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The Impact of Episodic and Chronic Poverty on Child CognitiveDevelopment

JAKE M. NAJMAN, PHD, FASSA, MOHAMMAD R. HAYATBAKHSH, MD, PHD, MICHELLE A. HERON, PHD, WILLIAM BOR, PHD,MICHAEL J. O’CALLAGHAN, MBBS, MSC, FRACP, AND GAIL M. WILLIAMS, PHD

bjective To determine whether changes in family poverty between pregnancy, early childhood, and adolescence predicthild cognitive development at 14 years of age.

tudy design We conducted a population-based prospective birth cohort study of 7223 mothers who gave birth to a liveingleton baby, observed to 14 years of age. Family income was measured on 4 occasions from pregnancy to the 14-yearollow-up. Child cognitive development was measured at the 14-year follow-up using the Raven’s Standard Progressiveatrices and Wide Range Achievement Test.

esults Poverty experienced at any stage of the child’s development is associated with reduced cognitive outcomes.xposure to poverty for a longer duration (birth to 14 years) is more detrimental to cognitive outcomes than experiencingoverty at only 1 period. For each additional exposure to poverty, the Raven’s Standard Progressive Matrices scores declinedy 2.19 units and the Wide Range Achievement Test scores declined by 1.74 units.

onclusion Children experiencing family poverty at any developmental stage in their early life course have reduced levelsf cognitive development, with the frequency that poverty is experienced predicting the extent of reduced cognitive scores.J Pediatr 2009;154:284-9)

hildren from low-income families have lower cognitive test scores when compared with children from more affluentbackgrounds. This has been reported for children from 2 years of age and to adolescence.1-7 The association remainseven after statistical control for maternal cognitive skills, parent education,1,6,8,9 and family structure.9,10 It is estimated

hat children reared in poverty score between 15% and 40% of a SD lower on cognitivessessments than children from higher income backgrounds.11 Earlier investigations havelso found that parent and grandparent socioeconomic status (SES) are independentlyssociated with lower child cognitive development at 5 and 14 years of age.12 However,hese findings leave unresolved the issue of whether poverty experienced at a particulartage of the child’s developmental trajectories (in pregnancy, early childhood, or adoles-ence) has an independent impact on cognitive development and whether those effectsight be particularly important or cumulative.

Some studies have investigated the effect of timing (childhood versus adolescence)nd duration of poverty on cognitive development. Duncan et al6 report that experiencingoverty in early childhood (birth to 5 years) has a greater impact on cognitive achievementhan experiencing poverty in middle childhood (6-10 years) or adolescence (11-15 years).ipman and Offord13 report that experiencing poverty earlier in the life course (betweenand 12 years) is more detrimental than between 8 and 16 years. For duration of poverty,ersistent poverty appears to be more detrimental than transient poverty.1,3,4,7,10

Guo14 reports that exposure to poverty during childhood (birth to 6 years) appearso have a more detrimental effect on childhood cognitive ability than experiencing povertyuring early adolescence. Poverty experienced in the 4 years before adolescence had nodditional impact on child cognitive outcomes beyond the effects observed for povertyxperienced in early childhood. Guo’s study uses data taken from the National Longitu-

NCOVA Analysis of covarianceNOVA Analysis of variance

SES Socioeconomic statusSPM Standard Progressive Matrices

From the School of Population Health, Uni-versity of Queensland, Brisbane, Australia(J.N., M.H., G.W.); School of Social Science,University of Queensland, Brisbane, Austra-lia (J.N.); Qom University of Medical Sci-ence, Qom, Iran (M.H.); Department ofPsychology, University of Sheffield, Shef-field, United Kingdom (M.H.); and MaterMisericordiae Children’s Hospital, Brisbane,Australia (M.O.).

The core study was funded by the NationalHealth and Medical Research Council ofAustralia, but the views in this paper arethose of the authors and do not reflect inany way the views of any funding body. Theauthors declare no conflicts of interest.

Submitted for publication Jan 23, 2008; lastrevision received Jun 23, 2008; acceptedAug 4, 2008.

Reprint requests: Jake M. Najman, PhD,School of Population Health, University ofQueensland, Herston Road, Herston, QLD4006, Australia. E-mail: [email protected].

0022-3476/$ - see front matter

Copyright © 2009 Mosby Inc. All rightsreserved.

PVT Peabody Picture Vocabulary Test WRAT Wide Range Achievement Test

84

10.1016/j.jpeds.2008.08.052

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inal Survey of Youth (NLSY) and the children of the NLSYNLSY-C). Income data is from early childhood and adoles-ence, with no data on income during pregnancy or very earlyhildhood.

Although experimental approaches offer evidence ofow changed family circumstances enhance later cognitiveutcomes, natural experiments involving changes of house-old income levels during childhood may provide importantests of how income change influences children’s cognitiveevelopment.15 Longitudinal studies that capture naturalransitions in family income over time and child/adolescentognitive development can be used to further test the impactf income change on cognitive abilities. We investigated theffects of changes in poverty among pregnancy, early child-ood, and adolescence on cognitive ability in children aged 14ears, by using data from an Australian prospective birthohort study.

METHODSWe used data from the Mater-University of Queens-

and Study of Pregnancy, a prospective longitudinal study ofconsecutive cohort of individuals born at a major public

ospital (Mater Misericordiae Hospital) in Brisbane, Austra-ia between 1981 and 1983. The hospital was 1 of only 2

ajor obstetrical hospitals in Brisbane and served the southide of the city. Recruitment procedures for the larger studyave been detailed elsewhere.16,17 Baseline data were collectedt the first antenatal visit (average 18 weeks of pregnancy)rom 7223 consecutive women who subsequently gave birth toive singleton babies and were observed at 3 to 5 days, 6

onths, 5 years and 14 years after the birth. At the 6-monthollow-up visit, 6720 women (93%) responded to the ques-ionnaire; this number dropped to 5234 at the 5-year fol-ow-up visit and 5185 (72%) at the 14-year follow-up visit. At4 years, a child assessment questionnaire was completed by799 children (53%).17 Approximately 3000 participants pro-ided cognitive development scores at 14 years, and data werevailable on family income between pregnancy and the 14-ear follow-up for them. Written informed consent from theother was obtained at all phases of data collection. Ethics

ommittees at the Mater Hospital and the University ofueensland approved each phase of the study.

easurement of Economic StatusMothers were asked about gross annual household

family) income (including spouse’s income, child endow-ent, etc.) at the child’s birth and when the child was 6onths, 5 years, and 14 years old. Seven discrete income

ategories were given as response options (listed in weekly andnnual amounts). Mothers with family income in the categorylosest to the bottom 20% of incomes were considered to beow income (poor). The low income figure selected at everyhase of data collection is similar to the estimate of theroportion of the Australian population living at or below theoverty level. We examined the effects of poverty when it is

imited to early childhood (birth to 5 years) or adolescence (14 c

he Impact of Episodic and Chronic Poverty on Child Cognitive Develo

ears) and persistent poverty (birth to 14 years) on cognitiveevelopment at 14 years of age. The sample from this studyerives from a public (free) hospital and is somewhat over-epresented by lower income earners. The overrepresentationf low income earners has the effect of increasing the numbersn this group, while reducing the numbers of very high in-ome earners in the study. This “shrinking” of the incomeariability evident in the broader population has the effect ofroviding a conservative test of the income and cognitiveevelopment relationship.

easurement of Cognitive DevelopmentAt the 14-year follow-up, assessments of cognitive de-

elopment were based on youth scores on the Raven’s Stan-ard Progressive Matrices (SPM)18 and the Wide Rangechievement Test (WRAT).19 The Raven’s SPM is a test ofon-verbal reasoning ability that is widely used for psycho-

ogical assessment in clinical and educational contexts.18,20

lthough there is some debate about the specific cognitivettributes the Raven’s SPM measures, it has demonstrated aigh correlation with full-length intelligence tests21 and isenerally accepted as a measure of general intelligence. Deemos22 re-standardized Raven’s SPM scores, on the basis of

he mean and SD at each year level. However, in this study,hild scores have been standardized in 6 monthly groupingsather than yearly levels.

The WRAT is an age-normed referenced test thatssesses reading and word decoding skills.19 It has been foundo be a stable measure23 and to have high test-retest reliabil-ty24 and high internal consistency reliability coefficients.25 Inhis study, only the reading subscale of the WRAT wasdministered. WRAT scores were standardized (M � 100;D � 15) for consistency with other measures. The WRAT

s intended to measure basic reading skills and academicchievement. It is intended to identify children who haveifficulties with reading.26,27 Although the Raven’s SPM andhe WRAT both provide a measure of child IQ, the SPM isikely to reflect the child’s general ability whereas the WRATeflects the degree that learning has taken place. The Pearsonorrelation between the Raven’s SPM and WRAT was 0.42P � .001; n � 3784).

emographic InformationOnly mothers and their children were followed in this

tudy, with limited (no self-report) paternal data available.arital status when the child was 5 years old was divided incategories: mothers who were married or living in a de facto

elationship, and mothers with no partner (single, separated/ivorced or widowed). Maternal education at entry to thetudy was coded in 3 categories: high school not completed,ompleted high school, and studies beyond high school. Ma-ernal age at entry to the study was included as a discreteriginal variable. We adjusted for marital status and maternalge because these factors are associated with both SES and
ognitive development. Similarly, maternal education was
pment 285

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ontrolled to distinguish home environment effects support-ng educational outcomes from the broader impact of poverty/ocioeconomic disadvantage.

ata AnalysisWe first examined univariate relations (1-way analysis

f variance [ANOVA]) in family economic status at eachhase of the study, measured between pregnancy and the4-year follow-up, and child Raven’s SPM and WRAT scorest 14 years. Next, a series of 1-way analysis’ of covarianceANCOVA) was conducted with the same variables control-ing for maternal education and age at first clinic visit and

aternal marital status assessed at the 5-year follow-up. Toxamine the association between family income at each fol-ow-up and child cognitive development, we conducted a

ultivariate ANCOVA controlling for family income andotential confounders at other phases. In a further analysis,sing family income at 4 phases of the study, we created aomposite variable that measures the number of exposures tooverty during 14 years of life. This variable comprised 4ategories: never poor, once, twice, and 3 or more times poor.inally, a 1-way ANOVA was run to test the relation betweenumber of exposure to family poverty and child cognitiveevelopment measured with Raven’s SPM and WRAT.

RESULTS

aven’s Standard Progressive MatricesA 1-way between-subjects ANOVA was run with fam-

ly income as the independent variable and cognitive devel-pment (Raven’s scores) at 14 years as the dependent variableTable I). A significant difference between the means for each

able I. Exposure to poverty at different stages overcore at 14 years

PhasePovertystatus

Unadjustedmodel

Ad

regnancy F (df) 22.30 (1,2924)P (�.001)

Poor 98.41Not poor 101.29

months F (df) 20.18 (1,2901)P (�.001)


years F (df) 50.84 (1,2920)P (�.001)


4 years F (df) 37.34 (1,2908)P (�.001)


, df, P values, and standardized Raven’s score.

hase of data collection, with the low income group consis- r

86 Najman et al

ently experiencing lower scores, was revealed with theNOVA. Next, a 1-way ANCOVA was run with the same

ariables, but with adjustment for poverty at each other stage.overty during pregnancy, at 5 years, and at 14 years remain

ndependently associated with the Raven’s score, suggestingoverty additionally contributes to cognitive outcomes at eachf these stages of the life course. Additional adjustment forome key socio-demographic variables has limited impact onhe mean differences. For model 3, poverty in childhood anddolescence independently contribute to Raven’s scores, evenfter additional adjustment for some indicators of familyocioeconomic circumstances.

In Table II, we examine the frequency with which thehild/adolescent experiences poverty by the child’s Raven’sPM outcomes. There is a linear trend that shows a reduction

n Raven’s SPM scores associated with increased frequency ofxposure to poverty. By using a regression to estimate theinear trend of the association between frequency of poverty inhe early life course and Raven’s SPM scores, we find thathere is a reduction of 2.19 points for every additional expe-

early life-course and child standardized Raven’s

d for poverty ater stages ofvelopment

Adjusted for poverty at other stagesof development and maternal

educational age and marital status

.98 (1,2921) 2.35 (1,2918)(0.026) (0.125)

99.40 99.74100.91 100.77

.39 (1,2898) 2.03 (1,2895)(0.239) (0.154)

99.86 99.67100.74 100.79

.92 (1,2917) 17.13 (1,2914)(�.001) (�.001)

97.90 97.92101.21 101.20

.84 (1,2905) 18.30 (1,2902)(�.001) (�.001)

97.84 97.97101.03 101.01

able II. Exposure to poverty and mean Raven’score at 14 year follow-up*

Times poor n Mean Raven’s Score 95% CI

ever 1486 102.33 74.7-129.9713 100.09 71.0-129.2427 98.30 67.9-128.7

-4 times 311 95.52 63.7-127.3

Regression of times in poverty against Raven’s SPM indicates a reduction of 2.19 (95%I, 1.67-2.71) for every additional instance of exposure to poverty.

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ide Range Achievement TestUnivariate ANOVA was run with family income as the

ndependent variable and cognitive development (WRATcores) at 14 years as the dependent variable (Table III).ignificant differences in WRAT scores were revealed withhe ANOVA for those living in poverty at every phase of dataollection from pregnancy to the 14 year follow-up. Next, a-way ANCOVA was run with adjustment for poverty atther stages of child development. Family poverty duringregnancy, at 6 months, and at 14 year follow-up indepen-ently predicted WRAT scores. Additional adjustment foraternal education, age, and marital status in model 3 reduces

ome of the differences in WRAT scores (poor versus notoor), but 3 of the 4 differences remain statistically signifi-ant.

In Table IV, we have aggregated the number of timeshe child lived in a family that scored around or below theoverty line. The data here points to a cumulative linearrend, with frequency of exposure to poverty associated withecreasing WRAT scores. A trend test (regression) indicateshat the WRAT scores decline by 1.74 points per everydditional instance a child is exposed to family poverty.

odeling the Effects of Loss to Follow-upOf those for whom mother’s family income are recorded

t entry to the study, 45.2% of lowest income group mothersnd 57.4% of other income group mothers remained in thetudy at 14 years. To estimate the association between cog-itive ability and loss to follow-up, we examined child Pea-ody Picture Vocabulary Test (PPVT) scores at 5 years as aredictor of loss to follow-up at 14 years. Of those who

able III. Exposure to poverty at different stages ovecore at 14 years

PhasePovertystatus

Unadjustedmodel

Adj

regnancy F (df) 27.32 (1,2918)P (�.001)


months F (df) 22.07 (1,2896)P (�.001)


years F (df) 13.74 (1,2914)P (�.001)


4 years F (df) 20.88 (1,2902)P (�.001)


, df, P values, and standardized WRAT score.

ompleted the PPVT at 5 years, 74.6% of those with normal w


nd higher scores remained in the study, compared with5.6% of those with less than normal scores who remained inhe study. Children subsequently lost to follow-up had a meanat age 5 years) PPVT of 96.85, compared with a mean of00.35 for children who remained in the study.

The existing data suggest that children in low incomeroups and who have lower PPVT scores are more likely to beost to follow-up. However, the magnitude of this associations modest, and loss to follow-up is about 10% to 15% highern the most disadvantaged groups.

The Appendix (available at www.jpeds.com) presentsarious estimates of the effect of loss to follow-up on thestimates of the association, on the basis of what is knownbout the characteristics of children lost to follow-up. On thessumption that approximately 60% of each group are lost toollow-up, but that the outcomes are 5%, 7%, and 10% worselower scores) in those lost to follow-up, then replacing theseases would generally slightly increase the differences inaven’s scores for increasing frequency of exposure to poverty.f it is estimated that the rate of loss to follow-up increases

e early life-course and child standardized WRAT

for poverty atr stages ofelopment

Adjusted for poverty at other stagesof development and maternal

education and age and marital status

97 (1,2915) 6.43 (1,2912)(0.001) (0.011)

98.57 98.94100.79 100.65

14 (1,2893) 2.64 (1,2890)(0.042) (0.104)

99.06 99.23100.55 100.50

46 (1,2911) 5.00 (1,2908)(0.227) (0.025)

99.49 98.78100.36 100.55

20 (1,2899) 15.75 (1,2896)(0.001) (�.001)

98.05 97.38100.57 100.71

able IV. Exposure to poverty and mean WRATcore at 14 year follow-up*

Times poor n Mean WRAT score 95% CI

ever 1483 101.53 75.0-128.0713 100.37 70.6-130.2425 97.82 66.4-129.2

-4 310 96.40 64.8-128.0

Regression of times in poverty against WRAT indicates a reduction of 1.74 points95% CI, 1.22-2.25) for every additional exposure to poverty.

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utcomes are worse for children lost to follow-up (also likely),hen the Raven’s score differences in poverty groups becomelightly larger than they were before the replacement of theissing cases. In every instance, it is clear that the actual

ndings are a conservative estimate of the association ob-erved without any loss to follow-up, and that the differencesetween the observed and estimated associations are minor.one of the main findings of the study are in conflict with any

f the projected associations on the basis of what is knownbout loss to follow-up, nor would any of the conclusionsiffer were any of the estimates to replace the observedndings.

DISCUSSIONPoverty experienced in early childhood is more detri-

ental to adolescent cognitive outcomes than poverty expe-ienced in adolescence alone.6,13 Our findings indicate thateither pregnancy, early childhood, nor the adolescent periodan be characterized as specifically sensitive for the impact ofoverty on cognitive development. Our findings suggest thathe frequency of childhood exposure to poverty has a greatermpact on child cognitive outcomes than the timing of thatxposure. However, it appears that poverty experienced at the4-year follow-up has the strongest and most consistent as-ociation with cognitive outcomes. Our results may differrom earlier studies for a number of reasons. First, our mea-ures of cognitive outcomes included the Raven’s and the

RAT, and the studies by Lipman and Offords13 and Dun-an6 used school outcomes (completion, placement in speciallass/remedial) and school performance as measures of cog-itive outcomes. Lipman and Offord’s13 subjects had a rangef ages (age at initial assessment ranged from 4-12 years), andhe period of follow-up was comparatively short (4 years).

The finding that more frequent experiences of familyoverty, in a child’s early life course, is associated with lower

evels of cognitive development, directs attention to theechanisms that link family poverty and cognitive develop-ent. Children from more economically disadvantaged back-

rounds are likely to experience many differences in theirnvironmental circumstances when compared with their moreconomically advantaged counterparts. Aside from a greaterome emphasis on learning and literacy, there is a betterhysical environment (better housing, more space per person),etter nutrition, and generally of better educational facilities.here may be fewer family disruptions and a generally more

table home environment. Although the impact of any ofhese differences may be small, the cumulative impact in aifetime is likely to be substantial.

Flynn28 has emphasized the potential of the environ-ental impact on child cognitive development, noting that

or a wide number of countries for which data are available,Q scores have been increasing at between 0.3 and 0.5 unitser year. For example, for the United States, with comparableests, there has been an average population increase of 14 IQoints in the period from 1932 to 1978. Flynn argues that
lthough IQ scores have been increasing with time, no single
s1

88 Najman et al

roposed cause can account for the observed changes.28 Im-roved economic conditions, better nutrition, and a betterhysical environment are all likely to contribute to increase inopulation IQ with time.

There are 3 policy directions that are a consequence ofur findings. First, the cumulative effect of poverty on ahild’s cognitive development suggests that initiatives are re-uired during the whole of the child’s early life course. Earlyhildhood intervention programs will need to be reinforced bynitiatives in later childhood and early adolescence, becauseoverty independently impacts on the child’s cognitive devel-pment, even when it occurs only in adolescence. Second,here is the possibility of targeted programs specifically di-ected to cognitive outcomes. These would include earlyhildhood interventions such as Head Start,29 but continuingeyond early childhood. Third, there are policies that have theffect of reducing economic inequalities in a population. Sucholicies would seek to move the chronically poor out ofoverty (eg, assist single mothers in re-entering the work-orce) and improve the physical environment in which chil-ren are reared. In part, this may involve a process of advocacyn behalf of disadvantaged children.

he authors thank the MUSP participants, the MUSP Researchnd data collection teams, and MUSP Data Manager Greghuttlewood for their support.

REFERENCES. Smith JR, Brooks-Gunn J, Klebanov PK. Consequences of living in poverty foroung children’s cognitive and verbal ability and early school achievement. In: Duncan, Brooks-Gunn J, editors. Consequences of growing up poor. New York: Russell Sageoundation; 1997. p. 132-89.. Taylor BA, Dearing E, McCartney K. Incomes and outcomes in early childhood.Hum Resources 2004;39:980-1007.. NICHD. Duration and developmental timing of poverty and children’s cognitivend social development from birth through third grade. Child Dev 2005;76:795-810.. Korenman S, Miller JE, Sjaastad JE. Long-term poverty and child development inhe United States: results from the NLSY. Child Youth Serv Rev 1995;17:127-55.. Black MM, Hess C, Berenson-Howard J. Toddlers from low-income familiesave below normal mental, motor, and behavior scores on the Revised Bayley Scales.Appl Dev Psychol 2000;21:655-66.. Duncan GJ, Brooks-Gunn J, Yeung WJ, Smith JR. How much does childhoodoverty affect the life chances of children? Am Sociol Rev 1998;63:406-23.. Brooks-Gunn J, Duncan GJ. The effects of poverty on children. Future Child997;7:55-71.. Crane J. Effects of home environment, SES and maternal test scores on mathe-atics achievement. J Educ Res 1996;89:305-14.

. Tong S, Baghurst P, Vimpani G, McMichael A. Socioeconomic position, mater-al IQ, home environment, and cognitive development. J Pediatr 2007;151:284-8.0. Duncan GJ, Brooks-Gunn J, Klebanov PK. Economic deprivation and earlyhildhood development. Child Dev 1994;65:296-318.1. Ryan RM, Fauth RC, Brooks-Gunn J. Childhood poverty: implications for schooleadiness and early childhood education. In: Spodek B, Saracho ON, editors. Handbookf research on the education of young children. Mahwah, New Jersey: Lawrencerlbaum Associates Publishers; 2006. p. 323-46.2. Najman JM, Aird R, Bor W, O’Callaghan M, Williams GM, Shuttlewood GJ.he generational transmission of socioeconomic inequalities in child cognitive devel-pment and emotional health. Soc Sci Med 2004;58:1147-58.3. Lipman EL, Offord DR. Psychosocial morbidity among poor children in Ontario.n: Duncan G, Brooks-Gunn J, editors. Consequences of growing up poor. New York:ussell Sage Foundation; 1997. p. 239-87.4. Guo G. The timing of the influences of cumulative poverty on children’s cognitivebility and achievement. Soc Forces 1998;77:257-88.5. Rutter M. Poverty and child mental health: natural experiments and social cau-
ation. JAMA 2003;290:2063-4.6. Keeping JD, Najman JM, Morrison J, Western JS, Andersen MJ, Williams GM.
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prospective longitudinal study of social, psychological and obstetric factors inregnancy: response rates and demographic characteristics of the 8556 respondents. Br Jbstet Gynaecol 1989;96:289-97.

7. Najman JM, Bor W, O’Callaghan M, Williams GM, Aird R, Shuttlewood GJ.ohort profile: the Mater-University of Queensland Study of Pregnancy (MUSP). IntEpidemiol 2005;34:992-7.8. Raven J. The Raven progressive matrices: an overview of international normingtudies. Psychol Test Bull 1989;2:7-16.9. Wilkinson GS. The Wide Range Achievement Test: administration manual.

ilmington, Delaware: Wide Range; 1993.0. de Lemos MM. Standard progressive matrices: Australian manual. Victoria:ustralian Council for Educational Research; 1989.

1. Raven JC, Court JH, Raven J. A manual for Raven’s Progressive Matrices andocabulary Tests. San Antonio, Texas: The Psychological Corporation; 1987.

2. de Lemos MM. The Australian re-standardization of the standard progressiveatrices. Psychol Test Bull 1989;2:17-24.

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3. Dura JR, Myers EG, Freathy DT. Stability of the Wide Range Achievementest in an adolescent psychiatric inpatient setting. Educ Psychol Meas989;49:253-6.4. Woodward CA, Santa-Barbara J, Roberts R. Test-retest reliability of the Wideange Achievement Test. J Clin Psychol 1975;31:81-4.5. Mishra SP. Reliability and validity of the WRAT with Mexican-American chil-ren. Psychol Schools 1981;18:154-8.6. Klimczak NC, Bradford KA, Burright RG, Donovick PJ. K-FAST and

RAT-3: are they really different? Clin Neuropsychol 2000;14:135-8.7. Orme DR, Johnstone B, Hanks R, Novack R. The WRAT-3 reading subtest asmeasure of premorbid intelligence among persons with brain injury. Rehabil Psychol004;49:250-3.8. Flynn JR. Massive IQ gains in 14 nations: what IQ tests really measure. Psycholull 1987;101:171-91.
9. Currie J, Thomas D. Does Head Start make a difference. Am Econ Rev995;85:341-64.
50 Years Ago in The Journal of PediatricsINTERSCORER AGREEMENT FOR THE GRAHAM BEHAVIOR TEST FOR NEONATES

Rosenblith JF, Lipsitt LP. J Pediatr 1959;54:200-5

Today it is as important to observe babies’ behaviors as it was in the past, despite the many technological advancesin the field of neonatology. Fifty years ago in The Journal, Rosenblith and Lipsitt reported satisfactory interscoreragreement across 4 domains of the Graham test, one of the first standardized behavioral examinations designed fornewborn infants. The authors raised a number of important issues including the need for norms for each day of life andcut-points for determining “normal” versus “abnormal” behavior. They also highlighted that “traumatized” infants mayperform differently from the “normal” babies. This raises the difficulty in defining the appropriate “norms” for differentgroups of infants, which remains an important issue for us today. How should we expect a baby of 23 weeks’ gestationto behave at 1 week of age, or, for that matter, upon reaching term? Should we compare preterm infant behavior withterm behavior?

As technology has advanced, so have the opportunities for greater understanding of the relationships between newbornbehaviors and cerebral injury using neuro-imaging, not available in 1959. Similarly, the examination of newbornbehaviors has progressed with the development of more complex tools such as the NBAS (Neonatal BehavioralAssessment Scale) and the APIB (Assessment of Preterm Infant Behavior). However, despite changing terminology, thethemes remain the same. Like Graham, Rosenblith, Lipsitt and others, we remain interested in babies’ “muscle-tension”(muscle tone), their irritability and self-regulatory behaviors, their maturation, and their ability to engage and orientateto specific stimuli. We still have much to learn from our infants’ behavior—although the latest monitors can tell us aboutnumerous vital signs, we can all do with a simple reminder to “observe the baby’s behavior.”

Nisha C. Brown, PhDVictorian Infant Brain Studies

Murdoch Childrens Research InstituteNewborn Research

The Royal Women’s HospitalDepartment of Obstetrics and Gynaecology

University of MelbourneMelbourne, Australia

Terrie E. Inder, MDDepartment of Pediatrics, Neurology, and Radiology

St. Louis Children’s HospitalWashington University

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ppendix. Estimated WRAT scores after adjustment for loss to follow-up: association between poverty andRAT cognitive development

Attrition(estimated)

Observedmean

Estimatedmean (5%)*

Estimatedmean (7%)†

Estimatedmean (10%)‡

ever poor 60% 101.53 98.48 97.27 95.44Poor 1 time 60% 100.37 97.36 96.15 94.35Poor 2 times 60% 97.82 94.89 93.7 91.95Poor 3-4 times 60% 96.40 93.51 92.35 90.62ever poor 50% 101.53 98.99 97.98 96.45Poor 1 time 55% 100.37 97.61 96.51 94.85Poor 2 times 60% 97.82 94.89 93.71 91.95Poor 3-4 times 65% 96.40 93.27 92.01 90.13

or estimated means, missing cases are replaced on the basis of known associations with projections for worst case scenarios.Estimated that cases lost to follow-up have 5% lower scores on cognitive development.Estimated that cases lost to follow-up have 7% lower scores on cognitive development.Estimated that cases lost to follow-up have 10% lower scores on cognitive development.

89.e1 Najman et al The Journal of Pediatrics • February 2009

the impact of episodic and chronic poverty on child cognitive development

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