Baseline Characteristics of the Study Population
The mean age among the 8249 study participants was 74.1 ± 7.1, and 56.4% (n = 4649) of the subjects were women (Table 1). Signiﬁcant dose–response relationships were observed between higher CVAI, advanced age, larger anthropometric indices (i.e. BMI, WC), increased blood pressure, increased fasting glucose, elevated UA level, more unfavorable HDL-C/TG profiles, and worsened renal function (P < 0.001) in both genders. Men with higher levels of CVAI were less likely to have regular exercise, which was inversely proportional in women (both P < 0.05). Those with higher CVAI were more inclined to have prevalent diabetes and undergo pharmacological treatment for hyperlipidemia, leading to lower TC and LDL-C (all P < 0.05). Similarly, those subjects with higher ABSI presented with higher BMI/WC, increased fasting glucose, more unfavorable HDL/TG ratio, increased UA level, larger CVAI, and reduced intensity of regular exercise and tended to have baseline prevalent diabetes, irrespective of gender (both P < 0.001) (Table 1). Overall, women had significantly higher CVAI (118.4 ± 33.8 vs 111.0 ± 41.8) yet slightly lower ABSI (0.12 ± 0.01 vs 0.13 ± 0.01, both P < 0.001) compared with men.
Validation of VAI with MDCT-defined Visceral Adiposity
Data on MDCT-defined peri-cardiac and peri-aortic adiposity burden were available in 374 study subjects. A significantly positive linear correlation was observed between larger peri-cardiac fat (PCF)/peri-aortic fat (TAT) burden and larger CVAI (r = 0.825 and 0.786 for PCF and TAT, respectively. Supplemental Figure 1). However, positively attenuated correlations were observed with ABSI.
Correlation of Adiposity Measures with Diabetes and Biochemical Metabolic Profiles
Baseline prevalent diabetes mellitus was present in 19% (n = 1539) of all study participants. Those with prevalent baseline diabetes mellitus had significantly higher CVAI (132.4 ± 36.9 vs 111.2 ± 36.7) and ABSI (0.128 ± 0.017 vs 0.125 ± 0.011, both P < 0.001) compared with those without diabetes mellitus. Associations among CVAI/ABSI and anthropometric or metabolic profiles are shown in Supplemental Table 1. Partial correlation assessment showed that larger CVAI was positively correlated with greater BMI (r = 0.83), higher blood pressure (r = 0.17 for both systolic and diastolic blood pressure, respectively), larger WC (r = 0.90), elevated FPG levels (r = 0.25), unfavorable lipid proﬁles (except LDL-C), higher UA levels (r = 0.29, all P < 0.001) and inversely associated with HDL-C (–0.53, P < 0.001) after adjusting for age and gender. Correlations among ASBI and the metabolic indicators showed a similar pattern, although the coeﬃcients were smaller compared to CVAI. No significant associations were observed between ABSI, blood pressure, TC, and LDL-C.
Association of CVAI or ABSI with DiabetesRisk
Unfavorable anthropometric measurements, lipid profile, and VAI (CVAI and ABSI) were all associated with higher baseline diabetes mellitus risk (Figure 1). Multivariable logistic regression models demonstrated increased diabetes mellitus risk across elevated CVAI or ABSI quartiles regardless of sex even after adjustment (Supplemental Table 3), with the association between CVAI and baseline diabetes being more evident in women than in men (all Pinteraction < 0.05). Overall, higher ABSI was also associated with higher diabetes mellitus risk, even after adjustment in both genders. These associations were, however, less prominent than those for CVAI (adjusted OR < 2 in models). Among the four anthropometric indices, CVAI had the highest area under ROC (AUC) for baseline diabetes in men (AUC = 0.65, 95% CI: 0.62–0.67), in women (AUC = 0.68, 95% CI: 0.66–0.70), and in all participants (AUC = 0.66, 95% CI: 0.65–0.68), followed by WC (AUC: 0.63, 0.66 and 0.65 for male, female, and all subjects) and BMI (Supplemental Figure 2 A-C). However, ABSI had the lowest AUC for diabetes in men (AUC = 0.56, 95% CI: 0.54–0.58), in women (AUC = 0.57, 95% CI: 0.55–0.59), and in all subjects (AUC = 0.57, 95% CI: 0.55–0.58). CVAI alone led to a significantly increased AUC over WC and other indices regardless of gender (all ∆ AUC P < 0.05, Supplemental Figure 2 A-C). Supplemental Table 2 shows the sensitivity, specificity, and corresponding optimal cut-off values of each index for identifying diabetes by gender. The optimal CVAI cut-off for identifying baseline diabetes mellitus was 126.09 in men and 117.77 in women.
Adiposity Measures as a Predictor of New-Onset Diabetes
Out of 6710 baseline non-diabetes mellitus subjects, 1360 developed new-onset type 2 diabetes mellitus during a median of 5.25 years (IQR: 3.07–6.44 years) follow-up. The number of mortality events recorded was 491, resulting in a composite of 1699 subjects with new-onset diabetes mellitus or death. Higher incidence rates of new-onset diabetes mellitus were observed across CVAI tertile groups (15.7%, 18.7%, and 26.4% for CAVI Q1, Q2, and Q3, respectively, P < 0.001) and new-onset diabetes mellitus/mortality group (19.0%, 21.5%, and 29.2% for CAVI Q1, Q2, and Q3, respectively, P < 0.001), with significantly higher CVAI observed in both cases (both P < 0.05) (Figure 2). New onset of diabetes mellitus was not statistically different across ABSI tertiles (20%, 21.1%, and 18.9% for ABSI Q1, Q2, and Q3, respectively, P = 0.144), nor was composite new-onset diabetes mellitus and death (22.4%, 24.2%, and 23.0% for ABSI Q1, Q2, and Q3, respectively, P = 0.34) (Figure 2). Higher CVAI was further independently predictive for new-onset diabetes mellitus (adjusted hazard ratio [aHR]: 1.26, 95% CI: 1.18–1.34) (Table 2) or composite new-onset diabetes mellitus/death (aHR: 1.17, 95% CI: 1.10–1.25, both P < 0.001) (Supplementary Table 4) in adjusted models, although these associations were non-significant when ABSI was used.