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Economics and Human Biology 11 (2013) 42–55

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he effect of low birth weight on height, weight and behavioralutcomes in the medium-run

abanita Datta Gupta a,*, Mette Deding b, Mette Lausten b

arhus University, Denmark

he Danish National Centre for Social Research, Denmark

Introduction

Low birth weight is a problem that developing and evenveloped societies must contend with. A large number ofdies have documented long run effects of low birth

eight (LBW),1 for example heightened risks of diseases inulthood (Barker, 1999; Eriksson et al., 2001), worse self-ported health at ages 23 and 33 (Currie and Hyson,99), significantly lower rates of high-school completiononley and Bennett, 2000), effects on health and IQ whichnslate into long run labor market outcomes such asucational attainment and earnings (Behrman andsenzweig, 2004; Currie and Moretti, 2007; Black et al.,07) and even a small effect on the birth weight of the

next generation (Royer, 2009). On the other hand, due toadvances in neonatal intensive care technology in indus-trialized countries, risks of higher mortality or poorerhealth in the first years of a child’s life due to adverse birthoutcomes have been greatly diminished (Conley et al.,2006; Voigt et al., 2004). For instance, exploiting bothwithin-twin pair variation in birth weight and controllingfor maternal heterogeneity Almond et al. (2005) foundonly small effects of LBW on hospital costs, health afterbirth and infant mortality. To date, however, there is verylittle knowledge about the possible medium run effects ofLBW, where medium run is interpreted as the time spanbetween infancy/toddlers and adults. This is because untilrecently, few child longitudinal surveys existed whichwere able to track children’s cognitive and non-cognitivedevelopment throughout childhood.

We accessed a large-scale representative survey fromDenmark of approximately 6000 children born in 1995and followed over time until 2007. Children’s outcomeswere recorded at different ages – 6 months, 3, 7 and

R T I C L E I N F O

icle history:

ceived 12 January 2010

ceived in revised form 6 June 2011

cepted 10 June 2011

ailable online 16 June 2011

classification:

ywords:

w birth weight

dium run effects

ight

eight and behavioral outcomes

ngitudinal child–mother survey

nmark

A B S T R A C T

A number of studies have documented negative long term effects of low birth weight. Yet,

not much is known about the dynamics of the process leading to adverse health and

educational outcomes in the long run. While previous studies focusing mainly on LBW

effects on physical growth and cognitive outcomes have found effects of the same size at

both school age and young adulthood, others have found a diminishing negative effect

over time. The purpose of this paper was to bring new evidence to this issue by analyzing

the medium run effects of low birth weight on child behavioral outcomes as well as

physical growth at ages 6 months, 3, 7 and 11 years using data from the Danish

Longitudinal Survey of Children. Observing the same children at different points in time

enabled us to chart the evolution of anthropometric and behavioral deficits among

children born with low birth weight and helped understanding the nature and timing of

interventions.

� 2011 Elsevier B.V. All rights reserved.

Corresponding author.

E-mail addresses: [email protected] (N. Datta Gupta), [email protected]

. Deding), [email protected] (M. Lausten).

The standard definition of LBW is birth weight <2500 g.

Contents lists available at ScienceDirect

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jou r nal h o mep age: h t t p: / /w ww.els evier . co m/lo c ate /eh b

70-677X/$ – see front matter � 2011 Elsevier B.V. All rights reserved.

i:10.1016/j.ehb.2011.06.002

http://dx.doi.org/10.1016/j.ehb.2011.06.002

mailto:[email protected]



http://www.sciencedirect.com/science/journal/1570677X

http://dx.doi.org/10.1016/j.ehb.2011.06.002

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N. Datta Gupta et al. / Economics and Human Biology 11 (2013) 42–55 43

1 years – which enabled an understanding of thevolution of anthropometric and behavioral deficitsmong children born with low birth weight and helpedo inform the nature and timing of interventions duringhis critical period of human capital formation (Carneirond Heckman, 2003; Doyle et al., 2009).

The objective was to analyze the effects of LBW on childutcomes in the medium run, including the developmentver time. Past research has claimed that the adverseonsequences of LBW of infants who were inappropriatelymall for age due to suboptimal uterine conditions may beffset by a period of accelerated growth post-birth, so thatBW infants may eventually attain their target growthajectories. Alternatively, the ‘fetal programming’ hypoth-

sis (Barker, 2002) argues that uterine under-nourishmentan permanently change the body’s structure, physiologynd metabolism, and thereby can substantially increasee risk of chronic diseases in adulthood, such as

ardiovascular and metabolic diseases (Ben-Shlomo,001). The evolution over time has been previouslyxamined with respect to physical growth and perfor-ance on cognitive tests and educational outcomes evenough past research has linked the manifestation of

ehavioral disorders among very low birth weight children their neonatal experiences and neurodevelopment

tatus (see, e.g., Astbury et al., 1985). Thus, extendinge previous literature, we explored the development over

me on physical growth and behavioral development aseasured on the psychosocial scale known as the Strength

nd Difficulties Questionnaire (SDQ) and brought newvidence to the analysis of medium run effects of LBW. As aeries of recent papers have shown, non-cognitiveevelopment is a highly necessary pre-requisite forognitive development and, furthermore, has been linked

future labor market success independent of cognitivechievement (Heckman et al., 2006; Cunha and Heckman,008; Segal, 2005). More recently, work by Currie andtabile have shown the long run negative test score andbor market outcomes of an ADHD diagnosis and ourndings have bearing for this discussion as well (Curriend Stabile, 2009).

The rest of the paper is organized as follows: Section 2resents data and the various outcome measures. Section 3iscusses the methodological framework and results areund in Section 4. Finally, Section 5 discusses the findings

nd concludes the paper.

. Data

The data we used in the analysis were drawn from theanish Longitudinal Survey of Children (DALSC). This

urvey followed children born between September 15 andctober 31 in the 1995 cohort and is representative ofhildren born in Denmark in that period. The survey dataas been merged with register data from Statisticsenmark from 1995 to 2005. The aim of the DALSC studyas to track children’s physical and mental development

long with supplying basic information on other aspects ofhildren’s development, their family background and theiraily family life. Typically, it was the mother who

questionnaire, a special health questionnaire was admin-istered in 2003 collecting objectively measured healthinformation from the first 7 years of the children’s lives.The register data link-up gave us information about familystructure and about the educational level and employmentstatus of the parents.

A total of 6011 children were randomly drawn for theDALSC in 1995. The first wave of the DALSC was carried outin 1996 when the children were 6 months old and includedinterviews with 5428 mothers. In subsequent waves in1999, 2003 and 2007 the numbers were 5288, 4971 and4802. The response rate in 2007 was 80% of the originalsample. Families with low socioeconomic status (e.g.,single mothers) have had lower response rates than otherfamily types. This means that the prevalence of children inless-privileged circumstances is lower than in the popula-tion at large, a condition to be kept in mind wheninterpreting the results.

Children’s birth weight was obtained from the registers,while the outcome measures came from the four surveywaves when the children’s ages were 6 months, 3 years, 7years and 11 years, respectively. The explanatory variableswere defined on the basis of both the survey and theregister data. Children with missing information on eitherthe outcome variables or the explanatory variables weredropped from the sample. So were the (few) children whoare developmentally retarded. These deletions reduced thesample to 4783 children: 2297 females and 2486 males.

2.1. Birth weight

The primary variable of interest was the birth weight ofthe children. To compare the children in DALSC to allchildren born in Denmark, we present average birth weightfor the entire birth cohort, all children in the survey as wellas the LBW children in the survey (Table 1). LBW wasdefined as a dummy variable which took the value 1 if birthweight obtained from medical registers was recorded asbeing < 2500 g and 0 otherwise. However, we alsoexplored the shape of the functional relationship amongthe LBW by, among other things, subdividing the group ofLBW into separate weight classes.2 The mean birth weightin the DALSC did not differ from the cohort mean for eithermales or females (Table 1). The share of LBW was slightlylower in the DALSC compared to the cohort mean possiblydue to the lower response rates of mothers of low socio-economic status. Although the absolute numbers of lowbirth weight children were not large in the survey (117females, 103 males), the richness of the data, in particular

2 The standard cutoff has been criticized for not taking into account

racial/ethnic differences in maternal height, weight, etc. (Rooth, 1980).

Also, while most studies use the threshold measure, Barker (1999) found a

linear relationship between birth weight and adult risk of diseases and

argued for exploiting the full distribution. Because of these objections, we

applied several other definitions of birth weight in the sensitivity

analyses including trying different cutoffs, applying a continuous

measure of birth weight, using alternative definitions based on fetal

growth and gestation age, and finally subdividing low birth weight into

ery low birth weight (<1500 g) and moderately low birth weight (1500–

499 g) (see, e.g., Tables 8–11).
ompleted the questionnaire. In addition to the standardv
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N. Datta Gupta et al. / Economics and Human Biology 11 (2013) 42–5544

e behavioral scale outcome and its sub-domains, enabled exploration into the mechanisms that produce negative

ng run educational and labor market outcomes of lowrth weight, i.e. physical barriers or behavioral difficultiesch as increased hyperactivity/inattention, peer relation-ip problems or conduct disorders, which in turn haveological antecedents.

. Outcome measures

Child outcomes included growth as measured bythropometric measures (z-scores for weight and height)primary measures of the nutritional status of childrenaterlow et al., 1977) – and the psychosocial scale SDQ.

e estimated separate models for weight and height, and the main specification, we also estimated the effect ofW on weight for height. Ideally, we would have liked to

disease conditions, but as argued above, the anthropomet-ric measures (especially height) reflect the effect of pastdiseases, and moreover, our sample was not large enoughfor the purpose of identifying meaningful effects whendisaggregating by disease conditions.

Weight and height were defined as z-scores, i.e. themeasures are standardized by the median and standarddeviation for females and males, respectively (Table 2).3

Note, that we applied the sample median and standarddeviation in the standardization because, as Table 1showed, the mean birth weight in the DALSC did notdiffer from the population mean for either males orfemales. For the first two waves (6 months and 3 years),

ble 2

ans of outcomes, 1996, 1999, 2003, and 2007 (standard deviations in parentheses).

Females Males

All LBW All LBW

996

eight (z-score) �0.07 (1.00) �1.38 (1.12)*** 0.02 (1.00) �1.56 (1.13)***

eight (z-score) 0.01 (1.00) �1.29 (1.11)*** �0.08 (1.00) �1.61 (1.10)***

eight for height 103.2 (11.7) 90.7 (14.6)*** 109.7 (12.1) 93.9 (13.5)***

999

eight (z-score) 0.14 (1.00) �0.34 (1.06)*** 0.01 (1.00) �0.84 (0.82)***

eight (z-score) 0.12 (1.00) �0.32 (0.96)*** �0.12 (1.00) �0.98 (1.09)***

eight for height 153.7 (14.4) 146.8 (16.0)*** 158.1 (13.8) 148.5 (11.5)***

DQ (pseudo) 9.32 (5.11) 9.95 (5.85) 10.33 (5.58) 10.58 (6.12)

003

eight (z-score) 0.03 (1.00) �0.23 (1.10)*** 0.22 (1.00) �0.33 (0.86)***

eight (z-score) 0.02 (1.00) �0.24 (1.09)*** 0.01 (1.00) �0.58 (1.11)***

eight for height 198.8 (28.1) 191.7 (31.7)** 203.8 (28.6) 189.0 (24.0)***

DQ 6.04 (4.68) 7.03 (5.72)* 6.80 (5.10) 7.51 (5.40)

Pro-social behavior 9.06 (1.26) 9.04 (1.46) 8.45 (1.62) 8.42 (1.80)

Peer relationship problems 0.64 (1.13) 0.71 (1.32) 0.81 (1.34) 0.77 (1.23)

Hyperactivity/inattention 2.19 (2.26) 2.54 (2.59) 2.83 (2.61) 3.35 (2.92)*

Emotional behavior symptoms 1.92 (1.96) 2.35 (2.42)* 1.80 (1.91) 2.03 (2.14)

Conduct disorder 1.29 (1.41) 1.44 (1.44) 1.37 (1.48) 1.37 (1.34)

007

eight (z-score) 0.10 (1.00) �0.23 (0.98)*** 0.13 (1.00) �0.22 (0.89)***

eight (z-score) �0.07 (1.00) �0.35 (1.06)*** 0.01 (1.00) �0.51 (1.00)***

eight for height 269.0 (45.5) 254.9 (44.2)*** 271.3 (45.7) 258.0 (40.3)***

DQ 5.57 (4.68) 6.87 (6.03)** 6.36 (5.03) 7.33 (5.84)

Pro-social behavior 9.27 (1.11) 9.05 (1.35) 8.83 (1.32) 9.02 (1.25)

Peer relationship problems 0.80 (1.33) 1.09 (1.68)* 0.95 (1.47) 1.04 (1.59)

Hyperactivity/inattention 1.83 (2.05) 2.13 (2.42) 2.67 (2.43) 3.38 (2.72)***

Emotional behavior symptoms 2.07 (2.00) 2.41 (2.43) 1.82 (1.92) 1.88 (2.05)

Conduct disorder 0.87 (1.14) 1.23 (1.46)*** 0.92 (1.19) 1.03 (1.19)

Significant difference between all children and LBW children at 10%.* Significant difference between all children and LBW children at 5%.** Significant difference between all children and LBW children at 1%.

ble 1

th weight of children born in 1995 in Denmark.

Females Males

All DALSCa LBW DALSCb All DALSC LBW DALSC

verage weight (g) (std dev) 3420 (567) 3461 (578) 2002 (425) 3550 (603) 3583 (601) 2012 (423)

hare of low weight children 5.42 5.09 100 4.20 4.14 100

umber of children 33617 2297 117 35591 2486 103

Danish Longitudinal Survey of Children.

Low birth weight children in the Danish Longitudinal Survey of Children.

3 The definition of the z-score for weight is: (weight � median weight

the group)/standard deviation for the group, and likewise for the z-

re for height.
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eight and height were obtained from a special healthuestionnaire with information obtained from visits made

the medical practitioner. These measurements wereus carried out by the doctor and should be highly

eliable. For the last two waves (7 years and 11 years),eight and height were reported by the mothers implyingat measurement error is a potential problem. On the

ther hand, as the children were all born within 6 weeks ofach other and as interviews with mothers all took placeithin a short time period of each other, the timing issue

egarding weight and height measurements was notelevant.

The SDQ-scale is a validated psychosocial measureased on the Strength and Difficulties Questionnaire

oodman, 1997, 1999; Goodman and Scott, 1999; Obelt al., 2003). The SDQ-scale ranges from 0 to 40, where aigher score indicates more difficulties in four of fiveubscales: emotional symptoms, misconduct symptoms,yperactivity, and peer problems. In addition, the fifthubscale measures pro-social behavior (such as beingonsiderate and kind to other people).4 The five items inach subscale are scored 0–2, giving scores ranging from 0

10 for each subscale. This makes the SDQ-scale sum to atal difficulties score ranging from 0 to 40 and a pro-social

core ranging from 0 to 10.5 Although the Strengths andifficulties Questionnaire is a relatively new instrument, itas already seen widespread use for psychiatric screeningf children and adolescents (Hawes and Dadds, 2004;lasen et al., 2000; Koskelainen et al., 2000; Mathai et al.,002; Woerner et al., 2004) and is used by most childohort studies (Cuffe et al., 2005; Wiles et al., 2006;orwood et al., 2008; Kelly et al., 2001, 2009). Psychol-gists use the SDQ-scale for categorizing children in termsf fewer or more difficulties than what is consideredormal, given the child’s age. For our analyses, however,e applied the continuous SDQ-scale. The parental version

f the SDQ-questions were included in the 2003- and the007-questionnaire, but not in the 1999-questionnaire.owever, in a previous paper, Andersen et al. (2010)

alculated a pseudo-SDQ score for the 3 year-olds based onimilar questions about difficulties in the 1999-question-aire. The two scales are not directly comparable, but inoth cases a higher score indicates more psychosocialifficulties. LBW children scored higher than average

eaning worse behavior) on the pseudo-SDQ scale in999 and on the SDQ scale in 2003 and 2007 in allimensions except pro-social behavior where they areated lower, again indicating worse behavior. The signifi-ance of the differences in means between all children andBW children was tested and the results are reported inable 2. The statistically strongest results were that LBWhildren had significantly lower weight and height z-scoresnd slightly lower weight for height (measured in units of/cm) in each of the waves in our data, while LBW femalesad significantly more conduct disorders and LBW males

significantly greater hyperactivity/inattention than allchildren at age 11.

2.3. Explanatory variables

The data included a wealth of variables. Some questionsrecurred in all waves of the survey, while others changedover time. The explanatory variables used in this paperwere grouped into four categories: (1) birth variables, (2)health of the mother, as a proxy for the intrauterineenvironment, (3) family structure, and (4) socioeconomicfactors.

The ‘‘birth’’ variables included LBW, the average birth

weight for siblings, a dummy for having no siblings, and adummy for missing birth weight for siblings. These variableswere taken from a special Fertility database at StatisticsDenmark 1980–2001 which includes the weight at birthregistered by medical authorities. Since siblings can belinked via the registers to their biological mother, we haveaccess not only to the individual child’s birth weight butalso that of his/her siblings from these registers. Theaverage of siblings’ birth weight in (g) was included tocapture an unobserved effect common to all children in thefamily, for example genetics. Ideally, we would have usedsibling comparisons to take into account the possibility of abiased effect of LBW if shared family characteristics arecorrelated with LBW. This was not possible due to datarestrictions and, thus, we used the second-best solution ofincluding sibling birth weight as a control in an attempt tocontrol for the effects of unobserved maternal or house-hold characteristics correlated with LBW that affect allsiblings symmetrically.6 For singletons, this was set tomissing, and the dummy variable for missing birth weightof siblings was included as well.

Information about ‘‘health’’ was taken from all fourwaves of the survey. For children, we observed thepresence of a developmental or neurosensory deficit, definedas reduced hearing, sight or complete deafness orblindness, as well as severe speech defects or beingphysically handicapped; and poor child health, definedbroadly as a chronic illness diagnosed by a medicaldoctor (e.g., diabetes, epilepsy or asthma). Having adevelopmental or neurosensory deficit was time-invariant,whereas the dummy variable for poor child health changedbetween waves. For all waves of the survey, we accessedself reported information about whether the mother hadbeen diagnosed with mental illness since the last interviewand also whether the mother had suffered from poorhealth in terms of having been hospitalized since the lastinterview.

The ‘‘family structure variables’’ existed for all fourwaves in the survey and included whether the child is the

4 See www.sdqinfo.org for a thorough description.5 Note, that for SDQ as well as for difficulties subscales, a higher score

6 While we had access to siblings’ birth weight, unfortunately we

lacked information on outcome variables for siblings to enable sibling-

difference estimation. Moreover, information on only 69 twin pairs was

present in the survey, including normal birth weight and low birth weight

children.7 We were not able to identify biological fathers other than as the man

plies more difficulties, whereas for the pro-social subscale a higher

ore implies better pro-social behavior.

living with the child at the time of the first survey (when the child is about

6 months old).

http://www.sdqinfo.org/

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stborn and number of siblings. By definition, the childrenher live with their mother and father or with a single

other in 1996—i.e. a two parent family or single mother.7

the children grow older, more parents divorce and inme cases the mother remarries, so that the child livesith the mother and stepfather. Danish municipalities aretegorized according to level of urbanization. Thisriable, originating from the registers, grouped geograph-l locations into three groups: Copenhagen (the metro-litan area), urban areas and rural areas.8

The socioeconomic variables were all taken from thegister data. Log household income was defined as (log)sposable income of all household members. In addition,mily level of employment was defined as a 0, 1, 2 variable,rresponding to whether neither the mother nor thether, either the mother or the father, or both, have been

ployed most of the year. Education was measured as theghest educational level attained and was grouped in sixtegories: no education, high school, vocational education,ort post-secondary education, medium post-secondary

ucation, and long post-secondary education. Thus family

level of education was defined as the sum of the mother’sand the father’s educational level, making it a categoricalvariable ranging from 0 to 12, where 0 indicated noeducation at all in the family and 12 indicated both parentshaving long post-secondary education. Finally, dummiesfor missing mother’s or father’s education were includedunder socioeconomic factors.9

2.4. Means of variables

The birth weight for siblings was around 3500 g onaverage but approximately 2800 g for LBW children (Table3). 40% of the children were firstborn. This number washigher for females and males in the LBW groups probablyreflecting the fact that children of higher birth order tendto be heavier. LBW children, not unexpectedly, had a

ble 4

ans of time-varying explanatory variables, 1996 (standard deviations in parentheses).

Females Males

All LBW All LBW

ealth variables

ummy for poor child health (1996) 0.03 (0.16) 0.08 (0.27) 0.04 (0.19) 0.10 (0.30)

other diagnosed with mental illness (1996) 0.02 (0.14) 0.06 (0.24) 0.02 (0.15) 0.01 (0.10)

amily structure

umber of siblings (1996) 0.83 (0.88) 1.00 (0.95) 0.81 (0.86) 1.00 (0.93)

wo parent family (1996) 0.97 (0.18) 0.93 (0.25) 0.96 (0.20) 0.95 (0.22)

ingle mother (1996) 0.03 (0.18) 0.07 (0.25) 0.04 (0.20) 0.05 (0.22)

openhagen (1996) 0.29 (0.45) 0.37 (0.48) 0.31 (0.46) 0.35 (0.48)

rban area (1996) 0.35 (0.48) 0.34 (0.48) 0.35 (0.48) 0.32 (0.47)

ural area (1996) 0.36 (0.48) 0.29 (0.46) 0.34 (0.47) 0.33 (0.47)

amily income, 1000 Dkr. (1996)a 240.11 (76.08) 223.71 (77.43) 237.82 (73.85) 227.22 (59.63)

amily employment, 0–2 (1996) 1.65 (0.57) 1.54 (0.64) 1.64 (0.58) 1.68 (0.56)

amily level of education, 0–12 (1996) 5.44 (2.04) 4.95 (1.91) 5.40 (2.02) 5.10 (1.84)

other’s education unknown (1996) 0.00 (0.07) 0.00 (0.00) 0.00 (0.06) 0.00 (0.00)

ather’s education unknown (1996) 0.01 (0.11) 0.02 (0.13) 0.02 (0.13) 0.04 (0.19)

The conversion rate between US$ and Dkr. is app. 5.5 Dkr for 1 US$ (January 2011).

ble 3

ans of time-invariant explanatory variables (standard deviations in parentheses).

Females Males

All LBW All LBW

verage birth weight for siblings (g)a 3521 (561) 2826 (669) 3490 (551) 2801 (643)

ummy for no siblings 0.09 (0.29) 0.09 (0.28) 0.11 (0.31) 0.15 (0.35)

issing birth weight for siblings 0.01 (0.10) 0.03 (0.16) 0.01 (0.10) 0.01 (0.10)

ummy for being firstborn 0.40 (0.49) 0.49 (0.50) 0.41 (0.49) 0.49 (0.50)

ummy for developmental or neurosensory deficit 0.05 (0.23) 0.12 (0.33) 0.07 (0.25) 0.12 (0.32)

other’s age at birth (years) 29.32 (4.63) 29.35 (5.73) 29.46 (4.50) 30.30 (4.92)

ather’s age at birth (years) 30.59 (8.17) 29.46 (10.86) 30.36 (8.77) 30.33 (9.36)

Summary for all siblings, 1980–2001, excluding zeros for singletons.

This variable was defined by Statistics Denmark and divides all

nicipalities into the metropolitan area, other municipalities with a

her degree of urbanization (largest town has at least 10,000

9 For the 1996 and 1999 waves only, we had information on whether

the mother smoked. However, smoking turned out not to be strongly

correlated with the incidence of low birth weight in the sample, and

therefore we decided not to include it in the regression. Furthermore,

there was also information in the survey on whether the mother had

breastfed the child in question. Again, the correlation was low between

this variable and low birth weight. The main results did not change when

adding these behavioral factors to the analysis (available on request).10
abitants) and other municipalities with a lower degree of
banization.

Means from the 1999, 2003 and 2007 waves are available from

authors upon request.

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igher incidence of developmental or neurosensoryeficits.

In terms of the time-varying explanatory variables, weresent means from the first wave in 1996 in Table 4.10

hese variables remain fairly stable over time, although theumber of siblings increased over time, while the fraction of

o parent families tended to decline and the share of singleothers increased. More mothers were coded as being

iagnosed with mental illness over time. Poor child healthecreased for the LBW children going over time. Finally,mily income (measured in fixed 1996-prices) increased.

. Results

Ordinary least squares (OLS) regression of each of theutcome measures, separately, on birth weight controlling

addition for birth variables, health variables, familytructure and family socioeconomic variables was carriedut. A condensed version of the results is shown in Table 5,here only the coefficients to the dummy for low birtheight were included.11 Separate estimations were

enerated for females and males. Thus, each cell in thisble reports the coefficient to LBW for each child outcome

egression.12

z-Scores for weight and height were the outcomes thatere affected the most by low birth weight (<2500 g).

ompared to children with a birth weight higher than500 g, females and males with low birth weight had a z-core for weight (height) in 1996 of around 1.3 (1.2)tandard deviations lower than the mean for females and 1.5

(1.5) standard deviations lower than mean for males. Theseeffects diminished over time. For females the weight(height) disadvantage reduced to 0.2 (0.2) standard devia-tions below the mean and for males to 0.6 (0.6) standarddeviations below the mean. Thus, females made up about 5/6ths of the disadvantage while males regained more thantwo thirds of the deficit. Between 2003 and 2007, LBW malescontinued to catch up to their NBW (normal birth weight)counterparts especially in terms of weight, whereas forfemales there was a slight increase in the weight disadvan-tage and no change in the height z-score (although thechanges between 2003 and 2007 were not significant).Weight for height (measured in g/cm) effects of LBW werealso negative, as expected, and U-shaped with age. Again,LBW males showed a bigger deficit.

Thus, the biggest changes in weight and height tookplace between 1996 and 1999. The gender difference wasalso evident in that the deficit for males in general waslarger than the deficit for females—all weight and heightcoefficients were statistically different between males andfemales except for weight in 1996 and height in 2007.Weight for height coefficients were in general notstatistically different by gender except for 2003, whereLBW males had a deficit of 16 g/cm and LBW females adeficit of 6 g/cm. This evidence is consistent with previousfindings of a greater vulnerability of male children topregnancy and birth complications and differences ingrowth trajectories by gender (Johnson and Breslau, 2000;Hack et al., 2003).

There was no effect from low birth weight on thepsychosocial measure, SDQ, in 1999 or in 2003. There was apositive and significant effect in 2007 for the males, i.e.males seemed to have more psychosocial difficulties thanaverage at the age of 11 if their birth weight had beenlower than 2500 g. On the other hand, there was nosignificant effect for the females at age 11. When

able 5

ffect of low birth weight (dummy for birth weight < 2500 g) on child outcomes.

1996 coef. 1999 coef. 2003 coef. 2007 coef.

Females child outcome

Weight (z-score) �1.291*** �0.426*** �0.239** �0.313***

Height (z-score) �1.224*** �0.388*** �0.199** �0.196*

Weight for height �12.532*** �6.202*** �6.401*** �14.006***

SDQa 0.550 0.617 0.701

Pro-social behavior 0.025 �0.180

Peer relationship problems �0.030 0.134

Hyperactivity/inattention 0.215 0.092

Emotional behavior symptoms 0.333* 0.198

Conduct disorder 0.099 0.277**

Males child outcome

Weight (z-score) �1.534*** �0.871*** �0.603*** �0.394***

Height (z-score) �1.473*** �0.929*** �0.626*** �0.523***

Weight for height �15.281*** �9.559*** �15.959*** �15.370***

SDQ 0.094 0.640 0.903*

Pro-social behavior �0.078 0.176


Hyperactivity/inattention 0.541** 0.755***

Emotional behavior symptoms 0.179 �0.012

Conduct disorder 0.020 0.114a Note that in 1999, the outcome is pseudo-SDQ.* Significant at 10%.** Significant at 5%.*** Significant at 1%.

1 Estimates on the covariates are available from authors upon request.2 In a previous version of the paper, the sets of mentioned right hand-

de variables were entered in succession, but this did not appear to affect

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saggregating SDQ into its sub-domains, we found thathile LBW females showed significantly more emotionalhavior symptoms at age 7; by age 11 this changed andW females began to display significantly more conductsorders. In contrast, LBW males showed significantperactivity/inattention at age 7 as well as by age 11,

hich may be the explanation for males’ greater learningsabilities (Johnson and Breslau, 2000). At age 11, malesowed significantly more hyperactivity/inattention pro-ems than females. However, we did not find manynificant impacts of LBW on the SDQ and its sub scores.

so, we found no significant impacts of LBW on eitherosocial behavior or peer relationships.In Table 5, we suppressed the control variables. Results

owing the estimates on the control variables are availablem the authors.13 These results showed that a develop-

ental or neurosensory deficit and poor child health werensistently associated with negative outcomes, be theyalth or behavioral. Mothers’ health through mental illness

hospitalization affected only SDQ. Males were onlyfected by mothers’ mental illness, whereas female out-mes were associated with both maternal mental illnessd maternal hospitalization. The birth weight of siblingsly affected the weight and height outcomes. The highere average birth weight of siblings, the higher was the z-ore for both weight and height for both males and females.

Family structure variables also affected child outcomes.nerally, the larger the family size, the worse thetcomes. Males tended to be more affected by birth orderan females. Being first born increased their height andeight and at the same time also produced better behavior

terms of SDQ and its domains, except for pro-socialhavior. First born females, on the other hand, displayedixed behavioral outcomes. The most striking result in thisea was that of maternal age at birth. The higher theother’s age at birth, the better were child behavioraltcomes such as the overall SDQ score, hyperactivity andotional behavior symptoms for males, and all of these

us conduct problems for females. Maternal age also had asitive and significant effect on child height. The observed

mily structure of mother and step-father tended tocompany negative behavioral outcomes, particularly forales. Both males and females in Copenhagen (theetropolitan area) seemed to have more psychosocialfficulties than males and females in other areas.

The socioeconomic variables did not affect z-scores foreight or height as much as they affected the SDQ. TheQ was significantly lower the higher was the familyucation level. This was true for both males and females.

addition, for males, there were strong positiveproving) effects of household income and familyployment on overall behavior and its sub-domains.The results concerning the control variables underscore

e importance of socioeconomic factors on children’salth and behavioral outcomes. Could parental socioeco-mic background mitigate the impact of LBW on childtcomes? For example, more educated families have

better jobs and higher income which they can use to investin sickly children’s health. Or it could be that educatedparents have greater health knowledge and are able tomake more efficient health investments which improvethe health of LBW children? Or even that educated familieshave healthier habits and different preferences fordiscounting and risk-aversion which are health-preserving(Case et al., 2002; Cutler and Lleras-Muney, 2008).14 Thesetheories would indicate that the impact of LBW on childhealth in particular, would be lower the greater the familylevel of education. To test this hypothesis in our setting,LBW effects were interacted with family level of education(available from authors upon request). The results showedthat for females in particular, there was some evidence ofan attenuating effect of family education of LBW effects onSDQ, hyperactivity and conduct problems, while for males,hardly any significant interaction effects were seen, whichmay indicate a greater biological vulnerability of malesfrom the outset. A similar finding that an advantaged socialenvironment protects against the development of behav-ioral problems and a disadvantaged environment increasesthe risk of such problems was reported in Kelly et al.(2001). For females’ growth, however, family educationtended to be associated with lower weight and height z-scores which may be indicative of some selection, i.e. thateducated families experienced higher survival rates of thesmaller LBW children.15

Thus, the results showed some consistent patterns in allof these estimations. In agreement with Hack et al. (1994),Boardman et al. (2002), we found that although LBW didproduce negative effects and some of which first appearedat later ages, many other social factors produced just aslarge if not larger effects; in particular, whether the motherwas diagnosed with mental illness, was hospitalized for anillness, maternal age, family educational level and familylevel of employment. Just as other researchers in this area,we were able to maximally explain about 13% of thevariation in outcomes, even with the best fitting model. Apositive finding was that LBW and the other variablesincluded explained a larger share of the observed variationin outcomes in the earliest year of the sample (1996) andthat the explanatory power of the model declined witheach year thereafter, which we interpret as the decliningimportance over time of the biological disadvantagegenerated by low weight at birth.

4. Sensitivity analysis

We tested the sensitivity of the findings to differentways of defining the sample and the primary variable ofinterest, the means of which are found in Table 6. Thesealternative specifications were used in this section.

14 Another linkage could be that education changes fertility choices

towards a preference for quality rather than quantity of children, but our

models control for family size and birth order.15 Interactions of LBW with other explanatory variables in our models

have been tried, such as family concurrent employment, family structure

(single mother, mother with stepfather), etc., but only in the case of

family education do we minimize concerns of endogeneity, as parental

This is due to page restrictions as Table 5 alone includes estimates

m 50 regressions.

education is typically completed prior to birth and shows little change

over the sample period.

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First, we explored whether changing cutoffs for LBW to2400 g, <2600 g, and then reverting back to <2500 g butmitting the HBW (<4500 g), changed our findings. The400 threshold is presented in Table 7, while the other twostimations are available from authors upon request. Theseesults lend further credence to our findings as in no caseere the results affected appreciably. Of course there were

mall differences. The results became sharper, respectivelyeaker, when the cutoff was placed at <2400 g versus at2600 g or when the HBW were removed from the sample.

An alternative to using a specific threshold for definingw birth weight is to use birth weight as a continuous

ariable. In these estimations, we enabled birth weight toffect outcomes across the whole distribution. Thestimation (Table 8) showed very similar results although

all coefficients now have the opposite sign. This is becausea higher birth weight reduces negative outcomes andincreases positive ones, which is consistent with what wefound earlier. Thus, both height and weight z-scores weresignificantly positively related and SDQ significantlynegatively related (better behavior) with increasing birthweight. For both females and males, it could be seen thatconduct problems significantly decreased with higherbirth weight, but also that hyperactivity was significantlyreduced by higher birth weight.16

The continuous specifications, though informative inthemselves, cannot be used to specifically address theissue of development in LBW effects over time in our set-up. Therefore, we retain the threshold specification as ourmain empirical model, which is also the conventionapplied in most of the literature.

When the models were estimated using a dummy forgestation (in weeks) being less than 35 instead of thedummy for low birth weight, having low gestation, asexpected, significantly affected females’ SDQ in 2003, i.e.females with low gestation have similar psychosocialdifficulties as found before (Table 9). On the other hand,males’ problems with hyperactivity were insignificant in

able 7

ensitivity test with dummy for birth weight < 2400 g on child outcomes.



Weight (z-score) �1.446*** �0.572*** �0.357*** �0.364***

Height (z-score) �1.390*** �0.510*** �0.350*** �0.220*

SDQ 0.541 0.923* 1.003*


Peer relationship problems 0.028 0.085


Emotional behavior symptoms 0.414** 0.303

Conduct disorder 0.186 0.387***

Males child outcome

Weight (z-score) �1.709*** �0.912*** �0.651*** �0.439***

Height (z-score) �1.556*** �0.993*** �0.714*** �0.596***

SDQ 0.106 0.740 0.841

Pro-social behavior 0.038 0.179

Peer relationship problems �0.126 �0.059

Hyperactivity/inattention 0.545* 0.724**

Emotional behavior symptoms 0.283 0.004

Conduct disorder 0.038 0.171* Significant at 10%.** Significant at 5%.*** Significant at 1%.

able 6

istribution of cutoff points, gestation age, and fetal growth among children born in 1995.

Females Males

All children born in 1995 DALSC children All children born in 1995 DALSC children

Share of LBW < 2500 g 5.42 5.09 4.20 4.14

Share of LBW < 2400 g 3.94 4.05 3.61 3.26

Average gestation age in weeks (std dev) 39.5 (1.84) 39.6 (1.88) 39.4 (1.94) 39.5 (1.95)

Share of low gestation age < 35 weeks 2.13 2.70 2.50 2.53

Average fetal growth (kg/week) (std dev) 0.086 (0.01) 0.087 (0.01) 0.090 (0.01) 0.090 (0.01)

Share of low fetal growth < 2.5 kg/37 weeks 6.54 5.75 5.20 4.18

Share of VLBW (<1500 g) 0.70 0.78 0.66 0.64

Share of MLBW (1500–2499 g) 4.72 4.31 3.54 3.50

Number of children 33,617 2297 35,591 2486

ote: Fetal growth = (birth weight in kilos/gestation age in weeks). The share of children with low fetal growth is defined by using the cutoff for low birth

eight (2.5 kg) and the cutoff for preterm birth (37 weeks), which gives 0.0675.

6 An alternative is to use birth weight as a continuous but non-linear

ariable in the analyses, i.e. birth weight in kg and its square. We have also

stimated this specification and we found that assuming non-linearity

aturally affected the results. Especially for females, the result produced

ven more significant coefficients regarding the behavioral outcomes at

ge 11 implying that high birth weight also carries some importance

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is specification but the difference in the results may bee to the fact that not all preterm babies are LBW andme full-term babies may be LBW. All other results usinge dummy for gestation weeks corresponded to thesults for low birth weight.

We also tried replacing LBW by fetal growth which iseasured as a dummy variable for birth weight forstation age with the cut-off point being the low birtheight limit at 2.5 kg divided by the full born gestation

it of 37 weeks (Table 10). By redefining the group ofW as those children who are small for gestational age,

e identified those children who were small for genetic/aternal/placental/environmental reasons as opposed toose who were born low-weight because of incompletestation. The first group should experience more severeurological and psychosocial difficulties and less devel-ment over time. The findings indeed confirmed our

supposition and showed stronger and more significanteffects compared to the results reported in Table 5. Hacket al. (2003) also subdivided VLBW (very low birth weight)subjects into SGA (small for gestation age) and appropriatefor gestation age and found that subnormal growthbetween 8 years and 20 years compared to NBW controlswas mainly experienced in the former group.

Our final specification test in Table 11 consisted ofsplitting up the LBW effect into an effect due to VLBW (verylow birth weight < 1500 g) and an effect due to MLBW(moderate low birth weight 1500–2499 g) similar toBoardman et al. (2002). Of the 5% (4.1%) of female (males)who were LBW, only 0.8% (0.6%) were VLBW and theremaining 4.3% (3.5%) were MLBW. Both VLBW and MLBWchildren experienced catch up in height and weightbetween 6 months and 3 years, although MLBW infantsmade up more of the initial disadvantage (significant

ble 9

nsitivity test with dummy for gestation age < 35 weeks on child outcomes.


emales child outcome

eight (z-score) �1.477*** �0.431** �0.055 �0.022

eight (z-score) �1.326*** �0.493*** �0.183 �0.143

DQ 0.864 1.191** 0.625


Peer relationship problems 0.123 �0.064


Emotional behavior symptoms 0.426* 0.275


ales child outcome

eight (z-score) �1.441*** �0.593*** �0.466*** �0.317**

eight (z-score) �1.464*** �0.772*** �0.556*** �0.454***

DQ �0.467 0.191 0.238

Pro-social behavior �0.097 0.128


Hyperactivity/inattention �0.078 0.259


Conduct disorder 0.033 �0.080

Significant at 10%.* Significant at 5%.** Significant at 1%.

ble 8

nsitivity test with continuous birth weight (bw in g/1000) on child outcomes.


emales child outcome

eight (z-score) 0.875*** 0.623*** 0.385*** 0.292***

eight (z-score) 0.849*** 0.552*** 0.372*** 0.297***

DQ �0.501** �0.387** �0.269

Prosocial behavior �0.020 �0.025


Hyperactivity/inattention �0.257*** �0.217***

Emotional behavior symptoms �0.118 0.041

Conduct disorder �0.052 �0.133***

ales child outcome

eight (z-score) 0.865*** 0.634*** 0.452*** 0.344***

eight (z-score) 0.836*** 0.519*** 0.437*** 0.387***

DQ �0.353* �0.498*** �0.506***

Prosocial behavior 0.066 �0.017

Peer relationship problems 0.030 �0.017

Hyperactivity/inattention �0.343*** �0.336***

Emotional behavior symptoms �0.078 �0.077

Conduct disorder �0.107** �0.076*

Significant at 10%.* Significant at 5%.** Significant at 1%.

Table 11

Effect of very low birth weight (dummy for birth weight < 1500 g) and effect of moderately low birth weight (dummy for birth weight between 1500 and

2499 g) on child outcomes.



VLBW

Weight (z-score) �2.491*** �0.799** �0.275 �0.259

Height (z-score) �1.742*** �0.432 �0.461* �0.044

SDQ 1.429 1.705 3.006***




Emotional behavior symptoms 0.940** 1.043**

Conduct disorder 0.001 0.818***

MLBW

Weight (z-score) �1.063*** �0.357** �0.232** �0.325***

Height (z-score) �1.144*** �0.380*** �0.151 �0.227*

SDQ 0.367 0.418 0.241

Prosocial behavior �0.011 �0.174


Hyperactivity/inattention 0.109 �0.049


Conduct disorder 0.117 0.169

Males child outcome

VLBW

Weight (z-score) �2.829*** �0.729* �1.136*** �0.921***

Height (z-score) �2.316*** �0.718** �1.003*** �1.046***

SDQ 0.868 1.255 2.525**

Prosocial behavior 0.136 0.298


Hyperactivity/inattention 0.633 1.397**


Conduct disorder 0.218 0.252

MLBW

Weight (z-score) �1.305*** �0.895*** �0.503*** �0.294**

Height (z-score) �1.363*** �0.967*** �0.557*** �0.422***

SDQ �0.036 0.528 0.577

Prosocial behavior �0.117 0.152

Peer relationship problems �0.121 �0.014

Hyperactivity/inattention 0.524* 0.626**


Conduct disorder �0.016 0.086* Significant at 10%.** Significant at 5%.*** Significant at 1%.

Table 10

Sensitivity test with dummy for fetal growth ((bw/1000)/gestation age < 0.0675) on child outcomes.



Weight (z-score) �1.254*** �0.616*** �0.429*** �0.354***

Height (z-score) �1.215*** �0.499*** �0.329*** �0.227**

SDQ 0.305 0.902** 0.715*



Hyperactivity/inattention 0.389** 0.341*

Emotional behavior symptoms 0.339** 0.094


Males child outcome

Weight (z-score) �1.503*** �0.944*** �0.594*** �0.472***

Height (z-score) �1.393*** �0.938*** �0.629*** �0.535***

SDQ �0.367 0.340 0.822

Prosocial behavior 0.189 0.300**

Peer relationship problems �0.219* �0.087

Hyperactivity/inattention 0.477* 0.785***


Conduct disorder �0.001 0.063


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fferences) (Table 11). Between 3 and 7, mainly the MLBWfants continued growing (significant for males). VLBWmales reduced the weight disadvantage only, whileBW males actually widened their height and weightficits (although insignificant). Between 7 and 11, allanges are insignificant, but MLBW males showed andency to sustained growth. These results gave support

the trends between 8 years and 20 years found earlier byck et al. (2003) who reported that VLBW males

mained significantly smaller than their controls at 20ars of age. Furthermore, by showing that the growth rateeling-off of VLBW children starts already at age 3, we

pplemented their evidence.In terms of the behavioral outcome, overall behavior

emed to get worse over time for both VLBW males andmales and the females actually scored higher on SDQgnificant for both males and females). The differencesross waves were insignificant, though, due to thelatively small sample sizes in this analysis. Also, therlier result we found that LBW females showedotional behavior symptoms at age 7 that manifest

emselves as conduct disorders at age 11 turned out to beiven by the VLBW females (the change in the coefficient

conduct disorder is statistically different at age 11mpared to age 7). In addition, the coefficients to conductsorder and emotional problems were significantly worser the 11-year-old VLBW females compared to the MLBWmales. For males, however, both VLBW and MLBWbgroups experienced increasing hyperactivity/inatten-n between ages 7 and 11, the strongest increase beingong VLBW males (although the changes were notnificant). Neither VLBW nor MLBW children showednificantly less prosocial behavior or significantly moreer relationship problems than NBW children at eithere 7 or age 11. This evidence is consistent with Elgen et al.002) and Martel et al. (2007). There are some differenceswever: we found no effect on prosocial behavior

hereas Elgen et al. found social problems at age 11.rthermore, we found deeper problems with the VLBW

hile Elgen et al. (2002) found effects of the same size forth VLBW and MLBW. Their study did not explore genderfferences and LBW was defined as <2000 g so that theBW and MLBW were more similar in their set-up.

ilar to Martel et al. (2007), we found a strongerlationship between LBW and inattention/hyperactivity

males, although their study drew children from thetroit area only, and measured outcomes solely at age 6.r results on increasing hyperactivity/inattention pro-

de a bridge between the results reported by Hack et al.009) and Botting et al. (1997) who found, respectively,gher rates of attention-deficient hyperactivity as well asmptoms pertaining to Autistic and Asperger’s disorderong ELBW (<1 kg) at 8 years of age, and ADHD disordersong VLBW at 12 years. Our study produced valuable

idence that these traits were only visible among LBWales and not females, and in fact tended to increasetween ages 7 and 11.We have examined the effect of attrition in the survey.

Section 2 it was mentioned that although the DALSC wasndomly drawn, families with low socioeconomic status

time, i.e. differential attrition from the sample. To checkthat our results were not being driven by a compositionaleffect, the models for each year were estimated on thebalanced sample of the mothers who were present in allwaves (results are available from authors upon request).Although response rates were high in all waves, thebalanced sample was considerably smaller—777 femalesand 802 males. The reason for single wave participationbeing high is that all families are traced through the DanishCentral Personal Registry (CPR), implying that participa-tion in one wave does not rely on participation in the lastwave. The key questions on the outcome variables height,weight and SDQ were administered differently to therespondents (mothers) in different waves. In some wavesseparate questionnaires were administered, i.e. a healthquestionnaire and a mother questionnaire. In other years(e.g., 2007), the mother questionnaire included all thequestions needed to define our outcomes. All in all, 6separate questionnaires need to be filled to be included inthe balanced panel. Conditioning on all of these are filledreduces the sample size considerably. The significance forthe balanced sample suffered due to the smaller samplesize, but the results remained essentially the same. Thus,differences in the sample composition over time did notaffect our findings.17

5. Discussion and conclusions

Previous research has linked LBW to a number ofadverse long run physical growth and developmentaloutcomes (Fitzhardinge and Steven, 1972; Hack et al.,1996, 2003; Brandt et al., 2005; Saigal et al., 2006; Elgenet al., 2005) but only a relatively new strand of literaturehas begun to focus on cognitive and behavioral difficultiesof LBW infants at school age (McCormick et al., 1992; Hacket al., 1994). As recent medical advances have been verysuccessful in minimizing health problems of LBW children,the focus seems to have shifted from looking only at healthoutcomes to investigating the extent of, primarily, learningdisabilities. Even fewer studies look at behavioral deficitsfor example, attention deficiency (Bhutta et al., 2002;Breslau, 1995; Kelly et al., 2001; Elgen et al., 2002; Wileset al., 2006 are a few exceptions). However, few studieshave benefited from the availability of child longitudinaldata sets allowing for follow-ups during various stages ofchildhood.

We used a large, representative, longitudinal sample ofDanish children born in 1995 and followed through 2007to study the medium run effects of low birth weight and tobring new evidence to the recent literature on how theseLBW effects on child outcomes develop over time. Weextended this literature by considering the impact of LBWon both anthropometric and behavioral outcomes, and byexploiting an especially rich and highly reliable set ofmeasures.

17 Only 0.15% of the total DALSC sample of children (9 out of 6011) died

or before the 2003 wave, indicating that excess mortality of males was

likely to play a role in this case.
.g., single mothers) became under-represented overon
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Our paper added to the literature in this area in at leastur important ways. First, the richness of our data allowed

s to simultaneously assess impacts of LBW on physicalrowth, as well as a multifaceted measure of psychosocialell-being. Behavioral outcomes have been argued to beore important for child development than cognitive

utcomes and have been shown to be the necessaryrerequisites for learning academic skills. Yet, LBW effectsn behavior remain an under-researched area (see theurvey by Breslau (1995) and a few recent studies by Kellyt al. (2001) and Wiles et al. (2006)). Second, while manyrevious studies have been hampered by small samples ofBW cases and NBW controls often drawn from localopulations, we used a large, nationally representativengitudinal sample of children who were followed for

ver a decade which allowed an understanding of theynamic processes involved in producing adverse out-omes over the full age-span of childhood, as well asllowing for estimating separate LBW impacts on a rangef male and female psychosocial outcomes, again aelatively unexplored area (Martel et al., 2007, is one ofw studies that explore sex differences in the pathways

etween LBW and hyperactivity/inattention). Third, ourirth weight measure was highly accurately measured as it

based on the actual registered weight in child medicalecords rather than on the mother’s self report, which is

e case in the National Longitudinal Survey of Youth datand other U.S. data sets (Boardman et al., 2002), so ourstimates did not suffer from misreporting bias. Finally,nlike many previous studies, we had a very rich set ofocioeconomic and family structure controls many ofhich were merged to the survey from highly reliable

dministrative registers including parallel information onoth parents with respect to labor force status, householdcome, detailed educational type as well as unique surveyformation on parental mental illness and hospitalizationr diseases. Allowing for a complete set of socioeconomic

nd family factors minimized bias in LBW impacts arisingom the confounding effects of these factors.

Our findings confirmed earlier findings by Hack et al.996) that low birth weight children exhibited a

ignificant early catch-up with respect to their physicalrowth. They found in a sample of 249 VLBW (<1500 g)hildren born between 1977 and 1979, that while 54%ere subnormal in weight and 60% subnormal in height at

0 weeks, by 8 years, 8% were subnormal in weight andeight. On the other hand, Elgen et al. (2005) compared aopulation-based sample of 130 non-handicapped LBWhildren to 131 NBW children born to term and found that

e differences and similarities in anthropometric mea-ures were the same at 5 and 11 years of age. Our studyund that while there was early convergence in the

nthropometric measures, it appeared that at later agesnly the MLBW males continued on this trajectory and theLBW, in particular the males, showed signs of stagnation.

While the effect of LBW on the SDQ scale was increasingver time for both males and females (i.e. worse behavior),

was not in general significant. When splitting up the LBWroup by weight, however, we found some evidence oforsening behavior over time among the VLBW group.hen we looked at the sub-domains of SDQ, we saw some

significant effects of LBW on psychosocial problems at theage of school start but that were different for males andfemales. Thus, unlike Johnson and Breslau (2000) whofound that only males were more vulnerable to learningdisabilities, our results showed that both females andmales were affected, but by different problems. While LBWfemales faced emotional behavioral symptoms at age 7 andconduct disorders at age 11, LBW males suffered fromhyperactivity/inattention problems at age 7 as well as age11. These effects, however, were largely driven by theVLBW subgroup although MLBW males also showed anincrease in hyperactivity/inattention. We found no signifi-cant impacts of LBW on either prosocial behavior or peerrelationships, and therefore our results are slightlydifferent from Kelly et al. (2001) who also applied theSDQ scale and found in a cross-sectional analysis ofchildren aged 4–15 that birth weight was a predictor ofhyperactivity among males but also peer problems amongfemales. But, our results are similar to Wiles et al. (2006)who also used the SDQ scale and found a relationshipbetween, in particular, birth length and hyperactivity andconduct problems in a cross-sectional sample of 4813children from the ALSPAC cohort in Bristol, UK. Neitherstudy, however, explored the dynamics of the process. Acomprehensive set of sensitivity checks, experimentingwith different LBW measures and sample compositionsupported the robustness of the findings.

As earlier studies (e.g., the large register-based study byBlack et al., 2007) showed, LBW can be causally linked tolong run underachievement in higher education comple-tion and lower labor market earnings. But these studiescould not explore the mechanisms underlying such longrun deficits. Our study provided important evidence thatthe medium run mechanisms influencing lower long runeducational attainment could be significantly higher ratesof hyperactivity/inattention among LBW males andemotional behavior problems and conduct disordersamong LBW females, which in turn may have neurodeve-lopmental antecedents. These problems showed up atschool starting age or before and intensified with time.These results have important long run implications. Arecent literature has linked non-cognitive skills such asschool readiness, the ability to sit still in class, concentrate,follow directions, etc. to future economic outcomes (Cunhaand Heckman, 2008; Heckman et al., 2006). Another strandof literature has found that early mental health conditionsas measured by Attention Deficit Hyperactivity Disorder(ADHD) diagnosed as early as age 4 affected future testscores and schooling attainment negatively (Currie andStabile, 2009). In terms of emotional behavior, measures ofpersistence, self-esteem, and optimism have been found toaffect not only schooling outcomes but also the probabilityof teenage pregnancy, smoking, and earnings, see Duncanet al. (2004) and Carneiro et al. (2007). Thus, the growingfocus in the literature on cognitive and behavioraldifficulties of low birth-weight infants in addition to theirphysical growth and development is well-founded.

Overall, our study brought important new evidence onthe dynamics in the medium run that lead to negativeoutcomes in the long run. While we found that differencesin height and weight decreases for most groups over time,

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havioral gaps opened up at school starting age, inrticular among the VLBW group. The results from thisper suggest that specific interventions targeting theW subgroups that were found to be most vulnerableust begin before school starting age and must focus onfferent behavioral domains for the two genders.

knowledgements

Janet Currie, Paul Gregg, Carol Propper, Inas Rashad,uti Dholakia-Lehenbauer and Anders Boman are thankedr helpful suggestions given on this paper at variousges. We also thank the anonymous referees and theitor, John Komlos, for their valuable comments.

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