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. 2023 Oct 12;18(10):e0291912. doi: 10.1371/journal.pone.0291912

The prevalence of infertility and factors associated with infertility in Ethiopia: Analysis of Ethiopian Demographic and Health Survey (EDHS)

Nanati Legese 1,*, Abera Kenay Tura 2, Kedir Teji Roba 3, Henok Demeke 1
Editor: Mojdeh Banaei4
PMCID: PMC10569515  PMID: 37824486

Abstract

Background

Despite having a high fertility rate, low-resource countries are also home to couples with infertility problems. Although many couples are suffering from the psychological impacts of infertility, its level and determinants are not adequately known. The main objective of this study is to assess the prevalence and factors associated with infertility among couples in Ethiopia using the 2016 Ethiopian Demographic and Health Survey (EDHS) data.

Method

The study employed a cross-sectional study design extracting variables from the 2016 EDHS. The study included all married or cohabitating women aged 15 to 49 years in the Couples Recode (CR) file data set. Weighted samples of 6141 respondents were analyzed. We used Stata 14 software for analyzing the data. The association of selected independent variables with primary, secondary, and total infertility was analyzed using a logistic regression model. We presented the results using an adjusted odds ratio (AOR) with a 95% confidence interval (CI) and a p-value <0.05 as a cut-off point for declaring statistical significance.

Results

The prevalence of infertility in the past 12 months was 24.2% (95% CI: 23.1–25.3%), of which the majority (90.7%) was secondary infertility. Greater than 35 years of age (AOR = 2.45, 95% CI (1.58–3.79)), rural residence (AOR = 1.06, 95% CI (1.01–1.39)), smoking (AOR = 2.29, 95% CI (1.39–3.77)), and <18.5 Body Mass Index (BMI) (AOR = 1.71, 95% CI (1.43–2.04)) were significantly associated with infertility. Conversely, infertility was less likely among women with formal education and better wealth index. Primary infertility was significantly higher among women whose partners drink alcohol (AOR = 1.55; 95% CI 1.06–2.28)) and chew khat (AOR = 1.62; 95% CI (1.12–2.36)). Secondary infertility was significantly higher among women with <18.5 BMI (AOR = 1.59, 95% CI (1.37–1.84)), >30 BMI (AOR = 1.54; 95% CI 1.01–2.35)), and <15 years of age at first birth (AOR = 1.40; 95% CI 1.15–1.69)).

Conclusion

More than one in five couples in Ethiopia has an infertility problem. Both male and female-related factors are associated with infertility. Primary infertility was significantly higher among women whose partner chews khat and drinks alcohol. Secondary infertility was significantly associated with being underweight, obese, smoking, and young age at first birth. Hence, taking action on preventable factors is the most critical treatment approach and will improve the health status of the couples in other ways.

Introduction

Infertility is the failure to achieve a clinical pregnancy after 12 months or more of regular unprotected sexual intercourse [1]. Infertility is classified into primary and secondary based on the presence or absence of previous pregnancy. Primary infertility is the inability to conceive, while secondary infertility is the inability to bear a child after having an earlier birth [2].

Infertility is a critical issue for couples of childbearing age over the world. Fifteen percent of couples around the world are suffering from infertility, in half of which the man is infertile.

In some parts of sub-Saharan Africa, a 15 to 45% prevalence was reported [3–6]. Infertility has significant negative social impacts on the lives of infertile couples and particularly women, being blamed for the problem [7–12].

Although there is a significant concern about the impacts of infertility, there are no comprehensive epidemiological studies about its risk factors in resource-limited countries [13]. Conventionally, factors such as age, obstetrical history, smoking, psychosocial stress, and obesity are indicated as the major risk factors leading to infertility [4, 14–16].

Preclinical and clinical studies identified khat chewing as one factor for male infertility [17–20]. Khat chewing contributes to infertility by affecting spermatogenesis and plasma testosterone concentration [17, 20]. A prospective cross-sectional study on the influence of khat on seminal fluid among 214 male partners of infertile couples in Ethiopia revealed a decreased sperm count, volume, and motility in chronic khat chewers [20, 21].

A growing body of evidence points to a link between obesity or underweight and female infertility. The adipose tissue through the production of leptin, free fatty acids, and cytokines, affect both ovarian and endometrium functions in obese women [22, 23]. On the other hand, being underweight can reduce a woman’s fertility by causing hormone imbalances that affect ovulation and the chance of getting pregnant [24].

In this study, we investigated the prevalence of infertility and analyzed the socio-demographic, behavioral, and reproductive factors associated with infertility in Ethiopia to guide its prevention and treatment. Previous studies focused on women’s socio-demographic factors and failed to identify other factors, including the male partner side [25, 26].

Methods

Study settings and data source

Ethiopia is the second-most populous country in Africa, with one of the highest total fertility rates (4.6 children per woman) [27]. There are nine regional states and two city administrations in the country. EDHS 2016 was a nationally representative study that involved all regions and city administrations. EDHS is a household survey that uses face-to-face interviews of women aged 15 to 49 and men aged 15–59 to collect data from a wide range of demographic, health, fertility, and nutrition tracking and effect evaluation measures. The survey employs stratified, multi-stage, random sampling [27]. The variables for this study were obtained from the Couples Recode (CR file) data set. The CR data set contains data for married or living together couples who both declared that they are married (living together) and had completed individual interviews [27]. The study sample involves all married or cohabitating women aged 15–49 years.

Description of variables

Dependent variables

Dependent variables were constructed based on their definition in this study (Table 1). Primary infertility is women who have been married for more than 12 months, who have had regular sexual intercourse without using contraception, and who have never conceived.

Table 1. Construction of dependent variables for infertility (EDHS 2016).
Variable name in the EDHS Label in the EDHS Remark
Duration of a relationship more than 12 months v852a How long ago first had sex with your most recent partner (in months) `
Had regular sexual intercourse in the past 12 months v853a Times in the last 12 months had sex with the most recent partner More than 78 times**
No contraceptive use in the past 12 months v361 Pattern of contraceptive use
No birth in the past 12 months v222 Last birth to interview in months
Currently not pregnant v213 Currently pregnant
Ever had given birth v201 Total number of children ever born
Never conceived v228, v201 v228 (Ever had terminated pregnancy), v201(Ever had given birth) Never conceived: Never had terminated pregnancy and never had given birth
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**Regular sexual intercourse was defined differently in several studies. It was reported that 4 to 9 times a month [28], 54 times a year [29], and 78 times [30, 31]. In the present study, more than 78 times were taken as regular sexual intercourse since it was reported specific to achieving conception.

Secondary infertility is women who have been married for more than 12 months, who have had regular sexual intercourse without using contraception, and who have at least one prior birth (EDHS 2016). We categorized women fulfilling either of the infertility definition under total infertility.

Independent variables

Wealth index: The wealth index is a composite measure of a household’s cumulative living standard. In the EDHS, households are given wealth index scores based on the number and kinds of consumer goods they own, ranging from a television to a bicycle or car, in addition to housing characteristics such as the source of drinking water, toilet facilities, and flooring materials. These scores are derived using principal component analysis. National wealth quintiles are compiled by assigning the household score to each usual household member, ranking each person in the household population by her or his score, and then dividing the distribution into five equal categories (poorest, poorer, middle, richer, and richest).

Education level attended: This variable indicates the level of education in the following categories; none, primary (grade 1 to 8), secondary (grade 9 to 12), and more than secondary (diploma or higher).

Ever had terminated pregnancy: This variable is if the respondent ever had a pregnancy that terminated in a miscarriage, abortion, or stillbirth (a pregnancy that did not result a live birth).

Last birth a cesarean section: This variable indicates if the last child was born by cesarean section. The base of this variable is those respondents who have had one or more births in the five years preceding the survey.

Age at first birth: The base of this variable is respondents who have had one or more births intending to find out the effect of teenage pregnancy on infertility.

Body mass index (BMI): Is defined as a woman’s weight in kilograms divided by the square of her height in meters (W/H2). The result was then categorized based on the classification of Centers for Disease Control and Prevention (CDC), <18.5 (underweight range), 18.5 to <25 (healthy weight range), 25 to <30 (overweight range), and 30 or higher (obesity range) [32].

Use of cigarettes or tobacco products: This variable includes the use of cigarettes or tobacco products. The type of tobacco includes any pipe full of tobacco, chewing tobacco, snuff by nose, kreteks, cheroots or cigarillos, water pipe, snuff by mouth, betel quid with tobacco, and others.

Khat chewing: this variable includes chewing fresh or dried khat leaf regularly and typically within one month before the data collection period.

Alcohol drinking: this variable includes using any traditional or modern alcohol regularly and typically within one month before the data collection period.

Data processing and management

We used STATA software version 14 for data processing and analysis. Before any statistical analysis, we weighted the data using sampling weight, primary sampling unit, and strata to restore the survey’s representativeness. To describe the study population, we used cross-tabulations and summary statistics.

We performed a chi-square test to check a bivariate association between infertility and each independent variable. We included all variables with a p-value <0.25 in the multiple logistic regression models. We checked the model’s goodness of fit by using Hosmer-Lemeshow statistics. We analyzed Receiver Operating Characteristics (ROC) to evaluate the predicting ability of the model (model accuracy). We presented the results using an adjusted odds ratio (AOR) with a 95% confidence interval (CI) and a p-value <0.05 as a cut-off point for declaring statistical significance.

Ethical considerations

The Ethiopian Health and Nutrition Research Institute (EHNRI) Review Board, the National Research Ethics Review Committee (NRERC), the Institutional Review Board of ICF International, and the CDC (USA) made the ethical approval of the 2016 EDHS [33]. Moreover, we accessed the data from the DHS website (http://www.measuredhs.com) with permission on Mar 06, 2020. The accessed data was used for the registered research only and treated as confidential.

Results

Characteristics of respondents

Socio-demographic characteristics

This study analyzed a total of 6141 couples in the 2016 EDHS. The mean age of respondents was 30.4 (±SD7.8). The majorities of the respondents live in rural areas (85.2%), in the Oromia region (40.1%), and follow orthodox religion (41.2%). Sixty-one percent of women had no formal education. On the other hand, more than half of the women (51.4%) had no occupation (Table 2).

Table 2. Socio-demographic, behavioral, and reproductive characteristics of married women in Ethiopia, 2016 (n = 6141).
Characteristics Frequency Weighted percentage
Age    
     <20 373 5.8
    20–35 4187 68.2
    >35 1581 26.0
Residence
    Urban 1393 14.8
    Rural 4748 85.2
Region
    Tigray 594 5.7
    Afar 357 0.7
    Amhara 880 25.1
    Oromia 959 40.1
    Somali 499 2.5
    Benishangul 562 1.1
    SNNPR 857 20.9
    Gambela 332 0.2
    Harari 325 0.2
    Addis Ababa 405 3.1
    Dire Dawa 371 0.5
Religion
    Orthodox 2386 41.2
    Muslim 2508 33.5
    Protestant 1140 22.9
    Catholic 39 0.9
    Other 68 1.4
Woman’s education level
    No education 3578 61.1
    Primary 1774 29.4
    Secondary 481 6.0
    More than secondary 308 3.5
Husband’s education level
    No education 2487 42.9
    Primary 2367 41.4
    Secondary 674 8.9
    More than secondary 613 6.8
Wealth index
    Poorest 1575 17.7
    Poorer 1040 21.2
    Middle 955 20.6
    Richer 953 20.5
    Richest 1618 20.0
Occupation
    Not working 3208 51.4
    Agricultural employee 1329 24.1
    Sales 831 13.1
    Skilled manual 224 3.6
    Services 140 2.7
    Professional/managerial 161 2.2
    Others 248 2.9
BMI    
    <18.5 1237 19.1
    18.5-<25 4054 73.3
    25-<30 525 6.3
    > = 30 143 1.4
Respondent smokes cigarettes/tobacco 112 0.9
Husband smokes cigarettes/tobacco 717 7.3
Respondent drinks alcohol 2093 35.2
Husband drinks alcohol 2723 46.9
Respondent chews khat 744 14.3
Husband chews khat 2231 32.2
Age at first sexual intercourse    
    <15 2592 44.7
    15–19 2537 39.8
    20–25 922 14.3
    >25 90 1.2
Age at first birth (n = 5584)    
    < = 15 895 16.7
    15–19 2745 50.7
    20–25 1681 28.9
    25–30 211 3.2
    >30 52 0.6
Ever use of contraceptive    
    Ever used 3436 60.8
    Never used 2705 39.2
Respondent circumcised (n = 2826) 2144 77.6
Last birth with caesarian section (n = 4335) 139 2
Ever had terminated pregnancy 668 10.2
Couple’s desire for children    
    Both want same 2577 41.1
    Husband wants more 1564 24.2
    Husband wants fewer 401 6.5
    Don’t know 1586 28.2
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SNNPR, Southern Nations, Nationalities, and People’s Region BMI, Body Mass Index

Behavioral characteristics

Nineteen percent of the women had less than 18.5 BMI. Around 0.9% of women and 7% of their partners smoke cigarettes or tobacco products. On the other hand, 14.3% of the women and 32.2% of their partners chews khat (Table 2).

Reproductive characteristics

The duration of the relationship of most of the couples (75%) was more than six years, and more than one-third (39%) had never used contraception. Nearly half (50.7%) of the women had their first birth in the 15–19 age group. On the other hand, 10.2% of the women have ever-terminated pregnancies (Table 2).

Prevalence of infertility

A total of 1487 women (24.2%; 95% CI 23.1–25.3) had infertility problems, of which the majorities were secondary (90.7%). Secondary infertility was more prevalent in the oldest age group (>35years) (16.5%), in rural residents (20.8%), in the Afar region (32.3%), in women with no formal education (23.9%), and in the poorest (25.5%). On the contrary, primary infertility was highest in the young age group (<20) (8.8%), in urban residents (3.5%), and in more educated women (4.1%) (Table 3).

Table 3. Socio-demographic and behavioral characteristics of women with infertility in Ethiopia, 2016 (n = 6141).

Total infertility Primary infertility Secondary infertility
Total prevalence 24.2%, 95% CI (23.1–25.3) 2.3%, 95% CI (1.9–2.6%) 21.9%, 95% CI (20.9–23%)
Characteristics N No (%) No (%) No (%)
Age
    <20 373 61(12.9) 35(8.8) 26(4.1)
    20–35 4187 181(12.3) 92(1.3) 769(15.7)
    >35 1581 291(16.5) 11(0.9) 554(33.3)
Place of residence  
    Urban 1393 271(16.6) 57(3.5) 214(13.1)
    Rural 4748 1216(22.0) 81(1.3) 1135(20.8)
Region  
    Tigray 594 140(22.0) 11(2.2) 129(19.8)
    Afar 357 124(35.1) 11(2.8) 113(32.3)
    Amhara 880 168(19.0) 19(2.3) 149(16.6)
    Oromia 959 213(22.2) 12(1.3) 201(20.9)
    Somali 499 132(24.6) 9(1.8) 123(22.8)
    Benishangul 562 179(31.4) 14(2.8) 165(28.6)
    SNNPR 857 177(21.1) 5(0.6) 172(20.4)
    Gambela 332 90(24.3) 11(0.0) 79(21.5)
    Harari 325 74(21.7) 12(3.5) 62(18.1)
    Addis Ababa 405 69(16.4) 20(4.4) 49(12.0)
    Dire Dawa 371 121(32.7) 14(3.7) 107(29.0)
Religion  
    Orthodox 2386 517(20.1) 63(2.1) 454(18.1)
    Catholic 39 6(15.6) 0(0.0) 6(15.6)
    Protestant 1140 275(22.3) 20(1.2) 255(21.1)
    Muslim 2508 669(22.2) 55(1.4) 614(20.8)
    Other 68 20(37.7) 0(0.0) 20(37.7)
Education level  
    No education 3578 1021(24.8) 43(0.9) 978(23.9)
    Primary 1774 338(16.7) 54(2.4) 284(14.3)
    Secondary 481 79(11.7) 23(3.1) 56(8.6)
    Higher 308 49(13.7) 18(4.1) 31(9.6)
Wealth index
    Poorest 1575 491(26.1) 24(0.7) 467(25.5)
    Poorer 1040 257(20.3) 18(1.2) 239(19.1)
    Middle 955 212(20.4) 15(1.6) 197(18.8)
    Richer 953 204(20.3) 20(1.6) 184(18.7)
    Richest 1618 323(19.7) 61(2.9) 262(16.8)
BMI
    18.5-<25 4054 899(19.6) 86(1.6) 813(18.0)
    <18.5 1237 406(29.5) 31(1.7) 375(27.8)
    25-<30 525 105(16.4) 16(1.2) 89(15.2)
    > = 30 143 34(20.1) 1(0.5) 33(19.6)
Respondents smoke cigarettes/tobacco 112 44(21.2) 1(0.0) 43(21.1)
Husband smokes cigarettes/tobacco 717 214(24.5) 15(2.1) 199(22.4)
Respondent drinks alcohol 2093 472(21.3) 53(2.3) 419(19.0)
Husband drinks alcohol 2723 612(20.4) 71(1.9) 541(18.5)
Respondent chews khat 744 202(24.1) 20(2.3) 182(21.8)
Husband chews khat 2231 533(20.3) 64(2.2) 469(18.1)
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Model fitness tests

The Hosmer-Lemeshow Test’s Prob > chi2 results were 0.99, 0.82, and 0.29 for the outcome variables (primary, secondary, and total infertility), respectively. Besides, the ROC test’s areas were 0.81, 0.83, and 0.82 for primary, secondary, and total infertility, respectively. Hence, the goodness of fit tests indicated that the model assumed is correctly specified.

Factors associated with infertility

In the binary regression, the age of women, place of residence, education level, wealth index, BMI, smoking (both partners), drinking alcohol (both partners), and khat chewing (women only) were significantly associated with infertility. Of the reproductive characteristics, the previous way of delivery had a significant association with infertility. In the multiple logistic regressions, greater than 35 years of age (AOR = 2.65), rural residence (AOR = 1.06), smoking (AOR = 2.24), and less than 18.5 BMI (AOR = 1.70) remained significantly associated with infertility (Table 4).

Table 4. Factors associated with infertility among couples in Ethiopia, 2016 (n = 6141).

    Variables COR(95% CI) P-value AOR(95% CI) P-value
Age of respondent        
    <20 1.00   1.00  
    20–35 1.32(0.99–1.75) 0.053 1.22(0.92–1.64) 0.16
    >35 2.84(2.12–3.8) 0.00* 2.65(1.96–3.60) 0.00*
Place of residence        
    Urban 1.00   1.00  
    Rural 1.42(1.23–1.67) 0.00* 1.06(1.01–1.39) 0.03*
Highest education level        
    No education 1.00   1.00  
    Primary 0.59(0.51–0.68) 0.00* 0.73(0.62–0.85) 0.00*
    Secondary 0.49(0.38–0.64) 0.00* 0.61(0.45–0.82) 0.00*
    More than secondary 0.47(0.34–0.66) 0.00* 0.59(0.41–0.86) 0.00*
Wealth index        
    Poorest 1.00   1.00  
    Poorer 0.72(0.59–0.89) 0.00* 0.74(0.60–0.91) 0.00*
    Middle 0.63(0.51–0.77) 0.00* 0.64(0.51–0.79) 0.00*
    Richer 0.60(0.49–0.74) 0.00* 0.65(0.52–0.82) 0.00*
    Richest 0.55(0.46–0.66) 0.00* 0.79(0.60–1.10) 0.09
BMI        
    18.5-<25 1.00   1.00  
    <18.5 1.71(1.5–1.96) 0.00* 1.70(1.40–2.01) 0.00*
    25-<30 0.88(0.70–1.10) 0.257 0.78(0.53–1.16) 0.22
    > = 30 1.09(0.73–1.63) 0.651 0,92(0.73–1.17) 0.20
Respondent smokes cigarettes/tobacco 2.06(1.43–2.96) 0.00* 2.24(1.35–3.44) 0.00*
Husband smokes cigarettes/tobacco 1.39(1.17–1.65) 0.00* 1.08(0.88–1.32) 0.43
Respondent drinks alcohol 0.87(0.75–1.00) 0.03* 0.92(0.76–1.10) 0.38
Husband drinks alcohol 0.86(0.75–0,98) 0.01* 0.93(0.78–1.12) 0.48
Respondent chews khat 1.19(0.98–1.46) 0.046* 1.15(0.93–1.43) 0.18
Ever use of contraceptive 0.92(0.80–1.06) 0.26 -   -
Respondent circumcised a 1.24(1.001–1.52) 0.043*  -  -
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Note: COR, crude odds ratio; AOR, adjusted odds ratio

*, significant association; CI, confidence interval; BMI, body mass index

a, not included in the multiple logistic model due to a large number of missing values (n = 3315).

We conducted a sub-analysis of factors associated with primary and secondary infertility. In the multiple logistic regression, primary infertility was significantly higher among women whose partners chew khat (AOR = 1.62) and drink alcohol (AOR = 1.55) (Table 5). On the other hand, secondary infertility was significantly higher among women >35 years of age (AOR = 3.58), less than 18.5 BMI (AOR = 1.59), >30 BMI (AOR = 1.54), smokers (AOR = 1.85) and, ≤15 age at first birth (AOR = 1.40) (Table 6).

Table 5. Factors associated with primary infertility among couples in Ethiopia, 2016 (n = 6141).

    Variables COR (95%CI) P-value AOR (95%CI) P-value
Age
    <20 1.00 1.00
    20–35 0.21(0.14–0.33) 0.000* 0.28(0.15–0.50) 0.00*
    >35 0.06(0.03–0.13) 0.000* 0.13(0.04–0.39) 0.00*
Place of residence    
    Urban 1.00 1.00
    Rural 0.41(0.29–0.57) 0.000* (0.31–1.39) 0.28
BMI    
    18.5-<25 1.00 1.00
    <18.5 1.19(0.78–1.80) 0.425 1.36(0.87–2.11) 0.17
    25- <30 1.45(0.85–2.47) 0.170 0.98(0.53–1.89) 0.96
    > = 30 0.32(0.04–2.37) 0.267 0.18(0.02–1.33) 0.09
Highest education level
    No education 1.00 1.00
    Primary 2.6(1.72–3.87) 0.000 1.2(0.77–1.89) 0.40
    Secondary 4.1(2.47–6.91) 0.000 1.6(0.87–3.07) 0.12
    More than secondary 5.1(2.91–8.96) 0.000 1.7(0.82–3.49) 0.15
Wealth index
    Poorest 1.00 1.00
    Poorer 1.1(0.61–2.11) 0.681 1.11(0.48–2.13) 0.75
    Middle 1.03(0.54–1.98) 0.926 1.01(0.77–2.87) 0.96
    Richer 1.34(0.76–2.52 0.286 1.49(0.80–2.96) 0.23
    Richest 2.5(1.57–4.08) 0000* 1.49(0.66–3.37) 0.33
Husband smokes cigarettes/tobacco    
    No 1.00
    Yes 0.92(0.53–1.60) 0.769 Na Na
Respondent drinks alcohol    
    No 1.00
    Yes 1.21(0.85–1.73) 0.290 Na Na
Husband drinks alcohol    
    No 1.00 1.00
    Yes 1.29(0.92–1.82) 0.140 1.55(1.06–2.28) 0.02*
Respondent chews khat    
    No 1.00
    Yes 1.24(0.78–1.97) 0.370 Na Na
Husband chews khat    
    No 1.00 1.00
    Yes 1.49(1.05–2.09) 0.024* 1.62(1.12–2.36) 0.01*
Age at first sexual intercourse    
    < = 15 1.00 1.00
    15–19 1.47(0.97–2.22) 0.073 0.97(0.63–1.51) 0.92
    20–25 2.44(1.53–3.89) 0.000* 2.27(1.35–3.81) 0.00*
    >25 5.38(2.36–12.28) 0.000* 5.93(2.3–15.2) 0.00*
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Note: COR, crude odds ratio; AOR, adjusted odds ratio

*, significant association; CI, confidence interval; BMI, body mass index; Na, not applicable

Table 6. Factors associated with secondary infertility among couples in Ethiopia, 2016 (n = 6141).

    Variables COR(95% CI) P-value AOR(95% CI) P-value
Age of respondent
    <20 1.00 1.00
    20–35 1.82(1.20–2.77) 0.005* 1.54(1.03–2.33) 0.037*
    >35 2.89(1.92–4.34) 0.000* 3.58(2.34–5.48) 0.000*
Place of residence    
    Urban 1.00 1.00
    Rural 1.73(1.45–2.07) 0.000* 1.11(0.82–1.49) 0.499
Highest education level    
    No education 1.00 1.00
    Primary 0.51(0.44–0.58) 0.000* 0.74(0.63–0.87) 0.000*
    Secondary 0.35(0.26–0.47) 0.000* 0.54(0.39–0.76) 0.000*
    More than secondary 0.29(0.19–0.45) 0.000* 0.53(0.33–0.85) 0.009*
Wealth index    
    Poorest 1.00 1.00
    Poorer 0.71(0.58–0.87) 0.001* 0.73(0.59–0.91) 0.004*
    Middle 0.62(0.50–0.76) 0.000* 0.63(0.51–0.79) 0.000*
    Richer 0.57(0.46–0.70) 0.000* 0.61(0.48–0.77) 0.000*
    Richest 0.46(0.38–0.55) 0.000* 0.76(0.57–1.03) 0.079
BMI    
    18.5-<25 1.00 1.00
    <18.5 1.73(1.51–1.99) 0.000* 1.59(1.37–1.84) 0.000*
    25- <30 0.81(0.64–1.04) 0.102 0.92(0.71–1.21) 0.561
    > = 30 1.20(0.79–1.80) 0.390 1.54(1.01–2.35) 0.048*
Respondent smokes cigarettes/tobacco 2.25(1.56–3.25) 0.000* 1.85(1.21–2.82) 0.004*
Husband smokes cigarettes/tobacco 1.43(1.20–1.70) 0.000* 1.07(0.87–1.32) 0.503
Respondent drink alcohol 0.84(0.72–0.98) 0.030* 0.89(0.74–1.08) 0.246
Husband drinks alcohol 0.82(0.71–0.95) 0.008* 0.90(0.75–1.08) 0.272
Respondent chew khat 1.17(0.95–1.44) 0.392 - -
Husband chew khat 0.94(0.81–1.10) 0.392 - -
Age at first birth    
    20–25 1.00 1.00
    < = 15 1.50(1.25–1.80) 0.000* 1.40(1.15–1.69) 0.001*
    15–19 1.22(1.05–1.40) 0.007* 1.21(1.03–1.41) 0.017*
    25–30 0.98(0.67–1.43) 0.905 0.88(0.58–1.33) 0.553
    >30 0.99(0.533–1.85) 0.987 1.12(0.56–2.22) 0.749
Ever had terminated pregnancy 1.25(1.04–1.52) 0.020* 1.20(0.97–1.47) 0.090
Respondent circumcised a 1.28(1.005–1.62) 0.046*  - -
Last birth a caesarian-section b 0.42(0.24–0.74) 0.003* -  -
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Note: COR, crude odds ratio; AOR, adjusted odds ratio

*, significant association; CI, confidence interval; BMI, body mass index; Na, not applicable

a not included in the multiple logistic model due to a large number of missing values(a = 3315 missing values; b = 1806 missing values)

Discussion

In this study, we assessed the prevalence of infertility and its associated factors among couples in Ethiopia using the 2016 EDHS data.

More than twenty percent of couples reported having infertility in the 12 months. Abnormal BMI, smoking, khat chewing, alcohol drinking, and young age at first birth were significantly associated with infertility.

The prevalence of infertility in the current study was lower than in the 2013 DHS in Nigeria (31.1%). In Nigeria, the prevalence of primary and secondary infertility was 17.4% and 34.1%, respectively [34]. The variation in the results could be due to methodological differences. This study used a constructed approach to estimate the prevalence of infertility, while the study in Nigeria used the current duration approach.

The prevalence of infertility in the present study was much higher than in a study in the United States that used both the current duration (15.5%) and the constructed approach (7.0%) to estimate the magnitude of infertility [35] and a prospective study on 2151 couples from two counties of Shanxi Province in northern China (13.6%) [13]. The variation in the magnitude of infertility could be due to the differences in the availability of infertility care, sociocultural value surrounding infertility, and the study design differences [36].

In the present study, being underweight was significantly associated with infertility. This finding is in line with a study in Northern China [37]. The underlying mechanism for the association of underweight and infertility could be because low body weight results in functional hypothalamic failure, ovulatory menstrual cycles, and amenorrhea [38]. Decreased adipose tissue in underweight women metabolizes estrogen into a less potent form [39].

The present study revealed the association of obesity with infertility. This finding was in agreement with a prospective study in China [13], a case-control study in Bangladesh [40], and a systematic review of several studies [41]. Studies revealed obesity contributes to anovulation, menstrual irregularities, reduced conception rate, and a reduced response to fertility treatment. It also increases miscarriage and contributes to maternal and perinatal complications [22–24, 42].

The current study revealed a significant association between older age of women and infertility. This could be due to the lower number of eggs and abnormal chromosomes in older women. Moreover, older women are at higher risk of uterine fibroids, endometriosis, and pelvic infection [43–45].

In the present study, the use of cigarettes/tobacco was significantly associated with infertility (AOR = 2.29). A case-control study in Iran (AOR = 2.88) [46], a Behavioral Risk Factor Surveillance System (BRFSS) conducted by the CDC (AOR = 1.98) [47], and a National Survey of Family Growth (NSFG) in the USA (AOR = 1.77) [48] reported similar findings. The association between smoking and infertility could be because the chemicals in the substance cause fewer eggs in the ovary and lower quality eggs. It even causes irreversible ovarian damage over a long period of use. Moreover, studies indicated that anti-mullerian hormone levels are lower, and the onset of menopause is about five years sooner in women who smoke [49–51].

In the current study, women whose partners chew khat had significantly higher odds of primary infertility (AOR = 1.55). A study on factors associated with time-to-pregnancy on 1150 pregnant women in Addis Ababa revealed a similar result (AOR 1.66) [19]. This finding could be because khat chewing affects the quality of sperm, lowers libido, and affects the potency of male sexuality by affecting spermatogenesis and plasma testosterone concentration [17, 18].

In the present study, women whose partners drink alcohol had significantly higher odds of primary infertility. The reason for this could be alcohol drinking leads to atrophy of the testes, impotence, reduced libido, and worse quality of sperm [52–55]. Hence, the American Society for Reproductive Medicine (ASRM) recommends that couples should avoid excessive alcohol drinking (≥ 2 drinks a day) during attempts to conceive [51].

The present study revealed that a higher level of education has a negative association with infertility. This could be due to educated people being more aware of the treatment, and complications, leading to an increased probability of seeking help [56, 57].

The present study found that a high wealth index has a protective effect on infertility. The reason for the finding could be a good economic status can resolve infertility problems by encouraging people to have fast access to treatments [56, 58]. Moreover, a better economy would influence people’s decision to have children [59].

The present study revealed a significant association between lower age at first birth and secondary infertility. Several studies indicated that teenage pregnancy is associated with adverse outcomes such as obstructed labor, pre-eclampsia, anemia, operative deliveries, puerperal endometritis, and postpartum hemorrhage, which affect fertility in women [60–63].

Strengths and limitations of the study

The study tried to estimate the national prevalence of infertility by constructing variables from DHS data. Besides, the study assessed the behavioral factors contributing to infertility from the male partner’s side. However, given the cross-sectional design, the temporal nature of factors associated with infertility needs to be considered. In addition, the implicit assumption that those not at risk of pregnancy (e.g., using contraception) are fertile and unrecognized pregnancies may have biased our findings. Furthermore, we restricted the study sample to cohabitating couples, which might result in the exclusion of women no longer in a relationship being responsible for infertility.

Conclusions

A significant percentage of couples in Ethiopia are struggling with infertility. Both female and male-related factors have a substantial role in infertility. Primary infertility was significantly higher in women with partners who chew khat and drink alcohol. Secondary infertility was significantly associated with maternal under-nutrition, obesity, smoking, and young age at first birth. This study also found a negative association between women’s socio-demographics (education, wealth index) with infertility. The findings of this study imply taking action on preventable factors is a critical strategy to prevent both primary and secondary infertility and will improve the health status of the couples in other ways. As a result, emphasis should be placed on health information dissemination and raising awareness of the preventable factors of infertility. Furthermore, improvement of the economy and level of education are the suggested strategies to prevent infertility.

Acknowledgments

The authors would like to thank all the individuals who were involved in the study.

Abbreviations

BMI

Body Mass Index

CHMS

College of Health and Medical Sciences

CR

Couples Recode

DHS

Demographic and Health Survey

EDHS

Ethiopian Demographic and Health Survey

NSFG

National Survey of Family Growth

Data Availability

The data are held in the public DHS repository: http://www.measuredhs.com.

Funding Statement

the author(s) received no specific funding for this work.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data are held in the public DHS repository: http://www.measuredhs.com.

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