Effect of nutrition education on the nutritional status of pregnant women in Robe and Goba Towns, Southeast Ethiopia, using a cluster randomized controlled trial – Nature.com 15:56 

Scientific Reports volume 14, Article number: 19706 (2024) 

Abstract

Maternal malnutrition is pervasive throughout the world, notably in sub-Saharan Africa (SSA), including Ethiopia. This study aimed to assess the effect of nutrition education on the nutritional status of pregnant women in urban settings in Southeast Ethiopia. A community-based two-arm parallel cluster randomized controlled trial was conducted among 447 randomly selected pregnant women attending antenatal care (224 intervention and 223 control). We used a multistage cluster sampling technique followed by systematic sampling to select the pregnant women. Pregnant women who participated in the intervention arm received six nutrition education sessions. Women in the control group received standard care. A nonstretchable mid-upper arm circumference (MUAC) tape was used to measure the MUAC. A linear mixed effects model (LMM) was used to evaluate the effect of the intervention on MUAC, accounting for the clustering. The net mean ± standard error of MUAC between the intervention and control groups was 0.59 ± 0.05 (P < 0.0001). The multivariable LMM indicated that having received nutrition education interventions (β = 0.85, 95% CI 0.60, 1.12, P < 0.0001) improved the MUAC measurement of pregnant women. Thus, nutrition education during pregnancy will combat undernutrition among pregnant women.

Trial Registration: Clinicaltrials.gov (PACTR202201731802989), retrospectively registered on 24/01/2022.

Introduction

Maternal nutrition during pregnancy influences fetal growth, development, and intrauterine programming1,2. It impacts child survival, chronic illness risk, and future human capital development3. Poor maternal nutrition prior to and throughout pregnancy is also significantly connected to an increased risk of maternal anemia, mortality, and unfavorable birth outcomes such as low birth weight and preterm birth, although the mechanism for this link is complex4. Despite substantial achievements and hints of progress over the last decade, maternal under nutrition continues to be a major public health concern in Ethiopia5,6. Maternal and child mortality rates in Ethiopia remain high, being in the order of 412 maternal deaths per 100,000 live births and 67 child deaths per 1000 live births5. This could be associated with the high prevalence of under nutrition among pregnant women in Ethiopia, ranging from 14.4 to 47.9%7,8. Maternal undernutrition contributes significantly to maternal mortality and morbidity, unfavourable birth outcomes, and intergenerational transmission of undernutrition9. In Ethiopia, maternal undernutrition accounts for more than half of newborn and child fatalities10.

Fruit and vegetable (FV) consumption is recommended as part of a nutrient-dense diet; however, intakes are frequently lower than recommended levels, including during pregnancy globally11. Furthermore, the most common public health issues in Ethiopia are macronutrient and micronutrient deficiencies in pregnant women, and FV is a food group that is often low. The consumption of vitamin-A-rich FV among women in the Oromia region and Addis Ababa was only 3.9% and 2.8%, respectively. However, the consumption of other FVs among women in the Oromia region and Addis Ababa was 8.4% and 10.4%, respectively12.

Nutrition education and counselling are often utilized strategies to enhance women’s nutritional status during pregnancy13. Nutrition education is critical in nutrition behavior change attempts because it improves participants’ nutrition and food literacy. Food literacy encompasses both nutrition literacy and the capacity to apply that knowledge to make sound decisions, whereas nutritional literacy is the set of skills required to comprehend and analyze information about food and its nutrients14. In addition, nutrition education interventions that enhance maternal nutritional status are among the most successful mother and child health promotion techniques15.

The first step in promoting nutrition education to produce favorable effects is to choose an acceptable model for counselling pregnant women. The Health Belief Model (HBM) includes themes such as perceived vulnerability, severity, advantages, obstacles to behaviour, signals to action, and self-efficacy that influence people’s motivation to prevent sickness16. The theory of planned behavior (TPB) considers intention to be the primary factor determining behaviour. Intention is influenced by a person’s attitude towards a behaviour, social influences from influential persons, and perceived control over the behavior17. Nutrition education based on an integrated HBM and the TPB increases women’s diet knowledge during pregnancy, dietary diversity, nutritional status, and pregnancy outcomes18. The study found that guided counselling using the HBM and TPB was effective in improving the nutritional status of pregnant women. It is a low-cost intervention that can improve knowledge, dietary practices, and nutritional status19. As a result, the HBM and TPB were employed in this study during the nutrition education intervention. The HBM comprises a number of key principles that predict why people take precautionary measures to avoid sickness. The TPB considers intention to be a direct driver of behavior. In turn, a person’s attitude towards a given behavior, an individual’s perception of social pressures caused by important people in practicing or not practicing a specific behavior, and perceived behavioral control all influence intention16. There is a variation in Ethiopian pregnant women’s socio-cultural, economic, educational status, and geographic, which affects Ethiopian pregnant women20,21,22.

Previous observational studies on maternal nutritional status have been undertaken in Ethiopia, and nutrition interventions are advocated20,23, such as counselling on the consumption of nutrient-rich, locally available foods, food and nutrient supplementation (for example, iron-folic acid (IFA), calcium, and multiple micronutrients), as well as on weight to ensure a healthy weight gain24. However, evidence on the effect of theory-based nutrition education on the undernutrition of pregnant women is lacking in the context of low-income countries. Therefore, we aimed to assess the effect of nutrition education on the nutritional status (measured by the mid-upper arm circumference, MUAC) of pregnant women in urban settings in Southeast Ethiopia.

Methods

Study design, setting, and participants

A community-based, two-arm, parallel cluster randomized controlled trial was conducted among pregnant women receiving prenatal care at health facilities in Robe and Goba towns, Bale Zone, Southeast Ethiopia, from February to December 2021. Details of this study have been published25. In brief, cluster randomization was used over individual-level randomization to decrease information contamination and for pragmatic reasons, as urban health extension workers (UHEWs) operate in clusters26. Robe and Goba towns, located 430 and 444 km from Addis Ababa city, respectively, were the chosen sites. In the municipalities of Goba and Robe, there were 1832 and 2048 pregnant women, respectively. The source population was all pregnant women attending antenatal care (ANC) in the Robe and Goba towns. The study population included all first- and early-second-trimester (the time between 12 and 16 weeks of gestation) pregnant women attending ANC in the Robe and Goba Towns. First- and early-second-trimester (the time between 12 and 16 weeks of gestation) pregnant women who were permanently residents of the study area were included in the study. Pregnant women with gestational diabetes mellitus or pregnancy –induced hypertension were not included in the study.

Sample size estimation and techniques

Using G-Power software version 3.1, the sample size was calculated by making the following assumptions: an effect size of 0.25, a 95% confidence level (CI), a precision of 0.05, and a power (1 − β) of 80%27. The calculated sample size was 120. The ultimate sample size was 264 after taking the largest sample size into account, along with a design effect of 2 and a 10% non-response rate. Nonetheless, 454 were drawn (intervention group = 227, control group = 227) since the computed sample size for one of the broader study’s other objectives was higher25. Data on births compiled by UHEWs were used to estimate the number of pregnant women in each cluster. Robe and Goba towns have 36 and 24 clusters, respectively. Using a probability proportional to size allocation, the sample size was assigned to each cluster. The systematic sampling technique was used to select pregnant women. In the event that a woman missed her interview due to being out of home, the next eligible pregnant woman in the serial number was contacted. The pregnant woman who had been absent from the interview was contacted the next day (Supplementary Fig. 1).

Randomization, intervention allocation, and blinding

The gestational age was calculated by asking about the beginning day of the last menstrual period, and the pregnancy was confirmed using a urine human chorionic gonadotropin test. Robe and Goba towns were chosen at random. Clusters were randomly allocated to the intervention and control groups. Pregnant women residing in Robe Town received the intervention, whereas those residing in Goba Town did not receive the nutrition education interventions. After pregnant women were evaluated for eligibility, the primary author randomly assigned clusters to the intervention and control groups in a 1:1 ratio to make a balance of clusters. The allocation sequence was produced using simple randomization techniques, including coin tossing.

Nutrition education interventions

Nutrition education was delivered in Afan Oromo and Amharic. An organized work schedule, counselling cards, and nutrition education were provided to the intervention group. The core messages for the lessons were generated utilizing the health belief model (HBM) and theory of planned behavior (TPB) theoretical principles16,28. These messages were taken from those recommended by the Ministry of Health (MOH), Ethiopia29.

Following the gathering of baseline data, pregnant participants in the intervention group received nutrition education for six sessions. Not all women received all 6 sessions; however, nearly 96 out of 100 received 5 of 6. Recruitment was done during the period when animal-source foods were allowed (i.e., during the non-fasting period). Following recruitment at their homes in each cluster, respondents received nutrition education for 30–45 min per session. Six nurses with Bachelor of Science (BSc) degrees delivered nutrition education, while two Master of Public Health (MPH) specialists supervised the nutrition education sessions. The core contents of the session were: increasing knowledge about iron-rich food sources, IFA, iodized salt, meal frequency, and portion size with increasing gestational age; food groups; taking day rest; reducing heavy workloads; enhancers and inhibitors of iron absorption; 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 diet adjustment; a food-based strategy; diversifying, enriching, and standardizing knowledge regarding FV intake; identifying obstacles and finding solutions to them. By engaging pregnant women in the assessment and analysis of their own FV difficulties using participatory approaches, learning by doing encourages pregnant women to devise their own solutions. Customize the strategy to address barriers such as cost, accessibility, preparation, time, and taste preferences. For example, consider inexpensive FV choices; lowering the perceived obstacles to creating an FV; motivating participants to find solutions to the obstacles; specific food taboos (meat and eggs); enhancing participants’ perceptions of control and intention; enhancing participants’ hand washing proficiency; and enhancing participants’ knowledge and attitudes on the capacity of pregnant women to adjust feeding patterns (Supplementary Table 1).

Nutrition education sessions included presentations, discussions, demonstrations, and picture-based exercises. Key messages, realistic activities, and the GALIDRAA (greet, ask, listen, identify, discuss, recommend, agree, and make follow-up appointments) processes were all identified by the trainers as crucial counselling abilities. However, no concealment was adopted in the trial due to the distinctive features of the cluster RCT and the nature of the intervention being studied. Because the two towns were so far apart, the study was not blinded. Pregnant women were made aware of the intervention yet were blinded to the research hypothesis. After the pregnant women were enrolled, reasonable attempts were made to encourage their retention and full follow-up for the duration of the trial by providing them with incentives to reduce missing data. Periodic conversations about compliance with the intervention during routine meetings and home visits by trainers served to retain interest in the study. After two weeks of nutrition education sessions, post-intervention measurements were assessed at 36–38 weeks. Moreover, home visits were planned to lessen the strain of follow-up visits among pregnant women.

No set schedule was given to the control groups. They did, however, receive standard health care. At the end of the trial, a brief intervention was given to the control group to ensure fairness and achieve a high level of postrecruitment satisfaction. Family health (family planning, nutrition, and vaccination services), disease prevention and control (human immunodeficiency virus/acquired immune deficiency syndrome, sexually transmitted infections, tuberculosis, malaria, and first aid care), hygiene and sanitation, waste disposal management, water supply, food hygiene and safety, control of insects and rodents, personal hygiene, and health education are among the 16 components of Ethiopia’s routine health extension programme packages30.

Data collection

An interviewer-administered, structured questionnaire was used to collect data. The data collection was paper-based. The data collection instruments were modified from the Ethiopian Demographic and Health Survey (EDHS) and previous studies5,31,32,33. For the two groups, baseline and final assessments were performed. Prior to the intervention, information on sociodemographic, economic, substance abuse (alcohol, smoking, tea, or coffee), and reproductive history was gathered. Before and after the intervention, data on nutritional issues, intimate partner violence, physical exercise, healthcare delivery systems, knowledge, practice, HBM, and TPB tools were gathered.

The dietary diversity score (DDS) was computed using a qualitative 24-h dietary recall, as previously described25. The DDS score was determined using nine food categories to reflect the sufficiency of the diet’s micronutrients. All food and beverages consumed the previous day, both inside and outside of participants’ houses, were asked to be recalled. Food groups that were consumed during the reference period were given a score of “1”, and those that were not consumed were given a score of “0” for the nine groups: (1) starchy foods; (2) dark green leafy vegetables; (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 food groups ingested during the reference period were added together and ranked into tertiles, with the highest tertile denoting a high DDS and the two lower tertiles denoting a low DDS34.

Principal component analysis (PCA) was used to generate a wealth index. Twenty-one variables entered into PCA included the availability of a water source, a latrine, a bank account, different types of living houses, livestock, agricultural ownership, and items of household property5,35. Details are published elsewhere25.

Twenty-seven previously approved questions were used to assess the state of food security. Families with fewer than the first two, two to ten, eleven to seventeen, and more than seventeen food insecurity indicators, respectively, were classified as food secure, mildly, moderately, and severely food insecure, respectively36,37.

Perceived susceptibility (3 questions), perceived severity and perceived benefits (4 items each), perceived barriers (5 items), cues to action and self-efficacy (4 items each) were individually evaluated using the sums of a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree)28 and TPB constructs: attitude and subjective norms (3 items each), perceived behavioral control (2 items), and behavioral intention (7 items)18. The factor scores were summed and divided into tertiles. Perceived susceptibility, severity, benefit, barriers, cues to action, self-efficacy, positive attitude, subjective norm, perceived behavioral control, and behavioral intention were all labelled “yes” in the highest tertile but “no” in the two lower tertiles.

The importance of fruits and vegetables was also assessed using a ten-item knowledge test38. A respondent received a 1 if they responded correctly; otherwise, they received a 0. The scores were then calculated and ordered in tertile order. Last, a high degree of nutrition knowledge was assigned to the top tertile, while a low level of nutrition knowledge was assigned to the two lower tertiles. After the data collectors were trained, they measured the MUAC of pregnant women. After 36 weeks and up to the time of birth, end-line data were obtained.

Outcome assessment

Mid-upper arm circumference (MUAC) was measured in this study to estimate the nutritional status of the women39,40. Because MUAC changes minimally during pregnancy, it is considered a better indicator of pregnant women’s nutritional status than body mass index (BMI), because pregnancy-related weight gain affects the reliability of using BMI to assess pregnant women’s nutritional status. MUAC measurements were taken on the left arm of subjects to the nearest 0.1 cm using flexible and nonstretchable measuring tape, using standard procedures40. Pregnant women with MUAC ≥ 23 cm were considered well-nourished, while those with MUAC < 23 cm were classified as undernourished40,41. Details have been described (Supplementary Table 2).

Data quality control

The questionnaire was initially created in English, translated into the local languages, “Afan Oromo” and “Amharic,” and then back-translated into English by language specialists to guarantee the consistency of the results. The questionnaire was pretested on 5% of the total sample size of study participants, and the questionnaire’s face and content validity were examined by an epidemiologist and a biostatistician25. Eight BSc data collectors and two MPH professionals each received training on the study’s goals, data collection tools, and ethical considerations to minimize interviewer bias. Supervisors rigorously monitored the data collectors every day to ensure that the questionnaire was successfully completed, and they promptly intervened if it was not. To increase the response rate, the study participants were questioned at their residences.

Data processing and analysis

The data were checked for completeness, consistency, and accuracy and entered into, cleaned, and analyzed using SPSS for Windows version 20 and STATA version 14. Descriptive statistics, including frequencies, percentages, means, standard deviations, and standard errors, were generated for the selected predictors and covariates. Details of model assumptions have been described (Supplementary Table 3). The baseline characteristics of the intervention and control groups were assessed using the chi-square test. The independent sample t test and paired t test were used to compare MUAC between and within the intervention and control groups, respectively. The difference in difference (DID) estimated the difference in the change in the mean value of the end-line and baseline of MUAC42.

We employed a linear mixed effect model (LMM) to evaluate the intervention effect on MUAC, accounting for the clustering effect. The identification of clusters and respondents was analyzed as a random effect in the analytic model. The intervention’s effectiveness was evaluated using time and intervention interaction.

Four models were fitted. The null model (model without predictors), model I (MUAC + group), model II (MUAC + group, time, group × time), and model III (MUAC + groups + predictors and covariates) were all fitted. The intraclass correlation coefficient (ICC) for MUAC in the null model was 0.795, indicating the variability of the conditions attributed to the clustering effect. The Deviance (− 2 LL), Akaike’s information criterion (AIC), and Bayesian information criterion (BIC) values were used for model comparison. The deviance value for Model III was the lowest, indicating that the full model for MUAC was a best-fit model. As a result, Model III was used to make interpretations. The effect size was expressed as an estimate (β), along with the SE and 95% CI. Sensitivity analysis using per protocol analysis was conducted. However, there was no difference in the effect size. Initially, randomly assigned pregnant women were examined in the groups to which they were assigned (intention-to-treat analysis principle). Pregnant women who discontinued due to adherence failure or relocation were included in the intention to treat analysis. The statistical significance of the association was declared at a p value of less than 0.05, and tests were two-sided.

Ethical approval

The current study was ethically approved by Jimma University’s Institutional Review Board before it began (Protocol #: IRB000296/2012). The health offices provided an authorization letter. All methods were carried out in according with the relevant tenets of Helsinki Declaration and good clinical practice43. Each respondent provided informed written consent. The respondents’ privacy and confidentiality were ensured throughout the data collection and administration procedures. The trial for the study was retrospectively registered on Pan African Clinical Trials.gov with a registration number of PACTR202201731802989 on 24/01/2022. The study was reported following the Consolidated Standards of Reporting Trials (CONSORT) 2010 statement44 (Related manuscript Table 1).Table 1 Baseline socio-demographic and economic characteristics of pregnant women in Southeast Ethiopia, 2021.

Full size table

Results

Sociodemographic and economic factors of the participants

A total of 224 (98.7%) and 223 (98.2%) pregnant women were successfully interviewed and had MUAC measured in the intervention and control groups, respectively (Fig. 1). This was due to the inability to provide end-line data as the study subjects changed locations. The mean (± SD) age of the respondents was 25.93 (± 5.52) years for the intervention group and 24.24 (± 4.24) years for the control group. There was no substantial difference in baseline characteristics between the intervention and control groups (P value > 0.05) (Table 1).

figure 1
Fig. 1

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-value < 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). Moreover, the HBM and TPB constructs revealed a strong correlation with MUAC (Supplementary Table 4).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.

Full size table

Mid-upper arm circumference

There was no difference between the control and intervention groups at baseline in terms of MUAC (P-value < 0.056). The end-line results did, nevertheless, reveal a significant difference between the control group and intervention group (P < 0.0001). The net mean MUAC difference (difference in differences) between the intervention and control groups was 0.59 ± 0.05 cm, which was statistically significant (P < 0.0001) (Table 3).Table 3 Differences between baseline and end-line measurements of MUAC and differences in the differences between the intervention and control groups during pregnancy in Southeast Ethiopia, 2021.

The variance of the residual errors at the individual level of the average MUAC was determined to be 0.41. This difference was statistically significant (P < 0.0001). The intraindividual correlation coefficient was 0.795, revealing the relevance of accounting when fitting four-level models. The multivariable linear mixed model revealed that having received nutrition education intervention was positively associated with MUAC (β = 0.85, 95% CI 0.60, 1.12, P < 0.0001) (Table 4).Table 4 Multivariable linear mixed model predicting MUAC among pregnant women, Robe and Goba Towns, Southeast Ethiopia, 2021 (n = 454 for baseline; n = 447 for end-line).

Discussion

We aimed to assess the effect of nutrition education interventions on nutritional status among pregnant women in Robe and Goba Towns, Southeast Ethiopia. The study’s findings revealed that nutrition education interventions were positively associated with MUAC among pregnant women. The net mean MUAC difference between the intervention and control groups was 0.59 cm. The MUAC of the pregnant women in the intervention group significantly improved compared to that of control group. This study’s findings supported those of other studies conducted in rural Ethiopia19,45. The possible explanation might be that nutrition education leads to favorable attitudes and, thus, changes in nutrition behavior.

Nutritional education interventions increased MUAC by 0.85 cm in urban pregnant women. The results agreed with those of studies conducted in rural Ethiopia19,45,46,47,48 and Rwanda49, in which there was a substantial improvement in MUAC among pregnant women after the intervention. This might be because nutrition education provided by public health specialists was effective in improving the MUAC of pregnant women. Our study’s findings would add to a body of knowledge as it was conducted in urban settings.

This study used nutrition education strategies. Nutrition educators employed education guides, the health belief model (HBM), and the theory of planned behavior (TPB), and trimester-based education. In contrast, the healthcare system’s current education does not include counselling guides, a health behavior model, or a theory. Similarly, this study’s finding agreed with a study conducted in Iran50. This could be because nutrition education interventions increase the awareness of nutrition intake of pregnant women.

Nutrition education interventions in our study were based on the HBM and TPB, two of the most commonly used health behavior models and theories16. Nutrition interventions based on an integrated HBM and the TPB increase pregnant women’s diet knowledge, dietary diversity, and nutritional status18.

A previous study found a significant favorable effect of using HBM and TPB constructs during prenatal counselling to encourage healthy eating behavior51. This could be because women who attend nutrition education using the HBM believe that the repercussions of malnutrition are severe, and they also believe that they are perceived to suffer the consequences of malnutrition. In addition, the pregnant women perceived that the benefits of consuming enough and diverse food outweighed the hurdles to obtaining it. Their perspective can then influence their attitude and actions. These components also have an important role in raising women’s intentions to eat a balanced diet, which directly contributes to increasing MUAC among pregnant women19.

Nutrition education can increase nutrition knowledge, but its effectiveness in changing actual eating behaviors and practices is often limited. This highlights the complex nature of nutrition interventions and the need for multifaceted approaches52. Education alone may be ineffectual if the environment does not encourage healthy behaviours. Nutrition education attempts frequently result in only modest or short-term improvements, with long-term behaviour change being more difficult to achieve with education alone. While education can help with knowledge and some behaviours, it may not be as effective as direct supplementation in treating critical nutrients deficits. Seasonality, distance to markets, family poverty, gender inequities, and cultural or religious traditions that influence food consumption can all have an impact on nutrition education’s efficacy53,54,55,56,57. It’s worth noting that a mix of education and supplementing strategies may be most effective in treating complicated nutritional concerns58. Furthermore, building an enabling atmosphere in which individuals can apply what they’ve learned is critical to the success of nutrition education programmes52.

Interventions to combat undernutrition during pregnancy can improve the mother’s and child’s health, as optimal nutrition decreases short-term impacts on mothers (adverse pregnancy outcomes, such as pre-eclampsia, gestational diabetes, anemia, and adverse birth outcomes, such as low birth weight, preterm birth, and stillbirth) and long-term impacts (stunting, micronutrient deficiencies, and chronic diseases) later in life59.

The findings have significant practical ramifications. The results indicated that tailoring current nutrition policies, strategies, and initiatives is justified to integrate the health behavior model and theory into nutrition education within Ethiopia’s current health system. Moreover, enhancing maternal dietary diversity in Ethiopia urgently needs interdisciplinary cooperation and a comprehensive strategy.

The main advantage of our study was that it was a community-based, cluster-randomized, controlled trial in which encouraging the consumption of fruits and vegetables was integrated with the HBM and TPB, both of which are applicable to relevant and conventional ANC. Cluster randomized controlled trials need to have both internal and external validity to be generalizable60. The cluster character of the study was taken into consideration during both the selection of the sample size and the data analysis. Evaluation of program execution and adoption, or the degree to which the setting is representative of the general population, could similarly be used to measure external validity60. However, recall bias and social desirability bias could have influenced the findings of our study. Despite this, efforts were made to probe pregnant women numerous times over the course of 24 h to improve dietary recall. Self-reporting, on the other hand, is frequently used in nutrition assessments and has been shown to have more predictive ability than objective assessments61. The nutrition education intervention was trimester-based, promoting improved dietary diversity, including increased fruit and vegetable intake during pregnancy.

Conclusion

The results showed that nutrition education interventions substantially improved mid-upper arm circumference (MUAC) among pregnant women. Integrating health belief model (HBM) and theory of planned behavior (TPB) are effective in improving MUAC among pregnant women. Moreover, it could be an important nutrition education intervention initiative in urban settings.

Data availability

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

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Acknowledgements

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

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Authors and Affiliations

  1. Department of Public Health, School of Health Sciences, Madda Walabu University, Goba, EthiopiaGirma Beressa
  2. Nutrition and Dietetics Department, Faculty of Public Health, Jimma University, Jimma, EthiopiaGirma Beressa & Tefera Belachew
  3. College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, CanadaSusan J. Whiting

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. SJW 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 the nutritional status of pregnant women in Robe and Goba Towns, Southeast Ethiopia, using a cluster randomized controlled trial. Sci Rep 14, 19706 (2024). https://doi.org/10.1038/s41598-024-70861-1

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