Consumption of Iron-Fortified Lentils Is Protective against Declining Iron Status among Adolescent Girls in Bangladesh: Evidence from a Community-Based Double-Blind, Cluster-Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: In many low-income countries, iron deficiency (ID) and its anemia (IDA) pose significant health challenges, particularly among females and girls. Finding sustainable and effective solutions to address this issue is critical. OBJECTIVES: This study aimed to evaluate the efficacy of incorporating iron-fortified lentils (IFLs) into the diets of rural Bangladeshi adolescent girls on their body iron (Fe) status. METHODS: A community-based, double-blind, cluster-randomized controlled trial involved n = 1195 girls aged 10-17 y. A total of 48 adolescent clubs (n = ∼27 girls each) were randomized into 3 groups: 1) 200 g cooked IFLs, 2) 200 g cooked noniron-fortified lentils (NIFLs), and 3) a control group with no lentils (usual dietary intake). The intervention, administered 5 days a week for 85 feeding days, provided ∼8.625 mg Fe from each serving of IFLs and 2.625 mg from NIFLs. Blood samples collected at baseline, midpoint (42 feeding days), and endpoint (85 feeding days) assessed key Fe and inflammation biomarkers. Statistical analyses were filtered for inflammation. RESULTS: Although all groups experienced a decline in Fe status over time, the IFL group exhibited a significantly reduced decline in serum ferritin (sFer -7.2 μg/L), and total body iron (TBI -0.48 mg/kg) level compared with NIFL (sFer -14.3 μg/L and TBI -1.36 mg/kg) and usual intake group (sFer -12.8 μg/L and TBI -1.33 mg/kg). Additionally, those in the IFL group had a 57% reduced risk of developing clinical ID (sFer <15 μg/L) compared with the usual intake group. CONCLUSIONS: Our findings suggest that incorporating IFLs into the diet can help mitigate a decline in sFer, indicating a positive impact on the body Fe status of adolescent girls. This research underscores the potential role of fortified foods in addressing ID and IDA in vulnerable populations, emphasizing the significance of food-based interventions in public health. TRIAL REGISTRATION NUMBER: This trial was registered at the clinicaltrials.gov on May 24, 2018 (https://clinicaltrials.gov/study/NCT03516734?locStr=Bangladesh&country=Bangladesh&distance=50&cond=Anemia&intr=Iron%20fortified%20lentils&rank=1) as NCT03516734.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".