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ADC Online First, published on June 12, 2011 as 10.1136/adc.2010.195917
Original article
What role for the home learning environment
and parenting in reducing the socioeconomic
gradient in child development? Findings from the
Millennium Cohort Study
Y Kelly,1 A Sacker,1 E Del Bono,1 M Francesconi,1 M Marmot2
▶ Appendices 1–3 are available online only. To view these
file please visit the journal
online (http://adc.bmj.com)
1Institute
for Social and
Economic Research (ISER),
University of Essex,
Colchester, UK
2Epidemiology and Public
Health, University College
London, London, UK
Correspondence to
Professor Y Kelly, Institute for
Social and Economic Research
(ISER), University of Essex,
Wivenhoe Park, Colchester
CO4 3SQ, UK;
[email protected]
Accepted 5 May 2011
ABSTRACT
Background Early child health and development (ECD)
is important for health in later life. Objectives were to
(1) examine the extent of socioeconomic inequality
in markers of ECD at ages 3 and 5 years; (2) examine
whether the ECD–income gap widens between
these ages; (3) assess the contribution of the home
learning environment, family routines and psychosocial
environment to observed inequalities in ECD.
Methods Data on socioemotional difficulties, and tests
of cognitive ability in 3-year-old (n=15 382) and 5-yearold (n=15 042) children from the UK Millennium Cohort
Study were used.
Results Children in the highest income group were
less likely to have socioemotional difficulties compared
with those in the lowest income group at 3 and 5
years (2.4% vs 16.4% and 2.0% vs 15.9%, respectively)
and had higher mean scores: age 3 ‘school readiness’
114 versus 99; verbal ability 54 versus 48, and age 5:
verbal ability 60 versus 51, non-verbal ability 58 versus
54 and spatial ability 54 versus 48 (all p<0.001).
The income gap in verbal ability scores widened
between ages 3 and 5 (Wald test, p=0.04). Statistical
adjustment for markers of home learning, family
routines and psychosocial environments did more to
explain the income gap in socioemotional difficulties
than in cognitive test scores.
Conclusion Our results suggest that relationships
between family income and markers of ECD are
amenable to change. The role of home learning, family
routines and psychosocial environmental factors are
potentially important in closing income gaps in ECD.
INTRODUCTION
Early child health and development (ECD) is
important for health in later life.1 The social gradient in markers of child development have been
documented in the UK and elsewhere. 2 – 5 It follows that if we do something about the social gradient in child development this might impact on
later social gradients in health.1
A vast array of environmental factors including
parenting styles and activities and the parent–
child relationship influence ECD,6 – 8 and in turn,
ECD at school entry predicts later educational
attainment.4 9 Government funded initiatives
aimed at improving the lives of young children
emphasise the importance of what parents do,
the home learning environment and the warmth
of relationships in fostering good developmental
outcomes in young children.10 11
What is already known on this topic
▶
▶
▶
Early child health and development (ECD) is
important for health in later life and social
gradients in ECD are evident.
Numerous environmental factors including
parenting styles and activities and the parent–
child relationship influence ECD.
Government funded initiatives emphasise the
importance parental activities, the home learning environment and warm relationships in
fostering good developmental outcomes.
What this study adds
▶
▶
▶
In the UK, there are strong socioeconomic
inequalities in ECD with income gaps in
socioemotional difficulties and cognitive ability
throughout the preschool period.
Income gaps in cognitive test scores widen
during the preschool years.
Markers of home learning, family routines and
psychosocial influences explained income
gaps in socioemotional difficulties better than
cognitive test scores.
Prior studies have documented social gradients
in markers of child development in school age
children,4 and at single time points in early childhood. 2 3 5 However, in contemporary UK settings
we do not know the magnitude of social inequalities in ECD across the preschool years, nor do we
know whether inequality gaps remain constant
throughout the preschool period or widen over
time. This paper adds to current knowledge by:
(1) examining the extent of inequality in markers
of ECD, according to income, at two time points –
ages 3 and 5 years; (2) examining whether the
ECD–income gap widens between ages 3 and 5
years; and (3) assessing the contribution of the
home learning environment, family routines
and psychosocial environment in explaining
observed inequalities in ECD.
METHODS
The Millennium Cohort Study
The Millennium Cohort Study (MCS) is a nationally representative longitudinal study of infants
born in the UK. The sample was drawn from
Kelly Y, Sacker
A, Del Bono
E, et al.
Archtheir
Dis Child
(2011). doi:10.1136/adc.2010.195917
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births in the UK between September 2000 and January 2002.
The survey design, recruitment process and fieldwork have
been described in detail elsewhere ( http://www.cls.ioe.ac.uk/
studies.asp?section=0001000200010010).12 The fi rst three
sweeps of the survey involved home visits by interviewers
when cohort members were aged 9 months, 3 years and 5
years. During structured interviews at home visits, questions
were asked about socioeconomic circumstances, demographic
characteristics, home learning, family routines and psychosocial environment. At ages 3 and 5, cognitive assessments were
carried out by trained interviewers and questions were asked
about the cohort members’ socioemotional difficulties.
Ethics approval for the MCS was obtained from the relevant
ethics committees and parents gave informed consent before
interviews took place, and separate written consent for cognitive assessments.
Socioemotional difficulties
When cohort members were approximately 3 and 5 years old,
parents were asked to complete the Strengths and Difficulties
Questionnaire (SDQ). At age 3 an age appropriate adapted version of the SDQ was used, and at age 5 the age 4–15 years
version was employed ( http://www.sdqinfo.org). Briefly, the
SDQ is a validated tool which has been shown to compare
favourably with other measures for identifying hyperactivity
and attention problems.13 14 The SDQ asks questions about
five domains of behaviour, namely: conduct problems, hyperactivity, emotional symptoms, peer problems and pro-social
behaviour. Scores from the conduct problems, hyperactivity, emotional symptoms and peer problems subscales are
summed to construct a total difficulties score. Clinically relevant cut-points for problem behaviours were determined to be
the scores of the top 10% of all MCS children with SDQ data
at ages 315 and 516 years, and were ≥17 and ≥15, respectively.
Cognitive ability assessments
Cognitive ability was assessed using widely validated,
age appropriate tests. At age 3 the tests were: the Naming
Vocabulary subscale from the British Ability Scale (BAS)
and the Bracken School Readiness Assessment (BSRA). The
BAS Naming Vocabulary assesses verbal ability/expressive
language. During this test children are asked to name items
pictured in a booklet.17 The BSRA measures basic concept
development and the readiness of the child for formal education – the higher the score the more ‘school ready’ a child
is considered to be. During the test children are shown a set
of colour pictures that contain six subtests to assess basic
concepts such as colours, letters, numbers/counting, sizes,
comparisons and shapes.18 Mean age standardised values for
the BSRA composite score are reported. At 5 years in addition to the BAS Verbal Ability subscale, two other BAS subscales were administered, namely: Picture Similarities which
assesses non-verbal/problem solving ability, during which the
child is asked to place a picture card against the most similar in concept among a set of four other pictures; and Pattern
Construction which assesses spatial ability and consists of a
set of timed tasks for the child, copying and constructing patterns with coloured tiles and cubes. These assessments use
age related starting points and alternative stopping points to
protect the motivation and self-esteem of the child.17 Mean
age standardised t score values for BAS subscales are reported.
The BSRA and BAS have been shown to be predictive of later
child cognitive performance.18 -20
2 of 6
Socioeconomic and demographic markers
Family income was categorised in to five broadly similar bands
across survey sweeps. Demographic markers were whether
the child was fi rst born, whether the household language was
English or another language, and the mother’s age at the time
of birth.
Home learning, routines and psychosocial environment
Variables were categorised into three theoretically informed
overlapping domains of the home environment, which were
learning, routines and psychosocial environmental factors.
Markers of the home learning environment from infancy
were: parental basic skills difficulties – this variable was a
composite measure based on responses to questions to parents on ability to read a children’s book, fi ll in forms and
check change in a shop; at age 3 questions were asked about
the frequency of learning activities: someone reads stories to the child, visits to the library, help with alphabet,
numbers/counting, learning songs, poems and rhymes, and
does drawing and painting; and at age 5 questions were
asked about the frequency of: someone reads to the child,
help with reading, writing and numbers, telling stories to
the child, visits to the library, musical activities and draws,
paints or makes things. Indicators of family routines at ages
3 and 5 were whether the child had regular bedtimes and
mealtimes. Markers of the psychosocial environment at age
3 were: maternal psychological distress (K6 questionnaire 21),
parent–child relationship (Pianta scale22), discipline strategies – this was a composite score of seven items, α=0.64
(How often do you do the following when child is ‘naughty’:
Ignore, Smack, Shout, Send to bedroom/naughty chair, Take
away treats, Tell off, Bribe), nine parent–child items from
the Home Observation for Measurement of the Environment
Inventory, α=0.60 (mother’s voice conveys positive feeling;
mother converses with child at least twice; mother answers
child’s questions or requests verbally; mother spontaneously
praises child’s qualities or behaviour twice during the visit;
mother caresses, kisses or cuddles child at least once during
the visit; mother introduces interviewer to the child; mother
scolds (shouts) or makes derogatory comments to child more
than once during the visit; mother uses physical restraint,
grabs or pinches child during the visit; mother slaps or
spanks the child during the visit – positively phrased items
were reverse scored), 23 whether the mother felt she was a
competent parent, whether the family had lots of rules and
whether these rules were enforced; and at age 5 were: maternal psychological distress (K6 questionnaire), discipline
strategies (the same items as age 3), whether the mother felt
she was a competent parent and whether the mother felt
close to the child.
Data analysis
Behavioural and cognitive outcomes are known to be moderated by multiple births. 24 Therefore, we analysed data for singleton infants with data on family income. We examine two
MCS samples based on those whose mothers (1) participated
in sweep 2 (age 3) of the survey (n=15 382), and (2) participated
in sweep 3 (age 5) of the survey (n=15 042).
For sample 1 (age 3), socioemotional behaviour data were
available for n=14 218, school readiness data for n=13 651
and verbal ability data for n=14 373. Results are presented for
cohort members with complete data for explanatory factors of
interest; this reduced the sample for socioemotional behaviour
Kelly Y, Sacker A, Del Bono E, et al. Arch Dis Child (2011). doi:10.1136/adc.2010.195917
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Original article
to n=11 562 (75.2%), school readiness to n=10 930 (71.1%) and
verbal ability to n=11 467 (74.5%).
For sample 2 (age 5), socioemotional behaviour data were
available for n=14 395, verbal ability data for n=14 764, nonverbal ability data for n=14 756 and spatial ability data for
n=14 707. Complete data for explanatory factors of interest
reduced the sample for socioemotional behaviour to n=13 603
(90.4%), verbal ability to n=13 537 (90.0%), non-verbal ability
to n=13 533 (90.0%) and spatial ability to n=13 488 (89.7%).
The distribution of explanatory variables in full sweep 2 and
3 samples compared with complete case samples was found
to be similar (see online appendix 1). Therefore, analyses are
based on the cases with complete data on relevant variables
using Stata v 11.0. The SVY command was used throughout
to take account of the clustered sample design and the unequal
probability of being sampled. Hence, all confidence intervals
and p values account for clustering and all proportions, means
and regression coefficients are weighted using sweep relevant
weights. These weights allow for non-response at all sweeps.
Multivariate regression models were used to investigate the
importance of demographic characteristics, home learning,
family routines and psychosocial environment for socioemotional difficulties (logistic regression) and cognitive ability scores (linear regression) in children according to family
income. All models adjust for gender. Socioemotional difficulties models additionally adjust for age at time of home visit,
but cognitive outcome models do not as individual scores
are age standardised. Model A adjusts for demographic characteristics; model B additionally adjusts for markers of the
home learning environment and family routines; and model
C additionally adjusts for psychosocial environment.
The percentage reduction in the income gradient before and
after full adjustment was calculated from the log odds for band
5 (poorest) versus band 1 (richest) in the socioemotional difficulties models and mean scores for band 5 versus band 1 in
the cognitive test score models. Cross model hypotheses were
assessed based on methods for comparing regression coefficients between models suggested by Clogg et al, 25 and implemented in Stata by the suest command.
To assess the policy relevance of our models, we estimated
the percentage change in the prevalence of socioemotional difficulties predicted by the fully adjusted model after randomly
reallocating (1) 50% and (2) 100% of the children from the
‘read to less than weekly’ group to the ‘read to daily’ group.
RESULTS
Markers of home learning, family routines and psychosocial environments were socially patterned, with the highest
income families more likely to have favourable profi les compared with lower income families (see online appendix 2).
Developmental outcomes were associated with home learning
activities, markers of family routines and psychosocial environment (see online appendix 3), and these associations were
independent of family income (data not shown).
There were strongly graded relationships between family
income and developmental markers (tables 1 and 2). At ages
3 and 5 years, crude prevalences show that children from
the lowest income families were approximately seven and
eight times, respectively, more likely to have socioemotional
difficulties compared with children from the highest income
families. Patterns of association between family income
and a continuous measure of socioemotional difficulties
Table 1 Odds of socioemotional difficulties data and regression coefficients for cognitive test scores at age 3 by family income
%
difficulties†
Socioemotional
Richest
Band 2
Band 3
Band 4
Poorest
Don’t know or refused
(n=11 562)
2.36
3.28
5.85
11.06
16.41
9.67
School readiness (n=10 930)
Richest
Band 2
Band 3
Band 4
Poorest
Don’t know or refused
Verbal ability (n=11 467)
Richest
Band 2
Band 3
Band 4
Poorest
Don’t know or refused
Model A
–
1.30 (0.62 to 2.71)
2.22 (1.08 to 4.57)
3.72 (1.85 to 7.50)
4.88 (2.43 to 9.79)
3.39 (1.71 to 6.72)
Model B
–
1.24 (0.59 to 2.59)
1.99 (0.96 to 4.11)
2.98 (1.48 to 6.03)
3.75 (1.87 to 7.54)
2.60 (1.31 to 5.15)
Model C
–
1.20 (0.55 to 2.65)
2.06 (0.95 to 4.50)
2.57 (1.20 to 5.50)
2.81 (1.31 to 6.03)
2.11 (1.00 to 4.43)
Mean
Model A
Model B
Model C
113.98
111.24
108.00
103.70
99.36
104.18
–
−2.39 (−3.89 to −0.88)
−5.18 (−6.83 to −3.52)
−8.13 (−9.81 to −6.45)
−11.66 (−13.24 to −10.07)
−8.12 (−9.84 to −6.41)
–
−1.91 (−3.31 to −0.51)
−4.32 (−5.88 to −2.76)
−6.46 (−8.05 to −4.86)
−9.58 (−11.12 to −8.04)
−6.40 (−8.00 to −4.79)
–
−1.84 (−3.22 to −0.46)
−4.29 (−5.80 to −2.78)
−6.01 (−7.54 to −4.47)
−8.52 (−10.03 to −7.02)
−5.97 (−7.57 to −4.37)
53.93
53.71
52.71
50.00
47.62
50.97
–
−0.10 (−1.05 to 0.86)
−0.94 (−1.84 to −0.05)
−2.89 (−3.80 to −1.98)
−4.77 (−5.72 to −3.81)
−2.05 (−3.09 to −1.01)
–
0.15 (−0.80 to 1.09)
−0.48 (−1.36 to 0.40)
−2.00 (−2.91 to −1.08)
−3.67 (−4.61 to −2.72)
−1.16 (−2.17 to −0.16)
–
0.12 (−0.80 to 1.04)
−0.55 (−1.40 to 0.30)
−1.85 (−2.74 to −0.95)
−3.19 (−4.13 to −2.25)
−0.99 (−1.99 to 0.01)
Model A adjusts for: gender, child is firstborn, languages spoken in the home, mother’s age at time of birth.
Model B additionally adjusts for: a parent has basic skills difficulties, someone reads stories to the child, visits to the library, help with the alphabet, help with numbers/
counting, learning songs, poems and rhymes, does drawing and painting, regular bedtimes, regular mealtimes.
Model C additionally adjusts for: maternal K6 score, child–parent relationship (Pianta) scale, discipline strategies, parent–child items from the HOME Inventory, mother’s
parenting competence, family rules, enforcement of rules.
†Models also adjust for child’s age.
HOME, Home Observation for Measurement of the Environment.
Kelly Y, Sacker A, Del Bono E, et al. Arch Dis Child (2011). doi:10.1136/adc.2010.195917
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Original article
Table 2
Odds of socioemotional difficulties data and regression coefficients for cognitive test scores at age 5 by family income
%
Socioemotional difficulties† (n=13 603)
Richest
Band 2
Band 3
Band 4
Poorest
Don’t know or refused
Verbal ability (n=13 537)
Richest
Band 2
Band 3
Band 4
Poorest
Don’t know or refused
Non-verbal ability (n=13 533)
Richest
Band 2
Band 3
Band 4
Poorest
Don’t know or refused
Spatial ability (n=13 488)
Richest
Band 2
Band 3
Band 4
Poorest
Don’t know or refused
2.03
4.00
6.43
11.24
15.88
11.98
Model A
Model B
–
1.84 (1.14 to 2.97)
2.72 (1.76 to 4.23)
4.40 (2.89 to 6.69)
5.82 (3.73 to 9.07)
5.21 (3.23 to 8.39)
–
1.72 (1.06 to 2.77)
2.47 (1.59 to 3.84)
3.52 (2.33 to 5.31)
4.44 (2.86 to 6.90)
3.97 (2.49 to 6.32)
Model C
–
1.49 (0.92 to 2.40)
2.00 (1.29 to 3.10)
2.53 (1.67 to 3.83)
3.03 (1.95 to 4.71)
2.78 (1.73 to 4.48)
Mean
Model A
Model B
Model C
59.85
57.66
56.13
53.09
51.17
54.03
–
−1.86 (−2.73 to −0.99)
−2.79 (−3.64 to −1.95)
−4.86 (−5.74 to −3.99)
−6.19 (−7.15 to −5.22)
−4.24 (−5.31 to −3.17)
–
−1.71 (−2.58 to −0.85)
−2.57 (−3.40 to −1.75)
−4.31 (−5.16 to −3.46)
−5.49 (−6.44 to −4.55)
−3.55 (−4.63 to −2.48)
–
−1.68 (−2.54 to −0.81)
−2.49 (−3.31 to −1.66)
−4.18 (−5.03 to −3.33)
−5.35 (−6.30 to −4.40)
−3.44 (−4.51 to −2.37)
58.44
56.60
55.62
54.54
53.63
55.89
–
−1.62 (−2.35 to −0.89)
−2.36 (−3.12 to −1.60)
−3.12 (−4.02 to −2.23)
−3.76 (−4.67 to −2.85)
−2.06 (−3.06 to −1.07)
–
−1.56 (−2.28 to −0.83)
−2.26 (−3.02 to −1.51)
−2.87 (−3.76 to −1.99)
−3.44 (−4.35 to −2.52)
−1.76 (−2.75 to −0.77)
–
−1.54 (−2.26 to −0.81)
−2.20 (−2.95 to −1.44)
−2.75 (−3.64 to −1.87)
−3.27 (−4.18 to −2.36)
−1.64 (−2.63 to −0.65)
53.58
52.39
51.36
49.39
48.26
51.32
–
−1.04 (−1.72 to −0.36)
−1.90 (−2.68 to −1.11)
−3.55 (−4.31 to −2.79)
−4.41 (−5.24 to −3.57)
−1.78 (−2.75 to −0.82)
–
−0.97 (−1.65 to −0.29)
−1.79 (−2.57 to −1.02)
−3.21 (−3.94 to −2.47)
−4.03 (−4.86 to −3.20)
−1.39 (−2.35 to −0.44)
–
−0.95 (−1.62 to −0.28)
−1.73 (−2.51 to −0.95)
−3.10 (−3.85 to −2.35)
−3.92 (−4.75 to −3.08)
−1.28 (−2.24 to −0.32)
Model A adjusts for: gender, child is firstborn, languages spoken in the home, mother’s age at time of birth.
Model B additionally adjusts for: a parent has basic skills difficulties, someone reads stories to the child, help with reading, help with writing, help with numbers, telling
stories to the child, visits to the library, musical activities, draws, paints or makes things, regular bedtimes, regular mealtimes.
Model C additionally adjusts for: maternal K6 score, discipline strategies, mother’s parenting competence, whether the mother feels close to the child.
†Models also adjust for child’s age.
were similar to those using the dichotomised score (data
not shown). Multivariate models showed that the likelihood of socioemotional difficulties in income bands 2–5
were reduced on adjustment for demographic, home learning, family routines and psychosocial environment. After
statistical adjustment for demographic, home learning and
family routines, the likelihood of socioemotional difficulties
remained at ages 3 and 5 (model B ORs 3.75 and 4.44, respectively). At ages 3 and 5 years, there was an approximate 50%
overall reduction (model C; age 3 OR 2.81, age 5 OR 3.03)
in the income gradient in fully adjusted models (Wald test,
p<0.0001) (tables 1 and 2).
Children from the highest income families had substantially
higher cognitive test scores compared with their counterparts
from the lowest income band. For verbal ability, which was
the only cognitive test with data available at both age points,
the income gap widened between 3 and 5 years of age (crude
difference, Wald test, p=0.04; fully adjusted difference, Wald
test, p=0.01). On adjustment for demographic, home learning
and family routines, differences across income bands in cognitive test scores remained (model B verbal ability coefficients
age 3 −3.67, and age 5 −5.49) Adjustment for demographic,
home learning, family routines and psychosocial environmental factors (model C) reduced the size of the income gradient
in cognitive test scores (Wald test, p<0.0001). Similar patterns
4 of 6
were seen for school readiness at age 3 and non-verbal and
spatial ability test scores at age 5 (tables 1 and 2). The reduction in income gradient for verbal ability was greater for age 3
test scores (49%) compared with those at age 5 (38%) (tables 1
and 2, model C).
For our policy relevant analysis when (1) 50% and (2) 100%
of the sample were randomly reallocated from the ‘read to less
than weekly’ group to the ‘read to daily’ group, holding all else
constant, the estimated proportion of children with socioemotional difficulties dropped by 10% and 20%, respectively.
DISCUSSION
There are strongly graded relationships between family income
and markers of child development at ages 3 and 5 years. And
for verbal ability, the only cognitive test for which we had data
available at both age points, the income gap appeared to widen
with increasing age. On statistical adjustment for demographic,
home learning, family routines and psychosocial environmental factors, there was a 50% reduction in the income gradient
for socioemotional difficulties, and between 27% and 49%
reductions in cognitive test score gaps. For verbal ability we
found that statistical models ‘explained’ more of the income
gradient at 3 years compared with 5 years, perhaps reflecting
shifts in the amount of time children spend in the home, that
is, with the transition to school environments.
Kelly Y, Sacker A, Del Bono E, et al. Arch Dis Child (2011). doi:10.1136/adc.2010.195917
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Our fi ndings are supported by other studies that have
shown the importance of parenting activities across income
groups.2 3 5 26 We found that for socioemotional difficulties,
statistical adjustment for psychosocial environmental markers
had additional explanatory power over and above adjustment
for markers of home learning and family routines. This is perhaps not surprising as indicators of home learning and family
routines likely tap the transactional element between child
and environment inherent with, for example reading a story
together, and having routines around bed and meal times,8 27
and it has been reported that such activities along with favourable psychosocial environments are most beneficial in families
with secure bonds between parent and child. 26 In contrast, for
cognitive test scores, statistical adjustment for psychosocial
environmental factors had relatively conservative effects on
estimated relationships, particularly when children were age 5.
This might be because cognitive development is less sensitive
to psychosocial aspects of the environment such as discipline
strategies. Or it may be because we had data on fewer markers of the psychosocial environment at age 5. Alternatively, it
might be because markers of home learning, family routines
and psychosocial environment tap into the same portion of
the family milieu that fosters cognitive development.
Our fi ndings from a large nationally representative sample
of 3- and 5-year-old children are consistent with those of other
studies. 3 5 A strength of this study was that we examined
data on objective measures, collected by trained observers,
of cognitive ability i n children. On the other hand, data on
socioemotional difficulties were only available from a parent
report and it has been shown elsewhere that multi-informant
measures are more reliable for clinical identification of problem behaviours. 28 However, the SDQ is a validated tool, and
importantly we determined age-appropriate norms in the current study by using the large MCS cohort data15 16 rather than
norms from a different age range. The cut-points use the same
>90th percentile cut-off criterion for clinical relevance as used
in the original norms.14 In common with a previous US study, 3
our statistical models left a substantial portion of the income
gap unexplained. But socioeconomic and family environment
variables used in models lack precision as they are surrogates
for a myriad of ill-defi ned socioenvironmental factors and thus
their importance is underestimated. Implicit in the work of
some researchers4 is that there is an underlying genetic explanation for income inequalities in ECD. However, genetic factors that influence socioemotional and cognitive development
have not been well characterised, nor have their frequencies
across socioeconomic groups been established. 29
The malleability of ECD30 31 has proven fruitful for policy
and several intervention programmes aimed at improving
developmental outcomes in the under-5s have demonstrated
benefits in aspects of ECD3 10 11 32 and have been shown to be
cost-beneficial in the long term. 32 These interventions along
with welfare reforms typically focus on the parent, or the
child, or both parent and child, and it appears that a range of
approaches are useful. 3 33 There is room for developing policy
aimed at closing the inequality gap in child development, and
to do this programmes need to be more effective in improving
developmental outcomes in disadvantaged children compared
with their advantaged peers. For example, in the current context, a simple counterfactual argument suggests that if half or
all of the 5-year-old children who were read to less than daily
were instead read to on a daily basis there would be corresponding 10% and 20% reductions in the proportion of 5 year
olds with socioemotional difficulties.
Kelly Y, Sacker A, Del Bono E, et al. Arch Dis Child (2011). doi:10.1136/adc.2010.195917
Our study used cross-sectional data, and future work
should consider a longitudinal view of the impact of relationships between income inequalities, home learning and psychosocial environments on ECD. Longitudinal analyses will
also help to reveal the direction of causality in the complex
sets of processes involved in social inequalities in ECD.
Acknowledgements The authors would like to thank the Millennium Cohort
Study families for their time and cooperation, as well as the Millennium Cohort
Study team at the Institute of Education. The Millennium Cohort Study is funded by
ESRC grants to Professor Heather Joshi (study director).
Funding This work was supported by a grant from the Economic and Social
Research Council RES-596-28-0001. The funders had no role in the interpretation
of these data or in the writing of this paper.
Competing interests None.
Contributors YK designed the study, analysed the data and drafted the
manuscript. AS provided analytical support and commented on drafts of the paper.
MF, EDB and MM provided input and comments on the design of the study and
comments on drafts of the manuscript.
Provenance and peer review Not commissioned; externally peer reviewed.
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Kelly Y, Sacker A, Del Bono E, et al. Arch Dis Child (2011). doi:10.1136/adc.2010.195917
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What role for the home learning
environment and parenting in reducing the
socioeconomic gradient in child
development? Findings from the Millennium
Cohort Study
Y Kelly, A Sacker, E Del Bono, et al.
Arch Dis Child published online June 12, 2011
doi: 10.1136/adc.2010.195917
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