The Accuracy of Visceral Adiposity Index for the Screening of Metabolic Syndrome: A Systematic Review and Meta-Analysis

Gender-specific accuracy of lipid accumulation product index for the screening of metabolic syndrome in general adults: a meta-analysis and comparative analysis with other adiposity indicators

BACKGROUND

Lipid accumulation product (LAP) is a novel predictor index of central lipid accumulation associated with metabolic and cardiovascular diseases. This study aims to investigate the accuracy of LAP for the screening of metabolic syndrome (MetS) in general adult males and females and its comparison with other lipid-related indicators.

METHODS

A systematic literature search was conducted in PubMed, Scopus, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and ProQuest for eligible studies up to May 8, 2024. Outcomes were pooled mean difference (MD), odds ratio (OR), and diagnostic accuracy parameters (sensitivity, specificity, and area under the summary receiver operating characteristic [AUSROC] curve). Comparative analysis was conducted using Z-test.

RESULTS

Forty-three studies involving 202,313 participants (98,164 males and 104,149 females) were included. Pooled MD analysis showed that LAP was 45.92 (P < 0.001) and 41.70 units (P < 0.001) higher in men and women with MetS, respectively. LAP was also significantly associated with MetS, with pooled ORs of 1.07 (P < 0.001) in men and 1.08 (P < 0.001) in women. In men, LAP could detect MetS with a pooled sensitivity of 85% (95% CI: 82%-87%), specificity of 81% (95% CI: 80%-83%), and AUSROC curve of 0.88 (95% CI: 0.85-0.90), while in women, LAP had a sensitivity of 83% (95% CI: 80%-86%), specificity of 80% (95% CI: 78%-82%), and AUSROC curve of 0.88 (95% CI: 0.85-0.91). LAP had a significantly higher AUSROC curve (P < 0.05) for detecting MetS compared to body mass index (BMI), waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), body roundness index (BRI), a body shape index (ABSI), body adiposity index (BAI), conicity index (CI) in both genders, and waist circumference (WC) and abdominal volume index (AVI) in females.

CONCLUSION

LAP may serve as a simple, cost-effective, and more accurate screening tool for MetS in general adult male and female populations.

Association of the visceral adiposity index with femur bone mineral density and osteoporosis among the U.S. older adults from NHANES 2005-2020: a cross-sectional study

Background

The visceral adiposity index (VAI) is a marker of abdominal fat distribution and adipose tissue function. However, the association between VAI and femur bone mineral density (BMD) and osteoporosis is unclear among the U.S. older adults.

Methods

Cross-sectional data for adults aged 60 years and older from the 2007-2020 National Health and Nutrition Examination Survey (NHANES) were included. Multivariable linear and logistic regression were used to evaluate the association between VAI and femur BMD and osteoporosis. We used the smooth curve fitting to address nonlinearity. Moreover, a two-piecewise linear regression model was used to explain the nonlinearity further.

Results

The findings of the multivariable logistic regression models showed that as the VAI value increased by one unit, the prevalence of osteoporosis decreased by 1.2% after adjusting for covariates associated with osteoporosis. The multivariable linear regression models demonstrated that VAI was positively correlated with femur BMD. Further analysis revealed an inverted L-shaped and inverted U-shaped relationship between VAI and femur BMD at different sites.

Conclusions

Our findings indicated that an increased VAI is independently linked to a higher prevalence of osteoporosis among the U.S. older adults. Further analysis reveals that once VAI reaches a certain threshold, femur BMD no longer increases and may even decrease. This suggests that a moderate accumulation of visceral fat may be beneficial for bone health, while excessive visceral fat could potentially have detrimental effects.

The Visceral Adiposity Index Is a Better Predictor of Excess Visceral Fat in Military Pilots: A Cross-sectional Observational Study

INTRODUCTION

Visceral adipose tissue (VAT) is related to cardiometabolic risk. Estimating it using the visceral adiposity index (VAI) could identify this risk in the Brazilian Air Force (BAF) aviator population. The aim here is to verify the predictive capacity of the VAI for identifying visceral fat areas compared to traditional obesity indicators in BAF pilots.

MATERIALS AND METHODS

Forty male BAF pilots were recruited. The study was conducted in two stages: the first applied a structured questionnaire to characterize the sample and identify sedentary behavior and the second obtained nutritional, anthropometric, and body composition data, carrying out biochemical and magnetic resonance imaging tests and investigating physical activity level in this stage. The comparison of the predictive capacity of the VAI with that of other adiposity indicators (body mass index [BMI], waist circumference, waist-height ratio, waist-hip ratio, and neck circumference) for detecting increased VAT and the determination of the optimal cutoff points for the different adiposity indicators were carried out using receiving operating characteristic (ROC) curves. An association was verified between the adiposity indicators and excess visceral fat using Poisson regression analysis with robust variance.

RESULTS

The VAI presented a better predictive capacity for VAT (area under the ROC curve = 0.941), while the BMI did not present diagnostic accuracy (95% CI < 0.5). The strength of the association with high visceral fat was also greater for the VAI than for the other indicators evaluated.

CONCLUSIONS

The VAI was shown to be a better predictor of excess VAT in relation to the other indicators studied. As it is a more easy-access and lower-cost technique than resonance, it enables greater applicability in tracing and monitoring the visceral obesity of a large contingent of military personnel.

Exploring the Potential Performance of Fibroscan for Predicting and Evaluating Metabolic Syndrome using a Feature Selected Strategy of Machine Learning

Metabolic syndrome (MetS) includes several conditions that can increase an individual's predisposition to high-risk cardiovascular events, morbidity, and mortality. Non-alcoholic fatty liver disease (NAFLD) is a predominant cause of cirrhosis, which is a global indicator of liver transplantation and is considered the hepatic manifestation of MetS. FibroScan^® provides an accurate and non-invasive method for assessing liver steatosis and fibrosis in patients with NAFLD, via a controlled attenuation parameter (CAP) and liver stiffness measurement (LSM or E) scores and has been widely used in current clinical practice. Several machine learning (ML) models with a recursive feature elimination (RFE) algorithm were applied to evaluate the importance of the CAP score. Analysis by ANOVA revealed that five symptoms at different CAP and E score levels were significant. All eight ML models had accuracy scores > 0.9, while treebags and random forest had the best kappa values (0.6439 and 0.6533, respectively). The CAP score was the most important variable in the seven ML models. Machine learning models with RFE demonstrated that using the CAP score to identify patients with MetS may be feasible. Thus, a combination of CAP scores and other significant biomarkers could be used for early detection in predicting MetS.

The association between visceral adiposity index and decreased renal function: A population-based study

Aims

We aimed to investigate the association of visceral adiposity index (VAI) with decreased renal function in US adults.

Design and methods

Cross-sectional data were analyzed for 35,018 adults in the National Health and Nutrition Examination Survey (NHANES) 2005–2018. VAI was determined using waist circumference, body mass index (BMI), triglycerides (TGs) and high-density lipoprotein-cholesterol. Albuminuria was defined as urinary albumin-to-creatinine ratio (ACR) &gt;30 mg/g. A low estimated-glomerular filtration rate (eGFR) was defined as an eGFR lower than 60 ml/min/1.73 m2. Chronic kidney disease (CKD) was defined as either albuminuria or low-eGFR. A multivariable logistic regression analysis was utilized to explore the relationship of VAI with albuminuria, low-eGFR and CKD. Subgroup analysis and interaction tests were also conducted.

Results

A total of 35,018 participants were enrolled with albuminuria, low-eGFR, and CKD prevalence rates of 5.18, 6.42, and 10.62%, respectively, which increased with the higher VAI tertiles. After full adjustment, a positive association of VAI with albuminuria (OR = 1.03, 95% CI: 1.00, 1.06) and CKD (OR = 1.04, 95% CI: 1.02, 1.06) was observed. Participants in the highest VAI tertile had a significantly 30% increased risk for albuminuria (OR = 1.30, 95% CI: 1.07, 1.58) and a 27% increased risk for CKD (OR = 1.27, 95% CI: 1.08, 1.49) compared with those in the lowest VAI tertile. No statistically significant association between VAI and low-eGFR was detected. Subgroup analysis and the interaction term indicated that there was no significant difference among different stratifications.

Conclusion

Visceral adiposity accumulation evaluating by VAI was associated with increased likelihood of the decline in renal function.

Diagnostic value of visceral adiposity index in chronic kidney disease: a meta-analysis

AIMS

Several studies have revealed inconsistencies about the predictive properties of visceral adiposity index (VAI) in identifying chronic kidney disease (CKD). To date, it is unclear whether the VAI is a valuable diagnostic tool for CKD. This study intended to evaluate the predictive properties of the VAI in identifying CKD.

METHODS

The PubMed, Embase, Web of Science, and Cochrane databases were searched for all studies that met our criteria from the earliest available article until November 2022. Articles were assessed for quality using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The heterogeneity was explored with the Cochran Q test and I² test. Publication bias was detected using Deek's Funnel plot. Review Manager 5.3, Meta-disc 1.4, and STATA 15.0 were used for our study.

RESULTS

Seven studies involving 65,504 participants met our selection criteria and were therefore included in the analysis. Pooled sensitivity (Sen), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and area under the curve (AUC) were 0.67 (95%CI: 0.54-0.77), 0.75 (95%CI: 0.65-0.83), 2.7 (95%CI: 1.7-4.2), 0.44 (95%CI: 0.29-0.66), 6 (95%CI:3.00-14.00) and 0.77 (95%CI: 0.74-0.81), respectively. Subgroup analysis indicated that mean age of subjects was the potential source of heterogeneity. The Fagan diagram found that the predictive properties of CKD were 73% when the pretest probability was set to 50%.

CONCLUSIONS

The VAI is a valuable agent in predicting CKD and may be helpful in the detection of CKD. More studies are needed for further validation.

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

Objective

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.

Method

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.

Results

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.

Conclusion

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.

Obesity in Caucasian Seniors on the Rise: Is It Truly Harmful? Results of the PolSenior2 Study

Obesity is associated with an increased risk of morbidity and mortality; however, data suggest that in old age, obesity is not detrimental. The study’s objective was to verify whether obesity frequency still increases in Polish Caucasian seniors and to verify the “obesity paradox”. Five thousand and fifty-seven community-dwelling individuals aged ≥ 65 years completed a detailed medical questionnaire, underwent measurements of the body mass index (BMI) and the waist circumference (WC), and an evaluation of physical and cognitive performances. Over a decade, general obesity increased by 2.1%, mostly due to a 3.9% increase in men. Abdominal obesity increased by 1.0%, mainly due to males, in whom it increased by 3.9%. Obesity increased the risk of several aging-related diseases, but this effect was less pronounced in the oldest-old. Obesity did not adversely affect the physical and cognitive functioning or mortality. Through a multivariable analysis, the BMI and WC remained the independent predictors of the Katz Activities of Daily Living score (p < 0.001 and p < 0.05, respectively) and Mini-Mental State Examination score (both p < 0.001). The Kaplan−Meier survival curves revealed that overweight and obesity classes 1 and 2 were associated with the lowest mortality. Through a multivariable analysis, overweight, class 1 obesity, and abdominal obesity remained the independent predictors of a decreased mortality (all p < 0.001). In conclusion, we found that overweight and obesity are not detrimental in seniors, including the oldest-old. We suggest that the anthropometric values defining obesity should be modified for age-advanced people.

Cardiovascular Disease Risk Reduction and Body Mass Index

PURPOSE OF REVIEW

Anti-hypertensive and lipid lowering therapy addresses only half of the cardiovascular disease risk in patients with body mass index > 30 kg/m², i.e., obesity. We examine newer aspects of obesity pathobiology that underlie the partial effectiveness of anti-hypertensive lipid lowering therapy for the reduction of cardiovascular disease risk in obesity.

RECENT FINDINGS

Obesity-related insulin resistance, vascular endothelium dysfunction, increased sympathetic nervous system/renin-angiotensin-aldosterone system activity, and glomerulopathy lead to type 2 diabetes, coronary atherosclerosis, and chronic disease kidney disease that besides hypertension and dyslipidemia increase cardiovascular disease risk. Obesity increases cardiovascular disease risk through multiple pathways. Optimal reduction of cardiovascular disease risk in patients with obesity is likely to require therapy targeted at both obesity and obesity-associated conditions.

The CUN-BAE, Deurenberg Fat Mass, and visceral adiposity index as confident anthropometric indices for early detection of metabolic syndrome components in adults

There is no definition for the metabolic syndrome; visceral obesity, elevated lipids and glucose, and hypertension coexist. The aim of the study is to determine which anthropometric indicators best determine it. Cross-sectional study in 418,343 Spanish workers. Metabolic syndrome was determined using the NCEP-ATPIII, IDF and JIS criteria. The anthropometric variables studied were: body mass index, waist circumference, waist-to-height ratio, CUNBAE, Deuremberg formula, body fat index, body surface index, normalized weight adjusted index, body roundness index, body shape index, visceral adiposity index (VAI), dysfunctional adiposity index, conicity index, metabolic score for visceral fat (METS-VF), waist triglyceride index. In men, the anthropometric indices with the largest areas under the ROC curve are VAI with ATPIII criteria and JIS. If we use the IDF criteria: waist circumference and METS-VF, with the same result. In women, the largest areas under the curve were observed with the Deuremberg formula in both ATPIII and JIS while with the IDF criteria it is METS-VF. The most useful anthropometric indices for identifying metabolic syndrome are CUN-BAE and Deuremberg, followed by the VAI. A single definition of metabolic syndrome should be agreed to determine the best anthropometric index with predictive capacity for its diagnosis.

Visceral adiposity-related dietary patterns and the risk of cardiovascular disease in Iranian adults: A population-based cohort study

Background

Visceral obesity is a significant predictor of cardiovascular disease (CVD). Diet may associate with CVD risk through its effects on visceral adiposity. This study aimed to find dietary patterns (DPs) related to indicators of visceral adiposity and to determine whether the DPs were associated with CVD risk.

Methods

This prospective study included 2,496 participants of the Tehran Lipid and Glucose Study (TLGS) without CVD, who were followed from the third study examination (2005–2008; baseline) to March 2018. DPs at baseline were determined using reduced rank regression (RRR) and partial least squares regression (PLS). The response variables were age and BMI-adjusted waist circumference (WC) and age-adjusted visceral adiposity index (VAI).

Results

Two and three DPs were retained with RRR and PLS, respectively. The first patterns of each method were mainly characterized by adjusted-WC (RRR: 10.8%, PLS: 8.6%); none of them were associated with CVD risk. The second pattern of RRR and the third pattern of PLS were mainly explained by adjusted-VAI (RRR: 3.3, PLS: 2.1%). After adjusting for CVD risk factors, the hazard ratios [95% confidence intervals (CI)] for CVD in the second and third tertiles of the RRR-pattern 2 were 1.76 (1.15, 2.69) and 1.55 (1.00, 2.43) vs. the first tertile (p-trend: 0.058). This pattern had high positive loadings for non-leafy vegetables, pickled vegetables, fried vegetables, and bread and high negative loadings for eggs, cakes, butter, jam-honey, red meat, poultry, fish, juice, non-fermented dairy, and fruits. Per one SD increase in PLS-pattern 3 score, the risk of CVD was 19% higher (95%CI = 3–38%). This positive association was also observed across tertiles of the pattern (p-trend: 0.032). This pattern was characterized by high intakes of leafy vegetables, non-leafy vegetables, organ meat, soft drinks, olive oil, pickled vegetables, fried vegetables, and bread and low intakes of biscuits, cakes, butter, eggs, and non-fermented dairy.

Conclusion

For each of the RRR and PLS approaches, a visceral-related DP that was positively linked to CVD was identified. These two patterns had a modest correlation. The pattern generated by PLS explained more variations in food groups and offered stronger evidence of association with CVD than the RRR-derived pattern.

Waist Circumference and Its Association With Premenstrual Food Craving: The PHASE Longitudinal Study

Visceral adiposity is a significant marker of all-cause mortality. Reproductive age women are at a considerable risk for developing visceral adiposity; however, the associated factors are poorly understood. The proposed study evaluated whether food craving experienced during the premenstrual period is associated with waist circumference. Forty-six women (mean BMI = 24.36) prospectively provided daily ratings of food craving across two-three menstrual cycles (122 cycles total). Their premenstrual rating of food craving was contrasted against food craving in the follicular phase to derive a corrected summary score of the premenstrual food craving increase. Study groups were divided into normal (n = 26) and obese (n = 20) based on the 80 cm waist circumference cutoff signifying an increase in risk. Waist circumference category was significantly associated with premenstrual food cravings [F _(1,44) = 5.12, p = 0.028]. Post hoc comparisons using the Tukey HSD test (95% family-wise confidence level) showed that the mean score for the food craving effect size was 0.35 higher for the abdominally obese vs. normal study groups (95% CI: 0.039 to 0.67). The result was statistically significant even following inclusion of BMI in the model, pointing to a particularly dangerous process of central fat accumulation. The present study establishes an association between temporal vulnerability to an increased food-related behavior and a marker of metabolic abnormality risk (i.e., waist circumference), thereby forming a basis for integrating the premenstruum as a viable intervention target for this at-risk sex and age group.

The Visceral Adiposity Index in Non-Alcoholic Fatty Liver Disease and Liver Fibrosis-Systematic Review and Meta-Analysis

(1) Background: In order to avoid a liver biopsy in non-alcoholic fatty liver disease (NAFLD), several noninvasive biomarkers have been studied lately. Therefore, we aimed to evaluate the visceral adiposity index (VAI) in NAFLD and liver fibrosis, in addition to its accuracy in predicting NAFLD and NASH. (2) Methods: We searched PubMed, Embase, Scopus, and Cochrane Library, identifying observational studies assessing the VAI in NAFLD and liver fibrosis. QUADAS-2 was used to evaluate the quality of included studies. The principal summary outcomes were mean difference (MD) and area under the curve (AUC). (3) Results: A total of 24 studies were included in our review. VAI levels were significantly increased in NAFLD (biopsy-proven and ultrasound-diagnosed), simple steatosis vs. controls, and severe steatosis vs. simple steatosis. However, no significant MD was found according to sex, liver fibrosis severity, simple vs. moderate and moderate vs. severe steatosis, pediatric NAFLD, and NASH patients. The VAI predicted NAFLD (AUC 0.767) and NASH (AUC 0.732). (4) Conclusions: The VAI has a predictive value in diagnosing NAFLD and NASH, with significantly increased values in adult NAFLD patients, simple steatosis compared to controls, and severe steatosis compared to simple steatosis.