Malaria in Pregnancy and Predisposing Factors in Jor District of Gambella Region, Southwest Ethiopia: A Cross‐Sectional Study

ABSTRACT

Background and Aims

Malaria in pregnancy remains a major public health concern in Ethiopia, particularly in high‐endemic regions like Gambella. Despite the high burden, no peer‐reviewed published study exists on its prevalence and associated risk factors among pregnant women in Jor District, Gambella region. This study aimed to determine the prevalence of malaria in pregnancy and its associated factors in Jor District, Gambella, Ethiopia.

Methods

A facility‐based cross‐sectional study was conducted from February 29 to April 10, 2024, among 446 pregnant women selected using systematic random sampling. Data were gathered through microscopy‐based blood film examination and face‐to‐face interviews using a structured questionnaire. Descriptive statistics were performed to obtain frequencies and percentages, whereas logistic regression analyses were performed to identify independent risk factors for malaria, with statistical significance set at p < 0.05. All analyses were performed with SPSS version 24 (IBM, USA).

Results

The prevalence of malaria was found to be 15.2% (95% CI: 11.4, 17.5). Plasmodium falciparum 8.96% (40/446) and Plasmodium vivax 2.7% (12/446) and 3.6% (16/446) for comorbidity (P. falciparum and P. vivax) are the two species identified in this study. The factors associated with malaria were no formal education (AOR = 1.32), lack of knowledge about malaria transmission (AOR = 2.7), presence of stagnant water near residence area (AOR = 3.61), non‐ownership of ITN (AOR = 5.74), and low altitude (AOR = 5.26). Due to smaller sample size in some of the categories of the independent variables such as non‐ownership of ITN and altitude the confidence intervals are wider.

Conclusions

The prevalence of malaria was high in the study area. Non‐ownership of ITNs, lack of formal education, lack of knowledge about malaria transmission, and residing at lower altitudes and presence of stagnant water near residence of pregnant women were significantly associated with malaria among pregnant women. Public health actions such as improving access of pregnant women's to formal education over the long term, increasing pregnant women' access to ITN along with health education on proper utilization of ITN, health information dissemination about transmission of malaria and environmental modification such as removal of stagnated water for the control of mosquito vectors were recommended.

Abbreviations

AOR

adjusted odd ratio

CI

confident interval

COR

crude odd ratio

IRS

indoor residual spray

ITN

insecticide treated bed net

LLIN

long‐lasting insecticidal net

OR

odds ratio

WHO

World Health Organization

1. Introductions

Globally, nearly half of the world's population lives in areas at risk of malaria, and the disease continues to pose a major threat to global health [1]. According to the 2024 World Malaria Report, an estimated 263 million malaria cases and 597,000 deaths occurred globally in 83 malaria‐endemic regions in 2023, increasing from 245 million in 2020. Malaria during pregnancy (MiP) is particularly concerning, as it is associated with adverse health outcomes for both mother and infant. The infection significantly contributes to childhood illness and mortality and increases the risk of complications for pregnant women, girls, and their developing fetuses [1]. In 2020, 121.9 million pregnancies occurred in malaria transmission areas, resulting in an estimated 70.9 million (58.1%) livebirths. The total number of pregnancies at risk of malaria was 52.9 million in the WHO South‐East Asia region, 5.1 million in the Western Pacific region, 46.1 million in the Africa region, 11.1 million in the Eastern Mediterranean region, and 6.7 million in the Americas (AMRO) region [2]. In 2023, in 33 moderate to high transmission countries in the WHO African Region, there were an estimated 36 million pregnancies of which 12.4 million (34%) were infected with malaria [1].

Exposure to malaria in pregnancy remained stable between 2022 and 2023. By WHO subregion, prevalence of exposure to malaria during pregnancy in 2023 was highest in west Africa, where about 6 million (36.4%) of an estimated 16.5 million pregnant women and girls had malaria infections, and in central Africa, where about 3.4 million (40.5%) of an estimated 8.4 million pregnant women and girls were infected with malaria [1]. According to a recent systematic review and meta‐analysis, the estimated pooled prevalence of malaria among pregnant women in Ethiopia was 12.72% [3]. Of all the regions and administrative cities in Ethiopia, Gambella has the highest prevalence of malaria 6% [4]. In Majang zone, Gambella the overall prevalence of asymptomatic malaria in pregnancy (AMiP) was 15.3% [5]. Similarly, the prevalence of gestational malaria, placental malaria and congenital malaria in Metti, Health Center, Majang zone Gambella were 24.4%, 34.4% and 5.0%, respectively [6].

The adverse outcomes associated with malaria, which affect both the mother and the newborn includes: stillbirth, preterm birth, maternal and neonatal mortality, congenital malaria, maternal anemia [7, 8]. Several factors contribute to the heightened risk of malaria during pregnancy, including decreasing age, not using an insecticide‐treated bed net, lack of consultation and health education about malaria prevention during antenatal care attendance, and living close to stagnant water [9]; being on second‐trimester pregnancy, and gravidae II [10]; pregnant women who did not regularly use LLINs (Long‐Lasting Insecticidal Nets) and accomplished less than four antenatal care visits (ANC < 4) and primigravid and paucigravid women who did not regularly use LLINs [11]; young maternal age and the use of insecticide spray [12]; being illiterate, first trimester, primigravidae, living far from health centers, not sleeping under long lasting insecticide treated nets and living near irrigation areas [13].

Over the past 2 years, Ethiopia has faced several challenges, including but not limited to suboptimal implementation of malaria prevention and control measures in conflict‐affected areas, emergence of new vector An. stephensi, vector resistance to insecticides, and climate change and variability [1]. Between January 2024 and October 2024, over 7.3 million malaria cases and 1157 deaths were reported in Ethiopia. Malaria poses a significant public health challenge in Ethiopia, where approximately 75% of the land mass is considered to be endemic to malaria. Around 69% of the population residing in these areas face the risk of infection [14]. In Gambella region malaria transmissions occur whole year round with the peak transmission occurs in summer. Jor district which is the study area for this study is among the least developed districts in terms of infrastructures. It's health related indicators are the poorest among Gambela regional state districts [15].

Jor district is highly prone to malaria epidemic in the region [15]. It is the district which is always affected by flood. This provides good mosquito breeding sites. In the Gambella region of Ethiopia, pregnant women exhibit a high awareness of malaria transmission by mosquito bites, with a majority recognizing it as a preventable disease treatable through health centers. However, despite this knowledge, a significant proportion of pregnant women remain at risk of malaria [5]. Hence to prevent the negative impact of malaria among pregnant women and their fetus, doing a study is of paramount importance in reducing the problems imposed by malaria infections. Despite the high burden, no peer‐reviewed published study exists on its prevalence and associated risk factors among pregnant women in Jor District, Gambella region. This study proves that the prevalence of malaria is high like the other district of the region. Over all, the information which had been provided by this study will help in reducing the negative impact that has been caused by malaria in the district.

2. Materials and Methods

2.1. Study Area, Design and Period

A facility based cross‐sectional study was conducted in Jor district from February 29, 2024 to April 10, 2024. Jor is found in Gambella regional state. It is bordered in the south with the Akobo River, which separates it from South Sudan, in the west and in the north, the borders with Neur zone, northeast with Abwobo and the east with Gog. Alworo River defines the northern part of the boundary. Its administrative town is located in Ongogi, where its only health center is located. It is among the swampy districts which are affected by flooding every year. The flooding makes the district at high risk for a malaria epidemic compared to other districts found in Gambella regional state. Among the rivers found in Jor, Gilo is the most important river which has a socioeconomic contribution to the area. According to the Atlas of the Ethiopian Rural Economy published by the Central Statistical Agency (CSA), around (15%) of the district is covered by notable landmarks like the Gambella National Park, which occupies the woreda north Gilo River [16].

2.2. Source Population

All pregnant women who visited Ongogi Health Center from Jor district and its suburbs.

2.3. Study Population

Pregnant women who were selected by systematic random sampling technique during data collection period and fulfilled the inclusion criteria.

2.4. Inclusion Criteria

Pregnant women who lived at least 6 months in Jor District and its suburb and who visited Ongogi health center during the study period were included.

2.5. Exclusion Criteria

Pregnant women with personality disorder with no guardian were excluded, pregnant women who have taken antimalarial drug or had just been treated for malaria within 2 weeks before the recruitment, pregnant women who were severely ill or in coma were excluded.

2.6. Sample Size Determination

2.6.1. Sample Size for Prevalence

The sample size was calculated using single population proportion formula.

$$n=Z^{2}P(1-P)/d^2$$

Where “n” is a minimum number of sample sizes, “Z” is the standard value, “P” is the prevalence value, and “d” is a marginal error. At a 95% confidence interval Z = 1.96 and the marginal error is 5%.

Based on a study conducted in Benishangul‐Gumuz among pregnant women in Sharkole, it showed that 51% have malaria [10]. The first one was selected randomly during a visit to ANC.

$$\begin{array}{cc}n& =Z^{2}P(1-P)/d^2\\ & =\left(1.96\right)²\left(0.51\right)\left(0.49\right)/\left(0.05\right)²\\ & =384\end{array}$$

Then, by adding a 10% nonresponse rate, the final sample size was 422.

2.7. Sample Size for Associated Factors

The sample size was calculated using the software Epi info version 7.2.5.0. The percent of outcome in nonexposed was 20.8% and the percent of outcome in exposed was 10.4% as per the study by Almaw and his colleagues in north Shoa [13]

$$n=\text{required}\text{sample}\text{size}$$

$$r=\text{ratio}$$

$$P_0=\text{proportion}\text{of}\text{diseases}\text{in}\text{exposed}$$

$$P_1=\text{proportion}\text{of}\text{disease}\text{in}\text{non}‐\text{exposed}$$

$$Z_{\mathit{\beta }}=\text{power}\text{of}\text{the}\text{study}(1-\beta )$$

$Z\alpha /2=(\mathrm{Z}=1.96)$

Two‐sided level confidence level: 95%

Power: 80

Ratio (unexposed: exposed): 1% (outcome in unexposed group): 20.8%

Risk ratio: 0.50

Odds ratio: 0.44 % outcome in exposed group: 10.4%

By adding 10% to 418 which is the highest result found after Epi info calculation, the final sample size was 460. Eventually, the larger of the two specific objectives 460 was the sample size of the study.

2.8. Sampling Technique

Systematic random sampling technique was used to select the study participants. The sampling frame was prepared by enrolling each pregnant woman visiting the Health Center on the enrollment list. To determine the value of k, the previous 3 years (in 2023, 2022, and 2021) patient (pregnant women) flow in the month of February and March was recorded from the laboratory register book and the average patient flow was found to be 700. Then k was calculated as N/n, that is, 700 divided by 460 and the resultant k value was 1.52 which was approximately two. Hence, every other pregnant woman visiting the Health Center Laboratory were taken as study participant of this study. We employed systematic random sampling technique as it is simple and efficient method to select a representative sample from a large, evenly distributed population and it is convenient when there is a list of the population [17].

2.9. Data Collection

The questionnaire was adopted from different literatures reviewed to conduct the study. The questionnaire was translated to Anywa language. Structured questionnaire after being pretested in Abwobo health center was applied as final tool for data collection. Principal investigator employed data collectors and supervisor after training. Data were collected by a Medical Laboratory Technician, nurses and midwives who were not working in the study health center. Data collection had been supervised by most senior medical laboratory technician. For this study, one supervisor and two data collectors were recruited to collect the data from participants. The principal investigator oversaw the entire data collection process in collaboration with the supervisor.

2.10. Procedure of Laboratory Data Collection

Blood samples were examined by microscopy‐based thin and thick blood film examination. Before blood sample collection, the data collector interviewed the pregnant women using the pre‐structured questionnaire. Capillary blood sample was collected by pricking the index finger after cleaning with 70% alcohol using a lancet and the first drop was wiped off and a large drop (which is approximately 6 µL) was placed on the slide 1 cm away from the frosted for thick smear preparation and a small drop (which is approximately 2 µL) was placed on the slide 1 cm away the thick smear for thin smear preparation. The thick smear was prepared by spreading in a circular fashion using the edge of the spreader slide which is 1 mm in diameter and the thin smear was prepared by placing the edge of the spreader slide 30° to 45° in front of the small drop of the blood and by drawing until it touches the drop of the blood and the blood was waited until it spread along the edge of the spreader slide and it was moved swiftly forward to make a tongue shaped thin smear having one cell layer thickness at its feather end [18]. After the slides were dried, the thin smear was fixed with methanol. Then the slides were stained using 10% Giemsa working solution for 10 min and the slides were washed gently using running tap water and then the slides were dried using air dry and made ready for microscopic examination [19]. Finally the slides were examined under the microscope using oil immersion objective to look for the asexual and sexual stages of Plasmodium species and reported accordingly [18]. Single infection of P. falciparum or P. vivax and double infection of P. falciparum and P. vivax were detected in the microscopy‐based examination. Quality malaria diagnosis was ensured by involving standardized procedures, and regular monitoring to maintain reliability and reduce misdiagnosis.

2.11. Study Variables

Variables.

2.12. Dependent Variable

Malaria infection.

2.13. Independent Variables

Mother age, educational background, knowledge about malaria transmission, economic status, residence, marital status, family size occupation, presence of stagnant water near home, house style, altitude, presence of bush around home, possession of ITN, ITN utilization, gestational age, antenatal care attendance, and history of IRS spray.

2.14. Operational Definitions

Frequency of ANC attendance: is number of follow up/visit pregnant woman made to health center to check health status.

History of insecticide residual spray: is frequency/number of chemical insecticides sprayed that has residual effect on the walls and roofs of house, that pregnant woman got her house sprayed in the last 12 months.

ITN utilization: refers to the actual use of insecticide‐treated mosquito nets for sleeping by the pregnant women.

Knowledge about malaria transmission: is a pregnant woman's understanding how the disease spreads, primarily through the bite of infected female Anopheles mosquitoes, and other less common routes like blood transfusions or contaminated needles.

Possession of insecticide treated bed net: proportion of pregnant women who possess ITN.

Prevalence of malaria: proportion of pregnant women who are tested positive for Plasmodium parasite/parasites.

2.15. Data Quality Assurance

Data collectors were trained well by a principal investigator on what they are going to conduct during data collection. The principal investigator was supporting and monitoring the entire data collection process to make sure that things are going well. This had been strict during data collection using procedure. On job methods of supervision were followed and continued corrections had been supplemented by supervisors. All data collected were checked before leaving the study area with data collectors in the presence of the principal investigator. Standard operating procedures as well as manufacturer's instructions were strictly followed while doing laboratory tests.

2.16. Data Analysis

Using EpiData, version 3.1. data were entered, edited, and cleaned before exporting it to IBM (International Business Machines Corporation) SPSS (Statistical Package for Social Science) version 24 program for analysis. Descriptive statistics were computed and summarized in table, figures, and text with frequencies, mean or standard deviations were appropriate. Bivariable and multivariable regression were computed to identify the association between independent variables and dependent variable or outcome. In Bivariate analysis variables which scored p value less than 0.25 were included in the multivariable analysis. Potential confounding factors that may influence the outcome variable were controlled at the analysis stage using multivariable regression analysis. The model goodness of fit was tested by the Hosmer‐Lemshow statistics. The model was considered a good fit if it was manifested to be insignificant for Hosmer‐ Lemshow statistics ( > 0.05). The association between malaria and independent variables were reported as odds ratio with 95% CI with a p value less than 0.05 in the multivariable logistic regression analysis were considered statically significant.

2.17. Ethical Consideration

An ethical approval letter for the research was obtained from Institutional Health Research Ethics Review Committee (IHRERC) of Haramaya University, College of Health and Medical Sciences with an ethical approval reference number IHRERC/058/2024. Informed voluntary written and signed consent was obtained from all individual participants in the study. Participation in this study was on voluntary basis. The participants' withdrawal from the study as per their interest was fully respected. All participants who were tested positive for malaria during study were treated. Regional health bureau or district health office was contacted to provide antimalaria drugs, anti‐pain and insecticides treated bed nets. Results were kept confidential.

3. Results

3.1. Sociodemographic Characteristics of Pregnant Women

A total of 446 pregnant women participated in this study with a response rate of 96.95%. One quarter, 26.7% (119/446), of the pregnant women were in the age group of 20–24 years. Concerning marital status, 92.8% (414/446), are married and 7.2% (32/446) are in the other category. Educational status of pregnant women revealed that, 36.1% (161/446) did not attend formal education, 40.4% (180/446) attended primary school, and 23.5% (105/446) attended secondary school. Concerning their occupational status, 75.3% (336/446) are farmers, 12.8% (57/446) are government employee, and 11.9% (53/446) are merchants. When we look at the family size of the pregnant women, ≤ 3, 72.2% (322/446) and ≥ 4, 27.8% (124/446), respectively. Their monthly income in Birr revealed that, < 2000 is 65.0% (260/446), 2000–3000, 30.7% (137/446), and ≥ 3000, 4.3% (19/446). Majority, of pregnant women possessed ITN, 88.6% (395/446), and about 83.0% (370/446) uses their ITN always. From the study participants 60.3% (269/446) are in first trimester and 67.0% (299/446) are multi‐gravid. About 57.2% (255/446) had completed ANC follow‐up. Concerning their knowledge about the disease malaria about 97.8% (436/446) knew malaria is communicable disease. From study participants 93.0% (415/446) of them live near stagnant water (Table 1).

Table 1.

Sociodemographic characteristics of pregnant women in Ongogi health center Jor district, Gambela southwest Ethiopia 2024 (n = 446).

Variables	Category	Frequency (%)
Age group (years)	15–19	89 (19.96)
	20–24	119 (26.71)
	25–29	93 (20.8)
	30–34	88 (19.73)
	≥ 35	57 (12.8)
Residence	Rural	336 (75.3)
	Urban	110 (24.7)
Marital status	Married	414 (92.8)
	Others	32(7.02)
Occupation	Farmer	336 (75.3)
	G/employ	57 (12.8)
	Merchant	53 (11.9)
Education	No formal education	161 (36.1)
	Primary	180 (40.4)
	Secondary	105 (23.5)
Family size	≤ 3	322 (72.2)
	≥ 4	124 (27.8)
Monthly income (birr)	< 2000	290 (65.0)
	2000–3000	137 (30.7)
	≥ 3000	19 (4.3)

3.2. Behavioral and Maternal Characteristics of Pregnant Women

Of the study participants 86.6% (395/446) owned ITN. Of which 48.9% (218/446) had two ITNs. Eight three percent (370/446) used the ITN always. Of the pregnant women participated in this study, 60.3% (269/446) were in the first trimester. Ninety four point four percent knew malaria is transmitted by mosquito bite (Table 2).

Table 2.

Behavioral and maternal characteristics of pregnant women in Ongogi health center Jor district, Gambela southwest Ethiopia 2024 (n = 446).

Variables	Category	Frequency (%)
ITN ownership	Yes	395 (88.6)
	No	51 (11.4)
Number of ITN	One	115 (25.8)
	Two	218 (48.9)
	Three and above	113 (25.3)
ITN utilization	Yes	431 (96.64)
	No	15 (3.36)
Frequency of ITN usage	Sometimes	76 (17.0)
	Always	370 (83.0)
Indoor residual spray (IRS)	Yes	398 (89.24)
	No	48 (10.76)
ANC attendance	Complete	190 (42.60)
	Incomplete	256 (57.40)
Number of trimesters	First	269 (60.3)
	Second	146 (32.7)
	Third	31 (7.0)
Number of gravid	Primigravida	147 (33.0)
	Multigravida	299 (67.0)
Knowledge of malaria communicability	Yes	431 (96.64)
	No	15 (3.36)
Knowledge about way of transmission	Mosquito bite	421 (94.4)
	Contaminated water	25 (5.6)

3.3. Environmental and Household Characteristics of Pregnant Women

About, 93.0% (415/446) of the participants live near stagnant water About 83.6% (373/446) of their home are surrounded by bush. Majority of the participants were from low altitude < 2000 m above sea level (asl), 97.1% (433/446) and remaining are from altitude > 2000 m asl 2.9% (13/446) (Table 3).

Table 3.

Environmental factors associated with malaria among pregnant women in Jor district, 2024 (n = 446).

Variable	Category	Frequency (%)
Presence of stagnant water	Yes	415 (93.0)
	No	31(7.0)
Housing style	Grass roof house	336 (75.3)
	Iron sheet roof house	110 (24.7)
Presence of bush around home	Yes	189 (42.4)
	No	257 (57.6)
Altitude	> 2000 m	51 (11.4)
	< 2000 m	395 (88.6)

Abbreviation: m = meter.

3.4. Prevalence of Malaria Among Pregnant Women

In this study, the prevalence of malaria was found to be 15.2% (95% CI: 11.4, 17.5). This prevalence is comparable with the national pooled prevalence among pregnant women in Ethiopia 12.72% [3]. Of which, 8.96% (40/446) were P. falciparum cases, 2.7% (12/446) were P. vivax cases and 3.6% (16/446) were mixed of P. falciparum and P. vivax.

3.5. Risk Factors Associated With Malaria Among Pregnant Women

In the bivariate analysis, variables including age, educational status, monthly income, ITN ownership, ITN utilization, altitude, knowledge about malaria transmission, and presence of stagnant water were the candidates for multivariable regression. Due to smaller sample size in some of the categories of the independent variables such as ITN ownership and altitude, the confidence intervals are wider (Table 4).

Table 4.

Bivariable analysis of factors associated with malaria among pregnant women in Ongogi health center Jor district 2024.

Variables	Category	Malaria status		Crud OR (95% CI)	p value
		Positive	Negative
Age	< 30	51 (16.9%)	250 (83.1%)	1.15 (0.94, 1.40)	0.18
	≥ 30	17 (11.7%)	128 (88.3%)	1
Residence	Rural	53 (15.8%)	283 (84.2%)	0.84 (0.45, 1.57)	0.59
	Urban	15 (13.6%)	95 (86.4%)	1
Marital status	Married	63 (15.2%)	352 (84.8%)	0.93 (0.34, 2.52)	0.89
	Others	5 (16.1%)	26 (83.9%)	1
Education	No formal education	21 (13%)	140 (87%)	0.69 (0.49, 0.97)	0.03
	Formal education	47 (16.5%)	238 (83.5%)	1
Family size	≤ 3	52 (16.1%)	270 (83.9%)	1
	≥ 4	16 (12.9%)	108 (87.1%)	1.30 (0.71, 2.38)	0.39
Monthly income (birr)	< 2000	41 (14.1%)	249 (85.9%)	0.69 (0.45, 1.06)	0.09
	2000–3000	20 (14.6%)	117 (85.4%)	1
	> 3000	7 (36.8%)	12 (63.2%)	3.41 (1.11, 9.71)	0.02
ITN ownership	Yes	60 (15.4%)	329 (84.6%)	1
	No	8 (14%)	49 (86%)	4.92 (1.12, 20.7)	0.03
Number of ITN	One	12 (10.4%)	103 (89.6%)	0.99 (0.69, 1.42)	0.95
	Two and above	56 (16.9%)	275 (83.1%)	1
ITN utilization	Yes	61 (14.2%)	370 (85.8%)	1
	No	6 (40.0%)	9 (60.0%)	2.53 (1.12, 5.73)	0.03
Frequency of ITN usage	Sometimes	11 (14.5%)	65 (85.5%)	0.93 (0.46, 1.87)	0.84
	Always	57 (15.4%)	313 (84.6%)	1
ANC attendance	Complete	30 (15.8%)	160 (84.2%)	1
	Incomplete	38 (14.8%)	218(85.2%)	0.93 (0.55, 1.56)	0.78
Number of trimesters	First	44 (16.4%)	225 (83.6%)	1
	Second	19 (13%)	127 (87%)	0.98 (0.36, 2.70)
	Third	5 (16.1%)	26 (83.9%)	1.13 (0.74, 1.75)	0.57
House style	Iron roof house	53 (15.8%)	283 (84.2%)	1
	Grass roof house	15 (13.6%)	95 (86.4%)	0.84 (0.45, 1.57)	0.59
Bush around	Yes	30 (15.9%)	159 (84.1%)	0.92 (0.55, 1.55)	0.75
	No	38 (14.8%)	219.(85.2%)	1
Altitude	> 2000 m	7 (13.7%)	44 (86.3%)	4.92 (1.17, 20.71)	0.03
	< 2000 m	66 (16.7%)	329 (83.3%)	1
Number of gravid	Primi	20 (13.6%)	127 (86.4%)	1.21 (0.69, 2.13)	0.50
	Multi	48 (16.1%)	251 (83.9%)	1
Knowledge of malaria communicability	Yes	61 (14.2%)	370 (85.8%)	1
	No	7 (46.7%)	8 (53.3%)	0.71 (0.15, 3.44)	0.67
Knowledge about way of transmission	Mosquito bite	59 (14.0%)	361 (86.0%)	1
	Contaminated water	10 (38.5%)	16 (61.5%)	0.29 (0.12, 0.69)	0.005
Presence of stagnant water	Yes	60 (14.5%)	355 (85.5%)	0.49 (0.21, 1.14)	0.09
	No	8 (25.8%)	23 (74.2%)	1

In the multivariable regression analysis, the odds of malaria was 1.32 (AOR = 1.32; 95% CI: 0.45–3.24; p = 0.02) times higher among pregnant women who had no formal education than mothers who had formal education. Pregnant woman who had no knowledge how malaria is transmitted were 2.7 times (AOR = 2.7; 95% CI: 0.14–4.67; p = 0.005) more likely to be malaria infected than their counterparts. Pregnant women who lived in areas where there is stagnant water had 3.61 times (AOR = 3.61; 95% CI: 1.15–6.45; p = 0.03) increased odds of having malaria infection compared to mothers who lived in areas where there is no stagnant water. The odd of malaria was 5.74 (AOR = 5.74; 95% CI: 1.32–24.8; p = 0.02) times higher among pregnant women who did not have insecticide treated bed net compared to their counterpart. Those who comes from altitude < 2000 m above sea level were 5.26 (AOR = 5.26; 95% CI: 1.193–23.18; p = 0.03) times more likely protected from malaria compare to the counterpart. Due to smaller sample size in some of the categories of the independent variables such as ITN ownership, ITN utilization and altitude, the confidence intervals are wider (Table 5).

Table 5.

Multivariable analysis of factors associated with malaria among pregnant women in Ongogi health center Jor district, 2024.

		Malaria status
Variable		Positive (%)	Negative (%)	Adjusted OR (95% CI)	p value
Age	< 30	51 (16.9%)	250 (83.1%)	0.81 (−0.03, 0.87)	0.42
	≥ 30	17 (77.9%)	128 (88.3%)	1
Monthly income in (birr)	< 2000	41 (14.1%)	249 (85.9%)	1.39 (0.10, 1.417)	0.16
	2000–3000	20 (14.6%)	117 (85.4%)	1
	> 3000	7 (36.8%)	12 (63.2%)
Education	No formal education	21 (13%)	140 (87%)	1.32 (1.04, 3.2)	0.02
	Formal education	47 (16.5%)	238 (83.5%)	1
ITN ownership	Yes	60 (15.4%)	329 (84.6%)	1
	No	8 (14%)	49 (86%)	5.74 (1.32, 24.8)	0.02
ITN utilization	Yes	61 (14.1)	370 (85.8%)
	No	6 (40.0%)	9 (60.0%)	−0.33 (−0.32, 0.23)	0.74
Knowledge about way of transmission	Mosquito bite	59 (14.0%)	361 (86.0%)	1
	Contaminated water	10 (38.5%)	16 (61.5%)	2.72 (1.41, 4.6)	0.005
Presence of stagnant water	Yes	60 (14. %)	355 (83.4%)	3.61 (1.15, 6.4)	0.03
	No	8 (25.8%)	23 (74.2)	1
Altitude	> 2000 m	7 (13.7%)	44 (86.3%)	1
	< 2000 m	66 (16.7%)	329 (83.3%)	5.26 (1.19, 23.18)	0.03

4. Discussion

In the present study, the prevalence of malaria among pregnant women was 15.2% (95% CI: 11.4–17.5). This finding is in line with a systematic review and meta‐analysis conducted in Ethiopia, such as 11.8% in Majang Zone, Gambella Region, Southwest Ethiopia [5], 12.72% a recent systematic review and meta‐analysis in Ethiopia [3] and studies carried out n East Dembia District Northwest Ethiopia 14% [20], in Kenya that reported 12.3% [21], in eastern Sudan 13.7% [22], and in Lake zone of Tanzania 12.8% [23].

Our finding, 15.2% is higher than the study conducted in Damot Woyide district, Southern Ethiopia which reported 8.2% [24], in Sherkole district, Benishangul Gumuz regional state 10.2% [10], and in Fendeka town health facilities, Jawi District, Northwest Ethiopia 11.2% [25], and in North Shoa which revealed 5.7% and 3.4% of malaria prevalence indicated by microscope and rapid diagnostic test (RDT), respectively [26], in Southwest Nigeria, Lagos 7.7% [27], in Chhattisgarh, India 1.3% among pregnant women at antenatal clinics and 1.9% at Delivery unit [28], in Ghana 8.9% [29] and in Akatsi South District in Ghana [30]. This higher finding in comparison with all the aforementioned studies could be explained by difference in sample size, study design, season of year, sociodemographic factors, access to health service, geographical location, and ITN coverage [31].

On the contrary, our result 15.2% was lower than the studies carried out in different part of the world such as 24.4% of gestational malaria in Metti health center in Majang zone Gambella Region [6], systematic review and meta‐analysis in sub‐Saharan Africa 26.1% [32], in Bungoma county, Kenya 26.1% [33], in a semi‐urban community of north‐western Nigeria 41.6% [34], in Lagos Nigeria 60% [35], in the middle belt of Ghana 20.4% [36], in Abakaliki southeast Nigeria 29% [37], in Port Harcourt, Rivers State, Nigeria 26% [38], in northern Ghana 47% [39], in northwestern Uganda 26.1% [40], in Kastina Metropolis, Nigeria 36.5% [41], in Kisumu, western Kenya 18.0% [42], and in Ekiti State, Southwest Nigeria [43]. The variation between our study and the above studies could be explained by difference in healthcare access, study design, seasonality, sample size, study population, the method of laboratory diagnosis, geographical factors, sociodemographic factors and ITN coverage [44].

In this study, 8.96% of the malaria were caused by P. falciparum, 2.7% were by P. vivax and 3.6% were by the mixed species of P. vivax and P. falciparum. This study indicated prevalence of plasmodium species lower than the study conducted in North Shoa which reported the overall prevalence of malaria among symptomatic pregnant women were 12.2%, 4.8%, and 3.8% were P. falciparum, P. vivax, and mixed infections, respectively [26]. The possible explanation for the difference may be attributed to altitude difference, environmental favorability for malaria parasite, difference in access to health service individual difference in applying malaria protection methods and the methods used for diagnosis [45].

In this study, 9.9% of the cases were caused by P. falciparum species this was lower than study conducted in Fendeka town health facilities, Jawi District, North west Ethiopia which reported 53% of the cases were caused by P. falciparum [25], and lower than the finding of a systematic review and meta‐analysis 22.1% [32]. This could be possibly explained by the difference in study designs, season of the year, geographical location and the methods used for data collection. Nevertheless, our finding of 9.9% for P. falciparum is in agreement with a study in Ghana 8.9% [29].

Pregnant woman who did not attended formal education were 32% (AOR = 1.32; 95% CI: 1.04–3.24; p = 0.02) more likely to be malaria infected than those pregnant women who attendee formal education. Pregnant women with less education are more likely to have malaria than those with more education; because educated mothers are more likely to involve in malaria preventive activities [46, 47, 48]. Furthermore, higher education levels are associated with a lower prevalence of malaria in pregnant women, likely due to improved access to information, resources, and healthcare, as well as better decision‐making power within the household [49]. This result is in consistent with a study done among pregnant women attending antenatal care at three health centers in northwest Ethiopia [13].

Pregnant women who didn't own ITN were six times (AOR = 5.74; 95% CI: 1.32–24.8; p = 0.02) more likely to be malaria infected than those pregnant women who owned the ITN. Insecticide‐treated bed net ownership and use among pregnant women varies by region, and is often below recommended levels [50]. Knowledge about ITN use, access to ITN, and its cost were the reasons that affect its use. This is supported by a previous study indicating that pregnant women who lack access to and don't use insecticide‐treated nets (ITNs) have a significantly higher risk of malaria infection compared to those who do, highlighting the crucial role of ITNs in preventing malaria during pregnancy [51]. This finding is consistent with studies carried out in north Shoa [52] and in east Belessa, northwest Ethiopia [53].

Pregnant women who had no knowledge how malaria is transmitted were three times (AOR = 2.7; 95% CI: 1.41–4.67; p = 0.005) more likely to be malaria infected than their counterparts. Pregnant woman's knowledge about way of transmission differs, and the influencers were income, educational status being rural or urban resident [47]. Additionally, in areas with malaria, better knowledge about malaria transmission among pregnant women is associated with lower malaria prevalence, as it enables them to take preventative measures and seek timely treatment [47]. This finding is in agreement with a study conducted in north Shoa [26, 34].

Residing near stagnant water is a predisposing factor for malaria in pregnant women. Pregnant women who lived in areas where there is stagnant water were four times (AOR = 3.61; 95% CI: 1.15–6.45; p = 0.03) more likely to be malaria infected than those mothers who lived in areas where there is no stagnant water. Furthermore, Jor district is among the swampy districts which are affected by flooding every year. The flooding makes the district at high risk for a malaria epidemic compared to other districts found in Gambella regional state [16]. Besides, pregnant women living near stagnant water have a significantly higher risk of malaria infection, with studies showing odds ratios ranging from 3.52 to 4.43 times greater than those living further away [54]. This finding is also in congruent with a study conducted in Ghana [29].

In areas with malaria transmission, altitude plays a crucial role in malaria prevalence [55]. In accordance with our study findings, pregnant women who lived in lowland area were five times (AOR = 5.26; 95% CI: 1.193–23.18; p = 0.03) more likely to be malaria infected than those mothers who lived in highland area. Also, Jor district in the Gambella region has an altitude that varies from 460 to 1650 m above sea level. The district is characterized by a large flat landscape and a modestly rising plateau to the east [56], making it a high‐risk region for malaria transmission, especially in the western lowland areas. Furthermore, lower altitudes generally have higher risk for pregnant women, but this can vary depending on other factors like temperature and climate [55]. This is also in line with a study conducted in Burkina Faso [57].

In all, the prevalence of malaria among pregnant women in our study was 15.2% (95% CI: 11.4–17.5). Lack of formal education, non‐ownership of ITNs, lack of knowledge about malaria transmission, residing at lower altitudes and presence of stagnant water near residence of pregnant women were found to be associated with prevalence of malaria.

5. Conclusion and Recommendations

5.1. Conclusion

The prevalence of malaria was high in the study area. Of the participated pregnant women, 3 out of 20 were found to be infected with malaria and P. falciparum is the most predominant Plasmodium species in the area. Non‐ownership of ITNs, lack of formal education, lack of knowledge about malaria transmission, and residing at lower altitudes and presence of stagnant water near residence of pregnant women were associated with the prevalence of malaria among pregnant women.

5.2. Recommendations

Public health actions such as facilitating access of pregnant women to formal education in the long run, increasing pregnant women' access to ITN along with health education on proper utilization of ITN, health information dissemination about transmission of malaria and environmental modification such as removal of stagnated water for the control of mosquito vectors were recommended. Furthermore, future research involving molecular methods like PCR is also recommended.

5.3. Limitations of the Study

Because the study used a cross‐sectional study design, it does not show a direct temporal relationship. Hence, future research needs to focus on case‐control or interventional studies to identify the actual predictors of malaria among pregnant women. The study was only conducted on some variables. The other second limitation of this study is the inability to diagnose the blood samples using PCR thereby decreasing the true prevalence anticipated to get as it is more sensitive than microscopy. Due to smaller sample size in some of the categories of the independent variables such as “non‐ownership of ITN and altitude the confidence intervals are wider” is the third limitation of this study.

Author Contributions

Okwom Oguta: conceptualization, methodology, software, data curation, investigation, formal analysis, writing – original draft. Jemal Mohammed: writing – review and editing, supervision. Ukash Umer: writing – review and editing, supervision. Ephrem Tefera Solomon: writing – original draft, writing – review and editing, supervision.

Conflicts of Interest

The authors declare no conflicts of interest.

Transparency Statement

The corresponding author, Ephrem Tefera Solomon, affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Oguta O., Mohammed J., Umer U., and Solomon E. T., “Malaria in Pregnancy and Predisposing Factors in Jor District of Gambella Region, Southwest Ethiopia: A Cross‐Sectional Study,” Health Science Reports 8 (2025): 1‐11, 10.1002/hsr2.71310.

Data Availability Statement

The data sets generated and analyzed for this study will not be available publicly due to data protection law. But it can be obtained from the corresponding author upon reasonable request.