Thumb-Sucking, Nail-Biting, and Atopic Sensitization, Asthma, and Hay Fever
Bibliographic record
Abstract
BACKGROUND: The hygiene hypothesis suggests that early-life exposure to microbial organisms reduces the risk of developing allergies. Thumb-sucking and nail-biting are common childhood habits that may increase microbial exposures. We tested the hypothesis that children who suck their thumbs or bite their nails have a lower risk of developing atopy, asthma, and hay fever in a population-based birth cohort followed to adulthood. METHODS: Parents reported children's thumb-sucking and nail-biting habits when their children were ages 5, 7, 9, and 11 years. Atopic sensitization was defined as a positive skin-prick test (≥2-mm weal) to ≥1 common allergen at 13 and 32 years. Associations between thumb-sucking and nail-biting in childhood, and atopic sensitization, asthma, and hay fever at these ages were assessed by using logistic regression with adjustments for sex and other potential confounding factors: parental atopy, breastfeeding, pet ownership, household crowding, socioeconomic status, and parental smoking. RESULTS: Thirty-one percent of children were frequent thumb-suckers or nail-biters at ≥1 of the ages. These children had a lower risk of atopic sensitization at age 13 years (odds ratio 0.67, 95% confidence interval 0.48-0.92, P = .013) and age 32 years (odds ratio 0.61, 95% confidence interval 0.46-0.81, P = .001). These associations persisted when adjusted for multiple confounding factors. Children who had both habits had a lower risk of atopic sensitization than those who had only 1. No associations were found for nail-biting, thumb-sucking, and asthma or hay fever at either age. CONCLUSIONS: Children who suck their thumbs or bite their nails are less likely to have atopic sensitization in childhood and adulthood.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".