The University Teaching Hospital of Bogodogo (UTH-B) is located in the city of Ouagadougou, the political and administrative capital of Burkina Faso, which was our field of study and the CHUB, our study setting.

This was a prospective descriptive and analytical cross-sectional study from December 15, 2022 to June 15, 2023.

The study population consisted of all couples who participated in the campaign.

The patients included in our sample met the following criteria:

(1) Having under 40 years of age;

(2) Having participated in the screening campaign for medically assisted reproduction in the UTH-B obstetrics and reproductive medicine department;

(3) Having completed their biological work-up (FSH, LH, AMH, Oestradiol….);

(4) having carried out 2 previous biological assessments with an interval of at least 6 months and concordant;

(5) Having given their verbal consent over the telephone to participate in the study.

A literature review from August 1 to October 302 with a questionnaire and a telephone interview from November 1 to 15 were used to collect the data.

The following variables were collected on the data collection forms:

(1) Socio-demographic characteristics: age, profession, marital status, level of education, place of origin;

(2) Gynaeco-obstetrical, medical and surgical history;

(3) Eating and physical habits;

(4) Clinical examination: blood pressure, Body mass index (BMI);

(5) Results of paraclinical examinations: hormone assessment (FSH, LH, estradiol, AMH, TSH prolactin…), ultrasound, hysterosalpingography (HSG), diagnostic hysteroscopy.

The dependent variable or variable of interest was premature ovarian failure, a qualitative binary variable (Yes/No). The independent variables were socio-demographic and lifestyle variables, and clinical and paraclinical variables.

A data entry mask was created and the data collected was entered progressively on a computer using Epi info software version 7.2.2.6. The manually collected data were entered, processed and analyzed on a computer, using Word, Excel version 2016 and Epi info version 7.2.5.0.

Data analysis involved 3 levels:

(1) Descriptive analysis: involved calculating percentages for qualitative variables and measures of central tendency (mean, median) and dispersion (standard deviation, minimum, maximum) for quantitative variables.

(2) Univariate analysis: the Chi-square test was used to compare percentages; when the conditions for applying the test were not met, Fisher’s exact test was used. The Student’s t-test was used to compare means.

(3) Multivariate analysis using logistic regression.

(4) A p threshold of less than 0.05 was considered significant; the Odds ratio was used as a measure of association with a 95% confidence interval.

1. Frequency

A total of 1,200 women of all ages took part in the assisted reproduction campaign at CHU-B. Of these, 53 women were diagnosed with premature ovarian failure, representing a frequency of 4.42%.

2. Socio-Demographic and Lifestyle Characteristics

A total of 261 women under 40 years of age were included. The mean age of women with ovarian insufficiency was 34.64 ± 3.97 years, with extremes ranging from 24 to 39 years. The level of education was high in 206 women from the general population, 41 of whom (19.90%) had been screened for POI. In the study population, 242 women were married, including 50 women screened for POI, i.e. 20.66%, and 66 consumed alcohol, including 17 screened for POI, i.e. 25.76% ( Table 1 ).

3. Clinical (History and Symptoms) and Paraclinical Data

In our study population, 145 women had an irregular menstrual cycle, including 48 with premature ovarian failure (33.10%). One hundred and thirty-four (134) women had dysmenorrhea, 23 of whom (17.16%) had been diagnosed with POI. Hypofertility was primary in 165 women, of whom 33 (20%) were screened for POI. Endometriosis was present in 18 women from the general population, including 3 with premature ovarian failure (16.66%). Diabetes was present in 7 women from the general population, including 3 women (42.86%) with premature ovarian failure. IVF was performed in 20 women from the general population, including 9 with premature ovarian failure (45%). Myomectomy was performed on 26 women from the general population, including 6 (23.08%) with premature ovarian failure ( Table 2 ).

Dyspareunia was present in 55 women, including 53 with premature ovarian failure (96.36%). AMH levels were low in 177 women from the general population and in all women with PCOI ( Table 3 ).

1. Univariate Analysis

In our study, the variables associated with premature ovarian failure in univariate analysis ( Table 4 ) were: history of gemellity (p = 0.002); history of pregnancy (p = 0.049); irregularity of menstrual cycle (p = 0.000), age over 30 (p = 0.068), diabetes (p = 0.018), oophorectomy (p = 0.089).

2. Multivariate Analysis

After uni-variate analysis, variables with p-values less than or equal to 0.20 were retained for multivariate analysis, and those with p-values less than 0.05 were significant.

Factors associated with POI were: cycle irregularity (p = 0.001); previous twin (p = 0.001); previous pregnancy (p = 0.047).

Our study had certain limitations and biases, notably the retrospective nature of the study, where some data were incomplete and some patients were unreachable, and the small sample size. In addition, the study was carried out in Ouagadougou, the capital of Burkina Faso, which may reduce the participation of women living in rural areas, thus compromising the extrapolation of results to the entire population of Burkina Faso. Notwithstanding these limitations and biases, we were able to compare our results with the literature.

The frequency of premature ovarian failure in our study was 4.4%. Our prevalence is higher than that of Coulibaly et al. (2.4%), Yeo J H et al. (3.1%), Mishra G D et al. (2%), Jambarsang S et al. (3%), Rostami Dovom M (3.5%), Lim J M (2.4%) [12] [15] - [18] . This discrepancy could be explained by the small size of our sample and our reduced study period; the prevalence of POI would have been overestimated.

1. Age

The mean age of our patients with premature ovarian failure was 34.64 years. Our results are similar to those of Coulibaly et al., Sato et al. and Zhu D, who found a mean age of 32.8, 32.9 and 33.52 years respectively [7] [19] - [21] . This average age could be explained in our context by late consultations due to financial or cultural constraints (traditional treatment).

2. Level of Education

In our study, the highest level of education was represented by 41 of the 53 women with POI. This is explained by the fact that the campaign took place in Ouagadougou, where the majority of vocational schools and universities were located. Also, the campaign was well publicized, and women with a high level of education had easy access to information. This is confirmed by certain studies which show that women with a high level of education are generally more aware of the symptoms, which may influence the earliness of diagnosis [4] [22] .

1. Duration and Type of Hypofertility

The average duration of hypofertility was 6.70 years. Our duration is shorter than that of Coulibaly et al. and longer than that of Zhu D et al. who reported a mean duration of 8.5 and 3.47 years respectively [7] [21] . Hypofertility was primary in 62.26% of our patients. Our rate is lower than that of Coulibaly et al. which was 72.55%, and higher than that of Zhu D et al. which was 32.25% [21] .

Our results are based on patients with premature ovarian failure and Coulibaly’s [7] . On the general population, hence the difference. The difference between our results and those of Zhu is explained by the delay in consultation due to financial difficulties and the fact that the problem of fertility remains a taboo subject in our context. In addition, the fact that our patients were recruited in the context of a fertility campaign where the cost of procedures was lower than in private structures could justify this. Could this difference also be an expression of renewed hope for couples with a long history of infertility?

2. Duration of Menarche

The average age of menarche in our study was 14.03 ± 1.60 years, higher than that of Bompoula et al. who reported an average age of 12.2 ± 2.2 [23] . This difference may be explained by nutritional conditions and climate, which can influence pubertal development through hormonal and metabolic mechanisms.

3. Dyspareunia and Hot Flushes

In our study, dyspareunia and hot flushes were major symptoms in 96.30% of cases. Our results corroborate those of Sullivan et al., Gupta et al., Moustaki M. et al., who found these two symptoms to be among the signs presented by women screened for POI [4] [22] [24] [25] . These signs are part of the classic signs of menopause linked to estrogen deficiency. Estrogen deficiency leads to vulvovaginal atrophy through reduced vascularization and thickness of the vaginal epithelium. This deficiency can also lead to dysregulation of the hypothalamus, causing instability of the thermal regulation threshold, leading to sudden vasodilatation and increased sweating. These symptoms underline the importance of hormone replacement therapy for patients with POI [27] .

1. Menstrual Cycle Irregularity

In our study having an irregular mentstrual cycle increased the risk of having premature ovarian failure 10.35-fold and this was statistically significant with p value = 0.001. Our results corroborate those of Bertone-Johnson E R et al. in 2018 who reported that cycle irregularity increased the risk of having POI 6.3-fold and this was statistically significant with p < 0.001. Similarly, Whitcomb B W et al in 2018 found that women with regular cycles had a lower risk than women with irregular cycles (OR = 0.51; p-value = 0.0001) [26] [27] . Indeed, irregular menstrual cycles, often associated with periods of amenorrhea (absence of menses), may indicate impaired ovarian function. In addition, irregularity may be a sign of fluctuations in the production of hormones, particularly estrogen and progesterone, which are necessary for the proper functioning of cycles. This may reflect a reduced ovarian reserve or ovarian dysfunction. It is, therefore important to monitor irregular menstrual cycles and consult a doctor for assessment, especially if symptoms occur.

2. Twin Pregnancy History

Twin pregnancy increases the risk of premature ovarian failure and this is statistically significant with an OR = 3.55; p-value = 0.0013 Mishra G D et al. in 2019 reported that twin pregnancy history was associated with the risk of developing POI [12] . One of the main reasons that may link the outcome of a twin pregnancy to the accumulated risk of POI is genetic predisposition. Women with a genetic predisposition to hyperovulation (releasing multiple oocytes) may have a lower long-term ovarian reserve. In fact, multiple ovulation consumes oocytes more rapidly, which could accelerate the depletion of ovarian reserve and therefore increase the risk of premature ovarian failure (POF). If this tendency is passed on genetically to the daughter, she could also develop a reduced ovarian reserve earlier than average.

3. Previous Pregnancy

The absence of previous pregnancy is associated with a statistically significant risk of premature ovarian failure, with OR = 1.4732; p-value = 0.047.

In the literature, some authors have found that nulliparity is statistically associated with a risk of premature ovarian failure [14] [27] . This may be linked to the protective effects of hormones produced during pregnancy on ovarian function. These hormones may delay follicular exhaustion or limit oxidative damage to the ovaries.

The results of our study may be explained by the fact that POI leads to infertility, reducing the chances of pregnancy. Primary hypofertility (which accounts for 62.26% of our patients screened for POI) could mean that POI leads to pregnancy failure, rather than the reverse. Lack of pregnancy could also be linked to delays in diagnosis or limited access to care.