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Cross-sectional study reveals dietary selenium affects prediabetes prevalence in a genetically homogeneous population, suggesting dietary adjustments may be beneficial.
Introduction Emerging evidence highlights the role of selenium (Se) in glucose metabolism through selenoprotein-mediated antioxidant and anti-inflammatory pathways. However, population-specific data remains inconclusive. This study aims to investigate the association between dietary Se intake and prediabetes prevalence in Newfoundland, a population characterized by genetic homogeneity and high obesity rates (39.4%). Methods This cross-sectional study used data from 2,665 participants in the Complex Diseases in the Newfoundland Population: Environment and Genetics (CODING) study. Prediabetes was defined by the American Diabetes Association criteria for impaired fasting glucose (FPG: 5.6–6.9 mmol/L). Dietary Se intake was assessed using the Willett food frequency questionnaire and expressed as both absolute (μg/d) and body weight-adjusted (μg/kg/d) metrics. Multivariate logistic regression, generalized additive model regression, piecewise regression models, and subgroup stratification were employed to examine the association. Results The study revealed a significant inverse relationship between body weight-adjusted dietary Se intake (μg/kg/d) and prediabetes prevalence in the fully adjusted models, with a non-linear threshold effect observed at 1.42 μg/kg/d. Below this threshold, each 1-unit increase in dietary Se intake (μg/kg/d) reduced prediabetes risk by 69% (OR = 0.31, P < 0.001). However, such an association did not reach statistical significance beyond 1.42 μg/kg/d. Subgroup analyses demonstrated consistent inverse associations across age groups, family history of diabetes, and history of smoking. However, the association was statistically significant in females (OR = 0.10, p < 0.001) but not in males. Absolute dietary Se intake (μg/d) showed no significant correlation with prediabetes after adjustment. Discussion Weight-adjusted dietary Se intake (μg/kg/d) exhibits an inverse non-linear, threshold-dependent relationship with prediabetes risk in this high-risk population. The findings underscore the critical importance of body weight normalization in assessing Se’s metabolic effects and formulating Se guidelines.
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Yu et al. (2025) studied this question.
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