Journal of Obesity Management

Journal of Obesity Management

Current Issue Volume No: 1 Issue No: 2

Research-article Article Open Access
  • Available online freely Peer Reviewed

  • Hirsutism And Anthropometric Profiles Among Subjects With Polycystic Ovarian Morphology? A Cross-Sectional Analysis

    1 Department of pathology PNS HAFEEZ 

    2 Department of ENT 

    3 Department of gynecology & obstetrics 

    4 Department of Biochemistry Islamabad Medical & Dental College 

    5 Medical officer PNS HAFEEZ 

    Abstract

    Background

    Polycystic ovarian syndrome (PCOS) is increasingly being diagnosed and treated with sometimes variable lifestyle advice and pharmacological interventions. Obesity is considered as the sole culprit and variable definitions in clinics compound the understanding of pathogenic heterogeneity of this syndrome. We evaluated the differences between various simple to calculate anthropometric indices along with some anthropometric-biochemical equations in subjects with or without PCOS.

     Objective

    To compare traditional measures like waist to hip and height ratio (WHpR and WHtR), BMI, newer markers depicting central obesity like Abdominal Volume index(AVI), Body roundness index (BRI), A Body Shape index (ABSI), Conicity index (C-index) along with biochemical-anthropometric equations like lipid Accumulation Products (LAP), Visceral Adiposity Index (VAI) and Chinese Visceral Adiposity Index (CVAI) for diagnosing PCOS as per the Rotterdam criteria

     Design

    Cross-sectional analysis

     Place & Study Duration

    Naval hospital, Islamabad from Jan- 2018 to July- 2019

    Subjects and Methods

    From our finally evaluated 333 female subjects we initially compared the differences for the presence of hirsutism as per modified Ferrimen Gallwey scores and biochemical hyperandrogenism by measuring free androgen index (Total testosterone/SHBG x 1000. We evaluated waist circumference, BMI, WHpR, WHtR,AVI, BRI, ABSI, C-index along with biochemical-anthropometric equations like LAP, VAI and CVAI for differences in subjects diagnosed to have PCOS by Rotterdam criteria or ultrasonography alone.

    Results

    Differences in hirsutism as defined by modified FG score between subjects defined to have PCOS or otherwise as per Rotterdam defined criteria were as [(PCOS=169, Mean=17.33 + 9.05) (No PCOS=164, Mean=8.21 + 5.74), p< 0.001] and ultrasound [(PCOS=87, Mean=16.95 + 9.57) (No PCOS=246, Mean=11.38 + 8.51), p< 0.001]. Similarly, the differences in FAI between subjects defined to have PCOS or otherwise as per Rotterdam criteria and ultrasound were as [(PCOS=169, Mean=6.41 + 4.88) (No PCOS=164, Mean=2.77 + 1.79), p< 0.001] and [(PCOS=87, Mean=5.75 + 5.01) (No PCOS=246, Mean=4.22 + 3.68), p= 0.011]. Anthropometric measures and anthropometric-mathematical equations were raised in non-PCOS subjects than PCOS subjects. Lean-PCOS demonstrated lower degree of hirsutism and biochemical hyperandrogenism in comparison to obese-PCOS.

    Conclusion

    Hirsutism and free androgen indices were raised in PCOS females. Anthropometric based measurements were not different in PCOS cases and non-PCOS females. Lean-PCOS demonstrated lower degree of hirsutism and biochemical hyperandrogenism in comparison to obese-PCOS.
    Author Contributions
    Received Aug 26, 2019     Accepted Sep 05, 2019     Published Sep 13, 2019

    Copyright© 2019 Hayat Khan Sikandar, et al.
    License
    Creative Commons License   This work is licensed under a Creative Commons Attribution 4.0 International License. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

    Competing interests

    The authors have declared that no competing interests exist.

    Funding Interests:

    Citation:

    Hayat Khan Sikandar, Alam Gul Asif, Manzoor Robina, Hanif Baig Aasyia, Anwar Roomana et al. (2019) Hirsutism And Anthropometric Profiles Among Subjects With Polycystic Ovarian Morphology? A Cross-Sectional Analysis Journal of Obesity Management. - 1(2):44-54
    DOI 10.14302/issn.2574-450X.jom-19-3000

    Introduction

    Introduction

    Polycystic ovarian morphology or Polycystic ovarian syndrome (PCOS), termed in common parlance as the “The thief of womanhood” has emerged in recent  times as a spectrum of disorders starting from menorrhagia, hirsutism to infertility. 1 The disorder not just carries with it the stigmata of reproductive disorders but also linked with various metabolic risks including insulin resistance and dyslipidemia.2 Though not much appreciated in developing countries, the problem is growing at an alarming pace within sub-continental community with prevalence touching up to 9% of the population in young females. 3

    Literature review provides variable results in terms of PCOS association with clinical and metabolic risk factors. Firstly, researchers have discovered different phenotypes of PCOS as regards to their clinic-pathological correlates, which vary as per the geographical zone one belongs to. 4The usual diagnosis revolves around establishing not just the clinical presentation including disturbances in a menstrual cycle like oligo or anovulation, but reliance has been placed on various biochemical, endocrine parameters and radiological findings for labeling   subjects with PCOS. 5 Secondly, there is data to support that available evidence is suggestive of inconsistent data regarding biochemical and endocrine parameters, probably due to inherent imprecision related to analytical techniques or rapidly changing hormonal cycle within the females. 6 Finally, multiple criteria starting from NIH from 1992, to Rotterdam and AE-PCOS are available to define PCOS, but yet consensus among authorities in far from converging to a common solution. 748 Furthermore, local data apart from its scarcity, still has been able to identify differences in phenotype especially for the sub-continental population. 9 While the clinical presentations due to symptoms vary across the cultures, authorities in past have been suggesting a simpler way to diagnose or suspect PCOS, where the role of anthropometric measurements can play a major role especially in resource- scarce countries. 10 Earlier studies in this Pazderska et al have indirectly shown waist circumference to predict cardiometabolic disease in subjects with PCOS thus highlighting the usefulness of anthropometry in this condition. 11 Another Chinese study by Huang et al identified anthropometric indices and lipid peroxidation products to be useful in identifying the underlying risk in PCOS. 12Techatraisak et al have identified visceral adiposity index and other related measures like BMI to have the potential of predicting PCOS. 13 In recent times we had several new anthropometry based indices along with conventional parameters and anthropometric measures and biochemical mathematical equations which we as author feel can potential our diagnostic tool s to predict one of the commonest disorders affecting female fertility and onward a source to cardiometabolic risk.

    In the backdrop of shared evidence regarding anthropometric measures as candidate surrogate markers for diagnosing PCOS, cost-effectiveness in relation to developing and under-developed worlds and emergence of some new anthropometric measures with probable higher yields we decided to carry out a study to see the utility of various anthropometric measures and PCOS. The objective will be to compare traditional measures like waist to hip and height ratio (WHpR and WHtR), BMI, newer markers depicting central obesity like visceral adiposity index(VAI), Abdominal Volume index(AVI), Body roundness index (BRI), A Body Shape Index (ABSI), Conicity index (C-index) along with biochemical-anthropometric equations like lipid peroxidation for diagnosing PCOS as per the Rotterdam criteria.

    Results

    Results

    Mean age among our subjects was 27.89 (+ 7.62) years. Out of 333 subjects 93 were unmarried, while 238 subjects were married. History of anovulation was given by 205 patients while rest (n=128) did not give any menstrual cycle abnormality. Modified FG score was higher than or equal to 8 among 157 subjects in comparison to 175 ladies with less than 8 score out of the total designated 36 marks. 87 subjects were having radiological proven signs of PCOS, while 246 females did not show criteria defined PCOS signs in ovaries for PCOS. 169 females were diagnosed to have PCOS as per Rotterdam criteria against 164 who could not fulfill the criteria for PCOS. Hirsutism was found to be more prevalent in both subjects diagnosed to have PCOS either as per Rotterdam defined criteria or on ultrasonography. Figure 1 and Figure 2 Similarly free androgen index (FAI) was found to be raised in subjects with PCOS either defined by Rotterdam criteria or ultrasonography. Figure 3 and Figure 4 Lean PCOS demonstrated lower degree of hirsutism and biochemical hyperandrogenism in comparison to obese PCOS as depicted in Table 1, Table 2, Table 3, Table 4.

    Differences in hirsutism as defined by modified FG score between subjects defined to have PCOS or otherwise as per Rotterdam defined criteria ((PCOS=169, Mean=17.33 + 9.05) (No PCOS=164, Mean=8.21 + 5.74), p< 0.001) Differences in hirsutism as defined by modified FG score between subjects defined to have PCOS or otherwise as ultrasound diagnosis ((PCOS=87, Mean=16.95 + 9.57) (No PCOS=246, Mean=11.38 + 8.51), p< 0.001) Differences in free androgen index (FAI) between subjects defined to have PCOS or otherwise as per Rotterdam criteria ((PCOS=169, Mean=6.41 + 4.88) (No PCOS=164, Mean=2.77 + 1.79), p< 0.001) Differences in free androgen index (FAI) between subjects defined to have PCOS or otherwise as ultrasound diagnosis ((PCOS=87, Mean=5.75 + 5.01) (No PCOS=246, Mean=4.22 + 3.68), p= 0.011) Differences in conventional anthropometric indices among subjects diagnosed to have PCOS or otherwise as per Rotterdam criteria and ultrasound PCOS diagnosis (n=333)
    Anthropometric measure PCOS diagnosis (Rotterdam criteria) Mean Std. Dev Sig.(2-tailed) PCOS diagnosis (USG diagnosis) Mean Std. Dev Sig.(2-tailed)
    Waist circumference (cm) YES (n=169) 90.90 11.51  0.561 YES (n=87) 88.33 10.04  0.032
    NO(n=164) 90.19 10.95 NO(n=246) 91.34 11.54
    BMI YES (n=169) 29.23 5.75  0.233 YES (n=87) 27.93 5.39  0.077
    NO(n=164) 28.48 5.66 NO(n=246) 29.19 5.74
    WHpR YES (n=169) 0.91 0.054  0.617 YES (n=87) 0.903 0.050  0.098
    NO(n=164) 0.91 0.050 NO(n=246) 0.913 0.051
    WHtR YES (n=169) 0.58 0.074  0.674 YES (n=87) 0.565 0.069  0.013
    NO(n=164) 0.58 0.072 NO(n=246) 0.588 0.074
    Differences in newer anthropometric indices among subjects diagnosed to have PCOS or otherwise as per Rotterdam criteria and Ultrasound PCOS diagnosis (n=333)
    Anthropometric measure PCOS diagnosis (Rotterdam criteria) Mean Std. Dev Sig.(2-tailed) PCOS diagnosis (USG diagnosis) Mean Std. Dev Sig.(2-tailed)
    AVI YES (n=169)  16.73 4.14  0.617 YES (n=87) 15.81 3.53  0.029
    NO(n=164) 16.50 3.98 NO(n=246) 16.91 4.20
    BRI YES (n=169) 5.75 5.75  0.621 YES (n=87) 5.48 0.94  0.007
    NO(n=164) 5.70 5.66 NO(n=246) 5.71 1.00
    BAI YES (n=169) 33.55 6.04  0.389 YES (n=87) 32.13 5.99  0.034
    NO(n=164) 32.99 5.71 NO(n=246) 33.69 5.79
    ABSI YES (n=169) 1.46 0.57  0.189 YES (n=87) 1.56 0.63  0.334
    NO(n=164) 1.55 0.67 NO(n=246) 1.48 0.62
     Conicity index YES (n=169) 1.24 0.11  0.454 YES (n=87) 1.23 0.10  0.181
    NO(n=164) 1.26 0.13 NO(n=246) 1.25 0.12
    Comparison of biochemical-anthropometric equations between subjects with and without PCOS defined as per Rotterdam criteria
    Anthropometric measure PCOS diagnosis (Rotterdam criteria) Mean Std. Dev Sig.(2-tailed) PCOS diagnosis (USG diagnosis) Mean Std. Dev Sig.(2-tailed)
    VAI YES (n=169) 0.96 0.09  0.330 YES (n=87) 0.95 0.097  0.330
    NO(n=164) 0.97 0.10 NO(n=246) 0.97 0.104
    LAP YES (n=169) 45.88 34.99  0.839 YES (n=87) 45.69 36.31  0.839
    NO(n=164) 45.66 34.76 NO(n=246) 46.46 34.31
    CVAI YES (n=169) 73.81 46.33  0.876 YES (n=87) 64.32 0.05034  0.875
    NO(n=164) 74.59 44.74 NO(n=246) 76.69 0.051
    Differences for free androgen index (FAI) and Modified Ferrimen Gallwey (mFG) scores between lean or obese PCOS phenotype
      Lean or obese PCOS phenotype N Mean Std. Dev Sig. (2-tailed)*
    Free Androgen Index (FAI) Obese PCOS 120 6.84 4.83 0.090
    Lean PCOS 48 5.43 4.92
    Modified Ferrimen Gallwey (mFG) score Obese PCOS 120 17.83 8.8 0.345
    Lean PCOS 48 16.38 9.33

    Discussion

    Discussion

    Our findings suggested that PCOS females demonstrated higher degree of clinical hyperandrogenism as measured by hirsutism and biochemical hyperandrogenism (Free Androgen Index) among patients diagnosed to have PCOS either by Rotterdam criteria or ultrasound alone. These findings are in accordance with multiple studies on PubMed. 212223 However, anthropometric measures including conventional, newer and mathematical models of biochemical and anthropometric measures did not demonstrated less rise in anthropometric measures among PCOS females than non-PCOS subjects especially for waist circumference, WHtR, BAI, BRI and AVI where the results were statistical significant. Lean PCOS females demonstrated slightly lower clinical and biochemical hyperandrogenism than obese PCOS subjects. This phenomena was in contrast to common belief that PCOS results due to extra fat accumulation or in some way associated with obesity as demonstrated in some studies. 24

    So the First Question Arises that why Anthropometric Measures Failed to Predict PCOS?

    First of all such findings have previously been defined in the literature. Gonzalez et al have suggested two types of PCOS phenotypes including lean and obese phenotype with association linked to ingestion of saturated fat diets leading to production of reactive oxygen species involved in pathogenesis of PCOS. 25 Second explanation comes in from our inclusion of females in pubertal age group, where evidence not only showing marked heterogeneity in diagnosis also provides a linking explanation where Witchel et al and Sritzer et al have suggested that pubertal developmental stage could have some overlapping features resembling PCOS and thereby suggested that the PCOS diagnosis may only be made after 2 years of menarche. 2627 Provided, we only included females who had at least two years of menarche, still we believe some younger females could have puberty related varying hormonal changes and the current screening recommendations may suggest a period of four or more years of after onset of menarche to allow hormonal stability. More so our sample size had only 16 females with age less than 16 years. Finally, the obesity pattern across globe varies as is true for the population from sub-continent. 7 Our study has many cases with normal anthropometric measures i.e., lean PCOS, where you may find some of the characteristics features of PCOS like oligo-ovulation/anovulation, hirsutism or biochemical hyperandrogenism as well as ultrasound evidence of PCOS but some regional data has suggested unlike the Caucasian population. Probable reason to these differences could be the specific Asian PCOS phenotype, varying environmental triggers and adipocyte behavior which have been documented to be different from non-Asian population. 28329 Finally, Panidis et al categorized PCOS into four phenotypes where one of the phenotype with hyperandrogenism and ultrsound presence of PCOS was not associated with obesity in all phenotypes. 30

    Though a long study with so many variables well-evaluated we still feel the study has limitations. Firstly, the study was a cross-sectional study which provides level-III evidence and needs to be replicated in well-controlled prospective trails. Secondly, the study was based in hospital and included mostly subjects with some clinical symptoms. Therefore, a broad spectrum epidemiological study must follow to learn the real heterogeneity and phenotypic differences within our population in order to dissect out sub-types of PCOS. We tried but also feel lack of basic education and cultural limitations could be another reason for female subjects to give clear narrative of their reproductive complaints. We will appreciate readers to interpret our findings in the backdrop of these limitations.

    Clinical implications pertaining to non-significant anthropometric measures with a sizeable proportion of PCOS being lean highlights the importance of appreciating PCOS phenotypes within a given population. The evidence merits more attention as current debate suggests a different management strategy for lean PCOS types then obese PCOS patients. 31 We also want to highlight the heterogeneity of PCOS in terms of underlying pathogenesis as being multifactorial in origin, and may actually depict different metabolic pathways converging to common symptomatology.

    Conclusion

    Conclusion

    Though Rotterdam defined PCOS criteria and radiological diagnosis of PCOS had significantly higher scores for clinical (modified FG cores for hirsutism) and biochemical hyperandrogenism (Free Androgen Index), still anthropometric measures the anthropometric measures or anthropometry couple biochemical equations did not show higher obesity indices among subjects with PCOS as per Rotterdam defined criteria indicating a lean-PCOS pattern in our studied population.

    Affiliations:
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