Effect of nutrition education integrating the health belief model and theory of planned behavior on dietary diversity of pregnant women in Southeast Ethiopia: a cluster randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Maternal anemia, miscarriage, low birth weight (LBW), preterm birth (PTB), intrauterine growth restriction (IUGR), prenatal and infant mortality, morbidity, and the risk of chronic disease later in life are all increased by a lack of dietary diversity during pregnancy. However, evidence for the effect of nutrition education on the dietary diversity score (DDS) among pregnant women was sparse in Ethiopia, particularly in the study areas. This study aimed to assess the effect of nutrition education on dietary diversity among pregnant women in urban settings in Southeast Ethiopia. METHODS: A community-based two-arm parallel cluster randomized controlled trial was conducted among 447 randomly selected pregnant women attending antenatal care (224 intervention group and 223 control group) 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 participated in the interventions were given nutrition education starting at 16 weeks of gestation and continuing for 6 months. We used a pre-tested, interviewer-administered, structured questionnaire to collect the data. A 24-hour qualitative dietary recall was used to calculate the dietary diversity score (DDS). A multivariable generalized estimating equation (GEE) model was conducted to evaluate the intervention effect. RESULTS: After the intervention, the proportion of adequate dietary diversity was 14.15% higher in the intervention arm compared to the control group (45.09% versus 30.94%, P = 0.002). The overall difference in adequate dietary diversity between the two groups was 8.5%. After adjusting for background characteristics, the multivariable GEE binary logistic model revealed that having received intervention [(AOR = 1.89, 95% CI: 1.27, 2.79)], being literate [(AOR = 3.41, 95% CI: 1.13, 10.23)], and having high wealth [(AOR = 1.60, 95% CI: 1.09, 2.35)] significantly improved adequate dietary diversity. CONCLUSION: The findings indicated that having received the intervention, being literate, and having a high level of wealth significantly improved maternal dietary diversity. Efforts should be made to increase nutrition education using the health belief model (HBM) and the theory of planned behavior (TPB). Moreover, there is a need to improve literacy and economic empowerment through income-generating activities to enhance adequate dietary diversification during pregnancy. TRIAL REGISTRATION: Clinicaltrials.gov (PACTR202201731802989, Retrospectively registered on 24 January 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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".