Applied Developmental Science Exposure to Neighborhood

This article was downloaded by: [Bibliothèques de l'Université de Montréal]
On: 27 August 2014, At: 11:13
Publisher: Routledge
Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,
37-41 Mortimer Street, London W1T 3JH, UK
Applied Developmental Science
Publication details, including instructions for authors and subscription information:
http://www.tandfonline.com/loi/hads20
Exposure to Neighborhood Affluence and Poverty in
Childhood and Adolescence and Academic Achievement
and Behavior
a
a
Sara Anderson , Tama Leventhal & Véronique Dupéré
a
b
Tufts University
b
Univeristé de Montréal
Published online: 17 Jul 2014.
To cite this article: Sara Anderson , Tama Leventhal & Véronique Dupéré (2014) Exposure to Neighborhood Affluence and
Poverty in Childhood and Adolescence and Academic Achievement and Behavior, Applied Developmental Science, 18:3,
123-138, DOI: 10.1080/10888691.2014.924355
To link to this article: http://dx.doi.org/10.1080/10888691.2014.924355
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained
in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no
representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the
Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and
are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and
should be independently verified with primary sources of information. Taylor and Francis shall not be liable for
any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever
or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of
the Content.
This article may be used for research, teaching, and private study purposes. Any substantial or systematic
reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any
form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://
www.tandfonline.com/page/terms-and-conditions
APPLIED DEVELOPMENTAL SCIENCE, 18(3), 123–138, 2014
Copyright # Taylor & Francis Group, LLC
ISSN: 1088-8691 print=1532-480X online
DOI: 10.1080/10888691.2014.924355
Exposure to Neighborhood Afﬂuence and Poverty
in Childhood and Adolescence and Academic
Achievement and Behavior
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
Sara Anderson and Tama Leventhal
Tufts University
Ve´ronique Dupe´re´
Univeriste´ de Montre´al
Evidence points to associations between the socioeconomic composition of neighborhoods and children’s and adolescents’ development. A minimal amount of research,
however, examines how timing of exposure to neighborhood socioeconomic conditions
matters. This study used longitudinal data from the NICHD Study of Early Child Care
and Youth Development (N ¼ 1,364) to explore if timing of exposure (early childhood,
adolescence, and cumulative) to neighborhood afﬂuence and poverty had differential
associations with children’s achievement and behavior problems concurrently and in
adolescence. Results indicate that children in neighborhoods with more afﬂuent residents during early childhood had higher achievement and fewer internalizing behaviors
contemporaneously and that these associations endured until adolescence for reading
achievement. Long-term exposure to afﬂuent neighborhoods was associated with children’s math and reading achievement in adolescence. Findings are discussed in terms
of research and policy implications.
Neighborhoods are an important social context for
children and adolescents because they provide access to
resources, opportunities, and interactions that inﬂuence
development (Sampson, 2000). One of the most consistent empirical ﬁndings supporting this view is the frequently observed association between neighborhood
socioeconomic status (SES) and children’s development
(Leventhal, Dupe´re´, & Shuey, in press). Neighborhood
afﬂuence, often conceptualized as the presence of afﬂuent, college-educated, and=or professional residents, is
favorably associated with children’s and adolescents’
achievement-related outcomes, such as test scores and
educational attainment (e.g., Boyle, Georgiades, Racine,
& Mustard, 2007; Sastry & Pebley, 2010). Neighborhood
afﬂuence may be important for children’s achievement
because those living in afﬂuent neighborhoods typically
Address correspondence to Sara Anderson, Center for Promise,
177 College Avenue, Eliot-Pearson Department of Child Study and
Human Development, Tufts University, Medford, MA 02155. E-mail:
[email protected]
have access to high quality institutions and have daily
exposure to role models supportive of education
(Dupe´re´, Leventhal, Crosnoe, & Dion, 2010). Conversely, neighborhood poverty or disadvantage, typically
deﬁned in term of residents with incomes below the
poverty level, who are unemployed, and who receive
public assistance, places children and adolescents at risk
for social, emotional, and behavioral problems (e.g.,
Dupe´re´, Lacourse, Willms, Leventhal, & Tremblay,
2008; Xue, Leventhal, Brooks-Gunn, & Earls, 2005).
Neighborhood poverty may be central for children’s
functioning because it erodes neighborhood institutions and social cohesion and control, which can cause
a breakdown in shared norms and values regarding
young people’s behavior (Sampson, Morenoff, &
Gannon-Rowley, 2002). Thus, the ways in which
neighborhood afﬂuence and poverty contribute to
children’s development as well as what they signal
about community resources and processes are likely
quite distinct.
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
124
ANDERSON ET AL.
Despite rather consistent evidence that neighborhood
SES is linked with developmental outcomes in both
childhood and adolescence, several reviews suggest that
adolescence may be a period of unique vulnerability to
direct neighborhood effects (Leventhal et al., in press;
Steinberg & Morris, 2001). A minimal amount of
empirical research, however, has explored whether
neighborhood inﬂuences are particularly salient during
adolescence or the issue of developmental timing and
neighborhood exposure more generally (as exceptions,
see Sastry & Pebley, 2010; Wheaton & Clarke, 2003).
Moreover, the few studies that address this topic are
limited in scope because they did not consider both
neighborhood afﬂuence and poverty or a range of
developmental outcomes. As such, this study’s goal is
to close these gaps by using longitudinal data from a
diverse sample of youth followed from birth through
early adolescence to examine associations between
exposure to neighborhood afﬂuence and poverty in
early childhood and=or adolescence, and children’s
achievement (reading and math) and behavior problems
(externalizing and internalizing) during those same
developmental periods. The timing of exposure to
neighborhood afﬂuence and poverty is important to
consider, as the role of the neighborhood context may
vary as children experience different demands and transitions across development (Elder, 1995). Identifying
which aspect of neighborhood SES matters most, for
which outcomes, and when is critical for informing
policy and practice.
Issues related to selection bias are a major threat to
the validity of studies linking neighborhood characteristics and development. Families have some choice as to
where they live and any observed associations between
neighborhood SES and children’s development, regardless of timing, may be due to unmeasured characteristics
(e.g., personality, mental health) that lead parents to
choose certain neighborhoods and that are associated
with children’s development. Several approaches have
been used to address selection bias. The most powerful
are experimental studies conducted in the context of
housing programs for poor families. Moving to Opportunity is the most well-known experimental study in
which a subset of poor, mostly minority families living
in public housing in high poverty neighborhoods were
given the opportunity to move to low poverty neighborhoods, while another subset remained in high poverty
neighborhoods. A recent 10-year evaluation reported
beneﬁcial effects of moving from high- to low-poverty
neighborhoods (vs. staying in high poverty) on adolescent girls’ mental health outcomes (Sanbonmatsu
et al., 2011). Although methodologically strong, experiments have their limitations, notably around issues of
generalizability of results obtained in the very speciﬁc
context of relocation out of highly disadvantaged urban
neighborhoods. Because of our interest in associations
between a more normative range of neighborhood conditions and development, we took an observational
approach, common in the ﬁeld. Studies using wellcontrolled observational designs are thought to be a
necessary to complement the results from experimental
studies that address a very narrow set of research
questions (Wright, 1999).
Conceptual Models of Neighborhood Timing
Ecological and developmental systems theories describe
how children are nested in interrelated contexts, including family, neighborhood, school, and peers, that are
critical for development; the salience of these contexts
shifts across development (Bronfenbrenner & Morris,
2006; Elder, 1995; Lerner, 2006). Developmental challenges during these periods are relatively universal and
require new modes of adaptation to biological, psychological, or social changes (Graber & Brooks-Gunn,
1996). Moreover, a life-course perspective suggests that
development is lifelong and that no period should be
considered in isolation (Johnson, Crosnoe, & Elder,
2011).
Bioecological and developmental systems theories
should be employed in conjunction with domainand period-speciﬁc developmental transitions to make
predictions about how and when neighborhoods matter. For example, adolescents have more independence, afﬁliate more with peers, and have more
direct access to the neighborhood social and physical
environment than younger children so adolescence
may be a period when exposure to neighborhood conditions is particularly relevant (Steinberg & Morris,
2001). However, rapid cognitive, physical, and socioemotional development during early childhood and the
importance of access to resources during this period
raise the possibility that early childhood may be a period when neighborhoods matter most (Shonkoff &
Phillips, 2000). Based on these perspectives, we propose three theoretical models for conceptualizing the
timing of neighborhood effects: early exposure and
carry forward, adolescent exposure, and cumulative
exposure (see Figure 1). The models focus the analytic
approach to our study. These models are likely to be
complementary, varying in applicability by aspect of
neighborhood SES and child outcome. We present
the theoretical and empirical grounds for each model
in the larger developmental and neighborhood literature. For each model, we consider achievement and
internalizing and externalizing behaviors because they
represent distinct domains of development that can
have implications for subsequent functioning (Duncan
& Magnusson, 2011; Lescheid, Chiodo, Nowicki, &
Rodger, 2007).
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
EXPOSURE TO NEIGHBORHOOD AFFLUENCE AND POVERTY
125
FIGURE 1 Conceptual models of neighborhood afﬂuence and poverty on child outcomes.
Early Exposure and Carry Forward Model
The early exposure and carry forward model proposes
that early exposure to neighborhood SES is associated
with children’s concurrent and, likely, their later development. This model grows out of developmental
research pointing to early childhood as a period of
unique vulnerability to environmental inﬂuences (Carnegie Corporation, 1994). Because children’s cognitive
abilities develop throughout childhood and adolescence
and build upon prior skills, early childhood experiences
may set children on a trajectory that carries into later
development (Magnuson, Duncan, & Kalil, 2006). A
relatively large body of research on family economic status has explicitly tested whether the association between
economic conditions and children’s outcomes varies
across developmental periods (Brooks Gunn, Duncan,
& Maritato, 1997; Duncan & Brooks-Gunn, 1997;
Evans & Schamberg, 2009; Guo, 1998; McLeod &
Shanahan, 1996). Consistent with an early exposure
model, research on family income indicates that
exposure to poverty during early childhood, as opposed
to other developmental periods, is most salient for
children’s achievement (vs. behavior problems) (e.g.,
Duncan & Brooks-Gunn, 1997).
Extant research demonstrates the importance of
neighborhood SES during early childhood for achievement and, to a lesser extent, behavioral functioning. A
study with a British sample found that early childhood
neighborhood poverty was associated with achievement
at that time but not in middle childhood or adolescence
(McCulloch & Joshi, 2001). Another study with a diverse
U.S. sample reported that neighborhood afﬂuence in
early childhood was associated with children’s reading
achievement in ﬁrst grade, but not with subsequent
learning rates into adolescence (Dupe´re´ et al., 2010). A
ﬁnal study using nationally representative data found
that exposure to neighborhood poverty in childhood,
compared with exposure in adolescence or early adulthood, had the largest associations with mental health
in early adulthood (Wheaton & Clarke, 2003). Thus,
several studies point to the importance of exposure to
neighborhood conditions during early childhood; however, comparisons with other periods and across multiple
domains of functioning are lacking. Based on this limited
126
ANDERSON ET AL.
body of research, we hypothesized that early childhood
exposure to neighborhood afﬂuence will be favorably
associated with contemporaneous achievement and that
this association will persist into adolescence.
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
Adolescent Exposure Model
The adolescent exposure model proposes that neighborhood SES has pronounced associations with developmental outcomes during this period (McLoyd et al.,
2009). This expectation is based on the fact that by early
adolescence, and to a lesser extent middle childhood
(Eccles, 1999), parents begin to grant older children more
autonomy than in prior developmental periods. Thus, in
adolescence, youth typically have more direct exposure
to extra-familial inﬂuences than in prior periods, notably
to neighborhoods and peer groups (Brown & Larson,
2009). Somewhat surprisingly, almost no research has
explored the premise that neighborhood effects are
especially pronounced in adolescence; however, indirect
support for this notion comes from the large body of
research examining neighborhood SES and adolescents’
development, particularly links between poverty and
adolescents’ delinquent, criminal, and violent behavior
(Sampson, Morenoff, & Rowley, 2002). The focus on
problem behaviors, such as drinking and delinquency,
likely stems from their well-documented increase in
adolescence (Loeber & Burke, 2011; Mofﬁtt, 1993) and
from the peer-oriented nature of these behaviors (Dodge,
Coie, & Lynam, 2007).
A restricted body of neighborhood research that
speciﬁcally compares developmental periods does not generally support the adolescent exposure model (for example
Wheaton & Clarke, 2003, as reviewed in the prior section).
A study employing longitudinal data on a diverse sample
of youth reported associations among middle childhood
and adolescent neighborhood safety with adolescent and
young adult depression and substance use (Kiff et al.,
2012), but differences in the associations between periods
were not directly tested. Yet, a large body of work demonstrates associations between adolescent neighborhood
poverty with concurrent outcomes (for reviews see
Leventhal, Dupe´re´, & Brooks-Gunn, 2009; McBride
Murry, Berkel, Gaylord-Harden, Copeland-Linder, &
Nation, 2011), although associations are generally not
compared with other developmental periods. With respect
to this model, we hypothesized that neighborhood poverty
will be more strongly associated with children’s externalizing behaviors during adolescence than during prior
developmental periods and for other outcomes.
neighborhood conditions may be more strongly
associated with adolescents’ outcomes than exposure
during any single period. Individual exposure to neighborhood SES may have a variety of trajectories based
on neighborhood change across time and residential
moves, with differential implications for children’s behavior (Leventhal & Brooks Gunn, 2011). Likewise, prior
research on family economic conditions indicates that
living in poverty continuously, compared with no
exposure to poverty, had a large adverse association with
children’s achievement and that associations for transient
poverty were small (Smith, Brooks-Gunn, & Klebanov,
1997). Accordingly, we examined how trajectories of
children’s exposure to neighborhood afﬂuence or poverty
over time may differentially shape their development.
A minimal amount of research, to our knowledge, has
examined children’s neighborhood trajectories and
adolescent development; however, studies examining
exposure to neighborhood SES over time may be
informative. Findings from a nationally representative,
longitudinal study reported that associations among
neighborhood income and children’s achievement and
behavior were strongest for those who lived in their
neighborhoods for three or more years (Lo´pez Turley,
2003). Other studies using national data found that
cumulative measures of neighborhood SES, as opposed
to a single point in time measure, had larger associations
with adolescents’ odds of high school dropout and sexual
initiation (Crowder & South, 2011; South & Crowder,
2010; Wodtke, Harding, & Elwert, 2011). This body of
research suggests that long-term exposure to various trajectories of neighborhood afﬂuence and poverty may be
differentially associated with adolescent outcomes than
single measures within developmental period.
Speciﬁcally, we anticipated different trajectories of
neighborhood afﬂuence and poverty, ones indicating
stability and change over time, based on demographic
trends at the family and neighborhood levels (Kan,
1999; Schachter, 2001). We expected that exposure to
neighborhood conditions marked by growing advantaged or disadvantaged circumstances will be associated
with children’s achievement (higher achievement living
in high and increasing afﬂuence) and externalizing behaviors (more problem behaviors living in high and increasing poverty) in adolescence. Given research suggesting
adverse internalizing outcomes for exposure to point-intime measures of neighborhood afﬂuence and poverty
(Luthar, 2003; Xue et al., 2005), we did not develop a
speciﬁc hypotheses for this outcome.
Current Study
Cumulative Exposure Model
The cumulative exposure model is based on the assumption that prolonged exposure to adverse or favorable
The goal of this study was to examine developmental
differences in associations between exposure to early
childhood and adolescent neighborhood afﬂuence and
EXPOSURE TO NEIGHBORHOOD AFFLUENCE AND POVERTY
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
poverty and children’s outcomes in early childhood and
adolescence; and to examine differences in associations
between cumulative aspects of neighborhood afﬂuence
and poverty, indicated by the trajectories of neighborhood afﬂuence and poverty, and adolescent outcomes.
The outcomes considered are achievement and behavior
problems. Although we explored all associations
between neighborhood afﬂuence and poverty and participants’ outcomes, we anticipated different associations
depending on participants’ developmental status, trajectories of exposure, and outcome of interest as reviewed
in the prior sections.
METHOD
Study Design and Sample
This study used data from the NICHD Study of Early
Child Care and Youth Development (NICHD SECCYD, see NICHD Early Child Care Research Network,
2005). Data collection began in ten sites across the
United States in 1991 in: Little Rock, AR; Irvine, CA;
Lawrence, KS; Boston, MA; Philadelphia, PA;
Pittsburgh, PA; Charlottesville, VA; Morganton, NC;
Seattle, WA; Madison, WI. Participants were recruited
by hospital visits around the time the child was born.
To be eligible for the study, the mother had to be at least
18 years of age, healthy, and conversant in English, and
the infant had to be a singleton. One month
post-recruitment, 1,364 families enrolled in the study.
The collection of data occurred in the home, laboratory,
child care, and school settings from birth through
approximately ninth grade (15 years of age) and proceeded in four phases with multiple assessment periods,
from every six months to annually, within each phase
(birth to 54 months, kindergarten to ﬁrst grade, second
to sixth grade, and seventh grade to ninth grade). The
SECCYD is not nationally representative, but it
included children from across the socioeconomic spectrum and was representative of its catchment areas. It
is comprised of 18% racial=ethnic-minority children,
10% low-education mothers (less than a high school),
and 21% single parents. The study was primarily
designed to examine the long-term associations between
early childhood care and later development but has been
used to examine diverse facets of development, including
neighborhoods and child development (e.g., Dupe´re´
et al., 2010; Lund & Dearing, 2012).
As is common in longitudinal studies, some participants dropped out, missed occasional data collection
points, and=or had partial missing data on speciﬁc measures. Data were missing for 0% (demographic characteristics, early childhood measures) to 30% (measures of
adolescent behavior) of the sample. No single covariate
127
signiﬁcantly predicted missingness of grade nine outcome
variables (which had the most missing data), which we
take as evidence that data were missing at random (full
results available from ﬁrst author upon request). We
employed full information maximum likelihood (FIML)
estimation techniques with robust standard errors in
Mplus 7.0 to handle missing data and 10 multiply
imputed data sets with Stata 12.0 for descriptive
analyses.
Measures
Three developmental periods—early childhood (birth to
54 months), middle childhood (kindergarten to grade
ﬁve), and early adolescence (grade six to grade nine)—
were distinguished in our study. Early childhood and
adolescence were the focus of the analyses reported here
given our theoretical models that propose associations
between neighborhood SES and child outcomes in early
childhood, adolescence, or cumulatively (with associations with adolescent outcomes) and a general lack of evidence for associations between neighborhood SES and
middle childhood outcomes over and above exposure in
other periods (e.g., Wheaton & Clarke, 2003).
Achievement
Reading and math achievement were measured on
three occasions (54 months, ﬁfth grades, and ninth
grade) by subtests of the Woodcock-Johnson PsychoEducational Battery-Revised (WJ-R, Woodcock &
Johnson, 1989). For reading achievement, no single
subtest was administered throughout the observation
window; earlier subtests gauged basic reading skills,
whereas later subtests assessed more complex abilities
such as comprehension. The Letter-Word Identiﬁcation
(LW) subtest was used at 54 months, broad reading ability at ﬁfth grade (letter-word, reading ﬂuency, and passage comprehension), and Passage Comprehension at
ninth grade. For math achievement, a single subtest,
Applied Problems (AP), was used at all periods. All
subtests had high internal reliabilities (a ¼ .81 to .92).
Raw scores on reading and math subtests were converted to W scores, special transformations of the Rasch
ability scale that centered the raw score on a value of
500, to assess change over time.
Behavior Problems
Externalizing and internalizing behaviors were
measured by standardized subscales of the Child Behavior Checklist (CBCL; Achenbach, 1991a) completed
by parents at 54 months, ﬁfth grade, and ninth grade.
Children also completed the Youth Self Report at ninth
grade (YSR; Achenbach, 1991b). The externalizing scale
128
ANDERSON ET AL.
consists of the Delinquent Behavior (e.g., lies or cheats)
and Aggressive Behavior (e.g., argues a lot) subscales
(a ¼ .84 to .91). The internalizing behavior scale is comprised of the Withdrawn (e.g., won’t talk, shy, sad),
Somatic Complaints (e.g., dizzy, tired, stomachaches),
and Anxious=Depressed (e.g., lonely, cries, worthless)
subscales (a ¼ 86 to .87). For both scales, possible scores
ranged from 30 to 100, with higher scores indicating
greater afﬁnity to display behavior problems. Both
measures are normally distributed (skew ¼ .17 to .27).
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
Neighborhood SES
The main variables of interest were neighborhood
afﬂuence and poverty. On an annual basis, families’
reported addresses (including any interim address
changes) were linked to 1990 (1–54 months; early childhood) and 2000 (ﬁrst through ninth grade; middle childhood and adolescence) U.S. Census data at the block
group level. Census block groups are subdivisions of
a census tract that comprise a combination of street
blocks and contain from 600 to 3,000 residents. Following previous work (e.g., Duncan & Aber, 1997), we created standardized composite variables for neighborhood
afﬂuence and poverty indicators for each developmental
period by taking the average of all Census indicators
within each period. Neighborhood afﬂuence consisted
of the percentage of adults with at least a B.A. degree
and the percentage of adults in managerial=professional
jobs. Neighborhood poverty included the percentage of
single mothers, the percentage of households under the
U.S. poverty level, and the percentage of adults unemployed. (See Appendix A for correlations among
neighborhood variables.) Conﬁrmatory factor analysis
supported the appropriateness of our neighborhood
SES measures for each developmental period. All ﬁt
statistics indicated good model ﬁt and coefﬁcients from
observed to latent variables were of the appropriate and
anticipated size and magnitude (results available upon
request). The ranges of the standardized neighborhood
afﬂuence values were 2.25 to 3.52 (early childhood),
2.67 to 2.87 (middle childhood), and 2.96 to 2.78
(early adolescence). Ranges for standardized neighborhood poverty were: 2.09 to 7.24 (early childhood),
1.68 to 5.71 (middle childhood), and 2.60 to 7.23
(adolescence). Although residential mobility was common, participants tended to move to relatively similar
neighborhoods (results available upon request).
Child, Parent, and Family Background Control
Variables
A wide variety of child=adolescent, parent, and
family background characteristics were employed to
minimize, though not eliminate, the threat of selection
bias, as suggested by prior research (e.g., Anderson,
Leventhal, & Dupe´re´, 2014). Both ﬁxed and time varying covariates were used in our analyses. Fixed child
covariates employed included child gender (female ¼ 0;
male ¼ 1) and race=ethnicity (with two dichotomous
variables indicating Black and other race=ethnicity, with
White as omitted referent). Fixed maternal covariates
include education and age (in years), verbal ability
assessed by the Peabody Picture Vocabulary TestRevised (PPVT-R, Dunn & Dunn, 1981), beliefs about
parenting (traditional and progressive; Schaefer &
Edgerton, 1985), personality characteristics due to the
potential association with proclivity to move (neuroticism, extroversion, and agreeableness; Costa & McCrae,
1985); and study site (with a set of nine dummy variables). The time-varying covariates were characteristics
measured across the three developmental periods and
were entered as covariates on each of the neighborhood
SES variables. They included maternal depression as
measured by the Center for Epidemiological Studies
Depression Scale (CES-D; Radloff, 1977; a ¼ .88); the
percentage of time that parents were married; an
average of annual income-to-needs ratio (total annual
family income divided by ofﬁcial poverty threshold for
household size); and the number of times the child
moved, assessed from mother-reported addresses at
yearly interviews.
Analytic Strategies
To examine our hypotheses about how neighborhood
afﬂuence and poverty were associated with children’s
achievement and behavior problems, path analyses were
used to test our early and adolescent exposure models,
and growth mixture models (GMM) were used to test
our cumulative exposure model. We selected these
approaches over alternative ones for several reasons.
First, multilevel modeling was not used because there
was insufﬁcient clustering of participants within neighborhoods to warrant that approach and ICCs could
not be calculated (Raudenbush & Bryk, 2002); 65–83%
of participants (depending on the study year) were the
only study child in their neighborhood. Second, as an
alternative to GMM, we considered individual growth
curve models, path models, and latent cumulative models but rejected them because of concerns about
assuming linear relationships between and among variables (additional details and results available from
authors upon request). Thus, the selected approaches
were deemed most appropriate for testing our research
questions given the available data.
As a ﬁrst step, we developed growth mixture models
(GMMs) for our cumulative exposure models. These
models assigns respondents to subgroups within a
sample based on latent associations among selected
EXPOSURE TO NEIGHBORHOOD AFFLUENCE AND POVERTY
129
TABLE 1
Descriptive Statistics for Neighborhood, Achievement, Externalizing, Internalizing Variables, and Covariates by Developmental Period
Early Childhood
Middle Childhood
Adolescence
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
a
Neighborhood
Proportion single moms
Proportion HH < 100% poverty
Proportion unemployed adult
Proportion with B.A.
Proportion with professional job
Covariates
Child characteristics
Male
White
Black
Minority—other
Maternal age
Maternal education
PPVT-R
Traditional parent beliefs
Progressive parent beliefs
Neuroticism
Agreeableness
Extroversion
% time father’s=mother’s partner
in home
# times moved
Maternal depression
Income=needs
Achievement
WJ Reading
WJ Math
Externalizing
Internalizing
M
M
M
M
M
(SD)
(SD)
(SD)
(SD)
(SD)
%
%
%
%
M (SD)
M (SD)
M (SD)
M (SD)
M (SD)
M (SD)
M (SD)
M (SD)
M (SD)
M (SD)
M (SD)
M (SD)
M
M
M
M
(SD)
(SD)
(SD)
(SD)
8.92
10.41
5.30
26.77
33.58
(8.48)
(10.02)
(5.12)
(17.56)
(14.35)
51.7%
80.4%
12.9%
6.7%
28.10
14.23
97.99
60.39
32.71
29.89
46.44
42.44
.69
(5.64)
(2.51)
(19.66)
(15.23)
(3.53)
(7.53)
(5.57)
(6.28)
(.40)
1.08 (1.40)
9.88 (6.59)
3.40 (2.74)
368.86
423.51
51.86
47.27
(24.02)
(22.65)
(10.13)
(10.47)
10.06
8.89
4.58
31.41
37.81
(8.87)
(8.38)
(5.17)
(19.83)
(16.27)
9.10
8.37
4.36
31.97
38.30
(8.98)
(8.45)
(6.01)
(20.70)
(17.03)
.65 (.45)
.66 (.50)
1.06 (1.43)
8.90 (7.42)
3.95 (3.42)
.32 (.72)
9.85 (9.17)
4.70 (5.33)
507.26
510.32
45.99
48.88
(15.79)
(15.00)
(10.78)
(11.73)
519.50
523.69
49.70
47.45
(15.22)
(20.62)
(11.83)
(11.46)
Note. N ¼ 1,364. Results combined across 10 imputed datasets. HH refers to household. WJ is Woodcock-Johnson Psychoeducational
Battery (Woodcock & Johnson, 1989).
a
Conditions in early childhood based on 1990 U.S. Census and in middle childhood and adolescence on 2000 U.S. Census.
variables by identifying meaningful patterns of initial
status and change over time (Muthen, 2004). Using
FIML, GMM provides ﬁt information (i.e., Bayesian
Information Criterion [BIC], Akaike Information Criterion) to evaluate the number of groups (or classes) that
best captures the latent classes within the sample, the
accuracy of the groups identiﬁed, and the number of
participants per group. Using best practices in developing growth mixture models (Jung & Wickrama, 2007),
we chose the most parsimonious models by selecting
those with the lowest BIC, a signiﬁcant Low-MendellRubin likelihood (LMR; tests the k and nested k 1
models to determine which model best ﬁts the data),
entropy close to 1.0 (near 1.0 indicates perfect classiﬁcation), classes with no less than 5% of total sample
in a class, and from a visual inspection of the data with
plots of predicted classes. We considered the combination of ﬁt statistics, number of classes, and visual
inspection equally. We also conducted split-half
replications, and trajectories were the same.
We next tested our hypotheses regarding early,
adolescent, and cumulative exposure to neighborhood
SES1. All models included the full battery of covariates
described in the previous section (see Table 1) and children’s achievement or behavioral problems at prior
ages, providing important additional controls over
potential selection or omitted variable bias. We estimated three models for each outcome (math and reading
achievement and externalizing and internalizing behaviors). In Model 1, early childhood outcomes were predicted from early childhood neighborhood SES
variables using path models, to test the early childhood
hypotheses. For Model 2, we used path models (one for
each outcome) to predict early childhood and adolescent
outcomes from early childhood and adolescent neighborhood afﬂuence and poverty variables to probe the
1
We chose our analyses to speciﬁcally test our proposed models,
omitting direct tests of middle childhood and early adolescence for
example.
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
130
ANDERSON ET AL.
carry forward and adolescent exposure hypotheses. We
did not include middle childhood neighborhood characteristics because they did not demonstrate signiﬁcant
associations with child outcomes in middle childhood
and were collinear with adolescent neighborhood variables. We examined the indirect effects of early childhood neighborhood SES to early adolescent outcomes
through middle childhood outcomes using the Model
Indirect command in Mplus to test the carry forward
hypothesis. The delta method, used in the Sobel Test,
was employed in computing standard errors with this
command (Muthe´n & Muthe´n, 1998–2010). The chi
square (v2), comparative ﬁt index (CFI), standardized
root mean squared residual (SRMR), and the root mean
square error of approximation (RMSEA) were examined to assess model ﬁt. Signiﬁcant chi square values
indicate poor ﬁt. CFI values of >0.90 indicate an
adequate ﬁt, and values of >0.95 indicate a good ﬁt of
the data to the model (Hu & Bentler, 1999). Values
<0.08 of the SRMR are considered favorable. RMSEA
values <0.06 indicate a good ﬁt.
Finally for Model 3, we tested the cumulative
exposure model with the classes identiﬁed through
GMMs and conducted chi square analyses to determine
if identiﬁed classes were differentially associated with
adolescents’ outcomes at ninth grade (Model 3; see
Figure 1 for conceptual representations of all models).
For these models, we were unable to examine the identiﬁed latent growth classes with the child outcomes and
covariates in a single model because Mplus does not
permit the use of latent classes and covariates to predict
an outcome in a single model. As such, the residuals of
regression equations predicting the child outcome from
all previously described covariates were employed in
these analyses, a technique used in prior analyses
(Jung & Wickrama, 2007), and one that is analytically
comparable.
RESULTS
Descriptive Analyses
Descriptive analyses by developmental period are presented in Table 1. Generally, neighborhood afﬂuence
indicators increased across developmental periods. In
addition, family income-to-needs increased over time,
suggesting growth in family wealth over time. Conversely, neighborhood poverty indicators declined from
early childhood to middle childhood and early adolescence. Participants generally moved more often during early and middle childhood than in adolescence.
Neighborhood afﬂuence and poverty variables were correlated with participant’s outcomes in the anticipated
directions. (See Appendix B for correlations between
the neighborhood variables and child and adolescent
outcomes.)
Cumulative Neighborhood SES: Growth Mixture
Models
Two latent class growth curves were developed to examine stability and change over time in children’s exposure
to neighborhood afﬂuence and poverty, and perhaps
more importantly, to investigate how different types of
cumulative exposure to neighborhood afﬂuence or poverty were associated with adolescents’ achievement and
behavior. Based on the criteria described, results of the
GMM indicated four distinct trajectories of neighborhood
afﬂuence (see Table 2 and Figure 2): high-increasing
(10.2% of sample; intercept ¼ 1.60, p < .001; slope ¼ .09,
p < .05), moderate=high-increasing (22.3%; intercept
¼ .74, p < .001; slope ¼ .08, p < .05), moderate-stable
(29.0%; intercept ¼ .14, p < .05; slope ¼ .004, ns), and
low-decreasing (38.2%; intercept ¼ .85, p < .001; slope ¼
.08, p < .01).
For the neighborhood poverty model, two distinct
groups were observed and ﬁt the data best, with most
participants (88.5%; intercept ¼ .22, p < .001; slope ¼
.01, ns) in the low=moderate-stable neighborhood poverty class, whereas 11.5% were in the high-stable poverty
class (intercept ¼ 1.72, p < .001; slope ¼ .07, ns).
Predicting Achievement and Behavior: A
Comparison of Three Models
In this section, we describe the results pertinent to the
three theoretical models by outcome. Results of path
analyses for the early exposure and carry forward
models are presented ﬁrst, followed by analyses for the
adolescent exposure model. Finally, we present results
of cumulative models with the GMM classes as main
independent variables. In all cases, the ﬁt statistics indicated a good ﬁt of the data to the models (see footnotes
of Table 3).
TABLE 2
Growth Mixture Models of Neighborhood High and Poverty From 1
Month Through Ninth Grade
Number of
Latent Classes
Number
Parameters
Neighborhood Poverty
2
8
3
11
Neighborhood Afﬂuence
2
8
3
11
4
14
5
16
y
p < .10;
p < .01;
BIC
Entropy
LMR
LRT (df)
8377.06
7855.48
.96
.89
1550.34 (3)
543.11 (3)y
8004.81
7398.44
7175.06
7784.77
.86
.81
.85
.84
1922.60
570.94
301.87
159.37
p < .001.
(3)
(3)
(3)
(3)
EXPOSURE TO NEIGHBORHOOD AFFLUENCE AND POVERTY
131
Achievement
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
Math
FIGURE 2 Distinct trajectories of neighborhood afﬂuence and poverty
across (1) early childhood, (2) middle childhood, and (3) early adolescence.
In Model 1, the results revealed that children who
lived in neighborhoods with more afﬂuent residents in
early childhood had higher early childhood math
achievement (b ¼ .07, p < .05); however, in Model 2,
when early childhood and adolescent neighborhood
afﬂuence variables were included in the same models,
the association between early childhood neighborhood
afﬂuence and concurrent math achievement was attenuated. Similarly, the indirect association between early
childhood afﬂuence and adolescents’ math achievement
through middle childhood math achievement was marginally signiﬁcant (see Table 3). The association between
living in a neighborhood with more afﬂuent residents in
adolescence and children’s math achievement in ninth
grade was signiﬁcant (b ¼ .08, p < .05). Thus, results
were primarily consistent with the adolescent exposure
hypothesis for neighborhood afﬂuence and math
achievement; no signiﬁcant associations were found for
neighborhood poverty and children’s math achievement.
In the overall model, the four neighborhood afﬂuence
latent classes marginally differentiated adolescents’
math achievement (v2 [3] ¼ 7.15, p ¼ .07); however, pairwise comparisons demonstrated that participants
exposed to high-increasing neighborhood afﬂuence had
greater math achievement in adolescence (M ¼ 3.99;
SD ¼ 1.99) than those exposed to either low-decreasing
TABLE 3
Unstandardized Path Coefficients From Path Models Relating Neighborhood High and Poverty to Achievement and Problem Behaviors
Math Achievement
Model 1
Model 2a
Reading Achievement
Model 1
Model 2b
Externalizing
Model 1
Model 2c
Internalizing
Model 1
Model 2d
Early Childhood Achievement
.59 (.44)
.66 (.44)
.22 (.38)
.24 (.38)
Early Childhood Poverty
1.06 (.83) .88 (.83) 1.54 (.89)y 1.25 (.89)
Early Childhood Afﬂuence
1.49 (.74) 1.45 (.77)y
2.54 (.84)
2.43 (.86) .20 (.38) .12 (.37) .73 (.35) .70 (.35)
Direct and indirect neighborhood SES
to adolescent achievement
Adolescent Poverty
.26 (.49)
.16 (.33)
.09 (.43)
.07 (.35)
Adolescent Afﬂuence
1.36 (.53)
.06 (.40)
.17 (.46)
.05 (.48)
Indirect early child poverty to
.24 (.22)
.16 (.12)
.05 (.04)
.02 (.03)
adolescence through middle
childhood outcome
Indirect early child afﬂuence to
.39 (.21)y
.31 (.11)
.01 (.03)
.06 (.03)þ
adolescence through
middle childhood outcome
Note. Standard errors in parentheses. Standardized scores are available upon request to the ﬁrst author and included within the body of the text if
p < .05. N ¼ 1,364. Covariates include, site, child gender, Black=Other race, maternal PPVT-R, personality characteristics, parenting beliefs, age, and
education; and repeated assessments of income=needs, proportion of time mother had husband=partner, residential mobility, and maternal
depression. Similar or identical results found when only investigated high or low neighborhood in separate models.
a
Fit indices: v2(30) ¼ 39.54, CFI ¼ .994, RMSEA (95% CI) ¼ .015 (.000, .027), SRMR ¼ .005.
b
Fit indices: v2(30) ¼ 37.89, CFI ¼ .995, RMSEA (95% CI) ¼ .014 (.000, .026), SRMR ¼ .004.
c
Fit indices: v2(30) ¼ 58.93, CFI ¼ .958, RMSEA (95% CI) ¼ .027 (.016, .037), SRMR ¼ .007.
d
Fit indices: v2(30) ¼ 58.93, CFI ¼ .958, RMSEA (95% CI) ¼ .027 (.016, .037), SRMR ¼ .007.
y
p < .10; p < .05; p < .01.
132
ANDERSON ET AL.
(v2 [1] ¼ 4.45, p ¼ .04; M ¼ .55; SD ¼ .80. d ¼ 2.99) or
moderate-stable (v2 [1] ¼ 5.35, p ¼ .02; M ¼ 1.39;
SD ¼ 1.25, d ¼ 3.24) neighborhood afﬂuence. Results
from the neighborhood poverty growth trajectories
revealed that cumulative exposure to neighborhood poverty was not signiﬁcantly associated with adolescent math
achievement (v2 [1] ¼ .96, p ¼ .33). Findings were consistent with the cumulative exposure hypothesis, but only for
neighborhood afﬂuence among some trajectories.
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
Reading
Model 1 suggested that living in a neighborhood with
more afﬂuent residents in early childhood was signiﬁcantly associated with children’s concurrent reading
achievement (b ¼ .10, p < .01). In Model 2, reading
achievement gains conferred by living in a neighborhood
with afﬂuent residents in early childhood were indirectly
associated with reading achievement in adolescence
through middle childhood achievement (b ¼ .02,
p < .01), but no support was found for the adolescent
exposure hypothesis. Exposure to neighborhoods with
more afﬂuent residents was associated with concurrent
reading achievement, which endured to early adolescence in further support of the early exposure and
carry forward hypothesis.
Results indicated no overall signiﬁcant differences in
reading achievement for children of different neighborhood afﬂuence trajectories (v2 [3] ¼ 5.13, p ¼ .16), but
several pairwise comparisons were signiﬁcant.
Participants who were exposed to high-increasing
neighborhood afﬂuence had higher reading achievement
in adolescence (M ¼ 2.55; SD ¼ 1.22) than those
exposed to either low-decreasing (v2 [1] ¼ 3.92, p ¼ .05;
M ¼ .30; SD ¼ .76, d ¼ 2.80) or moderate-stable
(v2 [1] ¼ 4.30, p ¼ .04; M ¼ .52; SD ¼ .86, d ¼ 2.91)
neighborhood afﬂuence. Results from the neighborhood
poverty model indicated that the two poverty neighborhood trajectories did not signiﬁcantly differentiate
adolescent reading achievement (v2 [1] ¼ .26, p ¼ .61).
In sum, ﬁndings partially support the cumulative
exposure hypothesis for neighborhood afﬂuence and
reading achievement.
Behavior Problems
Externalizing
No signiﬁcant associations emerged for early childhood or adolescent exposure to neighborhood afﬂuence
or poverty and children’s externalizing behaviors (see
Table 3). Furthermore, we found no evidence that differential cumulative exposure to neighborhood afﬂuence (v2
[3] ¼ 1.32, p ¼ .72) or poverty (v2 [1] ¼ 3.03, p ¼ .08) was
associated with participant’s externalizing behaviors.
Thus, no support for any of our hypothesized models
emerged for participant’s externalizing behaviors.
Internalizing
Exposure to afﬂuent residents in early childhood was
associated with fewer children’s concurrent internalizing
symptoms (Model 1; b ¼ .07, p < .05); however, in the
carry forward and early adolescent model (Model 2),
we found no indication that this relationship signiﬁcantly endured. In addition, neighborhood poverty
was not associated with children’s internalizing symptoms for either of our models.
The overall chi square for differences in internalizing
symptoms between the four neighborhood afﬂuence trajectories was non-signiﬁcant, indicating that exposure to
different trajectories was not associated with children’s
internalizing symptoms in adolescence (v2 [3] ¼ 2.743
p ¼ .49). All pairwise comparisons were non-signiﬁcant
as well. Similar results were found for children’s exposures to the cumulative neighborhood poverty trajectories and their internalizing symptoms in adolescence
(v2 [1] ¼ 1.51, p ¼ .22). In short, we found no support
for the cumulative exposure model for neighborhood
afﬂuence or poverty and children’s internalizing
symptoms.
DISCUSSION
This study is one of the ﬁrst, to our knowledge, to
explore how associations between neighborhood afﬂuence and poverty and children’s achievement and behavior problems varied as a function of time and timing of
exposure. With the beneﬁt of a longitudinal design and a
rich set of stable and time-varying covariates to minimize selection bias, we found differential associations
between neighborhood afﬂuence and poverty and participant’s achievement and externalizing and internalizing
behaviors depending on the timing of exposure. Our
ﬁndings generally supported the early exposure and
cumulative exposure models for achievement and to a
lesser extent the adolescent exposure model for math
achievement only. Results contribute to developmental
theory and build upon prior research on neighborhood
dynamics.
Socioeconomic conditions in early childhood have
been found to be critical to concurrent and later achievement (Duncan, Ziol-Guest, & Kalil, 2010). It was thus
expected that associations between neighborhood SES
and developmental outcomes would be strong during
early childhood. In line with these expectations, results
revealed that neighborhood afﬂuence in early childhood
was favorably associated with children’s math and
reading achievement and internalizing symptoms at that
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
EXPOSURE TO NEIGHBORHOOD AFFLUENCE AND POVERTY
time. However, this advantage endured to adolescence
for reading achievement only, providing modest support
for the carry-forward hypothesis. Overall, these ﬁndings
are consistent with the limited neighborhood research on
developmental timing (e.g., Wheaton & Clarke, 2003) as
well as research on family poverty (Brooks Gunn &
Duncan, 1997), as both literatures highlight the sensitivity of early childhood to socioeconomic inﬂuences.
Although it was expected that the early exposure
model would apply primarily to achievement outcomes,
it is not surprising that it extended to internalizing problems as well. Prior research supports the notion that
neighborhood afﬂuence may play a protective role in
children’s development of internalizing behaviors (Xue
et al., 2005). Indeed, neighborhood advantage has been
shown to support effective parenting behaviors,
including the provision of stimulating experiences as
well as parental warmth (e.g., Kohen, Brooks-Gunn,
Leventhal, & Hertzman, 2002), which are conducive to
both achievement and socioemotional functioning.
Alternatively, the same institutional resources that promote children’s early achievement in afﬂuent neighborhoods, such as quality preschool programs as well as
recreational and social programs, may foster their
socioemotional well-being (Dupe´re´ et al., 2010).
The association between neighborhood afﬂuence and
developmental outcomes in early childhood reinforces
other work highlighting the importance of socioeconomic contexts during early childhood for concurrent
and subsequent development (Duncan & Brooks-Gunn,
1997; Shonkoff & Phillips, 2000); however our ﬁndings
mainly point to current beneﬁts and not ones that are
carried forward (except for reading). Early neighborhood afﬂuence may facilitate or limit exposure to social
contexts that are relevant for the development and promotion of children’s school-readiness skills. Once children enter formal schooling, however, neighborhood
inﬂuences may be mitigated by exposure to school contexts that are similar across large populations of children, as opposed to diverse and changing child care
and preschool contexts that characterize children’s
experiences in early childhood (Dearing, McCartney,
& Taylor, 2009). In addition, early childhood trajectories may be reinforced, and possibly augmented, by
subsequent contexts (Crosnoe, Leventhal, Wirth, Kim,
& Pianta, 2010), but our results only supported this
notion for children’s reading achievement. The beneﬁts
of neighborhood afﬂuence also may carry forward to
adolescence only for children’s reading because afﬂuent
neighborhoods’ resources such as libraries and enrichment programs may be especially relevant for early
literacy skills (Neuman & Celano, 2001).
The effect sizes for neighborhood afﬂuence associations with children’s achievement and internalizing
symptoms were small (Cohen, 1988), approximately
133
.08 to .10 for achievement and .07 for internalizing,
comparable to those reported in the literature
(Leventhal & Brooks-Gunn, 2000). Nonetheless, a comparison of effect sizes for background factors known to
be associated with children’s achievement such as
mother’s education, verbal ability, and family incometo-needs ratio reveals that the effect sizes for neighborhood afﬂuence were comparable if not larger than other
factors in this study (e.g., Bradley & Corwyn, 2002), suggesting that neighborhood afﬂuence is an important
context that should not be overlooked in studies of
children’s achievement.
Results provided some support for the cumulative
exposure model, at least when it comes to neighborhood
afﬂuence and achievement. Findings indicated, in line
with other studies (e.g., Crowder & South, 2011), that
long-term exposure to neighborhood afﬂuence, compared with exposure to low-decreasing or moderate
neighborhood afﬂuence, may be advantageous for adolescents’ achievement. Prolonged exposure to an advantaged neighborhood context in particular, compared
with one marked by stagnant or declining afﬂuence,
may allow for an accumulation of beneﬁts over time
from high-quality resources that support learning in
children’s everyday lives, notably childcare=preschools
and schools (Heckman, 2008).
It is notable that individuals exposed to the most
afﬂuent neighborhoods consistently (that is, starting in
childhood) had better outcomes than those exposed to
less afﬂuent neighborhoods at some point during childhood or adolescence. Meanwhile, we found very limited
support for the carry forward and adolescent exposure
models. Even in the absence of consistent support for
these models, and without sustained effects of early
afﬂuence, it may be that differences in achievement during adolescence are found only for those continuously
exposed to the most afﬂuent neighborhoods. Exposure
to such neighborhoods in adolescence only may have
been insufﬁcient to shape development. Thus, the results
suggest that exposure to afﬂuent neighborhoods is likely
most beneﬁcial if that exposure is prolonged, perhaps
similar to the way in which exposure to chronic (vs.
transient) childhood poverty is associated with more deleterious outcomes (e.g., Najman et al., 2009).
Unexpectedly, we found no evidence for a link
between cumulative exposure to neighborhood poverty
(vs. low levels of neighborhood poverty) and children’s
externalizing or internalizing behaviors as expected
and in line with prior work (e.g., Leventhal & Brooks
Gunn, 2011). This ﬁnding could result from limited variation in neighborhood poverty, as this sample includes
relatively few participants from highly disadvantaged
neighborhoods (although standardized neighborhood
poverty variables varied considerably). Our sample
also was geographically diverse, whereas prior studies
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
134
ANDERSON ET AL.
documenting associations between neighborhood
poverty and children’s socioemotional development
often rely on exclusively urban samples with greater
concentrations of neighborhood disadvantage (e.g.,
Criss, Shaw, Moilanen, Hitchings, & Ingoldsby, 2009).
Perhaps neighborhoods characterized by relatively low
levels of disadvantage (even as compared with those
with lower levels) maintain social cohesion and control
and limit exposure to antisocial role models thought to
underlie links between neighborhood poverty and
adverse childhood outcomes (Sampson et al., 2002).
In general, we found limited support for the adolescent exposure model, particularly with respect to
neighborhood poverty and children’s behavior problems. This ﬁnding is surprising given the abundance of
studies linking adolescent neighborhood characteristics
and such outcomes (Leventhal et al., 2009). The lack
of association may be explained by the fact that we
examined adolescence up to ninth grade, or 15 years
old, whereas exposure to neighborhood conditions
may become more important later in adolescence as
autonomy is further established. For example, research
demonstrates that aggressive and antisocial behavior
tends to peak around 17 years old (Dodge et al., 2007;
Mofﬁtt, 1993), an age excluded in our sample. In
addition, controlling for prior exposure to neighborhood conditions may have restricted the variance in
adolescent outcomes, a factor perhaps not accounted
for in prior studies. However, models that included only
adolescent neighborhood poverty were similar to those
incorporating both the early childhood and adolescent
neighborhood variables, which suggests that neighborhood conditions during adolescence may not by themselves contribute to concurrent development. As
previously mentioned, results also could be due to the
moderate levels of neighborhood poverty in our study,
particularly during middle childhood and adolescence.
Finally, for those adolescents residing in poor neighborhoods, the persistence of such conditions into adolescence may have a minimal connection to their
functioning during early adolescence over and above
prior exposure.
Limitations should be noted, in addition to those
already mentioned. First, our sample was geographically
and economically diverse but was not nationally
representative, precluding generalization to the U.S.
population. Second, although we used a diverse set of
covariates to adjust for issues of selection, there is no
way to fully rule out the possibility that the associations
attributed to neighborhood afﬂuence and poverty were
not due to other, unmeasured characteristics inﬂuencing
both neighborhood choice and children’s outcomes
(Leventhal & Brooks-Gunn, 2000; Tienda, 1991). Third,
our data ended at ninth grade, or 15 years old, precluding
generalizations to late adolescence and somewhat
limiting generalizations that can be drawn for
externalizing behaviors in particular. Finally, we
acknowledge the persistent threat of selection bias;
however, studies employing a variety of methodological
techniques conclude that associations between neighborhood SES and child outcomes persist. These approaches
include sibling ﬁxed-effect models which hold family
characteristics constant (Vartanian & Buck, 2005);
instrumental variable analysis that minimize unmeasured correlations between neighborhood characteristics
and child outcomes (Foster & McLanahan, 1996); behavior genetic models which differentiate between genetic
and environmental inﬂuences (Caspi, Taylor, Mofﬁtt,
& Plomin, 2000); and propensity scoring methods which
match children who do and do not live in certain types of
neighborhoods (Harding, 2003). Our research question
and available data were not amenable to employing
these techniques; however, given the robustness of
ﬁndings with other analyses, we are conﬁdent that
employing theoretically-relevant covariates is a reasonable approach.
Our ﬁndings have implications for future neighborhood research and policy. They point to the importance
of developmental timing and duration of exposure. In
our study, early childhood arose as a period when
neighborhood conditions may matter for children’s development, but these associations may not endure into adolescence. These ﬁndings are consistent with research on
family economic circumstances and highlight the importance of understanding the developmental signiﬁcance
of economic contexts in early childhood. Somewhat surprisingly, adolescence was not a developmental period
during which neighborhood SES seemed to play a salient
role, which conﬂicts with prior theoretical work. However, cumulative exposure to highly-resourced neighborhoods may confer achievement beneﬁts in adolescence.
Identifying the processes that account for the
observed associations is a critical gap in understanding
how the patterns arise, particularly across development,
and a necessary next step for making recommendations
for policy and practice. Other aspects of neighborhoods
(e.g., institutional resources and collective efﬁcacy) as
well as parenting behaviors (e.g., home environment
and monitoring)—shown to be important in explaining
associations between neighborhood SES and children’s
outcomes (Jencks & Mayer, 1990; Leventhal et al.,
2009)—were beyond the scope of this study as relevant
data were not consistently available across developmental periods, and future research will need to explore
these proposed developmental pathways. We may
anticipate, however, following prior work (Dupe´re´
et al., 2010), that neighborhood afﬂuence is linked to
children’s achievement through stimulating experiences
in more proximal environments like the family, child
care, and school. Finally, policy makers should be aware
EXPOSURE TO NEIGHBORHOOD AFFLUENCE AND POVERTY
that targeted neighborhood-based interventions may
differentially beneﬁt children at different periods of
development. For example, our results suggests that
investments in community resources such as tutoring
programs for adolescents may have limited beneﬁts if
not accompanied by programs targeting young children
as well. Clearly more research is required to make deﬁnitive recommendations, but growing evidence suggests
that not all neighborhood characteristics matter for all
children, at all times.
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
ACKNOWLEDGMENTS
We gratefully acknowledge the data set provided by
this study and express our appreciation to NICHD for
support; to the study coordinators at each site who
supervised data collection; to the research assistants
who collected the data; and especially to the children,
parents, and teachers who participated in this study.
FUNDING
Support was provided by the William T. Grant Foundation to the second author. The NICHD Study of Early
Child Care and Youth Development was supported by
the Eunice Kennedy Shriver National Institute of Child
Health and Human Development through a cooperative
agreement (U10) that calls for a scientiﬁc collaboration
between NICHD staff and participating investigators
(Leventhal and Crosnoe were Co-PIs for Phase IV).
REFERENCES
Achenbach, T. M. (1991a). Manual for the child behavior checklist=
4–18. Burlington, VT: University of Vermont, Department of
Psychiatry.
Achenbach, T. M. (1991b). Manual for the youth self-report and 1991
proﬁle. Burlington, VT: University of Vermont, Department of
Psychiatry.
Anderson, S., Leventhal, T., & Dupe´re´, V. (2014). Residential mobility
and the family context: A developmental approach. Journal of
Applied Developmental Psychology, 35(2), 70–78. doi: http:==
dx.doi.org=10.1016=j.appdev.2013.11.004
Boyle, M. H., Georgiades, K., Racine, Y., & Mustard, C. (2007).
Neighborhood and family inﬂuences on educational attainment:
Results from the Ontario Child Health Study Follow-up 2001. Child
Development, 78, 169–189.
Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic status and
child development. [Review]. Annual Review of Psychology, 53,
371–399.
Bronfenbrenner, U., & Morris, P. A. (2006). The bioecological model
of human development. In W. Damon, & R. M. Lerner (Eds.),
Handbook of Child Psychology (6 ed., Vol. 1, pp. 793–828). New
York, NY: Wiley.
135
Brooks Gunn, J., & Duncan, G. J. (1997). The effects of poverty on
children. Future of Children, 7(2), 55–71.
Brooks Gunn, J., Duncan, G. J., & Maritato, N. (1997). Poor families,
poor outcomes: The well being of children and youth. In G. D. J.
Brooks Gunn (Ed.), Consequences of growing up poor (pp. 1–17).
New York, NY: Russell Sage Foundation.
Brown, B. B., & Larson, J. (2009). Peer relationships in adolescence. In
R. M. Lerner, & L. Steinberg (Eds.), Handbook of adolescent psychology (Vol. 2, pp. 74–103). Hoboken, NJ: John Wiley.
Carnegie Corporation. (1994). Starting points: Meeting the needs of our
youngest children. New York, NY: Author.
Caspi, A., Taylor, A., Mofﬁtt, T. E., & Plomin, R. (2000). Neighborhood deprivation affects children’s mental health: Environmental
risk identiﬁed in a genetic design. Psychological Science, 11(4),
338–342.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences
(2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
Costa, P. T., & McCrae, R. R. (1985). The NEO personality inventory
manual. Odessa, FL: Psychological Assessment Resources.
Criss, M. M., Shaw, D. S., Moilanen, K. L., Hitchings, J. E., &
Ingoldsby, E. M. (2009). Family, neighborhood, and peer characteristics as predictors of child adjustment: A longitudinal analysis of
additive and mediation models. Social Development, 18(3), 511–
535. doi: 10.1111=j.1467-9507.2008.00520.x
Crosnoe, R., Leventhal, T., Wirth, R. J., Kim, M. P., & Pianta, R.
C. (2010). Family socioeconomic status and consistent environmental stimulation in early childhood. Child Development, 81(3),
972–987.
Crowder, K., & South, S. J. (2011). Spatial and temporal dimensions
of neighborhood effects on high school graduation. Social Science
Research, 40, 87–106.
Dearing, E., McCartney, K., & Taylor, B. A. (2009). Does high quality
early child care promote low-income children’s math and reading
achievement in middle childhood? Child Development, 80, 1329–
1349.
Dodge, K. A., Coie, J. D., & Lynam, D. (2007). Aggression and antisocial behavior in youth. In W. Damon & R. M. Lerner (Eds.),
Handbook of child psychology (pp. 719–788). Hoboken, NJ: John
Wiley & Sons.
Duncan, G. J., & Aber, J. L. (1997). Neighborhood models and measures. In J. Brooks Gunn, G. J. Duncan & J. L. Aber (Eds.), Neighborhood Poverty: Contexts and Consequences for Children (pp. 62–
78). New York, NY: Russel Sage Foundation.
Duncan, G. J., & Brooks-Gunn, J. (1997). Income effects across the
life span: Integration and interpretation. In G. J. Duncan & J.
Brooks-Gunn (Eds.), Consequences of growing up poor (pp. 596–
610). New York, NY: Russell Sage Foundation Press.
Duncan, G. J., & Magnusson, K. (2011). The nature and impact of
early achievement skills, attention skills, and behavior problems.
In G. J. Duncan, & R. M. Murnane (Eds.), Whither Opportunity?
(pp. 47–69). New York, NY: Russel Sage Foundation.
Duncan, G. J., Ziol-Guest, K. M., & Kalil, A. (2010). Early-childhood
poverty and adult attainment, behavior, and health. Child Development, 81(1), 306–325.
Dunn, L. M., & Dunn, L. M. (1981). Peabody Picture Vocabulary
Test-Revised. Circle Pines, MN: American Guidance Service, Inc.
´ ., Willms, J. D., Leventhal, T., & Tremblay,
Dupe´re´, V., Lacourse, E
R. E. (2008). Neighborhood poverty and early transition to sexual
activity in young adolescents: a developmental ecological approach.
Child Development, 79, 1463–1476.
Dupe´re´, V., Leventhal, T., Crosnoe, R., & Dion, E´. (2010). Understanding the positive role of neighborhood socioeconomic advantage in achievement: The contribution of the home, child care
and school environments. Developmental Psychology, 46,
1227–1244.
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
136
ANDERSON ET AL.
Eccles, J. S. (1999). The development of children ages 6 to 14. Future of
Children, 9, 30–44.
Elder, G. H. (1995). The life course paradigm: Social change and individual development. In P. Moen, G. H. Elder, & K. Luscher (Eds.),
Examining lives in context: Perspectives on the ecology of human
development (pp. 101–139). Washington, DC: American Psychological Association.
Evans, G. W., & Schamberg, M. A. (2009). Childhood poverty,
chronic stress, and adult working memory. Proceedings of the
National Academy of Sciences, 106(16), 6545–6549. doi: 10.1073=
pnas.0811910106
Foster, E. M., & McLanahan, S. (1996). An illustration of the use of
instrumental variables: Do neighborhood conditions affect a young
person’s chance of ﬁnishing high school? Psychological Methods,
1(3), 249–260.
Graber, J. A., & Brooks-Gunn, J. (1996). Transitions and turning
points: Navigating the passage from childhood through adolescence. Developmental Psychology, 32(4), 768–776.
Guo, G. (1998). The timing of the inﬂuences of cumulative poverty on
children’s cognitive ability and achievement. Social Forces, 77(1),
257–287. doi: 10.1093=sf=77.1.257
Harding, D. J. (2003). Counterfactual models of neighborhood effects:
The effects of neighborhood poverty on dropping out and teenage
pregnancy. American Journal of Sociology, 109(3), 676–719.
Heckman, J. J. (2008). Schools, skills, and synapses. [Article]. Economic Inquiry, 46(3), 289–324. doi: 10.1111=j.1465-7295.2008.00163.x
Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for ﬁt indices in
covariance structure analysis: Conventional criteria versus new
alternatives. Structural Equation Modeling, 6, 1–55.
Jencks, C., & Mayer, S. (1990). The social consequences of growing up
in a poor neighborhood. In L. Lynn & M. McGeary (Eds.),
Inner-city poverty in the United States (pp. 111–186.). Washington,
DC: National Academy Press.
Johnson, M. K., Crosnoe, R., & Elder, G. H. (2011). Insights on adolescence from a life course perspective. Journal of Research on Adolescence, 21(1), 273–280. doi: 10.1111=j.1532-7795.2010.00728.x
Jung, T., & Wickrama, K. A. S. (2007). An introduction to latent class
growth analysis and growth mixture modeling. Social and Personality Psychology Compass, 2=1, 302–317.
Kan, K. (1999). Expected and unexpected residential mobility. Journal
of Urban Economics, 45(1), 72–96. doi: 10.1006=juec.1998.2082
Kiff, C. J., Cortes, R. C., Lengua, L. J., Kosterman, R., Hawkins,
J. D., & Mason, W. A. (2012). Effects of timing of adversity on
adolescent and young adult adjustment. Journal of Research on
Adolescence, 22(2), 284–300.
Kohen, D., Brooks-Gunn, J., Leventhal, T., & Hertzman, C. (2002).
Neighborhood income and physical and social disorder in Canada:
Associations with young children’s competencies. Child Development, 73(6)(6), 1844–1860.
Lerner, R. M. (2006). Developmental science, developmental systems,
and contemporary theories of human development. In R. M. Lerner
(Ed.), Handbook of Child Psychology (6 ed., Vol. 1, pp. 1–17).
Hoboken, NJ: Wiley.
Lescheid, A., Chiodo, D., Nowicki, E., & Rodger, S. (2007). Childhood predictors of adult criminality: A meta-analysis drawn from
prospective longitudinal literature. Canadian Journal of Criminology
and Criminal Justics, 50(4), 435–467.
Leventhal, T., & Brooks-Gunn, J. (2000). The neighborhoods they live
in: Effects of neighborhood residence upon child and adolescent
outcomes. Psychological Bulletin, 126, 309–337.
Leventhal, T., & Brooks Gunn, J. (2011). Changes in neighborhood
poverty from 1990 to 2000 and youth’s problem behaviors.
Developmental Psychology, 47(6), 1680–1698.
Leventhal, T., Dupe´re´, V., & Brooks-Gunn, J. (2009). Neighborhood
inﬂuences on adolescent development. In R. M. Lerner & L. Steinberg
(Eds.), Handbook of adolescent psychology (3rd ed., pp. 411–443).
New York, NY: John Wiley.
Leventhal, T., Dupe´re´, V., & Shuey, E. (in press). Children in neighborhoods. In M. H. Bornstein & R. M. Lerner (Eds.), Ecological
Settings and Processes within the Relational, Developmental System
(7 ed., Vol. 4). Hoboken, NJ: Wiley.
Loeber, R., & Burke, J. D. (2011). Developmental pathways in juvenile
externalizing and internalizing problems. Journal of Research on
Adolescence, 21(1), 34–46. doi: 10.1111=j.1532-7795.2010.00713.x
Lo´pez Turley, R. N. (2003). When do neighborhoods matter? The role
of race and neighborhood peers. Social Science Research, 32(1),
61–79.
Lund, T. J., & Dearing, E. (2012). Is growing up afﬂuent risky for adolescents or is the problem growing up in an afﬂuent neighborhood?
Journal of Research on Adolescence. doi: 10.1111=j.1532-7795.
2012.00829.x
Luthar, S. S. (2003). The culture of afﬂuence: Psychological costs of
material wealth. Child Development, 74(6), 1581–1593.
Magnuson, K., Duncan, G. J., & Kalil, A. (2006). The contribution of
middle childhood contexts to adolescent achievement and behavior.
In A. C. Huston & M. H. Ripke (Eds.), Developmental Context
of Middle Childhood: Bridges to Adolescence and Adulthood
(pp. 150–172). Cambridge, UK: Cambridge University Press.
McBride Murry, V., Berkel, C., Gaylord-Harden, N. K., CopelandLinder, N., & Nation, M. (2011). Neighborhood poverty and
adolescent development. Journal of Research on Adolescence,
21(1), 114–128. doi: 10.1111=j.1532-7795.2010.00718.x
McCulloch, A., & Joshi, H. E. (2001). Neighborhourhood and family
inﬂuences on the cognitive ability of children in the British National
Child Development Study. Social Science and Medicine, 53, 579–591.
McLeod, J., & Shanahan, M. J. (1996). Trajectories of poverty and
children’s mental health. Journal of Health and Social Behavior,
37, 207–220.
McLoyd, V. C., Kaplan, R., Purtell, K. M., Bagley, E., Hardaway, C. R.,
& Smalls, C. (2009). Poverty and socioeconomic disadvantage in adolescence handbook of adolescent psychology. Hoboken, NJ: John Wiley.
Mofﬁtt, T. E. (1993). Adolescent-limited and life-course-persistent
antisocial behavior: A developmental taxonomy. Psycological
Review, 100(4), 647–701.
Muthen, B. O. (2004). Latent variable analysis: Growth mixture
modeling and related techniques for longitudinal data. In D. Kaplan
(Ed.), Handbook of quantitative methodology for the social exiences
(pp. 345–368). Thousand Oaks, CA: Sage.
Muthe´n, L. K., & Muthe´n, B. O. (1998–2010). Mplus user’s guide (6th
ed). Los Angeles, CA: Author.
Najman, J. M., Hayatbakhsh, M. R., Heron, M. A., Bor, W.,
O’Callaghan, M. J., & Williams, G. M. (2009). The impact of
episodic and chronic poverty on child cognitive development. The
Journal of Pediatrics, 154(2), 284–289. e281. http:==dx.doi.org=
10.1016=j.jpeds.2008.08.052
Neuman, S. B., & Celano, D. (2001). Access to print in low-income
and middle-income communities: An ecological study of four
neighborhoods. Reading Research Quarterly, 36(1), 8–26.
NICHD Early Child Care Research Network. (2005). Child care and
child development: Results from the NICHD study of early child care
and youth development. New York, NY: Guilford Press.
Radloff, L. (1977). The CES-D Scale: A self-report depression scale
for research in the general population. Applied Psychological
Measurement, 1, 385–401.
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models:
Applications and data analysis methods. Thousand Oaks, CA: Sage.
Sampson, R. J. (2000). The neighborhood context of investing in
children: Facilitating mechanisms and undermining risks. In S. H.
Danziger, & J. Waldfogel (Eds.), Securing the future for children
(pp. 205–227). New York, NY: Russell Sage Foundation.
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
EXPOSURE TO NEIGHBORHOOD AFFLUENCE AND POVERTY
Sampson, R. J., Morenoff, J. D., & Gannon-Rowley, T. (2002).
Assessing ‘neighborhood effects’: Social processes and new
directions in research. Annual Review of Sociology, 28, 443–478.
Sanbonmatsu, L., Ludwig, J., Katz, L. F., Gennetian, L., Duncan,
G. J., Adam, E. K., . . . Lindau, S. T. (2011). Moving to opportunity
fair housing demonstration program: Final impacts evaluation.
Cambridge, MA: National Bureau of Economic Research.
Sastry, N., & Pebley, A. R. (2010). Family and neighborhood sources
of socioeconomic inequality in children’s achievement. Demography,
47, 777–800.
Schachter, J. (2001). Why people move: Exploring the March
2000 Current population survey. Washington, D.C.: U.S. Census
Bureau.
Schaefer, E., & Edgerton, M. (1985). Parental and child correlates of
parental modernity. In I. E. Sigel (Ed.), Parental belief systems:
The psychological consequences for children (pp. 287–318). Hillsdale,
NJ: Lawrence Erlbaum.
Shonkoff, J. P., & Phillips, D. A. (Eds.). (2000). From neurons to neighborhoods: The science of early child development. Washington, DC:
National Academy of Sciences.
Smith, J. R., Brooks-Gunn, J., & Klebanov, P. (1997). Consequences
of living in poverty for young children’s cognitive and verbal ability
and early school achievement. In G. J. Duncan & J. Brooks-Gunn
(Eds.), Consequences of growing up poor (pp. 132–189). New York,
NY: Russell Sage Foundation.
South, S. J., & Crowder, K. (2010). Neighborhood poverty and
nonmarital fertility: Spatial and temporal dimensions. Journal of
Marriage and Family, 72, 98–104.
Steinberg, L., & Morris, A. S. (2001). Adolescent development. Annual
Review of Psychology, 52, 83–110.
Tienda, M. (1991). Poor people and poor places: Deciphering neighborhood effects on poverty outcomes. In J. Huber (Ed.), Macro-micro
linkages in sociology (pp. 244–262). Newbury Park, CA: Sage.
Vartanian, T. P., & Buck, P. W. (2005). Childhood and adolescent
neighborhood effects on adult income: Using siblings to examine
differences in OLS and ﬁxed effect models. Social Service Review,
78(1), 60–94.
Wheaton, B., & Clarke, P. (2003). Space meets time: Integrating temporal and contextual inﬂuences on mental health in early adulthood.
American Sociological Review, 68, 680–706.
Wodtke, G., Harding, D. J., & Elwert, F. (2011). Neighborhood Effects in
Temporal Perspective. American Sociological Review, 76(5), 713–736.
Woodcock, R. W., & Johnson, M. B. (1989). Woodcock-Johnson PsychoEducational Battery - Revised. Allen, TX: DLM Teaching Resources.
Wright, D. A. N. (1999). Student mobility: A negligible and confounded inﬂuence on student achievement. The Journal of Educational Research, 92(6), 347.
Xue, Y., Leventhal, T., Brooks-Gunn, J., & Earls, F. J. (2005). Neighborhood residence and mental health problems of 5- to 11-year olds.
Archives of General Psychiatry, 62, 554–563.
APPENDIX A
Correlations Among Neighborhood High and Poverty by Developmental Period
Early Childhood
Poverty
Early Childhood
Afﬂuence
Middle Childhood
Poverty
Afﬂuence
Early Adolescence
Poverty
Afﬂuence
Middle Childhood
Afﬂuence
Poverty
0.683
0.419
0.192
0.646
0.515
0.582
0.365
0.163
0.598
0.797
0.438
Early Adolescence
Afﬂuence
Poverty
0.451
0.913
0.496
0.202
Note. N ¼ 1,364. Results combined across 10 imputed dataset.
p < .0001.
137
138
ANDERSON ET AL.
APPENDIX B
Correlations Among Neighborhood High and Poverty and Child Outcomes by Developmental Period
Child Outcomes
Math Achievement
Downloaded by [Bibliothèques de l'Université de Montréal] at 11:13 27 August 2014
Neighborhood SES
Early Poverty
Proportion single moms
Proportion HH < 100% poverty
Proportion unemployed adult
Early Afﬂuence
Proportion with B.A.
Proportion with professional job
Middle Poverty
Proportion single moms
Proportion HH < 100% poverty
Proportion unemployed adult
Middle Afﬂuence
Proportion with B.A.
Proportion with professional job
Adolescent Poverty
Proportion single moms
Proportion HH < 100% poverty
Proportion unemployed adult
Adolescent Afﬂuence
Proportion with B.A.
Proportion with professional job
Reading Achievement
Externalizing Behavior
Early
Middle
Adolescence
Early
Middle
Adolescence
.27
.28
.19
.30
.31
.20
.25
.30
.19
.22
.24
.16
.27
.28
.17
.27
.30
.22
.12
.14
.10
.13
.16
.09
.17
.18
.09
.29
.31
.26
.27
.32
.33
.32
.32
.29
.30
.32
.33
.17
.17
.18
.19
.16
.18
.26
.27
.13
.27
.29
.18
.26
.29
.20
.23
.18
.14
.25
.25
.16
.24
.23
.16
.13
.19
.12
.16
.22
.14
.15
.20
.10
.34
.35
.28
.29
.35
.34
.33
.33
.32
.32
.35
.35
.19
.19
.20
.22
.19
.20
.23
.24
.14
.24
.24
.15
.24
.25
.15
.17
.20
.11
.20
.21
.12
.22
.22
.14
.13
.18
.11
.16
.22
.15
.15
.19
.11
.32
.32
.26
.26
.34
.34
.32
.32
.32
.30
.33
.33
.19
.18
.21
.22
.19
.20
Note. N ¼ 1,364. Results combined across 10 imputed dataset.
Early
Middle
Adolescence

Download Report