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Article

Vitamin D Metabolite Ratio in Pregnant Women with Low Blood Vitamin D Concentrations Is Associated with Neonatal Anthropometric Data

by
Tomozumi Takatani
1,*,
Yuzuka Kunii
1,
Mamoru Satoh
2,
Akifumi Eguchi
3,
Midori Yamamoto
3,
Kenichi Sakurai
3,
Rieko Takatani
3,
Fumio Nomura
2,
Naoki Shimojo
3 and
Chisato Mori
3,4
1
Department of Pediatrics, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
2
Division of Clinical Mass Spectrometry, Chiba University Hospital, Chiba 260-8677, Japan
3
Center for Preventive Medical Sciences, Chiba University, Chiba 263-8522, Japan
4
Department of Bioenvironmental Medicine, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
*
Author to whom correspondence should be addressed.
Nutrients 2022, 14(11), 2201; https://doi.org/10.3390/nu14112201
Submission received: 3 April 2022 / Revised: 20 May 2022 / Accepted: 21 May 2022 / Published: 25 May 2022
(This article belongs to the Section Nutritional Epidemiology)
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Abstract

:
Existing evidence on the correlation between maternal vitamin D concentrations and birth outcomes is conflicting. Investigation of these associations requires accurate assessment of vitamin D status, especially in individuals with low 25-hydroxyvitamin D (25(OH)D) concentrations. This study examined the correlations between birth outcomes and the maternal vitamin D metabolite ratio (VMR) 1 (defined as the ratio of 24,25(OH)2D3 to 25(OH)D) and VMR2 (defined as the ratio of 3-epi-25(OH)D3 to 25(OH)D) using data from the Japan Environment and Children’s Study at Chiba Regional Center. A total of 297 mother–neonate pairs were analyzed. Using liquid chromatography–tandem mass spectrometry, we measured 25(OH)D2, 25(OH)D3, 24,25(OH)2D3, and 3-epi-25(OH)D3 concentrations in maternal serum samples. These data were analyzed in relation to birth anthropometric data using multivariable linear regression. Of the study participants, 85.2% showed insufficient vitamin D concentrations. VMR1 was strongly correlated with 25(OH)D concentrations, whereas VMR2 showed a weak correlation. Only VMR2 was associated with all anthropometric data. VMR2 in pregnant women with low vitamin D blood concentrations is a useful marker for neonatal anthropometric data and is independent of 25(OH)D. Accurate measurement of vitamin D metabolites could help better understand the effects of vitamin D on birth outcomes.

1. Introduction

Intrauterine growth is regulated by multiple genetic and environmental factors. Although genetic factors have been proven to play a substantial role in intrauterine growth, accumulating evidence shows that the intrauterine environment contributes significantly more to fetal growth. A study using embryo transfer revealed that the recipient mother affected intrauterine growth more than the donor mother [1]. Other studies have suggested that 25–40% of the variability in birth weight can be explained by fetal genes [2,3,4]. Prenatal growth is an important public health concern worldwide because intrauterine growth restriction is a major cause of mortality in neonates and infants [5]. Moreover, prenatal growth is significantly associated with adult morbidity throughout life, such as cardiovascular disease, neurodevelopmental complications, and endocrine disorders [6,7,8]. In Japan, the average weight of a newborn has decreased over the last 3 decades from 3200 g to 3020 g [9]. Although several attempts have been made to determine which factors contribute to birth size, these factors are not fully known. Vitamin D is an important nutritional factor, and its deficiency is related to several negative health outcomes. However, scientific evidence for the association between vitamin D and birth outcomes is controversial [10,11,12,13,14,15,16,17,18,19].
A World Health Organization scientific group meeting defined Vitamin D insufficiency as total serum 25-hydroxyvitamin D (25(OH)D) concentrations of less than 20 ng/mL [20]. However, some ethnic groups who have low serum 25(OH)D concentrations show healthy bone mineral density, which is a major health outcome associated with 25(OH)D. African–Americans are representative of such groups with low 25(OH)D concentrations [21,22,23] and paradoxically show a higher bone mineral density and a lower risk of fracture than White Americans [24,25,26,27]. This finding suggests that the current measurement of 25(OH)D concentrations is not directly correlated with some health outcomes in certain groups. A more detailed analysis of vitamin D status may be required to determine its relationship to health outcomes.
A recent report has shown that the ratio of 24,25-dihydroxyvitamin D3 (24,25(OH)2D3) to 25(OH)D is a better risk indicator for hip fracture than 25(OH)D because this ratio reflects vitamin D receptor (VDR) activity [28]. Moreover, other reports have suggested that the C-3 epimer 25-hydroxyvitamin D3 (3-epi-25(OH)D3), which is converted from 25(OH)D3 by 3-epimerase in the liver, is also related to several health outcomes [29,30]. The availability of newer technologies, such as liquid chromatography–tandem mass spectrometry (LC-MS/MS), which can distinguish 3-epi-25(OH)D3 from 25(OH)D3, have increased interest in 3-epi-25(OH)D3 when considering its association with health outcomes. The metabolite 3-epi-25(OH)D3 is thought to be less potent physiologically than 25(OH)D, and the ratio of 3-epi-25(OH)D3 to 25(OH)D is associated with diabetic complications [31]. Both ratios can reflect vitamin D metabolism more closely than either metabolite alone, and both can be markers of several health outcomes independent of 25(OH)D. However, the associations between these ratios in pregnant women with low 25(OH)D concentrations and prenatal growth have not been investigated.
To address this lack of knowledge, we measured the ratio of 24,25(OH)2D3 to 25(OH)D, which we defined as the vitamin D metabolite ratio (VMR) 1, and the ratio of 3-epi-25(OH)D3 to 25(OH)D, which we defined as VMR2. To verify whether VMR1 and VMR2 are independent of 25(OH)D, we determined the correlations between 25(OH)D and VMR1 and between 25(OH)D and VMR2 by a Spearman correlation test. We analyzed their associations with birth outcomes using data from the Japan Environment and Children’s Study (JECS) at the Chiba Regional Center. The JECS is an ongoing birth cohort study. A report using JECS data has shown that most Japanese pregnant women had insufficient vitamin D concentrations [32,33]. Therefore, in this Japanese cohort, we clarified the associations between vitamin D metabolite concentrations in pregnant women who have low 25(OH)D concentrations and neonatal anthropometric data.

2. Materials and Methods

2.1. Study Participants

This study used data obtained from the Chiba Regional Center. This study was conducted as an adjunct study of the JECS funded by the Ministry of the Environment, Japan. The JECS protocol was described previously [34]. In 15 regional centers, the JECS recruited pregnant women in early pregnancy between January 2011 and March 2014. We analyzed jecs-ta-20190930 (released in October 2019), which is a dataset from the JECS. The JECS protocol was approved by the Institutional Review Board on Epidemiological Studies of the Ministry of the Environment and by the Ethics Committees of all participating institutions. The project code of this adjunct study at the Chiba Regional Center was #1538. Written informed consent was obtained from all participating women according to the Declaration of Helsinki.

2.2. Measurement of Vitamin D Metabolites

Of the 103,060 JECS pregnancies, 1965 mother-infant pairs with available maternal serum samples at Chiba Regional Center were included in this study. Maternal serum samples were collected before 22 weeks of pregnancy and between 22 weeks and 35 weeks of pregnancy. We randomly selected 400 maternal serum samples collected between 22 weeks and 35 weeks of pregnancy. Sampling was conducted throughout the year, and samples were stored at −80 °C until analysis. Vitamin D and its metabolites, such as 25(OH)D2, 25(OH)D3, 24,25(OH)2D3, and 3-epi-25(OH)D3, were measured using LC-MS/MS as previously described [35]. We are part of the Vitamin D External Quality Assessment Scheme (DEQAS). We calculated 25(OH)D as the sum of 25(OH)D2 and 25(OH)D3.
The standard reference material (SRM) 972a from the National Institute of Standards and Technology was used to examine the accuracy of the LC-MS/MS method in this study. The SRM 972a consists of four levels: 25(OH)D2, 25(OH)D3, 24,25(OH)2D3, and 3-epi-25(OH)D3 [36].

2.3. Covariate and Birth Outcome Data

We collected data on birth outcomes and covariates as previously described [34]. Anthropometric measurements at birth, the neonate’s sex, gestational period, maternal age at delivery, parity, and the mode of delivery were acquired from medical records transcribed during pregnancy and after delivery. Data on annual family income, education levels, and smoking and drinking habits during pregnancy were collected using self-administered questionnaires, which were filled in during registration to this study and during mid–late pregnancy. Maternal anthropometric data, maternal age, pre-pregnancy height, and weight were obtained from medical records and questionnaires. Maternal body mass index (BMI) was calculated as follows: body weight(kg)/(height(m))2.

2.4. Statistical Analysis

Simple and multiple linear regression models were used to calculate unadjusted and adjusted differences (β) and 95% confidence intervals (CIs) for weight, length, head circumference, and chest circumference at birth. Linear regression models were used to calculate expected differences in the birth anthropometric measurements for each 1 ng/mL increase in vitamin D metabolites or 1-unit increase in VMR1 or VMR2.Multiple linear regression models were adjusted for maternal age (<25, 25–29, 30–34, and ≥35 years), parity (0 and ≥1), pre-pregnancy BMI (<18.5, 18.5–< 25, and ≥25.0 kg/m2), maternal education (<10, 10–12, 13–16, and ≥17 years of education), household income (<2, 2 to <4, 4 to <6, 6 to <8, 8 to <10, and ≥10 million Japanese yen (JPY)), smoking habit during pregnancy (never smoked, ex-smokers who quit before pregnancy, and smoked during pregnancy), alcohol habit during pregnancy (never drank, ex-drinkers who quit before pregnancy, and drank during pregnancy), the mode of delivery (vaginal delivery, cesarean section), and the neonate’s sex. Covariates were selected a priori based on the literature and biological plausibility [37,38]. The Spearman correlation test was performed to determine the correlations between 25(OH)D and VMR1 and between 25(OH)D and VMR2.
For all analyses, p-values of less than 0.05 were used to denote statistical significance. All statistical analyses were performed using R (version 4.0.3; R Development Core Team, Vienna, Austria; http://www.R-project.org, accessed on 8 November 2020).

3. Results

After excluding mothers with stillbirth, miscarriage, and multiple births, 358 mother–neonate pairs were included in this study. Then, we excluded mother–neonate pairs with one or more missing data (i.e., birth weight, birth length, birth head circumference, birth chest circumference, age, BMI before pregnancy, parity, smoking during pregnancy, drinking during pregnancy, education level, annual household income, and mode of delivery). Finally, the completed dataset comprised 297 mother–neonate pairs (Figure 1).

3.1. Baseline Characteristics

The characteristics of the mothers and neonates enrolled in this study are shown in Table 1 and Table 2, respectively. The mean age of the mothers at delivery was 31.3 ± 4.8 years. Approximately 90% of the participants had a BMI of less than 25 kg/m2 before pregnancy. Moreover, 32.7% of the participants showed an annual household income between 2 and 4 million JPY, which is almost the median annual income of the Japanese working population. Most participants had more than 10 years of education, which represented high school or higher education. Overall, 53.5% of the mothers never smoked, whereas 15.2% smoked during early pregnancy. Additionally, 43.4% of the mothers drank during early pregnancy. The mean gestational age was 39.2 ± 1.5 weeks for 297 singletons.

3.2. Vitamin D Metabolite Concentrations

The mean, interquartile range, minimum, and maximum values of vitamin D metabolites, VMR1, and VMR2 are shown in Table 3. All metabolites were detected in all samples. Moreover, 85.2% of the participants had insufficient vitamin D concentrations when the threshold was set at 20 ng/mL (Table 1). The Spearman correlation test showed a strong correlation between VMR1 and 25(OH)D concentrations (r = 0.732; p < 0.001), whereas a weak correlation between VMR2 and 25(OH)D concentrations was found (r = 0.304; p < 0.001) (Figure 2). Quality control analyses of the vitamin D measurements, shown in Supplementary Table S1, demonstrated acceptable quality.

3.3. Factors including VMR and Neonatal Anthropometric Data

Unadjusted linear regression revealed that neither the individual vitamin D metabolites nor VMR1 were significantly associated with birth outcomes. Notably, VMR2 showed significant associations with all birth outcomes, including birth weight (β = 5907.30; 95% CI: −10,285.77 to −1528.86), birth length (β = −23.24; 95% CI, −45.71 to −0.78), birth head circumference (β = −20.66; 95% CI, −35.14 to −6.19), and birth chest circumference (β = −26.55; 95% CI, −44.41 to −8.69) (Table 4). Moreover, multiple linear regression analysis showed that VMR2 was correlated with birth weight (β = −4937.35; 95% CI, −8455.06 to −1419.64), birth length (β = −19.48; 95% CI, −37.39 to −1.58), birth head circumference (β = −18.75; 95% CI, −32.71 to −4.79), and birth chest circumference (β = −23.66; 95% CI, −38.44 to −8.87), whereas VMR1 and the vitamin D metabolites were not correlated with any neonatal anthropometric data (Table 4).

4. Discussion

The findings here show that most women we analyzed in this study were deficient in 25(OH)D, which is consistent with the findings of several previous reports [32,33]. Several studies on pregnant women of different ethnicities have shown insufficient vitamin D concentrations, as found in our study [12,39,40]. These studies have reported that 25(OH)D concentrations were not correlated with neonatal anthropometric measures. In an attempt to determine better parameters showing the associations between vitamin D and health outcomes, we found the ratio of 24,25(OH)2D to 25(OH)D to be a better marker for vitamin D sufficiency and bone health than 25(OH)D concentrations in older adults [41]. Therefore, the ratios of vitamin D metabolites may be more suitable than 25(OH)D alone for evaluating associations of vitamin D status with certain health outcomes. In fact, a report has shown an association between hip fracture risk and VMR1 in adults [28]. However, our data did not show any correlations between neonatal anthropometric data and VMR1. As 5-hydroxyvitamin D-24-hydroxylase (CYP24A1) converted 25(OH)D3 into 24,25(OH)2D3, VMR1 is considered to reflect the activity of VDR because it regulates CYP24A1 expression [28]. However, CYP24A1 expression is regulated by not only VDR but also parathyroid hormone and fibroblast growth factor 23 [42,43]. Both hormones are lower in fetuses than in adults [44,45,46]. Therefore, owing to the differences in these hormones, VMR1 may not be a robust indicator of VDR activity in neonates. This finding indicates that VMR1 is not a good indicator of bone metabolism in the neonatal period.
By contrast, this study showed that maternal VMR2 was significantly associated with anthropometric outcomes at birth, suggesting that VMR2 can be used as a predictor of these neonatal outcomes in pregnant women with low vitamin D status. In this study, VMR1 showed a strong correlation with 25(OH)D concentrations, suggesting that the production of 24,25(OH)2D3 depends on 25(OH)D concentrations. However, VMR2 only showed a weak correlation with 25(OH)D concentrations, suggesting that VMR2 could be an independent predictor of certain health outcomes. Regulatory factors other than 25(OH)D concentrations could be involved in the production of 3-epi-25(OH)D3.
Our results indicated that epimers were metabolites with potential correlations with neonatal anthropometric data in pregnant women who had low 25(OH)D concentrations. Epimers are increased in the pregnancy and neonatal periods [47,48,49]. Researchers have investigated pregnant women with low 25(OH)D concentrations and shown that 3-epi-25(OH)D3 was more correlated with health outcomes, such as cardiovascular complications of diabetes [31,50]. Epimers differ in their configurations around a single site of carbon atom (in this case, C-3α- vs. C-3β-hydroxy); otherwise, they have the identical chemical structures [51]. The epimerization of 25(OH)D3 at the C3 location is formed by 25(OH)D3-3-epimerase in the endoplasmic reticulum of liver, bone, and skin cells [52]. Epimerization may also be related to liver immaturity because infants show higher concentrations of epimers than adults [47]. Moreover, higher concentrations of epimers are detected in pregnant women than in non-pregnant women [48]. Studies have attempted to determine the physiological role of higher levels of C-3 epimers. In vitro experiments have shown that 3-epi-1,25(OH)2D3, which is metabolized from 3-epi-25(OH)D3 and is the most active form of the three 3-C epimers, showed nearly 10% transcription of the osteocalcin gene in human osteoblast cells compared with 1,25(OH)2D3. Moreover, the antiproliferative and differentiation-inducing activities of 3-epi-1,25(OH)2D3 were observed in 29% and 9.4% of 1,25(OH)2D3 forms, respectively [53]. Therefore, the transcriptional activity and biological effects of 3-epi-1,25(OH)2D3 are limited compared with those of its nonepimeric form. A future study focusing on the biological effects of epimers on fetal development is required.
Moreover, vitamin D metabolism may vary based on age; specific markers may be required in the neonatal period to consider vitamin D metabolism. In the future, an analysis of individuals of different ages, such as adults and/or older individuals, will also be required to determine whether vitamin D metabolism depends on age.
This study had several strengths. First, vitamin D and its metabolites were measured with high accuracy owing to modern technology. Second, this study was based on well-characterized, homogeneous Japanese pregnant women. Additionally, the covariates were well-adjusted because the data were based on a well-designed prospective cohort in Japan.
However, this study also had several limitations. First, we only measured maternal circulating blood vitamin D levels, not vitamin D levels in the uterus or placenta, which may be more relevant to neonatal growth. However, the blood of pregnant women may reflect the status of the interaction between mothers and fetuses. Moreover, blood sampling is more practical than placental or amniotic fluid sampling from the uterus during pregnancy. Second, this study was a complete case analysis, which could have caused bias due to potential differences among women with and without complete covariate data available.
In future research, our findings should be confirmed with another cohort comprising other ethnicities with low vitamin D levels. Clarifying the importance of maternal VMR2 as an independent indicator of birth outcomes will extend our knowledge and on the importance of vitamin D in the prenatal period.

5. Conclusions

In conclusion, VMR2 in Japanese pregnant women with vitamin D insufficiency is associated with neonatal anthropometric data. VMR2 during pregnancy appears to be an independent marker of 25(OH)D, which is important in predicting birth outcomes. Our results suggest that VMR2 should be determined when studying birth outcomes. Measuring and considering vitamin D metabolites may help interpret conflicting results regarding the associations between vitamin D status in pregnant women and birth outcomes.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nu14112201/s1, Table S1: Quality Control (QC) sample measurement values.

Author Contributions

T.T. and N.S. conceived the idea and designed the study; T.T. wrote the manuscript; T.T., R.T. and A.E. analyzed the data; R.T., M.Y. and C.M. contributed to the data sampling; Y.K., M.S. and F.N. contributed to the measurement of vitamin D metabolites; K.S., N.S. and C.M. contributed to the discussion and edited the manuscript. All authors reviewed and approved the manuscript. T.T. is a guarantor of this work and, as such, had full access to all data in this study and takes responsibility for the integrity and accuracy of data analyses. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the Ministry of the Environment, Japan. The findings and conclusions of this article are solely the responsibility of the authors and do not represent the official views of the aforementioned government agencies.

Institutional Review Board Statement

The JECS protocol was approved by the Institutional Review Board on Epidemiological Studies of Ministry of the Environment and by the ethics committees of all participating institutions. The project code of this adjunct study at the Chiba Regional Center was #1538.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data are unsuitable for public deposition owing to ethical restrictions and the legal framework of Japan. The Act on the Protection of Personal Information (Act No. 57 of 30 May 2003, amendment on 9 September 2015) prohibits public deposition of data containing personal information. The Ethical Guidelines for Medical and Health Research Involving Human Subjects enforced by the Japan Ministry of Education, Culture, Sports, Science and Technology and the Ministry of Health, Labour and Welfare also restrict open sharing of epidemiological data. All inquiries about access to JECS data should be sent to the following e-mail address: [email protected]. The person responsible for handling enquiries sent to this e-mail address is Dr Shoji F. Nakayama, JECS Programme Office, National Institute for Environmental Studies.

Acknowledgments

We express our gratitude to the children and families who participated in the JECS. We greatly appreciate the cooperation of the health care providers. We also thank all JECS staff members. The JECS was funded by the Ministry of the Environment, Japan. The findings and conclusions of this article are solely the responsibility of the authors and do not represent the official views of the aforementioned government agencies.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Brooks, A.A.; Johnson, M.R.; Steer, P.J.; Pawson, M.E.; Abdalla, H.I. Birth weight: Nature or nurture? Early Hum. Dev. 1995, 42, 29–35. [Google Scholar] [CrossRef]
  2. Magnus, P.; Gjessing, H.K.; Skrondal, A.; Skjaerven, R. Paternal contribution to birth weight. J. Epidemiol. Community Health 2001, 55, 873–877. [Google Scholar] [CrossRef] [Green Version]
  3. Lunde, A.; Melve, K.K.; Gjessing, H.K.; Skjaerven, R.; Irgens, L.M. Genetic and environmental influences on birth weight, birth length, head circumference, and gestational age by use of population-based parent-offspring data. Am. J. Epidemiol. 2007, 165, 734–741. [Google Scholar] [CrossRef] [Green Version]
  4. Clausson, B.; Lichtenstein, P.; Cnattingius, S. Genetic influence on birthweight and gestational length determined by studies in offspring of twins. BJOG 2000, 107, 375–381. [Google Scholar] [CrossRef] [Green Version]
  5. Katz, J.; Lee, A.C.; Kozuki, N.; Lawn, J.E.; Cousens, S.; Blencowe, H.; Ezzati, M.; Bhutta, Z.A.; Marchant, T.; Willey, B.A.; et al. Mortality risk in preterm and small-for-gestational-age infants in low-income and middle-income countries: A pooled country analysis. Lancet 2013, 382, 417–425. [Google Scholar] [CrossRef] [Green Version]
  6. Mericq, V.; Martinez-Aguayo, A.; Uauy, R.; Iniguez, G.; Van der Steen, M.; Hokken-Koelega, A. Long-term metabolic risk among children born premature or small for gestational age. Nat. Rev. Endocrinol. 2017, 13, 50–62. [Google Scholar] [CrossRef]
  7. Pariente, G.; Sheiner, E.; Kessous, R.; Michael, S.; Shoham-Vardi, I. Association between delivery of a small-for-gestational-age neonate and long-term maternal cardiovascular morbidity. Int. J. Gynaecol. Obs. 2013, 123, 68–71. [Google Scholar] [CrossRef]
  8. Savchev, S.; Sanz-Cortes, M.; Cruz-Martinez, R.; Arranz, A.; Botet, F.; Gratacos, E.; Figueras, F. Neurodevelopmental outcome of full-term small-for-gestational-age infants with normal placental function. Ultrasound Obs. Gynecol. 2013, 42, 201–206. [Google Scholar] [CrossRef]
  9. Ministry of Health, Labour and Welfare. Vital Statistics of Japan 1980–2010. Available online: https://www.mhlw.go.jp/english/database/db-hw/FY2010/live_births.html (accessed on 26 March 2021).
  10. Gernand, A.D.; Simhan, H.N.; Klebanoff, M.A.; Bodnar, L.M. Maternal serum 25-hydroxyvitamin D and measures of newborn and placental weight in a U.S. multicenter cohort study. J. Clin. Endocrinol. Metab. 2013, 98, 398–404. [Google Scholar] [CrossRef] [Green Version]
  11. Morales, E.; Rodriguez, A.; Valvi, D.; Iniguez, C.; Esplugues, A.; Vioque, J.; Marina, L.S.; Jimenez, A.; Espada, M.; Dehli, C.R.; et al. Deficit of vitamin D in pregnancy and growth and overweight in the offspring. Int. J. Obes. 2015, 39, 61–68. [Google Scholar] [CrossRef]
  12. Rodriguez, A.; Garcia-Esteban, R.; Basterretxea, M.; Lertxundi, A.; Rodriguez-Bernal, C.; Iniguez, C.; Rodriguez-Dehli, C.; Tardon, A.; Espada, M.; Sunyer, J.; et al. Associations of maternal circulating 25-hydroxyvitamin D3 concentration with pregnancy and birth outcomes. BJOG 2015, 122, 1695–1704. [Google Scholar] [CrossRef] [Green Version]
  13. Boyle, V.T.; Thorstensen, E.B.; Mourath, D.; Jones, M.B.; McCowan, L.M.; Kenny, L.C.; Baker, P.N. The relationship between 25-hydroxyvitamin D concentration in early pregnancy and pregnancy outcomes in a large, prospective cohort. Br. J. Nutr. 2016, 116, 1409–1415. [Google Scholar] [CrossRef] [Green Version]
  14. Miliku, K.; Vinkhuyzen, A.; Blanken, L.M.; McGrath, J.J.; Eyles, D.W.; Burne, T.H.; Hofman, A.; Tiemeier, H.; Steegers, E.A.; Gaillard, R.; et al. Maternal vitamin D concentrations during pregnancy, fetal growth patterns, and risks of adverse birth outcomes. Am. J. Clin. Nutr. 2016, 103, 1514–1522. [Google Scholar] [CrossRef]
  15. Hauta-Alus, H.H.; Viljakainen, H.T.; Holmlund-Suila, E.M.; Enlund-Cerullo, M.; Rosendahl, J.; Valkama, S.M.; Helve, O.M.; Hytinantti, T.K.; Makitie, O.M.; Andersson, S. Maternal vitamin D status, gestational diabetes and infant birth size. BMC Pregnancy Childbirth 2017, 17, 420. [Google Scholar] [CrossRef]
  16. Francis, E.C.; Hinkle, S.N.; Song, Y.; Rawal, S.; Donnelly, S.R.; Zhu, Y.; Chen, L.; Zhang, C. Longitudinal Maternal Vitamin D Status during Pregnancy Is Associated with Neonatal Anthropometric Measures. Nutrients 2018, 10, 1631. [Google Scholar] [CrossRef] [Green Version]
  17. Wen, J.; Kang, C.; Wang, J.; Cui, X.; Hong, Q.; Wang, X.; Zhu, L.; Xu, P.; Fu, Z.; You, L.; et al. Association of maternal serum 25-hydroxyvitamin D concentrations in second and third trimester with risk of macrosomia. Sci. Rep. 2018, 8, 6169. [Google Scholar] [CrossRef] [Green Version]
  18. Boghossian, N.S.; Koo, W.; Liu, A.; Mumford, S.L.; Tsai, M.Y.; Yeung, E.H. Longitudinal measures of maternal vitamin D and neonatal body composition. Eur. J. Clin. Nutr. 2019, 73, 424–431. [Google Scholar] [CrossRef]
  19. Thompson, W.D.; Tyrrell, J.; Borges, M.C.; Beaumont, R.N.; Knight, B.A.; Wood, A.R.; Ring, S.M.; Hattersley, A.T.; Freathy, R.M.; Lawlor, D.A. Association of maternal circulating 25(OH)D and calcium with birth weight: A mendelian randomisation analysis. PLoS Med. 2019, 16, e1002828. [Google Scholar] [CrossRef] [Green Version]
  20. WHO Scientific Group on the Prevention and Management of Osteoporosis. Prevention and Management of Osteoporosis: Report of a WHO Scientific Group; World Health Organization: Geneva, Switzerland, 2003. [Google Scholar]
  21. Ginde, A.A.; Liu, M.C.; Camargo, C.A., Jr. Demographic differences and trends of vitamin D insufficiency in the US population, 1988–2004. Arch. Intern. Med. 2009, 169, 626–632. [Google Scholar] [CrossRef] [Green Version]
  22. Gutierrez, O.M.; Farwell, W.R.; Kermah, D.; Taylor, E.N. Racial differences in the relationship between vitamin D, bone mineral density, and parathyroid hormone in the National Health and Nutrition Examination Survey. Osteoporos. Int. 2011, 22, 1745–1753. [Google Scholar] [CrossRef] [Green Version]
  23. Mitchell, D.M.; Henao, M.P.; Finkelstein, J.S.; Burnett-Bowie, S.A. Prevalence and predictors of vitamin D deficiency in healthy adults. Endocr. Pract. 2012, 18, 914–923. [Google Scholar] [CrossRef] [Green Version]
  24. Bischoff-Ferrari, H.A.; Dietrich, T.; Orav, E.J.; Dawson-Hughes, B. Positive association between 25-hydroxy vitamin D levels and bone mineral density: A population-based study of younger and older adults. Am. J. Med. 2004, 116, 634–639. [Google Scholar] [CrossRef]
  25. Cauley, J.A.; Lui, L.Y.; Ensrud, K.E.; Zmuda, J.M.; Stone, K.L.; Hochberg, M.C.; Cummings, S.R. Bone mineral density and the risk of incident nonspinal fractures in black and white women. JAMA 2005, 293, 2102–2108. [Google Scholar] [CrossRef]
  26. Hannan, M.T.; Litman, H.J.; Araujo, A.B.; McLennan, C.E.; McLean, R.R.; McKinlay, J.B.; Chen, T.C.; Holick, M.F. Serum 25-hydroxyvitamin D and bone mineral density in a racially and ethnically diverse group of men. J. Clin. Endocrinol. Metab. 2008, 93, 40–46. [Google Scholar] [CrossRef]
  27. Cauley, J.A.; Danielson, M.E.; Boudreau, R.; Barbour, K.E.; Horwitz, M.J.; Bauer, D.C.; Ensrud, K.E.; Manson, J.E.; Wactawski-Wende, J.; Shikany, J.M.; et al. Serum 25-hydroxyvitamin D and clinical fracture risk in a multiethnic cohort of women: The Women’s Health Initiative (WHI). J. Bone Min. Res. 2011, 26, 2378–2388. [Google Scholar] [CrossRef] [Green Version]
  28. Ginsberg, C.; Katz, R.; de Boer, I.H.; Kestenbaum, B.R.; Chonchol, M.; Shlipak, M.G.; Sarnak, M.J.; Hoofnagle, A.N.; Rifkin, D.E.; Garimella, P.S.; et al. The 24,25 to 25-hydroxyvitamin D ratio and fracture risk in older adults: The cardiovascular health study. Bone 2018, 107, 124–130. [Google Scholar] [CrossRef]
  29. Shah, I.; Petroczi, A.; Naughton, D.P. Exploring the role of vitamin D in type 1 diabetes, rheumatoid arthritis, and Alzheimer disease: New insights from accurate analysis of 10 forms. J. Clin. Endocrinol. Metab. 2014, 99, 808–816. [Google Scholar] [CrossRef] [Green Version]
  30. Karras, S.N.; Shah, I.; Petroczi, A.; Goulis, D.G.; Bili, H.; Papadopoulou, F.; Harizopoulou, V.; Tarlatzis, B.C.; Naughton, D.P. An observational study reveals that neonatal vitamin D is primarily determined by maternal contributions: Implications of a new assay on the roles of vitamin D forms. Nutr. J. 2013, 12, 77. [Google Scholar] [CrossRef] [Green Version]
  31. Ahmed, L.H.M.; Butler, A.E.; Dargham, S.R.; Latif, A.; Chidiac, O.M.; Atkin, S.L.; Abi Khalil, C. Vitamin D3 metabolite ratio as an indicator of vitamin D status and its association with diabetes complications. BMC Endocr. Disord. 2020, 20, 161. [Google Scholar] [CrossRef]
  32. Kanatani, K.T.; Nakayama, T.; Adachi, Y.; Hamazaki, K.; Onishi, K.; Konishi, Y.; Kawanishi, Y.; Go, T.; Sato, K.; Kurozawa, Y.; et al. High frequency of vitamin D deficiency in current pregnant Japanese women associated with UV avoidance and hypo-vitamin D diet. PLoS ONE 2019, 14, e0213264. [Google Scholar] [CrossRef]
  33. Kanatani, K.T.; Adachi, Y.; Hamazaki, K.; Onishi, K.; Go, T.; Hirabayashi, K.; Watanabe, M.; Sato, K.; Kurozawa, Y.; Inadera, H.; et al. Association between vitamin D deficiency and allergic symptom in pregnant women. PLoS ONE 2019, 14, e0214797. [Google Scholar] [CrossRef]
  34. Kawamoto, T.; Nitta, H.; Murata, K.; Toda, E.; Tsukamoto, N.; Hasegawa, M.; Yamagata, Z.; Kayama, F.; Kishi, R.; Ohya, Y.; et al. Rationale and study design of the Japan environment and children’s study (JECS). BMC Public Health 2014, 14, 25. [Google Scholar] [CrossRef] [Green Version]
  35. Satoh, M.; Ishige, T.; Ogawa, S.; Nishimura, M.; Matsushita, K.; Higashi, T.; Nomura, F. Development and validation of the simultaneous measurement of four vitamin D metabolites in serum by LC-MS/MS for clinical laboratory applications. Anal. Bioanal. Chem. 2016, 408, 7617–7627. [Google Scholar] [CrossRef]
  36. Phinney, K.W.; Bedner, M.; Tai, S.S.; Vamathevan, V.V.; Sander, L.C.; Sharpless, K.E.; Wise, S.A.; Yen, J.H.; Schleicher, R.L.; Chaudhary-Webb, M.; et al. Development and certification of a standard reference material for vitamin D metabolites in human serum. Anal. Chem. 2012, 84, 956–962. [Google Scholar] [CrossRef] [Green Version]
  37. Yamamoto, M.; Sakurai, K.; Eguchi, A.; Yamazaki, S.; Nakayama, S.F.; Isobe, T.; Takeuchi, A.; Sato, T.; Hata, A.; Mori, C.; et al. Association between blood manganese level during pregnancy and birth size: The Japan environment and children’s study (JECS). Environ. Res. 2019, 172, 117–126. [Google Scholar] [CrossRef]
  38. Kobayashi, S.; Kishi, R.; Saijo, Y.; Ito, Y.; Oba, K.; Araki, A.; Miyashita, C.; Itoh, S.; Minatoya, M.; Yamazaki, K.; et al. Association of blood mercury levels during pregnancy with infant birth size by blood selenium levels in the Japan Environment and Children’s Study: A prospective birth cohort. Environ. Int. 2019, 125, 418–429. [Google Scholar] [CrossRef]
  39. Farrant, H.J.; Krishnaveni, G.V.; Hill, J.C.; Boucher, B.J.; Fisher, D.J.; Noonan, K.; Osmond, C.; Veena, S.R.; Fall, C.H. Vitamin D insufficiency is common in Indian mothers but is not associated with gestational diabetes or variation in newborn size. Eur. J. Clin. Nutr. 2009, 63, 646–652. [Google Scholar] [CrossRef] [Green Version]
  40. Prentice, A.; Jarjou, L.M.; Goldberg, G.R.; Bennett, J.; Cole, T.J.; Schoenmakers, I. Maternal plasma 25-hydroxyvitamin D concentration and birthweight, growth and bone mineral accretion of Gambian infants. Acta Paediatr. 2009, 98, 1360–1362. [Google Scholar] [CrossRef] [Green Version]
  41. Ginsberg, C.; Hoofnagle, A.N.; Katz, R.; Hughes-Austin, J.; Miller, L.M.; Becker, J.O.; Kritchevsky, S.B.; Shlipak, M.G.; Sarnak, M.J.; Ix, J.H. The Vitamin D Metabolite Ratio Is Associated With Changes in Bone Density and Fracture Risk in Older Adults. J. Bone Min. Res. 2021, 36, 2343–2350. [Google Scholar] [CrossRef]
  42. Armbrecht, H.J.; Hodam, T.L.; Boltz, M.A.; Partridge, N.C.; Brown, A.J.; Kumar, V.B. Induction of the vitamin D 24-hydroxylase (CYP24) by 1,25-dihydroxyvitamin D3 is regulated by parathyroid hormone in UMR106 osteoblastic cells. Endocrinology 1998, 139, 3375–3381. [Google Scholar] [CrossRef]
  43. Perwad, F.; Azam, N.; Zhang, M.Y.; Yamashita, T.; Tenenhouse, H.S.; Portale, A.A. Dietary and serum phosphorus regulate fibroblast growth factor 23 expression and 1,25-dihydroxyvitamin D metabolism in mice. Endocrinology 2005, 146, 5358–5364. [Google Scholar] [CrossRef] [Green Version]
  44. Allgrove, J.; Adami, S.; Manning, R.M.; O’Riordan, J.L. Cytochemical bioassay of parathyroid hormone in maternal and cord blood. Arch. Dis. Child. 1985, 60, 110–115. [Google Scholar] [CrossRef] [Green Version]
  45. Papantoniou, N.E.; Papapetrou, P.D.; Antsaklis, A.J.; Kontoleon, P.E.; Mesogitis, S.A.; Aravantinos, D. Circulating levels of immunoreactive parathyroid hormone-related protein and intact parathyroid hormone in human fetuses and newborns. Eur. J. Endocrinol. 1996, 134, 437–442. [Google Scholar] [CrossRef]
  46. Takaiwa, M.; Aya, K.; Miyai, T.; Hasegawa, K.; Yokoyama, M.; Kondo, Y.; Kodani, N.; Seino, Y.; Tanaka, H.; Morishima, T. Fibroblast growth factor 23 concentrations in healthy term infants during the early postpartum period. Bone 2010, 47, 256–262. [Google Scholar] [CrossRef] [Green Version]
  47. Singh, R.J.; Taylor, R.L.; Reddy, G.S.; Grebe, S.K. C-3 epimers can account for a significant proportion of total circulating 25-hydroxyvitamin D in infants, complicating accurate measurement and interpretation of vitamin D status. J. Clin. Endocrinol. Metab. 2006, 91, 3055–3061. [Google Scholar] [CrossRef] [Green Version]
  48. Schleicher, R.L.; Encisco, S.E.; Chaudhary-Webb, M.; Paliakov, E.; McCoy, L.F.; Pfeiffer, C.M. Isotope dilution ultra performance liquid chromatography-tandem mass spectrometry method for simultaneous measurement of 25-hydroxyvitamin D2, 25-hydroxyvitamin D3 and 3-epi-25-hydroxyvitamin D3 in human serum. Clin. Chim. Acta 2011, 412, 1594–1599. [Google Scholar] [CrossRef]
  49. van den Ouweland, J.M.; Beijers, A.M.; van Daal, H.; Elisen, M.G.; Steen, G.; Wielders, J.P. Evaluation of 3-epi-25-hydroxyvitamin D3 cross-reactivity in the Roche Elecsys Vitamin D Total protein binding assay. Clin. Chem. Lab. Med. 2014, 52, 373–380. [Google Scholar] [CrossRef]
  50. Butler, A.E.; Dargham, S.R.; Latif, A.; Mokhtar, H.R.; Robay, A.; Chidiac, O.M.; Jayyousi, A.; Al Suwaidi, J.; Crystal, R.G.; Abi Khalil, C.; et al. Association of vitamin D3 and its metabolites in patients with and without type 2 diabetes and their relationship to diabetes complications. Adv. Chronic. Dis. 2020, 11, 2040622320924159. [Google Scholar] [CrossRef]
  51. Yetley, E.A.; Pfeiffer, C.M.; Schleicher, R.L.; Phinney, K.W.; Lacher, D.A.; Christakos, S.; Eckfeldt, J.H.; Fleet, J.C.; Howard, G.; Hoofnagle, A.N.; et al. NHANES monitoring of serum 25-hydroxyvitamin D: A roundtable summary. J. Nutr. 2010, 140, 2030S–2045S. [Google Scholar] [CrossRef] [Green Version]
  52. Tuckey, R.C.; Cheng, C.Y.S.; Slominski, A.T. The serum vitamin D metabolome: What we know and what is still to discover. J. Steroid Biochem. Mol. Biol. 2019, 186, 4–21. [Google Scholar] [CrossRef]
  53. Kamao, M.; Tatematsu, S.; Hatakeyama, S.; Sakaki, T.; Sawada, N.; Inouye, K.; Ozono, K.; Kubodera, N.; Reddy, G.S.; Okano, T. C-3 epimerization of vitamin D3 metabolites and further metabolism of C-3 epimers: 25-hydroxyvitamin D3 is metabolized to 3-epi-25-hydroxyvitamin D3 and subsequently metabolized through C-1alpha or C-24 hydroxylation. J. Biol. Chem. 2004, 279, 15897–15907. [Google Scholar] [CrossRef] [Green Version]
Nutrients 14 02201 g001 550
Figure 1. The flow chart of the participants included in this study.
Figure 1. The flow chart of the participants included in this study.
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Nutrients 14 02201 g002 550
Figure 2. Scatter plots of VMR1 and 25(OH)D (a) and VMR2 and 25(OH)D (b). Scatter plots show that VMR1 has a strong correlation with 25(OH)D3 (r = 0.732; p = 2.20 × 10−16), and VMR2 has a weak correlation with 25(OH)D (r = 0.304; p = 8.76 × 10−5). 25(OH)D, 25-hydroxyvitamin D; VMR, vitamin D metabolite ratio.
Figure 2. Scatter plots of VMR1 and 25(OH)D (a) and VMR2 and 25(OH)D (b). Scatter plots show that VMR1 has a strong correlation with 25(OH)D3 (r = 0.732; p = 2.20 × 10−16), and VMR2 has a weak correlation with 25(OH)D (r = 0.304; p = 8.76 × 10−5). 25(OH)D, 25-hydroxyvitamin D; VMR, vitamin D metabolite ratio.
Nutrients 14 02201 g002
Table
Table 1. The characteristics of the mothers included in this study.
Table 1. The characteristics of the mothers included in this study.
Characteristics All
(N = 297)
N%
Age at delivery (years), mean (SD) 31.3 (4.8)
<25248.1
25–<308528.6
30–<3510836.4
35≤8026.9
Education (years)
<1082.7
10–<1319967.0
13–<178829.6
17≤20.7
Parity
010736.0
1≤19064.0
BMI before pregnancy (kg/m2), mean (SD) 21.5 (3.3)
<18.54314.5
18.5–<2522174.4
25≤3311.1
Annual household income (million Japanese Yen)
<2155.1
2–<49732.7
4–<610736.0
6–<84816.2
8–<10196.4
10≤113.7
Smoking habits
Never15953.5
Quit before pregnancy9331.3
Smoking early pregnancy4515.2
Alcohol consumption
Never11137.4
Quit before pregnancy5719.2
Drink early pregnancy12943.4
Pregnancy-induced hypertension 93.0
Gestational diabetes mellitus 103.4
Diabetes Mellitus 103.4
Vitamin D insufficiency (25(OH)D < 20 ng/mL) 25385.2
BMI, body mass index; 25(OH)D, 25 hydroxyvitamin D; SD, standard deviation.
Table
Table 2. The characteristics of the infants included in this study.
Table 2. The characteristics of the infants included in this study.
All
(N = 297)
N%
Sex
Male14548.3
Female15250.7
Mode of delivery
Vaginal23377.7
Cesarian6421.3
Birth weight (g), mean (SD)3028.5 (416.0)
Birth length(cm), mean (SD)48.6 (2.1)
Birth head circumference(cm), mean (SD)33.2 (1.4)
Birth chest circumference(cm), mean (SD)31.7 (1.7)
Gestational week, mean (SD)39.2 (1.5)
SD, standard deviation.
Table
Table 3. Levels of Vitamin D metabolites in maternal blood.
Table 3. Levels of Vitamin D metabolites in maternal blood.
MeanSDMinimum25 PercentilesMedian75 PercentilesMaximum
25(OH)D (ng/mL)15.82 7.105.31 10.31 14.63 19.27 44.45
25(OH)D2(ng/mL)0.51 0.520.14 0.34 0.43 0.56 8.18
25(OH)D3 (ng/mL)15.31 7.094.97 9.89 13.82 18.42 44.05
24,25(OH)2D3 (ng/mL)0.66 0.560.08 0.27 0.46 0.85 4.42
3-epi-25(OH)D3 (ng/mL)0.79 0460.17 0.48 0.66 0.96 2.76
VMR1 (×10−2)3.66 1.501.37 2.49 3.46 4.59 10.38
VMR2 (×10−2)4.84 1.082.22 4.20 4.67 5.34 9.65
25(OH)D, 25-hydroxyvitamin D; 25(OH)D2, 25-hydroxyvitamin D2; 25(OH)D3, 25-hydroxyvitamin D3; 24,25(OH)2D3, 24,25-dihyroxyvitamin D3; 3-epi-25(OH)D3, 3-epi-25-hydroxyvitamin D3; VMR, vitamin D metabolite ratio; SD, standard deviation.
Table
Table 4. Estimated differences (and 95% CIs) in birth anthropometrics per 1 ng/mL increase in vitamin D metabolites or 1-unit increase in VMR.
Table 4. Estimated differences (and 95% CIs) in birth anthropometrics per 1 ng/mL increase in vitamin D metabolites or 1-unit increase in VMR.
Birth Weight (g)
Model 25(OH)D 25(OH)D2 25(OH)D3 24,25(OH)2D3 3-epi-25(OH)D3 VMR1VMR2
Unadjusted β0.28 66.08 −0.08 −8.63 −49.42 −155.80 −5907.30
(95% CI)(−6.44, 6.99)(−25.49, 157.65)(−6.80, 6.65)(−93.07, 75.82)(−153.68, 54.85)(−3357.23, 3045.53)(−10,285.77, −1528.86)
p-value0.9360.1570.9820.8410.3520.9240.008
Adjustedβ−0.2134.21−0.39−3.81−46.58−113.99−4937.35
(95% CI) (−5.61, 5.20) (−39.89, 108.31) (−5.80, 5.02) (−71.79, 64.17) (−130.41, 37.26) (−2693.21, 2465.23)(−8455.06, −1419.64)
p-value0.9400.3640.8880.9120.2750.9310.006
Birth length (cm)
Model 25(OH)D 25(OH)D2 25(OH)D3 24,25(OH)2D3 3-epi-25(OH)D3 VMR1VMR2
Unadjusted β0.01 0.24 0.01 0.09 −0.11 3.63 −23.24
(95% CI) (−0.03, 0.04) (−0.23, 0.70) (−0.03, 0.04) (−0.34, 0.52) (−153.68, 54.85) (−12.71, 19.97) (−45.71, −0.78)
p-value0.6210.3210.6720.6810.6970.6620.043
Adjustedβ0.00 0.040.00 0.09−0.133.87−19.48
(95% CI) (−0.02, 0.03) (−0.34, 0.42) (−0.02, 0.03) (−0.26, 0.43) (−0.56, 0.29) (−9.18, 16.92) (−37.39, −1.58)
p-value0.8080.8340.820 0.6140.5330.560 0.033
Birth head circumference (cm)
Model 25(OH)D 25(OH)D2 25(OH)D3 24,25(OH)2D3 3-epi-25(OH)D3 VMR1VMR2
Unadjusted β−0.01 0.13 −0.01 −0.07 −0.29 −3.38 −20.66
(95% CI) (−0.03, 0.01) (−0.17, 0.44) (−0.03, 0.01) (−0.35, 0.21) (−0.63, 0.06) (−13.97, 7.21)(−35.14, −6.19)
p-value0.3690.395 0.3350.6140.100 0.530 0.005
Adjustedβ−0.010.05−0.01−0.05−0.27−2.64−18.75
(95% CI) (−0.03, 0.01) (−0.25, 0.34) (−0.03, 0.01) (−0.32, 0.22) (−0.60, 0.06) (−12.86, 7.58) (−32.71, −4.79)
p-value0.3480.7420.3350.7240.1090.612 0.009
Birth chest circumference (cm)
Model 25(OH)D 25(OH)D2 25(OH)D3 24,25(OH)2D3 3-epi-25(OH)D3 VMR1VMR2
Unadjusted β0.00 0.36 −0.01 −0.11 −0.30 −4.23 −26.55
(95% CI) (−0.03, 0.02) (−0.01, 0.73) (−0.03, 0.02) (−0.46, 0.23) (−0.73, 0.12) (−17.31, 8.85)(−44.41, −8.69)
p-value0.7490.060 0.6470.5130.1640.5250.004
Adjustedβ−0.010.22−0.01−0.10 −0.30 −4.21−23.66
(95% CI) (−0.03, 0.02) (−0.10, 0.53) (−0.03, 0.01) (−0.38, 0.19) (−0.66, 0.05) (−15.08, 6.66) (−38.44, −8.87)
p-value0.5630.1740.4980.5020.090 0.4450.002
Models were adjusted for maternal age, body mass index (pre), alcohol habit, smoking habit, household income, education, gestational age, sex, and parity. VMR, vitamin D metabolite ratio. p-values marked with bold indicate statistically significant p-values.
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Takatani, T.; Kunii, Y.; Satoh, M.; Eguchi, A.; Yamamoto, M.; Sakurai, K.; Takatani, R.; Nomura, F.; Shimojo, N.; Mori, C. Vitamin D Metabolite Ratio in Pregnant Women with Low Blood Vitamin D Concentrations Is Associated with Neonatal Anthropometric Data. Nutrients 2022, 14, 2201. https://doi.org/10.3390/nu14112201

AMA Style

Takatani T, Kunii Y, Satoh M, Eguchi A, Yamamoto M, Sakurai K, Takatani R, Nomura F, Shimojo N, Mori C. Vitamin D Metabolite Ratio in Pregnant Women with Low Blood Vitamin D Concentrations Is Associated with Neonatal Anthropometric Data. Nutrients. 2022; 14(11):2201. https://doi.org/10.3390/nu14112201

Chicago/Turabian Style

Takatani, Tomozumi, Yuzuka Kunii, Mamoru Satoh, Akifumi Eguchi, Midori Yamamoto, Kenichi Sakurai, Rieko Takatani, Fumio Nomura, Naoki Shimojo, and Chisato Mori. 2022. "Vitamin D Metabolite Ratio in Pregnant Women with Low Blood Vitamin D Concentrations Is Associated with Neonatal Anthropometric Data" Nutrients 14, no. 11: 2201. https://doi.org/10.3390/nu14112201

APA Style

Takatani, T., Kunii, Y., Satoh, M., Eguchi, A., Yamamoto, M., Sakurai, K., Takatani, R., Nomura, F., Shimojo, N., & Mori, C. (2022). Vitamin D Metabolite Ratio in Pregnant Women with Low Blood Vitamin D Concentrations Is Associated with Neonatal Anthropometric Data. Nutrients, 14(11), 2201. https://doi.org/10.3390/nu14112201

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