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Record W3155599483 · doi:10.1093/jn/nxab066

A Randomized Multiple Micronutrient Powder Point-of-Use Fortification Trial Implemented in Indian Preschools Increases Expressive Language and Reduces Anemia and Iron Deficiency

2021· article· en· W3155599483 on OpenAlexaff
Maureen M. Black, Sylvia Fernandez‐Rao, K. Madhavan Nair, Nagalla Balakrishna, Nicholas Tilton, Kankipati Vijaya Radhakrishna, Punjal Ravinder, Kimberly Harding, Gregory A. Reinhart, Doris P. Yimgang, Kristen Hurley

Bibliographic record

VenueJournal of Nutrition · 2021
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsNutrition International
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentMathile Institute for the Advancement of Human Nutrition
KeywordsMicronutrientMedicineAnemiaPlaceboAnthropometryRandomized controlled trialEarly childhoodPediatricsEnvironmental healthPsychologyDevelopmental psychologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Anemia is a global public health problem that undermines childhood development. India provides government-sponsored integrated nutrition/child development preschools. OBJECTIVES: This double-masked, cluster-randomized controlled trial examines whether point-of-use multiple micronutrient powder (MNP) compared with placebo fortification of preschool meals impacts child development and whether effects vary by preschool quality (primary outcome) and biomarkers of anemia and micronutrients (secondary outcomes). We also measured growth and morbidity. METHODS: We randomly assigned 22 preschools in rural India to receive MNP/placebo fortification. We administered baseline and endline blood sampling and measures of childhood development (Mullen Scales of Early Learning, inhibitory control, social-emotional), anthropometry, and morbidity to preschoolers (aged 29-49 mo). Preschools added MNP/placebo to meals 6 d/wk for 8 mo. We conducted linear mixed-effects regression models accounting for preschool clustering and repeated measures. We evaluated child development, examining effects in high- compared with low-quality preschools using the Early Childhood Environment Rating Scale-Revised and the Home Observation for the Measurement of the Environment Inventory, modified for preschools. RESULTS: At baseline, mean age ± SD was 36.6 ± 5.7 mo, with 47.8% anemic, 41.9% stunted, and 20.0% wasted. Baseline expressive/receptive language scores were higher in high-quality compared with low-quality preschools (P = 0.02 and P = 0.03, respectively). At endline (91% retention, n = 293/321), we found MNP compared with placebo effects in expressive language (Cohen's standardized effect d = 0.4), inhibitory control (d = 0.2), and social-emotional (d = 0.3) in low-quality, not high-quality, preschools. MNP had significantly greater reduction of anemia and iron deficiency compared with placebo (37% compared with 13.5% and 41% compared with 1.2%, respectively). There were no effects on growth or morbidity. CONCLUSIONS: Providing multiple micronutrient-fortified meals in government-sponsored preschools is feasible; reduced anemia and iron deficiency; and, in low-quality preschools, increased preschoolers' expressive language and inhibitory control and reduced developmental disparities. Improving overall preschool quality by incorporating multiple components of nurturing care (responsive care, learning, and nutrition) may be necessary to enhance preschoolers' development. This trial was registered at clinicaltrials.gov as NCT01660958.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.015
GPT teacher head0.289
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

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Citations32
Published2021
Admission routes1
Has abstractno

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