. . –—

.

Diet and Dental

Health, A study of

ReIatiomMps:

United States, 1971-74

This report presents findings on the

relationship between dietary intake and dental

health from the first National Health and

Nutrition Examination Survey, a national

probabilityy sample survey that was conducted

in 1971-74. Data on decayed, missing, and

filled permanent teeth and on the periodontal

index are examined using regression

techniques in relation to food intake, fluoride

concentration, tooth-brushing frequency,

smoking history, and alcohol consumption.

Data From the National Health Suwey

Series 11, No. 225

DHHS Publication No. (PHS) 82-1675

U.S. Department of Health and Human Services

Public Health Service

Office of Health Research, Statistics,

and Technology

National Center for Health Statistics

Hyattsville, Md.

January 1982
Library of CorsWaasCatofoging in Publication Data

Diet and Dental Health, A Study of Relatimships: United States,

1971-74.

(Vital and haalth statistics. Series 11, Data from the national health

survey; no. 225} (DHHS publication; (PHS) 82-1675)

Bibliography: p. 27

1. Nutrition and dental haalth-Unitad States. 2. Den~l SuMYS_

‘,UnitOd statES.3.Nutrition surveys-Unitad State$i 4. H@th and

Nutrition Examination Survay. 5. Regression analysis. 1.8urt, 8rian

Aubrey. i 1.Series. II 1.Series. DHHS publication; (PHS) 82-1675.

[DNLM: 1. DMF index. 2. Periodontal index. 3. Nutrition surveys–

United Statasdiet surveys. 4. Diet–Advarsa affacts-Statist ics.

5. Mouth disaases-Etiology -Statistics. 6. Tooth diseesas-Etiology–

Statistics. W2 A N 148vk no. 2251

RA407.3.A347 no. 225 [RK281 ] 312“.0873s 81-14233

IS8N 0B40&0235-9 [61 7.6’30711 AACR2

For sale by the Superintendent of Documents, U.S. Government Printing 013ce, Washington, D.C. 20402

L
National Center for Health Statistics

DOROTHY P. RICE, Director

ROBERT A. ISRAEL, Deputy Director

JACOBJ. FELDMAN,Ph.D., Associate Director for Analysis

and Epidemiology

GAIL F. FISHER, Ph.D., Associate Director for the

Cooperative Health Statistics System

GARRIE J. LOSEE, Associate Director for Data Processing

and Services

ALVAN O. ZARATE, Ph.D., Assistant Director for

International Statistics

E. EARL BRYANT,Associate Director for Interview and

Examination Statistics

ROBERT C. HUBER,Associate Director for Management

MONROE G. SIRKEN, Ph.D., Associate Director for Research

and Methodology

PETER L. HURLEY, Associate Director for Vital and Health

CareStatistics

ALICE HAYWOOD,Information Officer

Office of Interview and Examination Statistics Program

E. EARL BRYANT,Associate Director

MARY GIU4CEKOVAR, Special Assistant for Data Policy and

Analysis

Division of Health Examination Statistics

ROBERT S. MURTHY,Director

KURT R. MAURER, Chief Survey Planning and Development

Branch

Cooperation of the U.S. Bureau of the Census

Under the legislation establishing the National Health Survey, the

Public Health Service is authorized to use, insofar as possible, the

services or facilities of other Federal, State, or private agencies. In

accordance with specifications established by the National Center for

Health Statistics, the U.S. Bureau of the Census participated in the

design and selection of the sample and carried out the household

interview stage of the data collection and certain parts of the statistical

processing.

SIDNEY ABRAHAM,Chief Nutrition Statistics Branch

JEAN ROBERTS, Chie~ Medical Statistics Branch
Foreword and

Acknowledgments

The National Health and Nutrition Examination Survey

(NHANES) is the only source of general U.S. population data

that providesa directlinkbetweenindicators of health and

nutritional status and reported dietary intake information. The

Congress provided resources in the Departments of Labor and

Health, Education, and Welfare, and Related Agencies Appropriation Bill, 1980 to the National Center for Health Statistics

(NCHS) to fund an initiative to undertake more detailed analyses of nutrition-related health problems as measured in the

first NHANES. As part of this initiative, the Division of Health

Examination Statistics funded a contract (no. 223-79-2092)

with the School of Public Health at the University of Michigan

to examine relationships among dietary intake, food consumption patterns, and measures of dental health.

The approach and depth of analysis presented in this

report differ from previous reports from the Division of Health

Examination Statistics. This report is based on a statistical

rather than a descriptive presentation of the data. The tables

and text present the results of a regression analysis that incorporates the full design effect of the complex survey.

Cognizant that the underlying assumptions of traditional

statistical anrdyses are violated to some extent, the degree of

which is unknown, the authors and NCHS staff jointly determined that the assumptions made in the analyses presented in

this report are reasonable in light of present knowledge. In

addition, the authors have presented throughout the text and

technical appendix material concerning appropriate qualifications that the reader should consider in interpreting the results

and conclusions presented.

Mary Grace Kovar, the NCHS Project Officer, was instrumental in bringing the project to a successful completion. Her

continuing interaction with the authors and their cooperation

throughout the project aided the Center in dealing with difficult and highly technical analytic issues not faced previously

by NCHS.

The authors gratefully acknowledge the technical assistance of Sharon A. Stehouwer, Ruth A. Serokman, James M.

Lepkowski, and Edward DeVol in many aspects of data

processing, implementation of the statistical analysis, text

processing, and proofreading of the statistical appendix.

) Robert S. Murphy

Director

Division of Health Examination Statistics

...

Ill
Foreword and Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Sources and limitations ofdata. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The dental examination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Nutritional data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Limitations ofdata interpretation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Analytic approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Highlights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Detailed results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Dental decay anddietary intakepatterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Relationship between the number ofdecayed, missing, and filled teeth and the enamel fluoride contentof theteeth. . . . .

Relationship between dental caries experienceandthecalcium/phosphorus ratio. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Relationship between dental caries experience and periodontal disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Relationship between periodontal disease and alcohol consumption, tooth brushing, and smoking . . . . . . . . . . . . . . . . .

Relationship between dietary intake patterns of adults with natural teeth and those of adults without natural teeth or

whose remaining teethareindicated for extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Relationship between dietary intake patterns anduseof artificial dentures foresting byedentulous adults . . . . . . . . . . .

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Listofdetailed tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Appendixes

1. Statistical notes. . . . . . . . . . . . . . . . . . . . . . . ..ti . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Il. Definitions ofterms andvariables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

111. Thedental examination.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

List of Text Tables

A.

B.

c.

D,

Model-based estimates of mean number ofdecayed, missing, and filled (DMF) permanent teeth, by calories from sugarrich foods as apercent oftotal calories ingested, for persons ages 6-64 years: United States, 1971-74 . . . . . . . . . . . .

Model-based estimates of mean number ofdecayed, missing, and filled (DMF) permanent teeth, by calories from sugarrich foods consumed between meals as a percent of total calories ingested, forpersons ages 6-64 years: United States,

1971-74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Model-based estimates of mean number ofdecayed, missing, andfilled (DMF) permanent teeth, by stated frequency of

consumption of sugar-rich foods between meals, for persons ages 6-64 years: United States, 1971-74 . . . . . . . . . . . .

Model-based estimates ofmean numberof decayed, missing, and filled (DMF) permanent teeth, by stated frequency of

consumption of non-sugar-rich foods between meals, for persons ages 6-64 years: United States, 1971-74 . . . . . . . . .

...

Ill

1

3

3

3

4

6

8

10

10

14

16

17

18

21

26

27

29

59

73

78

11

12

13

13

v
E.

F.

G.

H.

J.

K.

L.

M.

N.

o.

P.

Q.

R.

s.

T.

u.

w.

i’.

z,

AA.

BB.

cc.

Mean number of decayed, missing, and filled (DMF) permanent teeth for white males, by age and fluoride concentration ofenamel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mean number of decayed, missing, and filled (DMF) permanent teeth forwhite females, by age and fluoride concentration of enamel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Number ofwhite males examined, by age and fluoride concentration ofenamel . . . . . . . ., . . . . . . . . . . . . . . . . . .

Number ofwhite females examined, by age and fluoride concentration ofenamel. . . . . . . . . . . . . . . . . . . . . . . . . .

Number ofexaminees (n), mean number of decayed, missing, and filled (DMF) permanent teeth, and periodontal index

(PI} score, by age group and biopsy status for persons ages 18-74 years: United States, 1971 -74 . . . . . . . . . . . . . . . .

Model-based estimates of mean number of decayed, missing, and filled (DMF) permanent teeth, by various periodontal

index (Pl)scores, for three age groups: United States, 1971-74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Model-based estimates of mean number of decayed, missing, and filled (DMF) permanent teeth, by various periodontal

index (Pi) scores, for three age groups from whom enamel biopsies were taken: United States, 1971-74. . . . . . . . . . .

Model-based estimates of mean number of decayed, missing, and filled (DMF) permanent teeth, by various periodontal

index (Pi ) scores, for three age groups from whom no enamel biopsies were taken: United States, 1971-74 . . . . . . . .

Average and median periodontal index (Pi) scores per person among persons ages 25-74 years, by drinking category,

with standard errors and sample sizes: United States, 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Average and median residual of periodontal index (P1) scores per person among persons ages 25-74 years, by drinking

category, with standard errors and sample sizes: United States, 197’1-74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Average and median periodontal index (Pi) scores per person among persons ages 25-74 years, by tooth-brushing frequency, with standard errors and sample sizes: United States, 1971-74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Percent of persons ages 25-74 years with periodontal index (P1) scores of zero and greater than zero, by tooth-brushing

freql~ency: United States, 1971-74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Average and median periodontal index (Pi) scores per person among persons ages 25-74 years, by smoking history, with

standard errors and sample sizes: United States, 1971 -74...... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Percent of persons ages 25-74 years with periodontal index (Pl ) scores of zero and greater than zero, by smoking

history :United States, 1971-74.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mean and median percent of N HAN ES standards for selected dietary components, by dental status for white males ages

18-74 years, with standard errors: United States, 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mean and median percent of NHANES standards for selected dietary components, by dental status for white females

ages 18-74 years, with standard errors: United States, 1971-74. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . .

Mean and median percent of NHANES standards for selected dietary components, by dental status for black males ages

18-74 years, with standard errors: United States, 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mean and median percent of NHANES standards for selected dietary components, by dental status for black females

ages 18-74 years, with standard errors: United States, 1971-74. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Percent of white males ages 18-74 years at or above the recommended levels for various nutrients, by dental status:

United States, 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Percent of white females ages 18-74 years at or above the recommended levels for various nutrients, by dental status:

United States, l!371-74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Percent of black males ages 18-74 years at or above the recommended levels for various nutrients, by dental status:

United States, 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Percent of black females ages 18-74 years at or above the recommended levels for various nutrients, by dental status:

United States, 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

15

15

15

15

16

17

18

18

19

19

20

21

21

21

22

23

23

24

24

25

25

26
Symbols

--- Data not available

. . . Category not applicable

Quantity zero

0.0 Quantity more than zero but lessthan

0.05

z Quantity more than zero but lessthan

500

*

Figure does not meet standards of

reliability or precision

# Figure suppressed to comply with

confidentiality requirements

vii
Diet and Dental Health,

A Study of Relationships

by Brian A. Burt, B.D. Se., M. P.H., Ph.D.; Stephen A. Eklund,

D. D.S., M. H.S.A., Dr. P.H.; J. Richard Landis, Ph.D.; Frances

A. Larkin, Ph.D.; Kenneth E. Guire, M.S.; and Frances E.

Thompson, M. P.H., School of Public Health, The University

of Michigan

Introduction

The National Health and Nutrition Examination

Survey is one of a series of surveys conducted by the

National Center for Health Statistics. It is unique in

that specially designed and constructed mobile examination centers are moved to selected sample areas so

that physical examinations can be given under standardized conditions in a controlled environment. The

team of interviewers and examiners also moves with

the examination centers. The standardized physical

examinations of a probability sample of the population have several advantages over other means of collecting data about the health of the population. They

are (1) the examination can be designed to focus on

specified conditions and to furnish more reliable estimates of the prevalence of the specified conditions

than can be obtained by interview; conditions unknown to the examinee can be identified and the criteria for diagnosis can be carefully specified, (2) the

use of mobile examination centers and a constant

team of trained personnel reduce the variability found

in studies using local facilities and personnel, (3) the

tistruments are recalibrated and the interviewing and

examining are monitored so the only source of variation is the person being examined. The geographically

defined probability design reduces the bias that might

be found in populations selected for specific purposes

or in areas that are not characteristic of the country.

The importance of these data for formulating

policy has already been recognized. They were a basis

for recommendations made by the Institute of Medicine in 19801 on improving dental health. The central

issue of that report is the need for implementing and

financing primary prevention programs. This report,

from the National Center for Health Statistics, complements the Institute of Medicine publication;

knowledge of the relationship between diet and

dental health is necessary to develop those prevention

programs.

The first National Health and Nutrition Examination Survey included a dental examination, a dietary

interview, and a medical history interview. Data from

these three components are the basis of this report.

This report presents relationships between various

dental examination findings and nutritional and medical history information collected during the first

National Health and Nutrition Examination Survey.

Whereas most of the previous reports on data from

this survey have been descriptive or bivariate in

nature, this report uses multiple regression analysis

techniques to explore these relationships in greater

depth.

The dental findings are based on examinations

given by 10 dentists during 1971-74 to more than

20,000 people ages 1-74 years. Those who were examined were part of a probability sample of approximately 28,000 people selected from the civilian noninstitutionalized population of the coterminous

United States, except those living on land reserved for

the use of American Indians. A detailed description

of the design, content, and operation of the survey

has been published. A brief description of the sample

design is also given in appendix I of this report. Definitions of the terms are in appendix II, and a copy of

the dental examination form is in appendix III.

Since one area of emphasis in the survey was

nutrition, the sample was selected so that certain

population groups believed to be at high risk of malnutrition (those with low incomes, preschool children,

women of childbearing age, and the elderly) were

oversampled at specified rates. Because of this oversampling, and the complexity of the sampling design

necessary in a national survey, statistical weighting

adjustments were made for the sampling design, oversampling procedure, and nonresponse. These methods

were used to adjust apparent relationships among

variables as described in detail in appendix I. The

sampling design for NHANES I is also described in

that appendix.

1
At 65 survey locations, 20,749 sample persons were

examined. Dental measurements and nutritional information were obtained from 20,218 of these 20,749

examinees. Dental data were imputed from those 531

persons whose records were lost or who did not receive

the dental examination for some reason. In addition,

a detailed medical examination was given to a subsample of 3,854 persons ages 25-74 years at the same

65 survey locations. This detailed examination included the information on smoking, dental visits, and

tooth-brushing frequency. As a result, several of the

relationships examined in this report that used this

information could only be tested among this subsample. Separate sampling weights were developed for

this detailed examination.

As part of NHANES I, there was also an “augmentation” survey of 3,059 adults ages 25-74 years

continued until October 1975 at 35 additional survey locations. However, no information from this

augmentation survey is included in this report since :a

dental examination was not part of the augmentation

survey.

Information about each sample person examined

during NHANES I was obtained by means of a household interview; a general medical history; a 24-hour

dietary intake recall interview; a food frequency irlterview; a food program questionnaire; a general

medical examination; dental, dermatological, and

ophthalmological examinations; anthropometric measurements; and 24 hematological, blood chemistry, and

urological laboratory determinations. Hand-wrist

X-rays were taken on those 1-17 years old.

Descriptive information on results of the dental

examination has been given in two reports.3 Y4 Several

descriptive reports on nutritional information in

NHANES I have also been issued,5-7 as well as a

further publication of nutritional interest from

NHANES 1.8
Sources and limitations of data

The dental examination

The dental examiners derived their findings as

uniformly as possible by following a written set of

objective standards in which they had been carefully

trained. The standards were guidelines that, in effect,

narrowed the range of examiner variability by eliminating many borderline or questionable conditions

that are frequently a source of disagreement. To avoid

other sources that might have resulted in systematic

bias, the dentists did not dry or isolate teeth, remove

oral debris and calculus, or probe tooth surfaces

unless they showed overt signs of decay.

The examining dentist dictated the condition of

each tooth present to a trained recorder (health technician). The teeth were classified as sound, filled, decayed, filled-defective, or nonfunctional. Missing

permanent teeth were classified under one of the following four categories: unerupted, carious extraction,

accidental loss, or orthodontic extraction. The

decayed-missing-filled (DMF) index,g a cumulative

index of lifetime dental caries experience, was derived

from these recordings. When missing teeth were replaced on a fixed or partial denture, the condition of

the tissue under the prosthesis as well as the adequacy

of the prosthesis itself were rated. When there were

no natural teeth remaining in a jaw, the condition of

the jaw and the status of an artificial replacement, if

one was present, were recorded.

The next step of the examination was to assess

the periodontal structures and the status of oral hygiene. The periodontal indexl 0 (PI) was used to assess

the presence or absence of periodontal disease. By

this system of classification, scores are assigned to all

teeth present in the mouth according to the extent of

gingival inflammation, the presence or absence of

periodontal pockets, and the firmness of teeth in

their sockets. To assess oral hygiene by the simplified

oral hygiene indexl 1 (OHI-S), scores are recorded for

all or any of six predesignated teeth. The scores indicate the extent of both debris and calculus on selected

tooth surfaces. Fluoride and nonfluoride opacities

and other conditions such as bleeding gums, diffuse

marginal inflammation, swollen red papillae, and

gingival recession are also recorded.

The occlusion of persons ages 6-21 years was

appraised by a series of counts and measurements.

The anteropostenor position of the Iower jaw in relation to the upper jaw was recorded. Counts were

made of malaligned teeth and posterior teeth in a

crossbite relationship. Measurements of mandibular

protrusion and anterior overjet, overbite, and openbite were taken.

An enamel biopsy was done for persons who had

an upper permanent incisor with a front surface free

of cavities and fdlings. The enamel sample was “polished off” from an area about one-eighth-inch in

diameter and approximately 0.0002-inch deep. This

is about as much enamel as that removed during a

routine cleaning by a dentist or dental hygienist. The

sample was analyzed to determine the fluoride content of the tooth it was removed from. Fluoride

biopsy samples could only be obtained from 5,481

subjects, due to unforeseen problems with equipment

and some unexpectedly high refusal rates, plus absence of the necessary teeth in very young, edentuIous, and semi-edentulous persons.

DetaiIed information on the dental examination

and a copy of the dental record form are given in appendix 111.Some data on interexaminer variability are

also given in appendix III (table XVI). Additional information about self-perceived needs for dentzd care

and the receipt of dental care is available from the

Health Care Needs Supplement.z

Nutritional data

The dietary interview was conducted with each

sample person to obtain information about total food

and drink consumption during the preceding 24 hours.

This was followed by questions about the frequency

of specific food group intake for the preceding 3

months. These interviews were conducted by dietary

3
staff who graduated from accredited colleges and universities m-d who majored in home econ-omits with

emphasis in foods and nutrition. The parent or other

adult responsible for a child’s feeding provided information about preschool children. Usually both the

parent and child were interviewed for subjects ages

6-12 years.

Information on food intake was obtained for the

day, midnight to midnight, preceding the interview.

Food recall included foods eaten on Monday through

Friday but excluded foods eaten on the weekend as

there was no examination on Sunday and Monday.

It is recognized that weekend eating patterms may differ from those during the week.l 2

The dietary interview lasted approximately 20

minutes (maximum allowance was 30 minutes) and

usually was administered in the mobile examination

center. A small percent of the interviews took place

in the subject’s home. Home visits were made for

several reasons. Some aged or ill examinees wished to

spend less time at the examination center. Some

mothers had several children who were examined, and

it was more convenient for the mothers to have the

children interviewed at home. Occasionally, home

visits were made to collect dietary information because the mother or babysitter did not accompany a

child to the examination center or because translators

were needed when the examinee did not know enough

English to understand or answer the interviewer.

Food portion models were used to assist the

respondent in estimating amounts of foods consumed.

The models developed for another surveylg were used

with slight modifications. A computer program, used

to determine nutrient values of foods consumed was

adapted from one developed and used in the TenState Nutrition Survey14 and was based on a program

developed originally at Tulane Universit y. The original

nutrient data base used in NHANES I was derived

from the U.S. Department of Agriculture Handbook

No. 8 (1963), table 1,15 as well as information from

other sources. Because of the constantly changing

food supply, nutrient composition values for existing

or new food products were added or updated continually according to information provided by the U.S.

Department of Agriculture, food processors, and

manufacturers.

The constituents of the food groups used in the

24-hour recall data are shown in appendix II. Major

sources of calories and specific nutrients are also

shown in appendix II, as are problems associated with

deficiency and standards for evaluation of daily nutritional intakes used in NHANES I (tables XIV and XV).

The food frequency method served as a quality

control technique for the 24-hour recall method of

obtaining data while depicting diet profile patterns

over a longer period of time. The frequency of consumption of food from the food groups ingested daily

and/or weekly over the 3-month interval prior to the

nutrition interview

quency interview.

was obtained from the food freAll regular meals and betweenmeals foods or snacks eaten during the week (inclucling special occasions and holidays) were reported in

six frequency categories.

Limita~tions of data interpretation

Th[e analyses presented in this report are crosssectional in nature, and therefore are subject to the

limitations of all cross-sectional studies. These limitations relate principally to the fact that data collected

can be difficult to apply directly to the answering o,f

questions generated after the survey is completed.

Several such instances were encountered in these

analyses, with the result that questions sometimes

could not be answered completely. Others were a~-

proached through the generation of new variables

from those provided.

Relationships found among these data can also

demonstrate only associations, they can not show

causal relationships. Some of the associations prdsented in this report are probably of a causal natur~

since they confirm the results of other studies, while

others may be chance relationships. Although the

temptation to impute cause-and-effect from the data

in N13!ANES I is strong, to succumb would be tb

stretch the data beyond their limitations.

There are some inherent difficulties in associating

the dental and dietary data gathered in the NHANES:1

survey. These problems stem from the fact that the

DMF index is a cumulative measure of lifetime dental

caries experience, while the 24-hour dietary history

records a recent event. To make the associations valid,

the dietary history recorded for the previous da~y

would need to typify a lifetime diet, whic$hin most

cases is probably unlikely. A 40-year-old person, fck

example, probably accumulated the bulk of his or her

recorded dental caries experience between the ages of

10 and 24. The dietary history recorded, in many

cases, would not typify the dietary habits at that

time. In view of these circumstances, when relatiotiships i]re found it seems more likely that they are real

rather than due to chance; their magnitude could also

be underestimated. In addition, it is likely that mumerous confounding variables are present that act

to obf~cure relationships between dietary history and

caries experience.

Variability in day-to-day eating patterns makes ‘

the 24-hour dietary record potentially misleading for

correlation analysis on an individual basis.l 6-20 Results of these studies on the validity of 24-hour

dietary recalls suggest that recall is subject to overrepor~ing of low intakes and underreporting of high

intakes, thus increasing the danger of false negatilte

information.

An additional problem related to the 24-hotir

recall as an estimate of long-term dietary patterns is

4
the measurement error caused by day-to-day variation

in individual dietary patterns. This kind of error in an

independent variable in a regression equation will bias

the estimates of the coefficients toward zero. However, because some empirical work has provided estimates of the ratio of interindividual (true betweensubject variation in usual intake) to intraindividual

(day-to-day variation in individual intake) variation,

estimates of the magnitude of this bias are possible.zl

Given these inherent deficiencies in the nature of the

24-hour dietary recall data together with the potential for some statistical correction of these deficiencies, it is estimated that the trends in dental caries

experience related to lifetime dietary patterns, as presented in this report, are likely to be underestimated.

A further limitation to be recognized with respect

to the dental data is the likely influence of what is

called “the treatment effect” in the information obtained. The treatment effect means that the DMF

teeth count cannot necessarily be interpreted at face

value solely as a measure of caries experience; it also

reflects to some extent the type of treatment available and utilized by the individuals throughout their

lives. It is likely, for example, that some filled teeth

(therefore counted in the F part of DMF) would not

have been diagnosed as carious by the examining

dentists in the NHANES I survey had they been seen

before they were ftied. Another way of expressing

this problem is that criteria used by dental practitioners to make a decision on whether or not to fill a

tooth are not the same as the criteria used by epidemiologists in determining whether a tooth is to be

called sound or carious.22>23 The possibility must,

therefore, be entertained that a person with a given

DMF tooth score, of which a high percentage is

accounted for by ffled teeth, may really have a lower

caries experience than a person with the same DMF

tooth score, of which a low percent is made up of

filled teeth. This problem of the treatment effect,

well recognized by oral epidemiologists, can be partly

estimated by the use of a measure such as the ratio

F/DMF.

There is virtual certainty that some degree of

measurement error has been included in a survey of

this size, a problem that can be recognized but

probably not controlled. The corrective procedures

required to adjust the observations for the comdexities of the sampling design

viously and are discussed in

have been mentionej

detail in appendix I.

pre5
Analytic approach

This report presents results from analysis of the

following specific relationships:

1.

2.

3.

4.

5.

6.

7.

The relationship between decayed, missing, and

filled (DMF) teeth and dietary intake patterns.

The relationship between DMF teeth and fluoride

content of the dental enamel.

The relationship between DMF teeth and the

calcium/phosphorus dietary intake ratio.

The relationship between DMF teeth and periodontal disease.

The relationship between periodontal disease and

alcohol consumption, tooth-brushing frequency,,

and smoking history and habits.

The relationship between dietary patterns of

adults with natural teeth and dietary patterns of

those adults without natural teeth or whose teeth

are indicated for extraction.

The relationship between dietary intake patterns

and the use of artificial dentures by edentulous

adults.

Almost all of these relationships are subject to

profound theoretical complications. The primary

variables involved are all likely to be correlated with

factors such as education, race, sex, and age. Because

these interrelationships make bivariate analyses of the

primary relationships a potentially misleading undertaking, a multiple regression approach was considered

to be more appropriate. Multiple linear regression has

been the method employed because of its ability to

handle many possible specifications and interactions

of the variables involved, and because most of the variables employed could be considered to be continuous.

While regression is an appropriate and powerful

method for analyzing these relationships, numerous

uncertainties remain as they always do with real data.

Inevitably, theoretically important variables in the

relationships are unavailable, and in many instances

are unknown. The most appropriate specification for

each variable is, at best, speculative. Distributions,

6

while almost never perfectly normal even for single

variables, become vastly more complex when joint!

normality is considered in a multiple regression model.

Unquantifiable measurement error further complicates the picture. All of these factors combine to produce uncertainty about the true magnitude of the

coefficients and probability estimates.

These resemations about the method of analysis

for the NHANES I data should not, however, be construed as reflecting concern over the appropriateness

of the method or the validity of the conclusions. The

regression model approach actually permits more

certainty about the stated conclusions than would be

possible with bivmiate analyses. This is because the

inclusion of an important covariable in an analysis

model in a theoretically plausible form, even if it is

not specified perfectly, is likely to lead closer to the

truth than would the implied specification of that

variable when it is excluded from the model.

For each relationship to be investigated, a list of

potentially related variables was assembled in add)-

tion to the dependent and independent variables

specified. These lists included such covariables as age,

race, sex, education, and income, amongst others.

The selection of these variables was based on existing

knowledge and on theory and was dictated by what

was available in the data base. Sometimes a required

variable was not available but had to be generated

from several that were available, none of which individually was precisely what was needed. For example,

there is no variable called “dietary intake pattern.”

A conceptual definition of what this term meant had

to be developed, then made operational by selecting

a list of dietary and nutritional variables from those

available.

The basic model used is of the following form:

Yi=B1+B2X2i +B3X3i+. ..+ BkXki +Ei.

In general, the models can be described as being clesigned to assess the average effect of the independent

variable on the dependent variable, given adjustments
for various theoretically important covariables. The

actual specifications of the equations can be determined from the tables of the regression results (shown

in tables 1-28), with reference to appendix II for

units and form of each variable. Most of these regressions were run separately for each of the five age

groups examined (6-1 1, 12-17, 1844, 45-64, and

65-74) to allow for the likelihood that the age effect

is different in some of the age groups.

The sheer bulk of data dictated the initial steps in

the analyses. Because there were limitations on the

number of variables from such a large sample that

could be analyzed simultaneously, subsets of the selected variables were analyzed. Any that failed to

demonstrate patterns of potential importance were

eliminated from further consideration, while those

that showed any chance of being important were

subjected to more rigorous analysis.

The variables selected for initial analysis in each

relationship are shown in appendix II. Some of these

variables were eliminated as analysis proceeded; those

that were used in the analyses described in detail in

this report can be found in tables 1-28. Many relationships that were tested and found to be nonexistent have not been described in this report. Results

presented have been adjusted for sampling weights

and sample design using the specific methods described in appendix I.

Several aspects of the presentation of data in this

report should be mentioned here. One is that the

number of subjects (in statistical terms, the “n”) was

not the same in all of the areas examined. Although

the full sample numbered 20,749, several of the

analyses

detailed

used information only collected from the

subsample (see “Introduction”). In others,

analysis was restricted to persons with specific conditions (such as absence of teeth), and in still others,

the necessary data could not be collected from many

intended subjects (such as fluoride content of dental

enamel). As a result, in some of the analyses the number of subjects in certain age-sex-race groups becomes

too small for useful presentation.

Finally, the conclusions in this report are based

principally on the results of multiple linear regression

analysis. All the multiple regression tables employed

in this analysis are listed in tables 1-28. Many tables

shown in the text are model-based estimates, simplified to show relationships between the two variables

adjusted for the effect of the covariables in the regression model. They are, for the most part, not simple

bivariate tables because such a method of demonstrating relationships, as described earlier, could be

misleading.

These model-based estimates, shown in tabular

form to provide a simplified presentation of the

results, were obtained as predicted values from the

corresponding multiple regression model. In effect,

they quantify the relationship between two variables,

adjusting for the effects of the covariables used in the

regression model. Where regression coefficients are

refen-ed to and specified in the text, therefore, they

describe an estimate of the average change in the dependent variable that is associated with a unit change

in the independent variable. Given the same units, the

higher the value of the coefficient, the larger the

change.
Highlights

The word “diet” refers to the nature of the food

ingested, whereas “nutrition” refers to the absorption

of nutrients. The results of this study show that clear

relationships exist between certain dietary practices

and cumulative dental caries experience, though no

relationship could be demonstrated between the level

of intake of specific nutrients and dental caries

experience.

Dental caries experience, as measured by the

decayed-missing-filled (DMF) teeth index, was examined in relation to the intake level of a large number of specific nutrients. These nutrients included

protein, fat, carbohydrate, riboflavin, calcium, phosphorus, iron, vitamin A, niacin, thiamin, vitamin C,

sodium, and potassium. Dietary factors related to the

DMF index were total calories ingested from sugarrich foods, percent of calories ingested from sugar-rich

foods, percent of calories ingested from sugar-rich

foods as snacks between meals, frequency of ingestion of sugar-rich foods as snacks between meals, and

the frequency of ingestion of other less sugary foods

as snacks between meals. A factor that could have a

powerful influence on these relationships but that

could not be tested for the entire sample was the

fluoride content of dental enamel.

Specific findings for nutrition and oral health can

be summarized as follows:

● There is no statistically significant relationship of

clinical importance between DMF experience and

the levels of intake of specific nutrients in the

United States.

● No statistically significant relationship of clinical

importance could be demonstrated between dental caries experience and the ratio of calcium to

phosphorus in the diet. Similarly, no statistically

significant relation of clinical importance between

dental caries experience and calcium to phosphorus ratio in blood serum could be demonstrated.

● A considerably higher proportion of persons with

natural teeth ingested vitamin C at levels at or

8

above the NHANES standard than did persons

without natural teeth or whose natural teeth were

indicated for extraction. In some age groups,

slightly higher proportions of those with natural

teeth also achieved the NHANES standards for

ingestion of iron and protein. Most of these differences were statistically significant.

● Among edentulous persons, there were no statistically significant differences of clinical importance

in nutrient intake by whether the subjects reported eating with their dentures in place or not.

Specific findings for dietary sugar and dental

caries can be summarized as follows:

There is a direct, strong, and statistically significant relationship between DMF experience and

tht~ frequency of intake of sugary snacks between

meals. Persons who report greater frequency of

ingestion of sugar-rich snacks between meals tend

to have higher DMF scores.

There are direct and statistically significant relaticmships between DMF scores and the frequency

of ingestion of less sugary snack foods between

meals. While evident, this relationship is not as

strong as that found between DMF scores and fr&-

quency of ingestion of sugar-rich snacks between

meals.

There are direct and statistically significant relationships between DMF scores and total calories

ingested from sugar-rich foods between meals.

While evident, this relationship is not as strong m

that found between DMF scores and frequency ~f

ingestion of sugar-rich snacks between meals.

There is little evidence of a statistically significant

or clinically important independent relationship

between DMF experience and total caloric intake

of su~ar-rich foods. meaning those sugar-rich foods

inges;ed both with’and between meals.

Specific findings for enamel fluoride can

marized as follows:

be sum-
● Younger persons tend to have higher levels of fluoride in their dental enamel than do older persons.

● The fluoride content of dental enamel tends to

show a statistically significant inverse relation to

dental caries experience.

Specific findings for correlates of periodontal

disease can be summarized as follows:

● A strong, statistically significant, inverse relationship was found between reported frequency of

tooth brushing and levels of periodontal disease.

● There was no statistically significant relationship

between periodontal disease experience and reported levels of alcohol consumption when the

effects of age, sex, education, income, toothbrushing habits, dental visits, and smoking were

taken into account.

A clear and statistically significant relationship

was found between smoking and periodontal disease. The highest levels of periodontal disease

were found among present smokers, and the lowest levels were found among those who reported

that they had never smoked.

No evidence of a negative correlation between

dental caries experience and periodontal disease

experience could be found. There was a statistically significant but clinically unimportant positive correlation found between the experience of

the two diseases among these persons who did not

receive an enamel biopsy.

These highlights are discussed in more detail in

the subsequent section.

9
Detailed results

Dental decay and dietary intake patterns

Dental and nutritional data were recorded for

20,749 persons ages 1-74 years. Analysis was restricted to the 14,375 persons ages 6-64 years for

whom usable data were available. Missing data kept

the numbers below that total for most of the analyses.

“Dietary intake pattern” had to be defined conceptually and operationally for analytic purposes. As

described earlier in this report, “diet” refers to the

nature of the food ingested. In the dental disease context, dietary influences are those that have an immediate and local effect on dental plaque and subsequently on dental or periodontal tissues. “Nutrition, ”

on the other hand, refers to the nutrients absorbed,

unrelated to the physical form of the food ingested.

“Dietary intake pattern, “ in this area of analysis, was

defined as including both dietary and nutritional

variables.

Dental information came from the dental examination; dietary and nutritional data came from the

24-hour recall interview. The 24-hour data were usecl

to determine nutritional intake values and to summarize types of food ingested in 18 different food

categories, both with and between meals. Data from

the 3-month food intake information were not used

directly in the analyses in this report because the frequency of ingestion reported there did not differentiate between ingestion with meals and between

meals. The 24-hour recall data did make this differentiation, so they were used in these analyses.

Each of a series of nutritional variables was related

to decayed-missing-filled (DMF) teeth values and examined within various age, sex, and race groups, both

individually and in multiple regression models. These

variables are protein, fat, and carbohydrate intake as

a percentage of total calories and per kilogram of

body weight, vitamin A, riboflavin, thiamin, niacin,

vitamin C, calcium, and iron as percentages of

NHANES standards (appendix III). No meaningful

relationship of any kind could be demonstrated, and

hence no tabular information in this area is presented.

This finding is in accordance with previous research

in this area, which has generally failed to demonstrate

any correlation between dental caries experience and

quality of nutrition in either well-nourished or malnourished populations. 24

In the variables related to diet, analysis was chiefly

concentrated on the relationship between sugar intake and dental caries. This area of analysis was

chosen as the first priority because of the bulk of evidence, epidemiological and experimental,25 that implicates sugar in the decay process more than ady

other aspect of diet.

The nature of the data precluded a comprehensive

or direct estimate of total sugar consumed. Frequenay

of consumption with meals and between meals was

recorded on the 24-hour recall data, which categorized food ingested into 18 food goups (appendix II),

inclucled categories on (a) sugar and primarily sugar

products, including candy and sweetened beverages,

(b) desserts and sweets, including cakes, pies, and

pastries, and (c) cereals and grain products. Sucrose

levels were not documented for each food type and

could only be inferred from the general description of

the fc~od.For example, it was assumed that the carbohydrate in the foods in the “sugar and primarily sugar

products” group was predominantly sucrose. Tl~is

same assumption was required, though to a lesser d,egree, for the latter two categories.

It is likely that the bulk of sugar consumed woudd

be included in these three food categories, but they

would not include all sugar consumed. Sugar used

extensively in food processing, the so-called “hidden

sugar’” that occurs in products such as processed

meats, ketchup, salad dressing, soups and a variety of

other foods, could not be readily estimated from the

NHANES data. Whether this “hidden sugar” has any

important relationship with dental caries experience

is unknown, and unfortunately could not be addressed

in this analysis. Of course, just as the 16 “low sugaM’

food groups are not free of sugar, it is also recognized

that the 3 “sugar-rich” food categories are not dntirely made up of sugar. A further issue of interest in

10
dentistry is that the different types of sugar consumed (sucrose, glucose, fructose, maltose, lactose,

among others) could not be differentiated in the

NHANES I data in the form in which they are readily

available. “Sugar” is used as a generic term in this

report, though the bulk of sugar consumed at the

time of this survey was sucrose.

What was addressed, therefore, was the relationship between DMF values and the three major sugarcontaining food groups from the 24-hour dietary

recall record. This approach was considered the most

appropriate in view of the constraints presented by

available data. These three sugar-rich categories were

tested jointly as a combined category, referred to as

“sweets,” generated from summing the three food

groups. Similarity, the “low sugar” categories were

summed to provide a new category of “nonsugary”

foods.

AU of the patterns discussed here are taken from

the results of multiple regression analysis, which takes

into account the effects of age, sex, race, and the

socioeconomic variables of income and education.

Consideration of age in the analyses was critical, even

within each age-specific group, because both dietary

practices and DMF values are strongly correlated with

age.

Percent of total calories from sweets. –This specific analysis was generated by the question: What

relationship exists between the relative quantity of

sugar consumed and dental caries experience’? As

stated previously, it was not possible to quantify

accurately the total amounts of sugar ingested because of the “hidden sugar” in processed foods.

Analysis proceeded on the assumption that cereals

and grain products, sugar and primarily sugar products, and desserts and sweets accounted for much of

the sugar consumed.

The variable for percent of total caloric intake

from the three high-sugar categories was generated by

summing the caloric values of each category from the

24-hour recall tape and dividing this sum by the total

caloric intake from the 24-hour recall (X 100). This

variable was then included in a

model, along with age, sex, race,

tion variables for the four age

multiple regression

income, and educacategories of 6-11,

12-17, 18-44, and 45-64 years: The r&ults, shown ~

tables A, 1, and 2, give little evidence of a pattern. In

none of the age groups do the estimated effects of

total sweet consumption approach significance, and

the direction of the effect is inconsistent and of little

practical importance.

It can be concluded that the NHANES I data fail

to suggest that the effect of total caloric consumption

of sweets on’ dental caries experience is important.

Some inherent limitations in the nature of the data

analyzed, to be discussed more fully later in this section, require that this conclusion be accepted with

some caution.

Percent of total calories from sweets ingested

between meals. –If the percent of total caloric consumption from sugar-rich foods, both with meals and

between meals, seems to be of little importance in its

association with caries, the next question was: Is

dental caries experience associated with the percent

of total calories from sweets consumed only between

meals? Existing evidence indicates that sweets consumed between meals are more damaging than those

consumed with meals.26

The percent of total calories from consumption

of the three sugar-rich food groups between meals

(“sweets”) was determined as before, except that the

numerator was restricted to those sweets identified as

consumed between meals. This variable was again included in a multiple regression model with the variables of age, sex, race, income, and education. Results

in all age-~oups except for the youngest, indicate a

statistically significant trend in DMF values related to

between-meal sweets (tables B, 3, and 4). Regression

coefficients in ascending order of age group are

0.013,0.018, 0.046, and 0.053 (table 3). These values

indicate that in, for example, the 12-17-year age

group, each additional percent of calories from

between-meal sweet consumption is associated with,

on average, DMF values that are approximately 0.02

Table A. Model-basedl estimates of mean number of decayed, missing, and filled (DMF) permanent teeth, by calories from sugar-rich foods2 as a

percent of total calories ingested, for persons ages 6-64 years: United Statesr 1971-74

Mean DMF, by age group

Calories from sweets as percent of total calories

6-11 years3 12-17 years3 18-44 years3 45-64 years3

10 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 6.6 15.4 23.2

20 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 6.5 15.5 23.2

30 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 6.3 15.6 23.1

40 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 6.2 15.6 23.1

50 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 6.1 15.7 23.0

60 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 6.0 15.8 22.9

1Modal d~~~~fbad in ~ppandi~ 1.

Zvariable described in detail in appendix 11.

3Trend not significant atp = 0.05.

11
Table B. Model -basedl estimates of mean number of decayed, missing, and filled ( DMF) permanent teeth, by calories from sugar-rich foodsz

consumed between meals as a percent of total calories ingested, for persons ages 6-64 years: United States, 1971-74

Mean DMF, by age group

Calories from between-meal sweets as percent o f total calories

6-11 years3 12-17 years 18-44 years 45-64 years I

o . . . . . . . . . . . . . . . . . . . . . . . . 1.5 6.0 15,1 22.7

lo”:::::::::::::::::::: : : : . . . . . . . . . . . . . . . . . . . . . . . . 1.7 6.2 15.6 23.2

20 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 6.4 16.0 23.8

30 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.9 6.6 16.5 24.3

40 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.0 6.8 16.9 24.8

lMod~l d~$~~ib~d inappendix 1,

Zvariable described in detail in appendix Il.

3Trend notsignificantatp= 0.05.

higher after the effect of the other variables listed

has been accounted for.

It can be concluded from these NHANESI data

that total consumption of sweets between meals as

recorded by the 24-hour dietary recall is related to

dental caries experience, but that this effect maybe

ofonly moderate clinical importance.

Frequencyofingestion ofsweets between meals.–

The next step was to test the relationship between

the frequency of consumption of sweets between

meals and dental caries experience. Frequencyof consumption of food from all categories and time of ingestion is reported in the 24-hour recall data. The

between-meal frequency of sweet consumption was

generated by summing the frequencies of ingestion of

the same three sugar-rich food groups used in the previous analyses, but restricted to those reported to

occur outside of mealtimes. As before, this variable

was included in a multiple regression model with age,

sex, race, income, and education.

Results (tables C, 5, and 6) show that in each age

group the regression effect of frequency of consumption of between-meal sweets (the independent variable) on dental caries experience (the dependent variable) is statistically significant at a probability level of

at least p = 0.05. In addition, the coefficients are of a

magnitude that can be considered clinically important. In ascending order of age groups the coefficients

are 0.098, 0.145, 0.375, and 0.446. These values indicate that in the 18-44-year age group, for example,

each additional reported instance of between-meal

sweet snack consumption on the 24-hour recall record

is associated with DMF values that are, on average,

0.375 higher after the effects of age, sex, race, income, and education have been accounted for.

It can be concluded that the NHANES I data

show that the frequency of consumption of sugar-rich

foods between meals has a statistically significant

relationship with dental caries experience. The

strength of the trend can be considered to be of some

clinical importance.

Some further aspects of these relationships were

explored. It could be expected that quantity and frequency of consumption of sugary foods are related,

and that indeed proved to be so. The results, shown

in tables 7-10, show that these two variables are

highly correlated, with correlation coefficients ranging

from C1.676in the 18-44-year age group to 0.773 in

the 6-1/1-year age group. To determine which of thd

two eflfects (quantity consumed or frequency of consumption) is most strongly associated with DMF

values, analyses with both of these variables in the

model at the same time were undertaken. The results,

displayed in table 11, indicate that in the 18-44-year

and 45-64-year age groups between-meal frequency ii

considerably more important than between-meal

quantity, and that the, previously observed relational

ship o:f between-meal quantity to DMF values could

be attributable to the high correlation between frequency and quantity. For the two younger age groups,

the picture is far less clear. Neither of the variables

attains statistical significance, indicating that there is

not enough uncorrelated explanatory power in eithet

of the~m. In the younger age groups it can thus be said

that while between-meal sugar intake clearly has ii

strong association with DMF values, the relative importance of quantity and frequency is not clear frotil

these data.

In the two younger age groups, 6-11 and 12-17

years, the increased DMF values associated with iry

creased snacking frequency were due predominantly

to higher values in decayed and filled teeth. In the

older age groups, 18-44 and 45-64 years, the higher

DMF values were largely attributable to missing teeth

(tables 12-14).

The apparent relationship between caries experience i~nd frequency of between-meal sugary snacks

prompted the question about other snacks of the

nonsugary kind. Could it be just snacks per se, rathdr

than [sugary snacks specifically, that are principally

associated with caries? This question was tested bj

examining the frequency of consumption of foods in

the 16 “nonsugary” groups (described earlier in thk

section) between meals, relative to DMF values. The

answer appears to be a qualified “No.” While there

was an apparent, although small, association between

frequency of ingestion of nonsugary snacks and cari~s

experience in all age groups (tables D, 15, and 16),

12
Table C. Model-besedl estimates of mean number of decayed, missing, and filled (DMF) permanent teeth, by stated frequency of consumption

of sugar-rich foods between meals,2 for persons ages 6-64 years: United States, 1971-74

Mean DMF, by age group

Frequency of consumption

6-11 years 12-17 years 18-44 years 45-64 years

o . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 6.0 14.9 22.5

1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 6.1 15.3 23.0

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 6.3 15.7 23.4

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 6.4 16.1 23.9

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.9 6.6 16.4 24.3

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.0 6.7 16.8 24.7

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 6.8 17.2 25.2

lM~d~ld~~~~ib~d inappendi~ ].

Zvariable described indeteil in appendix II.

Table D. Model-basedl estimates ofmeannumber ofdecayed, missing, and filled (DMF) permanent teeth, bystated frewency ofconsurrwtion

of non-sugar-rich foods betwaen meals, 2forpersons ages 6-64years: United States, 1971-74

Mean DMF, by age group

Fraquency of consumption

6-f 1 years3 12-17 years3 18-44 years 45-64 years

o . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....... . . . . . . . . . . . 1.6 6.0 15.1 22.3

1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 6.1 15.2 22.6

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 6.2 ‘15.4 22.9

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 6.4 15.6 23.2

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 6.5 15.8 23.4

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8 6.6 75.9 23.7

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.9 6.7 16.1 24.0

lModeldeacribed inappandiX 1.

%ariabled escribedindeteil in appendix Ii.

3Trendnot significant atp= 0.05.

this association impossibly duetothe relatively high

correlation between sugary and nonsugary snacks in

all age groups (tables 7-10). Again to investigate

further these relationships, analyses were run with

both of these variables in the model at the same time.

The results, displayed in table 17, continue to show

that, on average, the association of sweet snacks with

DMF teeth is stronger than the association of nonsweet snacks with DMF teeth. Whether this smaller

although persistent association between nonsweet

snacks and DMF teeth is attributable to the sugar that

is inevitably present in many of them, or to snacks

per se, is not known. Nevertheless, what have been

classified as sweet snacks seem to have the larger

average effect.

The inherent difficulty in the philosophical basis

of relating DMF to dietary data, (discussed earlier in

“Limitations of data interpretation”) requires that

these findings be accepted with caution. To interpret

properly the results so far presented, it is important

to understand the consequences of this kind of measurement problem. In reality, what the tabular data

present are the relationships between yesterday’s

dietary patterns and lifelong caries experience. In the

representation of that relationship, the magnitude of

the coefficients presented should be reasonable approximations. However, in terms of the more important question, that is of the relationship of lifetime

dietary patterns to DMF teeth, these probably represent gross underestimates, as detailed in appendix I.

Despite this difficulty, the patterns that emerged

are quite distinct. It could be suggested that older

persons who now have a taste for sweet snacks developed this taste in their youth, so that while the

snacks themselves are now different, their basic sugarcontaining quality is not. The pattern of the relationship found, with an increasingly greater magnitude

with age, tends to support this suggestion of a cumulative lifelong effect. Further, the relationship between frequency of sugary snacks and dental caries

experience may be strong enough to emerge in spite

of the inherent deficiencies of the data. It could be

concluded that while the stated quantification of the

snack frequency-caries relationship should perhaps

not be taken literally, the relationship itself is likely

to be real.

The findings in this analysis confirm the results of

previous studies on the relationship between sugar

consumption and dental caries. While sugar consumption per se is probably neither a necessary nor

13
sufficient cause of dental caries, it is at least a strong

contributing cause.2G,27 The nature of the data analyzed in this report does not allow conclusions regarding cause-and-effect, but it is highly likely that the

associations found between aspects of sugar consumption and dental caries experience are in fact causal.

The NHANES I data are supportive of previous research and the weight of previous research, both epidemiological and experimental,2$30 leads overwhelmingly toward such a conclusion. Considerable value of

the results from the NHANES I survey lies in the fact

that these findings appear to be the first obtained

from a large, nationally representative sample under

nonexperimental conditions.

Accordingly, it can be concluded from the data in

NHANES I that the frequency of between-meal consumption of sugary snacks is an important dietary

determinant of dental caries activity in the United

States. Total between-meal consumption of sugary

foods is also a factor, though possibly of lesser importance, and total sugary food intake per se seems

to be of i.elatively little importance. Nutritional factors seem to be unrelated to dental caries activity

among the population of the United States.

Relationship between the number of decayed,

missing, and filled teeth and the enamel

fluoride content of the teeth

The cariostatic effect of the fluoride ion has been

extensively documented, and the use of fluoride in

various forms constitutes a major part of dentistry’s

efforts to prevent caries.3O While the benefits of

fluoride have been well-demonstrated in experimental

situations and special demonstrations,s I it is of interest to assess the relationship between dental caries

experience and exposure to fluoride in the nonexperimental situation of the NHANES I survey.

Caries experience was assessed, as before, by use

of the decayed-missing-filled (DMF) index.9 Fluoride

exposure was measured by use of the enamel biopsy

technique? 2 a procedure by which a few microns of

surface enamel are removed by use of a special rotary

instrument. The removed enamel can then be analyzed

chemically for fluoride and other constituents.

Fluoride biopsies could only be carried out on

5,481 examinees ages 6-74 years, although it was intended to carry one out on all dentate subjects. Analysis is theretore restricted to this group. Because the

sample is small, the sampling errors are large, and estimates must be interpreted with caution. Reasons for

this reduced response rate relate to unforeseen equipment failures, refusals, and absence of suitable teeth.

Difficulties in obtaining high response rates for fluoride biopsies have been reported before.3s

The enamel fluoride concentrations from the

enamel biopsies were ranked, and the distribution

divided into quintiles. Each quintile therefore contained the same number of subjects. The cutoff

14

points, in parts per million (ppm) of fluoride in the

sample of enamel, were as follows:

First quintile:

Second quintile:

Third quintile:

Fourth quintile:

Fifth quintile:

O– <682 ppm

682 – <970 ppm

970-<1300 ppm

1,300-<1803 ppm

1,803 and over ppm.

Tables E-H show some of the patterns of distribu:

tion of enamel fluoride concentration in white males

and white females. Data for races other than white

are not tabulated because of very small numbers in

many cells.

In addition to the apparent trend of lower DMF

values in the younger age groups with increasing con:

centrations of enamel fluoride, there is an interesting

pattern in the distribution of the numbers of subjects

within each table (tables G and H). Most young people

have relatively high concentrations of fluoride, while

older people have lower concentrations.

Black persons initially appeared to have higher

enamel fluoride levels than white persons. However;

when distributed by age group (data not shown, as

mentioned previously) this tendency disappeared, because it was due to the relatively large proportion of

younger black persons in the sample. The disparity in

enamell fluoride concentrations among age goup$

seemecl as apparent among black persons as among

white persons. There seemed to be no age-specific

differences between black persons and white persons.

Mclre detailed multiple regression analysis confirmed the pattern seen in tables E and F. Table 18

demonstrates that higher concentrations of enamel

fluoride have a strong kverse association with DM~

teeth in the 6-1 l-year, 12-17-year, and 18-44-year age

groups. The 45-64-year age group has a less pronounced coefficient for the fluoride variable, and it

has failed to attain statistical significance.

The findings on enamel fluoride concentratiori

are among the most interesting in this NHANES

project and emphasize what a pity it was that the

data could be obtained only from such a small

sample. The question arose as to whether this subsample represented any special self-selected group,

and further investigation indicated that it did. Table J

shows that those who received the enamel biopsy had

distinctly lower levels of both DMF experience and

periodontal disease than did those who did not. A

possible reason for this difference could be that the

enamel biopsy was perceived by many survey subjects

as an operative dental procedure, and hence tended to

be accepted by more regular dental patients (assuming

their oral health levels were higher) than by more

irregular patients. Unfortunately the relationship between enamel fluoride levels and frequency of dental

visits could not be tested because dental visit frequency was only recorded for the subsample that
Table E. Mean number of decayed, missing, and filled (DMF) permanent teeth for white males, by age and fluoride concentration Of anamel

Fluoride concentration

Age

All First Second Third Fourth Fifth

levels quintile~ quintile quintile quintile quintile

Allages,6-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 15.0 13.6 11.8 9.2 6.4

S-n years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 3.0 3.9 2.0 2.7 1.6

12-17years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 8.5 5.0 7.2 6.0 4.6

18-44years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.1 14.5 14.1 12.5 11.3 11.0

45-64years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.1 18.4 17.7 18.0 19.9 16.4

65-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.4 19.2 16.8 19.2 21.1 15.4

lThasa~uin~i[es are based ~nadivi$ion~f all subjects forwhom fluoride data areavailabla, regardlassof race.

Tabla F. Mean number ofd=ayed, missing, and filled (DMF)permanent teeth fOrwhite females, bYageand fluOride concentration Of enamel

Fluori& concentration

Age

All First Second Third Fourth Fifth

levels quintile 1 quin tile quin tile quin tile quintile

Allagesr6-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.0 15.4 14.5 12.1 10.1 7.4

6-n years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 2.0 2.9 2.7 2.5 1.9

12-17years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 8.7 7.6 6.1 6.5 5.9

18-44years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13.9 15,2 15.0 13.5 13.1 11.0

45-64years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.6 19.5 19.6 18.2 17.9 16.4

65-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.5 20.1 19.2 19.6 20.5 12.4

lThe~aqui~tiles are basad~n a division of all ~“bjects forwhom fluoride data are available, regardless of race.

TableG. Number of white males examined, by age and fluoride concentration of enamel

Fluoride concentration

Age

All First Second Third Fourth Fifth

levels quintilel quintile quintile quintile quintiie

Allages,6-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,714 385 328 323 335 343

S-n years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 8 12 26 62 101

12-17years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 390 24 50 67 114 135

18-44years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 780 236 191 161 118 74

45-64years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228 80 51 47 30 20

65-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 37 24 22 11 13

lThemquintiles araba~d~n a division of all subjects forwhom fluoride data are available, ragerdlessof race.

Table H. Number ofwhite females examined, bya~and fluoride concentration of enamel

Fluoride concentration

Age

All First Second Third Fourth Fifth

levels quin tile 1 quintile quintile quintile quintile

All ages,6-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,727 647 569 !%6 512 433

S-n years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 12 18 37 70 100

12-17years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443 46 59 97 123 118

18-44years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,645 461 392 349 262 181

45-64years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 74 63 50 33 27

65-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 54 37 33 24 7

lThesequintiles are based one division of all subjects forwhom fluorida data are available, regardless of race.

15
Table J, Number ofexaminees (rr), mean number of decayed, missing, and filled (DMF) permanent teeth, and periodontal index (Pi) score,

byagegroup and biopwstatus forpersons ages 18-74 years: United States, 1971-74

No biopsy

Age group

BioPsy

n DMF PI n DMF PI

18-44years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4,071 16.28 1.06 2,894 13.27 0.40

45-64years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,584 21.57 1.87 575 17.61 0.90

65-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,510 23.20 2.67 310 18.61 1.23

received the detailed examination. The number of

subjects who therefore had both dental visit frequency and enamel fluoride Ievelsrecorded was too

small for adequate testing. Whether ornotthebiopsied group represented more regular dental patients, it

did represent those with superior levels of oral health,

relative to the total sample. Conclusions reached

therefore must be accepted cautiously because of the

special nature of the group examined.

An additional area that could not be tested satisfactorily was the potential interaction between enamel

fluoride levels and frequency of ingestion of sweet

snacks. Additional theoretical and statistical development is required before this interaction can be satisfactorily tested with NHANES-type data.

Within the limitations discussed, it is concluded

that younger persons have higher levels of fluoride in

their dental enamel than do older persons. It is also

concluded that higher levels of enamel fluoride are

associated with lower DMF values, though the data

do not permit the conclusion that this relationship is

one of cause-and-effect. The enamel biopsy technique

is exacting; experience has shown that it should be

used only with upper central incisor teeth (i.e., those

most accessible) if reliable results are to be obtained.34~35 Minor variations in pressure on the

rotary instrument or in time of its application can

make considerable difference in the depth of the

enamel removed. Because the concentration of fluoride in enamel diminishes sharply with increasing

depth from the surface,32136 the resultant fluoride

concentration determined is related to the weight of

the enamel sample removed. Statistical techniques

have been developed to standardize results from

enamel samples of varying weights in group studies.37

Fluoride levels of outer enamel layers appear to

be higher among children with reduced incidence of

dental caries, at least as reported from clinical trial

data.33~3G~3‘Y39 The findings from NHANES data in

this report seem to confirm this relationship. The

relationship between whole enamel and DMF values is

less clear~”) 41 probably because of the diminished

fluoride concentration with increasing depth of

enamel.

Fluoride concentration of outer layers of enamel

is a result of both systemic and topical influ-

.ences.33,34’38 It cannot be determined from the

NHANES survey data whether the greater concentration of enamel fluoride in younger persons relative to

older persons comes from higher quantities of fluoride in the food chain, or whether it comes from

greater exposure of immature enamel to topical fluorides (e.g., dentifrices) than was available to older

persons at the same stage of their dental development. Certainly this subject is worthy of additional

study.

Relationship between dental caries experience

and the calcium/phosphorus ratio

The presence of calcium (Ca) and phosphorus (P)

ions in the dental plaque, and their ratio to each

other, have been shown to influence the early stages

of cariogenesis.AZY43 Expressed in necessarily simplified fonm, the initial stages of the carious process involves, among other things, a dissolution of Ca and P

ions from the outer layers of the dental enamel. If Ca

and P icms are available in the adherent dental plaque,

this dernineralization process can be arrested and the

lesion cloes not proceed to clinical cavitation. This

knowledge has led to efforts to prevent caries devel-,

opment by supplementing diets with phosphates, a

procedu~re that has proved successful with animals but

disappointing in human studies.43

The Ca and P in the dental plaque must originate

from dietary sources. This analysis was carried out to

see if the Ca : P ratio in the diet was related to caries

experience; the rationale was that the Ca : P ratio in

the constituents of the diet maybe directly related to

the Ca : P ratio in the dental plaque.

The analysis was carried out on 17,854 persons

ages 6-74 years for whom both caries experience and.

dietary information were recorded. Caries experience

was recorded by the DMF index, and the Ca : P ratio

was determined from the record of dietary calcium

and phosphorus from the 24-hour dietary recall. In

additio:n, the levels of serum calcium and phosphorus

from the blood studies were assessed to examine their

relatiorlship to DMF.

Because of the previously observed correlation of

age with both decayed, missing, and tilled teeth3 and

dietary intake pattern,5 initial scatterplots and regressions (correlations) were developed using the following five age groups: 6-11 years, 12-17 years, 18-44

years, 45-64 years, and 65-74 years. Each of the si?t

16
dependent variables (dietary calcium, dietary phosphorus, dietary Ca : P ratio, serum calcium, serum

phosphorus, and serum Ca : P ratio) was plotted and

regressed on the DMF values, within each of these age

groups.

No pattern of obvious practical importance

emerged from this first look at the data. A few relationships, however, did achieve statistical significance,

but the nature of these relationships was almost

always negative in the age groups under 45 years, and

positive in the age groups 45 years and over, even for

the same nutrient. This consistent pattern resembles

the underlying correlation between diet and age, and

thus prompted a look at the statistically significant

relationships by 1-year intervals within each age

group. The previously apparent correlations between

DMF values and the nutrients in question disappeared with this closer inspection. These findings support the previous speculation that the correlations

observed in broader age groups are caused by the correlation of both DMF values and dietary practices

with age. However, there does not appear to be any

direct relationship between DMF values and any of

the Ca and P variables tested in this analysis.

In addition, the Ca : P ratio in both the diet and

serum was related to DMF values using the multiple

regression model described previously, and again no

significant relationship could be demonstrated. The

levels of Ca and P in dental plaque were not determined in the NHANES I survey, so no relationship

between Ca and P in the plaque and in the diet and

serum could be assessed.

Although the Ca and P constituents of the dental

plaque clearly originate from dietary sources, their

presence in the dental plaque is most directly related

to saliva, and their concentration in plaque is presumably dictated by local factors in the oral environment. Their levels in serum are presumably a function

of initial intake and systemic controlling factors. It

must also be recognized that the dietary and biochemical measurements of Ca and P are probably imprecise indicators of the respondents’ nutritional

status. The 24-hour dietary recall, as mentioned, may

not measure usual intake, and serum calcium levels

are essentially constant over a wide range of intakes.

Given an adequate supply of these nutrients in the

diet, one conclusion from this analysis is that there is

no relationship between dental caries experience and

the Ca : P ratio in the diet or in serum. This conclusion based on NHANES data is for a population receiving adequate amounts of the nutrients in question; it may or may not be similar for a nutritionally

deprived population.

Relationship between dental caries experience

and periodontal disease

The belief that dental caries experience and periodontal disease are inversely related has been expressed

within some quarters in dentistry for a long time.44

The availability of data from NHANES I provided a

good opportunity to test the relationship; analysis

could be carried out for 10,944 persons, ages 18-74

years, for whom both DMF values and periodontal

index (PI) data were recorded. Persons under 18 years

of age were not included in this analysis because periodontal disease is considered insufficiently advanced

at that age to provide useful comparisons.45

Initial regression of DMF values on PI data seemed

to indicate a relatively large and statistically significant positive association between PI scores and DMF

values. As DMF values increased, apparently so did

PI scores, even after age, sex, race, income, education,

and between-meal sweet-eating habits have been

accounted for. Table K shows these results; the trends

for increased DMF values among persons with higher

PI scores is evident. The regression statistics from

which these data are derived are shown in table 19.

However, when the enamel fluoride variable was

included in the multiple regression model (resulting

in a much smaller sample size because of the relatively

small group who received an enamel biopsy, described

previously), the apparent positive association of DMF

values and PI scores is sharply diminished. Table L,

based on the regression analysis in table 20, shows no

significant relationship between PI and DMF scores in

the 18-44-year and 45-64-year age groups among the

3,779 persons ages 18 and over who received an

enamel biopsy. Table M, the analogous table for persons who did not receive an enamel biopsy, shows

slightly stronger evidence of a positive relationship

between PI and DMF scores.

The reason for these findings seems likely to be

found in the data shown in table J: the systematic

bias that seemed to be operating in the selection of

subjects who received an enamel biopsy. As shown in

table J, subjects with high PI scores and high DMF

teeth scores were far less likely to have a fluoride

biopsy taken, and therefore the two samples (those

who received an enamel biopsy and those who did

Table K. Model-basadl estimates of mean number of decayed, missing,

and filled (DMF) permanent teeth, by various periodontal index

(Pi) scores,2 for three age groups United Statas, 1971-74

Mean DMF, by age group

Periodontal index

1844 years 45-64 years 65-74 years

o . . . . . . . . . . . . . . 14.55 19.76 21.04

1 . . . . . . . . . . . . . . 14.99 20.10 21.48

2 . . . . . . . . . . . . . . 1!5.44 20.45 21.93

4 . . . . . . . . . . . . . . 16.33 21.14 22.82

6 . . . . . . . . . . . . . . 17.22 21.83 23.71

8

* *

. . . . . . . . . . . . . . 24.60

1Mocj~l d~~ribed in appendix 1.

2Variable described in detail in appendix 11.

17
Table L. Model-basedl estimates of mean number of decayed, missing,

and filled (DMF) permanent teeth, by various periodontal index

(Pi) scores,z for three age groups from whom enamel biopsies

ware taken: United States, 1971-74

Mean DMF, by age group

Periodontal index

18z14 years3 45-64 years3 65-74 years

o . . . . . . . . . . . . . . 13.28 17.52 17.81

1 . . . . . . . . . . . . . . 13.19 17.59 18.60

2 . . . . . . . . . . . . . . 13.10 17.66 19.39

I M~&i d~~=~ib~d in appandi~ 1.

2Variable described in detail in appendix 11.

3Trend not significant at p = 0.05,

Table M. Model-basedl estimates of mean number of dacayad, missing, and filled (DMF) permanent teeth, by various periodontal

index (pl ) ~core~rz for three age groups from whom no enamel

biopsies were taken: United States, 1971-74

Mean DMF, by age group

Periodontal index

18-44 years 45-64 years3 65-74 years

o . . . . . . . . . . . . . . 15.92 21.13 22.44

1 . . . . . . . . . . . . . . 16.26 21.33 22.66

2 . . . . . . . . . . . . . . 16.61 21.52 22.88

4 ., . . . . . . . . . . . . 17.29 21.92 23.32

6 . . . . . . . . . . . . . . 17.97 22.32 23.77

8

* *

... ..,., . . . . . . 24.21

1 Model described in appendix i.

2Variable deacribad in detail in appendix 11.

3Trend not significant at p = 0.05.

not) are comprised of quite different people in terms

of dental health. The results from multiple regression

analysis for those who had an enamel biopsy taken

(table 20) shows that in this group with less severe

disease, the relationship between PI scores and DMF

values is unclear. For those who did not have the

enamel biopsy taken, and who tended to have more

severe oral disease (table 21), the positive association

is a little more evident.

It can be concluded that there is no evidence in

the data from this survey to support the existence of

an inverse relationship between the severity of dental

caries and periodontal disease. Among persons with

lower levels of oral health there is a tendency toward

a direct relationship, while among those with higher

levels of oral health there is little relationship of any

kind. These results confirm the findings of White and

Russell$4

Relationship between periodontal disease and

alcohol consumption, tooth brushing, and smoking

Periodontal disease is considered to be predominant y a bacterial disease of local origin, though

systemic factors are thought to be of some influence

in the etiology of the condition.46

Little evidence concerning the relationship between periodontal disease and alcohol consumption is

available,, though there is some evidence of a relationship between tobacco smoking and periodontal

disease.4’7-49 The link between periodontal disease

and tooth brushing has been shown many times to be

strong and direct.so The NHANES I survey provided

the chance to examine the strength of these relationships in the U.S. population.

The analyses are limited by the availability of

what are considered to be relevant covariables. Data

on frequency of dental visits (a relevant covariable),

smoking history, and tooth brushing are available

only for those individuals included in the detailed survey (see “Introduction”), thus limiting the usable

sample to no more than 3,847 persons. Missing data

on other variables reduces the sample further in the

multiple regression analyses.

Periodontal disease experience was assessed by

the periodontal index (PI) score in each subject’s dental record. However, several other variables employed

in the anmlysiswere generated from the provided variables. Most important among these are overall measures of smoking and drinking activity. The object was

to develop variables that would be sufficiently discriminating while at the same time to leave reasonable

numbers of individuals within categories. This latter

concern was accentuated by the relatively small

sample from which data on smoking were available.

A new “tobacco-use” variable was developed from

seven otl~er variables related to use of tobacco (see

appendix II). Tobacco use was determined for the

detailed sample, persons ages 25-74 years, who completed the medical history questionnaire. The new

variable of tobacco use allocated subjects into one of

three following categories:

1.

2.

3.

Never have used tobacco in quantities up to or

equal. to the amounts stated in the medical history

questionnaire, that is, at least 100 cigarettes, 50

cigars, or 3 packages of pipe tobacco during the

subject’s lifetime.

Have used tobacco at least up to the amounts

stated in the questionnaire, but do not use tobacco

now.

Used tobacco at the time of the interview, at least

up tot the amount stated in the questionnaire.

The creation of an alcohol-use variable was slightly

more co]mplex in that frequency and quantity were

thought to be less correlated than with smoking,

hence requiring that both of these factors be captured

in the summary variable. This new summary yariable

was developed from three other variables. The following four categories were defined:

1. Those who claimed not to have had a drink in the

past (called “none” in the tables).

18
2.

3.

4.

Those who claimed to drink no more than once a

week and when they did drink had three or fewer

drinks (called “little” in the tables).

Those who stated they drank more often than

once a week but have three or fewer drinks at a

time, or those who said they drink no more than

once a week but have four or more drinks when

they do (called “moderate” in the tables).

Those who claimed to drink more than once a

week and have four or more drinks at a time

(called “heavy” in the tables).

Daily tooth-brushing frequency was recorded in

the medical history questionnaire for the detailed

sample of persons ages 25-74 years and could therefore be used directly as an independent variable in

the analysis.

Because the dependent variable (PI scores) remains the same in these tests, and because the explicit

independent variables in these relationships are probably related (drinking, smoking, and tooth brushing),

these three relationships have been analyzed together

in a multiple regression model. The distribution of

the PI scores for the subsample available is close

enough to normal to warrant tests based on parametric assumptions.

In a f~st look at the PI scores stratified by levels

of alcohol consumption, an interesting pattern

emerged (table N). It can be seen that nondrinkers

and heavy drinkers appear to have higher levels of

periodontal disease than moderate drinkers, a pattern

described as a “U-shaped” relationship. The question

naturally arose as to whether or not this pattern is

real or spurious. The analysis proceeded thi-ough

numerous steps, ending with a multiple regression

model with PI as the dependent variable, alcohol consumption as the independent variable, and assorted

additional variables designed to account for education, income, sex, race, age, tooth-brushing frequency,

dental visits, and smoking. Table 22 shows the result

of this multiple regression analysis.

The principal detail of interest in analyzing the

relationship between periodontal disease and alcohol

consumption is the lack of statistical significance

(t = 1.413) of the regression coefficient for the drinking variable shown in table 22. This suggested that the

apparent relationship between alcohol consumption

and periodontal disease (table N) was spurious, but it

was still possible that this tinding could have resulted

from a nonlinear (possibly U-shaped) relationship between these two variables. To test this possibility, a

reduced multiple regression model (the full model

with the drinking variable omitted) was computed,

the residual values saved, and these residuals assessed

in terms of the drinking variable. These residuals

represent the unexplained variations in the PI scores

after allowance has been made for the other variables

in the model. The results of this analysis of residuals

are shown in table O. These results indicate that the

observed U-shaped distribution in the bivariate analysis (table N) is spurious, and that when the covariables

are included in the analytic model the levels of

Table N. Average and median periodontal index (PI) scores per person among persons ages 25-74 years, by drinking category,’ with

standard errors and sample sizes United States, 1971-74

Drinkhg category

Number

Standard

Mean PI Median Pi examined error of

mean

All categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,843 1.28 0.42 0.05

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 713 1.60 0.59 0,10

Little . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,176 1.12 0.38 0.06

Moderate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 827 1.21 0.38 0.09

Heavy > . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ---------- 227 1.66 0.82 0.18

lThe~e c~teg~rie~ are described in the text.

Table O. Average and median residual of periodontal index (Pi) scores per person among persons ages 25-74 years, by drinking category,l with

standard errors and sample sizes: United States, 1971-74

Drinking category

Number Mean Median Standard

examined residual residual error of

mean

All categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,715 0.00 -0.33 0.05

None . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 650 0.05 -0.35 0.08

Little . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,098 -0.01 -0.26 0.06

Moderate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 755 -0.05 -0.44 0.09

Heavy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212 0.14 -0.33 0.15

lThese ~eteg~ries are described in the teXt.

19
alcohol consumption can no longer be shown to be

associated with PI scores.

It can be concluded that consumption of alcohol

per se is not associated directly with periodontal

disease. If there is no association, then obviously

there cannot be any cause-and-effect relationship

hypothesized.

Turning to the relationship between reported

tooth-brushing frequency and PI scores, bivariate

analysis of PI by tooth-brushing frequency shows a

strong association between increased tooth-brushing

frequency and low PI scores. This pattern is demonstrated in tables P and Q.

This strong bivariate association demonstrated between tooth brushing and periodontal disease persists

within the multiple regression model previously described (table 22). The magnitude of the coefficient

for tooth-brushing frequency in table 22 suggests

that, given the implicit assumptions of the model, on

average the PI score decreases measurably for each

additional occurrence of daily tooth brushing, even

when factors of age, race, sex, socioeconomic status,

alcohol consumption, smoking habits, and pattern of

dental visits are taken into account. It is further evident that tooth brushing has its effect on the PI

through its effect on oral cleanliness. This effect can

be seen by adding the simplified oral hygiene index

(OHI-S) score as an independent variable in the muBiple regression model, as shown in table 23. Tooth

brushing, which was statistically significant in table

22, is not significant in table 23; instead OHI-S is

highly significant. In other words, the OHI-S variable

becomes the strongest explanatory variable, and R2

in table 23 is considerably larger than in table 22. In

addition the variables for education, income, one of

the race variables, and dental visits, in addition to the

tooth-brushing variable, are no longer statistically

significant.

The explanation for these changes is that tooth

brushing, race, and the socioeconomic factors associated with education, income, and dental visits combine to determine the effectiveness of an oral hygiene

regimen and thus play an important indirect role in

the prevalence and severity of periodontal disease.

The actual effect of these variables on OHI-S can be

seen in table 24, where they are all shown to strongly

influence the periodontal index.

It can be concluded that the NHANES I data show

a strong association between tooth brushing and periodontal disease, an association that previous evidences suggests is one of cause-and-effect. The effectiveness of tooth brushing in improving oral hygiene

and thus limiting periodontal disease is influenced by

factors associated with the socioeconomic variables of

education, income, and dental visits, as well as by race.

The strong association between levels of oral hygiene and prevalence and intensity of periodontal

disease lhas been demonstrated many times, and a

cause-and-effect relationship has also been estabIished.s 1 The results of this analysis are therefore to

be expected and add further weight to the importance of oral hygiene as a preventive and controlling

factor in periodontal disease. Tooth-brushing frequency is clearly directly related to levels of oral

hygiene (table 24). While one is tempted to say

“naturally” after that last statement, dentists know

that many persons who brush their teeth do not do so

very well. However, the data show that brushing per se

is important, apart from any consideration of its efficiency. Dental health education programs directed at

improving oral hygiene might be advised to spend

more effort on inducing people to brush regularly

rather than directing their energies at brushing

methods.

The relationship between smoking and periodontal index scores was tested for the 2,948 subjects

ages 25-’74 years for whom both types of data were

available. In this group, the mean PI score is 1.28.

Bivariate analysis of PI by smoking category suggests

an increased score with reported smoking as shown in

tables R and S. The pattern evident in these bivariate

tables is maintained remarkably well in the multiple

regression model (table 22). This table shows that

smokers,, on average, have noticeably higher PI scores

Table P. Average and median periodontal index (Pi) scores per person among persons ages 25-74 years, by tooth-brushing frequency, with standard

errors and sample sizes: United Statesr 1971-74

Number Standard

Daily tooth-brushing frequency Mean PI examined Median PI error of

mean

All frequencies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,903 1.27 0.41 0.05

Zero . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 3.54 4.05 0.32

One . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,180 1.40 0.57 0.06

Two . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,294 1.05 0.32 0.06

Three . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 0.99 0.31 0.10

Four . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 0.89 0.20 0.04

Five . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 0.19 0.08 0.13

Six . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 0.00 0.00 0.00

20
Table Q. Percent of persons ages 25-74 years with periodontal index

(Pi) scores of zero and greater than zero, by tooth-brushing

frequency: United States, 1971-74

Table S. Percent of persons ages 25-74 years with periodontal index

(Pi) scores of zero and greater than zero, by smoking history:

United States, 1971-74

PI score

Daily tooth-brushing Number

frequency examined Percent Percent

= zero > zero

PI score

Smoking history Number

examined Percent Percent

= zero > zero

All frequencies . . . . . . . . . . . . . 2,903 48.0 52.0

Zero . . . . . . . . . . . . . . . . . . . . 152 17.4 82.6

One . . . . . . . . . . . . . . . . . . . . 1,180 42.8 57.2

Two . . . . . . . . . . . . . . . . . . . . 1,294 53.3 46.7

Three . . . . . . . . . . . . . . . . . . . 237 52.3 47.7

Four . . . . . . . . . . . . . . . . . . . . 28 60.6 39.4

Five . . . . . . . . . . . . . . . . . . . . 10 85.7 14.3

Six . . . . . . . . . . . . . . . . . . . .< 2 100.0 0.0

than do nonsmokers, even after age, race, sex, socioeconomic factors, dental visits, and tooth-brushing

habits have been taken into account. This difference

is highly statistically significant. While conclusionson

causal relationships, as stated, cannot be made with

NHANES data, previous evidence suggests that such a

relationship exists.4 7-49

The finding that smoking has an adverse association with the development of periodontal disease is

strengthened by examining the patterns of those who

have smoked in the past but do not do so now. The

multiple regression analysis in table 22 shows that

those who have quit smoking have slightly higher PI

scores than do those who have never smoked, though

this difference is not statistically significant.

It could be suggested that interactions might exist

between smoking, alcohol consumption, and toothbrushing habits. Such interactions were explored, but

none could be demonstrated with these data from

NHANES L

Smoking is a health hazard and is adversely related

to a number of life-threatening diseases. The results

of this analysis suggest that periodontal disease can be

added to the list of diseases linked to smoking. Additional experimental research may identify the potential etiological role of smoking in periodontal disease.

All histories . . . . . . . . . . . . . . . 2,948 48.0 52.0

Never . . . . . . . . . . . . . . . . . . . 1,104 55.2 44.8

Past . . . . . . . . . . . . . . . . . . . . 516 53.0 47.0

Now . . . . . . . . . . . . . . . . . . . . 1,328 40.5 59.5

Relationship between dietary intake patterns of

adults with natural teeth and those of adults

without natural teeth or whose remaining teeth

are indicated for extraction

There is little firm evidence to show that loss of

teeth has deleterious effects on general health, though

some potential effects have been identified.s 2 One

aspect that has received little study is the relationship

between dietary and nutritional intake and loss (or

imminent loss) of teeth. This was examined for the

13,479 persons ages 18-74 years for whom data were

available.

“Dietary intake pattern” was defined earlier in

this report to test the relationship between DMF

values and the intake of sugar-rich foods. In this analysis, the term is interpreted as the intake of specific

nutrients-protein, calcium, iron, vitamin A, and vitamin C–as well as total calories. NHANES standards

for intake of these nutrients in males and females of

different ages have been defined (appendix III), so

that intake of these nutrients could be determined in

the following two ways:

1.

2.

The mean and median percent of NHANES standard achieved for each nutrient, for each age and

race group for males and females.

The .~ercent of .~ersons at or above the NHANES

standard of intake for each nutrient, for each age

and race group for males and females.

A new variable for presence of teeth had to be developed from information given. This variable was

Table R. Average and median periodontal index (Pi) scores per person among persons ages 25-74 years, by smoking history, with standard errors

and sample sizes: United States, 1971-74

Smoking history Number Standard

Mean Pf examined Median PI error of

mean

All subjects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,948 1.28 0.42 0.05

Never . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,104 1.01 0.31 0.07

Past . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 516 1.10 0.34 0.08

Now . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,328 1.55 0.68 0.08

21
created by subtracting the teeth diagnosed as requiring extraction, for any reason, from the number of

teeth present. This new count was then converted to

a two-level variable, with the first level indicating

some sound natural teeth remaining and the second

level indicating all teeth missing or indicated for

extraction.

Tables T and U show the mean and median intake

of the five nutrients and total calories, expressed as

percents of NHANES standards for white males and

white females. Tables W and Y present the same data

for black males and black females. These data hint at

favoring those with some natural teeth in the attainment of NHANES standards, though the pattern is

not clear-cut. Another way of looking at the trends is

shown in tables Z-CC, which present the proportion

of black and white males and females who attain or

exceed the NHANES standards for the nutrients

under study. These tables are similar to others presented in a previous reports and contain data of a

similar magnitude. Patterns in tables Z-CC are essentially the same as in tables T-Y. The trends shown in

tables T-CC are, however, difficult to quantify and

interpret. Therefore multiple regression models were

again employed, using the measures of NHANES

standards for nutrient intake in turn as dependent

variables. The independent variable of primary concern was the previously described dichotomous variable of presence or absence of teeth. To ensure that

the effects of age were allowed for, age was included

as a covariable in these analyses for the 18-44 year,

45-64 year, and 65-74 year age groups separately.

The instances when dental status was related to

specific nutrients to a statistically significant degre;

are shc~wnin tables 25-27. The coefficient in all five

models is negative, indicating that a lower proportion

of edentulous persons tended to attain NHANES nutritionaJ standards than did dentate persons. The

clearest and most consistent pattern is seen with differences in the intake of vitamin C. In all three age

groups (table 25) the coefficient is of remarkably

similar magnitude, and in all age groups the difference

in attainment of vitamin C standards between edentu10USand dentate groups attains a high level of statistical significance. The regression coefficients in table

26, relating to protein, and table 27, relating to iron,

are smaller. No statistically significant differences

were detected between dentate and edentulous per.

sons with respect to total calories, calcium, and

vitaminl A.

The difference in intake of vitamin C between tha

dentate and the edentulous is intriguing. Some would

suggest that the difference may be a causal relationship, that is that reduced vitamin C intake leads to

tooth loss. While such a relationship is theoretically

possible through the effect of insufficient vitamin C

i

Table T. Mean and median percent of NHAN ES standards for selected dietary components, by dental status for white males ages 18-74 years,

with standard errors: United States, 1971-74

Some natural teeth Edentulous or

indicated for extraction

Nutrient

Mean Median Standard Mean Median Standard

error error

18-44 years

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45-64 years

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

65-74 years

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium .,..............,.. . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

vitamin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Number examined = 1,765 Number examined = 97

93.2 88 1.3

/

96.2 96 .5.0

142.0 130 2.0 140.3 129 8,0

259.9 216 6.7 280.5 175 28.3

158.8 147 2.4 172.3 167 10.2

153.9 109 5.9 170.8 93 40.4

163.1 113 5.8 119.6 80 13.8

Number examined = 804 Number examined = 325

83.7 7~j 1.4 83.0 80 2.8

124.4 114. 3.1 112.8 107 4.0

212.5 179 6.4 197.7 170 12.7

146.9 137 2.8 136.1 125 4,4

153.6 I Og 6.8 159.6 91 22.6

159.3 128 6.5 124.7 72 8.5

Number exa!mined = 626 Number examined = 717

77.1 7;! 1.5 72.7 69 1.8

104.5 97, 2.1 97.0 91 2.6

188.6 164 6.0 178.6 148 6.3

128.6 116 2.9 116.8 111 3.0

177,7 1()$) 12.4 136.8 88 9.0

169.3 I 44 6.5 130.5 86 8.0

22
Table U. Mean and median percent of NHAN ES standards for selected dietary components, by dental status for white females ages 18-74 years,

with standard errors United States, 1971-74

Some natural teeth Edentulous or

Nutrient

indicated for extraction

Mean Median Standard Mean Median Standard

error error

18-44 years

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45-64years

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

65-74 years

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Number examined = 3,763

80.3 76 1.0

106.3 97 1.6

113.6 95 2.3

58.5 53 0.7

118.9 76 3.2

150.0 100 3.6

Numbarexamined =889

83.0 80 1.4

107.6 97 1.6

101.4 66 0.9

77.3 68 1.5

160.6 66 1.7

171.6 139 1.6

Number examined = 724

79.6 77 1.3.

95.6 90 2.1

100.2 87 2.4

97.8 90 2.3

145.8 87 14.2

180.7 159 6.1

Number examined = 247

75.0 72 2.0

93.7 88 3.6

101.6 82 5.3

51.9 49 1.6

94.0 65 7.4

119.5 74 11.3

Number examined = 361

83.0 77 2.0

102.5 93 3.1

100.6 83 4.8

82.9 76 3.3

169.5 73 38.6

146.9 114 9.8

Numbarexamined ’766

75.8 72 1.5

87.0 79 2.1

93.2 80 2.7

90.4 79 1.9

154.3 83 16.6

147.3 121 6.1

Table W. Mean and median percent of NHANES standards for selected dietary components, by dental status for black males ages 18-74 years,

with standard error.% United States, 1971-74

Some natural teeth Edentulous or

indicated for extraction

Nutrient

Mean Median Standard Mean Median Standard

error error

16-44years Numkerexamined =322 Numb?r examined = 15

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87.8 80 2.5 63.5 69 7.9

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131.1 121 4.8 191.2 98

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

14.3

181.6 156 10.7 161.8 136 48.2

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143.6 136 5.3 101.5 105 14.1

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156.3 64 13.6 102.4 102 27.4

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150.6 80 15.9 58.6 19 13.2

4564years Number examined = 176 Number examined = 39

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71.2 68 2.7

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113.3 101 7.6

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144.3 120 11.6

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125.1 115 6.4

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186.0 92 21.9

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157.5 101 20.7

65-74 years Numb-erexamined =153

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61.0 57 2.3

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64.7 78 5.1

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134.7 116 10.5

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104.6 89 8.9

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179.4 98 48.5

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127.2 110 14.8

78.3 62 13.2

111.9 88 16.3

181.6 117 48.4

148.0 103 31.0

169.4 82 37.1

149.4 90 42.7

Number examined = 140

70.0 64 4.8

88.1 83 5.1

138.6 123 8.7

110.7 93 13.7

155.0 80 38.8

149.0 96 24.7

23
Tabla Y. Mean and median percent of NHANES standards for selected dietary components, by dental status for black females ages 18-74 yaars,

with standard errors: United Statas, 1971-74

Some natural teeth Edentulous or

indicated for extraction

Nutrient

Mean Median Standard Mean Median Standard

error error

18-44 years

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45-64 years

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

65-74years

calories, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Number examined = 923 Number examined = 70

75,2 71 1.6

95.4 83 2.0

77.9 67 2.5

53.6 47 1.4

119,1 67 9.9

146.6 93 6.6

Number examined =169

75.1 64 7.9

99.4 91 12.3

67.8 49 7.7

51.3 46 6.5

97.8 49 25.0

67.0 28 12.6

Number examined =75

68.6 62 2,7

89.0 75 7.3

66.7 54 4.8

61.6 52 3.3

144.0 62 23.4

122.8 85 13.8

Number examined = 119

73.4 68 5,6

95.8 84 9.8

76.9 78 5.8

89.3 76 6.9

149.0 67 19.9

186.6 116 43.4

72.4 69 3.8

83.5 75 5.3

79.6 63 7.6

63.8 63 4.7

157.0 92 24.1

176.4 162 23.2

Number examined = 194

69.7 66 3.8

80.5 72 6.1

76.4 62 3.5

76.4 70 3.6

153.9 78 14.0

127.2 92 14.9

Table Z. Percent of white males ages 18-74years atorabove therecommended levels forvarious nutrients, by dental status:

United States, 1971-74

Edentulous or Some natural teeth

Nutrient indicated for extraction

Percent Standard error Percent Standard error

18-44 years Numbarexamined =1,765 Number examined = 97

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

35<3 1.8

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73.6 1,1

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83.7 1.1

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 ;2 1.0

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55.6 1.6

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53.9 2.1

45-64years Number examined = 804

46.0 7.4

68.7 5.2

80.5 5.3

83.2 4.8

47.1 6.8

40.0 6.9

Number examined = 325

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24.5 1.8

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66J5 2.8

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80;7 1.6

iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79.9 2.0

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54.16 2.3

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58)0 2.1

26.2 3.7

57.3 3.0

72.4 3.4

67.5 3.4

46.5 2.4

41.2 3.4

65-74 years Number examined = 626 Number examined =717

calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.8 1.4 13.5 1.6

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46.9

calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.7 40.8 3.0

75.5 2.1 74,4 2.6

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67.1 2.1 59.1 2.2

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53.3 2.2 44.6

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2.8

63.9 2.4 47.0 2.4

24
Table AA. Percent ofwhite females ages l&74years atorabove therecommended levels forvarious nutrients, by&ntal status:

United Statas, 1971-74

Nutrient

Some natural teeth Eden tulous or

indicated for extraction

Percent Standard error Percent Standard error

18-44 years

calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45-64years

calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A........ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

65-74 years

CeIorias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vkamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Number examined = 3,763

23.2 1.0

48.0 1.3

47.5 1.3

7.7 0.6

37.2 1.3

50.2 1.0

Number examined = 889

26.4 1.9

47.9 2.1

41.5 1.9

22.7 1.9

43.9 2.1

59.6 2.2

Number examined = 724

Number examined = 247

18.9 2.9

37.0 3.8

40.1 3.6

3.1 1.1

33.2 3.8

38.4 4.1

Numtrar examined = 361

26.5 3.0

43.5 3.1

37.2 3,4

30.5 3.3

39.2 3.1

53.3 3.8

Number examined = 766

19.9 1.9

41.4 2.9

42.3 2.5

39.8 2.6

43.7 2.8

67.1 2.5

15.8 1.8

27.8 2.2

37.0 2.4

31.7 1.8

42.6 2.3

55.1 2.3

Table BB. Percent of black males ages 18-74years atorabove therecommended lwelsfor various nutrients, by dental status:

United States, 1971-74

Some natural teeth Edentulous or

Nutrient indicated for extraction

Percent Standard error Percent Standard error

18-44 years

calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45-64 years

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

65-74years

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calcium, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Number examined =322 Numberexamined =15

29.1 2.6

64.6 3.8

69.8 3.8

67.1 2.9

43.6 3.5

42.7 3.2

Numberexamined =176

4.7 4.8

48.6 19.4

64.2 15.6

52.2 19.0

52.7 18.8

24.8 9.2

Numkerexamined =39

9.8 2.6

50.2 5.4

57.0 5.6

61.0 6.3

49.2 6.2

51.6 5.5

Number examined = 153

28.4 13.8

46.9 12.2

58.1 10.9

59.8 9.8

38.0 9.1

47.2 7.8

Number examined = 140

5.6 2.5

26.6 5.7

53.6 6.0

38.0 4.9

47.7 5.0

50.2 7.0

9.1 4.8

30.8 6.2

64.2 6.4

44.0 6.3

33.9 5.0

50.0 6.6

25
Table CC. Percent of black females ages 18-74yeam atorabove therecomnlended levels forvarious nutrients, by dental status:

United Statesr 1971-74

Edentulous or Some natural teeth

Nutrient indicated for extraction

Percent Standard error Percant Standard error

18-44 years Number examined = 923

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19.”7 1.7

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39.4 2.0

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.8 2.3

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.9 1.2

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.5 2.6

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47.6 1.9

46-64 years Numbarexamined =169

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.2 3.4

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26.3 5.6

Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20.0 3.8

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14.1 3.7

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36<,8 4.9

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47<,0 7.2

65-74 years Number examined = 119

.

Calories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.0 6.6

Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33.1 6.1

calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.1 6.8

Iron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29.7 6.2

Vitamin A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44.6 6.8

Vitamin C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54.4 6.8

Numbw examined = 70

25.2 9.6

50.0 8.5

23.5 6.9

3.2 2.2

19.8 5.7

22.3 4.8

Number examined = 75

14.4 5.5

28.9 6.6

26.5 6.3

13.0 5.6

46.3 8.8

69.6 7.4

Numtx?rexamined =194

17.5 3.8

26.6 6.5

29.7 3.3

23.1 4.3

41.6 4.5

44.4 5.5

on periodontal tissue, it seems unlikely to be occurring in this instance. Tables T-CC show that there is

hardly an insufficiency ofvitamin C (at least inrelation to N“HANES standards). Although there are

differences between the groups, even those with the

lowest levels of intake are still relatively well-off.

A more plausible explanation is that loss of teeth

is likely to influence dietary choices. It is reasonable

to assume that persons with dentures or nonfunctional natural teeth find mastication offibrous foods

such as fruits and vegetables more difficult than do

persons with healthy natural teeth, and that therefore

they tend to avoid such foods. This explanation is

strengthened by the results ofanalysisof reported ingestion of fruit by dentate and edentulous persons.

The record offruit ingestion wastaken from thefood

frequency interview. Results show that edentulous

persons consume less fruit than do dentate persons

(table 28).

This analysis suggests that total tooth loss might

result in a diminution of vitamin Cintake becauseof

the resulting change in dietary habits. Ingestion of

protein andiron maybe similarly affected to alesser

extent.

Relationship between dietary intake patterns

and use ofartiilcial dentures foresting by

edentulousadults

This analysis investigated whether, among th~

edentulous, there were nutritional differences accord;

ingto whether dentures were worn for eating ornott

There were 3,046 edentulous persons examined id

three a~gegroups, 18-44years,45-64 years,and65-7~

years. They were categorized as(a) those whodormt

wear a denture while eating, (b) those who wear one

denture, and (c) those who wear both upper and

lower dentures. Nutrients examined were the sameas

before, that is, total calories, protein, calcium, iro~,

and vitamins A and C.

Bivariate analysis andmultiple regression analysis,

the latter including age, sex, race, education, and income as covariables, were carried out. No consistent

trends were apparent in the bivariate analysis, and no

differences among the three groups were found in the

multiple regression analysis. Thus tabular results are

not presented.

It was concluded that nutritional intake among

edentulous persons is not associated with wearidg

dentures for eating.

26
References

1Institute of Medicine: Public Policy Options for Better Dental

Health. Washington. National Academy Press, Dec. 1980.

2National Center for Health Statistics: Plan and operation of

the Health and Nutrition Examination Survey, United States,

1971-1973, by H. Miller. Vital and Health Statistics. Series 1-

Nos. 10a and 10b. DHEW Pub. No. (HSM) 73-1310. Health

Services and Mental Health Administration. Washington. U.S.

Government Printing Office, Feb. 1973.

3National Center for Health Statistics: Basic data on dental

examination findings of persons 1-74 years, United States,

1971-1974, by J. E. Kelly and C. R. Harvey. Vital and Health

Statistics. Series 1 l-No. 214. DHEW Pub. No. (PHS) 79-1662.

Public Health Service. Washington. U.S. Government Printing

Office, May 1979.

4 National Center for Health Statistics: Decayed, missing, and

filled teeth among persons 1-74 years, United States, by C. R.

Harvey and J. E. Kelly. Vital and Health Statistics. Series 11-

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27
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tobacco smokers. 1 Periodontal. 42(5): May 1971.

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disease with 12 selected variables. I. Periodontal disease. 1

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Dentistry, 1977. p. 309.

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Examination Survey, United States, by E. E. Bryant, M. G.

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67. DHEW Pub. No. (HRA) 76-1341. Health Resources A~-

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Oct. 1975.

54Lepkowski, J. M.: Design Effects for Multivariate Categor~-

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55Survey Research Center Computer Support Group: 0SIRI!3

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recall data: Implications for nutrition study design and inte~-

pretation. Am. J. Clin. Nutr. 32(6): Dec. 1979.

28
List of detailed tables

1. Effect of percent of calories from sweets on the number of 14. Effect of frequency of between-meal sweet snacks on the

decayed, missing, and filled (DMF) permanent teeth control- number of missing permanent teeth controlling for specified

Iing for specified variables, by age for persons ages 6-64yaars: variables, by age for persons ages 6-64 years: United States,

United States, 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . 31 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

2. Estimated population by age group and parcent of calories 15. Effmtof frequency of between-meal nonsweet snacks on the

fromsweets: United States, 1971-74. . . . . . . . . . . . . . . 32 number of decayed, missing, and filled (DMF) permanent

3. Effect of percent of calories from sweets consumed between

meals on the number of decayed, missing, and filled (DMF)

permanent teeth controlling for specified variables, by age for

persons ages6-64years: United States, 1971-74 . . . . . . . .

4. Estimated population by age group and percent of calories

from sweets consumed between meals: United States, 1971-

74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5. Effect of frequency of between-meal sweet snacks on the

number of decayed, missing, and filled (DMF) permanent

teeth controlling for specified variables, by age for persons

agas6-64 years: United States, 1971-74 . . . . . . . . . . . . .

6. Estimated population by age group and frequency of

between-meal sweet snacks: United States, 1971-74. . . . . .

7. Correlation matrix of variables used in the analysis of diet

versus decayed, missing, and filled (DMF) permanent teeth

for l,923personsages6-ll years. . . . . . . . . . . . . . . . .

8. Correlation matrix of variables used in the analysis of diet

versus decayed, missing, and filled (DMF) permanent teeth

for2,012persons ages12-17 years. . . . . . . . . . . . . . . .

9. Correlation matrix of variables used in the analysis of diet

versus decayed, missing, and filled (DMF) permanent teeth

for6,947persons ages 18-44 years. . . . . . . . . . . . . . . .

10. Correlation matrix of variables used in the analysis of diet

versus decayed, missing, and filled (DMF) permanent teeth

for 2,665 persons ages 45-64 years . . . . . . . . , . . . . . . .

11. Effect of percent of calories from sweets consumed between

meals and number of between-meal sweet snacks on the number of decayed, missing, and filled (DMF) permanent teeth

controlling for specified variables, by age for persons ages

6-64years: United States, 1971-74. . . . . . . . . . . . . . . .

12. Effect of frequency of between-meal sweet snacks on the

number of filled permanent teeth controlling for specified

variables, by age for persons ages 6-64 years: United States,

1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13. Effect of frequency of between-meal sweet snacks on the

number of dacayed permanent taeth controlling for specified

variables, by age for persons ages 6-64 years: United States,

1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

33

34

35

36

37

38

39

40

41

42

43

teeth controlling for specified variables, by age for persons

ages 6-64 years: United States, 1971-74. . . . . . . . . . . . . 45

16. Estimated population by age group and frequency of

between-meal nonsweet snacks: United States, 1971-74. . . . 46

17. Effect of frequency of batween-meal sweet and nonsweet

snackson the number of decayed, missing, and fiiled(DMF)

permanent teeth controlling for specified variables, by age for

persons ages 6-64 years: United States, 1971-74 . . . . . . . . 47

18. Effect of enamel fluoride levels and frequency of betweenmeal sweet snacks on the number of decayed, missing, and

filled (DMF) permanent teeth controlling for specified variables, by age for persons ages 6-64 years: United States,

1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48

19. Relationship of periodontal index (Pi) score to the number

of decayed, missing, and filled (DMF) permanent teeth controlling for specified variables, by age for persons ages 18-74

years: United States, 1971-74. . . . . . . . . . . . . . . . . . . 49

20. Relationship of periodontal index (PI} score to the number

of decayed, missing, and filled (DMF) permanent teeth controlling for specified variables, by age for persons ages 18-74

years from whom enamel biopsies were obtained: United

States, 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

21. Relationship of periodontal index (P1 ) score to the number

of decayed, missing, and filled (DMF) permanent teeth controlling for specified variables, by age for persons ages 18-74

years from whom no enamel biopsies were obtained: United

States, 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

22. Relationship of periodontal index (P1 ) score to alcohol consumption controlling for specified variables, by age for persons ages 25-74 years: United States, 1971-74 . . . . . . . . . 52

23. Relationship of periodontal index (P1) score to toothbrushing frequency controlling for specified variables, by age

for persons ages 25-74 years: United States, 1971-74 . . . . . 52

24. Relationship of oral hygiene index (OHI-S) score to toothbrushing frequency controlling for specified variablas, by age

for persons ages 25-74 years: United States, 1971-74 . . . . . 53

25. Relationship of an absence of teeth to percent of the

NHANES standard attained for vitamin C controlling for

29
specified variables, by age for persons ages 18-74 years: variables, by age for persons ages 65-74 years: United States,

United States, 1971 -74 . . . . . . . . . . . . . . . . . . . . ...54 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...55

26. Relationship of an absence of teeth to percent of the 28. Relationship of an absence ofteeth andweekly frequency of

NHANES standard attained forprotein controlling forspeci- fruit ingestion to percent of the NHANES standard attained

fied variables, by age for persons ages 65-74 years: United for vitamin C controlling for specified variables, by age for

States, 1971-74 . . . . . . . . . . . . . . . . . . . . . . . . ...55 persons ages 18-74 yaars:United Statas,1971-74. . . . . . . . 56

27. Relationship of an absence of teeth to percent of the

NHANES standard attained for iron controlling for specified

30
Tablel. Effe@of percent ofcalories from smetson thenum&r ofdecayed, missing, and filled (DMF)~rmanent teeth controlling forspecitied

variables, byagefor persons ages6-64years: United States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized

coefficient (B) Sigma (Beta) Partial r

coefficient (Beta)

6-11 yearsl R2 = 0.239

Independent variable:

Percent of calories from sweets . . . . . . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Otherindicator . . . . . . . . . . . . . . . . . . . . . . .

12-17 years2 R2=0.142

Independent varieble:

Percent ofcalories from sweets . . . . . . . . . . . . . .

Covariable%

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

16-44years3 R2 = o.281

Independent variable:

Percent ofcaloriesfrom sweets . . . . . . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age atinterview . . . . . . . . . . . . . . . . . . . . . . . .

sax indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Blackindicator . . . . . . . . . . . . . . . . . . . . . . .

Otherindicator . . . . . . . . . . . . . . . . . . . . . . .

45-64yeers4 R2=o.13fj

Independent variable

Percentofcaloriesfrom sweets . . . . . . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

0.004

-0.198

-0.439

0.001

0.556

0.114

0.016

0.406

-0.012

0.168

-0.489

-0.000

0.968

1.100

-0.548

-0.116

0.008

1.604

0.577

-0.018

0.510

1.172

-3.078

-4.151

-0.006

0.806

-0.133

-0.050

0.273

1.058

-7.387

-9.799

0.004

0.127

0.167

0.010

0.033

0.095

0.142

0.520

0.007

0.277

0.388

0.020

0.061

0.288

0.533

2.266

0.007

0.571

0.533

0.017

0.014

0.224

0.548

0.912

0.011

0.564

0.662

0.029

0.022

0.398

0.639

2.980

0.960

1.556

2.630

0.090

16.877

1.208

0.114

0.782

1.650

0.605

1.262

0.015

15.778

3.818

1.027

0.051

1.040

2.809

1.007

1.092

37.432

5.228

5.618

4.550

0.524

1.428

0.201

1.719

12.598

2.654

11.561

3.289

0.024

-0.050

-0.086

0.003

0.480

0.029

0.003

0.016

-0.039

0.018

-0.044

-0.000

0.348

0.117

-0.040

-0.002

0.015

0.101

0.034

-0.015

0.504

0.074

-0.120

-0.060

-0.011

0.052

-0.007

-0.047

0.797

0.068

-0.272

-0.098

0.026

0.031

0.035

0.030

0.025

0.024

0.025

0.018

0.023

0.028

0.035

0.028

0.022

0.030

0.039

0.035

0.014

0.036

0.033

0.014

0.013

0.014

0,023

0.014

0.022

0.036

0.036

0.027

0.016

0.026

0.027

0.037

0.028

-0.041

-0.074

0.003

0.480

0.033

0.003

0.018

-0.042

0.015

-0.033

-0.000

0.351

0.125

-0.041

-0.002

0.018

0.075

0.024

-0.016

0.502

0.086

-0.136

-0.070

-0.012

0.046

-0.006

-0.043

0.203

0.073

-0.273

-0.104

lE~timated t~talp~pu/ati~n~f 23,356,053 bared On l,920per~~ns e~amined.

2Estimatad total population of 24,653,755 based on l,998pamcmsaxa mined.

3Estimated total population of 73,881,716 based on 6,904 persons examined.

4Estimated total population of 42,362,317 basadon 2,655 persons axaminad.

31
Table2. Estimated population byagegroup and percent of calories from sweetsl: United States, 1971-74

Percent of calories from sweetsq

Age group

0-9 10-19 20-29 30-39 40-49 50-59 60

or more

6-n years . . . . . . . . . . . . . . . . . . . . . . . . . 249,380 2,148,791 5,175,4:35 6,591,271 5,638,750 2,648,306 904,119

12-17 years . . . . . . . . . . . . . . . . . . . . . . . . 648,987 2,443,578 5,671,5’17 6,331,384 4,848,167 2,887,853 1,822,268

18-44years . . . . . . . . . . . . . . . . . . . . . . . . 4,227,888 10,950,339 17,272,043 17,570,196 12,698,400 7,259,074 3,903,775

45-64years . . . . . . . . . . . . . . . . . . . . . . . . 2,812,279 6,865,816 9,698,690 10,567,758 7,086,086 3,494,481 1,837,207

lSum~fthe three f~~dgr~up~; cereal~and grain pr~duct$, s"gar and primarily sugar proclucts, anddesserts andsweets, from the24-hour recall record.

32
Tabla3. Effect ofpercent ofcalories from swetsconsumed btmenmeals onthenumbr ofdecayed, missing, and filled (DMF)~rmanentteath

controlling forspecified variablesr bya~for persons ages6-64years: United States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized

coefficient (B) Sigma (Bata) Partial r

coefficient (Bata)

6-11 yearsl R2 = 0.243

Independent variable:

Parcent of calcwiesfrom between-meal sweats . . . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Blackindicator . . . . . . . . . . . . . . . . . . . . . . .

Otherindicator . . . . . . . . . . . . . . . . . . . . . . .

12-17 years2 R2=0.143

Independent variable:

Percent ofcalories from between-meal swets . . . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sax indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

18-44yaars3 R2=0.284

Independent variable:

Percent ofcalories from between-meal sweets . . . . .

Covariable~

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

Collegeindicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageatinterview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Otherindicator . . . . . . . . . . . . . . . . . . . . . . .

45-64 yaa rs4 R2=oa140

Independent variable:

Percent ofcalorias from between-meal sweets . . . . .

Covariable~

Education:

Highschool indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

0.013

-0.181

-0.409

-0.000

0.556

0.117

0.031

0.425

0.018

0.194

-0.445

-0.000

0.9!54

1.121

-0.645

0.047

0.046

1.573

0.575

-0.019

0,515

1.132

-3.091

-4.101

0.053

0.808

-0.063

-0.048

0.280

1.048

-7.317

-10.031

0.006

0.123

0.162

0.010

0.032

0.094

0.140

0.496

0.010

0.270

0.385

0.020

0.059

0.296

0.540

2.298

0.009

0.560

0.550

0.016

0.014

0.226

0.542

0.923

0.021

0.564

0.694

0.029

0.022

0.394

0.636

3.269

2.233*

1.473

2.519

0.040

17.151

1.237

0.219

0.B56

1.878

0.717

1.154

0.026

16.177

3.786

1.195

0.020

4.845’

2.810

1.045

1.159

36.602

0.071 0.032 0.081

-0.038

-0.068

–0.001

0.481

0.034

0.006

0.019

0.051

0.017

-0.030

-0.001

0.348

0.128

-0.049

0<001

-0.046

-0.090

-0.001

0.479

0.030

0.030

0.034

0.031

0.025

0.024

0.005

0.017

0.025

0.018

0.048 0.025

0.020

-0.040

-0.001

0.343

0.119

0.029

0.035

0.029

0.022

0.030

-0.047

0.001

0.039

0.035

0.062 0.013 0.073

0.099

0.035

-0.015

0.509

0.071

0.035

0.033

0.013

0.013

0.014

0.074

0.025

-0.017

0.508

4.998 0.084

5.701

4.442

-0.121

-0.059

0.022

0.014

-0.138

-0.070

2.544* 0.067 0.026 0.072

1.433

0.090

1.621

12.602

2.656

0.052

-0.003

-0.045

0.202

0.088

0.036

0,038

0.027

0.017

0.026

0.046

–0.003

–0.041

0.208

0.072

11.508

3.069

-0.289

-0.100

0.027

0.038

-0.271

-0.107

lEstimated total population of 23,356,053 basedon l,920persons examinecL

2Emimated tOtal p~pulationof 24,653,755 ba~ad on I,99B peraonse~amined.

3Etiimatad total population of 73,881,716 basadon 6,904 parsons examined.

4E~imatadtotal population of 42,362,317 baaed on2,655persons examined.

“Denotes statistical significance at tha 5-parcant level.

33
Table4. Estimated population byagegroup and percent of calories from sweets consumed between meals 1.. lJnited Stetes,1971-74

percent of calories from between-meal swets~

Age group

o-9 10-19 20-29 30-39 40-49 50-59

6-n years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13,456,967 6,,402,223 2,235,448 894,698 242,085 124,632

12-17years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12,127,278 6,970,766 3,267,421 1,398,071

18-44years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

508,917 381,302

44,268,369 17,402,964 8,040,185 2,874,440 881,499 414,259

45-64years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29,434,346 8,,114,513 3,139,478 1,178,303 314,161 181,517

lSum of the three food groups; cereals and grain products, suger and primarily sugar proclucts, and desswts endsweats, from the24-hour recall record,

and recorded as aaten at other than mealtimes.

34
Tabie5. Effect of frequency of between-meal sweet snacks onthenumber ofdecayd, missing, andtilled (DMF)permanent teeth controlling

for specified variables, by age for persons ages6-64 years: United States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized Sigma (Beta) Partial r

coefficient (B) coefficient (Beta)

6.11 year~l /72 = Q-244

Independent variable:

Number of between-meal sweet snacks , . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age atinterview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Otherindicator . . . . . . . . . . . . . . . . . . . . . . .

12-17 years2 RZ=o.144

Independent variable:

Numbarof between-meal sweet snacks . . . . . . . . .

Covariables

Educatiom

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageatinterview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

18-44 years3 R2 =0.286

Independent variable:

Number of betwaen-meal swaet snacks . . . . . . . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sexindicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45.64 years4 R2=o.143

Independent variable:

Numberofbetween-rnaal sweet snacks . . . . . . . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

Collegeindicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sax indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Blackindicator . . . . . . . . . . . . . . . . . . . . . . .

Otherindicator . . . . . . . . . . . . . . . . . . . . . . .

0.098

-0.190

-0.422

-0.001

0.555

0.115

0.029

0.390

0.145

0.204

-0.428

-0.001

0.862

1.129

-0.607

-0.012

0.375

1.530

0.552

-0.021

0.514

1.308

-3.009

-4.021

0.446

0.711

-0.138

-0.049

0.282

1.131

-7.226

-9.982

0.036

0.124

0.163

0.010

0.032

0.094

0.140

0.500

0.074

0.269

0.389

0.020

0.061

0.291

0.534

2.313

0.051

0.562

0.555

0.016

0.014

0.224

0.!548

0.940

0.122

0.561

0.694

0.030

0.022

0.386

0.641

2.928

2.744*

1.532

2.588

0.129

17.332

1.228

0.206

0.778

1.863*

0.757

1.102

0.068

15.806

3.885

1.138

0.005

7.349*

2.719

0.984

1.310

37.612

5.835

5.489

4.275

3.651 *

1.267

0.199

1.632

12.869

2.928

11.264

3.409

0.078

-0.048

-0.092

-0.004

0.479

0.030

0.’005

0.016

0.050

0.022

-0.039

-0.002

0.346

0.120

-0.044

-0.000

0.080

0.096

0.033

-0.017

0.507

0.082

-0.117

-0.058

0.068

0.046

-0.008

-0.046

0.204

0.073

-0.266

-0.100

0.030

0.031

0.034

0.031

0.024

0.024

0.025

0.018

0.026

0.029

0.035

0.028

0.022

0.030

0.039

0.035

0.011

0.035

0.034

0.013

0.013

0.014

0.022

0.014

0.025

0.036

0.038

0.028

0.016

0.025

0.027

0.036

0.089

-0.040

-0.071

-0.004

0.481

0.034

0.006

0.018

0.054

0.018

-0.029

-0.002

0.350

0.128

-0.046

-0.000

0.093

0.072

0.024

-0.019

0.506

0.086

-0.134

-0.068

0.094

0.040

-0.006

-0.042

0.210

0.078

-0.268

-0.107

lE~~irna~~d~~~=l population of 23,356,053 ba~d on l,923person~ examined2Estimated total population of 24,653,755 based on2,012 persons examined.

3Estimatad total population of 73,681,716 based on 6,947 parsons examined.

4Eetimated total population of42,362,317 based on2,665persons examined.

*Denotes statisticalsignificance at tha 5-parcant level.

35
Table6. Estimated population byagegroup and frequency of betwaen-meal sweet snacksl: United States, 1971-74

Frequency of between-meal sweet snacks~

Age group

o 1 2 3 4 5 6

More

than 6

6-n years . . . . . . . . . . . . . . . . 5,885,758 6,754,462 4,863,890 2,879,,092 1,698,036 717,993 389,878 166,946

12-17 years . . . . . . . . . . . . . . . . 4,891,414 6,412,763 6,039,416 3,400,326 1,852,988 1,294,884 437,697 324,268

18-44 years . . . . . . . . . . . . . . . . 19,829,235 19,564,823 14,570,994 9,374,317 5,222,512 2,739,523 1,375,145 1,205,169

45-64 years . . . . . . . . . . . . . . . . 16,627,709 10,933,814 6,845,777 4,010,128 2,070,494 1,142,906 359,492 371,997

I sum of the b~ween-meal freq”en~y of three food groups; cereals and grain products, sugar and primarily sugar products, and desserts and SWc3@S,

from the 24-hour racall record.

36
0

?

r-

“w

00

gg

!-

00

qz

mm

mm

. .

. .

. .

. .

. .

CO U3CD. OKY

yyyooy

CQt-ooo.o.

(orJo-oleYooo.OOO.

bo!-*NeJNel

.l-Ia)E(omcoo

o.

Ooyyoooo

Ooooq.oo.o

ercoomm.m

d-od-d-.-oa

Oyyooyyo

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. .. . . . . . . . .

. . . . . . . .

. . . . . . . .
CJ

co

Table8. Correlation matrix of variables used intheanalysis ofdietversus decay ed, missing, and filled (DMF)parmanent teeth for2,012persons agas12-17yaars

Variable

Variable

Percent of

DMF

Percent of calories Frequency of Frequency of High

calories from between-meal between-meal College Family Age at Race

teeth school indicator Sex

from sweets between-meal swae ts

income interview (black) nonsweets indicator

sweets

Percent ofcaiorias from sweets . . . . . . . . . . . .

Percent of calories from between-meal

sweets . . . . . . . . . . . . . . . . . . . . . . . . . . .

Frequency of between-meal sweet snacks .

Frequency of between-meal nonsweet

snacks . . . . . . . . . . . . . . . . . . . . . . . . . . .

High school indicator . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . .

Family income . . . . . . . . . . . . . . . . . . . . . .

Agaat interview . . . . . . . . . . . . . . . . . . . . . .

Sex . . . . . . . . . . . . . . . . . . . .

Race (black), . . . . . . . . . . . . . . . . . . . . . . .

Raca (other) . . . . . . . . . . . . . . . . . . . . . . . .

-0.0311

0.0681

0.049

0.054

0.048

-0.055

-0.014

0.351

0.121

-0.045

0.005

0.5362

0.3532

–0.1042

-0.003’

–0.048’

–0.060’

0.041 ‘

-0.0441

0.088’

–0.038’

0.7081

0.1862

–0.003’

–0.030’

–0.01 6’

0.069’

–0.0061

0.086’

–0.032’

0.407

-0.028 0.021

0.021 0.004 -0.603

0.042 0.012 -0.091 0.438

0.026 0.030 0.013 -0.018 -0.005

-0.064 -0.035 0.002 -0.034 –0.050 0.009

0.020 0.029 0.009 -0.145 -0.286 -0.027 0.013

-0.013 -0.000 -0.005 0.015 -0.026 0.019 -0.011 -0.033

lN”~b~~~~a~inedequals 1,998,

~Number examined equals 2,117.
Table9. Correlation matrix ofvariables used intheanalysis ofdietversus decayed, missing, andtilled(DMF) permanent teeth for6,947persons ages 18-44 years

Variable

Variable

Parcent of

DMF Percent of calories Fraquancy of Fraquency of High

calories from between-meal between-meal

Collaga Family Aga at Race

teeth school indicator sex

from sweats between-meal

income interview (black)

sweats nonsweets indicator

sweets

Percent of calories from sweets . . . . . . . . . . . .

Percent Of calories from between-meal

sweets . . . . . . . . . . . . . . . . . . . . . . . . . . .

Frequency of between-meal sweet snacks . . . . .

Frequency of between-meal nonsweet

snacks . . . . . . . . . . . . . . . . . . . . . . . . . . .

High schoolindicator . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . .

Familyincome . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . .

Sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Race (black) . . . . . . . . . . . . . . . . . . . . . . . .

Race (other) . . . . . . . . . . . . . . . . . . . . . . . .

-0.0061

0.0251

0.056

0.117

0.074

-0.045

0.100

0.502

0.070

-0.121

-0.063

0.5082

0.3082

-0.1472

0.025’

–0.087’

-0.107’

-0.041 ‘

0.090’

0.065’

0.010’

0.6761

0.1842

0.052’

-0.062’

-0.042’

-0.085’

0.063’

0.029’

–0.01 3’

0.471

0.051 0.014

-0.030 0.024 -0.764

0.027 0.097 -0.087 0.215

-0.047 0.119 -0.002 -0.019 0.192

-0.110 -0.143 0.011 -0.023 -0.050 -0.003

-0.036 -0.076 0.039 -0.137 -0.193 -0.017 0.034

-0.023 -0.012 -0.053 0.065 -0.014 -0.007 -0.021 -0.040

lNumber axamined equals 6,904.

2Number axamined equals 7,274.
&

Table 10. Correlation matrix ofvariables used inthe analysis of diatversus decayed, missing, and filled (DMF)permanant teeth for2,665persons agas45-64 years

Variable

Percent of

DMF

Percent of calories Frequency of Fraquency of High

calories from between-meal between-meal

College Family Age at

school

Race

taeth indicator Sex

from sweets between-meal sweets nonswaets

income interview (black) indicator

swaets

Percent of calorias from sweets . . . . . . . . . .

Percent of calories from betwean-meal

sweats . . . . . . . . . . . . . . . . . . . . . . . . . . .

Frequency of Wween-meal sweat snacks . . . . .

Frequency of batween-meal nonsweet

snacks . . . . . . . . . . . . . . . . . . . . . . . . . . .

High school indicator . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . .

Family income . . . . . . . . . . . . . . . . . . . . . .

Ageatinterviaw . . . . . . . . . . . . . . . . . . . . . .

Sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Race (black) . . . . . . . . . . . . . . . . . . . . . . . .

Race (other) . . . . . . . . . . . . . . . . . . . . . . . .

–0.01 51

0.063’

0.083

0.092

0.069

-0.041

-0.040

0.214

0.075

-0.269

-0.095

0.4692

0.3152

-0.1252

–0.029’

-0.111’

–0.136’

0.030’

0.021 ‘

0.054’

0.024’

0.7141

0.2452

0.039’

–0.041 ‘

-0.013’

–0.067’

0.010’

–0.032’

0.028’

0.474

0.057 0.048

0.002 0.064 –0.51 8

0.041 0.116 -0.008 0.402

-0.081 -0.114 -0.071 –0.056 –0.1 95

-0.075 –0.102 0.033 –0.046 -0.117 0.023

-0.065 -0.140 -0.075 -0.106 -0.200 -0.034 0.017

0.016 0.047 -0.059 0.051 -0.009 0.001 -0.012 -0.024

1 Number examined equals 2,655.

2Numberexamined 6qutiiS2,850.
Table Il. Effect ofpercent ofcalories from sweets consumed between meals andnumber of beWeen-meal sweet snacks onthenumber of decayed,

missing, and filled (DMF)permanent teeth controlling forspecitied variables, byagefor persons ages6-64 years: United States, 1971-74

Age and variable

Regression analysis statistics

Regression Sigma (B) t-statistic Standardized

coefficient (B)

S&ma (Beta) Partial r

coefficient (Beta)

6-11 yearsl R2 = 0.245

Independent variables

Percent of calories from between-meal sweet snacks .

Number of between-meal sweet snacks . . . . . . , . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

Collage indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

12-17 years2 R2= 0.143

Independent variables:

Percent ofcalories from betwaen-meal swaet snacks .

Number of batwaen-meal sweet snacks . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

18-44 years3 R2 = o.287

Independent variables

Percent ofcalories from betwaen-meal sweet snacks .

Numbarof betwaen-meal swaetsnecks . . . . . . . . .

Covariables

Education

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45-64 years4 R2= 0.144

Independent variables

Percent ofcalories from betwaen-meal swaet snacks .

Numbarof between-meal swaet snacks . . . . . . . . .

Covariablas

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Rac&

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

0.005

0.070

-0.183

-0.411

-0.001

0.555

0.119

0.028

0.396

0.014

0.043

0.197

-0.445

-0.001

0.955

1.128

-0.640

0.038

0.011

0.318

1.523

0.540

-0.022

0.515

1.294

-3.018

-4.016

0.007

0.419

0.746

-0.128

-0.049

0.283

1.150

-7.245

-9.985

0.009

0.054

0.122

0.161

0.010

0.032

0.084

0.140

0.500

0.012

0.084

0.270

0.385

0.020

0.059

0.293

0.539

2.292

0.014

0.081

0.561

0.558

0.016

0.014

0.220

0.543

0.845

0.025

0.151

0.569

0.700

0.030

0.022

0.391

0.645

3.001

0.581

1.300

1.502

2.546

0.120

17.182

1.263

0.202

0.793

1.221

0.508

0.728

1.156

0.045

16.147

3.850

1.186

0.017

0.807

3.809”

2.714

0.869

1.361

35.991

5.868

5.562

4.251

0.269

2.770’

1.310

0.183

1.645

12.801

2.941

11.234

3.327

0.027

0.056

-O.O46

-0.080

-0.004

0.479

0.030

0.005

0.016

0.037

0.015

0.021

-0.040

-0.001

0.343

0.120

-0.047

0.001

0.016

0.068

0.086

0.033

-0.018

0.509

0.081

-0.118

-0.058

0.008

0.083

0.048

-0.007

-0.046

0.204

0.074

-0.267

-0.100

0.047

0.044

0.030

0.034

0.031

0.025

0.024

0.025

0.018

0.030

0.029

0.028

0.035

0.028

0.022

0.030

0.039

0.035

0.019

0.018

0.035

0.034

0.013

0.013

0.014

0.022

0.014

0.031

0.030

0.036

0.038

0.027

0.017

0.026

0.027

0.037

0.020

0.041

-0.038

-0.069

-0.004

0.481

0.035

0.006

0.018

0.028

0.011

0.017

-0.030

-0.001

0.347

0.128

-0.048

0.001

0.013

0.058

0.072

0.024

-0.020

0.506

0.094

-0.134

-0.068

0.006

0.062

0.042

-0.006

-0.042

0.210

0.079

-0.269

-0.107

lE~timatad total population of23,356,053 basad On l,920persons examined.

2Estimated total population of 24,653,755 bared on l,998parsons examined.

3Estimated total population of 73,881,716 basadon 6,904 persons examined.

4Estimatedtotel population of42r362,317 based on 2,655 parsons axaminecl.

“Danotes statistical significance attha 5-percent Iavel.

41
Table 12. Effect of frequency of between-meei weetsnacks onthenum&r of filled p(~rmanent teeth controlling forspecified variables, by age

forpersons ages 6-64years: United State!s,1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized

coefficient (B) Sigma (Beta) PartiaJ r

coefficient (Beta)

6-11 yearsl /72=0.176

Independent variable;

Number of between-meal sweet snacks . . . . . . . . .

Covariables:

Education:

I-ligh school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator....,......,.. . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

12-17years2 R2=0.169

Independent variable:

Number of between-maal swaet snacks . . . . . . . . .

Covariable$

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income .,....... . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Otherindicator . . . . . . . . . . . . . . . . . . . . . . .

18-44 years3 R2 = 0.209

Independent variable:

Numbarof betwaen-meal sweet snacks . . . . . . . . .

Covariables

Education:

I-ligh school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45.64 year54 R2= 0,233

Independent variable:

Number of between-meal sweet snacks , . . . . . . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview .,....... . . . . . . . . . . . . . . .

Sex indicator...,...,.. . . . . . . . . . . . . . . . .

Race:

Blackindicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

0.050

0.062

0.108

0.028

0.325

0.220

-0.233

-0.561

0.131

0.664

0.964

0.069

0.642

0.543

-2.271

0.005

0.006

2.807

5.393

0.158

0.044

0,531

-4.473

-2.522

-0.070

1.695

5.012

0.185

-0.141

0.626

-3.389

-2.853

0.034

0.119

0.149

0.009

0.026

0.082

0.126

0.335

0.069

0.220

0.360

0.018

0.046

0.231

0.240

2.691

0.045

0.374

0.409

0.015

0.013

0.178

0.324

1.144

0.112

0.375

0.543

0.027

0.033

0.326

0.342

1.462

1.474

0.520

0.724

3.079

12.441

2.678

1.854

1.675

1.889

3.016

2.675

3.799

13.928

2.355

9.471

0.002

0.127

7.497

13.172

10.240

3.356

2.987

13.804

2.204

0.628

4.518

9.228

6.902

4.312

1.923

9.914

1.951

0.053

0.020

0.031

0.118

0.370

0.074

-0.055

-0.029

0.053

0.083

0.103

0.115

0.272

0.068

-0.196

0.000

0.001

0.218

0.404

0.160

0.053

0.041

-0.216

-0.045

-0.016

0.126

0.314

0.199

-0.117

0.046

-0.143

–0.033

0.037

0.040

0.044

0.038

0.020

0.028

0.028

0.018

0.028

0.028

0.038

0.032

0.018

0.029

0.023

0.049

0.012

0.029

0.030

0.016

0.016

0.014

0.019

0.020

0.026

0.028

0.036

0.029

0.028

0.024

0.014

0.018

0.058

0.016

0.023

0.111

0.376

0.081

-0.057

-0.032

0.058

0.070

0.078

0.106

0.286

0.074

-0.202

0.000

0.002

0.154

0.271

0.166

0.058

0.046

-0.230

-0.050

-0.018

0.116

0.261

0.191

-0.129

0.052

-0.156

-0.037

lEstimated total population of 23r356,053 basedon 1,923 persons examined.

2E~timated total population of 24,653,755 based on 2,012 parsons examhed.

3E~timated total populationof 73,881,716 based on 6,947 persons exwrined.

4Ewimated total populetionof 42,362,317 basad On 2,665 pemonsexarnined.

42
Table 13. Effect of frequency of&twen-meal smetsnacks onthenum&r ofdecayed ~rmanent teeth controlling forspecified variables, by age

forpersons ages6-64 years: United States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized Sigma (Beta) Partial r

coefficient (B) coefficient (Beta)

6-11 yearsl R2 = 0.121

Independent variable:

Number of betwaen-maal sweet snacks . . . . . . . . .

Covariablex

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

Collage indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Blackindicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

12-17 years2 R2= 0.090

Independent variable:

Number of betwaen-meal sweet snacks . . . . . . . . .

Covariablex

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Otherindicator . . . . . . . . . . . . . . . . . . . . . . .

18-44years3 R2= 0.099

Independent variable:

Number of between-maal sweet snacks . . . . . . . . .

Covariablex

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Totel family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45-64 years4 R2= 0.032

Independent variable:

Numberof between-meal sweet snacks . . . . . .ti . .

Covariablex

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age atinterview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

0.039

-0.229

-0.466

-0.025

0.179

-0.028

0.112

0.768

0.026

-0.387

-1.016

-0.042

0.171

0.184

1.028

-0.784

0.010

-0.488

-1.102

-0.025

-0.047

-0.251

1.317

-0.121

0.027

0.054

0.041

-0.022

-0.030

-0.124

0.477

0.381

0.019

0.104

0.102

0.004

0.015

0.051

0.092

0.600

0.037

0.180

0.191

0.011

0.037

0.103

0.244

0.590

0.023

0.144

0.159

0.008

0.006

0.075

0.222

0.309

0.024

0.082

0.093

0.005

0.006

0.092

0.148

0.813

2.033’

2.189

4.550

6.438

11.738

0.552

1.222

1.279

0.700

2.151

5.322

3.916

4.634

1.789

4.212

1.329

0.453

3.386

6.928

3.060

7.195

3.327

5.945

0.393

1.155

0.667

0.439

4.267

5.106

1.356

3.218

0.468

0.052

-0.095

-0.168

-0.132

0.254

-0.012

0.033

0.050

0.016

-0.073

-0.163

-0.106

0.110

0.035

0.134

–0.024

0.007

-0.098

-0.213

-0.066

-0.148

-0.050

0.164

-0.006

0.027

0.018

0.011

-0.103

-0.110

-0.041

0.089

0.019

0.024

0.043

0.036

0.019

0.019

0.021

0.027

0.038

0.023

0.034

0.029

0.026

0.023

0.019

0.034

0.018

0.016

0.028

0.029

0.022

0.018

0.015

0.028

0.014

0.024

0.026

0.026

0.022

0.021

0.029

0.028

0.030

0.055

-0.073

-0.119

-0.120

0.261

-0.012

0.034

0.053

0.017

-0.059

-0.118

-0.094

0.114

0.036

0.133

-0.025

0.008

-0.066

-0.138

-0.065

-0.151

-0.053

0.166

-0.006

0.028

0.015

0.009

-0.089

-0.109

-0.041

0.087

0.020

lEstimated total population of 23,356,053 basedon 1.923 persons examined.

2E~imated total population of 24,653,755 based on2,012 Persons examined.

3E$timated total population of 73,881,716 basad on6,947 persons examined.

4Estimated total population of 42,362,317 based on 2,665 persons examined.

*Denotes statisticalsignificance at the 5-percent Ieval.

-. ., ...

,. ,

43
Table 14. Effect of frequency of between-maal sweet snacks onthe number of missing lpermanent teeth controlling forspecified variables, by age

forpersons ages 6-64 years: United States, 1971-74

Regression analysis statistics

Age and variable

Regression

Sigma (B) t-statistic Standardized Sigma (Beta) Partial r

coefficient (B) coefficient (Beta)

6-11 yearsl R2 = 0.030

Independent variable:

Number of between-meal sweet snacks . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator, . . . . . . . . . . . . . . . . . . . . . .

12-17 years2 R2 = Q.067

Independent variable:

Number of between-meal sweet snacks . . . . . . . . .

Covariablas

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageatintewiew . . . . . . . . . . . . . . . . . . . . . . . .

%xindicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Rata:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

18-44 years3 R2 = 0.286

Independent variabla:

Number of between-meal sweet snacks . . . . . . . .

Covariables:

Education:

High schOol indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageatintarview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Rata:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45-64 yea rs4 R2 =0.152

Independent variable:

Number of between-meal sweet snacks . . . . . . . ,

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageatinterviaw . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Othar indicator . . . . . . . . . . . . . . . . . . . . . . .

0.008

-0.023

-0.063

-0.004

0.051

-0.077

0.150

0.183

-0.011

-0.073

-0.376

-0.028

0.149

0.401

0.636

0.766

0.359

-0.790

-3.739

-0.154

0.518

1.028

0.147

-1.378

0.489

-1.038

–5.190

-0.212

0.454

0.629

-4.314

–7.510

0.011

0.050

0.050

0.003

0.009

0.032

0.072

0.221

0.030

0.140

0.125

0.008

0.026

0.118

0.343

0.570

0.056

0.500

0.508

0.013

0.012

0.221

0.409

0.545

0.200

0.775

0.992

0.046

0.042

0.531

0.698

2.098

0.738

0.466

1.272

1.390

5.534

2.394

2.071

0.829

0.381

0.525

3.009

3.378

5.714

3.413

1.853

1.345

6.431’

1.57B

7.365

11.870

41.608

4.650

0.358

2.530

2.449*

1.339

5.234

4.611

10.857

1.186

6.177

3.580

0.018

-0.016

-0.039

-0.037

0.124

-0.055

0.075

0.020

–o.C09

-0.018

-0.079

-0.092

0.125

0.099

0.108

0.031

0.073

-0.048

-0.216

-0.121

0.489

0.062

0.005

-0.019

0.087

-0.046

-0.197

-0.138

0.228

0.028

-0.110

-0.052

0.025

0.038

0.032

0.031

0.028

0.020

0.032

0.024

0.024

0.040

0.038

0.024

0.028

0.019

0.052

0.024

0.012

0.030

0.028

0.011

0.012

0.013

0.015

0.007

0.028

0.035

0.038

0.030

0.021

0.024

0.019

0.016

0.018

-0.012

-0.026

-0.032

0.124

-0.056

0.072

0.021

–0.009

-0.014

-0.057

-0.081

0.128

0.102

0.108

0.032

0.086

-0.036

-0.157

-0.132

0.492

0.072

0.008

-0.022

0.072

-0.041

-0.159

-0.127

0.234

0.030

-0.115

-0.056

lE~~i~a~ed~o~a\population of 23,356,053 based on l,923par~on~ e~a~inad.

2Estimated total population of 24,653,755 basedon 2,012 persons examined.

3Estimated total population of 73,881,716 based on 6,947 persons examined.

4Esti~ated total population of 42,362,317 based on2,655 persons examined.

*Danotes statistical significance at the 5-percant level.
Table 15. Effect of frequency of&tween-meal nonsweet sn~kson thenum&r ofdecayed, missing, and filled (DMF)permanent teeth controlling

forspecifiad variables, byegefor persons ages 6-64 yaar* United States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized Sigma (Beta) Partial r

coefficient t (B) coefficient (Beta)

6-11 yearsl R2 = 0.240

Independent variable:

Number of betwaen-meal nonsweet snacks . . . . . . .

Covariablex

0.055

-0.203

-0.436

-0.000

0.557

0.115

0.033

0.449

0.114

0.170

-0.453

0.000

0.962

1.116

-0.609

-0.046

0.168

1.539

0.497

-0.022

0.503

1.301

-2.987

-4.086

0.281

0.692

-0.212

-0.053

0.286

1.169

-7.052

-10.268

0.032

0.127

0.164

0.010

0.032

0.095

0.140

0.519

0.071

0.273

0.391

0.020

0.060

0.290

0.533

2.323

0.039

0.558

0.547

0.016

0.013

0.230

0.551

0.893

0.061

0.554

0.683

0.029

0.022

0.402

0.640

2.882

1.719 0.047 0.027 0.054

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageatintarview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

12-17 years2 R2 = 0.144

1.604

2.662

0.050

17.261

1.213

-0.051 0.031 –0.042

-0.096 0.035 -0.073

-0.002 0.031 -0.002

0.481 0.024 0.482

0.029 0.025 0.034

0.237

0.866

0.006 0.025 0.006

0.018 0.018 0.020

0.050 0.031 0.053

Independent variable:

Number of between-meal nonsweet snacks . . . . . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

18-44 years3 R2 = 0.284

Indapandent variable:

Number of between-meal nonswaetsnecks . . . . . . .

Covariables

Education:

Highschool indicator . . . . . . . . . . . . . . . . . . .

Collage indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Aga at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45-64 years4 R2 =0.144

Independent variable

Number of between-meal nonsweet snacks . . . . . . .

Covariables:

Education:

Highschool indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

1.613

0.624

1.158

0.006

15.992

3.843

0.018

-0.041

0.000

0.346

0.119

0.029

0.035

0.028

0.022

0.030

0.015

-0.031

0.000

0.350

0.127

1.142

0.020

-0.045

-0.001

0.039

0.036

-0.046

-0.001

4.274’ 0.060 0.013 0.069

2.759

0.908

1.336

37.530

5.664

0.097

0.030

-0.018

0.496

0.082

0.035

0.033

0.013

0.013

0.015

0.073

0.022

-0.020

0.495

0.095

5.422

4.574

-0.116

-0.059

0.023

0.013

-0.132

-0.069

4.628* 0.096 0.020 0.101

1.250 0.045 0.036 0.039

0.310 -0.012 0.037 -0.009

1.819 -0.050 0.027 -0.046

13.128 0.207 0.016 0.212

2.904 0.076 0.026 0.080

11.025 -0.260 0.027 -0.261

3.562 -0.103 0.037 -0.110

1 Estimated totil population of 23,356,053 based on 1,923 persons examined.

2Efiimatedtota[ population of 24,653,755 based on 2,012 persons axaminad.

3Efiimatad total popuiationof 73,881,716 basadon 6,947 persons examined.

4Emimatad totil population of 42,362,317 based on 2,665 Persons axamined.

“Danotas statistical significance at the 5-percant Ieval.

45
Table 16. Estimated population byagegroup and frequency of between-meal nonsweetsnacksl: United States, 1971-74

Frequency of between-meal nonsweet snacksq

Age group

o 1 2 3 4 5 6

More

than 6

6-n years . . . . . . . . . . . . . . . . 5,965,905 6,530,888 4,567,750 3,279,786 1,597,937 664,938 345,458 403,391

12-17 years . . . . . . . . . . . . . . . 5,650,529 6,604,733 4,678,223 3,269,598 1,873,459 1,068,598 557,955 950,659

18-44 years . . . . . . . . . . . . . . . 12,833,931 13,705,255 12,546,012 10,178,866 7,639,630 5,014,794 3,891,419 8,071,808

45-64 years . . . . . . . . . . . . . . . 8,187,947 7,877,170 7,468,068 5,510,755 4,483,180 2,858,478 2,207,340 3,769,378

I sum of the between-meal fre.q~ency of the 16 “onSweet food groups from the 24-hour recall record.
Table 17. Effect of frequency of between-meal sweet and nonsmeet snacks on the number of decayed, missing, and filled (DMF) permanent teeth

control Iing for specified variables, by age for persons ages6-64 years: United States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Star) dardized Sigma (Beta) Partial r

coefficient t (B) coefficient (Beta)

6-11 yearsl /72 = o.245

Independent variables:

Number of between-meal sweet snacks . . . . . . . . .

Number of between-meal nons.weet snacks . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

12-17 years2 R2 = o.145

Indepandent variables:

Numtw of between-meal sweet snacks . . . . . . . . .

Number of between-meal nonsweet snacks . . . . . . .

Covariable~

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Othar indicator . . . . . . . . . . . . . . . . . . . . . . .

18-44 years3 R2= 0.287

Independent variables:

Number of between-meal sweet snacks . . . . . . . . .

Number of between-meal nonsweet snacks . . . . . . .

Cavariablex

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Totelfamily income . . . . . . . . . . . . . . . . . . . . . .

Aga at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Rac~

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45-64 years4 R2= 0.147

Independent variables:

Number of between-meal sweet snacks . . . . . . . . .

Number of between-meal nonsweet snacks . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age atinterview . . . . . . . . . . . . . . . . . . . . . . . .

Sax indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

0.088

0.025

-0.191

-0.418

-0.001

0.556

0.119

0.033

0.398

0.104

0.080

0.187

-0.441

-0.001

0.960

1.132

-0.619

-0.022

0.315

0.078

1.513

0.527

-0.022

0.510

1.347

-2.980

-4.012

0.285

0.204

0.667

-0.203

-0.052

0.289

1.195

-7.047

-10.241

0.036

0.032

0.124

0.162

0.010

0.032

0.095

0.140

0.497

0.072

0.071

0.270

0.390

0.020

9.WO

0.291

0.532

2.321

0.061

0.046

0.558

0:552

0.016

0.014

0.229

0.547

0.929

0.136

0.067

0.554

0.690

0.030

0.022

0.396

0.647

2.873

2.458*

0.800

0.070

0.022

0.030

0.027

0.074

0.023

-0.040

-0.070

-0.005

0.482

0.035

0.006

0.018

0.036

0.034

0.017

-0.030

-0.002

0.350

0.129

-0.047

-0.000

0.069

0.028

0.072

0.023

-0.020

0.499

0.088

-0.132

-0.068

0.054

0.086

0.038

-0.009

-0.045

0.214

0.082

-0.261

-0.110

1.542

2.582

0.152

17.233

1.250

-0.048

-0.092

-0.005

0.479

0.030

0.031

0.034

0.031

0.024

0.025

0.237

0.801

0.006

0.016

0.025

0.017

1.461

1.128

0.036

0.035

0.025

0.031

0.693

1.129

0.057

15.987

3.891

0.020

-0.040

-0.002

0.346

0.120

0.029

0.035

0.028

0.022

0.030

1.163

0.009

-0.045

-0.000

0.039

0.035

5.129*

1.689

0.067

0.028

0.014

0.016

2.712

0.955

1.389

37.108

5.876

0.095

0.032

-0.018

0.504

0.065

0.035

0.033

0.013

0.013

0.015

5.446

4.319

-0.116

-0.058

0.022

0.014

2.099’

3.029’

0.056

0.070

0.027

0.022

1.205

0.294

1.749

13.136

3.016

0.043

-0.011

–0.048

0.209

0.077

0.036

0.038

0.027

0.016

0.026

10.897

3.565

-0.260

-0.102

0.027

0.037

lEstimated total population of 23,356,053 based onl,923 parsons examined.

2E~imatad towl population of 24,653,755 based on 2,012 Persons axaminad.

3Estimated total population of 73,881,716 based on6,947parsons exatninad.

4Estimated totel population”of 42,362,317 based on 2,665 persons exarninad.

*Denotes statisticalsignificance attha 5-parcant Ieval.

47
Table 18. Effect ofenamel fluoride levels and frequency of between-meal smetsnacks onthenumbr ofdecayed, missing, and filled (DMF)

permanent teeth controlling forspecified variables, byagefor persons ages G64years United States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized

coefficient (B) Sigma (Bata) Partial r

coefficient (Beta)

6-11 yearsl R2 =0.188

Independent variables:

Number of betwaen-meal sweet snacks . . . . . .

Enamel fluoride level . . . . . . . . . . . . . . . . . . . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income, . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator, . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

12-17 yearsz R2 =0.157

Independent variables

Number of between-meal swaet snacks . . . . . . . . .

Enamel fluorlde level . . . . . . . . . . . . . . . . . . . . .

Covariable$

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview, . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . .,

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

18-44 years3 RZ =0,312

Independent variables:

Number of between-meal sweet snacks . . . . . . . . .

Enamel fluoride level . . . . . . . . . . . . . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageatintewiew . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45-64 years4 R2 = o.215

Independent variables:

Number of between-meal sweet snacks . . . . . . . .

Enamel fluoride level . . . . . . . . . . . . . . . . . . . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

0.158

-0.651

-0.353

-0.569

0.009

0,547

-0.011

-0.322

0.121

-1.157

0.347

-0.099

0.021

0.874

0.778

-0.922

1.281

0.369

-1.473

2.532

2.432

0.008

0.420

1.094

-2.444

-3.367

0.402

-0.332

2.486

3.461

0.022

0.023

1.099

-7.457

-8.106

0.077

0.220

0.292

0.362

0.020

0.065

0.211

0.287

0.096

0.306

0.403

0.515

0.029

0.095

0.302

0.734

2,513

0.065

0.294

0.520

0.502

0.024

0.016

0.268

0.586

1.183

0.232

0.585

0.741

1.034

0.052

0.063

0.555

1.166

6.184

2.043’

2.966*

1.210

1.574

0.458

8.450

0.052

1.121

1,256

3.786*

0,861

0.193

0.710

9.150

2.575

1.256

0.510

5.717”

5.01 5*

4.874

4.842

0.321

26.789

4.078

4.168

2.847

1.732

0.568

3.352

3.349

0.423

0.364

1,982

6.396

1.311

0.123

-0.160

-0.085

-0.122

0.028

0.356

-0.003

-0.051

0.044

-0.133

0.038

-0.009

0.029

0.324

0.086

-0.068

0.027

0.093

-0.131

0.193

0.184

0.008

0.494

0.083

-0.100

-0.054

0.092

-0.034

0.200

0.260

0.028

0.019

0.088

-0.330

-0.137

0.066

0.048

0.070

0.077

0.061

0.039

0.052

0.044

0.035

0.035

0.044

0.049

0.042

0.034

0.032

0.054

0.048

0.017

0.027

0.038

0.038

0.025

0.018

0.020

0.024

0.018

0.052

0.056

0.058

0.078

0.065

0.053

0.044

0.056

0.078

0.135

-0.173

-0.064

-0.085

0.027

0.365

-0.003

-0.054

0,047

-0.141

0.031

-0.007

0.028

0.329

0.092

-0.070

0.030

0.110

-0.155

0.129

0.121

0.009

0.497

0.099

-0.116

–0.065

0.102

–0.037

0.1648

0.190

0.026,

0.021

0.096

-0.340,

-0.151

lEstimatedtotaI population of 23,356,053 basad on 569 personsin Sample.

2E~imated total population of 24,653,755 based on l,036persons ensample.

3Estimatedt~tal population of 73,881,716 based 0n2,753Pers0ns in samPle.

4E@imated total population of 42,362,317 basedon 539pers0ns ensample.

*Denotes statistical significance at the 5-percent level.

48
Table 19. Relationship ofpariodontal index (Pl)wore tothenum&rof decayed, missing, and filled (DMF)~rmanent teeth controlling fors~cified

variables, byagefor persons ages 18-74 years: United States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized

coefficient t (B) Sigma (Beta) Partial r

coefficient (Beta)

18-44 yearsl R2 = 0,274

Independent variables

Periodontal index . . . . . . . . . . . . . . . . . . . . . . .

Number of between-meal sweet snacks . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45-64 years2 R2 =0.159

Independent variablas:

Periodontal index . . . . . . . . . . . . . . . . . . . . . . .

Number of between-meal sweet snacks . . . . . , . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

65-74 years3 R2 =0.082

Independent variables

Periodontal index . . . . . . . . . . . . . . . . . . . . . . .

Number of between-meal sweet snacks . . . . . . . . .

Covariablex

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageatinterview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

0.444

0.364

0.107

0.052

4.136’

7.066’

0.081

0.084

0.019

0.012

0.035

0.034

0.016

0.014

0.015

0.024

0.016

0.037

0.024

0.041

0.046

0.027

0.027

0.028

0.035

0.047

0.034

0.034

0.042

0.047

0.038

0.029

0.037

0.036

0.052

0.089

0.097

0.091

0.068

0.020

0.462

0.104

-0.134

-0.070

0.108

0.106

0.128

0.139

0.032

0.111

0.115

-0.272

-0.124

0.176

0.090

0.064

0.116

0.046

0.094

0.048

-0.120

-0.084

1.824

1.468

0.021

0.441

1.333

0.519

0.524

0.018

0.015

0.220

3.515

2.801

1.170

29.698

6.046

0.124

0.097

0.018

0.467

0.081

–0.120

-0.060

-2.808

-0.802

0.538

0.984

5.218

3.862

0.345

0.447

0.112

0.108

3.072’

4.157*

0.107

0.099

2.070

2.729

0.032

0.129

1.464

0.577

0.726

0.025

0.033

0.381

3.588

3.758

1.269

3.935

3.846

0.153

0.180

0.034

0.105

0.108

-0.274

-0.115

-6.102

-9.100

8.195

2.839

0.745

3.205

0.445

0.471

0.086

0.180

5.182*

2.623*

0.178

0.087

0.948

2.116

0.050

0.210

0.610

0.558

0.706

0.037

0.068

0.475

1.699

2.999

1.355

3.086

1.285

0.070

0.142

0.050

0.081

0,047

-0.123

-0.081

-2.706

-6.297

0.775

4.034

3.491

1.561

lEs&imated total population of 73,881,716 based on 6,611 persons examined.

2E~imatadt~tal population~f 42,362,317 ba~ad on 2,011 par~~n~e~amined.

3Estimated total population of 12,773,574 basedon l,616persons examined.

*Denotes statisticalsignificance at the 5-percant level.

49
Table 20. Relationship ofperiodontal index (Pl)score tothenumber ofdecayed, missin!], and filled (D MF)permanent teeth controlling for specified

variablesr byagefor persons ages 18-74years from whom enamel biopsies were obtained: United States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized Sigma (Beta) Partial r

coefficient (B) coefficient (Beta)

18-44 yearsl R2 = o,312

Independent variables

Periodontal index . . . . . . . . . . . . . . . . . . . . . . .

Enamel fluoride content . . . . . . . . . . . . . . . . . . .

Number of between-meal sweet snacks . . . . . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45-64 years2 R2 = o.2q5

Independent variables:

Periodontal index . . . . . . . . . . . . . . . . . . . . . . .

Enamel fluoride content . . . . . . . . . . . . . . . . . . .

Number of between-meal sweet snacks . . . . . . . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income.......,.. . . . . . . . . . . . .

Ageatintetview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

65-74 years3 R2 =0.205

Independent variables:

Periodontal index . . . . . . . . . . . . . . . . . . . . . . .

Enamel fluoride content . . . . . . . . . . . . . . . . . . .

Number of between-meal sweet snacks . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Otherindicator . . . . . . . . . . . . . . . . . . . . . . .

-0.087

–1.466

0.371

2.511

2.394

0.006

0.421

1.074

-2.422

-3.341

0.070

-0.341

0.401

2.497

3.496

0.025

0.022

1.124

-7.479

-8.191

0.791

-1.136

0.149

0.826

2.698

0.066

0.112

1.787

-8.026

-4.550

0.176

0.292

0.065

0.518

0.508

0.024

0.016

0.272

0.584

1.190

0.242

0.584

0.232

0.744

1.050

0.051

0.062

0.557

1.181

6.221

0.280

0.990

0.405

1.395

1.722

0.100

0.169

0.974

1.313

4.629

0.494

5.026’

5.709’

4.847

4.714

0.268

27.157

3.952

4.150

2.807

0.291

0.584

1.724

3.357

3.329

0.488

0.349

2.017

6.330

1.317

2.826*

1.147

0.368

0.592

1.567

0.611

0.659

1.835

6.112

0.983

-0.011

-0.131

0.093

0.191

0.181

0.007

0.496

0.082

-0.099

-0.054

0.015

-0.035

0.092

0.200

0.262

0.031

0.018

0.090

-0.331

-0.139

0.212

-0.106

0.025

0.064

0.202

0.068

0.049

0.141

-0.305

-0.030

0.022

0.026

0.017

0.038

0.038

0.025

0.017

0.021

0.024

0.018

0.053

0.056

0.052

0.058

0.080

0.064

0.053

0.045

0.056

0.080

0.075

0.091

0.06B

0.107

0.123

0.100

0.075

0.079

0.070

0.023

-0.013

-0.154

0.110

0.128

0.118

0.008

0.494

0.097

-0.115

-0.065

0.016

-0.038

0.102

0.164

0.191

0.029

0.020

0.098

-0.340

-0.151

0.215 :

-0.114

0.027

0.058

0.166

0.069

0.053

0.152

-0.313

-0.033

lEstimated total population of 73,8Bl,716 based on2,753persons examined.

2Estimated total population of 42,362,317 based on 539 persons examined.

3Estimated total population of 12,773,574 baSed On 281 persons examined.

“Denotes statistical significance at the 5-percent level.

50
Table 21. Relationship ofperiodontil index (Pl)score tothenum&r ofdecayed, missing, and filled (DMF)permanent teeth controlling forsWcified

variables, byagefor persons ages 18-74years from whom no enamel biopsies were obtained: United States, 1971-74

Regression analysis statistics

Age and variable Regression Sigma (B) t-statistic Standardized Sigma (Beta) Partial r

coefficient (B) coefficient (Beta)

18-44 yearsl R2 = ()+26()

Independent variables

Periodontal index . . . . . . . . . . . . . . . . . . . . . . .

Number of, between-meal sweet snacks . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Otherindicator . . . . . . . . . . . . . . . . . . . . . . .

45-64years2 R2=0.153

independent variables:

Periodontal index . . . . . . . . . . . . . . . . . . . . . . .

Number of between-meal sweet snacks . . . . . . . . .

Covariables

Education:

Highschool indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

65.74Years3 R2=0.071

Independent variables

Periodontal index . . . . . . . . . . . . . . . . . . . . . . .

Number of between-meal svmet snacks . . . . . . . . .

Covariablex

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Blackindicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

0.341

0.333

1.440

0.943

0.056

0.427

1.482

-3.248

-4.350

0.198

0.342

1.868

2.313

0.058

0.121

1.445

-5.614

-8.563

0.222

0.49B

1.406

2.379

0.039

0.193

0.269

-1.745

-6.942

0.123

0.079

0.555

0.623

0.022

0.019

0,324

0.659

1.403

0.121

0.133

0.589

0.709

0.031

0.039

0.408

0.877

4.725

0.089

0.170

0.467

0.660

0.036

0.0B8

0.471

0.622

4.431

2.767*

4.191*

2.597

1.515

2.484

22.137

4.573

4.930

3.100

1.638

2.566*

3.173

3.263

1.871

3.068

3.537

6.402

1.812

2.482”

2.925*

3.009

3.605

1.092

2.201

0.571

2.805

1.566

0.071

0.075

0.094

0.057

0.046

0.432

0.096

-0.145

–0.070

0.Q68

0.078

0.140

0.152

0.061

0.100

0.109

-0.266

-0.097

0.097

0.099

0.109

0.162

0.041

0.0B7

0.022

-0.086

-0.102

0.025

0.018

0.036

0.038

0.018

0.019

0.021

0.030

0.023

0.043

0.031

0.043

0.046

0.033

0.032

0.031

0.043

0.055

0.039

0.035

0.037

0.046

0.038

0.039

0.038

0.030

0.065

0.077

0.086

0.074

0.044

0.049

0.430

0.110

-0.161

–0.081

0.069

0.084

0.120

0.120

0.056

0.106

0.115

-0.262

-0.104

0.096

0.102

0.100

0.133

0.036

0.089

0.022

-0.084

-0.105

1 Emimated total popu Iation of 73,881,716 based on 3,858 parsons examined.

2E~jmated total population of42,362,317 based0n 1,472 persons examined.

3E.stimated total population of 12,773,574 based0n 1,335 persons examined.

“Denotes statistical significance at the 5-parcent level.

51
Table 22. Relationship ofpariodontal index (Pl)score toalcohol consumption controlling forspecified variabl-, byagafor persons ages

25-74 years: Unitad States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized Sigma (Beta) Partial r

coefficient (B) coefficient (Beta)

25-74 yearsl R2 = 0.205

Independent variables

Alcohol consumption . . . . . . . . . . . . . . . . . . . . . 0.068 0.048 1.413 0.031 0.022 0.031

Daily tooth-brushing frequency . . . . . . . . . . . . . -0.240 0.045 5.347* -0.097 0.018

Clental visit pattern . . . . . . . . . . . . . . . . . . . . . .

-0.101

0.153 0.026 5.647” 0.138 0.023 0.142

Use tobacco now . . . . . . . . . . . . . . . . . . . . . . . . 0.091 0.130 0.699 0.018 0.026 0.018

Usedtobacco in past . . . . . . . . . . . . . . . . . . . . . 0.420 0.110 3.809’ 0.112 0.028 0.102

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . . -0.493 0.115 4.298 -0.131 0.030 -0.101

Collage indicator . . . . . . . . . . . . . . . . . . . . . . -0.650 0.114 5.703 -0.163 0.030 -0.117

Total family income . . . . . . . . . . . . . . . . . . . . . . -0.036 0.006 5.721 -0.132 0.022 -0.128

Ageatinterviaw . . . . . . . . . . . . . . . . . . . . . . . . 0.032 0.004

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

8.203 0.216 0.027 0.225

-0.028 0.084 0.334 -0.008 0.022

Race:

-0.007

Black indicator . . . . . . . . . . . . . . . . . . . . . . . 0.468 0.135 3.464 0.076 0.023 0.082

Other indicator . . . . . . . . . . . . . . . . . . . . . . . 1.360 0.719 1.890 0.067 0.033 0.074

lEstimatedtotil population of 104,340,369 based on2,715 parsons examined.

“Danotes statistical significance at the 5-percent level.

Tabla 23. Relationship of periodontal index (Pi) ~oratotooth-brushing frequency {controlling fors~cified variables, byagefor persons ages

25-74 years: Unitad States, 197’l-74

Regression analysis statistics

Age and variable

Regression Sigma(B) t-statistic Standardized Sigma(Beta) coefficient (B) Partial r

coefficient (Beta)

25-74years1 R2. o.493

Independent variables:

Daily tooth-brushing frequency . . . . . . . . . . . . . . -0.026 0.047 0.545 -0.011 0.020 -0.014

Dantal visit pattern . . . . . . . . . . . . . . . . . . . . . . 0.035 0.020 1.758 0.033 0.019

Usetobacco now . . . . . . . . . . . . . . . . . . . . . . . .

0.042

0.115 0.100 1.146 0.025 0.022 0.030

Usedtobecco inpast . . . . . . . . . . . . . . . . . . . . . 0.208 0.096 2.167* 0.059 0.027 0.069

Oral hygiene index (OH1-S) . . . . . . . . . . . . . . . . . 0.918 0.055 16.570* 0.624 0.034 0.597

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . . -0.072 0.132 0.547 -0.020 0.038 -0.019

College indicator . . . . . . . . . . . . . . . . . . . . . . -0.063 0.148 0.426 -0.017 0.040 -0.015

Total family income . . . . . . . . . . . . . . . . . . . . . . -0.009 0.005 1.808 -0.035 0.019 -0.043

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . . 0.022 0.003 6.438 0.153 0.024 0.203

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . . 0.063 0.085 0.964 0.018 0.018

Race:

0.022

Black indicator . . . . . . . . . . . . . . . . . . . . . . . 0.047 0.126 0.376

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

0.008 0.022 0.011

1.443 0.677 2.131 0.078 0.035 0.108

lEstimated total population of 104,340,369 basedon 2,436 persons examined.

*Denotes statistical significance at the 5-percent Ieval.

52
Table 24. Relationship oforalhygiene index (OHl-S) score totooth-brushing frequency controlling fors~cified variables, by~efor~rsonsa~s

25-74 years United States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized

coefficient (B) Sigma (Beta) Partial r

coefficient (Beta)

25-74 yearsl /72 = 0.278

Independent variablex

Daily tooth-brushing frequency . . . . . . . . . . . . . . -0.208 0.040 5.224* -0.130 0.025 -0.142

Dental visit pattern . . . . . . . . . . . . . . . . . . . . . . 0.140 0.020 6.857* 0.198 0.027 0.210

Usetobacco now . . . . . . . . . . . . . . . . . . . . . . . . 0.027 0.070 0.390 0.009 0.023 0.009

Used tobacco in past . . . . . . . . . . . . . . . . . . . . . 0.237 0.056 4.259* 0.099 0.024 0.097

Covariablex

Education:

High school indicator . . . . . . . . . . . . . . . . . . . -0.532 0.082 6.485 -0.222 0.033 -0.176

College indicator . . . . . . . . . . . . . . . . . . . . . . -0.744 0.093 8.009 -0.296 0.036 -0.216

Total family income . . . . . . . . . . . . . . . . . . . . . . -0.024 0.003 7.312 -0.139 0.018 -0.142

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . . 0.005 0.002

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

2.612 0.051 0.020 0.058

-0.160 0.058 2.754 -0.067

Race:

0.024 -0.071

Black indicator . . . . . . . . . . . . . . . . . . . . . . . 0.451 0.115 3.931 0.116 0.032 0.129

Other indicator . . . . . . . . . . . . . . . . . . . . . . . -0.070 0.220 0.319 -0.006 0.016 -0.006

lE~timatad tOtal population Of 104,340,369 basedon 2,437 Persons examined.

*Danotas statistical significance attha5-parcant level.

53
Table 25. Relationship ofanabsence ofteeth topercent of the NHANESWndard attair)ed forvitamin CcontroIling forspecified variables, by age

forpersons ages 18-74 years: United Statm,1971-74

Regression analysis statistics

Age and variable Regression Sigma (B) t-statistic Standardized Sigma (Beta) Partial r

coefficientt (B) coefficient (Beta)

18-44 yearsl /32 = 0.021

Independent variable:

Absence of teeth . . . . . . . . . . . . . . . . . . . . . . . .

CoVariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total femily income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Blackindicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45-64 years2 R2 = o,048

Independent variable:

Absence of teeth . . . . . . . . . . . . . . . . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Age at interview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Rata:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

65-74 years3 R2 =0.069

Independent variable:

Absence ofteeth . . . . . . . . . . . . . . . . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageatintewiew . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

-20.454

14.946

28.453

2.124

-1.969

-11.210

2.089

14.256

-22.097

20.0B5

37.614

2.394

3.452

12.458

10.119

22.471

-18.331

27.210

67.317

2.527

1.491

IB.008

13.695

33.388

8.378

6.963

7.012

0.417

0.351

5.039

9.144

26.363

8.270

8.929

14.470

0.662

0.671

7.848

10.949

33.206

7.204

6.986

9.750

0.812

0.976

7.143

15.155

72.046

2.43B*

2.146

4.058

5.089

5.611

2.225

0.228

0.540

2.672’

2.249

2.599

3.617

5.143

1.588

0.924

0.677

2.545*

3.895

6.904

3.113

1.528

2.521

0.904

0.463

-0.027

0.044

0.081

0.082

-0.091

-0.033

0.004

0.010

-0.067

0.069

0.109

0.199

0.133

0.043

0.020

0.012

-0.065

0.092

0.182

0.104

0.030

0.063

0.027

0.017

0.011

0.021

0.019

0.017

0.016

0.014

0.017

0.018

0.025

0.031

0.042

0.033

0.026

0.027

0.021

0.014

0.025

0.025

0.030

0.033

0.019

0.025

0.030

0.035

-0.026

0.028

0.050

0.077,

–0.088

-0.033

0.004

0.010

-0.064

0.058

0.083

0.104

0.129

0.044

0.020

0.012

-0.064

0.087

0.154

0.095

0.031

0.065

0.028

0.018

lEstimated total population of 73,881,716 baaed on6,947 persons examined.

2Estjmated total population of42,362,31 7basadon 2,665 persons examined.

3Estimated total population of 12,773,574 basad cm 3,080 persons examineci.

“Denotes statistical significance at the 5-parcent level.

54
Table 26. Relationship ofanabwme ofteeth topercent of the NHANESWandard attiined forprotein controlling forsWcified variables, bya~

forpersons eges65-74 years: United States, 1971-74

Age and variable

Regression Sigma (B) t-statistic Standardized Sigma (Beta)

coefficient (B)

Partial r

coefficient (Beta)

65-74 yearsl R2 = 0.032

Independent variable:

Absence of teeth . . . . . . . . . . . . . . . . . . . . . . . . -5.454 1.846 2.955* -0.066 0.023 -0.065

Covariables

Education:

Highschool indicator . . . . . . . . . . . . . . . . . . . 4.397 2.042 2.154 0.051 0.024 0.048

Collage indicator . . . . . . . . . . . . . m. . . . . . . 4.699 2.594 1.812 0.044 0.024 0.037

Total family income . . . . . . . . . . . . . . . . . . . . . . 0.316 0.135 2.340 0.045 0.020 0.040

Age at interview . . . . . . . . . . . . . . . . . . . . . . . . -1.074 0.348 3.080 -0.074 0.025 -0.075

Sexindicator . . . . . . . . . . . . . . . . . . . .. . . . . . . -7.402 1.763 4.198 -0.090

Racw

0.021 -0.080

Black indicator . . . . . . . . . . . . . . . . . . . . . . . -5.087 3.294 1.544 -0.035 0.023 -0.035

Other indicator . . . . . . . . . . . . . . . . . . . . . . . 0.145 16.954 0.008 0.000 0.026 0.000

lEstimatedtowl population of 12,773 r574 based on3,080 persons examined.

*Denotes steti.stical significance attha 5-percent Iavel.

Table 27. Relationship of anabwnce ofteeth topercent of the NHANESstandard atiained foriron controlling fors~cified variable, byage for

persons ages65-74 years United States, 1971-74

Age and variable

Regression analysis statistics

Regression Sigma (B) t-statistic Standardized

coefficient (B)

Sigma (Beta) Partial r

coefficient (Beta)

65-74 years’ R2=0.092

Independent variable:

Absanceofteeth . . . . . . . . . . . . . . . . . . . . . . . . -6.640 2.295 2.883’ -0.064 0.022 -0.064

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . . 2.645 2.597 1.018 0.024 0.024 0.023

College indicator . . . . . . . . . . . . . . . . . . . . . . 5.050 3.595 1.405 0.037 0.026 0.032

Totel family income . . . . . . . . . . . . . . . . . . . . . . 0.515 0.209 2.461 0.058 0.023 0.053

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . . -1.049 0.416 2.518 -0.057 0.023 -0.059

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . . -27.010 2.246 12.025 -0.258 0.020 -0.258

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . . -10.412 4.810 2.165 -0.056 0.027 -0.058

Other indicator . . . . . . . . . . . . . . . . . . . . . . . -2.773 21.782 0.127 -0.004 0.027 -0.004

1Estimated rotaI population of 12,773,574 basad on 3,080 persons examined.

*Denotes statistical significance at the 5-percent level.

55
Table 28. Relationship ofanabsence ofteeth andweekly frequency of fruit ingestion topercent of the NHANESstandard attained forvitamin C

controlling forspecified variables, byagefor ~rsonsages 18-74 years: United States, 1971-74

Regression analysis statistics

Age and variable

Regression Sigma (B) t-statistic Standardized Sigma (Beta) coefficient (B) Partial r

coefficient (Beta)

18-44 yearsl R2 = (3097

Independent variables:

Absence of teeth . . . . . . . . . . . . . . . . . . . . . . . .

Weekly frequency of fruit ingestion . . . . . . . . . . .

Covariables:

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageat interview . . . . . . . . . . . . . . . . . . . . . . . .

Sexindicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

45-64 years2 R2=o.160

Independent variables

Abswrce ofteeth . . . . . . . . . . . . . . . . . . . . . . . .

Weekly frequency of fruit ingestion . . . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageatinterview . . . . . . . . . . . . . . . . . . . . . . . .

Sexindicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Slack indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

65-74 years3 R2=o.181

Independent variables:

Absence ofteeth . . . . . . . . . . . . . . . . . . . . . . . .

Weekly frequency of fruit ingestion . . . . . . . . . . .

Covariables

Education:

High school indicator . . . . . . . . . . . . . . . . . . .

College indicator . . . . . . . . . . . . . . . . . . . . . .

Total family income . . . . . . . . . . . . . . . . . . . . . .

Ageatinterview . . . . . . . . . . . . . . . . . . . . . . . .

Sex indicator . . . . . . . . . . . . . . . . . . . . . . . . . .

Race:

Black indicator . . . . . . . . . . . . . . . . . . . . . . .

Other indicator . . . . . . . . . . . . . . . . . . . . . . .

-13.771

7.208

3.574

7.332

1.396

-2.062

–1 9.067

9.576

0.930

-14.768

7.456

4.126

20.317

1.194

2.677

-1.775

24.311

46.140

-10.070

7.381

20.221

48.959

1.545

1.598

7.333

33.710

34.354

8.241

0.601

7.207

5.903

0.386

0.374

4.994

9.605

18.972

7.491

0.568

8.055

14.096

0.619

0.673

7.447

10.922

32.438

6.363

0.615

6.256

8.714

0.815

0.814

6.283

14.086

59.766

1.671

11 .985*

0.496

1.242

3.620

5.513

3.818

0.997

0.049

1.971++

13.128*

0.512

1.441

1.927

3.980

0.238

2.226

1.422

1.582

12.000”

3.232

5.619

1.895

1.962

1.167

2.391

0.575

-0.018

0.282

0.010

0.021

0.054

-0.095

-0.056

0,017

0.001

-0.044

0.354

0.014

0.059

0.059

0.103

-0.006

0.047

0.024

-0.035

0.350

0.068

0.132

0.083

0.032

0.026

0.066

0.018

0.011

0.027

0.021

0.016

0.016

0.016

0.014

0.018

0.012

0.023

0.023

0.028

0.041

0.031

0.026

0.026

0.021

0.017

0.022

0.026

0.022

0.027

0.033

0.016

0.022

0.027

0.029

-0.018

0.277

0.007

0.013

0.052

-0.095

-0.059

0.018

0.001

-0.046

0.344

0.012

0.048

0.055

0.106

-0.007

0.049

0.026

-0.037

0.346

0.068

0.119

0.062

0.035

0.028

0.071

0.019

1 Estimated totel population of 73,881,716 based on 6,850 Persons examined.

2E~timatecj t~tal population of 42,362,317 based on 2,620 parsons examined.

3E~timated total population of 12,773,574 based on2,974 persons examined.

“Danotes statistical significance at the 5-percent level.

56
Appendixes

Contents

1.

Il.

Ill.

Statistical notes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...

Survey design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Nonresponse. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Missing data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Imputation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Design considerations forexamined persons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Analytical strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Continuous variables: Means... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Continuous variables: Multiple regression models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Assumptions ofthe multiple regression model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Specification error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Measurement error. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Heteroscedasticity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Nonnormality ofrandomvariation term . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Empirical results for regressionmodels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Definitions ofterms andvariables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Statistical terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Demographicvariables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Dietary variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Dental variables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Behavioral variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Othervariables used. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Definitions offoodgroups in24-hour recall data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The dental examination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The examination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Theperiodontal index (Pa) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Thesimplified oral hygiene index(OHl-S) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Edentulous arches–denture status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Treatment needs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The examiners . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Appendix Figure

1. Dental examination form..... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

59

59

61

62

62

63

64

65

66

66

66

68

68

68

68

73

73

73

73

74

74

75

75

78

78

83

83

83

84

84

79
List of Appendix Tables

1. NHANES I population estimates for examination locations 1-65, by sex, race, and age at examination . . . . . , ., ., . .

Il. Sampling rates byage-sex groups for general sample of the NHANES 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1[1. Subsampling rates by age-sex groups for detailed sample of the NHANES 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

IV. Percent distribution ofadjustment factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

v. Total number of examinees and those without dental examination records, by age and sex: National Health and Nutrition Examination Survey, United States, 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

V1. Number of primary sampling units (PSU’S) and number of examined persons for the general and detailed survey, by

stratum number forthe NHANES I design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

V1l. Comparative analyses of standard errors and design effects for multiple and paired sampling error computational units

(SECU’S) within certainty strata for decayed, missing, and filled (DMF) teeth and calories, by age for NHANES I

data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vll 1. Number of examined persons, estimated means, standard deviations, standard errors of the mean, and design effects for

decayed, missing, and filled (DMF) teeth, calories, and age, under analysis options 1-3 for NHANES 1data . . . . . . . .

IX. Number of examined persons, estimated means, standard deviations, standard errors of the mean, and design effects for

decayed, missing, and filled (DMF) teeth and calories within age grcmsps,under analysis options 1-3 for NHANES I

data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

x. Summary of simple regression models of decayed, missing, and filled (DMF) teeth and calories on age under analysis

options l-3, byraceand sex for NHANES [ data . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Xl. Number of examined persons by race, sex, and stratum number in the NHANES I design . . . . . . . . . . . . . . . . . . . . .

Xi 1. Number of examined persons by race, sex, and stratum number in the NHANES I design for the detailed sample . . . . .

X111. Summary of multiple regression models for decayed, missing, and filled (DMF) teeth on age, race, sex, and sweets for

6,349 examined persons ages 11-30 years, under analysis options 1-3 , . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

XIV. Major functions, problems associated with deficiency, and major food sources of calories and selected nutrients . . . . . .

XV. Standards for evaluation of daily dietary intakes used in the National Health and Nutrition Examination Survey, by age,

sex, andphysiological state: United States, 1971 -74 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

XVI. Present distribution of differences in dental findings between senior dentists and other dentists on 360 replicate examinations: National Health and Nutrition Examination Survey, 1971-74. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

60

61

61

62

62

63

65I

65

67

70

71’

7:!

72’

76

77

85

58
Appendix I

Statistical Notes

Survey design

The sample design for the first National Health

and Nutrition Examination Survey (NHANES I) is

basically a three-stage, stratified probability sample of

loose clusters of persons in land-based segments. The

sample was designed to be representative of the civilian

noninstitutionalized population within designated age

ranges in the coterminous United States, excluding

persons resjding on lands set aside for the use of

American Indians. Successive elements dealt with in

the process of sampling were the primary sampling

unit (PSU), census enumeration district (ED), segment (a cluster of households), household, eligible

person, and finally sample person.

For the period April, 1971 to June, 1974, the design provided for selection of a representative sample

of the target population 1-74 years of age to be given

the health interview and a medical examination. A

subsample of adults 25-74 years of age who would

also receive a more detailed examination focused on

other aspects of health and health care needs. To increase the size for this subsampling and consequently

the usefulness of the da+a obtained, the design further

provided for the selection of an additional nationally

representative sample of adults 25-74 years between

July 1974 and September 1975, who were to be given

the more detailed examination. This extension of

NHANES I isreferred to as the “augmentation survey.”

The estimated civilian noninstitutionalized U.S.

population aged 1-74 years is shown in table I by sex,

race, and age at examination. The estimates closely

approximate the U.S. population estimated by the

U.S. Bureau of the Census as of the midpoint of the

survey sample design. The figures in table I may differ

slightly from the census estimates because the latter

are based on the ages of sample persons at the time

they were examined, whereas the poststratification

was based on the ages at interview. Because certain

analyses must be done on the basis of age at examination, the population estimates have also been based

on age at examination for the sake of consistency.

The starting points in the first stage of this design

were the 1960 decennial census lists of addresses and

the neady 1,900 primary sampling units (PSU’S) into

which the entire United States was divided. Each PSLT

is either a standard metropolitan statistical area

(SMSA), a county, or two or three contiguous counties. The PSU’S were grouped into 357 strata, as they

were for use in the National Health Interview Survey,

and subsequently collapsed into 40 superstrata for use

in NHANES I. This same procedure had been used in

Cycles II and III of the National Health Examination

Surveys of 1963-65 and 1966-70, respectively.

During the April 1971- June 1974 period, 15 of

the 40 superstrata that contained a single large metropolitan area of more than 2 million population were

chosen in the sample with certainty. The remaining

25 noncertainty strata were classified into 4 broad

geographic regions of approximately equal population

(when the large metropolitan areas selected with certainty were included) and cross-classified into 4 broad

population density groups in each region. Then a

modified Goodman-Kish controlled-selection technique was used to select 2 PSU’S from each of the 25

noncertainty superstrata, with the probability of selection of a PSU proportionate to its 1960 population,

and so that proportionate representation of specified

State groups and rate of population change classes

were maintained in the sample. In this manner a total

fh-st-stage sample of 65 PSU’S was selected. These 65

sample PSU’S are the areas within which a cluster

sample of persons was selected for examination at the

particular examination location designated within

each area. The mobile examining units were moved

from one location to the next during this 39-month

period (197 1-74) to permit administering those singletime examinations to the cross-sectional sample of

the target population.

Although the 1970 census data were used as the

frame for selecting the sample within the PSU when

they became available, the calendar of operations required that the 1960 census data be used for the first

59
Table 1. NHAN ES I population estimates for examination locations 1-65, by sax, race, and age at examination

Estimated population

Age at examina tion Male Female

Tot%l

All races White Black All races White Black

Total . . . . . . . . . . . . . . . . . . . . . . . . . 193,976,381 94,239,866 82,740,899 10,413,986 99,736,515 86,867,546 11,999,935

I year . . . . . . . . . . . . . . . . . . . . . . . . 3,313,458 1,693,074 1,401,508 280,212 1,620,384 1,327,657 257,289

2-3years . . . . . . . . . . . . . . . . . . . . . . 6,963,162 3,553,765 2,997,107 479,362 3,409,397 2,872,581 505,442

45years . . . . . . . . . . . . . . . . . . . . . . 6,672,346 3,378,503 2,866,374. 485,872 3,293,843 2,755,016 511,134

6-7years . . . . . . . . . . . . . . . . . . . . . . 7,193,663 3,652,322 3,060,888 573,867 3,541,341 2,951,927 576,578

8-9years . . . . . . . . . . . . . . . . . . . . . . 7.696,597 3,880,396 3,279,649 586,419 3,816,201 3,257,936 539,855

10-n years . . . . . . . . . . . . . . . . . . . . 8,465,793 4,381,730 3,732,593 563,823 4,084,063 3,424,070 617,793

12-14years . . . . . . . . . . . . . . . . . . . . 12,335,321 6,312,591 5,397,061 879,377 6,022,802 5,122,189 I 836,252

15-17years . . . . . . . . . . . . . . . . . . . . 12,318,434 6,312,519 5,311,596 812,321 6,111,265 5,233,091 853,294

18-19years . . . . . . . . . . . . . . . . . . . . 7,352,200 3,673,321 3,206,467 404,045 3,678,879 3,158,930 504,417

20-24years . . . . . . . . . . . . .. s..... 17,325,038 8,109,775 7$0948036 866,201 9,215,263 7,972,486 1,073,358

25-34years . . . . . . . . . . . . . . . . . . . . 26,936,001 13,002,514 11,594,115 1,231,793 13,933,487 12,160,578 1,646,337

35-44years . . . . . . . . . . . . . . . . . . . . 22,268,477 10,675,731 9,515,530 1,004,953 11,592,746 10,111,458 1,318,050

45-54 years . . . . . . . . . . . . . . . . . . . . 23,313,316 11,150,110 10,039,124 1,056,837 12,163,206 10,879,167 1,237,459

55-64 years . . . . . . . . . . . . . . . . . . . . 19,049,001 9,072,586 8,274,948 702,647 9,976,415 9,037,157 871,098

65-74 years . . . . . . . . . . . . . . . . . . . . 12,773,574 5,496,351 4,969,903 486,257 7,277,223 6,603,303 651,579

44 locations in the sample. The 1970 census data were

thenused forthefina121 stands of the sample.

Beginning with the use of the 1970 census data,

the segment size was changed from an expected 6

households selected from compact clusters of 18

households to an expected compact cluster of 8

households. This change was implemented because of

operational advantages and results of research by the

U.S. Bureau of the Census indicating that precision of

estimates would not be appreciably affected by such

a modification. In urban enumeration districts the

segments were clusters of addresses from the 1960

Census Listing Books (later the corresponding books

for 1970). For ED’s not having usable addresses, area

sampling was employed and consequently some variation in the segment size occurred. To make the sample

representative of the then current population of the

United States, the address or list segments were supplemented by a sample of housing units that had been

constructed since 1960.

Within each PSU a systematic sample of segments

was selected. The enumeration districts selected for

the sample were coded into one of two economic

classes. The first class, identified as the “poverty

stratum ,“ was composed of “current poverty areas”

that had been identified by the Bureau of the Census

in 1970 (pre-1970 Census), plus other ED’s in the

PSU with a mean income of less than $3,000 in 1959

(based on 1960 Census). The second economic class,

the “nonpoverty stratum,” included all ED’s not

designated as belonging to the “poverty stratum.” All

sample segments classified as being in the poverty

stratum were retained in the sample. For those sample

segments in nonpoverty stratum ED’s, the selected

segments were divided into eight random subgroups

and one of the subgroups was chosen to remain in the

60

NHANES I sample. Continuing research indicated that

efficiency of estimates could be increased by changing the ratio of poverty to nonpoverty segments from

8 : 1 to 2 : 1. Therefore, in the later stands the selected segments in the nonpoverty-stratum ED’s were

divided into two random subgroups, and one of the

subgroups was chosen to remain in the sample. This

procedure permits separate analyses, with adequate

reliabilityy, of those classified as being below the poverty level and those classified as being above the

poverty level.

After identifying the sample segments, a list of all.

current addresses within the segment boundaries was

made, and the households were interviewed to deter-.

mine the age and sex of each household member, as

well as other demographic and socioeconomic information required for the survey. If no one was at home

after repeated calls or if the household members refused to be interviewed, the interviewer tried to determine the household composition from questioning

neighbors.

To select the persons in the sample segments td

be examined in NHANES I, all household members

ages 1-74 years in each segment were listed on a

sample selection worksheet, with each household in

the segment listed serially. The number of household

members in each of the six age-sex groups shown in

table 11[were listed on the worksheet under the apprclpriate age-sex group column. The sample selection

worksheets were then put in segment number order,

and a systematic random sample of persons in each

age-sex group was selected to be examined using the

sampling rates displayed in table II. This sampling

strategy in the 65 stands of the general sample of

NHANES I resulted in the selection of 28,043 sample

persons 1-74 years of age, a sample that can be
regarded as representative of the target population

displayed in table I.

A subsample of those adults 25-74 years of age in

the total or “nutrition” sample was then selected to

also receive the detailed health examination at the

fiist 65 stands of NHANES L This detailed sample

was chosen systematically after a random start, using

the sampling rates shown in table III. Consequently,

adults 45-74 years of age in the f~st 65 PSU’S were

subsampled for the detailed examination at a somewhat higher rate than those 25-44 years of age.

Table 11. Sampling rates by age-sex groups for ganeral sample of the

NHANES I

Age and sex

Sampling

rate

l-5years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1/2

6-19years . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1/4

20-44 years (men) . . . . . . . . . . . . . . . . . . . . . . 1/4

20-44 years (women) . . . . . . . . . . . . . . . . . . . . 1/2

45-64 years . . . . . . . . . . . . . . . . . . . . . . . . . . . 1/4

65-74 years . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Tabla II 1. Subsampling rates by age-sex groups for detailed sample of

the NHANES I

Age and sex

Subsampling

rata

25-44 years (men) . . . . . . . . . . . . . . . . . . . . 215

2544years (women) . . . . . . . . . . . . . . . . . . 1/5

45-64 years . . . . . . . . . . . . . . . . . . . . . . . . . 3/5

65-74 yaars . . . . . . . . . . . . . . . . . . . . . . . . . 114

Nonresponse

In any health examination survey, after the sample

is identified and the sample persons are requested to

participate in the examination, the survey meets one

of its more severe problems. Usually a sizable number

of sample persons who are willing to complete the

household questionnaire and possibly some of the

medical history will not participate in the examination. Individual participation is determined by many

factors, some of them are uncontrollable, and many

are unrelated to health. Therefore, participation may

be treated as a random event with a particular probability of occurrence. If this probability were known

and were greater than zero for all persons, then the

examined persons would constitute a probability

sample from which unbiased estimates of the target

population could be derived. In this situation, the

effect of nonparticipation would only reduce the

sample size, thereby increasing the sampling variabilityy

of examination findings; this effect can be, and was,

planned for in the sample specifications.

In practice, however, a potential for bias due to

nonresponse exists because exact probabilities of nonparticipation are never known. A further potential for

bias exists if either a sizable proportion of sample persons have a zero probability of participation (that is,

they would never agree to participate in an examination survey employing the same procedures and inducements) or these persons differ from other sample

persons with respect to characteristics under examination. It is for these reasons that intensive efforts were

made in NHANES I to develop and implement procedures and inducements that would reduce the number

of nonrespondents and thereby reduce the potential

of bias due to nonresponse. These procedures are discussed elsewhere.2

Also during the early stages of NHANES I, when

it became apparent that the response rate for the examinations was lower than in the preceding health

examination surveys, a study of the effect of remuneration on response in NHANES I was undertaken.

The findings53 were considered sufficient to include

remuneration as a routine procedure in NHANES I

starting with the 21st and 22d examination locations.

Despite response rates at the household interview

stage of over 98 percent and these intensive efforts of

persuasion, only 20,749 (74 percent) of the sample

persons from the first 65 stands were examined. When

adjustments are made for differential sampling for

high-risk groups, the response rate becomes 75.2 percent. Consequently, the potential for a sizable bias

does exist in the estimates in this publication. However, from what is known about the nonrespondents

and the nature of nonresponse, the likelihood of sizable bias appears to be small. For instance, only a small

proportion of sample persons from the first 65 examination locations gave reasons for nonparticipation

that would lead to the belief that they would never

agree to participate in examination surveys and that

they may differ from examined persons with respect

to the characteristics under examination. Only 15 percent of nonrespondents gave the following reasons for

nonparticipating: personal illness, physical inability,

pregnancy, antidoctor feelings, or a fear of finding

something wrong. Typical among the reasons given by

the other nonrespondents were the following: inability to take time off from work, school, or household

duties; suspicion or skepticism about the program;

uninterested in participating; and considered their private medical care sufficient, or they had just visited

a doctor.

An analysis of the medical history data obtained

for most nonexaminees as well as examinees also supports the belief that the likelihood of sizable bias due

to nonresponse is small. No large differences were

NOTE: A list of references follows tbe text.

I

61
found between the examined group and the nonexamined group for the statistics compared. For example, the percent of persons examined who reported

ever being told by a doctor that they had arthritis was

20 percent; the percent for high blood pressure was

18 percent; and for diabetes, 4 percent. The corresponding percents for nonexamined persons were

arthritis, 17 percent; high blood pressure, 21 percent;

and diabetes, 4 percent.

A procedure (similar to that used in previous

National Health Examination Surveys) was used in

which the reciprocal of the probability of selection of

the sample persons is multiplied by a factor that

brings estimates based on examined persons up to a

level that would have been attained if all sample persons had been examined. This factor is the ratio of

the sum of sample weights for all sample persons with

a relatively homogeneous class defined by age, sex,

and five income groups (under $3,000; $3,000-

$6,999; $7,000-$7,999; $10,000-$14,999 and $15,000

or over) within each stand, to the sum of sample

weights for all responding sample persons within the

same homogeneous class for the same stand.

In addition, there is a poststratified ratio adjustment that makes the final sample estimates of the

population agree approximately with independent

controls prepared by the U.S. Bureau of the Census

for the noninstitutionalized population of the United

States as of November 1, 1972 (approximately midsurvey point), by race, sex, and age as shown in

table I. -

To the degree that homogeneous groups can be

defined that are also homogeneous with respect to

the characteristics under study, this poststratification

procedure can be effective in reducing the variance

and bias. Overall, the extent of adjustment for nonresponse and poststratification among the detailed examinees was 1.45 during the 1971-74 period.

For the 65-stand sample of NHANES I, the percent distribution of the adjustment factors used for

the 325

of the 5

table IV.

‘t)

cells (determined by the crossclassification

income groups by the 65 stands) is shown in

Table IV. Percent distribution of adjustment factors

Size of adjustmen t factor

Number Percent

of cells distribution

Total (1.00-3.03) . . . . . . . . . . . 325 100.0

1.00-1.24 . . . . . . . . . . . . . . . . 106 32.6

1.25-1.49 . . . . . . . . . . . . . . . . 125 38.4

1.50-1.74 . . . . . . . . . . . . . . . . 59 18.2

1.75-1.99 . . . . . . . . . . . . . . . . 24 7.4

2.00-2.4.9 . . . . . . . . . . . . . . . . 9 2.8

2.50-2.99 . . . . . . . . . . . . . . . . 1 0.3

3.00-3.03 . . . . . . . . . . . . . . . . 1 0.3

Missingdata

Ex,aminati?n surveys are subject to the loss of

information not only through failure to examine ajl

sample persons but also from the failure to obtain

and record all items of information for examined persons. Dental findings were obtained and records were

available for 20,218 of the 20,749 examinees in the

NHANES I survey. Those 531 persons whose dental

records were lost or not obtained through examinations were assigned imputed values as described in tide

next section. These imputed values are included in the

detailed tables and findings of this report. The age-sex

distribution of the examinees is shown in table V.

Imputation

Imputation of dental findings for an examinee

was done by randomly selecting a match from among

the group of examinees of the same age, race, sex,

and income group with information recorded. The

Table V. Total number of examinees and those without dental examination records, by age and sax: National Health and Nutrition Examination

Survey, United States, 1971-74

..

Age Both Male Female Both Male Femala

sexes sexes

Number without dental

Total number examined examination records

Allages, l-74years . . . . . . . . . . . . . . . . . . . . . . . . . ...”..... 20,749 8,819 11,930 531 207 324 -

l-5years . . .. c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,953 1,502 1,451 78 36 42

6-n years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,019 1,001 1,018 63 30 33

12-17 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,132 1,063 1,064 48 18 30

18-24 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,297 770 1,527 60 14 46

25-34 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,694 799 1,895 80 26 54

35-44 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,327 666 1,661 55 14 41

45-54 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,599 767 832 43 22 21

55-64 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,252 591 671 33 10 23

65-74 years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3,466 1,655 1,811 71 37 34

62
findings of this’’matched” examinee were then used

as the imputation for the examinee with missing data.

When data for the income variable was not available,

the match was limited to age, race, and sex.

Design considerations for examined persons

Although the sample design for this survey is

described in extensive detail in the previous sections

and in another report,2 the aspects of the design pertaining to data analysis considerations are discussed

further in this section. All 20,749 examined persons

received a specifically designed nutrition examination. In addition, approximately a 20 percent subsample (3,854 persons) of those aged 25-74 years

received a more detailed health examination based on

the prior National Health Examination Survey. The

data collection forms for the entire sample, together

with the additional forms for the detailed sample, are

contained elsewhere. z

Although the sample design for this survey was

fairly complex, the essential feature is the selection of

primary sampling units (PSU’S), such as counties or

groups of counties from each of several strata. In particular, the NHANES I design involved the selection

of 15 large metropolitan areas referred to as “certainty

strata,” each with a large number of enumeration districts selected as PSU’S, and the selection of exactly

2 PSU’S from each of the remaining 25 strata. However, for purposes of computing sampling variances,

these 15 certainty strata were combined to form only

10 strata. The data tapes from NCHS reflect this revised indexing of the certainty strata. The number of

PSU’S and the corresponding number of examined

persons in each of these strata are summarized in

NOTE:Alist of references follows the text.

table VI. Thus, for analytic purposes, this design can

be described as having the following characteristics:

1. 10 strata with multiple selection of PSU’S.

2. 25 strata with paired selection of PSU’S.

Throughout the remainder of this appendix these

paired or multiple clusters will be referred to as sampling error computational units (SECU’S), to indicate

their role in variance calculations.

Another important aspect of the NHANES I

design is the multiplication by the reciprocal of the

probabilities for selection to adjust for the oversampling of the following subgroups thought to be at

high risk of malnutrition (table II):

1. Persons with low income.

2. Preschool children.

3. Women of childbearing age.

4. Elderly persons.

Adjusted sampling weights that reflect these selection

probabilities and the poststratification adjustments

mentioned earlier were computed and are available on

the data tapes for analytic purposes.

An additional design complication arises because

at the frost 65 sites of the nutrition survey a subset of

the sample persons aged 25-74 years received a more

detailed health examination. No particular oversampling of subgroups of the population was done in

this subsample; for example, women of childbearing

age were not oversampled as they were for the major

nutrition component of NHANES I. The total number of examined persons involved in this detailed examination is 3,854 persons aged 25-74 years, for

which separate adjusted sampling weights have been

computed and are available on the data tapes.

Consequently, when computing estimates of analytic statistics and their estimated variance-covariance

Table V1. Number of primary sampling units (PSU’S) and number of examined persons for the general and detailed survey, by stratum number

for the NHANES I design

Number Number of examined

Stmtum number of PSWS persons

general and

detailed General Detailed

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,263 16,895 3,854

l-lo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,213 3,661 853

1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..+..... . . . . . . . . .

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ........ .

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....... ,.

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..+..... . . . . . . . . . . . . . . . . .

7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..

9

lo. ::::::::::::::::::::::::: : :::::::::::::::::::::::::: ::::::::::::

169

106

125

156

197

83

108

61

89

119

508

287

395

608

598

202

324

146

247

345

112

80

87

129

143

48

71

42

57

84

11-35 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 13,234 3,001

63
structure, the appropriate sampling weights need to

be utilized in the weighted analyses. Thus, hypotheses

involving variables from the initial detailed sample of

persons aged 25-74 years in stands 1-65 were investigated using the adjusted sampling weights associated

with the detailed persons. Otherwise, hypotheses involving variables from the entire initial sample (stands

1-65) utilized the adjusted sampling weights for the

entire initial sample (tape location 176-181).

Analytical strategies

Because of the complexities in the sample design,

each analysis could be performed one of three different ways depending on whether the sampling

weights were included and/or whether the design

structure was incorporated in the calculations. For

sirnplicit y, these three options are labeled in subsequent discussion and tabular results as follows:

Inclusion of sampling

Option

Weigh ts Design

1 ................... No No

2 . . . . . . . . . . . . . . . . . . . Yes No

3 . . . . . . . . . . . . . . . . . . . Yes Yes

As might be expected, the implementation of

each option in successive order from 1 to 3 involved

considerably more set-up time and computing costs.

Consequently, most hypotheses initially were investigated under option 1. Relationships found to be statistically significant at this stage were then subjected

to more definitive analyses under option 3 utilizing

the sample weights and the survey design effects. Consequently, the estimated covariance structure for the

sample estimators based on the complexities of the

survey design was utilized in all final models and

inferential conclusions.

In survey research, the design effect is commonly defined to be the ratio of the actual variance

for a statistic from a complex sample to the corresponding variance from a simple random sample.

These effects are used by survey designers and analysts for a variety of purposes. Quite frequently, the

design effect has been used to summarize conveniently

the effects of a complex sample design on the precision of estimates from the survey data and to formulate new survey designs. Increasingly, design effects

are being used to adjust estimates and statistics computed under simple random sampling assumptions for

the effects of the complexities in the sample design

on measures of precision. Given the importance of

these effects to persons who design and analyze surveys, simple but useful models have been sought for

design effects. Such models are useful not only for

methods to adjust estimates computed under independence assumptions for complexities in the sample

design. An extensive literature review of these design

effect considerations and analytical strategies for survey data from complex sample designs is presented by

Lepko wski.s4 Throughout the subsequent discussion,

the estimated design effects are computed under

option, 3 to illustrate the importance of utilizing these

effects in definitive hypothesis tests or model-fitting

calculations.

All analyses under option 1 were performed quit:

simply and inexpensively using standard statistic+

software. In this option sampling weights and design

effects were totally ignored. Thus, the data were regardecl as coming from a simple random sample with

equal representation and probability of selection. On

the other hand, analyses under option 2 incorporated

the adjusted sampling weights in estimating the analytic statistics, but simple random sampling computations were still utilized for the variance estimates.

These calculations were performed within the

OSIRIS IV software packages 5 Finally, analyses

under option 3 utilized both the adjusted sampling

weights and the sampling design in calculating the

estimated variance-covariance structure of analytic

statistics. In particular, the computer progra,~

&PSALMS was used for estimating ratio means and

the program &REPERR was utilized to fit regressi~~n

models. Both of these routines are available within

the OISIRIS IV library and are described in more cletail by Vinter.s T Briefly, for relatively simple statistics, such as ratio means, differences of such ratiqs,

and totals, the &PSALMS routine approximates the

complex sample variance of these estimators using a

linearized Taylor Series expansion. For more complex

statistics, such as regression coefficients, several replicated variance estimation procedures are available. ~n

particular, the balanced repeated replication (BRR)

opticln within the &REPERR routine was utilized to

fit multiple regression models.

The estimation procedure to implement option 3

can be extremely time consuming and expensive, particularly in fitting regression models by the balanced

haIf-sample approach, because of the multipIe sa,tnpling error computing units within the certainty

strata 1-10. To alleviate some of these difficulties, the

multiple sampling error computing unit identification

codes were randomly allocated into 2 “pseudoreplicates” for each of these 10 strata. Consequently, the

paired selection computations then could be utilized

for all 35 strata. The effects of randomly assigning

the multiple sampling error computing units to two

paired pseudoreplicates was investigated by the comparative analysis of standard errors and design effects

for decayed, missing, and filled teeth and calories

within the selected age groups shown in table VII.

deriving estimates of design effects for statistics for _

which they are not available but also for suggesting NOTE: A Iist of references follows the text.

64
Table VI 1. Cooperative analyses of standard errors and design effects for multiple and paired sampling error computational units (S ECU’S) within

certainty strata for decayed, missing, and filled (DMF) teeth and calories, by age for NHANES I data

Multiple SECLJ’S Pairad SECIJ%

Numbar of

Age axamined Mean Standard Square root Standard Square root

persons error of of design error of of design

mean effect mean effect

l-74years . . . . . . . . . . . . . . . . . . . . . . .

I-l?years . . . . . . . . . . . . . . . . . . . . . . .

18-24years . . . . . . . . . . . . . . . . . . . . . . .

25-34years . . . . . . . . . . . . . . . . . . . . . . .

35-44years . . . . . . . . . . . . . . . . . . . . . . .

45-54years . . . . . . . . . . . . . . . . . . . . . . .

55-64years . . . . . . . . . . . . . . . . . . . . . . .

65-74years . . . . . . . . . . . . . . . . . . . . . . .

l-74years . . . . . . . . . . . . . . . . . . . . . . .

l-17years . . . . . . . . . . . . . . . . . . . . . . .

18-24years . . . . . . . . . . . . . . . . . . . . . . .

25-34years . . . . . . . . . . . . . . . . . . . . . . .

35-44years . . . . . . . . . . . . . . . . . . . . . . .

45-54years . . . . . . . . . . . . . . . . . . . . . . .

55-64years . . . . . . . . . . . . . . . . . . . . . . .

65-74years . . . . . . . . . . . . . . . . . . . . . . .

20,749

7,104

2,297

2;694

2,327

1,599

1;262

3,466

20,749

7,104

2,297

2,694

2,327

1,599

1,262

3,466

14.723

3.965

11.924

16.918

21.436

22.826

25.744

27.727

2,000.0

2,011.0

2,294.8

2,177.5

2,042.9

1,897.3

1,723.2

1,518.9

DMF teeth

0.166 2.094

0.071 1.545

3.237 1.766

0.261 1.823

0.249 1.560

0.216 1.085

0.291 1.278

0.154 1.283

Calories

17.80 2.923

20.75 2.106

37.02 1.660

27.66 1.479

28.33 1.545

31.76 1.515

33.06 1.418

20.68 1.870

0.161

0.070

0.237

0.262

0.248

0.232

0.279

0.154

17.88

20.03

35.32

29.44

28.94

30.41

33.45

19.99

2.034

1.538

1.768

1.826

1.555

1.164

1.224

1.278

2.937

2.033

1.584

1.573

1.578

1.451

1.435

1.808

The means and standard errors were computed under

the multiple sampling error computing unit classification as well as under the paired sampling error cornputing unit groupings. At least forthese variables, it

is apparent that the random allocation of sampling

error computing units in the certainty strata to form

a complete paired design has not substantially altered

the estimates of variances or the corresponding design

effects.

As a result of this pairing for the 10 certainty

strata, all variance-covariance computations could be

obtained directly as appropriate sums of squares and

cross-products of differences across the 35 strata, and

thus, 70 sampling error computing units. Consequently, all the analyses under option 3 were performed assuming this paired selection design.

Continuous variables: Means

The basic calculations for means and standard

deviations were performed for several representative

variables to investigate the relative effects of the sampling weights and the sampling design. These results

are displayed in table VIII for three variables of

Table VI il. Number of examined persons, estimated means, standard deviations, standard errors of the mean, and design effects for decayed,

missing, and filled (DMF) teeth, calories, and age, under analysis options 1-3 for NHANES I data

Inclusion of Standard Square root

Option number sampling Number Mean Standard error of

examinad deviation

of design

mean effect

Weights Design

DMF teeth

1 ......................................... No No 20,749 14.93 11.418 0.079 ---

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yes No 20,749 14.72 10.776 0.075 . . .

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yes Yes 20,749 14.72 23.227 0.161 2.034

Calories

1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . No No 20,749 1,827.5

2

877.00 6.088 ---

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yes No 20,749 2,000.0 944.91 6.560 ---

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yes Yes 20,749 2,000.0 2,575.9 17.883 2.937

Age

1 ......................................... No No 20,749 32.23 22.972 0.159 . . .

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yes No 20,749 30.61 20.120 0.140 -..

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yes Yes 20,749 30.61 34.417 0.239 1.498

65
primary interest in these analyses, namely, decayed,

missing, and filled (DMF) teeth, calories, and age.

Note that for the total sample, the unweighed

and weighted analyses (options 1 and 2) for these

variables are quite similar, both for the means and

variances. However, under option 3, the complex

sample design introduces a considerable increase in

the estimated variance of the mean. In particular, the

ratio of the standard error of the mean under option

3 to that obtained under option 1 in the last column

in table VIII ranges from 1.498 to 2.937. Consequently, the design effects for these three variables

range from 2.24 to 8.63.

In view of the fact that age was a crucial variable

in the oversampling aspects of the design, one might

expect the design effects to be less important when

stratifying by age. To investigate this possibility,

means and standard deviations of these same variables

were computed within age groups as shown in table IX.

Even though the design effects are somewhat reduced,

they are certainly not negligible, ranging from

to 4.13.

Continuous variables: Multiple regression models

1.3s

The basic model used for the majority of the analyses in this report is the multiple regression model..

This model is as follows:

~ = B1 +B2X2i+ B3X3i+. ..+ B~X~j+Ei

where Yi denotes the ith observation of the dependent variable; Xi denotes the ith observation of each

independent or explanatory variable; and Ei is the

random variation of the ith observation of Y. The

subscripts 1, 2, . . . . k identify the specific explanatory variables. B, is the mean of Yiwhen each of the

explanatory variables is equal to zero; Bk is the

change in the expected value of Yi corresponding to a

unit change in the kth explanatory variable, holding

all other explanatory variables constant. B2, B3, . . .,

Bk are often referred to as the regression slopes or

(partial) regression coefficients.

Also presented in the regression results tables are

beta coefficients, which are the result of linear regression in which each variable is “normalized” by subtracting its mean and dividing by its estimated standard deviation. In other words, the beta coefficient

adjusts the estimated slope parameter by the ratio of

the standard deviation of the independent variable to

the standard deviation of the dependent variable. A

beta coefficient of 0.3 may be interpreted to mean

that a standard deviation change of 1.0 in the independent variable will lead to a 0.3 standard deviation

change in the dependent variable. Beta coefficients

are also used to make statements about the relative

importance of the X variables in the model.

Assumptions of the multiple regression model

The classical assumptions associated with the

regression model are as follows:

1. The model specification is correct.

2. The X’s are nonstochastic. In addition, no exact

linear relationship exists among two or more of

the independent variables.

3. The random variation has zero expected value and

cclnstant v~iance for aII observations.

4. Random variations corresponding to different

observations are uncorrelated.

5. The random variation term is normally distributed.

Any set of real data is unlikely to meet all these

assumptions, particularly one utilizing a complex

sample survey design such as the NHANES I survey.

However, certain violations of these assumptions may

not seriously affect statistical inferences. For example, under simple random sampling arguments, it is

straightforward to show that the least squares estimators of the regression coefficients retain their desirable

asymptotic properties (unbiased, consistent, and efficient]l, when the X’s are stochastic (violation of the

second assumption), provided that the explanatory

variables are each distributed independently of the

true errors in the model. See, for example, Kmenta?T

More detailed discussions of the properties of regression model estimates from complex sample surveys

can be found in Holt et al.s B

Specification error

If any variables are omitted from the regression

equation that are correlated with both the dependent

variable and the independent variable(s) whose regression coefficients are to be estimated, the estimates

will be biased. In fact, this phenomenon is the reason

a multivariable estimation procedure was chosen for

this analysis. For example, in the investigation of the

relationship between dietary intake patterns “troddantal caries experience, if a variable such as age is

omitted, biased estimates of that relationship emerge.

In spite of the effort made to include all the theordtically important variables in the model, if some have

been omitted either because they were not part of the

data collected or theory has not yet advanced sufficiently to suggest that they should be included, the

estimators given by the model could be biased.

Another concern relating to specification error is

the form of variables in the model. They are included

in forms that seem to be reasonable according to

theory, and, therefore, no serious rnisspecificatiqns

should be present that are attributable to the form of

the variables.

NOTE: A list of references follows the text66
Table IX. Number of examined persons, estimatad maansr standard deviations, standard errors Of the mean, and design effects for decayed, missing, and filled (DMF) taath and calories within age

groups, undar analysis options 1-3 for NHANES I data

Option 1 Option 2

Number of

Option 3

Age examined

Standard Standard Standard Standard Standard Square root

persons Mean error of Mean

Standard

deviation deviation error of Mean deviation error of of design

mean mean mean effest

l-74yeers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

l-17years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

18-24years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

25-34years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

35-44years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45-54years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

55-64years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

65-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

20,749

7,104

2,297

2,694

2,327

1,599

1,262

3,486

14.935

3.338

12.050

16.872

21.271

22.515

25.234

27.608

11.418

3.8493

6.4173

7.4408

7.6962

7.9700

8.0990

7.0741

0.793

0.0457

0.1339

0.1434

0.1595

0.1993

0.2280

0.1202

14.723

3.965

11.924

16.918

21.436

22.826

25.744

27.727

D MF teeth

10.776

4.0810

6.2566

7.2497

7.3482

7.5709

7.6022

6.7742

0.0748

0.0484

0.1305

0.1397

0.1523

0.1893

0.2140

0.1151

14.723

3.965

11.924

16.918

21.436

22.826

25.744

27.727

23.227

5.9219

11.345

13.589

11.966

9.2767

9.9110

9.0423

0.1613

0.0703

0.2367

0.2618

0.2481

0.2320

0.2790

0.1536

2.034

1.538

1.768

1.826

1.555

1.164

1.224

1.278

Calories

l-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..O 20,749 1,827.5 877.00 6.088 2,000.0 944.91 6.560 2,000.0 2,575.9 17.883 2,937

l-17years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7,104 1,880.4 830.42 9.8525 2,011.0

18-24years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

874.24 10.372

2,297

2,011.0 1,688.5 20.033 2.033

2,084.6 1,068.7 22.298 2,294.8

25-34years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,136.6 23.715 2,294.8 1,692.6 35.317

2,694

1.584

1,954.5 971.00 18.708 2,177.5

35-44years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1,050.1 20.232

2,327

2,177.5 1,527.8 29.435 1.573

1,829.0 884.65 18.339 2,042.9

45-54years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

966.51 20.036 2,042.9 1,395.8 28.935

1,599 1,840.4

1.578

838.33 20.965 1,897.3 816.17

55-64years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

20.411

1,262

1,897.3

1,679.2

1,216.0 30.410 1.451

828,08 23.310 1,723.2 814.02

65-74years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

22.914 1,723.2

3,466 1,497.2

1,188.5

651.06

33.454 1.435

11.059 1,518.9 649.50 11.032 1,518.9 1,176.9 19.991 1.808
The possibility also exists that some of therelationships studied might be better represented by a

series of simultaneous interdependent equations. It is

not difficult to imagine, for example, that the symptoms of periodontal disease influence the frequency

of dental visits, that dental visits influence toothbrushing behavior, and that tooth brushing in turn

affects periodontal disease. In such a circumstance,

ordinary least squares estimation of individual equations can lead to biased and inconsistent parameter

estimates. While it is not believed that these forms of

possible misspecification pose a serious threat to the

conclusions reached, they do warrant future exploration to more precisely assess the underlying form of

these relationships.

Measurement error

When variables are measured with error, they can,

of course, affect the results of statistical procedures

applied to them. In general, considerable effort was

expended to ensure a minimum of observer error in

the gathering of the data used in this analysis. Some

of the procedures employed are described in the section titled “Sources and limitations of the data.”

However, for the group of nutritional and dietary

variables from the 24-hour recall record, special note

is necessary. There are both short-term and long-term

variations in what people eat. Therefore the 24-hour

recall record is an imperfect measure of long-term

dietary patterns. This kind of random error in an independent variable in a regression equation will bias

the estimate of the regression coefficient of that

variable toward zero.

For example, under simple random sampling arguments, it is possible to demonstrate that the form of

the bias is as follows:

2’ = 2/(1 +A)

where

& = the biased estimate of the regression parameter as computed by ordinary least squares,

~ = the unbiased estimator, and

X = the ratio of the true variance to the additional variance attributable to the measurement error.

See, for example, Snedecor and Cochran.59 The extent to which the bias in estimates of regression coefficients can be expressed in this formulation under

the complexities of option 3, utilizing both the sampling weights and the survey design effects, would

require further investigation.

Because some empirical work has been done to

provide estimates of the ratio of interindividual (true

NOTE: A list of references follows the text.

68

between-subject variation in individual intake) to

intraindividual (day-to-day variation in individual intake) variation, rough estimates of this bias are POST

sible.5!) These data suggest that values of A of at least

one or two are not unreasonable. Based on this infolrr

mation, the trends in dental caries experience related

to 24hour recall variables are, as estimates of the

relationship between dental caries experience and lifetime clietary patterns, underestimates by a factor of

1/2 tc} 1/3. Stated another way, lifetime trend estimates are likely to be two or three times larger than

those provided by the 24-hour data.

When a variable with this type of error is used as

a dependent variable, as in the investigation of the

effect of dentulous status on dietary patterns, the

problem encountered is less severe. Standard errors

will be overestimated, but estimators will be unbiased.

Therefore, the only real hazard is the failure to reject

the null hypothesis when it should be rejected.

Heteroscedasticity

When the third assumption is violated, standard

errors estimated by ordinary least squares tend to be

inefficient. Because the variance of both the DMF

and PI measures tends to increase with age, the possibility of this phenomenon influencing the results pr~-

senteci was investigated. Weighted least squares procedures were employed using the same variables that

had been studied by means of ordinary least squares.

The computed t-statistics for the statistically significant regression coefficients were virtually identical

between the two methods, and there was no consi+-

ent pattern of one being larger than the other. Tl&

finding indicates that, at least for the models cclnsidered in this report, heteroscedasticity is not a

problem. The results presented are thus based (on

ordinary least squares.

Nonnorrnality of random variation term

The dependent variables of decayed, missing, add

tilled teeth and the periodontal index have distributions that are skewed toward zero in the younger a~e

groups. The random variation term is therefore n,pt

normally distributed, as demonstrated by the mediin

values in table O. The t-tests are nevertheless employed as though the disturbances are normally clistributed because the procedure is considered to be

relatively robust when sample sizes as large as these

are used.

Empirical results for regression models

In order to investigate predictive relationships

among continuous variables, multiple regression

models also can be fitted under either option 1, 2, or

3. Specifically, the effects of the sampling weiglits

and complex design on the precision of regression
coefficients was investigated under options 1-3 for

decayed, missing, and filled (DMF) teeth and calories

on age as summarized in table X. First, it can be observed in the corresponding entries under options 1

and 2 that the results are quite similar, particularly

for DMF teeth on age, which has a strong linear relationship in all the race-sex subclasses. However, for

calories on age, which has extremely small R 2 criteria

for all subgroups, the estimate of the slope is quite

different for some subclasses; in fact, for the “other

males” category there is a 12-fold increase in the slope

under option 2 compared with option 1, and for the

“other females” category it differs by a factor of

nearly 3. Of course, in both of these subclasses the

sample size is relatively small.

Otherwise, note in table X that the results under

option 3 are only reported for the white subgroups,

even though the number of black persons examined

appears to be reasonably large. This omission is due

to the failure of the balanced half-sample routine in

the weighted regression program in OSIRIS IV resulting from entire strata with no data for these subclasses

as shown in table XI. Modification of this routine or

another sampling error program could still be used to

obtain these estimates for the other subclasses. This

problem of missing sampling error computing units is

even more pronounced within the more restrictive

detailed examination as displayed in table XII. Consequently, due to the sparse design across strata, only

the white and black race data were used in many of

the analyses.

In addition to simple linear regression models,

multiple regression models can also be fitted within

this same framework. Table XIII summarizes the

results of DMF regressed jointly on age, race, sex, and

sweets for 6,349 cases ages 11-30 years. Here again,

the design effects for the regression coefficients range

from 1.19 to 6.40.

These empirical results, as expressed in terms of

estimated design effects, demonstrate the critical importance of incorporating the sampling weights and

the survey design adjustments into all definitive multiple regression models.

69
Table X. Summary of simple regression models of decayed, missing, and filled ( DMF) teeth and calories on age under analysis options 1-3, by race and sex for NHANES I data

Race and sex

Un weighted design (option 1) Weighted design

Number of

examined (Option 2) (Option 3)

Standard

Square root

persons R2 Slope t-statistic R2 Slope

error Standard Standard

of design

t-statistic t-statistic

arror error

effect

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

White males . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Blackmales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

All other males . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Whitefemales . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Blackfemales . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

All otherfemales . . . . . . . . . . . . . . . . . . . . . . . . . . .

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

White males . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Blackmales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

All other males . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Whitefemales . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Blackfemales . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

All otherfemales . . . . . . . . . . . . . . . . . . . . . . . . . . .

20,749

7,004

1,707

109

9,347

2,456

126

20,749

7,004

1,707

109

9;347

2,456

126

0.67

0.73

0.63

0.53

0.67

0.59

0.40

0.02

0.01

0.01

0.00

0.04

0.06

0.00

0.408

0.416

0.335

0.317

0.414

0.391

0.337

-4.90

-3.39

-3.74

1.00

–5.89

-8.39

-1.23

0.0020

0.0030

0.0062

0.0287

0.0030

0.0065

0.0372

0.2629

0.4873

0.921:

3.598

0.3034

0.6578

3.474

206.89

138.91

54.44

11.04

136.49

59.91

9.07

–1 8.64

-6.95

–4.05

0.28

–19.41

-12.75

-0.35

DMFonage

0.65 0.432 0.00>2

0.67 0.440 0.0037

0.47 0.308 CJ.0080

0.45 0.294 0.0316

0.68 0.439 0.0031

0.54 0.385 0.0072

0.25 0.244 0,0376

Calories on age

0.01 -5.50 0.3238

0.00 _3.52 0.6102

0.00 –1 .08 1.212

0.05 12.50 5.101

0.04” -6.44 0.3315

0.06 –9.45 0.7420

0.01 -3.35 3.899

196.52

118.93

38.52

9.28

139.50

53.29

6.50

-16.99

-5.78

-0.89

2.45

-19.43

–12.74

-0.86

0.0032

0.0042

---

.-.

0.0053

.-.

---

0.3171

0.6314

---

.-.

0.4339

..-

..-

135.09

105.49

..-

---

82.76

---

-..

17.35

-5.58

-..

---

-14.85

-..

---

1.62

1.39

---

---

1.75

---

.-.

0.98

1.03

---

---

1.31

. . .

---
Table Xl. Numkrof examined persons byrace, sex, andstratum numkrin the NHANESl design

Number of examined persons by r~a and sex

Stratum number Total

White Black All other White Black All other

malas males males females females females

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

9

lo:::::::::::::::::::::: :::::::::::::::::::::::: :

11 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

20 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

21 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

22 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

23 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

24 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

25 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

26 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

27 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

28 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

29 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

30 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

31 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

32 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

33 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

34 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

35 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

20,749

621

367

482

737

741

395

188

304

429

481

517

531

707

486

563

594

505

585

446

790

551

619

499

728

887

684

1,001

634

868

651

691

619

545

1,059

7,004

169

146

123

198

232

67

85

67

109

138

205

198

232

273

185

178

235

176

237

171

344

114

167

131

225

232

262

259

222

284

221

250

222

236

411

1,707

88

24

85

102

65

35

90

16

13

32

4

14

2

15

20

68

6

39

12

13

0

107

85

73

73

156

23

174

51

84

34

22

3

5

74

109

2

0

1

11

13

2

0

0

1

13

0

0

2

2

4

5

0

2

4

1

0

3

0

0

0

0

1

0

1

1

5

8

21

5

1

9,347

220

157

171

255

328

85

93

79

149

190

267

286

280

396

226

211

346

224

317

246

446

141

249

170

311

305

379

327

292

371

334

367

345

295

479

2,456

138

38

102

162

88

57

127

26

32

37

3

17

4

14

43

98

6

62

14

14

0

185

116

122

119

184

17

241

68

124

52

32

10

1

93

126

4

2

0

9

15

4

0

0

0

19

2

2

1

1

8

3

1

2

1

1

0

1

2

3

0

0

2

0

0

4

5

12

18

3

1

71
Table X1l. Num&rof examined persons byracer sex, andstratum numkrinthe NHANESl design forthe detailed sample

Number of examined persons by race and sex

Stratum number Total ~vhite

Black All other White Black All other

males males males females females females

6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

9 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

lo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .,

11 ................................................

12 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

16 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

18 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

20 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

21 . . . . . . . . . . . . . . . . . . ...< . . . . . . . . . . . . . . . . . . . . . . . . . .

22 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

23 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

24 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

25 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

26 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

27. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

28 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

29 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

30 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

31 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

32 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

33 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

34 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

35 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3,854

112

80

87

129

143

48

71

42

57

84

100

93

92

129

78

101

107

81

109

81

162

89

112

81

156

150

141

182

126

152

113

123

119

100

224

1,541

37

38

23

46

60

17

16

19

25

34

45

40

45

54

43

29

52

41

45

34

72

28

33

28

67

45

65

57

50

63

49

51

45

46

99

27’7

13

4

18

15

11

7

18

0

1

8

0

3

1

1

2

13

1

4

2

2

0

17

16

8

8

22

6

26

10

14

3

2

0

2

19

21

1

0

0

1

4

1

0

0

0

4

0

0

0

0

1

0

0

1

1

0

0

1

0

0

0

0

0

0

0

0

1

2

2

0

1

1,667

34

27

29

43

55

12

17

18

27

30

53

49

46

70

27

41

54

28

59

44

90

23

48

30

67

65

68

64

58

64

51

61

69

52

94

335

27

11

17

23

12

11

20

5

4

5

1

0

0

4

5

18

0

7

2

1

0

20

15

15

14

18

1

35

8

11

8

6

0

0

11

13

0

0

0

1

1

0

0

0

0

3

1’

1

0

0

0

0

0,

0

0

0

0

0

0

0

0

0

1

0

0

0

1

1

3

0

0

—.

Table Xl Il. Summary of multiple regression models for decayed, missing, and filled (DMF) teeth on age, race, sex, and sweets for 6,349 examined

persons ages 11-30 yews, under analysis options 1-3

Regression Standard Square root

Variable coeffieien terror of t-statistic of design

coefficient t effect

Unweighed SRS design (option 1)

Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.685 0.0130 52.42

Race . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . .

0.875 0.0899 9.73

Sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . .

-0.491 0.0752 -6.52

Sweets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . .

0.057 0.0070 8.21 ..-

Weighted SRS design (option 2)

Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.705 0.0125 56.29

Race . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

---

0.795 0.1072 7.42

Sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

.-.

-0.465 0.0898 -6.65

Sweets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . .

0.049 0.0068 7.17 . . .

Weighted complex sampling design (option 3)

Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.705 0.0209 33.67 1.60

Race . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.796 0.2277 3.50 2.53

Sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -0.465 0.0928 -5.01 1.23

Sweets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.049 0.0077 6.43 1.09

72
Appendix II

Definitions of Terms

and Variables

Statistical terms

Regression coefficient (B).–The estfiated additive effect on the dependent variable for each unit of

change in the independent variable within the multiple regression model for which all the other independent variables are held constant.

Sigma (1?).–The model-based estimated standard

emor of the regression coefficient (B).

Standardized coefficient (Beta). –The estimated

additive effect on the dependent variable for each

unit of change in the independent variable which has

been standardized to have mean zero and variance

unity, within the multiple re~ession model ~ which

all the other independent variables have been standardized and held constant.

Sigma (Beta). –The model-based estfiated st~dard error of the standardized coefficient (Beta).

Partial r.–The estimated correlation coefficient

between the dependent variable and the independent

variable within the multiple regression model for

which all the other independent variables are held

constant.

t-statistic. –The test criterion obtained as the ratio

of the regression coefficient @) to its estimated

standard error, Sigma (B), to test the hypothesis that

B is zero.

Demographic variables

High school indicator. –An indicator variable

based on the reported highest grade attained by head

of household. Coded 1 if head of household reported

highest grade as 9th grade, 10th grade, 11th grade, or

12th grade. Coded O for all other valid responses.

College indicator. –An indicator variable based on

the reported highest grade attained by head of household. Coded 1 if head of household reported highest

grade as fust year of college, second year of college,

third year of college, fourth year of college, or graduate. Coded Ofor all other valid responses.

Total family income. –An analytic variable for

total family income. The original data available were

in the form of 12 income categories. In order to

approximate a continuous variable, these codes were

transformed as follows:

Code

Income Transformed

reprasentad variabla

11.............

12 . . . . . . . . . . . . .

13 . . . . . . . . . . . . .

14 . . . . . . . . . . . . .

15 . . . . . . . . . . . . .

16 . . . . . . . . . . . . .

17 . . . . . . . . . . . . .

18 . . . . . . . . . . . . .

19 . . . . . . . . . . . . .

20 . . . . . . . . . . . . .

21 . . . . . . . . . . . . .

22 . . . . . . . . . . . . .

Under $1,000

$1,000-$1,999

$2,000-$2,999

$3,000-$3,999

$4,000-$4,999

$5,000-$5,999

$6,000-$6,999

$7,000-.$9,999

$10,000-$14,999

$15,000$19,889

$20,0(B$24,999

$25,IMO and over

o

1

2

3

4

5

6

8

12

17

22

29

Sex indicator. –An indicator variable for sex,

coded O for males, 1 for females.

Black indicator. –An indicator variable for race,

coded 1 for black, Ofor white and other.

Other indicator. –An indicator variable for race,

coded 1 for other, O for white and black.

Age categories. –Categorical variable based on age

of respondent at time of interview. Five categories,

ages 6-11, 12-17, 18-44, 45-64, and 65-74 years.

Age at interview. –Age of respondent at interview,

in years, taken directly from the supplied tapes.

Dietary variables

Chlories as a percent of standard. –Individual

caloric intake as the percent of NHANES I dietary

standards, computed for food items listed in 24-hour

recall.

Protein as a percent of standard. –Individual protein intake as the percent of NHANES I dietary

standards, computed for food items listed in 24-hour

recall.

73
Calcium as a percent of standard. –Individual calcium intake as a percent of NHANES I dietary standards, computed for food items listed in 24-hour recall.

Iron as a percent of standard. –Individual iron intake as a percent of NHANES I dietary standards,

computed for food items listed in 24-hour recall.

Vitamin A as a percent of standard. –Individual

vitamin A intake as a percent of NHANES I dietary

standards, computed for food items listed in 24-hour

recall.

Vitamin C as a percent of standard. –Individual

vitamin C intake as a percent of NHANES I dietary

standards, computed for food items listed in 24-hour

recall.

Percent of calories from sweets. –Individual caloric intake from the food groups sugar and primarily

sugar products, desserts and sweets, and cereals and

grain products as a percent of total caloric intake.

Computed for items listed in the 24-hour recall.

Percent of calories from between-meal sweets. –

Individual caloric intake from the food groups sugar

and primarily sugar products, desserts and sweets, and

cereals and grain products eaten between meals as a

percent of total caloric intake. Computed for items

listed in the 24-hour recall.

Number of between-meal sweet snacks. –Number

of between-meal snacks from the food groups sugar

and primarily sugar products, desserts and sweets, and

cereals and grain products eaten between meals. Computed for items listed in the 24-hour recall.

Number of between-meal nonsweet snacks. –

Number of between-meal snacks from the food

groups other than primarily sugar products, desserts

and sweets, and cereals and grain products eaten between meals. Computed for items listed in the 24-hour

recall.

Weekly frequency of fruit ingestion. –How often

fruit is eaten during the week.

Dental variables

Oral hygiene index (OWS).-Oral hygiene index

(simplified) score for entire mouth as given in the

data provided.

Periodontal index (P]).–Periodontal index score

for entire mouth as given in the data provided.

Nonfunctional carious teeth. –Total nonfunctional carious permanent teeth present. A subset of

total missing (because of caries) permanent teeth.

Decayed teeth (D). –Total carious permanent

teeth.

Missing teeth (M). –Total missing (because of

caries) permanent teeth.

Filled teeth (F). –Total filled permanent teeth

without decay.

Filled defective teeth. –Total filled defective permanent teeth. A subset of total decayed permanent

teeth.

DMIW –Sum of decayed (D), missing (M), and

filled (F) permanent teeth.

Absence of teeth. –Categorical variable for the

absence of functional natural teeth. Coded O if at

least cme functional natural tooth, coded 1 if edentu10USor all remaining teeth indicated for extraction.

One denture. –Categorical variable for the wearirig

of dentures by the edentulous for eating. Coded 1 if

one denture worn, coded Oif neither or both worn.

Both dentures. –Categorical variable for the wearing of dentures by the edentulous for eating. Coded 1

if both worn, coded Oif one or none worn.

Enamel jhoride content. –The’ natural logarithh

of the fluoride content of enamel in parts per millicm

that has been adjusted for biopsy depth. The formula

for depth adjustment is:

‘M( 1,287,817)

Fadjusted =

1,598,630

488,502 +

depth in microns

Daily tooth-brushing frequency. –Usual daiIy

tooth-brushing frequency.

Behavioral variables

Dental visit pattern. –An ordinal variable created

from answers to a series of questions concerning the

most recent dental office visit. The variable has the

following seven levels:

1. Less than 6 months ago.

2. At least 6 months, but less than 1 year.

3. At least 1 year, but less than 2 years.

4. At least 1 year, but less than 4 years.

5. Four or more years.

6. A, visit to a dentist at a site other than a dental

office (e.g., hospital emergency room).

7. Never visited a dentist.

Tobacco use.–The tobacco-use variable allocated

subjects into the following three categories:

1.

2.

3.

Never have used tobacco in quantities up to or

equal to the amounts stated in the medical history

questionnaire, that is, at least 100 cigarettes, 50

cigars, or 3 packages of pipe tobacco during the

subject’s lifetime.

Have used tobacco at least up to the amounts

stated in the questionnaire but do not use tobac~o

now.

LJsed tobacco at the time of the interview, at least

up to the amount stated in the questionnaire.

Used tobacco in the past. –An indicator variable

coded 1 = used tobacco in any form in the past but

do not use it now, O= other.

74
Use tobacco now. –An indicator variable coded

1 = use tobacco in any form now, O= other.

Alcohol consumption. –Categorical variable derived from three other variables. The four categories

are as follows:

1.

2.

3.

4.

None: Those who claimed not to have had a drink

in the past.

Little: Those who claimed to drink no more than

once a week and when they did drink had three

or fewer drinks.

Moderate: Those who stated they drank more

than once a week but have three or fewer drinks

at a time, or those who drink no more than once

a week but have four or more drinks when they

do.

Heavy: Those who claimed to drink more often

than ‘once a week and have four or more drinks at

a time.

Other variables used

Other variables that were used but that do not

appear in the detailed tables are the following:

Dietary calcium

Dietary phosphorus

Weekly frequency of desserts

Weekly frequency of candy

Weekly frequency of sugar drinks

Calories per kilogram of body weight

Protein per kilogram of body weight

Fat per kilogram of body weight

Carbohydrates per kilogram of body weight

Calcium per kilogram of body weight

Phosphorus per kilogram of body weight

Iron per kilogram of body weight

Sodium per kilogram of body weight

Potassium per kilogram of body weight

Vitamin A per kilogram of body w$ight

Thiamin per kilogram of body weight

Riboflavin per kilogram of body weight

Niacin per kilogram of body weight

Vitamin C per kilogram of body weight

Protein as a percent of calories

Fat as a percent of calories

Carbohydrates as a percent of calories

Calcium to phosphorus ratio (dietary)

Serum calcium

Serum phosphorus

Calcium to phosphorus ratio (serum)

Definitions of food groups in 24-hour recall data

Milk and milk products. –Includes milk drunk as a

beverage or used on cereals; flavored milk drinks;

cocoa made from milk; skim milk, yogurt, or buttermilk; ice milk; ice cream or puddings made with milk;

cheese and cheese dishes. Exception: cream cheese.

Meat. –Includes beef, pork, lamb, veal, luncheon

meats, canned meats, and frankfurters.

Poultry. –Includes chicken, turkey, duck, game

birds, and cornish hen.

Organ meats. –Includes liver, kidney, heart, and

spleen.

Fish or shellfish. -All varieties of fish and shellfish

regardless of whether canned, fresh, frozen, dried, or

salted.

Eggs.–Includes eggs eaten, e.g., fried, boiled,

poached, deviled, or egg salad. Exceptions: eggs in

cooked or baked dishes (as in custards or puddings).

Soups, sauces, and gravies. –Includes milk- and

water-based stocks and meat- and vegetable-based

gravies and sauces.

Fats and oils. –Includes butter, margwine, salad

oil, salad dressing, bacon, cream cheese, cream, peanut butter, nondairy cream, and olives.

Legumes and nuts. –Includes cooked dry beans

and peas and previously dried legumes and nuts such

as pinto; red beans, black-eyed peas, lentils, peanuts,

soy beans, and soy products.

Cereals and grain products. –Includes breakfast

cereals, either dry such as comflakes or cooked such

as oatmeal; grain products such as bread, rolls, biscuits, muffms, cornbread, crackers, unsalted pretzels,

rice, and pasta.

Fruits and vegetables. –Includes raw, canned,

frozen, or cooked produce; fruits and vegetables rich

in vitamin A; and fruits and vegetables rich in

vitamin C.

Sugar and primarily sugar products. –Includes all

candy, fruitades, soft drinks, jam, jelly, honey, sugar,

and icings.

Desserts and sweets. –Includes cake, pie, cookies,

fruit puddings, nonprotein gelatins, doughnuts (caketype and yeast-type), sherbet, and sweet snacks. Exceptions: ice cream and ice milk.

Miscellaneous. –Includes mustard, gelatin, malt,

beverage powders, chili powder, seeds, and low-fat

salad dressings.

Mixed protein dishes with ci.zrbohydrates (starches)

or vegetables. -Includes casseroles, pot pies, pizza,

and pasta dishes with meat. Exceptions: plain cheese

dishes.

Alcoholic beverages. –Includes beer, wine, and

distilled liquors.

Sugar-free and low-calorie beverages. –Includes

coffee (regular and decaffeinated), tea, bouillon,

consomme, and low-calorie carbonated drinks.

Salty snacks. –Includes potato chips, corn chips,

puffed snacks, cheese snacks, salted popcorn, and

salted pretzels.

75
. .

Table XIV. Major functions, problems associated with def iciancy, and major food sources of calories and selected nutrients

Calorie and

nutrient

Major function Problems associated with

deficiency

Major food sources

Calorie . .

Protein .

Vitamin A

Vitamin C .

. . . . . . . .

. . . . . . . .

. . . . . . . .

. . . . . . . .

Calcium . . . . . . . . . .

Iron . . . . . . . . . . . . .

Thiamin e . . . . . . . . .

Riboflavin . . . , . . . .

Niacin . . . . . . . . . . .

Supplies energy for growth anddevelopment, basal metaboi ism, and

physical activity

Essential for normal growth and

development; for maintenance and

repair of all body tissue

Essential for the maintenance of

healthy skin and mucous membranes, for normal night vision; aids

in maintain ingresistancato

infections

Production of intercellular cementing

substance ;wound healing ;playsa

rola in normal resistance to

infections

Necessary for formation of bones and

teeth ;plays a role in blood coagulation and normal reactions of nerve

and muscle tissue

Necessary for formation of hemoglobin, the oxygen-carrying pigmentof red blood cells

Essential for growth, normal function

of the nervous system, and normal

metabolism

Essential for utilization of protein

and is also involved in other metabolic processes

Essential for normal digestion and

utilization of food

Inadequate caloric intake in children

is evidenced by Iack of growth and

energy, loss of weight in all age

groups

Asevere or prolonged deficiency results in retarded growth ;symptoms

may include edema, lassitude, end

decreased resistance to infections

Deficiency signs: night blindness and

skin changes characterized by dry,

rough skin. Prolonged deficiency

can lead toperrnanentb lindness

Deficiency results in soft, spongy

gums, prolongad wound healing,

and inthe advance ddeficiency

stater the classical disease scurvy

Deficiency in children may be associatad with rickets ;inadults,calciurn

may belostfrc~m the bones (osteoporosis)

Weakness and fatigability; advanced

deficiency Ieacls to anemia

Deficiency results in retarded growth,

edema, and changes in the nervous

system; advanced deficiency can

result in beriberi

Deficiency can result in skin changes

such as angular lesions, tongue

changes, and poor growth

The classical deficiency state is

pellagra, characterized by diarrhea,

dermatitis, dementia, and death

Al I foods; starchy, sweet, and fat

foods are concentrated sources

Eggs, milk and milk products, meats,

fish, poultry, soybeans, dried beans,

peas, and nuts

Liverr whole milk and whole milk

products, and dark graen leafy and

deep yellow vegetables

Citrus fruits, tomatoes, strawberries,

cantaloupe, rawcabbage, andgrean

peppers

Milk and milk products, certain grean

Ieafy vegetables, oysters, clams, and

shrimp

Liver and other organ meats, dark

green leafy vegetables, dried fruits,

whole grain and enriched ceraals

and cereal products, and molasses

Liver, eggs, whole grain or enriched

cereals and careal products, and

lean meat

Dairy products are the major source,

butmeats and green leafy vegetablas are othar sources

Liver, maats, wholagrain, and enrichedcereals and cereal products

76
Table XV. Standards forevaluation ofdaily die@~intakes used in the National Health and Nutrition Examination Survey, byaga, sex, and

physiological state: United States, 1971-74

Age, sex, and physiological ste te

Calories Protein Calcium Iron Vitamin Vitamin

(gm per

B vitamins

(per kg)

kg) (m9) (mg) A‘

(Iu) (:9)

(all ages)

Age and sex

1-5 years:

12-23 months, maleandfemale. . . . . . . . . . . . . . . . . . . . . . .

24-47 months, maie and female.. . . . . . . . . . . . . . . . . . . . . .

48-71 months, maleand female. . . . . . . . . . . . . . . . . . . . . . .

6-7years, maleandfemale . . . . . . . . . . . . . . . . . . . . . . . . . . . .

8-9years,male andfemale . . . . . . . . . . . . . . . . . . . . . . . . . . . .

10-12 yearx

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13-16 years:

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

17-19 years:

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

, 20-29 years:

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

30-39years:

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

40-49 years:

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

50-54years:

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

55-59 years

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

60-69 years

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

70 years and over:

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Physiological state

Pregnancy (5th month and bayond), addto basic standard . . . . . . .

90

88

82

82

82

68

64

60

46

44

35

40

35

38

33

37

31

36

30

36

30

34

29

34

29

200

Lactating,addto basicstandard . . . . . . . . . . . . . . . . . . . . . . . . . 1,000

1.9

1.7

1.5

1.3

1.3

1.2

1.2

1.2

1.2

1.1

1.1

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

1.0

20

25

450

450

450

450

450

650

650

650

550

550

400

600

400

600

400

600

400

600

400

600

400

600

400

600

200

500

15

15

10

10

10

10

18

18

18

18

18

10

18

10

18

10

18

10

18

10

10

10

10

10

10

2,000

2,000

2,000

2,500

2,500

2,500

2,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

3,500

1,000

1.000

40

40

40

40

40

40

40

50

50

55

50

60

55

60

55

60

55

60

55

60

55

60

55

60

55

&?

5

Thiamin,

0.4 mgl

1,000

calories

Riboflavin,

0.55 mg/

1,000

calories

Niacin,

6.6 mgl

1,000

calories

1A~~”med 70 percent car~mne, 30 percent retin~l.

2For all pregnancies.

77
Appendix Ill

The Dental Examination

The examination

The dental examination findings were recorded

on a form that eliminated the time-consuming task of

coding and keypunching. The form (figure I), four

pages bound at the lefthand margin, was fed into an

Optical Mark Page Reader that read the findings and

entered the data directly on IBM cards.

Instructions for determining the conditions of

individual teeth and recording the information were

as follows:

1.

2.

3.

4.

5.

6.

7.

78

Primary tooth present–A primary tooth was

coded as “D,” and its status was also coded.

Permanent tooth present–Only the status of a

permanent tooth was coded.

Normal–Unfilled teeth without carious lesions

were coded as “3 .“

Carious–Unfilled teeth with carious lesions were

coded according to the surfaces involved.

Filled (including crown)–Teeth with satisfactory

fillings and no carious lesions were coded according to the surfaces involved.

Filled defective (or tooth both filled and carious)–Filled or crowned teeth with new or recurrent carious lesions were coded according to the

surfaces involved. Noncarious filled teeth were

coded in the same way when the restoration was

loose, or fractured, and the base or pulpal wall of

the cavity preparation was exposed. Teeth with

temporary fillings or crowns were coded as filled

defective.

Nonfunctional-carious-When decay had penetrated the pulp chamber of a tooth, the tooth was

coded under “XD.” Carious teeth are nonfunctional when there was the following evidence:

a. Visible evidence of a periapical abscess or

pulpal exposure.

b. Visible evidence of extensive undermining

of all enamel walls or if roots only were

remaining.

8.

9.

Retained deciduous teeth–When any portion of

the succedaneous tooth could be seen, it was

given an appropriate status code under teeth

present and also coded “XD” and “D.”

Missing teeth (unerupted, extracted, and repl[aced)–When neither a primary nor a permanent

tooth was present (the tooth space may have been

vacant or the missing tooth may have been lreplaced by a fixed or removable partial denture), a

code was recorded indicating the status of the

tooth space. For persons 35 years old or under,

the reason that the tooth was missing should have

been determined. When there was doubt, it v~as

scored as missing because of decay. The coclm

were as fo~ows:

2 =

o=

IIR =

1=

F; =

FD =

Unerupted, primary.

Unerupted, permanent.

Extracted, caries.

Extracted, accident, orthodontics, impaction.

Missing, replaced on a fixed bridge. The

reason for extraction was also coded if the

sample person was age 35 years or under.

Missing, replaced on a defective fixed

bridge. The- reason for extraction was also

coded if the sample person was age 35 years

or under.

Fixed bridges were defective:

A.

B.

c.

When one of the abutment teeth was ncmfunctional because of either caries or loss ,of

supporting structure, or when there was

visible evidence of periapical pathology.

When the connection of the pontic with its

abutment was broken.

When an abutment crown or inlay was defective because of one of the following reasons:

1. The tooth structures exposed by abrasion

of the crown or inlay were carious.
DEPARTMENT OF HEALTH, EDUCATION AND WELFARE Confidentiality has been assured the mdw!dual as set forth m 22 FR 1687 =

w8LIc HEALTH scwlrE

HEALTH SiRVl Ct5 AND MENTAL HEALTH ADMINISTRATION

—

—

—

—

———————

—

——

—

—

—

———

——

———

———

—

—

———

——

———

NAT10N41 CENTER FoR HEALTH STATISTICS

ROCKVILLE MARYLAND 20852

I -Q.

.,.. .= ~. .*

5 .6 -769

I

STAND

.s - “1 2. .3 .4 56789

HEALTH AND NUTRITION EXAMINATION SURVEY IS? AND

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:Q ,,1.. *. ,3. .4 5. 6 -7 e 9

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Figure 1. Dental examination form.

79
DENTAL EXAMINATIOJl

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OPACITIES

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PERIODONTAL INDEX

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UPPER

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. . . . . . . . . .

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. . . . . . . . . .

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Figure 1. Dental examination form-Con.

80
——

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:*: ::t:: :2: ::3: :*= ::%: :*: ::?= ::6: ::9

CONTROL

:*: ::1:: =&: ::3: Z-*: ::%: ::6= ::T= ::&: ::9

—

——

I :*:::e: :*

POSTERIOR CROSSBITE

immR’GHTciizmi —IUCCAL ‘EFT —LINGUAL

:,s, :*, ::S: ::6: ::Tx ::& ::s

ENAMEL BIOPSY

* TEETH ABSENT

m EQUIPMENT FAILURE

:- OTHER REASON

:Ysi TOOTH

::?:: Z*:

:Kt: :*:

———

—

BUCCAL SEGMENT RELATION

RIGHT LEFT

::ix ::t: MESIAL-SEVERE

::&: ::&: -MODERATE

::3: ::*: NORMAL

::*: ::&: DISTAL-MODERATE

::5: ::!5: -SEVERE

*: *: NOT APPLICABLE

:&: :5t:

:::= :::::

::&: ::.%:

:*: :3:

:*: ::4:

,*, :5=

*. MA:

———

——

——

/ ::!5: ::5:

EEl PRIMARY ARCH I I

——— HLD INDEX (HANDI( PPING lABIO-LlhGUAL DE ———

ATEONS)

OPENBITE

:*: :s%

::4:, :::::

=2= =2:

:3: :3=

:*:

:5::

:*:

::7::

::&:

:5=:

*,

OVERJET

:.Q: ::Q:

::i:: ::i::

::2: ::E:

=3: ::3:

::&:

::5:

::6:

:+%

::&:

:*:

:*

MANDIBULAR

PROTRUSION

::Q: :&:

::i:: ::i::

::&: -:E:

::3: :3:

::&:

::5:

::e:

::%:

::%:

::9-

*:

AiAUGNl

INCISOR RELATIONSHIP

OPENBITE (AVA)

:: A:: 4+

:Z2: 2+-4

::3: 0-2

OVERBITE

::6: INC 3RD

::5: MID 3RD

::&: GIN 3RD

::Z: TISSUE

::& : IMPINGING OVERBITE

OVERBITE DEFORMITY

,:::: AsmlT

::::: PREEEST

——

zft:

,:i::

:*:

:3:

::4:

:s:

::&:

::7::

:*:

::s7:

*,

—

-

—

—

——

————

~ NOT APPLICABLE_

I TEETH

——

EDENTULOUS ARCHES-DENTURE STATUS..- —

NA: ABSENT PRESENT DEFECTIVI

UPPER . .. . .

. .. .. ::.:: ::::

LOWER .. .. .

. .. .. . .. .. .. ..

... . . .. ..

WHEN YOU EAT, —YES —NO

DO YOU USE AN UPPER PLATE? . . .. . . .. ..

. .. .. .. . ..

DO YOU USE A LOWER PLATE? . ...- . .. ..

. .. .. . .. ..

REMARKS: PRESENT ::::: ABSENT ::::

——

—

:3: ::4:: —

:*: ::i::

:*: ::3: ::4: MINOR ::5:

:*: ::5: ::*: MAIOR ::5:

POSTERIOR

::&: ::3: ::4: MINOR ::5:

::Ez ::?c: ::&: MAJOR :5:

::Et:

::6: ———

:*: ::k:

:*: ::4::

:*: ::i?: ::&, ::%:

:*: ::?: ::&: :,9:

——

—

—— LOWER —

ANTERIOR

::&: ::3: ::4: MINOR ,:5:

:+k ::5: ::4:MAJOR ::s:

POSTERIOR

::2: :s: ::4: MINOR ::5:

::2: ::3: +: MAJOR ::5:

———

—

::6:

::6:

———

——

—

He.: ::j::

:Q: ::t::

::6: ::%: ::&: ::9:

:-6: ::?: ::%: :,s:

EXAMINER ::4:: ::&: ::3: RECORDER ::i:: ::&: ,s:

::6: ::5: ::6: Z:Z: ::8: :*: :5: :*: ::T: ::&,

Figure 1. Dental examination form–Con.

81
DENTAL EXAMINATIC)N —

—

:~: ::j:, ::2: ::s: ::*: ::S: ::6, ::?, ,,8: ,,s, —

STAND —

:*: ,:$:: :~: :,s, :.4’: ::s: :,e, :,R- ,,8, ,:s, —

AND

:*: ::*:: ,*, ,:s: ::*: :,s: :;U: ::Z: ::8: ::9: ❑

CONTROL

:s: :,J: :*., ,,s, ,,*, ,:S: ::8: :,~, ,,8, ,,9, z

I l—

TREATMENT NEEDS INTERVIEW

.

.

.

.

.

.

.

.

. NO APPARENT NEED FOR DENTAL CARE

Y&s g

.. ...

. ... . .. ...

..... .....

..... .....

...

. ... .....

. . . .....

..... ..

. . . .

.. . .

..... .,,::

.

..... .,:::

. .

.

.....

.. .....

..... .,::,

. .

..... . .

.... ... .

I

DO YOU HAVE ANY TROUBLE; YES NC

REMOVAL OF DEBRIS AND CALCULUS

L

CHEWING STEAKS, CHOPS OR FIRM MEATS? ::::: ::::

GINGIVITIS TREATMENT BITING APPLES OR CORN-ON-THE-COB? .. .. . .. ..

. . .. .. ..

PERIODONTAL DISEASE TREATMENT BITING OR CHEWING ANY OTHER FOODS? . .. .. ::::

... ..

SEVERE MALOCCLUSION TREATMENT

01234

DECAYED PRIMARY TEETH

56789

.. . .

.

ONE-SURFACE FILLINGS ““””

.. TENS

. . .. .. .. . .. .

. . . . .. .. .---- ::::: UNITS ::::: ::::: ::::: ::::: ::::

. . . .. . .,: :----.. . .------ . .. . ..

. TENS

TWO-SURFACE FILLINGS

. . ... . ,:, : . .. . .. ..

. .. .. . .. .. ::::: UNITS ::::: ::::: :::=: ::::: z:::

THREE (OR MORE)- . . .. . TENS

SURFACE FILLINGS . . . . . . .. . .. .. . .. ..

. . . . . . ,:::: UNITS ::::: ::::: ,,,:: :::,: ::::

. . .... ....

. .... ..... ..... TENS

EXTRACTIONS

.. .. .

. . . ::::: UNITS ::::: ::::: ::::: ::=:: ::::

0 I 2 3

DECAYED PERMANENT TEETH . . .. .. .

.. .. . TENS

ONE-SURFACE FILLINGS

. .

. . . ::::: UNITS ::::: ::::: ::::: ::::: ::::

. .. .. .,,:, .. . . ... . TENS

TWO-SURFACE FILLINGS

. . . .. . .

::::: UNITS ::::: ::::: ::::: ::::: ::::

THREE (OR MORE)- . . .. . . ..

... . . TENS

SURFACE FILLINGS . . . .

. . . . . .. . UNITS ::::: ::::: ::::: ..::: ::::

..... .,::. ... ..... TENS

EXTRACTIONS

,,:. . . . .. . .

::4:: UNITS ::;: ::::: .:.::

. .... .;::

. . . . . . . . . .. ..

0 I 23 6789

.. . . . ..:, :

EXTRACTIONS, PERIODONTAL DISEASE TENS

EXTRACTIONS, OTHER

FIXED BRIDGES AND/OR PARTIAL DENTURES INDICATED

REPLACING TEETH NO.’S

UPPER ARCH

LOWER ARCH

NO. OF BRIDGES

NO. OF PARTIALS

REPAIR OR RELINE OF REPAIII

DENTURE OR BRIDGE RELINE

CONSTRUCT DENTURE(S)

::::: UNITS ::::: ::::: ::::: ::::: ::::

- ..-

. TENS

. . . .. . .

. . .. . . UNITS :::: :-::: ::::: ::::: ::::

::4,, ::&: :3-: ::*: :5, :5:: ::7:: :*:

:*: :/0: :=: :12: :13: :16: :15: ::8:

j:?: :t8: .!9: :W. :2!: :22: :23: *

,= :m: .n. ,= := :Sz ,Sk: :M,

.:1.: 2. ::3: ::&: :5: :*:

:.,:: :.*: ::s-: ,*: :*: :*,

F,U. :.- F.L. ::::: P.u. ::::: P.L. :,,::

F.U. ..:. F,L, ,,,,: P.u. ::.:: p.1. ,,:::

F.u. :::: FL. :::::

———

——

—

———

—

——

—————

———

—

————————

—

——

————

—

——————

——

—

—

J—

Figure 1. Dental examination form–Con.

82
2. A carious lesion at one of the margins of

the restoration had resulted in extensive

undermining of an enamel wall.

The periodontal index (PI)

Scores were assigned according to the following

criteria:

O– Negative. There is neither overt inflammation in

the investing tissues nor loss of function due to

destruction of supporting tissues.

1 – Mild gingivitis. There is an overt area of inflammation in the free gingivae but the area does not circumscribe the tooth.

2 – Gingivitis. Inflammation completely circumscribes

the tooth but there is no apparent break in the

epithelial attachment.

6 – Gingivitis with pocket formation. The epithelial

attachment has been broken, and there is a pocket

(not merely a deepened gingival crevice due to

swelling in the free gingivae). There is no interference with normal masticator function; the tooth

is firm in its socket and has not drifted.

8 – Advanced destruction with loss of masticator

function. The tooth may be loose; may have

drifted; may sound dull on percussion with a

metallic instrument.

RULE: When in doubt, assign the lesser score.

Each tooth present in the mouth, unless it was a root,

was scored, and the arithmetic average of all scores

was the individual’s PI.

The simplified oral hygiene index (OHI-S)

Selected surfaces of six teeth were used in making

this estimation of oral hygiene status. For the purposes of this examination each surface that was used,

buccal or lingual, was considered to encompass half

of the circumference of the tooth. The buccal surface

of a molar, for example, was considered to include

half of the mesial surface and half of the distal.

On both sides of the arch the posterior tooth

assessed was the most anterior, fully erupted permanent molar or, in its absence, the most distal fully

erupted primary molar. In most cases, this was a first

permanent molar; in other cases it was a fwst or

second primary molar or a second permanent molar.

The buccal surfaces of upper molars and the lingual

of lower molars were examined. In the anterior portion of the mouth, the labial surfaces of the upper

right central incisor and the lower left central incisor

were examined. When these teeth were missing, only

the adjacent central incisor was examined.

Examining for oral debris. –The surface area

covered by debris was estimated by running a No. 5

explorer along the surface being examined and noting

the occlusal or incisal extent of the debris as it was

removed from the tooth surface and adhered to the

explorer.

Scores were assigned according to the following

criteria:

O– No debris or stain present.

1 – (a) Soft debris covering not more than the gingival third of the tooth surface, or

(b) the presence of extrinsic stains without debris

regardless of surface area covered.

2 – Soft debris covering more than one-third but not

more than two-thirds of the exposed tooth

surface.

3 – Soft debris covering more than two-thirds of the

exposed tooth surface.

Examining for oral calculus. –A No. 5 explorer

was also used to estimate the surface area covered by

supragingival calculus and to probe for subgingival

calculus.

Scores were assigned according to the following

criteria:

O– No calculus present.

1 – Supragingival calculus covering not more than

one-third of the exposed tooth surface.

2 – Supragingival calculus covering more than onethird but not more than two-thirds of the exposed

tooth surface and/or the presence of individual

flecks of subgingival calculus around the cervical

portion of the tooth.

3 – Supragingival calculus covering more than twothirds of the exposed tooth surface and/or a continuous heavy band of subgingival calculus around

the cervical portion of the tooth.

Edentulous arches-denture status

No entry was made in this section unless at least

one arch was edentulous. An arch with erupted or

partly erupted teeth was considered edentulous if a

full denture was being used.

Absent. –No teeth (or roots) were present in the

arch and the examinee did not have a denture either

in the mouth or on his or her person at the time of

examination.

Present. –A denture was present in the mouth and

not defective at the time of examination.

Defective. –There was visible evidence that the

denture was causing extensive destruction of the primary stress-bearing areas of the ridge or palate. Tissue

in these areas may have been acutely inflamed; bone

resorption may have occurred, hyperthrophied tissue

may have been present. The denture was also defective if it was in the possession of the examinee at the

83
time of the examination but not in the mouth. If a

denture status code for either or both arches was

marked, the following should also be true:

A.

B.

c.

The spaces for the appropriate arch (or arches)

under Status of Tooth Spaces, Periodontal Index,

and Malaligned Teeth should be left blank.

The “NA” spaces for the appropriate arch (or

arches) under OHI should be marked.

The “NA” spaces under Opacities, Buccal Segment Relation, Posterior Crossbite, Incisor Relationship, and Handicapping Labio-Lingual Deviations (HLD) index should be marked.

Treatment needs

This estimate was based on the examiner’s clinical

judgment. Certain factors, however, should have been

kept in mind when it was decided whether missing

teeth ought to be replaced and when all remaining

teeth in an arch ought to be extracted and a full denture constructed. In addition to the status of oral

hygiene and periodontal disease, the examinee’s age,

responses to the questions about chewing and eating,

and the probable benefit of recommended service to

the individual’s health and nutrition were all taken

into account.

A “yes” or “no” was reported for each area of

need. Counts of the numbers of fillings and extractions needed were recorded when appropriate, and

teeth to be replaced by fixed bridges or partial dentures were indicated. The type of denture was marked

in the area provided for repair, reline, and construction of dentures.

The examiners

Each of the 20,218 sample persons who received

dental examinations during 1971-74 (and for whom

the dental records were available) was examined by

one of the 10 dentists. The dentists included two

senior examiners, 1 and 2, who trained and supervised

the other dentists, 3-10.

Sample persons were not assigned randomly or

equally among the various examiners. At most survey

locations they were examined by only one dentist–3,

4, 5, 6, 7, 8, 9, or 10. At 18 of 65 locations, however,

a small subsample was examined by either 1 or 2 or,

as occurred at 4 locations, by both 1 and 2. Thus, the

senior dentists examined relatively few sample persons. All dental records that were done at survey location number 54 were lost, and data for them had to

be imputed. Examiner number is unknown for these

records. The number and percent of persons examined

by each dentist (with records available) are as follows:

—

Dental Number of

Percent

distribution of

examiner sample persons

number

sample persons

examined examined

l-lo . . . . . . . . . . . . . .

1...............

2 . . . . . . . . . . . . . . .

3 . . . . . . . . . . . . . . .

4 . . . . . . . . . . . . . . .

5 . . . . . . . . . . . . . . .

6 . . . . . . . . . . . . . . .

7 . . . . . . . . . . . . . . .

8 . . . . . . . . . . . . . . .

20,218

285

1,220

255

2,137

2,193

2,368

1,646

2,986

9 . . . . . 5,011

lo: : : : : : ::::..... 2.117

100.00

1.4

6.0

1.3

10.6

10.8

11.7

8.1

14.8

24.8

10.5

Most examinations completed by the senior dentists resulted from a planned series of replicate examinations. As a rule, the findings of the senior dentist

were made part of the sample person’s examination

recorcl, and the findings of the dentist with whom the

examinee was paired were kept separate. The primary

aim of the replicate examinations was to correct any

examiner divergence from the accepted examination

procedures.

Throughout the replicate examinations, the senior

dentist completed the examination first and dictated

the findings to a trained recorder. After completing

the examination, the senior dentist recorded the findings of the other dentist, who had previously beqn

absent from the examining room. Appreciable interexaminer differences as well as any procedure that

diverged from the accepted one were discussed and, if

indicated, either resolved or corrected while the

sample person was still present. However, the findings

originally recorded were not altered. To indicate the

level of agreement among examiners, the results of

the replicate examinations are shown in table XVI.

The direction of the disagreements that occurred is

shown by a plus or minus sign. A plus sign indicates

that a finding of the senior dentist was lower than

that of another dentist, and a minus sign indicates

the opposite.

84
Table XVI. Percent distribution of differences in dental findings between senior dentists and other dentists on 360 replicate examinations:

National Health and Nutrition Examination Survey, 1971-74

Dental findings

All Differences observed in affected teeth

replicate

examinations 4or _3 _2 _, ~ ~, +2 +3 +4 or

more more

Percent distribution

Decayad, missing, and filled teeth . . . . . . . . . . . . . . . . . . . . 100.0 6.1 2.8 7.2 9.7 44.1 10.6 9.2 2.8 7.5

Decayed teeth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 3.1 2.5 7.5 13.6 56.4 10.8 3.3 1.4 1.4

Missingteeth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 5.0 0.8 2.8 5.3 63.3 10.0 4.2 2.8 5.8

Filledteeth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 0.6 0.3 2.2 7.2 69.2 13.6 3.9 1.9 1.1

85
Vital and Health Statistics series descriptions

SERIES 1.

SERIES 2.

SERIES 3.

SERIES 4.

SERIES 10.

SERIES 11.

SERIES 12.

SERIES 13.

Programs and Collection Procedural.-Reports describing

the gsneral programs of the National Canter for Health

Statistics and its offices and divisions and the data collection methods used. They also include definitions and

other material necessary for understanding the data.

Data Evaluation and Methods Research .-Studies of new

statistical methodology including experimental tests of

new survey methods, studies of vital statistics collection

methods, new analytical techniques, objective evaluations

of reliability of collected data, and contributions to statistical theory.

Analytical and Epidemiological Studies. –Reports presenting analytical or interpretive studies based on vital

and health statistics, carrying the analysis further than

the expository types of reports in the other series.

Documents and Committee Reports. -Final reports of

major committees concerned with vital and health statistics and documents such as recommended model vital

registration Iawsand revised birth and death certificates.

Data From the National Haakhlnterview Survey .–Statistics on illness, accidental injuries, disability, use of hospital, medical, dental, and other services, and other

health-related topics, all based on data collected in the

continuing national household interview surfey.

Data From the National Health Examination Survey and

tha National Hrnkh and Nutrition Examination Survey.–

Data from direct examination, testing, and measurement

of national samples of the civilian noninstitutiona lized

population provide the basis for (1) estimates of the

medically defined prevalence of specific diseases in the

United States and the distributions of the population

with respect to physical, physiological, and psychological characteristics and (2) analysis of relationships

among the various measurements without reference to

an explicit finite universe of persons.

Data From the Institutionalized Population Surveys. -Discontinued in 1975. Reports from these surveys are included in series 13.

Data on Health Resources Utilization. –Statistics on the

utilization of health manpower and facilities providing

SERIES 14.

SERIES 15.

SERIES 20.

SERIES 21.

SERIES 22.

SERIES 23.

long-term care, ambulatory care, hospital care, and timily

planning services.

Data on Health Resources: Manpower and Facilitias.–

Statistics on the numbers, geographic distribution, and

characteristics of health resources including physicians,

dentists, nursw, other health occupations, hospitals,

nursing homes, and outpatient facilities.

Date From Special Surveys.-Statistics on health and

health-related topics collected in special suweys that

are not a part of the continuing data systems of the

National Center for Health Statistics.

Date on Mortality .-Various statistics on mortality’ other

than as included in regular annual or monthly reports.

Special analyses by cauw of death, age, and other demographic variables; geographic and time series analyses;

and statistics on characteristics of deaths not available

from the vital records based on sample suweys of those

records.

Data on Nataiity, Marriage, and Divorce. –Various statistics on natality, marriage, and divorce other than as

included in regular annual or monthly reports. Special

analyses by demographic variables; geographic and time

series analyses; studies of fertility; and statistics on

characteristics of births not available from the vital

records based on sample surveys of those records.

Date From the National Mortality and Nasality Srsrveys.-

Discontinued in 1975. Reports from these sample suweys

based on vital records are included in Series 20 and 21,

respectively.

Data From the National Su wey of Famiiy Growth.–

Statistics on fertility, family formation and dissolution,

family planning, and related maternal and infant health

topics derived from a periodic survey of a nationwide

probability sample of ever-married women 1544 years

of age.

For a list of titles of reports published in these series, write to:

Scientific and Technical Information Branch

National Center for Health Statistics

Public Health Sawice

Hyattsville, Md. 20782
U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Public Health Service

Office of Health Research, Statistics, and Technology

National Center for Health Statistics

3700 East-West Highway

Hyattsville, Maryland 20782

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for listings of publications in the VITAL AND HEALTH STATISTICS series, call 301-436-NCHS