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Record W4401907105 · doi:10.3390/adolescents4030028

Individual and Environmental Determinants of the Consumption of Iron-Rich Foods among Senegalese Adolescent Girls: A Behavioural Model

2024· article· en· W4401907105 on OpenAlexaff
Jérémie B. Dupuis, Aminata Ndéné Ndiaye, Nafissatou Ba Lo, El Hadj Momar Thiam, Mohamadou Sall, Sonia Blaney

Bibliographic record

VenueAdolescents · 2024
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsUniversité LavalUniversité de Moncton
Fundersnot available
KeywordsConsumption (sociology)Environmental healthAffect (linguistics)Path analysis (statistics)PsychologyFood consumptionTheory of planned behaviorDevelopmental psychologyMedicineControl (management)Economics

Abstract

fetched live from OpenAlex

To improve adolescent nutrition, it is crucial to understand factors underlying food behaviours. This study aims to identify pathways by which the environment and individual factors interact to affect the consumption of iron-rich food (IRF) among Senegalese adolescent girls in the hopes to reduce anemia. This is a cross-sectional study conducted among 600 adolescent girls (10–19 years old) of all 14 regions of Senegal. IRF consumption in the past day and night was evaluated using a food frequency questionnaire. Individual determinants, such as the attitude, the subjected norm, and the perceived behaviour control (PBC), and environmental determinants, such as food accessibility and price, were assessed using a validated and reliable questionnaire. Path analyses were conducted to examine relations between IRF consumption and individual and environmental variables. Overall, 83.7% of girls had the intention to eat IRF and 84.7% reported doing so. The PBC (β = 0.20, p < 0.01) and the attitude (β = 0.57, p < 0.01) predict the intention of consuming IRF daily. In turn, the environment predicts the attitude (β = −0.22, p < 0.01) and the PBC (β = 0.26, p < 0.01). The intention was a predictor of the IRF consumption (β = 0.16, p < 0.05). This research provides guidance to nutrition education programmes as well as to improve the food environment to facilitate the consumption of IRF among adolescent girls by inspiring community health initiatives based on empirical data.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.485

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 head0.027
GPT teacher head0.272
Teacher spread0.245 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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