Background: The risk of chronic diseases increases markedly with age and after menopause. An increase in bodily iron following menopause could contribute to this phenomenon of increased risk of chronic diseases. We aimed to investigate how various iron biomarkers change with advancing age, according to sex and menopausal status. Methods: We enrolled community-dwelling individuals with available information on ferritin, transferrin, iron, hepcidin, and soluble transferrin receptor levels from the Prevention of Renal and Vascular Endstage Disease study. The association of the iron biomarkers with age, sex, and menopausal status was investigated with linear regression models. Results: Mean (SD) age of the 5222 individuals (2680 women [51.3%], among whom 907 [33.8%] were premenopausal, 529 [19.7%] perimenopausal, and 785 [29.3%] postmenopausal), was 53.4 (12.0) years. Iron biomarkers showed a constant increase in women throughout their life course, in some cases at older ages surpassing values in men who, in turn, showed consistently higher levels of iron status compared to women in most age categories. Ferritin, hepcidin, and transferrin saturation levels were 3.03, 2.92, and 1.08-fold (all p < 0.001) higher in postmenopausal women compared to premenopausal. Conclusions: We found that iron accumulates differently depending on sex, age, and menopausal status. An increased iron status was identified in women, especially during and after menopause.

We investigated whether adding iron biomarkers into existing type 2 diabetes risk models improves risk prediction. Data from three population-based cohorts were used; CoLaus|PsyCoLaus in Switzerland (5250 participants, 54.9 % females, mean age± standard deviation 51.8 ± 10.5 years, median follow-up of 14.5 years; PREVEND in the Netherlands (4784 participants, 51.8 % females, 52.2 ± 11.5 years, follow-up 7.3 years); and EPIPorto in Portugal (806 participants, 40 % females, 62 ± 13 years, follow-up 7.8 years). The effect of adding iron, ferritin, and transferrin in seven type 2 diabetes risk models was examined. 486 participants (9.3 %) in the CoLaus|PsyCoLaus, 170 (3.6 %) in PREVEND, and 22 (3.4 %) in EPIPorto developed diabetes. There was a substantial association between type 2 diabetes and all risk scores. In the CoLaus|PsyCoLaus and PREVEND, ferritin levels were positively and independently associated with the incidence of diabetes and considerably enhanced its prediction. Transferrin levels were positively and independently associated with the incidence of diabetes across all risk scores in all cohorts and improved its prediction in PREVEND, EpiPorto, and certain risk models in CoLaus|PsyCoLaus. There was found to be no association between iron levels and type 2 diabetes. Adding ferritin or transferrin slightly improved most diabetes risk prediction models.