Determinants of Hemoglobin Among Pregnant Women at Agro-Pastoralist Communities in South Omo Zone,Ethiopia: Community Based Cross-Sectional Study,Nutrition Experience from Movable Community

Abstract

Background:

Low hemoglobin level is the most common public health problem during pregnancy in developing countries including Ethiopia, which is affecting both mother and fetus. However, the determinants of anemia among pregnant women are not well studied.

Objective:

To assess the determinates of hemoglobin among pregnant women in rural agro-pastoralist communities in the South Omo zone, Ethiopia

Method:

Community-based cross-sectional study was done in rural agro-pastoralist communities. A multistage stratified sampling technique was used to select 526 pregnant women. Data were collected by using structured questionnaires. Hemoglobin level was measured by using HemoCue ^® Hb301. Data were analyzed by using a statistical package for the social science version 26. Descriptive (Mean, standard deviation, frequency, range), bivariate and multivariate analysis was carried out to check the association between lower hemoglobin levels and independent variables. The output is presented in tables and figures.

Result:

The mean (±SD) of hemoglobin concentration was 11.8 ± 1.7. The overall prevalence of anemia was 39.9% [95% CI: 35.5, 44.4], 19.4% (95% CI: 16.0, 23.2) was mild, 19.6% (95% CI: 16.27, 2.5) was moderate and 0.9% (95% CI: 0.25, 2.25) was severe anemia. Not taking IFA (AOR = 5.7(3.3, 9.8)), severe under nutrition (AOR = 8.9(2.1, 37.3)), no fish food (AOR = 2.4(1.3, 4.5)), drinking coffee (AOR = 1.6(1.0, 2.6)), moderate food insecurity (AOR = 2.5(1.4, 4.6)), and no malaria infection (AOR = 0.6(0.4, 0.9)) were statistically significant with anemia.

Conclusion:

The anaemia is a public health problem in this study area. Therefore, nutrition education and counselling to enhance iron supplementation, dietary diversity and a flesh diets are very essential to enhance haemoglobin levels.

Keywords

Agro-pastoralist determinates hemoglobin level pregnant women rural community

Introduction

Globally, Anemia is the most common public health problem during pregnancy.¹ It affects developing and developed countries.² In recent estimate of anemia globally, 1.8 billion people are living with anemia.¹ About 30% of non-pregnant women and 37% of pregnant women were anemic.³ According to Karami et al⁴ the burden of anemia particularly among pregnant women is high, thus, demanding targeted interventions in this population. Furthermore, the current evidence on anemia demonstrated that, there is high proportion of pregnant women affected globally.^1,5-7

Moreover, systematic review and meta-analysis studies conducted in low- and middle-income counties had shown that, 42.7% of women experienced anemia during pregnancy.^4,8 Besides, in 2017, and 2019, WHO stated iron deficiency during pregnancy was identified as the most significant public health problem.^3,9

The documented evidence from 82 low and middle income countries on the burden of anemia among reproductive age is high, the developing country such as West Africa, Middle Easter and Asia, including Gambia 53.3%, Senegal 47.3%, Male 47.6%, Yemen 57.4%, India 49.9%, of prevalence was reported.¹⁰ Besides, other study proof from global burden of disease demonstrated high prevalence of anemia.¹

In Ethiopia, demographic and health survey (DHS) report indicated that, 24% women had anemia.¹¹ Besides, different localized researches studies in Ethiopia have revealed a high burden of anemia among pregnant women range from 23.2%−33%.^12-15

Pregnant women require supplementary iron and folic acid to meet their own nutritional needs as well as those of the developing fetus.^16,17 Micronutrient deficits in iron and folic acid during pregnancy can possibly and undesirably impact the health of the mother, her pregnancy, as well as fetal development.^18-20 Recent evidence has shown that the use of iron and folic acid supplements is associated with a reduced risk of iron deficiency and anemia in pregnant women.^21-23 Moreover, failure to take iron-folic acid during pregnancy, possibly lead to iron deficiency anemia.^19,24

Anemia is contributing significant public health consequences for human wellbeing and social and economic improvement.^1,9,25 In addition, anemia in pregnancy increases the risk of low birth weight, preterm birth, perinatal and maternal mortality.^8,26-28 Moreover, poor psychological and motor developments negatively affect productivity and economic growth.^29,30

In Ethiopia, the government has exerting unlimited efforts to improve pregnant women nutritional status, despite of that, the burden of anemia is still a medical challenge. On top of that, the existing published evidence concentered in central and agrarian communities. However, there is no evidence in remote and pastoralist communities. Therefore, this study aimed to assess determinates of hemoglobin among pregnant women in agro-pastoralist rural communities in South Omo Zone, Ethiopia.

Materials and Method

Setting

This study was conducted in the South Omo Zone, 1 of 15 zones in the Southern Nations, Nationalities, and People’s Region (SNNPR) of Ethiopia. The zone capital is Jinka, a city in the Southern part of the SNNPR; 480 km from the regional capital of SNNPR, Hawassa; and 850 km from Addis Ababa, the capital of Ethiopia.³¹ The Central statistical agency CSA estimates a population of 749 214 in the South Omo Zone, accounting for nearly 4% of the total population of the region, of whom 359 623 are males and 389 591 are women.³² An estimated 26 531 of the population is pregnant women and 11 487 pregnant women³¹ are residing in the study districts. The current study was conducted in 5 randomly selected districts of south Omo Zone such as Dasench, Hammer, Benytsemay, Malle, and South Ari.

The main food harvests produced in the Zone are maize, sorghum, “teff”, coffee, vegetables, root crops, pulses, and oilseeds. The communities in the Zone are mainly agro-pastoralist and their livestock include cattle, goat, sheep, horse, mule, and others.³³

Study design and period

The community-based, cross-sectional study design was used. This study was conducted from April to June 30, 2019.

Population

Source population

• Pregnant women aged 15 to 49 years who reside in the South Omo Zone.

Study population

Pregnant women aged 15 to 49 years who have been exposed to under nutrition in the previous year reside in randomly selected rural “kebeles” in the districts

Inclusion criteria and eligibility criteria

Inclusion criteria

• Pregnant women aged 15 to 49 years who exposed to under nutrition in the previous year

Exclusion criteria

• Pregnant women who were unable to respond or communicate due to critically illness during the data collection period.

• Pregnant women, who were unwilling to consent to blood testing

• Pregnant women who could not be found at home after 3 repeated visits

Sample size determination

The sample size was determined by using single population proportion formula: with the assumption of 95% confidence level and 5% margin of error, 5% of non-response rate, and 1.5 design effect, considering the previous proportion of 32% prevalence of anemia.³⁴ The final sample size considered for study was 526.

n = \frac{(zα / 2) 2 * p * (1 - p)}{d^{2}} = {(1.96)}^{2} \times 0.32 (1 - 0.32) / {(0.05)}^{2} = \underline{526}

Sampling technique

Multi-stage stratified sampling method used to stratify the ecological zones; the criteria used for ecological zone classification, considered altitude. Initially, all districts in the Zone were listed and stratified into 3 ecological zones based on their altitude: highland, midland, and lowland. For each stratum, districts were selected randomly and then kebeles (smallest administrative structure) were selected through computer based simple random sampling. The sample size was then allocated to the strata proportional to the population size. Pregnant women were registered in the kebele through a health extension program. Simple random sampling was used to select pregnant women age group of 15 to 49 years old from the registered list.

Data collection procedures

An interviewer administered, structured and pretested data collection tools were used to collect data. The socio-demographic aspect of the questionnaire was adapted from DHS¹¹ and food frequency component was prepared from existing literature and the dietary diversity assessment tool for pregnant women was also adapted from the Food and Agricultural Organization.³⁵ Moreover, a HemoCue ® Hb301 was used to measure blood hemoglobin levels. The samples were taken from pregnant women who had follow-up their pregnancy. Blood was taken from the fingertips of respondents using micro cuvettes and inserted into the Haemocue. The measurements were then recorded. The overall testing procedure was carried out by an experienced laboratory technician. Basic safety measures were taken during the collection of the blood samples. Initially, the questionnaires were developed in English and were later translated into the local language, and then the questionnaires were again translated back into English for language editing by experts. Eight trained nurses and 3 supervisors were recruited for data collection at field.

Operational definition

Anemia defines hemoglobin levels for pregnant women: <11 g/dl is mild anemia, a hemoglobin level between 7 and 10 g/dl with moderate anemia, and a hemoglobin level <7 g/dl with severe anemia.^9,36

Dietary diversity: A dietary variety consisting of fewer than 3 nutritional groups demonstrates minimum dietary diversity(MDD), a diet with between 4 and 5 nutritional groups comply with medium dietary diversity (MDD), while a variety of 6 or more nutritional categories demonstrates high dietary diversity (HDD).³⁵

Under nutrition: MUAC < 23 cm consider as risk for under nutrition.³⁷

Data quality assurance

The researchers carefully designed data collection tools. Data collectors were selected and recruited based on their experiences, such as nurses and laboratory technicians. After recruitment process completed, 2 days training had given for the data collectors and supervisors. The pre-test was carried out in the nearby “Bakadewela” district in which a population with comparable socio-demographic attributes to the study population. The pre-test study was conducted among 52 pregnant women. After the pre-test study was carried out, the discussion was made for half day at Jinka town and minor instrument revision had done based on findings. Researchers and supervisors had conducted field data collection supervision in daily bases.

Data management and analysis

The researchers were manually checked the data completeness, consistency, missed values and unlikely responses before actual data entry initiated. Moreover, coded the responses and entered data into Epi info version 7 and then exported to SPSS software version 26, and then cleaned, analyzed, interpreted, and summarized data. The descriptive and bivariate analysis was done, and then multivariate logistic regression analysis was applied to assess the association of socio-demographic and other independent factors with anemia. The outputs of the regression analysis were presented with a crude odds ratio (COR) and adjusted odds ratio (AOR) with their respective confidence intervals (CI). The criteria for exporting variables to the multivariate model were P-value <.25. Furthermore, variables with P-value <.05 were used to declare statistically significant association.

In this study, the model fitness was checked by Hosmer-Lemshow’s goodness fit test which was found non-significant. Besides, Multicollinearity was checked between independent variables by using variance inflation factors (VIF < 10) test. This was found no collinearity identified.

Ethical consideration

Ethical approval was secured from the Ethics and Higher Degrees Committee of the University of South Africa (UNISA). A permission letter was secured from the South Nation Nationality People Regional Health Bureau and the South Omo Zone health department. The permission letters clear the details of the community-based research study; the purpose and objectives of the study, the risks, and benefits to the respondents; explain the roles and responsibilities of the study respondents; ensured informed consent. The individuals who were not interested to participate were given the right to do so. The confidentiality of the respondents was ensured throughout the study. Ethical principles were respected in the study process.

Results

Demographic characteristics of respondents

A total of 526 study subjects were carefully selected, of which, 469 pregnant women successfully completed the questionnaire voluntarily, yielding a response rate of 89.2%. The mean (±SD) age of the research respondents were 27.4 ± 4.9 with minimum and maximum ages of 15 and 42 years old, respectively. The median initial marital age was 18.0. The mean ± (SD) for the first marriage was 18.31 ± 1.88 and a range with a minimum value of 14 and a maximum age value of 24 years, respectively(Table 1).

Table 1.

Demographic characteristics of pregnant women presented in community of South Omo Zone, Southern, Ethiopia.

Variable	Category	Frequency	Percent
Age (n = 469)
	15-24 y	123	26.2
	24-30 y	246	52.5
	>30 y	100	21.3
Marital status (n = 469)
	Single	12	2.6
	Married	451	96.2
	Divorced	2	0.4
	Widowed	4	0.9
Religion (n = 469)
	Protestant	172	36.7
	Orthodox	41	8.7
	Muslim	40	8.5
	Cultural religion	216	46.1
Education status PW (n = 469)
	No formal education	371	79.1
	Formal school attended	98	20.9
Pregnant women occupation (n = 469)
	Housewife	387	82.5
	Farmer	28	6
	Pastoralist	41	8.7
	Other	13	2.8
Family size (n = 469)
	1-3 member	148	31.6
	4-6 member	240	51.2
	>6 member	81	17.3
Spouse education (n = 465)
	No formal education	361	77.6
	Formal school attended	104	22.4

Majority of the respondents, 96.2% (n = 451) of the pregnant women were married. In this study area, >16 ethnic groups lived peacefully in cultural diverse settings. Nearly half of the respondents, 46.1% (n = 216) the pregnant women were cultural religion followers, followed by one-third of the respondents, 36% (n = 172) were protestant followers. The mean (±SD) for level of education attended was 1.26 (±2.77). A very large proportion, 78%(n = 366) of the pregnant women were illiterate. Similarly, 76% of the partner’s education were illiterate (Table 1).

Majority, 82.5% (n = 387) of the respondents were housewives. Besides, the mean (±SD) of the family size was 4.7(+2.7). Nearly, 50% of the partners were working as pastoralist, followed by 37.8% (n = 176) of the respondents were in farming, 6.5% (n = 30) were working as merchants, and 3.4% (n = 16) were working as employees. Almost all, 99.6% (n = 466) of the respondents were living within rural (Table 1).

Prevalence of anemia

The mean (±SD) of hemoglobin concentration adjusted for altitude was 11.8 ± 1.7 and smallest and largest values ranged from 6 to 16 g/dl. The overall prevalence of anemia was 39.9% [95% CI: 35.5, 44.4]; 19.4% (95% CI: 16.0, 23.2) was mild, 19.6% (95% CI: 16.27, 2.5) was moderate and 0.9% (95% CI: 0.25, 2.25) was severe anemia (Figure 1).

Figure 1.

Prevalence of anemia among pregnant women in the rural community of South Omo Zone, South nation nationality people, Ethiopia.

The main reason for not taking iron sulphate

Of the total respondents, 64% (n = 300) of the research respondents reported that they did not take ferrous sulfate pills, whereas only, 36% (n = 169) respondents reported as they were taking iron-folic acid (IFA) supplementation. The respondents were requested to provide the major reason for not taking or not using the tables continuously, 62.3% (n = 292) of the research respondents indicated that they were experienced unwanted consequences (side effects) of the tablets, followed by 56% (n = 267) of the respondents had reported that, many of them forgot to take the pills. Similarly, 48% (n = 255) of the respondents reported that they were unaware of the benefits of the pills and one-third (31.6%) of the respondents revealed that they were afraid to take the tablet, may harm their newborn baby. Moreover, a significant proportion of the respondents, 13.9% (n = 65) indicated the costs, even though the service was free for pregnant women. Simultaneously, more than a quarter, 28.4% (n = 133) of the pregnant women reported that they lacked belief in the usefulness of the pills (Figure 2).

Figure 2.

Reason for not taking or not using ferrous sulfate tablets among pregnant women at the community level, South Omo Zone, Ethiopia.

Predictors associated with anemia

Bivariate analysis was done to determine the significance level among following variables such as wealth quintile, ecology, religion, malaria infection, taking ferrous sulfate, dietary diversity, nutritional information, under nutrition, family size, pregnant women occupation, partner’s education, para, gestational age, ANC visit, knowledge score, nutrition practice score, workload, flesh meat, fish, drinking coffee /tea, health facility walking distance, awareness of anemia, iron-rich food, and food insecurity level were found to be statistically significant, with the P-value <.25 was accepted as the cut-off point for multivariate analysis.

Pregnant women who had low dietary diversity (LDD) in the 24-hour preceding the interview, indicated that there was a high prevalence of anemia (79.1%) when compared with pregnant women who consumed high dietary diversity (HDD) (4.0%). The prevalence of anemia decreased when the dietary diversity level increased and vice-versa.

Likewise, the prevalence of anemia was high (85.5%) among study respondents, who did not take iron sulfate when compared with those who took iron sulfate (14.4%) regularly. It was notable that, not taking/using iron sulfate was statistically significant with anemia (x² = 61.3, P = .000). The odds of being anemic were 5.7 times higher among pregnant women who were not taking or using iron sulfate than the respondents’ groups who were taking iron sulfate (AOR = 5.7, 95% CI: 3.3, 9.8).

After bivariate logistic regression model analysis was carried out, the eligible variables, with P-values that were <.25 were entered in the logistic model (called multivariate analysis) to control confounder factors.

The risk of anemia was reduced in the respondents’ groups who reported walking a short distance daily that is, walking <30 minutes to get to the health facility, compared to respondents who walked long distances (a distance greater than 30 minutes). The odds of anemia were 60% less likely to occur among those who walked <30-minutes than those who walked distances greater than 30 minutes (AOR = 0.4, 95% CI: 0.3, 0.6).

Moreover, the odds of anemia were 40% less likely to occur among the respondents who had no malaria infection in the past 3 months compared with those who had malaria infection in the past 3 months. In addition to this, pregnant women who had gestational age in the first and second trimesters were negatively associated with anemia (AOR = 0.5, 95% CI: 0.3, 0.9).

Table 2 indicated that pregnant women reported that the odds of being anemic were 8.9 times higher among the severely under-nutrition groups compared to those who had no under nutrition (AOR = 8.9, 95% CI: 2.1, 37.3). Moreover, pregnant women who had not consumed fish as a meal, had 2.4 times (AOR = 2.4, 95% CI: 1.3, 4.5) increased risk of having anemia. Moreover, the chance of developing anemia was 2.5 times higher among the “moderate food insecure” group compared with their food secured counterpart respondents [(AOR = 2.5,95% CI:1.4, 4.6) (Table 2).

Table 2.

Multivariate Analysis Variables Characteristics Among Pregnant Women in Rural Community of South Omo Zone, Ethiopia.

Variables	Predictors	Anemia		CrudeOR (95% CI)	AdjustedOR (95% CI)	P-value
Variables	Predictors	Yes	No	CrudeOR (95% CI)	AdjustedOR (95% CI)	P-value
Nutritional status
	Mild under nutrition	76	108	1.4 (0.9, 2.1)	1.5 (0.9, 2.3)	0.079
	Moderate Under nutrition	30	27	2.3 (1.2, 4.1)	2.3 (1.2, 4.4)	0.10
	Severe Under nutrition	10	3	6.7 (1.8, 25.3)	8.9 (2.1, 37.3)	0.003***
	Normal nutritional status	71	144	1	1	R
Have you eaten fish
	No	171	233	2.2 (1.2, 4.0)	2.4 (1.3, 4.5)	0.006***
	Yes	49	16	1	1	R
Drink coffee or tea
	No	56	43	1	1	R
	Yes	131	239	2.3 (1.5, 3.7)	1.6 (1.0, 2.6)	0.05
Know the benefit of birth spacing
	No	158	212	1.8 (1.1, 2.9)	1.7 (1.0, 3.0)	0.05
	Yes	29	70	1	1	R
Household food security level
	Food secured	22	32	1.3 (0.7, 2.5)	1.3 (0.6, 2.6)	1.3
	Mild food insecure	43	60	1.4 (0.8, 2.3)	1.5 (0.8, 2.7)	0.15
	Moderate food insecure	45	36	2.5 (1.5, 4.2)	2.5 (1.4, 4.6)	0.002***
	Severe food insecure	77	154	1	1	1
Distance to HF
	>30 min	62	159	1	1	1
	<30 min	125	123	0.3 (0.2, 0.6)	0.4 (0.3, 0.6)	0.000***
Taking IFA
	No	160	140	6.0 (3.7, 9.6)	5.7 (3.3, 9.8)	0.000***
	Yes	27	142	1	R	1
Malaria infection
	Yes	82	142	1	1	1
	No	105	140	0.8 (0.5, 1.1)	0.6 (0.4, 0.9)	0.04***
Gestational age
	First trimester	63	96	0.6 (0.4, 1.0)	0.5 (0.3, 0.9)	0.021***
	Second trimester	75	138	0.5 (0.3, 0.8)	0.6 (0.3, 1.0)	0.058
	Third trimester	49	48	1	1	R

***

NB: significantly associated (P-value < .05).

Discussion

In the current study, the overall prevalence of anemia was 39.9% [95% CI: 35.5, 44.4], which was a very high burden and categorized as having severe public health significance in the study area.⁹ This result was similar to the previous study evidence in Lao PDR, 39.2%,³⁸ Ghana, 40.8%,³⁹ and also study report from the local context, pastoralist communities of Ethiopia, 39.8%,⁴⁰ and Southern, Ethiopia, 39.94%.⁴¹

Our study had revealed a higher prevalence of anemia when compared with previous studies conducted by Enawgaw et al 12.9%,⁴² Lebso et al 23.2%,¹² Geta et al 26.4%,¹⁴ Getahun et al 27.6%,⁴³ Bekele et al 32.8%,⁴⁴ Kejela et al 33%,⁴⁵ Gebre and Mulugeta 36.1%,⁴⁶ Alemayehu et al 36.1%,⁴⁷ Karami et al 36.8%,⁴ and Animut and Berhanu 37.5%.⁴⁸ The possible explanations for higher burden of anemia in the study setting could be seasonal, socioeconomic, study respondents were movable communities, and agro-ecological variation may contribute for higher burden.

This finding had lower prevalence of anemia than the previous study conducted by Liyew et al 41.82%,⁴⁹ Shitu and Terefe 44.28%,⁵⁰ Wemarkor 50.8%,⁵¹ Meda et al 63.1%,⁵² Ekpe et al 72.6%,⁵³ Saaka et al 70%,⁵⁴ Bereka et al 63.8%,⁵⁵ and Gibore et al 80.8%.⁵⁶ The possible justification for prevalence difference could be socioeconomics, geographical/a study-setting discrepancy, and study respondent’s variations.

The proportion of anemia was higher (41.2%) among severe food-insecure households compared to food secured households (11.7%). The chance of developing anemia is 2.5 times higher among the modest food insecurity category compared with food secured respondents. This finding is comparable with other studies conducted elsewhere in Pakistan,⁵⁷ in Brazil,⁵⁸ and also from the local context, the Amhara region Ethiopia,⁵⁹ and North East Ethiopia.¹⁵ In contrast, anemia is not associated with Food insecurity.⁶⁰ The possible justification for this could be the lack of adequate and preferable food that is rich in iron nutrients lack may lead to malnutrition and then lead to anemia.

The finding of this study showed that, those who were under-nourished respondents were 8.7 times more susceptible to develop anemia than well-nourished respondents. This study was consistent with study conducted elsewhere in Gondar, Ethiopia,³⁷ West Shewa Zone, Oromia Region, Ethiopia,⁶¹ Wollega Oromia, Ethiopia⁶² and Dessie town, northern central Ethiopia,⁶³ Bench, Ethiopia,⁶⁴ and Jigjiga.⁶⁵ The likely explanation for this could be lack of adequate nutrition during pregnancy leads to deficiency of micronutrients so that there is a higher chance of developing anemia.

The results of this study demonstrated that pregnant women who did not consume fish are 2.4 times higher odds to have anemia than those who consumed fish. This finding was comparable with the existing studies conducted in Ghana,³⁹ Louisiana,^66,70 South Africa⁶⁷and Jigjiga, Ethiopia.⁶⁵ The possible clarification can be, fish/meat has a rich source of iron and is better absorbed from the body.

This finding revealed that, pregnant women who had low dietary diversity (LDD) in the 24 hours, had a high prevalence of anemia (79.1%) when compared with pregnant mothers, who had high dietary variety (HDD) (4.0%). The prevalence of anemia decreases when dietary diversity levels increase and vice-versa. Researchers could not find any other significant associations from multivariate analysis. This finding is comparable with the Study conducted in Ghana,⁵⁴ in India moderate/severe anemia not significantly associated dietary diversity.⁶⁸ However, the recent findings were contradict the previous study result which was conducted in Wollega Zone, Oromia, Ethiopia,⁶² West shewa,⁶¹ Hossana, Ethiopia,⁶⁹ Tanzania,⁵⁶ Sub-Saharan Africa¹⁴ and Zanizibar⁵⁶ dietary diversity was associated with anemia. The possible disparity could be lower socioeconomic status, pastoralist communities, and also nutritional taboos affecting dietary diversity levels.

The burden of anemia was higher in respondents who did not take iron sulfate when compared to their counterpart. Pregnant women who did not take iron sulfate had 5.7 times higher anemia than those who took it. This study is consistent with study conducted in various countries.^{12-14,48,58,62,70,71} The possible reason could be that during pregnancy the physiological iron desire is high and the measure of iron assimilated from the routine eating is not adequate to fill numerous pregnant women’s requirements. Therefore, iron supplementation is a very important component of programs to control iron inadequacy anemia and it also increases the hemoglobin concentration.

Our study demonstrated that pregnant women in the early gestational period have a lesser probability of becoming anemic than those in the third trimester. This study finding is comparable with study conducted in various study settings.^{12,41,64,70,72} The possible rationale for this could be pregnancy increases iron demand to compensate their physiological needs. Besides, there is a rapid growth of the embryo during this period that could decrease hemoglobin levels.

Malaria infection during pregnancy is a serious public health and life-threatening emergency in Ethiopia. Developing nations, particularly Africa, have a higher load of malaria.⁷³ Malaria causes severe anemia in sub-Saharan Africa during pregnancy.⁷⁴ The current study had shown that, pregnant women who had no history of malaria infection in the previous 3 months had a 40% lesser probability of becoming anemic than those who were infected. This finding is consistent with study conducted various countries.^13,39,75 The possible justification could be malaria species especially Plasmodium falciparum attacks red blood cells and consequentially cause anemia.

The proportion of lower hemoglobin level had higher among those who drank coffee when compared to their counterpart. Pregnant women who drank coffee immediately after a meal had 1.6 times higher risk to becoming anemic than those who did not. This result was consistent with existing evidence,^{56,61,64,71,76} it showed a positive relationship between drinking coffee and becoming anemic in pregnant women. The possible justification is coffee inhibits iron absorption and that facilitates iron inadequacy in the body consequently leading to anemia.

Strengthen and limitation

The researchers considered adequate sample size, and multiple variables. However, this study didn’t show temporal relationship; data collected at 1 season, and study conducted at rural community that may not represent town are the limitation of this study.

Conclusion

In general, 4 out of 10 pregnant women had lower hemoglobin level, which is a severe public health problem in the study area. No taking Iron Folic Acid (IFA), severe under nutrition, no fish food, moderate food insecurity, drinking coffee and having no malaria infection history were a contributing factors. Therefore, it desires particular attention to invest and promote in food security, dietary diversity, nutritional status, iron-folic acid supplementation, and nutritional information provision for the pastoralist and agrarian community to alleviate the anemia.

Footnotes

Acknowledgements

The manuscript part is taken from thesis submitted to University of South Africa (UNISA), The development of a community based prevention model for under nutrition among pregnant women in Southern, Ethiopia by Tsegaye Alemu Gute available at . Besides, we would like to extend our heartfelt appreciation to laboratory technicians and nurses who took part in blood sample and data collections at field. We would like to forward special thanks to Mr. Mintesnote Melka and TemsgenTefera who facilitated a finical support in-field data collection. Lastly, we would like to appreciate pregnant women who took part in this study.

Abbreviation

● DHS = Demography and health survey

● MUAC = Mid upper arm circumference

● SNNPR = South nation nationality people Region

● IFA = Iron Folic Acid

Authors’ Contributions

TA: Conceptualizing, methods, literature review, participated in data collection at the field, conducted data analysis and interpretation, draft result writing.

ZZN: Methodology, Supervising, validation of the research, resources, reviewing, editing, and writing the manuscript.

TY: Methodology, the literature reviewed, validation of the research, reviewing, editing, and writing the manuscript. All authors have read and approved the manuscript.

Declaration Of Conflicting Interests:

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

Funding:

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Availability of Data and Materials

Data used for this study interpretation is available at the hand of the authors

References

Safiri

Kolahi

Noori

, et al Burden of anemia and its underlying causes in 204 countries and territories, 1990-2019: results from the Global Burden of Disease Study 2019. J Hematol Oncol. 2021;14:185.

Stevens

Paciorek

Flores-Urrutia

, et al National, regional, and global estimates of anaemia by severity in women and children for 2000-19: a pooled analysis of population-representative data. Lancet Glob Health. 2022;10:e627-e639.

WHO. Global anaemia estimates, 2021 Edition. https://www.who.int/data/gho/data/themes/topics/anaemia_in_women_and_children

Karami

Chaleshgar

Salari

Akbari

Mohammadi

Global prevalence of anemia in pregnant women: a comprehensive systematic review and meta-analysis. Matern Child Health J. 2022;26:1473-1487.

Owais

Merritt

Lee

Bhutta

ZA.

Anemia among women of reproductive age: an overview of global burden, trends, determinants, and drivers of progress in low- and middle-income countries. Nutrients. 2021;13(2745):1-17.

Kassebaum

Collaborators

GBDA

; GBD 2013 Anemia Collaborators. The Global Burden of Anemia. Hematol Oncol Clin North Am. 2016;30:247-308.

Han

Ding

Global, regional, and national burdens of common micronutrient deficiencies from 1990 to 2019: a secondary trend analysis based on the Global Burden of Disease 2019 study. EclinicalMed. 2022;44:1-12.

Rahman

Abe

Rahman

, et al Maternal anemia and risk of adverse birth and health outcomes in low- and middle-income countries: systematic review and meta-analysis. Am J Clin Nutr. 2016;103:495-504.

World Health Organization. Nutritional Anaemias: Tools for Effective Prevention and Control. Geneva, Switzerland: World Health Organization; 2017:1-83.

10.

Kinyoki

Osgood-Zimmerman

Bhattacharjee

Kassebaum

Hay

; Local Burden of Disease Anaemia Collaborators. Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018. Nat Med. 2021;27:1761-1782.

11.

CSA I: Central Statistical Agency (CSA) [Ethiopia] and ICF. Ethiopia Demographic and Health Survey. Addis Ababa, Ethiopia and Calverton, MD, USA: CSA and ICF. 2016, 1.

12.

Lebso

Anato

Loha

Prevalence of anemia and associated factors among pregnant women in southern Ethiopia: a community based cross-sectional study. PLoS One. 2017;12:e0188783.

13.

Kare

Gujo

AB.

Anemia among pregnant women attending Ante Natal Care Clinic in Adare General Hospital, southern Ethiopia: prevalence and associated factors. Health Serv Insights. 2021;14:1-9.

14.

Geta

Gebremedhin

Omigbodun

AO.

Prevalence and predictors of anemia among pregnant women in Ethiopia: systematic review and meta-analysis. PLoS One. 2022;17(7):1-22.

15.

Woldu

Enawgaw

Asrie

, et al Prevalence and associated factors of anemia among reproductive-aged women in Sayint Adjibar town, Northeast Ethiopia: community-based cross-sectional study. Anemia. 2020;2020:1-8.

16.

Peña-Rosas

De-Regil

Garcia-Casal

Dowswell

Daily oral iron supplementation during pregnancy. Cochrane Database Syst Rev. 2015;2015:CD004736.

17.

Antenatal Iron Supplementation. https://www.who.int/data/nutrition/nlis/info/antenatal-iron-supplementation

18.

Suzuki

Nishigori

Obara

, et al. Japan Environment and Children’s Study Group. Maternal folic acid supplement use/dietary folate intake from preconception to early pregnancy and neurodevelopment in 2-year-old offspring: the Japan Environment and Children’s Study. Br J Nutr. 2022;128:2480-2489.

19.

Gaml-Sørensen

Brix

Høyer

, et al Maternal intake of folate and folic acid during pregnancy and markers of male fecundity: a population-based cohort study. Andrology. 2023;11:537-550.

20.

Organization

WH.

WHO Recommendations on Antenatal Care for a Positive Pregnancy Experience. World Health Organization; 2016.

21.

Lyoba

Mwakatoga

Festo

Mrema

Elisaria

Adherence to iron-folic acid supplementation and associated factors among pregnant women in Kasulu communities in north-western Tanzania. Int J Reprod Med. 2020;2020:1-11.

22.

Nasir

Fentie

Adisu

MK.

Adherence to iron and folic acid supplementation and prevalence of anemia among pregnant women attending antenatal care clinic at Tikur Anbessa Specialized Hospital, Ethiopia. PLoS One. 2020;15(5):1-11.

23.

Saragih

Dimog

Saragih

Lin

CJ.

Adherence to iron and folic acid supplementation (IFAS) intake among pregnant women: a systematic review meta-analysis. Midwifery. 2022;104(1):1-22.

24.

St-Laurent

Plante

Lemieux

, et al Higher than recommended folic acid intakes is associated with high folate status throughout pregnancy in a prospective French-Canadian cohort. J Nutr. 2023;153:1347-1358.

25.

Dimitrios Tomaras

Tremblay

Economic evaluation of severe anaemia: review-based recommendations and a conceptual framework. Eur Med J. 2020;5:45-54.

26.

Young

MF.

Maternal anaemia and risk of mortality: a call for action. Lancet Glob Health. 2018;6:e479-e480.

27.

Juul

Derman

Auerbach

Perinatal iron deficiency: implications for mothers and infants. Neonatol. 2019;115:269-274.

28.

Sun

McLeod

Gandhi

Malinowski

Shehata

Anemia in pregnancy: a pragmatic approach. Obstet Gynecol Surv. 2017;72:730-737.

29.

Daru

Zamora

Fernández-Félix

, et al Risk of maternal mortality in women with severe anaemia during pregnancy and post partum: a multilevel analysis. Lancet Glob Health. 2018;6:e548-e554.

30.

Blank

Tomonaga

Szucs

Schwenkglenks

Economic burden of symptomatic iron deficiency - a survey among Swiss women. BMC Womens Health. 2019;19:39.

31.

Department SOZH, ed. Annual Health Sector Performance Report. In: Melka

, ed. Book Annual Health Sector Performance Report. South Omo Zone; 2022:1-20.

32.

CSA. Population projection for 2022. In: Central Statistical Agency, ed. Book Population Projection for 2022. CSA; 2022:1-188.

33.

Sector SOZFaED. Socio economic and geo spatial data analysis and dissemination core work process: zonal annual statistical abstract. In: Terefe

, ed. Book Socio Economic and Geo Spatial Data Analysis and Dissemination Core Work Process: Zonal Annual Statistical Abstract. Brothers Printing Media; 2022:1-15.

34.

Kassa

Muche

Berhe

Fekadu

GA.

Prevalence and determinants of anemia among pregnant women in Ethiopia; a systematic review and meta-analysis. BMC Hematol. 2017;17:17.

35.

FAO. Minimum Dietary Diversity for Women. Rome: FAO; 2021.

36.

Gardner

Kassebaum

Global, regional, and national prevalence of anemia and its causes in 204 countries and territories, 1990–2019. Curr Dev Nutr. 2020;4:830-830.

37.

Kumera

Gedle

Alebel

Feyera

Eshetie

Undernutrition and its association with socio-demographic, anemia and intestinal parasitic infection among pregnant women attending antenatal care at the University of Gondar Hospital, Northwest Ethiopia. Matern Health Neonatol Perinatol. 2018;4:18.

38.

Keokenchanh

Kounnavong

Tokinobu

, et al Prevalence of anemia and its associate factors among women of reproductive age in Lao PDR: evidence from a nationally representative survey. Hindawi Anaemia. 2021;2021:1-9.

39.

Anlaakuu

Anto

Anaemia in pregnancy and associated factors: a cross sectional study of antenatal attendants at the Sunyani Municipal Hospital, Ghana. BMC Res Notes. 2017;10:402.

40.

Sahardiid Ali

. Anemia and its determinants among apparently healthy women from pastoralist communities of Ethiopia: a community based cross sectional study. Sci J Public Health. 2018;6:145-151.

41.

Gedefaw

Ayele

Asres

Mossie

Anemia and associated factors among pregnant women attending antenatal care clinic in Wolayita Sodo Town, southern Ethiopia. Ethiop J Health Sci. 2015;25:155-162.

42.

Enawgaw

Birhanie

Terefe

Asrie

Prevalence of anemia and iron deficiency among pregnant women attending antenatal care service at University of Gondar Hospital, Northwest Ethiopia. Clin Lab. 2019;65(4):479.

43.

Getahun

Belachew

Wolide

AD.

Burden and associated factors of anemia among pregnant women attending antenatal care in southern Ethiopia: cross sectional study. BMC Res Notes. 2017;10:276.

44.

Bekele

Tilahun

Mekuria

Prevalence of anemia and its associated factors among pregnant women attending antenatal care in health institutions of Arba Minch Town, Gamo Gofa Zone, Ethiopia: a cross-sectional study. Anemia. 2016;2016:1073192.

45.

Kejela

Wakgari

Tesfaye

, et al Prevalence of anemia and its associated factors among pregnant women attending antenatal care follow up at Wollega University referral hospital, Western Ethiopia. Contracept Reprod Med. 2020;5:26.

46.

Gebre

Mulugeta

Prevalence of anemia and associated factors among pregnant women in north western zone of Tigray, Northern Ethiopia: a cross-sectional study. J Nutr Metab. 2015;2015:165430.

47.

Alemayehu

Gedefaw

Yemane

Asres

Prevalence, severity, and determinant factors of anemia among pregnant women in South Sudanese refugees, Pugnido, Western Ethiopia. Anemia. 2016;2016. 11:1-11.

48.

Animut

Berhanu

Determinants of anemia status among pregnant women in Ethiopia: using 2016 Ethiopian demographic and health survey data; application of ordinal logistic regression models. BMC Pregnancy Childbirth. 2022;22:663.

49.

Liyew

Tesema

Alamneh

, et al Prevalence and determinants of anemia among pregnant women in East Africa; a multi-level analysis of recent demographic and Health Surveys. PLoS One. 2021;16(4):1-15.

50.

Shitu

Terefe

Anaemia and its determinants among reproductive age women (15-49 years) in the Gambia: a multi-level analysis of 2019-20 Gambian demographic and Health Survey Data. Arch Public Health. 2022;80:228.

51.

Wemakor

Prevalence and determinants of anaemia in pregnant women receiving antenatal care at a tertiary referral hospital in northern Ghana. BMC Pregnancy Childbirth. 2019;19:495.

52.

Meda

Coulibaly

Nebie

, et al Magnitude of maternal anaemia in rural Burkina Faso: contribution of nutritional factors and infectious diseases. Adv Public Health. 2016;2016:1-7.

53.

Ekpe

Adefemi

Pemi

MD.

Anaemia among pregnant women: Prevalence and pattern at booking clinic of a tertiary health care facility in North Central Nigeria. West Afr J Med. 2022;39:228-236.

54.

Saaka

Oladele

Larbi

Hoeschle-Zeledon

Dietary diversity is not associated with haematological status of pregnant women resident in rural areas of Northern Ghana. J Nutr Metab. 2017;2017:1-10.

55.

Gebretsadik Bereka

Gudeta

Abate Reta

Assefa Ayana

Prevalence and associated risk factors of anemia among pregnant women in rural part of JigJiga City, Eastern Ethiopia: a cross sectional study. J Pregnancy Child Health. 2017;04:1-7.

56.

Gibore

Ngowi

Munyogwa

Ali

MM.

Dietary habits associated with anemia in pregnant women attending antenatal care services. Curr Dev Nutr. 2021;5(1):nzaa178.

57.

Habib

Black

Soofi

, et al Prevalence and predictors of iron deficiency anemia in children under five years of age in Pakistan, a secondary analysis of National Nutrition Survey Data 2011-2012. PLoS One. 2016;11(5):1-13.

58.

Demétrio

Teles-Santos

CAS

Santos

DBD

. Food insecurity, prenatal care and other anemia determinants in pregnant women from the NISAMI cohort, Brazil: Hierarchical Model concept. Rev Bras Ginecol Obstet. 2017;39:384-396.

59.

Engidaye

Melku

Yalew

, et al Under nutrition, maternal anemia and household food insecurity are risk factors of anemia among preschool aged children in Menz Gera Midir district, Eastern Amhara, Ethiopia: a community based cross-sectional study. BMC Public Health. 2019;19:968.

60.

Demétrio

Teles

CAS

Santos

DBD

Pereira

Food insecurity in pregnant women is associated with social determinants and nutritional outcomes: a systematic review and meta-analysis. Cien Saude Colet. 2020;25:2663-2676.

61.

Deriba

Bulto

Bala

ET.

Nutritional-related predictors of anemia among pregnant women attending antenatal care in central Ethiopia: an unmatched case-control study. Biomed Res Int. 2020;2020:1-9.

62.

Tulu

Atomssa

Mengist

HM.

Determinants of anemia among pregnant women attending antenatal care in Horo Guduru Wollega Zone, West Ethiopia: unmatched case-control study. PLoS One. 2019;14(10):1-13.

63.

Tadesse

Seid

G/Mariam

, et al Determinants of anemia among pregnant mothers attending antenatal care in Dessie town health facilities, northern central Ethiopia, unmatched case-control study. PLoS One. 2017;12(3):1-9.

64.

Gudeta

Regassa

Belay

AS.

Magnitude and factors associated with anemia among pregnant women attending antenatal care in Bench Maji, Keffa and Sheka zones of public hospitals, Southwest, Ethiopia, 2018: a cross-sectional study. PLoS One. 2019;14(11):1-13.

65.

Osman

Nour

Bashir

, et al Risk factors for anemia among pregnant women attending the Antenatal Care Unit in selected Jigjiga Public Health Facilities, Somali Region, East Ethiopia 2019: unmatched case-control study. J Multidiscip Healthc. 2020;13:769-777.

66.

Drewery

Gaitán

Thaxton

Lammi-Keefe

CJ.

Pregnant women in Louisiana are not meeting dietary seafood recommendations. J Pregnancy. 2016;2016:1-9.

67.

Visser

Van Zyl

Hanekom

, et al Associations of dietary diversity with anaemia and iron status among 5- to 12-year-old schoolchildren in South Africa. Public Health Nutr. 2021;24:2554-2562.

68.

Jin

Talegawkar

Sedlander

, et al Dietary diversity and its associations with anemia among women of reproductive age in rural Odisha, India. Ecol Food Nutr. 2022;61:304-318.

69.

Delil

Tamiru

Zinab

Dietary Diversity and its association with anemia among pregnant women attending public health facilities in South Ethiopia. Ethiop J Health Sci. 2018;28:625-634.

70.

Fite

Assefa

Mengiste

Prevalence and determinants of anemia among pregnant women in sub-Saharan Africa: a systematic review and meta-analysis. Arch Public Health. 2021;79:219.

71.

Teshome

Meskel

Wondafrash

Determinants of anemia among pregnant women attending antenatal care clinic at public health facilities in Kacha Birra District, southern Ethiopia. J Multidiscip Healthc. 2020;13:1007-1015.

72.

Asrie

Prevalence of anemia and its associated factors among pregnant women receiving antenatal care at Aymiba Health Center, northwest Ethiopia. J Blood Med. 2017;8:35-40.

73.

Yimam

Nateghpour

Mohebali

Abbaszadeh Afshar

MJ.

A systematic review and meta-analysis of asymptomatic malaria infection in pregnant women in Sub-Saharan Africa: a challenge for malaria elimination efforts. PLoS One. 2021;16(4):1-15.

74.

Ssentongo

, et al Associations of malaria, HIV, and coinfection, with anemia in pregnancy in sub-Saharan Africa: a population-based cross-sectional study. BMC Pregnancy Childbirth. 2020;20:379.

75.

Grum

Brhane

Hintsa

Kahsay

Magnitude and factors associated with anemia among pregnant women attending antenatal care in public health centers in central zone of Tigray region, northern Ethiopia: a cross sectional study. BMC Pregnancy Childbirth. 2018;18:433.

76.

Kumera

Haile

Abebe

Marie

Eshete

Anemia and its association with coffee consumption and hookworm infection among pregnant women attending antenatal care at Debre Markos Referral Hospital, Northwest Ethiopia. PLoS One. 2018;13(11):1-14.