The study team used the Secure Anonymised Information Linkage (SAIL) Databank to connect routine health and education records for children born in Wales between 1998 and 2007, followed through to the end of 2019. The investigators identified children with major congenital anomalies using EUROCAT ICD-10 coding; coding of medicines and comorbidities used publicly documented phenotype libraries. Logistic regression models examined attainment at key stages 2 and 4 (ages 11 and 16), and the models adjusted for maternal and child socioeconomic deprivation, medicated long-term conditions, hospitalisation, gestational age, child sex, birth year, and recorded special education needs (SEN) provision. The study reported raw proportions and both unadjusted and adjusted odds ratios with 95% confidence intervals, and included subgroup analyses stratified by deprivation and SEN level.
At age 11 (KS2) the cohort showed lower raw attainment among children with major congenital anomalies: 81.9% met national standards versus 93.8% of children without anomalies. The odds ratio reported for this comparison was 0.30 (95% CI 0.28–0.32). By age 16 (KS4), 46.8% of children with anomalies achieved 5 GCSEs at grades C–A*, including English/Welsh, Maths and Science (EWMS), compared with 56.1% of unaffected children (OR 0.69; 95% CI 0.65–0.73). When the investigators added covariates into adjusted models, the differences narrowed. Accounting for SEN provision in particular reduced the adjusted association at KS2 to aOR 0.72 (95% CI 0.66–0.78) and at KS4 to aOR 0.93 (95% CI 0.87–1.00) for achieving 5 GCSEs C–A* with EWMS. The manuscript provides the full tables and figures of these model results.
Socioeconomic factors carried large effects on attainment. Using the maternal Welsh Index of Multiple Deprivation at birth, the study team reported that in the most deprived quintile, 29.7% of children with major congenital anomalies and 38.4% of unaffected children achieved 5 GCSEs C–A* with EWMS. In the least deprived quintile the equivalent figures were 67.6% and 75.0%, respectively. Children eligible for Free School Meals (FSM) formed a notably disadvantaged subgroup. Among children with anomalies who received maximum SEN support, only 5 of 192 (2.6%) who were FSM-eligible obtained 5 GCSEs C–A* with EWMS; among similarly supported children who were not FSM-eligible, 37 of 354 (10.4%) achieved that benchmark. The authors reported adjusted odds ratios showing FSM eligibility as a strong negative correlate of attainment (aOR 0.39; 95% CI 0.37–0.41 for 5 GCSEs C–A* with EWMS).
SEN provision modified observed associations between health status and academic outcomes. Children with statements of SEN had much lower odds of meeting the 5 GCSEs C–A* with EWMS benchmark (aOR 0.07; 95% CI 0.06–0.07). Yet, the study found that adding SEN variables to adjusted models substantially reduced the measured disadvantage linked solely to major congenital anomalies. In plain terms, the gap between children with and without anomalies became smaller when SEN support was taken into account—although it did not disappear, and children experiencing both health impairment and socioeconomic deprivation remained unlikely to reach GCSE benchmarks.
The study team examined several long-term conditions recorded in linked datasets. Epilepsy was associated with reduced odds of achieving 5 GCSEs C–A* with EWMS (aOR 0.60; 95% CI 0.45–0.80). Other examined conditions included asthma and diabetes, and hospitalisation and preterm birth were included as potential mediators or confounders in models. The source did not provide full detail for all comorbidity prevalence in this summary; the manuscript and supplementary tables list the complete model outputs and condition coding. Investigators noted that medicated comorbidities and increased hospital contact correlated with lower attainment in the multivariable analyses.
The authors acknowledged several limitations that affect interpretation. Education outcome data were missing for 15%–18% of children, primarily those educated outside mainstream state-funded schools—these children were not fully represented. Some comorbidities were incompletely captured in the available datasets. The study could not include measures such as school attendance or behavioural difficulties because the data were not available in the linked sources. The authors cautioned that findings may not generalise to children educated outside mainstream settings or to other countries. The SAIL Databank governance prevents export of raw individual-level data; the team reported aggregated results and made metadata and coding resources available as described in the manuscript.
The study ends by identifying unanswered questions that matter for policy and practice: which targeted health, social, and educational interventions most effectively raise attainment among children who live with both disability and socioeconomic deprivation, and how attendance, classroom behaviour, and school-level factors contribute to the observed disparities. These questions, the investigators noted, remain for future research rather than being resolved by the present linkage analysis.