Prof. Dr. Tripti Rani Das¹, Dr. Sabiha Islam², Dr. Dipika Majumder³, Dr. Iffat Rahman⁴, Dr. Shah Noor Sharmin⁵, Dr. Jinat Fatema⁶, Dr. Bidisha Chakma⁷*, Dr. Tanzina Iveen Chowdhury⁸

¹Professor, Department of Obstetrics & Gynecology, Bangladesh Medical University, Dhaka, Bangladesh

²Associate Professor, Department of Obstetrics & Gynecology, Bangladesh Medical University, Dhaka, Bangladesh.

³Medical Officer, Department of Obstetrics & Gynecology, Madaripur, Bangladesh

⁴Medical officer, Department of Obstetrics & Gynecology, Aliahat Hospital, Bogra, Bangladesh

⁵Medical officer, Department of Obstetrics & Gynecology, Bangladesh Medical University, Dhaka, Bangladesh.

⁶Assistant Professor, Department of Obstetrics & Gynecology, Bangladesh Medical University, Dhaka, Bangladesh.

⁷Associate Professor, Department of Obstetrics & Gynecology, Bangladesh Medical University, Dhaka, Bangladesh.

⁸Assistant Professor, Department of Obstetrics & Gynecology, Bangladesh Medical University, Dhaka, Bangladesh.

^*Corresponding author: Dr. Bidisha Chakma, Associate Professor, Department of Obstetrics & Gynecology, Bangladesh Medical University, Dhaka, Bangladesh (BMU).

Received: 06 May 2025; Accepted: 12 May 2025; Published: 20 May 2025

Article Information

Citation: Prof. Dr. Tripti Rani Das, Dr. Sabiha Islam, Dr. Dipika Majumder, Dr. Iffat Rahman, Dr. Shah Noor Sharmin, Dr. Jinat Fatema, Dr. Bidisha Chakma, Dr. Tanzina Iveen Chowdhury. Relationship Between Different Nutritional Status and Specific Hormone Levels in Sub Fertile Women in a Selected Tertiary Level Hospital in Dhaka, Bangladesh. Obstetrics and Gynecology Research. 8 (2025): 91-95.

DOI: 10.26502/ogr0183

Abstract

Keywords

Subfertility; Obesity; BMI; AMH; Ovarian Reserve; Reproductive Health; Subfertility

Article Details

INTRODUCTION

Subfertility, a condition affecting a significant portion of the global population, presents a major reproductive health challenge. Recent data from the World Health Organization indicates that approximately 1 in 6 people worldwide experience infertility, underscoring its widespread impact [1]. The prevalence of infertility exhibits geographical variations, with studies highlighting its burden in regions like India [2] and Bangladesh [3, 12, 15]. Among the various factors contributing to infertility in women, PCOS (PCOS), a common endocrine disorder, plays a substantial role [3, 12, 15, 16]. Understanding the determinants of fertility potential is essential for developing effective diagnostic and therapeutic interventions.

BMI has emerged as a key factor under investigation in relation to female reproductive health. AMH, a hormone produced by the ovarian follicles, serves as a crucial indicator of ovarian reserve and is widely utilized in the assessment of infertile women. Numerous studies have explored the association between BMI and AMH levels in diverse populations. Research has indicated a significant relationship between these two parameters in large cohorts of infertile women [4, 5] and in specific conditions such as PCOS [3, 7, 16]. Meta-analyses have further consolidated these findings, providing a broader understanding of the influence of BMI on ovarian reserve [6, 7]. Notably, alterations in metabolic hormones and adipokines associated with different BMI categories can impact ovarian function and AMH production [17, 18].

Within the South Asian context, including India and Bangladesh, studies have specifically examined the interplay between BMI and AMH in subfertile women [2, 8, 9, 10, 11, 13, 14]. These investigations contribute valuable insights into how nutritional status, as reflected by BMI, may affect crucial reproductive hormones like AMH in this specific population. Furthermore, evidence suggests that lifestyle modifications, including dietary changes and exercise, can influence both BMI and AMH levels, highlighting the potential for modifiable factors to impact ovarian reserve [19, 20]. The present study aims to further investigate the relationship between different BMI categories and serum AMH levels in subfertile women attending a selected tertiary level hospital in Dhaka City, Bangladesh, adding to the existing body of knowledge in this area.

Methods:

This cross-sectional analytical study was carried out at the Department of Obstetrics and Gynaecology, (BUM), Dhaka, over a period of 18 months (January 2023 - June 2024). A total of 148 sub-fertile women aged 15-44 years were enrolled using convenient sampling technique. Women with premature ovarian insufficiency, ovarian pathology, or previous ovarian surgery were excluded. Data on sociodemographic, reproductive, and clinical profiles were collected using a semi-structured questionnaire. Body weight and height were measured to calculate BMI. Two milliliters of venous blood were collected aseptically, and serum AMH was measured using CMIA at the BUM, Dhaka, endocrine lab. The comparison of AMH levels between the two groups was performed using appropriate statistical tests in SPSS version 26. Descriptive statistics were presented as frequency, percentage and appropriate graphs, and inferential statistics including independent sample t-test and regression analysis were applied. A p-value < 0.05 was considered statistically significant. Informed written consent was obtained from all participants, and confidentiality and ethical issues were strictly maintained.

Data Processing plan:

Figure

Results:

In this study Most participants 48.6% were aged 25–34 years, followed by 35-44 years 27.0% and 15–24 years 24.3%. About education, 36.5% had graduate-level or higher education, 32.4% completed higher secondary education, and 5.4% had simply primary education. Most respondents 64.9% stated a monthly family income of BDT 30,000-50,000, while 27.0% earned above BDT 50,000 and 8.1% got below BDT 30,000.

Subfertility above for one year was reported by 86.5% of participants. Nulliparity was noted at 62.2%, suggesting a high rate of initial infertility. Systematic menstrual cycles were noted in 59.5%, while 40.5% had unusual cycles. PCOS was displayed in 39.2% of participants, thyroid dysfunction in 32.4%, and diabetes mellitus in 18.2%.

A significant association was found between PCOS and physical activity level (p = 0.000), with sedentary women being 2.25 times more likely to have PCOS. PCOS was also significantly associated with subfertility status (t = -6.836; p = 0.000). Regression analysis showed that both serum AMH (B = 0.380; p = 0.000) and BMI (B = 0.583; p = 0.000) had significant effects on subfertility, supporting the association between BMI categories and AMH levels in sub-fertile women.

Table 1: Distribution of respondents by socio-demographic factors

Table 1 shows most sub fertile women were in the 25-34 years age group 48.6%, followed by 35-44 years 27.0% and 15-24 years 24.3%. Regarding educational status, a considerable proportion had completed graduate-level education or higher 36.5%, while 32.4% had completed higher secondary education. Only 5.4% had education up to the primary level.

Figure 1: Distribution of the respondents by monthly family income.

Figure 1 shows most respondents 64.9%, reporting a monthly family income between BDT 30,000 and 50,000, indicating a predominance of lower-middle-income households. A smaller proportion 27.0% belonged to higher income groups >BDT 50,000, while only 8.1% reported earnings below BDT 30,000.

Figure 2: Distribution of the respondents by present medical conditions (n=148).

Figure 2 shows a substantial proportion of the respondents, 86.5% experienced subfertility for one year or more. Most women were nulliparous 62.2%, highlighting their primary infertility status. Regular menstrual cycles were reported by 59.5% of the participants, while 40.5% had irregular cycles. Notably, 39.2% of the respondents had PCOS, which is a common endocrine disorder associated with subfertility. Thyroid dysfunction was present in 32.4% of women, and 18.2% had diabetes mellitus.

Table 2: Association between PCOS and level of physical activity

* 1 cell has expected count less than 5. f= Fisher's Exact Test.

Table 2 shows that there was a significant association between PCOS and level of physical activity (p=0.000), OR=2.250 indicates that PCOS is 2.25 times higher among sedentary lifestyle than physically active participants.

Table 3: Association between sub-fertility status and PCOS

* Independent Samples t-Test

Table 3 shows that the calculated t-value is -6.836 and p-value is .000 (2-tailed) which is (<0,05) with 146 degrees of freedom. This indicates that there is a significant association between sub-fertility status and PCOS.

Table 4: Adjusted regression coefficients of explanatory variables with their significance

*Dependent Variable: Sub-fertility * b. Predictors: (Constant), BMI, Serum AMH level

Table 4 shows that regression Coefficients (Unstandardized Coefficients and standardized Coefficients), p-value (sig) and 95% Confidence intervals (CI) for regression coefficients of all explanatory variables in the model along with the constant. The Unstandardized regression Coefficients (B) are for Serum AMH level (0.380; p=0.000) and BMI (.583; p=0.000). It was concluded that the Serum AMH level and BMI had significant influence on sub-fertility status of the participants.

Discussion

Our findings revealed a significant association between PCOS and the level of physical activity, with sedentary women having a 2.25 times higher likelihood of PCOS compared to physically active women. This aligns with existing literature highlighting the beneficial role of physical activity in managing PCOS [20, 21]. Moreover, the independent samples t-test demonstrated a strong association between subfertility status and the presence of PCOS, corroborating the established link between this endocrine disorder and impaired fertility [8, 22]. Notably, both serum AMH levels and BMI emerged as significant independent predictors of subfertility status in our study population, collectively explaining approximately 56% of the variance in subfertility. This finding underscores the importance of both ovarian reserve markers and nutritional status in the context of female fertility.

The significant predictive role of AMH levels in subfertility is consistent with its established utility as a marker of ovarian reserve [4, 23]. Lower AMH levels often indicate diminished ovarian follicle quantity and quality, which can directly impact the likelihood of conception. Similarly, the significant association between BMI and subfertility aligns with a wealth of research demonstrating the adverse effects of both underweight and overweight/obesity on reproductive outcomes [5, 9, 24]. Alterations in adipokines, insulin resistance, and hormonal imbalances associated with extremes of BMI can disrupt ovulation, oocyte quality, and endometrial receptivity [17, 18, 25]. The strong predictive value of the model incorporating both AMH and BMI suggests a synergistic effect of ovarian reserve and nutritional status on subfertility in our study population. These findings have important implications for the clinical management of subfertile women, emphasizing the need for a comprehensive assessment that includes both hormonal profiling and evaluation of body weight. Further research with larger, multi-centric studies is warranted to validate these findings and explore potential underlying mechanisms in this specific population.

Conclusion:

This study of subfertile women in Dhaka, Bangladesh demonstrates that lower AMH levels and non-optimal BMI are significantly associated with subfertility. Sedentary lifestyle increased the odds of PCOS, which was also linked to subfertility. These findings emphasize the need to consider ovarian reserve and BMI in managing subfertility and suggest a role for physical activity interventions.

Declaration of Interest:

The authors declare no competing interests.

Conflict of Interest:

The authors have no conflicts of interest to disclose related to this study.

Authors Contributions:

Prof. Dr. Tripti Rani Das and Dr. Sabiha Islam conceptualized the study and designed the methodology. Dr. Dipika Majumder and Dr. Iffat Rahman contributed data management and statistical analysis. Dr. Shah Noor Sharmin, Dr. Jinat Fatema and Dr. Bidisha Chakma assisted in manuscript drafting and critical revisions. Prof. Dr. Tripti Rani Das and Dr. Tanzina Iveen Chowdhury supervised the research and provided final manuscript approval. All authors reviewed and approved the final version.

References

1. World Health Organization. (2023). 1 in 6 people globally affected by infertility: WHO. Retrieved from https://www.who.int/news/item/04-04-2023-1-in-6-people-globally-affected-by-infertility/
2. Singh, A., & Singh, A. Infertility Burden Across Indian States: Insights from a Nationally Representative Survey Conducted During 2019-21. Journal of Reproductive Health, 20 (2023): 123-130.
3. Sultana, S., & Rahman, M. Prevalence and characteristics of women with PCOS in Bangladesh. Bangladesh Journal of Endocrinology and Metabolism, 28 (2023): 45-52.
4. Albu D, Albu A. The relationship between anti-Müllerian hormone serum level and body mass index in a large cohort of infertile patients. Endocrine 63 (2019): 157-163.
5. Wang, Y., & Zhao, H. Association of BMI with serum anti-Müllerian hormone and inhibin B levels among 8323 women attending a reproductive medical center: a cross-sectional study. Endocrine, 75 (2022): 284-292.
6. Moslehi N, Shab-Bidar S, RamezaniTehrani F, et al. Is ovarian reserve associated with body mass index and obesity in reproductive aged women? A meta-analysis. Menopause 25 (2018): 1046-1055.
7. Ramezani Tehrani, F., &Behboudi-Gandevani, S. The impact of BMI on anti-Müllerian hormone levels in women with PCOS: a systematic review and meta-analysis. Journal of Endocrinological Investigation 37 (2014): 715-721.
8. Haq, M. E., & Chowdhury, T. A. Prevalence of PCOS among infertile women in a tertiary care hospital in Bangladesh. Journal of Obstetrics and Gynaecology Research, 48 (2022): 1234-1240.
9. Casadei, L., Nacci, I., Vicomandi, V., et al. Relationship between Ovarian Reserve Markers and Body Mass Index in Infertile Women with and without Polycystic Ovary Syndrome: A Retrospective Case–Control Study. Reproductive Medicine 4 (2023), 198-209.
10. Das, S., & Roy, S. Association between BMI and anti-Müllerian hormone levels in infertile women: a hospital-based study. Journal of Human Reproductive Sciences, 13 (2020): 289-294.
11. Lim S, Kim S, Kim O, et al. Correlations among anti-Müllerian hormone levels, body mass index and lipid profile in reproductive-aged women: The Korea Nurses' Health Study. Nurs Open 8 (2021): 2996-3005.
12. Alam, M. M., & Akter, S. Prevalence of PCOS among women attending a tertiary care hospital in Dhaka. Bangladesh Medical Journal, 47 (2018): 15-20.
13. Wang Y, Wu L, Yang Z, et al. Association of body mass index with serum anti-Müllerian hormone and inhibin B levels among 8323 women attending a reproductive medical center: a cross-sectional study. Endocrine 75 (2022): 284-292.
14. Albu D, Albu A. The relationship between anti-Müllerian hormone serum level and body mass index in a large cohort of infertile patients. Endocrine 63 (2019): 157-163.
15. Begum, F., & Hossain, M. Prevalence of PCOS among women with infertility in Bangladesh. Journal of Reproductive Health, 19 (2015): 45-50.
16. Spinedi E, Cardinali DP. The Polycystic Ovary Syndrome and the Metabolic Syndrome: A Possible Chronobiotic-Cytoprotective Adjuvant Therapy. Int J Endocrinol 25 (2018): 1349868.
17. Havel, P. J. Role of adipose tissue in endocrine regulation: mechanisms regulating leptin production. Proceedings of the Nutrition Society, 63 (2004): 49-55.
18. Carmina, E., & Lobo, R. A. Do hyperandrogenemia and/or hyperinsulinemia explain the high frequency of altered body composition in women with PCOS? Fertility and Sterility, 71 (1999): 707-711.
19. Shang Y, Zhou H, Hu M, et al. Effect of Diet on Insulin Resistance in Polycystic Ovary Syndrome. J ClinEndocrinolMetab 105 (2020): dgaa425.
20. Thomson, R. L., Buckley, J. D., Moran, L. J. Exercise improves fertility in overweight and obese women with PCOS: a systematic review and meta-analysis. Human Reproduction Update, 14 (2008): 583-599.
21. Sanchez-Garrido MA, Tena-Sempere M. Metabolic dysfunction in polycystic ovary syndrome: Pathogenic role of androgen excess and potential therapeutic strategies. MolMetab 35 (2020): 100937.
22. Teede, H. J., Misso, M. L., Costello, M. F., et al. International evidence-based guideline for the assessment and management of PCOS 2018. Fertility and Sterility, 110 (2018): 364-379.
23. Ferraretti AP, Gianaroli L. The Bologna criteria for the definition of poor ovarian responders: is there a need for revision? Hum Reprod 29 (2014): 1842-1845.
24. Silvestris, E., de Matteis, S., Gaggini, M., et al. The influence of obesity on female fertility and the effectiveness of bariatric surgery: a systematic review and meta-analysis. International Journal of Obesity, 42 (2018): 983-992.
25. Wise, J., Hart, R., Martins da Silva, S., et al. The effect of BMI on in vitro fertilisation outcomes: a systematic review and meta-analysis. Human Reproduction Update, 29 (2023): 117-141.