Cardiometabolic multimorbidity (CMM) represents one of the most prevalent and stable multimorbidity patterns. Relative fat mass (RFM), as a novel anthropometric indicator for assessing adiposity, has shown promise as a predictor of individual cardiometabolic diseases. However, evidence regarding its association with the risk of CMM remains limited.

To investigate the association between RFM and the risk of CMM across different genders, and to evaluate the potential role of RFM in the prevention and management of CMM.

A total of 116 321 permanent residents from 12 urban communities (including Suzhou) were selected as study participants from March 2017 to July 2021. Based on gender and CMM status, participants were stratified into CMM and non-CMM groups. Baseline characteristics were compared between these groups separately for each gender. Multivariable Logistic regression analysis was employed to examine the association between RFM and the risk of CMM stratified by sex. Restricted cubic spline (RCS) curves were applied to explore potential non-linear relationships. Subgroup analyses and interaction tests were conducted to investigate variations in the association across different populations.

A total of 116 321 participants were included in this study. Among them, 46 637 (40.1%) were male, with 11 969 cases (25.7%) in the CMM group and 34 668 cases (74.3%) in the non-CMM group. While 69 684 (59.9%) were female, with 16 668 cases (23.9%) in the CMM group and 53 016 cases (76.1%) in the non-CMM group. RFM levels were significantly higher in the CMM group than in the non-CMM group for both sexes(P<0.001). After adjusting for confounders including age,education level, smoking, alcohol consumption, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), remnant cholesterol, blood glucose, systolic blood pressure, and diastolic blood pressure, multivariable Logistic regression analysis revealed that among males, the risks of CMM in the T2 to T4 groups were 1.530, 2.086, and 2.945 times that of T1 group, respectively (P<0.001). Among females, the risks of CMM in the F2 to F4 groups were 1.205, 1.532, and 1.760 times that of F1 group, respectively (P<0.001). Furthermore, for each unit increase in RFM, the risk of CMM increased by 1.109 times in males (OR=1.109, 95%CI=1.101-1.116, P<0.001) and by 1.054 times in females (OR=1.054, 95%CI=1.049-1.060, P<0.001). RCS analysis demonstrated a nonlinear relationship between RFM and CMM risk in both sexes. For males,the inflection point of OR=1 was 25.26 (P_nonlinearity <0.001). For females, the inflection point of OR=1 was 38.41 (P_nonlinearity=0.001). Subgroup analysis showed that the risk of RFM and CMM was significantly associated with male (OR=1.108, 95%CI=1.101-1.115), age≥45 years old (OR=1.011, 95%CI=1.008-1.013), less than high school education (OR=1.013, 95%CI=1.011-1.015), current smoking (OR=1.062, 95%CI=1.054-1.069), current drinking (OR=1.021, 95%CI=1.015-1.028) and BMI<24 kg/m² (OR=1.010, 95%CI=1.007-1.014). The results of interaction analysis showed that the association between RFM and the risk of CMM was affected by the interaction between gender, age, education level, smoking, drinking and BMI (P_interaction<0.05).

Higher RFM is significantly associated with an increased risk of CMM, and this association is more pronounced in males, individuals aged≥45 years, those with a high school education or below, smokers, drinkers, and individuals with a BMI<24 kg/m².