The modified role including mediating and synergistic interactive effects of glucose tolerance status in the associations between relative fat mass and the risks of cardiovascular disease and all-cause mortality from the 4C cohort study.

Abstract

Background: To investigate the associations between relative fat mass (RFM) and clinical outcomes in different glucose tolerance statuses and the modified effect of glucose tolerance status.

Methods: We analyzed 8,224 participants from a Chinese cohort study, who were classified into normal glucose status (NGT), prediabetes, and diabetes. Outcomes included fatal, nonfatal cardiovascular disease (CVD) events and all-cause mortality. Associations between RFM and outcomes were assessed using Cox regression. The modified effect of glucose tolerance status was investigated using mediation, interaction, and joint analyses.

Results: During up to 5 years of follow-up, 154 (1.9%) participants experienced fatal CVD, 153 (1.9%) experienced nonfatal CVD events, and 294 (3.6%) experienced all-cause death. 2,679 participants (32.6%) had NGT, 4,528 (54.8%) had prediabetes, and 1,037 (12.6%) had diabetes. RFM was associated with increased risk of fatal (HR [95% CI], 1.09 [1.06-1.12], p < 0.001), nonfatal CVD events (HR [95% CI], 1.12 [1.09-1.15], p < 0.001), and all-cause mortality (HR [95% CI], 1.10 [1.08-1.12), p < 0.001) in all and those with NGT, prediabetes, and diabetes, and these associations were modified by glucose tolerance status, which included mediating (mediation proportion ranges from 4.74% to 8.69%) and synergistic interactive effects (multiplicative effect ranges from 1.03 to 1.06). The joint analysis identified the subclassification that exhibited the highest HR among 12 subclassifications.

Conclusions: RFM was associated with increased risk of fatal, nonfatal CVD events, and all-cause mortality in NGT, prediabetes, and diabetes, and these associations were modified by glucose tolerance status, which could significantly influence how clinicians assess high risk and could lead to more personalized, effective prevention strategies.