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Record W3024900266 · doi:10.7939/r31z4242x

The prevalence and determinants of adequate vitamin D intake and supplementation among Canadian children

2016· article· en· W3024900266 on OpenAlexaboutno aff
Dona Munasinghe

Bibliographic record

VenueUniversity of Alberta Library · 2016
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEnvironmental healthDemographyPediatrics

Abstract

fetched live from OpenAlex

Most Canadian children are not meeting the dietary recommendations for vitamin D and have not enough sun exposure to synthesize vitamin D in their skin. Vitamin D supplementation therefore seems a necessity. However, no study has examined whether vitamin D from diet and supplements combined is enough to meet the Canadian recommendations. Likewise, no earlier study examined factors associated with vitamin D intake from diet and supplements, which is important information for public health decision makers and public health interventions. Therefore, this study aimed to assess the adequacy of vitamin D intake through both diet and supplements (objective 1), the determinants of meeting dietary guidelines (objective 2), and to assess the prevalence (objective 3) and the determinants of the use of vitamin D supplements (objective 4) and multivitamins (objective 5) among children in the province of Alberta, Canada. In 2014, a representative sample of grade five students (10-11y) in Alberta (n=2,686) was surveyed. Data on dietary intake and the use of supplements were obtained using a modified Harvard Youth/Adolescent Food Frequency questionnaire. Parents were asked how much they cared about healthy foods and physical activity and if they encouraged their child to eat healthy foods and be physically active. The adequacy of vitamin D intake was estimated using the two cut-offs given for the DRIs, i.e. the Estimated Average Requirement (EAR) of 400 International Units (IU) and the Recommended Dietary Allowance (RDA) of 600 IU. Mixed effect multiple logistic regression analysis was employed to identify the key correlates of meeting the DRIs and supplement use. Forty five percent of students met the EAR and 22% met the RDA through both diet and supplements. When vitamin D intake from diet alone was considered, only 16% and 2% met the EAR and the RDA, respectively. Out of 29% of vitamin D supplement users, 12% used supplements on a daily basis. Although 54% used multivitamins, only 28% used them on a daily basis. Parental education, household income and physical activity were positively correlated with meeting the DRIs, and students attending metropolitan area schools were more likely to meet the EAR than students attending rural area schools. Students who resided in a metropolitan area, who were more physically active, or whose parents completed college were more likely to take vitamin D supplements, independent of student’s gender, household income, body weight status and dietary practices. Students were more likely to supplement with vitamin D if their parents cared about and encouraged eating healthy foods and also cared about physical activity. The prevalence of vitamin D supplement use was highest among those who had a high vitamin D diet and those with under/normal body weight status, although supplement use was not statistically associated with either dietary vitamin D intake or body weight status. Household income, parental education and physical activity were positively associated with multivitamin use and students of parents who personally cared about eating healthy foods were more likely to take multivitamins. Public health initiatives are needed to promote supplementation of vitamin D among Albertan children. Parental awareness on the importance of providing the correct dose of vitamin D supplements to meet dietary recommendations and, educating and encouraging parents about healthy lifestyles should be a part of such initiatives.

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 score0.031
Threshold uncertainty score0.969

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 head0.007
GPT teacher head0.213
Teacher spread0.205 · 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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Citations0
Published2016
Admission routes1
Has abstractyes

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