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Population-Modifiable Risk Factors Associated With Childhood Stunting in Sub-Saharan Africa

2023· article· en· W4387728322 on OpenAlexaff
Kedir Y. Ahmed, Abel Fekadu Dadi, Felix Akpojene Ogbo, Andrew Page, Kingsley Agho, Temesgen Yihunie Akalu, Adhanom Gebreegziabher Baraki, Getayeneh Antehunegn Tesema, Achamyeleh Birhanu Teshale, Tesfa Sewunet Alamneh, Zemenu Tadesse Tessema, Robel Hussen Kabthymer, Koku Sisay Tamirat, Allen G. Ross

Bibliographic record

VenueJAMA Network Open · 2023
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineEnvironmental healthBody mass indexPopulationDemographyPsychological interventionPediatrics

Abstract

fetched live from OpenAlex

Importance: Identifying modifiable risk factors associated with childhood stunting in sub-Saharan Africa (SSA) is imperative for the development of evidence-based interventions and to achieve the Sustainable Development Goals. Objective: To evaluate key modifiable risk factors associated with childhood stunting in SSA. Design, Setting, and Participants: This cross-sectional study examined the most recent (2014-2021) Demographic and Health Surveys data for children younger than 5 years from 25 SSA countries. Exposures: Modifiable risk factors included history of diarrhea within 2 weeks, consumption of dairy products, maternal body mass index, maternal educational level, antenatal care visits, place of birth, wealth index, type of toilet, and type of cooking fuel. Main Outcomes and Measures: Stunting and severe stunting, measured using the height-for-age z score, were the main outcomes. Children who scored below -2.0 SDs or -3.0 SDs were classified as having stunted or severely stunted growth, respectively. Relative risks and 95% CIs were computed using generalized linear latent and mixed models and log-binomial link functions. Population-attributable fractions (PAFs) were calculated using adjusted relative risks and prevalence estimates for key modifiable risk factors. Results: This study included 145 900 children from 25 SSA countries. The mean (SD) age of the children was 29.4 (17.3) months, and 50.6% were male. The highest PAFs of severe childhood stunting were observed for mothers lacking a formal education (PAF, 21.9%; 95% CI, 19.0%-24.8%), children lacking consumption of dairy products (PAF, 20.8%; 95% CI, 16.8%-24.9%), unclean cooking fuel (PAF, 9.5%; 95% CI, 2.6%-16.3%), home birth (PAF, 8.3%; 95% CI, 6.3%-10.0%), and low-income household (PAF, 5.8%; 95% CI, 3.4%-8.0%). These 5 modifiable risk factors were associated with 51.6% (95% CI, 40.5%-60.9%) of the severe childhood stunting in SSA. Conclusions and Relevance: This cross-sectional study identified 5 modifiable risk factors that were associated with 51.6% of severe childhood stunting in SSA. These factors should be a priority for policy makers when considering future child health interventions to address chronic malnutrition in SSA.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.031
GPT teacher head0.269
Teacher spread0.239 · 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

Citations22
Published2023
Admission routes1
Has abstractyes

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