1 Institute for Anthropology, University of Vienna, A-1090 Vienna and 2 University Clinic for Gynecology and Obstetrics, Department for Endocrinology, A-1090 Vienna, Austria
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Abstract |
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Key words: body composition/fat distribution/matched controls/PCOS
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Introduction |
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One of the originally described symptoms of PCOS is obesity, which seemed to be associated with anovulation, hirsutism and infertility (Stein and Leventhal, 1935). Therefore the majority of previous studies were performed primarily on obese or overweight women with PCOS. However, obesity is not obligatory in PCOS women and furthermore it cannot be seen as a homogeneous phenotype. Of special importance is the topography of body fat, visible as fat distribution. The major endocrine symptom of PCOS, hyperandrogenicity, is clearly associated with a preponderance of fat localized to upper body sites (Evans et al., 1983
). This sex specific fat distribution, commonly called android fat distribution, is associated with obesity and a variety of metabolic characteristics, but is also mentioned as an indicator of reduced reproductive capability of the woman. In this way the phenotype of android fat patterning is in close association with the main symptoms of PCOS, such as being overweight and infertility. Nevertheless, up to now only few studies analysed fat distribution patterns in PCOS patients (Bringer et al., 1993
; Douchi et al., 1995
; Lefebre et al., 1997). These studies have documented a tendency to centralized or android fat patterning in young women with PCOS. Unfortunately the majority of studies described only fat distribution patterns in overweight PCOS women. The only study analysing body composition and fat distribution pattern in lean PCOS women documented no differences in body composition and fat distribution between lean PCOS patients and healthy controls (Good et al., 1999
). These results however, are in contradiction to the evolutionary based assumption that phases of infertility and sterility are associated with android fat distribution and this kind of fat distribution may be an indicator for reduced reproductive capability in a woman. We postulate that even in lean women suffering from PCOS an android type of fat distribution prevails. Therefore the purpose of our study was to analyse body composition, bone density and body fat patterning in lean PCOS women only.
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Materials and methods |
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Hormone concentrations
The examination started with the quantitative determination of 17ß-oestradiol, follicle stimulating hormone (FSH), LH, testosterone, dehydroepiandrostendionsulphate (DHEA-S), androstendione and sex hormone-binding globulin (SHBG). Blood samples were collected between 7.30 and 9.30am before day 10 of the cycle. The quantitative determination was made at the central hormone laboratory of the University Clinic for Gynecology and Obstetrics.
Anthropometrics
Stature (in cm) and body weight (in kg) was determined for each proband according to previously published methods (Knussmann, 1988). For a better description of the weight status the BMI was calculated as: weight in kg divided by the square of height in metres. Weight status was classified using the following BMI categories according to the World Health Organization (WHO, 1995):
Thinness:grade 1 BMI 17.0018.49 (mild thinness)
grade 2 BMI 16.0016.99 (moderate thinness)
grade 3 BMI < 16.00 (severe thinness)
Normal range:BMI 18.5024.99
Overweight:grade 1 BMI 25.0029.99 (mild overweight)
grade 2 BMI 30.0039.99 (severe overweight)
grade 3 BMI > 40.00 (obese)
Body composition
Body composition analyses were performed before day 10 of the cycle. Dual-energy x-ray absorptiometry (DEXA) (Hologic 2000) was used to measure bone, lean and fat mass (Blake and Fogelman, 1997). Although this method is indirect, its high reliability, relatively low costs and comfort for the probands make the dual energy x-ray absorptiometry especially useful for the determination of body composition. By DEXA, the body consists of soft tissue, i.e. fat and lean tissue and bone. DEXA measures total body bone mineral content (BMC) and density, fat mass and lean mass with a precision (coefficient of variation) of 0.9, 4.7 and 1.5% respectively. The precision for the abdominal fat mass and fat percentage is 4.3 and 3.4% respectively. The extinction of x-rays, which is dependent on the tissue, is measured and absolute and relative fat mass and lean body mass are estimated. The scanner uses an x-ray source, an internal wheel to calibrate the bone mineral content and an external luciate and aluminium phantom to determine the percentage of fat of each soft-tissue sample scanned. Simultaneous with the measurement of the skeleton, the percentage of fat is determined from the ratio of attenuation of the lower energy (70kVp) to that of the higher energy (140kVp) of the beam. This is calculated for all non-skeleton pixels scanned and extrapolated over the skeleton-containing pixels. The relatively low radiation dose with 0.1m Sievert and a short scanning time (<7 min) make this technique especially suitable for such determinations. Scanning was done by the Hologic total body scanner. A phantom, especially constructed for body composition determination and calibrated for fat and lean mass and bone mineral content, was placed beside the proband. Default software readings provided lines positioned to divide the body into six compartments, i.e. head, trunk, arms and legs. The trunk was defined by a horizontal line below the chin, vertical lines between trunk and arms and a lower border formed by oblique lines passing through colli femuri. The region below this lower border of the trunk, including both legs and the hip region is called lower body region. For each region of the whole body fat and lean body mass and BMC were determined.
Fat distribution
For a better description of the sex specific fat distribution the fat distribution index (FDI) (Kirchengast et al., 1997a) was calculated:
FDI = Upper body fat mass in kg/Lower body fat mass in kg
A fat distribution index below 0.9 indicates a gynoid fat distribution, i.e. the fat mass of the lower body surpassed the fat mass of the upper body. A fat distribution index >1.1 defines an android fat distribution. In this case the amount of fat tissue of the abdominal region surpassed the fat mass of the lower body. An FDI between 0.9 and 1.1 is classified as an intermediate stage of fat distribution. We used the FDI for quantification of the fat distribution instead of the widely used waist to hip ratio, because the waist to hip ratio describes body shape and silhouette but not the quantitative amount of fat distribution. Nevertheless we have to be aware that the FDI describes not the ratio of abdominal fat to gluteal-femoral fat, but the ratio between upper body fat, including abdominal fat and breast fat mass, and lower body fat.
Statistical analysis
The statistical analyses were carried out using SPSS Version 7.0 (Microsoft Corp.) according to a previously published method (Bühl and Zöfel, 1996). After computing descriptive statistics (means, SD) group differences were tested regarding their significance using paired student t-tests. Since the results of the Kolmogoroff-Smirnov test indicated that no normal distribution could be assumed for the hormonal variables, for statistical analysis of group differences in hormone levels the non-parametric Wilcoxon test for paired samples was applied. Furthermore linear regression analysis was computed in order to test the impact of body mass and body composition on fat distribution patterns.
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Results |
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Lean PCOS patients exhibited the significantly lower values in absolute bone mineral content, while the group differences of bone density of the total body were not of statistical significance (Table I).
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Discussion |
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Beside body composition and bone density the lean PCOS patients and lean controls differed significantly in their body fat distribution, however we have to state that body fat distribution was determined using the FDI only and not the widely used waist hip ratio (WHR). In our opinion, the FDI, which describes the quantitative ratio of upper to lower body fat, is an adequate measure of the fat distribution and may determine fat distribution to some extent better than the WHR, which describes first of all the body silhouette. We are aware that the amount of upper body fat does not only describe the amount of abdominal fat, but also the fat mass of the breasts, however, the fat mass of the breasts increases with increasing body weight and obesity but the PCOS patients of our sample were lean, normal weight and did not differ in weight status from the healthy controls. Furthermore we found no paper describing an increased breast size and an increased fat mass of the breasts in PCOS patients. Therefore we assume that the inclusion of breast fat into FDI plays no significant role in our findings. Good et al., (1999) used the upper body to lower body fat ratio too, beside the WHR (Good et al., 1999). Nevertheless our results differed from that of Good et al., (1999). While in our sample healthy controls exhibited gynoid fat patterning exclusively, the majority of lean PCOS patients (70%) showed a non gynoid type of fat patterning and the fat distribution patterns of 50% of the lean PCOS patients were classified as android. Good et al. (1999) found no differences in fat distribution between PCOS and lean controls, this was true of WHR as well as upper body to lower body fat ratio. These differences between our results and those of Good et al., (1999) should not be over interpreted because sample size in both studies was small. Furthermore Good et al. (1999) used a BMI <26.00 as the threshold value to exclude overweight probands from their sample. In the present study we used a BMI <25.00 as the threshold value according to the definitions of the World Health Organization (WHO, 1997
). Therefore, the mean BMI of the probands was higher in the study of Good et al. (1999) than in our sample (22.4 versus 20.7). So the differences in the results of Good et al., (1999) and the present paper may be due to the different mean weight status (BMI) of the two samples.
In our sample PCOS affected women showed an extraordinarily high prevalence of android or intermediate fat distribution, even lean women. Therefore the majority of PCOS affected women did not correspond to the cross-cultural constant standard of attractive female body shape. During our evolution and history only a few women were excessively obese during their fertile years or reached the post-menopause. The observation that android fat distribution in association with obesity or menopause is an indicator for reduced fertility or irreversible sterility was consequently historically extraordinarily rare. In contrast, PCOS is the most common endocrine disorder affecting fertility during adult life and is not strongly associated with severe obesity. In our sample we found an extremely high prevalence of android or intermediate fat distribution in PCOS women, even in lean ones. There is a cross-cultural association of female unattractiveness in relation to the body shape resulting from the android or intermediate fat distribution pattern. This could be seen as a consequence of the typical body shape of PCOS affected women.
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Acknowledgements |
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Notes |
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References |
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Submitted on November 29, 2000; accepted on February 20, 2001.