Vitamin B12 levels in children and adolescents on plant-based diets: a systematic review and meta-analysis

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Abstract

Context

The popularity of plant-based diets, characterized by a partial or complete exclusion of animal products, has increased significantly over the last 10 years. The exclusion of animal products removes the most common sources of vitamin B12, which can lead to vitamin B12 deficiency and result in irreversible damage, such as growth stunting.

Objective

This aim of this systematic review and meta-analysis was to qualitatively evaluate all studies on this subject and to quantify the potential difference in vitamin B12 levels in healthy children and adolescents aged 5 to 18 years.

Data Sources

PubMed and Embase databases were searched for relevant studies investigating vitamin B12 levels in healthy children and adolescents aged 5 to 18 years on plant-based diets.

Data Extraction

Studies were assessed qualitatively with the AXIS tool and quantitatively with Stata 16.0 software.

Data Analysis

Overall, children and adolescents on plant-based diets had a significantly lower vitamin B12 level than omnivorous children and adolescents (−97 pmol/L; 95%CI, −187 to −7; I2 = 98.5%), a difference that remained statistically significant after adjusting for methodological confounders. After subgroup analyses, this effect was not statistically significant for children and adolescents on vegetarian diets but remained significant in children and adolescents on vegan or macrobiotic diets. Moreover, total vitamin B12 intake nullified the mean difference in vitamin B12 levels.

Conclusion

Despite high heterogeneity across studies, these results indicate that children and adolescents on plant-based diets, especially those on vegan and macrobiotic diets, may be at risk of developing vitamin B12 deficiency.

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The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

Matthew J L Page, Joanne E McKenzie, Patrick Bossuyt … (2025)

The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.

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Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range

Xiang Wan, Wenqian Wang, Jiming Liu … (2014)

Background In systematic reviews and meta-analysis, researchers often pool the results of the sample mean and standard deviation from a set of similar clinical trials. A number of the trials, however, reported the study using the median, the minimum and maximum values, and/or the first and third quartiles. Hence, in order to combine results, one may have to estimate the sample mean and standard deviation for such trials. Methods In this paper, we propose to improve the existing literature in several directions. First, we show that the sample standard deviation estimation in Hozo et al.’s method (BMC Med Res Methodol 5:13, 2005) has some serious limitations and is always less satisfactory in practice. Inspired by this, we propose a new estimation method by incorporating the sample size. Second, we systematically study the sample mean and standard deviation estimation problem under several other interesting settings where the interquartile range is also available for the trials. Results We demonstrate the performance of the proposed methods through simulation studies for the three frequently encountered scenarios, respectively. For the first two scenarios, our method greatly improves existing methods and provides a nearly unbiased estimate of the true sample standard deviation for normal data and a slightly biased estimate for skewed data. For the third scenario, our method still performs very well for both normal data and skewed data. Furthermore, we compare the estimators of the sample mean and standard deviation under all three scenarios and present some suggestions on which scenario is preferred in real-world applications. Conclusions In this paper, we discuss different approximation methods in the estimation of the sample mean and standard deviation and propose some new estimation methods to improve the existing literature. We conclude our work with a summary table (an Excel spread sheet including all formulas) that serves as a comprehensive guidance for performing meta-analysis in different situations. Electronic supplementary material The online version of this article (doi:10.1186/1471-2288-14-135) contains supplementary material, which is available to authorized users.