Association between maternal vitamin D levels and risk of adverse pregnancy outcomes: a systematic review and dose–response meta-analysis

Rui Zhao a, Leilei Zhou a, Shanshan Wang a, Guoping Xiong b and Liping Hao *a
aDepartment of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety and the Ministry of Education (MOE) Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China. E-mail: haolp@mails.tjmu.edu.cn; Fax: +0086-27-83693307; Tel: +86-27-83650523
bThe Central Hospital of Wuhan, Wuhan, Hubei, China

Received 10th September 2021 , Accepted 26th November 2021

First published on 3rd December 2021


Abstract

Epidemiological studies have investigated the associations between vitamin D and the risk of adverse pregnancy outcomes; however, the results are conflicting and dose–response relationships remain to be confirmed. This study aimed to summarize previous studies on the associations of vitamin D levels with the risk of gestational diabetes mellitus (GDM), pre-eclampsia (PE), gestational hypertension (GH), and caesarean section (C-section), and to clarify the dose–response trends. PubMed, Embase, Scopus, and Web of Science were searched to identify eligible articles. A total of 69 prospective observational studies including cohort studies, case-cohort studies, or nested case-control studies were included in the current systematic review, of which 68 studies were available for meta-analysis. Compared with the lowest level, the highest level of 25(OH)D was significantly associated with a lower risk of GDM (RR: 0.76; 95% CI: 0.66–0.87), PE (RR: 0.74; 95% CI: 0.60–0.90;), and GH (RR: 0.87; 95% CI: 0.79–0.97); however, no significant relationship was found for C-section (RR: 1.00; 95% CI: 0.90–1.12). There was significant between-study heterogeneity for GDM (I2 = 69.2%; Pheterogeneity < 0.001), PE (I2 = 52.0%; Pheterogeneity = 0.001), and C-section (I2 = 59.1%; Pheterogeneity < 0.001), while no heterogeneity was found for GH (I2 = 0.0%; Pheterogeneity = 0.676). For each 25 nmol L−1 increase in 25(OH)D, the pooled RR was 0.92 (95% CI: 0.86–0.97) for GDM and 0.89 (95% CI: 0.84–0.94) for PE, respectively. Notably, the dose–response analysis showed a non-linear relationship between maternal 25(OH)D levels and the risk of PE (Pnon-linearity = 0.009). Our meta-analysis provides further scientific evidence of the inverse association between 25(OH)D levels and the risk of GDM, PE, and GH, which may be useful for the prevention of pregnancy complications. However, more evidence from prospective studies is needed regarding the dietary intake of vitamin D during pregnancy.


Introduction

Gestational diabetes mellitus (GDM), pre-eclampsia (PE), gestational hypertension (GH), and caesarean section (C-section) are serious adverse pregnancy outcomes that increase the risk of maternal and fetal/neonatal death and long-term health risks for the mother and offspring, such as diabetes mellitus, obesity, and cardiovascular disease.1–4 Vitamin D is an essential fat-soluble steroid hormone mainly produced through dietary intake and skin exposure to ultraviolet B rays from sunlight.5 However, increased air pollution, lifestyle changes, and the use of sunscreen products have further affected the synthesis of vitamin D, leading to a widespread prevalence of vitamin D deficiency, especially in pregnant women.6–8 In addition to the well-documented effect in regulating calcium and phosphorus balance and maintaining bone health, numerous studies have identified that vitamin D has anti-inflammatory and immunomodulatory functions,9,10 which take on pivotal roles in pregnancy.

Observational studies have extensively investigated the associations of maternal vitamin D deficiency with the risk of adverse pregnancy outcomes, but the results are inconsistent.11–16 Some cohort studies have found that vitamin D deficiency is associated with a reduced risk of GDM16 and PE.11 However, the results of some other studies showed no significant association between vitamin D deficiency and the risk of GDM, PE, GH, or C-section.12–15 Since 2011, many meta-analyses of observational studies have been published, showing that maternal vitamin D status is inversely associated with the risk of GDM17,18 and PE,19 but not with C-section.20 However, previous studies had some limitations in their design and therefore no clear conclusions could be drawn. For example, some research included studies with cross-sectional designs or case-control studies, which may affect the reliability of the results. To the best of our knowledge, no meta-analysis has examined the relationship between vitamin D levels and the risk of GH, and only one study in 2013 assessed the relationship between vitamin D levels and the risk of C-section. In addition, most of the studies did not explore the dose–response relationship of vitamin D levels with the risk of adverse pregnancy outcomes.

Due to the lack of a comprehensive meta-analysis of prospective studies on pregnancy complications, we performed this meta-analysis to provide updated evidence on the association of maternal blood and dietary levels of vitamin D with the risk of adverse pregnancy outcomes.

Methods

Search strategy

This meta-analysis was performed following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement (ESI Table S1),21 and our protocol has been registered in PROSPERO (CRD42021244431). We conducted a systematic search of electronic databases including PubMed, Embase, Scopus, and Web of Science from the inception to January 19, 2021. In short, we searched for the following keywords: (“Vitamin D” OR “25-hydroxyvitamin D” OR “25(OH)D” OR “Cholecalciferol” OR “Ergocalciferol”) AND (“Gestational diabetes mellitus” OR “Pre-eclampsia” OR “Hypertension, pregnancy-induced” OR “Caesarean section” OR “Pregnancy outcome”). Details of the search strategy are provided in ESI Table S2. Additionally, the bibliographies of relevant meta-analyses were manually searched to identify eligible literature.

Study selection

We included studies that met the following criteria: (1) studies with prospective design (cohort, case-cohort, or nested case-control studies); (2) reported the intake of vitamin D or 25(OH)D level as exposure; (3) reported the incidence of pregnancy outcomes such as GDM, GH, PE, and C-section as the outcome variables; (4) reported risk estimates and 95% confidence intervals (CIs), or provided sufficient data to calculate these values; and (5) for dose–response analysis, studies should report at least three exposure categories and provide the number of cases and participants in each category. We excluded letters, commentaries, reviews, meta-analyses, conference abstracts, studies without original data, and non-English articles.

Data extraction and quality assessment

Two investigators (RZ and LZ) independently extracted the following information from each eligible study using a standardized data collection form: first author's name, year of publication, country, study design, mean age or age range of participants, sample size, vitamin D assessment methods, type of outcomes, and adjustment factors. The study quality of selected studies was assessed using the Newcastle Ottawa Quality Assessment Scale (NOS).22 Studies scoring more than six stars are regarded as high in quality.

Statistical methods

RRs and corresponding 95% CIs were used as the risk estimates for studies, and HRs and ORs were considered approximately equal to the RRs. A random-effects model was used to pool RRs and 95% CIs for the comparison of the highest versus lowest category of exposure.23 We used risk estimates from the multivariate models. Heterogeneity between studies was evaluated by Cochran's Q test (P < 0.10) and the I2 statistic test.24I2 values of 25%, 50%, and 75% were considered as low, moderate, and high heterogeneity, respectively.25 We conducted the subgroup analyses to identify sources of heterogeneity by potential influencing factors such as study type, geographic location, study quality, sample size, 25(OH)D assay methods, blood sample type, trimester of sample collection, and whether adjusting for important factors. Meta-regression was performed to explore the heterogeneity between subgroups.26 Funnel plots and Egger's regression test27 were used to assess the publication bias. We also performed sensitivity analyses with a random-effects model to assess the effect of excluding each study on the overall estimates.

For the dose–response meta-analysis, 25(OH)D concentrations of ng mL−1 were converted to nmol L−1 by multiplying the values by 2.5. In studies that provided at least three categories of vitamin D levels, we extracted the mean or median vitamin D level in each category. When studies reported range values, we calculated the midpoint between the lower and upper limits of the category. If the highest category was open-ended, the width of the adjacent interval was used to calculate the upper bound. For studies that did not use the lowest category as the reference, we recalculated risk estimates using the method described by Hamling et al.28

A linear dose–response analysis of a random-effects model was performed using the generalized least squares regression to estimate the RRs for every 25 nmol L−1 increments in 25(OH)D levels.29 In addition, we examined the possible non-linear dose–response relationships by modeling the 25(OH)D levels through restricted cubic splines with 3 knots at the 10th, 50th, and 90th percentiles of the distribution.30,31 The non-linear P value (Pnon-linearity) was calculated by a likelihood ratio test.30,32 We used STATA version 15.1 (StataCorp, College Station, TX) for all analyses. Statistical tests were performed using a two-tailed method with a significance level of P < 0.05.

Results

Literature search and study characteristics

Our search retrieved 7427 records, of which 7212 were excluded by the initial screening according to titles and abstracts. After the full-text screening, 145 articles were further excluded (ESI Table S3), and we finally included 69 articles published from 2007 to 2021 (Fig. 1). Only one study reported the effect of vitamin D intake,33 the other 68 were studies on 25(OH)D levels, of which 36 studies were included in the meta-analysis for GDM,14–16,34–66 26 for PE,11,14,37,40,41,46,47,53,58,63,66–81 11 for GH,14,37,42,46,53,63,74,77,78,82,83 and 24 for C-section.12,16,37,38,41,42,46,47,53,56,66,84–96 For 25(OH)D levels, 17 articles detected 25(OH)D by LC-MS,12,36,37,39,40,44,49,50,52,59,61,69,70,74,75,80,89 10 by CLIA,11,14,41–43,55,64,79,81,91 eight by ECLIA,34,35,46,51,54,63,66,67 eight by ELISA,38,47,72,84,87,90,92,96 seven by RIA,15,45,57,60,71,77,82 six by HPLC,56,68,76,86,88,93 and three by EIA.65,78,95 Vitamin D intake was assessed using the food frequency questionnaire.33 Among all included articles, there were 46 cohort studies,12,14–16,33,34,37,38,40,42,44–51,53,54,56,59,62–64,66,67,74,76–79,81,83–94,96 21 nested case-control studies,11,35,39,41,43,52,55,57,58,60,61,65,68,70–73,75,80,82,95 and two case-cohort studies.36,69 Twenty articles were conducted in Asia,15,16,34,38,44,49,51,54,59,60,62–64,66,81,85,87,89,95,96 23 in North America,11,12,36,39,43,47,50,53,55,61,65,68–70,72,75–77,79,80,82,93,94 19 in Europe,33,37,41,45,46,52,56,57,67,71,73,74,78,83,84,88,90–92 five in Australia and New Zealand,14,40,42,48,58 and two in Africa.35,86 Forty-two studies were of high quality (ESI Tables S4 and S5). The characteristics of included studies are shown in Table 1.
image file: d1fo03033g-f1.tif
Fig. 1 Flow chart of study selection.
Table 1 Characteristics of included studies on maternal vitamin D levels and adverse pregnancy outcomes
Author, year Country, study type Study period Sample size Age range or mean age (years) Mean ± SD or median (IQR) vitamin D concentration Exposure assessment method Gestational week for vitamin D measurement Categories of vitamin D level Outcomes NOS score Adjusted variables
Abbreviations: CI, confidence interval; CLIA, chemiluminescent Immunoassay; C-section, caesarean section; ECLIA, electrochemical luminescence immunoassay; EIA, enzyme immunoassay; ELISA, enzyme-linked immunosorbent assay; FFQ, food frequency questionnaire; GDM, gestational diabetes mellitus; GH, gestational hypertension; HPLC, high-performance liquid chromatography; LC-MS, liquid chromatography-mass spectrometry; NOS, Newcastle Ottawa scale; NR, not reported; PE, pre-eclampsia; RIA, radioimmunoassay; RR, relative risk; T1, first trimester; T2, second trimester. Adjusted variables: (1) maternal age, (2) pre-pregnancy BMI/weight, (3) parity, (4) education, (5) race/ethnicity, (6) smoking, (7) alcohol consumption, (8) gestational age of blood sampling, (9) sampling season, (10) family history, (11) physical activity, (12) maternal height, (13)study site, (14) socioeconomic status,(15) gestational weeks at admission, (16) abnormal pregnancy history, (17) supplementation, (18) infant sex, (19) cholesterol, (20) high density lipoprotein, (21) triglyceride, (22) fasting plasma glucose, (23) CRP, (24) anaemia status, (25) CD4 cell count, (26) HIV RNA level, (27) ARV regimen, (28) skin color, (29) gestational weight gain, (30) sun exposure, (31) HbA1c, (32) menarche age, (33) menstrual cycle, (34) birth weight, (35) marital status, (36)religion, (37) blood pressure, (38) parathyroid hormone status, (39)gravidity, (40) homocysteine, (41) folate.
Chen et al. 202016 China, Retrospective cohort 2017–2018 2814 30.5 ± 4.98 53.1 ± 9.9 nmol L−1 Colloidal gold immunochromatography 16.3 ± 2.3 <50 nmol L−1 GDM, C-section 8 (1), (2), (3), (9)
≥50 nmol L−1
Xu et al. 201862 China, Prospective cohort 2015–2016 827 Case: 29 (26–34), Control: 25 (22–28) 15.3 (10.4–21.7) ng mL−1 NR At the first prenatal visit <10.4 ng mL−1 GDM 7 (1), (2), (5), (6), (8), (9), (10), (11), (14), (15), (16), (17), (19), (20), (21), (22), (23)
10.4–15.3 ng mL−1
15.4–21.7 ng mL−1
>21.7 ng mL−1
Zhu et al. 201915 China, Prospective cohort 2013–2014 3110 26 7 ± 3 7 18.2 ± 8.4 ng mL−1 RIA <14 <20 ng mL−1 GDM 9 (1), (2), (3), (4), (6), (7), (9), (10), (14)
20–30 ng mL−1
>30 ng mL−1
Yang et al. 201863 China, Prospective cohort 2013–2017 23[thin space (1/6-em)]100 32 ± 4.2 NR ECLIA 16 <30 nmol L−1 GDM, PE, GH 5 None
30–50 nmol L−1
>50 nmol L−1
Al-Ajlan et al. 201834 Saudi Arabia, Prospective cohort NR 419 28.7 ± 6.1 19.1 ± 15.1 nmol L−1 ECLIA 11.2 ± 3.4 <50 nmol L−1 GDM 7 (1), (2), (3), (9), (10), (11), (21), (29), (30), (31)
≥50 nmol L−1
Chen et al. 202085 China, Retrospective cohort 2015–2017 261 30.1 ± 4.0 22.2 ± 9.0 ng mL−1 NR 24–28 <20 ng mL−1 C-section 4 None
≥20 ng mL−1
Gernand et al. 201512 U.S., Prospective cohort 1959–1966 2798 NR 50.3 ± 27.8 nmol L−1 LC-MS ≤26 <30 nmol L−1 C-section 7 (2), (5), (13)
30–49 nmol L−1
50–74 nmol L−1
≥75 nmol L−1
Hemmingway et al. 201874 Ireland, Prospective cohort 2008–2011 1754 30.5 ± 4.5 22.7 ± 10.3 ng mL−1 LC-MS 15 <30 nmol L−1 GH, PE 7 GH: (2), (6), (11). PE: (2), (4), (17). SGA: (4), (11), (14)
30–<75 nmol L−1
≥75 nmol L−1
 
Yuan et al. 201796 China, Prospective cohort 2012–2015 1924 Case: 30.2 ± 3.8, Control: 28.9 ± 3.0 43.4 (35.2–56.9) nmol L−1 ELISA T2 <25 nmol L−1 C-section 8 (1), (2), (3), (9), (10), (13), (16), (32), (33)
25–37.4 nmol L−1
37.5–49.9 nmol L−1
50–74.9 nmol L−1
>75 nmol L−1
Al-Shafei et al. 202035 Sudan, Nested case-control 2017.1–2017.11 Case: 60 Control: 60 Case: 29.2 ± 6.0, Control: 28.0 ± 5.7 Case: 7.3 (5.7–8.8) ng mL−1, Control: 8.4 (6.6–11.9) ng mL−1 ECLIA ≤14 <6 ng mL−1 GDM 6 None
≥6 ng mL−1
Yue et al. 202064 China, Retrospective cohort 2018–2020 8468 NR NR CLIA ≤20 <20 ng mL−1 GDM 8 (1), (2), (3), (19), (21)
20–30 ng mL−1
≥30 ng mL−1
Abd Aziz et al. 202038 Malaysia, Prospective cohort NR 60 34.8 ± 3.9 34.5 ± 14.1 nmol L−1 ELISA 12–14 ≤50 nmol L−1 GDM, C-section 6 None
>50 nmol L−1
Dwarkanath et al. 201944 India, Prospective cohort 2008–2014 392 23.9 ± 3.8 34.4 (23.8–45.8) nmol L−1 LC-MS 12 <30 nmol L−1 GDM 9 (1), (2), (3), (4), (9), (11)
<50 nmol L−1
<75 nmol L−1
Li et al. 202051 China, Retrospective cohort 2014–2017 34[thin space (1/6-em)]417 30.6 ± 3.5 42.9 (32.9–51.9) nmol L−1 ECLIA 16 <50 nmol L−1 GDM 7 (1)
≥50 nmol L−1
Xia et al. 201861 U.S., Nested case-control 2009–2013 Cases: 107, Control: 214 Case:30.5 ± 5.7, Control:30.4 ± 5.4 NR LC-MS 10–14 <50 nmol L−1 GDM 8 (1), (2), (3), (5), (8), (9), (10), (11), (13)
15–26 ≥50 nmol L−1
Thiele et al. 201994 U.S., Retrospective cohort 2009–2013 357 30.6 ± 4.5 29.9 ± 10.9 ng mL−1 NR <36 ≤20.9 ng mL−1 C-section 5 None
21.0–29.9 ng mL−1
>30 ng mL−1
Shao et al. 202059 China, Prospective cohort 2011–2018 2789 28.7 ± 3.8 18.6 ± 8.6 ng mL−1 LC-MS 8–14 <20 ng mL−1 GDM 9 (1), (2), (3), (4), (8), (9), (11), (14), (29)
≥20 ng mL−1
Salakos et al. 202157 French and Belgium, Nested case-control 2012–2014 Case: 250, Control: 941 Case: 32.8 ± 5.3, Control: 32.3 ± 5.0 Case: 21.1 ± 10 ng mL−1, Control: 22.7 ± 10 ng mL−1 RIA 10–14 <10 ng mL−1 GDM 6 None
10–30 ng mL−1
≥30 ng mL−1
 
Öcal et al. 201990 Turkey, Prospective cohort 2012–2014 600 Case: 18.4 ± 1.3, Control: 28.7 ± 5.4 Case: 15.4 ± 7.9 ng mL−1, Control: 14.9 ± 4.7 ng mL−1 ELISA During pregnancy <10.9 ng mL−1 C-section 4 None
≥10.9 ng mL−1
Kısa et al. 202088 Turkey, Prospective cohort 2017 86 18–40 13.6 ± 6.6 ng mL−1 HPLC 11–13 ≤10 ng mL−1 C-section 6 None
>10 ng mL−1
Iqbal et al. 202049 India, Prospective cohort 2019 290 24.9 ± 2.7 Case: 33.5 ± 16.3 nmol L−1, Control: 38.2 ± 18.5 nmol L−1 LC-MS T1 <30 nmol L−1 GDM 8 (1), (2), (3), (4), (9), (11)
30–50 nmol L−1
50–75 nmol L−1
50–75 nmol L−1
≥75 nmol L−1
Bomba-Opon et al. 201483 Poland, Prospective cohort NR 280 NR NR NR 11–13 <20 ng mL−1 GH 5 None
≥20 ng mL−1
Bozdag et al. 202041 Turkey, Nested case-control NR 283 NR 9.5 ng mL−1 CLIA T1 <10 ng mL−1 GDM, PE, C-section 5 None
≥10 ng mL−1
Hajianfar et al. 201987 Iran, Prospective cohort NR 812 NR NR ELISA 8–16 <10 ng mL−1 C-section 6 None
32–34 10–29 ng mL−1
>30 ng mL−1
Griew et al. 201948 Australia, Prospective cohort 2011–2013 742 29.1 ± 4.9 43.5 ± 21.9 nmol L−1 NR 6–18 <12.5 nmol L−1 GDM 6 None
12.5–29.9 nmol L−1
30–49.9 nmol L−1
≥50 nmol L−1
Benachi et al. 201971 French and Belgium, Nested case-control 2012–2014 Case: 83, Control: 319 Case: 32.2 ± 5.9, Control: 31.7 ± 5.0 Case: 20.1 ± 9.3 ng mL−1, Control: 22.3 ± 11.1 ng mL−1 RIA 10–14 <10 ng mL−1 PE 5 None
10–30 ng mL−1
≥30 ng mL−1
Wilson et al. 201814 Australia and New Zealand, Prospective cohort 2004–2008 2800 28 ± 6 68.1 ±27.1 nmol L−1 CLIA 14–16 <44 nmol L−1 PE, GH, GDM 9 (1), (2), (5), (6), (7), (11), (13)
44–63 nmol L−1
63–81 nmol L−1
>81 nmol L−1
Eggemoen et al. 201845 Norway, Prospective cohort 2008–2010 745 29.8 (29.5–30.2) 50.2 (48.3–52.1) nmol L−1 RIA 15 <50 nmol L−1 GDM 8 (1), (3), (4), (5), (9), (13)
≥50 nmol L−1
 
Wen et al. 201795 China, Nested case-control 2012–2015 4718 NR 43.7 (35.5–57.9) nmol L−1 EIA Mid-late pregnancy <25.0 nmol L−1 C-section 8 (1), (2), (3), (8), (9), (10), (13), (16), (32), (33)
25.0–37.4 nmol L−1
37.5–49.9 nmol L−1
50.0–74.9 nmol L−1
>75.0 nmol L−1
Gbadegesin et al. 201786 Nigeria, Prospective cohort 2012–2013 461 31.26 NR HPLC 10–28 0–20 ng mL−1 C-section 5 None
21–30 ng mL−1
>30 ng mL−1
Van Weert et al. 201678 The Netherlands, Prospective cohort 2003–2004 2074 30.2 ± 4.6 60.0 ±29.8 nmol L−1 EIA <17 <20 nmol L−1 PE, GH 8 (1), (2), (4), (5), (6)
20–29.9 nmol L−1
30–49.9 nmol L−1
≥50 nmol L−1
Dodds et al. 201643 Canada, Nested case-control 2002–2010 Case: 395, Control: 1925 NR Case: 45.5 (35.9–56.7) nmol L−1, Control: 51.9 (40.6–62.4) nmol L−1 CLIA <20 <30 nmol L−1 GDM 8 (1), (2), (8), (9), (13)
30–<50 nmol L−1
≥50 nmol L−1
Boyle et al. 201640 New Zealand, Prospective cohort 2005–2008 1710 30.3 ± 4.7 72.9 ± 27.0 nmol L−1 LC-MS 15 <25 nmol L−1 PE, GDM 8 (2), (5)
25–49.9 nmol L−1
50–74.9 nmol L−1
>75 nmol L−1
Baca et al. 201669 U.S., Case-cohort 1999–2010 Cases: 650 Sub-cohort: 2327 NR Case: 57.8 (57.3–58.3) nmol L−1, Sub-cohort: 64.6 (64.4–64.8) nmol L−1 LC-MS <20 <25 nmol L−1 PE 8 (1), (2), (3), (4), (5), (6), (8), (9), (14), (35)
25–50 nmol L−1
50–75 nmol L−1
≥75 nmol L−1
Ates et al. 201637 Turkey, Prospective cohort 2012–2014 229 29.5 ± 4.9 13 ± 9.4 ng mL−1 LC-MS 11–14 <10 ng mL−1 GDM, GH, PE, C-section 7 None
≥10 ng mL−1
Rodriguez et al. 201556 Spain, Prospective cohort 2003–2008 2382 32.0 ± 4.2 29.4 (21.8–37.2) ng mL−1 HPLC 13.5 ± 2 <20 ng mL−1 GDM, C-section 9 (1), (2), (3), (4), (6), (7), (13), (14), (18)
20–29.99 ng mL−1
≥30 ng mL−1
Nobles et al. 201553 U.S., Prospective cohort 2007–2012 237 NR 30.4 ± 12.0 ng mL−1 NR 15.2 ± 4.7 <30 ng mL−1 GDM, GH, PE, C-section 9 (1), (2), (5), (8), (9), (29)
≥30 ng mL−1
 
Loy et al. 201589 Singapore, Prospective cohort 2009–2010 940 30.5 ± 5.1 81.0 ± 27.2 nmol L−1 LC-MS 26–28 ≤75 nmol L−1 C-section 8 (1), (2), (3), (4), (5), (6), (11), (16), (18)
>75 nmol L−1
Jain et al. 201560 India, Nested case-control NR Case: 32, Control: 178 <45 Case:11.9 ± 3.4 nmol L−1, Control: 22.3 ± 15.3 nmol L−1 RIA <20 <20 ng mL−1 GDM 6 None
20–29 ng mL−1
>30 ng mL−1
Gidlöf et al. 201573 Sweden, Nested case-control 1994–1995 Case: 39, Control: 120 Case: 29.2 ± 5.4, Control: 29.2 ± 4.6 Case: 52.2 ± 20.5 nmol L−1, Control: 48.6 ± 20.5 nmol L−1 NR 12 <50 nmol L−1 PE 6 None
≥50 nmol L−1
Flood-Nichols et al. 201547 U.S., Retrospective cohort 2014 235 24.3 ± 4.4 27.6 (13–71.6) ng mL−1 ELISA 8–12 <50 nmol L−1 GDM, PE, C-section 7 (2), (5), (6), (9)
50–75 nmol L−1
>75 nmol L−1
Davies-Tuck et al. 201542 Australia, Prospective cohort 2009–2010 1550 30.0 ± 5.4 47.0 (12–178) nmol L−1 CLIA 13.7 ± 3.3 <50 nmol L−1 GDM, GH, C-section 7 (1), (2), (3), (13)
50–74 nmol L−1
>74 nmol L−1
Aydogmus et al. 201584 Turkey, Prospective cohort 2013–2014 148 Groups I: 23.9 ± 4.6, Groups II: 24.9 ± 5.9 Groups I: 10.8 ± 3.8 ng mL−1, Groups II: 23.8 ± 13.3 ng mL−1 ELISA >28 <15 ng mL−1 C-section 5 None
≥15 ng mL−1
Arnold et al. 201536 U.S., Case-cohort 1996–2008 Case: 135, Control: 517 Case: 33.5 ± 4.6, Control: 32.6 ± 4.4 Case: 27.3 ± 8.7 ng mL−1, Control: 29.3 ± 8.3 ng mL−1 LC-MS 16 <20 ng mL−1 GDM 8 (1), (2), (5), (9), (10)
20–29 ng mL−1
≥30 ng mL−1
Anderson et al. 201582 U.S., Nested case-control NR Case: 37, Control: 11 Case: 25.3 ± 0.7, Control: 24.2 ± 0.6 NR RIA T1 <20 ng mL−1 GH 6 None
21–29 ng mL−1
>30 ng mL−1
Alvarez-Fernandez et al. 201567 Spain, Retrospective cohort 2010–2013 257 NR Case: 35.8 (27.6–46.0) nmol L−1[thin space (1/6-em)], Control: 33.9 (23.8–44.9) nmol L−1[thin space (1/6-em)] ECLIA 9–12 <50 nmol L−1 PE 7 None
≥50 nmol L−1
Achkar et al. 201511 Canada, Nested case-control 2002–2010 Case: 169, Control: 1975 NR Case: 47.2 ±17.7 nmol L−1, Control: 52.3 ±17.2 nmol L−1 CLIA <20 <30 nmol L−1 PE 8 (1), (2), (3), (6), (8), (9), (13)
30–<50 nmol L−1
≥50 nmol L−1
 
Zhou et al. 201466 China, Prospective cohort 2010–2012 1953 Group A: 29.2 ± 3.5, Group B: 29.5 ± 3.6, Group C: 30.3 ± 3.9 27.03 ± 7.92 ng mL−1 ECLIA 16–20 ≤20 ng mL−1 GDM, PE, C-section 6 None
21–29 ng mL−1
≥30 ng mL−1
Wetta et al. 201480 U.S., Nested case-control 2007–2008 Case: 89, Control: 177 Case: 26.1 ± 5.5, Control: 25.2 ± 6 Case: 27.4 ± 14.4 ng mL−1, Control: 28.6 ± 12.6 ng mL−1 LC-MS 15–21 <15 ng mL−1 PE 9 (1), (2), (3), (5), (6), (8), (9), (16)
<30 ng mL−1
≥30 ng mL−1
Park et al. 201454 Korea, Prospective cohort 2011–2012 523 Case: 34.8 ± 3.6, Control: 33.6 ± 3.7 Case: 35.3 ± 16.5 nmol L−1, Control: 32 ± 14.5 nmol L−1 ECLIA 12–14 <25.0 nmol L−1 GDM 8 (1), (2), (8), (9), (16), (17)
25.0–49.9 nmol L−1
≥50.0 nmol L−1
Schneuer et al. 201458 Australia, Nested case-control 2006–2007 5109 NR 56.4 (43.3–69.8) nmol L−1 NR 10–14 <37.5 nmol L−1 PE, GDM 8 (1), (2), (3), (6), (9), (16), (13), (14)
37.5–49.9 nmol L−1
50–75 nmol L−1
>75 nmol L−1
Reichetzeder et al. 201492 Germany, Prospective cohort 2007–2008 547 30.9 ± 6.1 18 ± 19 nmol L−1 ELISA Prior to delivery <1 nmol L−1 C-section 5 None
1–25 nmol L−1
≥25 nmol L−1
Lacroix et al. 201450 Canada, Prospective cohort NR 655 28.4 ± 4.5 63.0 ± 18.8 nmol L−1 LC-MS 6–13 <50 nmol L−1 GDM 6 None
50–74.9 nmol L−1
≥75 nmol L−1
Scholl et al. 201376 U.S., Prospective cohort 2001–2007 1141 22.8 ± 5.4 NR HPLC 13.7 ± 5.7 <12 ng mL−1 PE 8 (1), (2), (3), (5), (6), (15)
12–15.9 ng mL−1
16.0–19.9 ng mL−1
≥20.0 ng mL−1
Wei et al. 201279 Canada, Prospective cohort 2004–2006 697 Case: 30.9 ± 5.3, Control: 30.3 ± 4.8 Case: 51.1 ± 14.8 nmol L−1, Control: 56.0 ± 19.1 nmol L−1 CLIA 12–18 <50 nmol L−1 PE 7 (1), (2), (6), (9)
≥50 nmol L−1
Scholl et al. 201293 U.S., Prospective cohort 2001–2007 1153 NR NR HPLC 13.7 ± 5.6 <30 nmol L−1 C-section 8 (1), (2), (3), (5), (6), (9), (15)
30–49.9 nmol L−1
50–125.0 nmol L−1
>125 nmol L−1
Perez-Ferre et al. 201291 Spain, Prospective cohort 2010 266 33 (29–36) 18.9 (11.5–24.7) ng mL−1 CLIA 24–28 <20 ng mL−1 C-section 6 (1), (2), (5), (6), (16)
≥20 ng mL−1
 
Parlea et al. 201255 Canada, Nested case-control 2008–2009 Case: 116, Control: 219 Case: 34.3 ± 4.3, Control: 34.3 ± 4.1 Case: 56.3± 19.4 nmol L−1, Control: 62.0 ± 21.6 nmol L−1 CLIA 15–18 <46.9 nmol L−1 GDM 5 (2), (8)
46.9–60.4 nmol L−1
60.4–73.5 nmol L−1
≥73.5 nmol L−1
Fernandez-Alonso et al. 201246 Spain, Prospective cohort 2009–2010 466 NR 27.6 ±9.9 ng mL−1 ECLIA 11–14 <20 ng mL−1 GDM, PE, GH, C-section 7 None
20–29.99 ng mL−1
≥30 ng mL−1
Baker et al. 201239 U.S., Nested case-control 2004–2009 Case: 60, Control: 120 Case: 35 (31–37), Control: 33 (30–36) 89 (73–106) nmol L−1 LC-MS 11–14 <50 nmol L−1 GDM 8 (1), (2), (8), (9), (14)
50–74.9 nmol L−1
≥75 nmol L−1
Makgoba et al. 201152 UK, Nested case-control NR Case: 90, Control: 158 Case: 34.2 ± 4.9, Control: 33.1±4.7 Case: 18.9 ± 10.7 ng mL−1, Control: 19.0 ± 10.7 ng mL−1 LC-MS T1 <25 nmol L−1 GDM 6 None
25–50 nmol L−1
≥50 nmol L−1
Azar et al. 201168 U.S., Nested case-control NR Case: 23, Control: 24 Case: 28.5 ± 5.6, Control: 29.9 ± 3.8 NR HPLC 12.2 ± 1.9 <15 ng mL−1 PE 5 None
15–20 ng mL−1
20–30 ng mL−1
≥30 ng mL−1
Shand et al. 201077 Canada, Prospective cohort 2004–2008 221 NR 47.7 (34.2–67.9) nmol L−1 RIA 10–20 <37.5 nmol L−1 PE, GH 6 None
37.5–49.9 nmol L−1
50–75 nmol L−1
>75 nmol L−1
Powe et al. 201075 U.S., Nested case-control 1998–2006 Case: 39, Control: 131 Case: 28.9 ± 6.4, Control: 30.4 ± 6 Case: 27.4 ± 1.9 ng mL−1, Control: 28.8 ± 0.8 ng mL−1 LC-MS T1 Q1–Q4 PE 7 (2), (5), (9), (28)
Baker et al. 201070 U.S., Nested case-control 2004–2008 Cases:43 Controls: 198 Case: 30 (25–34), Control: 28 (23–32) Case: 75 (47–107) nmol L−1, Control: 98 (68–113) nmol L−1 LC-MS 15–20 <50 nmol L−1 PE 8 (1), (2), (3), (8), (9)
50–74.9 nmol L−1
≥75 nmol L−1
Haugen et al. 200933 Norway, Prospective cohort 2007 23[thin space (1/6-em)]423 NR Case: 7.7 (1.5-30.0) μg d−1, Control: 8.4 (1.7-31.4) μg d−1 FFQ During the first 4–5 months of pregnancy <5.0 μg d−1 PE 7 (1), (2), (4), (6), (9), (12)
5.0–9.9 μg d−1
10.0–14.9 μg d−1
15.0–20.0 μg d−1
>20.0 μg d−1
 
Zhang et al. 200865 U.S., Nested case-control 2002–2004 Case: 57 Control: 114 Case: 34.3 ± 4.8, Control: 33.1 ± 3.9 Case: 24.2 ± 8.5 ng mL−1, Control: 30.1 ± 9.7 ng mL−1 EIA 16 <20 ng mL−1 GDM 8 (1), (2), (5), (10)
20–29 ng mL−1
≥30 ng mL−1
Bodnar et al. 200772 U.S., Nested case-control 1997–2001 Case: 49 Control: 216 NR Case: 45.4 (38.6-53.4) nmol L−1, Control: 53.1 (47.1–59.9) nmol L−1 ELISA <22 <37.5 nmol L−1 PE 6 (2), (4), (5), (8), (9), (17)
37.5–75 nmol L−1
>75 nmol L−1
Yue et al. 202181 China, Retrospective cohort 2017–2019 7976 NR NR CLIA <20 <10 ng mL−1 PE 8 (1), (2), (3), (19), (21), (37), (40), (41)
10–20 ng mL−1
20–30 ng mL−1
≥30 ng mL−1


Maternal vitamin D levels and the risk of gestational diabetes mellitus

Thirty-six studies, including 101[thin space (1/6-em)]116 individuals and 11[thin space (1/6-em)]127 cases, indicated that the highest level of 25(OH)D was significantly associated with a 24% reduction in the risk of GDM compared to the lowest level (RR: 0.76; 95% CI: 0.66–0.87); however, significant heterogeneity was found between studies (I2 = 69.2%, Pheterogeneity < 0.001) (Fig. 2 and Table 2). In most subgroups, a significant negative association between 25(OH)D levels and risk of GDM was still observed, particularly in nested case-control studies, participants from North America, and studies controlling for maternal age, BMI, and season in their analysis (Table 3).
image file: d1fo03033g-f2.tif
Fig. 2 Maternal 25(Oh)D levels and risk of gestational diabetes mellitus, the highest versus lowest category.
Table 2 Maternal 25(OH)D levels and the risk of adverse pregnancy outcomes, the highest vs. lowest and dose–response meta-analyses
Outcomes Highest vs. lowest meta-analyses Dose–response meta-analyses
N RR (95% CI) I 2 (%) P heterogenity N RR (95% CI) I 2 (%) P heterogenity
Abbreviations: CI, confidence interval; C-section, caesarean section; GDM, gestational diabetes mellitus; GH, gestational hypertension; PE, pre-eclampsia; RR, relative risk.
GDM 36 0.76 (0.66, 0.87) 69.2 <0.001 24 0.92 (0.86, 0.97) 73.6 <0.001
PE 26 0.74 (0.60, 0.90) 52.0 0.001 19 0.89 (0.84, 0.94) 49.4 0.008
GH 11 0.87 (0.79, 0.97) 0.0 0.676 7 0.98 (0.92, 1.04) 26.6 0.226
C-section 24 1.00 (0.90, 1.12) 59.1 <0.001 9 1.03 (0.99, 1.08) 26.5 0.209


Table 3 Subgroup analyses of maternal 25(OH)D levels and risk of adverse pregnancy outcomes
  GDM PE GH C-section
Subgroups N RR (95% CI) I 2 (%) P h 1 P h 2 N RR (95% CI) I 2 (%) P h 1 P h 2 N RR (95% CI) I 2 (%) P h 1 P h 2 N RR (95% CI) I 2 (%) P h 1 P h 2
Abbreviations: CI, confidence interval; CLIA, chemiluminescent Immunoassay; C-section, caesarean section; ECLIA, electrochemical luminescence immunoassay; EIA, enzyme immunoassay; ELISA, enzyme-linked immunosorbent assay; GDM, gestational diabetes mellitus; GH, gestational hypertension; HPLC, high-performance liquid chromatography; LC-MS, liquid chromatography-mass spectrometry; NC, not calculable; NOS, Newcastle Ottawa scale; PE, pre-eclampsia; RIA, radioimmunoassay; RR, relative risk; T1, first trimester; T2, second trimester. Ph1 = P for heterogeneity within each subgroup. Ph2 = P for heterogeneity between subgroups with meta-regression.
All studies 36 0.76 (0.66, 0.87) 69.2 <0.001 26 0.74 (0.60, 0.90) 52.0 0.001 11 0.87 (0.79, 0.97) 0.0 0.676 24 1.00 (0.90, 1.12) 59.1 <0.001
Study type
Cohort 25 0.81 (0.70, 0.94) 73.1 <0.001 0.15 16 0.75 (0.67, 0.85) 2.4 0.426 0.81 10 0.88 (0.79, 0.97) 0.0 0.662 0.38 22 0.99 (0.88, 1.12) 58.6 <0.001 0.63
Nested case-control 11 0.61 (0.46, 0.81) 38.0 0.096 10 0.68 (0.42, 1.12) 75.5 <0.001 1 0.51 (0.15, 1.73) 2 1.09 (0.75, 1.57) 81.9 0.019
Geographic location
Europe 5 0.91 (0.72, 1.16) 0.0 0.847 0.54 6 0.87 (0.59, 1.28) 28.8 0.219 0.27 4 1.08 (0.69, 1.69) 11.4 0.336 0.27 4 0.76 (0.48, 1.19) 68.3 0.024 0.01
North America 9 0.62 (0.46, 0.83) 18.7 0.276 12 0.53 (0.39, 0.71) 31.5 0.139 3 0.67 (0.34, 1.32) 0.0 0.867 5 0.76 (0.60, 0.96) 0.0 0.498
Asia 16 0.79 (0.65, 0.95) 81.6 <0.001 5 0.89 (0.53, 1.52) 70.6 0.009 2 0.85 (0.76, 0.95) 0.0 0.759 13 1.05 (0.94, 1.17) 52.5 0.014
Others 6 0.64 (0.41, 1.01) 50.3 0.074 3 1.13 (0.78, 1.63) 0.0 0.592 2 1.01 (0.54, 1.91) 0.0 0.549 2 1.40 (0.89, 2.21) 65.2 0.090
Study quality
<7 11 0.73 (0.53, 1.00) 71.4 <0.001 0.99 8 0.88 (0.59, 1.32) 68.6 0.002 0.25 4 0.84 (0.76, 0.94) 0.0 0.536 0.11 12 1.08 (0.92, 1.26) 57.3 0.007 0.10
≥7 25 0.75 (0.64, 0.88) 67.7 <0.001 18 0.67 (0.52, 0.85) 38.7 0.048 7 1.12 (0.84, 1.50) 0.0 0.906 12 0.91 (0.82, 1.01) 24.5 0.203
Sample size
<2000 26 0.64 (0.49, 0.84) 68.2 <0.001 0.14 19 0.79 (0.59, 1.04) 49.8 0.007 0.39 8 1.02 (0.75, 1.38) 0.0 0.562 0.64 20 1.03 (0.91, 1.17) 54.0 0.002 0.26
≥2000 10 0.86 (0.76, 0.98) 68.8 0.001 7 0.64 (0.47, 0.89) 60.9 0.018 3 0.86 (0.77, 0.95) 0.0 0.723 4 0.87 (0.80, 0.95) 0.0 0.742
Blood sample type
Serum 26 0.83 (0.72, 0.95) 63.6 <0.001 0.08 24 0.72 (0.58, 0.89) 54.8 0.001 0.46 11 0.87 (0.79, 0.97) 0.0 0.676 NC 20 1.03 (0.92, 1.16) 61.4 <0.001 0.16
Plasma 9 0.54 (0.34, 0.86) 79.5 <0.001 2 0.97 (0.52, 1.80) 0.0 0.434 0 4 0.84 (0.63, 1.12) 40.3 0.170
25(OH)D assay methods
LC-MS/HPLC 11 0.76 (0.60, 0.98) 42.7 0.065 9 0.58 (0.40, 0.83) 34.7 0.140 0.05 2 1.28 (0.88, 1.87) 0.0 0.680 0.09 7 1.04 (0.75, 1.44) 71.8 0.002 0.62
ELISA/EIA 3 0.63 (0.23, 1.68) 19.8 0.287 0.64 3 0.54 (0.20, 1.43) 66.3 0.051 1 0.93 (0.37, 2.35) 8 0.98 (0.87, 1.11) 9.3 0.358
RIA 4 0.90 (0.57, 1.42) 61.0 0.053 2 0.72 (0.40, 1.30) 24.3 0.251 2 0.63 (0.27, 1.45) 0.0 0.641 0
ECLIA 7 0.88 (0.66, 1.17) 84.5 <0.001 4 0.77 (0.70, 0.86) 0.0 0.594 2 0.85 (0.76, 0.95) 0.0 0.757 2 1.10 (0.99, 1.23) 0.0 0.794
CLIA 6 0.61 (0.45, 0.84) 40.2 0.138 5 0.77 (0.41, 1.43) 73.9 0.004 2 1.01 (0.54, 1.91) 0.0 0.549 3 0.84 (0.44, 1.62) 84.0 0.002
Others 5 0.71 (0.45, 1.12) 79.4 0.001 4 1.08 (0.74, 1.56) 49.0 0.117 2 0.58 (0.21, 1.58) 0.0 0.327 4 0.87 (0.79, 0.96) 0.0 0.519
Trimester of sample collection
T1 17 0.72 (0.55, 0.94) 66.9 <0.001 0.60 9 1.29 (0.96, 1.73) 0.3 0.431 0.01 4 0.63 (0.31, 1.27) 0.0 0.643 0.74 7 1.22 (1.04, 1.44) 0.0 0.452 0.49
T2 11 0.83 (0.69, 1.00) 75.1 <0.001 8 0.78 (0.60, 1.01) 37.2 0.132 3 1.02 (0.73, 1.43) 58.5 0.090 6 0.91 (0.74, 1.10) 74.7 0.001
T3 4 0.92 (0.82, 1.04) 0.0 0.428
During pregnancy 9 0.65 (0.45, 0.95) 61.1 0.008 9 0.47 (0.37, 0.61) 0.0 0.604 4 0.82 (0.48, 1.39) 0.0 0.990 8 0.99 (0.77, 1.28) 61.5 0.011
Number of adjusted factors
<6 22 0.79 (0.67, 0.93) 65.5 <0.001 0.78 17 0.87 (0.69, 1.10) 44.0 0.027 0.06 9 0.87 (0.78, 0.96) 0.0 0.545 0.76 18 1.05 (0.92, 1.21) 64.8 <0.001 0.16
≥6 14 0.71 (0.53, 0.94) 74.5 <0.001 9 0.55 (0.39, 0.79) 53.5 0.028 2 1.02 (0.53, 1.95) 0.0 0.544 6 0.89 (0.80, 1.00) 0.0 0.539
Adjusted for confounding factors
Age Yes 21 0.74 (0.62, 0.88) 72.5 <0.001 0.75 11 0.56 (0.41, 0.77) 50.1 0.029 0.03 4 0.94 (0.59, 1.52) 0.0 0.909 0.91 9 0.86 (0.76, 0.98) 37.2 0.121 0.001
No 15 0.77 (0.59, 1.00) 61.7 0.001 15 0.91 (0.71, 1.17) 44.0 0.035 7 0.90 (0.73, 1.11) 12.6 0.334 15 1.13 (1.01, 1.28) 33.1 0.103
BMI Yes 20 0.70 (0.56, 0.87) 68.6 <0.001 0.52 15 0.57 (0.44, 0.74) 37.7 0.070 0.01 5 1.15 (0.85, 1.56) 0.0 0.796 0.10 11 0.85 (0.76, 0.96) 26.0 0.197 0.001
No 16 0.82 (0.68, 0.98) 67.4 <0.001 11 1.02 (0.76, 1.37) 51.0 0.026 6 0.84 (0.76, 0.94) 0.0 0.795 13 1.16 (1.03, 1.30) 31.4 0.132
Season Yes 15 0.70 (0.55, 0.90) 72.1 <0.001 0.65 9 0.58 (0.37, 0.90) 64.6 0.004 0.16 0 NC 5 0.86 (0.78, 0.94) 9.0 0.355 0.03
No 21 0.80 (0.68, 0.95) 65.6 <0.001 17 0.82 (0.66, 1.02) 38.8 0.052 11 0.87 (0.79, 0.97) 0.0 0.676 19 1.08 (0.96, 1.21) 45.1 0.018


Twenty-four publications on the association between 25(OH)D levels and the risk of GDM were included in the dose–response analysis. No evidence of a non-linear association between 25(OH)D levels and GDM risk was found (Pnon-linearity = 0.695) (ESI Fig. S1). For linear dose–response meta-analysis, we found a significant 8% reduction in the risk of GDM for each 25 nmol L−1 increase in 25(OH)D levels (RR: 0.92; 95% CI: 0.86–0.97), with high heterogeneity (I2 = 73.6%, Pheterogeneity < 0.001) (Fig. 3 and Table 2).


image file: d1fo03033g-f3.tif
Fig. 3 Linear dose–response meta-analysis of maternal 25(Oh)D levels (per 25 nmol L−1 increase) and risk of gestational diabetes mellitus.

Maternal vitamin D levels and risk of pre-eclampsia

Twenty-six studies with a total of 55[thin space (1/6-em)]203 participants and 4518 cases were included in this analysis. The pooled RR for the risk of PE, comparing the highest with the lowest level of 25(OH)D, was 0.74 (95% CI: 0.60–0.90), indicating a significant inverse association. However, there was evidence of moderate heterogeneity between studies (I2 = 52.0%, Pheterogeneity = 0.001) (Fig. 4 and Table 2). Subgroup analyses showed that the associations between 25(OH)D levels and risk of PE was significant in cohort studies, studies conducted in North America, studies of higher quality, studies using LC-MS/HPLC or ECLIA for 25(OH)D assays, and studies in which samples were collected throughout pregnancy. At the same time, the between-study heterogeneity was significantly reduced in these subgroups (Table 3).
image file: d1fo03033g-f4.tif
Fig. 4 Maternal 25(Oh)D levels and risk of pre-eclampsia, the highest versus lowest category.

Nineteen articles with sufficient data were identified for inclusion in the dose–response meta-analysis of PE. We found that each 25 nmol L−1 increase in 25(OH)D levels was associated with an 11% lower risk of PE (RR: 0.89; 95% CI: 0.84–0.94), with moderate heterogeneity (I2 = 49.4%, Pheterogeneity = 0.008) (ESI Fig. S2 and Table 2). Results of the dose–response meta-analysis showed a non-linear trend between 25(OH)D levels and PE risk (Pnon-linearity = 0.009), where the RRs continued to decrease as 25(OH)D levels increased from zero to higher; however, the risk declined more significantly from 40 nmol L−1 onwards (Fig. 5).


image file: d1fo03033g-f5.tif
Fig. 5 Non-linear dose–response meta-analysis of maternal 25(Oh)D levels and risk of pre-eclampsia.

We only retrieved one study from the Norwegian Mother and Child Cohort Study that examined the association between vitamin D intake and risk of PE. The result showed that the intake of vitamin D from supplements was associated with a reduced risk of PE.33 However, due to the small number of articles, we did not conduct a further meta-analysis.

Maternal vitamin D levels and the risk of gestational hypertension

A total of 11 studies with 32[thin space (1/6-em)]657 participants and 2572 cases provided data on the relationship between the highest versus the lowest level of 25(OH)D and the risk of GH. Highest level of 25(OH)D in comparison with lowest level decreased risk of GH by 13% (RR: 0.87; 95% CI: 0.79–0.97), with no significant between-study heterogeneity (I2 = 0%, Pheterogeneity = 0.676) (Fig. 6 and Table 2). Subgroup analyses revealed that the associations between 25(OH)D levels and risk of GH was significant in cohort studies, studies from Asia, studies of lower quality, studies with sample sizes ≥2000, studies using ECLIA for 25(OH)D assays, studies with fewer than six adjusting factors, and studies without adjustment for BMI (Table 3).
image file: d1fo03033g-f6.tif
Fig. 6 Maternal 25(Oh)D levels and risk of gestational hypertension, the highest versus lowest category.

Seven publications were incorporated into the dose–response meta-analysis for GH. There was no evidence of a non-linear relationship between maternal 25(OH)D levels and the risk of GH (Pnon-linearity = 0.209) (ESI Fig. S3). Moreover, the linear dose–response relationship between each 25 nmol L−1 increase in 25(OH)D levels and GH risk was not significant (RR: 0.98; 95% CI: 0.92–1.04; I2 = 26.6%, Pheterogeneity = 0.226) (ESI Fig. S4 and Table 2).

Maternal vitamin D levels and the risk of caesarean section

Twenty-four studies were included in the highest versus lowest meta-analysis on the relationship between maternal 25(OH)D levels and the risk of C-section, with a total of 25[thin space (1/6-em)]107 participants and 7670 cases. We found no significant association between maternal 25(OH)D levels and risk of C-section (RR: 1.00; 95% CI: 0.90–1.12; I2 = 59.1%, Pheterogeneity < 0.001) (ESI Fig. S5 and Table 2). Subgroup analyses revealed that the inverse association between maternal 25(OH)D levels and risk of C-section was significant in studies conducted in North America, studies with sample sizes ≥2000, and studies adjusted for maternal age, BMI, or season (Table 3).

Out of 24 articles, nine studies were included in the dose–response analysis. In the non-linear dose–response analysis, the maternal 25(OH)D levels were not associated with the risk of C-section (Pnon-linearity = 0.773) (ESI Fig. S6). Estimation of a linear dose–response trend demonstrated that an increase of 25 nmol L−1 in 25(OH)D was not associated with a higher risk of C-section (RR: 1.03; 95% CI: 0.99–1.08; I2 = 26.5%, Pheterogeneity = 0.209) (ESI Fig. S7 and Table 2).

Sensitivity analysis and publication bias

Due to the significant heterogeneity among studies between maternal 25(OH)D levels and the risk of GDM, we performed sensitivity analyses using a random effect model to test whether the pooled RR was significantly influenced by a specific study in the highest versus lowest meta-analysis (ESI Table S6). The results suggested that the overall estimates were not substantially altered by excluding one study at a time, with the pooled RRs ranging from 0.73 to 0.80. None of the excluded studies explained the large degree of heterogeneity in the findings. Similarly, sensitivity analyses demonstrated that none of the individual studies significantly affected the overall results for PE, GH, and C-section. Based on the funnel plot and Egger's regression test, no evidence of publication bias was observed for PE (P = 0.698), GH (P = 0.858), or C-section (P = 0.983). For GDM, the funnel plot was asymmetrical and the Egger's test (P = 0.016) showed a significant publication bias (ESI Fig. S8–S11).

Discussion

Main findings

This meta-analysis of sixty-eight prospective studies systematically assessed the associations of vitamin D levels with the risk of GDM, PE, GH, and C-section by comparing the highest and lowest levels and performing dose–response analyses. The findings showed that the highest level of 25(OH)D was significantly correlated with reduced risk of GDM, PE, and GH compared to the lowest level. Further, the dose–response analysis suggested that each 25 nmol L−1 increase in 25(OH)D was associated with an 8% and 11% reduction in the risk of GDM and PE, respectively. There was evidence of a non-linear trend in the risk of PE, with a more dramatic decline in 25(OH)D from 40 nmol L−1. Moreover, we found no association between vitamin D levels and the risk of C-section.

Strengths and limitations

Our study has several strengths. Firstly, this is the first comprehensive systematic review and dose–response meta-analysis to investigate the linear and non-linear relationships between maternal vitamin D levels and the risk of adverse pregnancy outcomes, including GDM, PE, GH, and C-section. Secondly, we incorporated studies that were truly prospective designed, excluding studies in which the gestational week of vitamin D measurement co-occurred as the endpoint or after the endpoint, to ensure a more plausible inference of causality. Thirdly, the large number of participants and cases provided sufficient statistical power to quantitatively assess the association of 25(OH)D levels with the risk of adverse pregnancy outcomes.

Besides these strengths, this study also has some limitations that should be acknowledged. Firstly, there was significant heterogeneity among studies for GDM, PE, and C-section risk. We performed extensive subgroup analyses and sensitivity analyses to explore the potential source of heterogeneity. The results identified factors including geographic location, 25(OH)D assay methods, trimester of sample collection, and whether adjustment for confounding factors may be a significant source of heterogeneity. Secondly, although the RRs were derived from the multivariate models, our results could not completely rule out the unmeasured confounders. Thirdly, the gestational week vitamin D measured was not explicitly described in some of the included studies, limiting our estimate of the effect of vitamin D levels on outcomes at different trimesters. Moreover, there are few studies on the association between the dietary intake of vitamin D and pregnancy outcomes, so insufficient data are available to perform a meta-analysis. More studies which combine vitamin D intake with blood biomarkers are necessary for the future. Finally, there was a publication bias in this meta-analysis, which can be partly explained by the fact that some studies reporting negative results for the association of vitamin D levels with GDM risk were not published. In the future, more large sample population studies are needed to verify our results further.

Interpretation

In agreement with our findings, recent studies have found a significant protective effect of higher vitamin D levels on the risk of GDM.17,18,97 However, controversy still exists regarding the dose–response relationship between vitamin D and the risk of GDM. In a recent systematic review and meta-analysis by Sadeghian et al.,97 each 10 nmol L−1 increase in circulating 25(OH)D was associated with a 2% reduction in the risk of GDM. However, findings from another meta-analysis by Milajerdi et al.18 indicated a U-shaped non-linear association between serum vitamin D levels and risk of GDM. Several methodological limitations may restrict the validity of the estimated effect values from these studies. The authors included studies in which 25(OH)D was measured on the same day as or after screening for GDM and could not ensure the prospective property of the studies. Also, they only included studies with serum samples, which resulted in fewer GDM cases being included in the study. In contrast, our study included both serum and plasma samples and further explored differences in subgroup analyses. Overall, it is necessary to conduct well-designed studies to elucidate the dose–response relationship between vitamin D levels and GDM risk.

We found a significant non-linear dose–response association between vitamin D levels and the risk of PE, with the risk decreasing more rapidly when vitamin D levels exceeded 40 nmol L−1. Several meta-analyses on the same topic were previously published, but they did not examine the potential non-linear and linear associations.19,20,98–100 Similar to our findings, some of these studies found that vitamin D deficiency or insufficiency was related to a higher risk of PE.19,20,100 However, two other studies showed that PE risk was not influenced by vitamin D levels during pregnancy.98,99 The discrepancies can be primarily attributed to the different inclusion criteria, with some studies including both cohort and cross-sectional studies, whereas the current meta-analysis included only prospective studies.

In this meta-analysis, maternal vitamin D levels in the highest category were protectively associated with the risk of GH compared with the lowest category. However, we did not find a significant dose–response relationship. To the best of our knowledge, this is the first meta-analysis to quantitatively summarize the association between vitamin D levels during pregnancy and GH. Nevertheless, the above results are based on a small number of studies, and further research is needed to shed light on this issue.

In line with the current study, the results of a systematic review and meta-analysis in 2013 showed no significant association between vitamin D levels and risk of C-section.20 Although vitamin D was found to reduce the common causes of the occurrence of C-section such as GDM and PE, and most studies did not distinguish whether the outcome was a primary C-section or whether it was an active elective cesarean delivery, which may somewhat influence the results. Future studies on this association need to consider and collect these essential factors associated with outcomes to improve the existing evidence.

The specific mechanisms behind the effects of vitamin D on adverse pregnancy outcomes are not well understood; however, the extra-skeletal effects of vitamin D may play a crucial role. For instance, vitamin D has an integral part in maintaining glucose and insulin homeostasis;101 therefore, higher vitamin D levels may reduce the risk of GDM. In addition, active vitamin D can inhibit the renin–angiotensin system (RAS),102 which is an essential pathway in the regulation of PE and GH.103 Furthermore, vitamin D is considered to have anti-inflammatory properties that may reduce the maternal inflammatory response.104 Consequently, these mechanisms may explain why higher vitamin D levels may reduce the risk of adverse pregnancy outcomes. However, more animal studies or clinical trials are needed to demonstrate the specific mechanisms.

In addition, our systematic review found that the mean 25(OH)D concentrations in pregnant women were highly varied in different regions, from 18 nmol L−1–98 nmol L−1.12,70,92 There are several possible influential factors that may contribute to discrepancies in vitamin D status between populations, such as sun exposure, diet, nutritional status, and renal function.105 Also, differences in the assay methods for blood 25(OH)D concentrations may have contributed to the discrepancy.105 Furthermore, the bioavailability of vitamin D intake varies among individuals, which may be explained in part by genetic variability in the vitamin D receptor (VDR).106,107

Conclusions

In conclusion, our comprehensive meta-analysis provides further evidence that higher 25(OH)D levels during pregnancy are associated with a lower risk of GDM and PE in a dose–response manner. However, the inverse association between maternal 25(OH)D levels and GH was significant in the highest versus lowest meta-analysis, but no dose–response relationship was found. Moreover, we found no association between vitamin D levels and the risk of C-section. More randomized controlled trials and animal experiments are needed to further evaluate the associations of vitamin D levels with adverse pregnancy outcomes to prove our findings.

Author contributions

Rui Zhao: conceptualization, methodology, software, formal analysis, and writing – original draft. Leilei Zhou: methodology, validation, data curation, and writing – original draft. Shanshan Wang: methodology, resources, and validation. Guoping Xiong: conceptualization, supervision, writing – review and editing, and funding acquisition. Liping Hao: conceptualization, supervision, writing – review and editing, project administration, and funding acquisition. All authors have read and agreed to the published version of the manuscript.

Conflicts of interest

The authors declared no conflict of interest.

Acknowledgements

We would like to thank all members of our research team for their engagement and the original authors of the included studies for their excellent work. Funding statement: This work was supported by the National Natural Science Foundation of China [No. 81773426 and No.82173513, to L. H.] and the Foundation of the Health Commission of Hubei Province [WJ2021F003, to G. X.].

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Footnote

Electronic supplementary information (ESI) available. See DOI: 10.1039/d1fo03033g

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