Sex-specific associations between type 2 diabetes incidence and exposure to dioxin and dioxin-like pollutants: a meta-analysis
Notice bibliographique
Résumé
Abstract The relationship between persistent organic pollutants (POPs), including dioxins and dioxin-like polychlorinated biphenyls (DL-PCBs), and diabetes incidence in adults has been extensively studied. However, significant variability exists in the reported associations both between and within studies. Emerging data from rodent studies suggest that dioxin exposure disrupts glucose homeostasis in a sex-specific manner. Thus, we performed a meta-analysis of relevant epidemiological studies to investigate whether there are sex-specific associations between dioxin or DL-PCB exposure and type 2 diabetes incidence. Articles were organized into the following subcategories: data stratified by sex (16%), unstratified data (56%), and data from only 1 sex (16% male, 12% female). We also considered whether exposure occurred either abruptly at high levels through a contamination event (“disaster exposure”) or chronically at background levels (“non-disaster exposure”). Only 8 studies compared associations between dioxin/DL-PCB exposure and diabetes risk in males versus females within the same population. When all sex-stratified or single sex studies were considered in the meta-analysis, the summary odds ratio (OR) for increased diabetes risk was similar between females and males (1.78 and 1.95, respectively) when comparing exposed to reference populations, suggesting that this relationship is not sex-specific. However, when we considered disaster-exposed populations separately, the association differed substantially between sexes, with females showing a much higher OR than males (2.86 and 1.59, respectively). Moreover, the association between dioxin/DL-PCB exposure and diabetes was stronger for females than males in disaster-exposed populations. In contrast, both sexes had significantly increased ORs in non-disaster exposure populations and the OR for females was lower than males (1.40 and 2.02, respectively). Our review emphasizes the importance of considering sex differences, as well as the mode of pollutant exposure, when exploring the relationship between pollutant exposure and diabetes in epidemiological studies.
Conservé avec la notice de tri, où il sert de preuve aux étiquettes ci-dessus.
Comment cette classification a été obtenuedéplier
Le tri à trois modèles
les 5 600 travaux triés →Les trois modèles l'ont jugé hors champ.
Meta-analysis of dioxin exposure and diabetes risk by sex; it notes how often studies stratify by sex, but the knowledge produced is about an exposure-disease association.
This meta-analysis answers a substantive epidemiological question about pollutants and diabetes rather than studying evidence synthesis methods.
Meta-analysis answering whether dioxin exposure associates with diabetes by sex; synthesis used for a health question.
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 | 0,011 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,012 | 0,057 |
| Bibliométrie | 0,005 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».