The significance of awareness about iron deficiency anaemia in its prevention among Iraqi pregnant women attending primary healthcare centres
Bibliographic record
Abstract
Search, G -Funds CollectionBackground.Iron deficiency anaemia in pregnancy is one of the most common preventable causes of maternal morbidity and poor prenatal outcome.This study was conducted to assess the level of awareness about iron deficiency anaemia and the effect of the awareness in the prevention of anaemia. Material and methods.A cross-sectional study was conducted in randomly six selected primary healthcare centres in Al Najaf city, Iraq.Data was collected from 1 July to 20 September 2022 through the interview of participants using a self-structured questionnaire.A Chisquare test was used to test the association between awareness levels and different variables, and a binomial logistic regression was performed to ascertain the effects of awareness about iron deficiency anaemia on the likelihood of its prevention among participants.Results.The prevalence of iron deficiency anaemia among (343) pregnant women was 85.4%, and the mean haemoglobin level was 9.5 g/dL.Most of the participants had poor awareness about iron deficiency anaemia (69.4%), and only 6.1% had good awareness.Statistical analyses revealed that awareness was significantly associated with educational level, residence, financial status and parity number (p < 0.001).Binomial logistic regression analysis demonstrated that having adequate awareness increases the likelihood of not having anaemia by more than two and half times (OR = 2.72, 95% CI [1.02,7.27]). Conclusions.A low level of awareness regarding iron deficiency anaemia was found among pregnant women.Adequate awareness among participants can help in the prevention of anaemia.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".