Toenail Selenium and Incidence of Type 2 Diabetes in U.S. Men and Women
Siscovick, David S.
Morris, J. Steven
MetadataShow full item record
CitationPark, Kyong, Eric B. Rimm, David S. Siscovick, Donna Spiegelman, JoAnn E. Manson, J. Steven Morris, Frank B. Hu, and Dariush Mozaffarian. 2012. “Toenail Selenium and Incidence of Type 2 Diabetes in U.S. Men and Women.” Diabetes Care 35 (7): 1544-1551. doi:10.2337/dc11-2136. http://dx.doi.org/10.2337/dc11-2136.
AbstractOBJECTIVE Compelling biological pathways suggest that selenium (Se) may lower onset of type 2 diabetes mellitus (T2DM), but very few studies have evaluated this relationship, with mixed results. We examined the association between toenail Se and incidence of T2DM. RESEARCH DESIGN AND METHODS We performed prospective analyses in two separate U.S. cohorts, including 3,630 women and 3,535 men, who were free of prevalent T2DM and heart disease at baseline in 1982–1983 and 1986–1987, respectively. Toenail Se concentration was quantified using neutron activation analysis, and diabetes cases were identified by biennial questionnaires and confirmed by a detailed supplementary questionnaire. Hazard ratios of incident T2DM according to Se levels were calculated using Cox proportional hazards. RESULTS During 142,550 person-years of follow-up through 2008, 780 cases of incident T2DM occurred. After multivariable adjustment, the risk of T2DM was lower across increasing quintiles of Se, with pooled relative risks across the two cohorts of 1.0 (reference), 0.91 (95% CI 0.73–1.14), 0.78 (0.62–0.99), 0.72 (0.57–0.91), and 0.76 (0.60–0.97), respectively (P for trend = 0.01). Results were similar excluding the few individuals (4%) who used Se supplements. In semiparametric analyses, the inverse relationship between Se levels and T2DM risk appeared to be linear. CONCLUSIONS At dietary levels of intake, individuals with higher toenail Se levels are at lower risk for T2DM. Further research is required to determine whether varying results in this study versus prior trials relate to differences in dose, source, statistical power, residual confounding factors, or underlying population risk.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:11717504