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Record W2912237026 · doi:10.1002/dev.21823

Contextual risk factors impacting the colonization and development of the intestinal microbiota: Implications for children in low‐ and middle‐income countries

2019· review· en· W2912237026 on OpenAlexaff
Krysta Andrews, Andrea González

Bibliographic record

VenueDevelopmental Psychobiology · 2019
Typereview
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPsychosocialMalnutritionPsychological interventionEnvironmental healthPovertyLow and middle income countriesDysbiosisPsychological resilienceGut floraMedicineDeveloping countryPsychologyBiologyImmunologyPsychiatryEcology

Abstract

fetched live from OpenAlex

Early adversities, such as poverty, maternal stress, and malnutrition, can affect the structure and functioning of the developing brain with implications for biological systems such as the intestinal microbiota. To date, most studies examining the impact of these risk factors on the development and functioning of the intestinal microbiota have primarily been conducted in high-income countries. However, arguably, children in low- and middle-income countries may be at increased risk given cumulative biological and psychosocial adversities during their development. Accumulating evidence in low- and middle-income countries has linked dysbiosis of the intestinal microbiota to child health outcomes such as stunting, malnutrition, and diarrheal diseases characterized by reduced microbial diversity and elevated pathogenic bacteria, which has implications for psychosocial outcomes. This review summarizes empirical findings that highlight the association between risk factors prevalent in low- and middle-income countries and the intestinal microbiota of children. Additionally, we briefly survey the current evidence regarding the effect of nutritional interventions on the microbial composition of children in low- and middle-income countries. We conclude that these empirical studies have the capacity to inform future research investigating the influence of preventive interventions on biological systems by targeting the predominant risk factors faced by children in low- and middle-income countries.

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: Review · Consensus signal: none
Teacher disagreement score0.287
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.048
GPT teacher head0.331
Teacher spread0.283 · 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
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

Citations10
Published2019
Admission routes1
Has abstractyes

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