Serum folate deficiency and associated factors among pregnant women in Haramaya District, Eastern Ethiopia: a community-based study

Abstract

Objectives

We aimed to estimate the prevalence of folate deficiency and contributing factors among pregnant women.

Design

A community-based, cross-sectional study.

Setting

Haramaya District, Eastern Ethiopia.

Participants

Four hundred and forty-six pregnant women participated in the study.

Primary outcome measure

The prevalence of folate deficiency and risk factors.

Results

Overall, the prevalence of folate deficiency was 49.3% (95% CI 44.6% to 54.1%). Pregnant women with iron deficiency anaemia were 2.94 times more likely to develop folate deficiency (adjusted OR (AOR)=2.9, 95% CI 1.9 to 4.7). Respondents with good knowledge of folate-rich foods (AOR=0.3, 95% CI 0.1 to 0.7) and those who took iron and folic acid supplementation (AOR=0.6, 95% CI 0.4 to 0.9) during their pregnancy were less likely to develop folate deficiency.

Conclusions

In this study, a considerable proportion of pregnant women had folate deficiency during their pregnancy. Therefore, it is critical that nutritional treatment, education and counselling be strengthened to facilitate iron and folic acid supplementation during pregnancy.

Correspondence to Dr Kedir Teji Roba; [email protected]

Strengths and limitations of this study

• We used an accredited Ethiopian Public Health Institute laboratory in Ethiopia.

• This is a community-based study; however, due to its cross-sectional nature, causal inference between folate deficiency and its correlates was limited.

• It would be ideal if samples were taken before and after pregnancy and from a large sample size representative of the Ethiopian population or at least the eastern part of Ethiopia.

• The RBC folate test is superior to the serum/plasma test because it reflects long-term folate status over the previous 36 weeks.

• Serum folate was used to limit sample lysis, and as a result this study should be used with caution as serum folate indicates acute change.

Introduction

Folate is a water-soluble essential B vitamin and the natural form of vitamin B₉. It is required for the formation of red and white blood cells and conversion of carbohydrates into energy, as well as for general health, cell growth and function.^{1 2} Folate is required for cell production and maintenance, particularly during critical periods of rapid growth and development, such as during pregnancy which involves increased fetal and maternal tissue growth.³

Folate deficiency has serious metabolic and clinical implications. Chronic severe folate deficiency is associated with decreased DNA synthesis, resulting in impaired erythropoietin maturation and reduction in white cell count and platelets; general cell division is impaired due to folate’s role in nucleic acid synthesis, resulting in gastrointestinal symptoms and impaired absorption.^3–5 Furthermore, folate deficiency during pregnancy is linked to a number of negative outcomes, including folate-responsive neural tube defects (NTDs) and neural crest disorders, fetal growth retardation, low birth weight, preterm delivery, and neonatal folate deficiency. Causes of folate deficiency during pregnancy include inadequate dietary intake, increased requirements, malabsorption and use of antifolate drugs, as well as increased folate requirements during pregnancy and lactation to meet maternal and neonatal needs.^{2 6}

Global folate status data for women of reproductive age are limited and must be interpreted with caution due to methodological issues.⁶ There is a socioeconomic disparity between countries in terms of folate deficiency; many lower-income countries have a folate deficiency prevalence of greater than 20%, whereas it is usually less than 5% in higher economies.⁷ The prevalence of folate deficiency varies greatly between countries. For example, in African countries such as Kenya, Niger, Senegal and Sudan, the prevalence of folate deficiency among pregnant women ranges from 0.8% to 57.7%,^8–11 while in Ethiopia the prevalence is 27.5%.¹²

Folate deficiency is a potential public health problem in Ethiopia, according to studies. Various contributory factors, including maternal nutrition, socioeconomic factors, iron and folic acid supplementation, and physiological changes during pregnancy, contribute to folate deficiency. Ethiopia has obvious gaps because folate-fortified foods are unavailable¹³ and the Federal Ministry of Health micronutrient guidelines do not account for folate deficiency. There are policies and strategies in place to reduce the burden of micronutrient deficiency; however, studies show that there are gaps in preventing adverse birth and maternal health outcomes.^{12 14 15} Thus, information on the prevalence of folate deficiency and associated factors among pregnant women is required to prioritise and design interventional programmes to improve maternal nutrition. However, in Ethiopia, there is little information available about folate deficiency and related factors among pregnant women. Therefore, the purpose of this study was to determine the prevalence of folate deficiency and the associated factors among pregnant women in Haramaya District.

Methods and materials

Study setting and design

The research site was part of the Haramaya Health Demographic Surveillance and Health Research Centre (HDS-HRC), which was established in 2018. The HDS-HRC is located in Haramaya District, 500 km east of Addis Ababa, the capital city. Haramaya District is made up of 33 kebeles (the lowest administrative unit in Ethiopia). The HDS-HRC covers 12 rural kebeles which were chosen at random to represent a variety of geographical and environmental factors. The HDS-HRC was following 2306 pregnant women. The district is characterised by mixed farming, with khat (Catha edulis Forsk) serving as the primary cash crop.¹⁶ The research was carried out between 5 January and 12 February 2021.

Study design and population

A cross-sectional, community-based study of pregnant women in Haramaya District, Eastern Ethiopia, was conducted. All pregnant women in the district made up the source population. The study population, on the other hand, consisted of all pregnant women who had lived in the selected kebeles for at least 6 months during the study period. Because no previous community-based studies on folate prevalence in pregnant women in Ethiopia had been conducted, the sample size was calculated using a single population proportion formula under the following assumptions: the prevalence of folate deficiency is 50%, with 95% CI and 5% margin of error. Furthermore, after accounting for a 20% non-response rate, the final sample size was 461. Simple random sampling was used on the eight randomly selected kebeles after constructing a sampling frame from the HDS-HRC database. Eligible women were then chosen through a computer-generated lottery system.

Data collection methods

Data were gathered using an interview questionnaire administered by trained research assistants. The questionnaire collected information on pregnant women’s socioeconomic status, obstetric status, maternal perception, food consumption, dietary knowledge, attitude and practices. An individual with good command of both languages (English and Afaan Oromo) prepared the questionnaire in English and translated it into the local language (Afaan Oromo). It was pretested on 46 (10%) samples in Kersa District prior to data collection. In addition, the mid-upper arm circumference of participants was measured to assess nutritional status.

To assess the dietary diversity of the study participants, we used a previously validated Food Frequency Questionnaire (FFQ) containing 27 of the most commonly consumed foods by the district community.^17–22 First, after consulting with key informants living in the study area who were familiar with the culture, local language and commonly consumed foods, this list of commonly consumed foods was developed. Following this, the FFQ was pretested on 10% of the sampled pregnant women in the district who were not included in the main study; changes were made based on the observations. Finally, for the FFQ, daily, weekly and monthly intake of each specific food item for the previous 3 months was recorded to account for variations and fluctuations in dietary consumption. The FFQ food items were divided into 10 categories: cereal; white roots and tubers; pulses and legumes; nuts and seeds; dark green leafy vegetables; other vitamin A-rich fruits and vegetables; meat, fish and poultry; dairy and dairy products and egg; other vegetables; and other fruits. The number of food groups consumed by the women in a week was counted in order to calculate the dietary diversity score (DDS). DDS was converted into tertiles, with the highest tertile labelled ‘high’ DDS and the two lower tertiles combined labelled ‘low’ DDS. Animal Source Foods (ASF) was calculated by counting the frequency of each food from animal sources consumed by pregnant women over a 7-day period. The score was also converted into tertiles, with the highest tertiles labelled ‘high’ and the two lower tertiles combined labelled ‘low’ ASF.^20–22

Participants in the study were asked to recall the locally available food items they consumed in the previous 7 days, which included maize, rice, sorghum, millet, bread and other cereal, cassava, sweet potato, vegetables, fruits, beef, goat, poultry egg, fish, milk, yoghurt and other dairy, beans, peas, peanuts, cassava, nuts, oil, and sugar. Depending on the number of days consumed, each food item was assigned a score ranging from 0 to 7. Food items were classified into food groups, and the frequency of all food items surveyed in each food group was totalled. Any total food group frequency value greater than 7 was recoded as 7. Cereals, tubers, roots and crops were assigned 2 weights, pulses 3, vegetables 1, fruits 1, meats and fishes 4, milk 4, sugar 0.5 and oil 0.5. The food consumption score for each participant was calculated by multiplying each food group frequency by each food group weight and then averaging these scores to produce a single composite score. Given that overall consumption of oil and sugars was high among all study participants, the food consumption category of women used the following thresholds: a poor food consumption score of 0–28 and a borderline food consumption score of 28.5–42 were classified as unacceptable, while a food consumption score of >42 was acceptable. Pregnant women were defined as a ‘consumer’ of a food item if they had consumed that item at least once a week.^{21 23}

Blood sample collection, serum extraction and folate level determination

A 5 mL venous blood sample was collected aseptically from the antecubital vein and placed into anticoagulant-free test tubes. The blood samples were centrifuged, and the serum was separated before being frozen at −80°C and flown to the Ethiopian Public Health Institute (EPHI) to be measured for serum ferritin, folate and highly sensitive C reactive protein (hsCRP). Serum ferritin and folate levels were measured using the electrochemiluminescence method on a fully automated Cobas e411 (Cobas 4000 analyser series; Germany and Japan) immunoassay analyser at the EPHI using commercial kits supplied by Roche (Germany). hsCRP was measured using a fully automated clinical chemistry analyser, Roche/Hitachi Cobas 6000 c501 (Roche Cobas 6000 series; Germany and Japan). The tests were performed by trained and experienced medical laboratory technologists using standard operating procedures (SOPs).

There is no international standard for folate deficiency during pregnancy,⁶ but the WHO recommends 4 ng/mL as a cut-off for folate deficiency in serum folate for pregnant women based on metabolic indicators. Thus, we used the WHO recommendation for serum folate of 4 ng/mL as a cut-off for folate deficiency in this study, while values greater than 4 ng/mL were considered normal.²⁴ After adjusting for C reactive protein (CRP), iron deficiency was defined as serum folate less than 15 g/L. A clearly visible agglutination indicated a positive CRP result (CRP >5 mg/dL). Anaemia was defined as haemoglobin level of 11.0 g/dL or higher during pregnancy. If pregnant women were both iron-deficient and anaemic, they were diagnosed with iron deficiency anaemia.^{24 25}

Data quality assurance

Each data collector and supervisor went through 2 days of intensive training with the final version of the questionnaire. Supervisors double-checked the collected data every day before data entry. Furthermore, the supervisors checked the completed questionnaires for accuracy on a daily basis. The research team managed the overall data collection work.

The EPHI’s National Reference Laboratory for Clinical Chemistry monitored quality assurance during laboratory analysis (EPHI). The Ethiopian National Accreditation Office has accredited the EPHI laboratory to conduct tests in accordance with ISO 15189:2012, Quality and Competence in Medical Laboratory Requirements (accreditation number: M 0025). As a result, well-trained and experienced laboratory professionals adhered to the SOPs for the various parameters.

Two levels of quality control (QC) were performed at least once every 24 hours during testing; once per reagent kit and following each calibration to evaluate the functionality of the instrument and reagent. The results of the QC were assessed using the Levey-Jennings chart (Westgard rules). The calibration method was standardised against the WHO International Standard NIBSC (National Institute for Biological Standards and Control) Code 03/178, First International Standard NIBSC ‘Reagent for Ferritin (human liver)’ 80/602 and the reference preparation of IRMM (Institute for Reference Materials and Measurements) BCR470/CRM470 (Reference Preparation for Proteins in Human Serum) for serum folate, serum ferritin and serum hsCRP, respectively. Calibration was carried out in accordance with SOPs. A well-trained medical technologist measured haemoglobin concentration using capillary blood and a portable HemoCue Hb 301, which is considered the gold standard for fieldwork.

Data processing and analysis

The wealth index estimated the economic level of families; the wealth index was created using principal component analysis (PCA). The index was calculated using latrine ownership, agricultural land ownership and size, selected household assets, livestock quantity, and source of drinking water (including 41 household variables). The study used 16 knowledge questions about nutrition during pregnancy to assess women’s nutritional knowledge. The top tertile was labelled as having ‘good’ nutritional knowledge, while the bottom two-thirds were labelled as having ‘poor’ nutritional knowledge. Maternal attitude was assessed using PCA and 12 Likert-scale questions. The factor scores were added up and divided into tertiles (three parts): the highest tertile was defined as having ‘favorable’ maternal attitude, and the two lower tertiles were defined as having ‘unfavorable’ maternal attitude. PCA was used to assess maternal-perceived vulnerability to malnutrition using 10 Likert-scale questions. The factor scores were totalled and divided into tertiles (three parts): the highest tertile was defined as having ‘yes’ perceived maternal vulnerability, while the lower tertiles were defined as having ‘no’ perceived maternal vulnerability. Similarly, composite questions were used to calculate the perceived severity of malnutrition, perceived benefit of healthy nutrition, perceived barrier to healthy food and perceived self-efficacy to control malnutrition during pregnancy. Women’s autonomy was evaluated using seven validated questions adopted from the Ethiopian Demographic Health Survey.²⁶ For each response to a question, responses were coded as ‘1’ when pregnant women decided alone or jointly with their husbands; otherwise, responses were coded as ‘0’.

EpiData V.3.1 software was used for double entry of data. The data were cleaned, coded and checked for missing data and outliers before being exported to STATA V.14 for further analysis. To present sociodemographic characteristics, descriptive statistics such as mean, SD, median, frequency, percentiles and percentage were used. Using binary logistic regression, bivariate and multivariable analyses were performed to determine the relationship between the independent and outcome variables. The binary logistic regression assumptions were validated. The omnibus test and the Hosmer-Lemeshow statistical test for goodness of fit were used. To control for all possible confounders, all variables with p values of 0.25 in the bivariate analysis were included in the multivariable analysis final model. SE and collinearity statistics were used to determine the correlation between independent variables using the multicollinearity test (variance inflation factor >10 and SE >2 were considered suggestive of the presence of multicollinearity). The direction and strength of statistical association were measured using an OR with 95% CI. To identify factors associated with folate deficiency, an adjusted OR (AOR) with 95% CI was calculated. The Pearson correlation coefficient investigated the relationship between independent variables. To select variables for the final model, a p value of 0.25 was used as a cut-off point. Backward elimination was used with a statistically significant p value of 0.05.

Patient and public involvement

The public were not involved in the research design, conduct, reporting or dissemination plans.

Results

Sociodemographic characteristics of the respondents

In this study, 461 pregnant women were eligible and 446 consented, with a 96.8% response rate. The women’s average age was 25.7 (+5.1), ranging from 16 to 36. The majority of respondents (73.8%) could not read or write, were housewives (96.6%), were farmers (93.7%) and had a family size of 1–5 (76.5%) (table 1). In addition, 63.2% of the study participants had a history of antenatal care follow-up during their index pregnancy.

Table 1

Sociodemographic characteristics of pregnant women in Haramaya District, Oromia Regional State, Eastern Ethiopia, 2021 (N=446)

Variables	Categories	Frequency (n)	%
Age of the women (years) Mean (±SD): 25.70 (±5.15)	15–17	25	5.6
	18–24	164	36.8
	25–34	234	52.5
	>35	23	5.2
Educational level of the women	Cannot read or write	329	73.8
	Can read and write	26	5.8
	Primary (1–8) and above	91	20.4
Educational level of the husband	Cannot read and write	257	57.6
	Can read and write	61	13.7
	Primary (1–8) and above	102	22.9
	Secondary (9–12) and above	26	5.8
Occupational status of the women	Housewife	431	96.6
	Merchant	15	3.4
Occupational status of the husband	Farmer	418	93.7
	Merchant	28	6.3
	>5	105	23.5
Agricultural land possession	Yes	270	60.5
	No	176	39.5
Livestock possession	Yes	298	66.8
	No	148	33.2
Wealth index (quintile)	Poorest	90	20.2
	Poor	90	20.2
	Middle	88	19.7
	Rich	89	20.0
	Richest	89	20.0
Family size	1–5	341	76.4
	>5	105	23.5
	Richest	89	20.0
History of antenatal care visit	No	164	36.8
	Yes	282	63.2
Gravidity of the mother	Less than or equal to 5	373	83.6
	Greater than 5	73	16.4
Maternal parity	Nullipara	102	22.8
	Para 1–4	293	65.7
	5 and more	51	11.4

Dietary practices of the respondents

In the last 7 days, 66 (14.8%) of the 446 respondents consumed dark green vegetables, while 380 (85.2%) did not. There were 132 (29.6%) participants with highly diversified diets, while 314 (70.4%) had low diversified diets (table 2).

Table 2

Dietary practices of pregnant women in Haramaya District, Oromia Regional State, Eastern Ethiopia, 2021 (N=446)

Variables	Categories	Frequency (n)	%
Animal source foods	No	335	75.1
	Yes	111	24.9
Dark green vegetable	No	380	85.2
	Yes	66	14.8
Dietary diversity score	Low	314	70.4
	High	132	29.6
Food consumption score	Poor	47	10.5
	Borderline	157	35.2
	Acceptable	242	54.2
Food variety score	Low	278	62.3
	High	168	37.7

Nutritional and biomarker status of the respondents

This study found that 236 people (52.91%; 95% CI 48.2 to 57.5) were iron-deficient, while 210 (47.1%; 95% CI 42.5 to 51.6) were not; 205 people (46%; 95% CI 41.4 to 50.6) were anaemic and 214 (48%; 95% CI 43.4 to 52.6) were undernourished (table 3).

Table 3

Nutritional and biomarker status of pregnant women in Haramaya District, Eastern Oromia, Ethiopia 2021 (N=446)

Variables	Categories	Frequency (n)	%	95% CI
Iron deficiency anaemia (ferritin+haemoglobin)	Normal	321	72.0	67.6 to 76.0
	Deficient	125	28.0	24.0 to 32.4
Iron deficiency (ferritin)	Normal	210	47.1	42.5 to 51.8
	<15 ng/mL	236	52.9	48.3 to 57.5
Anaemia (haemoglobin)	Normal	241	54.4	49.4 to 58.6
	<11.0 g/dL	205	46.0	41.4 to 50.6
Folate status	Deficient		49.3	44.6 to 54.1
	Normal		50.7	–

Prevalence of folate deficiency

The mean (SD) serum folate concentration was 4.46 (+0.10) ng/mL (95% CI 4.26 to 4.66 ng/mL), ranging from 1.34 ng/mL to 14.78 ng/mL. Folate deficiency has a prevalence of 49.33% (95% CI 44.59% to 54.07%) (table 3).

Factors associated with folate deficiency

Iron deficiency anaemia, perceived benefit of iron and folic acid supplementation, knowledge of folate-rich food, meal frequency, receiving iron and folic acid supplementation, attitude, decision-making, parity and age were identified as candidates for multivariable analysis in the bivariable analysis at a p value of 0.25. Iron deficiency anaemia, taking iron and folic acid supplements and knowledge of folate-rich foods all had a p value of 0.05 and a significant association with folate deficiency in the multivariable logistic regression model. Pregnant women with iron deficiency anaemia had a 2.9-fold increased risk of folate deficiency (AOR=2.9, 95% CI 1.8 to 4.7). Respondents who were familiar with folate-rich foods (AOR=0.3, 95% CI 0.1 to 0.7) and who had taken iron and folic acid supplements (AOR=0.6, 95% CI 0.4 to 0.8) were less likely to develop folate deficiency (table 4).

Table 4

Bivariable and multivariable analyses of factors associated with folate deficiency among pregnant women in Haramaya District, Oromia Regional State, Eastern Ethiopia

Factors	Categories	Folate deficiency		COR (95% CI)	AOR (95% CI)
		Yes (%)	No (%)
Maternal age (years)	15–17	12 (5.5)	13 (5.8)	1	1
	18–24	80 (36.4)	84 (37.2)	1.0 (0.4 to 2.4)	1.0 (0.4 to 2.5)
	25–34	122 (55.5)	112 (49.6)	1.2 (0.5 to 2.7)	1.03 (0.41 to 2.60)
	>35	6 (2.7)	17 (7.5)	0.4 (0.1 to 1.3)	0.5 (0.1 to 1.9)
Knowledgeable about folate-rich food	No	210 (95.5)	198 (87.6)	1	1
	Yes	10 (4.6)	28 (28.1)	0.3 (0.2 to 0.7)	0.3 (0.1 to 0.7)*
Know the benefit of folic acid supplementation	No	172 (78.2)	153 (71.2)	1	1
	Yes	48 (21.8)	73 (28.8)	0.6 (0.4 to 1.0)	0.7 (0.4 to 1.2)
Iron deficiency anaemia	No	135 (61.4)	186 (82.3)	1	1
	Yes	85 (38.6)	40 (17.7)	2.9 (2.0 to 4.5)	2.9 (1.9 to 4.7)*
Meal frequency per 24 hours	≥4	52 (23.6)	65 (28.8)	1	1
	<4	168 (76.4)	161 (71.2)	0.8 (0.5 to 1.2)	1.2 (0.7 to 1.9)
Iron and folate supplementation	No	167 (75.9)	136 (60.2)	1	1
	Yes	53 (24.1)	90 (39.8)	0.5 (0.3 to 0.7)	0.6 (0.4 to 0.9)*
Has good attitude	No	159 (72.3)	141 (62.4)	1	1
	Yes	61 (27.7)	85 (37.6)	0.6 (0.4 to 1.0)	0.7 (0.5 to 1.4)
Autonomous in decision-making process	No	210 (95.5)	205 (90.7)	1	1
	Yes	10 (4.6)	21 (9.3)	0.5 (0.2 to 1.0)	0.7 (0.3 to 1.6)
Maternal parity	Nullipara	44 (20.0)	58 (25.3)	1	1
	1–4	153 (69.6)	140 (62.0)	1.4 (0.9 to 2.3)	1.3 (0.8 to 2.3)
	≥5	23 (10.5)	28 (12.4)	1.1 (0.6 to 2.1)	1.0 (0.4 to 2.3)
Gestational age of pregnancy	First trimester	49 (22.3)	57 (25.2)	1	1
	Second trimester	99 (45.0)	110 (48.7)	1.0 (0.7 to 1.7)	1.1 (0.6 to 1.8)
	Third trimester	72 (32.7)	59 (26.1)	1.4 (0.8 to 2.4)	1.5 (0.9 to 2.7)

*Variables significant in multivariable models.

AOR, adjusted OR; COR, crude OR.

Discussion

This study revealed that the prevalence of folate deficiency was 49.3%. Pregnant women with iron deficiency anaemia, mothers who had good knowledge of folate-rich foods and those who took iron and folic acid supplementation during pregnancy were significantly associated with deficiency.

The prevalence of folate deficiency among pregnant women in Haramaya District was 49.33%; iron deficiency anaemia was significantly associated with folate deficiency, while those taking iron and folic acid supplementation and women with knowledge of folate-rich foods were less likely to develop folate deficiency. The prevalence of folate deficiency observed in this study was higher than previous studies reported in Niger at 44.3%,⁹ Kenya at 0.8%⁸ and Ethiopia at 26.9%.²⁷ However, it is lower than in Sudan (57.7%)¹¹ and Senegal (54.3%).¹⁰ In Ethiopia, 46% of women of reproductive age were deficient in folate,²⁸ which falls within the scope of our study. The difference could be attributed to study setting, study area, design, study population, lifestyle, differences in the cut-off point and use of interventional strategies.

This study found that pregnant women with iron deficiency anaemia were more likely to develop folate deficiency, which contradicts findings from another Ethiopian study.²⁹ Given this population’s dietary intake, the link between folate deficiency and iron deficiency is not surprising. Both folate and iron deficiencies are well known to cause anaemia, and concurrent iron and folate deficiencies are frequently observed with anaemia, especially during pregnancy when there is increased nutrient demand.

Plant foods (dark green vegetables, fruits and cereals) and animal foods are the primary dietary sources of folate.^{2 30 31} According to our findings, pregnant women who were familiar with folate-rich foods are less likely to have folate deficiency. This is consistent with studies conducted in Addis Ababa, Ethiopia,¹² and in nine Ethiopian regions²⁹ which found that women who were knowledgeable about folate-rich foods during pregnancy had a lower risk of folate deficiency.

There are times when there is an increased demand for folate, and pregnancy is one of these times.³² We discovered that pregnant women who received iron and folic acid supplements were less likely than their counterparts to develop folate deficiency. This result was consistent with the findings of a study conducted in Southern Ethiopia.³³ Pregnant women are more likely than non-pregnant women to develop folate deficiency due to increased demands for folate during pregnancy for DNA and other one-carbon transfer reactions.³⁴ One of the benefits of folate during pregnancy is that it helps prevent NTDs.

Strengths and limitations of this study

A strength of this study was that trained health workers and medical laboratory technologists collected and analysed sociodemographic data and blood samples. The study also used serum folate as an indicator of folate status, which is preferred in a community-based study. However, due to the cross-sectional nature of the study, causal inference between folate deficiency and its correlates was limited. It would be ideal if the samples were taken before and after pregnancy and from a large sample size representative of the Ethiopian population or at least the eastern part of Ethiopia. We intended to estimate zinc and vitamin B₁₂ in our plan. However, due to lack of reagents in the country, we were unable to test this. The Red blood cell (RBC) folate test is superior to the serum/plasma test because it reflects folate status over the previous 36 weeks, whereas the serum/plasma test reflects folate status over a 13-week period. However, serum folate was used to limit sample lysis. As a result, this study should be used with caution as serum folate indicates acute change.

Conclusion

The findings of this study revealed that the prevalence of folate deficiency among pregnant women was high when compared with women in other areas of Ethiopia. Furthermore, iron and folic acid supplementation as well as knowledge of folate-rich foods were identified as factors that reduced folate deficiency. Iron deficiency anaemia, on the other hand, was significantly associated with increased folate deficiency. As a result, it is critical to strengthen nutritional education, treatment and counselling in order to facilitate iron and folic acid supplementation during pregnancy. This will improve women’s folate status during pregnancy by increasing dietary practice and compliance with iron and folic acid supplementation.

We would like to express our sincere appreciation to Haramaya University for this study. Special thanks go to the Haramaya district health office staff for their tremendous assistance during data collection. We also would like to thank the Ethiopian Public Health Institute for conducting the laboratory analyses and Goro Muti District for their assistance and historical sponsorship. Finally, we would like to thank all women who participated in the study, the data collectors and the supervisors.

Data availability statement

Data are available upon reasonable request.

Ethics statements

Patient consent for publication

Not required.

Ethics approval

This study involves human participants. All methods of this study were carried out in accordance with the Declaration of Helsinki ethical principle for medical research involving human subjects. An ethical approval letter was obtained from Haramaya University Institutional Research Ethics and Review Committee (ref no: IRERC/223/2020). Written informed consent to participate was obtained from participants and legally authorised representatives 'of minors below 16 years of age and illiterates' and their privacy and confidentiality were maintained. All personal identifiers were excluded and data were kept confidential and used for the proposed study only. Participants gave informed consent to participate in the study before taking part.

Footnote

Contributors NYM, HSR, MBF, GA, JA, MY, TW and KTR were involved in the conception, design of the study, statistical analysis and result interpretation. NYM, DBG, FCW, MT, WH, MW, TBR, MAK, DA and AM drafted the manuscript, which was reviewed for intellectual content by KTR, HSR, MBF and TW. All authors read and approved the final version for submission and agreed to be accountable for all aspects of the article. KTR is responsible for the overall content as the guarantor.

Funding Haramaya University funded this study with grant number 1189/2020 as part of NYM's Master of Public Health Nutrition programme. The funder has no involvement in the study's conception, design, statistical analysis, result interpretation, manuscript writing or publication decision.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

References

¹ Bailey LB, Gregory JF. Folate metabolism and requirements. J Nutr 1999; 129: 779–82. doi:10.1093/jn/129.4.779

² Moll R, Davis B. Iron, vitamin B 12 and folate. Medicine 2017; 45: 198–203. doi:10.1016/j.mpmed.2017.01.007

³ Bailey LB. Folate in health and disease. 2009: CRC press,

⁴ Bailey LB C. Folate. 2012: 321–42.

⁵ Ponziani FR, Cazzato IA, Danese S, et al. Folate in gastrointestinal health and disease. Eur Rev Med Pharmacol Sci 2012; 16: 376–85.

⁶ Bailey LB, Stover PJ, McNulty H, et al. Biomarkers of nutrition for development-folate review. J Nutr 2015; 145: 1636S–1680S. doi:10.3945/jn.114.206599

⁷ Rogers LM, Cordero AM, Pfeiffer CM, et al. Global folate status in women of reproductive age: a systematic review with emphasis on methodological issues. Ann N Y Acad Sci 2018; 1431: 35–57. doi:10.1111/nyas.13963

⁸ Mgamb EA. Folate deficiency among pregnant women attending antenatal clinic at pumwani maternity hospital. JKUAT-COHES; 2018.

⁹ Wessells KR, Ouédraogo CT, Young RR, et al. Micronutrient status among pregnant women in Zinder, Niger and risk factors associated with deficiency. Nutrients 2017; 9: 430. doi:10.3390/nu9050430

¹⁰ Ndiaye NF, Idohou-Dossou N, Diouf A, et al. Folate deficiency and anemia among women of reproductive age (15-49 years) in Senegal: results of a national cross-sectional survey. Food Nutr Bull 2018; 39: 65–74. doi:10.1177/0379572117739063

¹¹ Abdelrahim II, Adam GK, Mohmmed AA, et al. Anaemia, folate and vitamin B12 deficiency among pregnant women in an area of unstable malaria transmission in eastern Sudan. Trans R Soc Trop Med Hyg 2009; 103: 493–6. doi:10.1016/j.trstmh.2008.10.007

¹² Adela A. Assessment of RBC-folate level and other determinant factors of neural tube defect among first trimester pregnant women who attends ante natal care in lideta and T/haimanot health centers. Addis Ababa, Ethiopia Addis Ababa Universty; 2018.

¹³ FMOH. Assessment of feasibility and potential benefits of food fortification in Ethiopia; 2011.

¹⁴ Assefa H, Abebe SM, Sisay M. Magnitude and factors associated with adherence to iron and folic acid supplementation among pregnant women in Aykel town, Northwest Ethiopia. BMC Pregnancy Childbirth 2019; 19: 296. doi:10.1186/s12884-019-2422-4

¹⁵ Dessie MA, Zeleke EG, Workie SB, et al. Folic acid usage and associated factors in the prevention of neural tube defects among pregnant women in Ethiopia: cross-sectional study. BMC Pregnancy Childbirth 2017; 17: 313. doi:10.1186/s12884-017-1506-2

¹⁶ Marshall TA, Stumbo PJ, Warren JJ, et al. Inadequate nutrient intakes are common and are associated with low diet variety in rural, community-dwelling elderly. J Nutr 2001; 131: 2192–6. doi:10.1093/jn/131.8.2192

¹⁷ Neumann C, Harris DM. Contribution of animal source foods in improving diet quality for children in the developing world; 1995.

¹⁸ Lindsay KL, Gibney ER, McAuliffe FM. Maternal nutrition among women from sub-Saharan Africa, with a focus on Nigeria, and potential implications for pregnancy outcomes among immigrant populations in developed countries. J Hum Nutr Diet 2012; 25: 534–46. doi:10.1111/j.1365-277X.2012.01253.x

¹⁹ Nana A, Zema T. Dietary practices and associated factors during pregnancy in northwestern Ethiopia. BMC Pregnancy Childbirth 2018; 18: 183. doi:10.1186/s12884-018-1822-1

²⁰ Kennedy G, Ballard T, Dop MC. Guidelines for measuring household and individual dietary diversity. Food and Agriculture Organization of the United Nation; 2011.

²¹ Allen LH. Interventions for micronutrient deficiency control in developing countries: past, present and future. J Nutr 2003; 133: 3875S–3878S. doi:10.1093/jn/133.11.3875S

²² Belachew T, Lindstrom D, Gebremariam A, et al. Food insecurity, food based coping strategies and suboptimal dietary practices of adolescents in Jimma zone Southwest Ethiopia. PLoS One 2013; 8: e57643. doi:10.1371/journal.pone.0057643

²³ Workicho A, Belachew T, Feyissa GT, et al. Household dietary diversity and animal source food consumption in Ethiopia: evidence from the 2011 welfare monitoring survey. BMC Public Health 2016; 16: 1192. doi:10.1186/s12889-016-3861-8

²⁴ Cordero AM, Crider KS, Rogers LM, et al. Optimal serum and red blood cell folate concentrations in women of reproductive age for prevention of neural tube defects: World Health Organization guidelines. MMWR Morb Mortal Wkly Rep 2015; 64: 421–3.

²⁵ WHO. Serum and red blood cell folate concentrations for assessing folate status in populations. World Health Organization, 2015.

²⁶ Csa I. Ethiopia demographic and health survey. [Ethiopia]. Addis Ababa, Ethiopia and Calverton, Maryland, USA Central statistical agency (CSA) and ICF; 2016.

²⁷ Teshome BE. Folate and vitamin B-12 status of anemic pregnant women and association to hemoglobin during antenatal care, 17-37 weeks in ambo Hospital, oromia, Ethiopia, a multi regression analysis of socio-economic and serum folate and vitamin B-12. J Nutr Hum Health 2018; 2. doi:10.35841/nutrition-human-health.2.1.28-34

²⁸ Haidar J, Melaku U, Pobocik R. Folate deficiency in women of reproductive age in nine administrative regions of Ethiopia: an emerging public health problem. S Afr J Clin Nutr 2010; 23: 132–7. doi:10.1080/16070658.2010.11734327

²⁹ Haidar J. Prevalence of anaemia, deficiencies of iron and folic acid and their determinants in Ethiopian women. J Health Popul Nutr 2010; 28: 359–68. doi:10.3329/jhpn.v28i4.6042

³⁰ de Bree A, van Dusseldorp M, Brouwer IA, et al. Folate intake in Europe: recommended, actual and desired intake. Eur J Clin Nutr 1997; 51: 643–60. doi:10.1038/sj.ejcn.1600467

³¹ Davis RE, Nicol DJ. Folic acid. Int J Biochem 1988; 20: 133–9. doi:10.1016/0020-711x(88)90476-4

³² Rothman D. Folic acid in pregnancy. Am J Obstet Gynecol 1970; 108: 149–75. doi:10.1016/0002-9378(70)90221-8

³³ Yoseph HH. A communitybased randomized controlled trial providing Weekly ironfolic acid supplementation increased serum ferritin, folate and hemoglobin concentration of adolescent girls in southern Ethiopia. Scientific report; 2021.

³⁴ Bailey LB. New standard for dietary folate intake in pregnant women. Am J Clin Nutr 2000; 71: 1304S–7S. doi:10.1093/ajcn/71.5.1304s