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Record W4407238859 · doi:10.1186/s12889-025-21699-3

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

2025· article· en· W4407238859 on OpenAlexaff
Girma Beressa, Susan J. Whiting, Tefera Belachew

Bibliographic record

VenueBMC Public Health · 2025
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsUniversity of Saskatchewan
FundersJimma University
KeywordsMedicineBiostatisticsRandomized controlled trialPublic healthCluster (spacecraft)EpidemiologyEnvironmental healthPregnancyInternal medicineNursing

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.339
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2025
Admission routes1
Has abstractyes

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