Obesity represents a major global health issue and is increasingly prevalent among women of reproductive age. It is well-established that excess body weight negatively impacts female reproductive function, contributing to menstrual irregularities, anovulation, impaired oocyte quality, and reduced fertility rates [1, 2, 3, 4]. Epidemiological studies indicate that obese women are nearly three times more likely to experience infertility compared to women with a normal body mass index (BMI) [5]. Ovulatory dysfunction—manifesting as oligomenorrhea or anovulation—is more frequently observed in obese women and may occur independently or as part of polycystic ovary syndrome (PCOS), a condition closely linked with obesity [6]. Nevertheless, the precise mechanisms by which obesity impairs reproductive function remain incompletely elucidated.

In addition to reproductive disturbances, obesity is associated with systemic comorbidities such as insulin resistance, type 2 diabetes mellitus, hypertension, cardiovascular disease, and certain cancers, all of which may indirectly compromise reproductive health [7]. Notably, the pattern of fat distribution appears to influence reproductive outcomes. Central (visceral) adiposity, in particular, has been more strongly associated with ovulatory infertility than peripheral fat distribution [8, 9, 10]. Increasing evidence suggests that obesity is not solely a mechanical or metabolic burden but also an endocrine disorder, characterized by the secretion of bioactive molecules known as adipokines [11]. Among these, leptin plays a pivotal role in both energy homeostasis and reproductive regulation [12].

Leptin, primarily secreted by white adipose tissue, serves as a critical signal to the hypothalamic-pituitary-gonadal (HPG) axis and is essential for maintaining reproductive endocrine function. It promotes the secretion of gonadotropin-releasing hormone (GnRH) from the hypothalamus, which subsequently stimulates the anterior pituitary to release luteinizing hormone (LH) and follicle-stimulating hormone (FSH) [13]. The importance of leptin in reproductive physiology has been demonstrated in leptin-deficient animal models and in rare human cases of congenital leptin deficiency, both of which exhibit impaired reproductive function that improves with leptin supplementation [14, 15]. However, in the context of obesity, chronically elevated leptin levels may induce leptin resistance, impairing its regulatory effects and contributing to reproductive dysfunction [16]. Animal studies have further shown that obesity-induced hyperleptinemia can blunt the hypothalamic and ovarian responsiveness to leptin, thereby disrupting folliculogenesis and ovulation [17].

Beyond leptin, the hormones FSH and anti-Mullerian hormone (AMH) are widely recognized as key indicators of ovarian reserve and reproductive capacity [18]. FSH, secreted by the anterior pituitary, stimulates the growth and maturation of ovarian follicles. Elevated basal FSH levels—particularly during the early follicular phase—may reflect diminished ovarian reserve due to decreased negative feedback from estrogen and inhibin $\beta$ [19]. AMH, in contrast, is produced by granulosa cells of small pre-antral and antral follicles and serves as a reliable marker of the remaining follicular pool. Given its relative stability throughout the menstrual cycle and its decline with advancing age, AMH has become an essential tool in assessing ovarian reserve and predicting response to controlled ovarian stimulation [20].

Obesity has been shown to alter both AMH and FSH levels, although findings in the literature remain inconsistent [21]. Some studies have reported lower AMH levels in obese women, possibly due to impaired granulosa cell function or the inhibitory effect of leptin on AMH gene expression [22, 23]. Meanwhile, FSH levels in obese women may remain stable or slightly reduced, potentially due to increased peripheral estrogen synthesis via aromatase activity in adipose tissue, which suppresses FSH secretion through negative feedback mechanisms [24].

The hormonal dysregulation associated with obesity—including altered levels of leptin, insulin, estrogen, and androgens—may collectively interfere with normal folliculogenesis, ovulation, and fertility potential [2, 25]. To better understand this complex interplay, recent research has investigated composite hormonal indices, particularly the FSH/AMH ratio, as a more integrative marker of ovarian function [26, 27]. Since FSH and AMH exhibit opposing trends with declining ovarian reserve—FSH increasing and AMH decreasing—their ratio may more accurately reflect the dynamic hormonal milieu than either marker alone. Several studies have explored the utility of the FSH/AMH ratio in predicting ovarian response in assisted reproductive technology (ART) settings, with some reporting associations between higher FSH/AMH ratios and reduced oocyte yield or diminished ovarian function [28, 29].

Given the rising prevalence of obesity among reproductive-aged women and its multifaceted effects on ovarian physiology and endocrine function, further research is needed to clarify the relationships between obesity and reproductive hormone profiles. In the present study, we aimed to evaluate the associations between BMI and key reproductive markers—specifically FSH, AMH, and the FSH/AMH ratio—and to assess their predictive value for oocyte yield in women undergoing controlled ovarian stimulation. We further aimed to investigate whether the FSH/AMH ratio serves as a more sensitive indicator of ovarian reserve across different BMI categories, thereby enhancing fertility assessment and individualized treatment planning.

A total of 92 women met the predefined inclusion criteria: age between 25 and 35 years, FSH $\le$15.00 IU/mL, LH $\le$12.00 IU/mL, AMH between 0.50 and 4.50 ng/mL, and no more than 15 oocytes retrieved following controlled ovarian stimulation. The mean age of participants was 32.70 $\pm$ 2.80 years. Mean serum FSH and AMH levels were 7.06 $\pm$ 1.67 IU/mL and 1.72 $\pm$ 0.89 ng/mL, respectively. The mean FSH/AMH ratio was 5.77 $\pm$ 4.35, with values ranging from 0.88 to 20.44. The mean BMI was 25.20 $\pm$ 4.20 kg/m² (range: 17.30–39.20), and the mean number of oocytes retrieved was 8.13 $\pm$ 3.33 (range: 2–15).

Table 1 summarizes the baseline characteristics of the study population stratified by BMI category. Across BMI groups, LH levels differed significantly (p = 0.050), while no significant differences were observed for age, FSH, AMH, TSH, or oocyte count (all p $>$ 0.050). The BMI distribution confirmed expected differences across the categorized groups (p 0.001).

Spearman’s correlation analysis revealed a strong positive association between AMH and oocyte count (r = 0.63, p 0.001), and a strong negative association between the FSH/AMH ratio and oocyte count (r = –0.61, p 0.001). FSH demonstrated a weak negative correlation with oocyte count (r = –0.17, p = 0.11), while BMI showed no significant correlation with any ovarian reserve marker (r = –0.02, p = 0.84).

Participants were stratified into five BMI categories based on WHO classifications: underweight (n = 3), normal weight (n = 50), overweight (n = 29), class I obese (n = 7), and class II obese (n = 3). The highest median oocyte count was observed in the underweight group (11), followed by class II obese (10), class I obese (9), overweight (8), and normal weight (7). Median FSH/AMH ratios were 2.24 (underweight), 4.77 (normal weight), 4.32 (overweight), 5.09 (class I obese), and 9.40 (class II obese), as illustrated in Figs. 1,2. However, the Kruskal-Wallis test revealed no statistically significant differences among BMI groups in either oocyte count (H = 5.35, p = 0.253) or FSH/AMH ratio (H = 5.58, p = 0.134). These findings suggest that BMI category was not significantly associated with ovarian response or hormonal ratio within this cohort, although observable trends warrant further exploration in larger populations. To further examine the robustness of oocyte count estimates across BMI subgroups, non-parametric bootstrap analyses (10,000 iterations) were performed. The 95% CIs for the mean oocyte counts were as follows: underweight, 6.67–13.67; normal weight, 6.45–8.31; overweight, 6.70–8.28; class I obese, 6.57–10.71; and class II obese, 5.50–10.50. Notably, the widest CIs were observed in the underweight and class II obese groups, consistent with their limited sample sizes (n = 3 for each). Despite numerical differences in mean oocyte yield across BMI categories, the overlapping CIs indicate that these variations are likely due to sampling variability rather than statistically robust subgroup effects.

Fig. 1.

Distribution of oocyte counts across BMI categories.

Fig. 2.

Distribution of FSH/AMH ratios across BMI categories.

To further assess predictors of ovarian response, linear regression analysis was conducted (Fig. 3). In the initial model, which included both the FSH/AMH ratio and BMI as continuous variables, the FSH/AMH ratio was significantly and negatively associated with oocyte count ($\beta$ = –0.58; 95% CI: –0.74 to –0.42; p 0.001), explaining 37% of the variance (R² = 0.37). Conversely, BMI was not significantly associated with oocyte count ($\beta$ = –0.03; 95% CI: –0.25 to 0.19; p = 0.754). An interaction term (FSH/AMH ratio $\times$ BMI) was added to examine effect modification; however, the interaction was not statistically significant ($\beta$ = 0.00; p = 0.763), indicating that the predictive relationship between the FSH/AMH ratio and oocyte count was not influenced by BMI. A second regression model, adjusted for age, confirmed the robustness of these findings. The FSH/AMH ratio remained a significant independent predictor of oocyte count ($\beta$ = –0.38; 95% CI: –0.53 to –0.23; p 0.001), whereas BMI ($\beta$ = –0.02; 95% CI: –0.17 to 0.13; p = 0.782) and age ($\beta$ = 0.01; 95% CI: –0.19 to 0.21; p = 0.929) were not significant contributors. This adjusted model accounted for 24.1% of the variance in oocyte count (R² = 0.24; adjusted R² = 0.22). Model assumptions regarding linearity and homoscedasticity were verified, and the Breusch–Pagan test showed no evidence of heteroscedasticity (p = 0.77), supporting the validity of the regression estimates.

Fig. 3.

Relationship between FSH/AMH ratio and oocyte count across BMI categories. A scatterplot illustrates the negative association between the FSH/AMH ratio and the number of retrieved oocytes, stratified by BMI categories: underweight (18.50 kg/m²), normal weight (18.50–24.90 kg/m²), overweight (25.00–29.90 kg/m²), class I obese (30.00–34.90 kg/m²), and class II obese (35.00–39.90 kg/m²). Each dot represents an individual participant, and the shaded areas indicate 95% confidence intervals for the regression lines.

This study evaluated the predictive value of the FSH/AMH ratio for ovarian response and assessed whether BMI modifies this relationship in infertile women undergoing controlled ovarian stimulation. Our findings demonstrate that the FSH/AMH ratio is a robust and independent predictor of oocyte yield, whereas BMI and its interaction with the ratio were not statistically significant. These results highlight the clinical utility of the FSH/AMH ratio as a composite endocrine marker that integrates both pituitary function and ovarian reserve, providing a more reliable indicator of ovarian responsiveness than either hormone alone, regardless of BMI.

The association between obesity and impaired fertility is well-established and multifaceted. Excess adipose tissue adversely affects ovulation, oocyte quality, and endometrial receptivity, contributing to suboptimal reproductive outcomes in women with elevated BMI [2, 30]. Emerging evidence suggests that obesity disrupts the hypothalamic-pituitary-ovarian axis through alterations in insulin signaling, steroidogenesis, and the secretion of bioactive adipokines, thereby impairing ovarian function and responsiveness to gonadotropins. In this study, we observed numerically higher FSH/AMH ratios and lower oocyte yields among women in higher BMI categories, aligning with previous reports of diminished ovarian responsiveness in obese patients [2].

Although BMI is often cited as a determinant of reproductive outcomes, our results suggest that, among women with a preserved ovarian reserve and within a moderate BMI range, BMI alone does not significantly influence AMH, FSH, or their ratio. This finding aligns with prior reports indicating that AMH remains a consistent predictor of ovarian response and is relatively unaffected by BMI [27]. In contrast, FSH tends to exhibit greater variability and is less reliable when considered in isolation [18]. The FSH/AMH ratio has emerged as a more integrative marker, combining pituitary activity (FSH) with ovarian follicular output (AMH). In this study, a higher FSH/AMH ratio was strongly correlated with reduced oocyte yield, confirming previous observations that elevated ratios are associated with diminished follicular development and an increased risk of cycle cancellation [28, 29].

The FSH/AMH ratio may be particularly valuable in clinical scenarios where individual hormone levels are borderline or contradictory. Prior research has demonstrated that this ratio exhibits higher sensitivity and specificity for predicting poor ovarian response compared to AMH or FSH alone [27, 28]. Evidence from animal models of diet-induced obesity supports these findings, showing that elevated FSH/AMH ratios are associated with reduced follicle counts and impaired ovarian function [29]. Similarly, in our cohort, higher ratios were negatively correlated with oocyte yield across all BMI groups, suggesting that this composite index effectively captures subtle disturbances in ovarian function that may not be evident from individual hormone levels.

Although AMH is widely regarded as a marker of ovarian reserve, it is influenced by dynamic intra-ovarian processes. AMH secretion begins during the transition from primordial to primary follicles and peaks at the antral stage. Its expression is regulated by intra-ovarian factors and may be modulated by FSH [31]. A high FSH/AMH ratio may therefore reflect both a diminished follicular pool and a compensatory increase in pituitary output, indicating accelerated ovarian reserve depletion [18]. Furthermore, obesity has been reported to reduce AMH production through impaired granulosa cell function and decreased FSH receptor expression [22]. In our study, patients with both higher BMI and elevated FSH/AMH ratios exhibited the lowest oocyte counts, suggesting that adiposity may exacerbate hormonal imbalance and compromise ovarian responsiveness.

The majority of evidence supports that women with elevated FSH and low AMH levels have reduced oocyte yield and possibly lower oocyte quality, highlighting the importance of the interplay between these hormones [18, 32, 33]. Consistent with this, we observed lower oocyte numbers in patients with higher FSH/AMH ratios, regardless of BMI. While no significant interaction between BMI and the ratio was identified, the combination of elevated BMI and high FSH/AMH ratio identified a subgroup at greater risk for poor ovarian response.

Our findings highlight the potential clinical utility of the FSH/AMH ratio as a reliable predictor of ovarian response, independent of BMI. This marker may aid clinicians in optimizing patient counseling and stimulation protocols, especially in women with borderline ovarian reserve. Although BMI did not significantly influence hormonal parameters in this study, its potential role in modulating ovarian sensitivity warrants continued consideration during fertility assessment. It is important to note that our cohort included women with BMI values ranging from 17 to 39.9 kg/m², and therefore, the results may not be generalizable to individuals with class III obesity (BMI $\ge$40 kg/m²).

This study demonstrates that the FSH/AMH ratio is a valuable and BMI-independent predictor of oocyte yield in women undergoing controlled ovarian stimulation. While AMH and FSH are individually informative markers of ovarian reserve, their ratio provides a more integrated assessment of reproductive potential. Our findings confirm that higher FSH/AMH ratios are significantly associated with lower oocyte counts, supporting its clinical utility in identifying patients at risk for suboptimal ovarian response—particularly when standard markers yield inconclusive results.

Although BMI is a well-recognized factor influencing reproductive outcomes, it did not significantly impact hormonal profiles or the FSH/AMH ratio in this study. However, the combination of elevated BMI and a high FSH/AMH ratio was associated with a more pronounced reduction in oocyte yield, highlighting the importance of evaluating both endocrine and metabolic parameters during fertility assessment.

Given the rising prevalence of being overweight or obese among women of reproductive age, the FSH/AMH ratio may serve as a practical and reliable marker across BMI categories. Further prospective studies in larger, more diverse cohorts are warranted to confirm its clinical applicability and to explore whether BMI-adjusted thresholds could enhance its predictive performance.

The raw data supporting the conclusions of this article will be made available by the authors on request.

EK and EGA designed the research study, validated the data and results. EK developed the methodology, performed the software work, conducted the investigation, curated the data, and carried out the formal analysis and visualization. EGA provided resources. Both authors contributed to editorial changes in the manuscript. Both authors read and approved the final version of the manuscript. Both authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Acibadem Mehmet Ali Aydinlar University School of Medicine (protocol code 2023-10/427). Written informed consent was obtained from all participants prior to inclusion in the study.

This research received no external funding.

The authors declare no conflict of interest.

During the preparation of this work the authors used ChatGpt-4.0 in order to check spell and grammar. After using this tool, the authors reviewed and edited the content as needed and takes full responsibility for the content of the publication.