Effect of <i>Moringa Oleifera</i> leaf powder supplementation on reducing anemia in children below two years in Kisarawe District, Tanzania
Bibliographic record
Abstract
Abstract Anemia is a nutritional disorder that affects mostly children below 2 years and is mainly contributed by iron deficiency. Moringa oleifera leaves are rich in iron and other essential nutrients necessary for iron metabolism. We investigated the effect of M. oleifera leaf powder supplementation on reducing anemia among children below 2 years. A community‐based interventional study was conducted that enrolled 95 anemic children who were followed for 6 months. The intervention communities received M. oleifera leaf powder and nutrition education, while control communities only received nutrition education. Changes on mean hemoglobin (Hb) concentration and anemia prevalence were compared between the two groups using t test and proportional test where appropriate. At baseline, the mean Hb concentrations of control and intervention groups were 7.9 g/dl (SD = 1.3) and 8.3 g/dl (SD = 1.6) g/L, respectively (p‐value = 0.0943). After 6 months, anemia prevalence significantly decreased in the intervention group by 53.6% (100%–46.4%; p < 0.001) compared to 13.6% (100%–86.4%; p = 0.005) in control community. The mean Hb was 10.9 g/dl (95% CI: 10.2–11.4) for intervention and 9.4 g/dl (95% 7.8–10.1) for control (p‐value = 0.002). The effect was also observed in the reduction of the prevalence of moderate and severe anemia in the intervention communities by 68.2% and 77.9%, respectively, and by 23.3% and 56.9%, respectively, in the control communities. Increasing amount and time of using M. oleifera supplementation resulted to significant reduction in anemia cases therefore can be used as complementary solution in addressing anemia among children especially when the use of infant formulas and fortified food product is very poor.
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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 | 0.000 |
| 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) | 0.001 | 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".