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Reports indicate that the visceral adiposity index (VAI) is useful to predict cardiovascular disease (CVD) and the metabolic syndrome (MetS). Despite this, long-term studies that analyze the efficacy of the VAI in the prediction of CVD risk are limited and the association between the VAI and electrolytes is unclear. In this sense, Gulbahar et al. [1] reported results of a study aimed at determining if the VAI can be used as a predictor of CVD and provide the possibility of early diagnosis for future CVD. In addition, the authors also analyzed the impact of biomarkers and electrolytes on VAI as an indirect association with CVD. For this, postmenopausal women (aged >40 years; n=50) were included and categorized into two groups according to their VAI scores: mild/moderate and severe. The groups were compared in terms of insulin resistance, biochemical parameters, and anthropometric measurements. After ten years, women were re-assessed and surveyed for additional disease and cardiovascular risk. The study found that VAI scores of women with the MetS as compared to those without the syndrome were significantly higher (7.30 ± 4.75 vs. 2.95 ± 1.05, p < 0.01). In the sever group, serum magnesium levels were found significantly lower and serum zinc (Zn) and high sensitivity C-reactive protein (hsCRP) levels were higher. Correlation analysis showed significant positive correlations between VAI scores and total cholesterol, Zn, and fasting insulin levels and no significant association with the 10-year CVD incidence. The authors conclude that previous VAI results cannot assist in predicting the 10-year CVD risk. Additionally, including serum measurements of Zn, total cholesterol, fasting insulin, and glucose levels are a reasonable approach for managing postmenopausal women with unfavourable CVD risk profiles.


Worldwide, CVD is the leading cause of mortality. In 2019, 17.9 million people died from CVD, corresponding this figure to 32% of all deaths globally. Although it is known that men are at higher risk for CVD, after the menopause, due to estrogen deficiency, women are prone to have higher rates of CVD [2]. During the menopausal transition, due to a decline in ovarian function and estrogen secretion, women are subject to bio-psycho and social changes that can impair their quality of life. More importantly, after menopause, cardiovascular risk increases significantly, partly due to estrogen deprivation. Moreover, an increase in weight and other factors (e.g. sedentary lifestyle, dietary habits, etc) negatively impact metabolic parameters, making women more susceptible to cardiovascular events [3]. Various studies suggest that estrogens have positive effects on female lipid profile and vasculature due to their antioxidant effect, gene modulation expression and the regulation of the inflammatory pathways [4-6]. Therefore, predicting CVD in women during the perimenopausal stage is crucial in order to prevent related deaths. In this sense, the VAI has shown to be effective at determining CVD in the general population and in some populations with specific conditions (e.g. women with polycystic ovary syndrome and patients with chronic hepatitis C). Despite this, studies in postmenopausal women are limited. VAI is a mathematical model based on anthropometric measurements of body mass index (BMI) and waist circumference (WC), in addition to HDL-C and triglyceride levels; thus, providing insight into body fat distribution and function. The increased visceral fat found in postmenopausal women acts as an endocrine system by secreting inflammatory markers that play a role in the development of the MetS and CVD. Other biomarkers, such as hsCRP, magnesium (Mg), Zn, have also been used in the prediction of these conditions. Indeed, while hs-CRP is an indicative of low-grade chronic inflammation, the electrolytes Mg and Zn seem to play key roles in inhibiting inflammatory processes, maintenance of lipid metabolism, insulin secretion, glucose uptake, and regulation of vascular tone in in vitro studies [7,8]. Despite the latter, as the authors state, there are no studies addressing the association between VAI and hs-CRP, Mg and Zn.

The present study found that 54% of studied women had severe VAI scores, with this group displaying lower Mg and HDL-C levels and higher WC, BMI, triglyceride hs-CRP and Zn values. A higher rate of severe VAI scores were observed in women with the MetS. Despite this, after 10 years, severe VAI scores were not significantly associated with the incidence of CVD. Other studies have found a strong positive relationship between VAI scores and CVD risk in both men and women. These discrepancies may be due to some of study limitations which the author state clearly: first, small sample size which does not allow the generalization of the findings to broader populations and perhaps this is the reason why no association was found between VAI scores and 10 year CVD risk; and second, the lack of a premenopausal study group did not allow comparisons, which would have been interesting.

Despite, the above-mentioned limitations, the authors suggest including the monitoring of serum Zn, total cholesterol, fasting insulin and glucose levels as a reasonable approach in the management of postmenopausal women with unfavorable cardiovascular risk profiles. In order to reduce the prevalence of obesity and related diseases among postmenopausal women, it is necessary to implement dietary measures aimed at preventing weight gain and fat ratio increase.

I agree with the authors that a baseline VAI score does not predict long term CVD risk, only near-term CVD risks. There is a need for more studies with a greater population to clarify the utility of the VAI in the prediction of long term CVD in postmenopausal women.

Peter Chedraui, MD, PhD
Instituto de Investigación e Innovación en Salud Integral
Universidad Católica de Santiago de Guayaquil, Guayaquil Ecuador


  1. Gulbahar A, Caglar GS, Arslanca T. Evaluation of visceral adiposity index with cardiovascular risk factors, biomarkers in postmenopausal women to predict cardiovascular disease: A 10 year study. Exp Gerontol. 2022;170:111986.
  2. Mauvais-Jarvis F, Bairey Merz N, Barnes PJ, et al. Sex and gender: modifiers of health, disease, and medicine. Lancet. 2020;396(10250):565-582.
  3. Moccia P, Belda-Montesinos R, Monllor-Tormos A, Chedraui P, Cano A. Body weight and fat mass across the menopausal transition: hormonal modulators. Gynecol Endocrinol. 2022;38(2):99-104.
  4. Stice J, Lee J, Pechenino A, Knowlton A. Estrogen, aging and the cardiovascular system. Future Cardiol. 2009;5(1):93-103.
  5. Novella S, Dantas AP, Hermenegildo C, Hellsten Y. Regulatory Mechanisms of Estrogen on Vascular Ageing. Oxid Med Cell Longev. 2019;2019:4859082.
  6. Monteiro R, Teixeira D, Calhau C. Estrogen signaling in metabolic inflammation. Mediators Inflamm. 2014;2014:615917.
  7. Ghosh C, Yang SH, Kim JG, et al. Zinc-chelated Vitamin C Stimulates Adipogenesis of 3T3-L1 Cells. Asian-Australas J Anim Sci. 2013;26(8):1189-1196.
  8. Ün B, Dolapçıoğlu KS, Güler Okyay A, Şahin H, Beyazıt A. Evaluation of hs-CRP and viseral adiposity index in patients with polycystic ovary syndrome by clinical and laboratory findings. Eur J Obstet Gynecol Reprod Biol. 2016;204:16-20.

If you would like to add a comment or contribute to a discussion based on this issue, please contact Menopause Live Editor, Peter Chedraui, at

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