Adherence to Iron-Folic Acid Supplementation and Associated Factors among Antenatal Care Attendants in Public Health Institutions: The Case of Borena District, Amhara, Ethiopia: Cross-Sectional Study
Bibliographic record
Abstract
Introduction: Globally, iron deficiency is estimated to be responsible for half of all anemia cases. The reduction of iron deficiency anemia in pregnant women relies largely on their adherence to IFA supplementation. This study aimed to assess the factors associated with adherence to IFA supplementation among women attending antenatal checkups at health centers in Borena district, Ethiopia. Methods: Institution-based cross-sectional study design was conducted on 348 pregnant women. The data were analyzed using SPSS version 20. Variables with a p-value of ≤0.2 in the univariable logistic regression analysis were included in the multivariable analysis. Adjusted odds ratio with 95% confidence interval was reported, and variables with p<0.05 were considered statistically significant. Result: A total of 340 pregnant women were enrolled. The study revealed that 45.6% (95% CI: 40.27, 50.92%) of women adhered to the IFA supplement use. Women of husbands with primary education [AOR: 1.95; 95% CI: 1.07, 3.57] and who had taken IFA for two months [AOR: 2.81; 95% CI: 1.37, 5.79] were positively associated with adherence to IFA supplementation. However, women with a previous history of abortion [AOR: 0.16; 95% CI: 0.50, 0.53], who had disease other than anemia [AOR: 0.48; 95% CI: 0.28-0.79] and lack of family support [AOR: 0.12; 95% CI: 0.04, 0.39] were less likely to adhere to the supplement. Conclusion: This study revealed that nearly nine in twenty women adhered to the IFA supplement. Therefore, strengthening nutritional counseling, health education, and information on iron-folic acid supplementation in a health institution is important to improve adherence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".