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Record W3134264031 · doi:10.3390/ijerph18052449

Are Countries of the Eastern Mediterranean Region on Track towards Meeting the World Health Assembly Target for Anemia? A Review of Evidence

2021· review· en· W3134264031 on OpenAlexaff
Ayoub Al‐Jawaldeh, Mandy Taktouk, Radhouene Doggui, Zahra Abdollahi, Baseer Khan Achakzai, Hassan Aguenaou, Moussa Al-Halaika, Salima Almamary, Rawhieh Barham, Ferima Coulibaly-Zerbo, Laila El Ammari, Jalila El Ati, Noureen Aleem Nishtar, Nasrin Omidvar, Mohammad Qasem Shams, Abdul Baseer Qureshi, Lara Nasreddine

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2021
Typereview
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversité de Sherbrooke
FundersWorld Health Organization
KeywordsAnemiaMicronutrientMedicineMalnutritionEnvironmental healthSanitationMicronutrient deficiencyIron-deficiency anemiaEtiologyPediatricsInternal medicinePathology

Abstract

fetched live from OpenAlex

Anemia is a multifactorial condition, with a complex etiology that involves nutritional and non-nutritional factors. The misconception that iron deficiency is equivalent to anemia may mask the need to address other potential causative factors. This review paper aims to (1) assess the burden of anemia vs. iron deficiency anemia (IDA) amongst women of reproductive age (WRA), pregnant women (PW), and children under five years old (underfive children, U5C) in the Eastern Mediterranean region (EMR); (2) evaluate trends in anemia prevalence and whether countries are on track towards meeting the World Health Assembly (WHA) target for 2025; and (3) characterize anemia reduction efforts and provide a road map for future programs. A search of pertinent literature and databases was conducted. Anemia prevalence in the EMR ranged between 22.6% and 63% amongst PW, 27% and 69.6% amongst WRA, and 23.8% and 83.5% amongst U5C. Data showed that the EMR is not on course towards meeting the WHA target. The contribution of IDA to anemia was found to be less than half. Other potential contributors to anemia in the region were identified, including micronutrient deficiencies, parasitic infestations, and poor sanitation. A framework of action was proposed as a roadmap to meet the targets set by the WHA.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.913
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.355
GPT teacher head0.493
Teacher spread0.138 · 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 designOther design
Domainnot available
GenreReview

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

Citations54
Published2021
Admission routes1
Has abstractyes

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