Visceral Adiposity Index: Simple Tool for Assessing Cardiometabolic Risk in Women with Polycystic Ovary Syndrome

Characteristics of Different Obesity Metabolic Indexes and their Correlation with Insulin Resistance in Patients with Polycystic Ovary Syndrome

This study is aimed to investigate the characteristics of different obesity metabolic indexes [body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), cardiometabolic index (CMI), body roundness index (BRI), visceral adiposity index (VAI), and lipid aggregation products (LAP)] and their correlation with insulin resistance (IR) in patients with polycystic ovary syndrome (PCOS). The study was conducted on 140 subjects with PCOS and 133 control subjects aged 18-44 years. According to insulin resistance index (HOMA-IR) ≥ 2.69 and HOMA-IR < 2.69, PCOS group members were divided into insulin resistance group and non-insulin resistance group. Anthropometric and serological characteristics of the population with PCOS focused on calculating different obesity metabolic indexes and HOMA-IR. BMI, WC, WHR, WHtR, CMI, BRI, VAI, and LAP were significantly higher in PCOS patients than in the control group, and the differences were all statistically significant (P < 0.05); In the insulin resistance group of PCOS patients, BMI, WC, WHR, WHtR, CMI, BRI, VAI, and LAP were significantly higher than in the non-insulin resistance group (P < 0.05). In PCOS patients, BMI (r = 0.658, P < 0.001), WC (r = 0.0.662, P < 0.001), WHR (r = 0.377, P < 0.001), WHtR (r = 0.660, P < 0.001), CMI (r = 0.698, P < 0.001), BRI (r = 0.757, P < 0.001), VAI (r = 0.640, P < 0.001), and LAP (r = 0.767, P < 0.001) were positively correlated with IR. Obesity metabolic indexes associated with PCOS were elevated in the PCOS group compared to the control group, and in the PCOS insulin-resistant group compared to the non-insulin resistant group. Novel obesity metabolic indexes, especially CMI, BRI and LAP, might be more appropriate for evaluating the risk of concurrent IR in PCOS.

Utility of Visceral Adiposity Index and Lipid Accumulation Products to Define Metabolically-Unhealthy Polycystic Ovary Syndrome in Asian Indian Women - A Cross Sectional Study

Background

Polycystic ovary syndrome (PCOS) women are at risk of developing diabetes, cardiovascular disease and metabolic syndrome (MetS) due to insulin resistance (IR) and hyperandrogenism (HA). Both visceral adiposity index (VAI) and lipid accumulation product (LAP) are simple outpatient department-based metric tools that have been introduced to screen PCOS women who are metabolically unhealthy and are at risk of development of MetS.

Aims

The aim of the study was to evaluate VAI and LAP in women with PCOS and to correlate them with metabolic and endocrine markers. The study also assessed these parameters amongst different PCOS phenotypes and determined their usefulness to define metabolically healthy PCOS (MH-PCOS) and metabolically unhealthy PCOS (MU-PCOS).

Settings and Design

The design of the study was a cross-sectional study.

Materials and Methods

Two hundred PCOS women were included in the study, and all the clinical, anthropometric, hormonal, biochemical and metabolic markers were assessed. The cohort was divided into MH-PCOS and MU-PCOS by the modified National Cholesterol Education Programme criteria. VAI and LAP were calculated and correlated with clinical, endocrine and metabolic parameters.

Statistical Analysis Used

Univariate and multivariate logistic regression analysis was used to study the independent role of VAI and LAP to predict MetS. Adjusted and unadjusted odds ratios were calculated. Receiver-operating characteristic (ROC) analysis was done to define cut-offs in Asian Indian women.

Results

VAI and LAP had good ability to correctly discriminate MU-PCOS from MH-PCOS (area under the curve [AUC] [95% confidence interval (CI)]: 0.89 [0.82-0.95]) and (AUC [95% CI [0.81-0.92] =0.86) using ROC, respectively. The sensitivity of VAI and LAP corresponding to the optimal cut-off of ≥2.76 and ≥48.06 (Youden) was 84.09% and 79.55%, respectively. Similarly, the specificity of VAI and LAP was 85.26% and 79.49%, respectively. VAI has a positive predictive value of 61.7% (95% CI [23.7%-40.3%]) and a negative predictive value of 95% (95% CI [88%-99.1%]). LAP has a positive predictive value of 53% (95% CI [40.3%-65.4%]) and a negative predictive value of 93.3% (95% CI [87.6%-96.9%]). PCOS women having VAI ≥ 2.76 had 19.3 times ([95% CI: 6.50-57.70]) more chance of developing MetS. PCOS women having LAP (≥48.06) have 3.7 times ([95% CI: 1.35-10.60]) more odds. There was no difference between ROC curves of VAI and LAP (P = 0.32).

Conclusion

VAI cut-off ≥ 2.76 and LAP with a cut-off of ≥ 48.06 may be used as markers for predicting MetS amongst PCOS women.

Correlation of Body Mass Index with Anthropometric and Biochemical Parameters Among Polycystic Ovary Syndrome Phenotypes

This was a prospective observational study, conducted at a tertiary care health centre in Rajasthan. A total of 68 women with PCOS (Rotterdam criteria) attending OPD at Department of Obstetrics and Gynecology qualified as per inclusion and exclusion criteria were included in the study. Each participant was examined for anthropometric and biochemical parameters. The largest phenotypic group was phenotype A, (41.17%); followed by B (26.47%); C (20.58%), and D (P + O) phenotypes (11.76%). Hyperandrogenic phenotypes (A, B, C), had significantly higher prevalence of deranged serum glucose (fasting and postprandial), lipid profile and serum TSH than normoandrogenic phenotype D. BMI was strongly correlated with anthropometric (p < 0.001) and biochemical parameters (p < 0.05) in phenotype A among four phenotypes of PCOS. Phenotype A was the most common form of PCOS and a strong correlation of BMI with waist circumference (WC), dyslipidemia and Sub-clinical hypothyroidism (SCH) was observed in women of this phenotype of PCOS. These results indicate that phenotype A is at increased risk of CVD and diabetes and phenotype D has least metabolic risks.

The Visceral Adiposity Index (VAI) and Lipid Accumulation Product (LAP) Are Predictors of Insulin Resistance and Hyperandrogenaemia in Obesity/Overweight Women with Polycystic Ovary Syndrome

Objective

Hyperandrogenaemia and insulin resistance (IR) are the main characteristics of polycystic ovary syndrome (PCOS). Here, we study to find appropriate markers predicting IR and hyperandrogenaemia of women with PCOS in northwest China.

Methods

According to body mass index (BMI), 953 patients with PCOS were divided into two groups. All the patients underwent physical examination and ultrasonography and collected elbow vein blood. Their BMI, waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), LAP, VAI, homeostasis model assessment index of insulin resistance (HOMA-IR), and free androgen index (FAI) were calculated. Each group (normal weight and obesity/overweight) was further divided into two subgroups according to their HOMA-IR and FAI: the IR+ subgroup/IR- subgroup and FAI+ subgroup/FAI- subgroup. Furthermore, we compared the clinical indices, hormone levels, and metabolic makers separately between these groups. The correlations between these parameters and HOMA-IR or FAI were tested; sensitivity, specificity, and receiver-operating characteristic (ROC) curves were calculated.

Results

In the obesity/overweight group, the VAI (best cut-off value: 2.27, area under the curve (AUC) = 0.699) and LAP (best cut-off value: 45.54, AUC = 0.680) were sensitive predictors of IR (sensitivity = 72% and sensitivity = 67%). Additionally, the VAI (best cut-off value: 2.13, AUC = 0.624) and LAP (best cut-off value: 51.18, AUC = 0.582) were sensitive predictors of FAI (sensitivity = 87% and sensitivity = 64%). In the normal weight group, BMI could preferably predict HOMA-IR (AUC = 0.717, best cut-off value: 21.62) and HOMA-IR could preferably predict FAI (best cut-off value: 2.11, AUC = 0.648).

Conclusion

Our data indicated that the VAI and LAP may contribute to the early identification of IR and hyperandrogenaemia in the obesity/overweight patients of PCOS. In normal weight PCOS, BMI was a better predictor to IR, and HOWA-IR was a better predictor to FAI.

Visceral Adiposity Index as an Indicator for Menstrual Disturbance, Hormonal and Metabolic Dysfunction in Polycystic Ovarian Syndrome

BACKGROUND

Increase in visceral adiposity is characteristic of polycystic ovarian syndrome (PCOS) and is the main cause of insulin resistance and hyperandrogenism. This study tried to compare the visceral adiposity index (VAI) in PCOS women and control population, thereby exploring its correlation with ovarian morphology, hormonal and metabolic dysfunction.

MATERIALS AND METHODS

Reproductive-age women who fulfilled the Rotterdam criteria for PCOS constituted the cases. Control population consisted of the same number of non-PCOS women. History of menstrual irregularity and features of hyperandrogenism were noted. Overnight fasting serum hormonal profile on second day of the cycle, oral glucose tolerance test (OGTT) and serum fasting insulin and lipid profile were obtained. Ultrasound evaluation was done simultaneously. Free androgen index (FAI), homeostatic model assessment of insulin resistance (HOMA-IR) and VAI were calculated.

RESULTS

Serum androgen levels and OGTT were greater in PCOS women. No significant difference was noted in serum fasting glucose, fasting insulin and lipid profile between cases and controls. Both systolic and diastolic blood pressures were significantly higher among women with PCOS. Mean ovarian volume, antral follicle count, FAI and HOMA-IR were higher in PCOS women. VAI was significantly higher in cases compared to controls. VAI demonstrated a strong negative correlation with number of menstrual cycles per year. Increasing VAI was associated with longer menstrual cycles and correlated positively with greater severity of anovulation. VAI also showed highly significant correlation with fasting blood glucose and statistically significant moderately strong positive correlation with OGTT values at two hours post glucose challenge, systolic blood pressure and mean ovarian volume. There was no demonstrable correlation between androgen levels or HOMA-IR values.

CONCLUSION

VAI is higher in women with PCOS. It correlates positively with features of disease severity and ovarian morphology. An assessment of VAI in PCOS women could be predictive of a greater propensity for development of classical metabolic risk factors.

Relationships Between Indicators of Metabolic Disorders and Selected Concentrations of Bioelements and Lead in Serum and Bone Tissue in Aging Men

BACKGROUND

The aim of this study was to investigate the relationships between serum and bone concentrations of selected bioelements, ie, zinc (Zn), copper (Cu), iron (Fe), chrome (Cr), magnesium (Mg), and selenium (Se), and a heavy metal, ie, lead (Pb), and the selected indicators of metabolic disorders - Visceral Adiposity Index (VAI), Lipid Accumulation Product (LAP) and Body Mass Index (BMI).

MATERIAL AND METHODS

The study comprised 151 men aged 60 to 75 years who were scheduled for hip replacement surgery due to osteoarthritis. The concentrations of elements in the serum and bone tissue were measured using inductively coupled plasma optical emission spectrometry (Mg, Zn, Cu, Cr, Fe, and Pb) and the spectrofluorometric method (Se). Fasting plasma glucose (FPG), high-density cholesterol (HDL-Ch), and triacylglycerols (TAG) were determined. Lipid accumulation product (LAP) and visceral adiposity index (VAI) were calculated.

RESULTS

There was no relationship between serum and bone concentrations of bioelements and lead and the BMI index. Bone Mg was significantly higher in men with higher VAI, but no such relation was observed in the serum. Similarly, bone Mg and Zn were higher in patients with higher LAP, which was not observed in the serum. Multivariate logistic regression analysis with adjustment for age was performed. There was a correlation between serum Zn concentration and the cut-off point for VAI. The cut-off point for LAP was related to the bone tissue concentrations of Mg, Zn, and Cu.

CONCLUSION

We found some relationships between the concentrations of selected bioelements and Pb and VAI, LAP, and BMI in bone but not in the serum. VAI positively correlated with bone Mg, while LAP positively correlated with bone Cu, Zn, and Mg.

Lipid ratios and obesity indices are effective predictors of metabolic syndrome in women with polycystic ovary syndrome

BACKGROUND

Insulin resistance (IR) is common in women with polycystic ovary syndrome (PCOS). Metabolic syndrome (MS) involves IR, arterial hypertension, dyslipidemia, and visceral fat accumulation. Therefore, fatness indices and blood lipid ratios can be considered as screening markers for MS. Our study aimed to evaluate the predictive potential of selected indirect metabolic risk parameters to identify MS in PCOS.

METHODS

This cross-sectional study involved 596 women aged 18-40 years, including 404 PCOS patients diagnosed according to the Rotterdam criteria and 192 eumenorrheic controls (CON). Anthropometric and blood pressure measurements were taken, and blood samples were collected to assess glucose metabolism, lipid parameters, and selected hormone levels. Body mass index (BMI), waist-to-height ratio (WHtR), homeostasis model assessment for insulin resistance index (HOMA-IR), visceral adiposity index (VAI), lipid accumulation product (LAP), non-high-density lipoprotein cholesterol (non-HDL-C), and triglycerides-to-HDL cholesterol ratio (TG/HDL-C) were calculated. MS was assessed using the International Diabetes Federation (IDF) and the American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI) criteria.

RESULTS

MS prevalence was significantly higher in PCOS versus CON. Patients with both MS and PCOS had more unfavorable anthropometric, hormonal, and metabolic profiles versus those with neither MS nor PCOS and versus CON with MS. LAP, TG/HDL-C, VAI, and WHtR were the best markers and strongest indicators of MS in PCOS, and their cut-off values could be useful for early MS detection. MS risk in PCOS increased with elevated levels of these markers and was the highest when TG/HDL-C was used.

CONCLUSIONS

LAP, TG/HDL-C, VAI, and WHtR are representative markers for MS assessment in PCOS. Their predictive power makes them excellent screening tools for internists and enables acquiring accurate diagnoses using fewer MS markers.

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

BACKGROUND AND AIMS

Visceral adiposity index (VAI) is a novel marker of fat distribution and function which incorporates both anthropometric and laboratory measures. Recently, several studies have suggested VAI as a screening tool for metabolic syndrome (MetS). Here, we aimed to consolidate the results of these studies by performing a systematic review and meta-analysis.

METHODS AND RESULTS

We searched PubMed and EMBASE online databases for eligible studies that investigated the association of VAI and MetS. After reviewing 294 records, we included 33 eligible papers with a sum of 20516 MetS and 53242 healthy participants. The risk of bias in the included studies was assessed, and the relevant data was extracted. All included studies reported a significant association between VAI and MetS screening, but were highly heterogeneous in their reported effects. We pooled the diagnostic test accuracy metrics of VAI for MetS screening and showed that it has a moderate-to-high accuracy with an area under the summary receiver operating characteristics curve of 0.847, a pooled sensitivity of 78%, and a pooled specificity of 79%. Besides, we pooled the difference in means of VAI between patients with MetS and healthy controls, revealing that VAI was 2.15 units higher in MetS patients.

CONCLUSIONS

VAI is an accurate, low-cost, and widely available screening marker for MetS. However, further studies are needed to evaluate its applicability in clinical practice, determine an optimal cut-off, and identify populations that would benefit the most from it.

Evaluation of the relationship between serum ferritin and insulin resistance and visceral adiposity index (VAI) in women with polycystic ovary syndrome

PURPOSE

There is a relationship between polycystic ovary syndrome (PCOS) and adipose tissue dysfunction (ADD), but this relationship is not clear. It has been recently shown that iron accumulation in adipose tissue is among the causes of adipose tissue dysfunction. Data on adipose tissue dysfunction in women with PCOS are insufficient. In this study, we aimed to evaluate the relationship between serum ferritin levels (iron accumulation biomarker) and visceral adiposity index (an indicator of adipose tissue dysfunction).

METHODS

The study is a case-control study. Women with diagnosed PCOS with 2003 Rotterdam Diagnostic Criteria (n = 40) were compared with non-PCOS group (n = 40). In this study, the cholesterol ratios, the homeostatic model evaluation index for insulin resistance (HOMA-IR) and the quantitative insulin sensitivity control index were calculated using biochemical parameters, and the visceral adiposity index (VAI) and the lipid accumulation product (LAP) were calculated using both anthropometric and biochemical parameters. In this study, insulin resistance was evaluated by HOMA-IR and adipose tissue dysfunction was evaluated by VAI index.

RESULTS

According to the results of this study, women with PCOS have a worse metabolic status than women without PCOS. However, this has been shown only in overweight and obese women, not in women with normal weight.

CONCLUSION

As a result, the presence of obesity in women with PCOS exacerbates metabolic status.

LEVEL OF EVIDENCE

Level V, cross-sectional descriptive study.

Neck Circumference as a Predictor of Obesity and Metabolic Syndrome in Bangladeshi Women with Polycystic Ovary Syndrome

BACKGROUND AND OBJECTIVE

Researchers have identified neck circumference (NC) as a valuable tool to detect obesity and metabolic syndrome (MS). We conducted this study to define cutoffs of NC to identify obesity, abdominal obesity, and MS in adult women diagnosed with polycystic ovary syndrome (PCOS).

METHODS

Adult women newly diagnosed with PCOS using the revised Rotterdam criteria having NC measure data in a cross-sectional study titled "Biochemical and Hormonal Profile of Patients with Polycystic Ovary Syndrome" were analyzed.

RESULTS

Finally, 200 women were analyzed; their mean age was 23.3 (±4.9) years, body mass index (BMI) 26.47 (±5.09) kg/m², NC 34.6 (±3.04) cm, waist circumference (WC) 88.18 (±11.98) cm, and visceral adiposity index (VAI) was 3.31 (±1.37). NC had positive correlations with age, BMI, WC, systolic and diastolic blood pressure, serum triglyceride, VAI, and testosterone levels. NC cutoff 32.75 cm showed 87.3% sensitivity and 74.4% specificity in detecting abdominal obesity (AUC 0.889, P < 0.001) and 88.0% sensitivity and 68.0% specificity for diagnosis of overweight/obesity (AUC 0.877, P < 0.001). NC 34.25 cm showed 63.0% sensitivity and 64.0% specificity for diagnosis of MS (AUC 0.681, P < 0.001).

CONCLUSION

Neck circumference may be a simple and convenient tool in assessing obesity, central obesity, and MS in women with PCOS.

Elucidating the impact of obesity on hormonal and metabolic perturbations in polycystic ovary syndrome phenotypes in Indian women

Polycystic ovary syndrome is a complex endocrinopathy with heterogeneous presentation and multifactorial etiology. We have undertaken this case-control study to compare metabolic and endocrine characteristics in different phenotypic subgroups of women with PCOS and the impact of obesity on them. Women with PCOS (n = 489) were classified into 4 phenotypes according to Rotterdam criteria. Comparisons of clinical, biochemical and hormonal parameters were performed across all phenotypic groups of PCOS and with controls (n = 270) by Welch’s ANOVA with subsequent Games-Howell post-hoc test. We found maximum prevalence of normoandrogenic phenotype D, which is milder form of PCOS in terms of insulin resistance, gonadotropin levels and dyslipidemia, followed by phenotype A, in our total study population. After classification of the study group into lean and obese groups, only few insulin and lipid-related traits showed marked differences between phenotypes. Further, we noted that obese women showed adverse metabolic but not androgenic traits compared to lean counterparts in the same phenotype. Metabolic syndrome frequency is increased in hyperandrogenic phenotypes with HDL-C and waist circumference being most predominant contributing factors in total, lean and obese groups. We demonstrate that in our study population there is greater occurrence of phenotype D of PCOS. Our study highlights the importance of clinicians concurrently employing Rotterdam criteria along with obesity status for ascertaining accurate PCOS status and formulating suitable therapeutic intervention.

The Role of Visceral Adiposity Index as Predictor of Metabolic Syndrome in Obese and Nonobese Women with Polycystic Ovary Syndrome

Background: To evaluate anthropometric-metabolic biomarkers as predictors of metabolic syndrome (MS) in women with polycystic ovary syndrome (PCOS) with and without obesity. Methods: This was an observational cross-sectional study. Patients were classified as nonobese-PCOS (body mass index, BMI <30 kg/m², n = 385), and obese-PCOS (BMI ≥30 kg/m², n = 261). The anthropometric parameters waist circumference, waist/hip ratio, lean body mass, fat body mass, visceral adiposity index (VAI), lipid accumulating product, and biomarkers of glucose and lipid metabolisms were compared between groups. Binominal logistic regression analyses were performed to identify predictors of MS. Results: Obesity was diagnosed in 40% of all PCOS women (P < 0.001). Blood pressure and anthropometric abnormalities were significantly more frequent in obese-PCOS women (P < 0.001, for all comparisons). Glucose metabolism markers were higher in obese-PCOS compared with nonobese-PCOS (P < 0.001, for all comparisons). High-density lipoprotein cholesterol was lower in obese group than in nonobese group (1.26 mM vs. 1.08 mM, P < 0.001). MS was found in 23 of 385 (6%) nonobese-PCOS and in 116 of 261 (44.4%) obese-PCOS (P < 0.001). VAI was the best predictor of MS in both nonobese-PCOS (OR = 4.1, 95% CI 1.5-11.1) and obese-PCOS (OR = 12.9, 95% CI 5.7-29.0). Conclusions: MS is more prevalent in PCOS women with obesity. VAI was the strongest predictor of MS in both obese and nonobese PCOS women, and can be applied in clinical practice for early detection of risk for MS and precocious intervention in women with PCOS, particularly in obese women.