The incidence of metabolic syndrome amongst a group of migrants to Qatar employed in Hamad Medical Corporation 24 months post-migration: a prospective longitudinal observational cohort study
Notice bibliographique
Résumé
Over the past two decades, the International Organisation for Migration highlighted the increasing proportion of international migration from 2.8% (150 million in 2000) to 3.5% (272 million in 2020) of the total world population. In 2019, the Labour Force Survey conducted by the Planning and Statistical Authority in Qatar estimated that migrants represented 91% of the total population in Qatar. Several studies have investigated the effect of migration on migrants' health, particularly relating to metabolic syndrome (MetS) development. A major limitation is that most studies researched migration to Western counties such as the USA, Canada, and Europe. The results and conclusions of these studies may not be generalisable to Qatar hence there is a gap in the literature. In addition, there was a lack of synthesis of the specific roles, activities, and impact of pharmacists in relation to MetS. The overall aim of this project was to explore the role of pharmacists in screening, prevention and management of MetS. The first phase was a longitudinal observational cohort study. The study aimed to investigate the effect of migration to Qatar on new MetS incidence amongst initially MetS-free migrants who were also employed at Hamad Medical Corporation (HMC), 24-months post residing in Qatar. The unique study design controlled for ethnic origin risk factors and attributed the MetS incidence to the migration process itself. The incidence of MetS amongst the initially MetS-free migrants rose to 17.0% during Qatar's two years of residence. Consuming medications that might induce MetS was the key determinant of MetS and increased the risk by 6-fold. The increase in MetS incidence shown in phase 1 indicated a need to alleviate the effect of migration on MetS risk among migrants. A systematic review of the pharmacists' role in MetS screening, prevention and management was conducted as the second phase of the PhD project. Ten studies were included in the review, and the settings included community pharmacies, primary health centres, inpatient and outpatients' clinics. Patient groups ranged from paediatrics with risk factors, adults with co-morbid conditions and psychiatric patients. Integration of the pharmacist within the multidisciplinary team, an easy referral process and accessibility of service were potential facilitators. Inadequate funding was the key barrier. The limited number of studies describing pharmacist input in MetS provides some evidence of positive outcomes of screening and management as part of collaborative practice. The finding of both the longitudinal study and the systematic review were taken into account to recommend a bespoke pharmacist model of care to screen, prevent and manage MetS amongst Qatar's migrants. The scope is to utilise pharmacists' skills as medication experts to alleviate adverse medication effects on MetS. This is of particular relevance as medications inducing MetS was a key determinant of MetS identified amongst Qatar's migrants. This study provides evidence about the impact of migration to the Middle East in new-onset MetS incidence. Assessment and follow-up of these migrants in terms of MetS and the elements will generally improve health status, control risk factors, and result in a less likelihood of longer-term consequences and an enhanced quality of life. This study will guide policymakers within the Ministry of Public Health and HMC in implementing preventative measures to combat MetS among migrants and develop strategies for early warning systems. In conclusion, the unique study design of the prospective study has added to the knowledge about the effect of migration to Qatar as part of the Middle East on MetS development. In addition, the systematic review has added robust evidence about pharmacists' competence in MetS screening, prevention, and management. Further research is recommended to examine the suggested pharmacist model of care around MetS in Qatar.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| 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 | 0,001 |
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 ».