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What difference can fathers make? Early paternal absence compromises Peruvian children's growth

2011· article· en· W1958549277 on OpenAlexfundno aff
Kirk A. Dearden, Benjamin T. Crookston, Hala Madanat, Joshua H. West, Mary E. Penny, Santiago Cueto

Bibliographic record

VenueMaternal and Child Nutrition · 2011
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
FundersUniversity of California, San DiegoDepartment for International DevelopmentInternational Development Research CentreBernard van Leer FoundationBrigham Young University
KeywordsMedicinePsychosocialEarly childhoodMillennium Cohort Study (United States)DemographyOddsChild developmentPsychological interventionOdds ratioPediatricsMalnutritionCohortCohort studyDevelopmental psychologyLogistic regressionPsychologyPsychiatry

Abstract

fetched live from OpenAlex

Considerable evidence suggests that fathers' absence from home has a negative short- and long-term impact on children's health, psychosocial development, cognition and educational experience. We assessed the impact of father presence during infancy and childhood on children's height-for-age z-score (HAZ) at 5 years old. We conducted secondary data analysis from a 15-year cohort study (Young Lives) focusing on one of four Young Lives countries (Peru, n = 1821). When compared with children who saw their fathers on a daily or weekly basis during infancy and childhood, children who did not see their fathers regularly at either period had significantly lower HAZ scores (-0.23, P = 0.0094) after adjusting for maternal age, wealth and other contextual factors. Results also suggest that children who saw their fathers during childhood (but not infancy) had better HAZ scores than children who saw their fathers in infancy and childhood (0.23 z-score, P = 0.0388). Findings from analyses of resilient children (those who did not see their fathers at either round but whose HAZ > -2) show that a child's chances of not being stunted in spite of paternal absence at 1 and 5 years old were considerably greater if he or she lived in an urban area [odds ratio (OR) = 9.3], was from the wealthiest quintile (OR = 8.7) and lived in a food secure environment (OR = 3.8). Interventions designed to reduce malnutrition must be based on a fuller understanding of how paternal absence puts children at risk of growth failure.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.014
GPT teacher head0.210
Teacher spread0.196 · 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 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

Citations31
Published2011
Admission routes1
Has abstractyes

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