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Record W4396715238 · doi:10.19080/jojph.2022.06.555700

Potential For Dietary Calcium to Prevent Fluoride Uptake in Children in Halaba Special District, Southern Ethiopia: Knowledge, Attitudes, and Practices of Mothers

2022· article· en· W4396715238 on OpenAlexaff
Tamirat Getachew Bantero, Demmelash Mulualem, Derese Tamiru Desta, Getahun Wansisa Worancha, Bergene Boshe Boricha, Susan J. Whiting

Bibliographic record

VenueJuniper Online Journal of Public Health · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFluoride Effects and Removal
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCalciumFluorideEnvironmental healthMedicinePsychologyChemistryInternal medicineInorganic chemistry

Abstract

fetched live from OpenAlex

Fluorosis is a public health problem in Ethiopia.Fluoride (F) absorption can be decreased by dietary calcium (Ca) which forms insoluble complexes with the fluoride ion F-.The aim of this study was to assess maternal knowledge, attitudes, and practice (KAP) towards calcium in an area with high water F (9.7± 0.27mg/L) in Halaba, Southern Ethiopia.A cross-sectional study was conducted in 254 child-mother pairs randomly chosen from two kebeles of the district, and a questionnaire was used to obtain KAP.Teff, maize, millet were the major cereals in the study area and milk followed from the animal source food.The majority (96.5%) of respondents had never heard about fluoride.More than two-thirds reported that they did not know about the causes of teeth decay and skeletal fluorosis, and just 2% were aware that calcium could mitigate fluorosis symptoms.As a follow-up, nutrition education was provided that included sources of calcium stressing locally available foods.This study suggests that future research should focus on behavior communication for enhancing the community's knowledge, attitude, and practices towards fluorosis including improving calcium intake.

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)0.003
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 score0.407
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.001
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 head0.031
GPT teacher head0.337
Teacher spread0.306 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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