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Record W4318217945 · doi:10.1111/mcn.13477

Antenatal care is associated with adherence to iron supplementation among pregnant women in selected low‐middle‐income‐countries of Asia, Africa, and Latin America & the Caribbean regions: Insights from Demographic and Health Surveys

2023· article· en· W4318217945 on OpenAlexaff
Elvina Karyadi, J. C. Reddy, Kirk A. Dearden, Tutut Purwanti, Mardewi, Eriana Asri, Loreto B. Roquero, Jocelyn A. Juguan, Angelita Sapitula‐Evidente, Binu Anand, Kirti Warvadekar, Anjali Bhardwaj, Md. K. Alam, Susmita Das, Gopa K. Nair, Anuj Srivastava, Manoj Kumar Raut

Bibliographic record

VenueMaternal and Child Nutrition · 2023
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsNutrition International
Fundersnot available
KeywordsMedicineLatin AmericansEnvironmental healthPublic healthLogistic regressionDeveloping countryHealth careCross-sectional studyDemographyEconomic growthNursing

Abstract

fetched live from OpenAlex

Anaemia is a global public health problem affecting 800 million women and children globally. Anaemia is associated with perinatal mortality, child morbidity and mortality, mental development, immune competence, susceptibility to lead poisoning and performance at work. The objective of this article is to identify whether antenatal care-seeking was associated with the uptake of iron supplementation among pregnant women, adjusting for a range of covariates. This article used data from the cross-sectional recent Demographic and Health Surveys (DHS) of 12 countries in Asia, Africa and Latin America & the Caribbean regions. The individual-level data from 273,144 women of reproductive age (15-49 years) were analysed from multi-country DHS. Multiple Logistic regression analyses were conducted using Predictive Analytics Software for Windows (PASW), Release 18.0. Receiving at least four antenatal care visits was significantly associated with the consumption of 90 or more iron-containing supplements in 12 low and middle income countries across three regions after adjusting for different household and respondent characteristics, while mass media exposure was found to be a significant predictor in India and Indonesia. Antenatal care seems to be the most important predictor of adherence to iron intake in the selected countries across Africa, Asia, Latin America and Caribbean regions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.240
Teacher spread0.225 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

Quick stats

Citations15
Published2023
Admission routes1
Has abstractyes

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