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Effect of nutrition education on hemoglobin level of pregnant women in Southeast Ethiopia: a cluster randomized controlled trial

BMC Public Health volume 25, Article number: 507 (2025) Cite this article

Abstract

Background

Maternal hemoglobin (Hgb) is considered an essential, modifiable risk factor for adverse pregnancy outcomes (APOs). Evidence for the effect of nutrition education on the Hgb levels of pregnant women in low-income countries, including Ethiopia, is inconclusive. This study aimed to assess the effect of nutrition education on the Hgb levels of pregnant women in urban settings in the Bale Zone, Southeast Ethiopia.

Methods

A community-based two-arm parallel cluster randomized controlled trial was carried out among 447 randomly selected pregnant women attending antenatal care (224 intervention and 223 control groups) at health facilities from February to December 2021. A multistage cluster sampling technique followed by systematic sampling was used to select the pregnant women. Pregnant women who took part in the intervention arm received six nutrition education sessions, whereas pregnant women in the control group received routine standard care. We used a pretested, interviewer-administered, structured questionnaire to collect the data. The Hgb level of pregnant women was measured by collecting a finger-prick blood sample using a HemoCue Hb 301. A generalized estimating equation (GEE) model was used to isolate the net effect of the intervention on Hgb, accounting for the clustering. Beta coefficients (β) along with a 95% confidence interval (CI) were used for interpretations.

Results

The mean difference in Hgb levels between the intervention and control groups was 0.12 ± 0.04 (P value < 0.002). The multivariable GEE linear model revealed that nutrition education significantly improved the Hgb levels of pregnant women [β = 0.36, 95% CI: (0.30, 0.43)]. An increase in the consumption of a cup of coffee or tea decreased Hgb levels by 0.14 g/dL [β = -0.14, 95% CI: (-0.23, -0.06)].

Conclusion

The findings showed that a comprehensive nutrition education intervention using the health belief model (HBM) and theory of planned behaviour (TPB) designed to improve dietary diversity substantially improved hemoglobin (Hgb) levels among pregnant women. While we found no single dietary factor to be significant, in this group of pregnant women in Ethiopia, an increase in the daily consumption of a cup of coffee or tea decreased Hgb levels. As a consequence, pregnant women should be advised to limit their coffee or tea consumption. The study was registered on Clinicaltrials.gov retrospectively with the registration number PACTR202201731802989 on 24/01/2022.

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Introduction

Anemia is defined as hemoglobin (Hgb) levels less than 11 g/dL, in pregnant women [1]. Iron deficiency anemia, defined as serum ferritin less than 15 µg/L, is the most prevalent cause of anemia in pregnancy [2]. Iron deficiency can occur as a result of inadequate iron intake and absorption and increased physiologic iron requirements during pregnancy [3]. The prevalence of anemia in pregnant women is 14% in high-income countries (HICs) and 51% in low- and middle-income countries (LMICs) [4]. Anemia is a serious public health issue that affects 32.4 million (38.2%) pregnant women worldwide [5, 6].

Maternal anemia is thought to be an essential modifiable risk factor for adverse pregnancy outcomes (APOs), although the debate persists [7]. Anemia during pregnancy is linked to a range of negative outcomes for both the mother and her offspring [8]. The adverse outcomes include premature birth, low birth weight (LBW), miscarriage, delayed psychomotor improvement, impairment of cognitive memory, and lower totals on the intelligence (IQ) test level of the newly born baby, all of which have an impact on the children’s later lives [9]. As a result, anemia remains a global health issue, particularly in resource-constrained settings [10], and hence maternal Hgb is an important biomarker [7]. Lowering the risk of anemia is an important aspect of improving women’s health, and the World Health Organization (WHO) has set a global goal of attaining a 50% decrease in anemia among women of reproductive age by 2025 [11].

Nearly one-quarter of Ethiopian women in the reproductive age group are anemic and at any point in time 29% of them are pregnant [12, 13]. The prevalence of prenatal anemia in Ethiopia varies from 7.9 to 56.8% [14,15,16,17,18]; by meta-analysis, the pooled prevalence of anemia among pregnant women in Ethiopia is 31.66% [19]. A history of excessive menstrual bleeding [20, 21], hookworm infections, HIV infection [22, 23], malaria infection [19, 21], and not taking iron-folate supplements [24] are all factors that increase the risk of anemia during pregnancy in Ethiopia. The consumption of vitamin-A-rich fruit and vegetables (FV) among women in the Oromia region and Addis Ababa was only 3.9% and 2.8%, respectively; the consumption of other FV among these women was higher but still low at 8.4% and 10.4%, respectively [25]. Many foods that may influence Hgb production are cultural food taboos in Ethiopia during pregnancy, including FVs, grains, and salty foods [26,27,28]; dairy foods such as yoghurt, milk, and cheese [27, 29]; and eggs, fatty meat, and honey [27, 28].

Several attempts have been launched by the Ethiopian government to lower the country’s high anemia rate by implementing national nutrition program and strategies [30, 31]. Ethiopia’s healthcare system frequently provides uneven and poor nutrition education to pregnant women. There is a need to develop and expand nutrition education programmes in prenatal care. Recent attempts at using nutrition education to raise hemoglobin levels and lower anemia rates among pregnant women in Ethiopia are proving to be successful, but more evidence for success is needed [32].

Efforts to alleviate the burden of anemia require a tailored approach and targeted interventions. Nutrition education is critical in attempting to change nutrition behaviors as it can improve participants’ nutrition and food literacy [33]. Understanding good nutrition and a balanced diet during pregnancy is vital for the health of both the mother and the fetus [34]. The effectiveness of health education and health promotion models in influencing behavior and attaining useful results has been reported [35]. The health belief model (HBM) comprises a number of key principles that predict why people take precautionary measures to avoid sickness [36]. The theory of planned behavior (TPB) is one of the most effective theories for successfully converting harmful behaviors to healthy behaviors as it views individual beliefs, social influences, and the drive to follow key people in life as a network of elements driving behavior change [36, 37].

Interventions using nutrition education during pregnancy, involving education on the consumption of nutrient-rich, locally available foods, on avoiding food taboos, on having food and nutrient supplementation (for example, iron-folic acid [IFA], and multiple micronutrients), as well as on weight to ensure a healthy weight gain, have all been recommended [38,39,40,41] to ensure a healthy pregnancy in Ethiopia. This study set out to determine the effect of a comprehensive nutrition education intervention on hemoglobin levels among pregnant women in urban settings in Southeast Ethiopia. The use of theory-based nutrition education initiatives to boost iron-folate acid supplements, promote iron-rich food consumption, and use iron enhancers during pregnancy will bolster the need for anemia prevention. The study contributes to the scant research in this area by highlighting the potential for such intervention to improve pregnancy outcomes.

Methods

Study design, setting, and participants

The study was carried out in Robe and Goba Towns, located in the Bale Zone, Southeast Ethiopia, which are 430 and 444 km from Addis Ababa, respectively. A community-based, two-arm, parallel cluster randomized controlled trial (cRCT) was conducted from February to December 2021 among pregnant women receiving antenatal care (ANC) at medical facilities, as the authors have described previously [42]. Clusters were the zones (small areas) of the clusters in the kebeles within the community. The Bale Zone has 87 health clinics, more than 300 health posts, and four hospitals: Goba Referral Hospital, Robe, Dalomena, and Ginnir. In Goba and Robe towns, the corresponding numbers of pregnant women were 1,832 and 2,048, respectively [43, 44]. The source populations were all pregnant women who attended ANC in the Robe and Goba towns. The study population included all first- and early-second-trimester pregnant women attending the ANC in the Robe and Goba towns. Pregnant women in their first and early second trimesters who lived permanently in the study area were included. The study did not include pregnant women who had been diagnosed with hypertension (HTN) or diabetes mellitus (DM).

Sample size and sampling techniques

Assuming an effect size of 0.25 for hemoglobin, a 95% confidence level (CL), a precision of 0.05, and a power (1- β) of 80%, the sample size was calculated using G-Power software version 3.1 [45]. It was based on Cohen’s conventional criteria. The computed sample size was 120. Using the maximum sample size and considering a design effect (DE) of 2 [39] and a 10% attrition rate, the final sample size was 264. Nonetheless, 454 were drawn (intervention group = 227, control group = 227) since the computed sample size for one of the objectives was larger [42].

Robe and Goba were the two towns that were chosen at random [42]. Robe and Goba towns have 36 clusters and 24 clusters, respectively. The number of pregnant women in each cluster was determined using birth data prepared by urban health extension workers (UHEW). Clusters were randomly randomized to the intervention and control groups. Pregnant women in Robe Town received nutrition education, while those in the Goba Town control group did not. The sample size was allocated to each cluster by probability proportional to size (PPS). Pregnant women were recruited using a systematic sampling technique. If a woman was not at her house for the interview, she was interviewed the following day (Supplementary Fig. 1). Gestational age was determined by asking about the first day of the last menstrual period and confirming pregnancy with a pregnancy test.

Randomization, intervention allocation, and blinding

Pregnant women were assessed for eligibility. Clusters were allocated randomly to the intervention and control groups using a 1:1 ratio. The allocation sequence was generated using coin tossing. During nutrition education, the local languages, Afan Oromo and Amharic, were employed as the languages of communication. The intervention group received nutrition education, education cards, and a structured work schedule. The guiding principles of the health belief model (HBM) and theory of planned behavior (TPB) were used to develop the key takeaways of nutrition education. Prediction of intention and behavior was also conducted using the TPB constructs [36, 46], and constructed our education sessions so that then included but also enhanced the specific recommendations of the Ministry of Health (MOH), Ethiopia [47].

Baseline and end-line assessments were made for the two groups. After baseline data collection, pregnant women in the intervention group received nutrition education for six sessions. Out of two hundred twenty-four pregnant women, two hundred fifteen received six intervention sessions, whereas nine received five. The nutrition educations were delivered over six months. Nutrition education was delivered for 30 to 45 min every session for respondents after they were recruited at their homes in each cluster. Nutrition education was conducted by six Bachelor of Science (BSc)-holding nurses, and supervision was provided by two Master of Public Health (MPH) specialists.

The main topics covered in the session included: increasing knowledge of iron-rich food sources, iron-folate acid supplements (IFAS), iodized salt, meal frequency, and portion size with increasing gestational age; diversifying one’s diet to include many food groups; iron absorption enhancers and inhibitors; reducing heavy workloads; taking days off; exercising; increasing utilization of health services; and interrupting the intergenerational life cycle of malnutrition; increasing pregnant women’s perceptions of under nutrition and factors leading to it, poor eating practices causing inadequate dietary intake and disease, a food-based strategy, dietary changes, raising awareness of FV intake through diversification, enrichment, and standardization, identifying obstacles and finding solutions to them, lowering the perceived obstacles to creating an FV, enlisting the help of participants in coming up with solutions; the improvement of participants’ perceptions of control and intention; specific food taboos (meat and eggs); knowledge and attitudes about pregnant women’s capacity to modify feeding practices; and the improvement of participants’ hand washing proficiency.

The methods used to give education included presentations, discussions, demonstrations, and picture-based exercises. Observation, self-report, and attendance were used to assess compliance. Critical education techniques, important messages, realistic activities, and the GALIDRAA (greet, ask, listen, identify, discuss, recommend, agree, and make a follow-up appointment) processes were all identified by the trainers.

The intervention group consistently received dietary education from nurses. However, due to the unique characteristics of the cluster RCT and the nature of the intervention under investigation, no allocation concealment was adopted in the trial. Because the two towns were very far apart, the study was not blind. The researcher was not blinded, but the laboratory personnel and data collectors were. Pregnant women in both arms were aware of the intervention yet were blinded to the statistical analysis.

Once the pregnant women were enrolled, reasonable steps were taken to encourage their retention and complete follow-up for the duration of the trial by providing them incentives to reduce missing data. In this way, interest in the study was maintained through regular conversations about compliance with the intervention as well as home visits by trainers. Moreover, home visits were planned to minimize the load placed on pregnant women by follow-up visits.

There was no set schedule for the control groups who received regular medical care. At the conclusion of the study, the control group received a brief intervention to ensure justice and a high level of postrecruitment satisfaction. The MOH’s routine health extension programme packages in Ethiopia include 16 components: family health (family planning, maternal and child health, nutrition, and vaccination services); disease prevention and control (HIV/AIDS and sexually transmitted infections (STIs); tuberculosis; malaria; and first aid care); hygiene and sanitation (promotion of sanitary latrines; waste disposal management; water supply; food hygiene and safety; control of insects and rodents; personal hygiene); and health education) [48].

Data collection

An interviewer-administered, structured questionnaire was used to collect data. The data collection instruments were adapted from the Ethiopian Demographic and Health Survey (EDHS) and other literature [14, 49, 50]. Prior to the intervention, data on sociodemographic and economic aspects, substance abuse (alcohol, smoking, tea, or coffee), and reproductive history were obtained. The amount of alcohol intake was typically measured as the number of drinking occasions over a specific time period (e.g., per week or in the last 30 days), and coffee consumption was measured as an estimated standard of 70 mL coffee cups. Nutritional, intimate partner violence (IPV), physical exercise, the health care delivery system, knowledge and practice of HBM, and TPB instruments were collected before and after the intervention. The data collections were made at home. Each group had two distinct data collectors. The data collectors were not the same individuals who delivered the intervention.

A 24-hour qualitative dietary recall was used to compute the dietary diversity score (DDS). The DDS for women is a nine-food group score that is indicated as a qualitative indicator of micronutrient sufficiency in a diet [51]. The score was calculated using nine food groups to represent the micronutrient sufficiency of the diet. Participants were asked to recall everything they had eaten and consumed in the previous 24 h, both in and out of their residences. End-line data were collected after 36 weeks. In addition, participants were asked to recall any snacks they had eaten in between large meals. Consumption of a food item during the reference period received a score of “1,” but nonconsumption received a score of “0.” The foods were then divided into nine categories: (3) vitamin A-rich fruits and vegetables; (4) other fruits and vegetables; (5) beans, nuts, and seeds; (6) meat and fish; (7) fats and oils; (8) milk and milk products; and (9) eggs. The DDS was rank ordered into tertiles, with the highest tertile representing high DDS and the two lower tertiles representing low DDS [52]. Mid-upper arm circumference (MUAC) was measured using standard procedures [53, 54]. Details are available elsewhere [55].

Android principal component analysis (PCA) was used to generate the wealth index. Details have been described elsewhere [42]. The status of food security was assessed using 27 previously verified questions. Food-secure, slightly, moderately, and severely food-insecure families were characterized as having less than the first two, two to 10, eleven to seventeen, and more than seventeen food insecurity indicators, respectively [56].

Each HBM was determined using the sums of a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree) to form a composite question: perceived susceptibility (3 items), perceived severity, and perceived benefits (4 items each), perceived barriers (5 items), cues to action, and self-efficacy (4 items each) [46] and TPB questions: attitude and subjective norms (3 items each), perceived behavioral control (2 items), and behavioral intention (7 items) [57]. To assess the relevance of fruits and vegetables, a ten-item knowledge test was also used [58]. Details have been described previously [42].

Data quality control

The questionnaire was also pretested on 5% of the total predicted sample size, which had similar characteristics to the research population in a different neighboring context. Training was given on the objective of the study, data collection instruments, and ethical issues. Details have been described elsewhere [42]. Due to the unique characteristics of the cluster RCT and the nature of the intervention under investigation, the bias due to the Hawthorne effect was controlled by GEE, which accounts for clustering and potential confounding effects. Cronbach’s alpha was also utilized to assess the internal consistency of the tools’ cognitive, affective, and psychomotor domains (Supplementary Table 1).

Outcome assessment

Hemoglobin level is one of the secondary outcome variables. The Hemo-Cue1 Hb 301 system (HemoCue AB, Angelholm, Sweden) was used at each study setting by skilled medical laboratory technologists to measure the hemoglobin concentration (in g/dL) of pregnant women. The middle finger tip was pricked after the area had been disinfected using alcohol. To measure the Hgb concentration, the device’s cuvette holder was filled with the second drop of blood after the first drop had been washed off and collected [1]. Meanwhile, 5 mL of venous blood was taken and centrifuged for 5 min in a microhematocrit tube with an anticoagulant to obtain hemoglobin [59]. Anemia was defined as Hgb levels of less than 11 g/dL. It was further classified as severe, moderate, mild, and not anemic, with Hgb levels ranging from 7.0 to 9.9 g/dl, 10.0 to 10.9 g/dl, and 11.0 g/dl, respectively [49]. Comparative Sahli’s approach was used to estimate Hgb. Hgb values were adjusted for altitude as described by Cohen and Hass [60].

Data processing and analysis

The data were reviewed for completeness, consistency, and accuracy, entered into, cleaned, and analysed using SPSS Windows version 20 and Stata™ version 14 software. Descriptive statistics such as frequencies, percentages, and means were generated for the selected predictors. We assessed the baseline characteristics of the intervention and control groups using the chi-square test. We also used an independent t test and a paired t test to compare the variables of interest between and within the intervention and control groups, respectively.

The difference-in-difference (DID) method estimated the difference in the change in the mean value of the end line and baseline Hgb level [61]. The intervention’s effect was assessed using a DID and multivariable Generalized estimating equations (GEEs) linear model to compare Hgb levels (continuous outcome) between the intervention and control groups before and after the intervention. The changes in the intervention group’s Hgb levels (from baseline to end-line) were compared to the changes in the control group (from baseline to end line) [62]. We adjusted for the clustering effects by including clusters and identifying participants in the model.

To account for potential confounders in the final GEE linear model, variables with p-values less than 0.25 in the binary GEE linear regression model were chosen. GEEs are a valuable statistical model for analyzing longitudinal or clustered data [63]. GEE can manage missing data values without the need for explicit imputation by taking into account all pregnant women who have had at least one follow-up visit and automatically deleting the missing values using the GEE linear regression model [63]. Although the GEE method is thought to be resistant to incorrect working correlation structure (WCS) selection, the best WCS of the Hgb was chosen as an unstructured matrix by assessing the working correlation matrix of the observed correlations between subsequent measurements to maintain the goodness of the model fitness and thus obtain a more precise estimation of the intervention effect. Accordingly, the quasilikelihood under the independence model criterion (QIC) was employed to maintain the goodness of model fitness. The results of the working correlation structures were similar.

The intervention’s effectiveness was determined using time and treatment interactions. Effect sizes were expressed as beta coefficients along with a 95% confidence interval (CI) for the interpretation of the strength of the predictive power of the explanatory variables in Hgb levels. Initially, randomly assigned pregnant women were examined in the groups to which they were assigned (intention-to-treat analysis principle). The statistical significance of the association was set using a p value of less than 0.05, and all tests were two-sided.

Ethical approval

The current study was ethically approved by Jimma University’s Institutional Review Board before its start (Protocol #: IRB000296/2012) in Ethiopian calendar/2020 Gregorian calendar. The health offices provided a letter of authorization. All methods were carried out in accordance with the principles of the Helsinki Declaration and good clinical practice [64]. Each responder provided written informed consent. The respondents’ privacy was protected. Throughout the whole data collection and management process, confidentiality was preserved. The trial for this study was registered at clinicaltrials.gov (PACTR202201731802989||http://www.pactr.org/), retrospectively registered on 24/01/2022). The study was reported following the Consolidated Standards of Reporting Trials (CONSORT) 2010 statement (CONSORT checklist) [65] (Related manuscript Table 1 CONSORT checklist).

Results

Sociodemographic and economic characteristics of the study subjects

A total of 224 (98.67%) and 223 (98.24%) pregnant women were successfully interviewed in the intervention and control groups, respectively (Fig. 1). The mean (± SD) age of the pregnant women was 25.93 (± 5.52) years for the intervention group and 24.24 (± 4.24) years for the control group. There was no statistically significant difference in baseline characteristics between the intervention and control groups (P > 0.05) (Table 1).

Fig. 1
figure 1

CONSORT flow diagram of pregnant women

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Table 1 Baseline socio-demographic and economic characteristics of pregnant women in Southeast Ethiopia, 2021
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Health belief model and the theory of planned behavior scores

There was a significant improvement in the score of the HBM and TPB constructs except for perceived benefit and cues to actions among the intervention group before and after the intervention (P < 0.0001). Furthermore, with the exception of perceived severity and cues to action, there was a significant difference in the dimensions of the HBM and TPB in the end-line data (Table 2). The HBM and TPB constructs showed that perceived susceptibility, perceived benefits, perceived barriers, self-efficacy, and TPB were all correlated with interventions. However, there was no correlation between dietary diversification and HBM and TPB constructs (Supplementary Table 2).

Table 2 Comparison of the health belief model and the theory of planned behavior constructs between and within the intervention and control groups during pregnancy in Southeast Ethiopia, 2021
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Table 3 Differences between baseline and end-line measurements of hemoglobin (g/dL) and differences between the intervention and control groups
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Hemoglobin concentration

The control group and intervention group did not significantly differ from one another at the beginning of the study (P = 0.058). The endpoint results did, however, show a significant difference between the control group and intervention group (P = 0.003). The difference in the mean hemoglobin (Hgb) level between the intervention and control groups was 0.12 ± 0.04 g/dL, which was statistically significant (P = 0.002) (Table 3). In a multivariable GEE linear model, having received nutrition education interventions improved Hgb levels among pregnant women (β = 0.36, 95% CI: 0.30, 0.43). An increase in the consumption of a cup of coffee or tea decreased Hgb levels by 0.14 g/dL (β = -0.14, 95% CI: -0.23, -0.06) (Table 4).

Table 4 Multivariable GEE linear regression analyses predicting hemoglobin levels of pregnant women, Southeast Ethiopia, 2021 (N = 447)
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Discussion

This study determined the effect of a comprehensive nutrition education intervention on hemoglobin (Hgb) levels among pregnant women in urban settings in Southeast Ethiopia. After adjusting for potential confounders, the study’s findings revealed that having a nutrition education intervention improved Hgb levels compared to a control group that received standard care. An important finding showed that increases in the consumption of a cup of coffee or tea per day decreased Hgb levels.

The results indicated that the nutrition education interventions improved Hgb levels by 0.36 g/dL among pregnant women in the intervention group compared to their counterparts, which is in accord with the reports of studies conducted in Ethiopia [66], Ghana [67], Iran [68, 69], Malaysia [70, 71], Indonesia, and India [72, 73]. A systematic review of RCTs conducted in anemic women where dietary counselling was one intervention type included pregnant women, and for this group, this was effective in improving Hgb [74]. A study conducted in Kenya highlighted the necessity of establishing educational programmes to promote nutritional knowledge and sensitization of women to ensure appropriate iron intake and enhance iron bioavailability in food [75]. This may be due to the fact that vitamin C-rich foods such as fruits and vegetables can improve iron bioavailability. Similarly, it is beneficial for Hgb to eat more meat, which has highly absorbable heme iron and provides the meat-fish-poultry (MFP) factor that improves non-heme absorption [76]. However, in our study, changes in meat and fruit and vegetable consumption did not explain the improvement in Hgb of our study subjects.

Studies conducted in Jordan and Indonesia indicated that there was an improvement in the mean Hgb level following the nutrition education intervention trial [77, 78]. Likewise, a study conducted in Palestine [79] found a substantial favorable link between dietary patterns and increased Hgb levels in pregnant women. Moreover, the education program only resulted in a substantially higher Hgb change when compared to the control group among pregnant Nepalese women [80]. However, a randomized control trial conducted in Greece found that dietary education and counselling had no significant effect on Hgb levels in the intervention group compared to the control group [81]. A possible explanation could be differences in cultural perspectives.

An increase in the consumption of a cup of coffee or tea decreased hemoglobin levels by 0.14 g/dL. This study is in agreement with studies conducted in Ethiopia [82], Tanzania [82], Northern Ghana [83], and Morocco [84], in which the consumption of a cup of tea or coffee with a meal was the dietary habit predicting low Hgb levels in pregnant women. This could be because polyphenol chemicals found in coffee, whether ordinary coffee or decaffeinated coffee, are known to limit nonheme iron absorption. Furthermore, the main phenolic compound in coffee, chlorogenic acid, is also a potent inhibitor of nonheme iron absorption [85]. Due to their aversion to the smell of coffee, pregnant women from different parts of Ethiopia have been known to crave and therefore drink coffee dregs and green coffee leaves at least once a day, a practice that can inhibit iron absorption [86].

The nutrition education intervention in our study was based on the HBM and TPB, two of the most commonly used health behavior models and theories [36]. Nutrition interventions based on an integrated HBM and TPB increase pregnant women’s diet knowledge, dietary diversity, and nutritional status [57]. Likewise, a previous study found a significant favorable effect of using HBM and TPB constructs during prenatal counselling to encourage healthy eating behavior [87]. Our study’s findings were supported by those of an Iranian study, which found that education in the context of HBM enhanced the understanding of nutrition during pregnancy as well as dietary behavior [88].

This study’s results were expected in light of the HBM model constructs: if people have a higher perception of threats or health problems, they take potential health warnings into account and thus take action to prevent health problems or threats, resulting in significant changes in their attitudes and behaviors [89].

Policy implications

This study’s findings have significant implications for food and nutrition policies. Despite the efforts of the government of Ethiopia, the high burden of anemia indicates a policy gap in Ethiopia’s pregnant women. The findings have implications for implementing food and nutrition policy, national nutrition strategy, national nutrition programme, and micronutrient deficiency prevention and control strategy by improving the nutrition intake to enhance hemoglobin level of pregnant women, which in turn combat the prevalence of anemia.

The strengths of this study include conducting a community-based, study in which we combined encouraging health foods with the HBM and TPB as applicable to relevant and conventional ANC. The cluster character of the study was considered in both sample size determination and data analysis. However, some limitations should be acknowledged. The conclusions of this study could have been influenced by recall bias and social desirability bias, despite efforts to probe pregnant women many times over the course of 24 h to improve dietary recall. The use of cRCT might also be a limitation, as women from the same cluster may respond similarly to an intervention, limiting variability and thus underestimating intervention benefits, so that results may not be applicable outside the individual clusters analysed. The responses of the study subjects were based on a self-reported questionnaire. The confounding influence of inflammation [90, 91] and physiological changes in plasma volume expansion during pregnancy complicate iron biomarker interpretation. The complicated etiology of anemia, as well as the importance of biological, social, and ecological determinants of anemia (including both nutritional and nonnutritional factors), can vary greatly between contexts [90]. Inconsistencies impact hemoglobin levels [66]. There is a current controversy about using HemoCue for measuring hemoglobin in the field [92]. Many pregnant women may struggle to consistently incorporate iron-rich foods into their diets due to cultural preferences, economic constraints, or lack of access to these foods [93].

Conclusion

The findings showed that a comprehensive nutrition education intervention using the health belief model (HBM) and theory of planned behaviour (TPB) designed to improve dietary diversity substantially improved hemoglobin (Hgb) levels among pregnant women. While we found no single dietary factor to be significant, interpretation should be made with caution. Importantly, in this group of pregnant women in Ethiopia, an increase in the daily consumption of a cup of coffee or tea decreased Hgb levels. As a consequence, pregnant women should be advised to limit their coffee or tea consumption.

Data availability

All relevant data for this study are available from the corresponding author upon reasonable request.

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Acknowledgements

We would like to express our gratitude to Jimma University and local administrative officials for their support. Our thanks also go to the educators, supervisors, data collectors, and pregnant women for their participation.

Funding

We did not receive specific funding for this study.

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Authors and Affiliations

  1. Department of Public Health, School of Health Sciences, Madda Walabu University, Goba, Ethiopia

    Girma Beressa

  2. Nutrition and Dietetics Department, Faculty of Public Health, Jimma University, Jimma, Ethiopia

    Girma Beressa & Tefera Belachew

  3. College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, Canada

    Susan J. Whiting

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  1. Girma Beressa
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Contributions

GB participated in the conceptualization, formal analysis, investigation, methodology, resource acquisition, software, supervision, validation, writing the original draft, writing a review, and substantial editing. SW and TB participated in the conceptualization, formal analysis, investigation, methodology, resource acquisition, software, supervision, validation, substantial review, and editing. All the authors have read and approved the manuscript.

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Correspondence to Girma Beressa.

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Beressa, G., Whiting, S.J. & Belachew, T. Effect of nutrition education on hemoglobin level of pregnant women in Southeast Ethiopia: a cluster randomized controlled trial. BMC Public Health 25, 507 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12889-025-21699-3

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