Determinants of infertility among married women who attend gynecologic unit at health facilities of Gamo Zone and South Omo Zone, Southern Ethiopia: A case control study

doi:10.21203/rs.3.rs-4712838/v1

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Determinants of infertility among married women who attend gynecologic unit at health facilities of Gamo Zone and South Omo Zone, Southern Ethiopia: A case control study

https://doi.org/10.21203/rs.3.rs-4712838/v1

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Background: Infertility is a disease of the reproductive system defined by the failure to achieve a clinical pregnancy after 12 months or more of regular unprotected sexual intercourse. Globally, infertility affects 15% of couples in the reproductive age.

Purpose: To identify determinants of infertility among married women who attend care at public health facilities of Gamo Zone and South Omo Zone, Southern Ethiopia

Patients and Methods: An Institution-based un-matched case-control study was conducted from May 1, 2022-May 30, 2023G.C. Participants were selected by systematic random sampling method after allocating the sample size proportionally to the health facilities. The data was collected by using the Open Data Kit (ODK) app through face-to-face interviews and exported to SPSS version 25 for analysis. The chi-square test and multivariable logistic regression model were used to identify determinants. P value<0.05 is used as statistically significant.

Result: A total of 760 married women (152 cases and 608 controls) in the reproductive age group were included in this study. The mean age of the respondents was 26.5(SD + 5.27) years. In multivariable analysis: age, educational status of the woman, residence, family size, ever use of contraceptives, history of STI, history of abortion, menstrual pattern and current alcohol use were identified as determinants of infertility.

Conclusion: age greater than or equal to 30, educational status of high school, rural residents, family size less than 4, not ever using contraceptives, history of STI, history of abortion, irregular menstrual pattern, and current alcohol use were determinant factors.

infertility

determinants

case-control

Gamo Zone

South Omo Zone

According to world health organization (WHO) infertility is a disease of the reproductive system defined by the failure to achieve a clinical pregnancy after 12 months or more of regular unprotected sexual intercourse [1]. When a pregnancy has never been achieved by a person it is Primary infertility whereas secondary infertility is when at least one prior pregnancy has been achieved [2]. Primary infertility is much more common than secondary infertility in resource-rich countries but the opposite is true in sub-Saharan Africa (SSA) [3].

Globally, infertility affects 15% of couples of reproductive age and it has been identified as a public health priority [4]. According to a national survey of family growth report from 2006–2010, it is estimated that 6% of married females aged 15– 44 years in the United States are infertile [5]. On the other hand, among couples of reproductive age in China, the prevalence of infertility was 25% [6]. In Sub-Saharan Africa region, infertility problem prevalence ranges from 30% in Nigeria to 9% in Gambia [7]. In Ethiopia, the prevalence of primary infertility has declined from 4.4% in 2000 to 3.3% in 2005 whereas secondary infertility increased from 4.3% in 2000 to 4.6% in 2005.11 Based on a research finding from an analysis of 2016 EDHS data, the prevalence of infertility was 24.2% in Ethiopia [8].

Couples can face infertility due to problems in either women or men, not necessarily both. Based on a survey performed in developed countries, the WHO estimates that female infertility accounts for 37% of cases in infertile couples, male infertility for 8%, and both male and female infertility for 35% [9].

Infection is the most common cause of infertility in developing countries and the majority of African women's infertility is due to infectious causes related to sexually transmitted diseases [10]. In SSA the high secondary infertility rate is thought to be due to sexually transmitted infections (STIs) and medical interventions under unhygienic conditions, particularly during delivery or induced abortions [11]. Additionally Fertility declines with age both in men and women, but the effects of age are much greater in women [12].

Infertility has a great effect on women's quality of life in different dimensions such as physical, mental, and social health [13]. In many African countries, the success of marriage depends on the ability of a woman to bear children. Being infertile results in serious psychological trauma and social stigma. In some cases, it may cause social disgrace and exclusion, verbal and physical abuse, and marriage violence and breakup [14].

In Ethiopia, studies are very scarce in assessing determinants of infertility, especially in our study area there is no previous study on this topic. So the main aim of this study is to identify determinants of infertility in the study area. Understanding the determinants of infertility can inform public health strategies aimed at prevention, diagnosis, and treatment. By identifying factors contributing to infertility, health policymakers, and practitioners can develop targeted interventions to improve reproductive health outcomes among women in the study area.

Study area, period, and design

This facility based case-control study was conducted at public health facilities found in Gamo and South Omo Zones. Gamo zone is located 450km south from Addis Ababa. There are 6 hospitals, 60 health centers, and 302 health posts providing routine curative and preventive health services in the Gamo zone. Moreover, South Omo Zone is located 820 kilometers from Addis Ababa .There is one general hospital, one health center, and six health posts in Jinka town. The study period was from May 1, 2022-May 30, 2023G.C.

Population and eligibility criteria

Source Population

For cases: all married women aged18 to 49 years who were confirmed cases of infertility and attained care in the Gynecologic unit at public health facilities of Gamo, and South Omo zones was the source population
For controls: all married women aged18 to 49 who were attending immediate PNC follow up at public health facilities of Gamo, and South Omo zones were the source population.

Study Population

For Cases; all married women aged 18 to 49 years who were confirmed cases of infertility and attained care in the Gynecologic unit at public health facilities of Gamo and South Omo Zone during the study period was the study population and
For controls; all married women aged18 to 49 years who were attending immediate postnatal care at public health facilities of Gamo and South Omo Zone during the study period were the study population.

Eligibility Criteria

For Controls; married women who gave birth and at immediate postnatal care at public health facilities of Gamo and South Omo Zone were included in the study.

For cases; married women aged 18 to 49 years who were confirmed as infertile by a gynecologist at public health facilities of Gamo and South Omo Zone were included in the study.

Women who were seriously ill and did not communicate at the time of the study in the control group and those women who experienced infertility due to male factors were excluded from the study.

Sample size and sampling technique

The sample size was calculated on EPI-info version 7 by using a two-population proportion formula. It was estimated using two different exposure variables and the result with the largest sample size was taken by considering 95% CI, 80% power of the study, and the case-to-control ratio of 1:4. After adding a 10% non response rate the final sample size was 770 (154 cases and 616 controls) [15].

In Gamo and South Omo Zones, Arbaminch General Hospital and Jinka General Hospitals provide infertility screening and treatment service, so these two hospitals were selected. Then the calculated sample size was allocated proportionally to their population size based on case flow which was taken from the previous one-year record. Study Subjects were selected using a systematic sampling technique. Both cases and controls were selected from the same health facilities.

Variables

Dependent variable: infertility
Independent variables: Socio-demographic and economic (age, residence, occupation, ethnicity, religion, educational status, income ) family size, Sexual behavior (multiple sexual partners), History of STD, Substance use (Khat chewing, Alcohol drinking, Cigarettes smoking), Age at first marriage, Premenarcheal sex, Order of marriage, Reproductive history (age at first pregnancy, Contraceptive use, Abortion, Stillbirths, pattern of menstrual flow, duration of menstrual flow, Outcome of last pregnancy )

Data collection tools and quality control

The questionnaire was adopted and adapted by reviewing different literature and similar studies. The questionnaire was initially prepared in English and then it was translated into Amharic and back to English to ensure its consistency. A structured questionnaire was administered by four BSc midwives and supervised by two MPH holders from Arbaminch University. The data was collected by using a Smartphone-based Open Data Kit (ODK) app through face-to-face interviews. To ensure the quality of data collection adequate training was given for data collectors and supervisors. As well as pretest was conducted out of the data collection site on 38 women (5% of the sample size) at Otona Hospital, Wolayita Sodo town. During data collection, the supervisor checked the completeness and adequacy of the data collected daily and corrected them based on the problems identified. Besides, the investigator monitored and evaluated the overall quality of the data collection process.

Data processing and analysis

The data collected by ODK was exported to SPSS version 25 for analysis. First descriptive analysis was done to describe the variables involved in the study. Bivariable analysis was conducted for the determinants associated with infertility. Those variables scored under p-value < 0.25 were selected for the multivariable analysis. Then multiple logistic regression model was fitted using the default (Enter) method to identify variables independently associated with infertility at a 5% significance level. The AOR and the corresponding 95% CI for the variables in the final model were reported.

Socio demographic characteristics of the respondents

A total of 760 married women (152 cases and 608 controls) in the reproductive age group were included in this study with a 98.8% response rate. The mean age of the respondents is 26.5 years with a standard deviation of ± 5.27(Table 1).

Table 1

Socio-demographic and economic characteristics of study participants who attend care at public health facilities of Gamo and south Omo zone 2023
S .No	Variables	Choices	Cases		Controls
S .No	Variables	Choices	Frequency	Percent	Frequency	Percent
1	Age	< 30	98	64.5	449	73.8
1	Age	>=30	54	35.6	159	26.2
2	Educational status	No formal education	40	26.5	99	16.3
		Elementary	51	33.8	127	20.9
		High school	34	22.4	210	34.5
		College or university	26	17.8	172	28.3
3	Residence	Urban	50	32.9	389	57.8
3	Residence	Rural	102	67.1	219	42.2
4	Occupation	Housewife	91	59.9	342	57
		farmer	30	19.7	56	9.2
		Private business/merchant	5	3.3	69	11.3
		Government employee	19	12.5	130	21.4
		Daily laborer	6	3.9	11	1.8
		Other	1	0.7	0
5	Religion	Orthodox	52	34.2	237	39
		Protestant	98	64.5	330	54.3
		Muslim	2	1.3	41	6.7
6	Duration of marriage	< 5 years	78	51.3	319	52.5
		5–10 years	43	28.3	174	28.6
		> 10 years	31	20.4	115	18.9
7	Is your current marriage first?	Yes	143	94.1	594	97.7
7	Is your current marriage first?	No	9	5.9	14	2.3
8	Income	< 5000	82	53.9	206	33.9
8	Income	>=5000	70	46.1	402	64.1
9	Husband’s educational status	No formal education	26	17.1	84	13.8
		Elementary	20	13.2	52	8.6
		High school	62	40.8	183	30.1
		College or university	44	28.9	289	47.5
10	Husband’s occupation	Farmer	29	19.1	157	25.8
		Private business/merchant	53	34.9	123	20.6
		Government employee	56	36.8	274	45.1
		Daily laborer	14	9.2	52	8.6
11	Family size	≤ 4	145	95.4	373	61.3
11	Family size	≥ 5	7	4.6	235	38.7

Infertility related information of cases

In this study, primary and secondary infertility had relatively comparable findings, which were 75(49.3) of the cases had primary infertility and 77(50.7%) had secondary infertility. In both cases and controls rural dwellers hold a higher proportion of infertility (Fig. 1).

Figure 1:Types of infertility among infertile women (cases) based on their residence in Gamo Zone and South Omo Zone, 2023

Obstetrics related and other gynecologic characteristics of the respondents

Regarding with age at first marriage 82(53.9%) cases and 373(61.2%) controls age were greater than and equal to 20 years. Concerning with family history of infertility 11(7.2%) of cases and 106(17.4%) of control had a family history of infertility. Twenty-two (14.5%) of cases and 255(41.9%) of controls had ever used contraceptives. According to the respondents' responses, 47(31.1%) of cases and 163(26.8%) of the controls had irregular patterns of menstruation (Table 2).

Table 2

Obstetrics and other gynecologic related characteristics of respondents at public health facilities of Gamo and South Omo Zone, 2023.
S .No	Variables	Choices	Cases		Controls
S .No	Variables	Choices	Frequency	Percent	Frequency	Percent
1	Age at first marriage	≤ 19	70	46.1	236	38.8
1	Age at first marriage	≥ 20	82	53.9	372	61.2
2	Have you Ever been pregnant before?	Yes	77	50.7	515	84.7
2	Have you Ever been pregnant before?	No	75	49.3	93	15.3
3	Age at first pregnancy	≥ 19	20	26	143	27.8
3	Age at first pregnancy	≥ 20	57	74	372	72.8
4	Number of pregnancy	1–3	71	92.2	412	80,0
4	Number of pregnancy	4–9	6	7.8	103	20.0
5	Did you deliver a child?	Yes	48	62.3	501	97.3
5	Did you deliver a child?	No	29	37.7	14	2.7
6	Number of child delivered	1–4	48	100	457	91.2
6	Number of child delivered	≥ 5	0		44	8.8
7	History of Abortion	Yes	33	21.7	58	9.5
7	History of Abortion	No	119	78.3	550	90.5
8	Number of abortions	1	18	91.4	53	54.5
8	Number of abortions	≥ 2	5	8.6	15	45.5
9	History of Still birth	Yes	5	3.3	29	4.8
9	History of Still birth	No	147	96.7	579	95.2
10	Outcome of your last pregnancy	Live birth	47	61.0	582	95.7
		Abortion	27	35.1	5	0.8
		Still birth	3	3.9	21	3.5
11	Number of living children	0–4	48	100	463	92.4
11	Number of living children	5–8	0		38	7.6
12	Family history of infertility	Yes	11	7.2	106	17.4
12	Family history of infertility	No	141	92.8	502	82.6
13	Contraceptive ever used	Yes	22	14.5	255	41.9
13	Contraceptive ever used	No	130	85.5	353	58.1
14	Duration of modern contraceptive use	≤ 3years	14	63.6	167	65.5
14	Duration of modern contraceptive use	≥ 4years	8	36.4	88	34.5
15	Pattern of your last three menstrual cycle	Regular	104	68.4	445	73.2
15	Pattern of your last three menstrual cycle	Irregular	48	31.6	163	26.8
16	When did you see your menses	Before first sexual intercourse	147	97.4	597	98.2
16	When did you see your menses	After first sexual intercourse	4	2.6	11	1.8

Sexually Transmitted disease and behavioral characteristics of the respondents

Concerning with STI status of respondents 25(16.4%) cases and 25(4.3%) controls had a history of STI (Table 3). Eight (5.3%) of cases and 14(2.3%) of controls had a history of multiple sexual partner.

Table 3

STI related and behavioral characteristics of the respondents at public health facilities of Gamo and South Omo Zones, 2023.
S. No	Variables	Choice	Cases			Controls
			frequency	percent		frequency	percent
1	Have you ever had abnormal vaginal discharge	Yes	22		15.1	25	4.1
		No	129		84.9	583	95.9
2	Have you ever had genital ulcer	Yes	2		1.3	1	0.2
		No	150		98.7	607	99.8
3	STI status of the women	Yes	25		16.4	25	4.3
		No	127		83.6
4	Husband’s history of STI	Yes	13		8.6	16	2.6
		No	139		91.4	592	97.4
5	Ever drink alcohol	yes	9		5.9	35	5.8
		no	143		94.1	573	94.2
6	Current alcohol drinking	yes	8		5.3	4	0.7
		no	143		94.7	604	99.3
7	Ever smoked cigarettes	yes	1		0.7	1	0.2
		no	150		99.3	607	99.8
	Current smoking	yes	1		0.7	0	0
		no	151		99.3	608	100
9	Have you ever chewed khat	yes	3		2.0	11	1.8
		no	148		98.0	597	98.2
10	Current chat chewing	yes	2		1.3	1	0.2
		no	149		98.7	607	99.8
11	Multiple sexual partner	No	144		94.7	594	97.7
		yes	8		5.3	14	2.3

Body mass index (BMI)

Figure 2: Body mass index of the respondents at public health facilities of Gamo and south Omo zone, 2023.

Determinant factors of infertility

To identify determinants of infertility first Bivariable analysis was done then variables with a p-value < 0.25 were included for multiple logistic regression analyses. hence, the results of multiple regression analysis showed that Age, educational status of the respondents, residence, family size, history of abortion, contraceptive ever use, STI, the pattern of menstrual cycle, and current alcohol use had significant association with infertility (Table 4).

Table 4

Determinants of infertility among respondents at public health facilities of Gamo Zone and South Omo zone
Variable	Category	Cases, n (%)	Controls, n (%)	COR	AOR	95% CI		P value
Variable	Category	Cases, n (%)	Controls, n (%)	COR	AOR	lower	upper	P value
Age **	< 30	98(64.5%)	449(73.8%)	1	1			0.001
Age **	≥ 30	54(35.6%)	159(26.2%)	1.56	7.373	3.707	14.661	0.001
Educational status *	No formal education	40(26.5%)	99(16.3%)	1	1
	Elementary	51(33.8%)	127(20.9%)	2.57	1.146	0.567	2.316	0.704
	High school*	34(22.8%)	210(34.5%)	2.56	0.422	0.194	0.916	0.029
	College or university	26(17.8%)	172(28.3%)	1.03	1.001	0.402	2.489	0.999
Residence **	Urban	50(32.9%)	389(57.8%)	1	1			0.001
Residence **	Rural	102(77.1%)	219(42.2%)	3.62	2.727	1.491	4.986	0.001
Income	< 5000	82(53.9)	206(33.9)	1	1
Income	≥ 5000	70(46.1)	402(64.1)	2.28	0.850	0.462	1.563	0.61
Husband’s educational status	No formal education	26(17.1%)	84(13.8%)	1	1
	Elementary	20(13.2%)	52(8.6%)	1.24	0.670	0.229	1.954	0.463
	High school	62(40.8%)	183(30.1%)	1.1	0.930	0.309	2.806	0.898
	College or university	44(28.9%)	289(47.5%)	0.49	0.729	0.187	2.842	0.649
Family size**	≤ 4	145(95.4%)	373(61.3)	13.05	25.498	9.485	68.548	0.001
Family size**	≥ 5	7(4.6%)	235(38.7)	1	1			0.001
Age at first marriage	≤ 19	70(46.1)	236(38.8)	1	1			0.429
Age at first marriage	≥ 20	82(53.9)	372(61.2)	0.74	0.809	0.479	1.367	0.429
History of abortion*	Yes	33(21.7)	58(9.5)	2.63	2.008	1.034	3.902	0.040
History of abortion*	No	119(78.3)	550(90.5)	1	1			0.040
Contraceptive ever use**	Yes	22(14.5)	255(41.9)	1	1			0.001
Contraceptive ever use**	No	130(85.5)	353(58.1)	4.23	3.998	2.073	7.709	0.001
Family history of infertility	Yes	11(7.2)	106(17.4)	0.37	1			0.357
Family history of infertility	No	141(92.8)	502(82.6)	1	1.490	0.637	3.486
STI**	No	127(83.6%)	582(95.7%)	1	1			0.000
STI**	Yes	25(16.4%)	26(4.3%)	3.95	6.007	2.233	16.16	0.000
Husband’s History of STI	Yes	13(8.6%)	16(2.6%)	3.49	1			0.802
Husband’s History of STI	No	139(91.4%)	592(97.4%)	1	0.850	0.240	3.017	0.802
Current alcohol drinking	Yes	8(5.3)	4(0.7)	8.45	9.419	1.405	63.13	0.02
Current alcohol drinking	No	143(94.7)	604(99.3)	1	1			0.02
Current Khat chewing	Yes	2(1.3)	1(0.2)	0.12	1			0.294
Current Khat chewing	No	149(98.7)	607(99.8)	1	0.217	0.010	4.783	0.294
Pattern of menstrual cycle**	Regular	104(68.9)	445(73.2)	1	1			0.003
Pattern of menstrual cycle**	Irregular	47(31.1)	163(26.8)	1.23	2.354	1.333	4.154	0.003
multiple sexual partner	No	144(94.3%)	594(97.7%)	1	1
multiple sexual partner	Yes	8(5.7%)	14(2.3%)	2.35	1.196	0.329	4.345	0.785
BMI	Healthy(< 18.5)	128(84.2)	374(61.5)	1	1
	Underweight(18.5–25)	2(1.3)	2(0.3)	2.92	1.383	0.140	13.658	0.781
	Overweight(25–30)	20(13.2)	204(33.6)	0.29	0.479	0.253	1.08	0.054
	Obesity(> 30)	2(1.3)	28(4.6)	0.21	0.117	0.014	1.072	0.061
* Statistically significant **statistically highly significant

The present study tries to identify determinants of infertility among women who were seeking health services from Gamo and South Omo Zone public facilities. Accordingly, age, educational status of the respondents, residence, family size, history of abortion, contraceptive ever use, STI, pattern of menstrual cycle, and current alcohol use were found to be the major determinants of infertility in this study.

Age is one of the determinants of infertility, in this study, women with age greater or equal to 30 years of age were more infertile than those who were younger than 30 this finding is consistent with a study conducted in China [16]. Another study on correlates of infertility found the same result. This indicates that for each additional year of age for women and men in these countries, the odds of secondary infertility increased by 20-30% [17]. It is also consistent with a finding from India [18] .This is attributed to, A woman being born with all the eggs she is going to have in her lifetime and its quality and quantity decline with age[19].

In this study, the odds of infertility among women with high school-level educational status were less than those with no formal education. This finding is consistent with a study conducted on EDHS data which revealed that a higher level of education has a negative association with infertility [8]. This may be due to those women with higher levels of education may have a better understanding and seek care.

Residence is one of the determinants that affect infertility. In this study, rural dwellers were 3.89 times more infertile than their counterparts. This finding was consistent with a study conducted in Adama, in which rural dwellers were 27.8 times more infertile than urban residents, [20] another study on EDHS data also revealed that rural residents experience infertility more than their counterparts.8 The possible explanation for this could be due to low access to health services, particularly gynecology and obstetrics specialty clinics nearby may be a barrier to getting early screening and treatment services [21].

In this study family size was found to be a determinant factor of infertility, the odds of infertility among women whose family size was less than or equal to 4 was higher than those women whose family size was greater than 5. This could be due to those women who experience infertility having a lesser number of children than fertile women.

According to the results of the present study, the odds of infertility were higher among women who did not ever use contraceptives compared to those women who have a history of contraceptive use. This finding is in line with a study conducted in Ethiopia at Adama town which documented that the odds of primary infertility in women were 85% less likely among family planning users as compared to those who did not use family planning [20]. This is due to those women who have infertility since they want to achieve pregnancy they were less likely to use contraceptives than fertile women. In addition, women who use contraceptives can prevent unwanted pregnancy so they will have less chance of abortion and its complications.

This study identified that the odds of developing infertility are two times higher among women who had abortions compared to those who had no previous history. This finding is consistent with a study finding at Addis Ababa, in which those women who had abortions more than three times were more infertile than their counterparts [22] In addition, a systematic review on determinants of infertility in East Africa mentioned abortion as one risk factor [3]. Evidence explains the increased odds of infertility among women who had a history of abortion resulting from one of the many possible causes. First, it could be from cervical damage which arises as complications during the process of surgical abortion which result in cervical incompetence, second infection or pelvic inflammatory disease due to the surgical procedure, third, due to incomplete abortion which is a known risk factor for the development of infection during surgical intervention [23].

Many studies explained the relation between infertility and sexually transmitted diseases. In this study, the odds of infertility are higher among women with a history of STI than their counterparts. This finding was in line with a study finding in Desse Women who had a history of STI were 2.8 times more likely to be infertile than those who did not have a history of STI.15 and from Rwanda [24]. The reason for the highest odd among this group was explained by Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) infections are common bacterial sexually transmitted infections (STI) that cause cervicitis in women and ascend to the upper reproductive tract in 10–20% of cases, leading to pelvic inflammatory disease (PID). PID can cause inflammation and damage to fallopian tubes that result in tubal factor infertility (TFI) [25].

In addition, this study identified that the Pattern of menstrual flow has a significant association with infertility. In this study, the odds of infertility were 2 times higher among women who had irregular patterns compared to women who had regular patterns. This finding was in line with a research finding from Malaysia,[18] and Adama [20]. A research finding revealed that increased variation in cycle length was a predictor of reduced fecundity [26] This could be due to irregular menstrual patterns are an indication of menstrual disorder that can be symptoms of infertility due to another cause, such as polycystic ovary syndrome (PCOS) and uterine fibroids. In addition, the inability of women to ovulate and regulation of hormone levels leads to hormonal imbalances. These hormonal disorders are characterized by symptoms such as irregular menstrual cycles, excessive bleeding or very little bleeding, absence of menstruation, or long menstruation periods which are risk factors for infertility [27].

In this study the odds of infertility among women who currently drink alcohol were 9.4 Times higher than fertile women this finding was consistent with a study finding from Iran in which The odds of female infertility in women with a history of alcohol consumption were 0.78 times higher compared to those who did not mention the history of alcohol use [28]. Evidence suggested that Alcohol use is associated with altered levels of estrogen and progesterone and irregularities in the menstrual cycles and ovulation, which can decrease female fertility and lead to infertility [29]

In the current study age greater than or equal to 30, educational status of high school, rural residents, family size greater than 5, not ever using contraceptives, history of STI, history of abortion, irregular menstrual pattern, and current alcohol use were determinants of infertility.

The local government should strengthen STI prevention services and family planning programs to increase awareness of women about the complications of STIs and abortion through different meetings and using mass media. along with developing different strategies that are targeted to women greater than 30 years old to increase their involvement in early screening is vital because early intervention is important for detecting and managing the disease.

Strengths and limitations of the study

The study tried to identify the determinants of infertility by conducting a hospital-based case-control study. The use of a relatively large sample size and exhaustive inclusion of potential confounders in the model are among the strengths of this study. Further, to the best of our knowledge, this is the first study in Southern Ethiopia to examine the determinants of infertility. Besides, the study assessed the behavioral factors contributing to infertility from the female side. However, the study did not include male factors which contribute to infertility

AOR: Adjusted Odd Ratio, BMI: Body Mass Index, C:I Confidence Interval, EPI –INFO: Epidemiological Information, HX: History, IRB: Institutional Review Board, MPH: Masters of Public Health, MVA: Manual Vacuum Aspiration, ODK: Open Data Kit, OPD: Out Patient Department, PNC: Post Natal Care, SSA: Sub Saharan Africa, STD: Sexually Transmitted disease, STI: Sexually Transmitted Infection, WHO: World Health Organization

Acknowledgements

We would like to acknowledge Arba Minch University for offering us the opportunity to conduct this research project. All study participants for their willingness to participate in this study and all data collectors and supervisors for their unlimited effort to cascade this research project. Our heartfelt gratitude also extends to all Zonal health offices and hospitals for their cooperation

Authors’ contributions

FH: hypothesized and developed the research project, data analysis, and develop the manuscript. SG: was responsible for hypothesized and developed the research project, data analysis and revised the manuscript, HA: hypothesized and developed the research project, assisting in data analysis and revised the manuscript. YG: assisted in developing the research project, MH: assisted in developing the method and data analysis and revised the manuscript

Funding

No funding was received for publication

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. All relevant data are presented within the manuscript

Ethics Declarations

Ethics approval and consent to participate

Ethical approval letter was obtained from the Institutional Review Board (IRB) of Arba Minch University with reference number IRB/1151/2021, College of Medicine and Health Sciences. A formal letter of support was obtained from the research coordination offices of health departments and public health facilities in Gamo and South Omo zones. Written informed consent was obtained from study participants. The privacy of the study participants was respected and the information collected from them was kept confidential. Participants' participation in the study was voluntary and they were informed that if they wished to terminate their participation at any time, they could withdraw without restrictions.

Consent for publication

Not applicable.

Competing interest

The authors declare that they have no competing interests.

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No competing interests reported.

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Determinants of infertility among married women who attend gynecologic unit at health facilities of Gamo Zone and South Omo Zone, Southern Ethiopia: A case control study

Status:

Version 1

Abstract

Figures

Introduction

Method

Study area, period, and design

Population and eligibility criteria

Source Population

Study Population

Eligibility Criteria

Sample size and sampling technique

Variables

Data collection tools and quality control

Data processing and analysis

Result

Socio demographic characteristics of the respondents

Infertility related information of cases

Obstetrics related and other gynecologic characteristics of the respondents

Sexually Transmitted disease and behavioral characteristics of the respondents

Body mass index (BMI)

Determinant factors of infertility

Discussion

Conclusion and Recommendation

Abbreviations

Declarations

Ethics approval and consent to participate

References

Additional Declarations

Status:

Version 1