European Journal of Cardiovascular Medicine

Substantial changes have been observed in the human environment, activities, and lifestyle over the previous fifty years. The metabolic syndrome is merely one of the several health hazards that these alterations have introduced, alongside enhancing living conditions in communities. Metabolic syndrome (MetS) is defined as the presence of a cluster of at least three of the five related metabolic risk factors: hypertension, central obesity, impaired glucose tolerance, low serum HDL, and high serum triglycerides. The metabolic syndrome comprises various metabolic risk factors, and the determination of cut-off points for each component significantly influences the syndrome's prevalence. [1]

The revised NCEP ATP III standards propose that waist circumference cut-off points be ethnicity-specific, recommending 90 cm for men and 80 cm for women of Asian descent.
Diabetes and the onset of coronary artery disease are intricately associated with metabolic syndrome. The ramifications of metabolic syndrome, which coexists with obesity and polycystic ovarian syndrome (PCOS), extend beyond women of reproductive age. These disorders correlate with adverse reproductive outcomes and infertility. Consequently, investigations into the relationship between reproductive failure and metabolic syndrome are ongoing. [3]

Obesity affects the female reproductive axis throughout their lifespan. It is associated with an increased risk of hyperandrogenism and ovulatory dysfunction in women of reproductive age, and it may influence pubertal development in these individuals. Concentrations of anti-Mullerian hormone (AMH) have been associated with reduced adiposity. AMH serves as an indicator of reduced ovarian reserve and is secreted by the granulosa cells of the ovary. [4, 5] MetS may directly influence oocyte quality. The follicular fluid of obese women has elevated levels of C-reactive protein (CRP), indicating a distinct link between the maternal metabolic environment and the ovarian follicular microenvironment. Follicular fluid in obese women exhibits increasing levels of CRP, indicative of inflammation and increased oxidative stress, which has been associated with diminished egg developmental potential. [6]

The number of primordial ovarian follicles, as shown by ovarian reserve, reflects a woman's reproductive potential. [7]The quantity of follicles consistently diminishes with age, from adolescence until the onset of menopause; nevertheless, among women of comparable ages, there exists considerable variability in both the follicle count and the pace of decline. [8–10] Assessing ovarian reserve helps forecast the age of menopause, the likelihood of infertility, and the efficacy of assisted reproductive technologies (ARTs) in women experiencing infertility. 7 Environmental factors can influence the rate of follicular decline alongside genetic and age-related factors. Women are increasingly postponing marriage and childbirth, making it essential to uncover modifiable factors related to ovarian reserve. [11] Metabolic syndrome may affect women's reproductive health. An higher body mass index heightens the risk of ovulatory and menstrual disorders, delayed fertility, and infertility. Moreover, women seeking ART who are obese have decreased success rates compared to their non-obese counterparts. The age of menopause has been shown to correlate with BMI. Numerous reasons have been proposed to elucidate the relationship between female reproductive failure and BMI. The connections among ovarian reserve, metabolic syndrome, and infertility are contentious and not fully clear. [12, 13]

Global studies have shown that individuals with metabolic syndrome endure infertility for a more extended duration compared to those without the illness. Insulin resistance significantly contributes to metabolic syndrome (MetS); hence, early detection and intervention with dietary modifications and pharmacotherapy can facilitate optimal conception opportunities. The objective of this study is to ascertain the incidence of various metabolic syndrome markers and to investigate potential correlations between metabolic syndrome and ovarian reserve in infertile women.

JUSTIFICATION
The rising prevalence of infertility and metabolic syndrome in our nation has not been adequately examined in terms of their association. The current study aims to determine the incidence of several metabolic syndrome indicators in infertile women with diminished ovarian reserve.

The present study was planned and carried out in Department of Medicine, MGM college & MY hospital and MTH Hospital, Indore for 1 year. This study included 298 consecutive patients who fulfilled the inclusion criteria and attended Endocrine OPD, Department of Medicine, MGM Medical College and M.Y.H and associated Hospitals, Indore OR attended infertility clinic OPD in MTH hospital.

Study Design

Observational Cross-sectional study.

Sample Size

Sample size calculation was done using G*Power software 3.1.9.2 version and 95% confidence interval and 90% Power and a final sample size of 298 based on convenient sampling.

Inclusion Criteria

• Married females with primary infertility only.
• Age group of 20 – 40 years
• Consent given by patient.

Exclusion Criteria

• Prisoners and Psychiatric patients.
• Patients with chronic renal failure, chronic liver failure, other systemic disease ,gynecological abnormalities such as PCOD,dysfunctional uterine bleeding or menorrhagia.
• Patients with iatrogenic cause of infertility such as ovarian /uterine surgery, chemo radiotherapy in young.
• Patient with secondary infertility and infertility due to anatomical Mullerian anomalies.

Study Duration

The study was conducted for a period of 12 months.( January 23- December ,2023)

Methodology

We used the modified Asian NCEP ATP III criteria in our study. We used recommended cut-off for abdominal circumference for Asians population (90 cm in men and 80 cm in women) as there are no national cut-off values specific for India.

A pre-tested, pre-validated proforma was used to collect data from patients and medical records. After written informed consent all data was collected.

Relevant data recorded was –

Demographic data – Age, place (urban/rural), religion.

Detailed medical history-

• Presenting complaints.
• Past history of chronic medical and surgical illness.
• History of drug treatment.
• Family history of chronic medical and surgical illness.
• Personnel history – Dietary, sleep, bowel and bladder.
• History of substance abuse.
• History of infertility treatment.

Clinical examination-

• General examination
• Systemic examination

Routine Laboratory investigations:

• Complete Blood Count
• Liver Function Test
• Renal Function Test
• Fasting lipid profile
• Fasting Blood sugar /Post prandial blood sugar
• Thyroid profile
• Baseline ECG
• Sonographic assessment for ovarian reserve –USG Pelvis and Trans vaginal sonography (Best time 2^nd and 3^rd day of menstrual cycle)

Statistical Analysis

The data was entered and cleaned using MS Excel and analyzed statistically using SPSS-25. Quantitative variables were expressed as mean value ± standard deviation or median ± interquartile range. Qualitative data was expressed as percentages (%) and proportion. Appropriate statistical test was used to infer association between 2 variables and a p value of < 0.05 was considered statistically significant.

Ethical considerations

The protocol was presented before the ethical committee for approval. After due approval from the ethical committee, the study was initiated. Before including any patient for the participation in the study, a voluntary written consent for participation was obtained from either the patient and/or his/her legally acceptable representative.

Financial inputs and funding

The study was carried out in the Government hospital (Maharaja Yeshwant Rao Hospital) of central India. Here all types of treatments and investigations are provided free of cost to the patients. Hence, there was no additional financial burden on the patient and/or his/her legally acceptable representatives. The present study has not been funded by any pharmaceutical company or institution.

Table 1 Sociodemographic Details of Study Participants

The study participants had the following characteristics: the majority of the participants were aged between 21 and 30 years, accounting for 84.6% (n=252), while 15.4% (n=46) were aged 31-40 years. Regarding religion, 65.4% (n=195) of the participants were Hindus, and 34.6% (n=103) were Muslims. The duration of infertility for most participants was ≤ 3 years, representing 79.5% (n=237), while 18.5% (n=55) had infertility lasting 4 to 6 years, and 2.0% (n=6) reported infertility for more than 6 years. All participants had primary infertility (100%, n=298).

Table 2 Anthropometric and Clinical examination of study participants

The study participants exhibited the following clinical characteristics: waist circumference, 29.9% (n=89) had a measurement of less than 80 cm, and 70.1% (n=209) had waist circumferences of 80 cm or more. Fasting triglyceride levels were below 150 mg/dL in 35.9% (n=107) of participants, whereas 64.1% (n=191) had levels equal to or greater than 150 mg/dL. For fasting HDL, 48.0% (n=143) had levels below 50 mg/dL, and 52.0% (n=155) had levels of 50 mg/dL or higher. The majority of participants, 80.5% (n=240), had fasting blood glucose levels under 100 mg/dL, while 19.5% (n=58) had levels of 100 mg/dL or more. Systolic blood pressure was below 130 mm Hg in 63.4% (n=189), while 36.6% (n=109) had systolic readings of 130 mm Hg or higher. For diastolic blood pressure, 71.8% (n=214) had values below 85 mm Hg, and 28.2% (n=84) had values of 85 mm Hg or higher. HbA1c levels indicated that 61.1% (n=182) were non-diabetic (HbA1c < 5.7), 24.8% (n=74) were prediabetic (HbA1c 5.7–6.4), and 14.1% (n=42) were diabetic (HbA1c ≥ 6.5).

Table- 3 Prevalence of Mets in Study Particiapnt

The prevalence of metabolic syndrome among the study participants was 36.9% (n=110), while 63.1% (n=188) did not have metabolic syndrome. When analyzed 36.9% (n=110) of participants with primary infertility had metabolic syndrome. Additionally, 51.3% (n=153) of females fulfilled two criteria for metabolic syndrome, while 48.7% (n=145) did not. Regarding body mass index (BMI), 22.8% (n=68) of participants had a normal BMI (18.5–22.9 kg/m²), 24.5% (n=73) were classified as overweight (23–24.9 kg/m²), and 52.7% (n=157) were obese (BMI ≥ 25 kg/m²).

Metabolic syndrome and infertility are intricate disorders that can profoundly affect a woman's reproductive health. Recent studies have generated interest in examining the correlation between metabolic syndrome and ovarian function, especially in women with diminished ovarian reserve. This article examines the many aspects of metabolic syndrome and their effects on infertility and reduced ovarian reserve.

Parameters of Metabolic Syndrome: Metabolic syndrome comprises a constellation of interrelated risk factors, including central obesity, insulin resistance, hypertension, and dyslipidaemia. Each characteristic can uniquely influence ovarian function, potentially leading to infertility in women with reduced ovarian reserve.Central obesity, defined by an excess deposition of visceral fat, is a defining characteristic of metabolic syndrome. Adipose tissue releases several adipokines and inflammatory cytokines that might impair ovarian function via diverse routes. Elevated concentrations of adipose tissue-derived hormones such as leptin and diminished levels of adiponectin correlate with compromised ovarian folliculogenesis and diminished oocyte quality. Hyperinsulinemia, frequently seen in insulin-resistant conditions, can impair ovarian steroidogenesis and follicular maturation. Insulin resistance may also play a role in hyperandrogenism, a prevalent characteristic of polycystic ovary syndrome (PCOS), which is strongly associated with infertility and diminished ovarian reserve.Hypertension is an additional element of metabolic syndrome that might negatively impact ovarian function. Chronic hypertension can hinder ovarian blood flow, resulting in diminished ovarian perfusion and impaired follicular growth. Moreover, hypertension-induced vascular dysfunction might disturb the intricate equilibrium of ovarian hormones, hence intensifying infertility in women with diminished ovarian reserve. Dyslipidemia denotes aberrant lipid levels, commonly marked by raised triglycerides, increased low-density lipoprotein (LDL) cholesterol, and/or reduced high-density lipoprotein (HDL) cholesterol. Oxidative stress and inflammation caused by dyslipidemia might harm ovarian tissue and hinder follicular growth and maturation. Elevated LDL cholesterol levels have been linked to reduced ovarian reserve, underscoring the possible influence of dyslipidemia on reproductive results. The relationship between metabolic syndrome parameters and ovarian function is essential for enhancing fertility treatment approaches in women with low ovarian reserve. Modifying lifestyle and utilizing pharmacotherapy to address underlying metabolic disturbances may enhance ovarian responsiveness and improve fertility outcomes in this population.

This is a comparison of our findings with current literature to assess the Generalizability of the results.
Among the 298 study participants, the majority (84.6%) were aged 20 to 30 years, while the remainder (15.4%) were aged 31 to 40 years. The majority of study participants identified as Hindu (65.4%), while the remainder identified as Muslim (34.6%).In a comparable study conducted by Ishak A et al [14], the youngest participant was 18 years old, while the oldest was 41 years old, yielding a mean age of 29.6 years ± 4.9. In a comparable study conducted by Delavar MA et al[15], the mean ± standard deviation (SD) of the participants' age was 40.2 (± 0.2) years, while the median age was 40.0 years. A majority of the study participants, specifically 79.5%, experienced less than 3 years of infertility, while 18.5% had a duration of infertility ranging from 4 to 6 years.

Criteria for Metabolic Syndrome (NCEP ATP III) and Body Mass Index (BMI)
Seventy percent of study participants exhibited a waist circumference of 80 cm or above, whereas thirty percent had a waist circumference of less than 80 cm.
64.1% of patients exhibited fasting triglyceride levels of 150 mg/dL or more, whereas 35.9% presented levels below 150 mg/dL.52% of study participants had fasting HDL values of 50 mg/dL or higher, whereas 48% had fasting HDL levels below 50 mg/dL.80.5% of study participants exhibited fasting blood glucose values below 100 mg/dL, whereas only 19.5% had fasting blood glucose levels at or over 100 mg/dL.63.4% of study participants exhibited a systolic blood pressure below 130 mm Hg, while 36.6% demonstrated a systolic blood pressure of 130 mm Hg or higher. 71.8% exhibited a diastolic blood pressure of less than 85 mm Hg, whereas 28.2% demonstrated a diastolic blood pressure of 85 mm Hg or above.

 
The American Diabetes Association (ADA) thresholds were employed to categorize participants as non-diabetic, pre diabetic, or diabetic. Approximately 61.1% of patients exhibited HbA1c readings below 5.7%, categorizing them as non-diabetics. Approximately 24.8% of study participants had HbA1c values between 5.7% and 6.4%, so categorizing them as pre-diabetic. 14.1 %   of subjects had HbA1c levels of 6.5% or higher and were categorized as diabetics. In our study, it was observed that around fifty-two point eight percent (52.7%) of the subjects had a BMI ≥ 25 kg/m² and were classified as obese. The remaining half was nearly evenly divided between the overweight category (24.5%) and the normal category (22.8%) of BMI.

 
In a similar study conducted by Ishak A et al [14], the following measurements were recorded: waist circumference (88.7), BMI (32.1), fasting blood glucose (5.7), triglycerides (1.9), systolic blood pressure (127.6), diastolic blood pressure (83.5), and HDL cholesterol (1.3). In a separate study conducted by Delavar MA et al [15], the mean (±SD) waist circumference was 96.9 (±11.7) cm, whereas the median waist circumference was 98.00 cm. Of the 944 women, 723 (76.6%) exhibited a waist circumference exceeding 88 cm. Women with metabolic syndrome exhibited markedly reduced HDL-cholesterol levels (p≤0.0001), elevated total cholesterol levels (p≤0.0001), increased triglyceride levels (p≤0.0001), and heightened glucose levels (p≤0.0001). These women exhibited markedly elevated body mass indexes (p≤0.0001), waist circumferences (p≤0.0001), systolic blood pressures (p≤0.0001), and diastolic blood pressures (p≤0.0001). Nevertheless, there was no statistically significant difference in mean LDL-cholesterol levels between women with and without metabolic syndrome.

Metabolic Syndrome

Our investigation revealed that the prevalence of metabolic syndrome, as per modified NCEP ATP III criteria, among females with diminished ovarian reserve was 36.9%. Among females with primary infertility, 36.9% were diagnosed with metabolic syndrome. In a comparable study conducted by Ishak A et al, a total of 99 patients were recruited and analyzed. The prevalence of MetS in this study was 43 (43.4%) based on IDF criteria.In a separate study conducted by Delavar MA et al [62], the overall prevalence of metabolic syndrome among urban women aged 30-50 in Babol was found to be 31.0% according to the ATPIII criteria

In conclusion, current research provides significant insights into the efficacy of dietary involvements in managing IBS symptoms and improving QoL. The low FODMAP diet emerges as a promising therapeutic option, offering significant symptom relief and enhancing Subjects' overall well-being. However, the implementation of dietary interventions in clinical practice requires careful consideration of individual patient preferences, nutritional needs, and longstanding sustainability. Healthcare providers should adopt a multidisciplinary approach to IBS management, incorporating dietary counseling, symptom monitoring, and psychosocial support to optimize treatment outcomes and improve Subjects' QoL.

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