{"paper_id":"920e5c11-e554-42ba-901d-61021f047825","body_text":"1 \n \nEducational attainment of children with major congenital anomalies \nduring primary school in England: a population cohort study using linked \nadministrative data from ECHILD \n \nJoachim Tan1,2, Ayana Cant2, Kate Lewis2, Vincent Nguyen2, Laura Gimeno2,3, Ania Zylbersztejn1,2, Pia \nHardelid1,2, Joan Morris4, Bianca De Stavola2, Katie Harron2, Ruth Gilbert2, on behalf of the HOPE Study \nTeam  \nAuthor affiliations \n1NIHR Great Ormond Street Hospital Biomedical Research Centre, 30 Guilford Street, London WC1N \n1EH, United Kingdom \n2UCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London WC1N 1EH, United \nKingdom \n3Centre for Longitudinal Studies, Social Research Institute, University College London, 55-59 Gordon \nSquare, London WC1H 0NU, United Kingdom \n4City St George’s, University of London, Cranmer Terrace, London SW17 0RE, United Kingdom \n \n \nCorresponding author \nJoachim Tan \nUCL Great Ormond Street Institute of Child Health \nUniversity College London \nLondon WC1N 1EH \nUnited Kingdom \nEmail: joachim.tan@ucl.ac.uk \n  \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \nNOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.\n\n2 \n \nAbstract  \nBackground  \nMajor congenital anomalies (CAs) occur in 2.3% of livebirths and are associated with lower educational \nattainment in affected children. Understanding how attainment changes throughout primary school \nwould inform parents, schools and organisations and help plan support. \nObjectives \nWe compared school enrolment and attainment at ages 5, 7 and 11 in children with different CAs and \ntheir peers in England using linked administrative hospital and education data in the ECHILD database.  \nMethods \nWe included all singleton children born in NHS-funded hospitals from September 2003 to August 2008 \nwho enrolled in state-funded schools at age 4-5. CAs were identified from hospital diagnoses, \nprocedures or death records. We described school enrolment, school-readiness, the percentages of \nchildren who sat curriculum assessments and who achieved expected levels in English and Maths at \nthree ages. We estimated risk ratios of children with CAs achieving expected levels compared with \npeers, adjusting for sociodemographic factors. \nResults \nOf 2,351,589 singleton children enrolled at age 5, 78,847 (3.5%) had CAs. At age 11, 88.7% of enrolled \nchildren with CAs sat assessments versus 97.2% of peers. Proportionally fewer children with CAs (45.7%) \nwere school-ready at age 5 versus peers (57.0%). For English, 56.9%, 55.4% and 65.3% of children with \nCAs achieved expected levels at ages 5, 7 and 11 respectively, consistently 11%-12% fewer than peers; \nsimilar gaps persisted for Maths. Children with CAs were on average less likely than peers to achieve \nexpected levels [adjusted risk ratio, aRR (95%CI): 0.86 (0.85,0.86)] but this varied substantially across CA \nsubgroups [aRR (95%CI) range: 0.01 (0.01,0.02) to 1.04 (0.96,1.12)]. \nConclusion \nThe attainment gap between children with CAs and peers remained unchanged across subjects and \nages, with proportionally fewer sitting assessments at age 11. Better monitoring and support for these \nchildren from school entry could help optimise learning experiences and fulfil their academic potential.  \n \nKeywords \nCongenital abnormalities, birth defects, educational attainment, cohort study, school-aged children  \n \nWord Count 3,485 \n \n  \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n3 \n \nSYNOPSIS \nStudy question \nWhat are the patterns of educational attainment in children with major congenital anomalies (CAs) \nthroughout primary school?  \n \nWhat is already known \nStudies of regional or registry-specific cohorts of children with CAs showed that proportionally fewer \nachieve expected attainment relative to peers at single stages of national assessments. There is limited \nevidence on children's participation in assessments and how attainment gaps change throughout \nprimary school at a population level. \n \nWhat the study adds \nLongitudinal analysis of whole-population cohorts from ages 4 to 11 found that attainment gaps \nbetween children with and without CAs remained largely constant across ages. Over half of children \nwith CAs were assessed as not 'school-ready' at age 5. Whilst almost all children with CAs remained \nenrolled in school at age 11, one in nine did not participate in assessments. \n  \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n4 \n \n1 | BACKGROUND \nMajor congenital anomalies (hereafter CAs), are inborn structural, chromosomal or genetic disorders \nwith significant medical, functional or social consequences for individuals. Many CAs are rare diseases, \naffecting under 1 in 2,000 people, but collectively they occur in 2.3% of births in England.1 Progressively \nimproving survival of children with CAs have led to more of them starting school,2 but fewer achieve \nexpected levels of attainment compared with their peers.3-5 Complex health needs, higher rates of \nschool absences, inherent learning disabilities, and inadequate support for special educational needs, \nare likely contributors to adverse outcomes for affected children, including those with non-\nchromosomal CAs such as cardiac defects, orofacial clefts or spina bifida.6-8 Such findings were \ncorroborated by a recent study using linked education and regional CA registries’ data in England, which \nshowed that attainment rates in national tests at ages 11 and 16 for children with a range of structural \nCAs were on average 5-7% lower than their peers.9  \n \nThis study aimed to describe the attainment trajectories for children with and without CAs in England by \nfollowing whole-population cohorts through primary school (ages 4-11 years). Understanding how the \nrates of school enrolment, curriculum assessments and attainment in children with different CAs change \nfrom school entry will provide evidence to inform timely support, thereby enriching their educational \nexperience and maximising their academic potential during these formative years. This project \ncontributes to the Health Outcomes of young People in Education (HOPE) research programme, \npreviously described elsewhere.10  \n \n2 | METHODS \n2.1 | Study Design \nThis is a population-based retrospective cohort study using linked administrative data from the ECHILD \n(Education and Child Health Insights from Linked Data) database.11  \n2.1.1 | Data Sources  \nECHILD contains routinely-collected data on hospital admissions from Hospital Episode Statistics (HES) \nlinked to education data from the National Pupil Database (NPD). HES captures about 97% of births in \nNHS-funded hospitals in England and 98-99% of secondary care contacts, including information on \ndemographic and geographical details, hospital stays, diagnoses and procedures12; the version of ECHILD \nused covered approximately 14.7 million individuals born 1995-2020.10, 11 ECHILD also contains death \nregistrations and causes of death from the Office for National Statistics. Diagnoses and causes of death \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n5 \n \nare coded using the International Classification of Diseases 10th Revision (ICD-10) whilst procedures are \ncoded using the Office of Population Censuses and Surveys Classification of Interventions and \nProcedures 4th Revision (OPCS-4). The NPD holds information on children attending state-funded \nschools in England between the ages of 4-18 years from academic year 2001/02.13 Data include teacher-\nassessed outcomes and national test marks at different key stages of education, pupils’ ethnicity, area-\nbased deprivation indices, free school meals eligibility (FSME) and geographical information. \n2.1.2 | Cohort Selection \nThe study population comprised all singleton children born in NHS-funded hospitals between 1st \nSeptember 2003 and 31st August 2008 who were linked to the NPD. We included children who were \nenrolled in Reception year (age 4/5) in state-funded schools, as recorded in the January school census. \nWe excluded children who were two or more years outside of the expected age for their school year. \nChildren were followed up until end of primary school (age 11), enrolment ceased or death (whichever \nwas earlier).  \n2.2 | Major congenital anomalies \nCA subgroups were defined by ICD-10 diagnosis codes according to the EUROCAT (European network of \npopulation-based registries for the surveillance of congenital anomalies) guide version 1.4.14 We also \nused alternative codelists combining diagnosis and OPCS-4 codes for severe congenital heart defects \n(CHD),15 orofacial clefts,3, 16, 17 anorectal malformations18 and hypospadias19; all except severe CHD \nproduced more conservative birth prevalence estimates than EUROCAT. We searched for relevant \ndiagnosis codes recorded before the first birthday and procedure codes (where specified) in HES, or \ncauses of death up to the 12th birthday.  \n \nWe described results for exemplar cardiac, orofacial, digestive, renal, and limb CAs and syndromic CAs \n(e.g. Down, Turner, Di George syndromes), and specific CAs where NPD data had been used.3, 4 For non-\nsyndromic CAs, we focused on the subset of children with isolated anomalies – i.e. one or more \nstructural defects occurring in the same organ system (e.g. polydactyly of hands and feet) classified \naccording to a EUROCAT algorithm.20 Those with CAs in multiple organ systems (not linked by a known \nsequence or chromosomal/genetic malformation) from a heterogeneous group and served as \ncomparators in sensitivity analysis (see below). CA subgroups are described in eTable1.  \n2.3 | Outcomes \nIn England, academic assessments based on the National Curriculum are conducted at the end of three \nkey stages of primary school – Early Years Foundation Stage Profile (EYFSP), Key Stage 1 (KS1) and Key \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n6 \n \nStage 2 (KS2) – interchangeably referred to using ages 5, 7 and 11 respectively. Specific to EYFSP is \nwhether children reach a Good Level of Development (GLD), a composite indicator of school \nreadiness.21 Attainment in English and Maths are measured by whether children achieve the age-specific \nexpected level, based on teacher-assessments (EYFSP and KS1) and nationally marked tests (KS2). Last, \ncontinuous subject z-scores (transformed from attained levels or test marks and standardised using raw \nscores from all pupils assessed in an academic year) were used to compare attainment across key \nstages. Details of assessment metrics are in eTable2.  \n2.4 | Covariates \nWe presented birth and sociodemographic characteristics including potential confounders of the \nassociation between CA status and outcomes: sex at birth, academic year of birth, month of birth, \nmaternal age at birth, birthweight, gestational age, ethnicity, income deprivation affecting children \nindex (IDACI) quintile, free school meals eligibility (FSME) and region of pupils’ residence. The first six \nare contained in HES whilst the remainder are from the NPD.  \n2.5 | Statistical Methods \nWe quantified the number of children who were enrolled in the Spring Census at ages 5, 7, and 11, and \nthose who died during primary school (with % relative to those enrolled at age 5). Using all enrolled \nchildren as the denominator, we reported the percentage: (1) who reached GLD; (2) who were assessed; \n(3) who achieved expected levels; and (4) the distribution of z-scores, for each subject and key stage, by \nCA subgroup.  \n \nGeneralised linear models (Poisson distribution, log link and robust standard errors) were used to \nestimate risk ratios of achieving expected levels for English and Maths at EYFSP , KS1 and KS2, comparing \nchildren in CA subgroups to children without CAs. We coded both “not assessed” and “assessed but not \nachieved” as “not achieved”. Models were adjusted for sex, and then for sex and maternal age, \nethnicity, IDACI quintile and FSME; year/month of birth and region were not significant confounders, \nwhilst birthweight and gestational age were likely mediators.22, 23 \n \nFor selected CA subgroups and all CAs combined, we fitted linear mixed models with random intercepts \nand random slopes to estimate the trajectories of z-scores, comparing children with and without CAs, \nadjusting for the factors described above. We included interaction terms to allow the differentials by CA \nstatus and sex to vary with age. To reduce computation time, a random sample consisting of 25% of \nchildren without CAs were used as the reference group. All analyses were performed using Stata version \n18 (StataCorp LLC, Texas, USA). \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n7 \n \n \n2.5.1 | Missing Data \nSex at birth, if missing, was substituted with gender recorded in the NPD. For region, FSME and IDACI, if \ndata were missing at age 5, we used the earliest non-missing record in any subsequent school census. \nEthnicity was based on the modal value across all censuses. Children in census without assessment \nresults were considered as not achieving the expected level. For all regression models, we analysed \ncomplete cases as <5% of the total had any missing covariate value. \n \n2.5.2 | Sensitivity Analysis \nWe compared outcomes for CA subgroups defined by EUROCAT and alternative codelists. We stratified \nattainment results by malformation type (isolated, multiple or chromosomal/genetic) to check that our \nresults were consistent with expectations of better attainment in the first group. We estimated risk \nratios using two populations: (1) all children enrolled at a given key stage; (2) a subset who were \nassessed at all three key stages; smaller differences were expected between the latter group and peers.  \n2.6 | Ethics  \nPermissions to use linked, de-identified data from Hospital Episode Statistics and the National Pupil \nDatabase were granted by the Department of Education (DR200604.02B) and NHS Digital (DARS-NIC-\n381972). Ethical approval for the ECHILD project was granted by the National Research Ethics Service \n(17/LO/1494), NHS Health Research Authority Research Ethics Committee (20/EE/0180 and \n21/SW/0159), and UCL Great Ormond Street Institute of Child Health’s Joint Research and Development \nOffice (20PE06).  \n  \n3 | RESULTS \nA total of 3,042,909 livebirths were extracted from ECHILD. Of the 2,940,072 (96.6%) singleton children \nwho were alive at their 4th birthday, 421,066 (13.8%) could not be linked to the NPD, whilst 167,417 \n(5.5%) who linked to the NPD were not enrolled at age 5, leaving just over 2.35 million children in our \nstudy (Figure 1). \n \nOf the study population, there were 78,847 (3.5%) children with one or more CA. Among them 71.5% \nhad isolated CAs, another 20.3% had chromosomal, genetic or non-system specific CAs, whilst 8.2% had \npotential multiple CAs (Table 1). Of all children without CAs enrolled at age 5, 1.4% and 4.0% were not \nsubsequently enrolled at ages 7 and 11 respectively, whilst corresponding percentages were 1.3% and \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n8 \n \n3.9% for children with CAs. Mortality during primary school was 0.4% in children with CAs, 10-fold \nhigher than peers (eTable3). \n \nMales comprised 51.4% of all children but 59.7% of those with CAs (Table 2). Compared to children \nwithout CAs, proportionally more children with CAs were born preterm (<37 weeks) and had low \nbirthweight (<2500g). Children with CAs were more likely to have mothers who were <20 or ≥40 years, \nbe of Asian/Chinese or Black ethnicity, have FSME, and be in the lowest two deprivation quintiles. Most \nvariables had no or relatively little missing data (<4.0%), except for birthweight (23.0%) and gestational \nage (33.6%), with a slightly higher rate for children with CAs. \n \n3.1 | Good Level of Development  \nOverall, 57.0% of enrolled children without CAs reached GLD at EYFSP, compared with 45.7% of children \nwith CAs (Figure 2). Children with isolated congenital hydronephrosis, club foot and polydactyly had the \nhighest proportions reaching GLD (≥51.9%), slightly below their unaffected peers, whilst those with \nhypoplastic left heart and congenital hydrocephalus had the lowest. Excepting Karyotype XXX, \nsyndromic CAs showed the lowest GLD achievement rates (<1% for Down syndrome). Sex differences \nexisted across CA subgroups, with 39.8% of males reaching GLD compared with 54.5% of females on \naverage (eTable4).  \n3.2 | Subject attainment for English and Maths \nThe assessment rate for English and Maths for children without CAs decreased from 99.3% at EYFSP to \n99.2% at KS1, and 97.2% at KS2, whereas for children with CAs it declined more sharply from 99.1% \n(EYFSP) to 98.6% (KS1) and 88.6% (KS2) (Table 3). Attainment rates for children with CAs in English rose \nfrom 56.9% (EYFSP) to 65.3% (KS2), which were consistently 11-12% lower than for their peers. \nAttainment rates for Maths remained stable but a similar gap existed (66-67% for children with CAs, 77-\n78% for peers). Amongst children with isolated CAs, those with renal anomalies, limb defects and cleft \nlip had the highest attainment rates, whereas those with congenital hydrocephalus had the lowest. \nChildren with patent ductus arteriosus (PDA), a non-severe heart defect, generally performed worse \nthan children with severe CHD and many non-syndromic CAs at all ages. For syndromic CAs, children \nwith Turner, Klinefelter and Karyotype XXX syndromes began with relatively high attainment rates, but \nthe latter two declined at older ages. Under 1% of children with Down Syndrome achieved expected \nlevels at KS1 and KS2. \n \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n9 \n \nAdjusting for sociodemographic factors, children with CAs were less likely than peers to achieve \nexpected levels in English, (adjusted risk ratio, aRR (95%CI): 0.86 (0.85,0.86) [EYFSP and KS1]; 0.87 \n(0.87,0.88) [KS2]) (Table 4). Similar results were seen for Maths (Table 5). Males were less likely than \nfemales to achieve expected levels, with no variation across CA subgroups (aRR (95%CI): 0.81 (0.81,0.81) \n[EYFSP], 0.91 (0.90,0.91) [KS2] for English; 0.93 (0.92,0.93) [EYFSP], 0.99 (0.99,0.99) [KS2] for Maths).   \n \nThe attainment rates for specific subgroups defined by EUROCAT and alternative codelists differed by \n≤1%, with some exceptions in severe CHD (eTable5). Amongst children with CAs, attainment rates were \nhighest for isolated, followed by multiple then genetic CAs across subjects and ages (eTable6). For the \nsubset of children assessed at all ages, adjusted risk ratios for achieving expected levels, comparing \nchildren with and without CAs, were closer to the null (eTable7, eTable8). \n3.3 | Standardised scores (z-scores) for English and Maths \nOn average, z-scores were lower by 0.36 (EYFSP), 0.39 (KS1) and 0.16 (KS2) points and showed greater \nvariation for children with CAs, compared with peers (eTable9); a unit z-score represented \napproximately 4-6 scale points at EYFSP , 4 points at KS1 and 9 marks at KS2. Differences with peers were \nsmallest for children with renal anomalies, cleft lip and polydactyly. Excepting Klinefelter and Karyotype \nXXX syndromes, mean scores for children with CAs peaked at KS2, although KS2 samples were smaller, \nparticularly for Down Syndrome (3% of EYFSP sample). \n \nEstimated mean z-scores decreased for females and stayed constant for males over time, with \nadjustment for sociodemographic factors having little impact (Table 6). Overall, the gap between \nfemales with and without CAs widened from -0.35 at EYFSP to -0.38 at KS2 for Maths (-0.32 and -0.31 \nrespectively for English). For males, the difference between children with CAs and peers very slightly \nreduced for English and increased for Maths at KS2. Most of the variation was at age 5 rather than in \nsubsequent rates of change (varianceintercept=0.64 [95%CI: 0.64,0.64]; varianceslopes=0.08 [95%CI: \n0.08,0.08]). Figure 3 shows the predicted trajectories stratified by CA (any) and sex, and Figure 4 shows \ntrajectories for selected CAs (sexes combined). \n   \n4 | COMMENT \n4.1 | Principal Findings \nAmongst children with CAs enrolled at age 5, 45% reached GLD overall, with variations by CA subgroup \nand sex. This was 11% fewer than children without CAs, similar to the observed gaps for achieving \nexpected levels in English and Maths at all ages. Proportionally more children with CAs were not \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n10 \n \nassessed at age 11 compared with their peers (11% versus 3%). Adjusting for sociodemographic factors, \nchildren with CAs were on average 12-15% less likely than peers to reach expected attainment. \nAttainment for children with cleft lip, renal and limb anomalies were generally comparable with peers. \n4.2 | Strengths of the study \nHES covers 96.4% of births in England and provided a large sample size for our study.24 Up to 99% of \nNHS-funded hospital admissions were captured, enabling a range of CAs to be studied and compared \nwith significant precision. Linkage to the NPD, containing information on pupils in state-funded schools \n(~93% of total),13 provided insights into the academic journey and potential of children with CAs. Hence \nour findings are representative of a substantial part of the school-age population in England.  \n4.3 | Limitations of the Data \nAbout 14% of total births could not be linked to the NPD, primarily due to the NPD not containing \nindividual-level data on home-schooled children or those attending independent schools. Choices are \nshaped by parents’ preferences and circumstances, although admittedly some may be due to special \neducational needs that cannot be adequately met in state-funded settings. Additional factors include a \ncombination of early exits (births to temporarily-resident mothers or emigration), linkage errors or \nincomplete matching identifiers.25 Given the diverse factors and comparatively small proportion, we \nexpect the net influence on our results to be modest.   \n \nMisclassification of CA status is a limitation. In contrast to CA surveillance registries,26 where cases are \nnotified by care teams and clinically reviewed, case ascertainment using administrative data relies on \napplying phenotype codelists deterministically to diagnosis and procedure codes, recorded primarily for \nreimbursement of healthcare provided. Children with CAs not requiring inpatient care could be missed \n(false negatives), whilst recording of suspected/differential diagnosis codes could generate false \npositives. Our estimated CA prevalence was 1.5% higher than EUROCAT statistics, and although CA \nregistries could under-ascertain CAs, this discrepancy should be examined in future work. Where \navailable, we have used alternative codelists which yielded more conservative prevalences to minimise \nthe false positive rate. This may bias results toward more severe cases, but could help ascertain the \nupper limit of group differences; for selected CAs, attainment rates by alternative methods seemed very \nsimilar.  \n4.4 | Interpretation \nOur aim was to provide evidence on the prognostic attainment trajectories in children with different CAs \nover the first seven years of their educational journey. Attainment rates peaked at KS2 for English and \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n11 \n \nstayed largely constant for Maths, but the gap between children with CAs versus peers remained \nremarkably consistent at 11% lower throughout. The relatively sharp decrease in proportion of children \nwith CAs assessed at KS2 is partially explained by transfers to special schools or disapplication from the \nNational Curriculum after KS1. After controlling for sociodemographic factors, the association between \nCAs and risk of lower attainment was mostly unchanged across key stages. This was also true of children \nwith CAs who sat all assessments, albeit differences with their peers were more attenuated.  \n \nAn earlier cohort (1994-2004) from regional English CA registries linked to the NPD found that 72% and \n73% of children with an isolated CA achieved expected levels in English and Maths at KS2 respectively, 6-\n7% fewer compared to peers.9 Our wider gaps of 11-12% are chiefly attributable to our overall CA group \ncomprising not only isolated but also potential multiple and syndromic CAs, well-established to be \nassociated with lower academic achievement,4 and secondarily to the different denominators used \n(number of children assessed versus enrolled). Once these have been accounted for, our findings are \nmutually reinforcing. This study found that the association of sex with attainment in children with CAs \nbroadly mirrored that of children without CAs, with males performing worse at earlier stages but \nnarrowing the gap with females by KS2 across all CA subgroups, particularly in English.  \n \nOur results also align with those of Park et al. on subject z-scores in children reported to the Cleft \nRegistry and Audit Network.3 Children with cleft lip had the highest scores, followed by those with cleft \nlip and palate, then cleft palate, a pattern which we observed as well. They estimated that children with \nisolated clefts scored up to -0.29 (95% CI: -0.36, -0.22) lower than the national average in English, Maths \nand Science across all ages. Another study of CA cases from a single hospital found that 56-59% and \n62% of children with CAs achieved expected attainment in English and Maths respectively at KS1.4 \nAllowing for differences in study settings and coding of outcome metrics, our findings were largely \ncompatible, which gives assurance regarding the reliability and reproducibility of our results. \n \nA pooled analysis using linked data from CA registries in Europe showed that children with CAs were at \nhigher risk of co-morbidities such as cerebral palsy, seizures, hearing loss and visual impairment \nbetween ages 0-9.27 For example, the prevalence of visual impairment and cerebral palsy was on \naverage 30 and 15 times higher respectively in children with CAs than those without CAs; nervous \nsystem CAs such as hydrocephalus were the most susceptible, but even isolated CHD, cleft palate and \ncongenital hydronephrosis showed elevated rates of seizures, epilepsy and cerebral palsy. This may \npartly explain the unexpected lower attainment seen with some CA subgroups, e.g. PDA.  \n \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n12 \n \nThe current classification of CA subgroups does not fully capture variations in disease severity, in part \ndue to the lack of granularity in the data. Additional factors include unidentified, or unidentifiable given \navailable data, underlying learning or cognitive deficits. A greater proportion of children with CAs \nreceive Special Educational Needs provision compared with their peers,17, 28 but this lies beyond our \ncurrent scope and is being investigated elsewhere within the HOPE programme.29 Yet non-clinical drivers \nfor lower academic achievement should not be overlooked. These may include unconscious bias or \npresuppositions about the academic potential of children with CA, which could predispose to self-\nfulfilling outcomes. Residual confounding by parental and familial factors, the home environment, as \nwell as wider drivers of social disadvantage, are also important to explore in further analyses of ECHILD \ndata.  \n4.5 | Conclusions \nOf those enrolled at age 5 in state-funded schools in England, the proportions who continue to age 11 \nwere similar between children with and without CAs. Children with CAs were however less likely to have \ncurriculum assessments, or to reach expected levels of attainment, at every key stage. Notwithstanding \nsome children with CAs who performed relatively well throughout, a significant minority did not \nparticipate in assessments after age 7. This highlights the need for close monitoring of children in this \ngroup, and for additional support to be provided, starting from an early age. With appropriate \nintervention, more children can be supported to advance the requisite skills and knowledge for \nsecondary school. Some, but not all, of these advances will be measurable through curriculum \nassessments, and Government should consider how to best evaluate the benefits of early support for \nchildren’s development.  \n \n  \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n13 \n \nAcknowledgements \nWe are grateful to all children and families whose de-identified data are used in this research. We thank \nthe Patient and Public representative groups who have helped to develop this study, and the wider \nHOPE study and ECHILD management teams for their support for this work. We acknowledge the \nprevious work by others who had developed methods for coding congenital anomalies cited in this \nstudy, as well as the EUROCAT network and EUROlinkCAT consortium for sharing their expertise and \nadvice. Funding from the NIHR HOPE (Health Outcomes of young People in Education) study, the NIHR \nGreat Ormond Street Hospital Biomedical Research Centre, and Health Data Research UK (grant number \nLOND1), contributed to this work. ECHILD is supported by Administrative Data Research UK and the \nEconomic and Social Research Council (part of UK Research and Innovation) (grant numbers \nES/V000977/1, ES/X003663/1, ES/X000427/1).   \n \nThe education data analysed for this publication have been extracted from the National Pupil Database \n(NPD) which is compiled and owned by the Department for Education (DfE). DfE does not accept \nresponsibility for any inferences or conclusions derived from the DfE Data Extracts by third parties. \nThis work contains statistical data from ONS which is Crown Copyright. The use of the ONS statistical \ndata in this work does not imply the endorsement of the ONS in relation to the interpretation or \nanalysis of the statistical data. This work uses research datasets which may not exactly reproduce \nNational Statistics aggregates. The analysis was carried out in the Secure Research Service, part of the \nOffice for National Statistics. \n \nData Availability \nECHILD data are being made available to accredited researchers for research that benefits the provision \nof healthcare and education in England. Permission to access the ECHILD database is via application to \nthe ECHILD team (ich.echild@ucl.ac.uk). Data can only be processed within the Office for National \nStatistics Secure Research Service by researchers who have undergone training through the Research \nAccreditation Service.  \nCompeting Interests \nThe authors report no conflicting interests. \n \n  \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n14 \n \nREFERENCES \n \n1. National Congenital Anomaly and Rare Disease Registration Service. NCARDRS Congenital \nAnomaly Official Statistics Report, 2021. 2024 [updated 28 Mar 2024; 17 Apr 2024]; Available from: \nhttps://digital.nhs.uk/data-and-information/publications/statistical/ncardrs-congenital-anomaly-\nstatistics-annual-data/ncardrs-congenital-anomaly-statistics-report-2021. \n2. Glinianaia SV, Morris JK, Best KE, Santoro M, Coi A, Armaroli A, Rankin J. Long-term survival of \nchildren born with congenital anomalies: A systematic review and meta-analysis of population-based \nstudies. PLoS Med. 2020; 17:e1003356. \n3. Park MH, Fitzsimons KJ, Deacon S, Medina J, Wahedally MAH, Butterworth S, et al. Longitudinal \neducational attainment among children with isolated oral cleft: a cohort study. 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Low Birth Weight and Congenital Heart Disease: Current Status and \nFuture Directions. The Journal of Pediatrics. 2021; 238:9-10. \n24. Zylbersztejn A, Gilbert R, Hardelid P . Developing a national birth cohort for child health research \nusing a hospital admissions database in England: The impact of changes to data collection practices. \nPLOS ONE. 2020; 15:e0243843. \n25. Libuy N, Harron K, Gilbert R, Caulton R, Cameron E, Blackburn R. Linking education and hospital \ndata in England: linkage process and quality. International Journal of Population Data Science. 2021; 6. \n26. The Global Health Network. Global Birth Defects: Surveillance networks. 2025 [09/06/2025]; \nAvailable from: https://globalbirthdefects.tghn.org/resources-inventory/Surveillance-networks/. \n27. Urhoj SK, Morris J, Loane M, Ballardini E, Barrachina-Bonet L, Cavero-Carbonell C, et al. 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CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n16 \n \nTABLES \nTable 1: Birth prevalence and number included in study, by congenital anomaly (CA) subgroup and \nmalformation type \nsubgroup Number \nof cases \nin HES \nBirth \nprevalence \n(per \n10,000) \nEnrolled in \nReception \nMALFORMATION TYPEa \nIsolated Potential \nmultiple \nGenetic, \nchromosomal \nor other \nAny CA  105,514  346.8  78,847  71.5% 8.2% 20.3% \nNeural Tube Defects  833  2.7  510  53.9% 42.5% 3.5% \nHydrocephalus  1,180  3.9  701  55.6% 39.2% 5.1% \nCongenital Cataract  614  2.0  470  81.3% 11.5% 7.2% \nCongenital Heart Defects (CHD)  23,792  78.2  15,852  71.7% 16.1% 12.2% \nVentricular Septal Defect \nwithout severe CHD \n 5,075  16.7  3,673  71.6% 14.6% 13.8% \nPulmonary Valve Stenosis \nwithout severe CHD \n 702  2.3  546  78.6% 11.9% 9.5% \nPDA as only CHD in term \ninfants \n 4,442  14.6  2,611  79.2% 15.3% 5.5% \nSevere CHD  6,630  21.8  4,283  69.8% 14.0% 16.2% \nAtrioventricular Septal Defect  1,398  4.6  832  40.5% 11.5% 48.0% \nTetralogy of Fallot  1,162  3.8  826  63.9% 17.9% 18.2% \nHypoplastic Left Heart  707  2.3  271  78.6% 15.1% 6.3% \nRespiratory  2,187  7.2  1,405  52.2% 39.6% 8.2% \nOrofacial clefts       \nCleft Lip  1,117  3.7  982  87.0% 10.7% 2.3% \nCleft Palate  1,906  6.3  1,653  62.6% 11.9% 25.6% \nCleft Lip and Palate  1,592  5.2  1,378  78.8% 14.9% 6.2% \nDigestive System  7,692  25.3  5,433  55.3% 35.9% 8.7% \nAnorectal Malformations  1,021  3.4  780  25.5% 58.8% 15.6% \nHirschsprung's Disease  730  2.4  602  75.4% 15.3% 9.3% \nGastroschisis  1,240  4.1  961  83.1%  **   <1.0%  \nUnilateral Renal Agenesis  583  1.9  453  71.3% 22.5% 6.2% \nCongenital Hydronephrosis  5,129  16.9  3,973  88.9% 8.4% 2.7% \nHypospadias  5,118  16.8  4,329  76.3% 9.6% 14.2% \nClub Foot - Talipes Equinovarus  3,328  10.9  2,565  86.3% 10.4% 3.3% \nPolydactyly  5,129  16.9  4,027  86.4% 6.4% 7.2% \nSyndactyly  2,432  8.0  1,918  80.6% 13.6% 5.8% \nCraniosynostosis  934  3.1  766  68.7% 16.4% 14.9% \nChromosomal Anomalies       \nDown Syndrome  3,023  9.9  2,134  -     -    100.0% \nTurner Syndrome  190  0.6  135   -     -    100.0% \nKlinefelter Syndrome  89  0.3  73   -     -    100.0% \nDi George Syndrome  198  0.7  136   -     -    100.0% \nKaryotype XXX  55  0.2  40   -     -    100.0% \nCA: congenital anomaly; CHD: congenital heart defect; HES: Hospital Episode Statistics; PDA: patent ductus \narteriosus. \na as percentage of children included in study \n** not presented due to suppressed quantity in adjoining cell  \n- not applicable \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n17 \n \nTable 2: Distribution of sociodemographic characteristics by congenital anomaly (CA) status \n  No CA, n (%) Any CA, n (%) All, n (%) \nTOTAL  2,272,742 (100.0) 78,847 (100.0) 2,351,589 (100.0) \nYear of birth 2003/04 421,195 (18.5) 14,483 (18.4) 435,678 (18.5) \n 2004/05 445,480 (19.6) 15,311 (19.4) 460,791 (19.6) \n 2005/06 459,846 (20.2) 15,920 (20.2) 475,766 (20.2) \n 2006/07 470,683 (20.7) 16,283 (20.6) 486,966 (20.7) \n 2007/08 475,538 (20.9) 16,850 (21.4) 492,388 (20.9) \n     \nSex at birth Male 1,160,586 (51.1) 47,101 (59.7) 1,207,687 (51.4) \n Female 1,112,156 (48.9) 31,746 (40.3) 1,143,902 (48.6) \n     \nGestational Age, \nweeks \n<32 10,687 (0.5) 1,965 (2.5) 12,652 (0.5) \n32-38 75,302 (3.3) 4,802 (6.1) 80,104 (3.4) \n37-41 1,355,335 (59.6) 41,817 (53.0) 1,397,152 (59.4) \n42+ 69,391 (3.0) 1,944 (2.5) 71,335 (3.0) \nMissing 762,027 (33.5) 28,319 (35.9) 790,346 (33.6) \n     \nBirthweight, \ngrams \n<2500 96,228 (4.2) 8,696 (11.0) 104,924 (4.5) \n2500-3999 1,453,552 (64.0) 44,758 (56.8) 1,498,310 (63.7) \n4000+ 201,694 (8.9) 5,890 (7.5) 207,584 (8.8) \nMissing 521,268 (22.9) 19,503 (24.7) 540,771 (23.0) \n     \nMaternal Age at birth, years \n<20 155,599 (6.8) 5,627 (7.1) 161,226 (6.9) \n20-29 1,009,114 (44.4) 34,321 (43.5) 1,043,435 (44.4) \n30-34 610,174 (26.9) 20,047 (25.4) 630,221 (26.8) \n35-39 340,290 (15.0) 11,739 (14.9) 352,029 (15.0) \n40+ 69,898 (3.1) 2,902 (3.7) 72,800 (3.1) \nMissing 87,667 (3.9) 4,211 (5.3) 91,878 (3.9) \n     \nMajor Ethnic Group \nWhite 1,611,153 (70.9) 54,834 (69.5) 1,665,987 (70.8) \nBlack 104,737 (4.6) 3,833 (4.9) 108,570 (4.6) \nAsian/Chinese 200,567 (8.8) 7,765 (9.9) 208,332 (8.9) \nMixed 106,556 (4.7) 3,668 (4.7) 110,224 (4.7) \nOther 26,943 (1.2) 853 (1.1) 27,796 (1.2) \nUnclassified 222,786 (9.8) 7,894 (10.0) 230,680 (9.8) \n     \nIncome Deprivation \nAffecting Children Index \n(IDACI) Quintile \nMost Deprived 596,343 (26.2) 21,685 (27.5) 618,028 (26.3) \n2nd most deprived 473,994 (20.9) 16,706 (21.2) 490,700 (20.9) \nMiddle  417,944 (18.4) 14,267 (18.1) 432,211 (18.4) \n2nd least deprived 398,665 (17.5) 13,195 (16.7) 411,860 (17.5) \nLeast deprived 378,084 (16.6) 12,702 (16.1) 390,786 (16.6) \nMissing 7,712 (0.3) 292 (0.4) 8,004 (0.3) \n     \nFree School Meals \nEligibility (FSME) \nNo 1,859,308 (81.8) 63,082 (80.0) 1,922,390 (81.8) \nYes 413,434 (18.2) 15,765 (20.0) 429,199 (18.2) \n     \nRegion \nEast Midlands 197,047 (8.7) 7,853 (10.0) 204,900 (8.7) \nEast of England 250,776 (11.0) 7,096 (9.0) 257,872 (11.0) \nLondon 349,531 (15.4) 9,686 (12.3) 359,217 (15.3) \nNorth East 117,115 (5.2) 4,045 (5.1) 121,160 (5.2) \nNorth West 295,778 (13.0) 12,263 (15.6) 308,041 (13.1) \nSouth East 357,730 (15.7) 12,175 (15.4) 369,905 (15.7) \nSouth West 218,526 (9.6) 7,480 (9.5) 226,006 (9.6) \nWest Midlands 231,208 (10.2) 10,675 (13.5) 241,883 (10.3) \nYorkshire and The Humber 247,535 (10.9) 7,286 (9.2) 254,821 (10.8) \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n18 \n \nMissing 7,496 (0.3) 288 (0.4) 7,784 (0.3) \nCA: congenital anomaly; FSME: Free School Meals Eligibility; IDACI: Income Deprivation Affecting Children Index\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n19 \n \nTable 3: Number of children enrolled, % assessed and % who reached expected level of attainment by Key Stage, subject and congenital anomaly (CA) \nsubgroup.  \n \nEYFSP KS1 KS2 \n  \nN in census English Maths \nN in census English Maths \nN in census English Maths \nsubgroup \n% assessed \n% expected \n% assessed \n% expected \n% assessed \n% expected \n% assessed \n% expected \n% assessed \n% expected \n% assessed \n% expected \nAll Children 2,351,589 99.3 68.2 99.3 78.1 2,319,460 99.2 66.6 99.1 78.4 2,257,545 96.9 75.9 97.0 77.4 \nNo CA 2,272,742 99.3 68.6 99.3 78.5 2,241,658 99.2 67.0 99.2 78.8 2,181,797 97.2 76.3 97.3 77.8 \nAny CA 78,847 99.1 56.9 99.1 67.6 77,802 98.9 55.4 98.6 66.8 75,748 88.7 65.3 88.6 66.4 \nNeural Tube Defects 275 98.5 50.2 98.5 63.3 272 99.6 54.0 98.9 59.9 266 85.0 59.8 84.6 57.9 \nHydrocephalus 390 97.9 31.0 97.9 39.5 386 97.9 29.3 96.9 36.8 374 61.0 36.9 61.0 35.6 \nCongenital Cataract 382 99.0 58.9 99.0 70.9 377 99.5 57.6 99.5 69.2 363 89.3 67.5 90.4 67.2 \nCongenital Heart Defects (CHD) 11,368 99.2 54.2 99.2 65.3 11,222 98.8 52.3 98.6 63.3 10,925 89.8 62.9 89.7 62.6 \nVentricular Septal Defect* 2,631 99.2 59.9 99.2 70.7 2,597 99.1 57.7 99.0 68.7 2,538 91.9 68.4 91.6 68.3 \nPulmonary Valve Stenosis* 429 99.1 53.8 99.1 66.0 422 99.3 55.0 99.1 64.5 413 91.3 64.4 91.5 60.8 \nPDA as only CHD in term \ninfants 2,068 98.9 49.4 98.9 60.7 2,047 98.5 47.8 98.3 57.4 2,001 88.6 61.1 87.9 56.5 \nSevere CHD 2,991 99.3 54.6 99.3 66.2 2,946 98.9 51.4 98.6 63.4 2,854 88.7 60.4 89.0 62.9 \nAtrioventricular Septal Defect 337 99.1 54.6 99.1 65.0 329 99.1 52.0 99.1 61.7 323 88.2 55.7 87.9 58.2 \nTetralogy of Fallot 528 100.0 55.1 100.0 67.4 517 99.0 51.8 98.8 62.9 501 88.8 61.3 89.6 65.7 \nHypoplastic Left Heart 213 98.1 41.3 98.1 56.3 208 98.1 39.9 98.1 51.0 196 82.7 51.5 80.6 47.4 \nRespiratory 734 98.8 52.2 98.8 63.6 723 98.6 52.3 98.6 63.2 706 89.0 62.2 89.2 63.2 \nCleft Lip  854 99.1 61.4 99.1 73.5 837 99.5 61.6 99.3 72.8 817 94.5 70.0 95.3 75.3 \nCleft Palate  1,034 99.8 54.6 99.8 66.1 1,023 99.6 53.3 99.4 64.5 1,001 91.4 65.3 92.5 65.4 \nCleft Lip and Palate  1,086 99.4 54.3 99.4 66.9 1,075 99.3 52.3 99.2 67.3 1,048 93.0 64.6 94.1 66.6 \nDigestive System 3,007 99.3 60.2 99.3 72.0 2,977 99.5 59.4 99.4 72.1 2,901 93.5 69.8 93.4 71.3 \nAnorectal Malformations  199 99.0 57.8 99.0 68.8 196 99.5 59.2 99.5 69.9 192 91.7 70.8 93.2 69.3 \nHirschsprung's Disease 454 99.6 59.7 99.6 73.6 448 99.6 58.0 99.3 72.8 437 93.1 69.6 92.7 71.9 \nGastroschisis 799 99.1 57.6 99.1 68.1 795 99.2 54.2 99.1 66.7 784 96.0 65.6 96.2 67.0 \nUnilateral Renal Agenesis 323 98.1 61.6 98.1 73.7 316 98.4 66.5 98.4 77.2 312 93.3 66.3 93.6 72.8 \nCongenital Hydronephrosis 3,532 99.4 64.2 99.4 75.5 3,479 99.0 61.3 98.9 77.5 3,392 95.7 74.1 95.9 76.4 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n20 \n \nHypospadias  3,302 99.2 57.8 99.2 71.8 3,265 99.2 55.5 99.2 73.8 3,195 94.3 69.5 94.5 74.2 \nClub Foot - Talipes Equinovarus 2,213 99.2 63.4 99.2 74.3 2,185 99.4 61.0 99.4 73.9 2,119 94.6 71.1 94.9 73.0 \nPolydactyly 3,480 99.2 63.0 99.2 74.3 3,433 99.1 63.2 99.1 74.2 3,345 95.0 72.5 95.0 74.1 \nSyndactyly 1,545 99.7 64.3 99.7 75.2 1,527 99.0 62.3 98.8 75.4 1,477 95.3 72.5 95.2 74.0 \nCraniosynostosis 526 99.2 60.5 99.2 73.0 516 99.0 57.6 98.6 69.4 502 91.6 69.1 91.4 68.5 \nDown Syndrome 2,134 97.4 2.7 97.4 4.0 2,113 95.1 0.7 91.7 0.7 2,083 3.2 0.9 2.9 0.7 \nTurner Syndrome 115 100.0 42.6 100.0 47.0 114 100.0 44.7 99.1 38.6 112 80.4 54.5 77.7 40.2 \nKlinefelter Syndrome 72 100.0 40.3 100.0 66.7 72 100.0 26.4 100.0 44.4 69 75.4 27.5 76.8 36.2 \nDi George Syndrome 136 98.5 8.8 98.5 10.3 135 97.0 - 96.3 - 132 39.4 - 37.1 - \nKaryotype XXX 40 97.5 60.0 97.5 65.0 39 100.0 30.8 100.0 48.7 39 87.2 38.5 87.2 35.9 \nCHD=congenital heart defect; GLD=Good Level of Development; EYFSP=Early Years Foundation Stage Profile; KS1=Key Stage 1; KS2=Key Stage 2; PDA=patent ductus \narteriosus \n* without co-occurring severe CHD \n- suppressed due to small counts \n% assessed = percentage of those in census who had an assessment \n% expected = percentage of those in census who reached expected level of attainment \n \n  \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n21 \n \nTable 4: Adjusted risk ratios for reaching expected levels of attainment in English, comparing children with and without congenital anomalies (CAs), by key \nstage and CA subgroup. For each comparison, number of children without CAs=2,177,654 \n  EYFSP KS1 KS2 \nsubgroup Cases, N \nRR (95%CI) \nSex adj. \nRR (95%CI) \nFull adj. \nRR (95%CI) \nSex adj. \nRR (95%CI) \nFull adj. \nRR (95%CI) \nSex adj. \nRR (95%CI) \nFull adj. \nAny CA 74,357 0.85 (0.84,0.86) 0.86 (0.85,0.86) 0.85 (0.84,0.85) 0.85 (0.85,0.86) 0.87 (0.86,0.87) 0.87 (0.87,0.88) \nNeural Tube Defects 248 0.73 (0.65,0.83) 0.77 (0.68,0.86) 0.80 (0.71,0.90) 0.83 (0.74,0.94) 0.81 (0.73,0.89) 0.83 (0.75,0.92) \nHydrocephalus 362 0.47 (0.41,0.55) 0.49 (0.42,0.57) 0.46 (0.40,0.54) 0.48 (0.41,0.56) 0.51 (0.44,0.58) 0.52 (0.45,0.59) \nCongenital Cataract 362 0.85 (0.78,0.93) 0.86 (0.79,0.93) 0.86 (0.78,0.93) 0.86 (0.79,0.94) 0.87 (0.81,0.94) 0.88 (0.81,0.94) \nCongenital Heart Defects (CHD) 10,216 0.81 (0.79,0.82) 0.82 (0.80,0.83) 0.80 (0.78,0.81) 0.81 (0.79,0.82) 0.83 (0.82,0.84) 0.84 (0.83,0.85) \nVentricular Septal Defect 2,498 0.88 (0.85,0.91) 0.89 (0.86,0.92) 0.86 (0.83,0.89) 0.87 (0.84,0.90) 0.91 (0.88,0.93) 0.91 (0.89,0.94) \nPulmonary Valve Stenosis 397 0.78 (0.71,0.85) 0.78 (0.71,0.85) 0.81 (0.74,0.89) 0.82 (0.75,0.89) 0.85 (0.79,0.92) 0.86 (0.79,0.92) \nPDA as only CHD in term infants 1,610 0.74 (0.71,0.78) 0.76 (0.72,0.79) 0.74 (0.71,0.78) 0.76 (0.72,0.80) 0.82 (0.79,0.85) 0.83 (0.80,0.86) \nSevere CHD 2,763 0.81 (0.79,0.84) 0.82 (0.79,0.85) 0.79 (0.77,0.82) 0.80 (0.77,0.83) 0.80 (0.77,0.82) 0.80 (0.78,0.83) \nAtrioventricular Septal Defect 320 0.81 (0.73,0.89) 0.82 (0.75,0.90) 0.77 (0.70,0.86) 0.79 (0.71,0.87) 0.74 (0.67,0.82) 0.75 (0.68,0.83) \nTetralogy of Fallot 506 0.82 (0.76,0.89) 0.83 (0.77,0.90) 0.79 (0.73,0.86) 0.79 (0.73,0.86) 0.81 (0.75,0.87) 0.81 (0.75,0.87) \nHypoplastic Left Heart 194 0.62 (0.53,0.73) 0.65 (0.55,0.76) 0.62 (0.52,0.73) 0.64 (0.54,0.76) 0.66 (0.57,0.76) 0.67 (0.58,0.78) \nRespiratory 665 0.78 (0.72,0.83) 0.79 (0.73,0.84) 0.79 (0.73,0.85) 0.80 (0.74,0.86) 0.82 (0.77,0.87) 0.82 (0.77,0.87) \nCleft Lip  825 0.92 (0.87,0.97) 0.93 (0.88,0.98) 0.95 (0.90,1.00) 0.96 (0.91,1.01) 0.93 (0.89,0.98) 0.94 (0.90,0.99) \nCleft Palate  989 0.79 (0.75,0.84) 0.80 (0.76,0.84) 0.79 (0.75,0.84) 0.80 (0.76,0.85) 0.87 (0.83,0.91) 0.87 (0.83,0.91) \nCleft Lip and Palate  1,044 0.81 (0.77,0.86) 0.83 (0.78,0.87) 0.81 (0.77,0.86) 0.83 (0.78,0.88) 0.86 (0.82,0.91) 0.87 (0.83,0.92) \nDigestive System 2,748 0.88 (0.85,0.91) 0.89 (0.86,0.91) 0.90 (0.88,0.93) 0.91 (0.88,0.94) 0.92 (0.90,0.95) 0.93 (0.90,0.95) \nAnorectal Malformations  172 0.85 (0.75,0.97) 0.86 (0.76,0.97) 0.94 (0.83,1.05) 0.94 (0.84,1.06) 0.95 (0.86,1.05) 0.95 (0.86,1.05) \nHirschsprung's Disease 411 0.93 (0.86,1.00) 0.94 (0.87,1.01) 0.92 (0.85,1.00) 0.93 (0.86,1.01) 0.94 (0.87,1.00) 0.94 (0.88,1.01) \nGastroschisis 705 0.83 (0.78,0.88) 0.92 (0.87,0.98) 0.81 (0.76,0.87) 0.92 (0.86,0.99) 0.87 (0.82,0.92) 0.94 (0.89,0.99) \nUnilateral Renal Agenesis 304 0.93 (0.85,1.02) 0.94 (0.86,1.02) 1.03 (0.95,1.11) 1.04 (0.96,1.12) 0.89 (0.82,0.97) 0.90 (0.82,0.97) \nCongenital Hydronephrosis 3,405 0.98 (0.96,1.01) 0.97 (0.95,1.00) 0.97 (0.94,0.99) 0.96 (0.93,0.98) 1.00 (0.98,1.02) 0.99 (0.97,1.01) \nHypospadias  3,170 0.94 (0.91,0.97) 0.94 (0.92,0.97) 0.94 (0.91,0.97) 0.94 (0.91,0.97) 0.97 (0.94,0.99) 0.97 (0.95,0.99) \nClub Foot - Talipes Equinovarus 2,145 0.94 (0.91,0.97) 0.94 (0.91,0.97) 0.93 (0.90,0.96) 0.93 (0.90,0.97) 0.94 (0.91,0.97) 0.94 (0.91,0.97) \nPolydactyly 3,352 0.93 (0.91,0.95) 0.96 (0.94,0.99) 0.96 (0.93,0.98) 0.97 (0.95,1.00) 0.96 (0.94,0.98) 0.97 (0.95,0.99) \nSyndactyly 1,504 0.97 (0.93,1.00) 0.95 (0.91,0.98) 0.97 (0.93,1.01) 0.96 (0.92,0.99) 0.96 (0.93,1.00) 0.96 (0.93,0.99) \nCraniosynostosis 502 0.90 (0.84,0.97) 0.89 (0.83,0.95) 0.87 (0.81,0.94) 0.86 (0.80,0.93) 0.91 (0.86,0.97) 0.90 (0.85,0.96) \nDown Syndrome 1,992 0.04 (0.03,0.05) 0.04 (0.03,0.05) 0.01 (0.01,0.02) 0.01 (0.01,0.02) 0.02 (0.01,0.03) 0.02 (0.01,0.03) \nTurner Syndrome 125 0.52 (0.42,0.65) 0.52 (0.42,0.64) 0.55 (0.44,0.68) 0.55 (0.44,0.68) 0.63 (0.53,0.76) 0.63 (0.53,0.76) \nKlinefelter Syndrome 69 0.66 (0.49,0.87) 0.63 (0.47,0.83) 0.42 (0.28,0.63) 0.40 (0.27,0.61) 0.37 (0.25,0.56) 0.36 (0.24,0.54) \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n22 \n \nDi George Syndrome 126 0.15 (0.09,0.25) 0.15 (0.09,0.26) 0.10 (0.05,0.19) 0.10 (0.05,0.19) 0.12 (0.07,0.21) 0.12 (0.07,0.21) \nKaryotype XXX 36 0.81 (0.62,1.05) 0.74 (0.57,0.96) 0.38 (0.22,0.64) 0.35 (0.21,0.59) 0.47 (0.30,0.72) 0.44 (0.29,0.69) \nCA=congenital anomaly; CI=confidence interval; EYFSP=Early Years Foundation Stage Profile; KS1=Key Stage 1; KS2=Key Stage 2; PDA=patent ductus \narteriosus; RR=risk ratio; Sex adj.= adjusted for sex at birth; Full adj.=adjusted for sex, maternal age at birth, ethnicity, income deprivation affecting children \nindex (IDACI) quintile, free school meals eligibility (FSME) \n \n  \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n23 \n \nTable 5: Adjusted risk ratios for reaching expected levels of attainment in Maths, comparing children with and without congenital anomalies (CAs), by key \nstage and CA subgroup. For each comparison, number of children without CAs=2,177,654 \n  EYFSP KS1 KS2 \nsubgroup Cases, N \nRR (95%CI) \nSex adj. \nRR (95%CI) \nFull adj. \nRR (95%CI) \nSex adj. \nRR (95%CI) \nFull adj. \nRR (95%CI) \nSex adj. \nRR (95%CI) \nFull adj. \nAny CA 74,357 0.87 (0.87,0.88) 0.88 (0.87,0.88) 0.86 (0.85,0.86) 0.86 (0.86,0.86) 0.86 (0.85,0.86) 0.86 (0.86,0.87) \nNeural Tube Defects 248 0.81 (0.74,0.89) 0.84 (0.76,0.92) 0.78 (0.70,0.86) 0.80 (0.72,0.88) 0.76 (0.68,0.85) 0.78 (0.70,0.86) \nHydrocephalus 362 0.52 (0.46,0.59) 0.53 (0.47,0.60) 0.49 (0.43,0.55) 0.50 (0.44,0.57) 0.47 (0.41,0.54) 0.48 (0.42,0.55) \nCongenital Cataract 362 0.89 (0.84,0.96) 0.90 (0.85,0.96) 0.88 (0.82,0.94) 0.88 (0.82,0.94) 0.85 (0.79,0.92) 0.85 (0.79,0.92) \nCongenital Heart Defects (CHD) 10,216 0.85 (0.83,0.86) 0.86 (0.84,0.87) 0.81 (0.80,0.82) 0.82 (0.81,0.83) 0.82 (0.80,0.83) 0.82 (0.81,0.84) \nVentricular Septal Defect 2,498 0.91 (0.88,0.93) 0.91 (0.89,0.93) 0.88 (0.85,0.90) 0.88 (0.86,0.91) 0.89 (0.86,0.91) 0.89 (0.87,0.92) \nPulmonary Valve Stenosis 397 0.84 (0.78,0.90) 0.84 (0.79,0.90) 0.81 (0.75,0.87) 0.81 (0.76,0.88) 0.77 (0.71,0.84) 0.78 (0.71,0.84) \nPDA as only CHD in term infants 1,610 0.79 (0.76,0.82) 0.81 (0.78,0.84) 0.76 (0.73,0.79) 0.77 (0.74,0.80) 0.76 (0.73,0.79) 0.77 (0.73,0.80) \nSevere CHD 2,763 0.86 (0.83,0.88) 0.86 (0.84,0.88) 0.81 (0.78,0.83) 0.81 (0.79,0.83) 0.81 (0.79,0.83) 0.81 (0.79,0.84) \nAtrioventricular Septal Defect 320 0.83 (0.77,0.90) 0.85 (0.78,0.91) 0.79 (0.72,0.86) 0.80 (0.73,0.87) 0.76 (0.69,0.84) 0.77 (0.70,0.84) \nTetralogy of Fallot 506 0.87 (0.82,0.92) 0.88 (0.83,0.93) 0.80 (0.75,0.85) 0.80 (0.75,0.86) 0.84 (0.79,0.90) 0.84 (0.79,0.90) \nHypoplastic Left Heart 194 0.72 (0.64,0.81) 0.74 (0.65,0.83) 0.66 (0.57,0.75) 0.67 (0.59,0.77) 0.61 (0.52,0.71) 0.62 (0.53,0.72) \nRespiratory 665 0.81 (0.77,0.86) 0.82 (0.78,0.87) 0.80 (0.75,0.85) 0.81 (0.76,0.86) 0.81 (0.76,0.86) 0.81 (0.76,0.86) \nCleft Lip  825 0.95 (0.91,0.99) 0.95 (0.91,0.99) 0.92 (0.88,0.96) 0.93 (0.89,0.97) 0.97 (0.93,1.01) 0.98 (0.94,1.02) \nCleft Palate  989 0.84 (0.81,0.88) 0.85 (0.81,0.88) 0.82 (0.78,0.86) 0.82 (0.79,0.86) 0.86 (0.82,0.90) 0.86 (0.82,0.90) \nCleft Lip and Palate  1,044 0.86 (0.83,0.90) 0.87 (0.84,0.91) 0.87 (0.83,0.91) 0.88 (0.84,0.91) 0.87 (0.83,0.91) 0.88 (0.84,0.92) \nDigestive System 2,748 0.92 (0.90,0.94) 0.93 (0.91,0.95) 0.92 (0.90,0.94) 0.93 (0.91,0.95) 0.92 (0.90,0.95) 0.93 (0.90,0.95) \nAnorectal Malformations  172 0.90 (0.82,0.99) 0.90 (0.82,0.99) 0.90 (0.82,1.00) 0.90 (0.82,1.00) 0.91 (0.82,1.01) 0.91 (0.82,1.01) \nHirschsprung's Disease 411 0.95 (0.90,1.01) 0.96 (0.91,1.02) 0.95 (0.89,1.00) 0.95 (0.90,1.01) 0.93 (0.87,0.99) 0.94 (0.88,1.00) \nGastroschisis 705 0.87 (0.83,0.92) 0.94 (0.90,0.99) 0.85 (0.80,0.89) 0.91 (0.87,0.96) 0.87 (0.82,0.92) 0.94 (0.89,0.99) \nUnilateral Renal Agenesis 304 0.95 (0.89,1.02) 0.96 (0.89,1.02) 0.98 (0.92,1.04) 0.98 (0.92,1.05) 0.94 (0.88,1.01) 0.95 (0.88,1.02) \nCongenital Hydronephrosis 3,405 0.98 (0.96,1.00) 0.97 (0.96,0.99) 0.99 (0.97,1.01) 0.99 (0.97,1.01) 0.99 (0.97,1.01) 0.98 (0.96,1.00) \nHypospadias  3,170 0.95 (0.93,0.97) 0.95 (0.93,0.97) 0.96 (0.94,0.98) 0.96 (0.94,0.98) 0.97 (0.95,0.99) 0.97 (0.95,0.99) \nClub Foot - Talipes Equinovarus 2,145 0.95 (0.93,0.98) 0.95 (0.93,0.97) 0.95 (0.92,0.97) 0.95 (0.93,0.97) 0.94 (0.91,0.96) 0.94 (0.91,0.97) \nPolydactyly 3,352 0.95 (0.93,0.97) 0.98 (0.96,1.00) 0.94 (0.93,0.96) 0.97 (0.95,0.99) 0.95 (0.93,0.97) 0.96 (0.94,0.98) \nSyndactyly 1,504 0.97 (0.94,1.00) 0.95 (0.93,0.98) 0.97 (0.94,1.00) 0.96 (0.93,0.98) 0.95 (0.92,0.98) 0.95 (0.92,0.98) \nCraniosynostosis 502 0.94 (0.89,0.99) 0.92 (0.88,0.97) 0.87 (0.82,0.93) 0.86 (0.82,0.92) 0.86 (0.81,0.92) 0.86 (0.81,0.92) \nDown Syndrome 1,992 0.05 (0.04,0.06) 0.05 (0.04,0.06) 0.01 (0.01,0.02) 0.01 (0.01,0.02) 0.01 (0.01,0.02) 0.01 (0.01,0.02) \nTurner Syndrome 125 0.57 (0.47,0.68) 0.56 (0.47,0.68) 0.46 (0.36,0.58) 0.46 (0.36,0.58) 0.47 (0.37,0.59) 0.47 (0.37,0.60) \nKlinefelter Syndrome 69 0.88 (0.75,1.04) 0.85 (0.72,1.00) 0.55 (0.42,0.73) 0.54 (0.41,0.71) 0.47 (0.34,0.65) 0.46 (0.34,0.64) \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n24 \n \nDi George Syndrome 126 0.17 (0.11,0.27) 0.17 (0.11,0.27) 0.11 (0.06,0.20) 0.11 (0.06,0.20) 0.11 (0.06,0.19) 0.11 (0.06,0.19) \nKaryotype XXX 36 0.82 (0.65,1.03) 0.77 (0.61,0.95) 0.59 (0.42,0.84) 0.57 (0.40,0.80) 0.44 (0.28,0.70) 0.43 (0.27,0.68) \nCA=congenital anomaly; CI=confidence interval; EYFSP=Early Years Foundation Stage Profile; KS1=Key Stage 1; KS2=Key Stage 2; PDA=patent ductus \narteriosus; RR=risk ratio; Sex adj.= adjusted for sex at birth; Full adj.=adjusted for sex, maternal age at birth, ethnicity, income deprivation affecting children \nindex (IDACI) quintile, free school meals eligibility (FSME) \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n25 \n \nTable 6: Mean differences in standardised English and Maths scores by sex and congenital anomaly \n(CA) status estimated by linear mixed models using all children with CAs and 25% sample of children \nwithout CAs. \nEnglish (total individuals 617,462) \n  \nEYFSP KS1 KS2 \nUnadjusted \nFemale No CA 0 0.01 (0.00, 0.01) -0.10 (-0.11, -0.10) \n Any CA -0.33 (-0.34, -0.32) -0.33 (-0.34, -0.32) -0.43 (-0.44, -0.42) \nMale No CA -0.34 (-0.34, -0.33) -0.32 (-0.32, -0.31) -0.34 (-0.35, -0.34) \nAny CA -0.67 (-0.68, -0.66) -0.65 (-0.66, -0.65) -0.67 (-0.68, -0.66) \nAdjusted for maternal age, ethnicity, IDACI quintile and FSME \nFemale No CA 0 0.01 (0.00, 0.01) -0.10 (-0.11, -0.10)  \nAny CA -0.32 (-0.33, -0.31) -0.32 (-0.33, -0.31) -0.41 (-0.42, -0.40) \nMale No CA -0.34 (-0.34, -0.33) -0.32 (-0.32, -0.31) -0.34 (-0.35, -0.34) \nAny CA -0.66 (-0.66, -0.65) -0.64 (-0.65, -0.63) -0.65 (-0.66, -0.64) \n \nMaths (total individuals 617,463) \n  \nEYFSP KS1 KS2 \nUnadjusted \nFemale No CA 0 -0.05 (-0.06, -0.05) -0.15 (-0.15, -0.15) \n Any CA -0.35 (-0.36, -0.34) -0.44 (-0.44, -0.43) -0.53 (-0.54, -0.52) \nMale No CA -0.12 (-0.13, -0.12) -0.06 (-0.07, -0.06) -0.10 (-0.11, -0.10) \nAny CA -0.47 (-0.48, -0.46) -0.44 (-0.45, -0.43) -0.48 (-0.49, -0.47) \nAdjusted for maternal age, ethnicity, IDACI quintile and FSME \nFemale No CA 0 -0.05 (-0.06, -0.05) -0.15 (-0.15, -0.15)  \nAny CA -0.34 (-0.35, -0.33) -0.42 (-0.43, -0.41) -0.51 (-0.52, -0.50) \nMale No CA -0.12 (-0.13, -0.12) -0.06 (-0.07, -0.06) -0.11 (-0.11, -0.10) \nAny CA -0.46 (-0.47, -0.45) -0.43 (-0.44, -0.42) -0.47 (-0.48, -0.46) \nCA = congenital anomaly; EYFSP=Early Years Foundation Stage Profile; FSME=Free school meals \neligibility; IDACI=Income deprivation affecting children index; KS1=Key Stage 1; KS2=Key Stage 2 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n26 \n \n \n  \nTotal births in Hospital Episode Statistics\n01/09/2003 to 31/08/2008\nN=3,042,909 \nNon-singleton (multiple) births\nn=88,005 (2.9%)Deaths before 4th birthday\nn=14,832 (0.5%)\nNot linked to National Pupil Database at \nanytime\nn=421,066 (13.8%)Not enrolled in Reception Census\nn=167,417 (5.5%)\nIncluded in study\nn=2,351,589 (77.3%)\nFigure 1: Flowchart showing starting population, exclusions and final numbers included in study\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n27 \n \nFigure 2: Percentage achieving Good Level of Development (GLD) at EYFSP , by sex and CA subgroup. Dashed lines \nrepresent values for children without CAs (blue=male; red=female)\n* without co-occurring severe CHD; Di George syndrome not shown due to small counts.\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n28 \n \n \n  \nFigure 3: Estimated trajectories of English and Maths mean z-scores by categories of CA status and sex using linear mixed effects regression. Plots\nconstructed using modal values of other adjusted covariates (maternal age: 20-29 years; ethnicity: White; IDACI quintile: 3rd quintile (middle); FSME: No)\nCA=congenital anomaly; EYFSP=Early Years Foundation Stage Profile; FSME=Free School Meals Eligibility; IDACI=Income Deprivation Affecting Children Index; KS1=Key \nStage 1; KS2=Key Stage 2\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint \n\n29 \n \n \nFigure 4: Estimated trajectories of mean standardised scores and 95% confidence intervals for English (top row) and Maths (bottom row),\ncomparing children without CA (blue) and those with selected CAs (red). Plotted using average values of adjusted covariates (sex, maternal\nage, ethnicity, IDACI quintile and FSME).\nCA=congenital anomaly; EYFSP=Early Years Foundation Stage Profile; FSME=Free School Meals Eligibility; IDACI=Income Deprivation Affecting Children Index; KS1=Key \nStage 1; KS2=Key Stage 2\n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprintthis version posted June 22, 2025. ; https://doi.org/10.1101/2025.06.21.25329922doi: medRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}