Vital and

HealthStatistics

Advance Data

From Vital and

Health Statistics:

Numbers 231–240

Series 16:

Compilations of Advance Data

From Vital and Health Statistics

No. 24

Data in this report from health and demographic surveys present statistics by age

and other variables on firearm mortality among people 1-34 years old, drug

utilization in medical office practice, office visits to urologists, home health and

hospice care, negative moods as correlates of smoking and heavier drinking,

office visits to psychiatrists, HIV antibody testing in women, AIDS-related behavior

among women, and office visits to dermatologists, Estimates are based on the

civilian noninstitutionalized population of the United States, These reports were

originally published in 1993, Number 233 was never released.

US, DEPARTMENT OF HEALTH AND HUMAN SERVICES

Public Health Service

Centers for Disease Control and Prevention

National Center for Health Statistics

July 1995

DHHS Publlcatlon No. (PHS) 95-1883
.... . ..—

copyright Informsnon

All material appearing in tlis report is in the public domain and may be

reproduced or mpiad without perrniaaiorx citation as to source, howaver, is

appmrciatad.

National Center for Health Stat&x. Advanca data from vital and health

statiaticq numbers 231 –240. National Center for Health Statistics. Vtal Health

Stat 16(24). 1995.
National Center for Health Statistics

Jack R. Anderson, Acting Director

Jennifer H. Madans, Ph.D., Acting Deputy Director

Jacob J. Feldman, Ph.D., Associate Director for AnaZysi.s,

Epidemwlogy and Health Promotion

Gail F. Fisher, Ph.D., Associate Director for Planning and

Extramural Programs

Peter L. Hurley, Associate Director for Wtal and Health

Statistics Systems

(Vacant), Associate Director for International Statistics

Stephen E. Nieberding, Associate Director for

Management

Charles J. Rothwell, Associate Director for Data

Processing and Services

Monroe G. Sirken, Ph.D., Associate Director for Research

and Methodology
Firearm Mortality Among Children, Youth, and Young Adults 1-34 Years of Age, Trends and Current Status

United States, 1985-90 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . No. 231

Drug Utilization in Office Practice: National Ambulatory Medical Care Survey, 1990 . . . . . . . . . . . . . . . . . . . . . . . . . . . No. 232

Office Vkits to Urologists 1989-90, National Ambulatory Medical Care Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . No. 234

Overview of Home Health and Hospice Care Patients Preliminary Data from the 1992 National Home and

Hospice Care Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . No. 235

Negative Moods as Correlates of Smoking and Heavier Drinking: Implications for Health Promotion . . . . . . . . . . . . . . No. 236

Office Visits to Psychiatrists: United States, 1989-90 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . No. 237

Human Immunodeficiency Virus Antibody Testing in Women 15-44 Years of Agtx United States, 1990 . . . . . . . . . . . . . No. 238

AIDS-Related Behavior Among Women 15-44 Years of Age: United States, 1988 and 1990 . . . . . . . . . . . . . . . . . . . . . . No. 239

Office Visits to Dermatologists: National Ambulatory Medical Care Survey, United States, 1989-90 . . . . . . . . . . . . . . . No. 240
Number 231 ● March 23, 1993

Advance

Data

From Vi and Health Statiq”csof the CENTERS FOR DISEASE CONTROL AND PREVENTION/National Center for Health Statistks

Firearm Mortality Among Children, Youth, and Young Adults

1-34 Years of Age, Trends and Current Status:

United States, 1985-90

by Lois A. Fingerhut, M.A., Division of Analysis

Introduction

A previous report released by the

National Center for Health Statistics

(NCHS) documented the level of

firearm mortality among childre%

youth, and young adults 1–34 years of

age from 1979 through 1988 (l). The

purpose of this report is to revise the

1985-88 data using newly available

intercensal population estimates and

to update the report with data

through 1990. Emphases are on race

and sex diEerences in homicide and

suicide associated with firearms

among males 15–34 years of age.

This report will be limited to data

for the period 1985 through 1990

because it was during the second

half of the decade that firearm

mortality increased for the younger

population (l).

Methods

Firearm death rates for 1985-89

are based upon intercensal rather

than the postcensal population

estimates used in the previous report.

Both sets of estimates were provided

by the Bureau of the Census.

Intercensal population estimates are

preferred to postcensal estimates

because they are consistent with the

1980 and 1990 decennial Census

enumerations, and thus, form a

continuous series over the decade (2).

The relative difference between the

two estimates, the error of closure, is

equivalent to the relative difference in

death rates based on the two

estimates. The error of closure was

larger for persons 18-24 yeara of age

than for any other age group.

However, the error of closure was not

so large that death rates for either

the black or the white populations

ages 1–34 were significantly affected.

Death rates for 1990 are based on

postcensal estimates of the July 1,

1990, population.

In previous reports on ilrearm

mortality (1,3), the definitions of

firearm homicide excluded legal

intervention by firearm. In this repo~

as in others (4#), the definition has

been amended to include those

deaths. The inclusion of these deaths

results in an increase in the overall

firearm death rate and the firearm

homicide rate with a concomitant

decrease in the nordirearm homicide

rate—all by relatively small amounts

(see appendix table I). For example,

adding in deaths coded to legal

intervention by a firearm to other

iirearm homicides among black and

white males 2G24 years of age

increased their respective firearm

homicide rates by 1 percent and

3 percent.

Current status

In 1990, 19,722 pxsons 1–34

years of age died as a result of a

firearm injury. This represented 17.6

percent of all deaths at those ages.

Among young chiIdren 10-14 years of

age, 560 died from a tirearm injury,

accounting for 1 out of every 8

deaths. Among teenagers 15-19 years

and young adults 20-24 years, 1 of

every 4 deaths were by firearm, and

for adults 25-34 years, 1 of 6 deaths

were by tirearm (figure 1).

Within these age groups,

variation by race and sex in the

p=mentage of all deaths due to

firearms is large. For example,

60 percent of deaths among black

teenage males 15-19 years old

resulted from a firearm injury

compared with 23 percent of deaths

among white teenage males. Among

females 15-19 years old, 22 percent

of deaths among black females

~*SEwms,o

&

$

%

$

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Public Heatth Service $ Centers for Disease Control and Prevention ?5%

>%%na National Center for Heafth Statistics —-’T!R Cm_
2 Advance Data No. 231 ● March 23, 1993

2a.e%

60

50

40

20

10

0

1-4 s-9 10-14 1s-19 20-24

*in years

NoTr3Tualp3KafR(atkQorbm8) lndudm-~-=w-.

Figure 1. Percent of deaths due to firearms for persons 1-34 years of age, by age, race,

an-d sex United States, 1990

resulted from firearms compared with

10 percent of deaths among white

females. By ages 25-34, the

proportion of deaths due to firearms

decreased for each race-sex group.

Fkearms were the cause of death for

25 percent of deaths among black

males, 16 percent among white males,

and 9 percent among black and white

females in this age group (figure 1).

Another way to look at the

differential impact of firearm

mortality on the population is to

focus on violent deaths (homicides

and suicides) that result from

firearms. The majority of homicides

among teenagers and young adults

15–34 years of age resulted from the

use of firearms. In 1990, 82 percent of

homicides among teenagers 15-19

years of age were associated with

firearms (91 and 77 percent among

black and white males, respectively);

at 20-24 years of age, 76 percent of

homicides were from firearms (87 and

71 percent among black and white

males, respectively); and at 25-34

years of age, 69 percent of homicides

(75 and 72 percent among black and

white males, respectively) were

caused by firearms. Proportions of

homicides due to firearms among

females were lower than among males

for both races and in each age group

(table 1).

The age-specific proportions of

suicides resulting from firearms were

lower than the proportions of

homicides, aver~gi~g 58-67 percent of

suicides at 15-19 years of age through

25-34 years of age. Differences by

race were smaller than for homicide,

and proportions for females were also

lower than for males (table 1).

Analysis of firearm death rates by

age, race, and sex, as well as by

manner of death facilitates the

assessment of relative levels of risk

associated with firearm fatalities

across demographic categories as well

as over time. Firearm death rates rise

until the young adult years and then

decline. In 1990, the firearm death

rate per 100,000 increased from

0.6-0.7 per 100,000 population at ages

1-4 and 5-9 years, to 3.3 at ages

10-14, to 23.5 at ages 15-19, peaking

at 28.1 at 20-24 years and declin~ing

to 21.8 at ages 25-34 years (figure 2),

Firearm death rates for 1990 are

shown in table 2 and numbers of

firearm deaths are shown in table 3.

Firearm death rates vary by race

and sex within age groups. For the

younger children, those 1-9 years of

age, rates for black children were

higher than for white children.

Because the firearm death rates at

those ages are based on small

numbers of deaths (fewer than 50 for

each race-sex group), relative

differences by sex are often not

significant. At ages 10-14 years,

firearm death rates are highest for

black males; 10.2 per 100,000, which

is more than twice the rates for white

males and black females and 10 times

the rate for white females. At ages

15-19 and 20-24 years, firearm death

rates were also highest for black

males, 119.9 and 157.6 per 100,IIIOO,

respectively. The age-specific rates for

these black males were 5 times the

respective rates by age for white

males and 10 to 11 times the agespecific rates for black females. At

ages 25-34 years the firearm death

rate for black males, 108.5 per

100,000, was 4 times the rate for

white males and 7 times the rate for

black females. The firearm deatlh

rates for white females 15-19 through

25-34 years were lower (about 5 per

100,000) than for any other race-sex

group.

Race and sex differences in

firearm mortaliq vary by manner of

death as well. For young children

ages 1-4 and 5-9 years firearm

homicide rates among black children

were higher than rates for white

children, while there were no

significant race differences in

unintentional firearm mortality. For

these young children, race and sex

specific death rates for both firearm

homicide and unintentional firearm

mortality were generally less than 1

per 100,000.
Advance Data No. 231 ● March 23, 1992 3

+ All firearm deaths ‘o- f%earm homioide

‘r +- Firearm 5u”* + Unintenthml firearm

2s

20

15

10

s

*-. o

-.

1-4 S9 10-14 1s-1s 20-24

*in years

Figure 2. Firearm death rates by manner of death and age, for persons aged 1-34 yearw

United States, 1990

At ages 10-14 years, there were

significant differences in the firearm

homicide rates by race as well as by

sex. The firearm homicide rate for

black males 10-14 years of age was

more than 5 times the rate for white

males (6.9 compared with 1.3 deaths

per 100,000) and the rate for black

females was close to 8 times the rate

for white females (3.1 compared with

0.4 per 100,000). Differences in

firearm homicide by sex were smaIler,

with rates for white and bIack maIes 2

to 3 times those for females. While

there were no differences by race in

firearm suicide or unintentional

firearm mortaiity at 10-14 years,

those rates were higher for males

than for females (table 4).

Firearm homicide for black males

15-19 years of age was 11 times the

rate among white males, 105.3

compared with 9.7 per 100,000

population. The rate for black

females was five times the rate for

white females, 10.4 compared with 2.0

per 100,000. Thus, the firearm

homicide rate for white males was

about 5 times that for white females

and the rate for black males about 10

times that for black females. Firearm

homicide rates for both white and

black maIes and females ages 20-24

years were about 1.2 to 1.3 times the

respective rates at ages 15-19 years.

Mortality race and sex ratios at 20-24

years were generally similar to those

at ages 15-19 years (table 4).

Among males ages 25-34 years,

race differences in firearm homicide

rates were smaIIer than for persons

20-24 years of age. The rate for bIack

males was 9 times the rate for white

males (94.4 compared with 10.8 per

100,000). Firearm homicide rates for

males were 5 to 7 times those for

females (table 4).

Firearm suicide, unlike homicide,

was higher for white males than for

bIack males at ages 15–19 through

25-34 years, although race differences

were considerably smaller than for

firearm homicide. For example, the

firearm suicide rate for white maIes

15-19 years was 1.5 times the rate for

black males, 13.5 compared with 8.8

per 100,000 population. With

increasing age, the race ratio

decreased. Sex differences for both

white and black persons in firearm

suicide rates were much larger than

race differences, with rates for white

and black males 5 to 10 times the

rates for femaIes at ages 15-19

through 25-34 years (table 4).

Trends (tables 2 and 3)

Consistent with earIier patterns

(l), there was virtuaHy no change

from 1985 to 1990 in the overall

firearm death rate among young

children 14 or 5-9 years of age. For

children ages 10-14 years, however,

the firearm death rate increased 18

percent from 1985 to 1990, reaching a

rate of 3.3 deaths per 100,000.

hong black males 10-14 years, the

firearm death rate more than doubled

from 1985 to 1990. Increases were

lar~est for firearm homicide; the rate

rose from 3.0 to 6.9 per 100,000.

There was also an increase in the rate

for black females in this age group;

the firearm death rate in 1990 was

more than twice what it was in 1986

and 1987 (3.7 compared with 1.4 to

1.7 per 100,000). Again, increases

were largest for firearm homicide.

The total firearm death rate

among teenagers 15-19 years of age

increased 77 percent from 1985

through 1990, to 23.5 deaths per

100,000, its highest IeveI to date.

Fireaxm death rates increased for all

four race-sex groups, with the largest

increases noted for bIack males. The

firearm death rate for bIack males

15-19 years of age more than

doubled, rising from 46.5 per 100,000

in 1985 to 119.9 per 100,000 in 1990

(figure 3). From 1985 through 1990,

the bIack teenage male firearm

homicide rate nearly tripled, rising to

105.3 per 100,000 (figure 4). At the

same time, the firearm homicide rate

for white males and black females

doubIed, rising to 9.7 and 10.4 per

100,000, respectively. While the

firearm suicide rate among black

teenage males was less than a tenth

the magnitude of the firearm

homicide rate, it increased 63 percent

from 1985 to 1990 to 8.8 per 100,000.

A far smaller increase (25 percent)

was noted for the firearm suicide rate

for white teenage males (figure 4).

Among black females 15-19 years old,

the firearm homicide rate doubled
4 Advance Data No. 231 ● March 23, 1993

~ Firearm, black male — Natural causes, black mate

‘r

-+- Firesnn, white mala ---- Naduralcausas, Whii mate

10 J ~ Q , u * 1

19ss 19ss 19s7 19aa 18s9 1s90

Year

Figure 3. Deaths rates for natural causes and firearm injuries, for males aged 15-19

years: United States, 198S-90

from 1985 to 1990, reaching 10.4 per

100,000.

hong males 15-19 years of age,

the nonfirearm homicide rate

averaged 9 to 11 per 100,000 for

black teenagers and 2 to 3 per

100,000 for white teenagers during

the period 1985-90. It is interesting

that although the nonfirearm

homicide rate increased from 1989 to

1990 for both white and black males,

the firearm homicide rates for white

and black males were still 3 and 10

times the respective nonfireann

homicide rates. Nonfirearm suicide

rates likewise showed little change

during 1985-90 with rates averaging 6

per 100,000 for white male teenagers

and 3 per 100,000 for black male

teenagers (figure 4). Rates for

females were also unchanged.

It was previously reported (1)

that 1988 was the first year in which

the firearm death rate for teenagers

(15-19 years) exceeded the death rate

associated with natural causes of

death. That trend has continued; in

1990, among all teenagers 15-19

years, there were 39 percent more

deaths from firearms than from

natural causes of death. Driving that

trend has been the rising rate for

firearm mortality among white

teenage males 15-19 years. For white

teenage males 15-19 years, the

natural cause death rate remained

relatively unchanged at 18 to 19 per

100,000 and the firearm death rate

increased from 21.4 per 100,000 in

1988 to 26.5 per 100,000 in 1990

(figure 3). Thus, the ratio of firearm

to natural causes mortality among

white teenage males 15-19 years

increased from 1.1:1 in 1988 to 1.3:1

in 1989 to 1.4:1 in 1990. Among black

males, that trend has also continued.

From 1988 to 1990, the natural cause

death rate declined 12 percent while

the firearm death rate increased 48

percent. Whereas in 1988, the firearm

death rate among black teenage

males was 2.8 times the natural cause

death rate, by 1990 the firearm death

rate was 4.7 times the rate for natural

causes.

The firearm death rate among

persons 20-24 years of age was 36

percent higher in 1990 than in 1985;

virtually all of the increase was a

result of increases in firearm

homicide among black males (figure

5). The firearm homicide rate more

than doubled in this group reaching

140.7 per 100,000, its highest level

ever. (The previous high was in 1972.)

Among white males ages 20-24 years,

increases in firearm mortality were far

more modest, with the firearm

homicide rate in 199032 percent

higher than what it was in 1985.

Increases in firearm suicide were also

minimal (figure 5). Among white

females ages 20-24 years, the firearm

death rate hovered around 5 per

100,000 for 1985 through 1990. For

black females, the firearm death rate

increased from 1985 to 1990

(although it was unchanged from

1989 to 1990) as a result of an

increase in the firearm homicide rate.

The firearm homicide rate for

white males 20-24 years remained

about twice the nonfirearm homicide

rate. Similar to the recent trend

among those 15-19 years, the

nonfirearm rate for those 20-24 :years

increased from 1989 to 1990. The

nonfirearm homicide rate for black

males was unchanged from 1985 to

1990 at about 22-23 per 100,000. The

firearm suicide rate for white males

remained close to twice the

nonfirearm suicide rate (figure 5).

By ages 25-34 years, the upward

trend in age-specific firearm mortality

slowed considerably. The firearm

death rate in 1990 was only 13

percent higher than in 1985, with.

the largest increase again noted in

firearm homicide among black males

(a 40 percent increase from 1985 to

1990). There was relatively little

change in the nonfirearm homicide

and nonfirearm suicide rates

(figure 6).

Discussion

Sixty percent of all deaths among

persons 1-34 years of age resulted

from unintentional and intentional

injuries in 1990, and about 30 percent

of those external deaths were fro]m

firearms. To compile the standard

cause-of-death rankings for persons 1

year of age and older, NCHS uses the

“List of 72 Selected Causes of Death

and HIV Infection” (6). However,

this ranking system is not particularly
Advance Data No. 231 ● March 23, 1992 5

200

100

50

20

10

5

2

1

i 1 P * * 1

1 I

* * I * [ 1

Im

50

20

10

5

2

_— _ /——”

* r.

f.%r”~

0“ . . . . . . . . . ...”” -

- - -..s. .

2“ -.:...... -* ----

——— ——— —

. . .

. . . ...*”*... ..O< .,....=

“:-. :. :...; . ...” “ *

. . *

---- e

-----. *

W&5 19e8 1987 1988 1s89 19s0 1s85 1988 1s87 1W8 1989 1990

Yesr %er

Figure 4, Homicide and suicide rates by firearm status for white and biack maies, aged 15-19 years: United States, 1985-80

100

50

20

10

5

2

1

— Horniie, black male ----l+omiie. whiimaia ------- Suicida, b&dtnrs)a —- Sukida,* rnda

Firearm

50

I r I r r t

——_ —-

.C. . . . ..”.*.... ●. . .

. .

.,. .

:“W.-.:. :.:. ?.V.V.- - - - -

----

1985 19s8 1987 1988 1989 1990

Year

20

10

5

2

1

Nontiresrm

——— ~ ——.

. . . . . . ..

.. . . .. . . ...”” ..*

. .

. . . . . . . . . . . . . . . . . .

------- **”

------- -.---

I I I I t 1

198.5 lW 1S87 1s88 1989 19S0

Year

gure 5. Homicide and suicide rates by firearm status for white and biack maies, aged 20-24 years: United States, 1985-90
6 Advance Data No. 231 ● March 23, 1993

— Homicide,black male -- - - Homiekte, whii male ..-- . . . Suiiide, black male — - S@J*, ** ~~

200 Firearm

2oo -

Nonfirearm

‘m i~ ‘“ !

c

!50 60 -

0

=m

3

i

v “_______

20

$

. . . . . . . . . . . . . . . . . . . .

. . ..””””... . . . . . . . . . . . . ——

------- ---

5 ‘0

--------- 10 -~

~..~ .

---

. . . . . . . . . . . . . . . . . . . . . . . . . . . . w

In

j5 - 5 -------

------- ------- -

2 2 -

1

1 I I I t I 1

8 1 I 1 I 1

19a5 1966 1967 1966 1989 1990 19a6 1966 1967 1966 19a6 1990

Year Year

Figure 6. Homicide and suicide rates by f}rearm status for white and black males, aged 25-34 years: United States, 1986-90

appropriate for persons 1–34 years of

age because it does not itemize

specific causes of unintentional

injuries, such as firearm injuries,

motor vehicle injuries, fires and

burns, and drowning. (They are

counted in the “List of 72...” within

the category “accidents and adverse

effects”.) Neither does the “List of

72” ranking specifi intentional injury

firearm deaths (which are counted in

the categories homicide and suicide).

In order to put firearms as a cause of

death into perspective, causes of

death for children, teenagers, and

young adults have been reordered in

an alternative ranking scheme that

includes detailed causes of injury.

Based on this new ranking,

firearms are the second leading cause

of death (after motor vehicle injury

fatalities) for children 10-14 years of

age, teenagers 15–19 years of age,

and young adults 20-24 years and

25-34 years of age. For persons 15-19

and 20-24 years of age, firearm

homicide as an individual category of

death was second only to motor

vehicle deaths. For persons 25-34

years of age, there were 11 percent

more deaths from firearms than from

HIV infection (table 5).

hong black males, firearm

injuries were the leading cause of

death among children 10-14 through

adults 25-34 years of age. For

children 10-14 years, firearms were

responsible for 30 percent more

deaths than motor vehicle injuries.

For black males 15-19 through 20-24

years, firearm homicide was the single

leading cause of death, with more

than 3 times the number of motor

vehicle deaths. Firearm homicide was

also the leading cause of death at

ages 25-34 years, with 12 percent

more deaths than from HIV infection.

(Data available upon request.)

The firearm homicide rates

among young persons 15–19 and

20-24 years continue to increase and

the rates of increase have recently

worsened for white males. For young

black males 15-19 and 20-24 years of

age, the average annual increases in

firearm homicide of 20 percent and

15 percent, respectively, observed

from 1985 to 1988 remained

unchanged through 1988 to 1990. For

white males 15-19 years, the firearm

homicide rate increased an average of

4 percent per year from 1985 through

1988 and remained unchanged for

those 20-24 years, whereas the

firearm homicide rate increased at

average annual rates of 24 percent

and 12 percent for white males 15-19

and 20-24 years, respectively, from

1988 through 1990. Not only is

progress not being made in reducing

the rate of increase in firearm

homicide for these young black males,

but attention must also be paid to

increasing firearm homicide rates

among young white males.

References

1. Fingerhut LA, Kleinman JC,

Godfrey E, and Rosenberg H.

Firearm mortality among children,

youth, and young adults 1-34 years

of age, trends and current status:

United States, 1979-88. Monthly

Vital Statistics Report; vol 39 no

11 suppl. Hyattsville, Maryland:

National Center for Health

Statistics. 1991.
Advance Data No. 231 ● March23, 1993 7

2.

3.

4.

5.

6.

7.

U.S. Bureau of Census. U.S.

population estimates, by age, sex,

race, and Hispanic origim 1980-91.

Series P-25, No. 1095 Advance

Report. 1993.

Fingerhut LA and IUeinman JC.

Firearm mortality among children

and youth. Advance data from

vital and health statistiw, no 178.

Hyattsville, Maryland National

Center for Health Statistics. 1989.

Fingerhut L& Ingram DD,

Feldman JJ. Fkearm and

nordirearm homicide among

persons 15-19 years of age:

Differences by level of

urbanization, United States,

1979-1989. JAMA 2623048-53.

1992.

Fingerhut L& Ingram DD,

Feldman JJ. Firearm homicide

among black teenage maies in

metropolitan counties, United

States 1983-85 to 1987-89. JAMA

26?3054-58. 1992.

National Center for Health

Statistics. Advance report of finai

mortaiity statistics, 1990. Monthiy

vital statistics repofi, vol 41 no 7

suppl. Hyattaville, Maryland

Public Health Service. 1993.

World Health Organization.

Manuai of the International

Statistical Ciasstieation of

Diseases, Injuries, and Causes of

Death, based on the

recommendations of the Ninth

Revkion Conference, 1975.

Geneva: World Heaith

Organization. 1977.

Table 1. Percent of homicides and suicides resulting from firearms by age, raae, and sex

for persons 10-34 years of agw United States, 1990

White Bkrelr

Age Total Male Female Male Female

Pereantof all homicidesdue to firearms

10-14 yeara. . . . . . . . . . . . . . . 72.5 ao.3 45.2 85.2 66.1

15-19 yeara. . . . . . . . . . . . . . . 81.7 76.7 54.8 90.9 67.0

20-24 yesr5 . . . . . . . . . . . . . . . 75.9 70.8 50.6 86.7 56.0

25-34 yeara . . . . . . . . . . . . . . . 69.1 71.8 54.5 75.4 50.1

Pereant of all auicidasdue to firearms

10-14 yeara . . . . . . . . . . . . . . . 65.0 53.7 56.1 71.4 62.5

15-19 years . . . . . . . . . . . . . . . 67.3 69.4 57.3 76.4 65.4

20-24 years. . . . . . . . . . . . . . . 83.4 65.2 54.2 69.2 51.4

25-34 yeara. . . . . . . . . . . . . . . 57.6 61.1 46.9 55.9 38.0

Nota Total includes races not shown separately.
Advance Data No. 231 ● March 23.1993 ,

Table 2. Death rates due to firearms and nortfirearms by manner of death (homicide, suicide, and unintentional injury), by age, race, and

sex for persons 1-34 years of age: United States, 1965-90

Age, race, and sex 1985 1986 1987 1988 1989 1990

1-4 yeara of age

Total . . . . . . . . . . . . . . . . . . .

Whte male . . . . . . . . . . . . . . .

Whtefemale . . . . . . . . . . . . . .

Black male . . . . . . . . . . . . . . . .

Black female . . . . . . . . . . . . . .

5-9 yeara of age

Total . . . . . . . . . . . . . . . . . . .

White male . . . . . . . . . . . . . . .

White female . . . . . . . . . . . . . .

Black male . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

10-14 years of age

Total . . . . . . . . . . . . . . . . . . .

Whitemale . . . . . . . . . . . . . . .

Whifefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

15-19 years of age

ToteI . . . . . . . . . . . . . . . . . . .

Whitemale . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

20-24 yeare of age

Total . . . . . . . . . . . . . . . . . . .

Whtiemale . . . . . . . . . . . . . . .

Whiiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . .

25-34 yeare of age

Total . . . . . . . . . . . . . . . . . . .

Whiiamale . . . . . . . . . . . . . . .

Whitefemaie . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

1-4 yeara of age

Total . . . . . . . . . . . . . . . . . . .

Whte male . . . . . . . . . . . . . . .

Whfiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

5-9 yeara of age

Total . . . . . . . . . . . . . . . . . . .

White male . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmele . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

0.7

0.6

0.5

2.2

0.9

0.7

0.9

0.4

0.9

1.3

2.8

4.5

1.0

4.8

0.7

13.3

18.4

3.5

46.5

6.1

20.6

29.1

5.2

76.1

10.2

19.3

26.3

5.7

79.6

12.8

0.4

0.3

0.2

1.1

0.7

0.3

0.4

0.2

0.5

1.0

0.6

0.5

0.4

1.9

0.9

0.6

0.7

0.3

1.2

1.3

2.7

4.4

1.0

4.9

1.7

14.4

20.1

3.7

49.7

7.9

22.9

30.6

5.7

94.7

12.0

20.4

27.0

5.5

93.1

13.8

0.4

0.2

0.2

1.4

0.6

0.3

0.3

0.1

0.6

0.8

Firearm deaths per 100,000 population

0.5 0.6

0.5 0.6

0.3 0.4

1.6 1.8

0.8 0.9

0.7 0.7

0.9 0.7

0.4 0.4

1.6 2.0

0.6 0.9

3.0 3.2

4.3 4.2

1.1 1.1

7.1 8.1

1.4 3.7

14.5 17.5

16.7 21.4

3.3 3.7

56.8 80.9

9.1 6.5

22.6 23.5

28.7 29.0

5.2 4.5

103.4 117.6

13.9 13.6

19.4 20.4

25.6 26.0

5.6 5.5

64.6 97.1

14.0 14.7

Firearm homicides per 100,000 population

0.3 0.3

0.2 0.3

0.2 0.2

0.6 1.1

0.7 0.6

0.3

0.4

0.2

0.7

0.4

0.4

0.3

0.3

1.2

0.7

0.7

0.7

0.4

1.7

1.2

0.8

0.8

0.4

1.6

0.9

3.3

4.6

1.0

9.4

2.4

19.6

23.1

4.1

96.2

9.7

25.1

29.7

4.6

133.2

15.4

20.4

26.2

5.2

98.6

13.2

0.5

0.4

0.3

1.0

0.6

0.4

0.3

0.4

1.0

0.7

0.6

0.6

0.3

1.2

1.1

0.7

0.6

0.4

1.5

1.2

3.3

4.2

1.0

10.2

3.7

23.5

26.5

4.6

t 19.9

12.2

28.1

32.5

4.9

i 57.6

14.4

21.6

27.8

5.5

106.5

14.6

0.4

0.4

0.2

0.8

0.9

0.3

0.2

0.3

1.0

0.9
Advance Data No. 231 ● March 23, 1993 9

Table 2. Death rates due to firearms and nonflrearms by manner of death (homicide, suic~,e, and unintentional injury), by age, race, and

sex for persons 1-34 years of agw United States, 19B5+0-Con.

Age, race, and sex 1985 1988 1987 1888 1989 19W

10-14 years of age

Total . . . . . . . . . . . . . . . . . . .

Whiiernale . . . . . . . . . . . . . . .

Whtefemale . . . . . . . . . . . . . .

Black male . . . . . . . . . . . . . . . .

Black female . . . . . . . . . . . . . .

15-19 years of age

Tonal . . . . . . . . . . . . . . . . . . .

VMemale.. . . . . . . . . . . . . .

Whiiefemale . . . . . . . . . . . . . .

Black male . . . . . . . . . . . . . . . .

Black female . . . . . . . . . . . . . .

20-24 years of age

Total . . . . . . . . . . . . . . . . . . .

Whiie male . . . . . . . . . . . . . . .

Whifiefemale . . . . . . . . . . . . . .

Black male . . . . . . . . . . . . . . . .

Black femele . . . . . . . . . . . . . .

25-34 years of age

Total . . . . . . . . . . . . . . . . . . .

Whiie male . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

10-14 years of age

Tonal . . . . . . . . . . . . . . . . . . .

Whtemale . . . . . . . . . . . . . . .

Whiiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blsckfemale . . . . . . . . . . . . . .

16-19yearsofage

Total . . . . . . . . . . . . . . . . . . .

Whiiemale . . . . . . . . . . . . . . .

Whiiefemale . . . . . . . . . . . . . .

BkackmsIe. . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

20-24 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtemale . . . . . . . . . . . . . . .

Whfefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

26-34 years of age

Total . . . . . . . . . . . . . . . . . . .

Whiiemale . . . . . . . . . . . . . . .

Whiefemde . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

0.8

0.9

0.4

3.0

o.e

5.8

5.0

1.2

37.4

5.0

9.9

9.8

2.2

63.1

8.8

9.8

9.5

2.5

87.3

10.7

0.8

1.5

0.4

0.5

0.0

6.0

10.8

2.0

5.4

0.7

9.2

18.8

2.7

10.5

1.4

8.4

15.0

2.9

10.2

1.5

0.9

1.0

0.4

3.4

1.0

6.8

5.8

1.5

42.2

6.6

12.1

11.0

2.4

82.5

10.6

10.8

10.2

2.3

79.4

11.6

0.9

1.5

0.4

0.8

0.2

6.1

11.6

1.8

4.7

1.0

9.4

17.2

2.9

9.9

1.0

8.6

15.2

2.9

11.3

1.7

l%eamhomicid~ per100,0OOppMian

1.1 1.1

0.8 0.9

0.4 0.4

5.3 4.7

1.1 2.6

7.0 9.0

5.2 6.0

1.2 1.3

50.1 69.2

7.3 7.2

12.4 13.2

10.2 10.1

2.3 2.3

90.4 102.5

12.1 11.8

10.0 11.0

9.3 9.5

2.4 2.4

71.2 62.4

11.8 12.7

Fireermsa-kMespar 100,OOOWJPUI*

0.9 0.8

1.7 1.2

0.4 0.4

0.5 0.7

0.1 0.4

6.0 6.8

10.9 12.4

1.9 2.2

6.4 6.6

1.3 0.9

6.9 8.9

16.3 16.6

2.5 1.9

10.0 12.0

1.1 1.5

8.5

15.0

2.8

11.5

1.7

8.6

15.2

28

12.4

1.5

1.4

1.2

0.4

6.8

1.8

11.1

7.5

1.7

65.5

8.7

14.5

11.1

2.2

113.7

13.1

11.2

9.8

2.3

66.3

11.7

0.8

1.4

0.3

0.8

0.2

e.8

12.5

2.1

7.3

0.7

9.2

16.5

22

14.6

1.8

8.4

15.0

2.7

11.5

1.3

1.5

1.3

0.4

6.9

3.1

14.0

9.7

2.0

105.3

10.4

17.1

12.9

2.3

140.7

124

12.2

10.8

2.4

94.4

12.7

0.8

1.2

0.5

1.1

0.4

7.5

13.5

23

8.8

1.3

9.6

17.5

2.4

13.2

1.3

8.7

15.6

29

12.2

1.4
10 Advance Data No. 231 ● March 23, 1993

Table 2. Death rates due to firearms and nonfkaarms by manner of death (homicide, suicide, and unintentional Injury), by age, race, and

sex for persons 1-34 years of age: United States, lW5-90-Con.

Age, race, srrd sax 1985 1988 1987 1988 1989 1990

l-l yeara of age

Total . . . . . . . . . . . . . . . . . . .

White male . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

5-9 yeara of age

Total . . . . . . . . . . . . . . . . . . .

Whiiemale . . . . . . . . . . . . . . .

Whiiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

10-14 years of age

Total . . . . . . . . . . . . . . . . . . .

Whitemale . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

15-19 years of age

Total . . . . . . . . . . . . . . . . . . .

Whdemale . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . .

B[ackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

20-24 yaars of age

Total . . . . . . . . . . . . . . . . . . .

Whiemale . . . . . . . . . . . . . . .

Whtefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemele . . . . . . . . . . . . . .

25-34 years of age

Total . . . . . . . . . . . . . . . . . . .

Whitemale . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

14 yeara of age

Total . . . . . . . . . . . . . . . . . . .

Whtemale . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

5-9 years of age

Total . . . . . . . . . . . . . . . . . . .

White male . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

0.3

0.3

0.2

1.0

0.2

0.3

0.5

0.2

0.3

0.3

1.0

2.0

0.2

1.2

0.1

1.3

2.1

0.2

3.3

0.4

1.1

1.9

0.2

1.9

0.1

0.8

f .3

0.2

1.8

0.4

2.1

1.6

1.4

5.4

5.6

0.7

0.3

0.5

1.9

1.4

0.2

0.2

0.1

0.5

0.4

0.3

0.4

0.1

0.6

0.5

0.9

1.7

0.2

0.6

0.4

1.3

2.2

0.3

2.2

0.2

1.0

1.7

0.2

2.0

0.3

0.7

1.2

0.2

1.7

0.3

2.3

1.7

1.2

8.1

6.3

0.5

0.2

0.3

1.4

1.9

Unintentional firearm deathe per 100,000 population

0.3 0.3

0.3 0.3

0.1 0.1

0.7 0.7

0.1 0.3

0.4 0.3

0.5 0.4

0.2 0.1

0.8 0.8

0.2 0.1

0.9 1.1

1.6 1.6

0.2 0.3

1.2 2.2

0.2 0.6

1.2 1.4

2.1 2.5

0.1 0.2

2.9 3.5

0.4 0.4

1.1 i .0

1.7 1.8

0.2 0.1

2.7 2.4

0.3 0.4

0.7 0.6

1.1 1.0

0.2 0.2

1.5 1.6

0.4 0.3

Nonfirearm homicides per 100,000 population

2.0 2.3

1.6 1.9

1.3 1.4

4.1 6.5

6.6 5.7

0.5 0.6

0.3 0.5

0.4 0.5

1.3 1.6

1.2 1.2

0.3

0.2

0.2

0.7

0.4

0.3

0.5

0.1

0.5

0.2

1.0

1.6

0.2

1.6

0.3

1.6

2.6

0.3

4.6

0.3

1.2

1.7

0.2

4.2

0.2

0.6

1.0

0.1

1.7

0.1

2.2

1.5

1.3

7.0

6.5

0.6

0.3

0.4

1.6

1.6

0.2

0.3

0.1

0.4

0.3

0.3

0.5

0.1

0.5

0.3

0.8

1.5

0.1

1.9

0.2

1.7

2.9

0.2

4.9

0.4

1.0

1.6

0.2

2.7

0.6

0.8

1.1

0.2

1.4

0.3

2.2

1.4

1.2

6.7

6.3

0.5

0.3

0.4

1.1

1.6
Advance Data No. 231 ● March 23, 1993 11

Table 2. Death rates due to firearms and nonfirearms by manner of death (homicide, suicide, and unintentional injury), by age, race, and

sex for persons 1-34 years of age: United States, lW5-90-Con.

Age, race, end sex 1985 1986 1987 1888 1989 1990

10-14 yeara of age

Tonal . . . . . . . . . . . . . . . . . . .

Whiie male . . . . . . . . . . . . . . .

WMefemale.. . . . . . . . . . . . .

Black male. . . . . . . . . . . . . . . .

Black female . . . . . . . . . . . . . .

15-19 yeara of age

Total . . . . . . . . . . . . . . . . . . .

Whiie male . . . . . . . . . . . . . . .

Whdafemale . . . . . . . . . . . . . .

Black male. . . . . . . . . . . . . . . .

Black female . . . . . . . . . . . . . .

20-24 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtie male . . . . . . . . . . . . . . .

Whiiefemale . . . . . . . . . . . . . .

Black male. . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

26-64 yeara of age

Total . . . . . . . . . . . . . . . . . . .

Whtiemale . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

10-14 yeara of age

Tonal . . . . . . . . . . . . . . . . . . .

Whitemale . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfamale . . . . . . . . . . . . . .

15-19 yeara of age

Tonal . . . . . . . . . . . . . . . . . . .

Whiiemale . . . . . . . . . . . . . . .

Whiiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

20-24 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtiemele . . . . . . . . . . . . . . .

WMefemale.. . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

25-34 yeare of age

Total . . . . . . . . . . . . . . . . . . .

Whtie male . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

0.6

0.5

0.6

1.1

1.1

2.8

2.2

1.5

9.3

5.3

5.0

4.4

2.1

22.1

9.1

5.1

4.5

1.9

28.3

9.3

0.8

1.1

0.5

0.6

0.4

3.9

6.2

2.1

2.9

0.9

6.2

10.1

2.5

7.7

1.1

6.9

10.6

3.5

9.6

1.5

0.6

0.2

0.6

1.3

1.1

3.1

2.7

1.9

9.7

5.6

5.5

4.e

2.7

23.6

9.5

5.5

4.6

2.1

30.2

10.5

0.7

0.9

0.4

0.8

0.2

4.0

6.4

2.2

2.4

1.1

6.2

10.5

2.4

5.9

1.4

7.3

11.6

3.4

10.3

2.2

Nonfirearm homioidea per100,0OOpc@ation

0.6 0.6

0.2 0.4

0.5 0.4

1.7 1.3

1.4 1.9

2.6 26

2.1 1.9

1.8 1.7

10.6 9.1

4.8 4.5

5.0 5.3

4.2 4.2

2.3 2.4

20.3 23.1

11.2 11.4

5.2 5.3

4.1 3.9

2.2 2.1

28.4 26.5

10.9 13.1

Nonfirearmsuicidaa par100,0Wpopulafii

0.8 0.7

0.9 0.9

0.3 0.4

1.2 0.6

0.2 0.6

4.1 4.3

6.4 6.8

25 25

2.6 29

1.4 1.3

6.1 5.7

10.4 9.4

2.2 2.4

6.6 7.4

1.3 1.4

7.1 7.0

11.0 10.9

3.6 3.4

10.0 10.2

2.3 2.3

0.6

0.3

0.6

0.8

2.0

2.4

1.9

1.5

8.4

3.1

5.0

4.0

2.2

21.7

9.7

5.3

4.2

2.0

29.5

11.9

0.6

0.8

0.4

0.9

0.5

4.2

6.4

24

3.2

1.6

5.6

9.2

2.0

8.5

1.6

6.6

10.4

3.3

11.0

2.5

0.6

0.3

0.5

1.2

1.6

3.1

2.9

1.6

10.5

5.1

5.4

5.3

2.2

21.6

9.7

5.5

4.3

2.0

30.8

126

0.7

1.1

0.4

0.4

0.2

3.6

5.9

1.7

2.7

0.7

5.5

9.3

2.0

5.9

1.3

8.4

10.0

3.1

9.6

2.3

whichallmtasarebeeed.Totelincludesracesnotshewnseperately.
12 Advance Data No. 231 ● March 23, 1993

Table 3. Deatha due to firearms and nonfirearms by manner of death (homicide, suicide, and unintentional injury), by age, race, and sex

for persons 1-34 years of ags United States, 193!5-90

Age, race, and sex 1965 1986 1987 1988 1989 1990

1 1-4 yeare of age

Total . . . . . . . . . . . . . . . . . . .

Whfie male . . . . . . . . . . . . . . .

Whtiefemele . . . . . . . . . . . . . .

Black male . . . . . . . . . . . . . . . .

Black female . . . . . . . . . . . . . .

5-9 yeacs of age

Total . . . . . . . . . . . . . . . . . . .

Whtiemele . . . . . . . . . . . . . . .

Whtefemele . . . . . . . . . . . . . .

Black male . . . . . . . . . . . . . . . .

Black female . . . . . . . . . . . . . .

10-14 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtiemale . . . . . . . . . . . . . . .

Whiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

16-19 yeare of age

Total . . . . . . . . . . . . . . . . . . .

Whtemale . . . . . . . . . . . . . . .

WMefemale .. . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

20-24 years of age

Total . . . . . . . . . . . . . . . . . . .

Whfiemale . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . . . .

Black male . . . . . . . . . . . . . . .

Blackfemele . . . . . . . . . . . . . .

2%34 years of age

Total . . . . . . . . . . . . . . . . . . .

Whkemale . . . . . . . . . . . . . . .

Whtiefemele . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

1+ yeara of age

Total . . . . . . . . . . . . . . . . . . .

White male . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

5-8 yeara of age

Total . . . . . . . . . . . . . . . . . . .

Whtemale . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . .

10-14 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtemale . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

96

35

26

24

9

120

61

28

11

16

470

319

70

63

9

2,498

1,445

263

643

84

4,380

2,615

458

1,055

151

6,050

4,664

1,002

1,909

347

53

19

13

12

7

58

25

15

6

12

141

63

26

40

6

62

27

21

20

10

110

52

20

16

17

453

297

64

63

21

2,717

1,581

279

690

108

4,746

2,675

479

1,307

175

8,654

4,651

971

2,284

382

51

13

14

15

6

52

21

10

8

10

f 52

67

29

43

12

Allfirearmdaeths

77 91

29 37

19 20

17 20

8 10

126 124

64 53

28 25

22 27

8 12

485 524

220 287

72 72

90 104

18 46

2,720 3,242

1,458 1,642

243 273

833 1,126

125 116

4,561 4,616

2,430 2,387

426 353

1,404 1,569

192 194

8,326 6,S01

4,665 4,728

989 980

2,126 2,476

395 420

Firearm homicides

41 50

12 17

12 12

9 12

7 7

55 71

26 20

12 20

10 16

5 10

174

56

28

67

14

183

59

25

60

32

105

41

25

19

13

138

62

xl

22

12

557

321

66

123

30

3,597

1,732

292

1,351

131

4,638

2,396

352

1,746

212

8,818

4,752

925

2,548

861

67

27

15

11

9

77

22

25

14

9

229

80

27

69

23

87

3s

19

14

13

121

43

28

21

16

560

298

69

136

48

4,173

1,936

319

1,640

163

5,369

2,600

377

2,045

195

9,412

5,026

976

2,815

423

56

22

13

9

10

63

13

20

14

12

263

94

28

92

41
Advance Data No. 231 ● March 23, 1993 13

Table 3. Deaths due to firearms and nonfirearms by manner of death (homicide, suicide, and unintentional injury),by age, race, and sex

for persons 1-34 years of agw United States, 1965-90-Con.

Age, race, errd sex 1985 1988 1987 1988 1888 Im

1%19 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtie male . . . . . . . . . . . . . . .

Whfiefemale . . . . . . . . . . . . . .

Black male . . . . . . . . . . . . . . . .

Black female . . . . . . . . . . . . . .

20-24 years of age

Total . . . . . . . . . . . . . . . . . . .

Whiie male . . . . . . . . . . . . . . .

Whfiefemale . . . . . . . . . . . . . .

Black male . . . . . . . . . . . . . . . .

Black femsle . . . . . . . . . . . . . .

25-34 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtemale . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfamale . . . . . . . . . . . . . .

10-14 years of age

Total . . . . . . . . . . . . . . . . . . .

WMemale .. . . . . . . . . . . . . .

Whtefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

15-19 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtiemale . . . . . . . . . . . . . . .

Whiiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfernale . . . . . . . . . . . . . .

20-24 yasrs of age

Total . . . . . . . . . . . . . . . . . . .

Whiiemale . . . . . . . . . . . . . . .

Whtefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemsle . . . . . . . . . . . . . .

25-34 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtiemale . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

l-4yasrscfage

Total . . . . . . . . . . . . . . . . . . .

Whtiemale . . . . . . . . . . . . . . .

Whfiafemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemde . . . . . . . . . . . . . .

Firearm homicides

1,312 1,657

402 481

87 97

697 a63

100 86

1,087

393

66

517

@

2,107

8S4

1,274

456

108

566

91

2,510

962

2,011

561

123

1,176

117

2,766

891

la

1,491

160

4,s35

1,782

402

2,201

2,464

707

136

1,441

140

3,274

1,029

173

1,826

186

52260

1,958

419

Z450

2,497 2,585

663 629

1s9 182

1,227 1,385

173 188

1s9 207

874 1,138

154

4,591

1,829

406

1,946

321

141

129

4,081

1,669

433

1,606

291

4,302 4,725

1,6S5 1,733

433 426

1,766 2,101

332 365 337 366

firearm suicides

139 151 125 13s

88

22

11

3

142

87

32

15

5

1,332

987

160

120

17

103 102 114 84

27 23

6 9

1 5

28

6

0

1,117

850

23

10

3

1,151

911

13s

65

14

1,946

1,606

244

136

14

3,627

2,723

514

276

46

31

14

7

5

4

1,129 1,261

850 954

141 163

69 95

18 13

1,241

941

147

100

10

150

74

9

1,a64

1,511

234

1,7e3 1,754 1,775

1,331

171

192

25

1,633

1,399

181

171

18

1,368 1,370

206 154

Isa 160

16 21

148

20

3,509

2,654

511

245

40

41

15

13

11

2

3,629 3,706 3,632

2,732

3,773

2,825

517

317

41

2,713 2,766

507 497

26s 315

49 44

296

36

Unintenticme.lfirwrm deaths

36 41 31

16

6

5

3

3a

14

10

8

4

17 20

7 8

8 8

1 3
14 Advance Data No. 231 ● March 23, 1993

Table 3. Deaths due to firearms and nonfirearma by manner of death (homicide, suicide, and unintentional injury), by age, race, and sex

for persons 1-34 years of age: United States, 1966-!XbCon.

Age, race, and sex 1985 1986 1987 1988 1989 1990

5-9 yeare of age

Total . . . . . . . . . . . . . . . . . . .

Whiie male . . . . . . . . . . . . . . .

White female . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

10-14 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtemale . . . . . . . . . . . . . . .

Whitefamale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

15-19 years of age

Total . . . . . . . . . . . . . . . . .

Whitemale . . . . . . . . . . . . . .

Whitafemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

20-24 years C4age

Total . . . . . . . . . . . . . . . . . . .

Whtemale . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

25-34 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtie male . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . .

Blackfemaie . . . . . . . . . . . . . .

14 yeare of age

Total . . . . . . . . . . . . . . . . . . .

Miiemale . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

5-9 yeara of age

Total . . . . . . . . . . . . . . . . . . .

White male . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . .

10-14 yeara of age

Total . . . . . . . . . . . . . . . . . . .

Whtiemale . . . . . . . . . . . . . . .

Whdefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

15-19 yeare of age

Total . . . . . . . . . . . . . . . . . .

White male . . . . . . . . . . . . . .

Whitefamale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

Unintentional firearm deaths

66 51

35 32

16 4

11 11

2 2

56

33

13

4

4

177

145

12

16

1

241

57

30

10

6

7

143

115

12

8

5

236

176

25

30

3

205

146

17

27

4

59

39

5

7

3

172

56

34

7

7

4

144 185 146

111 123

12 22

15 26

3 8

127 108

14

23

4

294

195

20

63

4

7

26

2

305

212

14

67

6

220 266

160 194

11 11

41 46

5 5

168

17

45

5

236 213 200

148 146

16 8

37 32

5 5

222 195

175 133

14

55

3

274

180

26

43

3

326

88

72

80

72

104

23

27

22

21

129

15

35

6

279

194

27

37

10

322

87

6a

79

72

93

24

31

15

21

21

27

2

339

232

39

44

12

291 264

196 175

36 29

36 41

10 8

Nonfirearm homicides

2s3 331

95 114

76 78

44 72

70 61

213

28

42

7

331

92

80

58

59

109

24

31

24

18

102

65

67

66

82

17

20

16

24

86 108

21 36

27 32

18 22

16 16

109

36

37

15

14

93

17

42

17

14

92

15

35

22

17

97

27

28

16

24

100

21

40

11

25

98

23

34

16

21

515

174

113

128

73

588

212

140

135

77

526

161

131

147

66

478

145

121

126

61

431

143

108

116

42

558

215

112

144

69
Advance Data No. 231 ● March 23, 1993 15

Table 3. Deaths due to firearms and nonfirearms by manner of death (homicide, suicide, and unintentional injury), by age, race, and sex

for persons 1-34 years of agw United States, 1985-90-Con.

Age, race, end sex 1985 1988 1987 1888 1539 1880

20-24 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtie male . . . . . . . . . . . . . . .

Whiiefemale . . . . . . . . . . . . . .

Black male . . . . . . . . . . . . . . . .

Black female . . . . . . . . . . . . . .

26-34 years of age

Total . . . . . . . . . . . . . . . . . . .

White mele . . . . . . . . . . . . . . .

Whtiefemale . . . . . . . . . . . . . .

Black mele . . . . . . . . . . . . . . . .

Black femele . . . . . . . . . . . . . .

10-14 years of age

Total . . . . . . . . . . . . . . . . . . .

Whtiemale . . . . . . . . . . . . . . .

Whitefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

16-19 yeare of age

Total . . . . . . . . . . . . . . . . . . .

w~~emale . . . . . . . . . . . . . . .

Whtefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

20-24 years of age

Total . . . . . . . . . . . . . . . . . . .

WMemale. .. . . . . . . . . . . . .

Whiiefemsle . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

25-34 years of age

Total . . . . . . . . . . . . . . . . . . .

Whiiemale . . . . . . . . . . . . . . .

Whiiefemale . . . . . . . . . . . . . .

Blackmale . . . . . . . . . . . . . . . .

Blackfemale . . . . . . . . . . . . . .

Nonfirearm homicides

1,063 1,150 1,019 1,041

368 402 360 349

187 226 191 189

306 325 275 308

134 136 150 180

2,109

768

334

677

251

136

77

35

11

5

2,313

835

374

740

291

109

64

23

10

2

2,244 2,267

744 713

396 377

736 726

306 375

Nonfirearm suicides

99 112

59 62

18 26

15 8

3 7

732 745 773 798

489 503 502 519

154 164 166 183

40 34 36 41

12 15 19 18

1,308 1,278 1,228 1,116

903 921 879 775

218 204 178 190

107 81 93 88

16 21 18 19

Z667 3,064 3,026 3,004

1,881 2,064 1,897 1,S8Q

613 596 633 24)1

230 253 251 259

41 60 64 67

957

326

170

265

134

2,300

761

355

762

344

96

52

23

12

6

766

463

172

44

21

1,066

743

154

111

22

2,933

1,B9Q

594

263

72

i ,036

424

169

281

132

2,363

766

35+)

800

366

116

75

25

6

3

647

435

119

37

9

1,057

74a

163

76

17

2,777

1,800

541

250

67

NOTE:Totslincludesrsceanotehownsspsrstely.Alltiresmrdeaths indudethoseforvhii theinteatwssunkncw.
16 Advance Data No. 231 ● March 23, 1993

Table 4. Firearm mortality race and sex ratioa, by manner of death for pereons 1-34 years of age United States, 1S90

Race ratio (black/white) Sex ratio (maleffemakj

Manner of death Male Female White Black

All firearm deaths

14years . . . . . . . . . . . . . . . . . . . *1 .9 %.4 *1.9

5-9yeare . . . . . . . . . . . . . . . . . . .

*1.1

2.4 $’3.0 1.6 *1.3

10-14 yeare . . . . . . . . . . . . . . . . 2.4 3.6 4.1 2.8

15-19 yeare . . . . . . . . . . . . . . . . . 4.5 2.6 5.7

20-24 years . . . . . . . . . . . . . . . . .

9.9

4.9 2.9 6.6 10.9

25-34 year n . . . . . . . . . . . . . . . . 3.9 2.6 5.1 7.5

Firearm homicide

l-4yeare . . . . . . . . . . . . . . . . . . . Z?.1 =.9 *1.6

5-9years . . . . . . . . . . . . . . . . . . .

Yr.9

*5.6 %3..2 *0.6 *1.1

10-14years . . . . . . . . . . . . . . . . . 5.2 7.5 3.2 2.2

15-19yeara . . . . . . . . . . . . . . . . . 10.9 5.3 4.9 10.1

20-24years . . . . . . . . . . . . . . . . . 10.9 5.5 5.7

25-34years . . . . . . . . . . . . . . . . .

11.3

8.7 5.4 4.6 7.5

Firearm suicide

10-14yeare . . . . . . . . . . . . . . . . . ‘Tr.9 *0.8 2.6 %2.9

15-19years . . . . . . . . . . . . . . . . . 0.7 *0.5 5.8 %9

20-24yeare . . . . . . . . . . . . . . . . . 0.8 *0.6 7.4 %9

25-34years . . . . . . . . . . . . . . . . . 0.8 0.5 5.4 8.7

Unintentional firearm

14years . . . . . . . . . . . . . . . . . . . ●1.6 %5 %2.5 *1.6

5-9years . . . . . . . . . . . . . . . . . . . ●1.1 %3.0 *4.6 *1.7

10-14yeare . . . . . . . . . . . . . . . . . 1.3 *1.5 *1 4.6 *12.7

15-19years . . . . . . . . . . . . . . . 1.7 %2.2 *I 4.3 *1 0.9

2(&24years . . . . . . . . . . . . . . . . . 1.7 %0 %2 *4.6

25-34years . . . . . . . . . . . . . . . . 1.3 %?.3 7.1 *4.1

NOIE:RW”osare asterisked (~ifeirlrer thenumersroror thedenomin.etor oftheratioisbased on200rfewerdeatt?s. 3eatsble2forrat.sa sndtsble3fornumbers ofdeafhs.

Tabie5. Selected causes ofdeath among persons l+years ofage, byagrx United Stetes, lS90

Age

Cause of death 1-4 yeara 5-9 years 10-14 years 15-19 yeara 20-24 years 25-34 years

All external causes . . . . . . . . . . . . . . .

Motor vehicle injuries. . . . . . . . . . . .

Drowning . . . . . . . . . . . . . . . . . . .

Firesandbums . . . . . . . . . . . . . . .

Firearms. . . . . . . . . . . . . . . . . . . .

Homicide . . . . . . . . . . . . . . . . . .

Suicide . . . . . . . . . . . . . . . . . . .

Unintentional . . . . . . . . . . . . . . .

Nonfirearm homicide. . . . . . . . . . . .

Nonfireamnsuicide . . . . . . . . . . . . .

All naturalcauses . . . . . . . . . . . . . . .

Congenital anomalies . . . . . . . . . .

Malignant neoplasma. . . . . . . . . . .

HIVinfaction . . . . . . . . . . . . . . . . .

Allexternalcausas . . . . . . . . . . . . . . .

Motorvehicle injunes. . . . . . . . . . . .

Drowning . . . . . . . . . . . . . . . . . . .

Firesand burns . . . . . . . . . . . . . . .

Firearms . . . . . . . . . . . . . . . . . . . .

Homicide . . . . . . . . . . . . . . . . . .

Suicide . . . . . . . . . . . . . . . .

Unintentional . . . . . . . . . . . . . . .

Nonfirearm homicide. . . . . . . . . . . .

Nonfirearmsuicide . . . . . . . . . . . . .

All naturalcauses . . . . . . . . . . . . . . .

Congenital anomalies . . . . .

Malignantnaoplasms. . . . . . .

HIVinfection . . . . . . . . . . . . . . . . .

20.0

6.2

3.8

3.7

0.6

0.4

. ..

0.2

2.2

. .

26.6

6.0

3.5

0.8

2,975

928

564

554

87

56

. .

31

322

. .

3,956

896

513

123

10.8

5.4

1.4

1.3

0.7

0.3

. . .

0.3

0.5

. .

11.3

1.6

3.1

0.4

1,951

970

246

226

121

63

. . .

56

93

. .

2,044

286

569

64

Deaths per 100,000 population

14.7

6.3

1.5

0.5

3.3

1.5

0.8

0.8

0.6

0.7

11.1

1.1

3.1

0.1

2,528

1,0s9

260

91

560

258

142

146

98

116

1,913

182

525

20

71.6

33.3

2.7

0.6

23.5

14.0

7.5

1.7

3.1

3.6

16.9

1.3

4.3

0.3

Deaths

12,707

5,918

478

114

4,173

2,434

1,332

305

556

647

3,004

224

759

46

34.0

35.0

2.2

1.0

28.1

17.1

9.6

1.0

5.4

5.5

25.9

1.4

5.5

2.6

16,067

6,669

430

183

5,369

3,274

1,333

195

1,038

1,057

4,955

267

1,060

493

71.4

23.6

2.0

1.1

21.8

12.2

8.7

0.6

5.5

6.4

67.9

1.1

12.6

19.7

:30,790

‘10,170

867

470

9,412

5,280

3,773

279

2,363

2,777

29,301

473

5,427

8,4S3
Advance Data No. 231 ● March 23,1993 17

Technical notes

Nature and sources of data

Data shown in this report are based

on information from all death

certiikates filed in the 50 States and the

District of Columbia.

Mortality statistics are based on

information coded by the National

Center for Health Statistics (NCHS)

from copies of the original death

certificates received from the State

registration offices and on State-coded

data provided to NCHS through the

Vital Statistics Cooperative Program.

Data for the United States refer to

events occurring within the United

States.

Cause-ofdeath classification

The mortality statistics presented in

this report were compiled in accordance

with the World Health Organization

regulations, which specify that member

nations classify causes of death by the

current Manual of the International

Statistical Classification of Diseases,

Injuries, and Causes of Death (7). In

this repo~ causes of death for 1985-90

were classified according to the Ninth

Revision of the ICD (ICD-9).

Homicides are classified according

to ICD-9 Nos. E960-E969 (Homicide

and injury purposely inflicted by other

persons) and Nos. E970-E978 (Legal

intervention). Homicides caused by

firearm are classfied under ICD-9, Nos.

E965.0-E965.4 (Assault by firearms)

and E970 (Legal intervention by

firearm). Suicides are classified

according to ICD-9 Nos. E950-E959

(Suicide and self-inflicted injury).

Suicides caused by firearms are

classified under ICD-9 Nos. E955.0-

E955.4. Unintentional firearm deaths are

classified under ICW9, No. E922

(lhiutentional injury caused by Iirearm

missile). Injury deaths by firearms,

undetermined whether unintentionally or

purposely inflicted

are classified under ICD-9,

NOS. E985.0-E985.4.

Random variation

Although the mortality data in this

report are not subject to sampling error,

Table I. Deaths due to legal intervention by a firearm among persons 15-34 yearn of age,

by sex and racw United States, 1985 and 1990

Male Female

Age Total Mite Hack White Hack

19ss Deaths

15-19 yeara . . . . . . . . . . . . . . . 23 11 11 0 1

20-24 yeats . . . . . . . . . . . . . . . 54 32 19 0 0

25-34 yeara . . . . . . . . . . . . . . . 87 52 32 0 0

1990

15-19 years . . . . . . . . . . . . . . . 22 12 10 0 0

20-24 yeara . . . . . . . . . . . . . . . 57 28 22 1 0

X-34yeara. . . . . . . . . . . . . . . 114 88 39 4 2

Note: Total inclurk reces not shown sepemteiy.

they may be affected by random

variation in the number of deaths

involved. When the number of events is

small (perhaps less than 100) and the

probability of such an event is small,

considerable caution must be observed

in interpreting the data. Such infrequent

events may be assumed to follow a

Poisson probability distribution. For this

distribution, a simple approximation

may be used to estimate the confidence

interval, as follow=

If N is the number of registered

deaths in the population and R is the

corresponding rate, the chances are 19

in 20 (approximate 95-percent

confidence interval) that

1. N- 2fland N+~

covers the “true” number of

events.

2. R-2> and R+2~

m m

covers the “true” rate.

If the rate R ~corresponding to N1

events is compared with the rate R2

corresponding to N2 events, the

difference between the two rates may

be regarded as statistically significant if

it exceeds

Additional information on random

variation may be found in the Technical

Appendix of Wal Statistics of the

United States, 198~ Volume II,

Mortrdity, Part A.

Rates of change

Annual rates of change are

represented by the slope of a least

squares regression line through the

logarithm of the annual rates.
Advance Data No. 231 ● March 23, 1993 19

Symbols

--- Data not available

. . . Category not applicable

Quantity zero

0.0 Quantity more than zero but less

than 0.05

z Quantity more than zero but less

than 500 where numbers are

rounded to thousands

* Figure does not meet standard of

reliability or precision
Number 232 ● March 25, 1993

Advance

Data

From Vi and Health Statisticsof the CENTERS FOR DISEASE CONTROL AND PREVENTION/National Center for Health Statistics

Drug Utilization in Office Practice

National Ambulatory Medical Care Survey, 1990

By Cheryl R. Nelson, M.S.P.H., Division of Health Care Statistics

In 1990 an estimated 704 million

office visits were made to office-based

physicians in the United States.

About 60 percent of the visits were

classified as a “drug visit,” a visit

during which one drug or more was

prescribed or provided to the patient.

This resulted in oflice-based

physicians prescribing or providing an

estimated 759 million medications to

their patients in 1990.

This report describes the drug

utilization for 1 year according to

data collected in the 1990 National

Ambulatory Medical Care Survey

(NAMCS). NAMCS, a year-long

sample survey of the nation’s

nonfederal, office-based physicians is

conducted by the Centers for Disease

Control and Prevention, National

Center for Health Statistics, Division

of Health Care Statistics. A summary

of general findings from the 1990

NAMCS (1) and reports on drug

utilization in office practice, 1985 (2)

and 1980 (3) have been published.

The term utilization is defined as

the prescribing or providing of a new

or continued drug by a doctor of

medicine or osteopathy in the course

of an office visit. It is not an

indication of the patient’s compliance

with the doctor’s instructions. Drug

utilization in this report will be

described in three ways: 1) by

frequency of drug use, namely, a drug

visi~ the proportion of visits during

which medications were prescribed or

provided, 2) by the intensity of drug

us% the proportion of visits during

which one, two, and three or more

drugs were prescribed or provide~

and 3) by the drug utilization ratq

the average number of medications

per visit. The terms “drug” and

“medication” are used

interchangeably and are broadly

delined to include any pharmaceutical

agent the dcztor prescribes or

provides to the patient during a visit.

Data presented in this report are

based on entries in item 15 on the

NAMCS Patient Record Form

(figure 1) that asks the responding

physician to report the names of up

to five specific drugs that were

prescribed or provided in the course

of the office visit (drugs prescribed

through telephone contact are

excluded). Physicians were asked to

report nonprescription and

prescription drugs, to distinguish

between new and continued

medications, and to indicate whether

the drug was intended for the

principal diagnosis associated with the

visit (item 10a).

Data highlights

Table 1 describes some key

dimensions of the drug data base.

New or continued statzu-About

half (51 percent) of the drugs

prescribed or provided were

descriied as continued medications.

Entry status--Seventy-one percent

of the drugs prescribed or provided

were specilic brand or trade names.

Prescription status-A great

majority (84 percent) of office-based

drug therapy utilized prescription

drugs.

Composition status-Seventy-five

percent of the drugs were single

ingredient medications.

Control status-Uncontrolled

drugs represented 87 percent of the

medications used in office-based drug

therapy. Controlled drugs were

distributed among the schedules as

shown in table 1. Only 6 percent of

the medications prescribed or

provided by the office-based

practitioner were classified as

controlled substances.

The data in tables 2 and 3 show

rank listings of the 50 drugs most

frequently prescribed or provided by

the office-based practitioner. Table 2

uses the entry names, that is, the

trade or generic names entered on

# SERWCE$,O

&

** +

#

U.S. DEPARTMENT OF HEALTHAND HUMANSERVICES

g Public Health Service

as Centers for Disease Control and Prevention 5%’

>

National Center for Health Statistics cm

%<tia= CWEF&Mw~&CL
2 Advance Data No. 232 ● March 25, 1993

A...rsna & Con660mMlw- All mt.m.lmn wtm.h WOUM pcmmt ent,ftc.u.m of . . D~rtnwnl of M..lth .nd Hum.. %rvms

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G+mons e.Lm9=d $...d f.rtwwwoses.1 Ihe sw.ev ●nd will not b. dnclos.d or ml.8.ed PLJ8(,CHe.Nh Serwce

10 othw perwru m .s.ti tar *nv otner 0. IPOS8. NJtmn.1 Cent.r for H#8iih StSIISIICS

1, DATE OF VISIT PATlENT RECORD

~

OMB No. 09204234

NATIONAL AMBULATORY MEDICAL CARE SURVEY

Expirss S-31 .S9

(PHSI 6 105B

2.21P CODE 4-SEX 5.::IR OR 6. ETHNICITY 7.~:;P;;O&j.W#) OF PAYMENT 8 WAS PATIE~

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9 PATIENTS COMPLAINT, SYMPTOM(S), OR OTHER

“REASONIS1 FOR THIS ViSil [In pmenf’s own words~

10. PHYSICIAN’S DIAGNOSES q 1, p%;::E;:sTd7

, MOST IMPDRTANT . PRINCIPAL OIAGNOSIS~OSLEM ASSOCIATED WITH ITEM 9*.

lD YES 2[]N0

i

IF YES, FOR THE CONO170N

b, OTHER b OTHER SIGNIFICANT CURRENT DIAGNOSES IN ITEM 1CW7

10 YES 2[]N0

—.. - ——

1 z OIAGNOSTICISCREENING SERVICES

“ /Chink all ordered or prmded] 13* ~~~ks;?~;~?;;!~ro,idti]

14 NON-MEDICATION THERAPY

‘ [Check all ordered or ptwided]

1 ❑ NONE 7 ❑ BLOOO PRESSURE CHECK 13 Q ORAL GLuCOSE TOL 1 ❑ NONE 1 ❑ NONE

2 ❑ PAP TEST 8 ❑ URINALYSIS I* Q CHOLESTEROL MEASLJRE 2 III WE’CJ+T’’OUC’1ON 2 ❑ PSYCHOTHERAPY

3 ❑ PELVIC EXAM 9 ❑ CHEST X. RAY 15 ❑ Htv 5ER0L0Gy 3 ❑ CHOLESTEROL REOUCTION 3 ❑ CORRECTIVE LENSES

4 ~ BREAS7 PALPATION 10 Q DIGITAL RECTAL EXAM 16 ❑ OTHER BLOOC) TEST

. ❑ SMOKING CESSATION 4 ❑ AMBuLATORY SURGERY

5 ~ MAMMOGRAM 5 Q HIV TRANSMISSION 5 ❑ PHYSIOTHERAPY

11 ❑ PHOCTISIGMOIDOSCOPY 17 ❑ OTHER &mtJv\

6 ❑ VISUAL ACUITY 6 ❑ PREAST SELF-EXAM 6 ❑ OTHER /SOrL+Yy/

12 ❑ STOOL BLOOO EXAM

~ ❑ OTHER ——

1 s. MEWA~NTH~MY/Rm& ollnewormnttnu& m&dcotiomorderedorpmvidtiat{hk v~it. usethesotne

brond name orgetwsk nome en!eredon my Rxor office mzkal nxwzt Include ,mmunizsng anddewwitivhg agems.)

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IF NONE. CHECK HERE . . Nsw b. FOR OX /Time

MEDICATtON~ IN ITEM 1087

YES NO YES NO

Ocl’uolly

2 ❑ RETURN AT SPECIFIED TIME spmrr with

physician]

1 ‘cl 20 lo 20 3 ❑ RETURN IF NEEOEO. P,li N.

2 ICI zCI ICI ZD

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5 ❑ ‘EFERRED 70 OTHER PHYSICIAN

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‘cl 20 10 20

7 ❑ AOMIT TO liOSPITAL

~r

5, ‘cl ‘cl 10 ‘cl S n OTHER [SW@j

o u.S. GOWPt4MENl PlW411ffi CFFICE1S69.=19

Figure 1. Patient RecordForm

the patient’s prescription or medical

record. The top three entry names,

amoxicillin, amoxil, and ceclor, are

antibiotics. In table 3 the data are

presented by the generic ingredients

of the drugs and provide a more

complete perspective of drug

utilization in the doctor’s office. The

most frequently used generic

substance was amoxicillin (5 percent),

an antibiotic. Seven other antibiotics

are in the top 50 list including

erythromycin and cefaclor. Other

drugs frequently prescribed or by their chief therapeutic effect.

provided by office-based physicians Antimicrobial agents, cardiovascularare the decongestants, phenylephrine, renal drugs, respiratory drugs, and

pseudoephedrine, and drugs used for relief of pain account

phenylpropanolamine, the for 53 percent of all drug mentions.

broncodilators, albuterol and

theophylline, and those drugs used in

treating diseases of the circulatory

system, hydrochlorothiazide, digoxin,

furosemide, triamterene,

nitroglycerin, diltiazem, and aspirin.

In table 4 the estimated 759

million drug mentions are classified

The remaining tables describe the

relationship between drug utilization

and other key variables in office care:

the characteristics of the attending

physician (table 5), the patient’s age

and sex (table 6), race and ethnicity

(table 7), and the principal diagnoses

(table 8).
Advance Data No. 232 ● March 25,1993 3

Table 1. Number and percent distribution of drug mentions by seleoted dimensions:

United States, 1990

Drug mentions Peroerrt

Drug dimension in thousands distribution

AIImentians . . . . . . . . . . . . . . . . . . . . . . . . . . . 759,4Q8 100.00

New or eorrtinued status

Newmadication . . . . . . . . . . . . . . . . . . . . . . . . 327,748

Continued medioation . . . . . . . . . . . . . . . . . . . . .

43.16

364,009 50.57

Undetermined . . . . . . . . . . . . . . . . . . . . . . . . . . 47,849 6.27

Entry status’

Genencname . . . . . . . . . . . . . . . . . . . . . . . . . . 131,893 17.37

Tradename . . . . . . . . . . . . . . . . . . . . . . . . . . . 543,357 71.55

Undatennined . . . . . . . . . . . . . . . . . . . . . . . . . . 34,158 11.08

Prescription status

Prescriptiondrug . . . . . . . . . . . . . . . . . . . . . . . . 837,30+3 63.92

Nonprescriptiondrug . . . . . . . . . . . . . . . . . . . . . 88,452 9.01

Undetermined . . . . . . . . . . . . . . . . . . . . . . . . . . 53,654 7.07

Composition status

3ingleingradientdnrg . . . . . . . . . . . . . . . . . . . . 573,483 75.52

Combinationdrug . . . . . . . . . . . . . . . . . . . . . . . 134,807 17.76

Undatennined . . . . . . . . . . . . . . . . . . . . . . . . . . 51,000 6.72

Federal control status

Controlladdrug . . . . . . . . . . . . . . . . . . . . . . . . . 49,613 6.53

-%hadulelldrug . . . . . . . . . . . . . . . . . . . . . . . 4,159 0.55

6cheduleIlldrug . . . . . . . . . . . . . . . . . . . . . . 13,153 1.73

3ohedulelVdrug . . . . . . . . . . . . . . . . . . . . . . 23,830 3.11

SchaduleVdrug . . . . . . . . . . . . . . . . . . . . . . 8,670 1.14

Nonoontmlleddrug. . . . . . . . . . . . . . . . . . . . . . 668,729 88.74

Undetermined.. . . . . . . . . . . . . . . . . . . . . . . . . 51,064 6.72

‘Thetredeorgenwic nemeusejbythe riysicianonltw pffhsaiprionorothw mdiilrscorck

Physician

Ninety-four percent of the patient

visits were to physicians who in the

1990NAMCS sample identified

themselves as doctors of medicine

(table 5). However a slightly higher

pereent of visits to doctors of

osteopathy (68 percent) were

classified m a drug visit than those

visits to doctors of medicine

(60 percent). Doctors of osteopathy

administered more single and

multiple medieations to patients than

did doetore of medicine. The drug

utilization rate for doctors of

osteopathy was 1.3 medications per

visit and 1.1 for doctors of medicine.

The physicians most likely to

prescribe or provide medieations were

those specializing in cardiovascular

disease, internal medicine, general

and family praetiee, pediatrks, and

neurology. Fiily-seven percent of the

patient visits were to these five

specialties and they accounted for

67percentofaU drug mentions.

Theintensityinadministering

medication was greatest for the

cardiovascxdar disease specialists.

Seventy-eight Percent ofthe visitsto

physicians specializing in

cardiovascular disease were drug

visits and42 percent of the visits

resulted inthree or more medications

prescribed or provided. Office-based

orthopedic surgeons and general

surgeons were the least likely to

provide medications to their patients

and about 18pereent of their visits

resulted in administeringa single

medication.

The drug utilization rate ranged

from Z.2 medications per visit for the

cardiovascular disease specialists to

0.3 medications per visit for

orthopedic surgeons. The drug

utilization rate for the internal

medicine specialty and “all other

specialties” was about 1.4 mediations

per visi~ followed by 1.2 medications

per visit for dermatologists,

neurologists, and general and family

practitioners. By contras~

obstetricians and gynecologists,

general surgeons, and urological

surgeons have drug utilization rates of

about 0.5 medication per visit, lower

than the average rate for all

physicians.

Patient

Patients 65 yeara of age and over

represented 22 percent of the office

visits and accounted for 28 percent of

the drug mentions. Table 6 shows that

the percent of drug visits and the

administering of multiple mediations

when analyzed by patients’ age are

greatest for older patients. Older

patients were most likely to receive

multiple drug therapy while younger

patients were most likely to reeeive

only one medication. A higher

percent of visits by patients 75 years

of age and over (23 percent) were

prescribed or provided three or more

mediations than their younger

counterparts. By contras~ patients

under 15 years of age were

administered more single drug

therapies (41 percent) than their

older counterparts. The drug

utilization rate for patients 65 years

of age and over, about 1.4

mediations per visi~ was significantly

higher thsn the drug utilization rate

for younger patients, 1.2 and 1.0

mediations per visit.

Table 6 also shows that more

oftiee visits were made by female

patients (61 percent) and more drug

mentions were prescribed or provided

to female patients (61 percent). There

was also a higher percent of drug

visits by females 65 years of age and

over (about 67 percent) than by males

of the same age (61 percent). The

drug utilization rate for female and

male patienta was about 1.1

medications per visit.

When the data were analyzed by

the patient’s race (table 7), white

patients have a higher percent of

visits (85 percent) and drug mentions

(84 percent) than black and “other

race” patienta. However, black

patients have a higher percent of

drug visits (68 percent) than did white

or “other race” patients (60 percent).

Sixteen percent of the visits by black
4 Advance Data No. 232 ● March 25,1993

Table 2. The 50 drugs most frequently utilized in office practice by entry name, number and percent of mentions, rank, and therapeutic

usrx United States, 1990

Number of

Entry name of drug and mentions

Rank principal generic substance’ in thousands Peroent Therapeutic use

i

2

3

4

5

6

7

8

9

10

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

36

37

38

39

40

41

42

43

*.

45

46

47

48

49

50

All drugs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Amoxicillin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Amoxil(amoxicillin) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Ceclor(cefaclor) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Lasix(furosemide) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Prednisone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Naproayn (naproxen) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Seldane(terfenadine) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Motrin (ibuprofen) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Z@ac(ranitidine) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Premarin (estrogens) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Lanoxin (digoxin) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vasatec(enalapril) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

AepirinorA.S.A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Proventil (albuterol) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Dyazide (tnamterene, hydrochlorothiezide) . . . . . . . . . . . . .

Diphtheriatetanustoxoids pertussis. . . . . . . . . . . . . . . . . .

Voitaren (diclofenacsodium) . . . . . . . . . . . . . . . . . . . . . .

Tylenol (acetaminophen) . . . . . . . . . . . . . . . . . . . . . . . . .

Synthroid (levothyroxine) . . . . . . . . . . . . . . . . . . . . . . . .

Xanax(alprazolam) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Cardizem (dtiazem) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Capoten (captopril) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Prozec(fluoxetine) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Calan(verapamil) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Ventolin (albuterol) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Theo-dur(theophylline) . . . . . . . . . . . . . . . . . . . . . . . . .

Polimoyeliiisvarxine . . . . . . . . . . . . . . . . . . . . . . . . . . .

Tavist(clemaetine) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Kefiex(cephalexin) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Tenorrnin (atenolol) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Vancenase (baclomathasonedipropinate). . . . . . . . . . . . . .

Inderal (propranolol) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Timoptic (timolol) . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Cipro(ciprofloxacin) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Augmentin (amoxicillin, potassium clavulanate). . . . . . . . . . .

Entex(phenyIpropanolamine,phenylephfine,guatienesin). . .

Tylenol No.3(acataminophen, codeine). . . . . . . . . . . . . . .

Procardia (nifedipine) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Darvocet-N (propoxyphene, acetaminophen) . . . . . . . . . . . .

Duricef (cefadroxil) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Micronaee (glyburide) . . . . . . . . . . . . . . . . . . . . . . . . . .

Tetracycline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Ampicillin. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Erythromycin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Coumadin (watfarin) . . . . . . . . . . . . . . . . . . . . . . . . . . .

E.E.S. (erythromycin) . . . . . . . . . . . . . . . . . . . . . . . . . . .

Valium (diezepam) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Benadryl (diphenhydramine) . . . . . . . . . . . . . . . . . . . . . .

Ortho-novum (norethindrone, eetradiol ormeatranol) . . . . . . .

Tagamet(cimetidine) . . . . . . . . . . . . . . . . . . . . . . . . . . .

759,406

17,891

13,446

8,910

8,868

7,830

7,585

7,251

6,96S

6,501

6,327

6,275

5,991

5,8S6

5,614

5,564

5,176

5,160

5,144

5,137

5,069

4,979

4,765

4,765

4,755

4,666

4,600

4,551

4,405

4,265

4,231

4,106

3,970

3,877

3,623

3,763

3,757

3,729

3,698

3,653

3,573

3,434

3,36s

3,310

3,260

3,163

3,172

3,168

3,150

3,041

3,014

1OQ.oo

2.36

1.77

1.17

1.17

1.03

1.00

0.95

0.92

0.86

0.63

0.63

0.79

0.78

0.74

0.74

0.66

0.6s

0.66

0.66

0.67

0.66

0.6s

0.6s

0.63

0.61

0.61

0.60

0.58

0.56

0.56

0.54

0.52

0.51

0.50

0.50

0.49

0.49

0.49

0.48

0.47

0.45

0.45

0.44

0.43

0.42

0.42

0.42

0.41

0.40

0.40

All therapeutic uses

Antibiotic

Antibiotic

Antibiotic

Diuretic, antihypertensive

Steroid replacement therapy, anti-inflammatcty agent

Nonstemidal anti-inflammato ryagent

Antihistaminic

Noneteroidal enti-infiammatory agent

Duodenel or gastric ulcer

Estrogen replacement therapy

Cerdiotoniokiigitelis

Antihypertensive

Analgesic, anti-inflammatory, antipyretic

Bronchodilator

Diuretic, antihypertensive

Immunization

Nonsteroidal anti-inflammatory agent

Analgesic

Thyroid hormone therapy

Anxietydisordera

Cardiotonickalcium channel blocking agent

Antihyperlensive

Antidepresaant

Cardiotonic/calcium channel blocking agent

Bronchodilator

Bronchodilator

Immunization

Antihiataminic

Antibiotic

Antihypertensive, angina peotons

Intranaeal steroid

Hypertension, angina pectoris, amhythmia, migraine

Glaucoma

Antibiotic

Antibiotic

Cough preparation

Analgesic

Cardiotonic/oalcium channel blocking agent

Analgesic

Antibiotic

Hypoglycemic

Antibiotic

Antibiotic

Antibiotic

Anticoagulant

Antibiotic

Anxiety disorders

Ardihistaminic

Oral oontrsceptive

Duodenal or gastric ulcer

‘The trade or gensric name used by the physician on ths prescription or otisr medical records. The usa of trads names is for idsntificstion on~ and doss not imply srrdorsement by tha Public

HsakhServiceorthe U.S.Dspsrtmentof Heakhend Humsn Servicas.Bacauss otitsnonspschlcnature, thaen~’’Allergyreliti orshots,’’w”ti4,lS4,COll mansions, isomilted.

patients compared with llpercentof

white and “other race” patients were

prescribed or provided three or more

medications during a visit. The drug

utilization rate was higher for black

patients, 1.3medications per visit,

compared with 1.1 medications per

visit for white and “other race”

patients. ’llreepercent of the visits previously mentioned dtierence sin

and2percentof the drugs mentioned visits, drug visits , drug mentions, and

were by patients whose race was drug utilization rates do not change.

“unspecified.’’Urider the assumption However ifthis assumption is

that these “unspecified” race visits incorrect, and these “unspecified”

and drug mentions are distributed race visits and drug mentions were all

proportionately among white, black, from black patients there is no

and “other race” patients, the
Advance Data No. 232 ● March25,1993 5

Table 3. The 50 moat frequently utilized generic substances In office practice by number and pewcentof mentions, rank, and therapeutic

use: United Statea, 1990

Numberof

mentions

Rank Genericsubstance in thousands’ Percent 77rerqoeuticuse

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

26

29

30

31

32

33

34

35

38

37

38

39

40

41

42

43

44

45

46

47

48

49

50

Alldrugs . . . . . . . . . . . . . . . . . . . . . . . .

Amoxlcillin. . . . . . . . . . . . . . . . . . . . . . .

Acatamlnophen . . . . . . . . . . . . . . . . . . .

Erythromycin . . . . . . . . . . . . . . . . . . . . .

Hydrochlorothiazide . . . . . . . . . . . . . . . . .

Codeine . . . . . . . . . . . . . . . . . . . . . . . .

Phenylephnne . . . . . . . . . . . . . . . . . . . .

Ibuprofen . . . . . . . . . . . . . . . . . . . . . . .

Phenyipmpanolamine . . . . . . . . . . . . . . .

Aspirin.. . . . . . . . . . . . . . . . . . . . . . . .

Albuterol . . . . . . . . . . . . . . . . . . . . . . .

Paeudoaphadrine . . . . . . . . . . . . . . . . . .

Naproxen . . . . . . . . . . . . . . . . . . . . . . .

Furosemide . . . . . . . . . . . . . . . . . . . . . .

Chlorpheniramine . . . . . . . . . . . . . . . . . .

D@xin... . . . . . . . . . . . . . . . . . . . . .

Cafaclor . . . . . . . . . . . . . . . . . . . . . . . .

Guaifenasin . . . . . . . . . . . . . . . . . . . . . .

Trimathorpim . . . . . . . . . . . . . . . . . . . . .

Sulfamathoxazole . . . . . . . . . . . . . . . . . .

Prednisone . . . . . . . . . . . . . . . . . . . . . .

Tnamterene . . . . . . . . . . . . . . . . . . . . . .

Esrfadiol . . . . . . . . . . . . . . . . . . . . . . . .

Theophyiline . . . . . . . . . . . . . . . . . . . . .

Hydmrxrrli-e . . . . . . . . . . . . . . . . . . . .

Tarfanadine . . . . . . . . . . . . . . . . . . . . . .

Seclomettraaone . . . . . . . . . . . . . . . . . . .

Naomych.. . . . . . . . . . . . . . . . . . . . . .

Insulin . . . . . . . . . . . . . . . . . . . . . . . . .

Oaphakcdn. . . . . . . . . . . . . . . . . . . . . .

Estrogens . . . . . . . . . . . . . . . . . . . . . . .

Verapamil . . . . . . . . . . . . . . . . . . . . . . .

Ranfkfine . . . . . . . . . . . . . . . . . . . . . . .

penicillin. . . . . . . . . . . . . . . . . . . . . . . .

Enalapnl . . . . . . . . . . . . . . . . . . . . . . . .

Dextromathotphan . . . . . . . . . . . . . . . . .

Polymixin B . . . . . . . . . . . . . . . . . . . . . .

Glyburide . . . . . . . . . . . . . . . . . . . . . . .

Capfopril . . . . . . . . . . . . . . . . . . . . . . .

Dexamethasone . . . . . . . . . . . . . . . . . . .

Ntiroglycarin . . . . . . . . . . . . . . . . . . . . .

Ntiadipina . . . . . . . . . . . . . . . . . . . . . . .

Triamoinolone . . . . . . . . . . . . . . . . . . . .

LavothYoxina . . . . . . . . . . . . . . . . . . . .

Diofofwracaodium . . . . . . . . . . . . . . . . .

Pradnisolone . . . . . . . . . . . . . . . . . . . . .

Alprazolam . . . . . . . . . . . . . . . . . . . . . .

Promathazina . . . . . . . . . . . . . . . . . . . . .

Diitiazem . . . . . . . . . . . . . . . . . . . . . . .

fluoxatine Hydrochloride . . . . . . . . . . . . .

Atenolol . . . . . . . . . . . . . . . . . . . . . . . .

759,406

37,011

23,416

19,474

15,011

14,435

12,287

11,864

11 ,4s9

10,823

10,505

10,474

10,354

9,570

9,197

8,924

8,910

8,890

8,849

8,282

6,035

7,974

7,e65

7,834

7,405

7,251

7,092

6,915

6,913

6,737

6,845

6,616

6,501

6,408

6,3S6

6,108

5,86s

5,6s7

5,885

5,655

5,842

5,544

5,518

5,510

5,180

5,130

5,089

5,060

4,979

4,785

4,780

100.0

4.87

3.0s

2.58

1.8a

1.80

1.62

1.58

1.51

1.4a

1.3s

1.33

1.38

1.26

1.21

1.18

1.17

1.17

1.14

1.08

1M

1.05

1.05

1.01

0.9s

0.85

0.93

0.91

0.91

0.89

0.88

0.87

0.8s

0.84

0.84

0.80

0.79

0.75

0.75

0.74

0.74

0.73

0.73

0.73

0.88

o.6a

0.67

0.67

0.66

0.83

0.83

All therapeutic u=

Antibotic

Analgesic, antipyfetic

Antibntic

Diuretic, antihypertensive

Ana!gaaic,antitusaive

Daoongeatant,vaaoconatriotor

Nonateroidal anti-inflammatory agent

Deoongeatant, anorexiant

Wgasic, antipyretic, anti-inflammatory

Bronohodilator

Decongestant

Nonataroidalanti-irrfl’arnmatory agent

Diuratic,antihyp@enaive

Antihtiinic

Cardiotonic/calcium channelblockingagent

Antibmtic

Expectorant

Antibmtic

Antibotic

Steroid replacement therapy, anti-inflammatory agent

DiurW.c, antihypartensiva

Estrogen replacement therapy, oral contraceptive

Bmnchcdilator

Steroidalanti-inffarnmatoty agent

Antihiiinic

Steroidalsnti-intiamrrratory agent

Antibmtic

Hyp3gfycamic

Antibntic

Estrogenreplacemarrf therapy, oralcontracaptiva

Carddonicksdaum channal blcckingagent

Duodenalorgaatric ulcer

Antibntic

Antihypartansive

Arrtihrssive

Antibti

Hypoglycemic

Antihy@ensive

Steroidalanti-inflammatory *nt

Vaaodilafor

Card@on”ticaloium channaibloc+dngagant

Steroidalanti-inflammatory agent

Thyroidhonncnetharapy

Nonstaroidalanti-inflammatory agent

Steroidalanti-inflammatory agent

Antianxiety agent

Antihiataminio

Cardioton.kkrlaum channelblcckingagent

Antidepressant

Cardioton-WBata-adrenergicblookingagent, antihypertansive

‘Frequsrxyofmmlfom combinessir@e-iiit _wirtrmenticms ofagsntsinacatinaticwingredii dtug.

difference between the drug

Wilizationrates byrace.

Non-Hispanicpatients accounted

for about 88 pereent of the visits to

office-bas edphysiciansand89percent

of the drug mentions. ‘f’herew asa

slight tierence in the intensity in

administenng medications bythe

patients’ ethnicity. Officevisitsby

Hispanicpatient8 were more often

administered single medication and

visits bynon+lispanic patients were

more often administered three or

more medications. Seven percent of

the visits and 6 percent of the drug

mentions were by patients of

“unspccfied” ethnicity. Again the

assumptions that these

“unspecified” ethnicity visits and drug

mentions are distributed

proportionately among Hispanic and

non-Hispanic patients. Under this

assumption the drug utilization rate

for Hispanics would not signiikdy
6 Advance Data No. 232 ● March 25,1993

differ from the drug utilization rate

for non-Hispanic patients. However if

this assumption is incorrect and these

“unspecified” ethnicit y visits and drug

mentions are all from Hispanic

patients, the drug utilization rate for

Hispanic patients becomes

significantly lower than the drug

utilization rate for non-Hispanic

patients.

Diagnoses

In table 8 patient visits and drug

mentions are displayed according to

the International Classification of

Diseases (ICD) and with selected

related principal diagnoses.

Medications were most likely

administered during visits in which

the patient’s diagnosis was from the

major ICD categories of diseases of

the respiratory system, diseases of the

circulatory system, or diseases of the

nervous system and sense organs. In

33 percent of the visits, the patient’s

diagnosis was from one of these three

major ICD categories and these visits

accounted for almost half of the

drugs mentioned. An estimated 100

million visits to doctors’ offices were

those in which the patient’s diagnosis

was categorized under diseases of the

respiratory system and 86 percent of

these visits were classified as a drug

visit. Drugs were administered during

79 percent of the visits in which the

patient’s diagnosis was categorized

under diseases of the circulatory

system.

The intensity in administering

medication was high during those

visits in which patients were

specifically diagnosed with asthma.

Ninety-one percent of these visits

were drug visits and in almost half

(48 percent) of these visits, three or

more medications were prescribed or

provided. Three or more drugs were

also administered during those visits

where patients were diagnosed with

ischemic heart disease (45 percent).

The drug utilization rate for visits in

which patients were diagnosed with

asthma or ischemic heart disease

were 2.5 and 2.3 medications per

visit. A high percent of drug visits was

also noted when patients were

diagnosed with otitis media or acute

upper respiratory infection

(86 percent). For those visits, in

which patients were diagnosed with

otitis media, 60 percent were

administered a single medication.

Single medications were also

administered in 52 percent of the

visits in which patients were

diagnosed as obese.

Medications were least likely

administered during visits where the

patient’s diagnosis was normal

pregnancy. Only a third of these visits

were drug visits and most

(25 percent) were administered a

single medication.

References

1.

2.

3.

4.

5.

SchappertSM. National

AmbulatoryMedicalCareSurvey

1990Summary.Advancedata from

vital and health statistiw, no 213.

Hyattsville, Maryland National

Center for Health Statistics. 1992.

Koch H, Knapp DA Highlights of

drug utilization in office practice,

National Ambulatory Medical

Care Survey, 1985. Advance data

from vital and health statistic no

134. Hyattsville, Maryland

National Center for Health

Statistics. 1987.

Koch H. Dmg utilization in office

practiw 1980. Advancedata from

vital and health statistic% no 81.

Hyattsville, Maryland National

Center for Health Statistics. 1982.

Food and Drug Administration.

National Drug Code Directory,

1985 Edition. Washington: Public

Health Service. 1985.

Public Health Service and Health

Care Financing Administration.

International Classification of

Diseases, 9th Revision, clinical

modiikation. Washingtorx Public

Health Service. 1980.

Symbols

--- Data not available

. . . Category not applicable

Quantity zero

0.0 Quantity more than zero but less

than 0.05

z Quantity more than zero but less

than 500 where numbers are

rounded to thousands

* Figure does not meet standard of

reliability or precision
Advance Data No. 232 ● March 25,1993 7

Table 4. Number and percent distribution of drug mentions by therapeutic catagorie= United States, 1990

Number of

mentions Percent

77rerapeuticolassirkations’ in thousands disbfbtion

Alldrugs . . . . . . . . . . . . . . . . . . . . . . . .

Anestheticdrugs. . . . . . . . . . . . . . . . . . .

Localanesthetic-s. . . . . . . . . . . . . . . . . . .

Antidotes. . . . . . . . . . . . . . . . . . . . . . . .

Antimicrobialagents. . . . . . . . . . . . . . . . .

Penicillins.. . . . . . . . . . . . . . . . . . . . .

Cephalosporins. . . . . . . . . . . . . . . . . .

ErylhromycinsendIincosamidas. . . . . . . .

Tetracycline . . . . . . . . . . . . . . . . . . . .

Funinoglymsides. . . . . . . . . . . . . . . . .

Sulfonamidesendtrimethoprim. . . . . . . .

Unnarytractantiseptios . . . . . . . . . . . . .

Antifungalagerdsforsystemiomycases. . .

Antiviraiagents . . . . . . . . . . . . . . . . . .

Hematolcgicagents. . . . . . . . . . . . . . . . .

Agentsusedtotreat derisietwy

anemias . . . . . . . . . . . . . . . . . . . . . .

Anticoagularrtsorthromt@tk2a. . . . . . . .

Oardiovsecular-renaldrugs . . . . . . . . . . . .

Cardiacgyloosides. . . . . . . . . . . . . . . .

Mtiarrhythmicegents. . . . . . . . . . . . . .

Antianginalagents . . . . . . . . . . . . . . . .

Agentsusedinperipherel orsarebral

Vasoulardisorders. . . . . . . . . . . . . . . .

Agentsusedtotrestshook . . . . . . . . . . .

Diuti.cs . . . . . . . . . . . . . . . . . . . . . . .

Coronaryvasadilators . . . . . . . . . . . . . .

Psychopharmacologicdrugs. . . . . . . . . . .

Antianxiatyegents. . . . . . . . . . . . . . . . .

Antipsychoticdrugs. . . . . . . . . . . . . . . .

Antidepressants.. . . . . . . . . . . . . . . . .

CNSW.mulants, anorexiante . . . . . . . . . .

Radiophsrmsceuticalehmfrastrnedia. . . . . .

Diagnostics,nonradioactive,and

radiopeque. . . . . . . . . . . . . . . . . . . . . .

Gastrointestinslagents. . . . . . . . . . . . . . .

~~:sedirrdisorders ofupper

. . . . . . . . . . . . . . . . . . . . . . .

Arrtidiarrhealagents. . . . . . . . . . . . . . . .

laxatives . . . . . . . . . . . . . . . . . . . . . .

Metsboliiand nutrientagents. . . . . . . . . . .

Agentsusedtotreef hyparfipidemia. . . . . .

Vtimins, minarals. . . . . . . . . . . . . . . . .

Replenishersand regulatorsof water

and electrolytes. . . . . . . . . . . . . . . . .

759,408

3,636

2,434

209

125,594

43,699

23,821

22,357

10,311

1,412

9,395

6,465

2,239

2,311

9,914

6,485

3,356

111,125

1,514

8,998

9,083

18,921

4,764

39,383

27,829

48,402

5,486

14,826

5,820

17,364

5,922

31,272

16,220

2,919

3,378

29,446

5,288

14,935

8,801

100.00

0.43

0.32

0.03

18.54

5.75

3.14

2.84

1.3a

0.19

1.24

0.85

0.28

0.30

1.3f

0.85

0.44

14.83

0.20

1.18

1.19

2.49

0.83

5.19

3.88

6.11

0.72

1.95

0.74

2.23

0.78

0.78

4.12

2.14

0.33

0.44

3.88

0.70

1.97

1.13

Numberof

mentions Percent

?trera~c classh%sdions’ in thousan& distribution

Hormonesand agents effectinghormonal

mechanisms... . . . . . . . . . . . . . . . . . .

AdrensJcorticosteroids.. . . . . . . . . . . . .

Estrogenarrdprcgastins . . . . . . . . . . . .

Bloodglucoseregulator . . . . . . . . . . . .

Agantsusad totreatthyroid disessa . . . . .

Contraceptiveagents. . . . . . . . . . . . . . .

Immunologicawards. . . . . . . . . . . . . . . . .

Vacchesandantisamrns . . . . . . . . . . . .

Skin/muoousmembmne . . . . . . . . . . . . . .

Dennatolcgics. . . . . . . . . . . . . . . . . . .

Necrologicdrugs. . . . . . . . . . . . . . . . . . .

Drugsused in extrapyramidal

rnovamentdisorders . . . . . . . . . . . . . .

Drugsusedto treat skeletal muscle

hyperactivity . . . . . . . . . . . . . . . . . . .

Antioonvulsants. . . . . . . . . . . . . . . . . .

Oncolytics. . . . . . . . . . . . . . . . . . . . . . .

Antinaoplsstk.. . . . . . . . . . . . . . . . .

OphthalmicDrugs . . . . . . . . . . . . . . . . . .

Agents usedtotrest glaucoma. . . . . . . . .

OoularanO-infectiveand sntiirrlfammatoryagents. . . . . . . . . . . . . . .

Otologicdrugs . . . . . . . . . . . . . . . . . . . .

Top-&l oOcprepara60ns. . . . . . . . . . . . .

Drugs USCKJinvertigo,nwtii

sickness,andvomiting. . . . . . . . . . . . .

Drugsusadfofrelief of pain. . . . . . . . . . . .

DrugsUSWIto treat mgreine and other

headaches . . . . . . . . . . . . . . . . . . . .

Dmgsusd ingotrl . . . . . . . . . . . . . . . .

Drugs usdincanfral pdrrsyndrornes. . . .

Antipsrasiticegents . . . . . . . . . . . . . . . . .

Res@atorytractdrugs... . . . . . . . . . . . .

Bred-mdiiators,ant ksthmatice . . . . . . . .

Nassldecongastents. . . . . . . . . . . . . . .

AMiWaiie,expdmnta,mudytica.. . . .

Antihistamines. . . . . . . . . . . . . . . . . . .

UnolaesMacVmiscellanaous.. . . . . . . . . . . .

67,549

19,703

12,341

16,322

7,308

9,619

19,337

19,286

43,777

41,168

14,140

1,830

7,805

4,474

5,776

4,632

30,704

10,287

14,882

4,734

1,640

3,095

77,444

38,8%

37,5tXl

2,521

1,842

87,491

24,587

22,423

18,750

21,627

43.088

8.89

259

1.83

2.15

0.88

1.27

2.55

2.54

5.76

5.42

1.68

0.21

1.04

0.59

0.76

0.84

4.04

1.35

1.97

0.62

0.22

0.41

10.20

4.83

4.95

0.33

0.24

11.52

3.24

295

2.47

2.86

5.67

%3rapeMc Clewbticm em basedonthe etardsrddrugc!assiiticae WA inthe NationalDrugCode Dirwhxy, 13S5Editim(4).
Advance Data No. 232 ● March 25,1993

Table 5. Number and percent of office vlslts and drug mentions, percent of office visits during which one or multiple drugs were used by

physician Identity and speciai~ United States, 1990

0ri5cevisits Drug visits ‘ Drug mentions

Drug

Number in Percent Dnq One drug Two drugs Three drugs Number in Percent utilization

Physician identity end specialty thousands distribution visits used used or more used thousands distribution rata

Ail physicians . . . . . . . . . . . . .

Physician identity

Doctor of medicine. . . . . . . . . .

Doctor of osteopathy . . . .

Specialty

General and family practice . . . .

Internal medicine. . . . . . . . . . .

Pediatrics . . . . . . . . . . . . . . .

Obstatrice and gynecology. . . . .

Ophthalmology . . . . . . . . . . . .

Orthopedic surgery . . . . . . . .

General surgery . . . . . . . . . . .

Dermatology . . . . . . . . . . . . .

Psychiatry . . . . . . . . . . . . . . .

Otolatyngology. . . . . . . . . . . .

Urological surgery. . . . . . . . . .

Cardiovascular disease. . . . . . .

Neurology . . . . . . . . . . . . . . .

Aliother specialties . . . . . . . . .

704,604 100.00 60.26 32,74 15.73 11.78 759,406 100.00 1.08

665,317 94.42

39,287 6.58

59.76 32.60 15.56 11.61 710,092 93.51 1.07

68.45 35.11 18.71 14.63 49,314 6.42 1.26

209,788 26.77

86,622 13.71

61,146 11.52

61,243 6.69

43,s42 6.22

32,917 4.67

22,402 3.16

24,009 3.41

20,863 2.96

17,959 2.55

9,546 1.35

11,240 1.60

6,226 0.68

66,6?i6 9.47

66.67

74.46

66.65

43.78

43.78

26.08

31.07

63.99

51.31

44.64

40.37

76.53

68.27

62.70

36.42

33.70

45.80

32.30

26.56

20.37

16.3S

29.46

26.66

27.95

30.23

19.47

33.16

26.05

20.16

19.82

15.82

6.89

10.63

4.19

5.40

17.86

16.22

11.23

7.70

17.45

18.49

15.33

12.08

20.97

5.13

2.59

6.40

1.52

7.30

16.55

8.21

5.46

2.44

41.60

14.62

21.33

251,960

149,370

76,370

35,667

30,806

11,035

12,597

29,572

18,516

12,341

5,145

25,153

7,566

93,265

33.18

19.87

10.06

4.70

4.06

1.45

1.66

3.89

2.44

1.63

0.66

3.31

1.CK1

12.26

1.20

1.55

0.94

0.58

0.70

0.34

0.56

1.23

0.66

0.69

0.54

2.24

1.22

1.40

‘Drug visksare percsntdiatribm’ons of all vista.

Tabie 6. Number snd percent of office visits and drug mentions, percent of office visits during which one or multiple drugs were used by

age and sex of Patient United States, 1980

Ofiice visits Drug ViSitS ‘ Drug mentions

Number in

Dmg

Peroerrt Dnq One drug TWO drugs Three drugs Number in Percent

Age and sex

utilization

thousands distribution visits used used or more used thousands distribution rate

All patients . . . . . . . . . . . . . . .

Age

Under 15years . . . . . . . . . . . .

15-24 years . . . . . . . . . . . . . .

25-44 years . . . . . . . . . . . . . .

45-64 years . . . . . . . . . . . . . .

65-74 years . . . . . . . . . . . . . .

75 years And over . . . . . . . . . .

Sex

Famale . . . . . . . . . . . . . . . . .

Male . . . . . . . . . . . . . . . . . .

Sex and age

Female:

Under 15yeers . . . . . . . . . .

15-24 yeare . . . . . . . . . . . .

25-44 years . . . . . . . . . . . .

45-64 years . . . . . . . . . . . .

65-74 yeare . . . . . . . . . . . .

75yeare and over . . . . . . . .

Male:

Under 15 years . . . . . . . . . .

15-24 years . . . . . . . . . . . .

25-44 years . . . . . . . . . . . .

45-64 yeare . . . . . . . . . . . .

65-74 years . . . . . . . . . . . .

75yeareand over . . . . . . . .

704,604

136,427

68,918

194,195

149,766

66,422

66,856

427,151

277,452

65,229

45,165

132,163

89,697

51,529

43,349

73,198

23,753

62,012

60,089

34,693

23,507

I00.00

19.65

9.76

27.56

21.26

12.27

9.49

60.62

39.36

9.26

6.41

16.76

12.73

7.31

6.15

10.39

3.37

8.80

8.53

4.95

3.34

32.74

40.56

35.45

31.99

30.31

26.56

26.62

32.93

32.46

41.76

36.01

32.53

30.79

26.76

27.05

39.46

34.36

30.a5

29.59

28.26

26.40

60.26 15.73 11.78 759,408 IOQ.oo 1.06

0.90

0.90

0.90

1.21

1.38

1.47

61.95

57.46

54.72

62.08

64.71

65.66

16.05

14.59

14.44

16.75

16.66

16.54

5.35

7.42

6.29

15.01

19.49

22.51

124,965

61,974

174,964

180,623

118,867

97,962

16.46

6.16

23.04

23.76

15.65

12.90

60.78

59.46

15.67

15.52

11.97

11.48

465,574

293,631

61.31

38.68

1.09

1.06

62.66

57.09

54.47

63.24

66.79

6s.45

16.04

14.45

13.69

17.37

16.17

17.91

5.05

6.64

8.25

15.06

19.67

23.46

59,1es

39,246

117,749

108,808

73,075

66,429

7.79

5.17

15.51

14.47

9.62

8.75

0.91

0.67

0.89

1.23

1.42

1.53

16.07

14.86

16.02

15.84

14.43

14.02

5.62

8.91

8.36

14.91

18.93

20.73

65,630

22,726

57,215

70,715

45,792

31,553

6.67

2.88

7.53

9.31

6.03

4.15

0.30

0.86

0.92

1.16

1.31

1.34

61.15

58.15

55.25

60.34

61.63

61.14

‘Drugvisiissrsparsentdistributionsof all visits.
Advance Data No. 232 ● March 25,1993 9

Table 7. Number and percent of office visits and drug mentions, percent of office vislta during which one or multiple drugs were used by

race and ethnicity of patient United States, 1980

0r7ice visits Drug visits1 Drugmentions

Drug

Numberin Percent Dnq Ona drug Twodrugs 17rraedrugs Numberin Percent utiiizzMrrr

Race and atirnicity Urousarrds distribution vkits used or mom usad ttrousands disfrlwtron rate

Allpatiente . . . . . . . . . . . . . . . . . . 704,604 100.00 60.26 32.74 15.73 11.78 759,408 100.00 1.08

Race

Whtie . . . . . . . . . . . . . . . . . . . . .

Black . . . . . . . . . . . . . . . . . . . . .

Other . . . . . . . . . . . . . . . . . . . . .

Unspecified’ . . . . . . . . . . . . . . . . .

597,306

62,317

23,684

21,287

84.77

8.84

3.36

3.02

59.88

67.91

60.48

48.21

32.86 15.47

33.18 18.83

32.89 16.55

ZS.04 13.33

11.%

15.80

11.03

6.84

837,424

80,536

24,715

16,731

83.84

10.61

3.25

2.20

1.07

1.28

i .04

0.78

Ethnicity

Hispanic . . . . . . . . . . . . . . . . . . .

Non-Hspanic . . . . . . . . . . . . . . . .

UnspecifiedZ. . . . . . . . . . . . . . . . .

35,468

619,747

49,401

5.03

87.96

7.01

62.31

60.71

53.07

38.21 16.13

32.88 15.79

30.91 14.75

9.97

12.23

7.41

37,042

679,551

42,813

4.88

88.48

5.84

1.04

1.10

0.87

‘Orugvis”b arepemantdletributiomsC4all visii.

‘Asii or PacificLskrrrdaf, andAnericanIndkmorNes+cenNative.

Table 8. Number and percent of offica visits and drug mentions, percent of offlca visits during which ona or multiple drugs were used by

physician dlagnosaa and ICD-9-CM code= United States, 1990

or%cavisits Drug ViSitS2 Drugmenfionss

Drug

Physiciandiagnosesand Numberin Percent Drug Ona drug Two drugs lhae drugs

\CD-9-Okf code’

Numberin Percent Utili.?eticfl

thousands distributionWts2 used usad ornroreu3ad thousands distribution rate

All diagnoses . . . . . . . . . . . . . . . . . . . . . . . . .

Infectious and parasitic diseases. . . . . ...001-139

Neoplasm. . . . . . . . . . . . . . . . . . ...14&238

Endocrine, nutritional and metabolic diseesas,

andimmunily cfhorders . . . . . . . . . ...24&289

Diseases of the endocrine glands. . . ...240-259

obesity. . . . . . . . . . . . . . . . . . . . . . ...278

Diseases of blood and blocd-fomsing

organs . . . . . . . . . . . . . . . . . . . . ...28&288

Mental disorders . . . . . . . . . . . . . . . ...280-319

Nonpsychotio dkxxdera . . . . . . . . . ...300-316

Diseases of nervous system tmd sense

organs . . . . . . . . . . . . . . . . . . . . ...320-388

Diseases of the central nervous system ..320-349

Eyedisordera . . . . . . . . . . . . . . . . ..380-379

Otiismadia . . . . . . . . . . . . . . . . . . . . ...382

Diseases of oirculatorj system . . . . . . ...380-459

Essential hypertension . . . . . . . . . . . . . ...401

Ischemic heart disease. . . . . . . . . . ...410414

Diseases of respiratory system . . . . . . ...480-519

Acute upper respirator infection . . . . . . ...485

Asthma . . . . . . . . . . . . . . . . . . . . . . ...493

Diseases of digestive system . . . . . . . ...520-579

Diseases of gerrifourinary system. . . . . ...580-828

Male genitourinaty system . . . . . . . ...600-808

Female genitourinary sysfem. . . . . . ...614-628

Diseases of skin and subcutaneous

tissue . . . . . . . . . . . . . . . . . . . . . ...880-708

Disease of musculoskelatal system . . . . . .710-738

Arthopathies . . . . . . . . . . . . . . . . . . .710-716

Symptoms, signs, and illdahed

mndtiions . . . . . . . . . . . . . . . . . . ...780-788

Injury and poisoning. . . . . . . . . . . . . . ..600-889

Normal pregnancy . . . . . . . . . . . . . . . . . .. VOZ2

Health supervision of infant or child . . . . . . . . V020

Other orundeterminad’ . . . . . . . . . . . . . . . . . .

704,604

27,075

21,841

29,456

19,289

3,840

3,552

100.00

3.84

3.11

4.18

2.74

0.55

0.50

4.25

3.21

11.37

0.88

5.48

2.38

7.95

3.68

1.31

14.23

265

1.01

3.71

5.83

0.84

2.89

5.23

6.88

1.81

3.88

7.26

3.34

2.22

12.41

80.28

88.83

37.72

70.26

74.22

60.87

73.86

68.79

51.31

61.88

77.43

43.26

88.48

79.21

83.68

80.11

88.35

85.80

91.41

61.49

58.34

60.38

57.48

88.73

84.88

78.53

52.88

48.38

32.88

48.22

33.91

32.74

48.32

17.13

3292

30.89

51.98

40.67

33.12

30.48

3a.03

35.18

28.04

58.92

28.88

38.46

16.94

40.01

43.45

20.42

33.40

37.39

33.83

37.86

36.80

38.53

37.67

28.59

28.85

24.73

25.04

21.72

15.73

14.32

9.25

17.61

18.33

5.77

20.58

16.02

12.68

15.84

23.83

11.77

20.82

19.71

23.38

18.17

28.58

31.31

22.20

17.14

13.05

11.08

14.87

20.32

15.48

18.49

13.64

9.54

6.87

16.85

7.33

11.78

6.19

11.35

19.74

25.00

3.13

12.52

9.85

7.85

7.61

18.58

7.47

5.74

29.54

24.14

45.00

19.77

11.04

48.79

10.95

5.80

5.84

4.84

13.58

12.88

22.17

9.74

5.20

1.26

6.22

4.84

759,408

26,208

17)350

43,509

32520

2,926

4,581

30,276

19,588

77,481

7,282

30,388

25,185

103,581

47,309

21,525

185,863

27,143

18,077

26,576

34,480

3,370

16,882

45,588

53,385

19,883

25,469

33,858

9,973

12,2S2

48,928

100.00

3.45

2,28

5.73

4.28

0.38

0.60

3.89

2.58

10.2U

0.88

4.00

3.32

13.84

6.23

2.83

21.85

3.57

2.38

3.76

4.54

0.44

224

6.00

7.03

2.82

3.35

4.43

1.3i

1.83

6.18

1.08

0.97

0.79

1.48

1.88

0.76

1.28

1.01

0.87

0.87

1.52

0.79

1.20

1.85

1.73

234

1.85

1.45

2.63

1.08

0.84

0.75

0.83

1.24

1.13

1.58

0.84

0.88

0.42

0.78

0.54

22,612

80,128

4,788

36,803

21,043

55,888

27,310

9,210

100,284

16,876

7,137

28,154

41,087

4,479

20,377

47,101

12,784

27,221

51,134

23,581

15,676

87,454

‘8aeed M the IrrternatiorrfdCkrss~i?an of D/seasss, @hRe!4sbfr, Clinical Modh%atkm(lCO-9-CM) (5).

2Drugvisle arepementdktributiomsof all visits.

31ncludssall dmgmentionswhetheror notassodatsdwitha principaldmgnoafs.

‘Inchrdascomplkationsof pregnancy,chitibirthendthepuarperium(SW-876~ ccmganitslananelii (740-759); cwteincondii originathgin thep.nstsl pwirrd(760-7~ aupplemmtsry

claedfcetiens(WM-VOS2, exdud~ V020 andV022~endbhnka,nmcodsbls,d illegibled~
10 Advance Data No. 232 ● March 25,1993

Technical notes Table L Relative standard errors for estimated number of drug mentions: National

Ambulatory Medical Care Survey, 1990

Source of data and sample

design

The information presented in this

report is based on data collected by

means of the National Ambulatory

Medical Care Survey (NAMCS) from

January 1990-December 1990. The

target universe of NAMCS includes

office visits made in the United States

by ambulatory patients to

nonfederally employed physicians who

are principally engaged in office

praetiee, but not in the specialties of

anesthesiology, pathology, or

radiology, or physicians who are

principally engaged in teaching,

research, or administration.

Telephone contacts, nonoflice visits,

and visits made to hospital emergency

or outpatient departments are also

excluded.

A multistage probability sample

design is used in NAMCS, involving

primary sampling units (Psu’s),

physician practices within PSU’S, and

patient visits within physician

practices. The PSU’s are counties,

groups of counties, county equivalents

(such as parishes or independent

cities), or towns and townships (for

some PSU’S in New England). For

1990 a sample of 3,063 non-Federal,

office-based physicians were selected

from master files maintained by the

American Medical Association and

the American Osteopathic

Association. The physician response

rate for the 1990 NAMCS was

74 percent. Sample physicians were

asked to complete Patient Records

(figure 1) for a systematic random

sample of office visits occurring

during a randomly assigned l-week

reporting period. Responding

physicians completed 43,469 patient

records and were asked to report up

to 5 drugs utilized.

Charaeteristies of the physician’s

practice, such as primary specialty

and type of practice, were obtained

from the physicians during an

induction interview. The U.S. Bureau

of the Census, Housing Surveys

Branch, was responsible for the

survey’s data collection. Processing

Specialty group

Estimated number of drug mentions

in ttrouwnds Afl A B c D

100 . . . . . . . . . . . . . . . . . . . . . . 82.6

171 . . . . . . . . . . . . . . . . . . . . . . 83.2

200 . . . . . . . . . . . . . . . . . . . . . . 56.5

300 . . . . . . . . . . . . . . . . . . . . . . 47.9

338 . . . . . . . . . . . . . . . . . . . . . . 45.1

400 . . . . . . . . . . . . . . . . . . . . . . 41.5

500 . . . . . . . . . . . . . . . . . . . . . . 37.2

600 . . . . . . . . . . . . . . . . . . . . . . 34.0

638 . . . . . . . . . . . . . . . . . . . . . . 33.0

700 . . . . . . . . . . . . . . . . . . . . . . 31.6

775 . . . . . . . . . . . . . . . . . . . . . . 30.0

800 . . . . . . . . . . . . . . . . . . . . . . 28.6

900 . . . . . . . . . . . . . . . . . . . . . . 27.9

I,ooo . . . . . . . . . . . . . . . . . . . . . 26.6

1,144 . . . . . . . . . . . . . . . . . . . . . 24.9

2,000 . . . . . . . . . . . . . . . . . . . . . 19.1

5,000 . . . . . . . . . . . . . . . . . . . . . 12.7

Io,ooo . . . . . . . . . . . . . . . . . . . . 9.7

Relafive standard error in percent

72.8

56.0

51.9

42.7

40.3

37.3

33.6

30.9

30.0

26.8

27.5

27.2

25.8

24.6

23.3

18.6

13.8

11.7

35.5

32.4

31.7

30.4

30,0

29.7

29.2

28.9

28.8

28.7

28.6

26.6

26.4

28.3

26.2

27.9

27.6

27.5

79.2

61.9

57.7

48.5

46.1

43.1

39.6

37.0

36.2

35.1

33.9

33.5

32.3

31.3

30.0

26.1

22.5

21.2

37.1

30.0

28.4

24.8

23.9

22.7

21.4

20.5

20.3

19.9

19.5

19.3

18.9

18.6

18.2

17.0

15.9

15.6

A General end famiiy pfadke, internal medicine.

B. Generalsurgery, neurology.

C. “All othei” spesieities.

D. Pedietrica,obstetricsandgynat.alqfy,orthopsdissurgery,csrdiovsaculerd~eese, dermatology,urology,PWhiaW,

ophthalmology, otorhinoleryngology, end dootore of osteopathy.

13+arnple of U* of talk An aggregate estimate of 2 million drug mentions by a cardiovsewler disease specialist has a relative

standard eatimete of 17.0 percent or a standard error of s40,004 drug mem-ons (17.0 percent of 2 million).

operations and medical coding were

performed by the National Center for

Health Statistics, Hospital Discharge

and Ambulatory Care Survey Seetion,

Research Triangle ParlG North

Csrolina.

Sampling errors

The standard error is primarily a

measure of the sampling variability

that occurs by chance when only a

sample, rather than an entire

universe, is surveyed. The relative

standard error of an estimate is

obtained by dividing the standard

error by the estimate itse~, the result

is then expressed as a percent of the

estimate. Relative standard errors of

the estimated number of drug

mentions are shown in table I ad

relative stsndsrd errors of the

estimated numbers of office visits are

shown in table II.

Alternatively, relative standard

errors for aggregate dmg mentions

and visits may be calculated using the

following general formula, where x is

the aggregate of interest in

thousands, and A and B are the

appropriate coefficient from table V.

RSE(X) =

$

++ 100.0

Standard errors for estimated percent

of drug mentions are shown in

table III and for estimates of the

percent of visits in table IV.

Similarly, relative standard errors

for pereent maybe calculated using

the following general formula, where

p is the percent of interest and x is

the denominator of the pereent in

thousands, using the appropriate

coefficient from table V.

RSE(p)= {

—,

B.(l-p) ~m ~

.

p-x

Adjustments for nonresponse

Estimates horn NAMCS data

were adjusted to aeeount for sample

physicians who were in scope but did

not participate in the study. This

adjustment was calculated to

minimize the impact of response on

final estimates by imputing to
Advance Data No. 232 ● March 25.1993 11

nonresponding physicians data from

visits to similar physicians. For this

purpose, physicians were judged

similar if they had the same specialty

designation and practiced in the same

Psu.

Test of significance and

rounding

In this report the determination

of statistical significance is based on a

two-sided t-test with a critical value

of 1.96 (0.05 level of confidence).

Terms relating to differences such as

“greater than” or “less than,”

indicate that the difference is

statistically significant. In the tables

estimates of office visits and drug

mentions have been rounded to the

nearest thousand. Consequently,

estimates will not always add to

totals. Rates and percents were

calculated from originrd unrounded

figures and do not necessarily agree

with percents calculated from

rounded data.

Definition of terms

Ambulatory patieru-An

ambulatory patient is an individual

seeking personal health services who

is not currently admitted to any

health care institution on the

premises.

Physician-A physician is a duly

licensed doctor of medicine (M.D.) or

doctor of osteopathy @.C).) who is

currently in office-based practice and

who spends some time caring for

ambulatory patients. Excluded from the

NAMCS are physicians who are

hospital-bead, who specialize in

anesthesiology, pathology, or radiolo~

who are federally employe@who treat

only institutionalized patientq or who

are employed full time by an institution

and spend no time seeing ambulato~

patients.

Ojice-Offices are the premises

physicians identify as locations for

their ambulatory practice; these

customarily include consultation,

examination, or treatment spaces that

patients associate with the particular

physician.

Visit-A visit is a direct personal

exchange between an ambulatory

Table IL Relative standard errors for eetimated number of office visik National

Ambulatory Medical Care Survey, 1990

Bpm”dfy group

Estimated number of offioa visits

in thousands All A B c D

100 . . . . . . . . . . . . . . . . . . . . . . 68.1

110 . . . . . . . . . . . . . . . . . . . . . . 64.9

200 . . . . . . . . . . . . . . . . . . . . . . 46.2

231 . . . . . . . . . . . . . . . . . . . . . . 44.9

300 . . . . . . . . . . . . . . . . . . . . . . 39.4

370 . . . . . . . . . . . . . . . . . . . . . . 35.5

400 . . . . . . . . . . . . . . . . . . . . . . 34.2

468 . . . . . . . . . . . . . . . . . . . . . . 31.6

500 . . . . . . . . . . . . . . . . . . . . . . 30.6

520 . . . . . . . . . . . . . . . . . . . . . . 30.0

700 . . . . . . . . . . . . . . . . . . . . . . 26.0

1,000. . . . . . . . . . . . . . . . . . . . . 21.8

2,000 . . . . . . . . . . . . . . . . . . . . . 15.6

5,000 . . . . . . . . . . . . . . . . . . . . . 10.3

100,000 . . . . . . . . . . . . . . . . . . . 4.3

Relatiie shndard error in percent

66.2

53.6

40.1

37.5

33.1

30.0

29.0

27.0

26.2

25.7

Z2.5

19.4

14.9

11.3

6.4

41.9

40.2

31.7

30.0

27.4

25.6

25.0

23.9

23.5

23.2

21.6

20.0

18.0

16.7

15.9

59.6

57.0

43.2

40.5

36.1

33.1

32.0

30.0

28.3

26.8

25a

22.6

18.7

15.8

13.6

31.2

30.0

23.9

22.7

20.9

19.6

19.2

18.4

18.1

16.0

16.8

15.6

74.4

13.6

13.0

A, General and farniiy Pram”ca and internal madkkw.

B. Orthopedic surgery.

C. “N ethef’ s~”aitiea.

D. Pediatrics, gerwal surgeiy, obstetrics acd gynadcgy, cardiovascular disease, dermatology, WOW, psychiatry, neurokw,

ophthalmology, OtorhindaryrWlc-gy, and dostors of osteopathy.

Eanple of use of table: An aggregate estimate of 2 million visia to a cwd~ Iar dbeaa SW”SM has a relatiwestandard

estimate of 14.4 percent or a atandwd error ef 23S,000 viets (14.4 persent of 2 milliin).

Table Ill. Standard errora for percents of estimated numbers of drug mentionx National

Ambulatory Medical Care Survey, 1990

Estimated percent

Base of percent drug mentions

in tfrousarrds lor S9 5or95 Ioor%l 20 or 80 30 or 70 50

8tandard errors in percentage points

200 . . . . . . . . . . . . . . . . . . . . . . 5.8 12.7 17.5 23.3 26.7 28.1

500 . . . . . . . . . . . . . . . . . . . . . . 3.7 6.0 11.1 14.7 16.9 18.4

1,000 . . . . . . . . . . . . . . . . . . . . . 26 5.7 7.6 10.4 11,9 13.0

2,000 . . . . . . . . . . . . . . . . . . . . . 1.8 4.0 5.5 7.4 6,4 9.2

5,000 . . . . . . . . . . . . . . . . . . . . . 1.2 2.5 3.5 4.7 5.3 5.6

Io,ooo . . . . . . . . . . . . . . . . . . . . 0.8 1.8 2.5 3.3 3.6 4.1

13,000 . . . . . . . . . . . . . . . . . . . . 0.7 1.6 2.2 2.9 3.3 3.6

20,000 . . . . . . . . . . . . . . . . . . . . 0.6 1.3 1.7 2.3 2.7 2.9

5moo.. . . . . . . . . . . . . . . . . . . 0.4 0.8 1.1 1.5 1.7 1.8

100,000 . . . . . . . . . . . . . . . . . . . 0.3 0.6 0.8 1.0 1.2 1.3

600,000 . . . . . . . . . . . . . . . . . . . 0.1 0.2 0.3 0.4 0.5 0.5

Example et uasoffsblw An estimate of30pwantbaa sdo+Ian aWWSte ef 13 milhdmg merdienshea aetendard enor et

3.3 paoent or a relative etarvhrd error of 11.0 percent (3.3 pwcant dtiad by 30 pareant).

patient and a physician (or a stak

member working under the

physician’s supervision), for the

purpose of seeking care and

rendering personal health services.

Drug visit-A drug visit is a visit

in which medication was prescribed

or provided by the physician.

Drug mention-A drug mention is

the physician’s entry of a

pharmaceutical agent-by any route

of administration-for prevention,

diagnosis, or treatment. Generic as

well as brand-name drugs are

include& as are nonprescription and

prescription drugs. Along with all new

drugs, the physician also records

continued medications if the patient

was specihdly instructed during the

visit to continue the medication.

Drug utilization rate—The average

number of medications per visit.

Control status-Controlled

medications, because of their

signMcant potential for dependence

or abuse and their possible diversion
12 Advance Data No. 232” March 25,1993

Table IV. Standard errors for percents of estimated numbers of office visits: National

Ambulatory Medical Care Survey, 1990

Estimated percent

Base of percent visits

in thousands loree 5 or 95 10 or 90 20 or 80 30 or 70 50

Standard errors in percentage points

200 . . . . . . . . . . . . . . . . . . . . . . 4.8 10.5 14.4 19.2 22.0 24.0

500 . . . . . . . . . . . . . . . . . . . . . . 3.0 6.6 9.1 12.2 13.9 15.2

1,000 . . . . . . . . . . . . . . . . . . . 2.1 4.7 6.4 8.6 9.8 10.7

2,000 . . . . . . . . . . . . . . . . . . . . 1.5 3.3 4.6 6.1 7.0 7.6

5,000 . . . . . . . . . . . . . . . . . . . . . 1.0 2.1 2.9 3.6 4.4 4.8

10,000 . . . . . . . . . . . . . . . . . . . . 0.7 1.5 2.0 2.7 3.1 3.4

13,000 . . . . . . . . . . . . . . . . . . . . 0.6 1.3 1.8 2.4 2.7 3.0

20,000 . . . . . . . . . . . . . . . . . . . . 0.5 1.0 1.4 1.9 2.2 2.4

50,000 . . . . . . . . . . . . . . . . . . . . 0.3 0.7 0.9 1.2 1.4 1.5

Ioo,ooo . . . . . . . . . . . . . . . . . . . 0.2 0.5 0.6 0.9 1.0 1.1

600,000 . . . . . . . . . . . . . . . . . . . 0.1 0.2 0.3 0.4 0.4 0.4

Exampleofuseof tsblizAnestimate of30pecentbssed onmaggregateof 13millionvisiihss astsndsrderrorof 2.7

percent or a relative standard error or 9,0 percent (2.7 percent dwided by 30 percent).

Table V. Coefficients appropriate for detarmlning relative standard errors by type of

eetimateand physician groups:National AmbulatoryMedkrd CareSurvey,l 990

CoefKcient

Type of estimate and physician group A B

Drug metitons

Overelltotals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.00259409 67.9417652

General andfamily practica,intemal medicine. . . . . . . . . 0.00866244 52.1276030

Generalsurgery, neurology. . . . . . . . . . . . . . . . . . . . 0.07521297 5.06446S43

“Allother’’specialtiesgroup. . . . . . . . . . . . . . . . . . . . 0.03665601 5S.8324479

Doctorsofostaopathy,pediatrice,obstetricsand

gynecology, orthopedic surgery, cardiovascular

disease, psychiatry, ophthalmology, and

otorhinolaryngolcgy . . . . . . . . . . . . . . . . . . . . . . . . (0.02306475 11.4557235

visits

Overalltotals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ( 46.1954141

General andfamily practice andintemal medicine. . . . . . ( 30.6610803

Orthopedicsurgery . . . . . . . . . . . . . . . . . . . . . . . . . ( 15.0649723

“Allother’’s pecialtiesgroup. . . . . . . . . . . . . . . . ( 33.7056023

Doctors ofoateopathy, pediatrics, general surgery,

obstetrica andgyneculogy, cardiovascular diseaee,

dermatology, urology, psychiatry, neurology,

ophthalmology, andotorhinolaryngology . . . . . . . . 0.01684S12 8.03232318

0.00138367

0.00659347

0.02504087

0.01820066

into illicit channels, areregulatedl

under Federal law by the Department

of Justice, Drug Enforcement Agency

(DEA). The Controlled Substance

Act of 1970 characterizes each

controlled drug into one of five

schedules. Schedule I drugs, like

heroin and LSD, have a higher

potential for abuse and no current

accepted medical usefulness for

treatment in the United States.

Schedule I drugs are outside the

scope of this report. Each successive

schedule, II-V, reflects a decreasing

degree of dependence and potential

for abuse.

Trade name disclaimer

The use of trace names is for identification

only and doea not imply endorsement by the

Public Health Service, U.S. Department of

Health and Human Services.

Suggested citation

Nelson CR. Drug utilization in office practice,

National Ambulatory Medical Care Survey,

1990. Advance data from vital and health

statistic no 232. Hyattsville, Maryland:

National Center for Health Statistics. 1983.

Copyright information

All material appearing in this report is in the

public domain and may be reproduced or

copied without permission; citation as to

source, however, is appreciated.

National Center for Health Ststistia

Director

Manning Feinleib, M. D., Dr. P.H.

Acting Deputy Director

Jack R. Anderson

U.S. DEPARTMENT OF HEALTH AND

HUMAN SERVICES

Public Health Service

Centers for Disease Control and Prevention

National Center for Health Statistics

6525 Belcrest Road

Hyattsville, Maryland 20782

OFFICIAL BUSINESS

PENALTY FOR PRIVATE USE, $300

To receive this publication regularly, contact

the National Center for Health Statistics by

calling 301-436-8500

DHHS Publication No. (PHS) 93-1250
Number 234 ● May 13, 1993

Advance

Data

From Vital and Health Statisticsofthe CENTERS FOR DISEASE CONTROL AND PREVENTION/National Center for Health Statistics

Office Visits to Urologists: United States,

by David A. Woodwell, Division of Health Care Statistics

During 1989 and 1990 an average

of 9,852,000 office visits were made

annually to urologists in the United

States. The information was collected

by means of the National Ambulatory

Medical Care Survey (NAMCS), an

ongoing probability sample survey of

the private office-based, non-Federal

physicians practicing in the United

States. The NAMCS excludes visits

made to hospital emergency or

outpatient departments. The survey

also excludes physicians who

specialize in anesthesiology,

pathology, or radiology and those

physicians principally engaged in

teaching, research, or administration.

The survey was conducted annually

from 1973 through 1981, again in

1985, and resumed as an annual

survey in 1989 by the Division of

Health Care Statistics, National

Center for Health Statistics, Centers

for Disease Control and Prevention,

Participation in the suwey is

voluntary.

The results published in this

report are from the 1989 and 1990

NAMCS, which were conducted in

identical fashion using the same

survey instrument, definitions, and

procedures. The two data sets were

combined to obtain more reliable

estimates. The estimates, including

the number of visits, drug mentions,

and visit rates, are annual averages,

not two-year totals. The national

estimates are calcdated from a

sample, not the entire universe of

visits to urologists, and are therefore

subject to sampling variability. The

technical notes at the end of the

report provide guidelines for judging

the precision of the estimates.

Definitions of key terms used in the

survey are also provided. The Patient

Record form used in data collection

is shown in figure 1 and will be useful

when reading the survey results.

Of the visits made to urologists,

about 87 percent were to physicians

who reported they were board

certiiied in urology, almost 11 percent

were to physicians who reported no

board certiiicatioq and approximately

1 percent were to physicians who

reported they were board cxxtifled in

surgery.

Data highlights

The average annual 9.9 million

visits to urologists represented

1.4 percent of all visits to office-based

ambulatory care physicians in the

United States during 1989–90, which

is 4 visits per 100 persons and places

urology as the 12th specialty of the 13

most frequently visited (table 1). In

the 1975-and i976 N~CS, “

urologists had an annual average of

10,364,000 visits or 1.8 percent of all

visits to office-based ambulatory care

physicians and a visit rate of 5 visits

per 100 persons (l). These numbers

are not statistically significantly

different from the current data.

Patient characteristics

Asshown in table 2 most visits to

the urologist are made by patients 25

years of age and over (about

91 percent). The percent of visits

increases significantly by age, from

nearly 4 percent for patients 15-24

years of age, to around 22 percent for

patients 2544 years of age. Since

1975–76, the percent distribution of

visits by age group has remained

statistically unchanged for all except

patients 65 years of age and over.

This age group accounted for about

28 percent of the visits to urologists in

1975–76 and about 44 percent in

1989–90. The visit rate increased from

1 visit per 100 persons for patients

under 15 years of age to 17 visits per

100 persons for patients 75 years of

age and over. Speciikally, the visit

rate more than doubled for patients

65–74 years old compared with

# wwrc&o

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patients 45-64 years old, from 6 to 13

visits per 100 persons.

Males made the majority of visits

to urologists (72 percent) while

females made the majority of visits to

all physicians (about 60 percent).

Males 25 years of age and over made

almost 66 percent of the visits to

urologists, and those 25-44 years of

age accounted for 5 times more visits

than the 15-24 year olds. The visit

rate for males rose from 1 visit per

100 persons for patients under 15

years of age to 33 visits per 100

persons for patients 75 year3 of age

and over. The most significant

increase in the visit rate was for male

patients 65-74 years of age with 23

visits per 100 persons compared with

8 visits per 100 persons for patients

45-64 years old. Males also showed a

significant increase in the visit rate

between the 65-74 and 75 years and

over age groups, from 23 to 33 visits

per 100 persons (table 2).

The percent distribution of visits

for females was simiIar in that la

significant increase occurred for

female patients 2544 years old. As

compared with 1975-76, the percent

of visits by males to urologists has

increased by about 21 pereent while

the percent of visits by females has

decreased by about 30 percent. The

visit rate for males was 3 times the

rate for females, 6 and 2 visits per

100 persons, respectively. Visit rates

for males were significantly higher
Advance Data No. 234 ● May 13, 1993 3

Table 1. Average annual number, percent distribution, and rate of office visits, by

physician specialw United States, 1869-80

Average annual Average annual

number of w“sita Percerd number of viaits

Physician specialty in thousands distribution per 100 persons

Allvisite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 698,653 100.0 265

General and family practice . . . . . . . . . . . . . . . . .

Internal medicine . . . . . . . . . . . . . . . . . . . . . . . .

Pediatrics . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Obstetrics andgynecology . . . . . . . . . . . . . . . . . .

Ophthalmology . . . . . . . . . . . . . . . . . . . . . . . . .

Orthopedic surgery . . . . . . . . . . . . . . . . . . . . . .

Dermatology . . . . . . . . . . . . . . . . . . . . . . . . . .

Generalsurgery . . . . . . . . . . . . . . . . . . . . . . . .

Psychiatry . . . . . . . . . . . . . . . . . . . . . . . . . . . .

otolaryngology . . . . . . . . . . . . . . . . . . . . . . . . .

Cardiovasculardisease . . . . . . . . . . . . . . . . . . . .

Urologicalsurgery . . . . . . . . . . . . . . . . . . . . . . .

Neurology . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Allotherspeciaities . . . . . . . . . . . . . . . . . . . . . .

208,045

87,719

64,280

59,812

41,302

34,033

25,164

23,891

18,790

16,957

11,040

9,652

6,167

71,603

29.8

12.8

12.1

8.6

5.9

4.9

3.8

3.4

2.7

2.4

1.6

1.4

0.9

10.2

85

36

34

24

17

14

10

10

8

7

5

4

3

29

Table2. Average annual number and percent distribution and average annual rsteofoffice

visits tourologists, bysex and age: United States, 1989-90

Averageannua! Average annual

numberofw”sita Percent numbarofviaits

Sex and age irrthousands distribution per 1# persons

Totalvisita . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Under 15years . . . . . . . . . . . . . . . . . . . . . . .

15-24yeara . . . . . . . . . . . . . . . . . . . . . . . . .

X-t4yeers. . . . . . . . . . . . . . . . . . . . . . . . .

45-64years . . . . . . . . . . . . . . . . . . . . . . . . .

65-74years . . . . . . . . . . . . . . . . . . . . . . . . .

75yearaandover . . . . . . . . . . . . . . . . . . . . .

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Under 15years . . . . . . . . . . . . . . . . . . . . . . .

15-24years . . . . . . . . . . . . . . . . . . . . . . . . .

25-14years . . . . . . . . . . . . . . . . . . . . . . . . .

45-64yeara . . . . . . . . . . . . . . . . . . . . . . . . .

65-74years . . . . . . . . . . . . . . . . . . . . . . . . .

75yeamandover . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Under15years . . . . . . . . . . . . . . . . . . . . . . .

15-24yeaffi . . . . . . . . . . . . . . . . . . . . . . . . .

25-44years . . . . . . . . . . . . . . . . . . . . . . . . .

45-64yeara . . . . . . . . . . . . . . . . . . . . . . . . .

65-74yeara . . . . . . . . . . . . . . . . . . . . . . . . .

75yearaand over ...,..... . . . . . . . . . . . .

9,652

492

370

2,120

2,575

2,377

1,917

7,098

369

266

1,446

1,818

1,805

1,392

2,754

123

102

874

757

573

526

100.0

5.0

3.8

21.5

26.1

24.1

19.5

72.0

3.7

2.7

14.7

18.5

18.3

14.1

28.0

1.3

1.0

8.8

7.7

5.8

5.3

4

1

1

3

6

13

17

8

1

2

4

8

23

33

2

0

1

2

3

6

7

than visit rates for females for the

three oldest age groups (table 2).

Visits to urologists by the

patient’s race are shown intable3.

About 90fevery 10 patients were

white persons, which issirnilarto that

for all physicians. When visit rates are

compared, there are no statistical

d~erences between the visit rates for

white, black, or “other” race groups.

Males accounted for more visits to

urologists than females did for all

race groups.

The expected sources of payment

for visits to the urologist are shown in

figure 2. Blue Cross/Blue Shield or

another commercial insurance was an

expected source ofpayment in about

49 percent of the visits, which is

about 40percent higher than for all

physicians. In about 46 percent of the

Visits to urologists, government

insurance (hfedicare and Medicaid)

was the expected source ofpayment

for all or part of the visit, which is

almost 70 percent higher than for all

physicirms. Selfpayment wasan

expected source ofpaymentin

approximately 16perccnt of the visits

orabout halfas many compared with

all physicians. HMO’s (health

maintenance organizations), IPA’s

(individual practice associations), and

other prepaid plans were the

expected source ofpayment in about

7.2 percent of the visits to urologists

as compared with 14.8percent for all

physicians.

As shown in table 4, about

14percent ofvisits made tothe

urologist were referred by another

physicirq which is considerably

higher than 5.5 percent for all

physicians. Most visits to the urologist

were “oldpatients’’( patientswho

had previously visited thephysician)

with an ’’old problem” (condition

previously treated by thephysiciau),

which represented almost threequartera ofthe visits. Oldpatients

with new problems represented about

5percent of the visits and new

patients to the urologists represented

about one-lifth ofthe visits.

Compared withall physicians,

urologists saw a higher percent of old

patients with old problems and a

smaller percemt of new patients. No

statistical difference was found in

comparison with data from the

1975-76 NAMCS.

Patient’s reason for visit

The principal reasons for visit are

presented in tables 5 and 6. The

principal reason for visit is the

patient’s problem, complaint or

symptom listed first on item 9 of the

Patient Record that necessitated the

officevisit. These data have been

classified and coded according to the

Reason for Visit Classification for

Anzbulato~ Care (RVC) (2).

The RVC is classified into eight

modules as shown in table 5. Almost

60 percent of the principal reasons

for visit to the urologist were for

symptoms, with over half of these
4 Advance Data No. 234 ● Mav 13, 1993

Table 3. Average annual number, percent distribution, and rate of visits to urologists, by

race and sex: United States, 1989-90

Avetage ennusl Avetage annual

number of n“s”ts Percent

Rats and sax

number of visits

in thousands dlsbibution per lW persons

Totslvisirs. . . . . . . . . . . . . . . . . . . . . . . . . . . 9,852 100.0 4

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 747 7.6 2

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 574 5.8 4

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 1.6 1

White . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8,7S5 89.2 4

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6,281 S3.6 6

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,503 25.4 3

Other’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134 1.4 2

Male . . . . . . . . . . . . . . . . . . . . . . . . . ...’. 102 1.0 2

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 0.3 .1

Unspecifwd .. . . . . . . . . . . . . . . . . . . . . . . . . 186 1.9 . . .

‘Includes Asiin and Pdfc Islander snd AmencarI Irdan. Eskimo, and Neut,

60 F

40

B30

3

5

z

5

$’20

10

0

Urdogista I All phyddana

w Mtidme Cab= Pm#d

WY

Other

Medicaid

J&a

Figure 2. Expeeted sourea of payment to urologlsk United States, 1989-90

visits being symptoms referable to the mostly into the symptom module

genitourinary system. Other principal (approximately 57 percent); the

reasons for visit were fortreatrnents diagnostic, screening, and

(about 17 percent) and for diseases preventive module (about

(almost 14 percent). The principal 16percent); and the treatment

reasons for visit to all physicians fell module (about 10percent).

Differences between urologists and all

physicians inthese modules were

statistically significant.

The top20 principal reasons for

visit to the urologist, which aceaunted

for about three-fifths of allvisits, are

listed intable6. Other urinary

dysfunctions (7.8 percent) is the first

Iisted principal reason forvisitamd

includes problems of retention,

hesitancy, orvolume ofurine. This

reason for visit has increased

significantly since 1975-76whenit

represented 3.4 pereent of the visits

to urologists and was the 8th listed

reason for visit (l). This change may

be associated with the significant

increase in the percent of visits for

the principal diagnosis, hyperpla~siaof

prostate (ICD-9-CM code 600),

discussed later in this report, and the

increase in the percent of visits :made

by patients 65 years of age and over.

Frequency and urgency of urination,

abnormalities of urine, painful

urination, and incontinence acccmnt

for five of the first ten reasons for

visit. Painful urination decreased

significantly from 10.7 percent in

1975-76 to 4.5 percent in 1989-90, a

decrease of 58 percent (1) and may

be associated with the significant

deerease in the percent of visits for

the principal diagnosis, inflammatory

diseases of the prostate (ICD-9--CM

code 601). Most of the other principal

reasons for visit have remained

statistically similar since 1975-76.

Physician’s diagnosis

Data on the principal diagnosis

rendered by the urologist are shown

in tables 7 and 8. The principal

diagnosis is recorded on item 10a of

the Patient Record and correspcmds

to the principaI reason for visit (item

9a). The diagnoses are coded and

classified according to the

Internatwnal Ciassij?cation of Diseases,

9th Reviswn, Clinical Modification

(lCD-9-CM) (3).

As shown in table 7, the

ICD-9-CM is organized into broad

categories relating to the major

systems of the body. As expected,

diseases of the genitourinary system

represented over half of the
Advance Data No. 234 ● May 13, 1993 5

Table 4. Average annual number and percent distribution of office visits to urologists, by

patients’ referral status and visit status: United States, 1869-90

Average annuat

number of visits Pement

Referral and w.sitstatus in thousands distribution

Allvisits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9,652 100.0

Patient referred

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,412 14.3

No. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8,440 85.7

Visitatatus

Newpatient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,027 20.6

Oldpatient, newproblem . . . . . . . . . . . . . . . . . . . . . . . . . . . . 476 4.8

Oldpatien~ oldproblem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7,349 74.6

Table5. Average annuai number and percent distribution ofofficevisftato uro[ogiata, by

principal reason forvlsitmodukx United Stetes,1989-90

Averagearrnual

Princi@ reason rbr number of w“aita Percent

w“sit module and RVC code’ in thousands distribution

Allpnncipal reasansfor visit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9,652 100.0

Symptommodule . . . . . . . . . . . . . . . . . . . . . . . . . . . ..SI=999 5,903 59.9

Symptoms referabletothe genitourinary system . . . . . . . . .3640-S828 4,560 46.3

Diseasemodule . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..DooI-D999 1,360 13.8

Diagnostic, screening, andprevenfiie module. . . . . . . . . . . .X1OO.-X699 528 5.4

Treatmentmodule . . . . . . . . . . . . . . . . . . . . . . . . . . . ..TIoo-T839 1,704 17.3

AJIothermodulesz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367 3.6

‘BasedmAResson tirWsfiClssshhmim rbrArrrbu/storyOsre(WC)(2).

21ncludeelnjurys.ndadverseeffecremoduIqteetrssullsmodulq adtinistrativernodulwurwodsbleandbbnkentries

Table6.Average annual number, percentdistributlon, and cumulative percentofofflce

visitato urologiste, bythe20 most common principal reasonsforvisk United Stetes,

1988-80

Averagearrnual CumulaPrincipal reason tir number of w.site

Rank

Percent h

wkit and RVC code’ inthouearrds dih”butbrr parcant

1

2

3

4

5

8

7

6

9

10

11

12

13

14

15

16

17

18

19

20

Allraasons forvisit . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Other urinary dysfunctions . . . . . . . . . . . . . . . . . . . ..ss60

Frequenoyand urgenoyofurination. . . . . . . . . . . . . . .S645

Abnormalities ofunne . . . . . . . . . . . . . . . . . . . . . . ..SS40

Psychosexual disorders. . . . . . . . . . . . . . . . . . . . . ..S160

Painful urinatio n . . . . . . . . . . . . . . . . . . . . . . . . ..s650

hlcontinence ofurine(enuresis) . . . . . . . . . . . . . . . . .S655

Symptoms of prostate. . . . . . . . . . . . . . . . . . . . . . ..S71O

Cancer, unnaryand male gen.kd tract. . . . . . . . . . . . . .D125

Urinatytraot diseaee (except oyatiis) . . . . . . . . . . . . ..D705

Symptoms ofscrotum andteates. . . . . . . . . . . . . . . . .s715

Diseases of themale genital organs. . . . . . . . . . . . . . .D710

Symptoms of the bladder . . . . . . . . . . . . . . . . . . . ..ss65

UflnarytraCt hfeCtiOn . . . . . . . . . . . . . . . . . . . . . . ..S&’5

Pain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..S055

Generial medical exam . . . . . . . . . . . . . . . . . . . . . ..xIoo

Symptoms of penis . . . . . . . . . . . . . . . . . . . . . . . ..S7W

Family planning . . . . . . . . . . . . . . . . . . . . . . . . . . ..x500

Sterilization to be performed

(atthisvisit) . . . . . . . . . . . . . . . . . . . . . . . . . . .. X525

Backsymptoms . . . . . . . . . . . . . . . . . . . . . . . . . . ..

Other aymptoms referable tourinerytract . . . . . . . . . . .B660

9,352

771

656

485

444

441

395

386

383

348

346

334

271

263

208

182

154

124

118

115

114

100.0

7.8

6.7

4.9

4.5

4.5

4.0

3.9

3.9

3.5

3.5

3.4

26

2.7

2.1

1.9

1.6

1.3

1.2

1.2

1.2

‘Based enA Reason for WSII Clsssiricstion for,hbukrmy Csre (WC) (2).

..-

7.8

14.5

19.4

23.9

28.4

32.4

36.3

40.2

43.7

47.2

50.6

53.4

56.1

58.2

60.1

61.7

63.0

64.2

65.4

66.6

diagnoses. Neoplasms, the second

most frequent diagnosis category,

represented about 12percent of the

visits. Together, these two categories

accounted for approximately

71 pereent of all the visits to

urologists. The percent of visits to

urologists that included diagnosea of

neoplasms have significantly increased

from 1975-76 to 1989-90 (horn about

6 percent to almost 12percent).

The top 20 diagnoses made by

urologistsin 1989-90, which represent

almost 78 percent of all visits, are

listed in table 8. Hyperplasia of

prostate, the first-listed principal

diagnosis, amounted for about

13 pmxmt of the visits in 1989-90, a

significant increase from 1975–76

when it represented almost 6 percent

of the visits and was the fifth-listed

principal diagnosis. Inflammatory

diseases of prostate, the fourth-listed

principal diagnosis, decreased

significantly, from 9.3 pereent of the

visits in 1975–76 to 5.4 percent in

1989-90. Cystitis, which accounted for

about 4 percent of the visits in

198!3-90, decreased by approximately

60 percent since 1975-76. In the

1975–76 survey, cystitis was the most

common diagnosis, with almost

11 percent of the visits (l). The other

top 20 diagnoses in 1989-90 have

remained similar since 1975-76.

Diagnostic and screening

services

Urologists ordered or provided a

urinalysis in about 72 percent of all

visits, abnost 6 times more than all

physicians. In addition, a digital rectal

exam was also ordered or provided 6

times more often by urologists (about

20 percent) than all other physicians

(approximately 4 percent). Urologists

performed or ordered fewer pelvic

exams, blood pressure tests, and

other blood tests than all other

physicians. Approximately one-third

of the visits included a diagnostic teat

that was not speeified on the Patient

Record (table 9).
6 Advance Data No. 234 ● May 13, 1993

Table 7. Average annual number and percent distribution of office visita to urologists, by

principal diagnoses rendered by the physician: United States, 1989-90

Average annual

Principal diagnoses and number of visits Percent

ICD-9-CM codes’ in thousends distribution

All principal diagnoses . . . . . . . . . . . . . . . . . . . . . . . . . . 9,852 100.0

Infectious and parasitic diseases. . . . . . . . . . . .00 I –I 39 213 2.2

Neoplasms . . . . . . . . . . . . . . . . . . . . . . . . . ...140-289 1,169 11.9

Endocrine, nutritional, and metabolic

diseases and immunity disorders. . . . . . . . . . . ...240-279 92 0.9

Mental disorders . . . . . . . . . . . . . . . . . . . . . . . ..290+19 330 3.4

Diseases of the nenrous system and sense

organs . . . . . . . . . . . . . . . . . . . . . . . . . . . ...320439 158 1.6

Diaeasesofthe genitourinarysyetem. . . . . . . . . . .580.-629 5,797 58.8

Symptoms, signs and ill-defined condtiions . . . . . ...780-799 593 6.0

%pplementary ctassifioations. . . . . . . . . . . . . . .VOOI-V062 850 6.6

Another diagnosesz . . . . . . . . . . . . . . . . . . . . . . . . . . . . 508 5.2

Unknown diagnoses3 . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 1.4

‘Bmedon /ntemationa/ C/aw’tidon of Disexes, WRswslon, C/iniAM@ifiaHon (lCBKM) (3).

‘Includes diseases of the blood forming organs (280-289); dieeesea of the circulatory system (390-459~ diseases of the

respirator eystsm (460-519X diseases et the digsetive system (520-579); complicationsof pregnancy, childbirth, and the

puetperium (830-876); diseases of the skin and subcutaneous tissue (8S(!-709); diseases of the musculoskeletaland

connective tissue (71 C-739); oongen”til anomalies ~40-759); certain oondtions originating in the perinatal period (7EJ3-779);

end injury and poisoning (soD-889).

‘Includes blank diagnoses, uncodable diagnoses, and illegible diagnoses,

Table 8. Average annual number, percent distribution, and cumulative percent of office

viaita to urologists, by principal diagnoses most frequently rendered by the physician:

United States, 1989-90

Average

annual

number of

Most common principal diagnoses visits Percent Cumulative

Rank and ICD–9-CM code 1 in thousands distribution present

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

All principal diagnoses . . . . . . . . . . . . . . . . . . . . . . . . .

Hyperpiasia of prostate . . . . . . . . . . . . . . . . . . . . ...600

Other disorders d urethra and urinary tract . . . . . . .599

Malignant neoplaem of proelate . . . . . . . . . . . . . . ...185

lnflammato~ diseases of prostate. . . . . . . . . . . . . ...601

Urethral atrioture . . . . . . . . . . . . . . . . . . . . . . . . ...598

Calculus ofkidneyand ureter . . . . . . . . . . . . . . . ...592

Symptoms involving urinary eyetem. . . . . . . . . . . ...766

cystitis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...585

Sexual Deviations and disorders. . . . . . . . . . . . . . ..302

Malignant neoplaem of bladder. . . . . . . . . . . . . . . . ..188

Other postsurgical atates. . . . . . . . . . . . . . . . . . . . .V045

Contraceptive management. . . . . . . . . . . . . . . . . . .V025

Urethritis, not sexually transmitted, and

urethral syndrome . . . . . . . . . . . . . . . . . . . . . . ...597

Orchtiis andepididymitis . . . . . . . . . . . . . . . . . . . ...604

Disorders of penis . . . . . . . . . . . . . . . . . . . . . . . ...607

Other disorders of bladder . . . . . . . . . . . . . . . . . ...596

Other disorders ofmalegenital organs. . . . . . . . . . ...606

Other paralytic syndromes . . . . . . . . . . . . . . . . . ...344

Neoplaems ofunspecified nsture . . . . . . . . . . . . . ...239

Redundant prepuce andphimoais. . . . . . . . . . ...605

9,652

1,257

994

695

536

535

497

469

423

325

233

217

212

188

195

187

166

148

148

120

103

100.0

12.6

10.1

7.1

5.4

5.4

5.0

4.8

4.3

3.3

2.4

2.2

2.2

2.0

2.0

1.9

1.7

1.5

1.5

1.2

1.0

---

12.8

22.9

30.0

35.4

40.8

45.6

50.6

54.9

58.2

60.6

62.8

65.0

67.0

69.0

70.9

72.6

74.1

75.6

76.8

77.8

'Bssedon /ntemational C/aseificationof Diseases,Sth Revision, CfinicsfModh7cation(/CWM) (3).

Medication therapy

or administered by the physician. In

As shown in table 10, only about contrast, the majority of visits made

40 percent of the visits made to to all physicirms were drug visits

urologists in 1989-90 were drug visits. (60 percent). Of the drug visits to

A dmg visit is one in which one or urologists, about three-quarters were

more medication(s) were prescribed visits in which one drug was

prescribed or administered. Of all the

drugs prescribed or administered lby

ambulatory care physicians, the drugs

prescribed or administered by

urologists accounted for roughly

1 percent.

As shown in table 11, the

estimated 5.5 million drug menticms

by urologists are classified into

therapeutic categories as defined by

the National Drug Code Director-y (4).

The majority of drug mentions were

antimicrobial agents (almost

52 percent), specifically sulfonamides

and trimethoprim (about 13 percent),

snd urinary tract antiseptics (about

24 percent). No comparison is

possible with the 1975–76 data

because therie data were not collected

until 1980. The top 20 generic

ingredients in order of frequency are

listed in table 12. Trimethoprim, the

first-listed generic ingredient,

represented nesrly 14 percent of the

estimated 5.5 million drug menticms

in 1989-90. Sulfamethoxszole an,d

Ciprofloxacin HCL, the second- and

third-listed generic ingredients,

follow with approximately 12 pencent

and 8 percent, respectively. The 20

most frequent medication entries

made by the physician on the Patient

Record are listed in table 13. The

physician is instructed to enter either

the brsnd or generic name of the

medication and to include both

over-the-counter and prescription

drugs that may be either prescribed

or administered. Cipro and

Macrodantin, two antibacterial

medications, top the list with about

8 percent and 7 percent, respectively.

Duration and disposition

Of the visits made to urologists,

approximately 60 percent lasted 15

minutes or less and approximately

35 percent lasted 16-30 minutes

(table 14). The mean duration of a

visit in 1989-90 was approximately

minutes, compared with

approximately 16 minutes in

17

19?5–76. Both means exclude visits of

zero minutes. A visit of zero minutes

is one in which the patient had no

face-to-face contact with the

physician but received care from a
Advance Data No. 234 ● May 13, 1993 7

Table 9. Average annual number and percent distribution of office visits to urologists and

percent distribution for all phyiscians, by diagnostic service ordered or provided:

United States, 1989-90

Wsitato all

Visits to urologists physioiarrs

Average annual

Diagnostic service number of

ordered or visits in Percent Percent

provided thousands distriirution diafn”butiorr

Total visits . . . . . . . . . . . . . . . . . . . .

Pelvic exam . . . . . . . . . . . . . . . . . . .

Blood pressure . . . . . . . . . . . . . . . . .

Urinalysis . . . . . . . . . . . . . . . . . . . .

Oigitalractalexam . . . . . . . . . . . . . . .

Otherbloodtest . . . . . . . . . . . . . . . .

Otherliafedservices’ . . . . . . . . . . . . .

Otherdiagnosticsewicas . . . . . . . . . .

None . . . . . . . . . . . . . . . . . . . . . . .

9,852

353

1,105

7,111

1,954

605

108

3,280

1,446

100.0

3.6

11.2

72.2

19.8

6.1

1.4

33.3

14.7

100.0

7.4

38.7

12.7

3.6

13.0

28.3

25.2

37.2

‘Includes pap t@ t#eest pelpetiom mammogram; visual acu”~ chest x ray proctoscopy/sigmoidoswp~ stool blood -

Oralglucoeetolerenca t~choleeterol meseurq HIVsarolcgy.

NOTE Numbare may not add tc tctsls becausa more then one dmgnestic s-”ce was pasible during the pa”ent visit

Table 10. Average annual number and

percent distribution of office visits to

urologists, bytype of visit and number of

medications ordered or prescribed:

Unhed States, 1988-90

Average annual

Type of visit and number of visits Percent

number of medications inthouaarrds distribution

Allviaits . . . . . . . . . . . 9,852 i 00.0

Type of visit

Nondrug visit

(O medications) . . . . . . 5,759 58.5

Drug Visit. . . . . . . . . . . 4,092 41.5

Number of medications

1 . . . . . . . . . . . . . . . . 3,045 74.4

2 . . . . . . . . . . . . . . . . 806 19.7

3 ormore . . . . . . . . . . 242 5.9

Table 11. Average annual number and

percent distribution of drug mentions to

urologkts by therapeutic category:

United States, 1989-90

Average annual

number of visits Percent

Therapeutic oatego~’ in Urou.swds distribution

All drug mentions. . . . . .

Antimicrobial agenta . . . .

Sulfonamides and

tnmefhoprim. . . . . . .

Unna~ tract

antiseptics . . . . . . . .

Cardiovascular-renal

drugs. . . . . . . . . . . . .

Psychopharmacologic

drugs . . . . . . . . . . . .

Gastrointestinal agents . .

Metabolic and nutrient

agents . . . . . . . . . . . .

Hormones and agents

affecting hormonal

mechanisms . . . . . . . .

Sldn/mumus

membrane . . . . . . . . .

Drugs usad for relief

of pain . . . . . . . . . . . .

Respiratory tract drugs. . .

Unclassified and/or

miscellaneous . . . . . . .

Allothers2 . . . . . . . . . .

5,475

2,828

719

1,265

564

150

133

*62

410

111

358

95

600

183

100.0

51.7

13.1

23.5

10.3

2.7

2.4

~.1

7.5

2.0

6.5

1.7

11.0

3.0

member of the physician’s staff. Visits

of zero minutes accounted for

approximately 1 percent of the visits,

which was similar to that for all

physicians (1.7 percent). The duration

of visit does not include time spent

waiting for the physician, waiting for

test results, or time with someone

else on the physician’s staff.

As shown in table 14, most visits

to the urologist had a disposition for

the patient to return at a specific time

(around 75 pereent), which is

statistically higher than for all

physicians (about 62 percent). This

was followed by instructions for the

patient to return if needed (about

13 percent), which is approximately

42 percent less often than for all

physicians. The 1989–90 disposition

data are not statistically different

than the 1975-76 disposition data.

References

1.

2.

3.

4.

Koch H. Offiec visits to urologists,

NationalAmbulatoryMedical

CareSurvey UnitedStates,

1975-76. Advance data from vital

health statistkq no 39. Hyattsville,

Maryland National Center for

Health Statistics. 1978.

Schneider D, Appleton L,

Mchmore T. A reason for visit

classification for ambulatory care.

National Csnter for Health

Statistics. Vital HeaIth Stat 2(78).

1979.

Public Health Service and Health

Care Financing Administration.

International classification of

diseases, 9th revision, clinical

mtieation. Washington Public

Health Service. 1980.

Food and Drug Administration.

National drug code directory, 1985

edition. WsshingtorK Public Health

Service. 1985.

‘-tic cl= bsed on She.sMIsFJ drug claMWarI

used in the Na?ions/DrugCWa Directcfy,19S5 Edtin (4).

21rWudes entistic dru@, smtidotee, hsrnetolegic agents,

rediophannaceutkd ccmtrest media, immut-dcgii agents,

rraurologic drugs, oncolyties, ophthalmic drugs, c401cgio

drugs, and antipmsitio egents.
8 Advance Data No. 234 ● May 13, 1993

Table 12. Average annual number and

percent distribution of the top 20 generic

ingredients most often utilized by

urologists: United States, 1989-90

Average

arrrrua/

number of

Generic mentions in Percent

Rank ingredient thousands’ distribution

All drugs mentions.

1 Trimethoprim . . . . .

2 Sulfamethoxa.zole. . .

3 Ciprofloxacin HCL

4 Nitrofurantoin . . . .

5 Norfloxacin. . . .

6 Oxybutynin. . . . . . .

7 Hyoscyamine . . . . .

6 Doxycycline . . . . .

9 Phenazopyridine . . .

10 Testosterone. . . . .

11 Acetaminophen . . .

12 Ibuprofen. . . . . , .

13 Atropine . . . . . . . .

14 Tetracycline . . . .

15 Oxymdone. . . . .

16 Methylene blue . .

17 Methenamine . . .

16 Phenyl salicylsfe . . .

19 Yohimbene. . . . ,

20 Cephalexin. . . . . . .

5,475 100.0

740 13.5

663 12.1

454 6.3

386 7.1

346 6.3

251 4.6

174 3.2

169 3.1

155 2.6

146 2.7

127 2.3

119 2.2

108 2.0

102 1.9

90 1.6

90 1.6

89 1.6

86 1.6

●7I 1.3

●59 *1.1

‘Frequencyof mentioncombinessingl~ingredienteagents

w%hmentionsofthe agentsse an ingredientina

combinationdrug.

Table 13. Average annual number and

percent distribution of the top 20

medication entries made by urologists:

United States, 1988-90

Average

annual

number of

mentions in Percent

Rank Entry name’ thousands distribution

All drug mentions . . .

1 Cipro . . . . . . . . . . .

2 Macrodantin . . .

3 Noroxin . . . . . . . . .

4 Bactrim DO.......

5 Ditropan . . . . . . . . .

6 Septra DO . . . . . . . .

7 Pyridium . . . . . . . . .

8 Bsctrim. . . . . . . . . .

9 Motrin . . . . . . . . . .

10 Tetracycline. . . . . . .

11 Urised . . . . . . . . . .

12 Septrs . . . . . . . . . .

13 Depo-Teatoaterone . .

14 Yohimbene . .

15 Doxycycline. . . .

16 Ampicillin . . . .

17 Testosterone . . . . .

18 Percocet+ . . . . . . .

19 Doryx . . . . . . . . . . .

20 Cyatospaz. . . . . . . .

5,475 100.0

454 6.3

381 7.0

346 6.3

305 5.6

242 4.4

145 2.7

139 2.5

113 2.1

99 1.6

94 1.7

86 1.6

80 1.5

77 1.4

71 1.3

‘%4 1.2

*59 *1 .1

*56 *1 .0

*44 ‘0.6

*44 *0.8

*41 *0.8

Table 14. Average annual number and

percent distribution of office visits to

urologists, by duration and disposition:

United States, 1989-90

Average annual

Durstion and number of visits Percent

disposition in thousands distribution

Total . . . . . . . . . . . . 9,852 100.0

Duration of visit

Zero minutes . . . . . 92 0.9

l–5 minutea. . . . . . 981 10.0

6-10 minutes . . . . . . . 2,218 22.5

11–15 minutes . . . 2,575 26.1

16-30 minutes . . . . . 3,441 34.9

31 minutes or more . . . 546 5.5

Disposition of visit

No followup planned . . 3,326 3.4

Return at specific

time . . . . . . . . . . . . 7,406 75.2

Return if needed . . . 1,307 13.3

Telephone followup

planned . . . . . . . . . . 238 2.4

Referred to other

physician . . . . . . . . . 144 1.5

Referred to referring

physician . . . . . . . . . 134 1.4

Admit to hospital . . . . . 292 3.0

Other . . . . . . . . . . . . 438 4.4

‘The entrynamerecordedon the PatientRecordfwm could

be e“tierthetradeor genericnameofthe medication.
Advance Data No. 234 ● May 13, 1993 9

Symbols

--- Data not available

. . . Category not applicable

Quantity zero

0.0 Quantity more than zero but less

than 0.05

z Quantity more than zero but less

than 500 where numbers are

rounded to thousands

* Figure does not meet standard of

reliabili&yor precision (estimate is

based on fewer than 20 births in

numerator or denominator)
10 Advance Data No. 234 ● May 13, 1993

Technical notes

Sources of data and

sample design

The information presented in this

report is based on data collected by

means of the National Ambulatory

Medical Care Survey (NAMCS) from

March 20, 1989, through December

30, 1990. The target universe of

NAMCS includes office visits made in

the United States by ambulatory

patients to nonfederally employed

physicians who are principally

engaged in office practice but not in

the specialties of anesthesiology,

pathology, or radiology. Telephone

contacts and nonoffice visits are

excluded.

A multistage probability sample

design is used in NAMCS, involving

samples of primary sampling units

(PSU’S), physician practices within

PSU’S, and patient visits within

physician practices. The PSU’S are

counties, groups of counties, county

equivalents (such as parishes or

independent cities), or towns and

townships (for some PSU’S in New

England). A sample of 2,535 nonFederal, office-based physicians was

selected in 1989 and 2,528 nonFederal, office-based physicians were

selected in 1990 from master files

maintained by the American Medical

Association and American

Osteopathic Association. The sample

included 118 urologists in both 1989

and 1990, of which 94 were eligible in

1989 and 96 were eligible in 1990.

The physician response rate for the

1989 NAMCS was 74 percent; in

1990, it was 75 percent. Urologists

had a response rate of 76 percent in

1989 and 72 percent in 1990. Sample

physicians were asked to complete

patient records (figure 1) for a

systematic random sample of office

visits occurring during a randomly

assigned l-week reporting period.

Responding physicians completed

38,384 patient records in 1989 and

43,469 in 1990. Urologists completed

1,569 Patient Record forms in 1989

and 1,584 in 1990. Characteristics of

the physician’s practice, such as

primary specialty and type of practice,

were obtained from the physicians

during an induction interview. The

U.S. Bureau of the Census, Housing

Surveys Branch, was responsible for the

survey’s data collection. Processing

operations and medical coding were

performed by the National Center for

Health Statistics, Hospital Discharge and

Ambulatory Care Survey Section,

Research Triangle Park, North Carolina.

Sampling errors

The standard error is primarily a

measure of the sampling variability that

occurs by chance when only a sample,

rather than an entire universe, is

surveyed. The relative standard error of

an estimate is obtained by dividing the

standard error by the estimate itselfi the

result is then expressed as a percent of

the estimate. Approximate relative

standard errors (RSE’S) of selected

aggregate statistics are shown in table I,

and the relative standard errors of the

estimated number of dmg mentions are

shown in table II. All frequencies in this

report are average annual figures and

must be doubled before a significance

test can be performed. Relative standard

errors for aggregate visits and drug

estimates may be calculated using the

following general formula, where x is

the aggregate of interest in thousands,

and A and B are the appropriate

coefficient from table IV.

RSE (X)=

I/

A+2X100.0

x

Approximate relative standard errors for

estimates of the percent of visits are

shown in table III. The RSE’S for

percent may be calculated using the

following general fonm.da, where p is

the percent of interest and x is the

denominator of the percent in thousands,

using the appropriate coefficient from

table W.

IIWP)xlmo RSE (p)= —

px “

Adjustments for nonresponse

Estimates from NAMCS data were

adjusted to account for sample

physicians who were in scope but did

not participate in the study. This

adjustment was calculated to minimize the impact of response on final

Table L Relative atsndard errora for

estimated numbers of office visit=

National Ambulatory Medical Care

Survey, 1989-90

Estimated number

of ofice visits All

in thousands specialties Urologists

Relative standard error

(RSE) in percent

100 . . . . . . . . . . . . . . 72.7 31.1

200 . . . . . . . . . . . . . . 51.5 23.4

am . . . . . . . . . . . . . . 42.1 20.1

400 . . . . . . . . . . . . . . 36.5 18.3

500 . . . . . . . . . . . . . . 32.6 17.1

700 . . . . . . . . . . . . . . 27.6 15.6

1,000 . . . . . . . . . . . . . 23.2 14.4

2,000 . . . . . . . . . . . . . 16.5 12.9

5,000 . . . . . . . . . . . . . 10.7 11.9

7,000 . . . . . . . . . . . . . 9.2 11.7

10,00+3 . . . . . . . . . . . . 7.9 11.5

30,000 . . . . . . . . . . . . 5.2 11.2

50,000 . . . . . . . . . . . . 4.5 11.2

100,000 . . . . . . . . . . . 3.9 11.2

500,000 . . . . . . . . . . . 3.3 11.1

700,000 . . . . . . . . . . . 3.2 11.1

1,400,000 . . . . . . . . . . 3.2 . . .

NOTE Urologist 30 percent RSE. 110,00Q all speeiattias

30 percent RSE. 593,000.

Example of use of table An aggregate estimate of 5 million

visits to a urologist has a relative stenderd estimsto of 11.9

percent w a standard anor of 595 thoussnd vis’b

(11.9 percent of 5 million).

Table IL Relative standard errors for

estimated numbers of drug mentions:

National Ambulatory Medical Care

Survey, 1989-90

Estimated number

of drug mentions All

in thousands specialties Urologists

Relative standard emor

(RSE) in percmt

100 . . . . . . . . . . . . . . 80.3 36.1

200 . . . . . . . . . . . . . . 63.9 27.0

300 . . . . . . . . . . . . . . 52.3 23.3

400 . . . . . . . . . . . . . . 45.3 21.1

500 . . . . . . . . . . . . . . 40.6 19.7

700 . . . . . . . . . . . . . . 34.3 18.0

1,000 . . . . . . . . . . . . . 28.8 16.6

2,000 . . . . . . . . . . . . . 20.6 14.7

5,000 . . . . . . . . . . . . . 13.4 13.5

7,000 . . . . . . . . . . . . . 11.5 13.3

10,00+3 . . . . . . . . . . . . 9.9 13.1

30,000 . . . . . . . . . . . . 6.5 12.6

50,000 . . . . . . . . . . . . 5.7 12.8

100,000 . . . . . . . . . . . 4.9 12.7

500,000 . . . . . . . . . . . 4.2 12.7

700,000 . . . . . . . . . . . 4.1 12.7

1,400,000 . . . . . . . . . . 4.0 . . .

NOTE Urologief 30 percent RSE = 155,00@ all Spm”aitise

SO PSMSnt RSE = 922,0C0.

Example of use of table An aggregate estimate cd 2 million

drug mentionsby a urologisthasa relativestandardestimate

of 14.7 psrcsmt or a standard wrw of 2S4 Ihoussnd drug

menticms (14.7 percent of 2 million).
Advance Data No. 234 ● May 13, 1993 11

Table Ill.Standard errors for percents of estimated numbers of office visits for the Netionai Ambulatory Medicai Care Survey

United States, 1989-90

Eti”matad paroent

Base of percent

(visits in thousands) lor99 5 or 95 10 or 90 20 or 80 30 or 70 50

100 . . . . . . . . . . . . . . . . . . . . . . . .

200 . . . . . . . . . . . . . . . . . . . . . . . .

500 . . . . . . . . . . . . . . . . . . . . . . . .

700 . . . . . . . . . . . . . . . . . . . . . . . .

1,000 . . . . . . . . . . . . . . . . . . . . . . .

2,000 . . . . . . . . . . . . . . . . . . . . . . .

5,000 . . . . . . . . . . . . . . . . . . . . . . .

7,000 . . . . . . . . . . . . . . . . . . . . . . .

10,000 . . . . . . . . . . . . . . . . . . . . . .

20,000 . . . . . . . . . . . . . . . . . . . . . .

30,000 . . . . . . . . . . . . . . . . . . . . . .

50,000 . . . . . . . . . . . . . . . . . . . . . .

80,000 . . . . . . . . . . . . . . . . . . . . . .

Ioo,ooo . . . . . . . . . . . . . . . . . . . . . .

500,000 . . . . . . . . . . . . . . . . . . . . . .

1,400,000 . . . . . . . . . . . . . . . . . . . .

2.9

2.1

1.3

1.1

0.9

0.6

0.4

0.4

0.3

0.2

0.2

0.1

0.1

0.1

0.0

0.0

6.3

4.5

2.8

2.4

2.0

1.4

0.9

0.8

0.6

0.5

0.4

0.3

0.2

0.2

0.1

0.1

Standard error in percentage points

8.7 11.6

6.2 8.2

3.9 5.2

3.3 4.4

2.8 3.7

2.0 2.6

1.2 1.7

1.0 1.4

0.9 1.2

0.6 0.8

0.5 0.7

0.4 0.5

0.3 0.4

0.3 0.4

0.1 0.2

0.1 0.1

73.3

9.4

6.0

5.0

4.2

3.0

1.9

1.6

1.3

1.0

0.6

0.6

0.5

0.4

0.2

0.1

14.6

10.3

6.5

5.5

4.6

3.3

2.1

1.7

1.5

1.0

0.8

0.7

0.6

0.5

0.2

0.1

Exempleofuseof tsblaAnastimate of30percentbssed onsneggregeteestimate oflOmiliionvislein 198S-90heeastendard errorof4.2~ent orarelativestenderd enorof14.Opercwt

(4.2 percent dwided by 30 pefcent).

estimates by imputing tononresponding physicians data from visits to

similar physicians. For this purpose,

physicians werejudged similarifthey

had the same specialty designation

and practicedin thesame PSU.

Test ofsignificance and

rounding

Inthisreport, the determination

of statistical inference is based ona

two-sided t-test. The Bonferroni

inequality was used to estimate the

critical value for statistically

significant ditlerences (0.05 level of

si@cance). Terms relating to

differences such as’’higher,” “less,”

and so forth indicate that the

differences are statistically significant.

Terms such as “similar” or”no

Tabie iV. Coefficients appropriate for

determining reiative standard errors, by

type of estimate and physician specialty:

Nationai Ambulatory Medicai Care Survey,

1989-90

TW of estimate Coafi7cient

and

physician spooiafty A B

Visits

Overaiitotals . . . . . . 0.00087549 52.77952164

Urologist. . . . . . . . . 0.01236777 8.46452955

Drug mentions

Overaiitotals . . . . . . 0.00157151 81.47054633

Urologist . . . . . . . . . 0.01603645 11.42008264

difference” mean that nonstatistical

significance exists between the

estimates being compared. In the

tables, estimates of office visits have

been rounded to the nearest

thousand. Consequently, estimates

will not always add to totals. Rates

and percents were calculated from

original unrounded figures and do not

necessarily agree with percents

calculated from rounded data.

Definition of terms

Ambulatory patient—An

ambulatory patient is an individual

seeking personal health services who

is not currently admitted to any

health care institution on the

premises.

Drug mention-A drug mention

the physician’s entry of a

pharmaceutical agent-by any route

of administration-for prevention,

diagnosis, or treatment. Generic as

well as brand-name drugs are

included, as are nonprescription and

is

prescription drugs. &ong with all new

drugs, the physician also records

continued medications if the patient

was specifically instructed during the

visit to continue the medication.

Drug visit-A drug visit is a visit

in which medication was prescribed

or provided by the physician.

Ofice-Ofiices are the premises

physicians identify as locations for

their ambulatory practice; these

customarily include consultation,

examination, or treatment spaces that

patients associate with the particular

physician.

Physician—A physician is a duly

licensed doctor of medicine (M.D.) or

doctor of osteopathy @.O.) who is

currently in office-based practice and

who spends some time caring for

ambulatory patients. Excluded from

NAMCS are physicians who are

hospital-base~ who specialize in

anesthesiology, pathology, or

radiology who are federally

employe~ who treat only

institutionalized patients; or who are

employed full time by an institution

and spend no time seeing ambulatory

patients.

Urologiw—A urologist is a

physician self-ckssfied as a urological

surgeon on the American Medical

Association (AMA) or American

Osteopathic Association (AOA)

master ties.

Visit-A visit is a direct personal

exchange between an ambulatory

patient and a physician (or a staff

member working under the

physician’s supervision), for the

purpose of seeking care and

rendering personal health services.
12 Advance Data No. 234 ● May 13, 1993

Trade name disclaimer

The use of trade names is for identification

only and does not imply endorsement by the

Public Health Service, U.S. Department of

Health and Human Services.

Suggested citation Copyright information

Woodwell DA. OtTce visits to urologists This report may be reprinted without further

1989-90, National Ambularoty Medical Care permission.

Survey. Advance data from vital and health

statistics no 234. Hyattaville, Maryland:

National Center for Health Statistics. 1992.

National Center for Health Statistics

Director

Manning Feinleib, M. D., Dr. P.H.

Acting Deputy Director

Jack R. Anderson

U.S. DEPARTMENT OF HEALTH AND

HUMAN SERVICES

Public Health Service

Centers for Disease Control and Prevention

National Center for Health statistics

8525 Be[crest Road

Hyattsville, Maryland 20782

OFFICIAL BUSINESS

PENALTY FOR PRIVATE USE, $300

To receive this publication regularly, contact

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DHHS Publication No. (PHS) 93-1250
Number 235 ● July 28, 1993

Advance

Data

From Vial and Health Statistks of the CENTERS FOR DISEASE CONTROL AND PREVENTION/National Center for Health Statistics

Overview of Home Health and Hospice Care Patients

Preliminary Data From the 1992 National Home and

Hospice Care Survey

by Genevieve W. Strahan, Division of Health Care Statistics

Introduction

Based on the 1992 National

Home and Hospice Care Survey

(NHHCS), this report presents

preliminary statistics on an estimated

1.3 million current patients and 3.4

million discharges from about 8,000

home and hospice care agencies in

the United States, The 1992 NHHCS,

a segment of the Long-Term Care

Component of the National Health

Care Survey (l), is the tit annual

survey of home health agencies and

hospices and their current patients

and discharges. The National Center

for Health Statistics instituted this

nationwide sample survey in response

to the rapid growth in the number of

these agencies throughout the United

States (2).

Estimates for this report are

preliminary. Further editing of the

data may produce estimates slightly

different from the ones shown here. .

The 1,500 agencies included in the

survey were selected from a universe

of 8,036 agencies classified by the

1991 National Health Provider

Inventory (NHI?I) (3) as agencies

providing home health and hospice

care. Also included in the universe

was a sample of potentially new

agencies identified between the time

the 1991 WI was conducted and

June 1992. Data collection for the

1992 NHHCS was conducted between

September and December 1992.

Detailed information on sample

design, selection methods, data

collection procedures, and sampling

errors is included in the Technical

Notes.

Home health care agencies and

hospices are usually defined in terms

of the type of care that they provide.

Home health care is provided to

individuals and families in their

places of residence for the purpose of

promoting, maintaining, or restoring

health or for maxhmz- ing the level of

independence while minimizing the

effects of disability and illness,

including terminal illness. These

agencies are often referred to today

as “hospitals without walls” because

advances in technology allow dozens

of complex illnesses once treated

almost exclusively in the hospital to

be treated at home.

Hospice care is defined as a

program of palliative and supportive

care services providing physical,

psychological, social, and spiritual

care for dying persons, their

families, and other loved ones.

Hospice services are available

in both the home and inpatient

settings.

The focus of this report is on

characteristics of patients receiving

care from agencies that provide home

health and hospice services. For the

two types of agencies, estimates are

presented for

● current patients-patients who

were on the rolk of the agency as

of midnight on the day

immediately prior to the date of

the survey.

“ discharges-patients who had been

removed flom the rolls of the

agency during a 12-month period

ending on the last day of the

month prior to the month of the

survey, including patients whose

episode of care ended because of

death.

Estimates for current patients

and discharges are presented by

agency and demographic and

diagnostic characteristics.

Future reports will present

additional data on topics such as

functional status, living arrangements,

and primary caregivers of patients

* S%XVICCS,

# q,

***

#

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

c

nf Public Health Service

as Centers for Disease Controland Prevention

“%> National Center for Heatth Statistics —m. ......-.UCOISSASE CONTROL ANDFSE4ENTIW
2 Advance Data No. 235 ● July 28, 1993

receiving home health or hospice

care.

Agency characteristics

According to the National

Association for Home Care, the

number of Medicare-certified home

health agencies grew by 250 percent

over a 15-year period, from 1967 to

1992 (2). This growth was sparked by

enactment in 1965 of the Medicare

law, which paid for certain home

health services thereby making them

more available to the elderly. The

growth’was further enhanced in 1973

when certain disabled younger

Americans also qualified as Medicaid

recipients of care from this industry.

According to the 1992 survey, about

85 percent of the estimated 7,000

agencies were Medicare and

86 percent were Medicaid certified.

Medicare added hospice benefits

in 1983, and in 10 years the number

of hospices increased by several

hundred percent (2). About

65 percent of the estimated 1,000

hospices were Medicare certified, and

57 percent were Medicaid certi.lied in

1992.

About the same percent of home

health agencies were privately owned

as were owned by nonprofit

organizations (38 and 42 percent,

respectively). Estimates from the

survey show that almost all

(94 percent) of the hospices were

owned by voluntary nonprofit

organizations. About 3 percent of the

hospices were privately owned. The

remaining 20 percent of the home

health agencies and 3 percent of the

hospices were owned by government

agencies.

Almost two-thirds of all hospices

and home health agencies are located

in the South and in the Midwest. The

southern states had 34 percent of the

home health agencies and 33 percent

of hospices. Fewer home health

agencies were located in the West

than in the other three regions and

fewer hospices were in the Northeast

than the Midwest or the South

(table 1).

Table 1. Number and percent distribution of home health agencies and hospices by

ownership, cettifieation, and geographic region: United States, 1992

Type of agency

Agency Home health

characteristic Total agency Hospiw

All agencies . . . . . . . . . . . . . . . . . . .

Ownership

Proprietary . . . . . . . . . . . . . . . . . . . . . . .

Voluntary nonproft . . . . . . . . . . . . . . . . . .

Government and other . . . . . . . . . . . . . . .

Certification

Certified by Medicare . . . . . . . . . . . . . . . .

Certiied by Medicaid . . . . . . . . . . . . . . . .

Region

Northeast . . . . . . . . . . . . . . . . . . . . . . .

Midwest . . . . . . . . . . . . . . . . . . . . . . . .

South . . . . . . . . . . . . . . . . . . . . . . . . . .

West . . . . . . . . . . . . . . . . . . . . . . . . .

8,000

34.0

48.0

18.0

82.2

82.4

22.1

29.8

33.9

14.2

7,000

Percent distribution

38.2

41.7

20.1

64.7

86.0

23.0

28.5

34.1

13.5

1,000

3.4

83.5

3.1

64.5

58.8

16.0

31.7

32.5

19.8

NOIE Figuresmay notaddto totalsbecauseof rounding.

Patients by agency

characteristics

Table 2 shows that the number of

current patients receiving home care

is also greater in the South and the

Northeast. According to the 1992

survey, 67 percent of the 1.3 million

current home health and hospice

patients were located in the southern

and northeastern States.

Most current patients and

discharges received home and hospice

care from voluntary nonprofit

agencies. In 1992, about 60 percent of

all home health and 86 percent of all

hospice patients were being cared for

by nonprofit agencies. Patients who

were discharged were included in the

survey if that discharge occurred

during the 12-month period prior to

the month of the survey. Home

health agencies that were nonprofit

delivered care to 67 percent of all

home health patients who had been

discharged while 91 percent of all

discharged hospice patients received

care from nonprofit agencies (tables 2

and 3). More than 90 percent of all

current and discharged patients

receiving home health care received

that care from home health agencies

certified by Medicare andlor

Medicaid. Over 85 percent of the

hospice current patients and

discharges received their care from

hospices certified by Medicare aud/or

Medicaid.

Patients by demographic

characteristics

At the time of the 1992 survey,

almost 1.3 million persons were on

the rolls the night before the agency

was surveyed as current patients

receiving home health or hospice

care. Almost 3.3 million persons had

completed episodes of care in the

12-month period prior to the month

of the smey (discharged patients).

The 1.2 million current patients

receiving home health care were most

likely to be elderly, female, white,

and married or widowed. The

likelihood of using home health

services increased with age because

usually functional status declines with

age (4). In 1992, more than

75 percent of all current home health

patients were 65 years or older. More

women (67 percent) were receiving

home health services than were their

male (33 percent) counterparts partly

because women outlive men. Only

about 17 percent of current patients

receiving home health care were

divorced, separated, or never married,

and 69 percent were married or

widowed (table 4). The distribution of

3.1 million discharges by age, sex,

race, and marital status was similar to
Advance Data No. 235 ● July 28, 1993 3

Table 2. Number and percent distribution of current patients receiving home health care and hospice care by type of agency ownership,

certification, and geographic region: United States, 1992

Home health osre Hospice care

Percent Percent Parc8nt

Agenoy characteristic Total distribution Total distriirotion Total ditiribotion

Allagancies . . . . . . . . . . . . . . 1,284,200 100.0 1,237,100 100.0 47,200

4,900

100.0

Ovmerehip

Propriekq . . . . . . . . . . . . . . .

Voluntary nonprofit. . . . . . . . . .

Government and othera . . . . . .

348,400

735,100

150,700

27.1

61.1

11.7

343,400

744,600

149,200

27.8

60.2

121

10.5

36.2

1,600 3.3

Certisloation

Certiied by Mediocre . . . . . . . .

Certified by Medicaid . . . . . . . .

1,173,300

1,176,300

91.4

91 .a

1,130,300

1,137,700

91.4

92.0

92.3

86.1

Northeast . . . . . . . . . . . . . . .

Midwest . . . . . . . . . . . . . . . .

couth . . . . . . . . . . . . . . . . . .

Weat . . . . . . . . . . . . . . . . . .

415,300

269,s00

438,900

160,200

32.3

21.0

34.2

12.5

399,200

260,600

423,300

154,000

323

21.1

34.2

12.4

16,100

9,300

15,500

6,200

34.1

19.7

33.0

13.2

NOTE Figuresmay notaddtototalsbecauseofrounding.

Table 3. Number and percent distribution of discharges who received home health care and hospke ears by type of ageney ownership,

eertificatlon, and geographic region: United states, 1992

Home hafth care Hospice care

Peroent Pwoent

Agenoy charaotarktio

Peroerrt

Total distribution Total distribution Total distribution

Allagencias . . . . . . . . . . . . . . 3,273,300 100.0 3,066,300 100.0 207,000 100.0

Proprietary . . . . . . . . . . . . . . .

Voluntary nonprofit. . . . . . . . . .

Government and othera . . . . . .

796,700

2,234,300

239,700

24.4

6s.3

7.3

7s5,700

2,C!45,800

234,800

25.6

66.7

7.7

13,000

169,100

4,ec0

6.3

91.4

2.4

Certification

Oartiied by Medicare . . . . . . . .

Certified by Msdiiaid . . . . . . . .

3,155,400

3,060,100

96.4

93.5

29s1,900

2,630,000

96.6

93.9

193,500

130,000

93.5

87.0

Region

Northeast . . . . . . . . . . . . . . .

Midwest . . . . . . . . . . . . . . . .

South . . . . . . . . . . . . . . . . . .

West . . . . . . . . . . . . . . . . . .

1,037,700

637,700

966,800

641$00

31.7

19.5

23.2

19.6

977,700

593,200

884,croo

601,400

31.9

19.3

28.2

19.6

60,000

44,400

62,900

39,600

29.0

21.5

30.4

19.1

NOTE Figuresmaynotaddtototalsbaceuesof rounding.

from care (usually because they died)

had demographic characteristics

similar to current patients (table 5).

Modification, Ninth Revision (ICD9-CM) (5). The first-listed diagnosis

at admission for home health and

hospice patients who are currently

receiving care is shown in table 6

grouped by ICD-9-CM chapter.

More than 25 pereent of the 1.2

million home health patients had

conditions that are in the ICD-9-CM

chapter, “Diseases of the Circulatory

System Group” (390-459). Persons with

heart disease, including congestive heart

t%ilure,made up 49 percent of all

conditions in this group. Stroke,

the distribution of current patients as

shown in table 5.

The 1,000 hospices were serving

47,200 patients at the time of the

1992 survey. Hospice patients

currently receiving care, like home

health patients, were elderly. More

than 76 percent of them were 65

years or older. Unlike home health

patients, however, hospice patients

were nearly as likely to be male as

female. Most current hospice patients

were white and married. Hospice

patients who had been discharged

Patients by diagnoses

Information on the primary and

other diagnoses at the time of

admission was collected from the

medical records for each home health

and hospice patient in the 1992

Survey. Diagnoses were coded

aeeording to the International

Classification of Diseases, Clinical
4 Advance Data No. 235 ● July 28, 1993

Table 4. Number and percent distribution of current patients receiving home health and hospice care by age, se% race, and mar’itsl

ststw United States, 1992

Home health care Hospice care

Percent Percent Percent

Patient characteristic Tokrl distritwtion Total distribution Total distribution

All patients . . . . . . . . . . . . . . . 1,2s4,200 100.0 1,237,100 100.0 47,200 100.0

Age

6.3

4.5

10.3

76.7

14.3

13.2

17.7

19.3

12.3

*

Under 45years . . . . . . . . . . . .

45-54 yeare . . . . . . . . . . . . . .

55-84 yeare . . . . . . . . . . . . . .

65years And over . . . . . . . . . .

85-69 years . . . . . . . . . . . .

70-74 years . . . . . . . . . . . .

75-79 years . . . . . . . . . . . .

80-64 yeara . . . . . . . . . . . .

S5years and over . . . . . . . . .

Unknown . . . . . . . . . . . . . . . .

140,700

49,90CI

115,900

965,700

136,100

176,900

212,100

220,800

219,600

12,0cml

11.0

3.9

9.0

75.2

10.6

13.8

16.5

17.2

17.1

0.9

137,600

47,800

111,100

929,500

129,400

170,600

203,700

211,700

214,100

10,900

11.1

3.9

9.0

75.1

10.5

13.8

16.5

17.1

17.3

0.9

3,000

2,100

4,900

36,204)

6,700

6,200

8,300

9,100

5,800

*

Sex

45.1

54.9

432,600

851,600

33.7

66.3

411,300

825,800

33.2

66.6

21,300

25,900

Male . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . .

Race

39,200 63.2

7.6

9.2

Whtie . . . . . . . . . . . . . . . . . .

Black . . . . . . . . . . . . . . . . . .

Other orunknown . . . . . . . . . .

879,700

169,200

235,300

68.5

13.2

18.3

S40,500

165,600

231,000

67.9

13.4

18.7

3,600

4,300

Marital status et admission

413,700

438,600

57,900

150,300

178,500

33.4

35.5

4.7

12.1

14.3

23,300

16,200

2,400

3,100

2,200

48.4

34.3

5.0

6.5

4.7

Married . . . . . . . . . . . . . . . . .

Widowad . . . . . . . . . . . . . . . .

Oivorcedorseparated . . . . . . .

Nevermarried . . . . . . . . . . . . .

Unknown . . . . . . . . . . . . . . . .

437,000

455,000

60,200

163,3043

178,700

34.0

35.4

4.7

11.9

13.9

NOTE Figuresmay notadd to totals because of rounding.

diabetes, and hypertension were also

frequent admission diagnoses for

current home health patienta.

Most hospice patients

(66 percent) had a first-listed

diagnosis of neoplasms (140-239).

Cancer of the lungs, colon, and

prostate accounted for 50 percent of

all neoplasms. The second largest

group was diseases of the circulatory

system, with congestive heart failure

accounting for45 percent of the

admission diagnosea for this group.

Hospice patients with human

immunodeficiency virus (HIV)

diagnoses were a major part

(94 percent) of the ICD-9-CM

chapter on infectious and parasitic

diseases. Becauae hospice care is

provided to patients who are in the

terminal stage of their illnesses, it is

not unexpected that these patients

would have first-listed admission

diagnoses of serious illnesses.

References 6. National Center for Health Statistics.

Development aud maintenance of a

national inventory of hospitals and

institutions. Vital Health Stat 1(3).

1965.

7. Bureau of the Census. Surnnxqy

report for the 1991 National

Health Provider Inventory.

Unpublished memo prepared by

the Health Surveys Branch. 1992.

8. Massey JT, Moore TF, Parsons

~ Tadros W. Design and

estimation for the National Health

InteMew Survey, 1985-94. National

Center for Health Statistics. Vital

Health Stat 2(110). 1989.

9. Hoffman K SpecMcations for

selecting NHHCS sample home

health agencies and hospices.

Unpublished memo. 1992.

10. Shah BV, Bamwell BG, Hunt lPN,

La Vrmge LM. SUDAAN user’s

manual, release 5.50. Research

Triangle Park, North Carolina

Research Triangle Institute.

1991.

1. Institute of Medicine. Toward a

national health care survey, a data

system for the 21st century.

Washington National Academy

Press. 1992.

2. National Association for Home

Care. Basic statistics about home

care. Information sheet. 1992.

3. Delfossc R. Hospice and home

health agency characteristics 1991

National Health Provider Inventory.

National Center for Health Statistics.

Vital Health Stat. In preparation.

4. Hing E, Bloom B. Long-term care

for the functionally dependent

elderly. National center for

Health Statistics. Vital Health Stat

13(104). 1990.

5. Public Health Service and Health

Care Fmsncing Administration.

International Classification of

Diseases, 9th Revision, Clinical

Modification. Washington Public

Health Service. 1980.
Advance Data No. 235 ● July 28, 1993 5

Table 5. Number and percent distribution of discharges by reiated patient characteristics, acoording to type of care received:

United States, 1992

Home hearth care Hospice care

Percent Percent Percent

Patient characteristic Total distribution Tok!l distribution ToW distribution

Alldischarges . . . . . . . . . . . . . 3,273,300 100.0 3,C@6,300 100.0 207,000 100.0

Age

Under 45years . . . . . . . . . . . .

4S54yeara . . . . . . . . . . . . . .

55-64 years . . . . . . . . . . . . . .

65yeare Andover . . . . . . . . . .

06-69 yaare . . . . . . . . . . . .

70-74 years . . . . . . . . . . . .

75-79 years . . . . . . . . . . . .

80-64 years . . . . . . . . . . . .

85yearsand over . . . . . . . . .

Unknown . . . . . . . . . . . . . . . .

400,200

162,600

263,300

2,421,600

373,400

463,600

574,900

521,700

497,600

26,600

12.2

5.0

8.0

74.0

11.4

13.9

17.6

15.9

15.2

0.6

336,700

143,300

237,400

2,274,500

344,500

418,200

542,800

498,600

470,400

23,900

12.6

4.7

7.7

74.2

11.2

13.6

17.7

18.3

15.3

0.8

13,500

18,800

25,900

147,000

28,900

35,600

32,100

23,200

27,200

*

6.5

9.1

12.5

71.0

14.0

17.2

15.5

11.2

13.2

*

sex

Male . . . . . . . . . . . . . . . . . . 1,231,900 37.6 1,128,800 36.8 103,000 49.7

Female . . . . . . . . . . . . . . . . . 2,041,500 62.4 1,837,400 68.2 104,000 60.3

Race

Whtie . . . . . . . . . . . . . . . . . . 2,245,200 63.6 2,067,600 67.4 177,600 65.8

Black . . . . . . . . . . . . . . . . . . 313,000 9.6 300,200 9.8 12,700 6.1

Otherorunknown . . . . . . . . . . 715,200 21.8 8S6,400 22.8 16,800 8,1

Marital statusatadmission

Married . . . . . . . . . . . . . . . . 1,239,400 37.9 1,145,800 37.4 93,500 45.1

Widowed . . . . . . . . . . . . . . . . 1,036,600 31.7 S66,300 31.5 70,200 33.9

Divmcadoraeparated . . . . . . . 164,400 5.0 141,300 4.6 23,200 11.2

Nevermanfed . . . . . . . . . . . . . 387,900 11.9 376,1W 12.3 11,800 5.7

Unknown . . . . . . . . . . . . . . . . 445,100 13.6 436,700 14.2 8,41Y3 4.1

NOTE F~urse may not add to totek because of rounding.

Table 6. Number of current home health and hospice patients by fiti-iiated diagnoses at admission: Unitad states, 1S92

Home health Hoapicas

iCD-8-CMprmWure oategoryand code pal%errts patients

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,237,100 47,200

Infectious andparasitic diseases . . . . . . . . . . . . . . . . . . . . . ...001-138 21,000 2,000

Neoplasm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...140-289 78,600 31,100

Endocrine, nutritional and metabolic diseases, and

immunity disorders......,.. . . . . . . . . . . . . . . . . . . . . . . 240-279 121,000 *

Oiseeses of the blood and b!cod-forrning organs.. . . . . . . . . . ...260-289 35,400 *

Mental disorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...290-319 3%,S)0 *

Oiseases of the nervous system and sense

organs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...320-368 76,900 1,300

Oiseasesofthecirculatoryaystem. . . . . . . . . . . . . . . . . . . . ...390-469 316,5(XI 5,900

Diseaseeofthersspiratorysyetem.. . . . . . . . . . . . . . . . . . . ...460-619 Bo,ooo *

Dkeaaesofthedigestivesystem. . . . . . . . . . . . . . . . . . . . . . . .520-579 43,000 *

Diseasesofthegenitourinaryaystem . . . . . . . . . . . . . . . . . . . ..58(P629 27,700 *

Complications of pregnancy, childbirth, and the

pUWpSIfUm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...630-678 1,800

Oiseaeeaoftheskinandaubcutaneoustiseue . . . . . . . . . . . . ...660-709 57,100

Oiseases of the musculoskelatal system and

connective tissue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 710-739 115,200 *

Congenitalanomalies . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...740-759 9,20Q *

Certeinmndiiionsoriginating intheperinatal

period . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...760-779 9,600 *

Symptoma,signs, andill-definedcondtions . . . . . . . . . . . . . . ...78&792 62,300

Injuryandpoisoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . soo—g2g

*

90,600 ●

Allotherorunknown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52,500 *

NOT~Figuresmay notaddtototfdsbecause ofrounrhg.
6 Advance Data No. 235 ● July 28, 1993

Technical notes

Source of data

The sampling frame consisted of

all home health agencies and hospices

identified in the 1991 National Health

Provider Inventory (NHPI) and all

agencies opened for business between

1991 and June 30, 1992, as identified

through the Agency Reporting System

(6). The NHPI is a comprehensive

census of nursing and related care

homes, residential care homes,

home health agencies, and hospices

conducted periodically by the

National Center for Health

Statistics (7).

Sample design

The sample design for the 1992

NHHCS is a stratified three-stage

probability design. Primary sampling

units (PSU’S) are selected at the first

stage, agencies are selected at the

second stage, and current residents

and discharges are selected at the

third stage.

The tirst stage utilized the

selection procedures that obtained

the 198 PSU’S used for the National

Health Interview Survey (NHIS), a

survey of the civilian

noninstitutionalized population of the

United States (8). The PSU’S are

counties, groups of counties, county

equivalents (such as parishes or

independent cities), or towns and

townships (for some PSU’S in New

England). Home health agencies and

hospices were selected within the

same PSU’S included in the NHIS to

minimize data collection costs and to

establish linkage between the two

surveys, allowing future research on

availability and use of services (7).

The second stage involved the

selection of agencies within six

primary strata of agencies. These

strata were formed in the 1992

sampling frame on the basis of type

of agency [hospices versus home

health agencies and mixed agencies

(providing both types of care or

unknown)], and type of PSU [selfrepresenting (SR) versus non-selfrepresenting (NSR), and within NSR

PSU’S Metropolitan Statistical kea

(MSA) versus non-MSA]. (MSA is a

metropolitan statistical area defined

by the U.S. Office of Management

and Budget on the basis of the 1990

Census.) Within these sampling

strata, agencies were arrayed by four

regions, five types of ownership, two

types of certification status, and

finally by the number of patients

currently being served by the agency.

The number of agencies selected

from each sampling stratum was

based primarily on results of research

into the optimum sample design for

the 1992 NHHCS. Hospices in the

NSR PSU’S and home health agencies

and mixed agencies in the non-MSA–

NSR PSU’S were selected with

certainty. Hospices in the SR PSU’S

and home health agencies and mixed

agencies in the MSA–NSR PSU’S and

the SR PSU’S were selected with

probability proportional to the

current patient size (as reported in

the NHPI sampling frame). A total

sample of 1,500 agencies was

selected; 384 were hospices, and the

balance was home health agencies or

mixed agencies (9).

The finrd stage is a systematic

random selection of six patients

currently served by the agency and six

patients discharged from care during

the last complete 12-month period.

Data collection procedures

The data collection for the

NHHCS began with a letter sent to

all 1,500 sampled agencies informing

the administrator of the authorizing

legislation, purpose, and content of

the survey. Within a week to 10 days

after the letter was mailed, the

interviewer assigned to conduct the

survey for a particular agency made

telephone contact to discuss the

survey and to arrange an appointment

with the administrator or person

designated by the administrator.

Three questionnaires and two

sampling lists were used to collect the

data. The Agency Questionnaire was

completed with the administrator or

designee. The interviewer would next

complete the Current Patient

Sampling List (CPSL) and

Discharged Patient Sampling List

(DPSL). With the CPSL, the

interviewer listed all patients on the

register of the agency on the evelting

prior to the day of the survey. The

DPSL was used to list all discharges

from the agency during the 12 full

months prior to the month of the

survey. Sampling of current patients

and discharged patients within

agencies was done by using tables

showing sets of sample line numbers

for each possible count of current

patients and discharged patients in

the agency. The interviewer drew a

sample of up to six current patients

and up to six discharges.

After the samples had been

selected, the Current Patient

Questionnaire and Discharged

Patient Questionnaire were

completed for each sampled person

by interviewing the staff member most

familiar with the care provided to the

patient. The respondent was

requested to refer to the medical or

other records whenever necessruy.

Sampling errors

Because the statistics presented

in this report are based on a sample,

they will differ somewhat from figures

that would have been obtained if a

complete census had been taken

using the same schedules,

instructions, and procedure. The

standard error is primarily a measure

of the variability that occurs by

chance because only a sample, rather

than the entire universe, is surveyed.

The standard error also reflects part

of the measurement error, but it does

not measure any systematic biases in

the data. The chances are 95 out of

100 that an estimate from the sample

differs from the value that WOUIC1be

obtained from a complete census by

less than twice the standard error.

The standard errors used in this

report were approximated using

SUIXL4N software. SUDAAN

computes standard errors by using a

first-order Taylor approximation of

the deviation of estimates from their

expected values. A description of the

software and the approach it uses has

been published (10). Exact standard

error estimates were used in tests of
Advance Data No. 235 ● July 28, 1993 7

signMcance in this report. Standard

errors for all estimates presented in

this report are presented in tables

I–VI.

The Z-test with a 0.05 level of

significance was used to test all

comparisons mentioned in this report.

Not all observed differences were

tested, so lack of comment in the text

does not mean that the diilerence was

not statistically significant.

TableL Standarderrorsfor numberandpercentdktributionof homehealthagencieaand

hospicesby ownership,certification,andgeographicregion:UnitedStates,1992

Type of agenoy

Honre health

Agenoy ohsracteriti”c Total agency Hoapioe

Number

Allagencies . . . . . . . . . . . . . . . . . 247 225 103

Peroent distribution’

Ownership

Proprietary . . . . . . . . . . . . . . . . . . 1.9 2.1 0.6

Voluntary nonprofit . . . . . . . . . . . . . . 2.2 2.3 1.1

Government andother . . . . . . . . . . . 2.0 2.3 0.8

Certified by Medicare . . . . . . . . . . . . 1.7 1.6 6.1

Certified by Madioaid . . . . . . . . . . . . 1.7 1.6 5.6

Region

Northeast . . . . . . . . . . . . . . . . . . . 1.0 1.1 2.3

Midwest . . . . . . . . . . . . . . . . . . . . 1.4 1.5 4.1

south . . . . . . . . . . . . . . . . . . . . . . 1.6 1.7 4.2

West . . . . . . . . . . . . . . . . . . . . . . 1.3 1.1 6.2

%endard errorsfor pwcentsem basedon anapproximathnbya multinominaldisMmion.

TableIl.Standarderrorsfor numberandpereentdistributionof currentpatientsreeeivinghomeheatthcareandhoaplceearsby typeof

agencyownership,eertifleetion,andgeographicregiomUnitedStems,1992

Home ksllh care Hospim oare

Percent Parcwrt

Agency charaotetistic Total

Perwrrt

distriZxrtion’ Total dmbtil Total diatrhrtiorr’

Allagencies . . . . . . . . . . . . . . . . . . 35,049 . . . 34,014 . . . 4,7S)6 . . .

Pro~iataty, . . . . . . . . . . . . . . . . . . . 23,355 1.8 23,147 1.8 1,270 2.6

Voluntary nonprofit. . . . . . . . . . . . . . . 32,035 2.0 30,996 2.1 4,648 2.9

Govemmentand others . . . . . . . . . . . 20,682 1.6 20,645 1.6 709 1.6

Oertifiestion

Certified by Medioare . . . . . . . . . . . . . 35,744 1.1 34,711 1.1 4,750 2.2

CerWedby Mediiid . . . . . . . . . . . . . 36,846 1.1 35,518 1.1 4,676 3.0

Northeast . . . . . . . . . . . . . . . . . . . . 20,054 1.3 16,339 1.3 3,677 5.8

Midwest . . . . . . . . . . . . . . . . . . . . . 16,307 1.2 16,571 1.2 1,269 2.7

South . . . . . . . . . . . . . . . . . . . . . . . 21,993 1.4 21,745 1.4 2,302 4.5

West . . . . . . . . . . . . . . . . . . . . . . . 6,763 0.7 6,654 0.7 1,036 2.3

‘Stsnrtsrdemxsfor permntsarebasedonan appmximrdionby a mukinomialdistribution.
8 Advance Data No. 235 ● July 28, 1993

Table Ill. Standard errors for number and percent distribution of discharges who received home health csre and hospice csre by type of

agency ownership, certification, snd geographic region Unitad States, 1992

Home health care Hospice care

Percent Percent Percent

Agency characteristic ToW distribution’ Total distritwtion’ Total diatribtion’

All agencies . . . . . . . . . . . . . . . . . . . 104,993 . . . 102,156 . . . 14,677 . . .

Proprietary . . . . . . . . . . . . . . . . . . . . 57,406 1.7 57,241 1.8 3,239 1.5

Voluntarynonprofit . . . . . . . . . . . . . . . 97,072 1.9 93,615 2.0 14,311 1.7

Govemmentand othera . . . . . . . . . 33,844 1.1 33,276 1.1 1,737 0.8

CertifiedbyMedicara . . . . . . . . . . . . . 106,554 0.5 103,844 0.5 14,770 1.4

CertifiedbyMediceid . . . . . . . . . . . . . 105,909 1.0 102,898 1.0 14,766 2.1

Northeast . . . . . . . . . . . . . . . . . . . . 62,272 1.6 59,248 1.7 8,393 3.3

Midwest . . . . . . . . . . . . . . . . . . . . . 36,874 1.1 38,872 1.2 4,040 2.0

south . . . . . . . . . . . . . . . . . . . 65,655 1.6 64,207 1.7 8,920 3.4

West . . . . . . . . . . . . . . . . . . . . . . . 38,414 1.2 37,892 1.2 7,006 3.0

‘Standard st’rors for percents are based on an spproximm”on by a multinomisl dlstributh.

Table IV. Stsndsrd errors for number and percent distribution of current patients receiving home health and hospice care by age, $e~

race, and marital status United States, 1992

Homehastthcsre Hospicecsre

Percent Percent Percent

Patient characteristic Total distritxdr”on’ Total distritwtiin’ Tots\ distribution’

All patients . . . . . . . . . . . . . . . . . . . . 35,049 . . . 84,014 . . . 4,795 . . .

Age

Under45years . . . . . . . . . . . . . . . . .

45-54years . . . . . . . . . . . . . . . . . . .

55-64years . . . . . . . . . . . . . . . . . . .

65yearsandover . . . . . . . . . . . . . . .

85-69years . . . . . . . . . . . . . . . . .

7C-74yeaE . . . . . . . . . . . . . . .

75-79years . . . . . . . . . . . . . . . . .

60-S4YWS . . . . . . . . . . . . . . . . .

B5yearaandover . . . . . . . . . . . . . .

Unknown . . . . . . . . . . . . . . . . .

12,911

4,252

7,733

28,664

8,388

7,952

11,263

12,424

10,754

2,499

1.0

0.3

0.6

1.0

0.6

0.6

0.6

0.8

0.6

0.2

12,892

4,246

7,712

27,890

8,226

7,692

10,835

12,043

10,691

2,334

1.0

0.4

0.6

1.1

0.6

0.6

0.8

0.8

0.8

0.2

624

298

697

4,442

1,507

1,270

2,015

2,164

913

893

i .3

0.7

1.6

3.0

2.9

2.6

3.2

3.4

2.0

1.8

Sex

Male . . . . . . . . . . . . . . . . . . . . . . .

Female . . . . . . . . . . . . . . . . . . .

17,107

25,351

0.9

0.9

16,8S7

24,888

1.0

1.0

2,516

3,206

3.3

3.3

Race

White . . . . . . . . . . . . . . . . . . . . . . .

Black . . . . . . . . . . . . . . . . . . . . .

Otherorunknown . . . . . . . . . . . . . . .

30,878

15,372

20,362

1.6

1.2

1.6

29,778

15,348

20,166

1.6

1.2

1.6

4,507

961

1,193

3.1

2.0

2.4

Marital status at admission

Married . . . . . . . . . . . . . . . . . . . . . .

widowed . . . . . . . . . . . . . . . . . . . . .

Divorcedorseparated . . . . . .

Nevermarried . . . . . . . . . . . . . . . . .

Unknown . . . . . . . . . . . . . . . . . . . . .

17,362

19,014

4,738

11,078

13,494

1.1

1.2

0.4

0.8

1.0

16,974

18,479

4,893

11,065

13,331

1.1

1.2

0.4

2,715

2,546

667

516

3.1

3.3

1.3

1.1

1.7

0.9

1.0 639

‘Standard srrora for pereents are baaed on en approximation by a muitinomhal diabibution.
Advance Data No. 235 ● July 28,1993 9

Table V. Standard errors for number and percent distribution of diachargea by eelactad patient characteristic, eccording to type of care

received: United Statee, 1992

Home health care Hw”ce care

Percent Parcarrt

Patient characteristic Total

Percent

distribution’ Tokd di.sbibufon’ Total distribtiorr’

Alldischarges. . . . . . . . . . . . . . . . . . 104,863 . . . 102,156 . . . 14,677 . . .

Age

Under 45yeare . . . . . . . . . . . . . . . . .

45-54 yeera. . . . . . . . . . . . . . . . . . .

55-64 yeers. . . . . . . . . . . . . . . . . . .

65yeareand over . . . . . . . . . . . . . . .

05-69 yem. . . . . . . . . . . . . . . . .

70-74 years . . . . . . . . . . . . . . . . .

75-79 yeare . . . . . . . . . . . . . . . . .

60-64 yeare . . . . . . . . . . . . . . . . .

85yeare and over. . . . . . . . . . . . . .

Unknown. . . . . . . . . . . . . . . . . . . . .

31,174

15,552

16,910

87,026

27,564

26,139

31,612

30,6U2

26,215

5,183

0.9

0.5

0.5

1.1

0.7

0.7

0.8

0.8

0.8

0.2

31,129

14,783

16,628

64,655

26,808

25,143

30,923

30,606

25,778

5,145

1.0

0.5

0.6

1.1

0.8

0.7

0.8

0.8

0.8

0.2

2,037

4,834

2,914

12,119

4,666

5,421

4,305

2,831

4,W-6

623

1.0

2.1

1.4

2.4

1.9

2.2

2.0

1.4

1.6

0.3

sex

Male . . . . . . . . . . . . . . . . . . . . . . . 49,228 1.0 47,500 1.0 9,322

Female. . . . . . . . . . . . . . . . . . . . . .

2.7

73,672 1.0 72,273 1.0 9,294 2.7

While. . . . . . . . . . . . . . . . . . . . . . . 61,410 1.7 77,730 1.8 13,886 1.6

Black . . . . . . . . . . . . . . . . . . . . . . . 30,668 0.9 30,780 1.0 2,166

Otherorunknown . . . . . . . . . . . . . . .

i .0

60,282 1.7 60,199 1.6 2,936 i .4

Marftalatatusatadmieeion

Married. . . . . . . . . . . . . . . . . . . . . . 51,662 1.1 51,015 1.2 7,235

widowed. . . . . . . . . . . . . . . . . . . . .

2.6

41,471 1.0 38,231 1.1 8,045 2.8

Divorcedorseparated . . . . . . . . . . . . 14,212 0.4 13,121 0.4 5,466

Nevermamied. . . . . . . . . . . . . . . . . .

2.2

27,067 0.8 26,853 0.8

Unknown. . . . . . . . . . . . . . . . . . . . .

2,168 1.0

39,597 1.1 39,472 1.1 2,W 1.1

‘Standerderrrssforpwcenrsarebssedonanepproxkrrariorrbyamukimm.@riMm@on.

TableVi.Standard erroreofnumber ofcurrenthome heafthandhospice patients byfket-iicted dicgnoeis atadmieeion:

United Stetes, l 992

lCD-r?-CMprtwedum cstagoryarrdcode

Hwna heaKh

Lwiwrts

Hospice

Datierrta

Total . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34,014 4,795

Irrfactiousandparaeiticdiseases.. ., . . . . . . . . . . . . . . ..001-I39 3,782 564

Neoplasm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...140-239 7,076 3,068

Endcxxire,nutritionaland metabolicdiseases,and

immunitydisordere. . . . . . . . . . . . . . . . . . . . . . . ...240.-278 6,420 *

Diseaaesof the bloodand blood-formingwgans. . . . . . . ...260-269 3,792

Mentaidisorders. . . . . . . . . . . . . . . . . . . . . . . . . . . ...290-319

*

4,179 *

Diseasesof the nervoussystemand sense

organs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...320-339 6,402 249

Diseaeesof thecirculatoryeyetem. . . . . . . . . . . . . . . . . ..3go-459 13,656

Diseaaesof therespiratoryayatam. . . . . . . . . . . . . . . . . ..4wlg

1,402

5,963 *

Diseasesof thedigeetive system. . . . . . . . . . . . . . . . . ...520-579 3,620 *

Diseaeesof thegenitourinary.syetem. . . . . . . . . . . . . . . ..56o-62g 3,470 ●

Compliions of pregnancy,childbirth,and the

puerparium. . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...330-676 806

Diseeeesof theskin andsubcutanaoustiwue . . . . . . . . ...660-709 5,620

Diseasesof the musculoakeletalsystemand

connectivetissue . . . . . . . . . . . . . . . . . . . . . . . . . ...71-739 9,031

Congenitalanomalies. . . . . . . . . . . . . . . . . . . . . . . . ...74&759

*

1,911 ●

Certainconditionsoriginatinginthe perinatal

period. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ..7313+’79 3,031

Symptorna,signs,andill-definedconditions.. , . . . . . . . ...760-788

●

5,102

hrjuryandpoieoning. . . . . . . . . . . . . . . . . . . . . . . . . . ..600-ggg

*

6,252

Allotheror unknown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

●

7,422 *
Advance Data No. 235 ● July 28, 1993 11

Symbols

--- Data not available

. . . Category not applicable

Quantity zero

0.0 Quantity more than zero but less

than O.O5

z Quantity more than zero but less

than 500 where numbers are

rounded to thousands

* Figure does not meet standard of

reliability or precision
Number 236 ● November 4, 1993 Reprinted 11/93

Advance

Data

From Vital and Health Statistics of the CENTERS FOR DISEASE CONTROL AND PREVENTION/National Center for Health StatiW”es

Negative Moods as Correlates of Smoking and Heavier

Drinking: Implications for Health Promotion

by Charlotte A. Schoenbom, M. P. H., and John Horm, M.SC.

Highlights

●

✎

●

✎

●

●

●

Of the five negative moods

reported (depression, loneliness,

restlessness, boredom, and upset),

the most prevalent among women

was depression (11.4 percent) and

among men restlessness

(10.9 percent).

About 40 million adults were often

depressed, lonely, restless, bored,

anchor upset in the past 2 weeks.

Over 8 million aduIts-3 million

men and 5 million women—

experienced three or more of these

negative moods in the past 2

weeks.

Adults who were often depressed

were about 40-50 percent more

likely to smoke than adults who

were never depressed.

Men and women who were often

lonely were about 60-70 percent

more likely to smoke than persons

who were never lonely.

On a negative mood scale ranging

from Oto 20, women with the

highest negative mood score were

almost three times as likely to

smoke as women who had a score

of zero.

Men with the highest negative

mood score were almost twice as

●

●

✎

likely to smoke as men with no

negative moods.

Men who were often lonely or

bored were almost twice as likely

to drink heavily as men who never

felt this way.

Odds of being a heavier drinker

more than tripled between men

who had no negative moods and

those with the highest Ievels of

negative moods no relationship

was found between negative moods

and heavier drinking for women.

Men with the highest levels of

negative moods were four times as

likely to combine smoking with

heavier drinking (three or more

drinks daily) than were men

reporting no negative moods.

Introduction

History of health promotion

Since1912, the United States

Public Health Service has taken the

lead protecting and promoting the

health of the American people (l). In

the early part of the 20th century,

prevention of acute, infectious

diseases such as tuberculosis,

diphtheria, and typhoid fever, were at

the forefront of public health

concerns. The t~chniquea for bringing

about change largely involved

quarantine, improved sanitation, and

later, immunization programs (2).

In the past several decades, with

management of most infectious

diseases (with the notable exception

of AIDS) largely under control,

public health officials have

increasingly turned attention to

prevention of chronic diseases such as

heart disease and cancer-which

often resuIt in years of disability,

reduced productivity, and premature

death. Multiple causal agents and a

long lag time between exposure and

fist manifestations of disease make

identifkation of the etiology of many

chronic diseases very complex.

Numerous epidemiological

investigations have been devoted to

identifying causal relationships

between environmental factors and

morbidity or mortality outcomes (3).

Studies have also examined the role

that personal health behaviors have in

increasing risks for disease, disability,

and death (4-11). Public health

efforts today are becoming

increasingly broader based,

encompassing environmental

regulation, health education, and

behavior change programs in order to

reduce risks of adverse health

outcomes (2).

**SH.WCE*,

& *.,

$- $

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES c sg Public Health Setvice

~a z= Centers for Disease Control and Prevention

‘~%.> National Center for Health Statistics CENTERS _FDL IFOR OISEASE CONTROL ‘wm&- No mwmnm
2 Advance Data No. 236 ● November 4, 1993

In 1978, the World Health

Organization hosted an International

Conference on Primary Health Care

at Alma-Ata, U.S.S.R. (12). An

outgrowth of this conference was the

establishment of a worldwide goal of

achieving “health for all by the year

2000” (13). This declaration was the

start of a formalized goal-setting

strategy for health promotion by

numerous governments and

international organizations (14). In

accordance with this new strategy,

U.S. Department of Health and

the

Human Services began a process of

establishing national health

promotion objectives for the United

States, setting specific target dates for

their accomplishment. The first U.S.

health promotion objectives,

commonly referred to as the 1990

Health Objectives for the Nation,

were established in 1980, with a

target date of 1990 (15). In 1990, the

status of progress in these objectives

was evaluated (16). Simultaneously,

drawing on lessons of the 1980’s, a

new set of objectives were established

for the next decade. These are the

National Health Promotion

Objectives for the Year 2000, also

referred to as Healthy People 2000

(17). Although the objectives were

developed under the sponsorship of

the Public Health Service, the project

was a national, not a Federal, effort.

Both the process of setting health

promotion goals and working toward

achieving them involves

representatives from Federal, State,

and local governments, nonprofit and

for-profit organizations, as well as

consumers of health services.

Significance of smoking, alcohol,

and mental health issues

Tobacco and alcohol use were

prominent in both the 1990 and year

2000 health promotion objectives.

Cigarette smoking and alcohol

consumption have been the subject of

extensive scientific investigation for

many years. Since 1964, with the

establishment of a National

Clearinghouse on Smoking (18)

(which later became the Office on

Smoking and Health) and the first

Surgeon General’s Report on

Smoking and Health (19), more than

20 reports to Congress have been

prepared on the health consequences

of smoking and other tobacco use.

Similarly, since 1971, seven major

reports to Congress have been

prepared by the National Institute on

Alcoholism and Alcohol Abuse

(NIAAA) outlining the current state

of knowledge of the causes and

consequences of alcohol abuse and

dependence (20).

Attention to mental health as a

national health priority came

somewhat later. Mental health was

first included as a priority area for

health objectives for the year 2000.

Since 1983, the National Institute of

Mental Health (NIMH) has published

five reports to Congress, entitled

Mental Health, United States,

summarizing the most current

information available on the Nation’s

mental health care delivery system

(21,22). In 1989, the National Health

Interview Survey (NHIS) included, for

the first time, a special section on

prevalence of chronic mental illness

in the U.S. adult, noninstitutionalized

population (22,23).

Interrelationships: smoking,

drinking, and mental health

In the national health promotion

objectives for the year 2000, tobacco

use, alcohol use, and mental health

are treated as discrete entities; their

interrelationships are not addressed.

However, this is not to say that these

have been ignored by the scientific

community. Heavy alcohol

consumption and cigarette smoking

have repeatedly been shown to be

associated: Smokers are more likely to

be heavy drinkers and heavy drinkers

are more likely to smoke (24-27).

The relationships between mental

health and these behaviors have also

been studied (28–32). Greater

knowledge of these interrelationships

provides a foundation for developing

more effective public health

education campaigns and advancing

progress toward meeting the health

objectives for the year 2000.

Rationale

In a climate of increased

knowledge of the adverse health

consequences of smoking and heavy

drinking, a decrease has been

observed in the prevalence of these

behaviors in the adult population.

Some of this reduction may be due to

people quitting smoking and drink~ng

because of health problems known to

be associated with these behaviora.

Some people have quit as a result of

their knowledge of the risks they

pose, while others who otherwise

might have taken them up, resisted

doing so. Thus, those individuals who

still smoke and drink heavily, in

today’s environment of widespread

knowledge of the associated healtlh

risks, may be people who find it more

difticult than others to avoid these

harmful behaviors. Assessment of the

relationships between harmful health

practices and selected negative moods

may provide important clues for

reaching these individuals. It is

hypothesized that emotional health

status may play an important role in

people’s decisions to engage in

behaviors that they know pose certain

health risks. Unfortunately, with

cross-sectional data (33) such as the

1991 National Herdth Interview

Survey of Health Promotion and

Disease Prevention (1991 NHISHPDP), the direction of causality

camot be determined. However,

whether it is the negative mood that

is causing the behavior, the behavior

that is causing the negative moo~ or

both being triggered by a common

third factor, evidence of their

co-occurrence would suggest that

mental health issues should be

addressed in tandem with more

traditional health education and

behavior modification approaches.

Contents of this report

This report presents prevalence

estimates for the adult U.S.

population for five negative mood

states (frequency of being depressed,

lonely, restless, bored, and upset)

drawn from the classic Bradbum

Affect Balance Scale (34) and used in

earlier population-based studies of
Advance Data No. 236 ● November 4, 1993 3

mental health (35). The report then

describes the relationship between

each of these moods and cigarette

smoking and heavy drinking. It goes

on to examine the relationship

between a total negative mood score

(an additive score composed of

responses to all five items), and

smoking and drinking, individually

and combined. The term “negative

mood” is used throughout this report

to describe these five measures of

negative affkct, also termed “negative

feelings” by Bradburn.

Methods

The 1991 NHIS-HPDP was

developed to gather baseline data for

tracking the year 2000 national health

promotion objectives, in order to

assess success or progress in achieving

the objectives by the turn of the

century. The 1991 NHIS-HPDP was

a component of the ongoing NHIS,

which has gathered information on

the health of the U.S. resident

household population each year since

1956 (36). In 1990, the National

Health Interview Survey of Health

Promotion and Disease Prevention

(1990 NHIS-HPDP) was fielded to

measure achievement of the 1990

Health Promotion Objectives for the

Nation (37). Although similarly titled

and both devoted to health promotion

issues, these two surveys contained

many different questions because

their purposes were to measure

progress toward ditferent sets of

objectives.

The 1991 NHIS-HPDP contained

a wide range of questions on personal

health behaviors, including tobacco

and alcohol use. The survey also

included a short section on mental

health, composed of the negative

afEectitems of the Bradbum Affect

Balance Scale (34).

The questions related to negative

moods in the 1991 NHIS-HPDP were

prefaced by telling respondents that

they were going to be asked questions

about how they had been feeling

emotionally. Respondents were then

asked how often in the past 2 weeks

they had felt depressed, lonely,

restless, bored, or upset. These

emotions have been shown to be

associated with other indicators of

mental health status such as anxiety,

marital tension, and job

dissatisfaction (34-35,38), but are not

the same as psychiatric diagnoses. For

example, a person who reported

being often depressed in the 1991

NHIS-HPDP may or may not be

clinically depressed according to

psychiatric diagnostic criteria (39-41).

Instruments exist to assess clinical

depression in population-based

surveys-most notably the Diagnostic

Interview Schedule, which has been

used in the National Health and

Nutrition Examination Survey (42).

The items included in the 1991

NHIS-HPDP are simply respondent

reports of the experience of negative

emotions or moods.

Like the questions related to

negative moods, the reference period

for the questions on alcohol

consumption was also the past 2

weeks; smoking status was based on

smoking practices at the time of

interview (see technical notes for

description of these variables).

One adult per family was

randomly selected from the full NHIS

sample for personal interview with

the health promotion questionnaire.

A total of 43,732 adults aged 18 years

and older responded to the 1991

NHIS-HPDP. The overall response

rate was 87.8 percent which is the

product of the response rate for the

basic NHIS household survey

(95.7 percent) and the response rate

for those persons identified in the

household as being eligible for the

HPDP component (91.7 percent).

Self-response was required for alI

questions in the HPDP.

Statistics shown and discussed in

this report were generated using

Software for Survey Data Analysis

(SUDAAN) (43). SUDMN is a

software package, designed

specifically for analysis of complex

survey data, that takes into account

the effects of the complex sample

design in the calculation of standard

errors. The SUDAAN Proc Descript

procedure was used to generate

prevalence estimates and their

associated standard errors for each of

the five negative moods for men and

women. Logistic regression, using

SUDAAN Proc Logistic with unequal

probabilities of selection, was then

run in order to test the hypothesis

that cigarette smoking and heavy

alcohol consumption were related to

severity of negative mood.

Sociodemographic and health

characteristics known to be associated

with these behaviors (age, education,

income, race, marital status, and

physical health status) were

controlled in order to assess the net

effect of negative moods. Response

categories for the negative moods

consisted of five levels ranging from

“never” to “very often.” The two

highest and two lowest categories

were combined in each case for

clearer presentation and because the

differences between “very often” and

“often” as well as between “rarely”

and “never” are analytically relatively

unimportant. For clarity in the

discussion, the term “often” is used

for the catego~ “often or very often”

and the term “never” is used for the

category “rarely or never.”

Beta coefficients and their

associated standard errors were then

transformed into the odds ratios

(OR =eP ) and their associated

95 percent confidence limits (95%

CI =e(p’’”%”s’p~(44) and are shown

in tables 1 and 2. The frequencies

shown in these tables represent the

weighted population estimates for

each of the negative moods, excluding

any cases for whom data for the

particular health behavior were

missing. This presentation allows the

reader to estimate at a glance, not

only the prevalence of each negative

mood, but also, with a simple

calculation (that is, prevalence of the

behavior multiplied by the population

estimate for a given mood), derive

the number of people in the adult

U.S. population with combined risks.

For example, 6,006,000 men were

often depressed, and 41.5 percent of

these men were current smokers.

Thus, 2,493,000 men (6,006,000 ●

41.5 percent) were both often

depressed and current cigarette

smokers. Similarly, 10,639,000 women
4 Advance Data No. 236 ● November 4, 1993

were often depressed, and

33.3 percent of these women were

current smokers. Thus, 3,543,000

women (10,639,000 .33.3 percent)

had both of these characteristics.

Findings

Prevalence of negative moods

Negative moods were experienced

by a substantial proportion of U.S.

men and women in 1991 (figure 1).

Depression was the most prevalent

negative mood among women and

rates of depression were higher for

women (11.4 percent) than for men

(7.1 percent). Restlessness was the

most prevalent negative mood among

men (10.9 percent); and rates of

restlessness were about the same for

women (10.3 percent). Boredom

ranked second for both women

(11.2 percent) and men (9.4 percent).

FeeIings of loneliness and

frequent upset were less common

than the other moods studied. Like

depression and boredorn.j prevalence

estimates for loneliness and upset

were higher for women than for men:

5.8 percent of women often felt lonely

compared with 3.4 percent of men,

and 4.5 percent of women reported

often feeling upset compared with

2.7 percent of men. These estimates

are unadjusted for any other

characteristics.

Rates shown in figure 1 were

transformed into population estimates

in figure 2. The estimates represent

the numbers of persons often

experiencing specific negative moods

in the past 2 weeks; a person may

have had more than one of these

moods. The percent and number of

men and women by total number of

negative moods experienced often or

very often in the past 2 weeks are

shown in figure 3.

Overall, almost 17 million adults

said they often felt depressed in the

past 2 weeks: 10.7 million women and

6.1 million men (figure 2). Al out 19

million men and women often felt

bored or restless. Loneliness was

experienced by about 3 million men

and almost 5.5 million women.

10

E

i

5

0

■ Men ❑ WomwI

11.4

10.9 11.2

5.8

4.5

013preseed Lonely Restiess Sored upset

Figure 1. Percent of men and women who oflen or very often felt depressed, lonely,

restless, bored, or upset in the past 2 weeks: United States, 1991

Depressed Lonely Restless Bored upset

Figure 2. Number of men and women who often or very often felt de!xessed, lonely,

restless, bored, or upset in the past 2 weeks: United States, 1991 -

Frequent feelings of upset affected 22.5 million women - often

fewer adults than any of the other experienced at least one of these

negative moods; almost twice as many negative moods during the 2 weeks

women (4.3 million) as men (2.3 preceding the NHIS intemiew, and

million) said they were often upset. over 8 million adults experienced

Figure 3 indicates that almost 40 three or more negative moods often

million adults —17 million men and during this period.
Advance Data No. 236 ● November 4, 1993 5

Number of na@ve moods

•None~l~2~3_5

Men Wcmen

(

Figure 3. Number and percent of men and women by total number of negative moods

experienced often or very often in the past 2 weeks: United States, 1991

Negative moods and smoking

Table 1 shows the percent of U.S.

men and women who smoked

cigarettes according to level of

depression, loneliness, restlessness

boredom, and feeling upset. Smoking

prevalence was markedly higher

among persons who often experienced

these negative moods than among

persons who never experienced them.

Smoking rates for persons who

sometimes had these feeIings were

also higher than for those who never

had them. Of the negative moods

studied, loneliness was the strongest

predictor of smoking for men and

boredom was the strongest predictor

for women. The prevalence estimates

shown in table 1 are unadjusted for

other characteristics that might

influence smoking behavior.

Many studies have shown that

smoking varies by sex, age, race,

income, education, and marital status

(37,4546). Smoking also affects and

is affected by physical health status

(47-48). To better assess the

relationship between negative moods

and smoking, the influence of these

other factors must be neutralized.

This was accomplished by calculating

odds ratios, ccmtrolIing for these

other characteristics (44). The odds

ratio is used as an approximation of

relative risk. Relative risk is defined

as the incidence rate among exposed

individuals divided by the incidence

rate among nonexposed individuals

(49). In this anaIysis, the exposed

groups are those with the negative

moods and the nonexposed are those

without the negative moods.

The odds ratios presented in

table 1 show the probability that

persons who have recently

experienced particular negative

moods wiH be smokers compared with

persons who have not had these

moods, after controlling for the

effects of se~ age, race, education,

income, maritaI status, and heaIth

status. Confidence limits, shown next

to each odds ratio, indicate whether

or not the increased probability is

suficientIy large that it is not likely to

occur by chance. When the lower

confidence limit is greater than one,

the odds ratio is statistically

significant.

Men and women who often felt

depressed had an odds ratio of 1.4

and 1.5, respectively, for smoking

compared with men and women who

never felt depressed. In other words,

frequently depressed adults were

about 40-50 percent more likely to

smoke than those who were never

depressed, Women who sometimes

felt depressed also had a higher risk

of smoking than nondepressed women

(OR = 1.3); the odds ratio for men

with this IeveI of depression

(OR =1.1) was not statistically

significant at the p S .05 level.

Frequent loneliness was a strong

predictor of smoking for both men

(OR = 1.7) and women (OR =1.6);

occasional loneliness also predicted

smoking for women (OR =1.2).

Although the odds ratio for men who

were sometimes lonely was aIso 1.2,

this was not statistically significant.

Women who were often restless

or bored had the highest odds ratio

for smoking (OR =1.7). Frequent

boredom was similarly predictive of

smoking for men (OR =1.6);

frequent restlessness was less so

(OR = 1.3).

Figure 4 shows the odds ratios for

smoking by men and women,

according to level of negative mood,

after adjusting for the effects of age,

race, education, income, marital

status, and health status. For women,

the odds of smoking cigarettes almost

tripIed between those with the lowest

and those with the highest negative

mood scores (OR =2.7 for women

with a score of 20). The odds of

smoking also went up for men as

negative mood scores increased,

although the relationship was not as

dramatic as for women: men with a

maximum score of 20 on the negative

mood index had an odds ratio of 1.8,

indicating that men with a lot of

negative moods were about

80 percent more IikeIy to smoke than

men who had no such moods.

Negative moods and drinking

Table 2 shows prevalence rates of

heavier drinking for men and women

according to levels of depression,

loneliness, restlessness, boredom, and

feeling upset. Odds ratios, described
6 Advance Data No. 236 ● November 4, 1993

Table 1. Prevalence (unadjusted) of cigarette smoking for men and women, by selected negative moods and odds ratios adjusted for

age, race, education, income, marital status, and health status: United States, 1991

Men Women

95-percent

Population Odds

95-percent

confidence Population Odds

Negative moods fin thousands) Prevalence

cmrfidence

ratio limits (in thousands) Prevalence ratio limits

Depressed

Very often or otten,

Sometimes . . . . .

Rarely or never. . .

Lonely

Very often or otten,

Sometimes . . . . .

Rarely or never. . .

Restless

Very often or often.

Sometimes . . . . .

Rarely or never. . .

Bored

Very often or often.

Somet]mes . . . .

Rarely or never. . .

Upset

Very often or often.

Sometimes . . . . .

Rarely or never. . .

. . . . . . .

. . . . . . .

. . . . . . ,

6,006

12,824

65,514

41.5

31.8

26.9

1.4

1.1

1.0

1.2,1.7

1.0,1.2

. . .

10,s39

20,423

62,379

33.3

27.2

1.5

1.3

1.0

1.4,1.7

1.2,1.4

21.4 . . .

2,842

5,479

76.090

44.9

36.2

27.5

1.7

1.2

1.0

1.4,2.1

1.0,1.4

. . .

5,405

9,868

78,182

35.7

28.0

22.7

1.6

1.2

1.0

1.4,1.9

1.1,1.3

. . .

. . . . . . .

. . . . . . .

. . . . . . .

9,220

13,040

61,956

39.2

29.9

26.8

1.3

1.0

1.0

1.1,1.5

0.9,1.2

. . .

9,637

13,977

69,708

35.8

26.1

21.6

1.7

1.3

1.0

1.5,1.9

1.1,1.4

. . .

. . . . . . .

. . . . . . .

. . . . . .

7,866

16,810

59,479

42.8

32.3

25.8

1.6

1.2

1.0

1.4,1.9

1.1,1.4

. . .

10,455

19,169

63,660

36.4

26.6

21.3

1.7

1.2

1.0

1.5,1,9

1.1,1,3

. . .

. . . . . . .

. . . . . .

. . . . . .

2,271

7,506

74,504

38.0

31.8

28.1

1.2

1.0

1.0

0.9,1.6

0.9,1.2

. . .

4,215

10,840

78,225

34.2

24.0

23.5

1.3

0.9

1.0

1.1,1.5

0.8,1.0

. . .

. . . . . . .

. . . . . . .

. . . . . . .

NOTES The population columns represent the number of men or women with spec!fied levels of selected negative moods. Popultilon estimates for smoking among these indwiduals can be

derwed by muit!piying the populalmn eet!mste for a partmular negative mood category by the prevalence estlmataa.

above, are also shown. Heavier per day for women. Because alcohol

drinking was defined as an average of affects women’s bodies more quickly

three or more drinks per day for men (thus taking less alcohol to make a

and an average of two or more drinks woman drunk) (50-53) and because

consumption of large amounts of

alcohol is considerably less common

among women than among men

(20,37,54-55), the number of drinks

defined as “heavier drinking” was set

lower for women. Even with this

lower cutoff, prevalence of heavier

drinking remained consistently lower

for women (less than 3 percent) than

for men across all.categories and

levels of negative moods. The highest

odds ratios, 1.4 for women who were

often bored or restless, failed to

reach statistical significance at

p s .05.

Findings for men and alcohol use

present quite a different picture.

Nearly 5 percent of men who did not

experience these negative moods

consumed an average of three drinks

or more daily. Among men who often

felt depressed, lonely, restless, bored,

or upset, rates of heavier drinking

were considerably higher. Among

men who were often lonely, over

9 percent drank heavily; among those

who were often restless or bored,

about 8 percent could be classified as

heavier drinkers. Prevalence of

3.0

[

/

Man

●. . .

. . .

J ...**”

/

.

. . .

.

,LdzZL I I 1 I 1

. .“

02 4 6810121416 1820

Negative moodscore

NOTE Nagatwe mod eixre k the SUM d an mdiwdualkacaa for each ofthe We negawe msosk depremad, bneh, ~

tofao, and upset Scuaioreach negatrva m.axl ranged trom 0 (nemr) m 4 (very ettan).

Figure 4. Odds ratios for smoking sccording to negative mood score, by sex, adjusted for

age, race, education. income, marital status, and health status: United States, 1991
Advance Data No. 236 ● November 4, 1993 7

Table 2. Prevalence (unadjusted) of heavier drinking for men and women by selected negative moods and odds ratios adjusted for age,

race, education, Income, marital status, and health status: United States, 1991

Men Women

95-percent

Odds

95-peroent

confidence Odds

Negative moods Population Pret@ence ratio limits Population

wnfidence

Prevalence ratio limits

Depressed

Very often or often. . . . . . . . 5,860 7.1 1.6 1.2,2.1 10,618 25 1.1 0.8,1.5

Sometimes . . . . . . . . . . . . 12,788 5.4 1.2 0.9,1.5 20,456 2.3 1.1 0.8,1.4

Rarely or never. . . . . . . . . . 65,594 4.7 1.0 . . . 62,670 2.3 1.0 . . .

Lonely

Very often or often. . . . . . . . 2,819 9.4 1.9 1.3,2.7 5,408 2.6 1.3 0.9,2.1

Sometimes . . . . . . . . . . . . 5,499 6.0 1.2 0.9,1.6 9,870 1.9 1.0 0.7,7.4

Rarely or never. . . . .. . . . . . 76,092 4.8 1.0 . . . 78,363 2.3 1.0 . . .

Restless

Ve~ often or often. . . . . . . . 9,186 7.7 1.7 1.3,2.1 9,625 29 1.4 1.0,1.8

Sometimes . . . . . . . . . . . . 13,004 4.8 1.1 0.9,1.4 14,074 1.9 0.9 0.7,1.2

Rarely or never. . . . . . . . . . 62,022 4.6 1.0 . . . 69,824 2.3 1.0 . . .

Bored

Very otten or often. . . . . . . . 7,640 8.2 1.9 1.5,2.4 10,452 2.9 1.4 1.0,1.8

Sometimes . . . . . . . . . . . . 16,742 5.3 1.2 1.0,1.5 19,227 1.9 0.8 0.6,1.1

Rarely ornever . . . . . . . . . . 59,600 4.5 1.0 . . . 83,604 2.3 1.0 . . .

Upset

Veryoften oroften . . . . . . . . 2,256 6.8 1.4 0.9,2.2 4,223 2.6 1.3 0.8,2.0

Sometimes . . . . . . . . . . . . 7,467 6.4 1.3 1.0,1.7 i0,891 22 1.1 0.8,1.5

Rarely or never. . . . . . . . . . 74,643 4.8 1.0 . . . 78,379 2.3 1.0 . . .

NOTES The Wpukrrlion columns repfesenl the number of P8rsons wtih speci?hd levels of nsgstib’e moods. Pofxlellon estimstes for heavier drinking (mem three or more drinks per dafi womem

2 or nmre drinks par day) smong these mdwtduals can be derived by mulupiying the populsmon in a partiilar negebva mocd caregory by she pmsiance estimates.

heavier drinking among men who

were often depressed or upset was

about 7 percent.

Odds ratios shown in table 2

confirm that men who often

experienced seIected negative moods

were considerably more likely to be

heavier drinkers than men who had

not had these moods, even after

adjusting for the effects of age, race,

education, income, marital status, and

health status. After controlling for

these other factors, men who were

often loneIy or often bored were

almost twice as likely to drink heavily

as men who had not felt these

negative emotions in the past 2 weeks

(OR = 1.9).

Figure 5 graphs the relationship

between total negative mood score

and heavier drinking in men and

women. As with the individual

3.5

3.0

1.5

1.0

r Men

I ●

.“-”

●

●

●

.*

●* I .

.

.

.*

*“

●“

●

●’

●

●

●

.-

.“*” ●*” women

.

.

.“

●*

●-=*

.

.*

●..*

.

02 46 8 10 12 14 16 18 20

Nagdve rnocd sum

problems, heavier drinking was

related to total score for men but not Figure 5. Odds ratios for heavier drinking among men (3 or more drinks dally) and women

for women. After adjusting for (2 or more drinks daily), by negative mood score, adjusted for age, race, education,

possible confounding characteristics, income, marftal status, and health status: United States, 1991

the odds of being a heavier drinker

more than tripled bewveen men with

no negative moods and those with a
8 Advance Data No. 236 ● November 4, 1993

maximum score of 20 (OR =3.3).

Among women, the odds ratio did not

rise significantly betieen those with

the lowest and highest negative mood

scores (OR = 1.5).

Negative moods and combined

smoking and drinking - men

A combination of smoking and

alcohol consumption has been

identified as significantly increasing

risks of life-threatening illnesses,

primarily cancers at various sites

(56-57). The association between

negative mood score and the cooccurrence of these behaviors is

shown for men in figure 6 for two

levels of alcohol consumption: three

or more drinks defined as heavier

drinking earlier in this report and a

somewhat more moderate level of two

or more drinks per day. Results are

consistent with other findings

presented: men with high negative

mood scores were at increased risk of

engaging in both of these behaviors

simultaneously. Men with the

maximum negative mood score of 20

were four times more likely to

combine smoking with drinking an

average of three or more drinks per

day (OR =4.1) than men with no

negative moods. Odds ratios for

combining smoking with drinking an

average of two or more drinks daily,

also were substantially higher for men

with the highest negative mood scores

(OR =3.3).

Discussion

These findings suggest that

emotional well-being may play a role

in cigarette smoking and heavy

drinking. If this is the case, it is likely

that programs designed to promote

behavior change could be made more

successful by addressing issues related

to emotional well-being. The link

found between negative moods and

these behaviors also lends support to

the suggestion by other researchers

that physicians could use information

on smoking and drinking practices,

routinely gathered in clinical Practice,

as clues-t; probe for underlying

emotional or mental conditions that

may deserve attention in their own

right as well as a means of improving

the prognosis for improvements in

physical health (58).

The issue of the direction of

causali~ in this analysis is

problematic. Certainly, engaging in

personal behaviors detrimental to

_ _ -3 or more drinks — 2 or mom drinks

4.5 r

and smoking and smoking

4.0

3.5

3.0

25

20

1.5

1.0

t

4

/’

/

02 46 0 10 12 14 16 18 20

t+egatie mood score

Figure 6. Odds ratios for combined smoking and heavy drinking among men, by negative

mood score adjusted for age, race, education, Income, marital status, and health status:

United States, 1991

health can be seen as a sign of less

than optimal mental health. Indeed,

both nicotine dependence and alcohol

abuse and dependence are classified

as psychiatric diagnoses in the

Diagnostic and Statistical ilfanua~

l%ird Edition, Revired (DSM-111-R),

published by the American

Psychiatric Association. On the other

hand, it is entirely logical that

emotional status can be influenced by

these health behaviors as well. The

neurological effects of alcohol abuse

have been well documented (20).

Further, in today’s antismoking

climate, stress associated with the

smoking habit may be sufficient to

have consequences for emotional

well-being of smokers.

The NHIS-HPDP, being a

cross-sectional survey, cannot address

the issue of causality. While the

Survey design would allow

longitudinal followup, there are no

current plans to conduct such an

investigation. Thus, the question

posed can only be addressed in its

most basic form: Are emotional.

health status and addictive personal

health behaviors sufficiently related to

warrant increased public health

initiatives that attempt to address

both issues together rather than one

at a time. Evidence suggests that they

are.

Conclusions

These findings have important

implications for current health

promotion activities and for setting

and attaining future health promotion

goals. Since the early days of public

sanitation and quarantine, activities

surrounding promotion of the public’s

health have continued to evolve.

Initial efforts to establish national

(1990) health promotion objectives

resulted in a set of 15 broad groups

of objectives, only some of which

were readily quantifiable. In the next

generation of health promotion,

objectives (year 2000), very specific,

quantifiable goals were set that

encompassed not only a wider range

of health problems, but also dealt
Advance Data No. 236 ● November4, 1993 9

with objectives related to special

populations, such as children, the

aged, racial-ethnic minorities, and the

disabled. Findings such as those

presented here suggest that current

health promotion activities designed

to reduce prevalence of harmful

health behaviors-such as smoking

and heavy drinking-might have

increased success if they could

address emotional (and by extension,

mental) health issues at the same

time. Such a step could help

accelerate progress toward attaining

current objectives to reduce

prevalence of harmful behaviors and

increase the health of the Nation’s

population. Beyond this, in

developing the next generation of

health objectives for the Nation,

establishment of cross-cutting

objectives that address harmful

personal health behaviors in the

context of emotional and mental

well-being should be seriously

considered.

References

1.

2.

3.

4.

Fee E. The origins and

developmentof public health in

the UnitedStates.Irx Holland

WW, DetelsR, Knox G, eds.

Oxford textbookof public health,

2d cd., VOI1, Influencesof public

health. New York Oxford

UniversityPress. 1991.

RichmondJB, KotelchuckM.

Co-ordinationand developmentof

strategiesand policy for public

health promotionin the United

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Printing office. 1992.

23. Barker P~ Manderscheid RW,

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24. DiFranza ~ Guerrera MP.

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27. Bradstock ~ Forman MR, Binkin

NJ, et al. Alcohol use and health

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1988.

28. Glassman AH, Helzer JE, Covey

LS, et al. Smoking, smoking

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York Oxford University Press,

107–20. 1991.

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Company. 1965.

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mental health in a general

population survey. Am J Epidemiol

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Health Interview Survey, 1991.

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United States, 1990. National

Center for Health Statistics. Vital

Health Stat 10(185). 1993.

38. McDowell I, Newell C. Measuring

health: A guide to rating scales

and questionnaires, 120-5. New

York Oxford University Press.

1987.

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Association. 1987.

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international statistical

classification of diseases and

related health problems, loth

revision, vol 1–3. Geneva: World

Health Organization. 1992.

41. World Health Organization. The

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disorders: clinical descriptions and

diagnostic guidelines. Geneva:

World Health Organization. 1992.

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Statistics. Plan and operation of

the third Health and Nutrition

Examination Survey, 1988-94.

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Statisti= Vital and Health Stat. In

preparation.

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al. SUD&%.Nuser’s manual,

release 5.50. Research Triangle

Park Research Triangle Institute.

1992.

44. Hosmer DW, Lemeshow S.

Applied logistic regression. New

York John Wiley and Sons. 1989.

45. Schoenbom CA Boyd G. Smoking

and other tobacco use: United

States, 1987. National Center for

Health Statistics. Vital Health Stat

10(169). 1989.

46. Pierce JP, Fiore MC, Novotny TE,

et al. Trends in cigarette smoking

in the United States. Education

differences are increasing. JAMA

261(l) :5ti0. 1989.

47. U.S. Department of Health and

Human Services. Reducing health

consequences of smoking 25 years

of progress. A report of the

Surgeon General. Chapter 2:

Advances in knowledge of the

health consequences of smoking.

Public Health Service, Centers for

Disease Control, Center for

Chronic Disease Prevention and

Health Promotion, Office on

Smoking and Health. 89-8411.

1989.

48. Colsher P~ Wallace RB,

Pormehn, PR, et al. Demographic

and health characteristics of

elderly smokers: Results from

established populations for

epidemiologic studies of the

elderly. Am J Prev Med 6(2):61–

70.1990.

49. Mausner JS, Baum AK.

Epidemiology: An introductory

text. Philadelphia: Saunders.

316-7.1974.

50. Jones BM, Jones MK. Women aud

alcohok Intoxication, metabolism

and the menstrual cycle. In:

Greenblatt M, Schuckit h@ eds.

Alcoholism problems in women

and children. New York Gmne

and Stratton. 1976.

51. Jones BM, Jones MK. Alcohol

effects in women during the

menstrual cycle. Ann NY Acad Sci

273:56747.1976.

52. Mello N. Some behavioral and

biological aspects of alcohol

problems in women. In: Kalant

OJ, ed. Alcohol and drug

problems in women. Research

advances in alcohol and drug

problems, vol 5. New York:

Plenum Press. 1986.

53. Roman PM. Biological features clf

women’s alcohol use: A review.

Public Health Reports 103(6):628-

37.1988.

54. Schoenbom CA Cohen BH.

Trends in smoking, alcohol

consumption, and other health

practices among U.S. adults, 1977

and 1983. Advance data from vital

and health statisti=, no 118.

Hyattsville, Maryland National

Center for Health Statistics. 1986.

55. Schoenbom CA. Health promoticm

and disease preventio~ United

States, 1985. Nationrd Center for

Health Statistics. Vital Health Stat

10(163). 1988.

56. Driver HE, Swarm PF. Alcohol

and human cancer (review).

Anticancer Res 1309-20.1987.

57. McCoy GD, Wynder EL.

Etiological and preventive

implications in alcohol

carcinogenesis. Cancer Res

392844-50.1979.

58. Parchman ML. Recognition of

depression in patients who smoke.

J Family Prac 33(3):255-8. 1991.

59. Levy PS, Lemeshow S. Sampling of

populations: Methods and

applications. New York John

Wiley and Sons. 1991.

60. Massey JT, Moore TF, Parsons

~ Tadros W. Design and

estimation for the National Health

Interview Survey, 1985-94.

National Center for Health

Statistics. Vital Health Stat 2(11(0).

1989.
Advance Data No. 236 ● November 4, 1993 11

Technical notes

Target population

The estimates presented in this

report are based on data from the

National Health Interview Survey

(NHIS), an ongoing survey of

households in the United States

conducted by the National Center for

Health Statistics. Each weeh a

probability sample of the civilian

noninstitutionalized population of the

United States is interviewed by

personnel of the U.S. Bureau of the

Census. Interviewers obtain

information about the health and

other characteristics of each member

of the households included in the

NHIS sample.

Description of the survey

The NHIS consists of two parts: a

basic health and demographic

questionnaire that remains almost the

same flom year to year and is

completed for each household

member, and special topic

questiomaires that vary from year to

year and usually are asked of just one

person in each family. In 1991, the

special topics included health

promotion and disease prevention,

encompassing environmental healt~

tobacco; nutrition; immunization and

infectious disease; occupational satety

and healti heart disease and stroke;

other chronic and disabling

condition~ clinical and preventive

services; physical activity and fitness

alcoho~ mental healti and oral

health. Other special topics in 1991

were pregnancy and smokin~ child

health; Acquired Immunodeficiency

Syndrome (AIDS) knowledge and

attitudes and drug and alcohol use.

With the exception of the questions

on drug use, all 1991 special topic

questiomaires were administered in a

face-to-face interview, with telephone

followup as needed. Seli-response was

required for all items. The drug

questionnaire was self-administered

with no telephone follow-up

permitted. Data tapes for these

surveys are available from the

Division of Health Interview Statistics

and can be linked for investigation of

cross-cutting research issues.

Response rates

The total sample interviewed for

1991 for the basic health

questionnaire consisted of 46,761

households containing 120,032

individuals. The response rate for the

basic health and demographic

questionnaire was about 95.7 percent

with proxy responses accepted for

household members not home at the

time of interview. For the IWllSHPDP, one adult per family aged 18

years or over was selected for

interview and self-response was

required. A total of 43,732 HPDP

questiomaires were completed,

representing 91.7 percent of

respondents identied as eligible at

the time of the household interview

and an overall response rate of

87.8 percent (the product of the

response rate for the basic

questionnaire and the response rate

for the special topic questionnaire).

Item nonresponse ranged from 1.3 to

2.1 percent for the questions

discussed in this report.

Sampie design and statistical

testing

Because the estimates shown in

this report are based on a sample,

they are subject to sampling error.

The standard errors for the statistics

shown in this report were calculated

using Software for Survey Data

Analysis (SUDAAN), developed by

the Research Triangle Institute (43).

SUDAAN is a software package,

designed specifically for analysis of

complex survey data, which takes into

account the effects of the complex

sample design in the cakxdation of

standard errors (59). The sampling

design of the NHIS has been fully

described elsewhere (60). Briefly, the

NHIS has a multistage sampling

design with stratification and

clustering. The fit stage of the

NHIS sample selection is the

selection of 198 primary sampling

units (PSU’S) from approximately

1,900 geographically defined PSU’S.

Within the sample PSU are%

segments are systematically selected,

and then clusters of housing units are

selected within the sample segments.

Finally, a sample person within each

household is selected for the HPDP

survey. Generally, variances and

standard errors are larger for such

designs than for simple random

samples of the same size. The

SUDAAN procedures used were

Proc Descript and Proc Logistic and

the design was Uneqwor (without

replacement sampling with unequal

probabilities of selection at the first

stage).

AU differences cited in this report

are statistically si~cant at the 0.05

level. A t-tes~ with a critical value of

1.96 was used to test all comparisons

that are discussed. Lack of comment

regarding the difference between any

two estimates does not mean that the

difference was tested and found not

to be statistically significant.

Definition of terms

Negative mood score—Additive

score of five negative moods

experienced in the 2 weeks preceding

the interview depressed, lonely,

restless, bored, and upset. Response

options for each were: O= neve~

1 = rarely; 2 = sometimew 3 =

often; 4 = very often.

Smokers-Persons who had

smoked at least 100 cigarettes in their

lifetime and currently smoked any

amount.

Heavier drinkers-Average daily

consumption of alcohol was

determined by multiplying the

number of days drank any alcoholic

beverages in the 2 weeks preceding

the interview by the number of drinks

consumed on the days drank divided

by 14 days. Although the total

amount of alcohol consumed in a

2-week period was averaged over 14

days, consumption was not necessarily

spread out evenly over this period.

Heavier drinking was defined as an

average of three or more drinks per

day for men and an average of two or

more drinks per day for women.

Odds ratiel%e odds ratio is an

approximation of relative risk.

Relative risk is defied as the
12 Advance Data No. 236 ● November 4, 1993

probability of a particular outcome

(smoking or heavier drinking) among

exposed individuals (yersons

experiencing negative moods), divided

by the probability of this outcome

among unexposed individuals

(persons experiencing no or lower

levels of negative moods). In

mathematical terms, it is the

exponential of the beta coefficient

generated by SUDAAN’S logistic

regression procedure (Proc Logist).

That is, OR =eP.

95-percent confidence limits of the

odds rati&In 95 percent of the cases,

the true odds ratio will fall within

these limits. When the lower limit

exceeds 1.0, the odds ratio is

statistically significant. In other

words, those in the exposed group

(with negative moods) are more likely

to smoke and/or drink than those in

the unexposed group (without

negative moods). In mathematical

terms, these limits were calculated as

the exponential of [the beta

coefficient (generated by Proc

I_.ogist)j-1.96 ● the standard error of

the beta coefficient], or

~i =e(tW%*S*)
Number 237 ● December 28, 1993

Advance

Data

From Vial and Health Statistics of the CENTERS FOR DISEASE CONTROL AND PREVENTION/National Centerfor Heafth Statistics

OfficeVisits to Psychiatrists: UnitedStates, 1989-90

by Susan M. Schappert, M.A., Division of Health Care Statistics

Introduction

During the 2-year period 1989-

90, an estimated 37.6 million visits

were made to nonfederally employed,

office-based physicians in the United

States who specialized in

psychiatry-an average of 18.8 million

visits per year. This report

summarizes data pertaining to these

visits in terms of patient

characteristics, physician practice

characteristic, and visit

characteristics. Two earlier reports

provide data on office visits to

psychiatrists for the years 1975-76

and 1985 (1,2).

The information presented in this

report is based on data collected by

means of the National Ambulatory

Medical Care Survey (NAMCS), a

national probability sample survey

conducted by the Division of Health

Care Statistics of the National Center

for Health Statistics, Centers for

Disease Control and Prevention. This

survey was conducted yearly from

1973 through 1981, and again in 1985.

It resumed an annual schedule with

the 1989 survey.

The 1989 and 1990 National

Ambulatory Medical Care Surveys

shared identical survey instruments,

definitions, and procedures. The

resulting 2 years of data have been

combined to provide more reliable

estimates, and the reader should note

that the estimates, percent

distributions, and rates presented in

this report reflect average annual

estimates based on the combined

1989 and 1990 data. The Patient

Record, the survey instrument used

by participating physicians to record

information about their patients’

office visits, is shown in figure 1.

The estimates presented in this

report are based on a sample, rather

than on the entire universe, of oflice

visits an~ as such, are subject to

sampling variability. The Technical

notes found at the back of this report

include a brief discussion of the

sample design, sampling errors, and

guidelines for judging the precision of

NAMCS estimates. Also located in

the Technical notes are definitions of

terms used in this repo~ including

the definition of a psychiatrist for

NAMCS purposes.

Several limitations of the data

should be emphasized. These include

the small number of psychiatrists who

participated in the 1989 and 1990

surveys (see the Technical notes for

additional discussion of sample size),

and the exclusion from participation

in the survey of all physicians who

were not primarily engaged in

office-based patient care as defined by

the American Medical Association.

Psychiatrists who are not classified by

the American Medical Association as

spending the majority of their

professional time in office-based

patient care may nevertheless spend a

significant proportion of their time

engaged in this type of activity in

addition to their “principal” activity.

Also excluded by the survey design

are psychiatrists who see patients at

community mental health centers and

other government-operated facilities.

It has been estimated that the

current NAMCS survey design

captures about 84 percent of all

ambulatory medical visits to

psychiatrists (3). Continuing

evaluation of the survey design may

result in a broader definition of

eligibility for participation in the

survey to better reflect the spectrum

of ambulatory medical care visits.

Several other publications

summarize overall tidings from the

1989 and 1990 National Ambulatory

Medical Care Surveys (4-6), and

reports on visits to other physician

specialties and related topics are also

available.

To obtain a list of NAMCS

publications, readem may contact the

Ambulatory Care Statistics Branch at

(301) 436-7132.

Patient characteristics

Visits to psychiatrists by patient’s

age, se~ and race are displayed in

* SEWICP*,O$

*Q

**

#

? U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

~

Public Health Service

Centers for Disease Control and Prevention

?+++

3

**= National Center for Health Statistics cENrERa

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Figure 1. Patient Record form

table 1. Overall, this specialty

received an average of 7.7 office visits

per 100 persons per year for 1989 and

1990, not significantly different from

visit rates noted in 1975-76 and 1985

(2). Visit rates were highest among

persons 25-44 years of age and 45-64

years of age. These age groups

together accounted for more than

three-quarters (79.9 percent) of all

psychiatrists’ visits, with persons in

the age group 25-44 years accounting

for nearly half of all visits

(48.2 percent). Visit rates for these

two groups did not differ significantly

from each other, at 11.4 visits and

12.8 visits per 100’persons,

respectively.

Persons 15-24 years of age and

65 years and over visited psychiatrists

significantly less frequently than did

persons 25-44 and 45-64 years of age,

with 4.2 and 4.6 visits per 100

persons, respectively. Persons under

15 years had the lowest visit rate of

the five age groups, with only 1.7

visits per 100 persons. These three

age groups (under 15 years, 15-24

years, and 65 years and over)

together accounted for only

20;1 percent of visits to this specialty.

The age distribution of visits to

psychiatrists is contrasted with that of

visits to all other physicians in

figure 2.

Females accounted for more than

half of the visits (59.1 percent) to

office-based psychiatrists in 1989--90,

significantly higher than the

40.9 percent of visits made by males.

However, there was no significant

difference found in the rate of visits
Advance Data No. 237 ● December 28, 1993 3

Table 1. Annual number, percent distribution, and rate of office vlsite to psychiatrists by

selected patient characteristics and geographic region, averaged over a 2-year period

United States, 1969-90

Number of Wit rate

visits in Percent

Patient characteristic thousands distributkm

per I&”

Personsf

Age

All ages . . . . . . . . . . . . . . . . . . . . . . . .

Under 15years . . . . . . . . . . . . . . . . . . .

15-24 years . . . . . . . . . . . . . . . . . . . . .

25-wyaars . . . . . . . . . . . . . . . . . . . . .

45-64 years . . . . . . . . . . . . . . . . . . . . .

65years andover . . . . . . . . . . . . . . . . .

Sex and age

Femele, all ages . . . . . . . . . . . . . . . . . . .

Under 15years . . . . . . . . . . . . . . . . . .

15-24 years . . . . . . . . . . . . . . . . . . . .

25+4yeafa . . . . . . . . . . . . . . . . . . . .

45-e4yeaB . . . . . . . . . . . . . . . . . . . .

65years andover . . . . . . . . . . . . . . . .

Male, all ages . . . . . . . . . . . . . . . . . . . .

Under 15years . . . . . . . . . . . . . . . . . .

15-24 Yscos. . . . . . . . . . . . . . . . . . . .

25-44years . . . . . . . . . . . . . . . . . . . .

-years . . . . . . . . . . . . . . . . . . . .

65yearsandover . . . . . . . . . . . . . . . .

Rase

Whtie . . . . . . . . . . . . . . . . . . . . . . . . .

Black . . . . . . . . . . . . . . . . . . . . . . . . .

Asianand Paciticlslander . . . . . . . . . . . . .

American lndian, Eskimo,andAleut . . . . . .

Unspachied.. . . . . . . . . . . . . . . . . . . .

Geogrephicregion

Northeast. . . . . . . . . . . . . . . . . . . . . . .

Miiest . . . . . . . . . . . . . . . . . . . . . . .

south . . . . . . . . . . . . . . . . . . . . . . . . .

West. . . . . . . . . . . . . . . . . . . . . . . . . .

18,790

940

1,464

9,065

5,950

1.351

11,100

229

918

5,487

3,466

990

7,6s0

712

565

3,5s6

2,464

361

17,355

1,0E41

201

66

126

6,325

4,132

5,359

2,974

100.0

5.0

7.9

48.2

31.7

7.2

59.1

1.2

4.9

28.3

18.4

5.3

40.9

3.8

3.0

19.0

13.2

1.9

92.4

5.6

1.1

0.3

0.7

33.7

22.0

28.5

15.8

7.7

1.7

4.2

11.4

12.8

4.6

8.8

0.9

5.2

13.6

14.4

5.7

6.5

2.6

3.2

9.2

11.2

29

8.4

3.5

..-

. . .

---

IZ8

6.9

6.4

5.7

Wisitratsssrebasad onU.S.Buresu oftheCensuses6rnetes ofthe&vi!hnmninSiMiand

lS89andiWo,averagSd overthe2-ysarpshf.

izadU.S.Wlaticm forJuiylof

topsychiatristsby femalesandmales

during this period (8.8 visits per100

females peryearcompared with6.5

visits per 100 males).

By agegroup, asomewhat

different proiileemerged. Males

under the ageof 15 were signMcantly

more likely to visit a psychiatrist than

were females under the age of 15. No

significant differences were noted

between males and femrdes 15–24

years,2544 years, and 45-64 years of

age, but the visit rate for females 65

years of age and over was signilkantly

higher than the rate for males in the

same age group.

Between 1985 and1990no

statistical diiferenees were found in

visit rates by age and sex. However,

significant increases were noted in the

percent of visits made by persons

45-64 years of age and 65 years and

over, along with a corresponding

decrease in the percent of visits by

persons 25-44 yeara of age.

White persons made 92.4 percent

of all visits to psychiatrists during

1989-90, while black persons

accounted for 5.6 percent. Asians and

Pacific Islanders represented only

1.1 percent of these visits.

Correspondingly, the visit rate for

white persons was higher (8.4 visits

per 100 persons per year) than for

black persons (3.5 visits per 100

persons).

Physician practice

characteristics

Psychiatrists received an average

of 2.7 percent of the office visits made

to ambulatory care physicians for

198%90, making them the ninth most

visited physician specialty overall

(table 2). However, psychiatry was the

iifth most visited specialty among

persons 25-44 years of age, receiving

an annual average of 9.1 million visits

by persons in this age group, or

4.5 percent of all visits made by

persons 2544 years of age during

1989-90.

Between 1975 and 1990, the

number of visits made to psychiatrists

went from a 2-year total of 30.6

million visits during 1975-76 to a

2-year total of 37.6 million visits in

1989-90, but this was not a

statistically significant change. The

1975-76 total represented 2.6 percent

of all visits to office-based physicians

during that period. This was not

signitlcantly different from their

1989-90 share.

Visit characteristics

Referral status and prior-visit

status

Only 2.1 percent of office visits

psychiatrists were the result of a

referral by another physician,

significantly lower than the

5.6 percent for visits to all other

physicians. The chronic nature of

to

psychiatric illness is underscored by

the fact that more than 90 percent of

the visits to this specialty were made

by patients who were returning to the

physician for care of a previously

treated condition, compared with

60.2 percent for visits to all other

physicians. Only 6.0 percent of

psychiatric visits were made by new

patients. Visits by referral status and

prior-visit status are summarized in

table 3.

Expected source of payment

Self-payment waa the expected

source of payment listed most

frequently at visit3 to psychiatrists

(63.5 percent). In contras$ selfpayment was cited at only

30.3 percent of visits to all other

physicians. Private insurance

(including commercial insurance and
4 Advance Data No. 237 ● December 28, 1993

Patient’sage

■ under El ,5-,4 Imnl 25-44 E 45-64 EEl rxyfmrs

15 years years years years end over

A&2

27.1

Viite to psychiatrists Viits to all other physicians

NOIE Sand on a 2-yaar awra@.

Figure 2. Percent distribution of office visits to psychistrlets and to all other physicians,

by patient’s age: United States, 1989-90

Blue Cross/Blue Shield) was Iisted at expected source of payment per visit.

41.6 percent of psychiatrists’ visits. It Visits to psychiatrists by expected

should be noted that physicians were source of payment are displayed in

able to report more than one table 4.

Table 2. Annual number, percent distribution, and rate of office visits by physician

speciafty, averaged over a 2-year period: United States, 1989-90

Number of Wslt mte

visits in Percent

Physician specialty thousands distribution ~eeGn?l

All visits . . . . . . . . . . . . . . . . . . .

General end family pmctice. . . . . . .

Internal medicine . . . . . . . . . . . .

Pediatrics . . . . . . . . . . . . . . . . . .

Obstetrics and gynemlogy . . . . . . .

Ophthalmology . . . . . . . . . . . . . .

Orthopedic surgery . . . . . . . . . . . .

Dermatology . . . . . . . . . . . . . . . .

General surgery . . . . . . . . . . . . . .

Psychiatry . . . . . . . . . . . . . . . . . .

Otolaryngology . . . . . . . . . . . . . . .

Csrdiov=cular diseesea. . . . . . . .

Urological surgery. . . . . . . . . . . . .

Neurology . . . . . . . . . . . . . . . . . .

Other . . . . . . . . . . . . . . . . . . . . .

S98,653

208,045

87,719

84,280

59,812

41,302

34,033

25,164

23,891

18,790

16,957

11,040

9,852

6,187

71,603

100.0

29.8

12.6

12.1

8.6

5.9

4.9

3.6

3.4

2.7

2.4

1.6

1.4

0.9

10.2

266.4

65.0

35.6

34.4

224.4

16.9

13.9

10.3

9.8

7.7

6.9

4.5

4.0

2.5

29.2

lWskrates erebasedon U.S. Bureau tithe Census etilmales 0fthecwi18an n0nlnstnW0wlUed ppulatmn of the Uniterl States

for Ju~l Of 19E9anCI lBSO, averaged Overthe 2.yearperlOd.

2VISIt rale is 47.2 VISILSper 1WI females. Females made 69.4 percent of the wsds to obstetnc!ens and gynecologists during thts

2-year p-mod.

Patient’s principal reason for

visit

Data in table 5 summarize the

patient’s principal reason for visiting

the physician, according to the eight

reason for visit modules, or groups of

reasons, outlined in A Reason fw VW

Classification for Ambulatory Care

(RVC) (7). Principal reason for visit

(item 9a on the Patient Recordl is

the patient’s most important

complaint, symptom, or other

reason(s) for this visit expressed in

the patient’s (or patient surrogate’s)

own words. Up to three reasons per

visit may be coded based on the

classification system found in the

RVC. It should be noted that the

principal reason for visit reported at

office visits to psychiatrists may ‘be

characterized by the psychiatrist

based on his or her assessment of the

patient’s condition, especially when

the visit is part of an ongoing caurse

of psychiatric treatment.

Two-thirds (67.8 percent) of all

visits to this specialty were due to a

symptomatic problem or complaint,

with the largest percent of symptoms

failing into the category of

psychological and mental disorders

(62.3 percent). Also prominent was

the treatment module, cited at

one-quarter (25.9 percent) of the

visits.

Specific reasons for visit are listed

in table 6. The single most frequently

mentioned principal reason for

visiting the psychiatrist was

depression, recorded at 28.2 percent

of visits. Anxiety or nervousness was

the second most frequent reason,

mentioned at 15.9 percent of visits. It

is important to note that the rank

ordering found in this and other

tables in this report may not always

be reliable, because near estimates

may not differ from one another

because of sampling variability.

Diagnostic and screening

services

About 7 percent of visits to

psychiatrists included one or more
Advance Data No. 237 ● December 28.1993 5

Table 3. Annual number and percent distribution of office visits to psychiatrists and to all

other physicians by patient’s referral status and prior-visit status, aversgad over a 2-year

period: United States, 1989-90

Viiitsto p.sychiatrfata Wits to all other physiu”ans

Number of Number of

visits in Percent w“sitsin Percent

Wit characteristic thousands distribution thousands distribution

Allviaii . . . . . . . . . . . . . . . . . . . 18,790 100.0 679,663 100.0

Patient’s referral status

Patient was referred to ttis visit

by another physician . . . . . . . . . . 395 2.1 37,830 5.6

Patient was not referred to this

visit by another physician . . . . . . . 18,395 97.9 642,033 84.4

Patient’s pnor-tisit status

Newpstient . . . . . . . . . . . . . . . . . 1,121 6.0 113,288 16.7

Old patient, new problem . . . . . . . . 132 0.7 157,506 23.2

Old patient, old problem. . . . . . . . . 17,537 93.3 409,089 80.2

Table 4. Annual number and pereent distribution of office visits to psychiatrists and to all

other physicians, by patient’s expaeted source of payment averaged over a 2-year period:

United States, 1989-90

Wsita to psychiatrists Wits to afl ofher physicr”ans

Number of Number of

E@SOted source of payment~

visits in Percent w’sifain Percent

thousands distribution thousands distribution

Allvisits . . . . . . . . . . . . . . . . . . . 18,790 1OQ.o 679,863 100.0

Self-pay . . . . . . . . . . . . . . . . . . . 11,922 83.5 206,139 30.3

Commercial insurance. . . . . . . . . . 5,077 27.0 154,166 22.7

Blue Cross/Blue Shield . . . . . . . . . 2,743

Mdiire . . . . . . . . . . . . . . . . . .

14.6 78,876 11.6

1,895 9.0 131,33s 19.3

Mediiid . . . . . . . . . . . . . . . . . . 1,156 6.2 55,487 8.2

Prepaid plarafHMO/lPA.lPP02. . . . . . 922 4.9 102,420 15.1

Nocharge . . . . . . . . . . . . . . . . . 163 0.9 12,746 1.9

Other. . . . . . . . . . . . . . . . . . . . . 1,245 6.6 37,007 5.4

Unknown . . . . . . . . . . . . . . . . . . 107 0.6 14,015 2.1

‘Numbersmay notaddto totalsbecausemorethanone sourceof paymentmaybe codedfor eachvisit.

2HM0is healthmeintanamaw~, IPAis indapadentwacticsassociation,andPPOla preferredpmvkrerWganizsriorr.

Table 5. Annual number and percent distribution of office visits to psychiatrists by

patient’s principal reason for visit averaged over a 2-year period: United States, 1~

Pnncr”pl reason for visit and RVC oode~

Number of

visits in

thousanrk

Percent

disfrilwtion

Allvisifs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18,790 100.0

Symptom mcdule . . . . . . . . . . . . . . . . ..S001s99 12,743 67.8

General symptoms. . . . . . . . . . . . . . . .SOOI-SOS 347 1.8

Symptoms referable to psychological and

mental disorders . . . . . . . . . . . . . . ..S100-S188 11,711 62.3

8ymptoms referable to the nervousystem

(excluding sense organs). . . . . . . . . . .S200+,259 295 1.6

symptoms referable to the digestive

syste m. . . . . . . . . . . . . . . . . . . ..S500-3639 197 1.0

Symptoms referable to the musculoskeletal

system . . . . . . . . . . . . . . . . . . . . ..S800-S999 93 0.5

All other symptoms. . . . . . . .S260-S4S9,S640-S869 99 0.6

Disease module. . . . . . . . . . . . . . . . . .. DOO1-D889 585 3.1

Oiagnoatic, screening, and preventive

mOdule . . . . . . . . . . . . . . . . . . . . ..Xlr30+699 9a 0.5

Treatment module. . . . . . . . . . . . . . . . ..TIoo-T6s9 4,875 25.9

Injury and adverse effects module . . . . . . . JOOI-J999 85 0.5

Other . . . . . . . . .R1otr-R700,Al 00++140,U99Cr-U999 40s 2.3

lBseadonA Reasonfor Wslt Classir%stim forhbufatory Cam (RVC) (7).

21noludeatestresultsendadministrfdiwrncdules,blanks,prtilem.s, arv-1ccmphhfa M el.sewhsrsCISSMWJ, em of IIM,)F

and illegibleantdes.

diagnostic or screening services

ordered or provided by the

psychiatris~ compared with

64.3 percent of visits to all other

physician. The “other” category was

checked most frequently

(5.4 percent). The mental status

exam, often used as a diagnostic tool

at the patient’s initial visit to the

psychiatris~ was included in the list

of specitic diagnostic and screening

cervices on the 1991 NAMCS Patient

Record, where it was cited at

40.3 percent of all visits to

psychiatrists. It did not appear as a

separate category in the NAMCS for

1989 or 1990.

Physician’s diagnoses

Data on principal diagnoses

rendered at office visits are obtained

from item 10a of the Patient Record,

which asks physicians to record the

principal diagnosis associated with the

patient’s most important reason for

the visit. Diagnoses are claasfied and

coded according to the International

Classification of Diseases, 9th Revisio~

Clinical Mod@cation (ICD-9-CM)

(8).

About 9 of every 10 visits to

paychiatrista resulted in a principal

diagnosis that waa classifiable to a

mental disorder (ED-9-CM codes

290-319). Principal diagnoses are

presented throughout this report

according to a cla.saiflcation system

suggested by the American

Psychiatric Aaaociation (APA) for use

with NAMCS data (see Technical

notes) (9). Grouped principal

diagnoses according to patient’s age

and sex are presented in tables 7

and 8.

The most frequently reported

diagnostic category was mood

disorders, including bipolar and

depressive disorders, which were

reported at 43.1 percent of all visits,

for an estimated average of 8.1

million otice visits per year for 1989

and 19$ . Within this group,

depressive disorders predominate~

accounting for 6.9 million visits, or

36.8 percent of all visits to officebased psychiatrists.
6 Advance Data No. 237 ● December 28, 1993

Table 6. Annual number and percent distribution of office visits to psychiatrists by the 20

most frequently mentioned principal reasons for visig averaged over a 2-year period:

United States, 1989-90

Number of

visits in Perc8nt

Principal reason for visit and RVC code~ thousands distribution

All visits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18,790 100.0

Depression . . . . . . . . . . . . . . . . . . . . . . . . ..S110

Anxiety or nervousness . . . . . . . . ., . . . . . . ..S100

Psychotherapy . . . . . . . . . . . . . . . . . . . . . . ..T410

Other signs or symptoms relating to

psychological and mental disorders. . . . . . . . .S165

Marital problems . . . . . . . . . . . . . . . . . . . . ..T705

Behavioral disturbances. . . . . . . . . . . . . . . .s130

Medication, other andunspecified trinds. . . . . . . .TI15

Parent-childproblems . . . . . . . . . . . . . . . . ...1710

Anger . . . . . . . . . . . . . . . . . . . . . . . . . . . ..sI15

Disfurbancesofsleep . . . . . . . . ... . . . . . . ..sI35

Social adjuatmentproblems . . . . . . . . . . . . . .1730

Occupational problems . . . . . . . . . . . . . . . ...1725

Psychosexual disordere. . . . . . . . . . . . . . . . .S160

Problems with identityand self-esteem . . . . . . . .s120

Fearaand phobias . . . . . . . . . . . . . . . . . . . ..S105

Otherproblemsoffamily relationship. . . . . . . . . .T7’15

Delusions orhallucinations . . . . . . . . . . . . . . . .S155

Functional psychoses. . . . . . . . . . . . . . . . . .D305

Counseling, notothenvise specfiad . . . . . . . . . .T605

Tiredness, exhalation . . . . . . . . . . . . . . . . . ..so15

Another reaaons . . . . . . . . . . . . . . . . . . . . . . . . .

5,303

2,983

1,300

1,030

6eo

610

441

372

357

321

319

294

233

227

223

219

212

209

194

164

3,070

28.2

15.9

6.9

5.5

3.7

3.2

2.3

2.0

1.9

1.7

1.7

1.6

1.2

1.2

1.2

1.2

1.1

1.1

1.0

1.0

16.3

Anxiety disorders accounted for

an average of 2.5 million office visits

peryearfor1989 and 1990,0r

13.4 percent of the total. The most

common diagnoses within this group

were generalized anxiety disorder

(ICD-9-CM code 300.02) with an

average of 693,000 visits per year rtnd

anxiety state, unspecified (ICD-%CM

code 300.00) with 500,000 visits per

year.

Also prominent among the

grouped diagnoses were personality

disorders. There was an annual

average of 1.9 million visits in this

category, or 10.2percent of the total.

Figure 3 illustrates the

distribution of secondary diagnoses at

visits to office-based psychiatrists.

Secondary diagnoses were reeorded at

6.8 million visits, or 36.3 percent of

the total. The largest group of

secondary diagnoses was personality

disorders, mentioned at 1.9 million

visits, or27.3 percent of all visits with

secondary diagnoses. Depressive

disorders were fisted at 1.2 million

visits, accounting for 17.Opercent of

the secondary diagnoses. Ill-defined

signs and symptoms and

nonpsychiatric medical conditions

(1.8 million visits) and anxiety

disorders (1.7 million visits) were also

prominent among secondary

diagnoses.

Visits to other physicians for

depression and anxiety

Pyschiatrists, as mentioned

earlier, received an annual average of

5.3 million visits at which the

patient’s reason for visiting the

physician was depression, and another

3.0 million visits for anxiety or

nervousness during 1989-90.

However, an additional 4.0 million

visits per year for depression and

anxiety were made to physicians other

than psychiatrists over the same

period. Listed in table 9 are office

visits made for selected reasons for

visit and diagnoses, according to

physician specialty. The data indicate

that primary care physicians receive a

significant number of visits for many

problems that may be psychiatric in

nature. An analysis of visits made for

depression, anxiety, and related

problems to physicians other than

psychiatrists is beyond the scope of

this report, but is scheduled to be the

topic of a later publication in this

series.

Therapeutic services

Data on therapeutic services,

including the use of medication,

ordered or provided at office visits to

psychiatrists are shown in tables

10-14. As used in the NAMCS, the

term “drug” is interchangeable with

the term “medication” and includes

all new or continued medications

ordered or provided at the visit. This

includes prescription and

nonprescription preparations,

immunizing agents, and desensitizing

agenta. “Drug mentions” refers to the

total number of medications listed in

item 15 of the Patient Record.

Physicians may record more than one

medication per visit, so that the total

number of drug mentions may exceed

the totrd number of visits. “Drug

visits” refers to visits with at least one

mention of medication ordered or

provided by the physician. An earlier

report describes the method and

instruments used in the collection and

processing of NAMCS drug data (10).

Table 10 presents data on the

range of therapeutic services ordered

or provided at visits to office-based

psychiatrists. Psychotherapy was the

type of therapeutic service mentioned

most frequently, at 89.5 percent of

the visits. More than one-third

(38.6 pereent) of psychiatric visits

included some form of counseling or

advice. This was most often reported

in the “other” category

(36.7 percent); of the specific types of

counseling mentioned on the Patient

Record, weight reduction was cited

most often, at 2.2 percent of visits.

Medication therapy was

mentioned at half of the visits

(50.2 percent), somewhat less than,

the 60.5 percent of visits to all other

physicians. More than half of all visits

made by females included medication

therapy (54.4 percent), signiticantl’y

higher than the 44.1 percent of visits

by males. Overall, the proportion (of

visits that included medication
Advance Data No. 237 ● December 28, 1993 7

Table 7. Annual number and percent dlatrlbution of vialts to office-based paychkstdsts by

grouped principal diagnoses, according to patient’s sexj averaged over a 2-year period

United States, 1989-90

Patient’s sex

Grwupad principal diagnosasl Tofa/ Female Male

Allvisiis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mental retardation, developmental disorders, and

other childhood disorders . . . . . . . . . . . . . . . . . . .

Hyperkinetic syndrome of childhood. . . . . . . . . . . .

other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Delirium, dementia, and other mental diaordera due

toagenarsl medicelcondtion . . . . . . . . . . . . . . . .

Subetanca-related disordera . . . . . . . . . . . . . . . . . .

Schizophrenia and other (nonmcmf)

psychotic disorders . . . . . . . . . . . . . . . . . . . . . . .

Mood disordera . . . . . . . . . . . . . . . . . . . . . . . . . .

Sipolardiaorders . . . . . . . . . . . . . . . . . . . . . . . .

Depraseive disorders . . . . . . . . . . . . . . . . . . . . .

Major depressive disordar . . . . . . . . . . . . . . . . .

Dyathymia . . . . . . . . . . . . . . . . . . . . . . . . . . .

Otherdepressivedisorders . . . . . . . . . . . . . . . .

Othermcmddisordars . . . . . . . . . . . . . . . . . . . . .

Anxietydisorders . . . . . . . . . . . . . . . . . . . . . . . . .

Panicdisorders . . . . . . . . . . . . . . . . . . . . . . . . .

Obsessive-compulsivedisorder. . . . . . . . . . . . . . .

Otheranxietydieorders . . . . . . . . . . . . . . . . . . . .

Adjuatrnentdkorders. . . . . . . . . . . . . . . . . . . . . . .

Personaliidisorders . . . . . . . . . . . . . . . . . . . . . . .

Othermentaldisorders . . . . . . . . . . . . . . . . . . . . . .

Otheroondtionsthatmaybaafoous oftreatnsent. . . . .

Ill-defined signs and symptoms and other

nonpsychiatricmedicsl mndtiions. . . . . . . . . . . . . .

Unknown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Numberofvisitsin thousands

I a,790

522

352

170

81

264

1,651

6,100

I,lm

6,920

2,820

3,054

1,046

%20

2,511

417

410

1,624

1,457

1,913

1,115

470

55a

126

11,100

93

5a

W7

64

60

974

5,420

797

4,603

1,626

2,011

766

%20

1,503

289

245

969

756

667

606

295

375

66

Percent distribution

7,680

429

296

133

97

204

676

2,630

363

2,317

994

1,043

280

1,006

128

165

715

700

1,046

509

174

163

62

Allvisits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100.0 100.0 100.0

Mental retardation, developmental disorders, and

otherchildhooddiaordera. . . . . . . . . . . . . . . . . . . 2.6 0.8 5.6

Hyparkineticsyndrome ofchildhood . . . . . . . . . . . . 1.9 0.5 3.9

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.9 W.3 1.7

Delirium,dementia, andothermental disordemdue

toageneralmedicalcondtion.. . . . . . . . . . . . . . . 0.4 0.6 W.2

Substance-relateddisorders... . . . . . . . . . . . . . . . 1.5 0.7 2.7

Schizophrenia and other (nonmoo@

paychoticdisorders . . . . . . . . . . . . . . . . . . . . . . . 6.6 8.6 6.6

Mooddisorders . . . . . . . . . . . . . . . . . . . . . . . . . . 43.1 46.6 34.9

Sipolardiaordera . . . . . . . . . . . . . . . . . . . . . . . . 6.2 7.2 4.7

Depressivedisorders . . . . . . . . . . . . . . . . . . . . . 36.8 41.5 30.1

Majordepressivedisorder. . . . . . . . . . . . . . . . . 15.0 16.5 12.9

Dysthymia . . . . . . . . . . . . . . . . . . . . . . . . . . . 16.3 18.1 13.6

Otherdepressivediaordera . . . . . . . . . . . . . . . . 5.6 6.9 3.6

Ofhermooddisorders . . . . . . . . . . . . . . . . . . . . . %.1 W.2

Am&tydisorders. . .. . . . . . . . . . . . . . . . . . . . . . 13.4

Panicdisordara . . . . . . . . . . . . . . . . . . . . . . . . .

13.5 13.1

2.2 2.6 1.7

Obsesaiva-oompulsivedisorder.. . . . . . . . . . . . . . 2.2 2.2 2.1

Otheranxietydiaorders . . . . . . . . . . . . . . . . . . . . 9.0 8.7 9.3

Adjusfmentdisorders . . . . . . . . . . . . . . . . . . . . . . . 7.8 6.6 9.1

Peraonaliidi.mrders . . . . . . . . . . . . . . . . . . . . . . . 10.2 7.8 13.6

Othermentaldisorders . . . . . . . . . . . . . . . . . . . . . . 5.9 5.5 6.6

Othercondtiinsthatmaybaafocus oftraatment. . . . . 2.5 2.7 2.3

Ill-defined signs and symptoms and other

nonpayohiatncmadical condtiona. . . . . . . . . . . . . . 3.0 3.4 2.4

Unknown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0.7 0.6 0.8

10iagnosticgmupingserebassdonackshlcation systarndevek$wdfortheAme+mn Psychii Aswdatfmtyf&chaal B.

First,M.D., d the NewYorkState Psychiatriclnstit@, for uso WM NAMC3 d~

therapy was not significantly different

from the46.3percent noted in1985.

Table 11 examines psychotherapy

and medication therapy used

separately orin combinational

psychiatrists’office visitsaccordingto

grouped principrd diagnoses, Again,

principal diagnoses arecombined

accordingtothe APA’ssuggested

classification system.

Medication therapy was most

often used as an adjunct to

psychotherapy; 45.6 percent of all

visits listed both psychotherapy and

medication therapy ordered or

provided by the psychiatrist while an

additional 43.9 percent listed

psychotherapy without medication.

Psychotherapy without medication

was provided more often than not at

visits for adjustment disorders

(74.6 percent of visits); personality

disordem (72.6 percent); substancerelated disorders (64.1 percent);

anxiety disorders excluding panic

disorder and obsessive-compulsive

disorder (56.1 percent} and

depressive disorders excluding major

depressive disorder (55.4 percent).

About three-quarters

(78.6 percent) of visita with diagnoses

of major depressive disorder reported

the use of psychotherapy and

medication. This treatment option

was also frequently cited at visits with

diagnoses of bipolar disordem

(72.9 percent); panic disorder

(71.7 percent); hypcrkinetic syndrome

of childhood (68.7 percent] and

schizophrenia and other noruoood

psychotic disorders (64.2 percent).

Additional data relating to the

utilization of medication at

psychiatrists’ office visita are shown in

tables 12-14. Among visits to

psychiatrist, there was an average of

15.9 million drug mentions pr year

for 1989-90, yielding about 1.7

mentions per drug visit and about 8

mentions for every 10 visits in

general. Data pertaining to selected

drug characteristics are shown in

table 12. Most of the drugs mentioned

at visits to office-based psychiatrists

were available by prescription only

(95.0 percent), were composed of a

single ingredient (93.3 percent), were

prescribed using a trade name
Advance Data No. 237 ● December 28, 1993

Table 8. Annual number, percent distribution, and cumulative percent of visits to

office-based psychiatrists by grouped principal diagnoses, according to patient’s age,

averaged over a 2-year period: United States, 1988-80

Number of

visits in Percent Cumulative

Groupad principst diagnoaesl thousands distribti”on percent

Under 15 years

All visits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mental retardation, developmental disorders, and other

childhooddisorders . . . . . . . . . . . . . . . . . . . . . . . . .

Hyperkineticayndromeofchildhood . . . . . . . . . . . . . .

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Adjuatmentdisorders . . . . . . . . . . . . . . . . . . . . . . . . .

Mooddisorders . . . . . . . . . . . . . . . . . . . . . . . . . . .

Depressivedkxders . . . . . . . . . . . . . . . . . . . . . . . .

Another. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

15-24 years

Allvisita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mooddisordera . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Bipolardkxdeffi.. . . . . . . . . . . . . . . . . . . . . . . . .

Deprassivedisorders . . . . . . . . . . . . . . . . . . . . . .

Adjustmentdiaordera . . . . . . . . . . . . . . . . . . . . . . . . .

Anxktydisordera. . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mental retardation, developmental disordera, andother

childhooddisorders . . . . . . . . . . . . . . . . . . . . . . . . .

Another . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2E#14 years

Allvisii . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mooddiaordera . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Sipolardisordecs . . . . . . . . . . . . . . . . . . . . . . . . . .

Depreaaivedieordera . . . . . . . . . . . . . . . . . . . . . . . .

Othermooddisorders . . . . . . . . . . . . . . . . . . . . . . .

Anxiatydisordera . . . . . . . . . . . . . . . . . . . . . . . .

Panicdisorders . . . . . . . . . . . . . . . . . . . . . . . . . . .

Obsessive-compulsivedisorder . . . . . . . . . . . . . . . . .

Otheranxietydieorders . . . . . . . . . . . . . . . . . . . . . .

Peraonalitydisorders . . . . . . . . . . . . . . . . . . . . . . . . .

Schaophrenia andother (nonmood) psychotic dkxders.

Adjustmentdisordere . . . . . . . . . . . . . . . . . . . . . . . . .

Another. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45-64 years

Allvisila . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mooddisorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Bipolardisordam . . . . . . . . . . . . . . . . . . . . . . . . . .

Depresaivedisorders . . . . . . . . . . . . . . . . . . . . . . . .

Anxialydiaorder’a . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Personaiiidisordars . . . . . . . . . . . . . . . . . . . . . . . . .

Adjuatmentdisordera . . . . . . . . . . . . . . . . . . . . . . . . .

Another. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

65 years and over

Allvisits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mooddkordere.. . . . . . . . . . . . . . . . . . . . . . . . . . . .

13ipolardisordar s . . . . . . . . . . . . . . . . . . . . . . . . .

Depraaeivedisorders . . . . . . . . . . . . . . . . . . . . . . . .

Othermooddisordere . . . . . . . . . . . . . . . . . . . . . . .

Allothar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

940

359

289

70

171

158

158

252

1,484

!S35

63

473

228

205

104

412

9,085

3,784

605

3,152

*8

1,419

188

194

1,026

1,041

766

693

1,358

5,950

2,795

397

2,396

699

735

322

1,399

1,351

647

95

740

12

504

i 00.0

36.2

30.8

7.4

18.1

16.8

16.8

26.8

100.0

36.1

4.2

31.9

15.3

13.8

7.0

27.8

100.0

41.5

6.7

34.8

W 1

15.7

2.2

2.1

11.3

11.5

8.7

7.7

15.0

100.0

47.0

6.7

40.3

11.6

12.3

5.4

23.5

100.0

62.7

7.1

54.8

0.9

37.3

. . .

38.2

. . .

. .

56.3

73.1

. .

100.0

. . .

36.1

. . .

. . .

51.4

65.2

72.2

100.0

. . .

41.5

. . .

. . .

. . .

57.2

. . .

. . .

. . .

68.7

77.4

65.1

100.0

. .

47.0

. . .

. . .

58.8

71.1

76.5

100.0

. . .

62.7

. . .

. . .

. . .

100.0

‘Diagnosticgroupingsare basedon a classificationsystemdeve!opedfortheAmericanPsychiatricAssociationby Mitiael B.

First,M.D., et the NewYoflrStatePsyclWric Institute,forusew“WNAMC3 dsta

(77.5 percent), and were not classified therapeutic classification, adapted

as a controlled substance by the Drug from therapeutic categories used in

Enforcement Agency (74.0 percent). theNationalDrug Code directory,

Dataintable13 summarize the 1985 edition (n). Incases wherea

number ofdrug mentionsby particular drug was classifiable to

more than one therapeutic category,

it was Iisted under the category for

which it was most frequently

prescribed.Asexpecte~

psychopharmacologic drugs were

prescribed most frequently

(82.8 percent of drug mentions).

Within this category, antidepressants

(39.7 percent of the mentions),

antipsychotic drugs (21.2percent),

and antianxiety agents (15.6 percent)

figured most prominently.

The generic substances used most

frequently in medications orderedor

provided at psychiatric office visits are

shown in table 14. Fluoxetine

hydrochloride (Prozac) wasthemost

commordy mentioned generic

ingredient, with 2.0 million mentions,

accounting for 12.7percent of the

total. It should be noted that drugs

containing more than one ingredient

arelisted in the data for each

ingredient.

Disposition of visit

Visits to psychiatrists were rnme

likely to include instructions to return

at aspeeiiic time (93.3 percent) than

were visits to all other physicians

(60.8 percent). Data on disposition of

visit are displayed in table 15.

Duration of visit

More than half (53.6 percent) of

all office visits to psychiatrists lasted

41 to 50 minutes (table 16). Average

duration of psychiatric visits was 42.7

minutes compared with 15.5 minutes

for visits to all other physicians.

Average durationis based onthe

time spent in direct, face-to-face

contact between the physician and

the patient. Itdoes not include visits

of ’’O’’-minutes duration, that is, visits

in which the patient did not meet

with the physician directly.

References

1. CypresaBKOfficevisitsto

psychiatrist: NationalAmbulatory

MedicalCareSmvey United

States, 1975-76. Advancedata

fromvital and health statistics;no.

38. Hyattsville,Maryland:National

Centerfor HealthStatistics.1978.
Advance Data No. 237 ● December 28, 1993 9

pe--r’r-~=3 Grouped secondary diagnoses

Mood dsorders (includes depressive

disorders-17.O percent)

18.4

Ill-defined signs and symptoms and

other nonpaychiatric medical

conditions

Anxiety disorders

Other mentaf disorders (dmaoeiative,

aomatoform, sleep, eating, sexual and

gender identity,end other disorders)

Childhood daorders

Substance- related disorders

“Other conditions fhat may be a focus

of freatment

3chuophrenia and other (nonmmrd)

psychotic disorders

Adjustment disorders

I I 1 t t I

o 5 10 15 m 25 30

Percent of all seconday dmgnoses

NOIES:OisOncak WX@WSsISMma chsmcstbrr y@Omdswk@sd fortt’m~ Pq-~ LyfAlchs@SLFlm& M.O., dtho NowVbrfcPs@Mrkl~ti

- withNAMCS daa Numbu d vidlswithsuonduy diquna8 = 6.S27mMon. SmJwSa amt,ssdonas-ynr~

Plgure 3. Percent distribution of secondary diagnoses at psychiatrists office visits by diagnostic group United States, 1989-90

2.

3.

4.

5.

Gardocki GJ. Office visits to

psychiatrist United States, 1985.

National Center for Health

Statistics. Vital Health Stat 13(94). 6.

1988.

Gardocki GJ, McLemore T,

DeLozier JE. The National

Ambulatory Medical Care

Complement Survey United

States, 1980. National Center for 7.

Health Statistics Vital Health Stat

13(77). 1984.

DeLozier JE, Gagnon RO. 1989

Summary National Ambulatory

Medical Care Survey. Advance

data from vital and health 8.

statistieq no. 203. Hyattsville,

Mmyland: National Center for

Health Statistics. 1991.

Schappert SM. National

Ambulatory Medical Care Survey:

1989 Summary. National Center

for Health Statistics. Vital HeaIth

Stat 13(110). 1992.

Schappert SM. NationaI

Ambulatory Medical Care Suwey

1990 Summary. Advance data from

vital and heaIth statistiq no. 213.

Hyattsville, Matyland: National

Center for Health Statistic. 1992.

Schneider D, Appleton ~

McLemore T. A reason for visit

classification for ambulatory care.

National Center for Health

Statistics. Vital Health Stat 2(78).

1979.

Public Health Setice and Health

Care Financing Administration.

International Classification of

Diseases, 9th Revision, clinicai

modification. Washington: PubIic

Health Sefice. 1980.

9. Fmt MB. Proposed groupings of

ICD-9-CM codes for NAMCS

reporting. New York State

Psychiatric Institute. Private

communication.

10. Koch H, Campbell W. The

collection and processing of drug

information. National Ambulatory

Medical Care Survey, 1980.

National Center for Health

Statistics. Vital Health Stat 2(90).

1982.

11. Food and Drug Administration.

National Drug Code directory,

1985 edition. Washington: Public

Health Service. 1985.

12. National Center for Health

Statistics. Public Use Data Tape

Documentation, 1989 National

Ambulatory Medical Care Survey.

Hyattsville, Maryland. 1991.
10 Advance Data No. 237 ● December 28, 1993

Table 9. Annual number and percent distribution of office visits for selected principal

reasons for visit and grouped principal diagnoses by physicisn specialty, averaged over a

2-year period: United States, 19S9-90

Physician specialty

Number of

visits in Pv7J?la1~ Ail other

Visit characteristic thousends Total Psychiatry sr.ww”aities

Percent distribution

Allvisits . . . . . . . . . . . . . . . . . . . . . . . . . .

Principal reason for visit

and RVC code2

All symptoms referable to psychological and

mental disorders. . . . . . . . . . . .SIOO-S199

Depression . . . . . . . . . . . . . . . . . . . ..SI1O

Anxiety and nervousness . . . . . . . . . . . .S1 00

Disturbances of sleep . . . . . . . . . . . . . .S135

Other signs or symptoms relating to

psychological and mental disorders. . . . .S165

Behavioral disturbances . . . . . . . . . .S130

Psychosexual disorders . . . . . . . . . . . . .S160

Anger . . . . . . . . . . . . . . . . . . . . . . ..S115

Fears andphobies . . . . . . . . . . . . . . ..sI05

Problems with identity and self-esteem. . .S120

Delusions or hallucinations . . . . . . . . . .S1 55

Grouped principal diagnoeeas

Mental retardation, developmental disordera, and

other childhood disorders . . . . . . . . . . . . .

Delirium, dementia, and other men~l disorders

due to a general medical condtion . . . . . . . .

Substance-related disordem. . . . . . . . . . . . , .

Schizophrenia and other (nonmood)

psychotic disorders . . . . . . . . . . . . . . . . . .

Mooddisorders . . . . . . . . . . . . . . . . . . . . .

Bipolar disordera . . . . . . . . . . . . . . . . . . .

Depressive disordera . . . . . . . . . . . . . . . . .

Major depressive disorder . . . . . . . . . .

Dyethymia . . . . . . . . . . . . . . . . . . . . . .

Other depressive ctisordere . . . . . . . . . . .

Other mood disorders . . . . . . . . . . . . . . . .

Anxiety disorders . . . . . . . . . . . . . . . . . . . .

Adjustment disordere . . . . . . . . . . . . . . . . . .

Personality dieordere . . . . . . . . . . . . . . . . . .

Other mental disorders . . . . . . . . . . . . . . . . .

Other condtions that may be a focus of

treatment . . . . . . . . . . . . . . . . . . . . . . . . .

Ill-defined signs and symptoms and ofher

nonpsychiatric mectiealeondtions . . . . . .

Unknown . . . . . . . . . . . . . . . . . . . . . . . . .

698,653

18,945

6,956

5,336

1,522

1,365

900

691

357

246

234

225

1,490

412

966

2,100

10,914

1,175

9,718

3,014

3,757

2,947

W

4,876

1,792

1,935

3,713

2,016

654,311

14,106

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

1Oi).o

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

2.7

61.8

76.2

55.9

21.1

75.5

61.0

26.1

100.0

90.6

96.9

94.3

35.0

*1 9.7

28.7

78.6

74.2

96.7

71.2

93.6

81.3

35.5

%.1

51.5

81.3

98.9

30.0

23.3

0.1

W.9

64.5

30.4

20.7

37.5

64.6

19.9

32.3

*1 7.4

—

%.4

%1

%2.8

60.6

44.0

65.3

18.3

21.6

*I .3

24.3

●5.9

16.5

53.3

41.6

17.1

*1.1

45.4

40.1

55.5

54.6

42.8

7.8

%1

6.6

●14.3

*4.6

%.7

56.5

—

%2.9

*4.2

X36.2

%0

%.1

4.0

4.4

W.6

%2.3

*1 1.2

●4.9

*6.9

●1.6

11.1

24.5

36.6

44.5

44.5

llncludes visits to general and family practitioners, internists, and pediatricians.

2BssedonAReason forViir ClassXcationforAnrbu/ato~W(RVC) ~.

‘Diagnosbcgroupings are based on a clessirication developed for the American Psychiatric Assocafiorr by Michael B. First,

M. D., of the Nsw York State Psychiatdc Institute, for use with NAMCS date.

13. National Center for Health

Statistics. Public Use Data Tape

Documentation, 1990 National

Ambulatory Medical Care Survey.

Hyattsville, Marykmd. 1992.
Advance Data No. 237 cDecember28, 1993 11

Table 10. Annual number and percent distribution of office visits to psychiatrists by

therapeutic service ordered or provided, averaged over a 2-year period: Untted States,

198940

Patient’s sex

Number of

Therapeutic service ordered vf”sitsin

or prvvided at visitl thousands Total Female Male

Percent distribution

Allviaii . . . . . . . . . . . . . . . . . . . . . . . . 18,790 1CO.o 100.0 100.0

New or continuing medication:

Nodrug mentions . . . . . . . . . . . . . . . . 9,353 49.8 45.6 56.9

Onedrug mention . . . . . . . . . . . . . . . . 5,106 27.2 28.5 25.2

Twodrug mentions . . . . . . . . . . . . . . . 2,662 15.2 17.5 11.9

Three drug mentions . . . . . . . . . . . . . . 988 5.3 5.5 4.9

Four or five drug mentions. . . . . . . . . . . 461 2.6 2.9 2.1

Counseling/advii.3

None . . . . . . . . . . . . . . . . . . . . . . . . 11,535 61.4 60.1 63.2

Weight reduction . . . . . . . . . . . . . . . . . 407 2.2 2.3 2.0

Smoking cessation . . . . . . . . . . . . . . . . 121 0.6 0.5 0.8

HIVtransmission . . . . . . . . . . . . . . . . . 62 0.3 W.1 0.7

Other . . . . . . . . . . . . . . . . . . . . . . . 6,804 36.7 38.2 34.7

Othernonmedication therapy

None . . . . . . . . . . . . . . . . . . . . . . . . 1,055 5.6 4.7 6.9

Psychotherapy . . . . . . . . . . . . . . . . . . 16,619 89.5 91.6 66.6

Other . . . . . . . . . . . . . . . . . . . . . . . 1,796 9.6 7.7 12.2

lNumbwe msynotaddtototalsbecausemoretian onetype of therapy maybe ordered or FXOVWXI at each visit.

2Nene of Ure epscirk therapeutic eetvkes listed in U’is catsgxy h@ frequsndea large erwwgh to meet NCHS mliillty

standards.

Table 11. Annual number and percent distribution of visits to office-based psychiatrists by type of therapy ordered or provided,

according to grouped principal diagnoses, averaged over a 2-yaar period: United States, 1969-90

TyIXOfthOr8pJtordersdorprtndded

Psyctx2- RS#h& Medication Neither

Number of tttewey mtfrout

Wta in Wifhord

Pa@JoGrouped prfnci~ diagrrosesi thousands Total nredicafion rnedhafion 6-Y; %%%Y;:3

Allvisits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mental retardation, developmental disorders, and other childhood

~=de= . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Hyperkinetic syndrome of childhood . . . . . . . . . . . . . . . . . . .

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Delirium, dementia, and other mental disordera due to a

general medical concfition . . . . . . . . . . . . . . . . . . . . . . . . . .

Substance-relatad disorders . . . . . . . . . . . . . . . . . . . . . . . . . .

Schizophrenia andother (nonrncm d)paychof icdiaordera.. . . . . . .

Mooddisorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Sipolardisorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Depreasivedisorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Majordepreasivedisorder . . . . . . . . . . . . . . . . . . . . . . . .

Dyathymia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Otherdepreasivediaordere . . . . . . . . . . . . . . . . . . . . . . .

Othermooddisorders . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Amdelydisorders. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Panicdisorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Obsessive-compulsivedisorder.. . . . . . . . . . . . . . . . . . . . .

Ofheranxietydisorders . . . . . . . . . . . . . . . . . . . . . . . . . . .

Adjustmentdkcrrdera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Peraonalilydisordera . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Othermentaldiaorders . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Othermnditiionsthat maybeafocusof treatment. . . . . . . . . . . .

111-definedsignsand aymptomsandother nonpsychiatricmedioel

Condtiions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Unknown.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

18,7S0

522

352

170

81

264

1,651

8,100

1,160

6,920

2,620

3,054

1,046

%?0

2,511

417

410

1,664

1,457

1,913

1,115

470

556

128

103.0

100.0

100.0

100.0

1OQ.o

100.0

1W.o

1OQ.o

100.0

100.0

100.0

100.0

100.0

100.0

1OQ.o

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

100.0

Perc9ntdistribufkm

45.6 43.9 4.6 5.9

67.9

6a.7

35.5

55.1

27.5

64.2

66.5

72.9

56.0

78.6

39.1

44.2

100.0

47.1

71.7

53.2

40.1

16.2

13.0

22.9

30.6

37.2

30.4

25.7

14.5

48.8

37.0

64.1

16.7

35.6

21.5

38.1

12.6

56.2

47.3

47.1

21.2

35.9

56.1

74.6

72.6

56.2

47.6

33.3

%22.7

11.0

12.6

7.6

V.9

*1.9

16.8

3.8

5.6

3.5

6.4

*1.0

%.3

2.3

V.1

%2.9

*1.0

%.1

W.9

W.5

%3.4

5.8

28.3

*5.4

*4.1

%1

. . .

*6.4

%2.4

%2.1

. . .

2.4

2.1

1.7

5.2

3.4

~.9

2.8

4.1

13.5

18.4

18.4

23.6

*1 7.6

10iagno~.cgroupingsarabasedonacleaaific!Mon syatemdavalopd fortheAmwicarr Psychiatric.tiaticm byMichaelB.Fitst, M.D.,oftheNsw YorkPaytiatric Instilute,foruse with

NAMC6 data.

2havemge of870,~tisb ikludWmti=ti ~Wme@nof ~ti-y. Wb,47.7~mt ~WoWm~li~ti dw4mpti@ *titiWti2O.l penxnt

r-rtsd~rnmwdication therapyatthevisit.

3Anavsrsgeofl .Imillionvisitadd rmtirdudepsyctmtherapy mmsdicstiontharapy. However,67.3pwcant ofthssedtadolhet mmmdication-, atvJ24.8p+jrcant rsportadthatothsr

counsallc@advice wasorrlsredorpmidwf.
12 Advance Data No. 237 ● December 28, 1993

Table 12. Annual number and percent Table 13. Annual number and percent

distribution of drug mentions at office visits distribution of drug mentions et office visits

to psychiatrists by selected characteristics, to psychiatrists by therapeutic clas:;ificaaveraged ovar a 2-year period: tion, averaged over a 2-year period:

United States, 1989-90 United States, 1989-90

Number of

Selected drug mentions Percent

characteristics in thousands distribution

Number of

CL%%%

drug mentions Percent

in thousands (iiafribti’on

All mentions . . . . . . . . .

Entry Status

Generic name . . . . . . . .

Trade name . . . . . . . . .

Undetermined . . . . . . . .

Prescription status

Prescri~ion drug . . . . . .

Nonprescription drug . . .

Undetermined . . . . . . .

Composition status

Single ingredient drug. . .

Combination drug. . . . . .

Undetermined . . . . . . . .

Control statusl

Controlled drug . . . . . . .

Schedule I . . . . . . . . .

Schedule 11 . . . . . . . .

Schedule ill . . . . . . . .

Schedule IV . . . . . . . .

Schedule V........

Uncontrolled drug. . . . . .

Undetermined. . . . . . . .

15,933

3,012

12,342

579

15,133

221

579

14,858

495

579

3,564

328

*116

3,125

11,790

579

I00.0

18.9

77.5

3.6

95.0

1.4

3.6

93.3

3.1

3.6

22.4

2.0

*0.7

19.6

74.0

3.6

1Refers to whether the mediifion is controlled by the Drug

Enforcement Agency (OEA). Tha D= classifies drugs into

five categories of mntml depending on therapeutic use arsl

potential for addition or habitation, with Schedule I dm~

having no currently accept~ medbl use and the highsat

potential for abuse. Schedule II-V drugs all have currentiy

eccepted medical uses, with potential for abuse ranging from

high for Schedule II to low relative to more retitied ~“~1

classes for Schedules Ill. N. and V.

Symbols

--- Data not available

. . . Category not applicable

Quantity zero

0.0 Quantity more than zero but less

than 0.05

z Quantity more than zero but less

than 500 where numbers are

rounded to thousands

All mentions . . . . . . . . .

Psychopharmacologic

drugs. . . . . . . . . . . . .

Antidepressants . . . . .

Antipsychotic drugs . . .

Antianxiety agente . . . .

Sedatives and

hypnotics . . . . . . . . .

CNS stimulants,

anorexianta. . . . . . . .

Necrologic drugs . . . . . .

Anticonvulsanta. . . . . .

Drugs used in

extrapyramidal

movement disorders. .

Pain relief . . . . . . . . . . .

Cardiovascular-renal

drugs. . . . . . . . . . . . .

Gastrointestinal agents . .

Hormones and agents

affecting hormonal

mechanisms . . . . . . . .

Metabolic, nutrient agents.

Respiratory tract drugs. . .

Antimicrobial agents . . . .

Hematologio agents . . . .

Other . . . . . . . . . . . . .

Unclassified,

miscellaneous . . . . . . .

15,933

13,191

6,331

3,375

2,484

619

362

1,018

590

426

287

264

*196

*170

V6

*52

%36

%20

*4O

579

100.0

82.8

39.7

21.2

15.6

3.9

2.4

6.4

3.7

2.7

1.8

1.7

1.2

*I .1

W.5

W.3

W.2

W.1

%3.3

3.6

lTherapeuIic clessikation is based on the etendarcl drug

rksfication used in the National Drug Code direck%y, t 9s5

sditJOn (11).

21ncludes anesthetics, antidotes, and tiologic drugs.

* Figure does not meet standard of

reliability or precision
Advance Data No. 237 ● December 28, 1993 13

Table 14. Annual number, percant distribution, and therapeutic classification of drug

mentions at office visits to psychiatrists by the 20 most frequently used generic

substances, averaged over a 2-year period: United States, 1969-90

Number.of

Generic substance ~m&~~~ J%%& .g”&:,

Allmentione . . . . . . . . . . . . 15,933 100.0 . . .

Fluoxetine hydrochloride. . . . 2,016

Lithium . . . . . . . . . . . . . . .

12.7 Antidepressants

1,269 8.0 Antipeychotic drugs

Alprazolam . . . . . . . . . . . . 951 6.0 Antiam”ety agents

Amitriptyline . . . . . . . . . . . . 851 5.3 Antidepressants

Imipremine . . . . . . . . . . . . 608 3.8 Antidepressants

Trazedone . . . . . . . . . . . . . 55s 3.5 Antidepressants

Thioridezine . . . . . . . . . . . . 553 3.5 Antipsychotic drugs

Nortriplyline . . . . . . . . . . . . 551 3.5 Antidepressants

Diazepam . . . . . . . . . . . . . 526 3.3 Antiam”ety agents

Desipramine . . . . . . . . . . . 521 3.3 Antidepressants

Lorazepam . . . . . . . . . . . . 436 2.7 Antianxkty agents

Doxepin . . . . . . . . . . . . . . 433 2.7 Antidepressants

Triffuoparazine . . . . . . . . . . 420 2.6 AntiPsychotic drugs

Haloparidol . . . . . . . . . . . . 344 2.2 htiPsYOhOtiC drugs

Perphanazk.. . . . . . . . . . 308 1.9 Arrtidepraeeants

Chlorpromazhre . . . . . . . . . ’29a 1.8 AntiPsychotic drugs

Temazepam . . . . . . . . . . . . 262 1.6 Sedatives and hypnotii

Benztropine . . . . . . . . . . . . 282 1.6 Drugs used in extrepyramidal movement

disordera

Maprotiline . . . . . . . . . . . . %!48 f’o.o Anfideprassante

Clonezepam . . . . . . . . . . . %245 %3.0 Anticonvulsanta

lFrequemy of mentioncombines single-ingradhrt agents with mentions of th agent as an ingredknt in a comhation drug.

~c class~~ h M ‘XI W Sandsnl dmgcksiflcatica yed intha Netbnsl DrugCode dimcfoy, 19S5edhien

(11). lncaaeewhwe agemsriosubm hdmm~~~ chssnWaM, itwaskstad inrhecatcQoryfer wtrkhit

was most fmquantly pfescribad.

Table 15. Annual number and percent distribution of office vlsita to psychiatrists and to all

other physicians, by disposition of visig averaged over a 2-year parted United States,

1969-90

Visits to psychiatrfets Wits to all otfwphysicisrre

Number of Number of

visitsin Percent Wts in Peromrt

Disposition of wsit~ thousands distribution tfrousarids distritn.rtim

A!lvieii . . . . . . . . . . . . . . . . . . . 18,790 100.0 679,863 100.0

Retumatspacified time . . . . . . . . . 17,526 83.3 413,531 60.8

Retumif neadad . . . . . . . . . . . . . . 843 3.5 159,043 23.4

No followup planned . . . . . . . . . . . 402 2.1 88,841 9.8

Telephone followup planned . . . . . . 226 1.2 25,656 3.8

Admit to bspii. . . . . . . . . . . . . 133 0.7 6,649 1.0

Refarto other physician. . . . . . . . . 120 0.6 21,335 3.1

Return to referring physician . . . . . . *5 I 113 6,624 1.0

Other dispositio n . . . . . . . . . . . . 233 1.2 13,2S2 2.0

lNumtws may notadd to totals txcause more than one dwition may be caded fm each VW

Table 16. Annual number and percent

distribution of office visits to psychiatrists

by duration of visk averaged over a 2-year

period: United states, 1969-90

Number of

visits in Percent

Durationof visitl thousands distributkrn

Allvisits . . . . . . . . . . . . 18,790 100.0

0minutes2 . . . . . . . . . . -

l-20 minutes . . . . . . . . 2,543 13.5

21-40 minutes. . . . . . . . 3,450 18.4

41-50 minutea . . . . . . . . 10,077 53.6

51 minutee and over. . . . 2,720 14.5

lMeen duration of physicisn-patient contact was 42.7

minutes.

%sits of O-minutes durafbnera thoseinwhiti therewas no

face-to-facecontactbetweenthe physkian and the patismt

Technical notes

Source of data and sample

design

The information presented in this

report is based on data collected by

means of the National Ambulatory

Medical Care Survey (NAMCS) over

a 2-yesr period horn 1989 through

1990. The target universe of NAMCS

includes office visits made in the

United States by ambulatory patients

to nonfederally employed physicians

who are principally engaged in office

practice, but not in the specialties of

anesthesiology, pathology, or

radiology. Telephone contacts and

nonoffice visits are excluded.

A multistage probability sample

design is used in NAMCS, involving

samples of primsry sampling units

(PSU’S), physician practices within

PSU’S, and patient visite within

physicien practices. The PSU’S are

counties, groups of counties or county

equivalents (such as parishes or

independent cities), or towns and

townships (for some PSU’S in New

England). Physicians were stratied

into 15 specialty groups during the

second stage of the survey design.

Detailed descriptions of the 1989 and

1990 survey design have been

published (4,12,13), and the reader is

urged to coneult these sources for

further technical information.

The 1989 NAMCS physician

sample included 2,535 physicians

selected from master ties maintained

by the Ameriean Medical Association

(AMA) and the American

Osteopathic Association (AOA); 104

of these were psychiatrist. Physicians

were screened at the time of the

survey to ensure that they were

eligible for survey participation, based

on a set of deeign criteria; of those

screened, 608 physicians, including 30

psychiatrists, were ruled ineligible

(out-of-scope), because they were

retired; employed primarily in

teaching, administration, or research;

or other reasons. Of the remaining

1,927 physicians, 74 percent

responded to the survey, including 58

psychiatrist, or 78 percsnt of those

surveyed.

Sample physicians were asked to

complete Patient Records (see

figure 1) for a systematic random
14 Advance Data No. 237 c December 28, 1993

sample of their office visits occurring

during a randomly assigned l-week

reporting period. Responding

physicians completed 38,384 forms,

including 1,184 forms completed by

psychiatrists.

For 1990, a sample of 3,063

non-Federal, office-based physicians

was selected from master files

maintained by the AMA and AOA.

Of this number, 127 were

psychiatrists. The overall response

rate for the 2,269 in-scope physicians

was 74 percent; the rate was

71 percent for the 91 in-scope

psychiatrists. Responding physicians

completed 43,469 patient records,

including 1,455 forms from

psychiatrists.

Characteristics of the physician

practice, such as primary specialty

and type of practice, were obtained

from the physicians during an

induction interview. The U.S. Bureau

of the Census, Housing Surveys

Branch, was responsible for the

survey’s data collection. Processing

operations and medical coding were

performed by the National Center for

Health Statistics, Health Care Survey

Section, Research Triangle Park

North Carolina.

The 1989 and 1990 National

Ambulatory Medical Care Surveys

were identical in terms of survey

instruments, definitions, and

procedures. The resulting 2 years of

data have been combined to provide

more reliable estimates. All estimates,

percent distribution, and rates

presented here, unless otherwise

noted, reflect 1989 and 1990 data,

which were averaged over the 2-year

period.

Sampling errors

The standard error is primarily a

measure of the sampling variability

that occurs by chance when only a

sample, rather than an entire

universe, is surveyed. The relative

standard error of an estimate is

obtained by dividing the standard

error by the estimate itse~ the result

is then expressed as a percent of the

estimate. Table I shows relative

standard errors for estimated

Table L Relative standard errors for

estimated numbers of office visits to all

specialists and to psychiatrist National

Ambulatory Medical Care Survey, 1988-90

Estimated

numbers of All wsite to

office vkits visitsl psychiatrists 2

Relative standard error in percent

100 . . . . . . . 72.7 31.1

200 . . . . . . . 51.5 23.4

500 . . . . . . . 32.6 17.1

1,000 . . . . . . 23.2 14.4

2,000 . . . . . . 16.5 12.9

5,000 . . . . . . 10.7 11.9

10,000 . . . . . 7.9 11.9

20,000. . . . . 6.0 11.3

50,000 . . . . . 4.5 11.2

100,000 . . . . 3.9 11.2

200,000. . . . . 3.5 11.1

500,000 . . . . . 3.9 11.1

1,000,000 . . . 3.2 11.1

1,400,000 . 3.2 11.1

1For visks overall, the smallest reliable eetimate is 593,csM

vk%s. Esbmates below this figure have a relative standard

error greater than 30 persent,

‘For vishs to psychiam”sts, the smallest reliable estimate is

110,000 visits,

Example of use of table An aggregate -“mate of 2 million

visia to pzychietrkts has a relative standtvd error of 12.9

parsent, or a standard error of 258,000 visits (12.9 percent of

2 million).

numbers of office visits for 1989–90,

and table II presents relative standard

errors for estimated numbers of drug

mentions. Standard errors for

estimated percents of visits are shown

in table III. Readers wishing to utilize

these tables should note that they

refer to combined years of data

rather than average annual estimates.

Alternatively, relative standard

errors for aggregate estimates may be

calculated using the following general

formula, where x is the aggregate of

interest in thousands, and A and B

are the appropriate coefficients from

table IV.

RSE(X)=r @ “ 100.0

Similarly, relative standard emors

for percents may be calculated using

the following general formula, where

p is the percent of interest and x is

the denominator of the percent in

thousands, using the appropriate

coefficient from table IV.

WP)==) ● 100.0

Adjustments for nonresponse

Estimates from NAMCS data

were adjusted to account for sample

physicians who were in scope but did

not participate in the study. This

adjustment was calculated to

minimize the impact of response on

final estimates by imputing to

nonresponding physicians data from

visits to similar physicians. For this

purpose, physicians were judged

similar if they had the same specialty

designation and practiced in the same

Psu.

Test of significance and

rounding

In this report, the determination

of statistical inference is based on the

t-test. The Bonferroni inequality was

used to establish the critical value for

statistically significant differences

(0.05 level of confidence). Terms

relating to differences such as

“greater than” or “less than” indicate

that the difference is statistically

significant. A lack of comment

regarding the difference between ;any

two estimates does not mean that the

difference was tested and found to be

not significant.

In the tables, estimates of office

visits have been rounded to the

nearest thousand. Consequently,

estimates will not always add to

totals. Rates and percents were

calculated from original unrounded

figures and do not necessarily agree

with percents calculated from

rounded data.

Diagnostic classification

system used in this report

Physicians’ diagnoses were

grouped throughout this report

according to a classification system

suggested by the American

Psychiatric Association (APA).

Table V shows the proposed

groupings of diagnostic codes that

were developed for the APA by

Michael B. First, M.D. for use with

NAMCS data. Diagnostic codes used

in this system are based on the

International Classification of Diseases,

9th Revisioq Clinical Modification

(ICD-9-CM) (8).
Advance Data No. 237 ● December28, 1993 15

Table H. Relative standard errora for

estimated numbers of drug mentions at

vislte to psychiatrists National Ambulatory

Medical Care Survey, 1969-90

Ekfimatert number of drug ReIative standard

mentions in fhouaarrds~ error in percent

100 . . . . . . . . . . . . . . . . .

200 . . . . . . . . . . . . . . . . .

500 . . . . . . . . . . . . . . . . .

1,000 . . . . . . . . . . . . . . . .

2,000 . . . . . . . . . . . . . . . .

5,000 . . . . . . . . . . . . . . . .

10,000 . . . . . . . . . . . . . . .

20,000 . . . . . . . . . . . . . . .

50,000 . . . . . . . . . . . . . . .

100,000 . . . . . . . . . . . . . .

2oo,ooa . . . . . . . . . . . . . .

500,000 . . . . . . . . . . . . . .

1,000,000 . . . . . . . . . . . . .

1,400,000 . . . . . . . . . . . . .

58.2

42.9

30.3

24.6

21.2

18.9

18.1

17.7

17.4

17.3

17.3

17.2

17.2

17.2

hesmallestreliabls aetimateofdnrg mantiamsatvisii to

peychii”eteb51 4,rW0.Esrimareebebw tib?igurehavea

r-standard errwgreetarthsn SOpercent

Exempleofuseof tablalmaggregata eetimateOflOmillbrr

dmgmantionehas arelativeetandard errorof18.lpercent

eraetandarderror ofl,810,000mantions (18.lpercentofl O

miliii).

Table IV. Coefficients appropriate for

determining relative standard errora by

type of estimate and physician groups:

National Ambulatory Medical Care Survey,

1969+0

Coefficient

(rbr estimates in thousands)

Type of estimate and

physician group A B

visita

Overall totals . . . . . .

General and family

practice, internal

medicine . . . . . . . .

Pediatrics, obstetrics

and gynecology. . . .

DOCtOrSOf osteopathy,

general surgery,

orthopedic surgery,

cerdiivascular

disea~s, sychiatry,

urologlca r surgery,

derrnatolcgy,

neurokrgy~-”

ophthalmology,

otolaryngology . . . .

Another. . . . . . . . .

Dcug mentions

Overall totals . . . . . .

General and family

prati”ce, internal

medicine . . . . . . . .

Psychiatry . . . . . . . .

DOCtOE Of osteopathy,

general surgery,

orthopedic surgery,

cardiovascular

diseases, urological

surgety, dermatology,

neurology,

ophthalmology,

Otolaryngol ,

obetetrice a‘%

Wgyg;$r$y,

. . . . . . . .

Another. . . . . . . . .

0.00097648

0.00456412

0.00755165

0.01236777

0.01169917

0.00157151

0.00589721

0.0296736

0.01603345

0.0187K!82

52.77952164

37.27953208

23.43030623

8.46452955

39.36793604

81.47054383

59.72607201

30.9506771

11.42009364

70.85063675

Table [[1.Standard errors for percents of estimated numbers of office visits to

psychiatris~ National Ambulatory Medical Care Survey 19S9-90

Eti”mafed percent

Base of percent

(visik in thousands) lor99 5or95 Ioorw 2oor60 30 or 70 50

Standard error in percentage points

200 . . . . . . . . . . . . . . . . . 2.1 4.5 6.2 8.2 9.4 10.3

500 . . . . . . . . . . . . . . . . . 1.3 2.8 3.9 5.2 6.0 6.5

0.9 2.0

;=:::::::::::::::: 0.6

2.8 3.7 4.2 4.6

1.4 2.0 2.6 3.0 3.3

5,000 . . . . . . . . . . . . . . . . 0.4 0.9 1.2 1.7 1.9 2.1

10,000 . . . . . . . . . . . . . . . 0.3 0.6 0.9 1.2 1.3 1.5

20,000 . . . . . . . . . . . . . . . 0.2 0.5 0.6 0.8 1.0 1.0

50,000 . . . . . . . . . . . . . . . 0.1 0.3 0.4 0.5 0.6 0.7

100,000 . . . . . . . . . . . . . . 0.1 0.2 0.3 0.4 0.4 0.5

600,000 . . . . . . . . . . . . . . <.1 0.1 0.1 0.2 0.3 0.4

*pie&u* of~W%*”m* dW~*Wmm~-timme 10millionvisitshaeastandsrd wmrefl.3

percentors relativestandarderrorof 4.3 prcent (1.3 perwnt dtidwl byS4 percent).

Table V. Proposed groupings of iCD4-CM codes for use with National Ambulatory

Medical Care Survey data

Grouped prfncipal diagrrasesl /cD-sLchf Coda.+

Mental retardation, developmental dieordera, 298,307.0,307.2-307.3,307.52+37.58%307.6+07.7,

andofher childhood disorders. . . . . . . . . . . . . . . 809.21,312.0-312.2, 312.4-315,317+1 9

Hypeddnetic syndrome of childhcmd. . . . . . . . . . . 314

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299,307.0,307.2-307.3,307.52407.53,307.6+07.7,

Dafirium, dementia, and other mentat disorders

duetoagenerat medicatcondiion. . . . . . . . . . . .

Subafance-related disorders . . . . . . . . . . . . . . . . .

Schizophrenia and other (~nm@

paychoticdiaorders . . . . . . . . . . . . . . . . . . . . . .

Mood disorders . . . . . . . . . . . . . . . . . . . . . . . . .

Sipolardieardens. . . . . . . . . . . . . . . . . . . . . . .

Depressive dieordws. . . . . . . . . . . . . . . . . . . .

Major depressive dsorder . . . . . . . . . . . . . . . .

Dyathymia . . . . . . . . . . . . . . . . . . . . . . . . . .

Other depraeeive disordere . . . . . . . . . . . . . . .

Other mood disorders . . . . . . . . . . . . . . . . . . . .

Anxiety disorders . . . . . . . . . . . . . . . . . . . . . . . .

309.21 ,312.O-312.2,312.4=313,315,317~19

290,293-294,310

2el-292@3+35

285,297,296

296.0-296.9,300.4,301 .13,311

296.0-226.1,296.4-296.81 ,296.68,301.13

296.2-286.3,296.62,24J0.4,31 1

296.2-286.3

800.4

296.62,311

Z96.6

800.O-2G0.9,WL2-300.3,306,308.81 ,309.69

Adjustment disorders . . . . . . . . . . . . . . . . . . . . . 308.0-309.1 ,309.23+J09.3,309.4,3C9.62408.63,203.9

Personatii diaordera . . . . . . . . . . . . . . . . . . . . . . 301.0-301.12,301 .2-W .50,301 .59+01.9

~har MEIntd disarder#. . . . . . . . . . . . . . . . . . . . 34)0.10-2LN).19,3m.sGoo.9,302,goIM07.l.!307.4.

307.50,&37.51,i07.54,307.5i4,307.8,Cj07.9,il 2.3,

316,646.4,780.5

Other COndfiOnSfhd may be a focws OfWfMard4. . . VI l,V17.O,V&)-VW,V&-2,9f15.2,g85.5,fW6.gl

W1-268,320+18.3,643.5-760.4,760.~.l ,996.3,

Illdefind signs and eymptoms and other 985.4,995.68489.9,V01 -V1 O,V12-V16,V17.1-V59.9,

nonpsychiatric medical condiions. . . . . . . . . . . . . V64-V65.1 ,V65.3-V82

Unknown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Includes blank, illegible, and uncodable diagnmsea.

‘Dmgrmstc~erebasedmac~ ‘ davalqA fortha Arr&fcan Peych@k Aswc&&m by fJii B. First,

M.D., of the NW Ycw’k8tata Psychii Inst%uta, h use wiUI NaIfcmai An’Wlafary Medical care 8urvey data

2D*grmetk codes are based cm the Irrtar-netional r3sssJtiti ofm~, ~ ~, ~ ~~, ~ (8).

%rCludee Cksedative dwars, aunetoferm dieorrkre, sleep d~, aatimJ d~, d~ of eakllal arid gender

idalltily, impulse COl$JOldismdere,elrdotherdisoWrs.

41ncludas twueing, lwusatmkj, end acormmio circamebnceq other fsmily charmatencae (family disruption, rnedtal publarw,

parent-child pmtM3ms, StC] atlw ps@@xla“ Icircumstenmq andotharcOrxWme.
16 Advance Data No. 237 GDecember 28, 1993

Definition of terms

Ambulatory patient-An

ambulatory patient is an individual

seeking personal health services who

is not admitted to any health care

institution on the premises.

Physician—A physician is a duly

licensed doctor of medicine (M.D.) or

doctor of osteopathy (D.O.) who is in

office-based practice and who spends

some time caring for ambulatory

patients. Excluded from NA.MCS are

physicians who are hospital-based;

who specialize in anesthesiology,

pathology, or radiology; who are

federally employed; who treat only

institutionalized patients; or who are

employed full time by an institution

and spend no time seeing ambulatory

patients.

Psychiatrist-A physician

described in this report as a

Suggested citation

Schappert SM. Office visits to psychiatrists

United States, 1989-90. Advance data from

vital and health statistic no 237. Hyattsville,

Maryland: National Center for Health

Statistics. 1993.

psychiatrist has self-designated a

practice specialty of psychiatry,

psychoanalysis, or child psychiatry on

the AMA’s Physicians’ Professional

Activities Questionnaire. The

physician’s specialty is also verified

during the NAMCS interview. About

72 percent of the visits to office-based

psychiatrists were made to physicians

who were certified by the American

Board of Psychiatry and Neurology.

Ofice-An office is the space that

physicians identify as a location for

their ambulatory practice. Offices

customarily include consultation,

examination, or treatment spaces that

patients associate with the particular

physician.

Visit-A visit is a direct personal

exchange between an ambulatory

patient and a physician or a staff

member working under the

Copyright information

All material appearing in this report is in the

public domain and may be reproduced or

copied without permission; citation as to

source, however, is appreciated. This report

may be reprinted without further permission.

physician’s supervision, for the

purpose of seeking care and

rendering personal health services.

Drug mention-A drug mention is

the physician’s entry of a

pharmaceutical agent+y any route

of administration-for prevention,

diagnosis, or treatment. Generic as

well as brand-name drugs are

included as are nonprescription and

prescription drugs. Along with all new

drugs, the physician also records

continued medications if the patient

was specifically instructed during the

visit to continue the medication.

Drug visit-A drug visit is a visit

in which medication was prescribed

or provided by the physician.

National Center for Health statistics

Director

Manning Feinleib, M.D., Dr. P.H.

Deputy Director

Jack R. Anderson

U.S. DEPARTMENT OF HEALTH AND

HUMAN SERVICES

Public Health Service

Centers for Disease Control and Prevention

National Center for Health Statistics

6525 Belcreat Road

Hyattsville, Maryland 20782

OFFICIAL BUSINESS

PENALTY FOR PRIVATE USE, $300

To receive this publication regularly, contact

the National Center for Health Statiqics by

calling 301-436-8500

DHHS Publication No. (PHS) 94-1250
Number 238 ● December 22, 1993

Advance

Data

From Vi and Health Statisticsof the CENTERS FOR DISEASE CONTROL AND PREVENTION/National Center for Health statistics

HumanlmmunodeficiencyVirus AntibodyTesting in Women

15+4 Years of Age: UnitedStates, 1990

by Jacqueline B. Wilson, M. P. H., Division of Vital Statistics

Highlights

In 1990, an estimated 20.4 million

women 154=4 years of age had been

tested at some time in their lives for

antibodies to human

immunodeficiency virus (HIV), the

virus that causes acquired

immunodeficiency syndrome (AIDS).

This includes 5.5 million women who

had donated blood since March 1985

but did not recognize that this

donation also involved a test for HIV

infection. Women 20-29 years of age

were most likely to have been tested,

as were formerly married women and

women with the most education.

Women with specific risk

characteristics were also more likely

to have been tested for HIV

infection: never-marned women who

had a positive history of sexually

transmitted diseases (STD’S), and

formerly and never-married women

with six or more sexual partners in

their lifetimes.

Most women reported that they

had been tested through the

American Red Cross or other blood

bank or by a doctor in a private

practice or a health maintenance

organization (HMO). Women who

reported that they were tested in

clinics were more often black and had

lower incomes than women tested at

other locations. A majority of women

reported that the test was done when

they saw a doctor for some reason

other than an HIV tes~ usually as

part of the blood donation process or

a medical examination. Testing for

antibodies to HIV infection among

women at risk for infection remains

an important part of the Centers for

Disease Control and Prevention’s

program to prevent the spread of

Hrv (l).

Introduction

The findings presented here are

from the National Survey of Family

Growth (NSFG) 1990 telephone

reintewiew, conducted by the

National Center for Health Statistics

(NCHS). This survey was not focused

exclusively on AIDS-related behavior

rather, it was designed to provide

data on a wide range of topics related

to childbearing, including pregnancies

and their outcomes, contraception,

infertility, use of medical services for

family planning, irrfertility and

prenatal care, and other selected

aspects of maternal and infant health.

Questions on AIDS-related behaviors,

including testing for HIV infectioz

were included in the 1990 interview

in response to requests for AIDSrelated information from other

agencies in the U.S. Public Health

Service.

The 1988 NSFG was based on a

national sample of 8,450 women

15-44 years of age. The women were

interviewed in person at home by

professional female interviewers

between January and August 1988.

This sample was obtained ftom

households participating in the

National HeaIth Interview Survey

(NHIS) between October 1985 and

March 1987. A complete description

of the 1988 survey methodology has

been provided elsewhere (2). The

tidings on AIDS-related knowledge

and behavior for 1988 were

summarized in a previous report (3).

Between July and November

1990, 5,686 women were interviewed

for the NSFG telephone reinterview.

The overall response rate was

67.5 percent. All interviews were

conducted by telephone; 5,359 were

reinterviews of women previously

interviewed in person in 1988. The

other 327 were first-time interviews

with women 15-17 years of age, who

had reached the age of 15 in the 2%

years since the 1988 interview.

The average length of interview

in 1990 was 20 minutes, compared

# Sl?.vrc*.ti

&

$

%

-g

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

F Public Health Service

~ Centers for Disease Controland Prevention %%.+-44 >*,xa

National Center for Health Statistics eENrERs

cm

FuR~ CONIROL

Am PREvENTum
2 Advance Data No. 238 ● December 22, 1993

with 70 minutes in 1988. In order to

minimize the interview time and

make room for additional questions,

the 1990 sample was split into two

“half-samples.” About 10 of the 20

minutes of the interview time was

devoted to questions that were asked

of all respondents. In the other 10

minutes of the interview time,

one-half of the sample (2,854

respondents, called “half-sample I”)

were asked detailed questions about

the use of contraception and familyplanning services. The other half of

the sample (2,832 respondents, called

“half-sample II”) were asked a series

of detailed questions related to HIV

and AIDS. However, women were not

asked about intravenous drug use or

types of sexual intercourse. ‘l%is

report includes analyses on halfsample II only (which includes 2,672

women who were reinterviewed and

160 young women from the teenager

supplement), because only these

respondents were asked questions on

HIV testing and other AIDS-related

behaviors. Further details on the

methodology of the telephone

reintewiew suwey are provided in the

Technical notes section of this report.

The nonresponse adjustments and

procedures for weighting the data for

the 1990 survey are described in

detail in a separate paper (4).

Data on HIV antibody testing are

also collected in the NHIS for men

and women 18 years of age and over.

Although the NHIS sample is

considerably larger than the NSFG

sample and the questions are worded

somewhat differently, NSFG data

offer an opportunity to see how some

characteristics not covered in the

NHIS are associated with HIV

testing. These include data on history

of STD’S, lifetime number of sexual

partners, and age at first sexual

intercourse. A comparison of NHIS

and NSFG data on HIV testing

appears later in this report.

The data presented in this report

cover four areas related to HIV

testing:

● HIV testing by demographic

characteristics including age, race,

education, marital status, region of

.

.

●

residence (in 1988), and residence

in a metropolitan statistical area

(MSA) (in 1988)

Location of testing and reasons for

testing

Behaviors and conditions

associated with HIV testing-ever

having an STD, ever having pelvic

inflammatory disease (PID),

lifetime number of sexual partners,

and age at first sexual intercourse

Attitudes and perceptions,

including ever knowing someone

with HIV, perception of chances

of becoming infected with HIV,

and level of knowledge about

transmission of HIV or AIDS.

Data are shown by race and

Hispanic origin in the tables and

figures. This does not imply that

differences shown are racial or

genetic per se. Differences between

non-Hispanic white women on the

one hand and black women

(regardless of Hispanic origin) on the

other are often associated with the

lower income and educational levels

of minority women, their limited

access to health care and health

insurance, the neighborhoods in

which they live, and other factors.

The causes of these dmerences merit

further investigation in future

research; describing characteristics of

subgroups of the population can help

focus AIDS education and prevention

efforts more effectively.

Findings

Inthe NSFG 1990 telephone

reinterview, all women in half-sample

II were asked: “Have you ever had

your blood tested for infection with

the AIDS virus?” Table 1 shows the

percent tested for HIV infection by

selected demographic characteristics.

About 26 percent answered “yes” to

this question. Positive responses to

this question are labeled as “selfreported tests” in table 1.

Since March 1985, the U.S. blood

supply has been screened for HIV

infection (5). If a respondent did not

report that she had ever had her

blood tested for infection with the

AIDS virus, she was still counted as

having been tested if she answered

“yes” to the question: “Have you

donated blood since March 1985?”

Including tests done as part of the

blood donation process since 1985,

35 percent of women have been

tested for HIV infection (these tests

are included in table 1, the “all tests”

column). In the remainder of this

report, past experience with HIV

testing includes all women tested for

HIV infection, including those who

did not report ever having been

tested but who had donated blood

since 1985. A description of the

reasons for including blood donors in

the total count of women receiving

HIV antibody testing is includecl in

the Technical notes section of this

report.

Non-Hispanicwhite women were

slightly but not significantlymore likely

to have been tested for HIV infkdon

than any other group of women

(36percen4 versus 30 percent for

Hispanic women and 35 percent for

non-Hisptic black women). These

results are sirnih to demographic data

on HIV testing from the NHIS (6).

Women with 13 or more yem of

educationwere signiikantly more likely

to have been tested than women with

less education (40 percent versus

31 percent).Published data from the

NHIS also show that persons with more

education are more likely to be teated for

HIV infectiorLhowever,these data are

not shown separately for women (6).

Formerly married women were

more likely than women of any other

marital status to have been tested for

HIV infection. This may be because

formerly married women were more

likely to have been sexually active for

a longer period of time and to have

had more sexual partners.

Women 20-29 years of age were

also more likely to report testing for

HIV infection, and the largest

proportions tested were for women

20-39 years of age. This is important

because two-thirds of female A[DS

patients are women 20-39 years of

age (63 percent are non-Hispanic

white women 20-39 years of age, and

66 percent are non-Hispanic black

women 20-39 years of age) (7).

In shorn demographic

characteristics are not highly
Advance Data No. 238 ● December22, 1993 3

Table 1. Numbar of women 1!5-44 years of age and percent ever teated for human

Immunodeficlency virus infeetlon, by source of test information and seleeted demographic

charaeterktiw United States, 1990

Percent ever fesfa7

Number of

womenin Self-repotied

(Yr8racteristic thousands test9’ .41 tes&

Allwomen3 . . . . . . . . . . . . . . . . . . . . 56,3s1 25.6 34.9

Race and ethnic origin

Hispanic . . . . . . . . . . . . . . . . . . . . . . 5,647 23.8 2S.8

Black, not H~panic . . . . . . . . . . . . . . . 7,526 28.5 34.8

Whiie, nct Hispanic . . . . . . . . . . . . . . . 42,636 25.4 35.8

Lessthan 12years . . . . . . . . . . . . . . . 5,618 24.6 31.0

12years, . . . . . . . . . . . . . . . . . . . . . 17,247 23.1 31.3

13years ormore . . . . . . . . . . . . . . . . . 27,033 28.6 39.9

Marital statue

Never marnsd . . . . . . . . . . . . . . . . . . . 20,123 26.0 35.7

Married . . . . . . . . . . . . . . . . . . . . . . . 31,417 23.6 32.5

Formerly married . . . . . . . . . . . . . . . . . 6,641 33.5 43.4

Age

15-19 yaars . . . . . . . . . . . . . . . . . . . . 8,4S3 21.5 28.7

20-24 yesra . . . . . . . . . . . . . . . . . . . . 9,154 27.0 40.8

25-29 years . . . . . . . . . . . . . . . . . . . . 10,s37 33.4 40.9

30-34 yasrs . . . . . . . . . . . . . . . . . . . . 11,091 27.5 37.1

35-39 years . . . . . . . . . . . . . . . . . . . . 10,111 22.0 31.5

4044yaars . . . . . . . . . . . . . . . . . . . . 8,S05 20.3 28.5

Residence in rnatfcpoliin areas

MSAjeentral city . . . . . . . . . . . . . . . . . 12,727 31.9 39.9

MSAjcther . . . . . . . . . . . . . . . . . . . . 28,961 26.1 3s.4

Non-MSA . . . . . . . . . . . . . . . . . . . . . 11,979 21.4 32.4

Regions

Northeast . . . . . . . . . . . . . . . . . . . . . 11,226 28.2 36.9

South . . . . . . . . . . . . . . . . . . . . . . . . 18,603 28.0 39.5

Midwest . . . . . . . . . . . . . . . . . . . . . . 14,453 23.8 34.0

West . . . . . . . . . . . . . . . . . . . . . . . . 10,405 25.4 33.5

Poverty-lavelincomes

0-149parcent . . . . . . . . . . . . . . . . . . 7,918 28.1 35.5

lEOparcentormore . . . . . . . . . . . . . . 41,960 25.9 36.0

%cludssoniytaste repatedinresponee tothequsstiem ’’Haveyousvwhadyeur b!ocdteetedforinfec+icnwiththsAfDS

virus?”

%eteJcwyimludssalltests tiHIVinfecMrr,inciud~ thoeadorwincormwticn withbboddometkm.

%cludes”ottrar’’races andwornenwtmssHIV testirrgetetuswaeun- noslwwnsaperafelybecauss ofsrnsllsample

eise.

%Vcrnsn20-44ysareof ageonly.

%lriivariablewasmllacted duringttre19S8survsy.

%iaticoftotalfferily lmxmetopowty level.Wornen20-44 yearscfa~only.

NOlESM6Aism@rcpolhn ststie+kalares.AIDS isacquiredimmuncdeiiciencysyrslrome.HIVislwman innnurmdelkiancy

tiNS.

associated with HIV testing.

However, the groups most likely to be

tested are the college-educated, the

formerIy married, women 20-29 yeara

of age, and women from a central city

of an MSA.

Location of testing

Women who indicated that they

had been tested for HIV infection

were asked “Where did you go to

have that test done?” More than

one-half (55 percent) of the tests

were done through the American Red

Cross or other blood bank (table 2).

Other, less common sources included

private doctors (20 percent), clinics

(14 percent), hospitals or emergency

rooms (12 percent), health

departments (10 percent), and other

locations (5 percent) (figure 1).

(Women could report more than one

location, if applicable.) In this repo~

testing at community and public

health departments was counted

separately from testing at other types

of clinics because health departments

provide partner notification and other

services related to testing for HIV

infection that some other cliniee do

not (8).

Among non-Hispanic

respondents, black women were 21%

times as likely as white women to

report having been tested at clinics

(27 percent versus 11 pereent,

table 2). Conversely, black women

were less likely than white women to

have been tested at the Red Cross

(34 percent compared with

60 percent, respectively). There were

no clear patterns of difference by age

in the sources of tests, but teenagers

had higher levels of testing at health

departments (21 percent for women

15-19 yeara of age) than did women

of other ages. (See table 2.)

Women who did not finish high

school were much more likely

(28 percent) to have been tested at a

hospital or emergency room than

were women with 12 years of

education (11 percent) and 13 or

more years of edueation (10 percent),

and much less likely to be tested at

the Red Cross (30 percen~ versus 52

and 62 percen~ respectively).

Income appeared to play an

important role in the location of HIV

testing: Lower income women were

more likely than higher income

women to have received testing at a

cliniq hospital or emergency room, or

health departmen~ and much less

likely to have received testing through

the Red Cross or other blood bank.

For example, 37 percent of tested

Iow-income women received their

tests at the Red Cross or other blood

banka, compared with 59 percent of

higher income women. There was no

difference by income in the percent

tested at private doctors’ offices.

In summary, women with less

education and income were more

likely to get their HIV tests at clinks,

hospitals, or emergency rooms, and

leas likely to be tested at the Red

Cross or other blood bank than were
4 Advance Data No. 238 ● December 22, 1993

Table 2. Number of women 1S44 years of age ever tested for human immunodeficiency virus infection and percent tested at spocifiad

locations, by selected demographic characteristic= United States, 1990

Location of test

Number of Hospital or Red Cross

women in emergency Private or other Health

Characteristic thousands Clinic’ room doctor% office blood bank depsrbrrent 2 Other3

Ailwomen4 . . . . . . . . . . . .

Race and ethnic origin

Hispanic . . . . . . . . . . . . . .

Black, not Hispanic . . . . . . .

Whtie, not Hispanic . . . . . .

Educations

Leeathan12yeare . . . . .

12years . . . . . . . . . . . . . .

13yeare ormore . . . . . . . . .

Marital etatus

Married . . . . . . . . . . . . . . .

Formerly married. . . . . . . . .

Never married . . . . . . . . . . .

Age

15-19 years . . . . . . . . . . . .

20-24 years . . . . . . . . . . . .

25-29 yeara . . . . . . . . . . . .

30-34 yeara . . . . . . . . . . . .

35-39 years . . . . . . . . . . . .

40-44 yeare . . . . . . . . . . . .

Residences

MSA, central city . . . . . . . . .

MSA, other . . . . . . . . . . . .

NoIFMSA . . . . . . . . . . . . .

Regions

Northeast . . . . . . . . . . . . .

South . . . . . . . . . . . . . . . .

Midwest . . . . . . . . . . . . . .

West . . . . . . . . . . . . . . . .

Poverty-lavel income’

O-149 percent . . . . . . . . . .

150percentormore . . . . . .

20,363

1,653

2,619

15,348

1,743

5,399

10,784

10,209

2,967

7,187

2,437

3,735

4,347

4,120

3,184

2,539

5,083

10,917

3,883

4,140

7,352

4,910

3,461

2,811

15,115

13.6

*13.2

26.5

10.8

21.2

14.5

12.4

12.0

17.5

14.2

*1 0.7

17.1

14.1

12.2

15.4

%.8

19.1

11.6

11.2

14.7

12.6

12.6

14.9

23.7

12.1

12.1 19.5 54.7 9.7 4.7

W.8

*1.4

5.5

*1.2

●4.O

6.5

6.3

*5.5

*1.9

——-

%2.6

%.9

7.7

8.9

%2

5.8

5.0

%2.8

%.5

6.1

%?.2

%3.6

*I .7

6.0

17.9

17.9

6.5

*11.8

15.0

11.7

29.0

19.8

19.4

50.0

34.4

59.8

27.9

10.9

10.4

18.8

23.9

17.6

29.6

52.2

81.5

*6.9

8.8

8.0

12.7

11.9

11.4

19.9

19.4

18.9

5s.1

50.3

61.5

7.5

10.0

12.6

20.7

9.9

11.5

10.6

*4.O

*1.0

11.4

T.o

15.0

8.9

15.6

16.6

16.5

22.5

23.1

17.7

13.5

20.2

47.7

53.9

51.5

55.9

58.7

60.7

10.1

11.6

13.6

19.3

19.1

21.6

45.9

60.7

55.4

13.9

6.3

10.4

16.5

23.1

18.7

17.6

53.4

57.1

56.5

55.3

*4.6

10.4

6.9

14.7

15.5

8.0

16.0

8.6

37.4

59.0

18.3

11.1

19.2

19.7

13.2

7.3

1Includes acquirad immurmdeficiency syndrome (AIDS)clinic,hosp”~l clinic, company clinic, and other types of clinics.

21ncludes community health department end public haaith deparbnent.

31ncludas ta$ting by an insuranse mmpeny, et school IX work, end teeting somewhere not mentioned in previous categories.

%otal includes “ether” races not shown aepareteiy because of small sample size.

%men 20-44 years of age oniy.

%s variable was collected only in tlw 198S survey.

7Ratio of total family Income to poverty level. Woman 2044 years of age only.

NOTE MSAis metrefxdii statisticalarea

women with higher education or

income.

then asked: “Did you have the test

done as part of a routine medical

examination, as part of a familyplanning visit, aa part of the

procedure when you donate blood, or

as part of some other kind of visit?”

Aa table 3 shows, only 16 percent

of ever-tested women reported testing

as the sole reason for such a visit. By

far, the most common occasion for an

HIV test was during blood donation

(55 percent). About 1 in 4 tested

women received the test as part of a

routine medical examination

(23 percent). Only 5 percent of

women ever tested had their tests

done during family-planning visits.

Non-Hispanic black women were

much more likely to receive an HIV

test as part of a medical examimtion

than were non-Hispanic white women

(36 percent versus 20 percent) and

much less likely than non-Hispatic

white women to have been testeld

Reasons for testing

Ir 1990, women who reported

testing for HIV infection were asked:

“When you went to (place where you

were tested) to have the AIDS test

done that time, was that your only

reason for going?” If that was not the

only reason for the visit, they were
Advance Data No. 238 ● December 22, 1993 5

70 r

So

sot

I

20 20 ,9

■ Ailvwrnen @ Blackworrm ❑ Whitevmrnen

so

as m

18

ti

Clinio Ho8pitai Prkte docbr Mica Rsdcrosssits HsaRhde@ment Oaler

Figure 1. Location of testing for acquired Immunodeflciency virus infection for women 15-44 years of age, by percent tested at specified

locations: United States, 1990

because they donated blood

(35 percent versus 60 percent). The

greater proportion of non-Hispanic

white women reporting testing as part

of a blood donation is the result of

the fact that these women were more

likely to report having donated blood

than were other women.

Women who did not finish high

schooI were much more likely to have

been tested as part of a medical

examination than were women with

more education (34 percent versus

20 percent for women with some

college education) and much less

likely than those with some college

education to report testing as part of

a blood donation (31 percent versus

62 percent for women with some

college education); however, the

sample of women who did not finish

high school is small.

Younger women, especially

teenagers, were more likely to be

tested at a family-planning visit than

were older women (11 percent for

women 15-19 years old versus

1 percent for women 35-39 years old),

ahhough the sampling errors for

these percents are relatively large.

Income also seemed to have some

association with the reason for HIV

testing. Women with lower incomes

were more likely to report that the

HIV test was the only reason for the

visit than were higher income women

(26 percent versus 16percent) and

much less likely to have received the

test because they donated blood

(38 percent versus 59 percent).

In summary, black women and

less-educated women were more

likely to receive their HIV test as part

of a medical examination, and less

Iikely to receive it as part of a b~ood

donation, than were white women

and those with more education.

Low-income women were more likely

than others to report that the HIV

test was the only reason for the visit.

Risk characteristics for

infection

Histog of STD or PID is a risk

factor for HIV infection (9). The data

in table 4 suggest that formerly

married women who had a positive

STD histo~ (ever had an STD) were

much more likely to have been tested

for HIV infection than were formerly

married women who had never had

an STD (54 percent versus

41 percent). This difference was ako

found for never-married

women - never-married women with a

history of STD were more likely

(50 percent) to be tested for HIV

than were never-married women with

no history of STD (34 percent).

However, there was no significant

difference for currently married

women. Although STD’Sare frequent

causes of PID, ever having had a PID

was not significantly associated with

having been tested among women of

any marital status (the difference for

never-marned women, 43 percent

versus 35 percent, was not

significant).

Number of sexwd partners in a

lifetime has rdso been associated with

increased risk of exposure to STD’S,

including HIV infection (10). In 1990,
6 Advance Data No. 238 ● December22, 1993

Table 3. Number of women 1S44 years of age ever tested for human Immunodeficiency virus Infection (all teats, Including those for

blood donation) and percent with speclfled reasons or circumstances for the test by selected demographic characteristics:

United States, 1990

Other reasons for test

Numbar

of wornen Test only Family

reason for Medical

tfrou~nds

planning Blood Other

Characteristic vkit’ examination visit donation visit 2

Allwomens . . . . . . . . . . . . . . . 20,363 16.1 22.9 4.7 55.0 12.7

Race and ethnic origin

Hispanic . . . . . . . . . . . . . . . . .

Black, not Hispanic . . . . . . . . . .

White, notliispani c . . . . . . . . .

1,653

2,619

15,346

26.2

21.2

13.3

25.6

36.5

20.1

%.3

*4.6

5.0

50.4

34.5

60.1

*1 2.7

14.3

11.9

Education4

*1 4.9

17.0

9.2

Lessthan12years . . . . . . . . . .

12years . . . . . . . . . . . . . . . . .

13years ormore . . . . . . . . . . . .

1,743

5,3es

10,764

19.1

13.8

18.4

33.8

24.9

19.6

%1

5.1

3.3

30.8

51.5

62.1

Marital status

Married . . . . . . . . . . . . . . . . . .

Formerly marriad. . . . . . . . . . . .

Never marriad . . . . . . . . . . . . . .

10,209

2,967

7,187

14.2

20.2

16.2

21.5

20.7

25.7

4.7

w.?

6.3

58.1

50.8

52.3

14.4

14.1

9.8

Age

46.4

54.2

51.4

55.9

60.0

60.9

17.6

9.0

13.6

15.1

9.7

12.1

15-19 years . . . . . . . . . . . . . . .

20-24 years . . . . . . . . . . . . . . .

2E-29years . . . . . . . . . . . . . . .

30-34 years . . . . . . . . . . . . . . .

35-39 years . . . . . . . . . . . . . . .

4044years . . . . . . . . . . . . . . .

2,4S7

3,735

4,347

4,120

3,164

2,539

*6.5

16.2

19.3

17.9

16.6

12.6

24.6

23.2

26.2

18.1

23.4

22.1

*1 0.7

*6.3

7.7

*1.8

*1.3

Residence 5

MSA, central city . . . . . . . . . . . .

MSA, other . . . . . . . . . . . . . . .

Non-MSA . . . . . . . . . . . . . . . .

5,063

10,917

3,8S3

26.3

12.2

14.5

25.4

19.6

26.4

X3.6

4.5

*4.6

45.3

61.5

55.4

11.4

13.4

11.0

Region6

23.1

25.7

19.5

16.7

%2.5

4.4

6.6

%3.2

53.1

57.4

57.5

55.3

10.8

9.6

14.3

17.7

Northeast . . . . . . . . . . . . . . . .

South . . . . . . . . . . . . . . . . . . .

Midwest . . . . . . . . . . . . . . . . .

West . . . . . . . . . . . . . . . . . . .

4,140

7,352

4,910

3,481

19.6

15.7

11.8

18.5

Poverty-level inoomeE

15.5

11.5

O-149 percent . . . . . . . . . . . . .

150percentormore . . . . . . . . .

2,811

15,115

25.5

15.5

27.2

21.8

*6.O

3.4

37.6

59.3

‘Includes a visil to any bafion wherethe HIV teS was the onlyreasonforths visii.

‘Includesre=ns suchas pregnancyvi.s”ks, marriagerequirement,illnessesOMWthan AIDS, and other reasons.

%otsl includes “othef’ races not shown sapsrately besause of small sample size.

%3men 20-44 years of age only.

%s variable was collected only in the 1SSS a.rvay.

‘Ratio oftotalfamilyincome to poverty level. Woman 20-44 yeacs of a~ only.

NOTES HIV Is human immunodefiuensy virus infection. AIDS is acquired immuncdmiciancy syndrome.

plausible finding, because there are

nonsexual reasons for HIV testing

(for example, immigration, insurance,

blood donation).

In summary, unmarried women

(that is, formerly married and

never-manied women) with positive

STD histories and six or more male

sexual partners in a lifetime we]refar

more likely to have been tested for

HIV infection than were unmarried

women without STD’S and those with

formerly manied women who had

each had six or more male sexual

partners were far more likely to

report HIV testing than formerly

married women with only one partner

in a lifetime (47 percent for women

with six or more partners, versus

12 percent for women with one

lifetime male sexual partner)

(table 4). This pattern also held true

for never-married and currently

married women.

Women who begin sexual

intercourse at a young age are also

considered at increased risk for

exposure to STD’S, including HIV

infection. There was no significant

difference in the proportions of

never-married women receiving

testing regardless of their age at first

intercourse. Nearly one-lifth of

women who had never had

intercourse (17 percent) had been

tested for HIV infection. This is a
Advance Data No. 238 ● December 22, 1993 7

Table 4. Number and percent of women 15-44 years of age ever tested for human immunodeflciency virus infeetion by marital status and

selaeted risk factors: United States, 1980

Curentiy Formerly Never Currentiy Formerly Never

Risk I%cior Total mm”ed M“krd M“ed mwried Inarrr”ed mm-al

Numberin thousasda Percent

Allwomen’ . . . . . . . . . . . . . . . . . . . . . . 20,363 10,209 2,987 7,187 32.5 43.4 35.7

Ever had a sexually transmitted disesaez

Yes. . . . . . . . . . . . . . . . . . . . . . . . . . .

No . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Ever had pelvic inflammatory disease

Yes . . . . . . . . . . . . . . . . . . . . . . . . . . .

No . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Number of lifetime male sexual partners

Never hadinteroourse . . . . . . . . . . . . . . .

Imsn . . . . . . . . . . . . . . . . . . . . . . . . . .

2+ men . . . . . . . . . . . . . . . . . . . . . . . .

6ormoremen . . . . . . . . . . . . . . . . . . . .

Age atfirstinteroourae

Neverhadintermurse . . . . . . . . . . . . . . .

Under15years . . . . . . . . . . . . . . . . . . . .

16-17yesrs . . . . . . . . . . . . . . . . . . . . . .

18-19yaara . . . . . . . . . . . . . . . . . . . . . .

200rmoreyears . . . . . . . . . . . . . . . . . . .

2,670 1,039 652 978

17,693 9,169 2,315 6,209

2,673 1,326 58U 757

17,680 8,883 2,377 6,430

871 --- --- 871

3,919 2,963 36 829

8,959 4,289 1,457 3,203

6,615 2,967 1,474 2,I a4

871 --- --- 871

1,853 781 320 756

8,381 3,828 1,224 3,328

5,550 3,025 1,189 1,336

3,703 2,573 234 698

34.7 54.1 49.5

323 41.1 242

30.0 36.6 43.3

32.9 45.5 35.0

--- --- *I 7.4

29.7 12.2 33.7

30.9 42.9 41.5

39.1 46.9 47.2

--- --- *I 7.4

39.1 40.7 35.7

33.0 39.4 42.7

31.7 52.5 43.4

31.1 34.5 41.9

‘Includsswcmenwithmiseiidats onrowvedablee.

2Awomanisidentified S.?l?avinglwdasexually trsmsrnitkeddisasee ifshelmdkstsdthat slwhadevwhd cmaormweofthe follcwingg@IsIwmts, gmxhea,chlarnyd~ orgdtslhaqMs

one partner. Differences were

smaller, but in the ssrne direction for

married women.

HIV knowledge and attitudes

The items on knowledge of HIV

in the 1990 survey included a series

of questions that asked

What would you say are the ways

in which a person can get the

AIDS virus? Would you say that

a person em get the AIDS virus

by:

A.

B.

c.

D.

E.

F.

G.

H.

I.

J.

Shaking hands or hugging?

Shsring hypodermic needles?

Sharing an apartment,

classroom, or office?

Receiving a blood

transfusion?

Sexual intercourse between

men?

Sexual intercourse between a

man and a woman?

Giving a blood donation?

Being bitten by an insect that

had bitten someone with the

ADSvirus?

Sharing personal items like

dishes or toilets?

Being born to a mother with

AIDs?

K Swimrnin gin a pool in which

someone with AIDS has also

been swimmin @

L. Kissing with exchange of

saliva?

Each item was answered “yes” or

“no.”

Auother question was: “Can a

person get AIDS from someone who

has only the AIDS virus but does not

have the disease?” Women who

indicated a high level of knowledge

on these questions (see the Technieal

notes for swring of the knowledge

items) were more likely (37 pereent)

to have been tested for HIV infeetion

than were women who had a medium

(33 percent) or low level of

knowledge (26 pereent) (fiWre 2).

In 1990, women were also asked:

What would you say are the

chances that you yourself could

get AIDS? Would you say you

have:

A. A very strong chance?

B. A strong chance?

C. Some chance?

D. Not much chance?

E. No chance at all?

Women who said they had some

chsnee or more of beeoming infected

with HfV were slightly but not

significantly more likely (38 pereent)

to report HIV testing than women

who said they had no chance of

beaming infected (36 percent)

(figure 2). However, the data suggest

that women who said they had some

chance or more of becoming infected

were more likely (38 percent) to have

received an HIV test than were

women who did not know their

chances of beeoming infected

(16 percent).

In 1990, women were also asked:

Have you ever personally known

anyone with AIDS or the AIDS

virus?

Women who said they Imew

someone with AIDS or the AIDS

virus were more likely (44 percent) to

report that they had been tested for

HIV infection than were those who

did not know anyone with the virus

(32 pereent) (figure 2).

Limitations of the data

Although previous research has

shown that HIV-testing information
$?“ .Advanm . . . . . ..- .

13ata . . . Nn- . . . . --- 238 ● ---------- December --,22.1 ----Q93

40

30

20

10

0

AIOS k

37

3s

2s

High Medium Low sum Notmuch Nona

16

I

Unknown

33

we NoKnowledge level Chancse ofinfactkm KnowsomeonewithAIDS

Figure 2. Level of knowledge of acquired immunodeficiency syndrome, chances of Infection with human Immunodeficiency virus,, and

knowing someone with acquired Immunodeficlency syndrome, In women 15-44 years of age, by percent tested for human

immunodeficlency virus infection United States, 1990

can be accurately reported by patients

who have been tested (11), these data

should be interpreted with caution.

Some of the HIV-testing rates in this

report are somewhat higher than

those found in the 1990 NHIS, which

are the most similar data to the

NSFG that are available for

comparison. This may be attributable

to a number of factors, including the

fact that the NSFG is a survey about

childbearing, sexual activity, and

reproductive health, and the NHIS is

a general health survey. In addition,

the HIV-testing questions are not

identical on the two surveys. A

methodological study is under way

comparing the NSFG with the NHIS

data to examine the differences in

reported HIV antibody testing.

One methodologic difference

between the NSFG and the NHIS is

that, in 1990, the NHIS asked a series

of questions about blood donation

and HIV testing that began with the

lead-in question: “Have you ever

heard of a blood test than can detect

the AIDS virus infection?” People

who responded “yes” to this question

were then asked a series of questions

on blood donation and were then

asked: “Except for blood donations

since March 1985, have you had your

blood tested for the AIDS virus

infection?” People who responded

that they had never heard of a test to

detect the AIDS virus were skipped

out of the entire series of questions

on HIV testing.

The initial comparison of these

NHIS data with the 1990 NSFG data

showed some significant differences

between rates of HIV testing

reported in the surveys. Women in

the NSFG reported testing at higher

rates than women in the NHIS, and

this difference was especially

apparent for non-Hispanic black

women in the two surveys. However,

this lead-in question in the NHIS was

dropped in 1991, so that all

respondents in the NHIS were asked:

“Except for blood donations since

March 1985, have you had your blood

tested for the AIDS virus infection?”

Because all respondents were asked

about having been tested for HIV

infection, overall reporting of HIV

testing in the NHIS increased. When

1991 NHIS testing data were

compared with the 1990 NSFG data,

the dfierences in the rates of

self-reported testing were smaller and

were virtually identical when all tests

(including blood donation) were

considered. Further analyses are

being conducted to account for

whatever differences remain. The

entire series of questions from the

1990 and 1991 NHIS surveys are

included in the Technical notes

section of this report.

One important distinction that

cannot be made from the NSFG data

is the difference between voluntary

and nonvoluntary tests for HIV

infection. It is unclear to what extent

self-reported tests were specifically

requested by the respondents or were

done as part of routine screening.

Questions to clarify who requested

the test and why would be useful

additions to future surveys.

Because the 1990 NSFG

reinterview did not ask about recent

HIV testing (for example, in the past

year), it is not possible to connect

HIV testing with other risk behaviors,

such as current condom use, that are

considered important in evaluating

the risk of acquiring HIV infe{:tion.

However, lifetime behaviors such as

ever having had an STD or PID and

lifetime number of sexual partners

can be evaluated in relationship to

HIV testing.
Advance Data No. 238

● December22, 1993

9

References 10. Seidman SN, Mosher WD, Arid

1.

2.

3.

4.

5.

6.

7.

8.

9.

Public Health Service. Healthy

People 2000 National Health

Promotion and Disease Prevention

Objectives. Washington, D.C.: U.S.

Department of Health and Human

Services. 1990.

Judkins D~ Mosher WD, Botman

S. National Survey of Family

Growth: Design, estimation, and

inference. National Center for

Health Statistics. Vital Health Stat

qlo9). 1991.

McNally JW, Mosher WD.

AIDS-related knowledge and

behavior among women 15-44

years of age United States, 1988.

Advance data from vital and

health statistiw, no 200.

Hyattsville, Maryland National

Center for Health Statistics. 1991.

Goksel H, Judkins DR, Mosher

WD. Nonresponse adjustments for a teIephone follow-up to a national

in-person survey. Im 1991

proceedings of the American

Statistical Association, Section on

Survey Research Methods, pp.

581-6.1992.

Centers for Disease Control and

Prevention. Provisional Public

Health Service inter-agency

recommendations for screening

donated blood and pIasma for

antibody to the virus causing

acquired immune deficiency

syndrome. MMWR 34(1}1-5.

1985.

Anderson J& Hardy AM, Cahill & Aral SO. HIV antibody testing

and post-test counseling in the

United States: Data from the 1989

National Herdth Interview Survey.

AJPH 82(11)1533-5. 1992.

Centers for Disease Control and

Prevention. HIV/AIDS

Surveillance Report. Atlanta, GA.

Year-end edition, p. 14, table 8.

1992.

Centers for Disease Control and

Prevention. Recommendations for

HIV testing services for inpatients

and outpatients in acute-care

hospital settings and technkal

guidance on HIV counseling.

MMWR 42(RR-2). 1993.

Hoegsberg B, Feldman J, Minkoff

H. Sexually transmitted diseases

and human immunodeficiency virus

infection among women with pelvic

inflammatory disease. AmJ Obstet

Gynecol 163(4):1135-9. 1990.

SO. Women with multiple sexual

partners. AJFH 82(10)1388-94.

1992.

11. McCusker J, StoddardM

McCarthy E. The validity of

self-reported HIV antibody test

results. AJPH 82(4)567-9. 1992.

12. U.S. Bureau of the Census.

Poverty in the United States, 1988

and 1989. Current Population

Reports, series P-60, no 163.1991.

Symbols

--- Data not available . . . Category not applicable

Quantity zero

0.0 Quantity more than zero but less

than 0.05

z Quantity more than zero but less

than 500 where numbers are

rounded to thousands

* Figure does not meet standard of

reliabilii or precision
10 Advance Data No. 238 ● December 22, 1993

Technical notes

Survey design

The National Survey of Family

Growth (NSFG) is a periodic survey

conducted by the National Center for

Health Statistics (NCHS) to collect

data on fertility, infertility,

contraception, and related aspects of

maternal and infant health. Fieldwork

for Cycle IV was conducted in 1988,

and the NSFG telephone reinterview

was conducted in 1990. The

contractor for the 1988 and 1990

surveys was Westat, Inc., of Rockville,

Maryland.

For the 1988 NSFG, personal

(face-to-face) interviews were

conducted between January and

August 1988 with a national sample

of women who were 15-44 years of

age as of March 15, 1988. Interviews

were completed with 8,450 women in

1988, including 2,771 black women,

5,354 white women, and 325 women

of other races. The sample for the

1988 NSFG was selected from

households that had participated in

the National Health Interview Survey

(NHIS)--also conducted by NCHSbetween October 1985 and March

1987. Respondents were interviewed

by trained female interviewers.

The interviews covered the

women’s pre~ancy history; past and

current use of contraception; ability

to bear childrew use of medical

services for contraception, infertility,

and prenatal care; marriage and

cohabitation, and a wide range of

social, economic, and demographic

characteristics. More detailed

information on the procedures used

in selecting the sample, weighting the

data to make national estimates, and

estimating sampling errors may be

found in two other publications (2,4).

For the 1990 NSFG telephone

reinteNiew, 5,686 women were

interviewed by telephone between

July 23 and November 5, 1990.

Reinterviews were conducted with

5,359 women who had been

interviewed in 1988, and tirst-time

telephone interviews were conducted

with 327 young women who had

reached 15 years of age in the 2 years

since the main study. The response

rate for the initial interviews with

those 15–17 years of age was

53 percent. The response rate for the

174-4-year-old women initially

interviewed in 1988 was 69 percent of

those originally interviewed in 1988.

Overall, the response rate was

67.5 percent. The most common

causes of nonresponse in 1990 were

inability to locate or contact the

respondent because she had moved

and inability to contact the

respondent because she had no

telephone or had an unpublished

telephone number. The 1990

reinterviews lasted an average of 20

minutes.

The 1990 sample was divided

equally into two “half-samples,” as

discussed in the text. This report is

based entirely on the results of

half-sample II, which contained the

most detailed questions on AIDSrelated behavior and HIV testing.

The data have been weighted to be

representative of the civilian

noninstitutionalized population of the

United States. However, the use of

the half-samples means that sampling

errors are larger than in the previous

reports based on the 1988 survey (4).

In this report, women 15–19 years

of age are excluded from tabulations

by education because it generally

takes until about age 19 to reach the

‘’13 years or more” education

category. This age group is also

excluded from tabulations by income

because it is generally difficult for

teenagers to accurately report the

income of their parents and because

income information was not collected

from 15–17-year-old women in the

1990 telephone reinterview teenager

supplement.

Reliability of estimates

Because the statistics presented

in this report are based on a sample,

they may differ from the statistics that

would result if all 58 million women

represented by the survey had been

interviewed. The standard error of an

estimate is a measure of such

differences. The standard error of an

estimated number or percent is

Table L Estimates of the parameter’sA and

B for estimating standard errors for

percents of women, by race: 1990 ?iiatlonal

Survey of Family Growth telephone

reinterview, half-sample

Psrarrreter

Race A B

Allraces . . . . . . . . . . . . .00042S4 25,000

White or other. . . . . . . . . -.0004947 25,000

Black . . . . . . . . . . . . . . -.0018417 14,450

calculated by substituting the

appropriate values of A and B from

table I in the following equations:

SE(N) = ~

and

i

BoP (1OO-P)

SE(P)=

x

where N =number of women

P =percent

X =number of women in the

denominator of the

percent

The parameters shown in table I

were used to generate table II

(estimates of standard errors for

percents of women of all races),

table HI (standard errors for white

women), and table IV (estimates of

standard errors for black women).

The chances are about 68 in 100

that a sample estimate would fall

within one standard error, and about

95 in 100 that it would fall within two

standard errors, of a statistic based

on a complete count of the

population represented by the NSFG.

Unless otherwise speciiied,

differences between percents

discussed in this report were found to

be statistically significant at the 0.05

level using a two-tailed normal

deviate test (z-test). This means that

in repeated samples of the same type

and size, a dtierence between the

percents in the population as large as

the one observed would occur in only

5 percent of the samples if there

were, in fact, no difference. The

phrase “the data suggest” indicates

that the dMerence was significant at

the 0.10 (lO-percent) level but not the
Advance Data No. 238 ● December 22, 1993 11

Table IL Standard errors for percents of women of all races: 1990 National Survey of Family Growth telephone reinterview, half-sample

Estimatadpercent

Bssa ofpercent 5 or 95 19 or 80 20 or 80 30 or 70 40 or 60 50

500,000 . . . . . . . . . . . . . . . . . *4.9 %.7 %.9 w 0.2 11.0 11.1

1,000,000 . . . . . . . . . . . . . . . . 3.4 *4.7 %3 7.2 7.7 7.9

5,000,000 . . . . . . . . . . . . . . . . 1.5 2.1 2.8 3.2 3.5 3.5

Io,ooo,ooo . . . . . . . . . . . . . . . . 1.0 1.5 2.0 2.3 2.4 2.5

30,000,000 . . . . . . . . . . . . . . . . 0.6 0.9 1.1 1.3 1.4 1.4

50,000,000 . . . . . . . . . . . . . . . . 0.5 0.7 0.9 1.0 1.0 1.1

Table Ill. Standard errors for percents of white women: 1990 National Survey of Family Growth telephone reinterview, half-sample

Estimatedpercent

Base ofpercent 5 or 95 19 or 80 20 or 80 30 or 70 40 or 60 50

500,000 . . . . . . . . . . . . . . . . . *4.9 %7 %.9 tio.2 11.0 11.2

1,000)000 . . . . . . . . . . . . . . . . 3.4 *4.7 %.3 7.2 7.7 7.9

5,000,000 . . . . . . . . . . . . . . . . 1.5 2.1 2.8 3.2 3.5 3.5

10, 000,000 . . . . . . . . . . . . . . . . 1.0 1.5 2.0 2.3 2.4 2.5

20,000,000 . . . . . . . . . . . . . . . . 0.8 1.1 1.4 1.6 1.7 1.8

40,000,000 . . . . . . . . . . . . . . . . 0.5 0.8 1.0 1.1 1.2 1.3

Table fV. Standard errors for percents of black women: 1990 National Survey of Family Growth telephone reinterview, half-sample

Estimatedpercent

Base of percent 5 or 95 19 or 80 20 or 80 30 or 70 40 or 60 50

500,000 . . . . . . . . . . . . . . . . . 3.7 %.1 %.8 7.8 8.3 8.5

I,ooo,ooo . . . . . . . . . . . . . . . . %?.6 ?3.6 *4.8 5.5 5.9 6.0

2,000,000 . . . . . . . . . . . . . . . . *1.8 2.6 3.4 3.9 4.2 4.3

3,000,000 . . . . . . . . . . . . . . . . *1.5 2.1 28 3.2 3.4 3.5

4,000,000 . . . . . . . . . . . . . . . . 1.3 1.8 2.4 2.8 2.9 3.0

7,000,000 . . . . . . . . . . . . . . . . 1.0 1.4 1.8 2.1 2.2 2.3

0.05 (5-percent) level. Lack of

comment in the text about any two

statistics does not mean that the

difference was tested and found not

to be significant.

The relative standard error (or

coefficient of variation) of a statistic

is the ratio of the standard error to

the statistic and is usually expressed

as a percent of the estimate. In this

report, percents and other statistics

with relative standard errors of

30 percent or larger are indicated

with an asterisk (*). These estimates

may be viewed as unreliable by

themselves, but they may be

combined with other estimates to

make comparisons of greater

precision.

Statistics in this report may also

be subject to nonsarnpling error, that

is, errors or omissions in responding

to the interview, recording answers,

and processing data. The data have

been adjusted for nonresponse and

adjusted to independent control totals

obtained from the U.S. Bureau of the

Census (4). These adjustments reduce

most types of nonsampling error.

Other types of nonsampling error

were eliminated by a series of quality

control procedures.

Definitions of terms

Race—Race refers to the race of

the woman interviewed. Each woman

was asked “Which of the (following)

groups best describes your racial

background?” The categories

included black white, Asian or Paciiic

Islander, and A.Iaskan Native or

American Indian. Because of the

small sample sizes, the last two

categories are combined and called

“other” in this report.

Hispanic origin—Each woman

asked “Which of the (following)

was

groups best describes your national

origin or ancestry?” Using a list of 15

groups, a woman was classified as

being of Hispanic origin if she

reported that her only or principal

national origin was Puerto Rican,

Cuban, Mexican American, Central

or South American, or other Spanish.

Origin is therefore classfied

independently of race, and Hispanic

women may be of any race.

Marital status-In this repo~

women were classified according to

their legal marital status. “Currently

married” means legally married at the

date of interview, “never married”

means never legally married as of the

date of interview, and “formerly

married” means widowed, divorced,

or separated. Cohabiting women who

are not legally married are therefore

classified in this report as unmarried,

Ever had sexual intercours+This

refers to a woman who has had sexual
12 Advance Data No. 238 ● December 22, 1993

intercourse at least once. Intercourse

before the first menstrual period is

excluded.

Number of lifetime sexual

p@ners-This refers to the number

of men with whom the woman has

had sexual intercourse in her life, as

of the date of the interview. In the

1990 data, this refers to the number

of men with whom she had had

intercourse as of the 1990 interview.

Pover@evel incomeThis is the

ratio of the total family income to the

poverty-level threshold for a family of

specified size, as published by the

U.S. Bureau of the Census. In the

1990 survey, 1989 Bureau of the

Census weighted average thresholds

for householders under the age of 65

years were used. The 1989 thresholds

used for 1990 data were $6,451 for

one person, $8,343 for a family of

two, $9,885 for a family of three,

$12,674 for a family of four, and up

to $25,480 for a family of nine or

more (12). Thus, if a family of four

had an income of $25,000, their

poverty-level income would be

$25,000 divided by $12,674, or

197 percent of the poverty level. In

the 1990 NSFG, family income

information was not collected from

the 327 women 15–17 years of age

who were interviewed for the first

time in 1990. In the tables of this

report, data are not shown for women

who did not report the income or

poverty level of their families and are

not shown for women under 20 years

of age.

Education—This refers to the

number of years of regular schooling

the woman had completed as of the

date of interview in 1990. In this

report, the following categories are

used: 0-11 years, meaning that the

woman did not complete high school;

12 years, meaning that she had

obtained a high school diploma or

general educational development

(GED) certificate but had not

completed a full year of college; and

13 years or more, meaning that she

had completed at least 1 year of

college. In all tables containing this

variable, women under the age of 20

are excluded from tabulations by

education because it generally takes

until at least age 19 to reach the ‘‘13

years or more” category.

Region of residence—Data are

classified by region of residence into

the four major census regions:

Northeast, Midwest, South, and West.

These regions, which correspond to

those used by the U.S. Bureau of the

Census, are as follows:

Regwn States included

Northeast Maine, Vermon4 New

Hampshire,

Massachusetts,

Connecticut, Rhode

Island, New York New

Jersey, and

Pennsylvania

Midwest Ohio, Illinois, Indiana,

Michigan, Wisconsin,

Minnesota, Iowa,

Missouri, North Dakota,

South Dakota,

Nebraska, and Kansas

South Delaware, Maryland,

District of Columbi~

West Virginia, Viiginia,

Kentucky, Tennessee,

North Carolina, South

Carolin~ Georgia,

Florida, Alabam%

Mississippi, Louisiana,

Oklahoma, Arkansas,

and Texas

west Montana, Idaho,

Wyoming, Colorado,

New Mexico, kizon~

Utah Nevad&

Washington, Oregon,

California, Hawaii, and

Alaska

Place of residence—Data are

classified by place of residence into

three categories, metropolitan

area-central city, metropolitan

area-other, and nonmetropolitan

area, using 1980 census counts.

Ever tested for HIV infection—

Women were asked the question

“Have you ever had your blood tested

for infection with the AIDS virus?” If

they responded “yes” to this item,

they were coded as having been

tested for HIV infection. In addition,

women who answered “no” to this

item but who responded “yes” to the

question: “Have you donated blood

since March 1985?” were also coded

as having been tested for HIV

infection because the U.S. blood

supply has been screened for

antibodies to HIV since March 1985

(5). Because women who donated

blood since March 1985 (but reported

no other I-W test) were not asked

questions on the Iocation or

circumstances of their test, they were

coded as having been tested at the

American Red Cross or other blood

bank and were coded as having had

the test as part of the blood donation

process for reasons or circumstances

of the test.

Knowledge of HIV/M.ZDS-This

measure was created by scoring each

correct answer on the knowledge

items with 1 point and each incorrect,

refused, or not-ascertained answer

with Opoints. These points were

totaled, the maximum being 13

points. A score of 12 or more Wiis

considered a high level of knowledge

on HIV/AIDS, a score of 9-11 points

was considered a medium leve~ and a

score of 8 or fewer points was

considered a low level of knowledge

on HIV/AIDS. The comect answlers

were:

What would you say are the ways

in which a person can get the

AIDS virus? Would you say that

a person can get the AIDS virus

by:

A. Shaking hands or hugging?

(no = 1 point)

B. Sharing hypodermic needles?

(yes = 1 point)

C. Sharing an apartment,

classroom, or office? (no = 1

point)

D. Receiving a blood

transfusion? (yes = 1 point)

E. Sexual intercourse between

men? (yes = 1 point)

F. Sexual intercourse between a

man and a woman? (yes = 1

point)

G. Giving a blood donatiornl?(no

4= 1 point)

H. Being bitten by an insect that

had bitten someone with the

AIDS virus? (no = 1 point)
Advance Data No. 238

● December 22, 1993 13

I. Sharing personal items like

dishes or toilets? (no=1 point)

J. Being born toa mother with

AIDS? (yes=1 point)

K Swimmin gina pool in which

someone with AIDS has also

been swimmin g? (no=1 point)

L. Kissing with exchange of

saliva? (no=1 point)

and

Cana person get AIDS from

someone who has only the AIDS

virus but does not have the

disease? (yes=1 point)

1990 NZMSquestions on HIV

testing— ●●●

✎

✎

Have you ever heard ofa blood

test that can detect the AIDS virus

infection?

To the best of your knowledge, are

blood donations routinely tested

for the AIDS virus infection?

Was one of your reasons for

donating blood because you

wanted to be tested for the AIDS

virus infection?

Except for blood donations since

March 1985, have you had your

blood tested for the AIDS virus

infection?

1991 NHIS questions on HW

testing— ● To the best of your knowledge, are

blood donations routinely tested

for the AIDS virus infection?

● Was one of your reasons for

donating blood because you

wanted to be tested for the AIDS

virus infection?

“ Except for blood donations since

March 1985, have you had your

blood tested for the AIDS virus

infection?
16 Advance Data No. 238 ● December 22, 1993

Suggested cltetion Copyright information

Wilson JB. Human immunodeficiency virus All material appearing in this report is in the

antibody testing in women 15-44 years of

age United States, 1990. Advance data from

public domain and may be reproduced or

vital and health statistics; no 238. Hyattsville,

copied without permission; citation as to

Maryland: National Center for Health Statistics.

source, however, is appreciated. This report

1993.

may be reprinted without further permission.

National Center for Health Statlatlcs

Director

Manning Feinleib, M. D., Dr. PH.

Deputy Dkector

Jack R. Anderson

U.S. DEPARTMENT OF HEALTH AND

HUMAN SERVICES

Public Health Service

Centers for Disease Control and Prevention

National Center for Health Statistics

6525 Belcrest Road

Hyattsville, Maryland 20782

OFFICIAL BUSINESS

PENALIY FOR PRIVATE USE, $300

To receive this publication regularly, contact

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PHWNCHS

PERMIT NO. G-281

DHHS Publication No. (PHS) 94-1250
Number 239 ● December 22, 1993

Advance

Data

From Vi and Health Stati~”esof the CENTERS FOR DISEASE CONTROL AND PREVENTION/National Center for Health StatiW”os

AIDS-Related Behavior Among Women 1544 Years of Age:

United States, 1988 and 1990

by William D. Mosher, Ph. D., and William F. Pratt, Ph. D., Division of Vital Statistics

In 1990, 10 percent of sexually

active women 15-44 years of age

(those who had intercourse in the last

month) were having intercourse with

partners who always used condoms,

either to prevent sexually transmitted

diseases (STD’S) or for contraception.

In 1990, about 6 percent of married

women and 16 percent of sexually

active unmarried women always used

condoms. Unmarried women with

more than one sexwd partner in the

last 3 months were also more likely

than those with one partner to use

condoms sometimes, but they were

not more likely to use condoms at

every recent act of intercoms

(always).

There was an increase from

14 percent in 1988 to 18 percent in

1990 in the proportion of sexually

experienced women who reported

changes in their sexual behavior to

avoid the human immunodeficiency

virus @IV), the virus that causes the

acquired immunodeficiency syndrome

(AIDS). Increases occurred in each

subgroup shown in this report. Most

of the increases were not statistically

significant, and none of the changes

for unmarried women were

signilkant. Thus, it appears that the

public health impact of these

reported changes was small.

These IWings are from the 1988

National Survey of Family Growth

(NSFG) and the 1990 NSFG

telephone reinterview, both

conducted by the National Center for

Health Statistics (NCHS). These

surveys were not focused exclusively

on AIDS-related behavior. Rather,

they were designed to provide a wide

range of data on topics related to

childbearing-including pregnancies

and their outcomes, contraception,

infertility, use of medical services for

family planning, prenatal care, and

other selected aspects of maternal

and infant health. Questions on

AIDS-related knowledge, behavior,

and condom use were included in the

1988 and 1990 interviews in response

to requests for AIDS-related

in.tormation from other agencies in

the United States Public Health

Service.

The 1988 NSFG was based on a

national sample of 8,450 women

15-44 years of age—2,771 black

women, 5,354 white women, and 325

women of other races. These women

were interviewed in person in their

own homes between January and

August 1988 by professional female

interviewers. The sample was

obtained from households that had

participated in the National Health

Interview Survey in the 18-month

period between October 1985 and

March 1987. The methodology of the

1988 survey is described in detail

elsewhere (1,2). The findings on

AIDS-related knowledge and

behavior for 1988 were summarized

in a previous report (3).

Between July and November

1990, 5,686 women were interviewed

for the NSFG telephone reinterview.

The overall response rate was

68 percent. All interviews in 1990

were conducted by telephone; 5,359

were reinterviews of women

previously interviewed in person in

1988. The other 327 were first-time

telephone interviews with women

15–17 yeara of age, who had turned

15 in the 2Y2years since the 1988

interview.

The average length of interview

in 1990 was only 20 minutes

compared with 70 minutes in 1988. In

order to save interview time and

make room for more questions, the

1990 telephone reinterview survey was

divided into two “half-samples.”

About 10 of the 20 minutes of

interview time was devoted to

questions that were asked of all

responding women. In the other 10

minutes of interview time, half the

sample (2,854 cases, called “half-

*$$ * “-%+

$

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

~w

~

Public Health Service

Centers for Disease Controland Prevention %%’

>

+4<baa

National Center for Health Statistics

—’%xm%%!i%i%i%!i%l% CK
2 Advance Data No. 239 ● December 22, 1993

sample I”) was asked detailed

questions on use of contraception and

family planning services, as in

previous NSFG interviews.

The other half of the sample

(2,832 cases, called “half-sample II”)

was asked questions related to HIV

and AIDS. These included questions

on how HIV is transmitted, the

sources and extent of HIV testing,

behavior change, and condom use.

Women were not asked about

injecting drug use or types of

intercourse. This report analyzes

results from only half-sample II

because half-sample I did not contain

the necessary questions on MDSrelated behavior and condom use.

Another report presents data on HIV

testing from half-sample II of the

1990 survey.

The methodology of the

telephone reinterview survey is

described in more detail in the

Technical notes of this report. The

nonresponse adjustments and

procedures for weighting the data for

the 1990 survey are described in

detail in a separate paper (4).

Unmarried women in 1990 will be

used as a group in many of the

analyses in this report. As a group,

women who were unmarried in 1990

were young 75 percent had never

been married and 68 percent were

under 30 years of age (not shown in

tabular form). This means that most

unmarried women began having

intercourse during the HIV-AIDS

era—the 1980’s.

Questions on AIDS-related

behavior in 1988 and 1990

In the 1988 NSFG, all women

who had ever had intercourse were

asked,

To keep people from catching

diseases such as genital herpes,

chlamydia, or AIDS, doctors have

suggested several changes people

can make in their sexual

behavior. In which of the ways

shown on card 27, if any, have

you changed your sexual

behavior?

The changes women could have

reported were:

A.

B.

c.

D.

E.

F.

G.

H.

Stopped having sexual

intercourse.

Stopped having other types of

sexual relations.

Don’t have sex as often.

Stopped having sex with more

than one man.

Stopped having sex with men I

don’t know well.

Stopped having sex with men

who are bisexual.

Stopped having sex with men

who use needles to take drugs.

Have made no changes.

Women who reported that they

had made any of these changes in

their behavior to avoid these diseases

were then asked,

Which of these changes, if any,

have you made since you first

heard about AIDS?

These questions on behavior

change were known to be limited

when they were written in 1986 and

1987. For example, there are no

questions asking how often the

woman did these things before she

heard of AIDS-such as questions

asking the woman whether she had

“other types of sexual relations”

(other than vaginal heterosexual

intercourse) before she heard of

AIDS (B), or how often she had

intercourse before she heard of AIDS

(C), or whether she had intercourse

“with more than one man” in the

same month (D), or whether she had

intercourse with men she didn’t

“know well” (E) before she heard of

AIDS. That is, there is no “baseline”

rate for those behaviors before the

woman heard of AIDS. However,

those “baseline” questions were

judged too sensitive to be used in

1988. The 1988 questions were,

primarily, an experiment to see

whether the subject of AIDS-related

behavior could be discussed in a

survey of the general population of

women. The questions did succeed in

that goal and produced the following

results.

About 3 percent of married

women and about 31 percent of the

sexually experienced unmarried

women reported making one or more

of these changes since they first heard

about AIDS (3). The most common

changes reported were “Stopped

having sex with more than one man,”

reported by 16 percent of unmarried

women who had ever had intercourse,

and “Stopped having sex with men I

don’t know well,” reported by

12 percent of unmarried women who

had ever had intercourse. These

results encouraged NCHS to ask

further questions.

In the 1990 NSFG telephone

reinterview, there was concern that a

list of changes in behavior like that

used in 1988 would be dMkult to

administer by telephone, would be

more sensitive over the telephone,,

and would take considerable

interview time-given that only 10

minutes were available for AIDSrelated questions in half-sample II.

As a result of such concerns, two

short questions were used in place of

the above Iisti

Since you first heard about AIDS

have you changed your sexual

behavior in ANY way? (an& if

“yes”) Have you changed your

sexual behavior specifically to

keep you or your partner from

being infected with the AIDS

virus?

This pair of questions in 1990 was

intended to be comparable to the

longer set of questions in 1988.

Assuming that they are approximately

comparable, trends in the number of

women reporting changes in their

behavior in response to the HIV can

be assessed. These trends are

reported in table 1, and they show an

increase between 1988 and 1990 in

the percent who reported changing

their sexurd behavior in all of the 21

race-marital status and number of

partners groups except one—

unmarried non-Hispanic black

women. The overall increase, from

14 percent in 1988 to 18 percent !m

1990, was statistically significant,

However, the changes were signiEcant

in only 6 of the 21 comparisons in

table 1, and none of the increases for

unmarried women was significant at
Advance Data No. 239 ● December 22,1993 3

Table 1. Number and pereent of women 15-44 yaam of age who have ever had Intareourea and who reported ehanglng their sexual

behavior spaeifieaiiy to avoid the AiDS virus, by aalaetad charaeteriatkx United Statea, 1988 and 1990

Allmarital statuses Marrid Unmarrid

selectedeharackwisiic lm 1988 1990 1988 1990 1W6

Numberin ttwwnds

Total’ . . . . . . . . . . . . . . . . . . . . . . . . . . . 5s,389 51,798 31,417 27,S40 21,952 20,264

Race and origin

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . 4,839 4,574 2,887 2&% 1,771 1,801

Non-Hspanicwhite . . . . . . . . . . . . . . . . . . 38,S31 33,553 24,921 22,513 14,6W 13,4s8

Non-H~p8nic black . . . . . . . . . . . . . . . . . . 7,015 6,778 2,388 1,977 4,618 4,276

IJfehe numberof sexual pattners

I-smen . . . . . . . . . . . . . . . . . . . . . . . . . 27,218 26,872 18,165 18,140 9,032 8,732

4-8rnen . . . . . . . . . . . . . . . . . . . . . . . . . 13,520 10,573 6,665 5,351 6,8S4 5,222

7menormor8 . . . . . . . . . . . . . . . . . . . . . 11,488 9,7s8 5,864 3,939 5,575 5,763

Pe$oant

Total’ . . . . . . . . . . . . . . . . . . . . . . . . . . . 18.0 14.4 5.3 29 36.3 32.8

Race and origin

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . 20.7 18.4 7.1 3.3 42.7 38.6

Non-Hspenicwhiie . . . . . . . . . . . . . . . . . . 15.0 11.2 4.4 2.4 33.1 27.6

Non-H~panicblaok . . . . . . . . . . . . . . . . . . 34.5 30.8 15.2 %4 44.5 45.9

Metimenumberof sexuslpartners

l-3men . . . . . . . . . . . . . . . . . . . . . . . . . 9.5 8.1 2.3 1.8 24.0 21.2

4-8men . . . . . . . . . . . . . . . . . . . . . . . . . 23.4 19.5 6.7 ●4.4 33.7 35.0

7menorrnofa . . . . . . . . . . . . . . . . . . . . . 30.9 20.6 13.1 6.5 48.7 47.2

‘Indudesdhwrscesami wcmsnwiwselibiimenumberofsexuslpatnerswasndascwahd ,nOtshOwnsqMatdy.

the5percent level. (The increase

from28t033percent among

unmarried non-Hispanic white women

wassigniiicant atthelOpereent

level.) Among black non-Hispanic

msrried womenin 1988, 6percent

reported changes in their behavior in

responsetothe AIDSvims;in1990,

15percentreported changes.

Thedataarealso shownin

table 1 by the lifetime number of

sexual partners. The lifetime number

of partners does not reveal when

women had those partners.

Nevertheless, number of partners is

considered one of the beat indicators

of the risk of STD’S (5). Only one of

the changes by number of partners

was significant: 6.5 percent of married

women with 7 or more partners in

their lifetimes reported changes in

1988 compared with 13 percent in

1990.

The dfierencea in table 1 by

maritrd status are very large: in 1990,

5 percent of married women and

36 percent of unmarried sexually

experienced women reported that

they made changes in their sexual

behavior since they heard of AIDS.

In 1988, these figures were 3 percent

and 33 percen~ respectively.

The differences between white

and black women were also quite

large in both 1988 and 1990. For

example, the percent of black women

who reported changes in their

behavior since hearing of AB)S was

35 pereent in 1990; for white women

it was 15 percent. For married black

women, the percent reporting a

change was 15 pereent compared with

4 percent of white married wome~

for unmarried wome~ the

comparable percents were 45 percent

of black and 33 percent of white

unmarried women.

If the data on behavior change in

table 1 were vsli~ objective indicators

of behavior would be expected to

show a reduction in the risk of HIV

infection. The only objective indicator

available in both the 1988 and 1990

surveys is the percent with more than

one partner in the 3 months before

the survey. A reduction in the

proportion with more than one

partner would suggest that women

have made an overall reduction in the

risk of HIV infection. But the

proportion with more than one

partner did not dro~ it increased

significantly, from 7.5 to 10 percent of

unmarried women. This one

comparison does not show that the

data on behavior change in table 1

are invalih because the characteristics

of partners have as much effect on risk

of HIV infection 8s the number of

partners (tj). But it should encoumge

caution in making inferences abut the

public health impact of the chnges

shown in table 1.

Condom use

Use of condoms has been

recommended as a means to avoid

HIV infection for those who do not

remain in a mutually monogamous

relationship (7). However, to be

effective as prevention, condoms must

be used consistently (at each act of

intercourse). Women in half-sample
4 Advance Data No. 239 ● December 22, 1993

II of the 1990 NSFG telephone

reinterview were asked separate

questions about condom use to

prevent STD’S and condom use for

contraception. The two questions

designed to measure condom use to

prevent STD’S were:

In the last 3 months in which you

were having intercourse, did you

use condoms to avoid getting

diseases such as genital herpes,

gonorrhea, or AIDS?

Those who answered “yes” were

asked,

Did you and your partner use

condoms to avoid getting diseases

such as genital herpes, gonomhea,

or AIDS every time you had

intercourse, on most occasions,

about half the time, or less than

half of the time?

Note that these questions ask

about the frequency, not the

correctness, of condom use. No

questions on the correctness of

condom use were asked. Women

were also asked,

In the last month, how

frequently, on average, did you

have intercourse?

Those who answered “not at all”

were excluded entirely from tables

2-8. (For ease of writing, the phrase

“women used condoms” is sometimes

used in the following text, although it

is clear that their male partners were

using the condoms.)

Table 2 shows sexually active

women (those who had intercourse in

the last month) by whether and how

often they were using condoms for

disease prevention: 6 percent were

using condoms every time they had

intercourse (labeled “Always” in the

table; also described as “consistent

use” in the text). Another 4 percent

used condoms “on most occasions”

(labeled “Most times” in table 2), and

5 percent half the time or less. Note

that less than half of all those using

condoms for disease prevention in

1990 used them always (that is, every

time they had intercourse). For

example, only 6 out of 15 percent

(less than one-hal~ used condoms

every time they had intercourse

(always).

It is no surprise that the

unmarried were much more likely to

use condoms for STD-HIV

prevention than married couples were

(for example, 14 percent of unmarried

women and 1 percent of married

couples always used condoms for

disease prevention). However, the

data by race and origin in table 2

reveal that occasional or tiequent

condom use is much more common

among the partners of non-Hispanic

black women than non-Hispanic white

women. For example, 13 percent of

black women and only 3 percent of

white women reported that their

partner used condoms “half the time

or less.” Among the unmarned,

19 percent of black women and only

9 percent of white women used

condoms half the time or less. The

estimates of the percent of women

protected from HIV infection or

other STD’S by condom use in tables

5-8 of this report will include only

those who used condoms every time

they had intercourse.

Table 2 also includes data on

condom use for STD prevention by

the woman’s education. Only

2.5 percent of unmarned women

without a high school education (O-11

years of education) had partners

using condoms consistently compared

with 18.6 percent of those with some

college education (13 years or more).

The differences in the proportions

using condoms most times or half or

less were not significant, either for

unmarried women or for all marital

statuses combined. This is in sharp

contrast to the data by race, where

the significant difference was in

inconsistent use.

The proportion of unmarried

women whose partners were using

condoms is also shown by the number

of sexual partners the woman had in

the last 3 months in which she was

having intercourse. (Reliable

estimates of the proportion of

married women who had multiple

partners could not be made because

the sample was not large enough.)

The difference in consistent condom

use by number of partners

(14 percent versus 16 percent) was

small and not signfican~ but the

proportion of those with two or more

partners who used condoms half the

time or less was 27 percent compared

with 11 percent of those with one

partner. However, the 27 percent for

unmarried women with more than

one partner was only about 498,000

women; and 498,000 is only about

3 percent of all 15.23 million sexually

active unmarried women shown in

table 2.

Comparable data on condom use

for STDIHIV prevention in 1988 are

not available. In the 1988 survey,

there was no followup question to ask

whether condoms were used

consistently (at every intercourse) or

not. In addition, the 1988 question

asked, “Do you use (condoms)?” This

question does not ask about a speciiic

time period (such as, “in the last

month,...” ) and the question

apparently allowed some women to

report that they were using condoms,

although they said elsewhere in the

interview that they were not having

intercourse in the month of interview.

The absence of questions in the 1988

survey on consistency of condom use

and the lack of a specific time

reference mean that some women

who did not use condoms consistently

in 1988, and some who are not having

intercourse currently, would be

classified as being protected from

STD’S by condom use in 1988. The

1990 data do not have these

problems.

Condom use can also be reported

for contraceptive purposes, and if

condoms are used consistently for

contraception, they can offer

protection from HIV infection as

well. Women in half-sample II in

1990 were also asked,

In the past month have you and

your partner used any method of

birth control or family planning?

(and if “yes”) What method or

methods was that?

Up to four methods were

recorded, so those reporting condom

use with other methods could be

counted as condom users. Those who

reported condom use (or any other
Advance Data No. 239 ● December 22, 1993 5

Table 2. Number and pereent distribution of women 15-44 years of ege who have had Intercoume in the pact month by fraquaney of condom

uae in the pact 3 months to avoid sexualfy transmitted dkeaeea, according to eelectad eharecterietkx United Statee, 1990

Ccmkxrrrisern ihepast3rnmths toawtiW~

dis@sea

SexlIa/ly *

Selectd Ctraraderistk

Haifttrafirrra

Mrrrrarr Toi2sI Navw Ahq?3 hkwttimes Orless

Nlmeritaietatuse# . . . . . . . . . . . . . . . . . . . . . . . . .

Racaandorigin bymaritalatatue

Hispanic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Non-Hispaniowhim . . . . . . . . . . . . . . . . . . . . . . . . .

Non-l-lispan icblac k . . . . . . . . . . . . . . . . . . . . . . .

MartMwomen2. . . . . . . . . . . . . . . . . . . . . . . . . . .

Ram:

Non-Hispanicwhile. . . . . . . . . . . . . . . . . . . . . . . .

Non+lispanic black. . . . . . . . . . . . . . . . . . . . . . . .

Unmarried virmlan3. . . . . . . . . . . . . . . . . . . . . . . . .

Rata

Non-l+ispsni cwhiie . . . . . . . . . . . . . . . . . . . . . . .

Non+lispanic blaok. . . . . . . . . . . . . . . . . . . . . . . .

Educaticmby marital statua4

All marital statuses

O-llyaafs . . . . . . . . . . . . . . . . . . . . . . . . . . . .

12years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13yeersorrrrore . . . . . . . . . . . . . . . . . . . . . . . . .

Married

O-n yeare . . . . . . . . . . . . . . . . . . . . . . . . . . . .

12yea’a. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13yearsormore . . . . . . . . . . . . . . . . . . . . . . . . .

Unmm”ed:

O-llyeafs . . . . . . . . . . . . . . . . . . . . . . . . . . . .

12yeara . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13yearsormore . . . . . . . . . . . . . . . . . . . . . . . . .

Nurnberofwxualpar-tnersinthe@3-

Unmarried:

I man . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

2ormoramen . . . . . . . . . . . . . . . . . . . . . . . . . .

Numberin

thousarKls’ Percent di~”lxdion

45,432

4,263

3s,646

5,465

30,200

23,625

2,223

15,232

9,921

3242

4,363

15,033

22,55s

3,246

10,759

15,966

1,715

4,s40

6,665

13270

1,630

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

100

66.5

81.4

66.2

67.0

97.4

66.2

93.5

620

67.5

46.8

67.4

W.o

67.0

94.7

97.9

97.5

73.4

70.2

61.3

65.3

39.0

5.5

8.0

4.4

10.3

1.2

12.6

16.8

?2.3

3.7

6.3

%2.2

W6

*1.2

%2.5

10.6

18.6

14.0

16.2

4.2

4.4

3.4

10.0

W.6

W.3

%?

11.2

10.6

15.4

%.2

3.1

3.3

TL2

%.8

%.7

14.6

9.4

9.7

10.1

17.7

4.6

6.2

3.1

127

0.9

W.6

%3.4

12.6

9.1

19.0

5.2

3.2

3.6

%?.9

W.6

W.6

%.5

9.8

10.4

10.6

27.2

‘Womanvhrodidnothaveintemoursein the monthWore htarvht areexclud+dfromtables2-6.

‘IncludesotherracesW show separately.

31ncludaswomenof Hispanicofiginandolharracesnotshow eaparateiy.

%ducationin yeas. Figuresbyeducationincludewomen1s-44pars of ageonly.

NOT=Bemueeor rounding,flguresmaynotaddtototale.

coitus-dependent method) were also

asked how frequently they usedit,

and only those who answered “every

time (I) had intercourse” were

classified as “consistent” condom

users intable3. In addition, those

who reported that they didnot have

intercourse at allin the month before

interview were excluded iiomtables2

and3. About 6percent were using

condoms consistently for

contraception and about 7percent,

inconsistently (table 3).

There are at least four important

Iindings in table 3. FirsL consistent

useislessthan halfofall

contraceptive condom use. Among

theunmarrie~ lOpercent ofsexually

active women used condoms

inconsistently, but only 6percent used

them consistently. 1’he second striking

iinding in table 3 is that although

there are pronounced marital status

and race differences in condom use

for STD prevention, the differences

by race and marital status in condom

use forcmtraceptionare quite small.

‘f’hir~ the pattern by education is

similar for contraceptive condom use

and preventive condom use

11 percent of college-educated

unmanied women were using

condoms for contraception in 1S90
6 Advance Data No. 239 ● December 22, 1993

Table 3. Percent distribution of women 1544 years of age who have had intercourse In the past month by how frequently her partner

used condoms for contraception in the past month, according to selected charscteriaticx United States, 1990

Condom use in thepast month for oontrsoaption

Selected characteristic Total’ Nevar Always2 inconsistent

Percent distribution

Sexually active women3 . . . . . . . . . . . . . . . . . . . 100 87.3 5.8 6.9

Race and origin by marital status

Hispanic . . . . . . . . .

Non-Hispanic whtie . .

Non-Hispanic black . .

All married women4 . .

Ram.

Non-Hispanic whte.

Non-Hispanic black.

All unmarried women4.

Race

Non-Hispanic whke.

Non-Hispanic black.

. . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . .

100 66.5

87.0

36.4

4.5

5.8

5.4

7.0

7.2

6.2

100

100

. . . . . . . . . . . . . . . . . . . 100 69.3 5.6 5.2

100

100

68.9

91.9

5.3

5.5

5.7

2.6

. . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . 100 63.5 6.2 10.2

10.6

8.7

100 82.5

66.0

6.9

5.3

. . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . 100

Education by marital etatus5

All marital statuses

O-n years . . . . . . . . . . . . . . . . . . . . . . . . . 100 91.0 %26 6.2

12yeara . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 91.0 4.3 4.7

13yeaffi ormore . . . . . . . . . . . . . . . . . . . . . 100 65.5 7.8 6.7

Married:

O-n years . . . . . . . . . . . . . . . . . . . . . . . . . 100 84.1 %.2 %2.7

12years . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 91.4 4.7 3.9

13yeare ormore . . . . . . . . . . . . . . . . . . . . . 100 67.2 6.4 6.5

Unmarried

O-n yeara . . . . . . . . . . . . . . . . . . . . . . . . 100 85.1 %.2 *1 2.7

12years . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 90.2 %3.2 6.6

13yearsor more . . . . . . . . . . . . . . . . . . . . . 100 81.3 11.4 7.3

Number of sexual partners in the past 3 months

Unmarried

I an . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 63.6 6.7 9.7

2men or more . . . . . . . . . . . . . . . . . . . . . . . 100 64.1 %3.3 *I 2.6

lPercente bessdon numberofwomenshownintable2.

“’Always” mesnsat evefy actof intermursa.

31ncludasotherracesnet shownseparately.

41ncludeswomenof Hispanicoriginandother races rot alwwm separately.

5Education in years. Figures byaducstion include women l%t4yeara ofage only.

NOTE Bscaussofrounding,figuresmaynotaddto totals.

compared with 2 and 3 percent in

the other two education groups.

Fourth, in sharp contrast to

condom use for disease prevention,

there was no significant difference

in contraceptive condom use by

number of sexual partners in the

last 3 months.

Table 4 shows the proportion of

sexually active women who reported

that they and their partners used

condoms consistently (every time she

had intercourse), either to avoid

STD’s or for contraception.

About 10 percent always used

condoms: 6 pereent of married and

16 percent of sexually active

unmarried women. The differences by

race and origin in consistent condom

use were not large and not signilkant.

The diiYerencesby race among the

unmarried in inconsistent use were,

however, quite large: The partnem of

21 percent of sexually active

unmarried white women and

34 percent of sexually active

unmarried black women were using

condoms inconsistently in 1990.

The dfierences by race in

condom use were in inconsistent use,

but the differences by education in

table 4 are found in the proportions

who used condoms always-at every

act of intercourse. Of unmarried

women with less than a high school

education, 4 percent were using

condoms consistently in 1990

compared with 11 percent of high

school graduates and 21 percent of
Advance Data No. 239 ● December 22, 1993 7

Table 4. Number and percent distribution of women 15-44 yeara of age who had Intercourse in the paat month by how frequently her

partner uses condoms either to avoid sexually tranemftted diasasea or for contraception, according to selected characteristics: United

States, 1990

Curmnfooruiomuse to preventsexualtytransmiifed

sexually diseasesor iv eonfrace~”on

active

Selectedcharacteristic women Total Never Ahvays’ Inconsistent

Number in

thousands

45,432

4,283

33,646

5,465

30,200

23,925

2,22a

15,232

9,921

3,242

4,963

15,088

22,653

3,248

10,759

15,268

1,715

4,340

6,5S5

Percent dim”bti”c+s

Tota[z . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Race and origin by marital status

Hispanic.. . . . . . . . . . . . . . . . . . . . . . . . . . .

Non-Hispanic while . . . . . . . . . . . . . . . . . . . . .

Non-liispani cblac k . . . . . . . . . . . . . . . . . . . .

Allmarried women3 . . . . . . . . . . . . . . . . . . . . .

Rac&

Non-Hispanic while . . . . . . . . . . . . . . . . . . . .

Non-l-lispan icblac k . . . . . . . . . . . . . . . . . .

Allunmarried women3. . . . . . . . . . . . . . . . . . . .

Racer

Non-Hispanic whtie . . . . . . . . . . . . . . . . . . . .

Non-Hispanic black. . . . . . . . . . . . . . . . . . . .

Eduoation by marital status’

All marital statmses

O-n yeara . . . . . . . . . . . . . . . . . . . . . . . . .

12yeans . . . . . . . . . . . . . . . . . . . . . . . . . .

13years ormore . . . . . . . . . . . . . . . . . . . . .

Married

O-n years . . . . . . . . . . . . . . . . . . . . . . . . .

12yeara . . . . . . . . . . . . . . . . . . . . . . . . . .

13yaars orrnOre . . . . . . . . . . . . . . . . . . . . .

Unmarried:

O-n yeare . . . . . . . . . . . . . . . . . . . . . . . . .

12yesra . . . . . . . . . . . . . . . . . . . . . . . . . .

13yea130r more . . . . . . . . . . . . . . . . . . . . .

Number of sexual parbrers in the paat 3 mordhs

Unmarried

lean . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13,270 100 624

2rnanor more . . . . . . . . . . . . . . . . . . . . . .

15.9 21.6

1,s30 100 38.0 16.2 44.8

“cAlwsy3”meenswe at evwyd of intercourse.

‘Includesotherrams notshownseparately.

31ncludsswomenof Hispsniocrigineml OlhsrrS.OSSnot* =wetety.

4Educatbninyears. F@xes by educstionimdudewomen19-44 years of age cWy.

100 78.1 9.6 12.3

100

100

100

100

100

100

100

100

100

75.5

81.0

63.8

10.9

8.6

13.3

13.5

10.4

22.9

87.5

87.9

66.3

56.5

64.4

48.4

6.4 6.1

5.9

6.5

15.8

14.9

17.9

6.2

7.2

24.6

20.7

33.7

100 83.4 *4.9 11.7

100 S4.o 6.9 9.1

100 77.3 11.3 11.4

100 91.2 %.4 %5

100 89.8 5.1 5.1

100 65.5 7.1 7.3

100 86.7 %3.9 27.4

100 66.5 11.4 19.1

100 57.3 21.4 21.3

NOT.E Bemuse of rounding,~ures may notaddto totsls.

those with college educations. The

differences by education in

inconsistent use were not significant

(27 percent versus 19 and 27 percent

versus 21 percent, both not

significant). Finally, women who had

tsvo or more partners in the last 3

months were twiee as likely to use

condoms inconsistently as those who

had only one partner in the last 3

months (45 percent versus

22 percent).

Of unmarried women who were

notusing condomsin 1990, 0nly

2 percent were trying to become

pregnan$ 45 percent said they had

“no chance at all” of contracting

HIV, and 37 percent said they had

“not much chsnee.” This leaves about

16 percent of those not using

condoms-about 10 percent of all

sexually active unmarried womeq or

1.46 million-whose reasons for not

using condoms were not clear.

AIDS-related behavior in 1990

Tables 5-8 show the percent of

sexually active women who had

changed their sexual behavior

spceilically to avoid the AIDS virus,

the percent who had always used

condoms to prevent STD’S or for

contraceptio~ the percent who either

were using condoms or changed their

sexual behavior, and the percent who

did both. Table 5 contains the data by

age and marital status.
8 Advance Data No. 239 ● December 22, 1993

Table 5. Number and percent of women 1!5-44 yeara of age who had intercourse in the past month, by age and marital statua and

selaetad characteristics: United States, 199o

Sexually

6oth

Behavior Condoms or ooncioms

active change to Always use behavior

Age and marital stafus

and bahavior

women avoid AIDS condoms ohange change

All marital statuses

15-44 years . . . . . . . . . . . . . .

15-19 years . . . . . . . . . . . . . .

20-24 years . . . . . . . . . . . . . .

26-29 years . . . . . . . . . . . . . .

30-34 yeara . . . . . . . . . . . . . .

35-14 years . . . . . . . . . . . . . .

Married

15-44 yearal . . . . . . . . . . . . . .

20-24 years . . . . . . . . . . . . . .

25-29 year n . . . . . . . . . . . . .

30-34 yea ffi . . . . . . . . . . . . . .

3S-44yeaffi . . . . . . . . . . . . . .

Unmarried

15-44 yaara . . . . . . . . . . . . . .

15-19 yeara . . . . . . . . . . . . . .

20-24 years . . . . . . . . . . . . . .

X-29years. . . . . . . . . . . . . .

30-34 years . . . . . . . . . . . . . .

35-44 yeara . . . . . . . . . . . . . .

Number in

thousends Percent

45,432

3,895

7,052

8,862

9,626

15,997

30,200

3,055

5,923

7,200

13,434

15,232

3,306

3,998

2,939

2,426

2,583

16.1 9.6 22.3 :3.3

33.2 15.3 40.4 [3.1

23.2 13.4 33.6 w o

18.6 7.4 24.0 q.o

12.6 10.5 19.7 :3.3

9.5 7.1 13.6 :3.0

5.3 6.4 11.1 0.6

13.0 *6.5 19.5 0.0

7.1 7.2 13.1 *1.1

3.7 7.7 11.1 W.3

3.5 4.9 7.9 W.5

37.5 15.8 44.7 13.7

37.6 15.4 44.5 !3.4

31.1 18.7 44.5 *5.4

41.9 7.9 46.0 X3.8

39.0 18.5 46.2 12.4

41.1 18.4 43.3 1IB.1

‘Includes women 1s19 years of age not shown separately.

The data on behavior change in

tables 5-8 show the percent who

answered “yes” to two questions:

Since you first heard about AIDS

have you changed your sexual

behavior in ANY way?”

(and if “yes”) “Have you change

your sexual behavior specifically

to keep you or your partner from

being infected with the AIDS

virus?

The percents in the “behavior

change” column in tables 5-8 differ

from those in table 1 because those in

table 1 are percents of all women who

have ever had intercourse at some

time in their lives. The percents in

tables 5–8, in contrast, are percents of

women who had intercourse in the

last month.

Overall, 16 percent of women

sexually active in the last month

reported that they changed their

sexual behavior to avoid the AIDS

virus, and 10 percent reported that

they used condoms consistently,

either to avoid STD’S or for

contraception. Most women were

:d

asked both the questions on behavior

change and the questions on condom

use. Behavior change and condom use

sre not mutually exclusive categories,

so some women (3 percent in table 5)

reported both.

The proportions who reported

chsnging their behavior declined

sharply ss age increased, from

33 percent of sexually active teenagers

to 10 percent of sexually active

women 3544 years of age. There

were not enough married teenagers in

the sample to make an estimate for

that group, but a decline (from 13 to

4 percent) from ages 20-24

years-ages 35-44 years is apparent

among married women. Among

sexually active unmarried women,

however, the percent who reported

changing their behavior was

38 pereent overall and did not vary

significantly by age.

Note that although 5 pereent of

married women reported that they

chsnged their behavior, they did not

necessarily change it while they were

married. The behavior change is

measured since the woman heard of

AIDS, not since she was married. She

may have changed her behavior

before she was married. It is possible

that getting married may have been a

response of some of these women to

the risk of HIV infection.

The proportion of sexually active

women who consistently used

condoms, either to prevent STD’S or

for contraception, was about

15 percent for teenagers, 13 percent

for those 20-24 years of age, and

7 percent for those 35-44 years. The

proportion always using condoms was

about 6 percent for married couples

and did not vary signiikrmtly by the

age of the woman. Among sexually

active unmarried women, about

16 percent used condoms and there

was no consistent pattern by age.

About 22 percent either changt:d

their behavior or always used

condoms; this proportion declined

from 40 percent among teenagers tlo

14 pereent at ages 35-44 years.

Among married couples, the percent

declined from 20 percent at ages

20-24 years to 8 percent at ages

3544 years. Among unmarried
Advance Data No. 239 ● December 22, 1993 9

All racea’. . . . . . . . . . . . . . . . . .

Race and origin

Hispanic . . . . . . . . . . . . . . . . . .

Non-Hispanic whte . . . . . . . . . . .

Non-l-lispan icblack. . . . . . . . . . .

Poverty-levelincome2

O-149 psrcent . . . . . . . . . . . . . .

150percentormore . . . . . . . . . .

Married

Race and origin

Allreces3 . . . . . . . . . . . . . . . .

Non-1-lispanicwhte.. . . . . . . . .

Non-l-lispan icblaok.. . . . . . . . .

Povetly-levelincomex2

0-149percent . . . . . . . . . . . . .

150percentormore . . . . . . . . .

Unmarried

Race and origin

Allrace33 . . . . . . . . . . . . . . . . 15,232 37.5 15.8 44.7 8.7

Non-!lispanicwhte.. . . . . . . . . 9,921 33.2 14.9 40.9 7.2

Non-1-lispanicblack. . . . . . . . . 3,242 46.9 17.9 52.5 12.4

Pove~-lavelincome2

0-149percent . . . . . . . . . . . . . 4,727 47.2 12.5 51.8 7.9

160parcentormora . . . . . . . . . 9,933 32.6 17.8 40.9 9.5

Table6. Number ofwomen 1544 yearsofagewho had intercoursein thepastmonth and pereentwho reportad thattheychanged their

sexual behavior, whose partners aiways use condoms, who either changad their behavior or always use condoms, and who did both, by

seieeted charaeteriati~ United States, 1990

Sexually Sehawbr Condomsor G3%%a

a@”ve change to Afwaya use behavior and lmhavbr

Selectedcharacteristic women avoidAIDS condoms Charrga change

Numberin

thousands Percent

45,432 16.1 9.6 22.3 3.3

4,263 19.1 10.9 26.2 3.9

33,a46 12.9 8.6 18.9 2.6

6,465 33.9 13.3 39.9 7.3

7,766 31.6 11.1 37.4 5.3

35,645 12.9 9.5 19.3 3.1

30,200

23,925

2,223

5.3

4.5

15.0

6.4

5.9

6.5

11.1

9.7

21.5

0.6

0.6

0.0

3,056

25,712

7.6

5.2

8.8

6.2

15.2

10.9

1.2

0.6

‘Includesotherrams notshownseparately.

%snen withpovwty-lwel iccomenots3cedainedare notshovmseparately.

31ncludeswomenof Hispanicotiginad otherracssmt shcm qxsrateiy.

women, there was no significant

pattern by age.

Table 6 contains the same

measures as table 5 for sexually active

women classified by race, Hispanic

origin, and poverty-level income

instead of age. About 34 percent of

sexually active non-Hispanic black

women compared with 13 percent of

non-l%spanic white women, reported

changes in behavior to avoid the

AIDS virus. Among married women,

15 percent of black wives and

5 percent of white wives have made

changes. Among sexually active

unmarried women, 47 percent of

black women and 33 percent of white

women made changes.

For all marital statuses,

13 percent of sexually active black

women and 9 percent of sexually

active white women used condoms

consistently. Some of this difference,

however, was due to the higher

proportion of black women who are

unmarried. Among married women,

the diileremx was very small

(5.9 for white women ver3us

6.5 percent for black women, table @

among unmarried women, the

ditlerence was 3 percentage points

(14.9 versus 17.9) and not significant.

As noted in connection with tables 2,

3, and 4, the larger dMerences by

race and origin were in inconsistent

condom use (using condoms

sometimes but not every time they

had intercourse). Differences by race

snd origin in the “Condoms or

behavior change” eohunn were due

primarily to differences in behavior

chsnge.

Poverty-level income is the total

income of the family divided by the

poverty level for a family of that size

(see Technical notes). Women with

low incomes (under 150 percent of

poverty level) were more than twice

as likely to report that they have

changed their behavior than highincome women (32 versus 13 percent,

table 6). Among married womeq the

difference was small and not

significant (7.6 versus 5.2 percent); for

unmarried women, it was large and

signilieant (47 versus 33 pereent).

Differences by income in condom use

were small overall and for married

couples. For the unmarried,

13 pereent of low-income, and
10 Advance Data No. 239 ● December 22, 1993

Table 7. Number of women 1544 years of age who had intercourse in the paat month and percent who reported that they changed their

sexual behavior, whose psrtners always use condoms, who either changed their behavior or always use condoms, and who did both, by

selected characteristic= United States, 1990

&th

Sexually Behaw”or Condoms or condoms

active change to Always use behavior and behavior

Selected chasctaristic women avoid AIDS condoms change change

Number in

thousands Percent

Total’ . . . . . . . . . . . . . . . . . . . . . . . . . . 45,432 16.1 9.6 22.3 3.3

lifetime number of sexual partners

l-3 men . . . . . . . . . . . . . . . . . . . . . .

4-6 men . . . . . . . . . . . . . . . . . . . . . .

7menormora . . . . . . . . . . . . . . . . . .

23,432

11,353

9,596

8.0

21.3

28.5

9.8

10.0

7.9

16.3

25.7

31.7

1.5

5.6

4.8

Have you ever personally known anyone W-W

the AIDS virus?

Yea . . . . . . . . . . . . . . . . . . . . . . . . . .

No . . . . . . . . . . . . . . . . . . . . . . . . . .

10,724

34,527

22.7

14.1

11.5

8.9

28.3

20.4

5.6

2.6

Married

Lifetime number of sexual partners

l-3men . . . . . . . . . . . . . . . . . . . . . .

4-6men . . . . . . . . . . . . . . . . . . . . . .

?menormore . . . . . . . . . . . . . . . . . .

17,551

6,400

5,576

2.4

6.7

13.3

7.5

4.6

*4.4

9.5

10.5

16.3

Have you ever personally known anyone with

the AIDS virus?

Yes . . . . . . . . . . . . . . . . . . . . . . . . . .

No . . . . . . . . . . . . . . . . . . . . . . . . . .

6,787

23,274

6.7

4.9

6.9

6.1

12.1

10.7

q .5

%4

Unmarried

Lifatimenumberof aexuslpsrtneffi

l-3men . . . . . . . . . . . . . . . . . . . . . .

4-6men . . . . . . . . . . . . . . . . . . . . . .

7menormore . . . . . . . . . . . . . . . . . .

5,661

4,953

4,020

24.8

40.2

49.6

16.8

17.0

12.8

36.6

45.3

58.0

5.0

“11.9

9.4

Have you aver personally known anyone with

the AIDS virus?

Yes . . . . . . . . . . . . . . . . . . . . . . . . . .

No . . . . . . . . . . . . . . . . . . . . . . . . . .

3,937

11,252

50.2

33.2

19.4

14.5

56.3

40.7

I 3.3

7.1

Numberofsexual parlnmsinthe

paat 3 months

Unmarried

I an.. . . . . . . . . . . . . . . . . . . . . . .

2menormore . . . . . . . . . . . . . . . .

13,270

1,630

35.8

4S.6

15.9

16.2

43.7

51.1

8.1

‘13.6

‘Indudeswomen wtwselifetinrerwmberofsexualpatners wasnotascertsinti alsoindudeswomsn withmissisgdataonwhatherthey haveaverknown aparsonwithths AIDSvirusriot

Sho’mlseperatdy.

18percent ofhigher income, women

reported consistent condom use

(significant at the 10-percent level).

Table 7 contains data by the

lifetime number of sexual partnera

and the number of reeent partners

As explained previously, the lifetime

number of partners does not specify

how long ago the woman had those

partners. Nevertheless, it is a good, if

not perfec~ measure of risk of STD’s.

About 8 percent of sexually active

women with 1–3 lifetime partners

changed their behavior compared

with 21 percent of women with 4-6

lifetime partners and 29 percent of

women with 7 or more partnera

(table 7). This increaae with number

of partners held for both married and

unmarried women. For sexually active

unmarned women with 7 or more

lifetime partners, 50 percent reported

that they had changed their behavior

specifically to avoid the AIDS virus.

Those who had more than one

partner in the last 3 months were also

more likely to have changed their

behavior than those with one partner

(49 pereent versus 36 percent).

Variations by number of lifetime

partners and by number of partners

in the last 3 months in current

consistent condom use were small

and not statistically significant.

Women in the survey were also

aaked,

Have you personally known

anyone with AIDS or the AIDS

virus?
Advance Data No. 239 cDecember22,1993 11

Table 8. Number of women 19-44 years of age who had Intercoume in the past month, and percent who reported that they chenged their

sexual behavior, whose partners always use condoms, who either changed their behavior or always uee condoms, and who did both, by

education and maritai statw United States, 1990

Educationand maritaIstatus

Sottr

sexually Behstior Coridorrrsor ixmdoms

active change to Always use behavior and behavior

wornen ava”dAIDS Umdonrs change change

Education

O-n yearn. . . . . . . . . . . . . . . . . . . . .

12years . . . . . . . . . . . . . . . . . . . . . .

13years ormore . . . . . . . . . . . . . . . . .

Married

O-n years . . . . . . . . . . . . . . . . . . . . .

12years . . . . . . . . . . . . . . . . . . . . . .

13years ormore . . . . . . . . . . . . . . . . .

Unmarried

O-n years . . . . . . . . . . . . . . . . . . . . .

12years . . . . . . . . . . . . . . . . . . . . . .

13years orrnore . . . . . . . . . . . . . . . . .

Numberin

thousanda Percent

4,963

15,0s9

22,553

3,24S

10,759

15,s66

1,715

4,340

6,5S5

20.6 4.9 24.3 1.2

14.9 6.9 19.5 2.3

13.2 11.3 21.0 3.5

10.5 5.4 14.7 1.2

5.7 5.1 10.6 0.3

3.7 7.1 10.4 0.4

39.9 3.9 42.4 1.3

37.6 11.4 41.6 7.4

36.2 21.4 48.6 11.0

Among sexually active unmarried

women, 50 percent of those who have

known someone with HIV or AIDS

reported that they had changed their

behavior compared with 33 percent of

unmarried women who did not know

anyone with HIV or AIDS (table ‘7).

However, this variable had no

significant effect on behavior change

among married women, and no

significant effect on consistent

condom use.

Table 8 shows women 19-44 years

of age by years of education. We use

19-44 because it generally takes until

at least age 19 to complete a year or

more of college. (Using 1944

prevents the lower 2 education groups

from being comprised of mainly those

still attending high school.) Among

married women, none of the

proportions in table 8 dMer

significantly by education. bong

unmarried women, the striking

difference in consistent condom use

by education is showm 4 percent of

those who did not complete high

school and 21 percent of those with

some college used condoms every

time they had intercourse (always

used condoms). The proportion of

unmarned women who changed their

behavior did not differ significantly by

education. The proportion who

always used condoms or chenged

their behavior also did not differ

si@cantly by education. The

proportio~ however, who used

condoms and changed their behavior

was 1 percent in the lowest education

category snd 11 percent in the highest

category.

Evaluation of the data

Our iindings suggest that in 1990,

about 1 in 3 sexually active unmarried

women reported that they were at

least attempting to make changes in

their sexual behavior to reduce their

risk of infection with H(V and other

STD’S. That proportion may have

increased slightly between 1988 and

1990, but as discussed previously and

in the Technical notes, comparison of

the 1988 and 1990 data requires some

caution because the questions used to

measure behavior change in 1988 and

1990 were different.

The data on condom use,

however, appear to be quite reliable

because of the separate questions on

condom use for disease prevention

and for contraception, the follow-up

questions on how often condoms are

used, and the question on whether

the woman was currently having

intercourse. All of these questions are

necessary to produce accurate

estimates of current condom use. A

less complete series would tend to

overestimate condom usc because it

would count those using condoms

inconsistently and those not currently

having intercoume as current condom

users. Variations in consistent

condom use by lifetime number of

sexual partners, whether the woman

has ever known a person with HIV

infection or AIDS, and race are

smaller than the variations in

behavior change by these

characteristks. Differences by

education in consistent condom use

among unmarried women, however,

sre quite large.

The analyses descrii here and

in the previous report (3) show that it

is possible to collect data on AIDSrelated behavior change snd condom

use from the general population of

women of childbearing age in the

United States. The success of these

questions to this extent suggests that

behavior change issues can be

measured more directly in these

surveys in the future. Recently,

NCHS has begun a series of smallscale studies to test new ways of

asking questions on MIX-related

behavior in the general population.

These studies include focus groups,

“cognitive” interviews (8), and

smrdl-scale surveys.
12 Advance Data No. 239 ● December 22, 1993

These studies may suggest ways

to obtain comparable data over time

on the number and characteristics of

women’s sexurd partners currently,

and in an earlier time period. This

could be done in a single survey by

asking retrospective questions for the

earlier time period (for example,

from January to December 1985), and

comparing them to a specific time

period of the same length just before

the survey (for example, the last 12

months).

Data like these could also be

collected in successive surveys by

asking only the questions on behavior

just before the survey and asking the

same questions again in the next

survey. This approach has been taken

in surveys of men who have sex with

men (9, 10). This approach was also

used in at least one survey of the

general population, but the details of

the question wording were not given;

that survey has not yet been repeated

and the data were not shown for

women of reproductive age, so

comparisons with our results are not

possible (11).

Estimates by Hearst and Hulley

(6) suggest that partner selection may

be just as important a factor in HIV

risk as the number of partners per se.

Their estimates suggest that in order

to evaluate whether and how much

women are reducing their risk of HIV

infection, objective data are needed

on what respondents mean when they

report that they have “stopped having

sex with men I don’t know well” (the

second most common change

reported in 1988). Concepts such as

“men I don’t know well” will have to

be defined-for example, by using

specific questions to determine how

long she knew the man, and what she

knew about him before they had

intercourse. Concepts such as

“stopped having sex with more than

one man” (the most common change

reported in 1988) can be define~ for

example, by determining the number

of partners women had in specific

time periods. Surveys providing

objective data at two or more points

in time could begin to measure

directly whether HIV-infection risk

was being reduced, and if so, by how

much.

The data on condom use could

also be refined to get a clearer idea

of how much reduction in HIVinfection risk is occurring. For the

close to 10 percent of unmarried

women who had more than one

partner in the past 3 months,

questions could be asked on whether

condoms are used by each partner,

and if so, whether they use them at

every act of intercourse with the

respondent. Women with multiple

recent partners account for only

10 percent of unmarried women but

they probably account for a larger

proportion of cases of STD’S and

HIV infection.

In summary, then, to evaluate

whether the general population of

women 15-44 years of age is reducing

its risk of HIV infection, and if so,

how much reduction is occurring,

data on the number and

characteristics of partners in specilic

periods of time, and data on condom

use specific to each partner, would be

useful. Research is being conducted

to determine the best and least

sensitive ways of asking for such

information.

References

1.

2.

3.

4.

Mosher W, Judkins D, Goksel H.

Response rates and non-response

adjustment in a national survey.

Im 1989 proceedings of the

Anerican Statistical Association,

Section on survey research

methods. 273-8.1990.

Judkins DR, Mosher WD, Botman

S. National Suwey of Family

Growtlx Design, estimation, and

inference. National Center for

Health Statistics. Vital Health Stat

2(109). 1991.

McNally JW, Mosher WD.

AIDS-related knowledge and

behavior among women 1544

years of age: United States, 1988.

Advance data from vitrd and

health statistics; no 200.

Hyattsville, Maryland. National

Center for Health Statistics. 1991.

Goksel H, Judkins D~ Mosher

WD. Nonresponse adjustments for

a telephone followup to a national

5.

6.

7.

8.

9.

in-person survey. J Official Stat

8(4):417-31. 1992.

Aral SO, Holmes KK.

Epidemiology of sexual behavior

and sexually transmitted diseases.

Irx Sexually transmitted diseases.

New York McGraw Hill, 19-36.

1990.

Hearst N, Hulley SB. Preventing

the heterosexual spread of AIDS:

Are we giving our patients the best

advice? JAMA 259 (16):2428-32.

1988.

Centers for Disease Control.

Update Barrier protection against

HIV infection and other sexually

transmitted d=ases. MMWR

42(30):58%91. 1993.

Lessler J, Tourangeau R, Salter

W. Questionnaire design in the

cognitive research laboratory.

National Center for Health

Statistics. Vital and Health

Statistics 6(l). 1989.

Adib S, Joseph J, et al. Relapse in

sexual beha~or among homosexual

mew A 2-year followup from the

Chicago MACS/CCS. Journrd of

Acquired Jrnmune Deficiency

Syndromes 5(6):757<0. 1991.

10. Stall R, Ekstrand M, et al.

Relapse from safer sex The next

challenge for AIDS prevention

efforts. Journal of Acquired

Immune Deficiency Syndromes

3(12)1181–7. 1990.

11. Catania JAj Coates TJ, Stall R, et

al. Prevalence of AIDS-related risk

factors and condom use in the

United States. Science 258:1101-6.

1992.

12. U.S. Bureau of the Census.

Poverty in the United States, 1987.

Current population report% series

P-60, no 163. Washington: U.S.

Department of Ckmmerce. 1989.

13. U.S. Bureau of the Census.

Poverty in the United States, 1988

and 1989. Current population

reportq series P-60, no 171:354-6,

especially table A-3. Washington

U.S. Department of Commerce.

1991.
Advance Data No. 239 ● December 22,1993 13

Technical notes

Survey design

The National Survey of Family

Growth (NSFG) is a periodic survey

conducted by the National Center for

Health Statistics (NCHS) to collect

data on fertility, infertility, family

planning, and related aspects of

maternal and infant health. Fieldwork

for Cycle IV was conducted in 1988,

and the NSFG telephone reinterview

was conducted in 1990. The

contractor for the 1988 and 1990

surveys was Westat, Inc., of Rockville,

Maryland.

For the 1988 NSFG, personal

(face-to-face) interviews were

conducted between January and

August 1988 with a national sample

of women who were 15-44 years of

age as of March 15, 1988. Interviews

were completed with 8,450 women in

1988, including 2,771 black womem

5,354 white wome~ and 325 women

of other races. The sample for the

1988 NSFG was selected from

households that had participated in

another NCHS survey, the National

Health Interview Survey (NHIS),

between October 1985 and March

1987. Respondents were interviewed

by trained female interviewers.

The interviews covered the

woman’s pregnancy history; her past

and current use of contraception her

abfity to bear childrew her use of

medical services for family planning,

infertility, and prenatal care; marriage

and cohabitation; and a wide range of

social, economic, and demographic

characteristics. More detailed

information on the procedures used

in selecting the sample, weighting the

data to make national estimates, and

estimating sampling errors may be

found in two other publications (1,2).

For the 1990 NSFG telephone

reinterview, 5,686 women were

interviewed by telephone between

July 23 and November 5, 1990.

Reinterviews were conducted with

5,359 women who had been

interviewed in 1988, and first-time

telephone interviews were conducted

with 327 young women (sampled from

the NHIS) who had reached 15 years

of age since March 15, 1988. They

were 15-17 years of age when

interviewed in 1990. The response

rate for the initial interviews with

those 15-17 years of age was

53 percent. The reinterview response

rate for the women initially

interviewed in 1988 was 69 percent of

those originally interviewed in 1988.

Overall, the response rate was

67.5 percent in 1990. The most

common causes of nonresponse in

1990 were inability to locate or

contact the respondent because she

had moved and inability to contact

her because she had no telephone or

had an unlisted telephone number.

The 1990 reintemiews lasted an

average of 20 minutes.

The 1990 sample was divided

equally into two “half-samples,” as

discussed in the text. This report is

based entirely on the results of

half-sample II, which contained the

necessary questions on AIIXkdated

behavior and condom use. The data

have been weighted to be

representative of the eiviiian

noninstitutionalized population of the

United States. However, the use of

the half-samples means that sampling

errors are larger than in the previous

report on AIDS-related behavior

from the 1988 survey (3).

Rellablllty of eetlmates

Because the statistics presented

in this report are based on a sample,

they may differ from the statistics that

would result if all 58 million women

represented by the 1990 survey had

been interviewed. The standard error

of an estimate (for example, a

percent) is a measure of such

differences. The standard error of an

estimated number or percent is

calculated by substituting the

appropriate values of A and B from

table I in the following equations

where

N = number of women

P = percent

X = number of women in

the denominator of the

percent

The parameters shown in table I

were used to generate table II

@preliminaryestimates of standard

errors for percents of women of all

races), table III (estimates of

standard errors for white women),

and table IV (preliminary estimates of

standard errors for black women).

The chances are about 68 in 100

(about 2 out of 3) that a sample

estimate would fall within one

standard error, and about 95 in 100

that it would fall within two standard

errors of a statistic based on a

complete count of the population

represented by the NSFG.

Unless otherwise speciikd,

differences between percents

. &cussed in this report were found to

be statistically significant at the 0.05

level using a two-tailed normal

deviate test (z-test). This means that

in repeated samples of the same type

and size, a difference as large as the

one observed would occur in only

5 percent of the samples if there

were, in fa~ no difference between

the percents in the population.

Statements using the phrase “the

data suggest” indicate that the

difference was signiikant at the 0.10

(lo-percent) level but not the 0.05

(5-percent) level. Lack of comment in

the text about any two statistics does

not mean that the difference was

tested and found not to be significant.

The relative standard error (or

coefficient of variation) of a statistic

is the ratio of the standard error to

Table L Eatlmatea of the parameters A and

B for eatimatlng standard errors for

percents of women, by racw 1990 National

Suwey of Family Growth telephone

reinterview, half-sample

A B

and

‘~’)=r_TAllraoes . . . . . . . -.00042S2 25,0CMI

Whiie or other. . . . -0004947 25,000

Black . . . . . . . . . -.eola417 14,450
14 Advance Data No. 239 ● December 22, 1993

Table Il. Standard errore for percents of women of ail rac~ 1990 Nationai Survey of Famiiy Growth teiephone reinterview, haif-aampie

Estimated peroent

Base ofperoant 5 or 95 19 or 90 20 or 80 30 or 70 40 or 60 50

Standard error in percentage~ints

500,000 . . . . . . . . . . . . . . . . . . . . . *4.9 %.7 *8.9 *10.2 11.0 11.1

1,000,000 . . . . . . . . . . . . . . . . . . . . 3.4 *4.7 *6.3 7.2 7.7 7.9

5,000,000 . . . . . . . . . . . . . . . . . . . . 1.5 2.1 2.8 3.2 3.5 3.5

10,000,000. . . . . . . . . . . . . . . . . . . . 1.0 1.5 2.0 2.3 2.4 2.5

30,000,000. . . . . . . . . . . . . . . . . . . . 0.8 0.9 1.1 i .3 1.4 1.4

50,000,000. . . . . . . . . . . . . . . . . . . . 0.5 0.7 0.9 1.0 1.0 1.1

Tabie iii. Standard errora for percents of white women: 1990 Nationai Survey of Famiiy Growth teiephone reinterview, haif-sampie

Estimatedperoent

Base of peroent 5or95 19or 90 20 or 80 30 or 70 40 or 60 50

Standardarror in percentage points

500,000 . . . . . . . . . . . . . . . . . . . . . *4.9 %7 %9 *I 0.2 11.0 11.2

1,000,000 . . . . . . . . . . . . . . . . . . . . %4 *4.7 *8.3 7.2 7.7 7.9

5,000,000 . . . . . . . . . . . . . . . . . . . . *1.5 2.1 2.8 3.2 3.5 3.5

Io,ooo,ooo. . . . . . . . . . . . . . . . . . . . 1.0 1.5 2.0 2.3 24 2.5

20,000,000. . . . . . . . . . . . . . . . . . . . 0.8 1.1 1.4 1.6 1.7 1.8

40,000,000. . . . . . . . . . . . . . . . . . . . 0.5 0.8 1.0 1.1 1.2 1.3

the statistic and usually is expressed

as a percent of the estimate. In this

report, percents and other statistics

with relative stsndard errors of

30 percent or larger are indicated

with an asterisk (*). These estimates

may be viewed as unreliable by

themselves, but they may be

combined with other estimates to

m8ke comparisons of greater

precision.

Statistics in this report may also

be subject to nonsampling error, that

is, errors or omissions in responding

to the interview, recording answers,

and processing data. The data have

been adjusted for nonresponse and

adjusted to independent control totals

obtained from the U.S. Bureau of the

Census. These adjustments reduce

most types of nonsampling error.

Other types of nonsampling error

were minimized by a series of quality

control procedures.

Definition of terms

Race—Race refera to the race of

the woman interviewed. Each woman

was asked, “Which of the (following)

groups best describe your racial

background?” The categories include

black white, Asian or Paci.tlc

Islander, and Alaskan Native or

American Indian. Because of small

sample sizea, the Asian or Pacific

Islander and Alaskan Native or

American Indian categories sre

combined and called “other” in this

report.

Hispanic origin-Each womsn was

asked, “Which of the (following)

groups best describe your nationsl

origin or ancestry?” Using a list of 15

groups, a woman was classified as

being of Hispanic origin if she

reported that her only or principal

national origin was Puerto Rican,

Cuban, Mexican American, Central

or South American, or other Spanish.

Origin is therefore classified

independently of race, and Hispanic

women may be of any race.

Marital status-In this report,

women were classified according to

their legal marital status. In this

report, “unmarried” means not

legally married-that is, never legally

married, widowed, divorce~ or

separated. “Married” means currently

legally married. Cohabiting women

who are not legally married are

therefore classified in this report as

unmarried. Marital status refers to

the data year indicated. For example,

if a woman was married in 1988 and

divorced by 1990, she is shown as

married in the 1988 data and as

unmsrried in the 1990 data.

Sexually active-This refers to a

woman who had intercourse at lea~st

once in the month (30 days) before

the survey.

Sexually experienced-This refers

to a woman who haa had sexual

intercourse at least once. Intercourse

before the first menstrual period is

excluded.

Number of lifetime sexual

partners-This refers to the number

of men with whom the woman has

had sexual intercourse in her life, as

of the date of interview. In the 1988

data, this refers to the number of

men with whom she had had

intercourse as of 1988; for 1990 clata,

this refers to the number of men with

whom she had had intercourse as of

the 1990 interview.

Number of sexual partners in the

last 3 rnonths-l%is refers to the

woman’s answer to a question asked

in half-sample II in 1990: “In the last

3 months in which you were having
Advance Data No. 239 ● December22, 1993 15

Table IV. Standard errors for percents of black women: 1990 National Survey of Family Growth telephone reinterview, haif-sample

Estimakxiperoent

Base ofpercwt 5or95 19 or 80 ZQwso 30 or 70 40 or 60 50

Standarderrorin percentage points

500,000 . . . . . . . . . . . . . . . . . . . . . %3.7 %.1 ●6.8 7.8 8.3 8.5

I,ooo,ooo . . . . . . . . . . . . . . . . . . . . %2.6 %.6 4.8 5.5 5.9 6.0

2,000,000. . . . . . . . . . . . . . . . . . . . W.8 2.6 3.4 3.9 4.2 4.3

3,000,000 . . . . . . . . . . . . . . . . . . . . *1.5 2.1 2.8 3.2 3.4 3.5

4,000,000. . . . . . . . . . . . . . . . . . . . 1.3 1.8 2.4 2.8 2.9 3.0

7,000,000. . . . . . . . . . . . . . . . . . . . 1.0 1.4 1.8 21 2.2 2.3

,intercoume, with how many men did

you have intercourse?” (’l%ephrase

“boys or men” was substituted for

“men” for younger teenagem.)

Poverty-kvel income—This is the

ratio of the total family income to the

poverty-level threshold for a family

of specified size, as published by the

U.S. Bureau of the Census. In the

1988 survey, 1987 poverty-level

threahholds were used (12). In the

1990 survey, 1989 Census Bureau

weighted average thresholds for

householdera were used. The 1989

thresholds used for 1990 data were

$6,451 for one person under age 65,

$8,343 for a family of two also under

age 65, $9,885 for a family of three,

$12,674 for a family of four, up to

$25,480 for a family of nine or more

(13). Thus, if a family of four had an

income of $25,000, their poverty-level

income would be $25,000 divided by

$12,674, or 197 percent. In the 1990

NSFG, family income was not

coIIected from the 327 women 15–17

yeara of age who were interviewed for

the fist time in 1990. In the tables of

this repo% data are not shown for

those women who did not report the

income or poverty level of their

families.

Education-This refers to the

number of years of regular schooling

the woman had completed as of the

date of interview in 1990. In this

report, the following categories are

used: 0-11 years, meaning that the

woman did not complete high schoofi

12 years, meaning that she obtained a

high school diploma or a GED, but

did not complete a full year of

collegq and 13 years or more,

meaning that she completed at least 1

year of college. In all tables

containing this variable, women 15-18

yews of age are excluded from

tabulations by edueation because it

generally takes until at least age 19 to

reach the ‘’13 yeara or more”

category.

Data on behavior change in

1988 and 1990

Asdiscussed in the te~ in 1988

women were asked if they had made

any of seven speciiic changes in

sexual behavior since hearing of

AIDS-including “stopped having sex

with more than one man,” “stopped

having sex with men I don’t know

well,” and five others. In 1990, they

were asked, “Since you tit heard

about AIDS have you changed your

sexual behavior in ANY way?”

Of the women who were asked

these questions in 1988 and 1990,

about 8 percent reported in 1988 that

they had made one or more changes

in their sexual behavior since hearing

of AIDS, but reported in 1990 that

they had never made any changes

since hearing of AtDS. Beeause

“since you first heard about AIDS”

refers to the same time before the

1988 interview, this is a logically

imposal%le answer, but at least three

explanations can be offered for it

●

9

●

Some of these women may have

heard the question incorrectly, and

may be saying that they have made

no FURTHER changes since 1988.

Some may be reporting that the

changes they had made as of 1988

were no longer in effect.

Some may have forgotten some of

the speefic items asked about in

1988, and thus answered “No” in

1990 even though the changes they

reported in 1988 were still in

effect.

Thus, the magnitude of the

changes reported in table 1 for 1990

may be affected by these kinds of

reporting error and by

misunderstanding of the question,

although it is likely that these three

types of reporting errors caned each

other out to some extent. Therefore

the error in the percentages probably

is small.

Cooperating agencies

The 1988 National Survey of

Family Growth and the 1990 NSFG

Telephone Reinterview were jointly

planned and supported by the

National Center for Health Statistics,

the National Institute of Child Health

and Human Development, and the

Office of Population AMrs, all of the

U.S. Department of Herdth and

Human Services.

Symbols

--- Data not available

. . . Category not applicable

Quant’@ zero

0.0 Quantity more than zero but less

than 0.05

z Quantity more than zero but less

than 500 where numbers are

rounded to thousands

* Figure does not meet standard of

reliabilii or precision
16 Advance Data No. 239 ● December 22, 1993

Suggested citation Copyright information National Center for Health StatiWcs

Mosher WD, Pratt WF. AIDS-related behavior All material appearing in this report is in the Director

among women 15-44 years of aga United

States, 1988 and 1990. Advance data from

public domain and may be reproduced or Manning Feinleib, M. D., Dr. P.H.

vital and health ststistiq no 239. Hyattsville, copied without permission; citation as to

source, however, is appreciated. This report Deputy Director

Maryland: National Center for Health

Statistics. 1993. may be reprinted without tirther permission. Jack R. Anderson

U.S. DEPARTMENT OF HEALTH AND

HUMAN SERVICES

c:

BULK RATE

Public Health Service

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PHSiNCHS

Centers for Disease Control and Prevention PERMIT NO. G-2131

National Center for Health Statistics

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Hyattsville, Maryland 20782

OFFICIAL BUSINESS

PENALTY FOR PRIVATE USE, $300

To receive this publication regularly, contact

the National Center for Health Statistics by

calling 301-436-8500

DHHS Publication No. (PHS) 94-1250
Number 240 . March 10, 1994

Advance

Data

FromVi and Health stati~”esofthe CENTERS FOR DISEASE CONl130LAND PREVENTION/National Centerfor Health Statistics

Office Visits to Dermatologists:

National Ambulatory Medical Care Survey,

United States, 1989-90

by Cheryl Nelson, Division of Health Care Statistics

Introduction

From January 1989 to December

1990, an estimated 698 million visits

were made to office-based physicians in

the United States. Vkiits to physicians

specializing in dermatology accounted

for 2$ million (4 percent) of these visits

(tabIe 1). T’hisreport descriies visits to

dermatologists over this 2-year period

according to data collected in the 1989

and 1990 National Ambulatory Medical

Care Survey (NAMCS). NAMCS, a

year-long sample survey of the Nation’s

non-Federal office-based physicians, is

conducted by the Centers for Disease

Control and Prevention, National Center

for Health Statistics, Division of Health

Care Statistics. Other NAMCS reports

or reports utilizing NAMCS data on

office visits to dermatologists have been

published (l–3), as have summaries of

general findings from the 1989 NAMCS

(4) and 1990 NAMCS (5).

The 1989 and 1990 National

Ambulatory Medical Care Surveys

shared identical survey instruments,

definitions, and procedures. The

resulting 2 years of data have been

combined to provide more reliable

estimates, and the reader should note

that the estimates, percent distributions,

and rates presented in this report reflect

average annual estimates based on

combined 1989 and 1990 data. The

Patient Record, the survey instrument

used by participating physicians to

record information about their patients’

office visits, is shown in figure 1.

GeneraI findings

Since 1975 the percent of visits and

the visit rate to dermatologists have not

changed significantly. In 1975-76, visits

to dermatologists accounted for

3 percent of all visits to all physicians,

with a visit rate of 9 visits per 100

persons. In 1985 visits to dermatologists

represented 4 percent of all visits, and

the visit rate was 10 visits per 100

persons (6).

Patient characteristics

Fifty-eight percent of the patients

seeking care from dermatologists were

femrde, significantly more than male

patients (42 percent) (table 2). Thirtytwo percent of the visits were made by

patients between the ages of 25 and 44

years, and 16 percent were made by

patients 15–24 years of age. In 1975–76,

the age proille of visits to

dermatologists was quite different (2):

During that period, patients under 25

years of age accounted for 40 percent of

visits to dermatologists, compared with

24 percent in 1989-90. As expected, in

private office-based settings and with

other specialties, there were more visits

to dermatologists by white and nonHispanic persons than visits by otherrace and Hispanic persons. Ninety-one

percent of the visits to dermatologists

were made by white patients, a higher

percent than for “all other” specialties

(85 percent). The visit rate was highest

for patients 65 years of age and older

(17 visits per 100 persons) and lowest

for patients under 15 years of age

(4 visits per 100 persons) and for black

patients (3 visits per 100 persons).

Table 3 shows that the major expected

sources of payment were “selfpaymen$” accounting for 37 percent of

the visits, and “Blue Cross/Blue

Shiel&” accounting for 16 percent.

The reasons patients visit

dermatologists are shown in table 4.

Seventeen percent of the visits were for

acne or pimples, and another 12 percent

were for skin rash. The 15 most

# mms.o

&

$

%

-#

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Public Health Service

~ Centers for Disease Control and Prevention %

%$,

>+4% National Center for Health Statistics

~f!mm%i%i%%i%

CK
2— ..Advance ---- ----------- Data No. 240 -. -–..● March .. . . . . 10.1994 . - , ----

A8sumnw of Con fkkntidbv - AN mformatlon wtdch would pwmtt #dent!flcatron of on Departmem of Heallh and Human Sew,cm

mdwldual, a practice. w an establishment wdl be held c.mhdentml. WI!I be used only by Center9 for Disease Control

pemons engaged In and for the purposes of the survey and will not be dmclosed or releasad Public Heal!h Sewice

to otlmr persons m sod for any other purpose. Nalicmal Cenmf 10, Health Stat#stlcs B

I.DATE OFVISIT PATlENT RECORD OMB No. 0920-0234

~ NATIONAL AMBULATORY MEDICAL CARE SURVEY

Expires 8-31 .S9

iFW} 6105B

2.21P CODE 4mSEX 5.CO~R OR 6.13HNICITY 7m~h:::~~NJR~[Sl OF PAYMENT 8 WAS PATIENT

“REFERREDFOR

1 ❑ WHITE EL(JE CROSS/

THISVISIT BY

I ❑ =LF.PAY4 ❑ BLUE SHfELD

1 ❑ FEMALE

7 ❑ NO CHARGE

, ❑ fili~Jlc ANOTHER

3mDATEoFslRTH 2 ❑ SLACK PHYSICIAN?

ASIAN/PACIRC 2 ❑ MEDP=ARE 5 ❑ INSURANCE

3 ❑ ISLANDER

‘mm commercial 8 ❑ ;’}/

~ 2 ❑ ‘“”

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lD YES 2C]N0

AMSRfCAN lNDfAN/

4 ❑ ESKIMO/ALEUT

FFIE.PAID PLAN

3 ❑ MEOICAID 6 ❑ HMO/lPA/PPO

9 PATlENT’SCOMPLAINT, SYMPTOMS), OROTHER

● REASONISI FORTHIS VISIT [In patienlk own words]

10m PHYSICIAN’S DIAGNOSES I I HAVEYOU SEEN—

“PATIENTSEFORE?

a,MOST lMFt3RTANT a, PRINCIPAL OIAGNOSIS/mOBLEM ASSOCIATE WITH ITEM 9a.

10 YES 2HN0

— + — IF YES. FOR THE CONDITION

b. OTHER b OTHER SIGNIFICANT CURRENT DIAGNOSES IN ITEM 10.3?

lD YES 2DN0

. .—. .—

12 “F;;:::;:::::::Y::d:FWcEs 13“ ~~h~~s~y~;~!~!;?rovidd]

14. Nolom#crc:03;;mm1 ❑ NONE 7 ❑ BLOOD PRESSURE CHECK 13 ❑ ORAL GLuCOSE TOL, 1 ❑ NONE 1 ❑ NONE

2 ❑ PAP TEST B ❑ URINALYSIS 14 ❑ CHOLESTEROL MEASURE 2 ❑ WEIGHT REDUCTION 2 ❑ PSYCHOTHERAPY

3 ❑ PELVIC EXAM S ❑ CHEST X RAY 15 ❑ HIV SEROLOGY 3 ❑ CHOLESTEROL REOUCTION 3 ❑ CORRECTIVE LENSES

4 ❑ wImsT pALPATION 10 ❑ DIGITAL flECTAL EXAM 16 ❑ OIWER BLOOD TEST 4 ❑ SMDKING CESSATION 4 ❑ AMBULATORY SURGERY

5 ❑ MAMMOGRAM 5 ❑ HIV TRANSMISSION 5 ❑ PHYSIOTHERAPY

11 ❑ PROCT/SIGM0100SCOPY I 7 ❑ 07HER IspPc,J,./

6 ❑ VISUAL ACUITY

6 ❑ BREAST SELF.EXAM 6 ❑ OTHER L%xrflv)

12 ❑ STOOL BLOOD EXAM

7 ❑ OTHER

.—. ... ——— —

Is- MEWA~NTHERAPY[Rwotiullnewormntinu&m&icotiomordcredorprovtdedotthk visit. Usethesame I em ~:~:WO;::;Hl+l,VISW I 7n::~~on

brandnume orgsnctic nameentsrdon any Rxoroffim medical mctwd. Include immunizing anddsssnsimng agsnLs.J

Vlsrr

IF NONE. CHECK HERE ❑ a. HEW b, FOR OX 1 ❑ NO FOLLOW.UP PLANNED Fime

MEGtCATfON? IN ITEM 10z? actually

YES MO YES NO 2 ❑ RETURN AT SPECIFIED TIME spent with

physician]

1 _____ ._ ——— In 20 10 20 3 ❑ RETURN IF NEEDEO, P,R,N,

TELEPHONE FOLLOW UP

1CI2CI102CI 4 ❑ PLANNED 2, . . . ..__. _ —.. . . . .

3

5 ❑ ‘5 FERRED TO OTHER PHYSICIAN

— .——. — —.. — ‘cl 20 In 20

6 ❑ ~ETu~Tu&~TO REFERRING

4 __ -— .—. 10 ‘o 10 20

7 ❑ AOMIT TO HOSPITAL Minutes

5, 10201020 6 n OTHER ISP?CILVI

Figure 1. Patient Reeord form

frequently mentioned reasons

represented 77 percent of all reasons

given. In 1975–76, 23 percent of the

visits to dermatologists were for acne

(2), compared with 16 percent in

1989-90. NAMCS data show that in

1975–76 and 1980-81 (7) about

24 percent of visits to dermatologists

were for acne complaints, compared

with 19 percent in 1985 (6) and

16 percent in 1989-90. Concurrently,

acne complaints resulting in visits to

general and family practitioners and

pediatricians rose from 3 pereent in

198&81 to 10 percent in 1989-90.

NAMCS data suggest that the decline in

acme complaints to dermatologists could

be due to a shift in specialties sought by

patients with acne complaints-the shift

from dermatologists to other physicians.

Table 5 shows that Diseases of the

sebaceous glands was the diagnosis

most often made (21 percent). Other top

diagnoses were Other derrnatoses

(12 pereent), Contact dermatoses and

other eczema (9 percent), Other diseases

due to viruses and chlamydiae

(8 percent), and Benign neoplasm of the

skin (6 percent). These top five

diagnoses accounted for more than half

(55 pereent) of all diagnoses madle

during visits to dermatologists.

The referral status of dermatology

visits in the 1989–90 NAMCS did not

dtier significantly from the referral

status in the 1975–76 NAIWS (2). As
Advance Data No. 240 ● March 10,1994 3

with other specialties, there were more

nonreferral visits to dermatologists

(91 percent) than referral visits

(9 percent). Table 6 also shows returning

patients-those visits characterized as an

“old patient” returning for treatment of

an “old problem’’—accounted for more

than half (60 percent) of the visits.

Table 1. Annual number, percent distribution, and rate of office visits by physician

speeiaity averaged over a 2-year period: United States, 1989-90

Number oi W#ts

Visitain Percerrt per I(U)

Physi”oian.s@ckMy ttwussnds distribution PWSorrs‘

Allvisits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 696,653 100.0 265

Generalandfamilypraotice . . . . . . . . . . . . . . . . . . .

Intefnalmedicine. . . . . . . . . . . . . . . . . . . . . . . . . .

Pediatrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Obstetricsandgynecology. . . . . . . . . . . . . . . . . . . .

Ophthalmology.. . . . . . . . . . . . . . . . . . . . . . . . . .

Orthopedicsurgery. . . . . . . . . . . . . . . . . . . . . . . . .

Dermatology. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Generalaurgery . . . . . . . . . . . . . . . . . . . . . . . . . .

Psychiatry. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Otolaryngology. . . . . . . . . . . . . . . . . . . . . . . . . . .

Cardiovasoulardisesse. . . . . . . . . . . . . . . . . . . . . .

Urologioalsurgery. . . . . . . . . . . . . . . . . . . . . . . . .

Neurolog y . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Otherspecialties . . . . . . . . . . . . . . . . . . . . . . . . . .

208,044

87,719

64,279

58,812

41,302

34,033

25,164

23,691

18,780

18,257

11,040

9,652

6,167

71,603

29.8

12.5

12.1

8.6

5.9

4.9

3.6

3.4

2.7

2.4

1.6

1.4

0.9

10.2

35

36

34

24

17

14

10

10

8

7

5

4

3

29

Therapy

Therapeutic services ordered or

provided by dermatologists are shownin

table 7. The vast majority of the visits

(80 percent) did not include any

diagnostic services. When diagnostic

services are examined for “all visits to

rdl specialties,’ ‘an averageof two

diagnostic services were usually ordered

or provided for patients. Obstetricians

and gynecologists were the exception;

they ordered or provided their patients

an average ofthree diagnostic services.

Reasons for such a disparity between

dermatologists and other specialists

could bedueto the choicesof

diagnostic services listed onthe Patient

Recordform(figure l,item 12).

However, the NAMCS Patient Record

form provides another optio~ the

“other/specify’’checkbox, for

dermatologists or for any specialty

providing a diagnostic service not listed

with a check box. The data show that,

when diagnostic services were ordered

orprovided by dermatologists, itwas

usuallyfo ronlyoneservice, and most

often thesemice selected was “other/

specify. ” Seventeen percent of visits to

dermatologists utilized “other/specify”

for diagnostic services. In 1989–90,

“other/specify” was selected in

diagnostic services in an average of 176

million visits (25 percent) to all

specialties. 0nly2percent of these 176

million visits were to dermatologists,

compared with 25 percent to general and

family practitioners and about 11 percent

each to physicians specializing in

pediatrics, ophthalmology, internal

medicine, and obstetrics and

gynecology.

Approximately 35 percent of the

visits to dermatologists involved no

administration of drugs. In about

65 percent of the visits, dermatologists

prescribed or provided drugs for

treatment, Multiple drugs were

‘Sas2rdOnU.S.SuresuoftheCenwseatirnstesOfrheciWkwrmi@Wh@a“sd PoPulsthoftlw Unit@Sra2esasG+Julyl,

19&9,sndJuly 1, 19S0, avsrs9edovwthe 2-yesr Pwiorl.

Tabie 2. Annual number, percent distribution, and rate of office visits to dannetoiogiste

by patient’s SSL age, race, and ethnicity, averaged over a 2-yesr periotk United states,

1969-90

Number of waits ~m

Sex, age, raoe, and athniciiy mmancls LiE%%n 4%X3

AIIVMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25,164 lml.o 10

sax

Female . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Male . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

14,657

10,507

56.2

41.8

12

9

Age

Lessthan 15years . . . . . . . . . . . . . . . . . . . . . . . .

15-24 years. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

25-44 years. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

45-64 years. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

&74yeare . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

75years andover . . . . . . . . . . . . . . . . . . . . . . . . .

2,210

3,353

8,126

5,623

3,069

1,883

8.8

15.7

32.3

23.1

12.2

7.9

4

11

10

13

17

17

Race*

While . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Black . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Other ?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

22,874

1,015

816

8Q.9

4.0

3.2

11

3

10

Ethnicily4

I-l@anic . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Non-Hispanic. . . . . . . . . . . . . . . . . . . . . . . . . . . .

637

23,266

3.5

92.5

. . .

---

‘WmU.S.WrmuofW_*@dtitih ~ PC$JUkdbnofthsUr@xlStarssssofJutyl,

18S9,srrdJu&l,18S0, avs4w#41w2rthe2-y2ar F-SIW.

%amwssuflknown or2459,000@srr2 rscds.

%rclude2A.4srrerMPaciilolslsrldward AnWican Mian, Esrrimo,andAbut

4Ethrrii was unbwwn CMI,O1l,OCO@isnt rscord%

administered in 35percent of those dermatological agents (55 percent).

visits, andinthe other 30percenta Retin-A (8 percent) was the drug most

single drug was administered, Table 8 often mentioned on the patient’s record

shows that 57percent of thedmgs (table 9). The typea of drugs

administered by dermatologists were administered most often were acne

classified as skin/mucus-membrane products, antibiotics, and corticosteroids.

drugs with most of these classified as Erythromycin (8 percent), tretinoin
4 Advance Data No. 240 ● March 10,1994

(8 percent), and benzoyl peroxide

(6 percent) were the three generic

substances most often contained in the

drugs.

Disposition and duration

Table 10 shows that patients visiting

dermatologists were most often told to

“return at specified time” (65 percent).

“Return at specified time” was also the

disposition most often given by other

specialties (table 11). The mean duration

of visits to dermatologists was

13 minutes, compared with 22 minutes

for cardiovascular disease specialists,

28 minutes for neurologists, and

42 minutes for psychiatrists.

References

1. Stem RS, Johnson ~ DeLozier J.

Utilization of physician sewices for

derrnatologic complaints the United

States, 1974. Arch Dermatol, 113(8):

10624, August 1977.

2. Ezzati T. Office visits to

3.

dermatologists: National Ambulatory

Medicrd Care Survey, United States,

1975-76. Advance data from vital

and health statisti~, no 37.

Hyattsville, Maryland National

Center for Health Statistics. 1978.

Stem RS, Gardocki GJ. Office-based

care of derrnatologic disease. J Am

Acad Derrnatol, 14286-93,

Februsry 1986.

4. Schappert SM. National Ambulatory

Medical Care Survey 1989

summary. National Center for Health

Statistics. Vital and Health Stat

13(110). 1992.

5. Schappert SM. National Ambulatory

Medical Care Survey: 1990

summary. Advance data from vitrd

and health statistics; no 213.

Hyattsville, Marylrmd: National

Center for Health Statistics. 1992.

6. Unpublished datx Nationsl

Ambulatory Medical Care Survey,

United States, 1985. Hyattsville,

Maryland: National Center for Health

Statistics.

7. Unpublished data National

Ambulatory Medical Care Survey,

United States, 1980-81. Hyattsville,

Maryland: National Center for Health

Statistics.

Table 3. Annual number and percent distribution of office visits to dermatologiata by

patient’s expected source of payment, aversged over a 2-year period: United !Nr@s,

1989-90

Number of vi.sik Peroent

Expected source of payment in thousands’ distribution

Allvisita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25,164 100.0

Self-pay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Mediesre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Medicaid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Blue Cross/Blue Shield . . . . . . . . . . . . . . . . . . . . . . . . . . .

Other commercial insurance . . . . . . . . . . . . . . . . . . . . . . . .

HMO/prepaid plan2. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Nocharge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Unknown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

9,265

4,281

1,036

4,145

4,985

3,704

669

816

364

36.8

17.0

4.1

16.5

19.8

14.7

2.6

3.2

1.4

‘Numbersmaynotaddto totalbecause more than one exp%ctad source of payment may be repatisd per visit.

‘HMO is healthmaintensnmorgan”kation.

Table 4. Annual number and percent distribution of office visits to derrnatologista by

patient’s most frequently mentioned principal reason for visit, averaged over a 2-year

period: United Ststes, 1989-90

Number of visits Pereent

Reason for visit and RVC code~ in thousands distribution

Allvisita . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25,164 100.0

Acneor pimples . . . . . . . . . . . . . . . . . . . . . . . . . ...1630

SI(inraah . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...1860

Skin lesion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...1865

Warta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...1850

Oismloration or pigmentation . . . . . . . . . . . . . . . . . ...1835

Other symptoms referable to skin. . . . . . . . . . . . . . . ...1860

Molas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...1645

Other skin growths . . . . . . . . . . . . . . . . . . . . . . . . ...1855

Symptoma raferableto hairandsealp. . . . . . . . . . . . ...1890

Skin inflations . . . . . . . . . . . . . . . . . . . . . . . . . . . ...1870

Cancer, skin andsubeutanaous tiaaues. . . . . . . . . . . ...2110

Ofherskin diseases . . . . . . . . . . . . . . . . . . . . . . . ...2825

Psoriasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...2820

Swelling of skin . . . . . . . . . . . . . . . . . . . . . . . . . . ...1875

Eezemaand derrmatiiis . . . . . . . . . . . . . . . . . . . . . ...2815

4,181

2,975

1,698

1,510

1,392

1,151

1,085

1,028

834

767

643

640

593

516

451

16.6

11.8

6.7

6.0

5.5

4.6

4.2

4.1

3.3

3.0

2.6

2.5

2.4

2.1

1.6

'Ssaedon ARe8son fOrWsitCksifir@onrOr Ambu/atOiyCsrs(Fl VC) (8).

8. Schneider D, Appleton L, McLemore

T. A reason for visit classification for

ambulatory care. National Center for

Health Statistics. VW and Health

Stat 2(78). 1979.

9. Public Health Service and Health

Care Financing Administration.

International Classi&.ation of

Diseases, 9th Revision, Clinical

Modification. WasKmgton, D.C.:

Public Health Service. 1980.

10. Food and Drug Administration.

National Drug Code directory, 1985

edition. Washington, D.C.: Public

Health Sewice. 1985.
Advance Data No. 240. March10,1994 5

Table 5. Annual number and percent distribution of office

visits to dermatologist by the 20 most frequently mentioned

principal diagnoses, averaged over a 2-year period: United

States, 1969-90

Table 7. Annual number end percent distribution of office visits

to dermatologists by number of diagnostic services ordered or

provided, type of vlsttj and number of medications provided to

patients, averaged over a 2-yesr period: United States, 1969-90

Number of

vr”sitain Percent

PrirrcI@I diagnosis and ICD-9-CM code’ tfwuaarrda distribufiin

Allvisits . . . . . . . . . . . . . . . . . . . . . . . . . .

Diseasesof sebamus glands . . . . . . . . ...706

Othardermatoses . . . . . . . . . . . . . . . ...702

Ckmtaofdennatosesand other eczema . . ...692

Other diseasesdue to virusesand

chlamydiae. . . . . . . . . . . . . . . . . . . . ...78

Bengnneoplasm of skin . . . . . . . . . . . ...216

Ofher malignantneoplasmof skin ., . . . ...173

Psoriasisand similardisordera . . . . . . . ...686

Disease of hairand hairfolliiles . . . . . . ...704

Erythematouscondtions . . . . . . . . . . . ...695

Other hypertrophicand atrophiccondtiions

Ofekin. . . . . . . . . . . . . . . . . . . . . . ...701

Otherdieordersof skin and subcutaneous

tissue . . . . . . . . . . . . . . . . . . . . . . ...709

E@hemata.squamousdennatosis. . . . . . ...690

Dermatophytosis. . . . . . . . . . . . . . . . ...110

Atopicdermatitisand relatedcondtions. . ...691

Pruritusand relatedcandtions . . . . . . . ...686

Malignantneoplasmwithoutspecificationof

site. . . . . . . . . . . . . . . . . . . . . . . . ...199

Urticaria . . . . . . . . . . . . . . . . . . . . . ...706

Diaesea ofoepillanes . . . . . . . . . . . . . ...446

Varicoseveins of lower extremities. . . . . ...454

Disorderaofsweatglands . . . . . . . . . . . ..7O5

25,164 100.0

5,251 20.9

2,942 11.7

2,164 8.6

1,968 7.8

1,436 5.7

1,354 5.4

1,300 5.2

965 3.8

679 2.7

647 2.6

467 1.9

453 1.8

4.5Q 1.8

362 1.4

327 1.3

247 1.0

240 1.0

181 0.7

173 0.7

160 0.6

1SassdontheIntemstionsl C&ssh5cstk#r ofDisaseas,9th Rsdskm, ClinicalMcdirlcsdon

(ICD-9-CM)(9).

Table 6. Annual number and percent distribution of office visits

to dermatologists by patient’s referral status and visit status,

averaged over a 2-year period: United States, 1959-80

Number of

visits in Percent

Referral status and visit status thouaan& disbfbuhrr

Allvisits . . . . . . . . . . . . . . . . . . . . . . . . . . 26,1s4 100.0

Patient’sreferralstatus

Referred by otherphysician. . . . . . . . . . . . . . 2,261 9.0

Notreferred . . . . . . . . . . . . . . . . . . . . . . . . 22,803 91.0

Patient’svisitstatus

Newpatient . . . . . . . . . . . . . . . . . . . . . . . . 6,663 26.5

Oldpatienf/new problem . . . . . . . . . . . . . . . . 3,421 13.6

Oldpatianf/oldproblem. . . . . . . . . . . . . . . . . 15,020 52.9

New-pmbIemvisita. . . . . . . . . . . . . . . . . . . . 10,064 40.1

Number of

w.sitsin Percent

Diagnoafh aam.cas and medication therapy’ tfrousands distribution

Nlvisiti . . . . . . . . . . . . . . . . . . . . . . . . 25,164 100.0

Numberof diagnosticsemkaa

orderedor provided

None . . . . . . . . . . . . . . . . . . . . . . . . . . 20,173 60.2

1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4,752 18.9

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226 0.9

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . *1o 0.0

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . WI 0.0

5ormore . . . . . . . . . . . . . . . . . . . . . . .

TW ofvisit

Drugvisi& . . . . . . . . . . . . . . . . . . . . . . 16,312 64.8

!fisitswithou tmentio nofmadicstio n,. . . . . . 8,852 35.2

Number of mediins

presaibad or prw.dad

1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7,646 30.4

2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4,631 18.4

3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2,512 10.0

4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1,146 4.6

5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378 1.5

‘IIICIU*presaf@iorI d- omr~ pmpm$em,bnrnunizirwawWS,daseneiL&iW

agents,#c.

%sik3atwtlidl.or nre&u!JswFxepwi dsdcf~bythaph@ckln.
6 Advance Data No. 240 ● March 10,1994

Table 8. Annual number and percent distribution of drug

mentions at office visits to dermatologists by the most frequent

therapeutic classification, averaged over a 2-year period:

United States, 1988-80

Table 9. Annual number, percent distribution, and therapeutic

classification of drugs most frequently mentioned at office visits

to dermatologists, by entry name and generic substances,

averaged over a 2-year period: United states, 1988-90

Number of

merrfr”ons

in Percent

Therapeutic claasir%ation and NDC code’ thousends distribution

All drug mentions . . . . . . . . . . . . . . . . . . . . . . .

Therapeutic classification and NDC code

Anesthetic druga . . . . . . . . . . . . . . . . . . ...01

Local anesthetics . . . . . . . . . . . . . . . ...0117

Medical gasas . . . . . . . . . . . . . . . . . ...0120

Antimicrobial agenta . . . . . . . . . . . . . . . . ...03

Penicillins . . . . . . . . . . . . . . . . . . . . ...0346

Cephalmsporins . . . . . . . . . . . . . . . . . ..0347

Erythromycins and Iincoaamides. . . . . . . . .034S

Tbtraoyclinas . . . . . . . . . . . . . . . . . . ...0350

Miscellaneous antibacterial agents. . . . . ...0355

Antifungal agenta for systemic mycosas . ...0356

Antiviral agents . . . . . . . . . . . . . . . . ...0366

Central nervous syatamdruga . . . . . . . . . . . ..o6

Sedatives and hypnotics. . . . . . . . . . . ...0626

Hormones and agents affading hormonat

mechanisms . . . . . . . . . . . . . . . . . . . . ...10

Adranal corticoatemids. . . . . . . . . . . . ...1032

Skin/mucous membrane . . . . . . . . . . . . . ...12

Derrnatologics . . . . . . . . . . . . . . . . . ...1265

Ophthalmic drugs . . . . . . . . . . . . . . . . . ...15

Ocular anti-infective and enti-inftammetory

agents . . . . . . . . . . . . . . . . . . . . . ...1566

Respirato~-traot drugs . . . . . . . . . . . . . . ...19

Bronchodilatora, antiaathmetics. . . . . . . ...1940

Antihistamines . . . . . . . . . . . . . . . . . ...1944

Unclassified/miscellaneous. . . . . . . . . . . . ...20

30,905

732

167

545

5,111

262

454

1,249

2,102

356

466

170

550

4S5

1,516

1,448

17,647

17,138

851

301

732

2s4

431

3,374

100.0

2.4

0.6

1.8

16.5

0.9

1.5

4.0

6.8

1.2

1.6

0.6

1.8

1.6

4.9

4.7

57.7

55.5

1.1

1.0

2.4

0.9

1.4

10.9

‘Baaed on the standard drug clssaifkdon used in ths IVafionsJ Drug Code Dkedcfy (WC),

1985 edition (10).

Number of

Errfry name and mentions Percent Therapeutic

generic substances in thousands distribution use

All drug mentions . . . . . . . . . . . .

Entry name of drug’

Retin-A . . . . . . . . . . . . . . . . .

Tetracycline . . . . . . . . . . . . . . .

Lidax . . . . . . . . . . . . . . . . . . .

Kenalog . . . . . . . . . . . . . . . . .

Minooin . . . . . . . . . . . . . . . . . .

Generic substance

Erythromycin . . . . . . . . . . . . . .

Tretinoin . . . . . . . . . . . . . . . . .

Benzoyl peroxide. . . . . . . . . . . .

Hydrocortisone . . . . . . . . . . . . .

Tnamcinolone . . . . . . . . . . . . . .

Tetracycline . . . . . . . . . . . . . . .

Betemethasone . . . . . . . . . . . . .

Fluocinonide . . . . . . . . . . . . . . .

Clindamycin . . . . . . . . . . . . . . .

2,373

603

795

773

662

2,564

2,373

1,693

1,564

1,505

1,464

SK13

601

797

100.0

7.7

2.6

2.6

2.5

2.1

8.3

7.7

6.1

5.1

4.9

4.8

2.9

2.6

2.6

Acne product

Antibiotic

CorIicoataroid

Colticosteroid

Antibwtic

Antibiotic

Acne product

Acne product

Catticoaternid

Corticosteroid

Antibiotic

Corticostemid

Acne product

‘Trade or genericnameusedbyphysloianon lxeacription or medical recurds.

Table 10. Annual number and percent distribution of office visits

to dermatologists by disposition of visits, averaged over a 2-year

period: United States, 1989-90

Number of

mentions Percent

Disposition in thousands distribution’

Allvisits . . . . . . . . . . . . . . . . . . . . . . 25,184 100.0

No followup . . . . . . . . . . . . . . . . . . . .

Return atspecified time . . . . . . . . . . . . .

Retumif neaded . . . . . . . . . . . . . . . . .

Telephone followup . . . . . . . . . . . . . . .

Refer to other physician . . . . . . . . . . . .

Return toother physician. . . . . . . . . . . .

Admit tohospital . . . . . . . . . . . . . . . . .

Other . . . . . . . . . . . . . . . . . . . . . . . .

2,635

16,317

5,085

807

171

*5 I

%

11.3

64.8

20.2

3.2

0.7

0.2

0.4

‘Numbers may not add to totals because more lhsn one disposition maybe reported par

visit

Table 11. Annual number and percent distribution of office visits

to dermatologists by duration of vls~ averaged over a 2-year

period: United States, 1989-90

Number of

visits Parcent

Duration of visits in fhousands distribution

Allvisits . . . . . . . . . . . . . . . . . . . . . .

Ominutae’ . . . . . . . . . . . . . . . . . . . . .

l-5minutee . . . . . . . . . . . . . . . . . . . .

6-10 minutes . . . . . . . . . . . . . . . . . . .

11-15 minules . . . . . . . . . . . . . . . . . .

16-30 minutes . . . . . . . . . . . . . . . . . .

31-60 minutes . . . . . . . . . . . . . . . . . .

Morethen 60 minutes . . . . . . . . . . . . . .

25,164

126

4,311

9,456

6,663

3,935

636

%3

100.0

0.5

17.1

37.6

26.5

15.6

2.5

0.1

‘Visits in which there wss no fscMo-face contact belwsen patient and physicisn.
Advance Data No. 240. March 10,1994 7

Technical notes

Sourceof dataand sample

design

The information presented in this

report is based on data collected by

means of the National Ambulatory

Medical Care Survey (NAMCS) over

the 2-year period 1989-90. The target

universe of NAMCS includes office

visits made in the United States by

ambulatory patients to nonfederally

employed physicians who are principally

engaged in office practice, but not in the

specialties of anesthesiology, pathology,

or radiology. Telephone contacts and

nonoffice visits are excluded.

A multistage probability sample

design is used in NAMCS, involving

primary sampling units (PSU’S),

physician practices within PSU’S,

physicians stratified into 15 specialty

groups, and patient visits within

physician practices. The PSU’S are

counties, groups of counties, county

equivalents (such as parishes or

independent cities), and towns and

townships (for some PSU’S in New

England). For 1989 and 1990, a sample

of 2,535 and 3,063 non-Federal

ollice-based physicians was selected

from master files maintained by the

American Medical Association and the

American Osteopathic Association. In

1989, 114 of these sample physicians

specialized in dermatolo~, in 1990, 135

were dermatologists. Sample physicians

were screened at the time of induction

into the survey to ensure their eligibility

for participation. In 1989 and 1990,

1,927 and 2,269 physicians were eligible

to participate, and for both years

74 percent responded to the survey,

resulting in 1,421 respondents in 1989

and 1,684 in 1990. Of the 1,927 eligi%le

physicians in 1989, 97 were

dermatologists and 78 of those

responded to the survey— an 80-percent

response rate. In 1990 there were 113

eligible dermatologists and a response

from 79— a 70-percent response rate.

Sample physicians were asked to

complete patient records (figure 1) for a

systematic random sample of office

visits occurring during a randomly

assigned l-week reporting period.

Responding physicians completed

38,384 patient records in 1989,

and 43,469 patient records in 1990.

Dermatologists completed 2,774 forms

in 1989, and 2,530 in 1990.

Characteristics of the physician’s

practice, such as primary specialty

and type of practice, were obtained

from the physicians during an

induction interview. The U.S. Bureau

of the Census, Housing Surveys

Branch, was responsible for the

surve y’s data collection. Processing

operations and medical coding were

performed by the National Center for

Health Statistics, Health Care Survey

Section, Research Triangle Park

North Carolina.

The 1989 and 1990 NAMCS’S

were identical in terms of survey

instmments, definitions, and

procedures. The resulting 2 years of

data have been combined to provide

more reliable estimates. AN estimates,

percent distributions, and rates, unless

otherwise noted, reflect 1989 and

1990 data that were averaged over the

2-year period.

Samplingerrors

The standard error is primarily a

measure of the sampling variability that

occurs by chance when only a sample,

rather than an entire universe, is

surveyed. The relative standard error of

an estimate is obtained by dividing the

standard error by the estimate itself.

The result is then expressed as a percent

of the estimate.

Readers wishing to utilize these

tables should note that they refer to

combined years of data rather than

average annual estimates. Average

anmd estimates must be converted back

to 2-year totals for use with these tables.

Relative standard errors for

estimates based on all physician

specialties and on dermatologists are

shown in tables I and 11. Standard

errors for estimated percents of visits

and drug mentions are shown in

tables 111and IV.

Alternatively, relative standard

errors for aggregate estimates may be

calculated using the following general

formula, where x is the aggregate of

interest in thousands, and A and B are

Table1.Relativestandarderror for

eatlmatednumbsrof officevisits

by selectedphysicianspecialties:

NationalAmbulatoryMedicalCare

Survey,1989-90

.Ei3tinratad

number of ofiea Physician specialty

visits in

thousands All Dermatology

Relative standard error in

percent

100 . . . . . . . . . 72.7 31.1

Ii O . . . . . . . . . 69.7 30.0

200. . . . . . . . . 51.5 23.4

593 . . . . . . . . . 30.0 16.3

1,000 . . . . . . . . 23.2 14.4

2,000 . . . . . . . . 16.5 12.9

5,003 . . . . . . . . 10.7 11.9

Io,ooo . . . . . . . 7.9 11.5

20,000 . . . . . . . 6.0 11.3

50,000 . . . . . . . 4.5 11.2

Ioo,ooo . . . . . . 3.9 11.2

5oo,ooe . . . . . . 3.3 11.1

750,000 . . . . . . 3.2 11.1

1,000,000 . . . . . 3.2 11.1

NOIEThasmarest rassblaas3me&ilrvisits toaggragstsd

aPa@mak5ew@JmEalkmaa Ilekrwlfri sliglrehsvs

areMva2Sandudarorgaatsr Uran30pemmtandare

~~~4-ti ~ mmb *mats iS

qOf~Of**4KP@S **0f5millh

---~ hasaralstW stamlwdsnorof

11.9~aaatmdmd wrwd5@5,~vktte (ll.9

perwIa0f51r#sc@.

TableIL Relativestandarderror for

estimatednumberof drug mentions

by selaetedphysicianspeeialtles:

NationalAmbulatoryMedicalCara

Suwey, 1989%0

Estimated

number of drug Physioian apeoialty

mentions in

thousands All Dermatology

100 . . . . . . . .

155 . . . . . . . .

200 . . . . . . . .

500 . . . . . . . .

922 . . . . . . . .

2,000 . . . . . . .

5,000 . . . . . . .

10,BOO......

20,000 . . . . . .

m,eoo. . . . . .

100,000 . . . . .

750,000 . . . . .

I,ooqooo. . . .

Relative standard error in

percent

90.3 36.1

728 30.0

63.9 27.0

40.6 19.7

30.0 16.9

20.6 14.7

13.4 13.5

9.9 13.1

7.5 12.9

5.7 12.8

4.9 12.7

4.1 12.7

4.1 12.7

NOl?ZTheemaMast ralWeasimata ofd~mardkosto

qxw?xadaP@@li=b =wJOdrugman@U.Mmatas

babwlhisllgua havaaraktive simdantwror graaterthen

33percentaml Medeenwd urrralWaby NCHSstandWs

l%d~nwntkmsty darmaW@ets, b srnslbst mlieble

estimate is 155,00U drug n’mtiom.

-~ ~- Of*A awmrgate e%mats of 10 milbn

w~ by dsrmatoi@sts has a relath standard

@M,fJte of 13.1 pSMSIM or a stsIxIe.rd error of 1,310,000 drug

MenMls (13.1 p3rwnt of 10 nwiorl).
8 Advance Data No. 240. March10,1994

the appropriate coefficients from

table V.

RSE(X)=

T

A+:-lOO

Similarly, relative standard errors

for percent maybe calculated using the

following general formul% where p is

the percent of interest and x is the

denominator of the percent in thousands,

using the appropriate coefficient from

table V.

r

B “ (1-p)

RSE(p) = ~ -100

Adjustments for nonresponse

Estimates from NAMCS data were

adjusted to account for sample

physicians who were in scope but did

not participate in the study. This

adjustment was calculated to minimize

the impact of response on tlnsl estimates

by imputing to nonresponding

physicians data horn visits to similar

physicians. For this purpose, physicians

were judged similar if they had the

same specialty designation and practiced

in the same PSU.

Test of significance and

rounding

In this repo% the determination of

statistical significance is based on a

two-sided t-test. The Bonferroni

inequality was used to establish the

critical value for statistically significant

differences. Terms relating to

differences, such as “greater than” or

“less thq” indicate that the difference

is statistically signifkant. A lack of

comment regarding the di.tTerence

between any two estimates does not

mean that the difference was tested and

found to be not significant.

In the tables, all estimates have

been rounded to the nearest thousand.

Consequently, estimates will not always

add to totals. Rates end percents were

calculated from original unrounded

figures and do not necessarily agree

with percents calculated from rounded

data.

Table Ill. Standard errors for percents of estimated number of office visits to

dermatologist= National Ambulatory Madieel Care Survey, 1989-90

Estimated pereant

Base of percent visits in thousands lor89 5or86 10 or S0 20 or 80 30 or 70 50

Standard emore in percentage points

100 . . . . . . . . . . . . . . . . . . . . . . . . 2.9 6.3 8.7 11.6 13.3 14.5

200 . . . . . . . . . . . . . . . . . . . . . . . . 2.0 4.5 6.2 6.2 9.4 10.3

500 . . . . . . . . . . . . . . . . . . . . . . . . 1.3 2.6 3.9 5.2 6.0 “ 6.5

I,oerf . . . . . . . . . . . . . . . . . . . . . . . 0.9 2.0 2.8 3.7 4.2 4.6

2,000 . . . . . . . . . . . . . . . . . . . . . . . 0.6 1.4 2.0 2.6 3.0 3.3

5,000 . . . . . . . . . . . . . . . . . . . . . . . 0.4 0.9 1.2 1.6 1.9 2.1

Io,ooo . . . . . . . . . . . . . . . . . . . . . . 0.3 0.6 0.9 1.2 1.3 1.5

20,000 .. . . . . . . . . . . . . . . . . . . . . 0.2 0.4 0.6 0.8 0.9 1.0

50,00e . . . . . . . . . . . . . . . . . . . . . . O.1 0.3 0.4 0.5 0.6 0.7

Ioo,orro . . . . . . . . . . . . . . . . ..-. . 0.1 0.2 0.3 0.4 0.4 0.5

200,000 . . . . . . . . . . . . . . . .. ---- 0.1 0.1 0.2 0.3 0.3 0.3

500,000 . . . . . . . . . . . . . . . . . . . . . 0.0 0.1 0.1 0.2 0.2 0.2

I,ooo,ooo . . . . . . . . . . . . . . . . . . . . 0.0 0.1 0.1 0.1 0.1 0.1

Exampleof use oftablet An estimate of 30 percent baaed en en aggregete of 5 million visits has a atanderderrorof 1.9 percent

or a relatfw standard error of 6.3 fmrcent (1.9 percent dwided by 30 percent).

Table IV. Standard errors for percents of estimated number of drug mentions by

dermatologlsw National Ambulatory Medieel Care Survey, 1989-80

Estimated percent

Base of pemenf

drug mentions in thousands 1 or99 5or95 10 or 90 20 or 80 30 or 70 50

Standard errors in percentage pointa

100, . . . . . . . . . . . . . . . . . . . . . . 3.4 7.4 10.1 13.5 15.5 16.9

200 . . . . . . . . . . . . . . . . . . . . . . . . 2.4 5.2 7.2 9.6 11.0 11.9

500 . . . . . . . . . . . . . . . . . . . . . . . - 1.5 3.3 4.5 6.0 6.9 7.6

l,txK1 . . . . . . . . . . . . . . . . . . . . . . . 1.1 2.3 3.2 4.3 4.9 5.3

2,000 . . . . . . . . . . . . . . . . . . . . . . . 0.8 1.6 2.3 3.0 3.5 3.8

5,000 . . . . . . . . . . . . . . . . . . . . . . . 0.5 1.0 1.4 1.9 2.2 2.4

10,000 . . . . . . . . . . . . . . . . . . . . . . 0.3 0.7 1.0 1.4 1.5 1.7

20,eeo . . . . . . . . . . . . . . . . . . . . . . 0.2 0.5 0.7 1.0 1.1 1.2

50,000 . . . . . . . . . . . . . -. . . ----- 0.2 0.3 0.5 0.6 0.7 0.8

Ioo,ooo . . . . . . . . . . . . . . . . . . . . - 0.1 0.2 0.3 0.4 0.5 0.5

2oo,eoo . . . . . . . . . . . . . . . . . . . . . 0.1 0.2 0.2 0.3 0.3 0.4

!3fJ0,0e o . . . . . . . . . . . . . . . . . . . 0.0 0.1 0.1 0.2 0.2 0.2

20,000,000 . . . . . ! . . . . . . . . . . . . . fJfJ 0.0 0.0 0.0 0.0 0.0

Sample of we of table AJ_Itimate of 20 percent baaed cm an aggregate of 10 million drug mentions hae a atanderd emor of

1.4 pwwnt w a re!adveetsndsrd error of 7.0 pwoent (1.4 percent dwidsd by 20 percent).

Table V. Coefficients appropriate for determining relative standard errora by typo of

estimate and physician spadaltw National Ambulatory Medical Care Survey, 198940

Coef?7cient

Type of estimate and physician spaoiatiy A B

Vriis

bemllttils . . . . . . . . . . . . . . . . . . . . . . 0.00009754 !52.77S52184

Dermatology . . . . . . . . . . . . . . . . . . . . . . . . 0.01236777 8.46452955

Drug mentions

Overell totels . . . . . . . . . . . . . . . . . . . . . . . 0.00157151 81.47054633

Dermatology . . . . . . . . . . . . . . . . . . . . . . . . 0.01603645 11.42009364
Advance Data No. 240. March10.1994 9

Definition of terms

Ambulatory patient-Au

ambulatory patient is an individual

seeking personal health services who is

not currently admitted to any health care

institution on the premises.

Dermatologist-A physician who

specializes in the diagnosis and

treatment of diseases of the skin. The

physician’s specialty is self-designated

in the master files of the American

Medical Association (AMA) or

American Osteopathic Association

(AOA).

Drug mention-A drug mention is

the physician’s entry on the Patient

Record of a pharmaceutical agent—by

any route of administration— for

prevention, diagnosis, or treatment.

Generic as well as brand-name drugs are

include~ as are nonprescription and

prescription drugs. Along with all new

drugs, the physician also records

continued medications if the patient was

speciilcally instructed during the visit to

continue the medication.

Drug visit-A drug visit is a visit

at which medication was prescribed or

provided by the physician.

Ojice-An oilice is the space that

physicians identiQ as a location for

their ambulatory practice. Offices

customarily include Consultation

examinatio~ or treatment spaces that

patients associate with the particular

physician.

Physician-A physician is a duly

licensed doctor of medicine (M.D.) or

doctor of osteopathy (II.O.) who is

cumently in office-based practice and

who spends some time caring for

ambulatory patients. Excluded horn the

NAMCS are physicians who are hospital

based; who specialize in anesthesiology,

pathology, or radiology who are

federally employed; who treat only

institutionalized patients; or who are

employed full time by an institution and

spend no time seeing ambulatory

patients.

Viiit-A visit is a direct personal

exchange between an ambulatory patient

and a physician (or a staff member

working under the physician’s

supervision) for the purpose of seeking

care and rendering personal health

services. Excluded are visits where

medical care was not provided, such as

walk-outs and visits made to drop off

specimens, pay bills, and make

appointments.

Symbols

--- Data not available

. . . Category not applicable

Quantityzero

0.0 Quantity more than zero but

lessthan 0.05

z Quantity more than zero but

lessthan 500 where numbers

are roundedto thousands

* Figure does not meet standard

of reliabilityor precision

“U.S.GOwnmsnt PrintingCffiw 1995— S3WW20018
12 Advance Data No. 240. March 10,1994

Suggested citation

Nelson C. Office visits to dermatologists

National Ambulatory Medical Care Survey,

United States, 1989-90. Advance data from

vital and health statistics; no 240. Hyattsville,

Maryland: National Center for Health

statistics. 1994.

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Copyright information

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public domain and may be reproduced or

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source, however, is appreciated.

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