Impact of age, sex, and thyroid autoimmunity on the association between selenium intake and type 2 diabetes mellitus

Abstract

Abstract Background The association between dietary selenium(Se) intake and type 2 diabetes mellitus (T2DM) remains controversial. The present study aimed to investigate this association using data from the National Health and Nutrition Examination Survey (NHANES) database for the years 2007–2012. Methods Three thousand seventy three individuals aged 20 years and above were eligible for inclusion in this cross-sectional study. The average age of the participants was 50.74 years and the proportions of males and females were nearly equal (49.12% vs. 50.88%). The odds ratios (OR) of the association between dietary Se intake (log2-transformed) and T2DM were examined through the multivariate logistic regression model. Subgroup analyses were conducted based on age, sex, and thyroid autoimmunity to assess the potential impact of these variables on the relationship. Fitted smoothing curves and threshold effect analysis were conducted to describe the nonlinear relationship. Results In the fully adjusted model, a significant positive association between Se intake and T2DM was observed (OR = 1.49, 95% CI: 1.16, 1.90, p = 0.0017). After stratifying the data by age, sex, and thyroid autoimmunity, a significant positive association between Se intake and T2DM was observed in individuals under 65 years of age, males, and those with negative thyroid autoimmunity. A two-segment linear regression model was analyzed for sex stratification, revealing a threshold effect in males with an inflection point of 90.51 μg, and an inverted U-shaped relationship in females with an inflection point of 109.90 μg, respectively. Conclusions The present study found a positive relationship between Se intake and the prevalence of T2DM. This association is particularly significant in younger individuals, males, and those with negative thyroid autoimmunity. Our results should be validated in future large prospective studies in different populations.