# Association Between Relative Fat Mass and the Serum Creatinine/Cystatin C Ratio and Cardiometabolic Multimorbidity: Evidence From Two Large Population‐Based Surveys

## TL;DR

This study shows that lower serum creatinine/cystatin C ratio and higher relative fat mass are linked to increased risk of cardiometabolic diseases.

## Contribution

The study identifies SCR/CysC and RFM as potential biomarkers for early detection of cardiometabolic multimorbidity.

## Key findings

- Higher SCR/CysC levels are associated with lower cardiometabolic multimorbidity risk.
- Higher RFM levels are linked to increased cardiometabolic multimorbidity risk.
- Findings are consistent across Chinese and American population datasets.

## Abstract

The serum creatinine–cystatin C ratio (SCR/CysC) and relative fat mass (RFM) are both important indicators reflecting muscle and fat content, respectively, and are closely related to metabolic diseases and cardiovascular diseases. However, the roles of SCR/CysC and RFM in cardiometabolic multimorbidity (CMM) remain unclear. This study is aimed at exploring the relationships between SCR/CysC, RFM, and CMM, providing a new perspective for the early identification and intervention of CMM.

This study included 9292 Chinese participants from the CHARLS database and 3822 American individuals from the NHANES database. Multivariate logistic regression analysis, restricted cubic spline (RCS) plots, and subgroup analyses were employed to explore the associations of SCR/CysC and RFM with CMM.

Analyses based on two databases revealed that the level of SCR/CysC levels was significantly negatively correlated with the risk of CMM. Conversely, higher RFM levels were positively correlated with an increased risk of CMM. Specifically, compared to the lower quartile (Q1) of SCR/CysC, the highest quartile (Q4) was associated with a decreased risk of CMM (CHARLS: odds ratio (OR) = 0.89, 95% confidence interval (CI): 0.87–0.91, p < 0.001; NHANES: OR = 0.90, 95% CI: 0.86–0.94, p < 0.001). Compared to the lower quartile (Q1) of RFM, the highest quartile (Q4) was associated with an increased risk of CMM (CHARLS: OR = 1.18, 95% CI: 1.16–1.21, p < 0.001; NHANES: OR = 1.20, 95% CI: 1.15–1.25, p < 0.001). The RCS plot results further supported this relationship, demonstrating that after adjusting for multiple confounding factors, a decrease in SCR/CysC and an increase in RFM were both associated with a higher risk of CMM.

This study found that SCR/CysC levels were negatively correlated with CMM risk, whereas RFM levels showed a positive correlation. Thus, SCR/CysC and RFM may both serve as potential biomarkers for CMM screening.