Evaluation of muscle strength assessment in adolescent polycystic ovary syndrome: a case control study

Abstract

Background

Polycystic ovary syndrome (PCOS) is a common endocrine disorder in adolescents characterized by irregular menstrual cycles, hyperandrogenism and metabolic disturbances. While much of the research on PCOS has focused on the hormonal and metabolic effects, the impact of PCOS on physical health, particularly muscle strength, has not been adequately studied. Previous studies suggest that hyperandrogenism may play a role in muscle strength, but the relationship between muscle function and PCOS in adolescents has not been well studied. Understanding this relationship is critical to improving health outcomes and managing the long-term effects of PCOS in adolescents. The aim of this study was to investigate muscle strength in adolescent women with PCOS and its possible association with dietary habits, hormonal markers and metabolic factors such as hyperandrogenism.

Methods

The study was conducted on 45 patients with polycystic ovary syndrome (PCOS) and 44 healthy adolescents who presented to the adolescent outpatient clinic of our hospital between September 2022 and January 2023. PCOS in adolescents was diagnosed according to the Rotterdam Criteria 2018. Free testosterone, follicle-stimulating hormone (FSH), insulin, estradiol, sex hormone-binding globulin (SHBG), anti-Müllerian hormone (AMH) and 25-OH vitamin D were measured in serum. The free androgen index (FAI) and the homeostatic model of insulin resistance (HOMA-IR) were calculated. The groups were compared using data from the SCOFF scale, the Food Craving Questionnaire-Trait (FCQ-T), the Night Questionnaire, the Eating Questionnaire (NEQ) and the Three-Factor Eating Questionnaire (TFEQ-R18). Hand grip strength was measured using the Jamar hand dynamometer for the dominant and non-dominant hand.

Results

The average age in the study and control groups was 17 years. There was no difference between the two groups in terms of age, body mass index (BMI) and lean BMI (p = 0.164, p = 0.074, p = 0.398). Muscle strength of the dominant hand was statistically higher in the PCOS group (p = 0.037). There was no statistically significant difference between the groups in SCOFF, FCQ-T, NEQ and TFEQ-R18 scores (p > 0.05). In the regression analysis, free androgen index (FAI), anti-mullerian hormone (AMH) and 25-OH vitamin D were statistically effective in explaining the level of muscle strength (p < 0.001; <0.001; 0.006). Every 1 mg/L increase in AMH level leads to a 1.42–2.18 kg increase in muscle strength (p < 0.001), and every 1 unit increase in FAI leads to a 0.54–0.92 kg increase in muscle strength (p < 0.001).

Conclusion

Our study shows that muscle strength of the dominant hand is higher in adolescent PCOS patients, emphasizing the importance of hyperandrogenism in the pathophysiology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12905-026-04275-8.

Background

Polycystic ovary syndrome (PCOS) is the most common cause of infertility in women and is responsible for most cases of hyperandrogenism and ovulatory disorders [1]. Although the incidence varies depending on the diagnostic criteria used, PCOS affects approximately 8–13% of women of reproductive age and 6–13% of adolescent women [2]. There is a consensus that PCOS should be diagnosed in the adolescent group when clinical and/or biochemical findings such as unexplained persistent ovarian dysfunction (by chronologic and gynecologic age-appropriate standards) and hyperandrogenism are present [3].

Although the exact etiology of PCOS is not known, it is thought that increasing obesity plays a role [4, 5]. In fact, about 90% of women with PCOS are overweight or obese [6, 7]. About half of the cases have abnormal insulin resistance, obesity or high levels of luteinizing hormone. A clinically significant improvement in hyperandrogenism and menstrual irregularities is observed with moderate weight loss (e.g. 5%) [8]. It is known that women with PCOS have a high percentage of body fat and often suffer from android obesity [9]. It is observed in both adolescent and adult women with a waist circumference of 88 cm or more [9]. Androgens are known to increase muscle mass and visceral fat in both men and women [10]. Studies have shown that mechanical muscle function altered and increased muscle strength is associated with hyperadrogenism [11, 12]. Approximately 90% of people with PCOS have abnormal androgenic ovarian function [9]. Thus, the common denominator of PCOS appears to be ovarian hyperandrogenism; insulin-resistant hyperinsulinism is a more common factor that exacerbates the pathophysiology. Given the potential of musculoskeletal abnormalities to affect metabolism and reproductive health, the theoretical risk should be considered in treatment and prevention strategies.

In this study, we investigated the relationship between PCOS, which is closely associated with metabolic changes, and muscle strength, particularly in adolescents. Our second aim was to investigate the effects of dietary habits on muscle strength.

Methods

The study was approved by the Ethics Committee for Clinical Research (No.: 2022/138). It was conducted with a total of 89 patients who presented to the adolescent outpatient clinic between September 2022 and January 2023. Forty-five adolescent PCOS patients who presented to the adolescent outpatient clinic were included in the study. The control group consisted of 44 healthy adolescents without PCOS. Our study was conducted in accordance with the latest principles of the Declaration of Helsinki.

It was planned as an analytical cross-sectional study. According to the 2018 ESHRE/ASRM guidelines, patients who fulfilled both criteria listed below were diagnosed with PCOS and included in the study group [3]; oligo- and/or anovulation*, clinical and/or biochemical hyperandrogenism.

The control group was selected from adolescent female patients who presented to the outpatient clinic for routine examination.

Inclusion criteria:

• ☐ Diagnosis of PCOS according to the 2018 guidelines [3].

• ☐ At least 1 year after menarche.

• ☐ Be under 18 years of age.

• ☐ No oral contraceptive treatment.

Exclusion criteria for the study:

• ☐ Patients over 18 years old.

• ☐ Patients with endocrine disorders such as hyperprolactinemia, Cushing’s syndrome, congenital adrenal hyperplasia, thyroid disease.

• ☐ Neuromuscular, hepatic, pancreatic or gastrointestinal disorders.

• ☐ These are individuals taking hormonal drugs such as antiandrogens, antidiabetics, glucocorticoids, insulin sensitizers and lipid regulators.

The patient and control groups were interviewed in person. Age, height (cm), weight (kg), body mass index (BMI) (kg/m2), medical history, medication use, smoking, menarche, menstrual cycle, gynecologic ultrasound examinations and clinical hyperandrogenism findings were evaluated. The modified Ferriman-Gallwey score (mFGS) was evaluated [13]. Venous blood samples were routinely taken from the antecubital region of the patients after 10 h of fasting. Moderately severe acne, moderate hirsutism and mFGS ≥ 8 were considered clinical signs of hyperandrogenism. Total testosterone, free testosterone and free androgen index (FAI) were used to determine biochemical hyperandrogenism. According to the acne scoring system used in the adolescent age group, comedonal or inflammatory scores between 1 and 10 are categorized as mild, between 11 and 15 as moderate, and over 25 as severe [14].

The formula “Homeostasis model assessment-estimated insulin resistance (HOMA-IR)” (fasting insulin UIU/ml x fasting blood glucose (FBG) (mg/dl) / 405) was used to calculate insulin resistance. Free androgen index (FAI) was calculated as total testosterone x 100/SHBG. All biochemical and hormonal analyzes were performed in the biochemistry and hormone laboratory of our hospital using BECKMAN AU680, USA modulators.

Evaluation of eating habits

Patients were administered the SCOFF scale and validated versions of the Food Craving Questionnaire-Trait (FCQ-T), the Night Eating Questionnaire (NEQ) and the Three-Factor Eating Questionnaire (TFEQ-R18) [15–19].

The SCOFF scale is the most commonly used screening instrument for the assessment of eating disorders in adults. It is a five-question questionnaire designed to screen for a suspected eating disorder, but not to make a diagnosis. The questions can be asked verbally or in writing. Patients with a score of 2 or more should be investigated further and referred to a dietitian.

A 39-item self-report questionnaire, the FCQ-T, was used. In this test, participants rated the frequency of each statement on a 6-point scale: 1 (never) to 6 (always). The TFEQ-R18 is used to measure cognitive restraint and uncontrolled and emotional eating in participants. It consists of 18 statements on a four-point Likert scale (1–4); higher scores indicate disordered behavior.

To assess nocturnal eating syndrome, the NEQ questionnaire contains questions on morning eating behavior, mood swings, sleep disturbances and nocturnal hyperphagia. Item 7 “Check here if your mood does not change during the day” was scored zero if it was checked; the other items were scored on a 5-point Likert scale (0–4). Items 1, 4 and 14 were reverse scored, with higher scores indicating more pronounced symptoms. Item 13 was used to assess other illnesses and was not included in the calculation of the total score.

The SCOFF scale consists of the following 5 questions.

1. Do you force yourself to vomit because you feel uncomfortably full?

2. Are you afraid of losing control over how much you eat?

3. Have you recently lost more than six kilograms in three months?

4. Did you think you were fat when others said you were very thin?

5. Do you feel that food dominates your life?

Anthropometric measurements and assessment of muscle strength

Height and weight were measured and BMI was calculated as body weight in kg divided by the square of height in meters. Lean body mass index (LBMI) was calculated using the formula (0.252 × body weight) + (0.473 × height) − 48.3. The height of the patients was measured standing on a Seca scale. Waist circumference (cm) was measured with a non-stretchable tape measure on the skin. Waist circumference was determined by measuring the distance between the costal arch and the anterior superior spinous process of the iliac spines. The neck circumference was measured in the anatomical position directly under the “thyroid cartilage” at the narrowest point. Hand grip strength was measured using a Jamar hand dynamometer (Takei Scientific Instruments Co., Japan), which is routinely used to measure muscle strength in the Physical Therapy and Rehabilitation Department of our hospital.

Statistical analysis

When calculating the sample size required for the study, the sample size was calculated using the G*Power 3.1.9.2 program in accordance with the information in the literature so that the power of the study was 80%. Accordingly, the sample size was 72 (n = 36, 2 groups), the margin of error 0.05 (alpha), the significance 80% (power) and the effect size 0.6 [11].

The power of a study (80%) means that the study has an 80% chance of correctly rejecting the null hypothesis (i.e. detecting an actual effect if it exists) and a 20% chance of making a type II error (not detecting an effect that actually exists). A power of 80% is considered acceptable in many studies, especially in preliminary research. An effect size of 0.6 indicates a medium to large effect according to Cohen’s criteria (0.2 = small, 0.5 = medium, 0.8 = large). If a medium or larger effect is expected, the calculated sample size (72) is considered sufficient to detect significant differences. By increasing the sample size above 72, the total number in our study was 89, which should help address concerns about statistical power and lead to more reliable and generalizable results.

Microsoft Excel and IBM SPSS ver.25 (IBM Corp. USA), a statistical package, were used to enter, clean, review, organize, and analyze all data. For data analysis, the conformity of all variables to the normal distribution was assessed using the Shapiro-Wilks test statistic. For normally distributed variables, the mean ± standard deviation (mean ± sd) was used as the descriptive statistic and the T-test for independent samples was used to examine the difference between the PCOS and control groups. For variables that were not normally distributed, the median (interquartile range) was used as the descriptive statistic and the Mann-Whitney U test was used for comparisons between groups. The relationships between the variables were analyzed using Pearson correlation coefficients for parametric variables and Spearman correlation coefficients for non-parametric variables. The chi-square test was used for the relationships between the qualitative data. As a further analysis, linear regression analysis was performed to examine the variables affecting muscle strength in the PCOS group. Receiver operating characteristic (ROC) analysis was applied to determine muscle strength in PCOS. In all analyzes, α = 0.05 was accepted as the error level.

Results

The study group consisted of 45 adolescent female patients diagnosed with PCOS and the control group consisted of 44 healthy female patients who presented to the adolescent outpatient clinic of our hospital for routine check-up. The comparative results of the demographic and anthropometric measurements of the groups are shown in Table 1. There was no statistically significant difference between the two groups in terms of age, BMI and waist/hip ratio (p > 0.05). The median age of the adolescent PCOS group was 17 (1) years and the median age of the control group was 17 (2) years (p = 0.164). The mean ± standard deviation (SD) of lean body mass index was 44.85 ± 5.53 kg/m2 in the adolescent PCOS group (n = 45) and 43.41 ± 4.72 kg/m2 in the control group (n = 44) ( p = 0.398). The median waist circumference/hip circumference was 0.76 in the adolescent PCOS group and 0.74 in the control group (p = 0.168). Neck circumference was statistically significantly higher in the adolescent PCOS group than in the control group (32 (3)cm vs. 31 (3)cm (p = 0.025). There was no statistically significant difference between the groups in terms of age at menarche and pubarche (p > 0.05). The median modified Ferriman-Gallwey (mFG) score was 5 in the PCOS group and 3 in the control group and a statistically significant difference was found (p < 0.001).

Table 1.

Comparison of adolescent PCOS and control groups in terms of demographic, anthropometric measurements and hormonal values

Parameters	Control(n = 44)	PCOS (n = 45)	T, z	p
Age (years)
(Median (IQR))	17(2)	17(1)	1.392	0.164
Age at menarche (years)
(Median (IQR))	12(1)	13 (1)	1.387	0.166
Cycle duration (day)
(Median (IQR))	30 (2)	60(55)	6.961	< 0.001
Dysmenorrhea, n(%)
No	19 (%43.1)	22 (%48.5)	0.292	0.589
Yes	25 (%56.8)	23 (%51.1)
Menstrual irregularity, n (%)
No	32 (%72.7)	8 (%17.7)	27.147	< 0.001
Yes	12 (%27.2)	37 (%82.2)
Hirsutism. n (%)
No	44 (%100.0)	17 (%37.7)	39.945	< 0.001
Yes	0 (%0.0)	28 (%62.2)
Acne, n (%)
No	35 (%79.5)	20 (%44.4)	26.313	< 0.001
Mild	9(%20.4)	9 (%2)
Modarate	0 (%0)	8 (%17.7)
Severe	0 (%0)	8 (%17.7)
Presence of PCOM on ultrasonography, n (%)
No	42(%95.4)	13(%28.2)	41.756	< 0.001
Yes	2(%4.5)	32(%71.1)
Body mass index (kg/m2)
(Median (IQR))	21.10 (5.40)	23.39 (7.34)	1.784	0.074
Ferriman-Gallwey Score
(Median (IQR))	3 (2)	15 (9)	8.132	< 0.001
Waist circumference (cm)
(Median (IQR))	71 (9)	76.00 (14)	2.526	0.012
Hip Circumference (cm)
(Mean ± SD)	95.28 ± 7.22	98.37 ± 10.56	1.820*	0.072
Waist / Hip Circumference
(Median (IQR))	0.74 (0.07)	0.76 (0.11)	1.379	0.168
Neck circumference (cm)
(Median (IQR))	31 (3)	32 (3)	2.235	0.025
Lean body mass index (kg)
(Mean ± SD)	43.41 ± 4.72	44.85 ± 5.53	0.849*	0.398
FSH (IU/L)	6.33 (2.28)	5.30 (2.41)	2.396	0.017
LH (IU/L)	8.28 (5.72)	8.24 (8.92)	0.636	0.525
SHBG (nmol/L)	35.80 (19.90)	25.10 (28.00)	3.024	0.002
DHEA-S(µg/dl)	204 (153)	185 (167)	0.501	0.617
Free Testosterone (pg/ml)	2.50 (1.76)	2.29 (1.57)	0.111	0.912
FAİ	2.62 (2.09)	4.49 (6.07)	2.864	0.004
AMH (mg/L)	2.51 (2.46)	5.37 (5.07)	4.620	< 0.001
Fasting Insulin Level (mU/L)	11.60 (8.75)	13.6 (16.12)	0.915	0.360
Fasting Blood Glucose (mg/dl)	83 (10)	82 (13)	0.834	0.404
HOMA-IR	2.25 (1.76)	2.62 (3.32)	1.145	0.252
25-OH Vitamin D (nmol/L)	10 (4)	11 (11)	0.462	0.665

*t value IQR Inter quantile range, SD Standard deviation, kg Kilogram, m Meter, cm Centimeter, PCOS Polycystic ovary syndrome, PCOM Polycystic ovary morphology, FSH Follicle-stimulating hormone, LH Luteinizing hormone, SHBG Serum sex hormone binding globulin, DHEA-SO4 Dehydroepiandrosterone sulfate, FAI Free Androgen Index, AMH Anti-müllerian hormone, HOMA-IR Homeostatic Model Assessment of Insulin Resistance, 25-OH Vitamin D 25-hydroxy vitamin D

However, hirsutism was significantly more common in the adolescent PCOS group than in the control group (0% vs. 62.2%; p < 0.001). The presence of ultrasonographic polycystic ovarian morphology was also significantly more common in the PCOS group (4.5% vs. 71.1%; p < 0.001). Acne was not observed in 44.4% (n = 20) of the adolescent PCOS group. In this group, 2% (n = 9) had mild acne, 17.7% (n = 8) had moderate acne and 17.7% (n = 8) had severe acne. Acne findings were significantly higher in the adolescent PCOS group (p < 0.001). Table 1 compares the hormonal and metabolic characteristics of the adolescent PCOS and control groups. There were no statistically significant differences in luteinizing hormone (LH), luteinizing hormone/follicle-stimulating hormone (LH/FSH), estradiol, prolactin, thyroid-stimulating hormone (TSH) and free thyroxine (T4), dehydroepiandrosterone sulfate (DHEAS), total testosterone and free testosterone. The mean FSH level was 5.30 IU/L (2.41) in the PCOS group and 6.33 (2.28) IU/L (p = 0.017) in the control group, which was statistically significantly higher. The median sex hormone-binding globulin (SHBG) was 25.10 (28.00) nmol/L in the adolescent PCOS group and 35.80 (19.90) nmol/L in the control group, with SHBG being statistically significantly lower in the PCOS group (p = 0.002). The mean FAI was 4.49 (6.07) in the adolescent PCOS group and 2.62 (2.09) in the control group, and the increase in FAI in the PCOS group was statistically significant (p = 0.004). The mean anti-mullerian hormone (AMH) level was 5.37 (5.07) mg/L in the adolescent PCOS group and 2.51 (2.46) mg/L in the control group, and the increase in AMH in the PCOS group was statistically significant (p < 0.001).

The isometric dynamometer analysis of the adolescent PCOS and control groups is shown in Table 2. It was found that the right hand was dominant in all patients in both groups (n = 89, 100%). The mean grip strength of the dominant hand was 24.51 ± 4.63 kg in the adolescent PCOS group and 22.13 ± 5.17 kg in the control group (p = 0.037). There was no statistical difference between the non-dominant hands (p = 0.152). The mean muscle strength of both hands was 19.94 ± 3.72 kg in the adolescent PCOS group and 18.21 ± 4.09 kg in the control group (p = 0.058). According to the ROC analysis used for the mean value of muscle strength of the right hand, the area under the curve was calculated as 0.628 ± 0.06 kg. For the most appropriate cut-off value of 22.3 kg, sensitivity and selectivity were 0.69 and 0.54, respectively. In the ROC analysis, the area under the curve for the mean muscle strength of the left hand was 0.592 ± 0.061. For the most appropriate cut-off value of 14.08, sensitivity and selectivity were calculated as 0.69 and 0.54, respectively. When evaluating the mean muscle strength of both hands, the area under the curve was 0.624 ± 0.06 kg. The most appropriate cut-off value was 10.083 and the sensitivity and selectivity for this value were 0.98 and 0.0, respectively (Fig. 1).

Table 2.

Isometric dynamometer analysis and eating habits evaluation of adolescent PCOS and control group

Parameters	Control (n = 44)	PCOS (n = 45)	t	p
Right Hand Muscle strength (kg)
(Mean ± SD)	22.13 ± 5.17	24.51 ± 4.63	2.123	0.037
Left Hand Muscle strength (kg)
(Mean ± SD)	14.19 ± 3.31	15.38 ± 3.07	1.446	0.152
Average of the right and left hand Muscle strength (kg)
(Mean ± SD)	18.21 ± 4.09	19.94 ± 3.72	1.924	0.058
SCOFF Score*	1 (2)	2 (1)	0.985	0.325
Food Cravings Questionnaire–Trait Score*	95(55)	105 (56.00)	0.320	0.749
Night Eating Survey Score†	17.19 ± 5.88	16.60 ± 5.70	0.426**	0.671
Three-Factor Nutrition Survey Score†	39.12 ± 7.33	39.58 ± 7.56	0.219*	0.827

* Median (interquartile range) † Mean ± standard deviation **t value

Fig. 1.

ROC analysis of muscle strength in the adolescent PCOS group

The eating habits of the adolescent PCOS and control groups were compared in Table 2. There was no statistically significant difference between the groups in terms of SCOFF score, food cravings questionnaire, night eating questionnaire and three-factor diet questionnaire (p = 0.325; 0.749; 0.671; 0.827). The relationship between the SCOFF score and muscle strength in adolescent PCOS patients is shown in Table 3. The adolescent PCOS patients were categorized into 2 groups based on the SCOFF score, the screening score for eating disorders. If the SCOFF score is equal to or above 2, an eating disorder is suspected. In the group of adolescent PCOS patients, muscle strength in the dominant hand was significantly lower in those who were not suspected of having an eating disorder when categorized by SCOFF score (22.6 ± 4.2 kg vs. 25.8 ± 4.4 kg, p = 0.018).

Table 3.

Relationship between SCOFF score and muscle strength in patients with adolescent PCOS

Hand Dynamometer (kg)	SCOFF < 2 (n = 21)	SCOFF ≥ 2 (n = 24)	t.z	p
Right Hand	22.6 ± 4.2	25.8 ± 4.4	2.459	0.018
Left Hand	14.4 ± 2.5	16.0 ± 3.2	1.763	0.085
Average	18.5 ± 3.2	20.9 ± 3.7	2.261	0.029

Every 1 mg/L increase in AMH resulted in a 1.42–2.18 kg increase in muscle strength (p < 0.001). Every 1 unit increase in FAI leads to an increase in muscle strength of 0.54–0.92 kg; 25-OH vitamin D leads to an increase in muscle strength of 0.35–0.72 kg (p < 0.001 and p = 0.006, respectively) (Table 4).

Table 4.

Regression analysis of right hand muscle strength mean value and hormonal values ​​in the PCOS group

Parameters	Coefficient	Standart error	t	p
FAİ	0.731	0.191	3.826	< 0.001
AMH (mg/L)	1.805	0.385	4.689	< 0.001
25-OH Vitamin D (nmol/L)	0.538	0.185	2.914	0.006
F:72.123 p < 0.001 AdjR2:0.86

FAI Free Androgen Index, AMH Anti-müllerian hormone, AdjR2 Adjusted

Discussion

PCOS is a multisystem disorder characterized by hyperandrogenism and hyperinsulinemia. These two hormonal conditions have a complex relationship. Skeletal muscle plays an important role in the metabolic system. There is evidence that local androgen exposure leads to modulation of metabolism in skeletal muscle, one of the target organs of androgens [19]. Recent studies have shown that cardiometabolic dysfunction has significant effects on skeletal muscle mass in PCOS patients [20, 21]. In this study, it was shown that metabolic changes led to changes in muscle strength in the PCOS group. On the other hand, it was observed that muscle strength was much lower in patients without suspected eating disorder than in patients with suspected eating disorder.

Muscle strength is influenced by a person’s exercise habits, lifestyle, and stress factors. Handgrip strength is a really useful and easily accessible measure of muscle function, particularly for assessing forearm musculature and hand strength. As there is a known correlation between handgrip strength and general physical fitness, particularly in adults, it is often used in clinical settings to provide a snapshot of a person’s general health and physical performance. However, in certain conditions such as polycystic ovary syndrome (PCOS), certain hormonal or metabolic factors affect grip strength. Increased androgen levels in women with PCOS affect muscle mass and strength. If this leads to increased muscle strength in the hand muscles, it may also indicate other muscle-related changes elsewhere in the body. PCOS is often associated with insulin resistance, which affect muscle strength and endurance due to changes in muscle metabolism. Kazemi et al. have shown that disturbances in insulin function in PCOS cause a decrease in bone and muscle mass [22]. This study also found higher bone and muscle mass in the PCOS subgroup associated with oligomenorrhea and hyperandrogenism. Hyperandrogenism is thought to have a protective effect on muscle and bone mass [20]. We identified 8 studies in the literature that examined muscle strength in PCOS [11, 23–29]. All of these studies were conducted in adults. Our study is important because it is the first study conducted in adolescent PCOS patients. Çalışkan and colleagues investigated mechanical muscle function in adult women with PCOS using an isokinetic muscle dynamometer and measured lower extremity muscle strength [11]. They showed that lower extremity dynamic muscle strength was higher in women with PCOS with hyperandrogenism than in control subjects and that this was related to hyperandrogenism. These measurements are statistically significant but correlate poorly with corrected testosterone levels. Some studies failed to demonstrate this change. However, these studies did not clearly show the relationship between metabolic outcomes and muscle strength [23, 28, 30]. In addition, these studies did not achieve homogeneity between the control groups and the study groups in terms of factors such as BMI and exercise. Kogure et al. demonstrated that androgen excess in PCOS leads to an increase in muscle strength and that there is a direct relationship with isometric muscle strength of the dominant hand [29]. In a meta-analysis, Cirone et al. analyzed 9 studies that examined muscle strength in PCOS patients [31]. Quantitative measures were used in 8 of these studies, and only 1 study examined muscle endurance. It showed that muscle strength did not differ between PCOS patients and control subjects. However, many studies included in the meta-analysis found that muscle strength was high in the PCOS group. However, the assessment of muscle strength in different muscle groups using different methods in the studies included in the meta-analysis may have led to misleading results. There are very few studies examining metabolic data and muscle mass in PCOS patients. In one study that examined uric acid levels and muscle strength, the lower extremity skeletal muscle mass index was found to increase in hyperuricemia and PCOS patients and was statistically significant (p < 0.001) [32]. Handgrip strength provides valuable information about a person’s muscle function, but does not accurately reflect the body’s overall muscle strength. However, in the case of PCOS, handgrip strength can be a useful part of a broader assessment of how the condition affects muscle mass, metabolic function and overall physical health.

One of the most important metabolic characteristics of PCOS is insulin resistance, which leads to increased insulin levels in the blood. In PCOS, the body’s cells are less sensitive to insulin, which leads to higher insulin levels in the blood. Although this does not always lead to obesity, it promotes fat storage and can lead to the accumulation of visceral fat (fat around the internal organs). Visceral fat is metabolically active and is associated with an increased risk of cardiovascular disease and type 2 diabetes. However, although women with PCOS tend to have a higher levels of fat, this does not result in a significant difference in BMI compared to other groups, especially when women with PCOS have a similar total body weight (including fat and lean mass) to other groups. Testosterone, a hormone that is elevated in PCOS, has been shown to promote muscle anabolism (muscle gain) to some extent. Therefore, women with PCOS may have higher muscle mass than other groups, even if they do not differ in overall BMI. However, this effect may not be sufficient to cause significant differences in fat-free BMI when comparing groups, especially if total body weight is similar. Women with PCOS often have an apple-shaped body - more fat accumulates around the abdomen than on the hips and thighs. This type of fat distribution (abdominal fat or visceral fat) is more strongly associated with metabolic disease than subcutaneous fat, even when total BMI is in a healthy range. But this visceral fat may not be adequately captured by BMI, which does not distinguish between visceral fat, subcutaneous fat and lean mass. More specific measurements are used to better understand how insulin resistance, testosterone and other metabolic factors influence body composition in PCOS. Body fat percentage: Measuring body fat percentage (using more advanced techniques such as calipers, bioelectrical impedance or DEXA scans) allows a more accurate assessment of how much of a person’s weight is fat and how much is lean mass. Waist-to-hip ratio (WHR): This ratio can help measure abdominal fat, which is particularly important in PCOS because visceral fat is more strongly associated with metabolic health risks. Waist circumference: Measuring waist circumference can be a useful indicator of visceral fat accumulation and provides more direct information about fat distribution. DEXA (Dual-Energy X-ray Absorptiometry): This is the gold standard for measuring fat-free mass and fat mass, including specific areas of fat (e.g. visceral fat). It provides an accurate picture of body composition and the effects of various factors (such as PCOS) on muscle and fat distribution. In our study, there were no statistically significant differences between body mass index (BMI), lean body mass index and waist-to-hip ratio. On the other hand, neck circumference was significantly higher in the adolescent PCOS group than in the control group.

Vitamin D is a fat-soluble vitamin that plays an important role in bone health and has been shown to affect muscle strength, especially skeletal muscle strength, and is essential for intestinal calcium absorption. Calcium plays an important role in muscle contraction. In addition, vitamin D is associated with the regulation of muscle fiber function, particularly type II fibers, which are responsible for muscle strength and performance. For these reasons, vitamin D deficiency can impair muscle function and reduce strength. There were no statistically significant differences between the vitamin D levels of participants in the PCOS and control groups. Therefore, vitamin D deficiency had no significant effect on muscle strength results.

The study found no statistically significant difference in LH levels between the adolescent PCOS group and the control group, although it is known that there is an association between poor PCOS and elevated LH levels. The participants in both the PCOS and control groups were adolescents, which may contribute to the similarities in LH levels. The average age in both groups was 17 years, suggesting that the participants were in the later stages of puberty, when hormonal fluctuations may have already stabilized. It is possible that LH levels are not as high in late puberty as in early puberty, when the hormonal dysregulation associated with PCOS is more pronounced. The study included participants with lean PCOS, a phenotype in which women typically have less body fat and may not have the same hormonal imbalances as in overweight or obese PCOS subtypes. Had the sample included a variety of PCOS phenotypes (e.g., those with and without insulin resistance), we might have observed less pronounced differences in LH levels between the study groups. The study reports that sex hormone-binding globulin (SHBG) was significantly lower in the PCOS group, which was associated with increased levels of free testosterone (as reflected in the Free Androgen Index or FAI). This may suggest that other aspects of hyperandrogenism, such as free testosterone, play a greater role in PCOS-related symptoms than LH alone. Insulin resistance in PCOS may contribute to elevated LH levels, but the study found no differences between groups in terms of insulin levels or HOMA-IR. It is possible that insulin resistance was not as pronounced in this particular adolescent sample as in the adult population, which could explain the lack of LH elevation. The lack of significant differences in LH levels between the PCOS and control groups could be due to several factors, including the weak PCOS phenotype, the pubertal stage of the adolescent participants, and the possible influence of other hormones such as SHBG, FAI, and AMH. The results of the study suggest that LH may not have significant variability in this adolescent population, but that other hormonal factors may contribute to the pathophysiology of PCOS in this age group.

In the study conducted by Cetik et al., one of the studies that investigated the relationship between eating disorders and PCOS, it was found that the components of eating behavior did not differ [33]. When the study was repeated in patients taking oral contraceptives for three months along with general lifestyle counseling, a significant decrease was observed in the eating behavior questionnaire [33]. Because of the effects of oral contraceptive use on the pathophysiology of hyperandrogenemia, it has been suggested that eating disorders may be related to hyperandrogenemia. In a study conducted with obese women with PCOS, Food Craving Questionnaire scores were higher than those published for non-PCOS populations [34]. Lean women with PCOS had similar scores to healthy controls, but lean women with PCOS had higher binge-eating symptom scores than lean healthy women [34]. This demonstrates the importance of screening women with PCOS for binge eating as part of weight management. In our study, we demonstrated that the eating habits of our adolescent PCOS patients and control patients were similar using the screening tool SCOFF and three different eating behavior questionnaires.The lack of significant differences in the results of the SCOFF, FCQ-T, NEQ and TFEQ-R18 scales despite the presence of hyperandrogenism in PCOS may be explained by a number of factors. Each of these scales measures specific aspects of eating behavior, binge eating, emotional eating, and eating disorder tendencies, and their scores are influenced by a combination of biological, psychological, and social factors. Hyperandrogenism (high levels of male hormones such as testosterone) in PCOS is often associated with symptoms such as hirsutism (excessive hair growth), acne and thinning scalp hair, but the impact on eating behavior are not as direct or obvious as the impact on metabolic or reproductive health. Hormonal imbalance may not lead to significant changes in eating habits, cravings or eating behavior in affected individuals. While hyperandrogenism could affect appetite regulation or stress responses, this may not be enough to cause marked behavioral differences in the questionnaires used (SCOFF, FCQ-T, etc.), especially if the affected individuals do not have obvious psychological symptoms related to eating behaviors or eating disorders. It may also be that some women with PCOS have learned to cope with the physical and emotional challenges associated with their condition, including hyperandrogenism. This means that they may not show significant changes in eating behavior despite the hormonal imbalance.

In reviewing the literature on metabolic outcomes and PCOS, we found that there was a significant association between AMH and PCOS in particular [35, 36]. To emphasize the importance of this association, AMH levels in the adult group were added to the PCOS diagnostic criteria in the newly published 2023 guideline [37]. Based on this development, we can assume that the metabolic consequences of PCOS play an important role in the pathophysiology and that the improvements obtained in these levels contribute to the quality of life of patients.

The results of our study should be interpreted considering their limitations. The main limitation of our study is that it was performed in a single center with a small number of patients. However, since our center is the largest in our city, all PCOS patients in the region are referred here. The sample size of the study may have been an obstacle to obtaining statistically robust and representative results. Future similar studies should be conducted with larger samples. In addition, multicentre studies can increase the generalizability of research. In this way, results can become more reliable and broader conclusions can be drawn about the impact of PCOS on physical health. Therefore, although the data we obtained are local, they cover almost the entire sample. However, since this study contains the first results studied in the adolescent group, it is obvious that there is a need for multicenter studies investigating its use in adolescents. With these studies, it seems possible to modify the negative consequences of PCOS in older age with life changes at a young age and positive quality of life and healthy living conditions. Our findings need to be supported by larger, well-designed, multicenter studies. Despite the moderate sensitivity and specificity values observed in your study, the ROC analysis is very valuable to evaluate the overall diagnostic value of muscle strength as a potential marker for PCOS. By evaluating the AUC and examining the sensitivity-specificity trade-off at different cut-off values, ROC analysis provides a more nuanced understanding of test performance, enabling better-informed clinical decisions and possible improvements in diagnostic strategies.

Conclusions

In contrast to the existing literature, we used surveys in this study to assess the dietary habits of the groups and to examine their relationship with muscle strength. It was found that muscle strength of the dominant hand was high in the PCOS group. The fact that many factors involved in the pathophysiology of muscle strength are similar in both groups sheds light on the pathophysiology of high muscle strength in terms of its relationship to hyperandrogenism. In the adolescent PCOS group, FAI, AMH, and 25- OH vitamin D emerged as effective explanations for the increased muscle strength. The results of the study suggest that hyperandrogenism may have a positive effect on muscle strength in women with PCOS, which could change treatment strategies. Rather than focusing solely on lowering testosterone levels to combat cosmetic symptoms, a more balanced approach is needed that also promotes muscle health and overall physical fitness. This includes exercise programmes, nutritional strategies and careful selection of medications to control both hormonal symptoms and muscle strength in women with PCOS. Exercise not only increases muscle mass and strength, but also helps manage other aspects of PCOS such as insulin resistance, weight management and cardiovascular health. In addition to exercise, proper nutrition (especially protein intake) is crucial for maintaining muscle strength. A diet rich in lean protein sources (e.g. chicken, fish, legumes and dairy products) can enhance the effects of resistance training and contribute to the maintenance of muscle mass in women with PCOS.

The results of this study contribute significantly to a broader understanding of PCOS (polycystic ovary syndrome) and its impact on physical health in adolescents by shedding light on some important aspects of the condition, particularly in relation to muscle strength, metabolic markers and hormone balance.The study emphasises the need for a longitudinal approach to the study of PCOS, particularly in adolescents. As the effects of the hormones and metabolic imbalance associated with PCOS may not fully manifest until later in life, this study provides valuable insight into early markers of the condition and potential interventions to reduce the long-term risks associated with PCOS.

We conclude that PCOS can be reduced by interventions such as nutritional measures, patient education on physical activity, and control of PCOS symptoms, and that further studies on this topic are needed.

Abbreviations

AMH

Anti-mullerian hormone

BMI

Body mass index

DHEAS

Dehydroepiandrosterone sulfate

E2

Estradiol

FAI

Free androgen index

FCQ-T

Food Craving Questionnaire-Trait

FSH

Follicle stimulating hormone

HOMA-IR

Homeostasis model assessment-estimated insulin resistance

LBMI

Lean body mass index

LH

Lutienizing hormone

mFGS

Modified Ferriman-Gallwey score

NEQ

Night Eating Questionnaire

PCOS

Polycystic ovary syndrome

ROC

Receiver operating characteristics

SHBG

Serum sex hormone binding globulin

SD

Standard deviation

T4

Free thyroxine

TFEQ-R18

Three Factor Eating Questionnaire-R18

TSH

Thyroid stimulating hormone

Authors’ contributions

Huriye Guvenc Sacinti Contribuitions: Data collection or management, Data analysis, Manuscript writing/editing. Mujde Can Ibanoglu Contribuitions: Data collection or management, Data analysis, Manuscript writing/editing. Gülsemin Erturk Celik Contribuitions: Data collection or management, Data analysis. Yavuz Sanisoglu Contribuitions: Data collection or management, Data analysis, Protocol/project development. Yaprak Engin-Ustun Contribuitions: Protocol/project development, Data collection or management, Data analysis, Manuscript writing/editing.

Funding

The study did not receive funding.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Approval was obtained by the institutional review board from Ankara Etlik Zubeyde Hanım Women’s Health Training and Research Hospital on 21.09. 2022 # 2022/142. A verbal and written informed consent was obtained from all participants. All authors read and approved the final version of the submitted manuscript.

Competing interests

The authors declare no competing interests.

Consent for publication

Not applicable.