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Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
Published on: September 27, 2024
Association between BMI, RFM and mortality and potential mediators: Prospective findings from the Moli-sani study
Anwal Ghulam1, Francesco Gianfagna2,3, Marialaura Bonaccio4
1Research Center in Epidemiology and Preventive Medicine (EPIMED), Department of Medicine and Surgery, University of Insubria, Varese, Italy.
Background:
Body mass index (BMI) is the most frequently used adiposity measure, yet it is unable to differentiate fat mass from lean mass. Relative fat mass (RFM) has been proposed as an alternative. This paper aims to study RFM and BMI association with mortality in a general Italian population and potential mediators of such association.
Methods:
20,587 individuals from the Moli-sani cohort were analysed (mean age = 54 ± 11, women = 52%, median follow up = 11.2 years, interquartile range = 1.96 years). Cox regressions were used to assess BMI, RFM, and their interactive association with mortality. Dose-response relationships were computed with spline regression, mediation analysis was performed. All analyses were separated for men and women.
Results:
Men and women with BMI > 35 kg/m2 and men in the 4th quartile of RFM showed an independent association with mortality (HR = 1.71, 95% CI = 1.30-2.26 BMI in men, HR = 1.37, 95%CI = 1.01-1.85 BMI in women, HR = 1.37 CI 95% = 1.11-1.68 RFM in men), that was lost once adjusted for potential mediators. Cubic splines showed a U-shaped association for BMI in men and women, and for RFM in men. Mediation analysis showed that 46.5% of the association of BMI with mortality in men was mediated by glucose, C reactive protein, forced expiratory volume in 1 s (FEV1), and cystatin C; 82.9% of the association of BMI in women was mediated by HOMA index, cystatin C and FEV1; lastly, 55% of RFM association with mortality was mediated by glucose, FEV1 and cystatin C. Regression models including BMI and RFM showed that RFM drives most of the risk in men, but is not predictive in women.
Conclusions:
The association between anthropometric measures and mortality was U shaped and it was largely dependent on sex. Associations were mediated by glucose metabolism, renal and lung function. Public health interventions should mainly focus on people with severe obesity or impaired metabolic, renal, or respiratory function.
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