Prospective cohort study of vitamin D and autism spectrum disorder diagnoses in early childhood
Bibliographic record
Abstract
Several studies have suggested an association between vitamin D in childhood and autism spectrum disorder. No prospective studies have evaluated whether lower vitamin D levels precede ASD diagnoses – a necessary condition for causality. The objective of this study was to prospectively evaluate whether vitamin D serum levels in early childhood was associated with incident physician diagnosed ASD. A prospective cohort study was conducted using data from preschool-aged children in the TARGet Kids! practice-based research network in Toronto, Canada, from June 2008 to July 2015. 25-hydroxyvitamin D concentration was measured through blood samples and vitamin D supplementation from parent report. Autism spectrum disorder diagnosis was determined from medical records at follow-up visits. Covariates included age, sex, family history of autism spectrum disorder, maternal ethnicity, and neighborhood household income. Unadjusted and adjusted relative risks and 95% confidence intervals were estimated using Poisson regression with a robust error variance. In this study, 3852 children were included. Autism spectrum disorder diagnosis was identified in 41 children (incidence = 1.1%) over the observation period (average follow-up time = 2.5 years). An association between 25-hydroxyvitamin D concentration and autism spectrum disorder was not identified in the unadjusted (relative risk = 1.04, 95% confidence interval: 0.97, 1.11 per 10 nmol/L increase in 25-hydroxyvitamin D concentration) or adjusted models (adjusted relative risk = 1.06; 95% confidence interval: 0.95, 1.18). An association between vitamin D supplementation in early childhood and autism spectrum disorder was also not identified (adjusted relative risk = 0.86, 95% confidence interval: 0.46, 1.62). Vitamin D in early childhood may not be associated with incident physician diagnoses of autism spectrum disorder.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".