P2-304 Childhood infectious diseases and premature adult mortality: results from the Newcastle Thousand Families Study
Bibliographic record
Abstract
Introduction Early life infections may negatively influence health in later life, but there have been few studies of the association, due to the difficulty of obtaining adequate information from throughout life. This study utilised longitudinal data from the Newcastle Thousand Families Study, a prospective cohort of 1147 individuals born in Newcastle-upon-Tyne (UK) in 1947, to assess the impact of various childhood infectious diseases on mortality between ages 18 and 60 years. Methods Detailed information was collected prospectively at birth and during childhood on a number of early life factors. Study members were “flagged” by the UK National Health Service Central Register when they died or emigrated. Death between ages 18–60 years was analysed in relation to childhood infections, adjusting for potential confounders, using Cox regression. Results History of infection with either tuberculosis or whooping cough was independently predictive of mortality between ages 18 and 60 years [Adjusted HR, aHR=2.00 (95% CI 1.17 to 3.41) and 1.95 (95% CI 1.21 to 3.14) respectively]. Of the other variables examined, adult mortality was more common among men [aHR=0.62 (95% CI 0.39 to 0.97)] and among first-borns [aHR=2.95 (95% CI 1.52 to 5.73)]. The effect of whooping cough on mortality was largely attributable to a higher risk of death from cancer, particularly non-smoking related cancers. Conclusion In a pre-vaccination cohort from Northern England (UK), childhood infection with tuberculosis or whooping cough was associated with an increased risk of premature adult mortality independent of other childhood circumstances. Further studies are required to investigate this association in different populations.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".