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Abstract

A growing body of research in the United States and Western Europe documents significant effects of the physical environment (toxins, pollutants, noise, crowding, chaos, and housing, school and neighborhood quality) on children and adolescents' cognitive and socioemotional development. Much less is known about these relations in other contexts, particularly the global South. We thus briefly review the evidence for relations between child development and the physical environment in Western contexts, and discuss some of the known mechanisms behind these relations. We then provide a more extensive review of the research to date outside of Western contexts, with a specific emphasis on research in the global South. Where the research is limited, we highlight relevant data documenting the physical environment conditions experienced by children, and make recommendations for future work. In these recommendations, we highlight the limitations of employing research methodologies developed in Western contexts (Ferguson & Lee, 2013). Finally, we propose a holistic, multidisciplinary, and multilevel approach based on Bronfenbrenner's (1979) bioecological model to better understand and reduce the aversive effects of multiple environmental risk factors on the cognitive and socioemotional development of children across the globe.
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The physical environment and child development:
An international review
Kim T. Ferguson
a
, Rochelle C. Cassells
b
, Jack W. MacAllister
a
& Gary W. Evans
c
a
Psychology Faculty Group , Sarah Lawrence College , Bronxville , NY , USA
b
Department of Human Development , Cornell University , Ithaca , NY , USA
c
Department of Design and Environmental Analysis, and Bronfenbrenner Center for
Translational Research , Cornell University , Ithaca , NY , USA
Published online: 28 Jun 2013.
To cite this article: Kim T. Ferguson , Rochelle C. Cassells , Jack W. MacAllister & Gary W. Evans (2013): The
physical environment and child development: An international review, International Journal of Psychology,
DOI:10.1080/00207594.2013.804190
To link to this article: http://dx.doi.org/10.1080/00207594.2013.804190
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The physical environment and child development:
An international review
Kim T. Ferguson
1
, Rochelle C. Cassells
2
, Jack W. MacAllister
1
, and Gary W. Evans
2,3
1
Psychology Faculty Group, Sarah Lawrence College, Bronxville, NY, USA
2
Department of Human Development, Cornell University, Ithaca, NY, USA
3
Department of Design and Environmental Analysis, and Bronfenbrenner Center for Translational
Research, Cornell University, Ithaca, NY, USA
A
growing body of research in the United States and Western Europe documents significant effects of the physical
environment (toxins, pollutants, noise, crowding, chaos, and housing, school and neighborhood quality) on
children and adolescents’ cognitive and socioemotional development. Much less is known about these relations in other
contexts, particularly the global South. We thus briefly review the evidence for relations between child development and
the physical environment in Western contexts, and discuss some of the known mechanisms behind these relations. We
then provide a more extensive review of the research to date outside of Western contexts, with a specific emphasis on
research in the global South. Where the research is limited, we highlight relevant data documenting the physical
environment conditions experienced by children, and make recommendations for future w ork. In these
recommendations, we highlight the limitations of employing research methodologies developed in Western contexts
(Ferguson & Lee, 2013). Finally, we propose a holistic, multidisciplinary, and multilevel approach based on
Bronfenbrenner’s (1979) bioecological model to better understand and reduce the aversive effects of multiple
environmental risk factors on the cognitive and socioemotional development of children across the globe.
Keywords: Physical environment; Child development; Global South; Chaos; Bronfenbrenner.
U
n corpus grandissant de recherches aux E
´
tats-Unis et en Europe de l’Ouest documente les effets significatifs de
l’environnement (toxines, polluants, bruit, surpopulation, chaos, qualite
´
des logements, des e
´
coles et du voisinage)
sur le de
´
veloppement cognitif et socio-e
´
motionnel des enfants et des adolescents. On en connaı
ˆ
t toutefois beaucoup
moins a
`
ce sujet dans d’autres contextes, particulie
`
rement dans les pays du Sud, en ge
´
ne
´
ral. Nous avons donc d’abord
brie
`
vement revu les relations entre le de
´
veloppement de l’enfant et l’environnement physique dans le contexte occidental
et discute
´
des me
´
canismes connus derrie
`
res ces relations. Ensuite, nous avons proce
´
de
´
a
`
une recension extensive des
recherches entreprises jusqu’a
`
maintenant en dehors du contexte occidental, avec une emphase spe
´
cifique sur les
recherches entreprises dans le Sud. Aux endroits ou
`
la recherche est pluto
ˆ
t limite
´
e, nous avons fait ressortir les donne
´
es
significatives portant sur les conditions de l’environnement physique ve
´
cues par les enfants et avons fait des
recommandations pour des recherches futures. Parmi ces recommandations, nous avons insiste
´
sur les limites de
l’utilisation des me
´
thodologies de recherche employe
´
es dans les contextes occidentaux (Ferguson & Lee, 2013). Enfin,
nous proposons une approche holistique, multidisciplinaire et multipartite base
´
e sur le mode
`
le bio-e
´
cologique de
Bronfenbrenner (1979) pour mieux comprendre et re
´
duire les effets nocifs des multiples facteurs environnementaux de
risque sur le de
´
veloppement cognitif et socio-e
´
motionnel des enfants a
`
travers le globe.
U
ncu
´
mulo creciente de investigacio
´
n en Estados Unidos y Europa occidental documenta los efectos significativos
del ambiente
´
sico (toxinas, contaminantes, ruido, densidad poblacional, caos, calidad de la vivienda, la escuela y
el vecindario) sobre el desarrollo cognitivo y socioemocional de nin
˜
os y adolescentes. Se sabe mucho menos acerca de
estas relaciones en otros contextos, en particular en la parte sur del globo. En consecuencia, revisamos de manera breve
la evidencia que apoya las relaciones entre el desarrollo infantil y el ambiente
´
sico en los contextos occidentales, y
q 2013 International Union of Psychological Science
This research was supported in part by grants from the W.T. Grant Foundation and the John D. and Catherine T. MacArthur Foundation.
Special thanks to Jane Gorski for her help in locating and organizing reference materials and to Sheridan Bartlett for advice on this paper.
Correspondence should be addressed to Kim Ferguson, Sarah Lawrence College, 1 Mead Way, Bronxville, NY 10708, USA. (Email:
kferguson@sarahlawrence.edu).
International Journal of Psychology, 2013
http://dx.doi.org/10.1080/00207594.2013.804190
Downloaded by [Kim Ferguson] at 12:21 30 June 2013
discutimos algunos de los mecanismos conocidos detra
´
s de estas relaciones. Luego, proporcionamos una revisio
´
nma
´
s
extensa de la investigacio
´
n a la fecha fuera de los contextos occidentales, con un e
´
nfasis especı
´
fico en la investigacio
´
nen
el sur del globo. Donde la investigacio
´
n es limitada, destacamos los datos relevantes que documentan las condiciones del
ambiente
´
sico que han vivido los nin
˜
os, y hacemos recomendaciones para el trabajo futuro. En estas recomendaciones
destacamos las limitaciones de emplear me
´
todos de investigacio
´
n desarrollados en los contextos occidentales (Ferguson
& Lee, 2013). Por u
´
ltimo, proponemos una aproximacio
´
n holı
´
stica, multidisciplinaria y multinivel basada en el modelo
bioecolo
´
gico de Bronfenbrenner (1979) para entender mejor y reducir los efectos adversos de muchos factores de riesgo
sobre el desarrollo cognitivo y socioemocional de los nin
˜
os por todo el globo.
The majority of the world’s children live in the
global South (countries with a low to medium
Human Development Index score, including Africa,
Central and Latin America, and most of Asia), yet
nearly all of the research on relations between the
physical environments experienced by children and
their cognitive and socioemotional development has
taken place within North America and Western
Europe. The purpose of this review is to call
attention to this important gap in the literature and
to introduce readers to emerging scholarship on
children’s environments in the global South. We do
not cover work on the physical environment and
children’s physical health because this literature is
extensive (cf. Wigle, 2003). We do, however,
discuss physiological indicators of stress in
explaining relations between components of the
physical environment (e.g., crowding, noise) and
children’s development.
We organize our review into a discussion of the
impacts of toxins and pollutants (heavy metals,
pesticides, and air a nd water pollution), noise,
crowding, chaos, housing quality, school and child-
care quality , and neighbo rhood quality on the
cognitive and socioemotional development of chil-
dren and adolescents across the globe. For each of
these commonly studied physical environment
factors, we briefly review what is currently known
in Western (North American and Western European)
contexts and, where appropriate, discuss some of the
known mechanisms linking each factor and children’s
development. We also identify when the evidence is
especially strong for particular influences. We provide
a more extensive review of the research to date
outside of Western contexts, with a specific emphasis
on research in the global South. As we do so, we
discuss the streng th of the e vide nce for each
influencing factor and, where there are gaps in the
extant research, we briefly discuss what we do know
(including available statistics) and make recommen-
dations for future work. In these recommendations,
we pay particular attention to the limitations of
employing the same research methodologies and
predicting similar results in previously understudied
contexts (Ferguson & Lee, 2013; Nsamenang, 1992,
2004). We close with a call for a holistic, multi-
disciplinary, and multilevel approach to investigate
the impacts of the physical environment on child and
adolescent development that employs an extension of
Bronfenbrenner’s bioecological model (Bronfen-
brenner, 197 9; Bronfenbrenner & Evans, 2000;
Ferguson, Kim, Dunn, & Evans, 2009; Ferguson &
Lee, 2013) as a theoretical framework.
TOXINS AND POLLUTAN TS
Lead
Needleman et al. (1979) documented the impacts of
lead exposure on young (grade school) children’s
intelligence quotient (IQ) and externalizing beha-
viors. Since then, many studies have shown that lead
significantly impacts the cognitive functioning of
children and adolescents in the United States and
Western Europe, even when controlling for socio-
economic status (SES) and other confounding factors
(Evans, 2006; Hubbs-Tait, Nation, Krebs, & Bellin-
ger, 2005; Koger, Schetteler, & Weiss, 2005; Surkan
et al., 2007; Wigle, 2003). A significant body of
research has documented the effects of prenatal and
childhood exposure to lead on children’s current and
prospective developmental functioning in middle-
income, newly industrial countries such as China
(Shen, Yan, & Guo, 1998; Tang et al., 2008; Wang,
Xu, Zhang, & Wang, 1989), India (Ahamed, Singh,
Behari, Kumar, & Siddiqui, 2007; Patel, Mamtani,
Thakre, & Kulkarni, 2006), the Philippines (Solon
et al., 2008) and Malaysia ( Zailina, Junidah,
Josephine, & Jamal, 2008). Similar impacts have
been documented in Egypt (Mostafa, El-Shahawi, &
Mokhtar, 2009), Mexico (Acosta-Saavedra et al.,
2011; Hu et al., 2006; Kordas et al., 2006), Peru
(Vega-Dienstmaier et al., 2006), and Bolivia (Ruiz-
Castell et al., 2012). Importantly, lead levels in these
and other countries in the global South are still high
and largely unregulated (Karrari, Mehrpour, &
Abdollahi, 2012; Shen et al., 1998; Tong, von
Schirnding, & Prapamontol, 2000; Walker et al.,
2007). In fact, it is estimated that around 40% of
children living in econom ically developing countries
2 FERGUSON ET AL.
Downloaded by [Kim Ferguson] at 12:21 30 June 2013
have elevated blood lead levels (Walker et al., 2007).
In addition, some of the most recent work across the
globe h as found that even very low levels of lead
exposure can be toxic to infants and young children
(Canfield et al., 2003; Lanphear, Dietrich, Auinger, &
Cox, 2000; Lanphear et al., 2005; Patel et al., 2006;
Ruiz-Castell et al., 2012; Zailina et al., 2008).
An important characteristic of many toxins is
that even after emissions are eliminated (e.g.,
removal of lead from gasoline and paint, the
banning of the pesticide dichlorodiphenyltrichloro-
ethane [DDT] in North America), they remain in
the ecosystem for a very long time (Meyer, Brown,
& Falk, 2008). There are several pathways that
enable this to occur. Heavy metals settle into the
ground, and so lead is still found in the soil and in
older houses that were painted prior to the banning
of lead over three decades ago in the US. Lead
used to be incorporated in plumbing (e.g., sodder)
and thus can potentially leach into water supplies.
Many toys and other common household products
used to be made with le ad, a practice that
unfortunately continues today in China, for
example (Meyer et al., 2008). Another pathway
that is perhaps more insidious is the crossgenera-
tional transmission of toxins. Some toxins are
lipophilic, which means they can be stored in body
fat. Thus prior exposure to some toxins, even
preconception, can eventually affect the developi ng
organism (Hubbs-Tait et al., 2005; Koger et al.,
2005). Finally, even when children themselves are
not exposed to toxins, they may be susceptible to
indirect exposure via parental exposures (Bouchard
et al., 2011). A common example of this is from
agricultural workers who absorb pesticides into
their skin and/or their clothes (Koger et al., 2005).
Tragically, child laborers in many parts of the
world remain in direct contact with toxins in
agricultural, construction, and manufacturing
sectors.
Numerous studies in North America document a
doseresponse function between body lead level
burdens and IQ reductions. These findings have been
replicated and demonstrated in prospective research
designs, and hold true even when statistical controls
rule out alternative explanations such as social class
(Evans, 2006; Hubbs-Tait et al., 2005; Koger et al.,
2005). For exam ple, Canfield et al. (2003) found that,
after controlling for SES and other demographic
variables, 3- to 5-year-olds’ blood lead levels were
significantly negatively associated with IQ, even at
levels of exposure below the US-regulated 10 mg/dl
level. Teachers also report more attentional problems
among children who have been exposed to lead
(Evans, 2006), and at least one North American study
uncovered lead-related deficits in attention, reaction
time, and visual motor integration among elemen-
tary school aged children (Chiodo, Jacobson, &
Jacobson, 2004).
Estimates of developmental impacts of toxins such
as lea d may underestimate effects because of genetic
differences in vulnerability. As an illustration, Nigg
et al. (2008) showed that blood lead levels among 8-
to 17-year-old American children were weakly
associated overall with hyperactivity and impulsivity.
However, these symptoms were significantly more
accentuated in the subset of youth with abnormalities
in a catecholamine receptor gene.
In the global South, most of the work to date has
considered the impacts of lead on general cognitive
functioning. Mostafa et al. (2009) showed that nearly
half (43%) of a middle-class sample of 6- to 12-year-
olds in Cairo had blood lead levels at or above the US
Centers for Disease Control and Prevention limit of
10 mg/dl. A large proportion (37%) of these children
were diagnosed with cognitive dysfunction. The most
significant independent predictor of cognitive dys-
function was a blood lead level at or above 10 mg/dl.
Similar to research in other contexts, a 1 mg/dl
increase in blood lead level was associated with a
two-point decline in IQ. Similarly, in a study of 6.5- to
8.5-year-old urban Malaysian children, Zailina et al.
(2008) found that blood lead levels, statistically
controlling for parents’ education, household income,
and other family demographic factors, predicted
children’s cognitive functioning. Studies in China
across a wide age range have documented similar
effects (Shen et al., 1998; Tang et al., 2012), as have
recent studies of 6- to 8.5-year-old children in Peru
(Vega-Dienstmaier et al., 2006) and E cuador
(Counter, Buchanan, & Ortega, 2008).
The evidence for long-term effects of lead on
children’s cognitive functioning following prenatal
exposure is equally strong. Most recently, Yorifuji,
Debes, Weihe, and Grandjean (2011) found that, after
controlling for SES and other potential covariates, 7-
and 14-year-old children living in the Faroe Islands
exposed to high levels of lead prenatally had deficits
in short-term memor y and attention compared to
children exposed to lower levels of lead. Hu et al.
(2006) found that maternal blood lead levels in the
first trimester, but not in the second or third trimester ,
predicted 12- and 24-month-old Mexican infants’
general cognitive functioning (Mental Development
Index, MDI). These effects were large: A 1 SD
increase in first-trimester maternal plasma lead level
was associated with a 3.5 point decrease on the MDI.
Shen et al. (1998) similarly found that, after
confounding factors such as family SES and parental
exposure to lead at work were statistically control led
for, 3-, 6-, and 12-month-old Shanghai infants with
high umbilical cord lead levels received significantly
PHYSICAL ENVIRONMENT AND CHILD DEVELOPMENT 3
Downloaded by [Kim Ferguson] at 12:21 30 June 2013
lower MDI scores than those with lower lead levels.
Current blood lead levels were not associated with
MDI scores. In contrast, Solon et al. (2008) found that
6- to 30-month-old Filipino infants’ current blood
lead levels significantly predicted their MDI scores.
And Patel and colleagues (2006) found that the cord
blood lead levels of neonates living in Nagpur, India
significantly predicted autonomic stability and abnor-
mal reflexes. In addition, among infants with cord
blood lead levels of 510 mg/dl, lead levels
significantly predicted arousal state regulation,
motor functioning, and autonomic stability. These
findings suggest that lead exposure has important
effects on early motor functioning, even at very low
levels.
Much less work on behavioral toxins has examined
potential adverse socioem otional c onsequences.
However, in Needleman et al.’s (1979) classic Boston
school children study of lead and IQ, teachers, blind to
the pupils’ lead dentine levels, rated children with
higher lead burdens with more overt classroom
behaviors indicative of behavioral problems such as
inhibitory control. Eleven years later, these same
children had higher rates of juvenile delinquency
(Needleman, Schell, Bellinger, Leviton, & Allred,
1990). Several other studies have shown linkages
between early lead exposure and impulsivity, aggres-
sion, and hyperactivity in children (Chandramouli,
Steer, Ellis, & Emond, 2009; Chiodo et al., 2004;
Evans, 2006; Hubbs-Tait et al., 2005).
The research on associations between lead exposure
and children’s socioemotional functioning outside of
the Western world is even more limited. However, in
an early study of the impacts of prenatal lead exposure
on both cognitive and socioemotional functioning at
ages 2, 4, and 7 years in Kosovo, Factor-Litvak,
Wasserman, Kline, and Graziano (1999) found that
children’s behavior problems were associated with
blood lead levels. Similarly, Bao et al. (2009) found
that levels of lead and zinc in 7- to 16-year-old Chinese
children’s hair samples predict ed their behavioral
functioning. And, in an intervention study in which 6-
to 8-year-old children living close to a metal foundry in
Torreo
´
n, Mexico were given iron, zinc, both, or
placebo nutrition supplements over a period of 6
months, Kordas et al. (2006) found that blood lead
levels were positively associated with passive off-task
behaviors within classroom settings and negatively
associated with activity levels during recess.
Mercury
The impacts of exposure to mercury on children’s
cognitive functioning are well documented. Low-
level maternal mercury exposure damages infant
sensorimotor functioning (Mckeown-Eyssen, Ruedy,
& Neims, 1983) and 6-year-old children’s IQ scores
and language development (Kjell strom, Kennedy,
Wallis, & Mantell, 1989). In addition, high-level
maternal mercury exposure in Japan (Matsumoto,
Koya, & Takeuchi, 1965; Takeuchi, 1968) and Iraq
(Cox et al., 1989; Cox, Marsh, Myer s, & Clarkson,
1995; Marsh et al., 1980) has been reported to
adversely affect prenatal and neonatal cognitive and
physical development. Two major longitudinal
projects, one in the Seychelles (e.g., Myers et al.,
2009; Stokes-Riner et al., 2011) and one in the Faroe
Islands (e.g., Debes, Budtz-Jørgensen, Weihe, White,
& Grandjean, 2006), have documented the adverse
impacts of prenatal exposure to mercury from
maternal consumption of seafood on young children’s
cognitive functioning. Little work has documented
impacts on socioemotional functioning, suggesting
that further work in this area is needed.
In the Seychelles Child Development Study,
maternal and child methylmercury (MeHg) levels,
children’s cognitive and behavioral development, and
various demographic factors have been assessed at the
ages of 6, 19, 29, 66 and 107 months (Myers et al.,
2009) following an assessment of prenatal MeHg
exposure. In the Faroe Islands study, postnatal MeHg
exposure and children’s cognitive and behavioral
functioning have been measured at ages 1, 7 and 14
years (Debes et al., 2006), following an assessment of
prenatal levels. In both studies, significant relations
between prenatal and current MeHg and children’s
early motor development and later cognitive function-
ing have been found, although the results are more
consistent in the Faroe Islands study (Myers et al.,
2009; Stokes-Riner et al., 2011). These differences
may have resulted from different ial sources of MeHg
(primarily fish in the Seychelles; primarily pilot whale
meat in the Faroe Islands), as well as lower levels of
aquatic food consumption in the Seychelles. Never-
theless, together these projects suggest that young
children’s motor and cognitive development, and
language, attention and memory in particular, are
compromised following pre natal exposure to
methylmercury.
Polychlorinated biphenyls (PCBs)
Prenatal exposure to polychlorinated biphenyls
(PCBs), which are used in the manufacture of vinyl
and other plastic compounds, has been linked with
children’s cognitive and socioemotional functioning
(Evans, 2006; Lai et al., 2002; Ribas-Fito
´
, Sala,
Kogevinas, & Sunyer, 2001; Williams & Ross, 2007).
In contrast, postnatal exposure appears to have few
effects, except in the case of severe poisoning (Ribas-
Fito
´
et al., 2001). These compounds have been banned
in most high-income countries, but they continue to
4 FERGUSON ET AL.
Downloaded by [Kim Ferguson] at 12:21 30 June 2013
persist in environments across the globe, particularly
as they tend to bioaccumulate in fish and other
animals (Faroon, Keith, Smith-Simon, & De Rosa,
2003; WHO, 2010).
A series of studies at two different American
sites indicate that prenatal PCB exposure due to
fish ingestion from polluted lakes has consistent
adverse effects on neonatal developmental status
(especially hypore sponsiveness) and memory
among preschool and elementary school aged
children (Evans, 2006). In a more recent set of
studies among Native American adolescents, New-
man and colleagues (2006, 2009) found that PCB
body burden was associated with memory impair-
ments and poorer comprehension/reasoning. This
replicates some prior work with preadolescents
(Evans, 2006). An important and sobering aspect of
these recent data is that, although indigenous
populations in both the global North and South are
frequently exposed to higher levels of toxins than
are other populations, the Nati ve American youths’
levels of PCBs were well within the “normal”
range found in American children. Most research
on PCBs and development has focused on highly
exposed populations.
No known research has investigated the impacts of
PCB exposure on the cognitive functioning of
children living in the global South, and in fact levels
of exposure are also largely unknown (Faroon et al.,
2003; WHO, 2010). However, pres umably the effects
would be consistent with those reported in other
contexts. This was found to be the case in a
longitudinal study assessing Taiwanese children’s
cognitive and behavioral development every year
through age 12 following prenatal exposure to PCBs
in cont aminated cooking oil (Lai et al., 2002). In
comparison to matched unexposed children, children
exposed to PCBs had long-term deficits in IQ.
Much less is known about PCB exposure and
various aspects of socioemotional development.
There may be problems with executive functioning
such as attentional control (Evans, 2006; Hubbs-Tait
et al., 2005; Koger et al., 2005). And Lai et al. (2002)
found that Taiwanese children exposed to high levels
of PCBs prenatally exhibited a greater number of
externalizing and internalizing symptoms than did
matched unexposed children.
One other developmental aspect of toxin exposure
and children’s maturation worth mentioning is that
lower SES contexts appear to accentuate the harmful
impacts of toxins on children’s development (Evans,
2006). This might occur for several reasons, including
chronic stress, levels of cognitive stimulation in the
home, co-occurrence of other toxin exposures, co-
occurrence of other risk factors, and, for older
children, poorer quality school environments.
Pesticides
Research on the developmental impacts of direct
residential pesticide exposure or indirect prenatal or
occupational exposu re (on the skin or clothing of
exposed caregivers) is somewhat limited. However,
there is an extensive research literature document-
ing severe impacts of pesticide exposure on both
rats and in vitro models of the mammalian brain
(see, e.g., Aldridge, Meyer, Seidler, & Slotkin,
2005; Jameson, Seidler, & Slotkin, 2007). Since
pesticides are neurotoxic agents, they may well
have serious effects on the developing brain.
Indeed, in a recent review, Jurewicz and Hanke
(2008) conclude that there is good evidence for the
impact of various pesticides on motor functioning
(abnormal reflexes) in the newborn human and both
motor and cognitive functioning (particularly
reaction times, attention, and short-term memory)
in children. We also know that the developing fetus
and young children have lower levels of the
detoxifying enzymes that may deactivate organo-
phosphate compounds in adults (Furlong et al.,
2006). This suggests that the effects of agricultural
pesticides on children may be particularly
problematic.
DDT and related organochlorine compounds used
as pesticides have been largely phased out in the
US and Europe (Rohlman et al., 2005). Thus their
impacts on children’s developmental functioning in
these contexts are unde rstudie d. However, a
longitudinal study in the early 1990s in the United
States found that prenatal dichlorodiphenyldichlor-
oethylene (DDE) exposure impacted motor func-
tioning at 18 and 24 months, but did not impact
cognitive development at ages 3, 4, and 5 years
(Jurewicz & Hanke, 2008). Two more recent
studies in Spain (Ribas-Fito
´
et al., 2003, 2006) and
one in the United States (Eskenazi et al., 2006),
however, using similar assessment tools, did find
significant relationships between cord blood and
maternal serum levels of DDE, DDT, and related
compounds on the cognitive and psychomotor
functioning of both infants and young children.
More contemporary organophosphate pesticides
may similarly impact reflexes in infants (Jurewicz &
Hanke, 2008), reaction times in early childhood
(Rohlman et al., 2005), and infant and early childhood
psychomotor development (Jurewicz & Hanke, 2008;
Rauh et al., 2006; Ruckart, Kakolewski, Bove, &
Kaye, 2004). There is als o some evidence for effects
on specific cognitive skills, particularly short-term
memory and attention (Jurewicz & Hanke, 2008;
Lizardi, O’Rourke, & Morris, 2008; Rauh et al., 2006;
Ruckart et al., 2004). In addition, these effects appear
to persist over time: Rauh et al. (2006) found that low-
PHYSICAL ENVIRONMENT AND CHILD DEVELOPMENT 5
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income, urban minority children in New York City
who were exposed to high levels of the insecticide
chlorpyrifos were more likely than other children to
have delays in their overall cognitive and motor
development at 12, 24, and 36 months, and were also
more likely to exhibit attention problems.
DDT and DDE are currently commonly used in
the global South (Jurewicz & Hanke, 2008; Mishra
& Sharma, 2011), yet there is almost no research
documenting the impacts of these compounds on
children’s developmental functioning. However, a
longitudinal study of infant cognitive and psycho-
motor functioning following prenatal exposure to
DDE in Mexico found that maternal serum levels
during the first trimester were negatively associated
with infants’ motor development at 1, 3, 6 and 12
months of age (Torres-Sanchez et a l., 2007).
Similarly, Grandjean, Harari, Barr, and Debes
(2006) and Harari et al. (2010) found that prenatal
exposure to pesticides adversely impacted Ecuador-
ian children’s cognitive functioning at ages 6 9
years. Children’s current exposure was negatively
associated with reac tion times, but not with other
cognitive measures. Likewise, Guillette, Meza,
Aquilar, Soto, and Garcia (1998) found that Mexican
4- and 5-year-olds’ prenatal and current exposure to
pesticides delayed their motor development and
some aspects of cognitive functioning. In a study
using a similar design, comparing children living in
rural areas with high pesticide u se to those residing
in low pesticide use areas, 4- to 5-year-old Indian
children showed a similar profile (Kuruganti, 2005).
And Rodrı
´
guez (2012) found that 7- to 9-year-old
children of Nicaraguan agricultu ral workers who
were exposed to a variety of pesticides prenatally
had deficits in working memory, verbal comprehen-
sion, and overall IQ. Eckerman et al. (2007)
demonstrated similar impacts on 10- to 18-year-old
Brazilian children’s memory and attention resulting
from current exposure. Thus there is some evidence
that prenatal exposure may be particularly proble-
matic, but that later exposure may also impact some
aspects of children’s cognitive development. In
addition, there is good evidence for high levels of
prenatal and childhood exposure to both organo-
chlorine and organophosphate compounds in low-
and middle-income countries, including India
(Mathews, Reis, & Iacopino, 2003; Mishra &
Sharma, 2011), Kazakhstan (Zetterstro
¨
m, 2003),
Ghana (Mull & Kirkhorn, 2005), Nigeria (Okafor,
2010) and Egypt (Kishk, Gaber, & Abd-Allah,
2004). In E cuador, Corriols & Arago
´
n (2010)
estimated that there have been 18,516 cases of
acute pest icide poisonings between 1995 and 2006
among children aged 5 14 years, based on the 2069
reported cases. Many of these were due to
occupational exposure, which is in fact a primary
mode of exposure for young children working in
agricultural settings in the global South (Dorman,
2008).
The research documenting effects of pesticide
exposure on children’s socioemotional development
is limit ed, and the findings are mixed (Ruckart et al.,
2004). Rodrı
´
guez (2012), however, found that ADHD
symptoms were more common among pesticide-
exposed girls, but not boys, in a sample of 7- to 9-
year-old Nicar aguan children. These findings make
sense, given othe r results documenting the impacts of
pesticide exposure on children’s attention processes.
Clearly, more research on the impacts of pesticide
exposure on the socioemotional functioning of young
children is warranted.
Air pollution
With ongoing rapid industrialization and urban
growth, poor air quality is a serious concern in
much of the global South, as well as in newly
industrial countries in g eneral (Bartlett, Hart,
Satterthwaite, de la Barra, & Missair, 1999). Here
we discuss work in both the global North and South
documenting the impacts of exposure to air pollution,
primarily resulting from proximity to industrial plants
and to air and road traffic, on childr en’s cognitive and
socioemotional development.
Among the most common pollutants to be studied
for its effect on cognition is nitrogen dioxide (NO
2
), a
toxicant produced by fossil fuel combustion and thus
closely linked to road traffic as well as gas stoves. In
Quanzhou, China, exposure to traffic-related pollution
was found to be associated with poor performance on
neurobehavioral tests (Wang et al., 2009). Similarly,
Dutch children exposed to high levels of NO
2
at home
were found to score lower on memory evaluations,
while no similar correlation was found between NO
2
exposure at school and cognitive outc omes (van
Kempen et al., 2012). A related study of children
living near London’s Heathrow airport, however,
found no association between exposure to NO
2
and
cognitive performance in 9- to 10-year-olds (Clark
et al., 2012).
In other work on air pollution, prenatal exposure to
environmental tobacco smoke was negatively associ-
ated with cognitive performance at age two in African
American and Dominican children in New York City
(Rauh et al., 2004). Within the same populations,
exposur e to h igh leve ls of a ir bor ne polyc y cl ic
aromatic hydrocarbons (PAHs) (largely from road
traffic fuel combustion) was associated with lower
cognitive scores and moderate developmental delay at
age three (Perera et al., 2006), and lower IQ scores at
age five (Per era et al., 2009). Similarly, exposure to
6 FERGUSON ET AL.
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PAHs was significantly associated with lower
nonverbal IQ scores among 5-year-olds in Poland
(Edwards et al., 2010). In China, children living in
proximity to a coal-fueled power plant were found to
have higher cord PAH leve ls than those in both the
New York City and Polan d studies, and these levels
were associated with a greater risk of delay in motor
development and language abilities at age two (Tang
et al., 2008). There are also potentially prolonged
consequences of overexposure to PAHs. Noting that
children highly exposed to PAHs were 2.89 times
more likely to have lower MDI scores than unexposed
children at the age of three, Perera et al. (2006)
suggested that greater exposure to such high levels of
pollution could adversely affect language, reading,
and math abilities later on.
Changes in brain structure as a result of
exposure to high levels of air pollution have been
proposed as a possi ble explanation for resulting
cognitive defects. In Mexico City, urban air
pollution was found to be associated with
prefrontal white matter hyperintense lesions in
both children and dogs; these lesions are believed
to be associated with poor cognitive outcomes
(Caldero
´
n-Garciduen
˜
as et al., 2008). Caldero
´
n-
Garciduen
˜
as and colleagues found that 56.5% of
children living in highly polluted Mexico City
possessed such lesions, in comparison to just 7.6%
of children living in Polotitla
´
n, an area with lower
levels of pollution. The former also performed
more poorly on psychometric tests. However, 7-
and 8-year-olds in Mexico City exposed to high
pollution levels generally scored lower in evalu-
ations of short-term memory, attention, and
learning ability than those in Polotitla
´
n, whether
they possessed such lesions or not (Caldero
´
n-
Garciduen
˜
as et al., 2011). Thus, as Caldero
´
n-
Garciduen
˜
as and Torres-Jardon (2012) note,
exposure to high levels of air pollution is just
one aspect of the environmental i nequalities
experienced by children from lower socioeconomic
backgrounds in both the global North and South
(Evans, 2004).
Against the backdrop of such settings as New York
City, Mexico City, and the rapidly growing cities of
China, most of the literature on the subject seems to
suggest that the relation between air pollution and
developmental outcomes is one largely tied to
industrialization and urbanization. A notable excep-
tion is Munroe and Gauvain’s (2012) investigation of
the assoc iation between indoor open-fire cooking—a
common practice in the global South—and cognition
in four communities: Garifuna in Belize, Logoli in
Kenya, Newar in Nepal, and Samoans in American
Samoa. A moderate negative correlation between
indoor open-fire cooking and block-building perform-
ance, memory, pattern recognition, and structured
play was found.
Water pollution, sanitation, and access
Many families in the global South have limited access
to clean water and sanitation facilities (Bartlett, 1999;
Bartlett et al., 1999; Walker et al., 2007). This section
will outline the effects of water quality (specifically
pollution and sanitation) on children’s cognitive and
socioemotional development in the global North and
South.
The most common water pollutant studied in
relation to children’s development is arsenic. Rosado
et al. (2007) found that among 6- to 8-year-old
children attending school near a smelter complex in
Torreo
´
n, Mexico, those with higher concentrations of
urinary arsenic performed worse on several measures
of cognitive and language development than did
children with lower concentrations. This relationship
was not impacted by lead exposure, demographics, or
nutritional factors, although lower SES children had
higher levels of urinary arsenic. Likewise Tsai et al.
(2003) found that young Taiwanese adolescents
exposed to arsenic in well water had lower scores
than unexposed adolescents on cognitive assessments
of memory and attention switching, even after
controlling for education and gender. And in a study
of 9.5- to 10.5-year-old children using tubewells in
Bangladesh, Wasserman et al. (2004) found that water
arsenic levels were associated with poorer cognitive
functioning. Asadullah & Chaudhury (2011) similarly
found that eighth-grade children exposed to arsenic-
contaminated tubewells in rural Bangladesh had
lower mathematics scores than those not exposed,
even when controlling for schooling history, prior
arsenic exposure, and parental factors. Wang et al.
(2007) likewise found that rural Chinese 8- to 12-
year-olds living close to wells with high levels of
arsenic received lower IQ scores than those who did
not, although it should be noted that this relationship
was only documented for children with high levels of
exposure, and sociodemographic factors were not
controlled for.
High manganese levels in the public water system
may also impact children’s behavior, as documented
by Bouchard et al. (2007) in a study of 6- to 15-year-
old childr en’s behavioral functioning in Canada. After
controlling for potential confounding variables (age,
sex and income), they found that hair manganese was
significantly associated with hyperactivity and oppo-
sitional behavior, as measured by teachers’ report.
Interestingly, the positive relationship between hair
manganese and hyperactivity was greater for older
children (above 11 years old).
PHYSICAL ENVIRONMENT AND CHILD DEVELOPMENT 7
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Research suggests that a lack of proper water
sanitation and waste management exposes many
children to water-borne diseases. For example,
Copeland et al. (2009) found that 30% of households
in Brazilian shantytowns had fecal contaminated
drinking water. Besides their health effects, water-
borne diseases also have adverse developmental
consequences for children. Guerrant and colleagues
(1999) explored the relationship between diarrheal
illness (a common water-borne disease) early in
childhood and the cognitive functioning of 6.5- to 9-
year-old children living in a Brazilian shantytown.
A significant negative correlation was found between
children’s cogni tive functioning and early childhood
diarrhea (see Niehaus et al., 2002 for similar results).
And Lima et al. (2004) found that the availability of
garbage collection and access to a toilet partially
explained differences in cognitive and psychomotor
performance of low-income 12-month-olds living in
northeast Brazil. Likewise, in an investigation of the
environmental conditions (including poor access to
drinking water, an inconsistent electricity supply and
inadequate sewage drains) impacting 7- to 8-year-old
children’s cognitive development in war-torn Bagh-
dad City, Ghazi and colleagues (2012) found that
below-average water quality (as reported by parents)
was associated with lower IQ scores, and that access
to services (including water quality, electricity supply
and acce ss to grocery stores) independently predicted
IQ, after adjusting for parent education and income.
In addition to direct impacts on cognitive
functioning, diarrhea and intestinal parasites resulting
from bacteria-contaminated water (often from sew-
age) contribute to malnutrition and stunting, b oth of
which impact children’s IQ and school performance,
and may also contribute to behavioral problems
(Bartlett, 2003). These associations may result as
early malnutrition and exposure to environmental
toxins and stress can alter both brain structure and
function, thus leading to long-term changes in
cognitive and socioemotional functioning (Gran-
tham-McGregor et al., 2007). In addition, both illness
and malnutrition may lead to increased absences from
school and attention problems when in school.
Further, acces s to water may impact school
attendance directly, particularly for girls in the global
South, who frequent ly have to walk long distances to
collect clean water (Bartlett, 2003). Finally, it is worth
noting that global climate change is likely to affect
access to clean water for millions of low-income
families in the global South, particularly in Africa and
parts of Asia, in the next 20 years (Bartlett, 2008).
A r ecent artic le suggests that contaminated
drinking water in childhood may have lasting effects.
Aschengrau et al. (2011) conducted a retrospective
study of children from eight towns in the US who
were exposed to water contaminated with tetrachlor-
oethane (PCE, a solvent used in dry cleaning) during
the prenatal period and/or early childhood. They
found that, after controlling for p arental SES and
other potential covaria tes, highly exposed individuals
had higher rates of cigarette, alcohol, and other drug
use in adolescence and early adulthood.
NOISE
Numerous studies in high-income countries reveal
that chronic noise exposure early in childhood
interferes with reading acquisition (Evans, 2006).
Although most studies are cross-sectional with
statistical controls for SES, several studies have
demonstrated a doseresponse function. Adverse
impacts on reading have also been replicated in
prospective longitudinal studies with the introduction
of a new major noise source such as an airport, as well
as in experiments with noise attenuation interven-
tions. Children in higher elementary school grades
suffer greater adverse reading outcomes; this has been
attributed to longer duration of exposure (Evans &
Hygge, 2007) but might also reflect greater awareness
of noise (Dockrell & Shield, 2004). Some studies have
shown worse reading outcomes for children exposed
to noise at home and school, bolstering the duration of
exposure explanation. Children with p oorer cognitive
skills appear more vulnerable to the induction of
reading deficits from noise exposure (Evans, 2006;
Dockrell & Shield, 2006).
Several cognitive deficits reliably associated with
noise exposure are candidate mechanisms for the
well-documented noisereading link. L ong-term
memory is adversely affected by noise, and
attentional strategies are altered by noise exposure
(Evans, 2006). Interestingly, a few studies have also
shown linkages between chronic noise exposure and
deficits in auditory discrimination (e.g., phoneme
perception), a critical aspect of speech perception
(Evans, 2006; Evans & Hygge, 2007). Speech
perception is a major buildi ng block of reading
acquisition. Finally, emerging work in neuroscience
indicates potentially detrimental noise effects on brain
speech function and structure (Kujala & Brattico,
2009).
Chronic nois e exposure, similar to many of the
environmental conditions described herein, is not only
aversive but also uncontrollable and sometimes
unpredictable. Repeated exposures to uncontrollable
as well as unpredictable events can undermine human
motivation (Cohen, Evans, Stokols & Krantz, 1986),
thus impacting the persistence and effort needed
(among other things) for academic achievement. The
first human studies of learned helplessness employed
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uncontrollable noise as the induction stimulus
(Hiroto, 1974; Krantz, Glass, & Snyder, 1974).
Since then, many studies have shown that uncontrol-
lable noise exposure can cause learned helplessness
(Evans & Stecker, 2004).
The bioecological perspective (Bronfenbrenner &
Morris, 1998) suggests a com plementary set of
processes that might also be related to noise and
reading acquisition. Noise might alter caregiving
behaviors salient to reading acquisition. We know, for
example, that teachers in high noise impact schools
alter their teaching methods and also complain about
interruption and fatigue (Evans, 2006). It i s
conceivable that parents might talk less to their
children, be less responsive to children’s verbaliza-
tions, and not read aloud as much to their children in
high noise settings.
Research on the relation between noise and
children’s cognitive development outside of the
United States and Europe is extremely limited.
However, what evidence there is suggests that noise
levels impact children in varying contexts similarly.
Seabi, Goldschagg, and Cockcroft (2012) found that
9- to 13-year-old South African children attending a
public school in a high aircraft noise area had poorer
reading comprehension and reduced visual attention
in comparison to a matche d group of children
attending a public school with typical levels of noise
exposure. No differences in working memory were
found, however. Clearly, further work in the global
South is desperately needed, particularly as there is
some evidence to suggest that noise levels might be
significantly higher than in higher-income countries.
For example, in a recent comparison of quiet versus
noisy public schools in urban India, Lepore, Shejwal,
Kim and Evans (2010) recorded a decibel level of 85
dBA. Since decibels are a logarithmic scale, and about
45 dBA is considered appropriate, this is very loud.
Outside of the global South, Hiramatsu and
colleagues (2004) found deficits in long-term but
not short-term memory among 8- to 11-year-olds
residing proximate to a large air force base in
Okinawa, Japan compared to their peers living in
quiet areas. Similarly, Kar sdorf and Klappach (1968)
found that secondary school aged children attending
noisy school s (proximate to road traffic) in Halle,
former East Germany, had more focused attention
problems compared to their peers in relatively quiet
secondary schools. Finally, recent work in Belgrade,
Serbia indicates that chronic residential noise
exposure from road traffic can interfere with
executive functioning, but only among elementary
school aged boys (Belojevic, Evans, Paunovic, &
Jakovljevic, 2012).
Evidence from both laboratory and field studies in
North America and Western Europe shows that noise
exposure is stressful, creating irritation and annoy-
ance and elevating cardiovascular indicators of stress
such as blood pressure and neuroendocrine stress
hormones (e.g., cortisol) (Evans, 2006; Paunovic,
Stansfeld, Clark, & Belojevic, 2011). In most of these
studies, resti ng physiological stress measures were
taken under quiet conditions. Thus the indications of
elevated stress are in relation to chronic noise
exposure. There are more studies of aircraft relative
to street traffic noise, with evidence for the former
having stronger physiological impacts than the latter
(Evans, 2006). However, Babisch, Neuhauser,
Thamm, and Seiwert (2009) found that a nationally
representative sample of 8- to 14-year-old German
children whose bedrooms faced a high-traffic street
had higher blood pressure than those with a bedroom
facing a low-traffic street. These relations were
independent of various sociodemographic factors.
Studies in Slovakia (Regecova & Kellcrova, 1995)
and Serbia (Belojevic, Jakovljevic, Stojanov, Pauno-
vic, & Ilic, 2008; Paunovic et al., 2009) also revealed
adverse impacts of road traffic noise on children’s
blood pressure, even after statistically controlling for
variables such as maternal education. Nine- to
13-year-old children residing near airports in Russia
in the mid-1960s had higher blood pressure than their
peers in quiet areas (Karagodina, Soldatkin, Vinokur,
& Klimukhin, 1969). In a study also conducted in the
mid-1960s in former East Germany, Karsdorf and
Klappach (1968) found that secondary school children
attending urban schools located proximate to busier
streets with higher noise levels had significantly
higher resting blood pressure. Finally, Wu, Chiang,
Huang, and Chang (1993) found that, among 7- to 12-
year-old Taiwanese children attending schools in high
road traffic noise areas of Taipei, those with typical
hearing had significantly higher blood pressure than
those who were deaf.
Data are mixed on chronic noise exposure and
children’s socioemotional development. Prospective,
longitudinal data show that German elementary school
children report lower levels of psychological well-
being with increases in noise exposu re from aircraft
(Bullinger, Hygge, Evans, Meis, & Mackensen, 1999).
A cross-sectional Austrian study of traffic noise
reported a doseresponse function between noise
levels and teacher ratings of psychological wellbeing
among elementary school children if the child had
biological risk factors such as prematurity or low birth
weight (Lercher, Evans, Meis, & Kofler, 2002). Two
different cross-sectional studies of European school
children have uncovered relations between aircraft
noise exposure and elevated symptoms of hyperactiv-
ity (Haines et al., 2001a; Stansfeld et al., 2009; but see
Haines, Stansfeld, Job, Berglund, & Head, 2001b).
None of these European studies found a link between
PHYSICAL ENVIRONMENT AND CHILD DEVELOPMENT 9
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noise levels and general, overall indices of psycho-
logical wellbeing. Finally, Ristovska, Gjorgjev, and
Jordanova (2004) compared several measures of
mental health among 4th grade children in Macedonian
schools varying in traffic noise exposure. Children in
the noisier schools had decreased social skills and
more oppositional behaviors but were similar in levels
of anxiety compared to their peers attending quieter
schools. Recall also that, as indicated above, several
studies have shown a link between chronic noise
exposure and elevated learned helplessness among
children (Evans, 2006).
CROWDING
The most consi stent crowding metric with human
consequences is people per room. Indices of external
density such as people per census tract typically yield
no associations with human behavior (Evans, 2006).
Studies that have teased apart residential density from
family size find the former rather than the latter to be
the more critical variable. Although many believe
there are differences in tolerance for crowding across
different cultural contexts, the cognitive and beha-
vioral development of children living in contexts as
diverse as the United States, India, Thailand, Egypt,
Hong Kong, South Africa, and Jamaica indicates
similar developmental correlates of crowding in both
residential and school settings (Evans, 2006; Liddell
& Kruger, 1987, 1989; Wachs & Corapci, 2003).
It is important to note that children in the global
South, relative to North America and Western Europe,
tend to live in more crowded home environments. For
example, Evans, Lepore, Shejwal, and Palsane (1998)
found that densities among primarily working-class
Indian families range d from .67 to 5 persons/room,
with a mean of 1.81. The US Census considers . 1
person/room to be crowded.
Significant research across multiple contexts
documents the impacts of crowding on general school
achievement and IQ, reading comprehension, and
object spatial relations (Evans, 2006). In a study of
low-SES rural Eygptian 3- to 6-month-olds, Rahma-
nifar et al. (1993) found that infants in more crowded
households were more lethargic and drowsy, con-
ditions associated with delayed development. In their
examin ation of 12-month-old children of recent
Haitian immigrants to the US, Widmayer and
colleagues (1990) found similarly that residential
crowding was linked to delays in psychomotor, but
not cognitive, development. These associations may
result from disruptions of children’s exploration, play,
and engagement with both objects and people in their
immediate environments (Heft, 1979; Liddell &
Kruger, 1987, 1989).
Crowding in educational envi ronments has also
been linked to more off-task time (Kantrowitz &
Evans, 2004; Krantz, 1974). For example, Liddell and
Kruger (1987) found that levels of crowding within a
crowded urban South African childcare center were
negatively associated with 3 2- to 64-month-old
children’s levels of cooperative play and positively
associated with the percenta ge of time spent
unoccupied. In a follow-up study, they found that
children from more crowded homes spent less time
engaged in play with objects, more time unoccupied,
and more time as onlookers (Liddell & Kruger, 1989).
Similarly, in an investigation of relationships between
the home environ ment and Egy ptian toddl ers’
adaptive behavior, Wachs et al. (1993) found that
24- to 29-month-olds’ simultaneous involvement with
persons and objects in their environment was
negatively correlated with density .
Residential crowding can also disrupt parentchild
interactions (Evans, 2006; Wachs & Corapc i, 2003).
In more crowded homes, parents talk less with their
infants and toddlers (Wachs et al., 1993) and use less
complicated vocabulary and sentence structures with
their toddlers (Evans, Maxwell, & Hart, 1999). Not
surprisingly, in an investigation of the influences of
parental SES on South African children’s outcomes,
Goduka, Poole, and Aotaki-Phenice (1992) found that
crowding predicted 5- to 6-year-olds’ vocabu lary
scores. Children’s physi cal development and quanti-
tative skills were also adversely associated with
household crowding.
Evans et al. (1998) showed that some of the adverse
effects of residential crowding, statistically control-
ling for SES, on Indian elementary school children’s
academic achievement were mediated by heightened
family conflict. Another variable that may help
account for the link between household crowding and
diminished academic achievement is inadequate
space to do homework. In a study of low-income
families living in apartments in Singapore, Hassan
(1977) found an inverse relationship between apart-
ment square footage and school performance among
children. More crowded apartme nts also had
inadequate privacy for students to study. The latter
relation was also reported among secondary school
pupils living in apartments in Hong Kong (Mitchell,
1971). These effects o f crowding on children’s
cognitive functioning have similarly been reported
in North America and Western Europe (Evans, 2006),
with consistent differences found for standardized
achievement scores in grade school children. More-
over, the adverse associations uncovered between
residential density and diminished academic achieve-
ment continue through secondary school, independent
of family SES (Evans, 2006). In addition, in an
instrumental variable analysis of national data in
10 FERGUSON ET AL.
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France, Goux and Maurin (2005) showed that the
probability of having to repeat a grade among 15-
year-olds was strongly linked to overcrowding in the
household.
Crowded home and school environments signifi-
cantly impact the behavior and socioemotional
functioning of both children and their parents
(Evans, 2006; Wachs & Corapci, 20 03). For example,
Ani and Gr antham-McGregor (1 998) found that
crowding independently predicted Nigerian elemen-
tary school boys’ levels of aggressive behavior in
school. Parental perceptions of residential crowding
were inversely associated with positive social
behavior among 3- t o 35-month-old Burundian
refugee children living in the United States (McAteer,
2012). Interestingly, in a study of feeding practices in
Jamaican primary schools, Grantham-McGregor,
Chang, Walker, and Powell (1998) found that the
negative impacts of classroom crowding on children’s
behavior were exacerbated by poor nutritio n.
One of the effects of high-density living may be
greater difficulty monitoring and regulating children’s
behaviors. Less parental monitoring is a well-
documented predictor of behavioral conduct dis-
orders, including juvenile delinquency. Parents in
both Singapore (Hassan, 1977) and Hong Kong
(Mitchell, 1971) noted greater difficulties monitoring
their children as a function of household crowding,
and in the former case this appeared to contribute to
greater juvenile delinquency rates.
Greater family conflict and tension have been
reported among crowded Indian and Thai families
(Evans et al., 1998; Fuller, Edwards, Vorakitphoka-
torn, & Sermsri, 1993), and a number of studies in
low-income countries have documented positive
associations between household crowding and physi-
cal pu nishment of children (Afifi, El-Lawin di,
Ahmed, & Basily, 2003; Gage & Silvestre, 2010;
Sumba & Bwibo, 1993; Vega-Lopez et al., 2008;
Youssef, Attia, & Kamel, 1998). In a survey of
parenting values conducted in 34 low- and middle-
income countries around the globe, Cappa and Khan
(2011) documented a relative ly consistent link
between household crowding and maternal endorse-
ment of the need for physical punishment in child
rearing.
In high-income countries both children and parents
report more strained, negative familial interactions in
high-density homes (Evans, 2006), as well as
instances of elevated punitive parenting practices.
Children in more crowded preschools and elementary
schools also evidence more aggressive behaviors
towards their classmates (Evans, 2006). One of the
factors believed to drive part of the crowding
aggression link is conflict over scarce resources such
as toys (Evans, 2006).
One of the ways in which crowded family members
appear to cope with crowding is to socially withdraw
from one another, which can have the unintended
consequence of diminishing socially supportive
relationships (Evans, Saltzman, & Cooperman,
2001b). A number of studies, including some with
random assignment, have shown that crowded
children tend to be more socially withdrawn (Evans,
2006). Parents in more crowded homes are also
typically less responsive to their children (Evans,
2006).
Given greater social withdrawal among children in
high-density homes and lower levels of parental
responsiveness in similar situations, some investi-
gators have explored whether crowding might also be
linked to psychological distress among children. As
indicated above, there is already evidence of elevated
rates of aggression, w ithdrawal, a nd behavioral
conduc t disorders such as juvenile delinquency.
A small number of studies in North America and
Europe have shown that children in more crowded
homes have higher levels of psychological distress
(Evans, 2006). They are also more susceptible to
learned helplessness (Evans, 2006; Evans & Stecker,
2004). This effect has been produced in a laboratory
experiment on crowding and pers istence on puzzles,
and at least two field studies showed a doseresponse
function between residential density and learned
helplessness (Evans, 2006).
In a study of 10- to 12-year-old Indian children,
Evans et al. (1998) showed that residential density
was inversely related to teacher ratings of behavioral
adjustment at school, and elevated conflict and lower
levels of social support within the family. SES was
included as a statistical control. For girls but not boys,
density was also related to learned helplessnes s.
Family conflict partially mediated these relationships.
The authors also found that resting blood pressure was
elevated among more crowded boys, but not girls.
This matches several studies indicating elevated
indices of physiological stress among children living
in more crowded home s or attending more crowded
schools/childcare (Evans, 2006).
CHAOS
Household chaos
Research on children’s environm ents focuses on the
intensity of exposures, largely ignoring temporal
issues such as duration and stochasticity. The paucity
of research on duration of exposure is unfortunate,
particularly in thinking about the maturation of
developing processes over time. This section brings
attention to another largely unexam ined property of
children’s environments—their degree of structure
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and predictability. One of Urie Bronfenbrenner’s
fundamental contributions to child development was
the insight that proximal processes, the exchanges of
energy between the developing child and the persons
and objects in their immediate settings, need to occur
on a regular, sustained basis in order to be effective
(Bronfenbrenner & Morris, 1998). Bronfe nbrenner
also argued that proximal processes need to be
reciprocal between the child and her surroundings and
become progressively more comple x as she matures.
Settings that are unpredictable and unstructured may
destabilize children’s development b ecause they
interfere with effective proximal processes (Bronfen-
brenner & Evans, 2000; Bronfenbrenner & Morris,
1998). This thinking has led to emerging interest in
chaos and children’s development (Evans & Wachs,
2010; Fiese, 2006). Most studies use parental or
observer ratings of levels of structures and routines
coupled with indications of noise, crowding, and
various other interruptions of household activit ies to
evaluate levels of chaos . Evans and Wachs (2010), in
a recent volume on chaos and child development,
provide an in-depth discussion of the mea surement of
chaos.
Chaos has been linked, primarily in cross-
sectional studies in North America, to academic
achievement and socioemotional development,
including behavioral conduct difficulties and
symptoms of internalization (e.g., depression,
anxiety) (Ackerman & Brown, 2010; Fies e &
Winter, 2010). Chaos has also been linked to
learned helplessness and deficits in self-regulation
(Brody, Flor, & Gibson, 1999; Evans, Gonnella,
Marcynyszyn, Gentile, & Salpekar, 2005) and to
difficulties comprehending social cues (Dumas
et al., 2005).
Although most of the work on chaos and child
development has been conducted in Western contexts
(Wachs & Corapci, 2003; Weisner, 2010), a recent
study by Shamama-tus-Sabah, Gilani, and Wachs
(2011) found that levels of chaos in the homes of 8- to
11-year-old Pakistani children uniquely predicted
internalizing and externalizing behavioral problems
and lower levels of adaptive behavior, as rated by both
mothers and teachers. No relations between chaos and
cognitive development were found. Using the same
data set, Shamama-tus-Sabah and Gilani (2010) also
found that home chaos predicted children’s conduct
problems. Clearly, further work in low-income
countries is warranted, particularly as at least some
components of chaotic environments (specifically the
interruption of daily routines, and thus children’s
proximal processes) likely impact children growing
up in the global So uth in similar ways to their
American and European counterparts (Wachs &
Corapci, 2003; Weisner, 2010).
Residential mobility
Poverty, substandard housi ng, and slum dwellings
without security of legal tenure often lead to excessive
residential mobility. Reliable housing is critical for
children’s security and stability, and is essential if
families are to establish daily routines (Bartlett et al.,
1999). High levels of residential mobility in North
America are associated with poorer psychological
adjustment, less socially supportive peer relation-
ships, and deficits in academic achievement (Adam,
2004; Jelleyman & Spencer, 2008; Oishi, 2010). In
addition, students and teachers in classes with high
levels of mobili ty face considerable challenges
because of the instability of their members. Early
childhood residential instability can also influence
developmental traje ctories. Adolescents with more
frequent moves tend to have diminished social
networks and hold comparatively less central
positions therein (South & Haynie, 2004), and are
vulnerable to earlier onset of sexual activity (South,
Haynie, & Bose, 2005). Bures (2003), using a
nationally representative sample of middle-aged
American adults, found that more frequent moves
during childhood were associated with poorer mental
health and more strained social relationships in
midlife, independent of race, income, and education.
In the global South, residential mobility is high,
particularly for low-income families living in urban
areas (Bartlett et al., 1999), who frequently face
forced evictions (Chatterjee, 2007). Although little
work in the global South has directly evaluated the
impacts of high residential mobility on children’s
cognitive and socioemotional functioning, it is likely
that high mobility disrupts proximal processes
(Bronfenbrenner & Evans, 2000). Further, children
whose families are evicted from their homes in a
violent manner may experience trauma. For example,
Dizon and Quijano (1997) have documented the
impact of violent forced evictions in Manila on young
children’s emotional functioning, noting that many
children report recurring nightmare s and/or become
withdrawn.
HOUSING
An extensive body of international research, much of
it employing adapted versions of the HOME scale
(Bradley & Caldwell, 1980), has documented the
impacts of the quality of the home environment on
children’s cognitive and socioemotional development
(Bradley & Corwyn, 2005; Evans, Wells, & Moch,
2003; Iltus, 2007). The HOME scale and its variants,
however, primarily consist of indices of parent child
interactions, with fewer items focused on the physical
environment. Furthermore, most studies with the
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HOME do not look at the impacts of individual
physical environment items on children’s develop-
mental outcomes. Wachs and colleagues’ Purdue
Home Stimulation Inventory (PHSI; Wachs, Francis,
& McQuiston, 1979) provides more detailed infor-
mation about the quality of the physical environment
experienced by children, but it has not been employed
as widely. In addition, although the HOME has been
widely used in various cultural contexts, the scale as a
whole, and the physical environment items in
particular, may not adequately assess the full range
of physical affordances o ffered by housing for
children, particularly in the globa l South (Hayes,
1997; Iltus, 2007; Ngorosho, 2010). In this section, we
focus on what is currently known regarding the effects
of housing type, physical housing quality, and the
availability of resources for children, such as books
and toys in the home.
Housing type
Research on housing type in more affluent countries
has focused primarily on the potential developmental
implications of high-rise housing. There is a long
history of popular discourse about the allegedly
harmful effects of living on the upper floors of large
buildings on children’s development. These concerns
are rooted in the association of large, multistory
housing blocks with crime in public housing in the
US, and with well-documented associations between
building scale and crime (Newman, 1972; Taylor &
Harrell, 1996). However, although a few studies in
high-income countries have shown an association
between children’s aca demic achievement and
residence in high-rise compared to low-rise buildings,
there are also several nonreplications of these
relations (Evans, 2006; Evans et al., 2003). One
study showed that the effects held only for boys,
which could also explain the mixed set of findings
since most studies have not investigated gender
differences in response to high-rise housing (Saegert,
1982).
Several studies in high-income countries have
found that children and youth in high-ri se buildings
manifest greater levels of behavioral c onduct
disorders (e.g., delinquency, aggression) (Evans,
2006; Evans et al., 2003). In an investigation of
relationships between high-rise dwelling and Japa-
nese children’s behavior, Oda, Taniguchi, Wen, and
Higurashi (1989) found that infants living on lower
floors received higher scores on independent beha-
viors (such as greeting and potty training) than did
those living on h igher floors. However, these
differences were not significant for kindergartners.
These findings largely mirror those in W estern
contexts (Evans, 2006; Evans et al., 2003). In
addition, although children’s outcomes were not
measured, Levi, Ekblad, Changhui, and Yueqin
(1991) found that parents living in high-rise
apartments in Beijing showed anxiety regarding the
lack of easily monitored play spaces for children. In a
study of families living in high- versus low-rise
apartments in Israel, Churchman and Ginsberg (1984)
similarly found that the outdoor play behavior of 4- to
5-year-old children living in high-rises was more
restricted than that of other children, although it
should be noted that these effects were not found at
other ages (within the range of 213 years).
In the global South, housing type is inextricably
connected to housing quality. There is little research
investigating the impacts of housing type alone.
Further, the variations in housing type are somew hat
different from those in the global North, with high-
rise dwellings being uncommon. However, ther e is
some evidence that a high percentage of families,
particularly low-incom e families in urban areas, live
in informal housing, and that such housing often lacks
basic amenities such as access to clean water (Bartlett
et al., 1999; Hall & Lobina, 2006). The implications
of an unclean water supply have been discussed
above. In addition, informal housing is typically
unstable, and children living in such areas frequently
face eviction and therefore frequent residential
mobility (Bartlett et al., 1999), the implications of
which have already been discussed. Children living in
informal housing may be more vulnerable to injury,
and are more likely to be exposed to toxins from
industrial waste. And children who are homeless or
who live in informal housing may be less likely to
attend school, as they lack a formal address (Wegelin
& Borgman, 1995). For exam ple, a recent survey in
Delhi found that only 54.5% of children in slums
enrolled in school, as compared to 90% across the city
as a whole (Aggarwal & Chugh, 2003). For those in
school, homelessness has significant impacts on
school performance and socioemotional wellbeing
(Hicks-Coolick, Burnside-Eaton, & Peters, 2003; Neil
& Fopp, 1992). There is also some evidence that
children’s self-esteem is negatively impacted by
residence in slum dwellings and other informal
settlements (Kruger, 2002).
In addition to direct effects, housing type may
interact with other physical characteristics of
children’s early environments to influence human
development. Delays in cognitive development
associated with residential density among preschool
children are attenuated if children have access to a
room where they can spend time alone (Wachs &
Gruen, 1982). Negative self- and teacher-ratings of
Austrian primary school children’s psychological
wellbeing in more crowded homes are exacerbated by
residence in multifa mily complexes in comparison to
PHYSICAL ENVIRONMENT AND CHILD DEVELOPMENT 13
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living in either single-family or small-row family
housing units (Evans, Lercher, & Kofler, 2002).
Housing quality
With ongoing urbanization, the number of families
living in substandard housing in the global South is
only likely to increase (Chawla, 2002; Meng & Hall,
2006). In addition, there is some evidence that
indigenous populations in Australia, for example, are
disproportionately exposed to substandard housing
(Dockery et al., 2010). Yet mos t research to date on
housing quality and children’s development has been
conducted in the US and Europe (Bradley & Putnick,
2012; Evans, 2006; Leventhal & Newman, 2010).
There is a desperate need for further work in this area.
A small number of studies in North America and
Europe have examined housing quality and cognitive
development. A few, including a large national British
cohort, reveal that, independent of SES, children
living in substandard housing have lower academic
competency (Evans, 2006; Evans et al., 2003). These
effects are amplified by duration of exposure to
substandard housing (Douglas, 1964), and one study
showed that when families moved into better housing,
elementary school performance improved (Wilner,
Walkley, Pinkerton, & Tayback, 1962). Dunifon,
Duncan and Brooks-Gunn (2004), using a US national
data set, also showed that residential clutter during
childhood predicted adult educational attainment.
A number of cross-sectional studies in North
America and Europe show that children living in
substandard housing suffer from greater psychologi-
cal distre ss (Evans, 2006; Evans et al., 2003). Nearly
all of these studies incorporate statistical controls for
SES, and the effects replicate in longitudinal studies
examining changes in housing quality (cf. Blackman
& Harvey, 2001). Learned helplessness is also greater
among children living in substandard housing, with
statistical controls for SES (Evans et al., 2001b) , and
two studies reveal elevated physiological stress
among low-income children inha biting poorer quality
housing. In a cross-sectional study, low-income
primary school children living in substandard housing
coupled with noise and crowding had higher levels of
overnight stress hormones (e.g., cortisol) (Evans &
Marcynyszyn, 2004). In a second, longitudinal study,
low-SES children residing in lower quality housing
had elevated cortisol over their first four years of life
(Blair et al., 2011). Differences were already present
at 7 months of age.
An important c onceptual limitation of N orth
American and European research is the rather limited
range of variation in housing quality. Because of
building codes and general levels of affluence, “bad”
housing in these contexts is a lot better than most of
the housing found in the global South. Note that,
unlike the potential problem of unaccounted for
confounds in cross-sectional research that might lead
us to overestimate the impacts of housing quality on
children’s development, the truncated ra nge in
housing quality leads to the opposite estimation bias.
A high percentage of children growing up in the
global South live in substandard housing (Bradley &
Putnick, 2012; Govender, Barnes, & Pieper, 2011)
constructed with inferior building materials, leaking
pipes, and cracks or holes in the walls and ceilings
(Chaudhuri, 2004). In 2002 it was estimated that more
than half the housing units in Zimbabwe, 52.6%, were
considered semipermanent dwellings (United Nations
Statistics Division, 2012). In 2010, 30.6% of the
housing units in Mexico did not possess basic
amenities such as bathrooms, kitchens, and piped
water within the household.
Substandard living conditions lead to higher levels
of exposure to lead and other toxins, air pollutants,
and pests (Govender et al., 2011). In addition, poor-
quality housing, and particularly unsafe dwellings,
place additional stress on low-income parents already
facing multiple stressors (Evans & English, 2002).
This may result in parental fatigue and thus reduce
caregivers’ capacity to be warm and responsive
(Bartlett et al., 1999; Bradl ey & Putnick, 2012; Evans
et al., 2003; Leventhal & Newman, 2010). Further-
more, in unsafe home environments parents and other
caregivers may constrain children’s play and other
activities, so as to reduce the risk of injury (Bartlett
et al., 1999; Bradley & Putnick, 2012; Evans et al.,
2003; Ferguson, 2008). Such constraints are not
unfounded: Dal Santo, Goodman, Glik, and Jackson
(2004) found that preschoolers’ estimated risk of
unintentional injury is almost four times greater for a
child living in a household needing repair. In rural
sub-Saharan African contexts, limited space renders
household items such as kerosene easily accessible for
children, and open fires for heating and cooking pose
a serious injury risk (Munro, Van Nieker k, & Seedat,
2006). Play constraints in particular likely have
important implications for children’s cognitive and
socioemotional development, given the importance of
play for healthy development (Bartlett, 1999; Milteer
et al., 2012).
Research on direct impacts of housing quality on
children’s cognitive and socioemotional development
in the global South is very limited. However, in one
study Ferguson (2008) found that the quality of
Malawian orphanages appears to be associated with
infants’ cognitive functioning. Space and furnishings
(e.g., room arrang ement, displays for c hildren)
predicted children’s cognitive outcomes. This effect
may partially be explained by the fact that the
provision of separate, soft, cozy areas for children
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may both offer comfort and help regulate social
interaction. Such processes may help counter some of
the negative effects of crowding and institutionaliza-
tion on children. In addition, separate, enclosed areas
with comfortable furnishings provide a more
“homey,” and less institutional, setting for young
children (Evans, 2006; Greenman, 1988; Olds, 2001;
Sanoff, 1995).
Given the limited work directly linking housing
quality to children’s developmental outcomes in the
global South, further rese arch in this area is
desperately needed. One useful data source may be
the Multiple Indicator Cluster Survey (MICS), an
international household survey that has been
implemented across a large number of countries in
the global South.
Resources for children
Another aspect of the physical environment that may
influence young children’s development is the
availability of learning materials (Bradley & Corwyn,
2005; Bradley & Putnic k, 2012). However, the
availability of such materials is seldom disentangled
from parent child interactions in the literature.
Nevertheless, there is a strong relation between
income and the provision of both stimulating
materials and experiences for young children from
birth thr ough adolescence (e.g., Bradley, Burchinal, &
Casey, 2001; Evans, 2004; McLoyd, 1998). Several
studies have shown that cognitive enrichment in the
home mediates much of the covariation between
parental income and child cognitive development
(Duncan, Brooks-Gunn, & Klebanov, 1994; Linver,
Brooks-Gunn, & Kobe n, 2002; Smith, Brooks-Gunn,
& Klebanov, 1997). Access to other material
resources such as electricity, a radio, a television, a
telephone, and transportation may also impact
children’s cognitive development in particular
(Bradley & Putnick, 2012).
There is m uch debate over what constitutes
appropriate learning materials in the home, particu-
larly cross-culturally (Bornstein et al., 2012; Bradley
& Putnick, 2012; Ferguson, 2008). Nevertheless, the
UNICEF-developed MICS, which has been adopted
for use in evaluating factors contributing to the
wellbeing of women and children by a large number
of governments worldwide, includes items evaluating
the number of books, the number of children’s books,
and the availability of various types of homemade and
store-bought toys and other play materials. There is
some evidence that such materials are rarely availa ble
in the global South and in rural areas of newly
industrial countries such as India, Thailand, and China
(Bradley & Putnick, 2012). The availability of other
material resources in the home is likewise limited.
A retrospective evaluation of developmental
impacts of the availability of learning materials and
material resources associated with modernity (w riting
tablets, books, electricity, piped water, a radio, a
television, and a transportation vehicle) on children’s
cognitive development at ages 3, 5, 7 and 9 years in
Belize, Kenya, Nepal, and American Samoa was
conducted by Gauvain and Munroe (2009). Access to
these resources was positively correlated with
children’s general cognitive functioning, perspective
taking, and levels of exploratory play. Similarly,
Hamadani et al. (2010) found that, after controlling
for socioeconomic variables, the variety of play
materials and the availability of magazines and
newspapers in rura l Bangladeshi homes indepen-
dently predicted 18-month-olds’ cognitive develop-
ment. And, in Ferguson’s (2008) investigation of
relations between the q uality of the physical
environments of Malawian institutions and infants’
developmental functioning, access to learning
materials independently predicted infants’ language
and socioemotional development.
SCHOOLS AND CHILDCARE
Unfortunately, continual innovation in the design of
schools and classrooms throughout the world is
typically not based on evidence, instead reflecting
current trends in architecture and design (Lackney,
2005). Much of instructional facility innovation at
present is driven by the infusion of information
technology into learning environments. Although this
practice has some potential benefits, we simply do not
know how to train teachers and designers in the use
and configuration of learning environments to take
advantage of the affordances offered by information
technology in schools. This explosion of lea rning
technologies in the West inevitably will be trans-
ported to the global South. Yet evidence to date from
low-income countries indicates no clear impacts of
exposure to computers and related technologies on
children’s academic achievement (Glewwe,
Hanushek, Humpage, & Ravina, 2011; Riddell,
2008).
There is a significant body of research investigating
the impacts of school quality on children’s school
achievement (Evans, 2006; Glewwe et al., 2011;
Irwin, Siddiqi, & Hertzman, 2007; Riddell, 2008).
However, as is true for the work on home
environments, little research has specifically investi-
gated the impacts of the physical environment of
schools on children’s developmental outcomes,
particularly in the global South. Most research in
the US and Europe on the physical characteristics of
educational settings has focused on open versus
PHYSICAL ENVIRONMENT AND CHILD DEVELOPMENT 15
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traditional plan co nfigurations (Evans, 200 6).
Because this issue has tangential relevance at best to
children throughout most of the world, we focus here
instead on school and classroom size; the quality of
building infrastructure (structural quality, lighting,
and indoor climate, and access to electricity, water,
and sanitation); and access to basic resources
(classroom furniture, blackboards, books, computers,
laboratories, and libraries), as these have the clearest
documented impact on children’s school achievement
in the global South (Glewwe et al., 2011; Riddell,
2008).
School and classroom size
There is a large body of research on school and
classroom size. Because nearly all of this work has
been conducted within the US and Western Europe,
we do not know what happens when much larger scale
schools or bigger classrooms occur. Although there is
some variation across regions, primary school pupil
teacher ratios (PTRs) in the global South are typically
much higher than those in the global North. For
example, compare PTRs of 81:1 (Central African
Republic), 76 :1 (Malawi), 61:1 (Chad) and 58:1
(Rwanda) to 18:1 (UK), 14:1 (US) and 13:1
(Germany) (World Bank, 2012). Notably, though,
PTRs in East Asia and the Pacific (average: 17.9:1)
and Latin America (22:1) are much lower than in
South Asia (40:1) and sub-Saharan Africa (42.5:1).
Students in smaller schools in the US and Western
Europe perform slightly better on standardized tests
and feel more connected to their school (Evans,
2006). There is some evidence that the benefits of
smaller school size are greater for low-income
children, and for children in lower grades (Woess-
mann & West, 2006). Similarly, classroom size
research yields a relatively consistent picture of small,
adverse effects on children in both high- and low-
income countries with increasing size (Blatchford,
2003; Ehrenberg, Brewer, Gamoran, & Will ms, 2001;
Woessmann & West, 2006). For example, in an
investigation of linkages between school physical
quality and rural Kenyan fi rst grade ch ildren’s
cognitive functioning and behavior, Daley et al.
(2005) found that the number of students per
classroom predicted levels of off-task behavior and
teachers’ ratings of general behavioral functioning.
There is also some evidence that smaller classrooms
support more student- as opposed to teacher-directed
learning and, similar to school size, are associated
with more socially supportive settings (Blatchford,
2003; NICHD Early Child Care Research Network,
2004).
It is worth noting that both school and classroom
size are confounded with crowding. Work on
household size and density shows that the critical
variable is density, not family size (Evans, 2006).
Insufficient work exists to tease apart school/class size
from crowding.
Physical quality
A surprisingly large number of school spaces for
American children are in disrepair. In a 2000 survey
of school principals in 32 countries in both the globa l
North and South, nearly 30% of US principals noted
that the quality of their school’s buildings and
grounds impacted student learning, and almost 40%
noted the same for available instructional space (von
Ahlefeld, 2007). Estimates were much higher for the
majority of other participating countries, including
the United Kingdom, Norway, Turkey, Uruguay, and
the Slovak Republic. In the global South, the majority
of rural schools in particular have inadequate building
facilities, including a lack of finished flooring
(Glewwe et al., 2011; Riddell, 2008). In many
countries, half to two thirds of schools lack electricity,
water, and basic sanitation facilities (UNICEF, 2010).
For example, the 2005 UNESCO EFA Global
Monitoring Report found that just 39% of classrooms
in Senegal had sanitation facilities, and even fewer
(33%) had access to drinking water.
One i mportant limitation in most work on
educational settings and student achievement, how-
ever, is over-reliance on school professionals’ ratings
of building quality. Since teachers and administrators
are well aware of children’s achievement profiles in
their own schools and are themselves likely affected
by building quality, the potential for spurious
associations in this measurement approach is
considerable. However, assessments of building
quality conducted by independent raters (e.g.,
structural engineers) have also been consistently
associated with standardized test scores (Evans,
2006). Further strengthening these concl usions are
several studies comparing performance before and
after building improvements (Evans, 2006). In two
recent studies utilizing the New York City school
facilities building quality database , Duran-Narucki
(2008) showed that the significant association
between these expert rating measures of school
building quality and academic achievement in
elementary school children was largely mediated by
attendance. Moreover , children in New York City
primary schools with higher rates of student mobility
suffer even worse achievement outcomes as a
function of substandard school facilities (Evans,
Yoo, & Sipple, 2010b).
Given that nearly all of the research on school
facility quality and student performance emanates
from wealthy countries where the range of school
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quality is truncated, this is an area of particular
importance to examine in the global South where the
range of quality is considerably broader. And, in fact,
improvements in the physical structure of schools in
the global South do appear to positively impact
students’ test scores (Glewwe et al., 2011). However,
the research to date in this area is very tentative, and
typically the schools being compared have multiple
factors that differ in quality, making it difficult to
clearly identify individual influences on children’s
outcomes.
In a recent meta-analysis of the research to date on
the impact of school quality, including both physical
and psychosocial factors, on children’s school
achievement in low-income countries, Glewwe et al.
(2011) found that there appears to be good evidence
for the impact of access to electricity on children’s
educational outcomes. And, in their investigation of
the relations between school physical quality and rural
Kenyan first-grade children’s cognitive functioning
and behavior, Daley et al. (2005) found that the
availability of natural light (in schools without
electricity) predicted students’ test scores. In high-
income countries, where lighting is typically suffi-
cient, research has focused more on potential benefits
of exposure to natural light. Although the work on
natural light exposure and children’s health and
performance is limited, some rigorous work
suggesting the pote ntial importance of natural light
for young children has been conducted in Sweden
(Ku
¨
ller & Lindsten, 1992). These investigators found
evidence for the importance of sufficient natural light
exposure for primary school children’s wellbeing
during periods of the year when daylight hours are
limited.
In North America, upper respiratory infections,
asthma and allergies are the most common cause of
primary school absenteeism and have been routinely
linked to exposure to mold and other allergens as well
as ambi ent p ollutants inside both schools and
children’s homes (United States Environmental
Protection Agency, 2003). Poorly maintained heating
and ventilation systems as well as low levels of
indooroutdoor air exchange exacer bate these
adverse indoor climate impacts on children (Evans,
2006). Although work in this area in the global South
is limited, similar impacts of poor- quality ventilation
and heating would be expected.
Consistent with the bioecological perspective
(Bronfenbrenner & Morris, 1998), in addition to
focusing on the direct effects of school setting
physical conditions on children themselves, it is
important to keep in mind that substandard working
conditions influence labor satisfaction and retention,
and the same holds true for teachers. Several
studies have shown that poor-quality school
physical conditions adversely influence teacher
satisfaction and retention (Buckley, Schneider, &
Shang, 2004).
Resources
In the global South, there is some evidence that access
to basic resources in school environments, such as a
sufficient number of desks, tables and chairs; access to
blackboards; access to textbooks and other books; and
the availability of a school library all impact
children’s school achievement (Glewwe et al., 2011;
Riddell, 2008). However, frequently these physical
environment factors are corr elated with each other
and with other physical and psychosocial factors such
as cla ss size, building qual ity and teacher training, and
so it can be difficult to clearly identify key factors
impacting child outcomes. In addition, the mechanism
explaining learning outcomes is somewhat unclear;
perhaps the availability of these resources partly
signals a commitment on the part of the school
administration and relevant local and national
government agencies to quality education (Glewwe
et al., 2011). Nevertheless, a numb er of carefully
controlled studies across multiple contexts document
the importance of having a desk, chair, and textbook
per student. For example, in their investigation of the
relations between school physical quality and rural
Kenyan first-grade children’s cognitive functioning
and behavior, Daley et al. (2005) found that the
number of books per student independently predicted
standardized test scores.
In preschool and childcare settings across the
global South, there is a growing interest in improving
the quality of both physical and psychosocial
environments for children (Engle et al., 2007; Hyde
& Kabiru, 2003; Irwin et al., 2007; Myers, 1992; Van
der Gaag & Tan, 1998). And, indeed, the most
commonly used assessment of the quality of childcare
environments, the Early Childhood Environment
Rating Scale (ECERS; Harms, Clifford, & Cryer,
1998), includes two rating scales that assess children’s
interactions with the physical environment: Space and
Furnishings, and Activities (which includes both the
availability of learning materials and their use).
However, although a significant body of research in
the United States indicates an association between
childcare quality and children’s cognitive and socio-
emotional outcomes (e.g., Sylva et al., 2006), there is
little research that considers the impact of the physical
environment directly.
There is almost no work documenting the impact of
the quality of childcare environments on children’s
developmental outcomes in the global South.
However, as part of a preschool intervention program
in rura l Banglad esh, Moore, Akhter, and Aboud
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(2008) implemented a series of changes, including
increasing the availability of learning materials for
reading and mathematical problem-solving. They
found that preschool scores on the Activities
subsection of the ECERS-R increased, and that
children’s cognitive outcomes and school readiness
improved. However, it should be noted that the
Activities subscale does not separate the availability
of learning materials from their use. In addition, many
researchers in the global South debate the applica-
bility of the ECERS-R in evaluating childcare and
preschool quality in non-Western contexts (Aboud,
2006; Moore et al., 2008).
NEIGHBORHOOD QUALITY
Sadly, most children growing up in the global South
live in neighborhoods of poor physical quality
(Bartlett, 1999; Chawla, 2002; Hardoy, Mitlin, &
Satterthwaite, 2001). Physical characteri stics of these
environments include high levels of air and water
pollutants; nonexistent or inadequate collection of
household waste; poor drainage; poor sanitation;
proximity to busy street traffic; and limited or absent
access to childhood reso urces such as open green
space, grocery stores, schools and hospitals, and play
space (e.g., Bartlett, 1999; Bartlett et al., 1999;
Chawla, 2002; Hardoy et al., 2001; Kruger & Chawla,
2002). Many of these neighborhoods are also unsafe
because of high traffic volumes and limited street
lighting (e.g., Bartlett et al., 1999; Kruger, 2002;
Kruger & Cha wla, 2002). However, the research
linking children’s cognitive and socioemotional
development to neighborhood physical conditions,
beyond those already discussed (exposure to toxins,
air and water pollution, sanitation, and high mobility)
is very limited. The situation is similar in high-income
countries. There is a large literature on neighborhood
quality and human health and wellbeing (Diez Roux
& Mair, 2010) and more specifically child develop-
ment (Leventhal & Brooks-Gunn, 2000), but this
work is bereft of considerations of the physical
environment of neighborhoods. In nearly all of the
extant research, neighborhood quality is defined by
the socioeconomic profile of the population. Two
areas of neighborhood physical environment that are
receiving considerable attention because of the
obesity epidemic are access to places for physical
activity and proximity to healthy food sources. This
work, although still in its early stages, indicates that
both of these neighborhood characteristics are related
to obesity in children and are much more likely to be
wanting in low-SES neighborhoods (Diez Roux &
Mair, 2010; Evans, Wells, & Schamberg, 2010a).
UNESCO’s Growing Up in Cities (Chawla, 2002)
provides some interesting insights into children’s
experiences in neighborhood environments in Argen-
tina (Cosco & Moore, 2002), India (Bannerjee &
Driskell, 2002), and South Africa (Kruger, 2002). In
all three contexts, children aged 1015 years reported
a keen awareness of the physical quality of their
neighborhood environments, noting specific aspects
of these environments (e.g., high traffic, litter, poor
sanitation, a lack of open green spaces) that limited
play opportunities. Similar data have been found
among Australian primary school children (Homel &
Burns, 1989). Perhaps most salient in children’s
narratives across these and the other contexts studied
(Australia, the United Kingdom, the United States,
Norway, Poland, South Africa) was the importance of
access to green play spaces. Other work in low-
income countries has similarly documented the
importance of play spaces and access to natural
settings for children (e.g., Bartlett et al., 1999).
However, little work has specifically investigated the
impacts of natural settings on the cognitive and
socioemotional development of children in the global
South.
Neighborhood physical quality
Parents rated their 9- to 12-year-old children in two
Canadian cities as higher in psychological distress if
the neighborhood was rated by trained observers as
lower in physical quality (Gifford & Lacombe, 2006).
Both longitudinal and cross-sectional studies (Diez
Roux & Mair, 2010) show that neighborhood upkeep
influences adults’ psychological distress. To illustrate
the potential power of neighborhood physical quality
on adult mental health, adjusting for income, race, and
neighborhood poverty, New York City adults living in
poor-quality neighborhoods were more than 30%
more likely to suffer from depression in the past six
months compared to adults residing in better physical
quality neighborhoods (Galea, Ahern, Rudenstine,
Wallace, & Vlahov, 2006). Psychol ogical distress in
adults is a central risk factor for healthy parenting.
Close proximity to street traffic caused Zurich
parents to restrict children’s outdoor play activities,
which in turn was associated with diminished social
and motor skills among preschoolers (Hu
¨
ttenmoser,
1995). High levels of street traffic have also been
associated with less social interaction among
neighbors in San Francisco neighborhoods (Apple-
yard & Lintell, 1972).
Natural settings
As has been discussed above, most research on the
impacts of access to the natural environment on
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children’s well being has taken place in the US and
Europe. Parallel to findings in North America and
Western Europe (Evans, 2006), children across the
global South prefer natural areas and engage in more
complex leve ls of play in such settings (Bannerjee &
Driskell, 2002; Bartlett, 1999; Bartlett et al., 1999;
Chawla, 2002; Cosco & Moore, 2002; Kruger, 2002;
Kruger & Chawla, 2002). Given the potential for
access to natural play spaces to mitigate some of the
impacts of poor-quality physical environments on
low-income children’s cognitive and socioemotional
development, further work in this area is warranted.
A few North American studies suggest that
children’s executive functioning may be enhanc ed
by access to nearby natural outdoor play spaces
(Evans, 2006), and a meta-analysis revealed that the
greening of school yards across multiple sites in
North America a nd Wes tern Europe has been
associated with improv ed academic performance
and better psychological wellbeing among pupils
(Bell & Dyment, 2008).
Evaluations of outdoor nature experiences such
as Outward Bound in high-income countries reveal
consistent, positive associations with psychological
wellbeing (Hattie, Marsh, Neill, & Richards, 1997).
Part of the apparent psychological benefits of
access to outdoor play areas is likely related to
enhanced physical activity, which has been
consistently linked in both children and adults to
proximate, outdoor recreational spaces (Evans
et al., 2010a). In a recent WHO study of
approximately 1200 6- to 18-ye ar-olds residing in
eight European cities, the well-documented inverse
relation between household income and childhood
obesity was explained, in part, by proximity to
open green space. Children from wealthier house-
holds had greater access to open green spaces,
which in turn was linked to higher levels of
physical activity. The latt er largely accounted for
the inverse household income BM I correlation
(Evans, Jones-Rounds, Belojevic, & Vermeylen,
2012).
Adults living in Los Angeles neighborhoods with
more parks, independent of SES characteristics,
perceived greate r collective efficacy, an index
reflecting greater social cohesion and social control
(Cohen, Inagami, & Finch, 2008). There are also
several studies showing that adults’ physiological
stress responses to aversive stimuli are attenuated by
natural surroundings (Evans, 2003). Thus some of the
benefits of nearby nature for children may also
operate via their parents. One study also revealed that
children’s psychological reactions to stressful life
events were attenuated by proximity to outdoor nature
(Wells & Evans, 2003).
CONCLUSIONS AND FUTURE DIRECTIONS
As can be seen on reviewing the current state of the
evidence on the physical environment and child
development, very little work has documented the
impacts of envi ronmental conditions on the develop-
ment of children growing up in the global South and
other low-income countries. This is unfortunate for
many reasons. Foremost, the majority of the world’s
children grow up outside of the affluent countries
where most of the work has transpired. In fact,
Bornstein and colleagues (2012) argue that less than
10% of developmental science research has studied
communities that account for 90% of the world’s
population.
What we do know suggests that the physical
environment experienced by children impacts their
cognitive and socioemotional development across the
lifespan, from the prenatal period through adulthood.
The development of interventions to improve the
physical environments experienced by children across
the globe is thus warranted. Interve ntions would also
offer tremendous research opportunities to examine
how environmental improvements can change devel-
opmental trajectories . Th is would help address
perhaps the major methodological weakness in most
work on children and the physical environment:
potential selection bias. Compa risons between chil-
dren living in different environmental conditions
nearly always face the alternative explanation that
some individual characteristic rather than environ-
mental conditions might be the root cause of
developmental changes. Another critical reas on for
studying children in the global South and elsewhere
outside of high-income countries is the severely
restricted range of environmental conditions typically
monitored in research on child settings in North
America and Wester n Europe. Essentially every
single environmental factor reviewed herein exists
in a substanti ally greater range in low-income
countries. Thus not only is 90% of the research on
children and the environment from samples of less
than 10% of children, but the same goes for the
environmental side of the equation. We know a
reasonable amount about how variability within the
top 10% or 20% of conditions matters. We know
almost nothing about how variability from the top to
the bottom 10% of environmental conditions affects
children.
With these caveats in mind, the evidence to date
documents adverse impacts of individual environ-
mental risk factors, partic ularly environment al toxins
and pollutants, on children’s cognitive development.
However, the impacts on socioemotional functioning
are less certain. In addition, the documented evidence
for impacts of noise, crowdi ng, and chaos on the
PHYSICAL ENVIRONMENT AND CHILD DEVELOPMENT 19
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cognitive and socioemotional development of chil-
dren growing up in the global South is tentative at
best. And, across the globe, the impacts of individual
aspects of the physical environment of housing,
schools and neighborhoods are unclear, primarily
because multiple factors tend to be correlated. This is
especially true for low-income families, underfunded
schools and poor neighborhoods in both the global
North and South, where poverty is frequently
associated with multiple environmental risks (Evans,
2004; Ferguson et al., 2009). It is also important to
recognize that when cumulative environmental insults
have been studied, they typically reveal worse
outcomes than singular environmental risks (De Fur
et al., 2007; Evans, Li, & Whipple, in press).
Furthermore, for low-income children, the confluence
of deteriorating physical conditions along with
inadequate psychosocial conditions is a primary,
underlying pathway that helps account for the ill
effects of poverty on child development (Evans &
Kim, 2013).
In order to better understand the effects of multiple
environmental risk factors on children’s cognitive and
socioemotional development, a holistic, multidisci-
plinary, and multilevel approach that encompasses the
complex interactions between biological, physical,
and psychosocial factors impacting children’s devel-
opmental outcomes is needed. Such an un derstanding
will allow us to more effectively intervene in
children’s actual lived environments. In other work
(Ferguson & Lee, 2 013), we have proposed a
bioecocultural framework that integrates key com-
ponents of Bronfenbrenner’s bioecological model
(Bronfenbrenner & Evans, 2000; Bronfenbrenner &
Morris, 1998) with Nsamenang and colleagues’
ecocultural approach (e.g., Nsamenang, 1992; Nsa-
menang & Dawes, 1998), and Li’s (2003) cross-level
dynamic biocultural coconstructivist paradigm (see
also Boivin & Giordani, 2009). We thus focus here on
outlining key steps involved in utilizing this frame-
work to better understand and address the impacts of
the physical environment on the cognitive and
socioemotional development of children living in
multiple contexts.
Developing and implementing a
bioecocultural framework
The first step in developing and implementing a
bioecocultural framework is to identify what is known
and what is not yet known about the impacts of
individual and intersecting environmental factors on
children’s development. The present review, in
conjunction with Evans’ (2006) earlier review that
focused on Western contexts, does just that. We
summarize the evidence to date below, while at the
same time considering when the methodolo gies
employed in related work are appropriate for filling
in the gaps in the research literature, and when they
are not. When they are not, it is important to identify
what is currently known in a particular cont ext, for
example identifying relevant country-level statistics
and databases. In addition, new tool s for assessing
children’s development in varying cultural contexts
might be needed (Ferguson & Lee, 2013; Nsamenang,
1992). Second, key factors—what public health
researchers call “leverage points”—influencing chil-
dren’s developmental outcomes should be identified
(see Ferguson et al., 2009). Where possible, those
leverage points most susceptible to change should be
noted. Th ird, all of this informatio n can be
incorporated into an overarching bioecocultural
framework, as outlined above, that identifi es all
known and hypothesized factors influencing a
particular developmental outcome (e.g., literacy),
key leverage points, known interacting influences
between factors and, when possible, the mechanisms
behind the relations between each factor and
children’s development. Once this is done, inter-
disciplinary, international research teams should
develop an d implement a collaborative research
program to test the model, with a specific focus on
filling in the gaps in the research literature in
understudied contexts, namely the global South. In
doing this work, the intimate involvement of
individuals, communities, local and national govern-
mental agencies, and researchers living in each
context studied is essential (Dawes & Donald, 2000;
Weisner, 2010). In fact, ideally relevant individuals
and communities should be involved in every stage
outlined above. This will ensure that similarities and
differences between contexts are adequate ly con-
sidered. Finally, in collaboration with all of these
important constituents, key leverage points can be
confirmed and leveraged in implementing a holistic
program of reform that will effectively address
current environmental inequalities, so as to ensure
healthy developmental outcomes for all children.
Phase 1: Identifying influencing factors
Conceptually, given their direct impact on children’s
biological systems, it is likely that environmental
toxins and pollutants (specifically lead, mercury,
PCBs, various pesticides, NO
2
, PAHs, environmental
tobacco smoke, arsenic, manganes e, and tetrachlor-
oethane) impact the cognitive and socioemotional
development of children living in different contexts
similarly. The limited evidence to date indicates that
this is the case. Further work on factors impacting
socioemotional development is warranted, however ,
especially in the global South. Similarly, despite
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differences in adults’ perceptions of crowding and
chaos, the evidence we have reviewed here suggests
that factors contributing to chaos, including noise and
crowding, likely impact children and adults across the
globe in similar ways. However, given the limited
work in this area, partic ularly in considering socio-
emotional development, these predictions need to be
tested more thoroughly in low-income countries.
In terms of home and school environments,
adequate building quality seems essential, but
determining what this should entail in differing
contexts is challe nging. Home, classroom and school
designs that reduce chaos may be particularly
important. In addition, adequate lighting and comfor-
table climatic conditions (temperature, indoor air
quality) are important for effective learning in school
environments. Finally, the availability of key material
and learning resources in both home and school
environments appears to be particularly important for
cognitive development, but the specific resources
needed in differing contexts is unclear. Further work
in this area is needed. Likewise, although it is clear
that children growing up in low-income neighbor-
hoods in both the global North and South encounter
numerous disadvantages that impact their cognitive
and socioemotional development, little is currently
known regarding the specific components of the
physical environment of neighborhoods impacting
these developmental outcomes. Neighborhood physi-
cal quality is the most understudied aspect of the
environmental characteristics discussed herein.
An important caveat at this point is that most of the
work discussed in this review, with a few notable
exceptions (discussed throughout), employs environ-
mental and outcome measures developed in the West.
Yet th e specific co mponents of the physical
environment impacting child development in the
global South may differ from those in the global
North, as we have noted throughout. In addition,
different cultural contexts, values, and beliefs in the
global South may mean that although, for example,
there are documented impacts of lead on Egyptian
children’s IQ scores, this aspect of children’s
development may be less important than socio-
emotional compete ncy in this context. Thus a
consideration of what engenders competence within
particular cultural contexts is essential (Ferguson &
Lee, 2013; Weisner, 2010).
The development of culturally appropriate assess-
ments of both environmental quality and children’s
developmental outcomes in the global South is sorely
needed. This could, and should, go hand in hand with
an evaluation of the effectiveness of a larger
bioecocultural model in capturing the multiple
environmental factors impacting childr en’s specific
developmental outcomes in particular contexts, so as
to provide a good test for the effectiveness of these
methodologies in each context (Ferguson, 2008;
Ferguson & Lee, 2013; Nsamenang, 1992). The
questionnaires developed for the MICS, an inter-
national household survey, may be a useful beginning.
The involvement of key stakehol ders living within
each context studied will also be essential in this
process. UNESCO’s Gro wing up in Cities project
(Chawla, 2002) provides a nice illustration of a
participatory process in which research questions and
assessment tools were developed jointly by research-
ers and community stakeholders.
Phase 2: Identifying leverage points and
mechanisms
Bronfenbrenner noted that proximal processes, the
exchanges of energy between the developing child
and the persons and objects in her immediate settings,
are the “engines of development” (Bronfenbrenner &
Morris, 1998; Bronfenbrenner & Evans, 2000). In
order for these processes to be effective, they need to
occur on a regular, sustained basis and become
increasingly complex as the child matures. Given this,
a starting point for identifying key leverage points is
the identification of envi ronmental factors that clearly
interrupt proximal processes for children. Factors that
contribute to chaos, including noise, crowding, and
residential mobility (partially instantiated by informal
housing facilities), are likely candidates here, as they
are likely to interfere with effective proximal
processes (Bronfenbrenner & Evans, 2000; Evans &
Wachs, 2010). As we have d iscussed above, housing
and school design may also contribute to chaos,
particularly when a large number of people live or
study in a small number of open-plan rooms. In
addition, schools and neighborhoods characterized by
high residential instability may contribute to chaos at
the macro level.
We have noted above that one of the unintend ed
consequences of various coping strategies for dealing
with crowding, noise, and chaos may be deteriorations
in socially supportive relationships and less respon-
sive parenting. The design of space s, not simply the
presence of stressors like chaos, can also influence
interpersonal relationships, thus affording or inhibit-
ing ease of interpersonal interactions. For example,
are typical travel routes likely to lead to unplanned,
impromptu interactions? Are there spaces that people
feel comfortable spending time in such as cafes and
common facilities (e.g., a communal laundry area,
community play spaces)?
In addition to proximal processes such as parent
child interactions (e.g., responsiveness, monitoring),
several other candidate mechanisms are worthy of
further examination in both the global North and
PHYSICAL ENVIRONMENT AND CHILD DEVELOPMENT 21
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South. One of the common qualities of many of the
suboptimal physical settings children encounter is
their uncontrollability. We need more examination of
mastery, se lf-efficacy and other control-related
processes in relation to the environment and
children’s development. Some of the ways in which
physical settings can influence mastery are:
uncontrollable stressors such as noise and crowding;
highly unpredictable and variable conditions such as
chaos; the degree of inflexibility and regimentation of
settings such as school; the scale and manipulability
of settings for childr en; and design and planning
features that afford crime, such as undifferentiated
spaces lacking in ownership and defensibility.
Considerable work shows that time spent in nature
and other restorative spaces can help counteract
cognitive fatigue and stress engendered by the fast-
paced, multitasking demands of modern life, increas-
ingly common throughout the world, regardless of
economic development (Kaplan & Kaplan, 1989).
Fascination or the experience of involuntary attention
(e.g., curiosity) is not the sole purview of natural
elements but can include human-made objects and
spaces that attract and hold attention effortlessly (e.g.,
people-watching in a plaza, gazing at a fountain,
meandering through a museum or good bookstore, or
enjoying street entertainment).
Stressors such as crowding, noise, traffic, and chaos
can directly strain physical and psychological
systems, but they also have the ability to alter
regulatory processes such as coping and executive
functioning (Evans & Kim, 2013). Thus another area
worthy of further scrutiny in considering children’s
environments is the role of coping and self-regulatory
processes. When children and their parents encounter
various suboptimal environments, they often adapt
strategies, be they behavioral, cognitive, or both, to
right the balance between environmental demands
and human comfort and wellbeing. These adjustments
and adaptations to the environment, in and of
themselves, can lead to developmental changes. For
example, parents who cope with too much unwanted
social interaction by withdrawing from their children
are likely to be less responsive.
The impact of the environment on adult caregivers
is a particularly important underlying process to
consider. Parents in crowded homes are typically less
responsive and less patient (Evans et al., 2001b).
Teachers in noisy schools report more fatigue and
frustration, and observations of noisy schools show
substantial reductions in teaching time (Evans &
Hygge, 2007). The stress and anxiety engendered by
knowledge of toxic exposures or parental struggles
with substandard housing are bound to translate into
less than ideal parent child interactions. Interest-
ingly, such parentchild interactions may in fact
modify children’s gene expression without altering
the nucleotide sequence, as recent work in epigenetics
has demonstrated (Meaney, 2010).
Phase 3: Identifying and addressing key
inequalities and opportunities
As we have discussed above, the final step involves
interdisciplinary, intern ational research teams both
filling in the gaps in the research literature in
understudied contexts and implementing interven-
tions to improve children’s developmental function-
ing. One key leverage point for both cognitive and
socioemotional development that might be further
studied and then addressed is chaos. Implementing
interventions within children’s home, school and
neighborhood environments that reduce chaos and/or
moderate its impacts on children may be a particularly
effective way to improve children’s developmental
outcomes. Interventions could include building sound
barriers to block out aircraft and traffic noise,
relocating homes and schools further from busy
highways and airports, and redesigning open-plan
homes and classrooms to include quiet, secluded
spaces for children.
One of the ways in which chaos has a particularly
insidious effect is in its interruption of play, a key
proximal process for young children’s cognitive and
socioemotional development (Bartlett, 1999; Milteer
et al., 2012). Unsafe housing, school and neighbor-
hood setti ngs also disrupt play, as was coherently
argued by the children living in such diverse contexts
as Argentina, India, South Africa, Australia, the
United Kingdom, the United States, Norway, and
Poland involved in UNESCO’s Growing Up in Cities
project (Chawla, 2002). Low-income urban children
may be at particular risk for interruption of play
processes (Chawla, 2002; Milteer et al., 2012), and
these same children frequently encounter multiple
environmental risk factors in their home, school, and
neighborhood environments (Bartlett et al., 1999;
Evans, 2004). Thus building safe, green play spaces
for low-income and other children across the global