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.

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.

The study was carried out between and at the University Clinic for Gynecology and Obstetrics, Department for Endocrinology, Vienna, Austria. All the women suffered from menstrual disorders, such as amenorrhoea or oligomenorrhoea, and had contacted the Department for Endocrinology because of undesired infertility.

The PCOS was diagnosed by ultrasound appearance of polycystic ovaries and determination of hormonal parameters. All women showed hyperandrogenism and the majority of women also showed elevated luteinizing hormone LH levels.

All probands were classified as normal weight with a BMI below The controls were recruited from the staff and students of the University clinic for Gynecology and Obstetrics and were matched for age and weight status of the PCOS group.

All controls had regular menstrual cycles 26—33 day cycles and age specific normal sex hormone levels. All probands, PCOS patients as well as controls, were in good health and were not on any medication which might affect hormone metabolism or body composition, even hormonal contraceptives were stopped for a minimum of four months prior to the present investigation.

All subjects were non-smokers and none of them was on excessive physical training. There was no population bias between patients and controls in the present study: both were of the same ethnic origin, and PCOS patients as well as controls stemmed exclusively from Vienna or the neighbouring Lower Austria.

All probands gave their written informed consent. The examination started with the quantitative determination of 17β-oestradiol, follicle stimulating hormone FSH , LH, testosterone, dehydroepiandrostendionsulphate DHEA-S , androstendione and sex hormone-binding globulin SHBG.

Blood samples were collected between 7. The quantitative determination was made at the central hormone laboratory of the University Clinic for Gynecology and Obstetrics. Stature in cm and body weight in kg was determined for each proband according to previously published methods Knussmann, 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, :. Body composition analyses were performed before day 10 of the cycle. Dual-energy x-ray absorptiometry DEXA Hologic was used to measure bone, lean and fat mass Blake and Fogelman, 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. 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. The precision for the abdominal fat mass and fat percentage is 4.

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 kVp 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.

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. 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. For a better description of the sex specific fat distribution the fat distribution index FDI Kirchengast et al. A fat distribution index below 0. the fat mass of the lower body surpassed the fat mass of the upper body.

In this case the amount of fat tissue of the abdominal region surpassed the fat mass of the lower body. An FDI between 0. 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.

The statistical analyses were carried out using SPSS Version 7. according to a previously published method Bühl and Zöfel, 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. As to be expected, the two proband groups differed in stature, body weight and BMI only insignificantly. In contrast, regarding body composition parameters, significant group differences were observed.

Although matched for weight and weight status, lean PCOS patients and lean controls differed significantly in absolute and relative amount of body fat. PCOS patients show a significantly higher amount of fat tissue of the total body and the upper body region, while no significant difference of the lower body fat mass was observable between the two proband groups.

Regarding lean tissue mass, significantly higher values were found for the controls, this was true of the lean mass of the total body as well as of the upper body. No significant differences between the two proband groups occurred in lower body lean mass. 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.

As to be expected PCOS patients exhibited higher LH and androgen levels. Nevertheless only the group differences of testosterone and DHEA-S were of statistical significance Table II.

The threshold to discriminate between gynoid, android and intermediate fat patterning are in accordance with published definitions Kirchengast et al. The lean controls exhibited exclusively a gynoid type of fat distribution Table III. Therefore significant differences of the FDI occurred. The linear regression analyses analysed the impact of weight status, and absolute and relative amount of body fat on fat distribution for each proband group separately.

A significant association between the fat distribution and the body composition parameters mentioned above was only found for the lean PCOS patients. In this group the FDI increased with increasing absolute and relative fat mass.

In case of relative fat mass this was also true of lean controls Table IV and Figure 1 A,B,C. Signs of potential reproductive success are classified as attractive. Cross-cultural studies show that moderate plumpness and a gynoid type of fat patterning are considered as typical signs of female attractiveness in the majority of investigated cultures Brown and Konner ; Brown ; Anderson et al.

This association between body fat mass and fat distribution and attractiveness may be due to the importance of body fat and gynoid fat patterning for potential reproductive success. A sufficient amount of body fat is absolutely necessary for the onset and maintenance of regular and ovulatory menstrual cycles.

Even during adult life a marked decrease of adipose tissue may result in secondary amenorrhoea. Body fat stores in females, especially at the lower body region Rebuffe-Scrive et al.

On the other hand the amount of body fat and especially the sex specific kind of fat distribution are indicators of the hormonal situation and reproductive status of a woman.

Peripheral fat tissue, especially in the lower body region is an important source of extra-ovarian oestrogen synthesis, because the aromatization from androgens to oestrogens takes place there.

The gynoid type of fat distribution develops during female puberty and persists during the fertile phase of adult life and remains stable even under worse conditions such as malnutrition and phases of amenorrhoea caused by undernutrition DeRidder et al.

At the end of the fertile phase the gynoid type of fat distribution changes through an intermediate stage when the amount of upper and lower body fat are more or less equal to the android type of fat distribution typical for the post-menopause when reproductive capability has ended irreversibly Ley et al.

However PCOS is often associated with overweight or obesity and the android fat distribution patterns may be the result of being overweight only. This assumption is supported by the finding of no differences in body fat distribution between lean PCOS patients and lean controls Good et al.

In contrast in our present study we found significant differences in body composition and fat distribution between lean women with PCOS and lean controls. Although lean PCOS patients and lean controls were matched for weight, lean PCOS women had a significantly higher amount of body fat, and a significantly lower amount of lean body mass than the lean controls.

Furthermore, significant differences occurred in bone mass: lean PCOS women showed a significantly lower total bone mass and an insignificantly lower bone density than the lean controls. This finding is in contradiction to the well described positive effect of androgen excess on bone density Dixon et al.

However, the majority of studies were performed on overweight or obese PCOS patients only. The observed higher bone density and bone mineral content in overweight or obese PCOS women may be explained by the assumption that obesity or overweight may increase bone mineral density through biomechanical forces Dumesic et al.

The low BMD of the lean PCOS patients is also in marked contrast to the results of Good et al. However Good et al. 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. Nevertheless our results differed from that of Good et al. These differences between our results and those of Good et al.

Furthermore Good et al. Therefore, the mean BMI of the probands was higher in the study of Good et al. So the differences in the results of Good et al.

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. Body size, fat distribution and body composition variables in lean PCOS patients and lean controls; paired Student t -tests. Sex hormone concentrations in lean PCOS patients and lean controls.

Wilcoxon test for paired sample. To whom correspondence should be addressed. E-mail: sylvia. kirchengast univie. The authors are gratefully indebted to their probands without whose co-operation the present study could not have been performed. Anderson, J. A cross-cultural review of the socioecology of ideals of female body shape.

Björntorp, P. Acta Med. Lancet , , — Blake, G. and Fogelman, I. Semin Nucl. Bringer, J. et al. New York Acad. Brown, P. and Konner, M. Bühl, A. and Zöfel, P. Conway, G. Clinical aspects. DeRidder, C.

Dagogo-Jack, S. Additionally, gender seems to play a role. New research suggests that gender influences how fat is distributed across the body, which, in turn, influences cardiometabolic risk.

The newest study was led by Dr. Miriam A. Bredella, a radiologist at the Massachusetts General Hospital and an associate professor of radiology at the Harvard Medical School, both in Boston, MA. Speaking about the motivation for her recent study, Dr.

Bredella and team examined overweight and obese but otherwise healthy adults. Ninety-one of the participants were male.

All participants had a similar body mass index BMI and age — which was 37 years, on average. In order to assess body composition, all the participants were examined using dual-energy X-ray absorptiometry and computed tomography scans after fasting overnight. Using a technique called magnetic resonance spectroscopy, the researchers were able to quantify and examine the fat, determining levels of serum glucose, insulin , and lipids.

Bredella and colleagues performed linear regression analyses between body composition and the risk factors for cardiometabolic conditions.

The study revealed that women had more fat overall and more fat below the skin, but they also had lower lean mass than men.

Men, however, had more of the so-called visceral adipose tissue, or ectopic fat , which are terms that describe fat that surrounds vital organs. Men had more ectopic fat in the muscles, abdomen, and liver. Women have a higher relative amount of total body fat and higher superficial thigh fat, which is protective for cardiometabolic health.

But surprisingly, ectopic fat did not increase the risk of cardiometabolic disease in men, while for women, the same ectopic fat correlated strongly with a high cardiometabolic risk. In other words:.

A similar study presented and led by the same Dr. Bredella examined the relationship between sarcopenic obesity and cardiometabolic health.

Sarcopenic obesity refers to an unhealthful combination of low muscle mass and high fat mass. This study, too, found that sarcopenic obesity was associated with a higher cardiometabolic risk, especially in women.

Bredella explains. Tetralogy of Fallot is a group of four heart abnormalities that can develop while a fetus is in the womb. It can affect how the blood flows in the…. New research suggests that women with a high risk strain of HPV may be at a four-time higher risk of dying from cardiovascular disease.

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My podcast changed me Can 'biological race' explain disparities in health?

Overview Fingerprint. ASJC Scopus subject areas Endocrinology, Diabetes and Metabolism Endocrinology. Access to Document Link to publication in Scopus. Link to the citations in Scopus. Fingerprint Dive into the research topics of 'Racial differences in body fat distribution among reproductive-aged women'.

Together they form a unique fingerprint. View full fingerprint. Cite this APA Standard Harvard Vancouver Author BIBTEX RIS Rahman, M. With decreased activity, muscle mass decreases. Does menopause affect body shape?

Although menopause may not be directly associated with weight gain, it may be related to changes in body composition and fat distribution. Several studies have shown that perimenopause, independent of age, is associated with increased fat in the abdomen as well as decreased lean body mass.

However, further study is needed on the exact role of menopause in body composition. Regardless of the different contributions of aging and menopause to weight gain and body composition, the fact is that most women in North America are overweight at midlife.

Any excess weight raises the risk of many diseases, including cardiovascular disease which is particularly linked with excess fat in the abdomen , type 2 diabetes, high blood pressure, osteoarthritis, and some types of cancer including breast and colon.

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Changes in Weight and Fat Distribution. Palmera and Clegg [ 19 ] also reported that females have different adipose distributions in different menstrual status: they tend to have more subcutaneous fat mainly on hips and thighs before menopause, which protects against the negative consequences associated with obesity and the metabolic syndrome [ 19 ].

However, in our analysis, we did not observe similar results. The fact that we could not distinguish between visceral and subcutaneous fat mass may be an explanation. Comparatively, the fat-free mass of postmenopausal women was lower than that of premenopausal women, which is consistent with physiological changes.

After menopause, decreases in estrogen and vitamin D levels and athletic ability may accelerate reduction in muscle and bone mineral levels, which mainly consists of fat-free mass.

BMI cannot reflect the distribution of fat. However, in our study, we used bioimpedance to separate fat in the trunk, arms, and legs and further analyze its association with the risk for breast cancer in both pre- and postmenopausal women.

However, we did not find any association between BMI, WC, and whole-body fat mass, or different segments and breast cancer risk in premenopausal women. This is consistent with the results of previous investigations [ 15, 17, 25 ]. The difference may, in part, be explained by the fact that the women we involved were 37—73 years of age and no much younger participants.

Other factors such as irregular menstrual cycle and abnormal follicular cycle, which have less exposure to estrogens and progesterone, may also reduce the risk [ 26, 27 ]. Despite the neutral effects of body fat distribution on the risk for breast cancer among premenopausal women, we still advocate for appropriate weight control because high BMI contributes to 4.

In our study, body fat mass was measured using bioelectrical impedance to further analyze the associations between body fat distribution in different parts and the risk for breast cancer in both pre- and postmenopausal women.

We concluded that body fat mass or fat mass in different body segments, BMI, and WC demonstrated a significant positive association with breast cancer among menopausal women. WC, BMI, overall fat, and body fat distribution were highly consistent with the risk for breast cancer among postmenopausal women.

The potential mechanisms have been analyzed in nine prospective studies, which suggested that postmenopausal women with breast cancer had higher levels of estradiol and estrogen than breast cancer-free postmenopausal women [ 32 ]. In addition, elevated estrogen levels may promote cell proliferation and pro-angiogenic activity, which may lead to the development of breast cancer [ 33 ].

Our results also suggest that not only fat mass in the trunk or abdominal adiposity but entire fat mass and fat mass in different body segments were associated with the increased risk for breast cancer among postmenopausal women.

This implies that a decrease in total body fat or BMI levels, resulting from a decrease in fat mass of any body segment, may be beneficial in mitigating cancer risk among postmenopausal women and is not limited to abdominal fat. Strengths of this study include its nationwide, prospective cohort and large sample sizes, with a follow-up of approximately 6.

Multivariable adjustments were used to control for multiple potential confounders. However, this study also had limitations, the first of which was the definition of pre- and postmenopausal women.

In general, there may be a misclassification bias in the number of pre- and postmenopausal women. Second, due to the lack of histological information, we did not further analyze the effects of fat mass on each subtype of breast cancer.

Third, body fat mass was measured only at baseline, and we could not analyze the association between body fat changes and the risk for breast cancer.

Finally, this cohort consisted mainly of Europeans; therefore, characteristics of other ethnicities remain unclear. In our study, we found that postmenopausal women have higher levels of whole-body fat and fat mass in different body segments compared to premenopausal women. Among postmenopausal women, the fat mass in different body segments was strongly associated with the increased risk for breast cancer.

This indicates that the management of whole-body weight and fat in any part of the body will contribute to reduce the risk for breast cancer but is not limited to the abdomen. This work was conducted using the UK Biobank Resource application number We thank the participants and staff of the UK Biobank cohort for their valuable contributions.

Subjects have given their written informed consent. This study protocol was reviewed and approved by the North West Multi-center Research Ethics Committee, Scottish Community Health Index Advisory Group, and the England and Wales Patient Information Advisory Group, approval number This work was supported by the Startup Fund for the Top Talents Program, Sun Yat-sen University, under Grant No.

SZSM; and the Hospital Research Fund of SAHSYSU under Grant No. Yang Cao wrote original draft. Zhen Zhang, Dan Hu, and Xinwei Huang contributed to the methods and discussion parts.

Bin Xia had the data analysis. Fangping Li and Jinqiu Yuan had revised the manuscript and finally approved the version to be published. Data were obtained from UK Biobank application number , approved August Further inquiries can be directed to the corresponding authors.

Sign In or Create an Account. Search Dropdown Menu. header search search input Search input auto suggest. filter your search All Content All Journals Obesity Facts. Advanced Search. Skip Nav Destination Close navigation menu Article navigation. Volume 16, Issue 4. Statement of Ethics.

Conflict of Interest Statement. Funding Sources. Author Contributions. Data Availability Statement. Article Navigation. Research Articles March 07 Association of Body Fat Distribution and Risk of Breast Cancer in Pre- and Postmenopausal Women Topic Article Package: Topic Article Package: Antibody-Drug Conjugates.

Subject Area: Endocrinology , Further Areas , Gastroenterology , General Medicine , Nutrition and Dietetics , Psychiatry and Psychology , Public Health.

Yang Cao ; Yang Cao. a Department of Endocrinology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.

This Site. Google Scholar. Bin Xia ; Bin Xia. b Clinical Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China. c Scientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.

Zhen Zhang ; Zhen Zhang. Dan Hu ; Dan Hu. Xinwei Huang ; Xinwei Huang. yuanjq5 mail. ZSQYNFMK Obes Facts 16 4 : — Article history Received:. Cite Icon Cite. toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest.

Association of Body Fat Distribution and Risk of Breast Cancer in Pre- and Postmenopausal Women Topic Article Package: Topic Article Package: Antibody-Drug Conjugates. Subject Area: Endocrinology , Further Areas , Gastroenterology , General Medicine , Nutrition and Dietetics , Psychiatry and Psychology , Public Health.

Yang Cao ; Yang Cao. a Department of Endocrinology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China. This Site. Google Scholar. Bin Xia ; Bin Xia. b Clinical Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.

c Scientific Research Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China. Zhen Zhang ; Zhen Zhang. Dan Hu ; Dan Hu. Xinwei Huang ; Xinwei Huang. yuanjq5 mail.

ZSQYNFMK Obes Facts 16 4 : — Article history Received:. Cite Icon Cite. toolbar search Search Dropdown Menu. toolbar search search input Search input auto suggest. Journal Section:. Table 1. Characteristics of study participants.

Whole-body fat mass premenopausal. Whole-body fat mass postmenopausal. N 23, 18, 16, 17, 38, 43, 44, 43, Age, mean SD , years View Large. Table 2. Comparison of segmental body composition between premenopausal and postmenopausal women.

Premenopausal women. Postmenopausal women. Whole-body fat mass, mean SD , kg SD, standard deviation; BFP, body fat percentage. Table 3. Bio-impedance measurement.

cases, n. age adjusted. multivariable adjusted. Whole-body fat mass, kg Q1 5. BFP, body fat percentage; BMI, body mass index; WC, waist circumference.

The authors have no conflicts of interest to declare. Global cancer statistics GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in countries. Search ADS. Non-dietary factors as risk factors for breast cancer, and as effect modifiers of the association of fat intake and risk of breast cancer.

Breast cancer and hormone replacement therapy: collaborative reanalysis of data from 51 epidemiological studies of 52, women with breast cancer and , women without breast cancer. Collaborative Group on Hormonal Factors in Breast Cancer.

Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U. Adiposity and breast cancer risk in postmenopausal women: results from the UK Biobank prospective cohort.

Long-term weight change and breast cancer risk: the European Prospective Investigation into Cancer and nutrition EPIC. Food, nutritional, physical activity, and the prevention of cancer:a global perspective. A meta-analysis of body mass index and risk of premenopausal breast cancer. van den Brandt.

Pooled analysis of prospective cohort studies on height, weight, and breast cancer risk. Premenopausal Breast Cancer Collaborative Group.

Association of body mass index and age with subsequent breast cancer risk in premenopausal women. Body size and breast cancer risk: findings from the European Prospective Investigation into Cancer and Nutrition EPIC.

Association of body fat and risk of breast cancer in postmenopausal women with normal body mass index: a secondary analysis of a randomized clinical trialand observational study.

Difference in segmental lean and fat mass components between pre- and postmenopausal women. UK Biobank. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age.

Body composition and risk of major gynecologic malignancies: results from the UK Biobank prospective cohort. The role of oestrogens and progestagens in the epidemiology and prevention of breast cancer. The age-specific quantitative effects of metabolic risk factors on cardiovascular diseases and diabetes: a pooled analysis.

Emerging Risk Factors Collaboration. Separate andcombined associations of body-mass indexand abdominal adiposity with cardiovascular disease: collaborative analysis of 58 prospective studies.

GBD Obesity Collaborators. Endogenous sex hormones and breast cancer in postmenopausal women: reanalysis of nine prospective studies. Estrogens, progestogens, normal breast cell proliferation, and breast cancer risk. The use of bioelectrical impedance analysis for body composition in epidemiological studies.

Body composition measurement: a review of hydrodensitometry, anthropometry, and impedance methods. Why bioelectrical impedance analysis should be used for estimating adiposity.

Yang Cao and Bin Xia contributed equally to this work. Published by S. Karger AG, Basel. This article is licensed under the Creative Commons Attribution-NonCommercial 4.

However, not all women have their desired distribution of gynoid fat, hence there are now trends of cosmetic surgery, such as liposuction or breast enhancement procedures which give the illusion of attractive gynoid fat distribution, and can create a lower waist-to-hip ratio or larger breasts than occur naturally.

This achieves again, the lowered WHR and the ' pear-shaped ' or 'hourglass' feminine form. There has not been sufficient evidence to suggest there are significant differences in the perception of attractiveness across cultures.

Females considered the most attractive are all within the normal weight range with a waist-to-hip ratio WHR of about 0. Gynoid fat is not associated with as severe health effects as android fat. Gynoid fat is a lower risk factor for cardiovascular disease than android fat. Contents move to sidebar hide.

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Download as PDF Printable version. Female body fat around the hips, breasts and thighs. See also: Android fat distribution. Nutritional Biochemistry , p. Academic Press, London. ISBN The Evolutionary Biology of Human Female Sexuality , p. Oxford University Press, USA.

Relationship between waist-to-hip ratio WHR and female attractiveness". Personality and Individual Differences. doi : Acta Paediatrica. ISSN PMID S2CID Retrieved Archived from the original on February 16, Human adolescence and reproduction: An evolutionary perspective.

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