Association of the Transmembrane Protease Serine 6 rs855791 Variant and Nongenetic Factors With Iron Deficiency Among Female Medical Students in Yogyakarta: Protocol for a Case-Control Study
Notice bibliographique
Résumé
BACKGROUND: Iron deficiency is the most widespread nutritional deficiency worldwide, and it is the primary cause of anemia, particularly in low- and middle-income countries such as Indonesia. Iron deficiency has a multifactorial etiology involving complex interactions between genetic factors, especially the transmembrane protease serine 6 (TMPRSS6) rs855791 variant, which encodes matriptase-2, a protein involved in regulating hepcidin expression, and nongenetic factors, including sociodemographics, nutritional status, iron intake, and menstrual patterns. Women of reproductive age, including medical students, are susceptible to iron deficiency owing to unhealthy dietary habits, growth requirements, and menstruation. Iron deficiency among medical students may lead to decreased academic performance and productivity. Additionally, as future mothers, women may experience a heightened risk of delivering children with intellectual disabilities and various psychosocial impairments. Owing to the significant consequences of this condition, identifying the underlying causes of iron deficiency is crucial. The high prevalence of iron deficiency in Indonesia poses a challenge in addressing these contributing factors to effectively reduce its occurrence. OBJECTIVE: This study aims to investigate the association of the TMPRSS6 rs855791 variant and nongenetic factors with iron deficiency among female medical students in Yogyakarta, Indonesia. METHODS: This is a case-control study. We will recruit female medical students from the Faculty of Medicine, Public Health, and Nursing of Universitas Gadjah Mada in Yogyakarta, Indonesia. The inclusion criteria are being a final-year female undergraduate medical student who has not entered the clinical clerkship phase, aged 18 to 24 years, not pregnant, providing written consent, and having no history of chronic and inflammatory diseases, congenital diseases, hematological disorders, or blood transfusions during the last 3 months. Participants will be excluded if the C-reactive protein level is higher than 5 mg/L. Participants will be further grouped according to iron status criteria. Profiles of hemogram and iron markers will be compared between the case and control groups using the independent samples 2-tailed t test or the Mann-Whitney U test, while genotype and allele frequencies will be analyzed using the chi-square test. One-way ANOVA or the Kruskal-Wallis test will be used to assess the impact of different genotypes on iron marker levels. Multivariate analysis will be performed with logistic regression to determine factors independently associated with iron deficiency risk. P≤.05 will be considered statistically significant. RESULTS: The study received funding in January 2025. Data collection began in February 2025 and is anticipated to conclude by October 2025. At the time of manuscript submission, 115 participants had been enrolled. The study findings are expected to be published in 2026. CONCLUSIONS: This study will determine the interaction between the TMPRSS6 rs855791 variant and nongenetic factors that contribute to the risk of iron deficiency among female medical students in Yogyakarta, Indonesia. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/79555.
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 | 0,006 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,017 | 0,003 |
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 ».