The Temporal Hyper-Morbidity of Asthma and Attention Deficit Disorder: Implications for Interpretation Based on Comparison of Prospective and Cross-Sectional Population Samples
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to test the hypothesis that a significant temporal relationship exists between asthma and attention deficit hyperactivity disorder (ADHD). METHODS: The population dataset consisted of 95,846,511 physician diagnoses for 768,460 (46% male) individuals spanning 1993-2010. Four groups were labeled as having neither Asthma nor ADHD, Asthma only, ADHD only, or both Asthma and ADHD and formed the basis of calculating the odds ratios for each sex describing the association of Asthma and ADHD by age, and, in addition, a prospective sample age (<5 years) between 1993 and 1996 was utilized to evaluate the temporal association between Asthma and ADHD. RESULTS: There was a significant relationship between ADHD and Asthma within the age strata of the sample, one from the cohort and two from the whole sample. When both ADHD and Asthma were diagnosed in the same patients, the age was younger in both cross-sectional and prospective cohort samples. ADHD arose significantly more often after Asthma in the cross-sectional samples stratified on age and in the prospective cohort sample. CONCLUSION: The results are consistent with previous literature where ADHD has been linked to allergic diseases, such as asthma.
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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 | 0.032 | 0.080 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".