Anemia prevalence in mothers with children under five years of age in Dodi Papase, Volta region of Ghana and preventive practices
Bibliographic record
Abstract
Abstract Introduction/Objective Sociodemographic factors influence the prevalence of anemia in endemic areas. The purpose of this study is to establish the prevalence and causes of anemia and to determine anemia preventive practices carried out by mothers with children under five years of age in the Kadjebi District of the Volta region of Ghana. Methods/Case Report This homogenous sampling study involved women of reproductive age with children less than five years of age from Saint Mary Theresa Hospital. Interview guides were administered, and the data collected were analyzed using the Statistical Package for Social Sciences (SPSS) version 21. Results (if a Case Study enter NA) A total of 150 participants were studied. 52.7% of the mothers indicated that their children had never been diagnosed with anemia; however, Hb levels recorded for these children showed that 73.3% were anemic, even though 93.8% of the mothers had been given iron supplements during their pregnancy. Furthermore, anemia prevention practices comprised of whether the child had been given any anti-malaria prophylaxis (98.4% denied / 1.6% confirmed) if the child had been dewormed in the last three months (89.9% denied / 10.1% confirmed), whether the child was given iron supplements in the last three months (59.7% denied / 40.3% confirmed), if the child had been given vitamin supplements in the last three months (24.0% denied / 76.0% confirmed). Conclusion Nutritional deficiencies, worm infestation, and malaria were identified as the major causes of anemia among the children. Mothers were educated about the possible causes and prevention methods of anemia.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".