Abstract
An increasing body of evidence implicates high levels of selenium intake in the development of diabetes, although prospective studies remain sparse. We conducted a nested case-control study of 622 diabetes incident cases and 622-age, sex, and follow-up time-matched controls in the prospective Jinchang cohort of 48,001 participants with a median of 5.8 years of follow-up. Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure all 622 case-control pairs' baseline serum levels of selenium (Se), which were then categorized into quartiles based on the frequency distribution among the controls. Multivariable adjusted conditional logistic regression and restricted cubic splines (RCS) models were applied to evaluate independent odds ratios (OR) as estimates for relative risks (RR) of diabetes according to quartiles (Q) of selenium levels. Compared to the lowest quartile (Q1 as reference), significantly greater diabetes risks (with 95% confidence interval) were observed in Q3 (OR = 1.62, 1.17–2.35) and Q4 (OR = 1.79, 1.21–2.64). Sub-analyses showed these increased risks of diabetes by serum levels of Se. appeared to differ by sex, age, BMI status, history of hypertension, and dyslipidemia. Further, application of RSC models showed that serum Se levels between 95 and 120 μg/L were significantly and positively associated with diabetes risk whereas no apparent relation exists when Se levels were under 95 μg/L in this cohort population.
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