Early Warning Signs of Functional Illiteracy: Predictors in Childhood and Adolescence [611227]

Early Warning Signs of Functional Illiteracy: Predictors in Childhood and Adolescence
Author(s): Nazli Baydar, Jeanne Brooks-Gunn and Frank F. Furstenberg
Source: Child Development , Vol. 64, No. 3 (Jun., 1993), pp. 815-829
Published by: Wiley on behalf of the Society for Research in Child Development
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Early Warning Signs of Functional Illiteracy:
Predictors in Childhood and Adolescence
Nazli Baydar
Battelle Seattle Research Center
Jeanne Brooks-Gunn
Columbia University
Frank F. Furstenberg
University of Pennsylvania
BAYDAR, NAZLI; BROOKs-GUNN, JEANNE; and FURSTENBERG, FRANK F. Early Warning Signs of
Functional Illiteracy: Predictors in Childhood and Adolescence. CHILD DEVELOPMENT, 1993, 64,
815-829. Early childhood, middle childhood, and early adolescence determinants of functional
literacy in adulthood are investigated, using 20-year longitudinal data from a sample of black
children of teenaged mothers from the Baltimore metropolitan area. Document literacy was
assessed by a test that consisted of a subset of items of the National Assessment of Educational
Progress (NAEP) adult literacy test. The Baltimore sample is compared to the NAEP sample.
Family environmental factors, early childhood developmental level, and educational career fac-
tors were considered as predictors of young adulthood literacy. Preschool cognitive and behav-
ioral functioning is highly predictive of literacy in young adulthood, even when the effects of
family environmental characteristics, including living arrangements, the quality of the home
environment, maternal education, and income, are controlled. Grade failure in elementary school
is also associated with literacy, but this effect disappears when the measure of preschool abilities
is controlled. Family environmental factors that are predictive of literacy include maternal educa-
tion, family size in early childhood, maternal marital status, and income in middle childhood
and early adolescence. Policy implications of these findings are discussed.
Literacy is essential for functioning in
industrial societies. Reading and writing
skills are keys to a lifetime learning pro-
cess in our society, where job requirements
change continuously (Miller, 1988; National
Academy of Science, National Academy of
Engineering, and Institute of Medicine,
1984). Moreover, literacy enables active par-
ticipation in a society where many of the po-
litical and economic transactions are based
on written documents. However, there are
significant literacy problems in the United
States. The United States ranks forty-ninth
among 159 members of the United Nations
in its average level of literacy (Larrick,
1987). The number of adults who are not
functionally literate in the United States is
estimated to be 54-64 million (Hunter &
Harman, 1979). About one-fifth of all young
adults and about one-half to one-third of
minority young adults in the United States
read under the eighth-grade level (Kirsch &
Jungeblut, 1986). The number of individuals
who have levels of literacy that are not ade-
quate for active participation in an advanced
technological society (Venezky, Kaestle, &
Sum, 1987) and the disparities in literacy
achievements of various subgroups, such
as minority versus nonminority populations
(Hunter & Harman, 1979), add to the literacy
problem.
Levels of literacy of individuals and so-
cieties are often taken as indicators of well-
We wish to thank the Ford Foundation, the Robert Wood Johnson Foundation, and the
Educational Testing Service for their support of the research reported in this article. Special
thanks to the Russell Sage Foundation for sponsoring Brooks-Gunn and Furstenberg as visiting
scholars during the preparation of this manuscript. We are grateful to Irwin Kirsch and Ann
Jungeblut for helpful comments on an earlier draft and their assistance in the construction of the
short form of the literacy test. Thanks also to Norma Norris for providing help with the NAEP
data and Lauren Beiar for editing the manuscript. Reprint requests may be addressed to N.
Baydar, Battelle Seattle Research Center, 4000 NE 41st Street, Seattle, WA 98105-5428.
[Child Development, 1993, 64, 815-829. ? 1993 by the Society for Research in Child Development, Inc.
All rights reserved. 0009-3920/93/6403-0006$01.00]
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816 Child Development
being. The literacy problem became a focus
of policymakers because of its implications
for social and economic well-being. Low
levels of literacy have been linked to low
productivity, high unemployment, low earn-
ings, and high rates of welfare dependency
and teenage parenting, all of which are com-
mon measures of the socioeconomic well-
being of a society (Berlin & Sum, 1988).
Therefore, preventing illiteracy and improv-
ing the levels of literacy in all subgroups of
the population, especially among minorities,
are important educational policies.
The primary goal of the research pre-
sented here is to identify early childhood,
middle childhood, and adolescence precur-
sors of document literacy in a sample of
black metropolitan young adults who were
born to teenage mothers. We do not attempt
to unravel the processes through which
childhood and adolescence circumstances
determine the formation of literacy skills.
Rather, our aim is to identify early predictors
of adulthood literacy levels that can be used
to define high-risk groups in each develop-
mental period (i.e., early childhood, middle
childhood, and early adolescence) and in all
developmental periods combined.
Environmental events occurring during
the young childhood years and the abilities
of the preschool child are key determinants
of later development (Hunt, 1961; Wachs &
Gruen, 1982), even though few studies have
followed very young children into young
adulthood (as notable exceptions, see
Brooks-Gunn, Phelps, & Elder, 1991; Elder,
1984; Gjerde & Block, 1991; Werner &
Smith, 1982). The middle childhood years
are less often postulated as a central devel-
opmental stage vis-a-vis young adult func-
tioning. However, grade failure is a pre-
dictor of low long-term educational
achievement (Haskins, 1989; Willet &
Singer, 1992), and behavior problems, espe-
cially aggression and disengagement in ele-
mentary school, are associated with later
school problems (Cairns, Cairns, & Necker-
man, 1989; Connell, 1991). The young ado-
lescent years are characterized by the con-
fluence of social, cognitive, and behavioral
events. The number of new challenges faced
by youth and the behavioral choices to be
made render it a stage of importance for later
functioning (Brooks-Gunn & Petersen, 1983;
Feldman & Elliot, 1990; Gunnar & Collins,
1988; Lerner & Foch, 1987).
Our data come from a 20-year follow-up
of approximately 250 teenage mothers and
their children from Baltimore, most of whom
are economically disadvantaged. These chil-
dren were 18 to 21 at the time of the literacy
assessment (Furstenberg, 1976). These data
lend themselves to an analysis of anteced-
ents of low literacy achievement because
they include family and educational histo-
ries from birth to young adulthood, and early
childhood assessments of cognitive and be-
havioral development. A multivariate model
is employed to exploit the wealth of these
data in order to identify early warning signs
of illiteracy.
One limitation of this study is its rela-
tively small, nonprobability, convenience
sample. In order to gain a better perspec-
tive on this sample, its characteristics are
compared to those of the metropolitan
black young adults from the sample of the Na-
tional Assessment of Educational Progress
(NAEP), Literacy Survey, conducted in 1985
on a national sample of young adults aged
21 to 25. Additional comparisons of the Balti-
more sample with the black subsample of
the National Survey of Children are pro-
vided. The comparisons lead to a qualitative
assessment of the generalizability of the Bal-
timore data.
Two questions are addressed regarding
the predictors of literacy in young adult-
hood. First, are circumstances in the early
childhood, middle childhood, or early ado-
lescence years predictive of later literacy?
Our premise is that, while the most proximal
events, specifically, those occurring in early
adolescence, will be highly predictive of
young adulthood literacy, earlier events will
also contribute to literacy, as has been dem-
onstrated for other outcome measures (Kel-
lum, Adams, Brown, & Ensminger, 1982;
Rutter & Garmezy, 1983; Werner & Smith,
1982). Prior research has indicated that liter-
acy skills are partly developed in early child-
hood (IRA, 1986; Larrick, 1987), and the
characteristics of the home environment,
such as language patterns and interaction
patterns at home, plus the value placed on
literacy and learning activities by a child's
family, may mediate the acquisition of liter-
acy (Fox, 1990). In addition, inadequate lit-
eracy experiences in early childhood were
found to inhibit literacy achievement (Auer-
bach, 1989; Chall & Snow, 1982; Fox, 1990;
Taylor, 1983). Since literacy is acquired pri-
marily in the early grade school years, and
since preschool circumstances are pre-
dictive of early school achievement, we ex-
pect that early childhood factors will be
strongly predictive of young adulthood liter-
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Baydar, Brooks-Gunn, and Furstenberg 817
acy. On the other hand, because middle
childhood is the period when most for-
mal literacy education is received, school
achievement in this period may be highly
indicative of young adulthood literacy.
While educational achievement in early ado-
lescence will be strongly associated with
young adulthood literacy, it is believed that
such indicators will have precursors in mid-
dle and even in early childhood.
The second question that is addressed
in this paper pertains to the relative contri-
bution of family environmental and cogni-
tive or educational factors to literacy levels
in young adulthood. Maternal life circum-
stances are known to determine later school
success (Furstenberg, Brooks-Gunn, & Mor-
gan, 1987; Garfinkel & McLanahan, 1986;
Kellum, Adams, Brown, & Ensminger, 1982;
Rutter, 1979), which, in turn, predicts lit-
eracy. To our knowledge, no longitudinal
study has explored the power of childhood
and adolescence family life circumstances
for predicting functional literacy in young
adulthood weighing the relative significance
of factors measured at three different stages
of the life cycle. Our expectation is that both
cognitive/behavioral or educational factors
will be more strongly predictive of literacy
than family circumstances. Family environ-
mental factors contribute to preschool cogni-
tive and behavioral functioning (Sameroff,
Seifer, Barocas, Zax, & Greenspan, 1987;
Wachs & Gruen, 1982), which in turn con-
tribute to subsequent school achievement
and literacy (Furstenberg et al., 1987).
Hence, family environmental factors may be
regarded as indirect determinants of liter-
acy, while cognitive-behavioral and educa-
tional factors may be regarded as its proxi-
mate determinants.
Method
SAMPLE
The Baltimore study is an approxi-
mately 20-year follow-up of a sample of
black teenage mothers and their firstborn
children. All of the black young adults who
are the focus of this study were born in a
particular hospital in Baltimore between
1966 and 1968. The sample consists of 125
males and 126 females who were last inter-
viewed in 1987 when they were 19 to 21
years old. From these, 202 young adults
completed the document literacy question-
naire.1 The six waves of the Baltimore study
provide longitudinal demographic data,
preschool cognitive and behavioral assess-
ments, and interviewers' evaluations of the
households and household members when
the subjects were in early childhood, middle
childhood, and early adolescence (for a de-
tailed description of these data, see Fur-
stenberg et al., 1987). The data used in this
study come from waves 4 (1972), 5 (1983-
84), and 6 (1987) of the follow-up study.
Statistical inferences to a well-defined
population using the Baltimore sample are
not possible since it is a convenience sam-
ple. Instead, we provide a qualitative assess-
ment of the degree to which the characteris-
tics of the Baltimore sample are similar to
those of the metropolitan black young adults
of the National Assessment of Educational
Progress (NAEP) literacy sample. The
NAEP adult literacy survey was adminis-
tered to 3,618 adults in 1985, who consti-
tuted a nationally representative sample of
approximately 21 million 21-25-year-old
adults in the United States. Each subject was
administered a background questionnaire
and three blocks of questions out of seven
possible blocks according to a Balanced In-
complete Block (BIB) spiraling design.2
MEASURES
Measures of Literacy
In this study literacy is assessed by a
document literacy test. Conventional liter-
acy assessments were based on the measure-
ment of abilities to read and write. Contem-
porary assessments of literacy measure the
ability to negotiate some common literacy-
dependent tasks. The emphasis on the skills
that are necessary to fulfill one's role as a
member of a society recognizes the social
context of literacy skills (Hunter & Harman,
1 Those who received the literacy assessment were not different from those who did not in
sex and age composition, self and mother's education, or preschool age Peabody Picture Vocabu-
lary Test scores.
2 The Balanced Incomplete Spiraling design allows a broad coverage of content in a ques-
tionnaire without requiring a lengthy questionnaire from each respondent. The NAEP literacy
questionnaire items were divided into seven blocks of tasks, and each respondent received three
such blocks in addition to the core questionnaire. Each block was answered by approximately
the same number of respondents, who constituted a random subsample of the NAEP sample
(Kirsch & Jungeblut, 1986).
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818 Child Development
1979; Pellegrino, 1988). The ability to use
written documents constitutes an important
part of daily functioning in today's society
(Guthrie, Seifert, & Kirsch, 1986). Document
literacy may be distinguished from prose lit-
eracy because of the distinct forms of gram-
mar and syntax that are used in documents
(Kirsch & Mosenthal, 1988).
The document literacy data used in this
study came from a questionnaire of 22 items
regarding 11 brief documents. All questions
except one were borrowed from the NAEP
adult literacy questionnaire. Subjects took
about 20 min (median) to complete the ques-
tionnaire. Only two subjects took longer
than 45 min. The tasks ranged from simple
(signing a document) to moderately difficult
(planning a trip using an arrival-departure
table).
In this study, a simple index of literacy
was employed denoting the percentage of
correct answers to the set of questions that
were administered to both Baltimore and
NAEP samples (X = 74, SD = 18). All mem-
bers of the NAEP sample did not answer the
same set of questions because of the BIB
questionnaire design. Hence, we computed
a literacy score for each NAEP subject who
was administered at least 10 questions out
of the 21 possible questions that were in-
cluded in both studies.3 Since the document
literacy proficiency scores reported by the
NAEP studies and the percentile scores re-
sult in similar rankings of individuals' liter-
acy levels, the interpretation of the profi-
ciency scores based on NAEP's calibration
studies (Kirsch & Jungeblut, 1986) can be
employed to aid the interpretation of our re-
sults.4
Percentage of correct answers up to 60% indicates
a successful negotiation of no more complex tasks
than those consisting of a single feature (a single
item to be identified on the document in order to
provide the correct answer) and a single exemplar
(distractor on the document). Such tasks include
signing and recognizing the expiration dates of
identification cards, filling in personal data on
application forms, and using television program
listings to identify the show time of a particular
program.
From 60% to 90% correct answers indicates
achievement of two feature and two or more ex-
emplar tasks. Scores of 75% to 90% indicate some
knowledge of the process as well. Examples of
such tasks are filling out a telephone message slip,
identifying coupons for a shopping list, identi-
fying the appropriate dosage for a medication, and
completing a school registration form.
Scores of 90% to 100% indicate achievement of
multiple feature-multiple exemplar tasks. Plan-
ning a trip using a bus schedule, writing narrative
telephone messages, checking the accuracy of a
shipping list, and interpreting tables and charts
are examples of multiple feature-multiple exem-
plar tasks.
Measures of the Family Environmental
Factors
We consider four types of measures that
describe the family environmental factors:
measures describing living arrangements,
quality of the home environment, maternal
commitment to education, and economic
well-being. These four types of measures are
discussed below.
Family living arrangements.-Family
characteristics are determined on the basis
of retrospective maternal reports taken when
the subjects were approximately 15-17
years old. These data were elicited by a life
calendar. The family living arrangement
variables were constructed for three periods
of childhood: ages 0-4, ages 5-10, and ages
11-15. In this study, measures describing
the living arrangements in each develop-
mental period of interest were used. Living
arrangements and their stability define an
important aspect of the family environment,
since they reflect the presence and continu-
3 NAEP studies often report "proficiency scores" which are statistically estimated on the
basis of the questions answered by each respondent and several parameters describing their
background and the difficulty of the questions (NAEP, 1986). "Proficiency scores" of reading,
prose comprehension, document utilization, and practical computation were estimated for the
NAEP literacy survey. Unfortunately, none of these scales correspond exactly to the set of ques-
tions that were administered to the Baltimore sample.
4 In order to interpret the percentile scores using concepts underlying the proficiency scores,
one must assume that the respondents answered all of the questions that they could, given their
level of literacy. In other words, one must assume that the respondents did not skip questions
that seemed too easy. For the Baltimore sample, both proficiency scores and percentage of correct
answers were computed. The comparison of the two measurements of literacy show that there
is almost complete agreement between them (r = .97). In the subsample of black young adults,
the NAEP scale that includes most of the Baltimore study's literacy questions, that is, the docu-
ment utilization scale, correlates .79 with the percentile score constructed for this study.
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Baydar, Brooks-Gunn, and Furstenberg 819
ity of parent figures, family support that was
available for the teenage mothers of the sub-
jects, and the opportunity for interactions
with the parents or parent figures. The fol-
lowing characteristics are considered in this
study for each age interval:
number of years the mother was the only adult in
the household,
number of years mother was married,
number of years the father was present in the
household,
number of siblings born.
Certain variables describing the living
arrangements of the mother during child-
hood and adolescence are highly correlated.
For example, the correlation between father
presence and mother's being married during
early childhood was .84, because during the
first few years following the child's birth,
teen mothers were most likely to marry the
fathers of their children. During early child-
hood, mother's being unmarried does not
imply that mother is the only adult in the
household because it was common among
teen mothers to continue living with their
mothers (the subjects' grandmothers; 29%).
However, by middle childhood and adoles-
cence, the negative association between be-
ing the only adult in the household and
being married increased (-.48 in adoles-
cence). In multivariate analyses, one vari-
able must be chosen among the collinear
variables. If more than one of the variables
denoting maternal marital status, whether
the mother was the only adult, and biologi-
cal father presence were significantly associ-
ated with literacy scores in bivariate analy-
ses, mother's marital status was chosen over
a variable representing father presence
since a father figure will have similar effects
on a child as the biological father. Further-
more, mother's marital status is often readily
available for the identification of at-risk
groups.
Physical and emotional quality of the
home environment.-Two scales measure the
physical and emotional quality of the home
environments of the children. The quality of
the relationship between the mothers and
children was reported by the inteviewers
when the children were 4-6 years old. This
scale includes eight items describing the de-
gree of involvement, encouragement, praise,
confidence, severity, warmth, and verbal
communication of the mother toward the
child (a = .76). The HOME scale is based
on the interviewers' ratings of the homes in
early childhood (ages 4-6) and in adoles-
cence (ages 15-17) and consists of seven
items that describe the physical quality of
the home and neighborhood environment.
These items measure whether the environ-
ment is safe for the child, the rooms are over-
crowded with furniture, the house is dark
or noisy, the furnishing quality is good, the
physical condition of the house is good, and
whether the house is kept in good condition.
This scale is similar to the "stimulating
physical environment" subscale of the
HOME scale (Bradley & Caldwell, 1981;
Bradley, Caldwell, & Elardo, 1979; Bradley
& Rock, 1985), which is predictive of cogni-
tive development in young children (e.g.,
Bradley & Caldwell, 1976). The reliability
of the HOME scale is .76 in early childhood
(X = 4.9, SD = 2.0) and .65 in adolescence
(X = 5.5, SD = 1.0).
Maternal commitment to education.-
There are three measures that reflect moth-
ers' commitment to education. These are the
maternal educational attainment when the
subjects were 4-6 years old, maternal educa-
tional aspirations at that time, and maternal
educational aspirations for the child (i.e., the
subject) at that time, all measured in years
of education. Since the measures of maternal
educational attainment and maternal educa-
tional aspirations are strongly correlated
(0.55), and since at the time of reporting the
mothers were very young, the educational
aspirations could be taken as an important
indicator of educational commitment, along-
side educational attainment. We use the
mean of the two measures to indicate mater-
nal educational level (X = 11.6, SD = 1.1).
The measure of maternal educational aspira-
tions for the subjects in early childhood is
correlated with this measure by 0.34. In mul-
tivariate analyses, when one of the two mea-
sures had to be selected, maternal educa-
tional level was preferred for the following
reason: The maternal educational aspira-
tions for the child may partly be determined
by the child's ability level, and hence con-
found the effects of early childhood develop-
mental outcomes with maternal commitment
to education.
Economic well-being.-Two measures
of economic well-being are available:
mother's dependence on public assistance,
and per-person family income. For each of
the three periods of childhood, variables de-
noting the number of years mother was de-
pendent on public assistance were con-
structed. The percentage of mothers who did
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820 Child Development
not receive any public assistance was 58%
in early childhood, 61% in middle child-
hood, and 67% in early adolescence. Per-
person family income is available at the time
of the interviews in 1972 (X = 1,509, SD =
1,397) and 1983 (X = 4,739, SD = 4,264).
While the number of years spent on public
assistance summarizes the level of economic
well-being over a period of several years, it
is not a very accurate measure of economic
well-being. Per-person family income, on
the other hand, provides an accurate mea-
sure of economic well-being, but only at two
points in time; hence it lacks the broader
time frame of the prior measure.
Measures of Cognitive and Behavioral
Development in Early Childhood
Three scales measure the level of cogni-
tive and behavioral development of the sub-
jects when they were aged 4 to 6. These are
(1) the Peabody Picture Vocabulary Test
(PPVT), (2) the Caldwell Child Behavior In-
ventory (CBI), and (3) the tester's rating of
the subject's verbal skills. The PPVT is a test
that measures verbal ability in early child-
hood by showing children four pictures and
asking them to point to the picture that best
describes a word that is read to them (Dunn
& Dunn, 1981). The mean PPVT score in the
Baltimore sample was 78 (national norm is
100). The CBI is an inventory of small tasks
that measure concept recognition, associa-
tive vocabulary, and social responsiveness
of preschoolers (Cooperative Tests and Ser-
vices, 1970). The mean CBI score in the
Baltimore sample was 58.5 The verbal skills
scale consists of the interviewer's ratings (X
= 8.2, SD = 2.2) and is based on four items
(a = .68) that describe verbal communica-
tion (3-point scale), verbal behavior (5-point
scale), ability for descriptive speech (2-point
scale), and the monosyllabic nature of the
speech (2-point scale). While the three mea-
sures of verbal and behavioral development
are correlated, they do not overlap totally.
The CBI and the interviewer's rating of ver-
bal development measure verbal as well as
social and behavioral skills, although the
PPVT measures verbal development only.
All three measures of cognitive and be-
havioral development are associated with
the age of the subjects at the time of testing.
In order to eliminate the confounding effects
of age, these three measures were standard-
ized to reflect measurements taken at age 5.6
The two standardized test scores measuring
the subjects' developmental level, PPVT
and CBI, are highly correlated (0.66). There-
fore, in this study we use the average stan-
dard test score as a measure of develop-
mental level (X = 77, SD = 26).
Measures of Educational Career
We consider two variables representing
the educational experiences of the children.
The first variable measures whether a child
has failed a grade in elementary school. This
variable is based on the self-reports of the
respondents in 1987, when they were 19-21.
If these reports indicated the repetition of
the sixth or a lower grade, a grade failure
was assumed (23%). Because of the self-
reported nature of these data, it is possible
that some kindergarten and early grade
school failures may be underreported. The
second variable indicates whether a child
was ever suspended from school, based on
self-reports (54%). Although further details
about the educational careers of Baltimore
subjects are available, it is not clear that such
measures can be interpreted as precedents
of literacy. For example, while elementary
school grade failure could be interpreted as
a precursor of low levels of adulthood liter-
acy, high school grade failure might be a
consequence of illiteracy rather than a pre-
cursor. Similarly, dropping out of high
school might be due to illiteracy, and hence
must be interpreted as a possible covariate
of illiteracy, not a precursor. School suspen-
sions are often a consequence of behavioral-
disciplinary problems rather than academic
problems. Therefore, one may interpret
school suspension as an indicator of behav-
ioral problems that might interfere with lit-
eracy acquisition.
Results
The Baltimore sample members have
lower levels of educational achievement
than metropolitan black young adults nation-
ally. Three out of 10 young adults 19 years
of age or older in the Baltimore sample have
not completed high school, as compared to
25% of 21-25-year-old metropolitan black
5 The Caldwell Preschool Inventory is predictive of some outcomes in adolescence, such
as juvenile delinquency in this sample (Furstenberg et al., 1987).
6 The following standardization procedure has been employed: The developmental scores
were regressed on age in months at the time of the testing. The predicted scores were then
computed using the age of 60 months as a predictor, and the residual for each observation was
added to compute the developmental measure standardized to age 5.
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Baydar, Brooks-Gunn, and Furstenberg 821
persons of the NAEP survey in 1985. The
mean completed grade level of the Balti-
more sample is 11.4. The educational drop-
out rates are 41% for males and 29% for fe-
males. Over half of the initial dropouts
occurred at or before the tenth grade. These
percentages compare to 17% of the 18-21-
year-old black subsample of the National
Survey of Children (NSC; Furstenberg,
Hughes, & Brooks-Gunn, 1990). Grade repe-
tition rates are 64% for males and 41% for
females, compared to 26% in the black NSC
sample. Disciplinary problems at school ac-
company and probably have contributed to
school failure. About 70% of males and 40%
of females report having been suspended at
least once, compared to 43% in the black
NSC sample.
Comparison of Literacy in NAEP and
Baltimore Samples
Levels of literacy in the NAEP metro-
politan black sample and the Baltimore sam-
ple are similar, with means of 77 (SD = 19)
and 74 (SD = 18), respectively. The propor-
tion of individuals who could complete no
more than single feature-single exemplar
tasks is 19% among the members of the Bal-
timore sample and 17% among the members
of the NAEP metropolitan black sample.
Table 1 compares the mean levels of lit-
eracy of various subgroups in the NAEP and
Baltimore samples. In both samples, females
have significantly higher literacy scores than
males. As expected, self and maternal educa-
tion are significantly associated with liter-
acy. However, one must add that high school
education does not assure high levels of doc-
ument literacy, either in the Baltimore or the
NAEP samples. Multiple feature-multiple
exemplar tasks could not be completed by a
total of 73% of the Baltimore and 78% of the
NAEP high school graduates (result not pre-
sented in Table 1).
This comparative description of the lit-
eracy levels of the NAEP metropolitan black
and Baltimore samples indicates that the two
samples are similar. The subgroup differ-
ences are of the same direction and approxi-
mately of the same magnitude.
Predictors of Young Adulthood Literacy in
the Baltimore Sample
Table 2 summarizes the differentials in
literacy scores by family environmental, de-
velopmental, and educational career factors
in early childhood, middle childhood, and
adolescence. Among the family environmen-
tal factors, measures of living arrangements
in early childhood do not account for a sig-
nificant proportion of the variance in literacy
scores in young adulthood. In middle child-
hood and adolescence, however, father pres-
ence and mother's being married predict
higher literacy scores. Similarly, mother's
being the only adult in the household for
three or more years during adolescence is
associated with significantly lower literacy
scores. Birth of two or more siblings in the
first 5 years of life results in significantly
lower literacy scores. Birth of siblings in
middle childhood and adolescence, how-
ever, is not a predictor of subsequent level
of literacy.
The physical and emotional quality of
the home environment in early childhood is
a significant predictor of literacy. Subjects
who had homes of high physical quality and
TABLE 1
COMPARISON OF THE LITERACY LEVELS OF THE NAEP AND BALTIMORE SAMPLES
NAEP METROPOLITAN
BLACK SAMPLE BALTIMORE SAMPLE
CHARACTERISTIC Mean pa N Mean pa N
Gender:
Male …………………………….. 73.5 .0 184 68.7 00 96
Female …………………………. 78.8 .0 298 78.2 106
Educational attainment:
Less than high school……. 70.9 135 64.7 85
High school or more ……… 78.4 .00 346 80.3 .00 117
Maternal education:
Less than high school……. 75.2 188 70.5 90
High school or more……… 78.5 .06 251 77.5 .01 93
a Probability levels indicate the significance of F statistic that tests the between-subgroup
differences as compared to within-subgroup variance.
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TABLE 2
COMPARISON OF MEAN LITERACY SCORES IN YOUNG ADULTHOOD BY FAMILY ENVIRONMENTAL
FACTORS, DEVELOPMENTAL LEVEL, AND EDUCATIONAL CAREER INDICATORS IN EARLY AND MIDDLE
CHILDHOOD AND EARLY ADOLESCENCE
EARLY MIDDLE
CHILDHOOD CHILDHOOD ADOLESCENCE
CHARACTERISTIC Mean pa Mean pa Mean pa
FAMILY ENVIRONMENTAL FACTORS
Living arrangements:
Mother was the only adult in household:b
Yes ………………………….. …………. 75.4 69.9 69.7
N o ……………………… … ………………….. ………………… 73.7 75.1 75.5
Father was present in the household for at least 1 year:
Yes ……………………………………………. 74.1 78.5 79.5
N o ……………………… ….. ……………….. ………………… 73.7 72.3 72.8
Mother was married for at least 2 years:
Yes ……………………………………………….. 75.8 77.4 78.0
N o ……………………… … ……. …………. ………………… 72.2 69.7 70.9
Had siblings born during the period:C
Yes ………………….. .. ………………. 59.0 75.6 76.0
N o …………………. …… ………………… …………………. 75.8 72.8 73.6
Physical and emotional quality of the home environment:
HOME scale:
Low ………………… ……………………….. ……………….. 70.7 70.5
High ………………………………….. 76.8 74.6
Quality of the mother's relationship with child:
L ow ………………….. ……………………………………………….. 69.5
H igh ………………….. ………… …………….. 76.0
Maternal commitment to education:
Maternal educational level:d
< H S ………………… ………………………………………………… 70.5
2 H S ……………………………………………………………………… 7 7 .5
Maternal educational aspiration for the subject:
< H S ……………………………………………… …………………. 70.5
S H S …………………………………………….. ………………….. 77.7
Economic well-being:
Mother received public assistance during the entire period:
Yes ………………………………. …………….. 71.4 69.1 0 68.4
N o …………………………………….. ……………….. 74.2 74.9 . 74.7
Per-person family income:
Low ………………….. ………………………. ………………… 72.4 70.8
High …………………………………………. 78.1 .05 79.8 .00
COGNITIVE AND BEHAVIORAL DEVELOPMENT OF THE CHILD
Mean standardized test score:
L ow ………………….. ……………………………………………….. 63.8
H igh …………………………………. 80.7
Interviewer's assessment of verbal development:
L ow ………………….. ……………………………………………….. 70.2
H igh ………………………………………………… 78.4
EDUCATIONAL CAREER OF THE CHILD
Repeated a grade in elementary school:
Yes …………………………………. .67.4
No…………………………… . …………………. 75.7
Got suspended from school:
Yes ………… ………………………………………..71.3
No……………. …. …………………………………………. 77.3 .02
a Probability levels indicate the significance ofF statistic that tests the between-subgroup differences as compared
to within-subgroup variance.
b Yes = 1 or more years in early childhood; yes = 3 or more years in middle childhood and adolescence.
SYes = 2 or more siblings in early childhood; yes = 1 or more siblings in middle childhood or adolescence.
d Mean of maternal educational attainment and aspiration.
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Baydar, Brooks-Gunn, and Furstenberg 823
subjects whose mothers initiated positive in-
teractions with them averaged higher liter-
acy scores than subjects who scored low on
these scales. The HOME scale measured in
adolescence is not a significant predictor of
literacy scores.
Mothers' commitment to educational
achievements when the subjects were in
early childhood strongly predicts literacy
differentials. High maternal educational
level, measured by achievement and aspira-
tions, and high educational aspirations for
the subject in early childhood predict high
literacy scores in young adulthood. One of
the measures of economic well-being, per-
person family income, both in early child-
hood and in adolescence, is a significant pre-
dictor of literacy scores. Early dependence
on public assistance, however, is not sig-
nificantly associated with young adulthood
document literacy in this sample.
All of the variables measuring different
aspects of cognitive and behavioral develop-
ment and educational achievement are sig-
nificant predictors of literacy. Early child-
hood standardized assessments significantly
differentiate literacy levels in young adult-
hood. The interviewer assessments of the
subjects' verbal development also predict
literacy differentials in young adulthood.
Educational careers of the subjects are also
strongly associated with literacy levels, such
that subjects who experienced early grade
failure and school suspension in adoles-
cence (i.e., severe behavioral problems in
school) scored significantly lower in the lit-
eracy assessment.
A Multivariate Analysis of Literacy in the
Baltimore Sample
In order to assess the relative contribu-
tion of different factors in early childhood,
middle childhood, and adolescence precur-
sors to young adulthood literacy, multivari-
ate least-squares regression models were es-
timated. Table 3 summarizes the findings
from these regression models. First, three
separate regression models were estimated
in order to identify the factors in each devel-
opmental period that account for most of the
variance in young adulthood literacy scores.
The factors that were identified as signifi-
cant bivariate predictors were included in
the multivariate regression model. Next we
estimated a model that combined the factors
from each developmental period that were
identified as statistically significant pre-
dictors of young adulthood literacy scores.
This model assesses the relative predictive
value of precursors of document literacy
in each period in a multivariate context.
Each model was estimated in two steps. The
first step included only those variables per-
taining to family environmental factors. The
second step included the measures of devel-
opmental level or educational achievement.
All models that are presented in Table 3 con-
trol for gender differences in literacy scores
(see Table 1), although these coefficients are
not presented. In addition, residuals of all
regression models were examined to assure
that outliers do not play an undue role in
the estimation of the regression coefficients.
Residuals with absolute standardized values
larger than 3.0 did not exist.
The first column (Model I) of Table 3
displays the estimated coefficients of the re-
gression model that represents the effects of
early childhood family environmental fac-
tors on young adulthood document literacy
scores. The number of siblings born during
early childhood is a significant predictor of
young adulthood literacy levels, controlling
for the indicators of the quality of the home
environment, maternal education, and eco-
nomic well-being. Maternal educational
level and per-person family income have
positive significant effects on young adult-
hood literacy, controlling for the other fam-
ily environmental factors. The indicators of
physical and emotional quality of the home
environment were not predictive of young
adulthood literacy scores, controlling for
other family factors.' The second column
(Model II) of Table 3 includes early child-
hood developmental level alongside the
variables describing family environmental
factors. Controlling for early developmental
level, each additional sibling born within
the first 5 years of life of the subjects re-
sulted in a 4 percentile point reduction in
predicted literacy scores. Although maternal
educational level, assessed when the sub-
jects were 4-6 years old, was a significant
predictor of young adulthood literacy when
only family environmental factors were con-
sidered, this association was no longer sig-
nificant when controlling for early develop-
mental level. Similarly, per-person family
income was significantly predictive of liter-
acy scores when only family environmental
factors were considered; when the measure
7 The emotional quality of the home environment, however, is a significant predictor of the
standardized measure of developmental level used in this study (p < .05).
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Baydar, Brooks-Gunn, and Furstenberg 825
of early childhood developmental level was
considered, however, this variable was no
longer a significant predictor. The measure
of developmental level of the child based on
standardized assessments was significantly
predictive of literacy scores assessed 15
years later. One standard deviation unit of
difference in the cognitive and behavioral
developmental measures resulted in a pre-
dicted literacy score different by approxi-
mately one-third standard deviation unit.
Overall, the factors measured in early child-
hood accounted for 28% of the variance in
adulthood literacy scores.
The third and fourth columns of Table
3 present the effects of factors pertaining to
middle childhood on young adulthood liter-
acy scores. The number of years mother was
married positively predicted literacy scores
in young adulthood; the measure of eco-
nomic well-being, that is, dependence on
public assistance, however, did not predict
literacy scores significantly. Repeating a
grade in early elementary school was sig-
nificantly predictive of adulthood literacy
scores. The factors measured in middle
childhood accounted for a much lower pro-
portion of variance in literacy scores than the
factors measured in early childhood (14% vs.
28%).
The fifth and sixth columns of Table 3
display the effects of family circumstances
and behavioral problems in adolescence on
literacy in young adulthood. Among family
environmental factors, the number of years
mother was married and higher per-person
family income in adolescence predicted
higher literacy scores. Having been sus-
pended from school was not significantly as-
sociated with literacy scores primarily be-
cause this variable is strongly associated
with gender, males being more likely to be
suspended than females, and a control for
gender was included in the multivariate
model.
The seventh and eighth columns of Ta-
ble 3 display the estimated coefficients of a
regression model that combined the signifi-
cant predictors of literacy scores from early
childhood, middle childhood, and adoles-
cence. Among the family environmental fac-
tors, the birth of siblings during early child-
hood resulted in lower predicted literacy
scores, controlling for other family environ-
mental characteristics. Total number of
years mother was married in middle child-
hood and early adolescence, maternal edu-
cation, and average per-person family in-
come were also significant predictors of
young adulthood literacy scores. Model VIII
in Table 3 presents the coefficients of a mul-
tiple regression model that includes devel-
opmental and educational career factors in
addition to the family environmental factors
from all three developmental periods under
consideration. Per-person family income
and maternal educational level were no
longer significantly predictive of literacy
score in young adulthood, controlling for
early childhood developmental level. Simi-
larly, grade repetition in grade school was
not predictive of young adulthood literacy,
controlling for early childhood develop-
mental level. The early childhood develop-
mental assessments were the strongest pre-
dictor of adulthood literacy, controlling for
other significant predictors from early and
middle childhood and early adolescence.
Model VIII accounted for 32% of the vari-
ance in literacy scores.
Discussion
In this paper, predictors of young adult-
hood literacy were investigated in a sample
of economically disadvantaged black young
adults who were born to teenage mothers in
Baltimore. This sample combines several at-
tributes that point to a high risk of educa-
tional failure. Nevertheless, the level of lit-
eracy of this sample is similar to that of the
nationally representative sample of black
metropolitan young adults of the NAEP
study. Only one-fifth of the study sample has
literacy skills required to complete tasks
such as finding information in an almanac,
checking the accuracy of a mail order ship-
ping slip, interpreting charts and tables, or
locating information in a tax table. A little
under one-fifth of the sample have inade-
quate literacy levels. At a minimum, these
young adults have attained a literacy level
that is sufficient for signing documents, rec-
ognizing traffic signs, extracting information
from television program listings, and filling
in personal information on documents. How-
ever, their skills are insufficient for tasks
such as making out a check, locating dosage
information on a medicine label, filling in a
school registration form, or using classified
advertisements. The majority of the sample
fall in between these two extremes of adept
and subsufficient functional literacy (see
also Carroll & Chall, 1975; Hirsch, 1987).
These young adults constitute the group that
Miller (1988) has labeled "semiliterate." Be-
cause of the historical trend in the job mar-
ket (i.e., increasing proportions of jobs re-
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826 Child Development
quiring higher levels of skill and literacy),
semiliterate adults are ill equipped to enter
today's work force (Berlin & Sum, 1988;
Diehl & Mikulecky, 1980).
In this article, the predictors of docu-
ment literacy were identified among family
environmental, developmental, and educa-
tional career-related factors from early and
middle childhood and early adolescence.
These factors include family living arrange-
ments, quality of the home environment,
maternal commitment to education, eco-
nomic well-being, developmental level of
the child, and educational career of the
child. A few limitations of this study must
be acknowledged before further discussion
of the findings. First, the generalizability of
our analyses is limited by the nature of our
sample. The sample is of limited size, and its
reference population is not heterogeneous.
Although we provide evidence that the char-
acteristics of the young adults in the Balti-
more sample are similar to high-risk sub-
samples of two nationally representative
samples, the analyses presented in this pa-
per will not lead to the identification of pre-
cursors of functional illiteracy in high-risk
subgroups that are not represented in our
sample (e.g., children of immigrant families,
nonminority children who are in poverty,
etc.). In addition, certain limitations of the
data must be noted. Despite the wealth of
information on early childhood, middle
childhood, and early adolescent living ar-
rangements, the reports on living arrange-
ments by the mothers may be subject to
some errors due to their retrospective na-
ture. In addition, information on other fac-
tors that may contribute to literacy acquisi-
tion are lacking. For example, details of
the educational experiences of the subjects
when they were children and adolescents
and measures of achievement in each devel-
opmental period are not available, although
undoubtedly these factors would have been
strong predictors of young adulthood lit-
eracy.
The most compelling finding of this
study is the significance of factors measured
in early childhood in predicting literacy lev-
els measured in young adulthood, support-
ing our hypothesis about the importance
of this developmental period. Particularly
noteworthy is the power of standardized
cognitive and behavioral assessments in
early childhood in predicting young adult-
hood literacy measured 15 years later. The
skills that are indicative of cognitive and be-
havioral development as measured by stan-
dardized tests, including items assessing
social responsiveness, concept recognition,
and associative vocabulary knowledge, are
powerful predictors of young adulthood lit-
eracy. This finding points to the importance
of early childhood intervention programs
that result in gains in cognitive abilities,
quality of language interactions, and social-
behavioral skills prior to entry in grade
school.
Our hypothesis that family environmen-
tal factors will affect literacy indirectly only
through early childhood developmental
level and educational achievement was not
supported. Certain aspects of early child-
hood family environment are predictive of
later literacy, even when early childhood de-
velopmental level is controlled. Such family
environmental factors may be regarded as
those facilitating or impeding a child's at-
tainment of his or her literacy potential.
These include number of years the mother
was married and number of siblings born.
These environmental factors are particularly
important since our and other research-
ers' results indicate that once a trajectory
for low verbal and cognitive ability and for
poor communication skills is established,
it strongly influences school achievement
(Bloom, 1961; Hunt, 1961) and literacy. Ad-
ditional environmental factors, such as the
quality of the home environment (see note
7) in early childhood, are strongly associated
with preschool cognitive and behavioral out-
comes (Brooks-Gunn & Furstenberg, 1987;
Sameroff et al., 1987; Wachs & Gruen, 1982).
These findings suggest that certain compo-
nents of the environment early in the child's
life influence adulthood literacy indirectly
via their impact on preschool abilities.
Nevertheless, unfavorable childhood envi-
ronmental factors often persist throughout
childhood and adolescence, and hence they
can also be viewed as indicators of risk fac-
tors for outcomes measured later in life.
Other studies have demonstrated that im-
provement of environmental conditions after
the preschool years results in an improve-
ment in cognitive skills in children (Duse-
wicz & Higgins, 1971).
A family environmental factor that can
be targeted by policies is the control of the
subsequent fertility of teenage mothers. Our
results show that childbearing in close suc-
cession after the first birth may have long-
term negative effects on children, such as
low levels of literacy. Other studies showed
the association between sibship size and
school performance (Polit, 1982; Steelman,
1985; Zajonc & Markus, 1975). This associa-
tion might be attributed to the ways children
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Baydar, Brooks-Gunn, and Furstenberg 827
spend their time and the extent of verbal in-
teraction between mothers and children
(Hill & Stafford, 1980; Stafford, 1987). Pro-
grams that promote fertility control and pro-
vide awareness of the risks of subsequent
high fertility result in a reduction of addi-
tional children born to teenage mothers in
close succession (Furstenberg et al., 1987;
Hayes, 1987; Paikoff & Brooks-Gunn, in
press), which in turn has the potential to pos-
itively influence long-term outcomes.
Our study showed that economic well-
being measured by per-person family in-
come is associated with young adulthood lit-
eracy, but not when the early childhood
developmental level is controlled. Hence,
the effects of economic well-being on long-
term outcomes such as adulthood literacy
may be primarily through its effects on cog-
nitive and behavioral development in early
childhood, again pointing to the importance
of targeting early childhood developmental
level. Grade failure in elementary school
was highly predictive of literacy levels.
Grade failure is an important indicator of
compliance with the requirements of the ed-
ucational system. However, when control-
ling for preschool cognitive and behavioral
functioning, the measures of school achieve-
ment are no longer significantly predic-
tive of literacy. This suggests that, regard-
ing adulthood literacy, preschool develop-
mental level may be a policy target even
more significant than educational remedia-
tion once a school failure has occurred. Eco-
nomically disadvantaged minority children
who are at risk of entering school with a de-
lay in cognitive and social-behavioral skills
might benefit from participation in high-
quality intervention programs that target
preschool children and their families. Par-
ticipation in high-quality intervention pro-
grams for disadvantaged toddlers and pre-
schoolers and their families results in
significant gains in verbal and cognitive abil-
ities and in school success as compared to
control group children not receiving such in-
tervention (Clarke-Stewart & Fein, 1983;
Haskins, 1989; Ramey, Bryant, Sparling, &
Wasik, 1985; Zigler & Muenchow, 1984).
Studies show that enhanced cognitive abil-
ity persists through childhood, as seen in
rates of grade failure and enrollment in spe-
cial education classes (Lazar, Darlington,
Murray, Royce, & Snipper, 1982).
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