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Record W4416979656 · doi:10.1016/j.eclinm.2025.103682

Association between maternal vitamin D supplementation during pregnancy and the risk of acute respiratory infections in offspring: a systematic review and meta-analysis

2025· article· en· W4416979656 on OpenAlexaff
David A. Jolliffe, Nicklas Brustad, Bo Chawes, Cyrus Cooper, Stefania D’Angelo, Nicholas C. Harvey, Augusto A. Litonjua, Rebecca J Moon, Shaun K. Morris, John Sluyter, Scott T. Weiss, Adrian R. Martineau

Bibliographic record

VenueEClinicalMedicine · 2025
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsInstitute for Clinical Evaluative SciencesCentre for Global Health Research
FundersNational Heart, Lung, and Blood InstituteNational Institutes of HealthBarts Charity
KeywordsPregnancyVitamin D and neurologyRespiratory systemvitamin D deficiencyRespiratory infectionRespiratory tract infections

Abstract

fetched live from OpenAlex

Background Acute respiratory infections (ARIs) are a leading cause of mortality in infants. Vitamin D supports innate antimicrobial effector mechanisms in leucocytes and respiratory epithelium. Maternal vitamin D supplementation during pregnancy has been proposed as a preventive strategy, however, an up-to-date synthesis of available data from randomised controlled trials (RCTs) has not been conducted. Methods We conducted a systematic review and meta-analysis of aggregate data from RCTs of maternal vitamin D supplementation for prevention of ARIs in offspring. Data were analysed using a random-effects model. We searched MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, Web of Science and the ClinicalTrials.gov from database inception to 5th August 2025. No language restrictions were imposed. Double-blind RCTs of maternal vitamin D supplementation, with placebo or lower-dose vitamin D control, were eligible if approved by Research Ethics Committee and if ARI incidence in offspring was collected prospectively and pre-specified as an efficacy outcome. Sub-group analyses were done to determine whether effects of maternal vitamin D supplementation on offspring ARI risk varied according to maternal baseline circulating 25-hydroxyvitamin D (25 [OH]D) concentrations (<25 nmol/L, 25–49.9 nmol/L, 50–74.9 nmol/L, or ≥75 nmol/L). The study was registered with PROSPERO, CRD42024527191. Findings Our search identified 405 unique studies, of which 4 RCTs (3678 participants) were eligible and included. For the primary comparison of any maternal vitamin D supplementation vs. placebo, the intervention did not significantly affect overall ARI risk in offspring (incidence rate ratio [IRR] 1.01, 95% CI 0.98–1.03, P=0.66; 4 studies; I 2 14.5%, absolute effects from GRADE assessment: 0.05 higher rate in vitamin D arm; moderate quality finding). Pre-specified subgroup analysis did not reveal evidence of effect modification by maternal baseline vitamin D status: <25 nmol/L group: IRR 1.12, 95% CI 0.98–1.27 (607 participants in 4 studies, I 2 47.8%) vs. 25–49.9 nmol/L group: IRR 1.04, 95% CI 0.96–1.13 (1154 participants in 4 studies, I 2 68.5%) vs. 50–74.9 nmol/L group: IRR 1.00, 95% CI 0.93–1.08 (789 participants in 4 studies, I 2 64.9%) vs. ≥75 nmol/L group: IRR 0.97, 95% CI 0.89–1.06 (505 participants in 4 studies, I 2 47.6%). A funnel plot did not indicate the presence of publication bias or small-study effects (P = 0.71, Egger's test). Interpretation Our analysis of current data does not support routine antenatal vitamin D supplementation for the prevention of ARI in offspring. Key limitations of the study were the administration of a low dose vitamin D standard-of-care in some populations which may have attenuated effects of the intervention, and heterogeneity in ARI case definitions which may have introduced misclassification bias. Targeted supplementation in deficient populations may warrant further investigation. Funding None.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.311
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
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 head0.048
GPT teacher head0.401
Teacher spread0.353 · 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
Published2025
Admission routes1
Has abstractyes

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