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Knowledge Attitudes and Practices Regarding Vitamin A Supplementation among Caregivers of Children Aged from Six to Fifty-Nine Months in Vihiga County, Kenya

2023· article· en· W4387022314 on OpenAlexaboutno aff
Elijah Njeru Mbiti, Alfred Owino Odongo, Dominic Mogere

Bibliographic record

VenueInternational Journal of Innovative Research and Development · 2023
Typearticle
Languageen
FieldMedicine
TopicAntioxidant Activity and Oxidative Stress
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMicronutrientLogistic regressionEnvironmental healthCross-sectional studyVitaminQuarter (Canadian coin)Micronutrient deficiencyDeveloping countryGerontologyGeographyInternal medicine

Abstract

fetched live from OpenAlex

Vitamin A is an essential micronutrient needed in small amounts for, among other uses, the normal functioning of the visual and immune systems. The deficiency of this vital nutrient, therefore, compromises a children's ability to fight diseases and increases their risk of getting sick. The World Health Organization recommends Vitamin A Supplementation (VAS) as a strategy to combat the effects of vitamin A deficiency, but unfortunately, the coverage is low (64% in priority countries and 59% in East and Southern Africa, as reported in UNICEF global nutrition database 2000-2021). The study area recorded low coverage at 26% in 2019 and 54.9% in the year 2020. This study employed a descriptive cross-sectional study design to determine the knowledge, attitude, and practices among caregivers of children 6-59 months regarding vitamin A supplementation in Vihiga County, Kenya, and the influencing factors. In total, 393 caregivers out of the sample size of 400 (98.3%) were recruited into the study. Binary logistic regression was used to determine associations between variables and a p-value <0.05 was considered significant. High VAS awareness was reported in this study, with 90.6% of caregivers having heard of VAS. The main sources of VAS information were health workers (74.3%) and Community Health volunteers (53.2%). Other sources were Radio & TV (6.9%), Social gatherings (7.1%). There was, however, low knowledge of the benefits of VAS (30%) and the problems associated with vitamin A deficiency (30.3%). Sadly, a quarter of caregivers (24.6%) did not know any VAS benefit. A significant proportion of caregivers (77.6% p=<0.001) had adequate knowledge of VAS, scoring more than half of the 10 knowledge questions. In addition, caregivers displayed a highly positive attitude towards VAS, scoring between 88.3% and 92.6% on attitude questions. There was low VAS uptake, with only 59.5% of children having taken the supplement during the semester preceding the survey, mainly sourced from health facilities (68.4%), outreach (15.8%), CHV (10.7%) and the ECDE centres (5.1%). For children who missed VAS in the semester of reference, 38% of caregivers indicated they had no reason for missing, 20% said there was no need since the child had completed immunization, while others just forgot (9%). The key drivers of VAS uptake were knowledge (p=<0.001), availability of services at health facilities (p=0.001) and services by community health volunteers) p=0.028). Although more than three-quarters (77.6%) of caregivers demonstrated good knowledge, it did not correspond to the VAS uptake recorded in this study, pointing to a knowledge-practice gap. The VAS knowledge was shallow in terms of specific areas like benefits. The caregivers, however, had very positive attitudes towards VAS. Further, this study concludes that better knowledge is an important ingredient for VAS uptake and recommends implementing programmes to improve caregiver knowledge and optimization of the various service delivery platforms to increase both knowledge and uptake.

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)0.001
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 score0.022
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.074
GPT teacher head0.432
Teacher spread0.358 · 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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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