Serum Selenium and Age as Predictors of Metabolic Health in Middle-Aged Women: A Regression-Based Study
Rattachement africain : pl. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Background: This study investigated the relationship between serum selenium concentration and metabolic markers—specifically lipid parameters and glycemic control indicators (fasting glucose, insulin, HbA1c, HOMA-IR)—in middle-aged women, considering age as a covariate. Methods: A total of 387 women aged 45–67 years participated. Serum levels of selenium, glucose, insulin, HbA1c, HDL, LDL, and triglycerides were measured. Multiple linear regression models were used to evaluate the predictive value of the serum selenium concentration compared to age in predicting lipid and glycemic markers. Results: Selenium concentration was significantly and positively associated with HDL cholesterol only. No significant relationships were found between selenium and glycemic markers or other lipid parameters. In contrast, age emerged as a consistent positive predictor of LDL cholesterol, fasting glucose, and HbA1c levels. Furthermore, exploratory analysis suggested that HbA1c may influence the relationship between selenium and HDL/LDL cholesterol, though no formal moderation analysis was performed. Conclusions: Although serum selenium concentrations were within the normal range, their predictive value was limited to HDL cholesterol. Age showed a stronger and more consistent association with key metabolic markers, highlighting its importance as a predictor of cardiometabolic health in middle-aged women.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Serum Selenium and Age as Predictors of Metabolic Health in Middle-Aged Women: A Regression-Based Study
- Date Crossref
- 24/04/2025
- Éditeur
- MDPI AG
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Les institutions déclarées
Une affiliation ne permet pas de déduire la nationalité d’un auteur.