Iron-fortified lentils to improve iron (Fe) status among adolescent girls in Bangladesh - study protocol for a double-blind community-based randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Lentils are generally considered to be a nutrient-dense food, and a good source of iron (Fe). This study aims to establish novel evidence of the effectiveness of the consumption of Fe-fortified lentils in improving the body Fe status and thus cognitive performance in non-pregnant adolescent girls in rural Bangladesh, compared to consumption of ordinary lentils. METHODS: We have designed a double-blind (both trial participants and outcome assessors), community-based, cluster-randomized controlled trial among 1260 Bangladeshi adolescent girls between the ages of 10-17 years who are non-smoking, not married, not pregnant, not breastfeeding, and generally healthy at the time of enrollment. The intervention will include three arms who will receive: (1) Fe-fortified lentils; (2) unfortified lentils; or (3) usual intake. Participants will be served a thick preparation of cooked Fe-fortified lentils (37.5 g raw lentils, approximately 200 g cooked lentils) 5 days per week for 85 feeding days (around 4 months) using a locally acceptable recipe. Lentils were fortified with Fe in the laboratory at the Department of Plant Sciences at the University of Saskatchewan in Canada. A subsample of participants (n = 360) will be randomly invited to be included in cognitive testing. DISCUSSION: Data on socio-demographic characteristics, household food security status, adolescent food habits and cognitive testing will be collected at baseline and endline (4 months). Venous blood samples will be collected at baseline, midline (2 months) and endline to measure adolescents' Fe status. Computerized cognitive testing will include five common measures of attentional (three of attention) and mnemonic functioning (two of memory) carried out using DMDX software. The results of this study will be used to garner support for and to substantiate large-scale production and market expansion of Fe-fortified lentils, and will contribute to knowledge about how to enhance Fe status in adolescents worldwide in resource-poor settings, using staple food crops. TRIAL REGISTRATION: ClinicalTrials.gov NCT03516734 . Registered on 24 May 2018.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.014 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.052 | 0.008 |
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".