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Maternal vitamin B12 in pregnancy and risk of preterm birth and low birth weight: A systematic review and individual participant data meta-analysis
Associated Data
Abstract
Vitamin B12 (B12)-deficiency in pregnancy is prevalent, and has been associated with lower birth weight (birth weight <2,500 g) and preterm birth (length of gestation <37 weeks). Nevertheless, current evidence is contradictory. We performed a systematic review and an individual participant data meta-analysis to evaluate the associations between maternal serum or plasma B12 concentration in pregnancy and offspring birth weight and length of gestation. Twenty-two eligible studies were identified (11,993 observations). Eighteen studies were included in the meta-analysis (11,216 observations). No linear association was observed between maternal B12 levels in pregnancy and birth weight, but B12-deficiency (<148 pmol/L) was associated with an increased risk of newborn low birth weight (adjusted risk ratio (RR) 1.15 (95% confidence interval (CI) 1.01, 1.31)). There was a linear association between maternal levels of B12 and preterm birth (adjusted RR for preterm birth was 0.89 (95% CI 0.82, 0.97) per one standard deviation increase in B12). Accordingly, B12-deficiency was associated with increased risk of preterm birth (adjusted RR 1.21 (95% CI 0.99, 1.49). Lower maternal B12 in pregnancy increased the risk of preterm birth. This finding supports the conduct of randomized controlled trials of vitamin B12 supplementation in pregnancy.
Globally, preterm birth and low birth weight (LBW) cause over a third of the 2.9 million neonatal deaths each year, and prevention of these events is important to reduce under-five year mortality (1,2). The etiology of preterm birth, however, is complex, and few interventions have been successful in preventing it (3).
Vitamin B12 (B12) is a vitamin with metabolic roles closely related to folate and homocysteine, and is found in animal-derived foods only (4). It is important for the synthesis (5) and methylation (6) of DNA, and plays a role in the energy production of the cell (7). It has been hypothesized that B12 may affect placentation and fetal growth (8). B12-deficiency may affect over three quarters of some pregnant populations (9).
Few supplementation-studies of B12 in pregnancy have been undertaken to assess possible effects on birth weight and length of gestation. However, a recent meta-analysis concluded that multiple-micronutrient supplementation may reduce the risk of LBW and the number of stillbirths, but not preterm birth or neonatal mortality (10). Thus, a more targeted micronutrient supplementation practice may be warranted.
The aim of this systematic review and individual participant data (IPD) meta-analysis was to study whether maternal serum or plasma B12 levels in pregnancy may be associated with birth weight and length of gestation. Individual studies have reported conflicting results. A recent systematic review that included traditional meta-analyses was unable to conclude whether maternal B12 levels were associated with offspring birth weight (9). However, high heterogeneity in the meta-analyses, dependence among some of the included studies, and reporting bias may have biased their results. We collected IPD and single-study estimates from eligible studies in order to pool effects across all studies in a meta-analysis. This approach allowed for exploration of confounding factors and evaluation of preplanned subgroup effects.
Methods
The systematic review and meta-analysis was reported according to the PRISMA and MOOSE guidelines (11,12), and the protocol was registered at PROSPERO (13).
Study inclusion criteria
We included studies that assessed the association between maternal B12 in serum or plasma during pregnancy and birth weight or gestational age at delivery.
Only studies of longitudinal cohort design were eligible for this review. To be eligible, information on birth weight had to be registered at birth and could not be retrospectively reported and length of gestation, in completed days or weeks, had to be estimated by either ultrasound or last menstrual period, or a combination of the two. Studies where B12 was measured after conception and prior to delivery were eligible. If a study was designed to evaluate women or offspring with a specific condition (e.g. preeclampsia or congenital malformations), and there was a marked overrepresentation of participants with such a condition, that study was excluded. Studies with fewer than 50 participants were not considered. Given the need to collaborate with authors of the original studies, we included only those studies published in 1998 or later.
Search methods
The electronic literature search was constructed by the first author (TR) and a librarian trained in medical database searches, and conducted in PubMed, Scopus, Web of Knowledge, EBSCO-host (CINAHL) and OvidSP (MEDLINE, EMBASE and GLOBAL HEALTH); last accessed August 2015. No language restriction was applied. The reference lists of all studies read in full-text were hand searched to find additional eligible studies. Web Appendix 1 provides complete information on the electronic searches.
Data collection
Electronic literature searches were carried out by the first author (TR). Duplicates were removed and eligibility of all references evaluated by screening of the titles and abstracts by the first author (TR). All potentially eligible studies were read in full-text and assessed for inclusion independently by two authors (TR and KRR). A handsearch of reference lists was done independently by two authors (TR and KRR or MJT). When multiple reports from the same study were found, we used the most complete report.
Risk of bias was independently assessed by two authors (TR and MJT) based on a modified version of the Newcastle-Ottawa Scale (range 0-7) (14). Disagreements were resolved by consulting a third reviewer (KRR). We defined high risk of bias as a score of four or less, and moderate to low risk was defined as scores five through seven.
Authors from all eligible studies were contacted to obtain IPD, each research group being approached at least three times. IPD was received without personal identification. For studies where IPD could not be shared, authors were asked to provide results from pre-specified reanalyzes of their data. When neither IPD nor reanalyzes could be retrieved, relevant estimates were extracted from the publications.
Variables
The main exposure of interest was vitamin B12 levels in maternal serum or plasma. We calculated trimester-specific standard deviation (SD) scores based on studies providing IPD and reanalyzed aggregate data. Analyses were performed for B12-deficiency pre-defined as <148 pmol/L (15), and B12 tertiles constructed on the basis of included individual data; <148 pmol/L (tertile 1), 148-216 pmol/L (tertile 2), and >216 pmol/L (tertile 3).
The three pre-defined main outcomes were: birth weight as a continuous measure in grams, LBW (birth weight <2,500 g) and small-for-gestational-age (SGA; birth weight SD score <10th centile) (1). Birth weight SD score was calculated using gestational age at delivery and sex-specific reference standards published by the INTERGROWTH 21st Project (16). We assumed birth weight SD score to serve as a proxy of fetal growth, and defined SGA as a proxy of restricted fetal growth. Outcomes related to length of gestation were gestational age at delivery (days) and preterm birth (gestational age at delivery <37 weeks).
Three main confounders were identified based on a priori assumptions of confounding factors, availability of data and exploration of effect of covariates on outcome and exposure: maternal age (continuous), pre-pregnancy or pregnancy body mass index (BMI, continuous) and parity (nulliparous versus primiparous or multiparous). Maternal weight was used when information on BMI was unavailable. Also, we considered smoking habits (smoking versus not smoking during pregnancy) and highest completed education (completed high school, equal to 13 years of education, versus not completed high school).
Statistical analysis
We applied a two-step IPD meta-analysis with random effects to pool the results across studies, including aggregate data from individual studies when IPD was not available. All presented results are adjusted for maternal age, BMI/weight and parity (the “main model”), unless otherwise specified. Precision was assessed by 95% confidence intervals (CI).
Mean difference of the continuous outcomes birth weight (g), gestational age at delivery (days) and birth weight SD score (SD) were analyzed by linear regression. To estimate risk ratios (RR), Poisson regression with robust error variance (17) was used to analyze the dichotomous outcomes LBW, SGA, and preterm birth.
We conducted a meta-analysis that evaluated how B12 was associated with maternal weight. Publication bias was explored using funnel plots. Heterogeneity between the studies was explored by computing the I2 statistic, and was considered to be present when I2 was greater than 30%. All statistical analyses were carried out using Stata SE version 13.1 (Stata Corporation, College Station, TX, USA). The statistical analyses, including sensitivity analyses, are described in more detail in Web Appendix 2.
Results
Availability of data
The electronic literature search and hand search of reference lists identified 606 unique references (Figure 1). Twenty-two studies met eligibility criteria (11,993 observations) of which 18 studies were included in the meta-analyses (11,216 observations), representing 94% of all eligible observations (18–35). Four eligible studies (777 observations) were not included as they neither reported on the association between maternal B12 and birth weight or length of gestation, nor provided the necessary IPD or results from requested reanalyzes (36–39). Fourteen of the included studies reported estimates for the association between B12 in pregnancy and birth weight or length of gestation, and were qualitatively appraised in the systematic review section (10,563 observations) (18,19,21,23–25,27,29–35).
B12, vitamin B12; IPD, individual participant data.
Four studies were not included because IPD or reanalyses were not provided, and results could not be abstracted from the published reports.
For the meta-analyses, ten studies provided IPD (8,928 observations) (18,19,21–23,26–29,32), two studies provided results from reanalyzes (973 observations) (20,35), and relevant information and estimates were extracted from the published reports of six studies (1,315 observations) where IPD or reanalyzes of original data were not provided (24,25,30,31,33,34).
Details of eligible studies
Studies included in the meta-analyses are described in Table 1; details of the eligible studies not included are presented in Web Table 1 (36–39). Of the included studies, one was conducted in North America (34), nine in Europe (18,19,22,25–28,31,32), one in Africa (30), one in Oceania (24), and six in Asia (20,21,23,29,33,35). The number of pregnancies studied ranged from 84 to 5,641. B12 was measured during the first trimester in seven studies (19,22,23,28,31–33), during the second trimester in 15 studies (18–24,26–29,31–33,35), and during the third trimester in 12 studies (18,20,21,23,25,27,29,30,32–35). Mean (SD) B12 concentrations in the first, second and third trimester were 219.8 (128.2), 187.8 (91.3) and 188.7 (82.5) pmol/L, respectively. Preterm deliveries were excluded from four studies (25,26,31,33).
Table 1
Characteristics of Studies Included in the Meta-Analysis
Week of B12 measurement | Included in specific meta-analysesa | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Study | Data | n | Country | Study years | B12 analysis method | Range | Median | Birth weight | LBW | SGA | Birth weight SD score | Length of gestation | Preterm birth |
Baker, 2009 (18) | IPD | 290 | The United Kingdom | 2004-2007 | RIA | 27-43 | 30 | x | x | x | x | x | x |
Bergen, 2012 (19) | IPD | 5,641 | The Netherlands | 2002-2006 | ECL | 5-18 | 13 | x | x | x | x | x | x |
Bhate, 2012 (20) | Reanalysed data | 214 | India | 2004-2006 | Micro-biological | 24-30 | 28 | x | x | x | x | ||
Chen, 2015 (21) | IPD | 988 | Singapore | 2009-2010 | ECL | 26-29 | 27 | x | x | x | x | x | x |
Dayaldasani, 2014 (22) | IPD | 187 | Spain | 2011 | ECL | 3-23 | 10 | xb | xb | xb | xb | xb | xb |
Dwarkanath, 2013 (23) | IPD | 344 | India | 2001-2003 | ECL | T1: 5-19 T2: 20-29 T3: 30-39 | T1: 12 T2: 24 T3: 34 | x | x | x | x | x | x |
Furness, 2013 (24) | Data from publication | 84 | Australia | NA | ECL | 18-20 | NA | xc | |||||
Halicioglu, 2012 (25) | Data from publication | 208 | Turkey | 2008 | ECL | >37 | NA | xd | |||||
Hay, 2010 (26) | IPD | 149 | Norway | 1997 | Micro-biological | 17-19 | NA | x | |||||
Hogeveen, 2010 (27) | IPD | 363 | The Netherlands | 2002-2004 | Micro-biological | 27-38 | 31 | xe | xe | xe | xe | xe | xe |
Kaymaz, 2011 (28) | IPD | 103 | Turkey | 2007 | ECL | 11-14 | 13 | x | x | x | x | ||
Krishnaveni, 2014 (29) | IPD | 654 | India | 1997-1998 | Micro-biological | 22-35 | 26 | x | x | x | x | x | x |
Mamabolo, 2006 (30) | Data from publication | 219 | South Africa | 1999-2000 | RIA | 28-36 | NA | xc | |||||
Relton, 2005 (31) | Data from publication | 500 | The United Kingdom | 2000-2002 | RIA | NA | 11.5 (5.8)f | xe | |||||
Sukumar, 2011 (32) | IPD | 209 | The United Kingdom | 2005-2010 | RIA (n=182), ECL (n=27) | 0-37 | 24 | x | x | x | x | x | x |
Takimoto, 2007 (33) | Data from publication | 88 | Japan | 2001-2003 | ECL | T1: 7-14 T3: 34-36 | T1: NA T3: NA | xg | |||||
Wu, 2013 (34) | Data from publication | 216 | Canada | NA | RIA | NA | 36 | xd | |||||
Yajnik, 2008 (35) | Reanalysed data | 759 | India | 1994-1996 | Micro-biological | NA | T2: 18 (2)f | x | x | x | x |
Studies are referred to according to their citation number in the text. ECL, electroluminescence; IPD, individual participant data; n, number of pregnancies; NA, not available; RIA, radioimmunoassay; SD, standard deviation; SGA, small-for-gestational-age; T1, 1st trimester; T2, 2nd trimester; T3, 3rd trimester.
Key maternal and newborn characteristics of the included studies are presented in Table 2. B12-deficiency was identified in 0% to 69% of pregnancies (median 33%). The incidence of LBW ranged from 0% to 33% (median 6%), preterm births from 4% to 14% (median 8%), and SGA from 5% to 32% (median 11%). Higher maternal weight was associated with lower maternal B12; one SD higher maternal BMI or weight was associated with an 11 pmol/L decrease in B12 (95% CI -15, -7).
Table 2
Maternal and Newborn Characteristics of Studies Included in the Meta-Analysis
Study | Maternal age (years), mean (SD) | Maternal BMIo (kg/m2), mean (SD) | Para 0 | Vitamin B12 (pmol/L), mean (SD) | B12-deficienta | Birth weight (g), mean (SD) | LBWb | SGAc | Length of gestation (weeks), mean (SD) | Preterm birthd | |||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
n | % | n | % | n | % | n | % | n | % | ||||||
Baker, 2009 (18) | 18 (1) | 65 (14)e | 277 | 96 | 192 (84) | 93 | 32 | 3,232 (534) | 26 | 9 | 33 | 12 | 39.7 (1.8) | 22 | 8 |
Bergen, 2012 (19) | 30 (5) | 25 (5) | 3,208 | 57 | 188 (93) | 2,098 | 37 | 3,418 (563) | 280 | 5 | 412 | 7 | 39.9 (1.8) | 268 | 5 |
Bhate, 2012 (20) | 23 (3) | 20 (3) | 165 | 71 | 145 (84) | 148 | 69 | 2,707 (411) | 49 | 25 | NA | NA | 38.6 (2.6) | 18 | 8 |
Chen, 2015 (21) | 31 (5) | 66 (12)e | 420 | 43 | 220 (79) | 161 | 16 | 3,101 (449) | 76 | 8 | 86 | 9 | 38.6 (1.4) | 85 | 9 |
Dayaldasani, 2014 (22) | 30 (6) | 26 (5) | 96 | 51 | 387 (123) | 0 | 0 | 3,267 (526) | 11 | 6 | 12 | 7 | 38.8 (1.9) | 14 | 8 |
Dwarkanath, 2013 (23) | 24 (4) | 53 (10)e | 203 | 59 | 205 (115)f | 100 | 29f | 2,771 (498) | 95 | 28 | 102 | 30 | 38.3 (1.7) | 47 | 14 |
Furness, 2013g (24) | 33 (7) | 27 (5) | NA | NA | 234 (129) | NA | NA | 3,390 (789) | NA | NA | 21 | 25h | 38.8 (2.9) | NA | NA |
Halicioglu, 2012g (25) | 28 (5) | NA | NA | NA | 120i | 99 | 48j | 3,357 (466) | NA | NA | NA | NA | NA | NA | NA |
Hay, 2010 (26) | 30 (4) | 65 (10)e | 67 | 45 | 294 (87) | 2 | 1 | 3,727 (476) | 0 | 0 | NA | NA | NA | NA | NA |
Hogeveen, 2010 (27) | 33 (4) | NA | 109 | 30 | 186 (69) | 120 | 34 | 3,436 (545) | 18 | 5 | 19 | 5 | 39.5 (1.6) | 21 | 6 |
Kaymaz, 2011 (28) | 27 (3) | 24 (4) | 45 | 44 | 152 (59) | 54 | 52 | 3,241 (553) | 5 | 5 | NA | NA | 38.4 (1.9) | 9 | 9 |
Krishnaveni, 2013 (29) | 24 (4) | 24 (4) | 331 | 51 | 187 (100) | 264 | 40 | 2,857 (475) | 126 | 19 | 202 | 32 | 39.0 (1.8) | 63 | 10 |
Mamabolo, 2006g (30) | 25 (7) | 27 (4) | NA | NA | 175 (77) | 36 | 16k | 3,120 (550) | NA | NA | 66 | 30l | NA | NA | NA |
Relton, 2005g (31) | 28 (6)m | NA | NA | 43m | 239 (97) | NA | NA | 3,430 (470)m | NA | NA | NA | NA | NA | NA | NA |
Sukumar, 2011 (32) | 31 (6) | 27 (6) | 68 | 33 | 168 (126) | 114 | 55 | 3,381 (558) | 10 | 5 | 16 | 8 | 39.3 (1.7) | 9 | 4 |
Takimoto, 2007g (33) | 29 (5) | 21 (3) | NA | NA | 405 (146)f | 13 | 16n | 3,120 (411) | 5 | 5 | NA | NA | 39.6 (1.0) | NA | NA |
Wu, 2013g (34) | 33 (4) | NA | NA | NA | 224 (96) | 51 | 24 | 3,486 (452) | NA | NA | NA | NA | NA | NA | NA |
Yajnik, 2008 (35) | 21 (4) | 18 (2) | 252 | 31 | 151 (78) | 447 | 59 | 2,612 (392) | 230 | 33 | NA | NA | 38.8 (2.1) | 87 | 11 |
Studies are referred to according to their citation number in the text. BMI, body mass index; LBW, low birth weight; NA, not available; SD, standard deviaton; SGA, small-for-gestational-age.
Systematic review
Birth weight/SGA
The association between B12 and birth weight or risk of SGA birth was reported in 14 of 22 eligible studies. Three studies reported a clear association: one study reported that birth weight was higher among B12-deficient women than among non-deficient women (34); another study reported that only among women with gestational diabetes mellitus, lower B12 was associated with higher birth weight (32). Conversely, a third study reported that lower values of B12 significantly increased the risk of SGA births (23). In the remaining 11 studies, there was weak evidence of an inverse association in three studies (25,27,33), and no association in eight studies (18,19,21,24,29–31,35).
Length of gestation
Only two published reports reported on the association between B12 and length of gestation or preterm birth. The first study observed that higher B12 was associated with a longer length of gestation and a reduced risk of preterm birth, but the small sample size yielded low precision of the estimates (21). The second study did not find evidence of an association between B12 and length of gestation (19).
Evaluation of the risk of bias showed that the scores ranged between three and seven, and that two studies were classified with high risk of bias (see Web Table 2).
Meta-analysis of maternal B12 in relation to birth weight and LBW
In the meta-analysis, we found no evidence of a linear association between B12 and birth weight (Figure 2): The adjusted estimate was 5.1 g increase in birth weight per SD increase in B12 (95% CI -10.9, 21.0; I2=30%).
Meta-analysis of studies of the association between vitamin B12 and birth weight after adjustment for maternal age, parity and body mass index or weight. Effect estimates are expressed as change in birth weight per one standard deviation increase of vitamin B12 (i.e. mean difference). CI, confidence interval; No, number pregnancies.
Subgroup and sensitivity analyses are presented in Web Table 3. Stratification by country income showed that there was an association between B12 and birth weight in low- and middle-income countries, but not in high-income countries. Heterogeneity among the studies was explained largely by country income level and maternal BMI or weight. Excluding a study that used late-pregnancy BMI (29), instead of pre-pregnancy or early pregnancy BMI/weight in the other studies, reduced the heterogeneity from I2=30% to I2=13% (results not presented). One study reported an association between B12 and birth weight that greatly deviated from the other studies (33). Excluding this study did not notably change the effect estimate, but resulted in a modest reduction in heterogeneity (from I2=30% to I2=21%; results not presented). Sensitivity analyses excluding each of the included studies one by one, and excluding studies only evaluating newborns born at term, did not meaningfully alter the association between B12 and birth weight (results not presented).
Results for categories of B12 supported our main results. Neither B12-deficiency nor B12 tertiles were associated with birth weight (see Web Table 4).
B12-deficiency was associated with a 15% (95% CI 1%, 31%; I2=5%) increased risk of LBW (Figure 3A).
Meta-analysis of studies of the association between vitamin B12-deficiency and the risk of low birth weight after adjustment for maternal age, parity and body mass index or weight. Effect estimate expressed as risk ratio of the outcome comparing B12 deficient to non-deficient. CI, confidence interval; No, number pregnancies.
The funnel plot of B12 and birth weight indicated low risk of publication bias (see Web Figure 1).
Since birth weight may be regarded as a summary measure of fetal growth and gestational age, we further performed analyses to assess a possible influence of B12 on these factors.
Meta-analysis of maternal B12 in relation to length of gestation and preterm birth
The analyses did not support a linear association between maternal B12 levels with length of gestation in days (0.1 days (95% CI -0.2, 0.3; I2=0%) per SD increase of B12). However, increasing levels of B12 were associated with a reduced risk of preterm birth (RR 0.89 (95% CI 0.82, 0.97; I2=0%) per SD increase in B12; Web Figure 2). Accordingly, B12-deficiency in pregnancy was associated with a 21% increased risk of preterm birth (95% CI -1%, 49%; I2=20%); Figure 3B).
Meta-analysis of studies of the association between vitamin B12-deficiency and the risk of preterm birth after adjustment for maternal age, parity and body mass index or weight. Effect estimate expressed as risk ratio of the outcome comparing B12 deficient to non-deficient. CI, confidence interval; No, number pregnancies.
The association between B12 and preterm birth was similar within all subgroup and sensitivity analyses, although there was a loss of precision in these subgroup analyses due to smaller sample sizes (see Web Table 5).
Meta-analysis of maternal B12 in relation to birth weight SD score and SGA
B12 was not associated with birth weight SD scores in the main analysis (see Web Figure 3). However, B12 was associated with birth weight SD score in low- and middle-income countries (0.08 SD per 1 SD increase in B12 (95% CI 0.03, 0.14; I2=0%)), but not in high-income countries (-0.02 SD (95% CI -0.05, 0.02; I2=23%)).
Women with B12-deficiency were not at higher risk of SGA births than non-deficient women (Figure 3C), and B12 levels were similar in SGA and non-SGA pregnancies (see Web Table 6).
Meta-analysis of studies of the association between vitamin B12-deficiency and the risk of small-for-gestational-age birth after adjustment for maternal age, parity and body mass index or weight. Effect estimate expressed as risk ratio of the outcome comparing B12 deficient to non-deficient. CI, confidence interval; No, number pregnancies.
Discussion
The results from this systematic review and meta-analysis do not support any linear association between vitamin B12 levels in pregnancy and offspring birth weight. However, our findings provide evidence that lower maternal B12 levels are associated with increased risk of preterm birth, and that the risk of preterm birth was particularly high in the presence of B12-deficiency during pregnancy.
Strengths and limitations
A strength of this study is the use of IPD and reanalyzed data. Due to substantial heterogeneity in the published analyses, a traditional meta-analysis could not answer our research questions. Incomplete or selective reporting may reduce the replicability of studies and distort the literature (40). This is illustrated by comparing the findings of this review with those of a recently published systematic review by Sukumar et al. with traditional meta-analysis on the association between B12 and birth weight (9). That study reported an odds ratio of 1.70 (95% CI 1.16, 2.50; I2=84%) of the association between “low B12” and “adverse birth weight”. A more moderate association was found in the present study in a comparable analysis of B12-deficiency in relation to LBW (RR 1.15 (95% CI 1.01, 1.31); I2=5%). One reason for the discrepant results may be that Sukumar et al. depended solely on data presented in the published reports and were unable to include results reported as being “insignificant”; for instance, from the largest individual study in the present review (19). The comparable meta-analysis in the present review included roughly ten times as many pregnancies as the meta-analysis in Sukumar’s review. Additionally, of eight individual results included in Sukumar’s meta-analysis, five evaluated most of the same women from a single original study, exaggerating the influence of a single, outlying study (8,23). By collecting IPD and requesting reanalyzes from contributing studies, we were able to standardize the analyses across most of the included studies, thereby reducing heterogeneity and facilitating interpretation of results. Compared with the review by Sukumar et al. that presented meta-analyses with high levels of heterogeneity (I2-scores from 74% to 98% in the primary analyses), the present study had I2-scores between 0% and 30% in the primary analyses. Additionally, the present study enabled conduction of subgroup and sensitivity analyses, along with more complete adjustment for important confounders (e.g. maternal weight).
We included 94% of all eligible participants, permitting an unbiased summary of the published literature. Given the relative large number of included subjects, we had increased power to evaluate findings reported with low precision in individual studies. We tested the stability of our findings with a broad range of sensitivity analyses.
Another strength was that our analyses were not post-hoc, but followed a detailed protocol. We performed a thorough literature search without language restrictions, and systematically reviewed all eligible studies.
There are several limitations. Unpublished studies were not considered for this review, which could potentially skew estimates. However, a funnel plot did not suggest publication bias. We were unable to include four eligible studies (777 observations, 6% of all observations). Given the small number of observations, it is unlikely that inclusion of these remaining studies would have importantly influenced our main results.
Our approximations of fetal growth and restricted fetal growth by use of gestational age and sex specific birth weight charts is suboptimal, as these outcomes are ideally estimated using serial ultrasound measurements during pregnancy (41). Furthermore, we did not have sufficient data at hand to evaluate the possible implications of low levels of B12 during different periods in pregnancy in the same woman. Sensitivity analyses stratified by trimester of B12 measurement across studies, however, did not reveal important variation in the association between B12 and the outcomes of interest.
Importantly, B12-deficiency may be a proxy for inadequate nutritional status, and it is possible that some of our findings are related to nutritional status, not specifically to B12. A predominantly plant-based diet is low in B12, but also other nutrients, such as vitamin D and zinc, which to some degree may be associated with preterm birth (42–44). We did not have information on dietary intake or blood levels of these nutrients. Nutritional status could explain the present finding of an association between B12 and birth weight in low- and middle-income countries but not high-income countries. However, lower vitamin B12 levels were associated with higher risk of preterm birth irrespective of country income. It seems less likely that nutritional status can fully explain this finding.
Mixing of effects is inherent in observational studies, and residual confounding cannot be ruled out. We emphasize that our study report associations, and that causal effects must be explored through trials (see below). Reassuringly, we found little discrepancy in the pooled results of adjusted main models as compared to extended adjusted models (i.e. additionally adjusting for maternal education and smoking habits).
Possible explanation of findings
Low birth weight is a result of preterm birth, of being born small at term, or a combination of the two (45). While we found an increased risk of preterm birth and LBW among B12-deficient women, there was little evidence that maternal B12 levels influenced offspring birth weight SD score or SGA status. It seems more likely that the observed higher risk for LBW in B12-deficient women can be explained by preterm birth rather than by reduced fetal growth.
Higher B12 was associated with higher birth weight in low- and middle-income countries, but not in high-income countries. Four of the five studies included in the low- and middle-income group were performed in an Indian population. Therefore, generalization of these results to low- or middle-income countries outside India should be treated with caution. Indian women generally have lower dietary intake of B12, due to a mainly vegetarian diet, making them susceptible to B12-deficiency (46). Additionally, Indian newborns are among the smallest in the world (45). Our findings suggest that pregnancies already at greatest risk of giving birth to small newborns were the ones most vulnerable to low levels of B12.
The association between B12 and the risk of preterm birth was consistent across studies in both high-income and low- and middle-income countries, and generalization to countries not studied may be feasible.
In line with our findings, maternal obesity has been associated with B12-deficiency in several populations (47,48). It is hypothesized that this association is due to altered fat distribution and metabolism in the overweight compared with normal weight (47). Maternal weight is positively correlated with newborn weight (49), and failure to adjust for maternal weight may underestimate a positive association between B12 and birth weight.
Potential mechanism of action
Preterm birth may be categorized into spontaneous and medically indicated, with varying etiologies (50). Unfortunately, information on spontaneous versus medically indicated preterm births were not available to us. Medically indicated preterm birth are most commonly caused by severe preeclampsia or severely restricted fetal growth (51). Our findings do not support maternal level of B12 to be associated with fetal growth. Maternal B12 may, however, be associated with risk of preeclampsia, potentially through homocysteine, but reports are discrepant (52–54). The rate of medically indicated preterm births is higher in high-income countries than in low- and middle-income countries (55). In analysis stratified by country income, we found similar associations between B12 and risk of preterm birth in low-, middle- and high-income countries. Still, this finding does not link B12 to specific etiologies of preterm birth, which is a topic that deserves further studies.
It is possible that supplementation of B12 or folic acid, with a subsequent reduction of homocysteine, increases birth weight and length of gestation. However, a Cochrane review concluded that supplementation of folic acid during pregnancy did not reduce risk of either preterm birth or LBW (60). Two small (256 pregnancies and 68 pregnancies) randomized controlled trials of B12 supplementation during pregnancy reported on birth weight and length of gestation (61,62). Both observed higher B12 plasma levels in the supplemented group compared with the control group, but no reduction in homocysteine levels. No differences were observed in birth weight, length of gestation, or frequency of LBW births or preterm births in the supplemented group compared with the control group in either study (C Duggan, Harvard University, personal communication, 2015) (61,62). However, the studies were not powered to detect small but meaningful differences in preterm birth.
Context
There are 15 million preterm births and 20 million low birth weight births globally each year (1). The greatest burden of LBW is found in South Asia, while preterm birth is highest in Africa (1). Preterm birth is the leading cause of neonatal deaths (1). In the era of The Millennium Development Goals (1990-2015), post-neonatal under-five mortality rate was reduced by 58% (2). Reduction in neonatal mortality was less pronounced (47%) (2). Prevention of preterm birth is thus a key strategy to reduce neonatal deaths and reach the new target of under-five year mortality of 25 per 1,000 live births by 2030, down from 43 per 1,000 in 2015 (2).
Our systematic review was not designed to study the prevalence of B12-deficiency during pregnancy. However, this condition was common in the studies in our review, and comparable to a systematic review of B12-deficiency during pregnancy (9). A large group of women are thus affected by a potential preventable risk of preterm birth.
Conclusion and implications for clinical practice and future research
Vitamin B12-deficiency during pregnancy is common. Results of this systematic review with IPD meta-analyses provides robust evidence that lower B12 levels during pregnancy are associated with increased risk of preterm birth, particularly in B12-deficient women. Our findings support conducting randomized controlled trials to evaluate whether maternal B12 supplementation in pregnancy reduces the risk of preterm birth.
Acknowledgement
We would like to acknowledge the following persons for their help in order to provide the necessary data for the present study: Professor Caroline H D Fall, MRC Lifecourse Epidemiology Unit, University of Southampton, UK; Dr Simon Wheeler, nutritionist at the MRC Epidemiology Unit, University of Cambridge; Professor Anura V Kurpad, Professor of Physiology, St. John’s Medical College, India; and Dr Nithya Sukumar, research fellow at Warwick Medical School, University of Warwick, UK. Also thanks to Professor Christopher Duggan, Professor in the Department of Nutrition, Harvard University, USA, for providing necessary unpublished results from a previous trial. Lastly, we would like to acknowledge Janis Glover, Academic Librarian at the Medical Library, Yale University, USA, who helped develop the search strategy.
Funding source: This work was supported by the Norwegian University of Science and Technology as part of the Ph.D. in Medicine-programme. The funding source was not involved in the design of the study, statistical analysis and results interpretation. The researchers were independent from the funders.
Abbreviations
B12 | vitamin B12 |
BMI | body mass index |
CI | confidence interval |
IPD | individual participant data |
LBW | low birth weight |
RR | risk ratio |
SD | standard deviation |
SGA | small-for-gestational-age |
Footnotes
Conflict of interest statement:
Keith M Godfrey and Yap-Seng Chong have received reimbursement for speaking at conferences sponsored by companies selling nutritional products. Keith M Godfrey and Yap-Seng Chong are part of an academic consortium that has received funding from Abbott Nutrition, Nestec and Danone. Oscar H Franco has received funding from Nestlé for research purposes. The other authors declare no support from any organisation for the submitted work, no financial relationships with any organisations that might have an interest in the submitted work in the previous three years, no other relationships or activities that could appear to have influences the submitted work.
Data sharing statement
All participating studies agreed on the use of data material for the purpose of this systematic review.
Ethics committee approval
This study was approved by the Regional Committee for Medical and Health Research Ethics, Norway. The studies included in this review were approved by their respective regional ethics committees.
Transparency declaration
The lead author (TR) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported, that no important aspects of the study have been omitted, and that any discrepancies from the study as planned have been explained.
Contributor Information
Tormod Rogne, Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway; Address: NTNU, Det medisinske fakultet, Institutt for samfunnsmedisin, postboks 8905, 7491 Trondheim, Norway.
Myrte J Tielemans, 1) Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands; Address: P.O. Box 2040, Rotterdam CA 3000 CA Rotterdam, the Netherlands. 2) The Generation R Study Group, Erasmus MC, Rotterdam, the Netherlands; Address: P.O. Box 2040, Rotterdam CA 3000 CA Rotterdam, the Netherlands.
Mary Foong-Fong Chong, 1) Singapore Institute for Clinical Sciences, A*STAR, Singapore; Address: Singapore Institute for Clinical Sciences, Brenner Centre for Molecular Medicine, 30 Medical Drive, Singapore 117609. 2) Clinical Nutrition Research Centre, Singapore Institute for Clinical Sciences, A*STAR, Singapore. 3) Department of Paediatrics,Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
Chittaranjan S Yajnik, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital Research Centre, Pune, India; Address: Kamalnayan Bajaj Diabetology Research Centre,6th floor Banoo Coyaji Building, King Edward Memorial Hospital Research Centre, Rasta Peth, Pune-411011, Maharashtra state, India.
Ghattu V Krishnaveni, Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mysore, India; Address: Epidemiology Research Unit, CSI Holdsworth Memorial Hospital, Mandi Mohalla, Mysore, Karnataka, India.
Lucilla Poston, Division of Women’s Health, King's College London and King's Health Partners, London, United Kingdom; Address: Division of Women's Health, Women's Health Academic Centre, King's College London and King's Health Partners, 10th floor, North Wing, St.Thomas' Hospital, London SE1 7EH, United Kingdom.
Vincent W V Jaddoe, 1) The Generation R Study Group, Erasmus MC, Rotterdam, the Netherlands; Address: P.O. Box 2040, Rotterdam CA 3000 CA Rotterdam, the Netherlands. 2) Department of Pediatrics, Erasmus MC, Rotterdam, the Netherlands; Address: P.O. Box 2040, Rotterdam CA 3000 CA Rotterdam, the Netherlands.
Eric A P Steegers, Department of Obstetrics and Gynecology, Erasmus MC, Rotterdam, the Netherlands; Address: P.O. Box 2040, Rotterdam CA 3000 CA Rotterdam, the Netherlands.
Suyog Joshi, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital Research Centre, Pune, India; Address: Kamalnayan Bajaj Diabetology Research Centre,6th floor Banoo Coyaji Building, King Edward Memorial Hospital Research Centre, Rasta Peth, Pune-411011, Maharashtra state, India.
Yap-Seng Chong, 1) Singapore Institute for Clinical Sciences, A*STAR, Singapore; Address: Singapore Institute for Clinical Sciences, Brenner Centre for Molecular Medicine, 30 Medical Drive, Singapore 117609. 2) Clinical Nutrition Research Centre, Singapore Institute for Clinical Sciences, A*STAR, Singapore. 3) Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore.
Keith M Godfrey, Medical Research Council Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom; Address: MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Mailpoint 95, Southampton SO16 6YD, United Kingdom.
Fabian Yap, 1) Department of Paediatrics, KK Women's and Children's Hospital, Singapore; Address: Department of Paediatrics, KK Women's and Children's Hospital 100, Bukit Timah Road, Singapore 229899. 2) Duke-NUS Medical School, Singapore. 3) Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
Raquel Yahyaoui, Clinical Laboratory and Newborn Screening Center of Oriental Andalucía, Málaga Regional Hospital and Instituto de Investigación Biomédica de Málaga, IBIMA, Málaga, Spain; Address: Laboratorio de Metabolopatías. Hospital Materno Infantil, Av. Arroyo de los Angeles s/n 29011 Málaga, Spain.
Tinku Thomas, Division of Biostatistics and Epidemiology, St John’s Research Institute, Bangalore, India; Address: 100 Feet Rd, John Nagar, Koramangala, Bengaluru, Karnataka 560034, India.
Gry Hay, The Norwegian Directorate of Health, Oslo, Norway; Address: Helsedirektoratet, Postboks 7000, St. Olavs plass, 0130 Oslo, Norway.
Marije Hogeveen, Department of Pediatrics, Radboud University Medical Center, Nijmegen, the Netherlands; Address: Radboudumc Amalia kinderziekenhuis, Postbus 9101, 6500 HB Nijmegen (804), Geert Grooteplein 10 (route 804), 024-3614430, the Netherlands.
Ahmet Demir, Department of Obstetrics and Gynecology, Elazig Training and Research Hospital, Elazig, Turkey; Address: Elazig Egitim ve Arastirma Hastanesi, Kadın Hastalıkları ve Dogum Klinigi, Merkez/Elazig/Turkey.
Ponnusamy Saravanan, Warwick Medical School, University of Warwick, United Kingdom; George Eliot Hospital, Nuneaton, United Kingdom; Address: Gibett Hill, Warwick Medical School, University of Warwick, CV4 7AL, United Kingdom.
Eva Skovlund, 1) Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway; Address: NTNU, Det medisinske fakultet, Institutt for samfunnsmedisin, postboks 8905, 7491 Trondheim, Norway. 2) Norwegian Institute of Public Health, Oslo, Norway.
Marit P Martinussen, 1) Department of Obstetrics and Gynecology, St. Olav’s University Hospital, Trondheim, Norway. 2) Department of Laboratory Medicine, Children’s and Women’s Health, Norwegian University of Science and Technology, Trondheim, Norway; Address: NTNU, Faculty of Medicine, Department for laboratory Medicine, Children's and Women's Health, P.O. Box 8905, Medisinsk teknisk forskningssenter, 7491 Trondheim.
Geir W Jacobsen, Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway; Address: NTNU, Det medisinske fakultet, Institutt for samfunnsmedisin, postboks 8905, 7491 Trondheim, Norway.
Oscar H Franco, Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands; Address: P.O. Box 2040, Rotterdam CA 3000 CA Rotterdam, the Netherlands.
Michael B Bracken, Yale Center for Perinatal, Pediatric and Environmental Epidemiology, Yale University, CT, USA; Address: Yale School of Public Health, PO Box 208034, 60 College Street, New Haven, CT, 06520-8034, USA.
Kari R Risnes, 1) Department of Public Health and General Practice, Norwegian University of Science and Technology, Trondheim, Norway; Address: NTNU, Det medisinske fakultet, Institutt for samfunnsmedisin, postboks 8905, 7491 Trondheim, Norway. 2) Department of Pediatrics, St. Olav’s University Hospital, Trondheim, Norway.