Birth weight, verbal cognition in early adolescence, and lexical and reading skills in late adolescence: a formal mediation analysis using a potential outcomes approach
Bibliographic record
Abstract
BACKGROUND: Oral and written language in late adolescence are influenced by many pre- and postnatal factors, including cognitive performance at earlier ages. We investigated whether the association between birth weight and lexical knowledge and reading comprehension in late adolescence (14-16 years) is mediated by verbal cognition during early adolescence (10-11 years). METHODS: We conducted a mediation analysis via a potential outcomes approach to data from three United Kingdom (UK) prospective birth cohorts - The National Child Development Study (NCDS; year of birth (Y.B.) = 1,958; analytic sample size (A.N.) = 9,399; original sample size (O.N.) = 18,558), British Cohort Study (BCS70; Y.B. = 1,970; A.N. = 6,591; O.N. = 17,196), and Millennium Cohort Study (MCS; Y.B. = 2,000-2,001; A.N. = 3,950; O.N. = 18,552) - to evaluate the indirect effects of birth weight on lexical knowledge (BCS and MCS) and reading comprehension measures (NCDS) in adolescence. RESULTS: We found an indirect effect but no statistically significant direct effects for the BCS and MCS cohorts. The proportion of the effect of birth weight on oral and written language in late adolescence mediated by early adolescence verbal cognition was 59.19% (BCS) and 8.41% (MCS) for lexical knowledge and 61.00% when the outcome was reading comprehension (NCDS). Sensitivity analyses, used to assess whether unmeasured variables could have affected our mediation estimates, showed that for reading comprehension, in NCDS, the indirect effect is robust; only unmeasured confounders highly correlated with the mediator and outcome (ρ = .68) would explain away the indirect effect. For lexical knowledge, smaller correlations with hypothetical confounders (ρ = .33 for BCS) would suffice to render the indirect effect non-significant; the indirect effect for MCS non statistical significant. CONCLUSIONS: Birth weight affects oral and written language skills (lexical knowledge and reading comprehension) in late adolescence via verbal cognition in early adolescence in two cohorts born in 1958 and 1970, but not in a cohort born at the turn of the millennium. These indirect effects were stronger than the direct effects and are unlikely to be explained by unmeasured confounders when the outcome involves complex skills such as reading comprehension.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".