Ratio of visceral fat area to body fat mass (VBR) is a superior predictor of coronary heart disease

To the Editor: Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality globally, with coronary heart disease (CHD) exhibiting the highest mortality rate. Obesity is an important risk factor for cardiometabolic complication and CVD. Visceral adipose (VA) and subcutaneous adipose (SA) tissues exert differential and possibly opposing effects on cardio-metabolic outcomes.[1,2] The currently applied adiposity indices are inefficient in predicting CHD. Research in which the discriminatory power of adiposity indices are compared in absolute and relative terms is inadequate, and few have compared men and women in this regard. We performed anthropometric and bioelectrical impedance analysis (BIA) measurements in Chinese adults and proposed a novel BIA measurement — the visceral fat area (VFA) to the body fat mass (BFM) ratio (VBR) — hypothesizing that the VBR could better assess cardiovascular risk with respect to visceral fat. We therefore assessed the efficacy of VBR and then compared it with the commonly used adiposity indices of body mass index (BMI), waist-to-hip ratio (WHR), BFM, percentage of body fat (PBF), and VFA in identifying CHD in both men and women so as to determine whether VBR is superior to the aforementioned indices. We analyzed a portion of the baseline data from the Beijing–Tianjin–Hebei (BTH) Medical Examination Cohort, which was conducted by recruiting adults undergoing annual medical examination in the BTH region of China from September of 2018 to January of 2020.[3] Individuals who were pregnant, in a state of physical infection, had implanted heart pacemakers, or who could not stand independently were excluded. Our study protocol was approved by the Ethics Review Boards of Nankai University (No. NKUIRB2016063). Height and weight were measured using the same device (GL-310, Seoul, Korea), and waist and hip circumferences were measured manually. We determined BFM, PBF, and VFA using a multifrequency impedance plethysmograph body-composition analyzer (Inbody-770, Seoul, Korea). Participants were instructed to fast for 8–10 h and not to engage in strenuous activity before the following morning's measurements. A standard questionnaire was used to collect data on participants’ age, sex, ethnicity, highest educational level achieved, marital status, occupation, personal, and family history of CHD, alcohol drinking, tobacco smoking, and physical exercise. All measurements were conducted by professional medical staff using standard methods.[4,5] Statistical analyses were performed using the Statistical Package for Social Sciences (SPSS), version 24.0 (SPSS Inc., Chicago, IL, USA) and MedCalc (MedCalc Software, Mariakerke, Belgium). Considering sex differences in adiposity distribution and CHD prevalence, all statistical analyses were stratified by sex. Normally distributed continuous variables are presented as mean ± standard deviation (SD) and compared with t tests, while variables that were not normally distributed are described using medians and interquartile ranges and analyzed by applying the rank-sum test. Categorical data are presented as numbers and percentages and compared with the chi-squared test. We exploited multivariate logistic regression to assess the relationships between the adiposity indices and CHD, adjusting for age, educational level, ethnicity, marital status, occupation, smoking, alcohol consumption, physical exercise, and a family history of heart disease. Before the analysis, the adiposity indices were standardized (i.e., we took the original data, subtracted the average, and then divided by the SD), such that the odds ratios (ORs) indicated the increase in CHD risk per SD. We used receiver operating characteristic (ROC) curve analysis to compare predictive validity. The area under the ROC curve (AUC) was then measured to examine the screening power for each adiposity index. Optimal cutoff values were measured by the Youden index, and the DeLong method was used to assess whether the differences between AUC values for the compared indicators were significant. Two-tailed P values<0.05 were considered to be statistically significant. As summarized in [Supplementary Table 1, https://links.lww.com/CM9/B433], we included 12,060 individuals aged 20 to 91 years with a median age of 40 (interquartile range, 32–54) years, of which 42.36% (n = 5109) were men. The overall prevalence of CHD was 2.65% (320/12,060) and it was higher in males than in females (3.54% (181/5109) vs. 2.00% (139/6951), P < 0.05). Younger age, college or undergraduate education, being single were negatively associated with CHD (all P < 0.05), while having a family history of CHD was positively associated with CHD both in men and women. Drinking alcohol was negatively associated with CHD in males (all P < 0.05). CHD patients reported engaging in more exercise than non-CHD individuals, and we discerned no statistically significant differences with respect to ethnicity or smoking status between CHD patients and non-CHD individuals regardless of sex. The mean VBR was larger in men than in women (P < 0.001). Compared with individuals without CHD, those with CHD exhibited a high VBR, BMI, WHR, BFM, PBF, and VFA in both men (P = 0.008 for BMI, and P < 0.001 for all other indices) and women (all P < 0.001). As shown in Figure 1, the adjusted standardized ORs regarding VBR, BMI, WHR, BFM, PBF, and VFA for CHD were significantly higher than the reference level in both men and women, suggesting that a 1-SD increase in each index was associated with increased risk of CHD in both sexes (except for BMI in men). VBR demonstrated the largest aOR (2.00; 95% confidence interval [CI], 1.69–2.37) for CHD in females, followed in a descending order by VFA (1.80; 95% CI, 1.54–2.10), PBF (1.76; 95% CI, 1.47–2.11), WHR (1.66; 95% CI, 1.41–1.96), BMI (1.46; 95% CI, 1.25–1.70), and BFM (1.42; 95% CI, 1.22–1.65). VFA demonstrated the largest aOR for CHD among males (1.46; 95% CI, 1.27–1.69), followed in a descending order by PBF (1.43; 95% CI, 1.22–1.67), WHR (1.33; 95% CI, 1.14–1.54), VBR (1.21; 95% CI, 1.10–1.34), and BFM (1.21; 95% CI, 1.04–1.39).Figure 1: Standardized ORs and ROC analysis of obesity indices for CHD by sex. (A) Standardized ORs and 95% CIs of obesity indices for CHD by sex. (B) ROC analysis of BMI, WHR, BFM, PBF, VFA, and VBR for predicting CHD in men. (C) ROC analysis of BMI, WHR, BFM, PBF, VFA, and VBR for predicting CHD in women. BFM: Body fat mass; BMI: Body mass index; CHD: Coronary heart disease; ORs: Odds ratios; PBF: Percentage of body fat; ROC: Receiver operating characteristic; VBR: Visceral fat area to the body fat mass ratio; VFA: Visceral fat area; WHR; Waist-to-hip ratio.Supplementary Table 2, https://links.lww.com/CM9/B433 and Figure 1 reveal that all adiposity indices possessed significant identifying power for CHD in both men and women (all AUCs > 0.5), with VBR generating the largest AUCs in both females and males (0.821 and 0.753, respectively). The optimal cutoff value for VBR was 4.84 cm2/kg with a sensitivity and specificity of 84.89% and 65.15% in females, and 4.63 cm2/kg with a sensitivity and specificity of 76.80% and 66.34% in males, respectively. VFA exhibited the second largest AUCs both in males and females (0.676 and 0.745, respectively). However, VBR outperformed VFA in identifying CHD, with a greater AUC in both women (0.821 vs. 0.745, respectively) and men (0.753 vs. 0.676, respectively). BMI, manifested the lowest AUC for CHD in males (0.556), and BFM reflected the lowest AUC for CHD in females (0.671). AUC for VBR was statistically larger than for any other analyzed index in identifying subjects with CHD in both men and women (all P values <0.001). VFA exhibited the second greatest discriminatory power of CHD across sex. The AUC for VFA was siginificantly larger than the AUCs for BMI, WHR, BFM (all P < 0.001), and PBF (P = 0.01) in men and larger than for BMI, BFM, and PBF in women (all P < 0.001) — whereas the differences between the AUCs for VFA and WHR were not significant in women (P = 0.16). In the current study, we established a novel relative adiposity index, VBR, to examine the cardiovascular risk associated with visceral fat on the basis of whole-body fat. Compared with BMI, WHR, PBF, and BFM, VBR provides the magnitude of visceral fat relative to total body fat rather than the absolute amount of visceral fat and thus provides some indication of the distribution of fat accumulation in the human body. VBR demonstrated the optimal efficacy in identifying CHD among all our analyzed indices across sex. VA and SA differ in their differentiation, apoptotic mechanisms, spectrum of surface receptors, lipolysis, lipogenesis, and cytokine and adipokine secretion.[6] Researchers have demonstrated that regional adiposity is more closely associated with cardiometabolic risk than generalized obesity. Excessive visceral fat strongly predicts the onset and severity of insulin resistance and metabolic syndrome, while the accumulation of subcutaneous fat does not. Intriguingly, even lower cardiovascular risk is demonstrated among individuals with more subcutaneous fat, regardless of their visceral obesity. Based upon these findings, we established an index of visceral fat relative to total body fat to measure the relative magnitude of visceral fat and to then evaluate its efficacy in identifying CHD. Numerous studies employed conventional anthropometric measures of WC and WHR to measure abdominal obesity as substitutes for VA accumulation and BMI in measuring general obesity, and revealed associations between the conventional anthropometric indices and CVD. However, as BMI cannot be used to discriminate between fat and muscle mass, and WC and WHR cannot distinguish between abdominal subcutaneous fat and visceral fat, the extant literature does not consistently describe a predictive value for the noted indices of CHD. Although some investigators have ascertained that visceral fat is a far more powerful predictor of CVD risk, it is suggested that the predictive ability of VFA for CHD varies across different populations and that visceral adiposity is not completely reliable as a predictor thought to be superior to conventional anthropometric measures in predicting CHD. In the current research, although VFA was superior to WHR, PBF, and BFM in identifying CHD, it showed a statistically lower efficacy relative to the novel index of VBR in both males and females. In the current study, both VBR and VFA showed sex differences in identifying CHD — with a higher efficacy for females — consistent with previous studies.[7] While the accumulation of adipose tissue (especially VA) is a common cause of low-grade systemic inflammation, regional fat distribution differs by sex — with women exhibiting relatively less VA and more SA than men. Moreover, sympathetic nervous system (SNS) activation enhances the inflammatory response. In men, the SNS is activated in visceral but not SA tissue, whereas in women, the SNS is not activated in either visceral or subcutaneous fat; and this may explain the differential discriminatory ability of visceral adiposity in predicting CHD and its risk factors between men and women. In summary, VBR exhibited the most robust discriminatory efficacy for CHD across sex and outperformed BMI, WHR, BFM, PBF, and VFA — suggesting that VBR may offer clinical value in CHD prevention. However, additional prospective studies are needed to validate the causal relationship between VBR and CHD. Funding This study was supported by a grant from the Chinese Key Research and Development Program (No. 2016YFC0900604) from the Chinese Ministry of Science and Technology. Conflicts of interest None.