Abstract
Background
The prevalence of metabolic syndrome (MetS) in polycystic ovary syndrome (PCOS) has been studied in different populations, but their results were so controversial regarding Iranian women. These controversial data indicated the need for more investigation of MetS characteristics in PCOS patients in our population. So this study aimed to evaluate the clinical and laboratory characteristics and metabolic features of patients with PCOS in Rasht.
Materials and Methods
This prospective cross sectional study was conducted on 215 PCOS women who lived in Rasht, north of Iran, from March 2010 to July 2012. The participants were then divided into two groups of women with MetS (n=62) and women without MetS (n=153). The diagnosis of PCOS and MetS were based on the Rotterdam 2003 criteria and the Adult Treatment Panel III (ATP III) criteria, respectively. Demographic characteristics, fertility characteristics, family history and laboratory findings were assessed.
Results
The prevalence of MetS in women with PCOS was 28.8%. In PCOS women of both groups, the waist circumference (WC) exceeded 88cm in 72.6%, hypertension [systolic blood pressure (SBP) and/or diastolic blood pressure (DBP) ≥130/85mm Hg] was prevalent in 9.3%, fasting blood sugar (FBS) level was ≥110 mg/dl in 6%, triglycerides (Tg) level were ≥150 mg/dl in 47%, and high-density lipoprotein (HDL) level was <50 mg/dl in 86%. The values of WC, SBP, DBP, body mass index (BMI), ovarian size, Tg, cholesterol, FBS, 2-hour blood sugar, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were significantly greater in PCOS women with MetS than women without MetS. Also HDL and luteinizing hormone (LH) levels in women with MetS were significantly lower than women without MetS.
Conclusion
Prevalence of MetS in PCOS women was 28.8%, indicating that this value is higher than other studies conducted on PCOS women in Iran and other studies conducted on general population in Iran. PCOS women are considered as a high-risk population for MetS. The special strategies are required to prevent MetS and its associated complications in PCOS women.
Keywords: Polycystic Ovary Syndrome, Metabolic Syndrome, Prevalence
Introduction
Polycystic ovary syndrome (PCOS) is one of the most common gynecological endocrinopathy among reproductive-aged women (1, 2). The prevalence of PCOS have been reported from 2.2 to 26% in different studies conducted in various countries, depending on sampling method , the criteria used for its definition and the method used to define each criterion (1-3). The clinical and biochemical features of PCOS may vary according to race, ethnicity and the diagnostic criteria used (4). In a study by Tehrani et al. (3), the prevalence of PCOS in a community sample of Iranian population was 7.1% using the National Institute of Health (NIH) definition, 11.7% by the Androgen Excess Society (AES) criteria and 14.6% using the Rotterdam consensus definition. The classic form of PCOS is characterized by chronic anovulation (oligomenorrhea or amenorrhea), hyperandrogenism, infertility, hirsutism, obesity and enlarged bilateral ovaries with cysts (5-7). The pathogenesis of PCOS is not fully understood, although genetic, metabolic and neuroendocrine interactions as well as environmental factors were discussed elsewhere (8-11). Alterations in several metabolic pathways such as steroid hormone regulation and insulin signaling pathway abnormalities were discussed in the pathophysiology of PCOS (12-14). More than 50 percent of women with PCOS are obese or overweight that may predispose them to metabolic disorders (15).
The metabolic syndrome (MetS) is one type of endocrine disturbance that consists of insulin resistance, dyslipidemia, obesity, central adiposity, and hypertension that has been shown to be associated with a two-fold increased risk of cardiovascular disease and a five-fold increased risk of type 2 diabetes (16). The prevalence of MetS in PCOS has been studied in different populations (16-19). In a study conducted in the USA showed that the prevalence of MetS in PCOS women was approximately 43 to 46%, while for aged-matched women in the general population, it was nearly 2-fold higher (16). However, the findings of several studies conducted in Iran regarding the prevalence of MetS in PCOS women were controversial (18-20). Hosseinpanah et al. (18) showed that MetS was less frequent in patients with PCOS. However, in other studies, MetS was noted in younger PCOS patients in comparison with older PCOS women (19, 20). These controversial data indicate the need for more investigation of MetS characteristics in PCOS patients in our population, as it may help in planning screening strategies to prevent long-term effects (17). Therefore, this study aimed to evaluate the clinical and laboratory characteristics and metabolic features of patients with PCOS in Rasht, North of Iran.
Materials and Methods
This prospective cross sectional study was conducted on 215 PCOS women aged 15-35 years who were referred to private and public gynecological endocrinology clinics, Rasht, north of Iran, from March 2010 to July 2012. The exclusion criteria were as follows: lactating and pregnant women, previous history of ovarian surgery, use of steroid hormone drugs such as oral contraceptive pill and progesterone for past 6 months, use of dyslipidemia drugs for last 3 months, and use of any medications known to affect glucose metabolism or BP. Furthermore women with following conditions were excluded: hypothyroidism, hyperprolactinemia, congenital adrenal hyperplasia, androgen- producing tumor, and Cushing’s syndrome that were diagnosed by physical examination and laboratory testing using serum levels of thyroid stimulating hormone (TSH), prolactin (PRL), and 17a-hydroxyprogesterone (17a-OHP). All patients provided a written informed consent before entering the study. The participants were then divided into two groups of women with MetS (n=62) and women without MetS (n=153). The study protocol was approved by the Ethics Committee of Guilan University of medical sciences, Rasht, Iran.
The diagnosis of PCOS was based on the Rotterdam 2003 criteria, in which any two of the following three conditions need to be fulfilled for the inclusion: i. Oligo- and/or anovulation (i.e. less than 9 menstrual periods in a year or menstrual cycles more than 35 days in length), ii. Clinical hyperandrogenism (i.e. acne or hirsutism; modified Ferriman-Gallwey scores ≥8) or biochemical hyperandrogenism [i.e. free testosterone (FT) ≥7.0 pg/ml], and iii. Ultrasonographic findings of polycystic ovarian morphology (presence of ≥12 follicles in each ovary measuring 2-9 mm in diameter). Based on these criteria, four phenotypes were formed as follows: type 1 including irregular menstruation+PCO using ultrasonographic examination+hyperandrogenism (IM+PCO+HA), type 2 including irregular menstruation+PCO using ultrasonographic examination (IM+PCO), type 3 including irregular menstruation+hyperandrogenism (IM+HA) and type 4 including PCO using ultrasonographic examination+hyperandrogenism (PCO+HA).
MetS was defined according to the Adult Treatment Panel III (ATP III) criteria as the co-occurrence of three or more of the following risk factors: i. Central obesity with waist circumference (WC) ≥88 cm in women, ii. Elevated systolic blood pressure (SBP) and/or diastolic blood pressure (DBP) of ≥130/85 mmHg, iii. Impaired level of fasting blood sugar (FBS) ≥110 mg/dL, iv. Elevated level of fasting serum triglycerides (Tg) ≥150 mg/dL and v. Fasting high-density lipoprotein (HDL) level <50 mg/dL.
Anthropometric measurements included height in centimeters, weight in kilograms, and hip and waist circumference in centimeters according to World Health Organization (WHO) categories. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters (kg/m2). Underweight was defined as less than 18.5 (normal range between 18.5 and 24.9), overweight between 25.0 and 29.9 and obese as 30.0 or higher. Sitting blood pressure was measured after a 5-minute rest using a standard sphygmomanometer.
After 12 hours fasting during days 3-5 of menstrual cycle, 10 cc of blood sample was obtained. Follicle-stimulating hormone (FSH) and luteinizing hormone (LH) levels were measured using Access Immunoassay System (Beckman Coulter, Fullerton, California, USA); FT, dehydroepiandrosterone sulfate (DHEAS), and 17a-OHP levels using radio-immunometric assay (RIA) kit (Siemens, USA); as well as TSH level using a chemiluminescence immunometric assay (Immulite 2000 Analyzer, CPC, USA). Also fasting blood sample was used to measure FBS level using Hitachi 7600 analyzer, Hitachi, Japan, while the levels of cholesterol (Chol), Tg, aspartate aminotransferase (AST), alanine aminotransferase (ALT), HDL, and low-density lipoprotein (LDL) were measured using enzymatic calorimetric method (Hitachi 7600). In addition a 75-gram oral glucose tolerance test was measured.
Demographic variables including age, education, occupation, and inhabitant area; reproductive characteristics including parity, history of infertility, type of menstrual irregularity such as oligomenorrhea, amenorrhea, and menometrorrhagia; and family history of diabetes mellitus were collected.
Statistical analysis
All data were analyzed using the Statistical Package for the Social Sciences (SPSS, SPSS Inc., USA) software version 16. Continues data were shown as mean ± standard deviation (SD). Kolmogorov-Smirnov test was used to assess the normality of continuous variable. Normal distribution of quantitative variables was analyzed by two-tailed independent t test and non-normally distributed variables by Mann-Whitney U test. Categorical data were shown as number (percentage). Fisher’s exact tests and chi-square test were used to compare the groups. Statistical significance was considered as P<0.05.
Results
Prevalence of MetS in women with PCOS was 28.8%. In PCOS women of both groups (15-35 years of age), the mean age was 25.63 ± 5.17. In this study, 72 patients were single and 123 were married, but in the analysis of reproductive characteristic, investigators did not assess single patients.
Most of women (83.8%) lived in urban area. Majority (79.7%) of women were housewife and some (38.4%) of women had a university degree. Mean infertility duration was 36.50 ± 41.26. About 54.9, 10.6, and 39.3% of married patients showed a history for infertility, abortion, and diabetes in their families, respectively. Twenty two percent of married women were multiparous. Oligomenorrhea was reported in 85.1% of women. Except family history of diabetes (P=0.043), there were no significant differences regarding demographic and fertility characteristics between PCOS women with MetS and without MetS (Table 1).
Table 1.
Variables | Total (n=215) | With MetS (n=62) | Without MetS (n=153) | P value |
---|---|---|---|---|
Age (Y) | 25.63 ± 5.17 | 26.81 ± 6.07 | 25.15 ± 4.69 | 0.057 |
Inhabitation areaRural | 34 (16.2) | 9 (14.5) | 25 (16.9) | 0.838 |
Urban | 176 (83.8) | 53 (85.5) | 123 (83.1) | |
JobEmployed | 32 (20.3) | 11 (24.4) | 21 (18.6) | 0.511 |
Housewife | 126 (79.7) | 34 (75.6) | 92 (81.4) | |
Educational levelUnder diploma | 42 (26.4) | 12 (27.3) | 30 (26.1) | 0.950 |
Diploma | 56 (35.2) | 16 (36.4) | 40 (34.8) | |
University | 61 (38.4) | 16 (36.4) | 45 (39.1) | |
Duration of infertility | 36.50 ± 41.26 | 30.39 ± 24.04 | 39.42 ± 47.21 | 0.705 |
History of infertility | 95 (54.9) | 30 (58.8) | 65 (68.4) | 0.615 |
History of abortion | 13 (10.6) | 5 (13.5) | 8(9.0) | 0.523 |
Family history of diabetes | 83 (39.3) | 31(50.8) | 52 (34.7) | 0.043 |
History of parityNulliparous | 96 (78) | 24 (75) | 59 (77.6) | 0.760 |
Multiparous | 27 (22) | 8 (25) | 17 (22.4) | |
Oligomenorrhea | 183 (87.6) | 52 (89.7) | 131(86.8) | 0.647 |
Amenorrhea | 20 (9.3) | 6 (10.3) | 14 (9.3) | 0.797 |
Polymenorrehae | 6 (2.8) | 0 | 6 (4) | 0.190 |
Normal | 6 (2.8) | 4(6.5) | 2 (1.3) | 0.059 |
Data are presented as mean ± SD or numbers (%).
The findings of both groups showed that the WC exceeded 88 cm in 72.6%, hypertension (SBP/ DBP ≥130/85 mm Hg) in 9.3%, FBS level was 110 mg/dl or greater in 6%, Tg level was 150 mg/dl or greater in 47%, and HDL level was less than 50 mg/dl in 86%. Individual components of the MetS in two groups of PCOS women (with MetS and without MetS) are shown in table 2.
Table 2.
Components of the MetS | Total (n=215) | With MetS (n=62) | Without MetS (n=153) |
---|---|---|---|
WC ≥88 cm | 156 (72.6%) | 59 (95.2) | 97 (63.4) |
Hypertension (SBP ≥130 mm Hg or DBP ≥85 mm Hg) | 20 (9.3) | 17 (27.4) | 3 (2.0) |
FBS ≥110 mg/dl | 13 (6.0) | 12 (19.4) | 1 (7.7) |
Tg ≥150 mg/dl | 101 (47.0) | 55 (88.7) | 46 (30.1) |
HDL ˂50 mg/dl | 185 (86.0) | 61 (98.4) | 124 (81.0) |
Data are presented as numbers (%). WC; Waist circumference, SBP; Systolic blood pressure, DBP; Diastolic blood pressure, Tg; Triglycerides, FBS; Fasting blood sugar and HDL; high-density lipoprotein.
In all patients, mean values of WC, SBP, DBP, and BMI were 87.37 ± 12.38, 110.32 ± 14.72, 69.90 ± 9.64, and 28.98 ± 11.19, respectively. Mean levels of Tg, FBS, and HDL were 152.39 ± 74.29, 93.02 ± 17.79, and 41.33 ± 8.64, respectively. Mean values of WC, SBP, DBP, and BMI in patients with MetS were significantly higher than women without MetS (Table 3).
Table 3.
Components of the MetS | Total (n=215) | With MetS (n=62) | Without MetS (n=153) | P value |
---|---|---|---|---|
WC (cm) | 87.37 ± 12.38 | 97.24 ± 11.14 | 83.37 ± 10.51 | 0.0001 |
BMI (kg/m2) | 28.98 ± 11.19 | 32.92 ± 10.80 | 27.37 ± 10.94 | 0.001 |
BMI ≥30 | 77 (36) | 42 (67.7) | 35 (23) | 0.0001 |
SBP (mmHg) | 110.32 ± 14.72 | 116.62 ± 15.64 | 107.77 ± 13.56 | 0.0001 |
DBP (mmHg) | 69.90 ± 9.64 | 72.42 ± 10.93 | 68.88 ± 8.91 | 0.015 |
Data are presented as mean ± SD. WC; Waist circumference, BMI; Body mass index, SBP; Systolic blood pressure and DBP; Diastolic blood pressure.
Some laboratory findings including Tg, Chol, FBS, 2-hBS, AST, and ALT were significantly greater in PCOS women with MetS than women without MetS. Also HDL and LH in women with MetS were significantly lower than women without MetS. In other laboratory findings, such as serum levels of LDL, PRL, DHEAS, T, FSH, FSH/ LH, 17OHP, and TSH, differences between two groups were not significant (Table 4).
Table 4.
Variables | Total (n=215) | With MetS (n=62) | Without MetS (n=137) | P value |
---|---|---|---|---|
Tg (mg/dl) | 152.39 ± 74.29 | 202.76 ± 90.69 | 132.0 ± 54.93 | 0.0001 |
Chol (mg/dl) | 180.37 ± 37.08 | 195.18 ± 36.27 | 174.33 ± 35.80 | 0.0001 |
FBS (mg/dl) | 93.02 ± 17.79 | 99.97 ± 29.37 | 90.20 ± 8.46 | 0.012 |
LDL (mg/dl) | 111.72 ± 28.00 | 117.42 ± 30.59 | 109.40 ± 26.63 | 0.057 |
HDL (mg/dl) | 41.33 ± 8.64 | 37.13 ± 6.31 | 43.03 ± 8.88 | 0.0001 |
2-h BS (mmol/l) | 112.90 ± 37.79 | 134.28 ± 54.21 | 104.50 ± 24.53 | 0.001 |
AST (mg/dl) | 22.47 ± 10.57 | 25.76 ± 10.23 | 21.12 ± 10.45 | 0.003 |
ALT (mg/dl) | 20.42 ± 12.94 | 23.53 ± 9.94 | 19.15 ± 13.81 | 0.024 |
PRL (ng/mL) | 19.33 ± 11.44 | 20.47 ± 14.52 | 18.85 ± 9.94 | 0.349 |
DHEAS (mg/dl) | 237.45 ± 136.88 | 228.04 ±145.99 | 241.20 ± 133.38 | 0.527 |
FT (nmol/l) | 1.72 ± 1.59 | 1.89 ± 2.42 | 1.65 ± 1.10 | 0.467 |
FSH (mg/dl) | 6.17 ± 1.77 | 6.01 ± 2.08 | 6.22 ± 1.65 | 0.494 |
LH (mg/dl) | 7.89 ± 4.12 | 6.79 ± 1.64 | 8.29 ± 4.66 | 0.002 |
LH/FSH | 1.34 ± 0.66 | 1.26 ± 0.53 | 1.38 ± 0.70 | 0.251 |
17OHP | 1.91 ± 14.31 | 0.85 ± 0.57 | 2.34 ± 16.91 | 0.494 |
TSH | 3.43 ± 7.75 | 4.95 ± 13.67 | 2.82 ± 2.91 | 0.228 |
Data are presented as mean ± SD. Tg; Triglycerides, Chol; Cholesterol, FBS; Fasting blood sugar, LDL; Low-density lipoprotein, HDL; Highdensity lipoprotein, 2-h BS; 2-hour blood suger, AST; Aspartate aminotransferase, ALT; Alanine aminotransferase, PRL; Prolactin, DHEAS; Dehydroepiandrosterone sulfate, FT; Free testosterone, FSH; Follicle-stimulating hormone, LH; Luteinizing hormone, 17OHP; 17hydroxyprogesterone and TSH; Thyroid stimulating hormone.
Prevalence of MetS in PCO+HA phenotype was highest, but this difference was not statistically significant among four PCOS subtypes (Table 5).
Table 5.
PCOS subtype | With MetS (n=62) | Without MetS (n=137) | P value |
---|---|---|---|
IM+PCO+HA | 38 (32.8) | 78(67.2) | 0.138 |
IM+PCO | 9 (33.3) | 18 (66.7) | |
IM+HA | 10 (17.2) | 48 (82.8) | |
PCO+HA | 5 (38.5) | 8 (61.5) | |
IM; Irregular menstruation, PCO; Polycystic ovary and HA; Hyperandrogenism.
Discussion
PCOS is one of the most important endocrine diseases in women. Many PCOS patients with several metabolic abnormalities are at increased risk of MetS. The prevalence of MetS differs in various populations which is mainly due to definition of PCOS or MetS, sampling methods, selecting controls, as well as age, race and weight of participants. Insulin resistance (IR) plays a crucial role in the pathophysiology of MetS. On the other hand, IR is well recognized to play a major role in the etiology of PCOS (21-23).
As expressed in previous reports, the prevalence of MetS in patients with PCOS is higher than general population (16, 18, 24), but its prevalence is not the same in different ethnic groups. Increased waist circumferences, elevated Tg level and reduced HDL level, known as important components of MetS, are associated with genetic factors and lifestyle characteristics (16, 24). The finding of an increased risk of MetS in PCOS women has raised further interest in identifying the predictors for MetS in these women (25). This study examined the prevalence and related factors of MetS in PCOS patients living in north of Iran.
In this study, the prevalence of MetS in PCOS women was 28.8%. This finding is higher than other studies in Iran (4, 18, 24), but lower than studies in United States (26, 27). Mehrabian et al. (4) showed that the prevalence of MetS were 24.9% among Iranian women diagnosed with different phenotypic subgroups of PCOS, based on the Rotterdam criteria. Moini et al. (24) who conducted a study in Tehran, Iran, reported that prevalence of MetS in PCOS women was 22.7%. In another large-scale population-based study in Tehran, the prevalence of MetS in PCOS subjects was 18.5% (18). This different prevalence may be related to population characteristics, diagnostic criteria and sample size.
This study showed that values of WC, SBP, DBP, BMI, obesity, and ovarian size were significantly greater in patients with MetS than patients without MetS. In a report by Mandrelle et al. (17), age and central obesity (waist-hip ratio/waist circumference) were considered as better predictors of MetS in PCOS women as compared to other parameters including BMI in this group of women.
This study showed that the values of biochemical parameters such as Tg, Chol, FBS, 2h BS, AST, and ALT were significantly greater in patients with MetS than without MetS. Also HDL and LH levels in women with MetS were significantly lower than women without MetS. Soares et al. (16) reported that the occurrence of low HDL was the most frequent individual component of MetS among Brazilian women with PCOS, followed by increased serum Tg.
For study limitation, our findings may be influenced by the criteria, by which PCOS and MetS were diagnosed. We used different equipment and different assessors during our study period that may affect our assessment reliability. Also this study was a cross sectional study with small sample size. So it is suggested to do more cohort or case control studies with greater sample size in future.
Conclusion
Based on our findings, prevalence of MetS in PCOS women was 28.8% that was higher than related values of other studies conducted on both PCOS women and general population in Iran. Among individual components of MetS, WC>88 cm, HDL>50, and Tg ≥150 were prevalent in more than 88% of PCOS women. PCOS women are high risk population for MetS. The special strategies is required for prevention of MetS and its related complications in PCOS women.
Acknowledgments
We appreciate the Vice Chancellor of Research of Guilan University of Medical Sciences for funding this project. The authors sincerely thank Mr. Davoud Pourmarzi for his help to edit manuscript. The authors state that they have no conflict of interest.
References
- 1.Azziz R, Woods KS, Reyna R, Key TJ, Knochenhauer ES, Yildiz BO. The prevalence and features of the polycystic ovary syndrome in an unselected population. J Clin Endocrinol Metab. 2004;89(6):2745–2749. doi: 10.1210/jc.2003-032046. [DOI] [PubMed] [Google Scholar]
- 2.Kauffman RP, Baker TE, Baker VM, DiMarino P, Castracane VD. Endocrine and metabolic differences among phenotypic expressions of polycystic ovary syndrome according to the 2003 Rotterdam consensus criteria. Am J Obstet Gynecol. 2008;198(6):670. e1-e7. doi: 10.1016/j.ajog.2008.01.037. [DOI] [PubMed] [Google Scholar]
- 3.Tehrani FR, Simbar M, Tohidi M, Hosseinpanah F, Azizi F. The prevalence of polycystic ovary syndrome in a community sample of Iranian population: Iranian PCOS prevalence study. Reprod Biol Endocrinol. 2011;25(9):39–39. doi: 10.1186/1477-7827-9-39. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Mehrabian F, Khani B, Kelishadi R, Kermani N. The prevalence of metabolic syndrome and insulin resistance according to the phenotypic subgroups of polycystic ovary syndrome in a representative sample of Iranian females. J Res Med Sci. 2011;16(6):763–769. [PMC free article] [PubMed] [Google Scholar]
- 5.Zhang HY, Guo CX, Zhu FF, Qu PP, Lin WJ, Xiong J. Clinical characteristics, metabolic features, and phenotype of Chinese women with polycystic ovary syndrome: a largescale case-control study. Arch Gynecol Obstet. 2013;287(3):525–531. doi: 10.1007/s00404-012-2568-z. [DOI] [PubMed] [Google Scholar]
- 6.Rotterdam ESHRE/ASRM-Sponsored PCOS consensus workshop group. Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome (PCOS) Hum Reprod. 2004;19(1):41–47. doi: 10.1093/humrep/deh098. [DOI] [PubMed] [Google Scholar]
- 7.Akbarzadeh M, Moradi F, Dabbaghmanesh MH, Jafari P, Parsanezhad ME. A survey of metabolic syndrome in firstdegree relatives (fathers) of patients with polycystic ovarian syndrome. JEMDSA. 2013;18(2):98–103. [Google Scholar]
- 8.Zhao Y, Fu L, Li R, Wang LN, Yang Y, Liu NN, et al. Metabolic profiles characterizing different phenotypes of polycystic ovary syndrome: plasma metabolomics analysis. BMC Med. 2012;10:153–153. doi: 10.1186/1741-7015-10-153. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Oliveira Rdo S, Redorat RG, Ziehe GH, Mansur VA, Conceição FL. Arterial hypertension and metabolic profile in patients with polycystic ovary syndrome. Rev Bras Ginecol Obstet. 2013;35(1):21–26. doi: 10.1590/s0100-72032013000100005. [DOI] [PubMed] [Google Scholar]
- 10.Hughes C, Elgasim M, Layfield R, Atiomo W. Genomic and post-genomic approaches to polycystic ovary syndrome- progress so far: mini review. Hum Reprod. 2006;21(11):2766–2775. doi: 10.1093/humrep/del222. [DOI] [PubMed] [Google Scholar]
- 11.Diamanti-Kandarakis E, Piperi C, Spina J, Argyrakopoulou G, Papanastasiou L, Bergiele A, et al. Polycystic ovary syndrome: the influence of environmental and genetic factors. Hormones (Athens) 2006;5(1):17–34. doi: 10.14310/horm.2002.11165. [DOI] [PubMed] [Google Scholar]
- 12.Diamanti-Kandarakis E. Polycystic ovarian syndrome: pathophysiology, molecular aspects and clinical implications. Expert Rev Mol Med. 2008;10:e3–e3. doi: 10.1017/S1462399408000598. [DOI] [PubMed] [Google Scholar]
- 13.Mukherjee S, Maitra A. Molecular & genetic factors contributing to insulin resistance in polycystic ovary syndrome. Indian J Med Res. 2010;131:743–760. [PubMed] [Google Scholar]
- 14.Azziz R. Polycystic ovary syndrome, insulin resistance, and molecular defects of insulin signaling. J Clin Endocrinol Metab. 2002;87(9):4085–4087. doi: 10.1210/jc.2002-021131. [DOI] [PubMed] [Google Scholar]
- 15.Ehrmann DA. Polycystic ovary syndrome. N Engl J Med. 2005;352(12):1223–1236. doi: 10.1056/NEJMra041536. [DOI] [PubMed] [Google Scholar]
- 16.Soares EM, Azevedo GD, Gadelha RG, Lemos TM, Maranhão TM. Prevalence of the metabolic syndrome and its components in Brazilian women with polycystic ovary syndrome. Fertil Steril. 2008;89(3):649–655. doi: 10.1016/j.fertnstert.2007.03.081. [DOI] [PubMed] [Google Scholar]
- 17.Mandrelle K, Kamath MS, Bondu DJ, Chandy A, Aleyamma T, George K. Prevalence of metabolic syndrome in women with polycystic ovary syndrome attending an infertility clinic in a tertiary care hospital in south India. J Hum Reprod Sci. 2012;5(1):26–31. doi: 10.4103/0974-1208.97791. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Hosseinpanah F, Barzin M, Tehrani FR, Azizi F. The lack of association between polycystic ovary syndrome and metabolic syndrome: Iranian PCOS prevalence study. Clin Endocrinol (Oxf) 2011;75(5):692–697. doi: 10.1111/j.1365-2265.2011.04113.x. [DOI] [PubMed] [Google Scholar]
- 19.Lankarani M, Valizadeh N, Heshmat R, Peimani M, Sohrabvand F. Evaluation of insulin resistance and metabolic syndrome in patients with polycystic ovary syndrome. Gynecol Endocrinol. 2009;25(8):504–507. doi: 10.1080/09513590902972083. [DOI] [PubMed] [Google Scholar]
- 20.Rahmanpour H, Jamal L, Mousavinasab SN, Esmailzadeh A, Azarkhish K. Association between polycystic ovarian syndrome, overweight, and metabolic syndrome in adolescents. J Pediatr Adolesc Gynecol. 2012;25(3):208–212. doi: 10.1016/j.jpag.2012.02.004. [DOI] [PubMed] [Google Scholar]
- 21.Diehr P, Newman AB, Jackson SA, Kuller L, Powe N. Weight-modification trials in older adults: what should the outcome measure be? Curr Control Trials Cardiovasc Med. 2002;3(1):1–1. doi: 10.1186/1468-6708-3-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Moran L, Teede H. Metabolic features of the reproductive phenotypes of polycystic ovary syndrome. Hum Reprod Update. 2009;15(4):477–488. doi: 10.1093/humupd/dmp008. [DOI] [PubMed] [Google Scholar]
- 23.Tsilchorozidou T, Overton C, Conway GS. The pathophysiology of polycystic ovary syndrome. Clin Endocrinol (Oxf) 2004;60(1):1–17. doi: 10.1046/j.1365-2265.2003.01842.x. [DOI] [PubMed] [Google Scholar]
- 24.Moini A, Javanmard F, Eslami B, Aletaha N. Prevalence of metabolic syndrome in polycystic ovarian syndrome women in a hospital of Tehran. Iran J Reprod Med. 2012;10(2):127–130. [PMC free article] [PubMed] [Google Scholar]
- 25.Cheung LP, Ma RC, Lam PM, Lok IH, Haines CJ, So WY, et al. Cardiovascular risks and metabolic syndrome in Hong Kong Chinese women with polycystic ovary syndrome. Hum Reprod. 2008;23(6):1431–1438. doi: 10.1093/humrep/den090. [DOI] [PubMed] [Google Scholar]
- 26.Glueck CJ, Papanna R, Wang P, Goldenberg N, Sieve- Smith L. Incidence and treatment of metabolic syndrome in newly referred women with confirmed polycystic ovarian syndrome. Metabolism. 2003;52(7):908–915. doi: 10.1016/s0026-0495(03)00104-5. [DOI] [PubMed] [Google Scholar]
- 27.Apridonize T, Essah PA, Iuorno MJ, Nestler JE. Prevalence and characteristics of the metabolic syndrome in women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2005;90(4):1929–1935. doi: 10.1210/jc.2004-1045. [DOI] [PubMed] [Google Scholar]