Spatial Distribution of No-Knowledge on Modern Contraceptive Methods Among Reproductive Age Women and Predictors in Ethiopia: Evidence From 2016 EDHS

Abstract

Though contraception has a significant importance for reproductive-age women, its knowledge among women has challenged by different barriers. Due to the growing concern regarding the poor knowledge and awareness of modern contraceptive methods among women, critical speculation for the contributing factors is quite important. This study then aimed to determine the prevalence and associated factors of women with no knowledge of modern contraceptive methods in Ethiopia. A cross-sectional survey data (EDHS-2016) was analyzed, including 15 604 reproductive-age women, concerning no-knowledge of modern contraceptive methods. We presented descriptive statistics using means, standard deviations, and proportions. The global Moran’s I statistic was employed to check the distribution. To spot spatial locations, Getis*-Ord-Gi statistics was applied, and spatial interpolation was applied to predict unknown locations of the outcome using the Ordinary-Kriging method. SatScan was used to identify the specific local clustering nature using the Bernoulli method. Multilevel-binary-logistic regression is used for inspecting individual and community-level factors. P < .25 to include variables in the final model and P < .05 to declare associations. AOR with 95% CI was used to explicate variables. The prevalence of no-knowledge of modern contraceptive methods was 4.6%. Age 25 to 34 (AOR = 0.66, 95% CI: 0.49, 0.88), no-formal-education (AOR = 3.54, 95% CI: 1.14, 10.99), poor wealth status (AOR = 2.02, 95% CI: 1.07, 3.82), rural place (AOR = 1.80, 95% CI: 1.65, 4.51), no_big_problem from health-facility (AOR = 0.70, 95% CI: 0.52, 94), low-level community education (AOR = 2.06, 95% CI: 1.01, 4.23), Afar (AOR = 7.5, 95% CI: 4.32, 9.89), Somali ( AOR = 7.1, 95% CI 5.42, 11.23), Gambela (AOR = 12.6, 95% CI :6.92, 18.50), and Harari (AOR = 7.4, 95% CI: 5.36, 10.20) were determinants. Living without the knowledge of modern contraceptive methods means, aggravating maternal problems in Ethiopia. Somali and Afar regions showed high no knowledge of modern contraceptive methods than others. Age, women with no formal-education, poor wealth status, low community level education, big-problem from health facility and rural residency were affecting the outcome.

Keywords

modern contraception spatial distribution reproductive age women no knowledge Ethiopia

Introduction

Reproductive health plays a vital role in the overall well-being of women and their families. Access to accurate information regarding modern contraceptive methods is crucial for reproductive-age women to make informed decisions about their sexual and reproductive health.^1,2 Contraception is the intentional avoidance of pregnancy by many methods, including sexual behavior, drugs, pharmaceuticals, and surgery.^1,3 Different types of contraceptive methods are available, such as traditional and modern methods across the global environment.^1,4 The goal of using contraception is to achieve least amount of expense and negative impacts while maximizing comfort and privacy. The dual benefit of barrier techniques, such as the use of male and female condoms, is that they offer protection against sexually transmitted infections (STDs).^1,2,5,6

The use of modern contraceptives enables women to pursue education and employment opportunities beyond their personal health. According to the report outlined by the United Nations Department of Economic and Social Affairs, Population Division (UN/DESA/POP), 874 million women are using modern contraceptives, and nearly 70 million women are projected to gain access to contraceptives by 2030.⁷

The prevalence of modern contraceptive rate has increased from 6% in 2000 to 23% 2016.⁸ However, there is a growing concern regarding the poor knowledge and awareness of modern contraceptive methods among women in this population.^9,10 Studies suggested that the interconnected nature of modern contraceptives and unintended pregnancy has become complicated.^11,12

Despite the availability and advancements in modern contraceptive methods, studies suggest that a significant number of reproductive-age women lack adequate knowledge about these methods. This knowledge gap creates barriers to effective family planning, leading to unintended pregnancies, unsafe abortions, and other adverse reproductive health outcomes.¹³ Similarly, there are several reasons why people choose not to use contraceptive techniques; these include misconceptions, lack of information, fear of side effects, difficulty accessing the methods, and insufficient training for health professionals.^9,11,14

According to a study (on the level of knowledge of modern contraceptive methods) conducted by Gebrehiwot Ayalew Tiruneh et al, more than half (56%) of the study participants had poor knowledge of modern contraceptive methods.¹⁵

The study briefly describes to investigate and understand the reasons behind the lack of knowledge on modern contraceptive methods among reproductive age women. Key factors contributing to this issue may include inadequate maternal education, cultural and social norms surrounding discussions on contraception, limited access to healthcare services, and misinformation or myths^16,17 about contraception. In low- and middle-class neighborhoods and places of deprivation, myths and misconceptions around contraception are rampant. This would lessen the women’s knowledge to use modern contraceptive methods, on the contrary.^18
-20

Therefore, this study aims to explore the extent of the knowledge gap by identifying the main factors influencing the lack of knowledge and proposing strategies to address the issue. By understanding the underlying causes and challenges, policymakers, healthcare providers, and organizations can develop targeted interventions, educational programs, and awareness campaigns to improve the knowledge and utilization of modern contraceptive methods among reproductive-age women across the study area. In addition, this research seeks to empower women with accurate information, enhance their reproductive autonomy, and contribute to improved reproductive health outcomes.

Methods

Study Design, Period and Setting

The was study was carried out using a cross-sectional survey study design in Ethiopia using the 2016 EDHS. The study area, Ethiopia, is located in the Horn of Africa and has 9 regional states and 2 city administrations (Figure 1).

Figure 1.

Study area indicating map on no knowledge of modern contraceptive methods among women in Ethiopia, 2016 EDHS.

Source and Study Population

The source population for the survey were all reproductive age (15-49) group women and the study population were all women who used any of contraceptive methods preceding the survey.

Sample Size and Sampling Procedure

To explore the population and health issues pertinent to Ethiopia, a standardized and validated questionnaire was modified from the DHS Program’s standard questionnaires for the 2016 EDHS. To choose representative samples for the entire nation, a 2-stage stratified sampling procedure was used. The nation’s regions were divided into rural and urban areas. Samples of enumeration areas (EAs) were then chosen in 2 steps for each stratum. Six hundred and forty-five EAs were chosen in the first stage with a probability that was proportionate to the size of the EA. According to the 2007 Ethiopian Population and Housing Census, the EA size is the total number of residential households in the EA. A predetermined number of 28 households per cluster were chosen at random from the household listing in the second step. The women’s data (IR) from the 2016 EDHS was used for this investigation. The Ethiopian Demographic and Health Survey reports on Measure DHS’s website (www.dhsprogram.com) contain a comprehensive sampling technique.

In this study, a total of 15 604 women were included, and weighted values were carried out and reestablished to verify the representativeness of the sampled data. The data was retrieved from the MEASURE DHS website (www.dhsprogram.com), after we requested and were allowed to download the data.

This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for (cross-sectional/cohort/case-control) studies to indicate its transparency and completeness.²¹

Variables

The outcome variable for this study was knowledge of any contraceptive methods, which was then coded as “0” if the women had knowledge of modern contraceptive methods and “1” if the women had no knowledge of modern contraceptive methods.

Knowledge: Women’s knowledge of modern contraceptives includes their comprehension, awareness, and familiarity with the many methods of modern contraception, including their use, efficacy, advantages, possible drawbacks, and accessibility. Oral contraceptive tablets, intrauterine devices (IUDs), injectables, implants, male and female condoms, sterilization (tubal ligation or vasectomy), hormonal patches, vaginal rings, and emergency contraception are examples of modern contraceptive methods.^9,16,19,22

Media exposure: In this study, we categorized media exposure into 2°: exposed (women who had access to television, radio and internet) and not exposed (women who had no access at all).

Individual-level Variables (Covariates)

Maternal educational level, age, religion, marital status, region, husband’s education, wealth index, and media exposure.

Community-level Variables

Region, community level education, distance from health facility, and place of residence.

Statistical Analysis

We weighted the data in order to correct for the non-proportional distribution of samples among strata and regions before doing the descriptive data analysis. Next, weighted and unweighted frequencies, mean ± (standard deviations), and percentage were used to show descriptive statistics. STATA version 17 was used for all analyses.

Spatial Analysis

We employed ArcGIS 10.7 for spatial analysis, which allowed us to ascertain the no knowledge of modern contraceptive methods random distribution, dispersion, and clustering characteristics. The range of Moran’s I output is (−1 to +1). Values around −1 represented distributed no knowledge of modern contraceptive methods, whereas values near +1 represented a clustering distribution. We examined the local Getis* Ord data to determine the regions with high and low levels of no-knowledge of modern contraceptive methods after finding a strong global autocorrelation.

Spatial Interpolation

We used the Ordinary Kriging spatial interpolation approach to statistically optimize the weight, which allowed us to forecast no knowledge of modern contraceptive methods for portions of the nation that were not sampled.

Spatial Scan Statistics Analysis

The software used for the local cluster detection was SaTScan Version 10.1.7. The study area was carefully traversed by a circular window to find a considerable clustering of no knowledge of modern contraceptive methods. Using log-likelihood (LL) and a P-value of less than .05, we reported the findings for the primary and secondary observed clusters.

Multivariable Binary Logistic Regression Analysis

We used multilevel analysis because country representative survey data typically have a hierarchical structure or are clustered. In order to find favorable determinants of no knowledge of modern contraceptive methods across the country, we went through 4 successive model-building techniques. Prior to the predictors being included, Model 0 was empty or null (the intercept only model). In order to calculate the amount of variance explained by the model, all individual-level variables that were initially significant at a P-value of less than .25 were included in Model 1 (fixed effect model). Model 2 (random effect model) included cluster-level (community-level) variables. A model was created using the logarithm of the no knowledge of modern contraceptive methods probability. Model 3 (the mixed effect model) was the final model in which both the individual and community level variables were incorporated to assess final model performance.

In addition to estimating the Proportional Change in Variance (PCV) and Median Odds Ratio (MOR), the Likelihood Ratio (LR) test for model comparison and deviance (−2LL) for the goodness of fit check were also computed

In the end, both fixed and random effect variables were fitted into the mixed effect model. P-value <.25 was used to include the variable in the model, and P-value < .05 was used to indicate the association. Moreover, the results were expressed using the AOR with 95% CI.

Results

Socio Demographic Characteristics of the Study Participants

A total of 15 604 reproductive age group (15-49), were considered in this study. The mean age of the participants was 28.15 (SD ±9.16). The higher proportion of women were from Oromia 5683 out of 15 604 (36.42%), Amhara 3677 out of 15 604 (23.57%), and SNNPR 3284 out of 15 604 (21.05%). The majority 6125 (39.25%) of the study participants were grouped in 15 to 24 age category. Regarding the educational status of the participants, nearly half, 7439 (47.68%), of them were illiterates. The wealth status of the respondents justified that 46.7% of them were supposed to be in the rich wealth index category. In this study we also identified that 6888 (64.7%) of the participants had an exposure to medias; like television, radio and internet (Table 1).

Table 1.

Individual Characteristics of Women of Reproductive Age Group in Ethiopia with no knowledge of Modern Contraceptives (n = 15 604), EDHS 2016.

Variables	Weighted frequency	Percent
Age (in years)
15-24	6125	39.25%
25-34	5270	33.77%
35-49	4209	26.98%
Educational status
No education	7439	47.68%
Primary education	5474	35.08%
Secondary education	1815	11.64%
Higher education	874	5.60%
Wealth index
Poor	5414	34.7%
Middle	2964	18.99%
Rich	7225	46.30%
Marital status
Single	4266	27.34%
Married	10.144	65.01%
Widowed	1192	7.64%
Religion
Orthodox	6741	43.20%
Catholic	120	0.77%
Protestant	3665	23.49%
Muslim	4868	31.20%
Traditional	210	1.35%
Media exposure
Not exposed	8717	35.30%
Exposed	6888	64.70%
Husbands educational status
No education	4685	46.18%
Primary	3772	37.18%
Secondary	975	9.61%
Higher	713	7.03%
Residence
Urban	3458	22.16%
Rural	12 146	77.84%
Region
Tigray	1121	7.18%
Afar	127	0.82%
Amhara	3677	23.57%
Oromia	5683	36.42%
Somali	454	2.92%
Benishangul	159	1.02%
SNNPR	3284	21.05
Gambela	43	0.28%
Harari	38	0.25%
Addis Ababa	924	5.9%
Dire Dawa	90	0.58%

Spatial Analysis of Women with No Knowledge of Modern Contraceptive Methods in Ethiopia

In Ethiopia the spatial variation of women with no knowledge of modern contraceptive methods was significantly varied in EDHS-2016 analysis across the study area. As indicated in the figure below the global Moran’s Index value was 0.138 (P-value < .001) and we failed to accept the null hypothesis which conceived random distribution of women with no knowledge of modern contraceptive methods at Moran Index’s value of 0.138 (P-value < .001; Figure 2).

Figure 2.

Spatial autocorrelation of no knowledge of modern contraceptive among women in Ethiopia, 2016 EDHS.

Hotspot Analysis of the Survey Study

From the EDHS-2016 sampled data, some part of Tigray, Afar, Somalia and Gambela were identified as a high risk (hotspot areas) for no knowledge of modern contraceptive method. Whereas, Amhara, SNNP, Addis Ababa, Dire Dewa, and Norther Tigray were regions with low risk (cold spot) of no knowledge of modern contraceptive methods (Figure 2).

Spatial Interpolation

To detect the spatial interpolation, the ordinary kriging was employed and discovered that the borders of Somalia, and Afar had indicated the largest proportion of no knowledge of modern contraceptive methods. In the opposite way, Amhara, Oromia, Addis Ababa, SNNP, Dire Dewa and Tigray showed the lowest proportion of not having knowledge of modern contraceptive methods among the reproductive age groups of women (Figures 3 -5).

Figure 3.

Hotspot/cold spot analysis of no knowledge of modern contraceptive methods among women in Ethiopia, 2016 EDHS.

Figure 4.

Spatial interpolation analysis of no knowledge of modern contraceptive methods among women in Ethiopia, 2016.

Figure 5.

StatsCan analysis of no knowledge of modern contraceptive methods among women in Ethiopia, 2016.

Spatial Scan Statistics Analysis

The result of the spatial scan statistics revealed that a total of 80 clusters were identified as significant cluster. Thirty-six (36) of the clusters were the most likely (primary clusters), and 30 were formed the second clusters. The primary clusters were located in Somalia, and border of Oromia which was centered (6.745502 N, 44.259011 E) with 320.00 km radius (Table 2).

Table 2.

Significant Clusters of Women with No Knowledge of Modern Contraceptive Methods, EDHS 2016.

Type of cluster	#cluster location	#pop	# case	RR	LLR	Coordinate/radius	P-value
Primary cluster	36	236	87	38.27	229.19	(6.745502 N, 44.259011 E)/320.00 km	<.001
Secondary cluster 1	30	64	11	11.87	17.76	(12.401068 N, 42.163134 E)/264.82 km	<.001
Secondary cluster 2	6	334	22	4.56	15.97	(7.491548 N, 36.339254 E)/59.54 km	<.001
Secondary cluster 3	8	339	19	3.94	11.73	(5.203234 N, 40.019732 E)/184.64 km	<.005

LLR = log-likelihood ratio; RR = relative risk.

The result of the spatial scan analysis indicated with log likelihood ratio: 229.186237 and relative risk was 38.27 with P-value < .01, which depicts that the women in the spatial circle (window) had 38.27 times the risk of no knowledge of modern contraceptive methods that those outside the spatial window.

Random Effect Analysis

The random effect analysis revealed the existence of significant difference between clusters regarding women with no knowledge of modern contraceptive methods. The community variance, (community variance = 8.20 with standard error = 1.099349), witnessed the significant differences thereto. Similarly, this difference was maintained by intra correlation coefficient, (ICC), of 71.4% in the null model revealed that the variability of women with no knowledge of modern contraceptive methods was attributable due to cluster variation. Moreover, the final model (Model IV), indicated that nearly 82.9% of the variability of women with no knowledge of modern contraceptive methods was attributable to the individual and community level factors (predictors).

Finally, we also assessed the model fitness using deviance (−2LL), and indicated that the model with the lowest deviance would be considered the best fitted. Therefore, Model IV with the least deviance value (2228.98) was selected as the best fitted 1 (Table 3).

Table 3.

Model Comparison and Random Effect Analysis.

Parameters	Null Model I	Model II	Model III	Model IV
Random effect
Community variance	8.202 (6.30, 10.66)	2.77 (1.99, 3.84)	1.57 (1.06, 2.30)	1.40 (1.02, 1.94)
ICC%	71.4%	45.67%	32.2%	29.92%
MOR	16.65 (11.71, 24.91)	5.02 (3.89, 6.74)	3.33 (2.66, 4.34)	3.12 (2.61, 3.82)
PCV%	1	66.22%	80.93%	82.9%
Model comparison
AIC	4186.687	2398.214	3807.134	2260.639
BIC	4201.996	2512.225	3937.258	2465.67
LLR	−2313.43	−1225.22	−1903.63	−1114.49
Deviance	4626.86	2450.44	30 807.26	2228.98

AIC = Akaike’s information criterion; BIC = Bayesian information criterion; LLR = log likelihood; MOR = median odd ratio; ICC = intra-class correlation coefficient and PCV (proportional change in variance).

Multi-Level Model Comparison

Multilevel Analysis

Determinants of Women With No Knowledge of Modern Contraceptive Methods

In this study we simultaneously presented both the individual and community level factors as seen in (Table 4). Maternal age, maternal educational status, wealth status, religion, as individual level and place of residence, distance from health facility, community level education, and region from community level were factors associated with no knowledge of modern contraceptive methods among women in Ethiopia. We have assessed the multicollinearity effect using variance inflation factor (VIF). In multi-linear regression, collinearity is frequently defined as a testing scenario in which the predictor variables have a strong linear relationship with 1 another. This implies that it would be challenging to determine which independent variable actually affects a dependent variable if there is a high or strong correlation between the 2 independent or predictor variables. If the variance inflation factor and tolerance are greater than 5 to 10 and lower than 0.1 to 0.2, respectively (R² = 0.8-0.9), multicollinearity exists.²³

Table 4.

Multivariable Multilevel Logistic Regression Analysis of Both Individual and Community-Level Factors Associated with No Knowledge of Modern Contraceptive Methods in Ethiopia, EDHS 2016.

Characteristics	Model II (95% CI AOR)	Model III (95% CI AOR)	Model IV (95% CI AOR)
Age category
15-24	1.03 (0.74, 1.43)		0.90 (0.65, 1.25)
25-34	0.68 (0.51, 0.90)^a		0.66 (0.49, 0.88)^b
35-49	1		1
Educational status
No education	4.3 (1.36,13.54) ^a		3.54 (1.14, 10.99)^b
Primary	2.0 (0.64, 6.30)		1.99 (0.64, 6.22)
Secondary	-
Higher	1		1
Media exposure
Not exposed	2.7 (1.72, 4.25)^a		2.15 (1.36, 3.41)
Exposed	1		1
Wealth index
Poor	4.7 (2.62, 8.31)^a		2.02 (1.07, 3.82)^b
Middle	2.6 (1.30, 5.32)^a		2.01 (0.97, 4.20)
Rich	1		1
Religion
Orthodox	1		1
Catholic	16.9 (3.74, 76.45)^a		4.74 (1.03, 6.67)^b
Protestant	5.4 (2.32, 12.41)^a		1.86 (0.74, 4.69)
Muslim	15.0 (7.25, 31.12)^a		1.58 (0.64, 3.91)
Traditional	7.8 (2.58, 23.44)		2.89 (0.99, 8.46)
Husband’s educational status
No education	1.1 (0.49, 2.34)		1.31 (0.61, 2.80)
Primary	0.64 (0.28, 1.43)		0.91 (0.41, 2.03)
Secondary	1.4 (0.58, 3.32)		1.51 (0.63, 3.58)
Higher	1		1
Community level factors
Place of residence
Urban		1	1
Rural		1.3 (0.71, 2.44)	1.80 (1.65, 4.51)^b
Distance from health facility
Big problem		1	1
Not big problem		0.61 (0.49, 0.77)^a	0.70 (052, 0.94)^b
Community level poverty
Low		1.6 (1.20, 2.23)^a	-
High		1	1
Community level education
Low		2.2 (1.29, 3.69)^a	2.06 (1.01, 4.23)^b
High		1	1
Community level media exposure
Low		2.0 (1.23, 3.28)^a	1.63 (0.86, 3.09)
High		1	1
Region
Tigray		1	1
Afar		8.8 (7.74, 15.53)	7.5 (4.32, 9.89)^b
Amhara		0.23 (0.054,0.98)^a	0.15 (0.01, 1.62)
Oromia		2.1 (0.83, 5.44)	1.21 (0.26, 5.63)
Somali		5.2 (2.75, 8.9)^a	7.1 (5.42, 11.23)^b
Benishangul		4.8 (1.86, 12.33)^a	3.79 (0.87, 16.48)
SNNPR		1.44 (0.52, 3.94)	1.27 (0.26, 6.18)
Gambela		9.95 (3.86, 25.63)^a	12.6 (6.92, 18.50)^b
Harari		10.04 (8.65, 17.67)^a	7.4 (5.36, 10.20)^b
Addis Ababa		2.78 (0.76, 10.09)	-
Dire Dewa		1.63 (0.47, 5.59)	0.33 (0.03, 4.67)

Variable significant at model 3.

Significant variables at final model.

The odds of no knowledge of modern contraceptive methods among women of age 25 to 34 were decreased by 34% (AOR = 0.66, 95% CI: 0.49, 0.88) compared to 35 to 49. The odds of no knowledge of modern contraceptive methods among women who had no education were 3.54 (AOR = 3.54, 95% CI: 1.14, 10.99) time higher compared to women with higher educational status. The odds of no knowledge of modern contraceptive methods among women who had poor wealth status were 2.02 (AOR = 2.02, 95% CI: 1.07, 3.82) times higher compared to their counter parts. Similarly, the odds of no knowledge of modern contraceptive methods among catholic religion follower women were 4.74 (AOR = 4.74, 95% CI: 1.03, 6.67) times higher compared to orthodox religion followers. The odds of no knowledge of modern contraceptive methods among women who lived in rural place were 1.80 (AOR = 1.80, 95% CI:1.65, 4.51) time higher compared to urban residents. The odds of no knowledge of modern contraceptive methods among women who had no big problem from health facility were decreased by 30% (AOR = 0.70: 95% CI: 0.52, 94) compared to women with distance from health facility who had a big problem. In addition, the odds of no knowledge of modern contraceptive methods among women the odds of no knowledge of modern contraceptive methods among women who had low level community education were 2.06 (AOR = 2.06, 95% CI: 1.01, 4.23) times higher compared to higher level community educated women. Moreover, women from Afar (AOR = 7.5, 95% CI: 4.32, 9.89), Somali ( AOR = 7.1, 95% CI 5.42, 11.23), Gambela (AOR = 12.6, 95% CI: 6.92, 18.50), and Harari (AOR = 7.4, 95% CI: 5.36, 10.20) had higher odds of no knowledge of modern contraceptive methods than women from Tigray regional state.

Discussion

This study was conducted to assess women with no knowledge of modern contraceptive methods in Ethiopia. The prevalence of women with no knowledge of modern contraceptive methods in Ethiopia using EDHS 2016 Survey was 4.6% with (95% CI: 0.42, 0.49). This study was consistent with a study conducted in Jigjig Somali region.² The current study indicated that women with no knowledge of modern contraceptive methods become spatially varied among individual level characteristics of the study participants. However, the current study was lower than a study conducted in Uaddara Barracks, Ghana which was 19.4% of the participants showed no knowledge of modern contraceptive methods.⁴ The possible discrepancy might be due to the number of study participants was very small among the study conducted in Ghana and higher in Ethiopian context.

Even though the EDHS-2016 report⁸ suggested that the knowledge of the whole contraceptive method use was universal in Ethiopia among currently married women, the finding of this study affirmed that these women with no knowledge of modern contraceptive methods was significantly vary across the study area. The reason for dealing women with the no knowledge of modern contraceptive methods would provide an information for decision makers to intervene appropriate sort of actions to help women in searching and using for the modern contraceptive methods currently available.^1,8 To improve family planning outcome, knowledge of modern contraceptive methods among women shall be dealt and instructive measures shall be determined. As clearly indicated in the map of the spatial autocorrelation, the geospatial distribution of women with no knowledge of modern contraceptive methods was non-random (Figure 1). Tigray, Afar, Somalia and Gambela were identified as a high risk (hotspot areas) for no knowledge of modern contraceptive method. Whereas, Amhara, SNNP, Addis Ababa, Dire Dewa, and Norther Tigray were regions with low risk (cold spot) of no knowledge of modern contraceptive methods. Apart from that, the spatial scan statistics result outlines that most predominantly cluster/ primary /likely cluster was located in Somali, and border of Oromia regions. The variation could be due to the differences of cultural, custom and values of the society toward modern contraceptive methods. Those study participants from Addis Ababa, Amhara, SNNP and Dire Dawa had the chance to get and use at least 1 modern contraceptive method as a result of their knowledge on modern contraceptive use.

In the multilevel analysis, Maternal age, maternal educational status, wealth status, religion, from individual level and place of residence, distance from health facility, community level education, and region from community level were factors associated with no knowledge of modern contraceptive methods among women in Ethiopia. This study discovered that age was determinant factor for no knowledge of modern contraceptive methods among women of reproductive age. The odds of no knowledge of modern contraceptive methods among women of age 25 to 34 were decreased by 34% (AOR = 0.66, 95% CI: 0.49, 0.88) compared to 35 to 49. The result of this study is in lined with a study conducted in Nigeria.²⁴ The possible reason might be the younger age groups are exposed to be aware of the modern contraceptive methods so that they are likely to use for their future time and these women who have the desire of more children were likely to be ignorant to not to use the modern contraceptive methods.^25,26 The result of this analysis indicated that the odds of no knowledge of modern contraceptive methods among women who had poor wealth status were 2.02 (AOR = 2.02, 95% CI: 1.07, 3.82) times higher compared to their counter parts. This study is in agreement with a study conducted in Ghana²² and Nepal,¹⁴ where women from poor socio economic activities cannot have access to information related to modern contraceptive methods rather they are adaptive to the traditional methods like, absenteeism. The other possible reason might be People with low incomes may encounter obstacles including exorbitant expenses, insufficient transportation, or limited access to healthcare facilities. Similarly, lack of information may cause poor moms to view giving birth as a choice and a way to generate money.²⁷

While, we conduct a mixed effect multilevel logistic regression analysis of community-level characteristics, it was shown that place of residency, community level education, no big problem from health facility, and region were significantly associated factors for women with no knowledge of modern contraceptive methods. Women living in rural areas had higher odds of no knowledge on modern contraceptive methods as compared to women living in urban areas. The finding of this study has congruence with other studies.^9,16,19,22 The possible reason could be women whose residency has based in rural areas have low media penetration to access information related to modern contraceptive methods than urban dwellers do and their day to day activities are the basic obstacles that hinder their experience as they lived in dispersed catchment which then directly could affect their knowledge of the modern contraceptive methods. As a result, they prefer giving birth traditionally without any modern contraceptive use.^5,9 In Ethiopia most women, particularly those living in rural areas, face several obstacles when trying to get and use modern contraceptives methods due to lack of knowledge and awareness.²⁸ In addition, this study figured out that community level education has positive association regarding the no knowledge of modern contraceptive methods among women of reproductive age. The odds of no knowledge of modern contraceptive methods among women who had low level community education were 2.06 (AOR = 2.06, 95% CI: 1.01, 4.23) times higher compared to higher level community educated women. The result of this study has a mirror image with the study conducted in Uganda,²⁹ Ghana^18,25 and Nigeria.³⁰ The possible justification would be as it is known that education could enhance the entire background/knowledge of the participant by providing general understandings to the topic of interest, those women with higher level of education would have the knowledge of modern contraceptive methods than women with low level of community education.^29,30 The other possible inference would be, inadequate access to comprehensive sexual education and reproductive health information can be more prevalent in low-income communities. This lack of education and awareness can contribute to a lower level of knowledge about modern contraceptive options and their availability.^31,32

Moreover, distance from health facility was a contributing community factor for women with no knowledge of modern contraceptive methods. The odds of no knowledge of modern contraceptive methods among women who had no big problem from health facility were decreased by 30% compared to women with distance from health facility who had a big problem. This result indicated that those women who were distant form heath facilities had very poor/no knowledge of modern contraceptive methods that are available in the health facilities. Whereas, those women who were not affected by distance from the health facilities had the chance to presume and perceive how modern contraceptive methods could be used as a means for family planning, reduce sexually transmitted diseases and others.³³

Finally, this study comprised an impressive finding that regions such as; Afar, Somali, Gambela and Harari revealed less tendency regarding the knowledge of modern contraceptive methods. Hence, women from Afar (AOR = 7.5, 95% CI: 4.32, 9.89), Somali (AOR = 7.1, 95% CI: 5.42, 11.23), Gambela (AOR = 12.6, 95% CI: 6.92, 18.50), and Harari (AOR = 7.4, 95% CI: 5.36, 10.20) had higher odds of no knowledge of modern contraceptive methods than women from Tigray regional state. The result has similarities with studies conducted in Ethiopia^2,33 Those regions may be difficult for health professional’s intervention and access to health care services as a result of poor health coverage, limited access to health information such as reproductive health education. Besides, those women from these regions were uneducated and this indicated that mothers do not know much about modern contraceptive methods. Similarly, as a normative belief mothers might think of having more kids has equal resemblance as a source of wealth and blessings from Almighty. The other possible explanation could be, women in Afar and Somali, who lived in rural and desert area were inaccessible for health education campaigns and it became very difficult to have knowledge on modern contraceptive methods.²

Strength and Limitation of the Study

The main strength of this study was the utilization of large and nationally representative samples to predict the prevalence of women with no knowledge of modern contraceptives. However, Similar to other cross-sectional data, a causal relationship cannot be established using the EDHS data. Because the data was collected cross-sectionally. In addition, while we accounted for individual and community-level variables, we did not measure the supply-side and Health system factors such as ;trained health personnel or the consistent availability (stock-outs) of specific contraceptive methods at local facilities.

Conclusion

The finding of this study witnessed about women with no knowledge of modern contraceptive methods in Ethiopia using EDHS 2016 survey. Even though, the prevalence of modern contraceptive methods in Ethiopia becoming in a state of changing, the knowledge of women about all modern contraceptive methods could be considered as an issue. Therefore, this study has brought contributing factors such as age, educational status, poor wealth status, residence, no big problem from health facilities, low level community education, and region. Government bodies, policy makers and every stakeholder should declare a clarion call to propagate appropriate interventions like maternal health education, securing problematic rural areas by ambulatory services and the likes. Similarly, the regional variation outlines that most of the Afar and Somali regions were exposed with mothers without knowledge of modern contraceptive methods. Hence, region-based support shall be granted so as to improving the level of knowledge toward modern contraceptive methods. Once, women are exposed and informed on modern contraceptive methods, they will open the bot to use these methods themselves and they will be a changing agent for the other who did not know about. Providing community education would enhance the knowledge of modern contraceptive methods.

Supplemental Material

sj-docx-1-inq-10.1177_00469580261432533 – Supplemental material for Spatial Distribution of No-Knowledge on Modern Contraceptive Methods Among Reproductive Age Women and Predictors in Ethiopia: Evidence From 2016 EDHS

Supplemental material, sj-docx-1-inq-10.1177_00469580261432533 for Spatial Distribution of No-Knowledge on Modern Contraceptive Methods Among Reproductive Age Women and Predictors in Ethiopia: Evidence From 2016 EDHS by Mulugeta Desalegn Kasaye, Robel Asaminew Mekonnen and Anas Ali Alhur in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Footnotes

Acknowledgements

We would like to share and extend our heartfelt thanks to the Measure DHS and the program office for providing excellent data sets to see the implication of this study.

Abbreviations

AOR Adjusted odds ratio

CI Confidence interval

CV Community variance

DHS District Health Survey

EDHS Ethiopian Demographic Health Survey

LL Log likelihood

MOR Median odds ratio

PCV Proportion of community variance

SNNP Southern Nation Nationalities and People

VIF Variance inflation factor

ORCID iD

Mulugeta Desalegn Kasaye

Ethical Considerations

This study did not require ethical approval or participant permission because we used secondary publicly accessible survey data from the MEASURE DHS program. Permission to acquire and utilize the data for this study from was given after we made a request to the DHS Program. The National Research Ethics Review Committee (NRERC) at the Ministry of Science and Technology and the Ethiopian Health Nutrition and Research Institute (EHNRI) Review Board gave their approval for the EMDHS data collecting.

Author Contributions

Mulugeta Desalegn Kasaye: has contribution for the design and conception of the study, preparation and analysis of the data, and interpretation of the findings and write up of the manuscript.

Mulugeta Desalegn Kasaye, and Anas Ali Alhur, and Dr. Robel Asaminew Mekonnen has substantial contribution in the design and conception of the study and supervise the whole research process during the data preparation, analysis and write-up.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Permission for data access was acquired from the measure Demographic and Health Survey through an online request by written letter of objective and significance of the study from website.

Supplemental Material

Supplemental material for this article is available online.

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