Parental
Attitudes
Do
Not
Explain
Underimmunization
Donna
Strobino,
PhD*;
Virginia
Keane,
MD;
Elizabeth
Holt,
DrPH;
Nancy
Hughart,
RN,
MPH*;
and
Bernard
Guyer,
MD,
MPH*
ABSTRACT. Objective.
This
article
describes
the
re-suits
of a community-based
study
to determine
the effect
of family knowledge and attitudes on the immunizationrates
of
a random
sample
of
children
younger
than
2
years
in the
poorest
census
tracts
of Baltimore.
Design and Methods. The
two
sources
of data
were
(1)
parent interviews that provided data on knowledge,
at-titudes,
and
beliefs
related
to immunization
and
socio-demographic characteristics, and (2) medical record
au-dits from which data on immunization status were
obtained. The protection motivation theory, a model of behavioral change, was used to select the variables to
assess
the
relation
of parental
attitudes
with
immuniza-tion status. A multivariate logistic regression analysis included only variables found to be significantly
associ-ated with immunization outcome in the preliminary
analysis.
Results. Mothers were well informed and generally
had favorable attitudes toward immunizations. Immuni-zation status was more strongly associated with the so-ciodemographic characteristics of the children than with the protection motivation theory variables. Only
two
pro-tection motivation theory variables were associated withmore than one immunization outcome. The children of
mothers who perceived that timing of vaccination did not matter were less likely to be immunized than children of care takers who thought that it did matter and children
whose
parents
believed
in the
safety
of multiple
immu-nizations were less likely to be immunized than children whose parents did not hold this belief.
Conclusions.
In this study, parents’ attitudes andbe-liefs
had
little
effect
on
their
children’s
immunization
levels.
Interventions
intended
to
heighten
parental
awareness about immunization may have little impact. Inpoor urban neighborhoods, African-American children
whose mothers are young, have multiple siblings, and do
not use the Women, Infants and Children program may
be at highest risk for delayed immunization. Pediatrics 1996;98:1076-1083; immunization, health beliefs, children.
ABBREVIATIONS. DTP, diphtheria, tetanus, and pertussis
vac-cine; OPV, oral polio vaccine; MMR, measles, mumps, and rubella
vaccine; PMT, protection motivation theory; WIC, Women,
In-fants, and Children program.
From the Departments of *Matemal and Child Health and §International
Health, Johns Hopkins School of Hygiene and Public Health, Baltimore; and the Department of Pediatrics, University of Maryland School of Medicine,
Baltimore.
Received for publication Dec 14, 1995; accepted Feb 20, 1996.
Reprint requests to (D.S.) Department of Maternal and Child Health, School
of Hygiene and Public Health, Johns Hopkins University, 624 N Broadway,
Baltimore, MD 21205.
PEDIATRICS (ISSN 0031 4005). Copyright © 1996 by the American
Acad-emy of Pediatrics.
Epidemics
of
measles
in
1989
and
1990
revealed
surprisingly
low
levels
of immunization
among
pre-school
children
in
the
United
States
and
stimulated
new
national
initiatives
to
improve
coverage.
In
1993,
the
President’s
Comprehensive
Childhood
Im-munization
Initiative
accelerated
efforts
to reach
the
Healthy People 2000
objective
that
90%
of
children
complete
the
basic
series
of
immunizations
by
the
time
they
are
2 years
old.1’2
The
President’s
Compre-hensive
Childhood
Immunization
Initiative
estab-lished
new
standards
for
measuring
immunization
coverage,
included
a national
outreach
campaign
to
increase
community
participation
and
educate
par-ents,
provided
increased
technical
support
to
state
and
local
immunization
groups,
and
expanded
ef-forts
to simplify
the
vaccine
schedule,
inform
provid-ers,
and
reduce
cost
barriers.2
These
efforts
have
not
been
entirely
successful.
The
Centers
for
Disease
Control
and
Prevention
es-timates
that
overall
immunization
levels
increased
from
55.3%
in
1992
to
67.1%
in
1993
for
the
basic
series
of four
diphtheria,
tetanus,
and
pertussis
vac-cines
(DIP),
three
oral
polio
vaccines
(OPV),
and
one
measles,
mumps,
and
rubella
vaccine
(MMR).
How-ever,
among
poor
children,
coverage
was
only
58.7%,
a level
not
very
different
from
the
53.9%
coverage
documented
in
Baltimore
in
1991.
The
reasons
for
these
low
levels
of
coverage
are
not
fully
understood.
One
explanation
frequently
voiced
by
physicians,
parents,
and
policymakers
is
that
the
knowledge
(or
lack
thereoO
and
attitudes
of
families
lead
them
to delay
their
children’s
immuni-zations.9
There
is a large
body
of literature
linking
these
parental
factors
to utilization
of health
services
for
both
preventive
health
and
illness
care.104
Fewer
studies
have
specifically
examined
the
relation
of
parental
knowledge
and
attitudes
regarding
child-hood
immunization.
These
studies
have
identified
parents’
perceptions
of
logistical
barriers
to
care,
health
beliefs,
and
attitudes
about
childhood
immu-nization
as
risk
factors
for
underimmunization.19
However,
it
is
difficult
to
draw
conclusions
from
these
studies
because
of the
variation
in ethnicity
and
income
among
the
populations
studied,
and
the
dif-ferences
in
methods
used
to
measure
health
beliefs
and
immunization
status.
We
describe
the
results
of
a
community-based
study
to
determine
the
effect
of
family
knowledge
and
attitudes
on
immunization
rates
of
children
younger
than
2 years
in
the
poorest
census
tracts
in
Baltimore.
We
hypothesized
that
parental
ARTICLES
1077
the
immunization
process
would
have
significant
effects
on
immunization
status,
and
that
demo-graphic
characteristics,
social
support,
and
health
care
access
would
also
affect
immunization
rates.
METHODS
Study
Population
and
Setting
Study children were selected from a birth cohort of 2489 chil-dren born between August 1988 and March 1989 to mothers who
resided in I of 57 census tracts in Baltimore. The census tracts were those in which at least 50% of the resident births in 1987 were to women who were eligible for medical assistance. Children with birth weights of less than 500 g or those who were adopted or deceased were excluded from the sample. A total of 1100 children were randomly selected for study eligibility from the remaining births.
Data Collection
Parent interviews and medical record audits were used as the
sources of data for our study. After obtaining written informed
consent, a trained interviewer conducted a structured interview in
the home of the parent or care giver of each study child. The interview included questions about demographic characteristics, health care access and utilization, social support, and knowledge, attitudes, and beliefs about immunizations and disease. The ques-tions in the interview that related to parental attitudes and beliefs about immunizations were based on the results of discussions
with three focus groups of health care consumers. These focus
groups, led by anthropologists, explored each domain of our conceptual model.8 The interviewer recorded all outpatient care sites, including hospital emergency departments, used by the child from birth. Respondents gave informed consent to review their children’s medical records. The site and date of each vacci-nation and a review of each health visit was obtained from these records.
Study
Framework
A model of behavioral change, the protection motivation theory (PMT),2’ with minor modification, formed the conceptual
frame-work for the selection of variables to assess the relation of parental
attitudes with immunization status. This model proposes that when environmental or personal factors pose a threat, such as the possibility of contracting a vaccine-preventable disease, decisions regarding coping responses to this threat are made as a result of
balancing the costs and benefits of the threat with those of the
coping behavior. Threat assessment includes evaluating one’s vul-nerability to and severity of the threat as well as the intrinsic and extrinsic rewards of experiencing the threat. Coping behavior includes evaluation of response efficacy; the perceived likelihood that the action will reduce the threat; one’s own self-efficacy; the belief that the individual can complete the adaptive behavior; and the costs and benefits of the coping behavior. The variables in-cluded under each area of the model are displayed in Table 2.
In our study, threat appraisal was assessed in relation to the parent’s perception of his or her child’s vulnerability to and se-verity of vaccine-preventable diseases. Vulnerability was mea-sured by two variables related to the likelihood of getting a preventable disease in general, and measles, in specific if the child were not immunized. Severity was defined by a scale measuring the parent’s perception of the seriousness of whooping cough, polio, and measles. We did not include a measure of the rewards of the threat in the parent interviews because we assumed that there were no rewards for a child having a vaccine-preventable disease.
Coping appraisal included response efficacy, parent’s self-effi-cacy, and response costs and benefits. Response efficacy was mea-sured by the parent’s perception that shots for measles, polio, and whooping cough are effective, that getting immunizations on time
is important, and the parent’s knowledge of the efficacy of each vaccine. Self-efficacy was defined as the capability of the parent to get the child immunized, as measured by his or her ability to complete the steps required to obtain immunizations (making an appointment, having money and time needed to get the immuni-zation, and having a way to get to the clinic), and to care for the child after vaccination. Response costs were measured by the
parent’s perception that the waiting time at the last visit was long and several scales defining three related constructs. The constructs were the parent’s perception that it is safe to get more than one shot at a time; his or her perception of the hassles associated with bringing other children to the clinic; and that the parent consid-ered not getting a shot for several reasons. Response benefit was measured by a scale of the parent’s perception that having up-to-date immunizations is a community norm.
In addition to the PMT variables, several demographic, social support, and health care access variables were explored as poten-tially confounding variables. Demographic characteristics in-cluded the mother’s race, education, and age at the birth of the child, family income, the child’s insurance, whether the family had ever paid out of pocket for immunizations, whether the family consisted of two parents, whether the biological mother was in the home, and the number of siblings in the family. Social supports were measured by the number of people the mother could count on for useful suggestions and whether the father of the child was dependable. Health access variables included in the analysis were whether the child ever received Women, Infants, and Children (WIC) program services in the first 2 years and whether the child’s provider had after hours emergency care.
The dependent variables were age-appropriate immunization for DTP1, DTP3, MMR, and up-to-date status (4 DTP, 3 OPV, I MMR) by 24 months. The definitions used for these indicators are listed in the Appendix. These definitions were based on the rec-ommendations of the 1988 edition of the American Academy of Pediatrics Red Book,21 which was in use when the study children were 24 months old.
Data Analysis
The data analysis was conducted in several steps. First, all items related to the PMT were evaluated for variability. The next step was creation of scaler variables measuring each domain of the PMT model. These variables were assessed for internal consis-tency using cronbach a and examined for the extent to which each item differentiated individuals with high and low scores on the scale. Only scaler variables with a cronbach a of 0.70 or more were included in our analysis.
Next, the PMT, demographic, social support, and health care access variables were evaluated by
x
tests regarding their relation with the four measures of immunization status. Statistical signif-icance was defined as a less than or equal to 0.05. A multivariate logistic regression analysis was then performed. This analysis included only the variables found to be significantly associated with any of the immunization outcomes in the bivariate analysis. Accordingly, the following PMT variables were not included in the multivariate analysis: care taker’s belief that the child is vul-nerable to getting vaccine-preventable diseases if not up-to-date on immunizations, belief that vaccine-preventable diseases are severe, incorrect knowledge about vaccine-preventable diseases, concern that she or he cannot care for child after the vaccine, and consideration of not getting the child immunized. Several demo-graphic variables and one social support measure were also ex-cluded. Mother’s education, family income, whether the mother had ever paid out-of-pocket for immunizations, and whether the father of the child was dependable were included in the bivariateanalysis but were not found to be related to the child’s
immuni-zation status in the multivariate analysis.
For each vaccine outcome, one regression model was estimated with only the PMT variables. A second model also contained the demographic, social support, and access variables that were re-lated to immunization coverage. This second model was estimated to investigate whether including these potentially confounding variables altered the relation of the PMT variables with the mea-sures of immunization status. Interactions in the effect of selected PMT and demographic variables were tested in these models, but no consistent results were found across the different measures of vaccine outcomes.
RESULTS
Of
the
I 100
children
eligible
for
the
survey,
735
(67%)
were
located.
Forty-five
of these
children
(6%)
were
found
to be
ineligible,
50 parents
(7%)
refused
to
be
interviewed,
and
83
parents
(12%)
were
not
interviewed
by
the
closing
date.
A total
of 557
(81%)
at Viet Nam:AAP Sponsored on August 30, 2020
www.aappublications.org/news
of
the
eligible
children
who
were
located
partici-pated
in
the
study.
There
were
no
significant
differ-ences
in birth
weight,
maternal
age,
and
marital
sta-tus
at
birth
between
the
557
children
whose
care
takers
were
interviewed
and
the
noninterviewed
families.
However,
89%
of
the
children
of
inter-viewed
care
takers
were
African-American
com-pared
with
95%
of
those
whose
parents
were
not
interviewed
(P
<.001).
The
maternal
characteristics
and
birth
weights
of the
557
children
closely
resem-bled
those
of
the
birth
population
in
the
57
census
tracts.
An
independent
assessment
of
bias
in
the
selection
of
the
sample
indicated
that
the
inter-viewed
children
were
representative
of the
inner-city
childhood
population
in Baltimore
at the
time
of the
study.4
Of
the
care
takers
who
were
interviewed
89%
gave
informed
consent
to review
their
children’s
medical
records.
Immunization
data
for
525
of the
surveyed
children
(94%)
were
obtained.
The
demographic,
so-cial
support,
access,
and
PMT
characteristics
were
compared
for
the
525
children
with
immunization
data
and
the
32
children
without
data.
The
two
groups
differed
in only
one
respect.
Seventy-one
per-cent
of the
care
takers
of children
with
immunization
data
compared
with
50%
of
the
care
takers
of
chil-dren
without
immunization
data
believed
their
chil-dren
were
vulnerable
to
vaccine-preventable
dis-eases
(P
<.05).
The
remaining
analyses
are
confined
to
the
525
children
with
immunization
data.
About
one
third
of children
were
born
to
teenage
mothers.
Only
17%
of
the
children
lived
in
two-parent
homes,
and
7%
were
not
in
the
care
of
their
biological
mother
(Table
1). Ninety
percent
of
moth-ers
were
African-American
and
42%
had
not
gradu-ated
from
high
school.
Insurance
characteristics
of
the
population
reflect
the
selection
criteria
for
the
study
sample.
More
than
80%
of children
were
coy-ered
by
medical
assistance
for
most
or all of their
first
2 years
and
only
9%
had
ever
been
uninsured
during
this
period.
Of
the
families,
339
(66%)
received
Aid
for
Families
With
Dependent
Children
benefits;
381
(73%)
received
food
stamps
and
147
(28%)
lived
in
public
housing.
Immunization
levels
were
low
for
the
study
chil-dren.
A total
of 283
children
(54%)
were
up-to-date
at
24 months;
374
(71%)
had
an
age-appropriate
DTP1,
186
(35%)
an
age-appropriate
DTP3,
and
276
(53%)
an
age-appropriate
MMR.
Table
2 shows
the
PMT
characteristics
of
the
525
children
studied.
Care
givers,
91 %
of
whom
were
mothers,
were
well
informed
about
the
vaccine-pre-ventable
diseases
and
generally
had
favorable
atti-tudes
toward
immunizations.
Most
care
givers
(96%)
believed
that
shots
do
more
good
than
harm,
and
99%
believed
that
a
child
was
safer
having
been
immunized.
There
was
a strong
belief
in the
value
of
immunizations
in
preventing
disease.
Nevertheless,
there
were
some
misconceptions
about
which
dis-eases
are
vaccine-preventable;
65%
of the
care
givers
had
incorrect
vaccine
knowledge
for
at
least
one
disease.
Only
about
8%
of
parents
ever
considered
not
getting
a shot.
The
majority
was
confident
that
they
could
do
what
was
needed
to get
their
children
immunized
and
to
take
care
of them
afterward.
The
parents’
sense
of
disease
severity
and
of
their
chil-dren’s
vulnerability
to
the
vaccine-preventable
dis-eases
appeared
to
be
high.
A total
of 89%
believed
that
the
diseases
were
severe
and
71 %
of
parents
thought
their
children
were
vulnerable
to them.
TABLE 1. Demographic, Social Support, a nd Health Care Access Characteristics of Study Children (N = 525)
Characteristic N ‘
Demographic
Race Not African-American 53 (10.1)
Maternal age at birth <20 y at birth
20-30 y (R)*
>30 y at birth
170 280 75
(32.4) (53.3) (14.3)
Maternal education <9th grade
10-11 grade H.S. graduate
66 157 302
(12.6) (29.9) (57.5)
Household income $10 000
>$I0000 Not reported
237 162 126
(45.1) (30.9) (24.0) Insurance at any time in first 2 y Medicaid
Private
None
426 129
45
(81.1) (24.6)
(8.6)
Out of pocket costs Has paid for vaccine out of pocket 192 (36.6)
Family composition Child lives in two parent household
Biologic mother not in home
89 34
(17.0) (6.5)
Number of siblings 0-1 siblings (R)
Two siblings
Three or more siblings
384 107 83
(73.0) (20.4) (15.8)
Social support Child’s father is dependable
Mother has no one to count on
113 29
(21.5)
(5.5)
Health care access WIC anytime in first 2 y
Provider site has after hours emergency care
383 202
TABLE 2. Protection Motivation Theory Characteristics of the Caretakers of the Study Children (N = 525)
ARTICLES
1079
PMT Domain Characteristic N %
Threat appraisal
Vulnerability Belief child is vulnerable if not up-to-date 374 (71.2)
Severity Belief vaccine preventable diseases are severe 466 (88.8)
Coping appraisal
Response efficacy
Self-efficacy
Belief shots are effective
Belief it does NOT matter if child misses a shot as long as he/she catches up by school entry Incorrect vaccine knowledge for 3 diseases Less than sure he/she can complete steps to get
child immunized
NOT sure he/she can care for child after vaccine
452 186
32 52
54
(86.1) (35.4)
(6.1) (9.9)
(10.3)
Response costs Thought total time at last visit was long (90 mm)
Belief it is safe to get more than one shot at a time Belief bringing other children to clinic is a hassle Considered NOT getting child immunized for
one or more reasons
257 249 35 44
(49.0) (47.4) (6.7) (8.4)
Response benefit Belief keeping shots up-to-date is NOT the norm 165 (31.4)
There
were
also
negative
attitudes
expressed
by
the
parents.
About
35%
of care
takers
said
that
it was
not
important
if a child
missed
a shot
as long
as he or
she
was
caught
up
by
preschool
or
school
entry.
Thirty-one
percent
believed
that
keeping
shots
up-to-date
was
not
the
norm
among
their
friends,
and
more
than
50%
did
not
believe
in the
safety
of
mul-tiple
immunizations.
Tables
3
through
6 show
the
logistic
regression
results
for
DTPI
age-appropriate,
DTP3
age-appro-priate,
MMR
age-appropriate,
and
up-to-date
status
at
2 years,
respectively.
Adjusted
odds
ratios
and
95%
confidence
intervals
are
presented
for
each
re-spective
immunization
variable
for
the
regression
models
with
the
PMT
variables
alone
(model
1) and
adjusted
for
the
demographic,
social
support,
and
access
variables
(model
2).
In
model
1,
each
PMT
variable
is adjusted
for
the
presence
of the
other
PMT
variables.
An
odds
ratio
greater
than
I means
that
a
child
with
the
given
characteristic
has
increased
odds
of
immunization
versus
the
reference
category.
An
odds
ratio
of less
than
1 means
that
the
child
with
a
given
characteristic
has
reduced
odds
of
immuniza-tion
relative
to the
reference
category.
The
reference
category
for
each
variable
with
more
than
two
cate-gories
is designated
by
an
(R)
in Table
I.
Only
two
of
the
PMT
variables
were
statistically
significant
for
more
than
one
immunization
out-come.
First,
for
all
but
the
first
DTP
immunization,
children
whose
primary
care
giver
perceived
that
it
TABLE 3. Adjusted Odds Ratios and Confidence Interv als for PMT Variables: DTPI Age-app ropriate Im munization (N = 525)
Characteristic Model I Model 2+
OR. (CI.)
OR. (CI.)
PMT (caregiver beliefs)
It is not important if child misses a shot
Less than sure can complete steps to get child immunized
Bringing other children to clinic is a hassle It is safe to get more than one shot at a time Keeping shots up-to-date is NOT the norm Total time at last visit was long (90 mm) Shots are effective
Demographic, social support, access Race (not African-American)
Maternal age <20 y at birth Maternal age >30 y at birth Ever not insured
Biologic mother not in home Child has two siblings
Child has three or more siblings Child lives in two parent household Mother has no one to count on WIC anytime in first 2 y
Provider has after hours emergency care
0.68 1.22
0.52 0.53 0.93 0.65 1.48
(0.46;I.0I) (0.63;2.36)
(0.26;I.07) (0.36;0.79) (0.62;I.42) (0.44;0.96)4 (0.86;2.55)
0.74 1.18
0.58 0.56 0.93 0.70 1.61
2.96 0.54 1.30 3.44 0.31 0.56 0.57 1.23 0.38 2.46 0.99
(0.48;I.14) (0.59;2.35)
(0.27;I,28) (0.37;0.84) (0.60;I.45) (0.46;I .07) (0.90;2.87)
(1 .25;6.97)* (0.34;0.86)
(0.68;2.54) (1 .39;8.50) (0.I4;0.70) (0.33;0.934
(0.32;I.02) (0.66;2.29) (0.16;0.914 (l.53;3.97)II (0.65;1 .52) * Model 1 includes the PMT variables only; each variable is adjusted for the presence of the other PMT variables.
+ Model 2 includes the demographic variables as well as the PMT variables; each PMT variable is adjusted for the presence of these variables along with the other PMT variables.
:1:P < .05. §P < .01.
I
P < .001.at Viet Nam:AAP Sponsored on August 30, 2020
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TABLE 4. Adjusted Odds Ratios and Confidence Intervals for PMT Variables: DTP3 Age-appropriate Immunization (N = 525)
Characteristic Model 1* Model 2+
OR. (CI.) OR. (CI.)
PMT (caregiver’s beliefs)
It is not important if child misses a shot 0.56 (0.37;0.83) 0.59 (0.39;0.90)
Less than sure can complete steps to get child immunized 0.52 (0.26;I.07) 0.51 (0.24;I.09)
Bringing other children to clinic is a hassle 0.32 (0.I2;0.84) 0.36 (0.13;0.99)*
It is safe to get more than one shot at a time 0.69 (0.47;I.00) 0.74 (0.50;I.I0)
Keeping shots up-to-date is NOT the norm 0.90 (0.60;I.34) 0.90 (0.59;1.36)
Total time at last visit was long (90 mm) 0.72 (0.50;I.05) 0.82 (0.55;1.22)
Shots are effective 0.78 (0.46;1.32) 0.81 (0.46;I.40)
Demographic, Social Support, Access
Race (not African-American) I .52 (0.77;3.00)
Maternal age <20 y at birth 0.64 (0.41 ;0.99)4
Maternal age >30 y at birth 0.86 (0.48;I.56)
Ever not insured 1.23 (0.60;2.54)
Biologic mother not in home 0.26 (0.09;0.77)
Child has two siblings 0.48 (0.29;0.8I)
Child has three or more siblings 0.41 (0.23;0.74)
Child lives in two parent household 1.92 (1.II;3.334
Mother has no one to count on 0.48 (0.17;I.41)
WIC anytime in first 2 y 2.40 (1.46;3.95)II
Provider has after hours emergency care 1.25 (0.84;1.87)
* Model 1 includes the PMT variables only; each variable is adjusted for the presence of the other PMT variables.
FModel 2 includes the demographic variables as well as the PMT variables; each PMT variable is adjusted for the presence of these variables along with the other PMT variables.
:t:P < .05. §P < .01.
lip
< .001.TABLE 5. Adjusted Odds Ratios and Confidence Intervals for P MT Variabl es: MMR Age-appropr iate Immu nization (N = 525)
Characteristic Model 1* Model 2t
OR. (CI.) OR. (CI.)
PMT (caregiver’s beliefs)
It is not important if child misses a shot 0.51 (0.36;0.744 0.51 (0.35;0.76)
Less than sure can complete steps to get child immunized 0.74 (0.41;1.34) 0.75 (0.40;I.41)
Bringing other children to clinic is a hassle 0.63 (0.31;I.28) 0.82 (0.38;1.76)
It is safe to get more than one shot at a time 0.86 (0.61;1.23) 0.91 (0.63;l.32)
Keeping shots up-to-date is NOT the norm 0.88 (0.61;I.29) 0.84 (0.56;1.24)
Total time at last visit was long (90 mm) 0.93 (0.65;I.32) 0.98 (0.67;1.44)
Shots are effective 1.46 (0.88;2.43) 1.62 (0.94;2.79)
Demographic, Social Support, Access
Race (not African-American) I .41 (0.73;2.70)
Maternal age <20 y at birth 0.89 (0.58;1.35)
Maternal age >30 y at birth 0.92 (0.52;1.63)
Ever not insured 0.99 (0.50;1 .93)
Biologic mother not in home 0.49 (0.22;l.06)
Child has two siblings 0.42 (0.26;0.67)
Child has three or more siblings 0.27 (0.15;0.47)
Child lives in two parent household I .35 (0.79;2.32)
Mother has no one to count on 0.94 (0.40;2.18)
WIC anytime in first 2 y 2.19 (I.4I;3.40)
Provider has after hours emergency care 1.27 (0.86;I.87)
*Model I includes the PMT variables only; each variable is adjusted for the presence of the other PMT variables.
t Model 2 includes the demographic variables as well as the PMT variables; each PMT variable is adjusted for the presence of these variables along with the other PMT variables.
:I:P < .001.
was
not
important
if the
child
missed
an
immuniza-tion
as
long
as
he
or
she
caught
up
by
entry
into
preschool
or
kindergarten
were
approximately
half
as
likely
to be
immunized
as
children
of care
givers
who
thought
that
it was
important.
Second,
a child
whose
parent
believed
in
the
safety
of
multiple
in-jections
was
less
likely
to
receive
his
or
her
first
immunizations
on
time.
A
few
additional
PMT
variables
were
related
to
receipt
of
a single
immunization
outcome.
A
child
whose
parent
perceived
that
he
or she
experienced
a
long
wait
at
the
child’s
last
visit
was
less
likely
to
initiate
immunization
on
time;
ie,
have
DTP1
on
time.
Children
of parents
who
believed
that
it was
a
hassle
to bring
other
children
with
them
to the
clinic
were
one
third
less
likely
to receive
their
third
DTP
on
time.
The
belief
that
shots
were
effective
was
positively
associated
with
being
up-to-date.
There
was
little
change
in the
estimates
of the
odds
ratios
for
the
PMT
variables
when
adjustment
was
made
for
the
demographic,
social
support,
and
ac-cess
variables.
However,
as
measured
by
the
at Viet Nam:AAP Sponsored on August 30, 2020
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ARTICLES
1081
TABLE 6. Adjusted Odds Ratios and Confidence Intervals for PM T Variabl es: DTP, OPV, MMR U p-to-Date by 24 mo (N = 525)
Characteristic Model 1* Model 2+
OR. (CI.)
OR. (CI.)
PMT (caregiver’s beliefs)
It is not important if child misses a shot
Less than sure can complete steps to get child immunized Bringing other children to clinic is a hassle
It is safe to get more than one shot at a time
Keeping shots up-to-date is NOT the norm
Total time at last visit was long (90 mm) Shots are effective
Demographic, social support, access Race (not African-American)
Maternal age <20 y at birth Maternal age >30 y at birth Ever not insured
Biologic mother not in home Child has two siblings
Child has three or more siblings Child lives in two parent household Mother has no one to count on WIC anytime in first 2 y
Provider has after hours emergency care
0.54 0.68 0.70 0.84
0.70
0.71 1.68
(0.37;0.78)IJ (0.37;I.24) (0.34;I.42) (0.59;I.20)
(0.48;I.03)
(0.50;1.01) (1.0I;2.824
0.52 0.70 0.80 0.91
0.64
0.75 1.91
2.23 0.91 0.92 1.10 0.38 0.58 0.33 I .27 0.31 3.01 1.54
(0.35;0.78) (0.37;I.33) (0.37;1.75) (0.62;1.34)
(0.42;0.96)
(0.51;1.II) (I.I0;3.32)
(1 .I2;4.444 (0.59;I.40) (0.51;I.66) (0.55;2.18) (0.I7;0.88) (0.36;0.944 (0.19;0.57)II
(0.73;2.22) (0.12;0.81)* (I.89;4.77)Jj (1.03;2.29)4
* Model 1 includes the PMT variables only; each variable is adjusted for the presence of the other PMT variables.
1-Model 2 includes the demographic variables as well as the PMT variables; each PMT variable is adjusted for the presence of these variables along with the other PMT variables.
:1:
P < .05. §P < .01.II
P < .001.tude
of their
estimated
odds
ratios,
the
demographic,
access,
and
social
support
variables
were
more
strongly
associated
with
immunization
status
than
the
PMT
variables.
With
few
exceptions,
the
children
who
lived
in
households
in
which
the
biological
mother
was
not
present
or
who
had
two
or
more
siblings
were
considerably
less
likely
to
get
an
age-appropriate
immunization
or
to be
up-to-date.
Chil-dren
who
had
received
WIC
services
were
two
to
three
times
more
likely
to
be
immunized
on
time.
African-American
children
and
children
of
parents
who
believed
they
had
no
support
system
were
less
likely
to initiate
or
complete
their
immunizations
on
time.
Being
born
to a teenage
mother
decreased
the
odds
of
receiving
the
DTP1
and
DTP3
immuniza-tions
on
time
and
having
two
parents
in
the
house-hold
increased
the
odds
for
age-appropriate
receipt
of
the
third
DTP.
DISCUSSION
Our
study
results
indicate
that
parents’
knowledge
and
attitudes
about
immunization
generally
do
not
explain
their
children’s
immunization
status.
In
this
poor
urban
population,
most
respondents
held
be-liefs
that
would
seem
to enhance
immunization;
they
tended
to
overestimate
the
severity
of
preventable
diseases
and
children’s
vulnerability
and
they
felt
capable
of getting
their
children
immunized
and
car-ing
for
them
after
vaccination.
Few
had
ever
consid-ered
not
getting
their
children
immunized.
Most
be-lieved
that
vaccines
are
effective,
and
that
children
are
safer
overall
if they
are
immunized.
Nevertheless,
some
parents
held
beliefs
that
could
adversely
affect
immunization.
About
half
of
the
parents
reported
having
to wait
a long
time
at visits
to their
child’s
provider
and
almost
one
third
did
not
believe
that
most
children
in
their
community
were
up-to-date
on
their
immunizations.
However,
the
children
of
parents
who
had
less
favorable
beliefs
generally
were
immunized
as often
as other
children.
Belief
in
the
safety
of
multiple
injections
was
in-versely
associated
with
the
first
immunizations.
It is
possible
that,
because
of the
relatively
large
number
of
variables
studied,
this
association
occurred
by
chance
alone
or
that,
because
the
belief
was
mea-sured
after
vaccination,
the
response
was
influenced
by
the
vaccine
experience.
In other
words,
parents
of
children
who
were
behind
on
immunizations
may
have
had
more
experience
with
receipt
of
simulta-neous
vaccines.
Alternatively,
their
belief
in
the
re-ceipt
of
multiple
immunizations
may
be
a rationale
for
not
bringing
their
children
in on
time
to get
single
vaccinations.
The
one
variable
that
appeared
to be
consistently
associated
with
later
immunizations
was
the
belief
that
immunization
timing
does
not
matter.
One
ed-ucational
message
to
emphasize
in
communicating
with
parents
may
be
that
early,
on
time
immuniza-tion
is important.
To
emphasize
this
point,
providers
could
inform
parents
at each
visit
of
the
date
of the
next
well
child
visit
or
immunization
as
well
as
en-couraging
them
to
ask
at
each
visit
when
the
next
immunizations
are
due.
The
health
beliefs
of mothers
appear
to be
far
less
important
than
sociodemographic
factors
in
deter-mining
the
immunization
status
of poor
urban
chil-dren,
a finding
consistent
with
those
of Bates
et al.18
The
demographic
and
social
support
variables
present
a compelling
picture
of children
at risk.
Chil-dren
born
to teenage
mothers,
living
in
larger
fami-lies,
and
in
households
in
which
their
biological
mother
was
absent
had
lower
immunization
rates
for
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most
antigens.
Maternal
isolation
(having
no
support
system),
a problem
for
almost
one
third
of mothers,
was
also
a
risk
factor.
These
effects
are
evident
throughout
the
first
2 years.
Families
with
these
char-acteristics
may
be important
to target
for
more
inten-sive
efforts.
Interventions
aimed
at high-risk
families,
although
difficult
to
deliver,
may
have
the
greatest
effect
on
community
immunization
rates.
Improved
provider-and
population-based
information
systems
may
be
useful
in identifying
children
and
families
at risk
for
more
intensive
support
and
outreach
services.
In
particular,
closer
tracking
of visits
for
well
child
care
and
immunizations,
either
directly
or
through
refer-ral
to
local
public
health
agencies,
may
be
an
effec-tive
approach
for
improving
the
immunization
levels
of
children
in
high-risk
communities.
In
these
corn-rnunities,
where
the
will
and
the
resources
may
not
be
enough
to ensure
active
immunization
seeking
by
parents,
enhanced
pediatric
programs
that
empha-size
parent
support
through
home
visits,
availability
of
advice
about
parenting
and
child
development,
use
of
development
specialists,
parent
groups,
and
other
support
services
may
provide
a
vehicle
for
improving
both
the
primary
care
received
by
chil-dren
and
their
immunization
coverage.
One
strategy
for
improving
immunization
rates
is
the
coordination
of immunization
services
and
pub-lic
programs
such
as
WICY-
In
this
study,
the
high
rates
of
immunization
among
WIC
participants
probably
reflect
families
who
are
socially
adept
and
skilled
at accessing
resources.
Although
there
is
cur-rently
an
effort
nationally
and
in Maryland
for
WIC
centers
to ensure
that
children
are
adequately
immu-nized,
these
programs
were
not
in place
at
the
time
this
cohort
of
children
was
less
than
2 years.
These
data
suggest
that
WIC
clients
are
already
well
im-munized,
and
that
this
approach
is
likely
to
have
only
a marginal
impact
on immunization
rates
in this
population.
The
ability
to
pay
for
immunizations,
as
reflected
by
income
and
out
of
costs,
was
not
associ-ated
with
immunization
status.
The
majority
of
chil-dren
was
covered
by
medical
assistance
or
private
insurance
and
lived
in neighborhoods
in which
free
vaccines
were
widely
available.
In
fact,
contrary
to
expectation,
children
who
were
uninsured
at
some
point
during
their
first
2 years
were
more
than
three
times
as
likely
to
be
immunized
age-appropriately
for
DTP1
as
those
who
were
insured
throughout
their
first
2 years.
This
finding
may
reflect
working
families
who
were
eligible
for
medicaid
when
their
infants
were
young
but
who
lost
their
coverage
as
family
income
rose.
The
Vaccines
for
Children
pro-gram
was
not
in effect
at the
time
of the
study.
These
results
suggest
that
the
provision
of free
vaccine
to
providers
through
the
Vaccines
for
Children
pro-gram
is unlikely
to improve
the
immunization
levels
of
these
children.
The
findings
of
our
study
must
be
interpreted
in
light
of
its
limitations.
A
major
limitation
was
the
collection
of
survey
data
from
parents
after
their
children’s
second
birthdays,
and,
thus,
after
the
time
period
during
which
we
measured
their
children’s
immunization
status.
For
some
of the
variables,
such
as belief
that
it is safe
to get
multiple
immunizations
at once,
the
parents’
attitudes
may
result
from
their
experience
with
multiple
injections.
This
effect
could
also
be
the
reason
for
the
strong
relation
of
immuni-zation
levels
after
DTPI
with
the
perception
of
the
care
taker
that
it is not
important
if the
child
gets
his
or
her
immunizations
on
time
as
long
as
the
child
is
up-to-date
by
school
entry.
However,
even
for
these
variables
we
cannot
be
certain
whether
the
attitudes
we
measured
reflect
parental
immunization-seeking
behavior
or
whether
their
immunization
experience
gave
rise
to or
reinforced
their
attitudes.
A
second
limitation
is
the
limited
variability
among
mothers
for
many
of
the
attitudes
we
mea-sured.
This
limited
variability
affected
our
ability
to
examine
the
relation
of these
attitudes
with
immuni-zation
status.
Most
parents
have
favorable
attitudes
about
vaccinating
their
children;
it is likely
that
im-munization-seeking
behavior
is influenced
by
factors
other
than
parents’
attitudes.
A
final
study
limitation
is
sample
attrition
that
may
have
reduced
the
variation
in
attitudes
of
the
parents
in our
sample.
The
parents
of the
32 children
for
whom
no
medical
records
data
were
available
were
less
likely
to perceive
their
children
as
vulner-able
to
vaccine-preventable
disease,
and,
accord-ingly,
may
have
had
lower
immunization
rates.
It is
impossible
to
predict
from
this
difference,
if
inclu-sion
of
these
32
children
would
have
altered
the
study
findings.
Improving
immunization
coverage
through
edu-cating
parents
has
been
a
popular
strategy
with
many
governmental,
philanthropic,
advocacy,
and
corporate
groups.
This
strategy
assumes
that
chil-dren
are
not
appropriately
immunized
because
their
parents
are
either
not
well
informed
or
have
poor
attitudes
about
vaccines.
The
results
of
this
study
indicate
that
such
assumptions
may
not
be
correct.
Achieving
the
Healthy People 2000objective
among
young,
poor
children
in the
inner-city
will
require
a
comprehensive
and
sustained
approach
to the
prob-lem
that
includes
the
development
of better
informa-tion
systems
to
identify
children
at risk
for
delayed
immunization
and
the
implementation
of programs
to ensure
they
are
appropriately
immunized.
APPENDIX: DEFINITIONS OF VACCINE
OUTCOMES
Age-Appropriate per Antigen Dose (Timing of Valid
Doses)
DTPI-received vaccine between 42 and 92 days, inclu-sive.
DTP3-received vaccine at least 28 days after DTP2 and before
or on 213 days
of life, and
DTP2
was
at least
28 days
after DTPI.MMR-an MMR (either first or second dose) given
be-tween
366 days
and
517 days of life, inclusive.Up-to-Date for 4 DTP, 3 OPV, and MMR by 24 Months
DTP-DTPI
was
received
on
or after
42 days,
DTP2
was
received at least 28 days after DTPI , DTP3 was received
at
ARTICLES
1083 184 days after DTP3 and between 14 months (426 days)and 24 months (730 days), inclusive.
OPV-OPVI was received on or after 42 days, OPV2 was
received at least 28 days
after
OPVI,
and
OPV3
was
re-ceived at least 28 days afterOPV2
and
between
14 months
(426 days) and 24 months (730) days), inclusive; or OPV4was received at least 28 days after OPV3 and between 14 months (426 days) and 24 months, (730) inclusive;
MMR-a
first
or
second
dose
of MMR
was
received
be-tween 366 days
and
730
days
(12
through
24
months),
inclusive.ACKNOWLEDGMENTS
This study was supported by the Division of Immunization, Centers for Disease Control and Prevention, contract 200-90-0850. The study was approved by the Committee on Human Research, Johns Hopkins School of Hygiene and Public Health and the Institutional Review Board of the University of Maryland at Baltimore.
We are grateful to Bonita Stanton for her leadership, comments, and support in the development of the study design and
ques-tionnaire and to Robert Aronson, Lisa Horton, and Tony Larry
Whitehead for the focus group research that formed the question-naire’s development. We wish to thank the families who partici-pated in the survey; interviewers; and members of the staff at Survey Research Associates, Incorporated, for carrying out the interviews; Di Guo, Debbie Hodges, William Hou, Surinda Kuntolbutra, Teng Li, Jeff Malter, Joy Nanda, Tern Sullivan, and Njideka Udochi for research assistance; Nira Bonner, Diane Dwyer, Neal Halsey, Alan Ross, Patrick Vivier, and the Advisory Group of the Baltimore Immunization Study for their advice; and Jorge Rosenthal, Lauri Markowitz, Felicity Cutts, and Peter Patriarca at the Centers for Disease Control and Prevention.
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