Visceral adiposity measures are strongly associated with cardiovascular disease among female participants in Southwest China: A population-based prospective study.

Controversy remains regarding the prediction effects of different adiposity measure indicators for the risk of cardiovascular disease (CVD). Our study aimed to assess the associations of three traditional anthropometric indicators, namely, waist circumference (WC), waist-to-height ratio (WHtR), and body mass index (BMI) as well as three non-traditional anthropometric indicators, namely, the Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), and body shape index (ABSI), with the risk of CVD among Southwest Chinese population. Our study was based on the Guizhou Population Health Cohort Study (GPHCS) conducted from 2010 to 2020. A total of 9,280 participants were recruited from 12 areas in Guizhou Province, China, from November 2010 to December 2012, and followed up for major chronic diseases until December 2020. A total of 7,837 individuals with valid data were included in this analysis. The gender-specific associations of WC, WHtR, BMI, CVAI, LAP, and ABSI with CVD were evaluated using Cox proportional hazards models. Receiver operating characteristic (ROC) curve analysis was used to estimate the prediction powers of different indicators for CVD. No association of six indicators with CVD was observed among male participants. Female participants with either WC-based central obesity (HR: 1.82, 95% CI: 1.12-2.97) or WHtR-based central obesity (HR: 1.68, 95% CI: 1.07-2.64) had a higher risk of CVD, after adjusted for age, area, ethnic group, smoking, alcohol drinking, MET, previous history of diabetes, hypertension and dyslipidemia, medication use, and nutraceutical intake. Compared with female participants in the lowest quartile (Q1), those in the highest quartile (Q4) of WHtR (HR: 2.24, 95% CI: 1.17-4.27), CVAI (HR: 3.98, 95% CI: 1.87-8.49), and ABSI (HR: 1.94, 95% CI: 1.06-3.52) had an increased risk for incident CVD. CAVI showed the maximum predictive power of CVD with the biggest AUC of 0.687 (95% CI: 0.654-0.720) compared to other indicators in female participants. Visceral adiposity measures, especially CVAI, are stronger predictive indicators of CVD among female and not male participants in Southwest China. Different anthropometric indexes need to be combined to comprehensively assess health risks.

Wang Y ，Zhao X ，Chen Y ，Yao Y ，Zhang Y ，Wang N ，Liu T ，Fu C ... -  《Frontiers in Endocrinology》

Dose-response association between Chinese visceral adiposity index and cardiovascular disease: a national prospective cohort study.

Chinese visceral adiposity index (CVAI) is a reliable visceral obesity index, but the association between CVAI and risk of cardiovascular disease (CVD) remains unclear. We explored the associations of CVAI with incident CVD, heart disease, and stroke and compared the predictive power of CVAI with other obesity indices based on a national cohort study. The present study included 7,439 participants aged ≥45 years from China Health and Retirement Longitudinal Study (CHARLS). Cox regression models were applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Restricted cubic splines analyses were adopted to model the dose-response associations. Receiver operator characteristic (ROC) analyses were used to compare the predictive ability of different obesity indices (CVAI, visceral adiposity index [VAI], a body shape index [ABSI], conicity index [CI], waist circumference [WC], and body mass index [BMI]). During 7 years' follow-up, 1,326 incident CVD, 1,032 incident heart disease, and 399 stroke cases were identified. The HRs (95% CI) of CVD, heart disease, and stroke were 1.50 (1.25-1.79), 1.29 (1.05-1.57), and 2.45 (1.74-3.45) for quartile 4 versus quartile 1 in CVAI. Linear associations of CVAI with CVD, heart disease, and stroke were observed (P nonlinear >0.05) and per-standard deviation (SD) increase was associated with 17% (HR 1.17, 1.10-1.24), 12% (1.12, 1.04-1.20), and 31% (1.31, 1.18-1.46) increased risk, respectively. Per-SD increase in CVAI conferred higher risk in participants aged<60 years than those aged ≥60 years (P interaction<0.05). ROC analyses showed that CVAI had higher predictive value than other obesity indices (P<0.05). CVAI was linearly associated with risk of CVD, heart disease, and stroke and had best performance for predicting incident CVD. Our findings indicate CVAI as a reliable and applicable obesity index to identify higher risk of CVD.

Ren Y ，Hu Q ，Li Z ，Zhang X ，Yang L ，Kong L ... -  《Frontiers in Endocrinology》

The Chinese visceral adiposity index: a novel indicator more closely related to cardiovascular disease than other abdominal obesity indices among postmenopausal women.

Liu L ，Peng J ，Zang D ，Zhang Y ，Wu Z ，Song C ，Chen S ，Guo D ，Lu F ，Zheng T ，Yang J ... -  《Journal of Translational Medicine》

Comparison of obesity indicators for predicting cardiovascular risk factors and multimorbidity among the Chinese population based on ROC analysis.

To date, the best obesity-related indicators (ORIs) for predicting hypertension, dyslipidaemia, Type 2 diabetes mellitus (T2DM) and multimorbidity are still controversial. This study assessed the ability of 17 ORIs [body mass index (BMI), body fat percentage (BF%), c-index, Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), a body shape index (ABSI), body adiposity index (BAI), waist circumference (WC), waist-hip ratio (WHR), waist-to-height ratio (WHtR), body roundness index (BRI), abdominal volume index (AVI), triglyceride glucose index (TYG), lipid accumulation product (LAP), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), waist triglyceride index (WTI) and cardiometabolic index (CMI)] to predict hypertension, dyslipidemia, T2DM, and multimorbidity in populations aged 40-69 years. From November 2017 to December 2022, 10,432 compliant residents participated in this study. Receiver operating characteristic curves were used to assess the ability of ORIs to predict target diseases across the whole population and genders. The DeLong test was used to analyse the heterogeneity of area under curves (AUCs). Multivariable logistic regression was used to analyse the association of ORIs with hypertension, dyslipidaemia, T2DM, and multimorbidity. The prevalence of hypertension, dyslipidaemia, T2DM, and multimorbidity was 67.46%, 39.36%, 12.54% and 63.58%, respectively. After excluding ORIs associated with the target disease components, in the whole population, CVAI (AUC = 0.656), BMI (AUC = 0.655, not significantly different from WC and AVI), CVAI (AUC = 0.645, not significantly different from LAP, CMI, WHR, and WTI), and TYG (AUC = 0.740) were the best predictor of hypertension, dyslipidemia, T2DM, and multimorbidity, respectively (all P < 0.05). In the male population, BF% (AUC = 0.677), BMI (AUC = 0.698), CMI (AUC = 0.648, not significantly different from LAP and CVAI), and TYG (AUC = 0.741) were the best predictors (all P < 0.05). In the female population, CVAI (AUC = 0.677), CUN-BAE (AUC = 0.623, not significantly different from BF%, WC, WHR, WHtR, BRI and BMI), CVAI (AUC = 0.657, not significantly different from WHR), TYG (AUC = 0.740) were the best predictors (all P < 0.05). After adjusting for all covariates, all ORIs were significantly associated with hypertension, dyslipidaemia, T2DM, and multimorbidity (all P < 0.05), except for ABSI and hypertension and BAI and T2DM, which were insignificant. Ultimately, after considering the heterogeneity of prediction of ORIs among different populations, for hypertension, BF% was the best indicator for men and CVAI for the rest of the population. The best predictors of dyslipidaemia, T2DM, and multimorbidity were BMI, CVAI and TYG, respectively. Screening for common chronic diseases in combination with these factors may help to improve the effectiveness.

Feng X ，Zhu J ，Hua Z ，Yao S ，Tong H ... -  《Scientific Reports》

Obesity- and lipid-related indices as a predictor of obesity metabolic syndrome in a national cohort study.

Metabolic syndrome is a common condition among middle-aged and elderly people. Recent studies have reported the association between obesity- and lipid-related indices and metabolic syndrome, but whether those conditions could predict metabolic syndrome is still inconsistent in a few longitudinal studies. In our study, we aimed to predict metabolic syndrome by obesity- and lipid-related indices in middle-aged and elderly Chinese adults. A national cohort study that consisted of 3,640 adults (≥45 years) was conducted. A total of 13 obesity- and lipid-related indices, including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), conicity index (CI), visceral adiposity index (VAI), Chinese visceral adiposity index (CVAI), lipid accumulation product (LAP), a body shape index (ABSI), body roundness index (BRI), and triglyceride glucose index (TyG-index) and its correlation index (TyG-BMI, TyG-WC, and TyG-WHtR), were recorded. Metabolic syndrome (MetS) was defined based on the criteria of the National Cholesterol Education Program Adult Treatment Panel III (2005). Participants were categorized into two groups according to the different sex. Binary logistic regression analyses were used to evaluate the associations between the 13 obesity- and lipid-related indices and MetS. Receiver operating characteristic (ROC) curve studies were used to identify the best predictor of MetS. A total of 13 obesity- and lipid-related indices were independently associated with MetS risk, even after adjustment for age, sex, educational status, marital status, current residence, history of drinking, history of smoking, taking activities, having regular exercises, and chronic diseases. The ROC analysis revealed that the 12 obesity- and lipid-related indices included in the study were able to discriminate MetS [area under the ROC curves (AUC > 0.6, P < 0.05)] and ABSI was not able to discriminate MetS [area under the ROC curves (AUC < 0.6, P > 0.05)]. The AUC of TyG-BMI was the highest in men, and that of CVAI was the highest in women. The cutoff values for men and women were 187.919 and 86.785, respectively. The AUCs of TyG-BMI, CVAI, TyG-WC, LAP, TyG-WHtR, BMI, WC, WHtR, BRI, VAI, TyG index, CI, and ABSI were 0.755, 0.752, 0.749, 0.745, 0.735, 0.732, 0.730, 0.710, 0.710, 0.674, 0.646, 0.622, and 0.537 for men, respectively. The AUCs of CVAI, LAP, TyG-WC, TyG-WHtR, TyG-BMI, WC, WHtR, BRI, BMI, VAI, TyG-index, CI, and ABSI were 0.687, 0.674, 0.674, 0.663, 0.656, 0.654, 0.645, 0.645, 0.638, 0.632, 0.607, 0.596, and 0.543 for women, respectively. The AUC value for WHtR was equal to that for BRI in predicting MetS. The AUC value for LAP was equal to that for TyG-WC in predicting MetS for women. Among middle-aged and older adults, all obesity- and lipid-related indices, except ABSI, were able to predict MetS. In addition, in men, TyG-BMI is the best indicator to indicate MetS, and in women, CVAI is considered the best hand to indicate MetS. At the same time, TyG-BMI, TyG-WC, and TyG-WHtR performed better than BMI, WC, and WHtR in predicting MetS in both men and women. Therefore, the lipid-related index outperforms the obesity-related index in predicting MetS. In addition to CVAI, LAP showed a good predictive correlation, even more closely than lipid-related factors in predicting MetS in women. It is worth noting that ABSI performed poorly, was not statistically significant in either men or women, and was not predictive of MetS.

Gui J ，Li Y ，Liu H ，Guo LL ，Li J ，Lei Y ，Li X ，Sun L ，Yang L ，Yuan T ，Wang C ，Zhang D ，Wei H ，Li J ，Liu M ，Hua Y ，Zhang L ... -  《Frontiers in Public Health》