthweight). Like 

proportions from the NCHS population or 

Table V. Percentage of fathers aged 15–44 with children under age 5 years who live with their children, by how often they played with their 

children in the last 4 weeks and father’s age: United States, 2006–2010 

How often fathers played with Effective Standard Relative 

their children in the last 4 weeks 

and father’s age (years)

 Sample 

size 

sample 

size1 

Percent 

estimate 

error of 

percent 

standard 

error 2 

Lower 

bound3 

Upper 

bound3 

Absolute 

CI width4 

Relative 

CI width5 

Degrees of 

freedom 

Number of 

events 

Never 

15–24 . . . . . . . . . . . . . . . . . . . . . . . . 212 80.5 6

1.95 1.54 79.0 0.14 8.06 7.91 405.5 47 3 

25–34 . . . . . . . . . . . . . . . . . . . . . . . . 989 7

2,020.6 0.26 0.11 43.3 0.05 0.82 0.78 295.3 92 6 

35–44 . . . . . . . . . . . . . . . . . . . . . . . . 587 7

2,724.2 0.04 0.04 99.5 0.00 0.70 0.70 1,892.7 88 1 

Once a week or less 

15–24 . . . . . . . . . . . . . . . . . . . . . . . . 212 78.8 6

2.09 1.61 77.1 0.17 8.38 8.21 393.0 47 4 

25–34 . . . . . . . . . . . . . . . . . . . . . . . . 989 743.4 1.65 0.47 28.3 0.86 2.87 2.01 121.8 92 23 

35–44 . . . . . . . . . . . . . . . . . . . . . . . . 587 506.6 0.58 0.34 58.0 0.12 1.73 1.61 276.1 88 8 

Once a week, less, or never 

15–24 . . . . . . . . . . . . . . . . . . . . . . . . 212 81.4 6

4.04 2.18 54.0 0.89 11.10 10.21 252.6 47 7 

25–34 . . . . . . . . . . . . . . . . . . . . . . . . 989 806.7 1.92 0.48 25.2 1.08 3.14 2.06 107.4 92 29 

35–44 . . . . . . . . . . . . . . . . . . . . . . . . 587 559.5 0.62 0.33 53.5 0.15 1.70 1.56 250.7 88 9 

1

Sample size divided by the design effect. It is calculated in this table using this formula:
 .
 2

Standard error divided by the estimated percent multiplied by 100%.
 

3

Lower and upper confidence bounds were computed using the Korn-Graubard method.
 

4

Difference between the upper and lower confidence bounds.
 

5

Absolute width divided by the estimated percent multiplied by 100%.
 

6

Relative CI width is greater than 130%. Estimate would be suppressed.
 

7

Effective sample size is greater than sample size. Sample size used in CI calculations.
 

NOTES: CI is confidence interval. Percent estimate and its lower and upper confidence bounds are equal to the proportion estimate and its lower and upper confidence bounds, respectively, multiplied 

by 100. Standard error of percent and absolute CI width are expressed in percentage points. Numbers in the table are subject to rounding. 

SOURCE: NCHS, National Survey of Family Growth. 
Series 2, No. 173  Page 13 

establishment surveys described earlier, ● The absolute CI width is greater than 

some proportions from vital statistics 0.00 and less than 0.05 (less than 

are multiplied by 100 and referred to 5,000 when multiplied by 100,000) 

as percentages (e.g., percentage low for all groups, indicating that these 

birthweight). However, as in the example proportions could be presented if all 

shown below, other proportions from other criteria are met. 

vital statistics, for rarer outcomes, are ● Using the previous DVS criterion 

multiplied by 1,000 or 100,000. where statistics based on fewer than Table VI shows the proportion of 20 events would be suppressed or 

triplet and higher-order multiple births identified as unreliable, statistics 

for mothers aged 10–19 and 40–54 by for several of the age and race and 

race and Hispanic origin multiplied by Hispanic-origin subgroups in 

100,000. This table is based on Table 26 in Table VI would not be shown. 

Births: Final data for 2015 (27). Statistics However, using the NCHS Data 

shown in Table VI range from 15.4 triplet Presentation Standards for 

and higher-order multiple births per Proportions, these estimates would 

100,000 live births to mothers aged 18–19 be presented. 

to 649.9 triplet and higher-order multiple 

births per 100,000 births to mothers 

aged 45–54. The number of triplet and 

higher-order multiple births (events in the 

numerator) for these statistics ranges from 

0 to 267, and the number of live births for 

each population subgroup ranges from 

1,240 to 229,715. The degrees of freedom 

criterion, used as a measure of precision 

for SEs from complex surveys, does not 

apply to vital statistics. 

● The sample size (i.e., the number 

of live births in the denominator) 

is 30 or higher for all population 

subgroups shown. 

● The number of triplet and higherorder multiple births (events in the 

numerator) for non-Hispanic white 

mothers aged 15–17 is 0. The number 

of live births is 20,406. If all other 

criteria are met for presentation, 

a proportion based on a 0 number 

of events would be flagged for 

statistical review and considered for 

presentation based on the validity of 

the point and interval estimates. 
Page 14  Series 2, No. 175 

Table VI. Proportion of triplet and higher-order multiple births, by age and race and Hispanic origin of mother for mothers aged 15–19 

and 40–54: United States, 2015 

Standard error Absolute 

Proportion of proportion Lower bound Upper bound CI width 

Age (years) and race and 

Hispanic origin of mother 

Number of 

events1 Sample size2 

(multiplied by 

100,000) 

(multiplied by 

100,000) 

(multiplied by 

100,000)3 

(multiplied by 

100,000)3 

(multiplied by 

100,000)4 

Relative 

CI width5 

15–19 

All races and Hispanic origins . . . . . . . . . . . . 41 229,715 17.8 2.8 12.8 24.2 11.4 64.0 

Non-Hispanic white. . . . . . . . . . . . . . . . . . . . . 5 90,833 5.5 2.5 1.8 12.8 11.0 200.0 

Non-Hispanic black. . . . . . . . . . . . . . . . . . . . . 15 50,039 30.0 7.7 16.8 49.4 32.6 108.7 

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 80,364 18.7 4.8 10.4 30.8 20.4 109.1 

15–17: 

All races and Hispanic origins . . . . . . . . . . . . 15 61,184 24.5 6.3 13.7 40.4 26.7 109.0 

Non-Hispanic white. . . . . . . . . . . . . . . . . . . . . – 20,406 6 

– --­ – 18.1 18.1 --­

Non-Hispanic black. . . . . . . . . . . . . . . . . . . . . 3 14,366 20.9 12.1 4.3 61.0 56.7 271.3 

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 24,187 49.6 14.3 25.6 86.6 61.0 123.0 

18–19: 

All races and Hispanic origins . . . . . . . . . . . . 26 168,531 15.4 3.0 10.1 22.6 12.5 81.2 

Non-Hispanic white. . . . . . . . . . . . . . . . . . . . . 5 70,427 7.1 3.2 2.3 16.6 14.3 201.4 

Non-Hispanic black. . . . . . . . . . . . . . . . . . . . . 12 35,673 33.6 9.7 17.4 58.8 41.4 123.2 

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 56,177 5.3 3.1 1.1 15.6 14.5 273.6 

40–44 

All races and Hispanic origins . . . . . . . . . . . . 267 111,848 238.7 14.6 211.0 269.1 58.1 24.3 

Non-Hispanic white. . . . . . . . . . . . . . . . . . . . . 151 55,040 274.3 22.3 232.4 321.7 89.3 32.6 

Non-Hispanic black. . . . . . . . . . . . . . . . . . . . . 44 14,592 301.5 45.4 219.2 404.6 185.4 61.5 

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 27,117 177.0 25.5 130.5 234.6 104.1 58.8 

45–54 

All races and Hispanic origins . . . . . . . . . . . . 58 8,925 649.9 85.1 493.8 839.3 345.5 53.2 

Non-Hispanic white. . . . . . . . . . . . . . . . . . . . . 26 4,657 558.3 109.2 365.0 817.0 452.0 81.0 

Non-Hispanic black. . . . . . . . . . . . . . . . . . . . . 9 1,240 725.8 241.1 332.4 1,373.3 1,040.9 143.4 

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1,519 724.2 217.6 362.0 1,292.0 930.0 128.4 

– Quantity zero.
 

--- Data not available.
 

1

Statistics based on fewer than 20 events would have been suppressed using prior criteria for these statistics from vital statistics.
 

2

Sample size is the number of live births.
 

3

Lower and upper CI bounds were computed using the Clopper-Pearson method.
 

4

Difference between the upper and lower confidence bounds.
 

5

Absolute width divided by the estimate and multiplied by 100%.
 

6

Number of events is 0. Estimate would be flagged for statistical review by the clearance official and may be presented or suppressed.
 

NOTE: Numbers in the table are subject to rounding. 

SOURCE: NCHS, National Vital Statistics System. 
Series 2, No. 175  Page 15 

Vital and Health Statistics 

Series Descriptions 

Active Series 

Series 1. Programs and Collection Procedures 

Reports describe the programs and data systems of the 

National Center for Health Statistics, and the data collection 

and survey methods used. Series 1 reports also include 

definitions, survey design, estimation, and other material 

necessary for understanding and analyzing the data. 

Series 2. Data Evaluation and Methods Research 

Reports present new statistical methodology including 

experimental tests of new survey methods, studies of vital and 

health statistics collection methods, new analytical techniques, 

objective evaluations of reliability of collected data, and 

contributions to statistical theory. Reports also include 

comparison of U.S. methodology with those of other countries. 

Series 3. Analytical and Epidemiological Studies 

Reports present data analyses, epidemiological studies, and 

descriptive statistics based on national surveys and data 

systems. As of 2015, Series 3 includes reports that would 

have previously been published in Series 5, 10–15, and 20–23. 

Discontinued Series 

Series 4. 	 Documents and Committee Reports 

Reports contain findings of major committees concerned with 

vital and health statistics and documents. The last Series 4 

report was published in 2002; these are now included in 

Series 2 or another appropriate series. 

Series 5. 	 International Vital and Health Statistics Reports 

Reports present analytical and descriptive comparisons of 

U.S. vital and health statistics with those of other countries. 

The last Series 5 report was published in 2003; these are now 

included in Series 3 or another appropriate series. 

Series 6. 	 Cognition and Survey Measurement 

Reports use methods of cognitive science to design, evaluate, 

and test survey instruments. The last Series 6 report was 

published in 1999; these are now included in Series 2. 

Series 10. 	 Data From the National Health Interview Survey 

Reports present statistics on illness; accidental injuries; 

disability; use of hospital, medical, dental, and other services; 

and other health-related topics. As of 2015, these are included 

in Series 3. 

Series 11.	 Data From the National Health Examination Survey, the 

National Health and Nutrition Examination Surveys, and 

the Hispanic Health and Nutrition Examination Survey 

Reports present 1) estimates of the medically defined 

prevalence of specific diseases in the United States and the 

distribution of the population with respect to physical, 

physiological, and psychological characteristics and 2) 

analysis of relationships among the various measurements. 

As of 2015, these are included in Series 3. 

Series 12. 	 Data From the Institutionalized Population Surveys 

The last Series 12 report was published in 1974; these reports 

were included in Series 13, and as of 2015 are in Series 3. 

Series 13. 	 Data From the National Health Care Survey 

Reports present statistics on health resources and use of 

health care resources based on data collected from health 

care providers and provider records. As of 2015, these reports 

are included in Series 3. 

Series 14.	 Data on Health Resources: Manpower and Facilities 

The last Series 14 report was published in 1989; these reports 

were included in Series 13, and are now included in Series 3. 

Series 15. 	 Data From Special Surveys 

Reports contain statistics on health and health-related topics 

from surveys that are not a part of the continuing data systems 

of the National Center for Health Statistics. The last Series 15 

report was published in 2002; these reports are now included 

in Series 3. 

Series 16. 	 Compilations of Advance Data From Vital and Health 

Statistics 

The last Series 16 report was published in 1996. All reports 

are available online; compilations are no longer needed. 

Series 20.	 Data on Mortality 

Reports include analyses by cause of death and demographic 

variables, and geographic and trend analyses. The last Series 

20 report was published in 2007; these reports are now 

included in Series 3. 

Series 21.	 Data on Natality, Marriage, and Divorce 

Reports include analyses by health and demographic 

variables, and geographic and trend analyses. The last Series 

21 report was published in 2006; these reports are now 

included in Series 3. 

Series 22. 	 Data From the National Mortality and Natality Surveys 

The last Series 22 report was published in 1973. Reports from 

sample surveys of vital records were included in Series 20 or 

21, and are now included in Series 3. 

Series 23.	 Data From the National Survey of Family Growth 

Reports contain statistics on factors that affect birth rates, 

factors affecting the formation and dissolution of families, and 

behavior related to the risk of HIV and other sexually 

transmitted diseases. The last Series 23 report was published 

in 2011; these reports are now included in Series 3. 

Series 24. 	 Compilations of Data on Natality, Mortality, Marriage, and 

Divorce 

The last Series 24 report was published in 1996. All reports 

are available online; compilations are no longer needed. 

For answers to questions about this report or for a list of reports published 

in these series, contact: 

Information Dissemination Staff 

National Center for Health Statistics 

Centers for Disease Control and Prevention 

3311 Toledo Road, Room 4551, MS P08 

Hyattsville, MD 20782 

Tel: 1–800–CDC–INFO (1–800–232–4636) 

TTY: 1–888–232–6348 

Internet: https://www.cdc.gov/nchs 

Online request form: https://www.cdc.gov/info 

For e-mail updates on NCHS publication releases, subscribe 

online at: https://www.cdc.gov/nchs/govdelivery.htm. 
 

 

 

 

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