A Comparison of Prenatal Exposures in Children with and Without A Diagnosis of Autism Spectrum Disorder in an Atlantic Canadian City
Notice bibliographique
Résumé
Abstract BACKGROUND: Autism spectrum disorder (ASD) is a multifactorial disorder characterized by varying deficits in social interactions, disordered communication and repetitive behaviour patterns. Signs that a child has autism are present in the early developmental stages and the symptoms cause significant impairment in many areas of functioning, including social, educational/occupational, and performance of everyday activities. There have been established genetic correlates and noticeable heredity with ASD diagnoses, but so far chromosomal genetic changes have only been found in approximately 25% of children with autism who were studied and there was no single variance that predominated. This signifies that there may be other external factors at play for autism to develop from preexisting genetic risk. Current studies suggest that prenatal exposures are more important to future autism diagnoses than those that happen after birth; there appears to be disruption of neuron gene networks in the cell cycle, protein folding, DNA damage repair and cell apoptosis. Potential prenatal triggers are the focus of this study, with interest to one geographical area in Atlantic Canada. OBJECTIVES: The study focused on the presence of environmental exposures during pregnancy in children who developed autism spectrum disorder and those who did not, with a specific focus on a specific Atlantic Canadian city. Exposures inquired about included: acetaminophen/ paracetamol use, air pollution, fever, parental age, maternal diabetes, prenatal vitamin use, workplace exposures, recreational drug use, seafood consumption, obesity, and maternal thyroid issues. DESIGN/METHODS: Mothers of children aged 0-10 years were asked to participate in a telephone interview regarding environmental exposures during their pregnancy. This was followed up by a prenatal chart review. There were two groups of participants: 107 from the autism group and 108 from the non-autism group. The data was analyzed with univariate tests and a logistic regression. RESULTS: Univariate analysis revealed significant differences between groups for presence of siblings with ASD, presence of family members with ASD, presence of fever, use of medications, use of cigarettes, and gesta-tional age at the start of prenatal vitamins. Logistic regression analysis found significance with use of medications, use of cigarettes, and gesta-tional age at the start of prenatal vitamins. CONCLUSION: The use of medications and cigarettes during pregnancy are associated with an increased rate of autism diagnosis. As well, a later starting date for use of prenatal vitamins was associated wth autism. Working towards an understanding of factors that come together to create a diagnosis of autism will be helpful for families, physicians, and allocating government resources.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».