Prevalence of the Infertility Among Couples in Ouagadougou (Burkina Faso): a Population-based Survey

Study Design and Concepts Definition

This study was a cross-sectional study with prospective data collection on households in Ouagadougou (Burkina Faso), from March to May 2014. We considered as primary infertility, couples who had never had a live birth to avoid the bias of misreporting of first semester pregnancies or voluntary terminations of pregnancies. The desire of a child was assumed to be a proxy of regular unprotected sexual activities without any contraceptive use. The secondary infertility prevalence was calculated as the primary one, but considering only couples who had already born a child.

Sample Size and Sampling

We selected a multiple step systematic random cluster sample with a proportional probability to the cluster size. To determine the sample size, we considered the formula for sample size calculation in prevalence surveys, a 95% confidence interval, an alpha error of 5% and an infertility prevalence of 15% [8]. We estimated the cluster effect at 2 to determine the final sample size of 461 households to which we added 5% (total sample size was 480) to address potential non responses. The 480 households were distributed into 40 enumeration areas or clusters considering that we surveyed 12 households per cluster. Usually, a cluster should include from 12 to 30 units. The smaller the number of units in a cluster the higher the number of clusters to be surveyed and the better the quality of the data.

Each investigator had to select 12 households plus 3 (for replacement purpose) per cluster. Then, we divided the total number of eligible households in each cluster by 15 to determine the pace of the sample in that cluster.

We enumerated during a pre-survey all eligible clusters, considering some selection criteria such as living in Ouagadougou since at least 12 months, in the same house with his/her partner, being between 18 and 55 years for men and between 18 and 45 years for women and willing to participate to the survey. Then each investigator had to randomly select a number between one and the pace to select the first and the subsequent households to be surveyed. Once we had the 15 households per cluster, we proceeded to the selection of the 3 replacement households, considering a pace of 5 (15/3) and following the same procedure.

We excluded all couples in which one partner was unable to bear a child because of known causes such as hysterectomy, vasectomy, tubal ligation, sexual impotence or castration happening as a complication of a traffic or other incident, or a history of prostate cancer or cancer therapy (chemo and radiotherapy).The collected variables included basic socio-demographic characteristics, data on the couple infertility, the medical and/or obstetric history and the couples’ lifestyle and sexual activities.

Data Analysis

To analyze the data, we ran a univariate analysis to describe our sample population, determining parameters such as means (continuous variables) and proportions (categorical variables) with a 95% confidence interval. In some table, some variables data were not applicable to both sexes like testicular trauma that was reported only for men. In these cases, we juste mentioned the note “not applicable” (N/A) in the corresponding cells. We did not report (N/R) smoking data in women because they were inconsistently collected with a lot of missing data. To avoid information bias (e.g. underreporting of polygamous men who may forget that they have an infertility issue, because they born children with other wives), we calculated infertility prevalence considering separately the responses of the men and women to determine what we named the “participant-reported infertility” as opposed to the “medically-diagnosed infertility”. The primary participant-reported infertility prevalence among women was calculated as the number of childbearing age women who have never born a child and who had been seeking a child for more than 12 months divided by the number of surveyed women which represented also our total sample size. The primary medically-diagnosed infertility prevalence among women was calculated as the number of the primary participant-reported infertile women who’s infertility had been confirmed by a physician’s investigation, divided by the number of surveyed women. The same method was applied to determine males’ primary participant-reported infertility prevalence. The male and female secondary infertility prevalence were calculated in the same way considering participant-reported and medically-diagnosed infertility. However, in the numerator, we considered as secondary-infertile men or women those men or women who have been seeking again a child for more than 12 months after having already born at list one child.

We further defined as male-related, female-related and dual-factor infertility all couples ‘infertility with the source/cause in men, women or both partners simultaneously. In all these prevalence calculation, the denominator was the total sample size of 480 participants.

We built logistic multivariate models separately for male and female partners, to explore risk factors for infertility. The dependent variable was infertility inside the couple (yes or no). The dependent variable combines all type of participant-reported infertility including primary and secondary, male and female-related infertility. We first run a bivariate analysis to identify all factors associated with infertility at a p-value of 20% that we included in an initial regression model. That model included the following independent variables: marital regime (poly or monogamous), religion, income, smoking status, duration in smoking, number of cigarettes per year, history of sexually transmitted disease, sexual activity disorders, knowledge of the woman’s period recurrence, past pregnancies’outcome. Further, using the backward step selection strategy, we selected our final model at a 5% p-value level. Though the tests were not significant, we forced some variables into the models due to their known relation with the infertility as reported in the litterature. Instances of such variables include sexually transmitted infection, male sexual activity disorders and the knowledge of the partner’s period.

Ethics

The study protocol obtained the Burkina Faso national ethic committee’s clearance and the protocol was implemented according to the Helsinki declaration. All participants were included after they have signed an informed consent form.

Participants’ Baseline Characteristics (Table 1)

To recruit the households, we randomly selected 40 out of 1223 clusters including 172 673 households and 1 247 699 people as of 2006 enumeration data (the most recent one). The 40 clusters included 9 358 households and 44 387 people that we examined for eligibility.

Overall 2324 households were confirmed eligible. We included 480 households interviewing the man and the wife in each household. The mean age was 38.6 (95% CI: 37.9 - 39.3) and 30.8 (95% CI: 30.2; 31.4) years for male and female participants respectively (Table 1). In the male group 81% were married and 95% of the married were living under monogamy regime; 19.5% had been to high school or to university; 81.5% lived with a maximum of $172.5 per month. In the female group these statistics were similar except for education and income where 9.8% had gone to high school or university and100% had a maximum income of $172.5 per month.

Infertile men were older, less educated, with smaller income and fewer under monogamy regime compared to the men from the general population. Infertile women presented similar characteristics but were younger with the same income than the general women population.

The Participants’ Clinical History and Infertility Prevalence (Table 2)

Among the participants, 91.2% (95% CI: 88.3; 93.5) and 90.3% (95% CI 87.3; 92.7) of men and women respectively had children. Ten per cent (95% CI: 7.6; 13.1) of men and 10.9% (95% CI: 8.4; 14.1) women were seeking a child. The men have been seeking a child for a mean duration of 11.2 years and the women for 11.3 years. The participant-reported infertility prevalence was 9.3% (95% CI: 7.0; 12.2) and 10.4% (95% CI: 7.9; 13.5) for men and women respectively. The primary and secondary infertility prevalence rates were 4.8% (95% CI: 3.2; 7.2) and 4.4% (95% CI: 2.9; 6.7) % respectively for men and 6.8% (95% CI: 4.8; 9.4) and 3.6% (95% CI: 2.2; 5.7) for women. Primary infertility concerned 52.3% (95% CI: 37.2; 67.0) and 65.3% (95% CI: 50.6; 77.6) of all infertile men and women respectively. Among the participant-reported infertile couples, 73.7% (95% CI: 47.6; 89.6) and 51.8% (95% CI: 32.5; 70.7) of the men and women respectively had a medical diagnosis of infertility. The prevalence of medically-diagnosed infertility was 2.9% (95% CI: 1.7; 4.9); 1.0% (95% CI 0.4; 2.5) diagnosed as male-related infertility and 1.3% (95% CI: 0.6; 2.8) as female-related, and 0.6% (95% CI 0.2; 1.9) attributed to both males and females. Considering only medically-diagnosed infertility, the proportion of male and female-related infertility represented 35.7% (95% CI: 13.7; 66.0) and 42.9% (95% CI: 18.3; 71.6) of the cases respectively and the dual-factor-related infertility 21.4% (95% CI: 5.9; 54.0).

Description of the Infertility Risk Factors (Table 3)

The clinical history of the participants (Table 3) showed that sexually transmitted diseases (STDs) were the most common event in both sexes (15.3% (95%CI:12.3; 18.8) of the men and 26.6% (95%CI:22.8; 30.8) of the woment) with a clear predominance in women., among infertile men, 24.9%, and 10% of infertile women were past or current alcohol drinkers.

More infertile males experienced STDs, testicular trauma, cirrhosis, a family history of infertility and sexual disorders than the general population men. Fifty-four per cent of the infertile men were past or current smokers compared to 36.9% in the general population. 89.6% (95% CI: 76.7; 95.7) of the infertile men had less than four sexual intercourses per month compared to 45.5% (95% CI: 41.1; 50.0) in the general population. None of the infertile men had more than 12 intercourses per month.

In infertile women population, the proportions of ectopic pregnancies, past abortion and still-births were higher than in the general women population. However, there was less history of infertility in the infertile women’s family than in the family of their general population’s counterpart. Among men and women, 17.9% and 25% respectively stated that they knew their partners’ or their own menstrual cycle (in order to know the fertile period). After checking the accuracy of the statement by comparing the answer to the question “what day in the menstrual cycle is the day of ovulation?” to the true answer, 3.3% and 10.4% of men and women respectively did know the correct menstrual cycle.

Risk Factors Analysis (Table 4)

The bivariate analysis showed that the polygamous couples were significantly more at risk of infertility than the monogamous ones with an unadjusted odd ratio (UOR) of 3.9 (95% CI: 1.5; 10.0) and 3.6 (95% CI: 1.3; 9.6) for women and men respectively. Stillbirth and abortion or miscarriages were significant risk factors for couple infertility at both unadjusted and adjusted analysis for both female and male partners with adjusted ORs of 13.6(95% CI: 3.81; 48.4) and 14.4 (95% CI: 3.9; 52.9) respectively. Being a past smoker or having a history of STD was also significant risk factors for men.

The Prevalence of Infertility in Ouagadougou (Burkina Faso)

In Ouagadougou (Burkina Faso) 9.3 and 10.4% of men and women respectively were found infertile. In our study the infertile males and females’ mean age was 38.7 (95% CI:36.7; 40.7) and 29.9 (95% CI:28.0; 31.7) years respectively. This was comparable to to two Nigerian studies that found a mean age of 39.1±6.0 for the male [9] and 31.1 years for the female partners [10]. Infertility was concentrated among women aged 25 to 34 in Nigeria [10] like in our study.

It is generally admitted that around 15% of the global population is affected by infertility [8, 9, 11-13]. We found a lower prevalence. However, this global average masks interesting variability according to geographical areas. Another study found a prevalence of 14% (no conception after 2 years of trying) in Aberden [14], 17% in Shropshire [15], 26% in Somerset [16] (no conception after 1 year). A recent review of studies concluded to a median prevalence of 9% in a study reporting results from 25 population surveys [17]. Other studies in the 1990s reported prevalence of 2.2% [16] and 3.5% [14] for unresolved infertility (those who probably underwent medical diagnosis).

Worldwide the prevalence of the primary infertility is between one and five per cent and is estimated at around 3% in developing countries. Highest rates of primary infertility are found in Central Africa [18]. Along the same lines but with an important difference in Africa, a UNDP/UNFPA/WHO/World Bank research between 1980 and 1986 in different African, Asian and Latin-American countries found that infertility rates ranged between 1.1 and 3.6% in the five Asian countries, 1.9% in Brazil, but up to 12% in Africa [18]. In 2010, according to a study compiling data from 277 demographic and reproductive health surveys, the primary infertility was 1.9% (95% CI/ 1.7; 2.2). The prevalence levels in 1990 were 2% (95% CI: 1.9;2.2) for primary infertility and 10.2% (95% CI: 9.3; 11.1) for secondary infertility one. These statistics did not change in 2010 [19]. The ranges spanned from 1.5% (95% CI: 1.2%, 1.8%) in the Latin America/Caribbean region to 2.6% (95% CI: 2.1%, 3.1%) in the North Africa/Middle East region. Within the SSA region, the prevalence varied from 1.0%-1.1% in East and Southern Africa to 2.5% or greater mostly in central SSA. However, this study used the demographic definition of infertility (that considers 5 years without conception). In our study, primary infertility represented 52.3% (95% CI: 37.2; 67.0) and 65.3% (95% CI: 50.6; 77.6) of all infertility cases in men and women respectively. At the contrary of our finding, a hospital-based study realized in Ouagadougou from January 1996 to June 1997 found that secondary infertility cases were predominant (65.6%). We need to find satisfactory explanation to this shift occurring almost 20 years later.

The secondary infertility rate was determined at 10.5% (95% CI: 9.5; 11.7) at the global level and 11.6% (95% CI: 10.6%, 12.6%) in the SSA region [19]. This prevalence is higher than ours. This is probably due to country variability. The levels of secondary infertility ranged between 7.5-15.3% in Thailand and Vietnam and higher at up to 24% in Pakistan [18]. Studies in Benin, Cameroun and Tanzania found a secondary infertility rates between 7% and 33% and up to 35.0% in Nigeria [10].

Regarding the origin of infertility, a meta-analysis of global data showed that infertility related to male factors represented 20-70% of all infertility and 2.5-12% of the general population [8]. The male contribution to all infertility is in the same range in our study (42.9% (18.3; 71.6)). However the prevalence we calculated was lower. In this study that used the WHO clinical definition of infertility like us, male infertility in SSA is estimated between 2.5-4.8% while the all-cause infertility ranged from 12.5%-16%. The highest levels of infertility were in North and West Africa while the rates in Central and East Asia were similar to our findings [8]. Yet in this sixteen-article meta-analysis published in 2015, most of the compiled studies were population-based studies like our work and the SSA’s findings were deemed an underestimate due to underreporting. These results were from different meta-analysis or systematic reviews and data were missing often regarding male or female contribution to infertility. The authors filled the gaps, using the Sharlip method [20] of calculation, which is based on the assumption that in general, in couple infertility, 50% of the cases are related to female factors, 20-30% to male factors and the remaining 20-30% is a combination of both male and female factors. We therefore believe that some of these hypotheses might have not held.

A study in Nigeria [10] found 42.4%, 25.8%, 20.7%, and 11.1%),for male only, female only, both partners and unexplained infertility respectively. Compared to our study, the rates of male and both partners’ contribution looked similar while we had a higher contribution of female partners (42.9% (95% CI: 18.3; 71.6)). We did not identify any unexplained case of infertility, probably because of the small absolute number of the medically-diagnosed cases (n=14). In Teheran, the male factors represented 23.7% and the male-female factor was 19.3% [21].

The Risk Factors of Infertility in Ouagadougou (Burkina Faso)

With respect to the causes of infertility, it is admitted that everywhere, there is a core of about 5% of infertility that is associated to biological (including genetic, endocrinological, and immunological problems) and anatomical factors. The remainder are infertile because of preventable conditions including infections, environmental risk factors and healthcare practices and policies. In this list, reproductive tract infections and particularly STDs play a leading role [4]. In our study, sexually transmitted diseases in the history of infertile men and women represented 22.9 and 29.4% respectively as opposed to 15.3 and 26.6% in the general population. Globally it is estimated that 27-64% of women infertility could be attributed to infectious causes [18]. We found much lower prevalence with regard to the other etiologies of infertility including varicocele and cryptorchidism [11, 22] probably related to underreporting.

The main risk factor was smoking and varicoceles in Teheran [21] and varicoceles and testicular surgery in the United States of America [23]. In our study, 54.2% of infertile men were past or current smokers while among the general population only 36.9% had ever smoked. Our finding is consistent with the proportion of one third of the global population aged over 15 years that smokes [24]. Smoking effect would virtually shift all male semen parameters (count, motility, morphology) away from their normal values and there would be no safe amount of cigarette smoke intake with regard to semen quality [24]. Interestingly, in our study, there were less alcohol drinkers among infertile people.

At the multivariate analysis, we found that having a history of STD and being a past smoker were significant risk factors for male infertility while having a history of abortion or stillbirth were significant risk factors for both males and females. A study in Nigeria identified also recurrent penile discharge (OR 7.8; 95%CI 2.9-21.5), recurrent pain on micturition (OR 2.2; 95%CI: 1.02-4.71, p<0.04) and genital ulcers (OR 8.8; 95%CI 3.7-9.2) as risk factors. Another risk factor for men in that study was a heavy consumption of alcohol and a history of previous induced abortions, vaginal discharge and previous pelvic inflammatory disease for women [25].