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Record W4229050701 · doi:10.1093/inthealth/ihab044

Gender differences in survival among low birthweight newborns and infants in sub-Saharan Africa: a systematic review

2021· review· en· W4229050701 on OpenAlexaff
Akalewold T. Gebremeskel, Arone Wondwossen Fantaye, Lena Faust, Pamela Obegu, Sanni Yaya

Bibliographic record

VenueInternational Health · 2021
Typereview
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsMcGill UniversityUniversity of Ottawa
Fundersnot available
KeywordsCINAHLMedicineScopusLow birth weightPopulationDemographyInfant mortalityMEDLINEInclusion (mineral)Child mortalityPediatricsPregnancyEnvironmental healthPsychological interventionPsychology

Abstract

fetched live from OpenAlex

Abstract In sub-Saharan Africa, low birthweight (LBW) accounts for three-quarters of under-five mortality and morbidity. However, gender differences in survival among LBW newborns and infants have not yet been systematically examined. This review examines gender differences in survival among LBW newborns and infants in the region. Ovid Medline, Embase, CINAHL, Scopus and Global Health databases were searched for qualitative, quantitative and mixed methods studies. Studies that presented information on differences in mortality or in morbidity between LBW male and female newborns or infants were eligible for inclusion. The database search yielded 4124 articles, of which 11 were eligible for inclusion. A narrative synthesis method was used to summarize the findings of the included studies. Seven studies reported more LBW male deaths, three studies reported more LBW female deaths and one study did not disaggregate the deaths by gender. Nine of the 11 studies that examined gender differences in mortality did not find significant evidence of gender differences in mortality among LBW newborns and infants. Likewise, no significant differences were found for gender differences in morbidity among this population. The review findings suggest a need for further research on this topic given the potential significance on child health and developmental goals.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.047
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.075
GPT teacher head0.364
Teacher spread0.288 · 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.

Study designSystematic review
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

Citations11
Published2021
Admission routes1
Has abstractyes

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