Notice bibliographique
Résumé
The paper by Gearhardt and colleagues 1 makes a valuable contribution to the debate about hyperpalatable foods, their abuse potential and how they impact the increasing prevalence of obesity. Importantly, they discuss how strategies that have successfully lessened the public health consequences of drug addiction may be applied to the toxic food environment. They also address relevant differences — for example, that drug exposure generally occurs in our teen years, while consumption of foods unnaturally high in fat, sugar and salt begins earlier in life, and typically has a chronic course. Consequently, they argue for intervention policies aimed largely at children and adolescents. In this author's view, however, that may be too late. There is now compelling evidence that in utero events can have long-lasting, and sometimes dire, consequences for the offspring 2-4. We have learned recently how maternal diet can modify the fetal genome substantially and contribute to deleterious health outcomes for the developing child. For instance, high-fat consumption during pregnancy has been shown to induce long-term alterations in dopamine and opioid gene expression in animal offspring, and to enhance their preference for palatable foods 5. In addition, there is evidence that children of obese mothers are at increased risk for insulin resistance and subsequent obesity and metabolic dysfunction 6. Using data collected from three affluent Scandinavian societies, a prospective study also showed, for the first time, that maternal obesity increased the risk of having a child with symptoms of attention deficit hyperactivity disorder (ADHD) compared to children of normal-weight mothers 7. Moreover, these findings persisted after controlling for baby's birth weight, maternal age and mother's smoking status. To test whether this relationship occurred because a genetic predisposition accounted for both the mother's weight status and the subsequent ADHD symptoms in the child, a large replication study extended this research. Again, it was found that children of obese mothers had a twofold increase on teacher-rated inattention scores compared to those of normal-weight mothers 8. These associations also remained statistically significant after controlling for ADHD symptoms in both parents. Of relevance to these findings are the strongly established links between prenatal alcohol exposure and symptoms of ADHD 9 and the high co-occurrence of ADHD symptoms and obesity, both in children and in adults 10. It is noteworthy in this context that alcohol and sugar are biochemically congruent substances, because ethanol is simply the fermented by-product of fructose 11. In our current food environment, with its superfluity of highly palatable foods, mothers who are overweight and obese are likely to consume larger and more frequent quantities of sweet foods than their normal-weight counterparts. Currently, high fructose sweeteners are used liberally in most of the processed foods we eat, and in much greater amounts than are found naturally in fruits and vegetables 12. When taken in large quantities, both alcohol and fructose have considerable abuse potential due to their potent activation of brain reward pathways 13, 14. They can also foster neuroadaptations that lead to compulsive use and dependence similar to other drugs of abuse 15, 16. It is therefore plausible that highly processed foods taken in abundance during pregnancy could contribute to deleterious outcomes for the unborn child such as those seen in the studies described above. In other words, excessive maternal ingestion of sweet foods could produce what I will loosely call a ‘fetal sugar spectrum disorder’, with symptoms that are not dissimilar to those seen in the offspring of women who drank alcohol during their pregnancy. Because postnatal life appears to be linked inextricably with environmental influences during fetal development, and because approximately 20% of women of reproductive age are obese, it seems of utmost importance to target pregnant women for prevention measures in a manner similar to the aggressive warnings about gestational alcohol use. It will behove health-care providers to issue strong nutritional guidance to women during pregnancy to avoid events that may have irreversible consequences for their children later in life. None.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».