Comparative Study
Journal Article
Research Support, Non-U.S. Gov't
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Cross-sectional and longitudinal associations of Iron biomarkers and cardiovascular risk factors in pre- and postmenopausal women: leveraging repeated measurements to address natural variability.

BACKGROUND: The association between iron biomarkers and cardiovascular disease risk factors (CVD-RFs) remains unclear. We aimed to (1) evaluate the cross-sectional and longitudinal associations between iron biomarkers (serum ferritin, transferrin saturation (TSAT), transferrin) and CVD-RFs among women, and (2) explore if these associations were modified by menopausal status.

METHOD: Cross-sectional and longitudinal analyses including 2542 and 1482 women from CoLaus cohort, respectively. Multiple linear regression and multilevel mixed models were used to analyse the associations between Iron biomarkers and CVD-RFs. Variability of outcomes and iron markers between surveys was accessed using intraclass correlation (ICC).

RESULTS: After multivariable adjustment, elevated serum ferritin levels were associated with increased insulin and glucose levels, while higher transferrin levels were linked to elevated glucose, insulin and total cholesterol, and systolic and diastolic blood pressure (p < 0.05). No association was observed between CVD-RFs and TSAT (p > 0.05). Iron biomarkers demonstrated low reliability across reproductive stages but exhibited stronger associations in the perimenopausal group. In longitudinal analysis, we found association only for transferrin with lower glucose levels [β = - 0.59, 95% CI (- 1.10, - 0.08), p = 0.02] and lower diastolic blood pressure [β = - 7.81, 95% CI (- 15.9, - 0.56), p = 0.04].

CONCLUSION: In cross-sectional analysis, transferrin was associated with several CVD-RFs, and the associations did not change according to menopausal status. Conversely, in the longitudinal analyses, changes in transferrin were associated only with lower glucose and diastolic blood pressure levels. These differences might stem from the substantial longitudinal variation of iron biomarkers, underscoring the need for multiple iron measurements in longitudinal analyses.

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