Body composition characteristics and fat distribution patterns in young infertile women

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1 FERTILITY AND STERILITY VOL. 81, NO. 3, MARCH 2004 Copyright 2004 American Society for Reproductive Medicine Published by Elsevier Inc. Printed on acid-free paper in U.S.A. Body composition characteristics and fat distribution patterns in young infertile women Sylvia Kirchengast, a.o.univ.prof, a and Johannes Huber, o.univ.prof b University Clinic for Gynecology and Obstetrics, Department of Endocrinology, University of Vienna Medical School, Vienna, Austria Objective: To document body composition and fat patterning characteristics in normal and underweight infertile women. Design: Status quo method. Setting: University clinics. Patient(s): Fifteen amenorrheic women with anorexia nervosa, 16 women with polycystic ovary syndrome (PCO2), 10 women with primary amenorrhea and 19 healthy controls. Intervention(s): None. Main Outcome Measure(s): Determination of body mass index, body composition parameters such as fat mass, lean body mass, bone mass using dual-energy x-ray absorptiometry (DEXA), fat distribution patterns, 17 -estradiol, FSH, LH, prolactin, progesterone, testosterone, DHEA-S, and androstenedione levels. Result(s): A statistically significant difference was found comparing all proband groups with healthy controls for the majority of body fat and bone mineral content parameters but not for lean body mass. Infertile women of normal weight, with PCOS, and with primary amenorrhea exhibited an extraordinarily high amount of fat tissue and a tendency toward android fat patterning. In contrast, patients with anorexia nervosa and the healthy controls showed predominantly gynoid fat patterning. According to logistic regression analyses, anorexia nervosa was characterized by reduced fat tissue and PCOS was characterized by android fat patterning and an increased fat percentage. Patients with primary amenorrhea were characterized by reduced bone mass. Conclusion(s): Infertile young women showed characteristic differences in body composition and fat distribution patterns when compared with healthy, fertile, age-matched counterparts. (Fertil Steril 2004;81: by American Society for Reproductive Medicine.) Key Words: Infertility, body composition, weight status, fat distribution, PCOS, primary amenorrhea, anorexia nervosa Received January 9, 2003; revised and accepted August 22, Reprint requests: Sylvia Kirchengast, Institute for Anthropology, University of Vienna, Althanstrasse 14, A-1090 Vienna, Austria (FAX: ; sylvia.kirchengast@univie.ac.at). a Institute for Anthropology, University of Vienna, Vienna, Austria. b University Clinic for Gynecology and Obstetrics, Department of Endocrinology, University of Vienna Medical School, Vienna, Austria /04/$30.00 doi: /j.fertnstert Several epidemiological studies have emphasized the importance of body composition, especially of abdominal or android fat distribution patterns, as risk factors for cardiovascular and metabolic diseases such as diabetes mellitus (1, 2). It seems obvious that steroid hormones have effects on human adipose tissue metabolism and distribution (3, 4). In the female, body composition parameters and weight status are also clearly associated with reproductive function (5 9). The importance of body fat and energetics for female reproductive success was first pointed out during the 1970s Frisch (10), although the so-called Frisch hypothesis has since been disproved (11 13). Although the energy costs of human reproduction are lower than those of any other group of mammals (13), human ovarian function is extremely vulnerable to an energy imbalance (11). Pregnancy requires about 50,000 calories over and above normal metabolic requirements, and lactation requires from 500 to 1000 calories per day (14). Therefore, ovarian function shows a graded continuum from fully competent cycles through luteal phase suppression, follicular phase suppression, ovulatory failure, oligomenorrhea, or amenorrhea in response to endogenous and exogenous factors affecting energy balance (11). Just as a negative energy balance and low amount of body fat have a negative effect on human ovarian function, a 539

2 highly elevated amount of body fat and android kind of fat patterning also seem to affect female reproductive function negatively (6, 14, 15). Disturbed ovarian function seems to be associated with an extremely low or an extremely high amount of body fat and abdominal or android fat patterning, which is typical in healthy, postmenopausal women only (16). Furthermore, an android kind of fat patterning is associated with significantly decreased conception rates (17 19). In this way, body composition parameters as well as fat distribution patterns may be interpreted as extragenital markers of human ovarian function. The aim of the present study was to document body composition and fat patterning of young, infertile, normal weight women to test the hypothesis that body composition and fat distribution patterns are markers of potential female fertility. MATERIALS AND METHODS Study Participants The study enrolled 41 infertile Austrian women aged 18 to 30 years (x 23.5) and 19 healthy, age-matched controls (x 23.7). All controls had regular menstrual cycles (cycles of 26 to 33 days) and age-specific normal sex-hormone levels. Chromosomal aberrations such as Turner syndrome were excluded from the present sample. The sample of infertile young women was divided into three subgroups. Group 1 was 15 women (age range: 18 to 29 years) with secondary amenorrhea for more than 9 months as a result of low body weight from anorexia nervosa; all were extremely underweight but at the time of investigation their weight status was not life threatening. Group 2 consisted of 16 women (age range: 18 to 30 years) with PCOS, as diagnosed by ultrasound appearance of polycystic ovaries combined with hyperandrogenemia and elevated LH levels; all had secondary amenorrhea or oligomenorrhea. Group 3 comprised 10 women (age range: 18 to 30 years) who suffered from primary amenorrhea. None of the women suffering from primary amenorrhea had anatomic abnormalities; their primary amenorrhea was classified as idiopathic. Remarkably, 7 of the 10 women with primary amenorrhea had never sought medical treatment for the condition until their 20s. They reported that they had had no problems with their primary amenorrhea up to the time when they would have liked to become pregnant. Women who exhibited a body mass index (BMI) kg/m 2 were excluded from the present analyses. All women enrolled in the present study were white, underweight or normal weight, native Austrians. All lived in Vienna or neighboring Lower Austria and belonged to the social middle class. No data regarding education, professional training, profession, or place of residence were collected. None of the probands had ever been pregnant. All women were nonsmokers, and none of them were taking any medication that might affect hormone metabolism or body composition. Hormonal contraceptive usage had been stopped for a minimum of 4 months before the present investigation. Menstrual History Using a structured questionnaire, all probands were interviewed regarding their menstrual history. Data were collected on age at menarche, minimum and maximum cycle length, duration of amenorrhea, and use of hormonal medication. Protocol and Measurements Body Composition Analyses Body composition analyses and bone density analyses were performed using dual energy x-ray absorptiometry (DEXA) (Hologic 4000; Hologic, Inc., Waltham, MA) at the University Clinic for Gynecology and Obstetrics in Vienna (20). Although this method is indirect, its high reliability, relatively low cost, and greater comfort for the patients make DEXA especially useful for the determination of body composition. With this method, body composition consists of soft tissue (i.e., fat and lean soft tissue, and bone): DEXA measures total body bone mineral content (BMC) and density (BMD), and fat mass and lean mass with a precision (coefficient of variation) of 0.9%, 4.7%, and 1.5% respectively. The precision for abdominal fat mass and fat percentage (fat %) is 4.3% and 3.4%, respectively. The relatively low radiation dose with 0.1 m Sievert and short scanning time ( 7 minutes) 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 patient. 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, and vertical lines passing through colli femuri. The region below this lower border of the trunk, including both legs and the hip region, is called the lower body region. For each region of the whole body, fat and lean body mass and BMC were determined. Fat Distribution Analysis For a better description of the sex typical fat distribution the fat distribution index (FDI) (21) was calculated: FDI Upper body fat mass (kg)/lower body fat mass (kg). An FDI below 0.9 indicates a gynoid fat patterning: the fat mass of the lower body surpasses the fat mass of the upper body. An FDI 1.1 defines an android fat distribution: the amount of upper body fat surpasses that of the lower body region. An FDI between 0.9 and 1.1 is defined as an intermediate stage of fat distribution. We are aware that the most widely used measure of fat distribution patterns is the waist-to-hip ratio. However, the waist-to-hip ratio describes actual body shape and body 540 Kirchengast and Huber Body composition and infertility Vol. 81, No. 3, March 2004

3 TABLE 1 Comparison of hormonal levels Kruskal-Wallis tests. Hormone Primary amenorrhea Anorexia nervosa PCOS Controls X (SD) X (SD) X (SD) X (SD) P value E 2 (pg/ml) 37.9 (36.1) 16.0 (7.3) (33.94) 78.4 (46.0).004 FSH (mu/ml) 2.98 (3.27) 5.65 (1.69) 5.17 (2.15) 6.80 (2.05).005 LH (mu/ml) 2.02 (3.69) 1.83 (2.60) 5.97 (5.11) 7.47 (4.32).007 HPRL (ng/ml) (13.88) (8.79) (17.16) 9.80 (3.05) NS P (ng/ml) 0.94 (2.19) 0.40 (0.13) 1.37 (1.64) 1.23 (1.91) NS T (ng/ml) 0.19 (1.11) 0.36 (0.20) 0.58 (0.37) 0.32 (0.11).004 A (ng/ml) 1.99 (0.74) 2.44 (0.89) 3.01 (1.62) 1.99 (0.59) NS DHEA-S ( g/ml) 1.80 (1.11) 1.68 (0.66) 2.31 (1.01) 1.82 (0.42).05 GH (ng/ml) 2.89 (3.83) 2.56 (2.06) 0.98 (0.37) 2.68 (3.18) NS TSH ( U/mL) 2.15 (1.17) 1.55 (0.80) 1.46 (1.14) 1.44 (0.74) NS Kirchengast. Body composition and infertility. Fertil Steril silhouette but not the quantitative amount of fat distribution. Furthermore, we are aware that the FDI describes not the ratio of abdominal fat to gluteofemoral fat but the ratio between upper body fat, including abdominal fat and breast fat mass, and lower body fat. Weight Status After stature (in cm) and body weight (in kg) had been calculated according to previously published methods (22), the individual s weight status was determined by means of body mass index (BMI): Weight (kg)/stature (m 2 ). World Health Organization (23) criteria were used for the weight status classification: Thinness grade 1: BMI (mild thinness) Thinness grade 2: BMI (moderate thinness) Thinness grade 3: BMI (severe thinness) Normal range: BMI Overweight grade 1: BMI (overweight) Overweight grade 2: BMI (obese 1) Overweight grade 3: BMI (obese 2) Hormonal Parameters Blood samples for the quantitative determination of hormone levels were collected between 7.30 AM and 9.30 AM before the 10th day of cycle (in menstruating women). The quantitative determination was made at the central hormone laboratory of the University Clinic for Gynecology and Obstetrics. After coagulation, the samples were centrifuged and the serum was stored at 20 C until further processing. Assays were employed according to NCCLS guidelines as follows (intra-assay and interassay CV in parentheses): The following hormones were determined: 17 -estradiol (5.2%; 8.5%) (Autodelfia; Wallac Oy, Turku, Finland), follicle-stimulating hormone (FSH) (4.2%; 8.3%) (Enzymun ES700; Böhringer Mannheim, Mannheim, Germany); luteinizing hormone (LH) (9.3%; 3.9%) (Autodelfia; Wallac Oy), prolactin (4.7%; 8.5%) (Enzymun; Böhringer Mannheim), progesterone (6.4%; 10.0%) by radioimmunoassay (Coat-A- Coat RIA; DPC, Los Angeles, CA), testosterone (6.5%, 11.2%), dehydroepiandrostendionsulfate (DHEA-S) (7.4%; 10.5%) by radioimmunoassay (Immunotech, Westbrook, ME); and androstenedione (6.6%; 9.0%) by radioimmunoassay (Immunotech, Westbrook, ME). Statistical Analyses Statistical analyses were performed by means of SPSS Version 10.0 (SPSS, Inc., Chicago, IL). After computing descriptive statistics (mean, standard deviation, median, range), Kruskal-Wallis tests were calculated to group differences with respect to their statistical significance. Because of the low number of patients and the results of the Kolmogorov-Smirnov test, which indicated that no normal distribution of the data could be assumed, nonparametric tests were applied predominantly. Chi-squares were computed to test group differences with respect to categorical variables. Binary logistic regression analyses were performed to test the association of body composition, weight status, and fat patterning with ovarian function (proband group). RESULTS Comparison of Hormone Levels In the first step of analyses, the sex-hormone levels of the four groups were compared. The four groups differed significantly in estradiol, FSH, LH, testosterone, and DHEA-S levels. As expected, PCOS patients exhibited the highest androgen levels and women with primary amenorrhea and anorexia nervosa showed lower estrogen, gonadotropin, and progesterone levels than PCOS patients and healthy controls (Table 1). Comparison of Body Composition and Fat Distribution Patterns Although only the normal weight and underweight women were included in the present analyses, the four FERTILITY & STERILITY 541

4 TABLE 2 Comparison of body composition parameters Kruskal-Wallis tests. Variable Primary amenorrhea Anorexia nervosa PCOS Controls X (SD) X (SD) X (SD) X (SD) P value Fat head (kg) 0.8 (0.1) 0.7 (0.0) 0.8 (0.1) 0.8 (0.1) NS Fat trunk (kg) 6.2 (2.7) 3.1 (1.6) 14.1 (7.5) 5.5 (2.4).0001 Fat arm (kg) 1.1 (0.4) 0.5 (0.2) 1.3 (0.5) 0.9 (0.4).0001 Fat leg left (kg) 3.8 (1.2) 2.5 (0.7) 4.6 (0.9) 3.9 (1.0).0001 Fat leg right (kg) 3.8 (1.2) 2.6 (0.8) 4.7 (1.1) 3.9 (0.9).0001 Fat total (kg) 16.7 (5.6) 10.2 (3.2) 21.7 (5.6) 16.1 (4.8).0001 Lean head (kg) 2.9 (0.3) 2.9 (0.2) 3.1 (0.3) 2.9 (0.2) NS Lean trunk (kg) 18.5 (2.3) 19.9 (1.8) 18.8 (2.5) 20.6 (2.0) NS Lean arm (kg) 2.1 (0.5) 1.8 (0.4) 1.5 (0.4) 2.0 (0.5).02 Lean leg left (kg) 6.2 (1.3) 5.9 (0.8) 5.5 (0.6) 6.4 (1.2) NS Lean leg right (kg) 6.3 (1.5) 6.2 (0.9) 5.6 (0.8) 6.6 (1.8) NS Lean total (kg) 37.9 (6.4) 37.7 (2.8) 35.4 (3.7) 40.4 (4.8) NS BMC head (g) (14.4) (77.6) (67.4) (79.4).006 BMC trunk (g) (718.8) (78.9) (0.99.2) (101.7).01 BMC arm (g) (23.0) (22.1) (14.9) (23.8).01 BMC leg left (g) (69.6) (57.3) (60.6) (56.0).04 BMC leg right (g) (64.9) (57.5) (65.8) (67.5).01 BMC total (g) (256.5) (233.1) (276.7) (245.2).008 Fat % head 20.2 (0.2) 17.1 (2.1) 17.4 (1.0) 18.3 (2.7).002 Fat % trunk 23.8 (7.6) 12.7 (6.1) 31.8 (10.4) 20.2 (5.9).0001 Fat % arm 31.9 (6.8) 22.5 (9.8) 43.3 (10.1) 31.6 (11.9).001 Fat % leg left 36.5 (6.4) 28.3 (6.5) 42.9 (6.3) 36.1 (5.1).0001 Fat % leg right 36.5 (7.2) 28.2 (7.1) 41.8 (6.9) 35.6 (5.1).0001 Fat % total 29.2 (5.7) 19.9 (5.5) 35.7 (7.6) 27.1 (4.4).0001 Stature (cm) (9.9) (4.5) (5.1) (5.7) NS Body weight (kg) 56.6 (11.9) 49.9 (4.9) 57.8 (3.9) 58.6 (9.1).001 BMI (kg/m 2 ) (3.4) (1.49) (1.42) (2.37).0001 FDI 0.81 (0.27) 0.58 (0.22) 1.03 (0.23) 0.70 (0.19).003 Kirchengast. Body composition and infertility. Fertil Steril groups differed significantly regarding weight status ( df 6; P. 003). None of the PCOS patients was underweight; this was also true of 16.7% of the controls, 73.5% of the anorexia nervosa patients, and 40% of the women with primary amenorrhea. Regarding body composition parameters, the three groups of infertile women and the healthy controls showed a highly statistically significant difference in nearly all body fat and bone mineral content parameters but not in lean body mass, with the exception of the lean mass of the arm (Table 2). Although overweight women were excluded from the present analyses, women with PCOS exhibited not only an extraordinarily high amount of absolute and relative fat tissue in comparison with the anorexia nervosa patients, women with primary amenorrhea, and healthy controls, but they also showed a tendency toward android fat distribution patterns. The fat distribution patterns of nearly 70% of the women with PCOS and 40% of those with primary amenorrhea were classified as intermediate or android. In contrast, about 80% of anorexia nervosa patients and the healthy controls showed a typically gynoid kind of fat patterning; none of them exhibited an android fat distribution. The group differences regarding fat distribution patterns were statistically highly significant ( , P.003, df 6). According to the results of the logistic regression analyses, anorexia nervosa patients were characterized by a significantly reduced fat mass (coefficient 0.54, P.01); PCOS patients, in comparison with healthy controls, are especially characterized by a high fat distribution index (coefficient 4.63, P.01), indicating android fat patterning and increased fat percentage (coefficient 0.19 P.05). Primary amenorrhea was most of all related to a reduced bone mass in comparison with healthy controls (coefficient 0.03, P.05). DISCUSSION Female reproductive function has been known to be associated with body composition characteristics for a long time. It is well known that female reproductive function is extremely vulnerable to energy imbalance and changes in energy storage (11, 24). A reduction of metabolic fuel availability below a critical level by food restriction or increased 542 Kirchengast and Huber Body composition and infertility Vol. 81, No. 3, March 2004

5 expenditure is appropriately accompanied by activation of multiple neuroendocrine changes, resulting in anovulation and amenorrhea (25). In particular, body fat, which is the most important compartment for the body s energy storage, influences ovarian function in different ways (24). The conversion from androgens to estrogens by aromatization takes place at the adipose tissue; nearly a third of circulating estrogens in women during reproductive phase stem from this conversion. Body fat influences the direction of estrogen metabolism to more potent or less potent forms; leaner women with a reduced amount of body fat show higher levels of less potent forms of estrogens, such as catechol estrogens. High amounts of body fat seem to be associated with reduced capacity to bind sex hormone-binding globulin; thus, an elevated percentage of free serum estradiol is found in obese and overweight women. Adipose tissue also can store steroid hormones; an indirect mechanism may be providing signals to the hypothalamus of abnormal control of temperature and changes in energy metabolism that accompany excessive leanness in women. Finally, a high amount of fat tissue, especially in combination with abdominal fat patterning, is associated with supranormal estrogen production due to increased activity of the aromatase system (6). Obesity and abdominal fat patterning are associated with hyperandrogenism, mostly found in women suffering from PCOS (7, 26, 27). Several studies had yielded an association between fat distribution patterns and reproductive function or reproductive success. Our study compared body composition parameters and fat distribution patterns of three groups of young women with ovarian failure. For measuring fat distribution patterns, we decided to use the fat distribution index rather than the waist-to-hip ratio (WHR). We are aware that WHR is frequently used to describe female body shape, but we wanted to estimate the quantitative ratio of upper to lower body fat, not simply describe the body silhouette. Although the majority of women suffering from PCOS are overweight, we included exclusively normal weight or underweight women in the present analysis to improve comparability of the data. Anorexia nervosa, PCOS, and primary amenorrhea have completely different etiologies and hormonal characteristics, but we could demonstrate that in all three forms of ovarian failure the body composition parameters and fat distribution patterns seem to be related to the disturbed ovarian function. Anorexia nervosa is characterized by restricted food consumption and a long-time negative energy balance (28 30). Therefore, the extremely low amount of body fat we found among our anorectic patients was expected. This decreased amount of fat tissue leads to a long-term negative energy balance and a suppression of ovarian function, although women may recover and ovarian function may normalize again. The typical gynoid fat patterning of anorexia nervosa may indicate the potential possibility of reproductive success after a time of nutritional surplus (31). In contrast, the prognosis for PCOS is worse. Although we excluded overweight women from the present analyses, the PCOS women exhibited the significantly highest amount of body fat; 50% of the women showed an android kind of fat patterning. This prevailing android fat patterning is not only in clear contradiction to standards of female attractiveness in 90% of investigated cultures (32, 33), it is also strongly associated with hyperandrogenism (6, 7, 26) and markedly decreased conception rates (17 19). In healthy women, android fat patterning is found nearly exclusively during the postmenopause period, the postreproductive phase of female life (16). Even the results of the binary logistic regression analyses demonstrated that PCOS women were characterized by an increased fat percentage and an increased fat distribution index, indicating a tendency toward android fat patterning. Furthermore, a decreased amount of lean body mass was found among the PCOS patients, which is in sharp contrast to the increased androgen levels found among this group. Because androgens act anabolically, an increased lean body mass might be assumed; however, the PCOS women of the present study exhibited the lowest amount of lean body mass at all anatomical regions among all of the study groups. The women with primary amenorrhea exhibited a slightly increased amount of body fat in comparison with healthy controls and anorectic patients. In contrast, their bone mineral content was significantly decreased. This may be due to the long-term decrease in sex-hormone levels. These young women actually never experienced the hormonal changes of puberty inducing menarche. The importance of sex steroids in the development and maintenance of the skeleton in women is unquestioned. Estrogen deficiency at any age is associated with negative skeletal effects (34). The low levels of sex steroids in this group may be the reason for their reduced bone mass. Reduced bone mass is not a visible marker of infertility, so we must consider the fat distribution patterns of women with primary amenorrhea. Although only underweight and normal weight women were included in the analyses, 20% of the infertile probands in our sample exhibited android fat patterning, and 80% exhibited a gynoid or an intermediate kind of fat patterning. In contrast, none of the healthy controls showed android fat distribution patterns. Although 20% is not a very high percentage, our sample size was rather small. 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