Abstract
Context
Polycystic ovarian syndrome (PCOS) is commonly associated with obesity, but the prevalence of the syndrome in obese patients is not well established.
Objective
The present study aims to investigate the prevalence of PCOS among overweight and obese premenopausal women and to evaluate the possible associations between the syndrome and metabolic disturbances in obese patients.
Methods
Medical records of all women referred to a single endocrine center because of obesity and/or metabolic disturbances during a three-year period were analyzed. A total of 262 overweight and obese patients of reproductive age were included in the retrospective study.
Results
The overall prevalence of PCOS using the Rotterdam criteria in the group of overweight and obese women was 26%. The degree of obesity did not influence the PCOS prevalence. Women with PCOS had higher blood glucose and insulin levels after glucose load in comparison to other obese patients despite the younger age.
Conclusions
PCOS is a common finding among obese women seeking endocrine help. The oral glucose tolerance test is an important tool for the early detection of carbohydrate disorders in women with the syndrome. Furthermore, screening for PCOS components might be justified in young obese women with pronounced insulin resistance or dysglycemia.
Keywords: PCOS, obesity, prediabetes, hypertension, diabetes
INTRODUCTION
Polycystic ovarian syndrome (PCOS) is one of the most common endocrine disorders that affects about one-tenth of premenopausal women, with a prevalence varying between 6.1% and 19.9% among different study groups according to the definition used (1,2). It is characterized by a complex and variable clinical presentation causing diagnostic and therapeutic difficulties (3-5). According to current guidelines, the main clinical features determining the syndrome include menstrual irregularities due to chronic anovulation, clinical and/or biochemical hyperandrogenism as well as polycystic ovaries visible by ultrasound (3-5). A well-known fact is that PCOS is commonly associated with overweight or obesity and both conditions might potentiate each other (4,6,7). Obesity might facilitate the development of PCOS in genetically susceptible women, while some of the PCOS features could contribute to further weight gain (6).
The prevalence of obesity in women with PCOS might vary significantly in different populations (8). Increased body mass index has been associated with a higher prevalence of metabolic syndrome and carbohydrate disturbances in patients with the syndrome (1,9,10). The role of obesity in women with PCOS is relatively well-studied, while on the opposite, the existing data on the prevalence of PCOS in obese women are scarce.
Therefore, the aim of the present study is to investigate the prevalence of PCOS among overweight and obese premenopausal women and to evaluate the role of the syndrome in the development of metabolic disturbances in overweight and obese patients.
MATERIALS AND METHOD
Participants
The current retrospective study included all female patients from Caucasian (Bulgarian) origin who were referred to a single tertiary Endocrine department in regards to overweight, obesity, and/or metabolic disturbances for the time period 2016-2018. Only overweight and obese patients with body mass index (BMI) ≥ 25 kg/m2 or waist circumference (WC) ≥ 80 cm were included in the study (a total of 636 women). The BMI and WC cut points were based on the World Health Organization and International Diabetes Federation recommendations for European patients, which are included also in the widely accepted harmonized criteria for metabolic syndrome (11-13). A total of 314 patients of reproductive age (18 to 45 years old) were enrolled. The main complaints of the patients included obesity, arterial hypertension, glucose intolerance, and/or dyslipidemia. Their anthropometric, biochemical, hormonal parameters and imaging studies were extracted from the hospital’s electronic database and anonymized.
Measurements and definitions
The obtained data of the selected women of reproductive age included the following anthropometric and clinical characteristics: height, weight, waist circumference, body mass index, presence of acne, hirsutism, alopecia, age of menarche, history of menstrual irregularities, infertility, pelvic ultrasound findings as well as concomitant medication. The most frequently used drug in the group was metformin, while only two patients were on treatment with oral contraceptives in regards to PCOS. Laboratory tests included blood count, fasting glucose, oral glucose tolerance test in non-diabetic patients, HbA1c in women with type 2 diabetes, lipid panel /total cholesterol, low-density cholesterol (LDL-ch), high-density cholesterol (HDL-ch), triglycerides (TG)/, uric acid, creatinine, alanine aminotransferase (ALAT), aspartate aminotransferase (ASAT), sodium, potassium, chloride and thyroid-stimulating hormone (TSH). The patients were referred to the clinic because of obesity and/or metabolic disturbances, and therefore, ovarian and/or adrenal steroid hormones were measured only in case of clinical indication according to the established clinical protocols. Thus, hormonal data were not available in all participants (free urine cortisol /n=198/, testosterone /n=131/, prolactin /n=140/, dehydroepiandrosterone-sulphate (DHEAS) /n=75/. The biochemical parameters were measured enzymatically by an automatic analyzer (Cobas Mira Plus; Hoffmann La Roche). Hormonal parameters were measured with commercially available RIA and IRMA kits. The intra- and inter-assay coefficients of variation for low and high levels, respectively, were 4.6%/6.2% and 4.4%/4.8% for testosterone (DIAsource ImmunoAssays S.A., Belgium, RIA), 5.9%/6.5% and 3.6%/6.5% for DHEAS (DIAsource ImmunoAssays S.A., Belgium, RIA), and 6.2%/8.7% and 7.7%/15.1% for free urine cortisol (DIAsource ImmunoAssays S.A., Belgium, RIA). Prolactin, TSH and insulin were measured with IRMA kits (Beckman-Coulter Inc., Czech). For the serum prolactin and TSH, the intra-assay coefficients of variation were ≤ 7.09% and ≤ 3.7%, and interassay coefficients of variation were ≤ 10.11% and ≤ 8.6%, respectively. For the serum insulin the coefficients of variation were below 3.99% for intra-assay and below 4.8% for inter-assay.
The presence of polycystic ovarian syndrome was established according to the ESHRE criteria in newly diagnosed patients or based on available medical records in women previously diagnosed with the syndrome (5). Women with overt hypothyroidism, hyperprolactinemia, Cushing’s syndrome, androgen-producing tumors, and congenital adrenal hyperplasia (n=33) were excluded from the study. Additionally, 19 patients were excluded because of premature ovarian failure history or increased FSH levels (14). Thus, a total of 262 patients were included in the final study group. Prediabetic conditions (impaired fasting glucose and/or impaired glucose tolerance) and type 2 diabetes (DM2) were diagnosed in accordance with the accepted international criteria (15).
Statistical analysis
All values are presented as mean±SD [median]. χ2 and Fisher’s exact tests were used for the analysis of dichotomous variables. Differences between the two groups were established with an independent sample t-test or Man-Whitney test according to the normality of the distribution. Additionally, Spearman correlation analysis was performed. Logistic regression analysis was used to estimate the risk factors associated with the PCOS diagnosis and main features after adjustment for age and BMI. Statistical significance was set at the “p” level of 0.05. Statistical analysis was performed with MedCalc Statistical Software version 19.2.6 (MedCalc Software Ltd, Ostend, Belgium).
RESULTS
The overall prevalence of PCOS using the Rotterdam criteria in the studied group of overweight or obese women was 26%. The highest prevalence of PCOS was found in the age group 18 – 25 years decreasing in the older age groups (Fig. 1). No significant differences in the PCOS prevalence were found amongst the patients with different degrees of obesity (Fig. 2). The main characteristics of the studied patients with and without PCOS are shown in Table 1.
Figure 1.
Prevalence of PCOS in overweight and obese patients of different age groups.
Figure 2.
Prevalence of PCOS in patients with different degrees of obesity.
Table 1.
Main characteristics of the studied overweight and obese women with (n=68) or without PCOS (n=194). SD-standard deviation
| Characteristics | Women with obesity without PCOS | Women with obesity and PCOS | p |
|---|---|---|---|
| Mean±SD (Median) | Mean±SD (Median) | ||
| Age (years)* | 33.38±7.37 (34.00) | 28.83±6.78 (28.00) | <0.001 |
| Waist circumference (cm) | 109.33±14.95 (107.00) | 109.67±15.44 (107.00) | 0.910 |
| BMI (kg/m2) | 36.92±7.35 (35.49) | 37.69±7.39 (35.75) | 0.410 |
| Systolic BP (mmHg) | 124.87±12.80 (120.00) | 122.83±17.13 (120.00) | 0.223 |
| Dyastolic BP (mmHg) | 80.42±9.32 (80.00) | 79.10±9.17 (80.00) | 0.692 |
| Cholesterol (mmol/L) | 5.08±0.99 (4.98) | 5.04±1.31 (4.99) | 0.920 |
| HDL-cholesterol (mmol/L) | 1.22±0.33 (1.16) | 1.19±0.33 (1.12) | 0.388 |
| Triglycerides = (mmol/L) | 1.66±1.68 (1.38) | 1.67±1.03 (1.46) | 0.679 |
| Glucose 0’ (mmol/L) | 5.82±1.45 (5.50) | 5.82±1.24 (5.50) | 0.856 |
| Glucose 60’ (mmol/L)* | 7.18±1.96 (6.70) | 8.78±3.21 (8.70) | 0.067 |
| Glucose 120’ (mmol/L)* | 5.93±1.59 (5.60) | 6.45±1.89 (6.30) | 0.041 |
| Insulin 0’ (µIU/mL) * | 18.43±10.14 (16.00) | 24.22±13.66 (21.75) | 0.004 |
| Insulin 60’ (µIU/mL) | 97.37±61.48 (86.00) | 144.27±108.58 (122.95) | 0.188 |
| Insulin 120’ (µIU/mL)* | 59.61±48.85 (48.50) | 101.36±63.85 (85.45) | 0.002 |
| HOMA-IR* | 4.88±3.73 (4.03) | 6.12±3.76 (5.15) | 0.011 |
| TSH (µIU/mL) | 2.70±1.55 (2.30) | 2.80±1.64 (2.40) | 0.797 |
| Prolactin (µIU/mL) | 320.63±175.90 (271.00) | 274.56±157.37 (240.00) | 0.168 |
| Testosterone (nmol/L)* | 2.14±1.22 (1.80) | 3.14±1.56 (3.00) | <0.001 |
| Urinary free cortisol (nmol/L) | 149.13±98.17 (123.70) | 148.70±130.85 (121.60) | 0.750 |
| DHEAS (µmol/L) | 8.47±4.84 (7.80) | 8.34±5.22 (7.40) | 0.911 |
The frequency of arterial hypertension did not differ significantly between the patients with and without PCOS (27.9% vs. 31.4%, p=0.590). The prevalence of impaired glucose tolerance (8.2% vs. 10.3%), impaired fasting glucose (19.1% vs. 18%) and DM2 (11.8% vs. 12.4%) was also similar in both groups (p>0.05 for all), despite the younger age of the PCOS patients. The PCOS patients showed significantly increased blood glucose and insulin levels after the glucose load in comparison to other obese women (Table 1). The percentage of patients treated with metformin did not differ between PCOS and non-PCOS obese groups (44.1% vs. 36.6%, p=0.274).
The testosterone levels in the investigated group were significantly associated with age (r= -0.252, p=0.004), HDL-cholesterol (r= -0.192, p=0.029), triglycerides (r= +0.206, p=0.029), as well as with fasting insulin (r= +0.200, p=0.031), DHEAS (r= +0.289, p=0.015), and TSH (r= +0.186, p=0.033), but not with BMI, waist circumference, blood pressure, glucose levels during OGTT or other metabolic parameters (p>0.05 for all). The DHEAS levels were inversely related to age (r= -0.297, p=0.010), but not to the investigated anthropometric, metabolic and hormonal indices (p>0.05 for all).
Logistic regression analysis showed that the main factors associated with PCOS in obese women were serum testosterone levels, as well as insulin concentrations, and they were more important predictors than HOMA-IR or glucose levels (Table 2).
Table 2.
Logistic regression analysis including metabolic and hormonal factors for the prediction of PCOS (2A), hirsutism (2B), and menstrual irregularities (2C) among obese women after adjustment for age and BMI
| 2A | |||
|---|---|---|---|
| Factor | Adjusted OR | 95%CI | p |
| Insulin 0’ (µIU/mL) | 1.038 | 1.009-1.068 | 0.010 |
| Insulin 60’ (µIU/mL) | 1.006 | 0.998-1.013 | NS |
| Insulin 120’ (µIU/mL) | 1.010 | 1.001-1.020 | 0.035 |
| Glucose 0’ (mmol/L) | 1.048 | 0.850-1.294 | NS |
| Glucose 60’ (mmol/L) | 1.266 | 0.961-1.668 | NS |
| Glucose 120’ (mmol/L) | 1.195 | 0.988-1.444 | NS |
| HOMA-IR | 1.069 | 0.983-1.162 | NS |
| Testosterone (nmol/L) | 1.627 | 1.218-2.174 | 0.001 |
| DHEAS (µmol/L) | 0.988 | 0.894-1.091 | NS |
| Urinary free cortisol (nmol/24h) | 1.000 | 0.996-1.003 | NS |
| 2B | |||
| Factor | Adjusted OR | 95%CI | p |
| Insulin 0’ (µIU/mL) | 1.018 | 0.990-1.048 | NS |
| Insulin 60’ (µIU/mL) | 1.001 | 0.994-1.008 | NS |
| Insulin 120’ (µIU/mL) | 0.997 | 0.987-1.007 | NS |
| Glucose 0’ (mmol/L) | 0.958 | 0.753-1.217 | NS |
| Glucose 60’ (mmol/L) | 1.208 | 0.937-1.556 | NS |
| Glucose 120’ (mmol/L) | 0.938 | 0.757-1.162 | NS |
| HOMA-IR | 1.049 | 0.964-1.141 | NS |
| Testosterone (nmol/L) | 1.372 | 1.054-1.785 | 0.019 |
| DHEAS (µmol/L) | 1.094 | 0.984-1.216 | NS |
| Urinary free cortisol (nmol/24h) | 0.998 | 0.995-1.002 | NS |
| 2C | |||
| Factor | Adjusted OR | 95%CI | p |
| Insulin 0’ (µIU/mL) | 1.009 | 0.984-1.035 | NS |
| Insulin 60’ (µIU/mL) | 1.000 | 0.994-1.007 | NS |
| Insulin 120’ (µIU/mL) | 1.010 | 1.001-1.019 | 0.034 |
| Glucose 0’ (mmol/L) | 0.974 | 0.812-1.168 | NS |
| Glucose 60’ (mmol/L) | 1.265 | 0.981-1.631 | NS |
| Glucose 120’ (mmol/L) | 1.213 | 1.015-1.450 | 0.033 |
| HOMA-IR | 0.991 | 0.917-1.070 | NS |
| Testosterone (nmol/L) | 1.179 | 0.904-1.538 | NS |
| DHEAS (µmol/L) | 0.973 | 0.880-1.077 | NS |
| Urinary free cortisol (nmol/24h) | 1.001 | 0.998-1.004 | NS |
Testosterone but not DHEAS or insulin was significantly associated with the presence of hirsutism in the investigated group of obese women. The insulin and glucose levels on the second-hour post glucose load were significant predictors of menstrual irregularities in obese women. The free urine cortisol levels were not associated with the presence of PCOS or its main features (Table 2).
DISCUSSION
Our results showed that the prevalence of PCOS in overweight and obese women was 26.0 % irrespective of obesity degree. The percentage of hypertension, carbohydrate and lipid abnormalities did not differ significantly between overweight and obese patients with and without PCOS. However, women with PCOS showed increased insulin and glucose levels post glucose load compared to other overweight and obese individuals. These data supported the results of two previous European studies of Spanish and Scandinavian obese women amongst whom the prevalence of PCOS was found to be 28.3% and 25.6% accordingly (16,17). However, other large studies have reported significantly different prevalence of PCOS in obese women of other ethnic groups – about 12% in American women with mild or severe obesity and over 60 % in obese Asians (18,19). Discordances in the published results might be associated with varying enrollment criteria, different ethnic backgrounds of the participants, as well as PCOS definitions used. For instance, the application of the broader PCOS criteria recommended by the Rotterdam consensus increases the prevalence of PCOS two- to three times in comparison to that obtained by the stricter criteria of the National Institute of Health (NIH) (1,20). Furthermore, the preselection of patients cannot be excluded because obese women with menstrual disturbances and/or infertility are more likely to seek endocrine advice in comparison to their equally obese peers without reproductive problems (19).
Despite the increased frequency of PCOS in our group of obese patients, the grade of obesity per se did not affect the prevalence of the syndrome, as in other studies (16,18). Consequently, obesity is an important risk factor that could worsen the clinical manifestation and metabolic health of women with PCOS, but it is not the main etiological determinant of the syndrome (16). Obesity has been associated with increased aromatase activity and insulin resistance (21,22). Thus, it might influence the estrogen to androgen ratio as well as gonadotropin secretion of the patients (23,24). Presumably, these pathophysiological mechanisms exert more pronounced negative effects on individuals with a genetic predisposition to PCOS.
An important but still unresolved question is whether the prevalence of PCOS differs between metabolically healthy obese individuals and obese patients with metabolic abnormalities. Two Asian studies found a similar prevalence of PCOS in both obese groups though PCOS was significantly more frequent in obese women compared to their lean counterparts (19,25). The prevalence of metabolic syndrome was also similar in obese women with or without PCOS (17). No differences in the blood pressure values were found between patients with PCOS and obesity in comparison to obese women without menstrual irregularities or hyperandrogenism, while the data regarding lipid abnormalities were inconclusive (16,17). Accordingly, our data did not show any significant differences in the blood pressure and lipid levels between obese women with or without PCOS. Moreover, the prevalence of type 2 diabetes mellitus did not differ between both groups. Recently, a meta-analysis of Anagnostis et al. found a three-fold increase of DM2 in patients with PCOS compared to healthy women, and the risk was associated mainly with the presence of overweight and obesity (26). Thus, obesity might be the main factor contributing to the increased cardiovascular morbidity in PCOS women.
On the opposite, our data revealed significant differences in the blood glucose and insulin levels between patients with and without PCOS regardless of the younger age of the women with the syndrome. Both groups had similar fasting glucose levels while the blood glucose rise after glucose load was much more pronounced in the PCOS patients. Patients with PCOS showed also increased fasting and almost double post-glucose load insulin levels as well as profound insulin resistance. Accordingly, other European studies did not find differences in fasting glucose levels between obese patients with and without PCOS, while contradictory results have been reported for fasting insulin levels and HOMA-IR (16,17). A screening algorithm for carbohydrate disturbances in PCOS women has been suggested based on a study conducted in the Netherlands. The authors recommend initial measurement of the fasting blood glucose levels and a subsequent oral glucose tolerance test only in patients with impaired fasting glucose (27). On the opposite, other studies conclude that the single measurement of fasting blood glucose levels could lead to the omission of 50% to 80% of cases with dysglycemia in women with PCOS (28, 29). Moreover, a recent large multicenter study has shown that measuring fasting glucose only would preclude the diagnosis of impaired fasting glucose and type 2 diabetes mellitus in one-third of patients (30). Our results support international position statements recommending OGTT in all overweight and obese patients with PCOS (5, 30-32). Moreover, the increased insulin levels during OGTT were among the main factors associated with the presence of PCOS in our group being more predictive than HOMA-IR or glucose concentrations. Thus, the investigation of insulin levels at fasting state and post glucose load in obese patients might help to identify patients prone to PCOS development.
Additionally, elevated glucose and insulin levels two hours post glucose load were associated with increased prevalence of menstrual irregularities in obese women irrespective of the presence of PCOS. Therefore, the detection of abnormal glucose and insulin values post glucose load in obese women should drive a targeted search for menstrual disorders, since such complaints are not always intentionally shared by the patients. Similarly, hyperandrogenism does not always present clinically with hirsutism, acne, or alopecia in the affected women, thus, measurement of testosterone levels (33) might be of clinical importance along with detailed gynecological history.
Our study found significant differences in the prevalence of PCOS amongst different age groups with a gradual decrease over time. Phenotypic changes have been commonly observed in ageing women with PCOS. Increased testosterone levels and enlarged ovarian volume usually decrease in late reproductive years in parallel with the ovarian follicle reserve depletion. On the contrary, metabolic disturbances in the same patients tend to worsen with age (34). Therefore, the proper diagnosis of the syndrome might be challenging in later reproductive years. Further research is required to establish the natural evolution of PCOS considering clinical presentation, metabolic risk, and possible complications in the context of ageing.
The main limitation of the current study is the use of the available medical records only, as in other retrospective studies. The women were referred to the clinic because of obesity and metabolic disturbances and therefore, hormonal and/or gynecological investigations were performed only in the patients with irregular menstruation or symptoms of hyperandrogenism. Thus, the prevalence of women with ovulatory PCOS (increased testosterone and polycystic ovaries) might be underestimated. Leptin, adiponectin, and other hormones of the adipose tissue have not been investigated, which is an additional limitation of the study. Nevertheless, our study is one of the very few available in the literature focusing on the PCOS prevalence in overweight and obese women.
In conclusion, our study has shown that at least a quarter of the patients with obesity and metabolic disturbances seeking endocrine help suffer also from polycystic ovarian syndrome. Obesity degree does not affect the prevalence of the syndrome. Changes in the glucose and insulin levels after glucose load are much more pronounced in obese patients with PCOS and menstrual disturbances in comparison to other obese women. Thus, the oral glucose tolerance test is an important tool for the early detection of carbohydrate disorders in women with the syndrome. Furthermore, screening for PCOS components might be justified in young obese women with pronounced insulin resistance, severe postprandial hyperinsulinemia, or impaired glucose tolerance.
Acknowledgements
This work is supported by the Bulgarian Ministry of Education and Science under the National Program for Research “Young Scientists and Post-doctoral Students”.
Conflict of interest
The authors declare that they have no conflict of interest.
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