Overweight and Obesity in Children with Autism Spectrum Disorders: Findings Consistent with Typically Developing Children
Notice bibliographique
Résumé
Childhood overweight and obesity are considerable problems both in the United States and worldwide.These abnormal weight categories are often accompanied by increased physical and mental health complications including diabetes mellitus, cardiovascular issues, and depression.Most concerning, elevated body mass in childhood generally leads to elevated body mass in adulthood, which is associated with higher rates of morbidity and mortality.Youth with intellectual or developmental disabilities, such as autism spectrum disorder (ASD), appear to be at heightened risk for overweight and obesity due to high medication use, atypical eating habits, and sedentary behavior.Previous literature is mixed as to whether these children actually have higher prevalence rates of overweight and obesity, although the methodology associated with some studies has been subpar due to use of parent-derived height and weight, and small sample sizes.This dissertation was designed to investigate the prevalence of abnormal weight in children with ASD, and to identify what variables were associated with elevated body mass.The sample comprised children from the United States and Canada who visited a hospital or clinic that was part of the Autism Treatment Network.In this sample, 32.9% of the children were overweight and 17.3% were obese, which was not significantly different from the rates of elevated body mass in typically developing children or from some previous studies of children with ASD.iii Multiple hierarchical regression models were run to analyze the data from a variety of perspectives, while trying to avoid confounds such as prescribed medication, different Child Behavior Checklist (CBCL) age versions, and clinical site.The most successful model was called "Atheoretical Empiricism," and it found that Asian heritage, high levels of paternal education, stimulant use, atomoxetine use, high scores of the Anxious/Depressed CBCL subscale, and having a pervasive developmental disorder -not otherwise specified (PDD-NOS) diagnosis were associated with lower BMI percentile.Hispanic heritage, SSRI use, alpha 2 agonist use, high scores on the Sleep Disordered Breathing subscale of the Children's Sleep Habits Questionnaire, and elevated scores of the CBCL Aggressive Behavior subscale and Withdrawn/Depressed subscale were associated with higher BMI percentile (greater likelihood of being overweight or obese).The variance accounted for declined when the more specific theory-driven investigations were conducted.The model had a better fit for older children whose parents completed the 6-18 year CBCL version rather than younger children whose parents completed the 1.5-5 year version.When evaluated by specific ASD diagnosis, the model fit best for children with PDD-NOS.There were great variations between model fit across sites; data from two Northeastern sites accounted for more variance (13.5% for Site 23 and 17.1% for Site 2) than any of the previous manipulations.Although far less variance was accounted for than initially hoped, variance levels in this study were consistent with amounts from other investigations.This study confirmed that several of the predictors for overweight and obesity in the neurotypical population held true for children with ASD.Future directions for research and weight-related interventions were discussed.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,003 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».