Magnitude and Determinants of knowledge of ovulatory period among young women in Somalia: multilevel analysis using 2020 SHDS

doi:10.21203/rs.3.rs-5293282/v1

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Research Article

Magnitude and Determinants of knowledge of ovulatory period among young women in Somalia: multilevel analysis using 2020 SHDS

https://doi.org/10.21203/rs.3.rs-5293282/v1

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Introduction

Ovulation is a key indicator of fertility and understanding its cycle is crucial for natural family planning. Despite its importance, knowledge of the ovulatory cycle (KOC) remains low among women, leading to unintended pregnancies.

Methodology

This study uses data from the 2020 Somalia Health and Demographic Survey (SHDS) to assess KOC among young Somali women. A multilevel binary logistic regression analysis was conducted to identify determinants of KOC.

Results

The prevalence of correct KOC was 21.83%. Factors positively associated with correct KOC included older age, higher education, and rural residency. Media exposure showed mixed effects on KOC.

Discussion

The study highlights a significant knowledge gap in Somalia, consistent with global trends. Regional factors and media content influence KOC. Interventions should target both individual and community levels, focusing on education and tailored media messages.

Conclusion

Enhancing KOC among young women in Somalia is vital for reducing unintended pregnancies and improving reproductive health. Addressing educational and regional disparities is essential for effective intervention strategies.

Sexual & Reproductive Medicine

Ovulatory cycle

fertility awareness

reproductive health

family planning

unintended pregnancies

multilevel analysis

Ovulation is a natural physiological process that occurs in women of reproductive age, serving as a key indicator of fertility [1]. The ovulatory cycle comprises three distinct phases: follicular phase (egg formation), ovulation (egg release), and the luteal phase. The most critical event in this cycle is ovulation, which involves the rupture of the follicle and the subsequent release of a mature egg into the fallopian tube, marking the fertile window within the ovarian cycle [2][3]. Understanding the ovulatory cycle is fundamental to the natural family planning (NFP) method [4]. A thorough comprehension of menstrual physiology, particularly the timing of ovulation, is essential for assessing fertility potential and for the effective application of family planning methods (FPMs), which are widely used by women globally [1] [5] [6].

Fertility awareness encompasses knowledge about the likelihood of conceiving during the menstrual cycle [7]. Insufficient understanding of the ovulatory cycle among sexually active women may lead to unintended pregnancies, especially in the absence of modern contraceptive options [7][8] [9] [10]. Hence, accurate knowledge of the ovulatory cycle is crucial for women seeking to either plan for conception or prevent unintended pregnancies and unsafe abortions [11] [12]. A woman’s ability to accurately identify her ovulation period is a pivotal aspect of her fertility awareness and serves as a valuable tool for recognizing her reproductive health [13].

Awareness of the fertility window is an effective strategy for reducing unintended pregnancies [14]. Women who correctly identify their ovulatory period are less likely to experience unwanted or unplanned pregnancies. Conversely, those who do not use contraception and lack awareness of their fertile period face a heightened risk of unintended pregnancy [15]. Despite its importance, research on the knowledge of the ovulatory cycle has been limited. Recent studies indicate a low prevalence of this knowledge among women; for example, only 11% of young women in India aged 15–24 demonstrated correct knowledge [16], while a study in Turkey found that only 50% of young women possessed accurate information, with 40% of the sample demonstrating correct knowledge [17].

A study by the World Health Organization (WHO) revealed that two-thirds of women wishing to delay or limit childbearing ceased using modern contraceptives due to concerns about side effects, health issues, and underestimating their chances of conception [14]. This lack of awareness regarding fertility periods, particularly in the absence of effective contraceptive use, can lead to adverse health outcomes, including unintended pregnancies and unsafe abortions, especially among vulnerable populations such as adolescents [7].

Prevalence rates of correct knowledge of the ovulatory cycle vary across regions, with estimates of 32.8% in the USA [1], 31.2% in Spain [18], and 15% in India [11]. In Africa, these rates range from 10.4–49%, with specific studies indicating 42.8% in Togo [7] [1][29] and 23.3% in Ethiopia [19].

Several studies have identified various factors influencing correct knowledge of the ovulatory cycle among women of childbearing age. These factors include age, geographical location, religion, education level, socioeconomic status, and contraceptive use [14] [20][21] [22][23][24]. Research indicates that younger women tend to have lower levels of knowledge regarding the ovulatory cycle [20][25][26] [27][28].

Evidence also suggests that young women with incorrect knowledge of the ovulatory cycle are more likely to report a higher proportion of unintended pregnancies, particularly in Africa [7]. Despite the increasing incidence of infertility, no comprehensive evaluation of fertility awareness among Indian women has been conducted. This study aims to assess the level of knowledge surrounding fertility practices and identify the determinants of ovulatory cycle knowledge among Somali women at both individual and community levels. Utilizing multilevel analysis will provide valuable insights for policymakers. This study's objective is to analyze the magnitude and determinants of ovulatory cycle knowledge among young women in Somalia.

This study employed a secondary data analysis approach using data from the 2020 Somalia Health and Demographic Survey (SHDS). The SHDS is a nationally representative survey conducted by the Ministry of Health of Somalia and the Demographic Health Survey (DHS) Program, providing comprehensive data on various health indicators, including reproductive health, for women of reproductive age in Somalia.

Study Setting

Somalia is located in the Horn of Africa, with an estimated surface area of 637,657 km2. The country's terrain consists mainly of plateaus, plains, and highlands, and it boasts the longest coastline in Africa, stretching over 3,333 km along the Gulf of Aden to the north and the Indian Ocean to the east and south. Somalia borders Djibouti to the north-west, Ethiopia to the west, and Kenya to the south-west.

Participants

The target population for this study consisted of all young women aged 15–49 years residing in Somalia. The study sample was drawn from the SHDS dataset, which utilized a two-stage stratified cluster sampling technique. The first stage involved stratifying the population by region, including both urban and rural areas. Subsequently, each stratum was further divided into clusters, or Enumeration Areas (EAs), which typically comprise 200–300 households. In the second stage of sampling, 645 EAs were randomly selected from each stratum (202 from urban areas and 443 from rural areas). Finally, a fixed number of 28 households were randomly selected from each chosen EA, resulting in a total sample size of approximately 16,360 households were selected for the survey sample.

Data Analysis

The study used a weighted sample of 4,979 young women from the SHDS dataset, accounting for the non-proportional allocation of the sample across different regions and potential variations in response rates. The data analysis was conducted using Stata version 16.

Outcome Variable

The outcome variable was women's knowledge of the ovulatory cycle (KOC), assessed through a single question: "When is the ovulation time?" The response options included: During her period, after period ended, middle of the cycle, before the period begins, at any time, don’t know

The response option "middle of the cycle" was considered correct KOC and recoded as 1, while all other options were recoded as 0, creating a binary outcome variable.

Independent Variables

The study considered several independent variables:

Individual-level factors

Age (categorized into age groups), household wealth index (categorized into wealth quantiles), Women's media exposure (exposure to radio, television, newspapers/magazines, and social media), Educational status of the women (categorized into no education, primary, secondary, and higher education), Region (categorized into different regions of Somalia), Religion (categorized into different religions practiced in Somalia), Marital status (categorized into married, widowed, divorced, and never married)

Community-level factors

Residence (categorized into urban, rural, and nomadic), Community-level media exposure (aggregated from individual-level media exposure, categorized as low and high based on the national median value), Community education level (aggregated from individual-level education, categorized as low and high based on the national median value), Community poverty level (aggregated from household wealth index, categorized as low and high based on the national median value)

Statistical Analysis

The study employed a multilevel binary logistic regression analysis to identify individual and community-level determinants of KOC. The analysis incorporated sampling weights to account for the complex survey design.

To assess the clustering effect in the data, the study calculated the intra-class correlation coefficient (ICC) and median odds ratio (MOR). Four models were fitted: a null model (containing only the outcome variable), Model I (individual-level factors only), Model II (community-level factors only), and Model III (both individual and community-level factors). Model III was chosen as the best-fitted model based on its lowest deviance value.

Variables with a p-value < 0.2 in the bivariate multilevel regression were included in the multivariable multilevel logistic regression analysis. Factors with a p-value < 0.05 were considered statistically significant predictors of correct KOC. The adjusted odds ratio (AOR) and its 95% confidence interval (CI) were reported to show the strength and direction of the association between correct KOC and the independent factors.

Ethical Considerations

This study utilized publicly available data from the SHDS dataset. Online permission to access the data was obtained from the DHS program, and all ethical considerations related to confidentiality and informed consent were met during the original data collection phase of the SHDS.

Sociodemographic profiles of the participants

A total of 4,979 weighted samples of women were included in the analysis. Approximately one-fifth (24.72%) of the participants were aged 25 to 29 years. The majority of respondents resided in the Banadir and Togdheer regions, comprising 10.58% and 11.63% of the sample, respectively, with urban dwellers accounting for 44.61%. Notably, 80.80% of participants had not received formal education, while only 1.61% reported attaining higher education. Furthermore, 21.65% of the respondents belonged to the wealthiest households, and 89.68% and 86.44% indicated that they did not have access to a listening radio or television, respectively (see in Table 1).

Knowledge of the ovulatory cycle among women of childbearing age

Among the total population of 4,979 women of childbearing age, it was found that 3,892 participants (78.17%, 95% CI: 0.76–0.79) demonstrated incorrect knowledge of KOC. Conversely, 1,087 women (21.83%) exhibited correct knowledge, as detailed in (Table 2).

Table 1

Socio-demographic characteristics of the study population, Somalia (SHDS), 2020
Variables	Categories	Frequency (n)	Percentage %
Age	15–19	380	7.63
	20–24	960	19.28
	25–29	1,231	24.72
	30–34	947	19.02
	35–39	814	16.35
	40–44	419	8.42
	45–49	228	4.58
Region	Awdal	297	5.97
	Waqooyi-galbeed	494	9.92
	Togdheer	579	11.63
	Sool	374	7.51
	Sanaag	473	9.50
	Bari	215	4.32
	Nugaal	171	3.43
	Mudug	237	4.76
	Galgaduud	290	5.82
	Hiraan	318	6.39
	Middle Shabelle	172	3.45
	Banadir	527	10.58
	Bay	129	2.59
	Bakool	259	5.20
	Gedo	168	3.37
	Lower Juba	276	5.54
Residence	Urban	2,221	44.61
	Rural	1,442	28.96
	Nomadic	1,316	26.43
Education	No Education	4,023	80.80
	Primary	681	13.68
	Secondary	195	3.92
	Higher	80	1.61
Wealth status	Lowest	1,108	22.25
	Second	919	18.46
	Middle	935	18.78
	Fourth	939	18.86
	Highest	1,078	21.65
Frequency of listening to radio	At least once a week	360	7.23
	Less than once a week	154	3.09
	Not at all	4,465	89.68
Frequency of watching television	At least once a week	520	10.44
	Less than once a week	155	3.11
	Not at all	4,304	86.44
Ever used internet	Yes	582	11.69
Ever used internet	No	4,397	88.31
Owns Mobile Telephone	Yes	4,114	82.63
Owns Mobile Telephone	No	865	17.37
Husband/partner’s ever attended school	yes	3,913	78.59
Husband/partner’s ever attended school	No	1,066	21.41

Table 2

Reproductive history of the study participants, Somalia, 2020
Variables	Categories	Frequency (n)	Percentage %
Knowledge of ovulatory cycle	No knowledge	3,892	78.17
Knowledge of ovulatory cycle	Have a knowledge	1,087	21.83
Heard family planning on radio	Yes	724	14.54
Heard family planning on radio	No	4,255	85.46
Heard family planning on TV	Yes	582	11.69
Heard family planning on TV	No	4,397	88.31
Heard family planning by text messages on mobile	Yes	399	8.01
Heard family planning by text messages on mobile	No	4,580	91.99
Heard family planning in newspaper/magazine	Yes	184	3.70
Heard family planning in newspaper/magazine	No	4,795	96.30
Heard family planning by text messages on social media	Yes	267	5.36
	No	4,712	94.64
At health facility, told of family planning	Yes	1,003	20.14
At health facility, told of family planning	No \|	3,976	79.86

Correlation Analysis

Table 3 The bivariate analysis conducted on the data from the SHDS survey provides valuable insights into the determinants of knowledge of the ovulatory period among young women in Somalia. The findings reveal several significant relationships. In the binary logistic regression analysis, factors such as place of residence, respondent’s education level, wealth index, current employment status, exposure to mass media family planning messages, and maternal occupation were identified as statistically significant predictors of correct knowledge of ovulatory cycle (KOC) at a p-value < 0.05.

Rural women had higher odds (AOR = 0.76; 95% CI: 0.65–0.899) of possessing correct KOC compared to their urban counterparts. Women aged 35–39 had 1.38 times greater odds (AOR = 1.38; 95% CI: 1.01–1.87) of having accurate KOC. The likelihood of correct KOC was notably higher among women who attained a higher level of education (AOR = 2.56; 95% CI: 1.63–4.02) compared to those with no formal education. Additionally, women from the richest wealth index households were 1.5 times more likely (AOR = 1.54; 95% CI: 1.25–1.88) to have correct KOC than those from poorer households. Similarly, participants from middle wealth index households also showed a significant association with correct KOC (AOR = 1.36; 95% CI: 1.10–1.68).

Moreover, women who had not been exposed to mass media family planning messages via television had 0.68 greater odds (AOR = 0.68; 95% CI: 0.56–0.84) of having correct KOC compared to those who had been exposed. Likewise, women who were employed were 0.8 times more likely (AOR = 0.8; 95% CI: 0.69–0.99) to have correct KOC than those who were not employed.

Table 3

Bivariate logistic regression analysis of determinants of knowledge of ovulatory period among young women in Somalia., data from SHDS 2020
Factors	knowledge of Ovulatory cycle		Crude Odds Ratio (95% CI)	Df	P-value
Characteristics	Frequency - percentage
Age	No knowledge	Have knowledge
15–19	309(81.32)	71(18.68)	1 (ref)	6
20–24	757 (78.85)	203(21.15)	1.16(0.86–1.57)		0.314
25–29	946(76.85)	285(23.15)	1.3(.98–1.75)		0.067
30–34	744(78.56)	203(21.44)	1.18(0.87–1.6)		0.263
35–39	618(75.92)	196(24.08)	1.38(1.01–1.87)		0.038*
40–44	343(81.86)	76(18.14)	0.96(.67–1.37)		0.842
45–49	175(76.75)	53(23.25)	1.31(0.88–1.96)		0.177
Maternal education
No education	3,158(78.50)	865(21.50)	1 (ref)	3
Primary	531(77.97)	150(22.03)	1.03(.84–1.25)		0.758
Secondary	156 (80.00)	39(20.00)	0.91(0.63–1.3)		0.618
Higher	47 (58.75)	33(41.25)	2.56(1.63–4.02)		0.000*
Residence
Urban	1,675 (75.42)	546(24.58)	1 (ref)	2
Rural	1,154 (80.03)	288(19.97)	0.76(0.65–0.899)		0.001*
Nomadic	1,063(80.78)	253 (19.22)	0.73(0.61–0.86)		0.000*
Region
Awdal	232(78.11)	65(21.89)	1 (ref)	15
Waqooyi-galbeed	387(78.34)	107(21.66)	0.98(0.69–1.39)		0.941
Togdheer	415(71.68)	164(28.32)	1.41(1.01–1.96)		0.041*
Sool	315(84.22)	59(15.78)	0.66(0.45–0.98)		0.044*
Sanaag	380(80.34)	93(19.66)	0.87(0.6–1.2)		0.457
Bari	206(95.81)	9 (4.19)	0.15(0.075–0.320)		0.000*
Nugaal	152 (88.89)	19(11.11)	0.44(0.25–0.77)		0.004*
Mudug	186(78.48)	51(21.52)	0.97(0.64–1.48)		0.919
Galgaduud	232(232)	58(58)	0.89(0.59–1.32)		0.575
Hiraan	244(76.73)	74(23.27)	1.08(0.741–1.58)		0.682
Middle Shabelle	161(93.60)	11(6.40)	0.24(.12–0.47)		0.000*
Banadir	370(70.21)	157(29.79)	1.5(1.08–2.1)		0.014*
Bay	93(72.09)	36(27.91)	1.38 (0.86–2.2)		0.180
Bakool	192(74.13)	67(25.87)	1.24(0.84–1.84)		0.271
Gedo	129(76.79)	39(23.21)	1.07(0.68–1.69)		0.741
Lower Juba	198(71.74)	78(28.26)	1.4(0.96–2.05)		0.079
wealth Quantile
Lowest	900(81.23)	208(18.77)	1 (ref)	4
Second	736(80.09)	183(19.91)	1.075(.86–1.34)		0.517
Middle	711(76.04)	224(23.96)	1.36(1.10–1.68)		0.004*
Fourth	750(79.87)	189(20.13)	1.09(0.875–1.358)		0.440
Highest	795(73.75)	283(26.25)	1.54(1.25–1.88)		0.000*
Owns Mobile Telephone
Yes	65 (92.86)	5,822(80.91)	1 (ref)	1
No	5 (7.14)	1,374(19.09)			0.016*
Frequency of listening to radio
At least once a week	276(76.67)	84(23.33)	1 (ref)	2
Less than once a week	124(80.52)	30 (19.48)	0.79(0.49–1.26)		0.336
Not at all	3,492(78.21)	973(21.79)	0 .91(.709 − 1.18)		0.496
Frequency of watching television
At least once a week	374(71.92)	146(28.08)	1 (ref)	2
Less than once a week	125(80.65)	30(19.35)	0.61(0.39–0.95)		0.031*
Not at all	3,393(78.83)	911(21.17)	0.68(0.56–0.84)		0.000*
Ever used internet
Yes	427(73.37)	155(26.63)		1
No	3,465(78.80)	932(21.20)	0.74(0.60–0.90)		0.003*
Maternal Occupation
Yes	3,194(77.64)	920(22.36)	1 (ref)	1
No	698(80.69)	167(19.31)	0.8(0.69–0.998)		0.048*

HP Health professional, FP Family planning, CI Confidence interval, Ref Reference group * Significant p- value

Determinants of KOC among women of childbearing age in Somalia

After running the bi-variable multilevel logistic regression analysis, the candidate variables for multivariable multilevel analysis (p < 0.2) were the age of women in years,, educational status of the women, household’s wealth index, women’s media exposure status, residence, Heard family planning on radio, Heard family planning on TV, Heard family planning by text messages on social media and At health facility, told of family planning.

The multivariable multilevel logistic regression analysis showed that age, religion, education, residence, media exposure, internet use, household wealth index, and at health facility, told of family planning rate were significantly associated with KOC at p < 0.05. The odds of having correct KOC were higher among women with the age of 25–29 (AOR = 1.1; 95% CI = 0.8–1.5), 30–34 (AOR = 1.18; 95% CI = 0.86–1.6). Older age groups (35–39 and 45–49) show increased odds of knowledge compared to the reference group (15–19). Notably, women aged 35–39 have an AOR of 1.37 (95% CI: 0.99–1.88) in Model II, indicating statistical significance.

Higher educational attainment significantly enhances knowledge. Women with higher education have an AOR of 2.20 (95% CI: 1.3–3.6) in Model II, which is significant. This effect remains strong across models. Community types influence outcomes. Rural residency results in higher odds compared to urban (AOR: 1.1; 95% CL = 0.8 ,1.4 for Model II). However, those in nomadic settings show a decreased likelihood (AOR: 0.75;95% CL = 0.6 ,0.94) in Model II. Geographic differences exist, with the Togdheer region presenting higher knowledge (AOR: 1.6; 95% CL = 1.1–2.34). In contrast, areas like Bari and Nugaal show significantly lower odds (AORs of 0.16 and 0.46, respectively). Increased wealth correlates with knowledge, especially within the middle (AOR: 1.38; 95% CL = 1.08–1.76) and highest wealth quantiles (AOR: 1.4; 95% CL = 1.1–1.8). Women whose mothers did not work have slightly lower odds of knowledge (AOR: 0.8; 95% CL = 0.47–1.65), though results are not statistically significant.

Hearing about family planning on radio improves knowledge significantly (AOR: 1.3; 95% CL = 1.03–1.68) in Model II), while absence of these media interactions reflects lowered knowledge. Regular internet usage does not appear to significantly affect knowledge. The intraclass correlation coefficient (ICC) indicates a small community-level variance (7.1% in Model I, decreasing to 4.79% in Model IV), suggesting individual characteristics predominantly explain knowledge levels.

Table 4

Random effect model and model fitness for factors associated with determinants associated with of knowledge of ovulatory period among young women in Somali., data from SHDS 2020
Measure of variation	Model 1(null)	Model 2	Model 3	Model 4
AIC	5187.463	5179.08	5082.484	5080.093
BIC	5200.489	5354.931	5206.231	5366.665
Log likelihood	-2591.7317	-2562.5402	-2522.242	-2496.0467

Table 4 Based on the results from the information criteria it shows us that the full model has the lowest AIC and BIC values which indicates that the full model outperforms the other competitive models and it has the highest performance compared to others.

Table 5

multi-level multivariable logistic regression models on individual and community-level determinants associated with of knowledge of ovulatory period among young women in Somali., data from SHDS 2020
Variables	Model I Empty model	Model II (Individual level variables) AOR (95% CI)	Model III (Community level variables) AOR (95% CI)	Model IV Both individual and community level variables) AOR (95% CI)
Age
15–19		1 (ref)		1 (ref)
20–24		1.1(0.8 1.5)		1.08(.79–1.48)
25–29		1.27(0.9–1.7)		1.27(0.94–1.7)
30–34		1.18(0.86–1.6)		1.18(0.85–1.62)
35–39		1.37(0.99–1.88) *		1.36(0.98–1.88)
40–44		0.95(0.65–1.38)		0.92(0.6–1.3)
45–49		1.38(0.91–2.09)		1.3(0.86–2.0)
Maternal education
No education		1 (ref)
Primary		1.01(.81–1.25)		0.99(0.79–1.23)
Secondary		0.788(0.53–1.16)		0.76(0.5–1.13)
Higher		2.20(1.3–3.6) *		2.07(1.2–3.46) *
Residence
Urban			1 (ref)
Rural			1.1(0.8–1.4)	1.18(0.9–1.5)
Nomadic			0.75(0.6–0.94) *	1.02(0.74–1.4)
Region
Awdal			1 (ref)
Waqooyi-galbeed			1.03(0.7–1.5)	1.0(0.67–1.49)
Togdheer			1.6(1.1–2.34)	1.6(1.16–2.47) *
Sool			0.74(0.48–1.13)	0.75(0.49–1.16)
Sanaag			0.95(0.6–1.4) *	0.99(.66 − 1.5)
Bari			0.16(0.07–0.35)	0.16(0.07–0.35) *
Nugaal			0.46(0.25–0.8) *	0.43(.24–0.787) *
Mudug			1.02(0.65–1.6)	1.03(0.65–1.6)
Galgaduud			0.86(0.55–1.35)	0.89(0.56–1.4)
Hiraan			1.15(0.75–1.75)	1.2(0.79–1.8)
Middle Shabelle			0.24(0.12–0.498)	0.25(0.12–0.5) *
Banadir			1.4(0.95–2.06)	1.47(0.99–2.19)
Bay			1.36(0.77–2.38)	1.56(0.88–2.79)
Bakool			1.39(0.90–2.16)	1.45(0.92–2.28)
Gedo			1.19(0.726–1.95)	1.3(0.8–2.2)
Lower Juba			1.38(0.90–2.1)	1.49(0.95–2.3)
wealth Quantile
Lowest		1 (ref)
Second		1.1(0.88–1.4)		1.13(0.87–1.45)
Middle		1.38(1.08–1.76) *		1.49(1.09–2.04) *
Fourth		1.08(.84–1.39)		1.16(0.8–1.6)
Highest		1.4(1.1–1.8) *		1.49(1.06–2.09) *
Maternal Occupation
Yes		1 (ref)
No		1.2(.15 − 9.2)		0.8(0.47–1.65)
Owns Mobile Telephone
Yes		1 (ref)
No		0.89(0.73–1.1)		0.89(0.7–1.1)
Frequency of listening to radio
At least once a week		1 (ref)
Less than once a week		0.86(0 .5–1.4)		0.86(.51 − 1.4)
Not at all		0.96(.71–1.28)		0.96(0.71–1.28)
Frequency of watching television
At least once a week		1 (ref)
Less than once a week		0.68(0.42–1.1)		0.68(.42–1.09)
Not at all		0.97(0.73–1.28)		0.97(0.73–1.28)
Ever used internet
Yes		1 (ref)
No		0.86(0.65–1.13)		0.86(0.66–1.13)
Heard family planning on radio
Yes		1 (ref)
No		1.3(1.03–1.68) *		0.46(.241 − .89)
Heard family planning on TV
Yes		1 (ref)
No		0.98(0.76–1.26)		0.98(0.76–1.27)
Heard family planning by text messages on mobile
Yes		1 (ref)
No		0.80(0.63–1.01)		1.02(0.71–1.47)
Heard family planning by text messages on social media
Yes		1 (ref)
No		1.14(0.8–1.6)		0.78(0.617–1.0)
At health facility, told of family planning
Yes		1 (ref)
No		0.99(0.83–1.19) *		1.0(0.83–1.2)
Random effect Community level Variance (SE)	0.25(0.07)	0.24(0.07)	0.164(0.055)	0.16(.057)
ICC (95%)	7.1%	6.9%	4.7%	4.79%

This study investigated the determinants of ovulatory cycle knowledge (KOC) among young women in Somalia, utilizing data from the 2020 Somalia Health and Demographic Survey (SHDS). The findings reveal a concerningly low prevalence of correct KOC (21.83%), highlighting a significant knowledge gap that may contribute to unintended pregnancies and related health risks.

The findings align with previous studies indicating a low prevalence of KOC among young women in other parts of the world, including India (11%) [16], Turkey (50%) [17], and Ethiopia (23.3%) [19]. These findings underscore the global nature of this issue, highlighting the need for comprehensive interventions to improve fertility awareness among women of reproductive age.

The multilevel analysis identified several individual- and community-level factors associated with correct KOC. At the individual level, older age, higher educational attainment, and residence in rural areas were positively associated with correct KOC. This finding is consistent with previous studies that have shown a correlation between higher levels of education and awareness of reproductive health [14, 20]. Exposure to family planning messages on the radio was also found to be significantly associated with higher odds of correct KOC, while television exposure was negatively associated, suggesting a potential influence of media content on knowledge acquisition.

However, the study revealed contradictory findings regarding the role of media exposure. While exposure to family planning messages via radio was positively associated with correct KOC, exposure to messages on television was negatively associated. This discrepancy may be attributed to the content and framing of messages disseminated through different media channels. Further research is warranted to explore the specific content and delivery strategies that are most effective in promoting KOC.

The influence of community-level factors on KOC highlights the importance of contextualized interventions. Notably, the Togdheer region exhibited significantly higher odds of correct KOC compared to other regions, suggesting the influence of regional-specific factors on knowledge dissemination. The negative association between residence in nomadic settings and correct KOC underscores the need for targeted interventions to address the unique challenges faced by this population group.

This study provides valuable insights into the determinants of KOC among young women in Somalia, highlighting the need for comprehensive interventions that address both individual and community-level factors. These findings contribute to the broader field of reproductive health by providing evidence-based guidance for the development of interventions aimed at improving fertility awareness and reducing unintended pregnancies.

The findings of this study are particularly relevant to the following Sustainable Development Goals (SDGs):

SDG 3: Good Health and Well-being: Promoting KOC is crucial for achieving improved maternal health outcomes, reducing unintended pregnancies, and ensuring access to safe and effective family planning methods.
SDG 4: Quality Education: Education is a key determinant of KOC, emphasizing the need for comprehensive sexuality education programs that empower young women with knowledge about their reproductive health.
SDG 5: Gender Equality: Enhancing women's reproductive rights and knowledge is essential for achieving gender equality, allowing women to make informed decisions about their reproductive health and future.
SDG 10: Reduced Inequalities: Addressing the disparities in KOC across different regions and social groups is crucial for promoting equity and reducing health inequalities.

This study reveals a critical need to improve knowledge of the ovulatory cycle among young women in Somalia. The low prevalence of correct KOC identified in our analysis highlights the potential for unintended pregnancies and associated health risks. Our findings emphasize the importance of addressing both individual and community-level factors to promote fertility awareness.

Policy Implications

The findings of this study have significant implications for policy development in Somalia. We recommend the following actions:

Strengthening Education and Information Campaigns: Develop comprehensive sexuality education programs that are age-appropriate, culturally sensitive, and accessible to all young women in Somalia. These programs should emphasize the importance of understanding the ovulatory cycle and provide accurate information about family planning options.
Targeting Media Interventions: Invest in media campaigns that effectively promote KOC and family planning through radio, television, and social media platforms. Content should be tailored to different age groups and communities, addressing specific concerns and misconceptions about fertility and contraception.
Expanding Access to Healthcare Services: Increase access to quality healthcare services for young women, particularly in rural and nomadic communities. Healthcare providers should be trained to provide accurate and comprehensive information about KOC and family planning methods, ensuring women have access to the resources they need to make informed decisions about their reproductive health.
Addressing Gender Inequality: Implement policies and programs that promote gender equality and empower women to make decisions about their reproductive health. This includes ensuring access to education, economic opportunities, and reproductive healthcare services for all women in Somalia.

By implementing these policy recommendations, we can work towards a future where all young women in Somalia are empowered to make informed decisions about their reproductive health and well-being.

We declare that this work has not been submitted as a manuscript to any other journal.

Consent for publication statement

We have obtained written consent from the patient's legal guardian to publish this case report, including any associated images or clinical data. The guardian has been informed of the purpose of the publication, its potential risks and benefits, and the steps taken to ensure patient confidentiality. The patient's identity has been protected, and all identifying information has been removed or altered to maintain anonymity. We acknowledge that this case report holds educational and scientific value, and we grant permission for its publication in a reputable medical journal or platform.

Ethical consideration

Authors got permission from Demographic and Health Surveys (DHS) Program and downloaded data. As this data is publicly available and has no personal identifiers, Ethical approval was not necessary.

Competing interests:

The authors affirm that there are no conflicts of interest pertaining to the publication of this article.

Funding

Not applicable

Conflicts of Interest:

The authors affirm that there are no conflicts of interest pertaining to the publication of this article.

Ayoola AB, Zandee GL, Adams YJ (2016) Women’s Knowledge of Ovulation, the Menstrual Cycle, and Its Associated Reproductive Changes. Birth 43(3):255–262. 10.1111/birt.12237
Simon DJ, Jamali Y, Olorunsaiye CZ, Théodat JM (2023) Knowledge of the ovulatory cycle and its determinants among women of childbearing age in Haiti: a population-based study using the 2016/2017 Haitian Demographic Health Survey. BMC Womens Health 23(1):1–10. 10.1186/s12905-022-02136-8
Getahun MB, Nigatu AG (2020) Knowledge of the ovulatory period and associated factors among reproductive women in Ethiopia: A population-based study using the 2016 ethiopian demographic health survey. Int J Womens Health 12:701–707. 10.2147/IJWH.S267675
Manhart MD, Fehring RJ (2018) The State of the Science of Natural Family Planning Fifty Years after Humane Vitae: A Report from NFP Scientists’ Meeting Held at the US Conference of Catholic Bishops, April 4, Linacre Q., vol. 85, no. 4, pp. 339–347, 2018, 10.1177/0024363918809699
Sherwood L Licensed to: iChapters User Human Physiology: From Cells to Systems, Seventh Edition, pp. 6–12
LLiubov B-N (2012) Conjoined Twins. Medical Research in Biblical Times from the Viewpoint of Contemporary Perspective., B. N. Publ. House, vol. Second Edi, no. January 2015
Iyanda AE, Dinkins BJ, Osayomi T, Adeusi TJ, Lu Y, Oppong JR (2020) Fertility knowledge, contraceptive use and unintentional pregnancy in 29 African countries: a cross-sectional study. Int J Public Health 65(4):445–455. 10.1007/s00038-020-01356-9
Bearak J, Popinchalk A, Alkema L, Sedgh G (2018) Global, regional, and subregional trends in unintended pregnancy and its outcomes from 1990 to 2014: estimates from a Bayesian hierarchical model. Lancet Glob Heal 6(4):e380–e389. 10.1016/S2214-109X(18)30029-9
Gadow EC et al (1999) Knowledge of likely time of ovulation and contraceptive use in unintended pregnancies. Adv Contracept 15(2):109–118. 10.1023/A:1006793509084
Wasswa R, Kabagenyi A, Atuhaire L (2020) Determinants of unintended pregnancies among currently married women in Uganda. J Heal Popul Nutr 39(1):1–17. 10.1186/s41043-020-00218-7
Mahey R et al (2018) Fertility awareness and knowledge among Indian women attending an infertility clinic: A cross-sectional study. BMC Womens Health 18(1):1–7. 10.1186/s12905-018-0669-y
Kshrisagar SP, Shirsath AS (2021) Fertile Period Awareness Knowledge, Attitudes and Practice in Infertile Couples Seeking Fertility Assistance: A Cross-sectional Study. New Front Med Med Res Vol 4(9):104–109. 10.9734/bpi/nfmmr/v4/3034f
Merid MW et al (2023) Spatial variations and multi-level determinants of modern contraceptive utilization among young women (15–24 years) in Ethiopia: spatial and multi-level analysis of mini-EDHS 2019. Contracept Reprod Med 8(1):1–13. 10.1186/s40834-023-00224-0
Wolde M, Kassie A, Shitu K, Azene ZN (2022) Knowledge of Fertile Period and Its Determinants Among Women of Childbearing age in Ethiopia: A Multilevel Analysis Based on 2016 Ethiopian Demographic and Health Survey, Front. Public Heal., vol. 10, no. May, pp. 1–8, 10.3389/fpubh.2022.828967
Boah M, Bordotsiah S, Kuurdong S (2019) Predictors of Unsafe Induced Abortion among Women in Ghana, J. Pregnancy, vol. 2019, 10.1155/2019/9253650
Payerle G et al (2015) Scholar (3), Annals of Tourism Research, vol. 3, no. 4. p. 45, [Online]. Available: http://www.ncbi.nlm.nih.gov/pubmed/25926610%5Cnhttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4492060%0Ahttp://www.sciencedirect.com/science/article/pii/S0160738315000444
Ozsoy S, Adana F, Colakoglu HS (2012) University students’ knowledge about fertile period. HealthMED 6(9):3174–3179
García D, Vassena R, Prat A, Vernaeve V (2016) Increasing fertility knowledge and awareness by tailored education: A randomized controlled trial. Reprod Biomed Online 32(1):113–120. 10.1016/j.rbmo.2015.10.008
Stern J, Larsson M, Kristiansson P, Tydén T (2013) Introducing reproductive life plan-based information in contraceptive counselling: An RCT. Hum Reprod 28(9):2450–2461. 10.1093/humrep/det279
Iyanda AE (2020) Cross-National Variation in Knowledge of Ovulation Timing in Sub-Saharan Africa. Women’s Reprod Heal 7(2):127–143. 10.1080/23293691.2020.1740484
Asresie MB, Fekadu GA, Dagnew GW, Gelaw YM (2020) Amhara ALL AGE- 2020 Further Analysis of Ethiopian Demographic Health Survey Data 2016, vol. no. Mc, 2020
Alam MZ, Sultan S (2019) Knowledge and practice of menstrual regulation (MR) in Bangladesh: Patterns and determinants. J Popul Soc Stud 27(3):220–231. 10.25133/JPSSv27n3.0014
Cheng KW (2011) The Effect of Contraceptive Knowledge on Fertility: The Roles of Mass Media and Social Networks, J. Fam. Econ. Issues, vol. 32, no. 2, pp. 257–267, 10.1007/s10834-011-9248-1
Dissertation M, Beatriz Nazareth de Souza Teixeira CARING ABOUT WOMEN AND THE ROLE OF QUANTIFICATION IN FAMILY PLANNING Beatriz Nazareth de Souza (2021) June, Teixeira CARING ABOUT WOMEN AND THE ROLE OF, no
Aragaw FM et al (2023) Spatial variations and determinants of knowledge of ovulatory period among young women in Ethiopia: a spatial and multilevel analysis using 2016 EDHS. BMC Womens Health 23(1):1–12. 10.1186/s12905-023-02706-4
Ali S et al (2011) Knowledge, perceptions and myths regarding infertility among selected adult population in Pakistan: A cross-sectional study. BMC Public Health 11. 10.1186/1471-2458-11-760
Bunting L, Tsibulsky I, Boivin J (2013) Fertility knowledge and beliefs about fertility treatment: Findings from the International Fertility Decision-making Study. Hum Reprod 28(2):385–397. 10.1093/humrep/des402
Lundsberg LS, Pal L, Gariepy AM, Xu X, Chu MC, Illuzzi JL (2014) Knowledge, attitudes, and practices regarding conception and fertility: A population-based survey among reproductive-age United States women. Fertil Steril 101(3):767–774. 10.1016/j.fertnstert.2013.12.006
Dagnew B et al (2021) Individual and community-level determinants of knowledge of ovulatory cycle among women of childbearing age in Ethiopia: A multilevel analysis based on 2016 Ethiopian Demographic and Health Survey. PLoS ONE 16:40–44 9 September. 10.1371/journal.pone.0254094
USAID Guide to DHS Statistics DHS-7, Demogr. Heal. Surv. Progr., vol. 7, no. version 2, 20AD

The authors declare no competing interests.

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Magnitude and Determinants of knowledge of ovulatory period among young women in Somalia: multilevel analysis using 2020 SHDS

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Abstract

Introduction and Background

Methodology

Study Setting

Participants

Data Analysis

Outcome Variable

Independent Variables

Statistical Analysis

Ethical Considerations

Results

Sociodemographic profiles of the participants

Knowledge of the ovulatory cycle among women of childbearing age

Correlation Analysis

Determinants of KOC among women of childbearing age in Somalia

Discussion

Conclusion

Policy Implications

Declarations

References

Additional Declarations

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