Is screening for type 2 diabetes worthwhile in adolescents and young adults in developing countries
Notice bibliographique
Résumé
R M Gali, Y P Mamza, and J Adeonote, Department of Medical Laboratory Science; also D S Mshelia, Department of Chemical Pathology; all at College of Medical Sciences, University of Maiduguri, Nigeria. Correspondence to Mrs Rebecca Mtaku Gali, Department of Medical Laboratory Science, College of Medical Sciences, University of Maiduguri, ,Maiduguri, Nigeria. Email: rmgali@yahoo.com Introduction Type 2 diabetes was once a disease occurring primarily, if not exclusively, in adults. Today the age of diagnosis is disquietingly declining accounting for about 8% to 45% of all new cases of diabetes in children and teenagers.1–4 Various centres have reported a 10 to 30-fold increase in American children with type 2 diabetes in the past 10 to 15 years, and in the next 15 years it is anticipated that the global incidence of type 2 diabetes in children and adolescents will increase by up to 50%.2,3,5 An alarming increase is also noticed in Canada,6 the UK,7 urban South-Asia,8 and Japan.9 Hence there seem to be increasing reports of type 2 diabetes in children and adolescents worldwide10 but a paucity of reports from Africa.11 However, according to a World Health Organization (WHO) non-communicable disease (NCD) surveillance report,12 and a report from the WHO regional office for Africa13 on the emerging NCD epidemic in that continent there is a wide dichotomy of prevalence of type 2 diabetes between rural and urban Abstract Reports of the age of diagnosis of type 2 diabetes are declining, with a paucity of information in Africa. We therefore screened young university undergraduates to determine the current status of fasting plasma glucose among adolescents and young adults in Africans living in Africa. Two hundred and thirty (230), age range 18 to 35 years, participated in the study. Mean (+SD) age was 23+6y, BMI 22.2+3.8 kg/m2, and fasting plasma glucose (FPG) 4.1+0.6 mmol/L. There was a positive but not a statistically significant correlation between BMI and FPG , but a statistically significant correlation between BMI and FPG in males but not in females. No subjects were found to have type 2 diabetes. areas, mainly due to a ‘westernised’ lifestyles, which are of concern to African diabetes services. The most important factor associated with the epidemic of type 2 diabetes and its declining age of onset is overweight/obesity and this appears to be due to increased calorie intake and a sedentary lifestyle.14–16 About half of patients with type 2 diabetes are diagnosed without symptoms and 50% have at least one diabetes-specific complication on diagnosis. Subsequently, the focus is increasing on the prevention, detection, and effective treatment of diabetes. We have screened young university undergraduates to demonstrate whether the declining age of onset of type 2 diabetes noticed in developed nations has started to manifest itself among adolescents and young adults in Africans living in Africa.
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 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 | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».