Vitamin D and multiple health outcomes

Research

Vitamin D and multiple health outcomes: umbrella review of systematic reviews and meta-analyses of observational studies and randomised trials

BMJ 2014348 doi: https://doi.org/10.1136/bmj.g2035 (Published 01 April 2014)Cite this as: BMJ 2014;348:g2035

  1. 1Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH8 9AG, UK

  2. 2Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK

  3. 3Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece

  4. 4Department of Public Health and Primary Care, Trinity College Dublin, Dublin 24, Ireland

  5. 5Stanford Prevention Research Center, Departments of Medicine and Health Research and Policy, Stanford University School of Medicine, Stanford, CA 94305-5411, USA

  6. 6Department of Statistics, Stanford University School of Humanities and Sciences, Stanford
  1. Correspondence to: E Theodoratou e.theodoratou@ed.ac.uk
  • Accepted 24 February 2014

Abstract

Objective To evaluate the breadth, validity, and presence of biases of the associations of vitamin D with diverse outcomes.

Design Umbrella review of the evidence across systematic reviews and meta-analyses of observational studies of plasma 25-hydroxyvitamin D or 1,25-dihydroxyvitamin D concentrations and randomised controlled trials of vitamin D supplementation.

Data sources Medline, Embase, and screening of citations and references.

Eligibility criteria Three types of studies were eligible for the umbrella review: systematic reviews and meta-analyses that examined observational associations between circulating vitamin D concentrations and any clinical outcome; and meta-analyses of randomised controlled trials assessing supplementation with vitamin D or active compounds (both established and newer compounds of vitamin D).

Results 107 systematic literature reviews and 74 meta-analyses of observational studies of plasma vitamin D concentrations and 87 meta-analyses of randomised controlled trials of vitamin D supplementation were identified. The relation between vitamin D and 137 outcomes has been explored, covering a wide range of skeletal, malignant, cardiovascular, autoimmune, infectious, metabolic, and other diseases. Ten outcomes were examined by both meta-analyses of observational studies and meta-analyses of randomised controlled trials, but the direction of the effect and level of statistical significance was concordant only for birth weight (maternal vitamin D status or supplementation). On the basis of the available evidence, an association between vitamin D concentrations and birth weight, dental caries in children, maternal vitamin D concentrations at term, and parathyroid hormone concentrations in patients with chronic kidney disease requiring dialysis is probable, but further studies and better designed trials are needed to draw firmer conclusions. In contrast to previous reports, evidence does not support the argument that vitamin D only supplementation increases bone mineral density or reduces the risk of fractures or falls in older people.

Conclusions Despite a few hundred systematic reviews and meta-analyses, highly convincing evidence of a clear role of vitamin D does not exist for any outcome, but associations with a selection of outcomes are probable.

Introduction

The associations between vitamin D concentrations and various conditions and diseases have been assessed in a large and rapidly expanding literature. In addition to observational studies, numerous randomised trials have examined the effect of vitamin D supplementation on a range of outcomes. Historically, vitamin D had been linked to skeletal disease including calcium, phosphorus, and bone metabolism,1 2 osteoporosis,3 fractures,4 5 muscle strength,6 and falls.7 In the 2000s, growing scientific attention turned to non-skeletal chronic diseases as vitamin D deficiency was linked to cancer,8 cardiovascular diseases,9 10 metabolic disorders,11 infectious diseases,12 and autoimmune diseases,13 14 15 as well as mortality.16 If causal, these associations might be of great importance for public health, as vitamin D deficiency has been found to be highly prevalent in populations residing at high latitudes or leading an indoors oriented lifestyle.17 However, the composite literature is often confusing and has led to heated debates about the optimal concentrations of vitamin D and related guidelines for supplementation.18 19 20

To provide an overview of the breadth and validity of the claimed associations of vitamin D with diverse outcomes, we have done an umbrella review of the evidence across existing systematic reviews and meta-analyses. We aimed to do a comprehensive evaluation of systematic reviews and meta-analyses of observational studies that examined associations of vitamin D concentrations with a range of clinical outcomes, as well as meta-analyses of randomised controlled trials of vitamin D supplementation. We also compared the findings of the observational studies with those from meta-analyses of randomised controlled trials of vitamin D supplementation, whenever these could be juxtaposed. We sought to summarise the health outcomes that have been associated with vitamin D concentrations, evaluate whether evidence exists of biases in this literature, identify health outcomes without evidence of biases, and examine the consistency of inferences from the meta-analyses of observational studies and of randomised controlled trials.

Methods

Structure of umbrella review

An umbrella review systematically collects and evaluates information from multiple systematic reviews and meta-analyses on all clinical outcomes for which these have been performed.21 Here, for evidence on observational associations between vitamin D concentrations and any health outcome, we sought to collect information from systematic reviews regardless of whether they also included quantitative syntheses (meta-analyses). Given the very large heterogeneity that may be encountered in observational studies, often meta-analysis may not be done in systematic reviews of observational studies, whereas this problem occurs much less frequently in systematic reviews of randomised controlled trials, for which meta-analysis is the norm, especially when interventions are drugs or vitamins.22 Where available, we also evaluated in more depth the quantitative results of the meta-analyses of observational associations and potential hints of bias in these meta-analyses.23 24 25 For evidence on randomised controlled trials of vitamin D supplementation, we considered only formal quantitative meta-analyses. We compared results from meta-analyses of observational studies and randomised controlled trials, whenever data were available for the same outcome.

Search strategy

Two reviewers (IT, ET) searched Medline and Embase in duplicate, using the search algorithm in supplementary table A, from inception to 11 October 2013 (last update) and limited the search to humans and English language, as the overwhelming majority of review studies are published in English language, peer reviewed journals. Any discrepancies were resolved with discussion. We firstly perused the title and abstract of each of these citations and then retrieved potentially eligible articles for perusal in full text.

Eligibility criteria and appraisal of included studies

Three types of studies were eligible for the umbrella review: observational associations between circulating vitamin D concentrations and any clinical outcome examined in systematic reviews, meta-analyses, or both; and meta-analyses of randomised controlled trials assessing supplementation of vitamin D or active compounds (both established and newer compounds of vitamin D). We excluded studies that examined genetic polymorphisms related to vitamin D metabolism (for example, vitamin D receptor); systematic reviews and meta-analyses of observational studies assessing dietary or supplementary vitamin D intake or ultraviolet B exposure; studies that had vitamin D status as the outcome; studies that investigated the prevalence of vitamin D deficiency in certain disease populations; and meta-analyses of randomised controlled trials in which the treatment arm combined vitamin D with calcium or other vitamins or compounds versus placebo. When the treatment arm and control arm included the same additional compound (for example vitamin D and calcium versus calcium), we included the meta-analysis in the review. We included meta-analyses regardless of the baseline characteristics (clinical setting or age) of the examined populations. If an article presented separate meta-analyses on more than one eligible outcome or type of clinical setting, we assessed those separately.

Appraisal of individual component studies was beyond the scope of this umbrella review. This was the aim of the original systematic reviews and meta-analyses, which should include an appraisal of studies’ quality. In respect to the selected systematic reviews and meta-analyses, we used methods that captured essential features of the quality of the evidence, and these are described in detail in the data analysis section.

Data extraction

Three investigators (ET, IT, LZ) extracted data independently. From each eligible systematic review or meta-analysis, we abstracted the PubMed ID, first author, journal, year of publication, vitamin D biomarker, population, and outcome examined. From each systematic review of observational studies, we recorded a statement summarising the authors’ main interpretations of their findings. From each meta-analysis of observational studies or randomised controlled trials, we further abstracted data on the studies included in the analysis: the study specific relative risk estimates (risk ratio, odds ratio, hazard ratio, or incident risk ratio, as reported by the authors of the meta-analysis), along with the corresponding confidence intervals and the number of cases and controls for each study.

We categorised outcomes into the following categories: autoimmune diseases, cancer outcomes, cardiovascular outcomes, cognitive disorders, infectious diseases, metabolic disorders, neonatal/infant/child related outcomes, pregnancy related outcomes, skeletal outcomes (including falls), and “other” outcomes (supplementary table B).

Data analysis

We carried out descriptive analysis for systematic reviews. We categorised the conclusions of each systematic review for the association of vitamin D and the outcome of interest in one of the following four categories: definite association, suggestive (possible) association, no association, or inconclusive (insufficient) evidence. Whenever more than one systematic review had been performed on the same outcome, we examined whether the main reported conclusions were concordant. We retained the most recent systematic review for further analyses.

When we identified more than one meta-analysis of observational studies examining the association between a given vitamin D biomarker and outcome pair in the same clinical setting, we examined the conclusions for concordance regarding the direction, level of statistical significance (at P≤0.05), and magnitude (overlapping confidence interval) of the association. Then, we again retained only the most recent meta-analysis with eligible data for further statistical analysis. We estimated the summary effect size and its confidence interval by using random effects models and calculated the I2 and its confidence interval metric for heterogeneity for each eligible meta-analysis that reported the effect sizes, number of cases, and total number of participants of the component studies.26 27 We used the regression asymmetry test to test for small study effects.28 We also applied the excess significance test, which evaluates whether the observed number of studies with statistically significant results (“positive” studies) differs from the expected number of positive studies, by using a χ2 test.29 30 31 The expected number of positive studies for each meta-analysis is calculated by the sum of the statistical power estimates for each component study. We estimated the power of each study for an effect equal to the effect of the largest study (study with the smallest variance), as previously described.32 We used appropriate equations to estimate the power, on the basis of whether the largest study reported a hazard ratio or an odds ratio.33 34 If the type of the metric was a standardised mean difference, we transformed this to an odds ratio before using it in the analysis.

Eight meta-analyses presented in five papers were not included in the excess significance bias analysis either because individual study data was unavailable35 36 or because it reported the logarithm of geometric mean ratio,37 the weighted mean difference,36 or the Fisher’s z score.38 Both the small study and excess significance tests were considered significant at P<0.10, as previously proposed.23

We specifically identified outcomes for which meta-analyses of observational studies showed nominally significant associations (at P≤0.05), did not have large between study heterogeneity, were based on evidence from more than 500 cases (or more than 5000 total participants if the type of metric was continuous), and showed no evidence of small study effects or excess significance. We also noted how many would satisfy the same criteria but with P≤0.001, which has been considered to be a more appropriate threshold of statistical significance to reduce false positives.39 40 41

When we identified more than one meta-analysis of randomised controlled trials examining the relation between vitamin D supplementation and outcome pair in the same clinical setting, we examined the conclusions for concordance regarding the direction, level of statistical significance (at P≤0.05), and magnitude (overlapping confidence interval) of the association.

When meta-analyses for the same outcome existed both for association studies of vitamin D concentrations and for randomised controlled trials of vitamin D supplementation, we compared their results in terms of whether a nominally statistically significant effect had been described (P≤0.05) and whether the effect estimate was in the same direction. We did not compare the magnitude of the effect sizes between circulating vitamin D concentrations and vitamin D supplementation, as these are difficult to translate to the same vitamin D concentration/treatment contrasts. Whenever no meta-analysis of observational studies existed for an outcome examined by a meta-analysis of randomised controlled trials, we compared the main results with the results of a systematic review of observational studies, if available. Finally, we applied a set of criteria to conclude whether the evidence for a given outcome was definite, probable, suggestive, not conclusive, or unlikely (see box).

We used Stata version 12.1 for statistical analyses. P values were two tailed.

Criteria for evidence categories

  • Convincing—Evidence existed from both observational studies and randomised controlled trials (RCTs), and association/effect was of the same direction, statistically significant at P≤0.001, and free from bias

  • Probable—Evidence existed from both observational studies and RCTs, and association/effect was of the same direction and statistically significant at P≤0.001, but excess significance could not be tested; or evidence existed from RCTs and effect was statistically significant at P≤0.001 and with no contrary results from observational data (that is, systematic reviews, if any exist, are also definitive or suggestive and meta-analyses of observational studies, if any exist, are in the same direction)

  • Suggestive—Evidence from RCTs with an effect at 0.001≤ P≤0.05 and with no contrary results from observational data (same as above); or evidence from meta-analyses of observational studies showing an association at P≤0.001, with no contrary results from randomised data (that is, meta-analysis of RCTs, if present, have effects in the same direction) and, if it could be tested, no evidence of small study effects (P≥0.10), not very large heterogeneity (I2≤75%), no evidence for excess significance, based on cumulative evidence of more than 500 disease events (or more than 5000 total participants if type of metric was continuous)

  • No conclusion—Not enough evidence from observational studies or RCTs to draw conclusion

  • Substantial effect unlikely—Evidence from observational studies or RCTs enough to conclude that a substantial effect is unlikely based on the magnitude and the significance level

Results

Overall, 1256 articles searched yielded 107 systematic reviews without meta-analyses (presented in 24 papers)3642 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 and 74 meta-analyses (47 papers)11 35 36 37 3852 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101102 103 104 105 of observational studies that investigated associations with circulating vitamin D concentrations. In addition, we identified and included 87 meta-analyses (32 papers)5 7 37 52 61 70 106 107 108 109 110 111 112 113 114115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 of randomised controlled trials of vitamin D supplementation (fig 1; supplementary tables C-E). Across all three study types, results on 137 unique outcomes were reported (fig 2; supplementary table B).

Fig 2 Map of 137 vitamin D related outcomes: percentage of outcomes per outcome category for all study designs

Vitamin D concentrations and health outcomes: systematic reviews of observational studies

The median number of observational studies included in the systematic reviews was four (range 1-28) (supplementary table C). Among the 107 identified systematic reviews, 76 unique ones were presented in 21 papers (supplementary table B),36 43 44 45 46 47 48 49 52 53 54 55 56 57 58 59 60 61 62 63 64 whereas more than one systematic review existed for 24 outcomes (in 15 of which the authors reached the same qualitative conclusion; supplementary table C).

For only six (8%) of the 76 unique outcomes, the systematic reviews concluded that a definite association existed (supplementary tables B and F). These were rheumatoid arthritis activity, colorectal cancer, hypertension in children, bacterial vaginosis in pregnant women, falls in older people, and rickets in children; for all these outcomes, higher concentrations of vitamin D were associated with lower risk. Conversely, for 10 (13%) outcomes, the authors concluded that no association existed between the examined outcome and vitamin D status. For 60 of the 76 unique outcomes, the systematic reviews did not reach a firm, unequivocal conclusion: for 43 (57%) authors reported that the reviewed data were inconclusive or insufficient to draw any firm conclusions, and 17 (22%) found that an inverse association was possible or suggestive. No systematic reviews concluded that a definite or suggestive association existed for increased risk with higher concentrations of vitamin D.

Vitamin D concentrations and health outcomes: meta-analyses of observational studies

We identified 74 meta-analyses of observational studies (supplementary table D). Among these, 48 unique meta-analyses were presented in 28 papers (fig 1; supplementary table G).35 36 37 38 66 68 71 74 76 78 79 82 83 84 8688 89 91 95 96 98 99 100 101 102 103 104 105 Forty three meta-analyses examined the link between vitamin D and outcome by using 25-hydroxyvitamin D and five by using 1,25-dihydroxyvitamin D. All meta-analyses reported estimates adjusted for a wide variety of other covariates. Meta-analyses examined a very wide range of outcomes including cancers (n=20), cardiovascular diseases (n=8), cognitive disorders (n=4), metabolic disorders (n=4), neonatal/infant/child related outcomes (n=4), skeletal diseases (n=3), pregnancy related outcomes (n=2), infectious disease (n=1), or other outcomes (n=2) (supplementary table G). The median number of studies included was seven (range 2-37), the median number of participants was 5905 (39-82 982), and the median number of events was 1289 (18-15 447). Overall, 30 (63%) of the 48 meta-analyses of observational studies reported a nominally statistically significant summary result (tables 1 and 2). Figure 3 shows a forest plot with the summary effects of all the non-overlapping meta-analyses of observational studies (for binary outcomes).

Table 1

 Characteristics and main findings of meta-analyses of observational studies reporting unique cancer and cardiovascular outcomes (direction of comparison is high versus low)

Table 2

 Characteristics and main findings of meta-analyses of observational studies reporting unique cognitive, infectious, metabolic, neonatal/infant/child related, pregnancy related, skeletal, and other outcomes (direction of comparison is high versus low)

Fig 3 Forest plot of all meta-analyses of observational studies stratified by measured biomarker with relative risk as type of metric

We found more than one published meta-analysis for 11 outcomes: Alzheimer’s disease (n=2 meta-analyses), breast cancer (n=6), colorectal adenoma (n=3), colorectal cancer (n=7), cardiovascular diseases (n=3), gestational diabetes (n=2), hypertension (n=3), prostate cancer (n=4), stroke (n=2), type 2 diabetes (n=3), and prevalence of type 2 diabetes (n=2). For all the outcomes, agreement existed between the meta-analyses on the direction, magnitude, and statistical significance of the association (supplementary table H).