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Record W4413638727 · doi:10.1186/s12889-025-24107-y

Vitamin intake and its association with type 2 diabetes mellitus (T2DM) among Malaysian adults

2025· article· en· W4413638727 on OpenAlexafffund
Zaleha Md Isa, Rosnah Ismail, Mohd Hasni Jaáfar, Noor Hassim Ismail, Azmi Mohd Tamil, Nafiza Mat Nasir, Noorhida Baharudin, Nurul Hafiza Ab Razak, Najihah Zainol Abidin, Victoria Miller, Khairul Hazdi Yusof

Bibliographic record

VenueBMC Public Health · 2025
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsHamilton Health SciencesMcMaster UniversityPopulation Health Research Institute
FundersCanadian Institutes of Health ResearchServierMinistério da Ciência, Tecnologia e InovaçãoSanofiHeart and Stroke Foundation of CanadaGlaxoSmithKlineOntario Ministry of Health and Long-Term CareAstraZeneca
KeywordsMedicineVitamin B12Type 2 Diabetes MellitusDiabetes mellitusEpidemiologyPopulationType 2 diabetesCross-sectional studyInternal medicineEndocrinologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Vitamin deficiency could increase the prevalence of type 2 diabetes mellitus (T2DM). Thus, this study aimed to determine the association between dietary vitamin intake and the prevalence of T2DM among the Malaysian adult population. METHODS: This cross-sectional study involved 9,314 participants from Prospective Urban and Rural Epidemiology Study (PURE) conducted in Malaysia. The participants comprised of 43% (4003) males and 57% (5311) females with mean age of 51.2 ± 9.4 years old. Participants were classified into the T2DM group if they reported having been diagnosed with T2DM or had a glucose level of ≥ 7 mmol/L (fasting blood glucose) or ≥ 11.1 mmol/L (non-fasting blood glucose). A validated food frequency questionnaire was used to measure the participants' usual dietary intake. The intake of dietary vitamins A, B6, B9, B12, C, E, and K was calculated based on nutrient databases. RESULTS: The T2DM prevalence was 16.9% among Malaysian adult population. The prevalences of inadequate dietary vitamin intake were elevated for vitamins A (22.8%) and C (28.8%), and notably high for vitamins B6 (98.3%), B9 (100.0%), B12 (80.5%), E (91.3%), and K (82.2%). The intake of dietary vitamins B6, B9, B12, C, E, and K was significantly lower among T2DM patients compared to those without T2DM (p-value < 0.05) when adjusted for covariates. Additionally, higher intake of dietary vitamins A, B6, B9, B12, C, E, and K was significantly associated with a reduced prevalence of T2DM (p-value < 0.05) when adjusted for covariates. CONCLUSION: This study found an alarming deficiency of vitamins A, B6, B9, B12, C, E, and K in the dietary intake among the Malaysian adult population regardless of T2DM status. The dietary vitamin deficiency (vitamins B6, B9, B12, E, and K) was more susceptible among those with T2DM compared to non-T2DM. This study indicated that higher dietary vitamin intake (vitamins A, B6, B9, B12, C, E, and K) could benefit by reducing the prevalence of T2DM. Therefore, an adequate intake of dietary vitamins is crucial for this study population to reduce the prevalence of T2DM.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.305
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), 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
Published2025
Admission routes2
Has abstractyes

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