Back

Vitamin D Supplementation For The Prevention Of Respiratory Infections In Childhood: A Systematic Review And Meta-Analysis

Sousa, H. K. P.; Siqueira, T. d. S.; Oliveira, M. A. M. d. C.; Carvalho, E. R. B. d.; Cavalcante, A. J. H.; Silva, J. B. T. d.; Viana, P. L. V.; Fidencio, G. S.; Costa, V. C. S.; Arnaud, L. M. L. B.; Matos, A. P. V.; Barbosa, J. M. R.

2026-10-13 pediatrics
10.64898/2026.10.11.26365254 medRxiv
Show abstract

Background: Vitamin D modulates innate and adaptive immunity and has been investigated for preventing pediatric respiratory infections. Objective: To assess the effects of vitamin D supplementation on respiratory tract infections (RTIs), including upper RTIs, lower RTIs/recurrent pneumonia, and hospitalization/clinical severity in children and adolescents. Methods: Systematic review and random-effects meta-analysis of 16 publications, of which 13 contributed to quantitative synthesis. Twenty-four effect estimates were pooled, eight per outcome. The odds ratio (OR) was analyzed on its natural logarithmic scale (logOR), using restricted maximum likelihood (REML) estimation and Knapp-Hartung (KH) adjusted inference. Where necessary, risk ratios (RRs), hazard ratios (HRs), and incidence rate ratios (IRRs) were approximated on the logOR scale. Results: For respiratory infection/upper RTI, pooled logOR was -0.284 (KH-adjusted 95% confidence interval [CI]: -0.678 to 0.110; OR 0.753; p = 0.132; I2 = 97.2%). For lower RTI/recurrent pneumonia, logOR was -0.445 (95% CI: -0.987 to 0.097; OR 0.641; p = 0.093; I2 = 89.5%). For hospitalization/clinical severity, logOR was -0.609 (95% CI: -1.134 to -0.083; OR 0.544; p = 0.029; I2 = 78.3%). Conclusions: Pooled estimates favored supplementation in direction for all three groups, although confidence intervals included the null for the first two. Heterogeneity was substantial, and the results are limited by approximations among effect measures, clinically diverse endpoints, and potentially correlated effects from individual studies.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.