The relationship between maternal iron status and risk of congenital heart defects: a case-control study

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A study on animals showed a link between maternal iron deficiency and congenital heart defects in mice, but this connection in humans is not yet clear. Our goal in this study was to assess the iron levels in mothers and infants with CHDs and to explore the potential relationship between maternal iron status and CHDs. Methods We conducted a case-control study in Damascus, Syria, including 70 cases and 30 controls. The study involved mothers whose infants were aged from 1 day to 1 year. We interviewed eligible mothers to gather information about their pregnancies and collected peripheral blood from both the mothers and their infants to analyze iron-related biomarkers. We used multinomial logistic regression to estimate the odds ratio (with 95% confidence intervals) for maternal iron status with CHDs. Results The iron-related biomarkers (serum ferritin (SF), serum iron (Fe), and transferrin saturation (TSAT) showed lower levels, while total iron binding capacity (TIBC) was higher among mothers of CHD infants compared to the control group (p-value < 0.05). Additionally, mothers of CHD infants were at a higher risk of having iron deficiency (OR=2.91, 95% CL: 1.143-7.418) compared to the control group. Conclusions Mothers of CHD infants exhibited lower levels of SF, Fe, and TSAT, and higher TIBC compared to the control group. Furthermore, the CHD mothers were more likely to have iron deficiency compared to the control group. maternal iron status iron deficiency pregnancy congenital heart defects Background Congenital heart defects (CHDs) are structural abnormalities of the heart or the great vessels of the heart. CHD develops during early fetal development and is presented at birth. CHD is considered the most common birth defect, accounting for about a third of all congenital anomalies [1]. The prevalence of CHD is between 8 and 12 cases of live births worldwide [2]. CHD is a major health problem as it is associated with lifelong illness and complication in infants with birth defects, and is the leading cause of death in children with congenital defects [1, 3]. The etiology of CHD remains elusive, with nearly 20% of CHD cases being attributed to well-known chromosomal or genetic disorders. Thus, the majority of CHD cases are thought to be multifactorial, and both genetic and environmental factors have contributed to the pathogenesis of the disease [4, 5]. Environmental risk factors, which affect pregnant women during the critical period of embryonic heart development (3w-8w), may lead to cardiac defects. These environmental risk factors include maternal diseases, teratogen exposure, and nutrient deficiencies [5, 6]. Iron deficiency (ID) is the most prevalent nutritional deficiency around the world, and it represents the most common contributor to anemia. Iron deficiency anemia (IDA) affects about 5 0 % of pregnant women globally [27]. Pregnancy is associated with increased iron demand due to increased blood volume in pregnant women and the growth of the fetus and placenta. Thus, pregnant women are at a high risk for developing iron deficiency [7]. Animal studies have shown that iron deficiency during pregnancy affects the growth and development of fetal organs such as the heart [8]. One animal study on mice has demonstrated that maternal iron deficiency disrupts embryonic heart development [9]. However, clinical studies on the relationships between maternal iron status and CHD are limited. There was one clinical study suggesting a relationship between low iron intake during pregnancy and the risk of CHD [10]. In addition, another study found that iron levels were high among mothers of CHD infants [15]. This study aimed to evaluate the iron status among mothers of CHD infants and their infants. Moreover, to verify the relationship between maternal iron status and the risk of congenital heart defects. Methods Study design and participants We performed a case-control study in two hospitals in Damascus City, Syria the Pediatrics ’ University Hospital, and the Heart Surgery University Hospital from November 2022 to November 2023. Cases and controls were selected from mothers whose infants aged from 1 day to 1 year. The case group included 70 mothers whose infants have an isolated CHD and their infants (n=70), whereas the control group included 30 mothers whose infants have no congenital abnormalities and their infants (n=30). Mothers in the two groups were excluded if they had any of the following: Diabetes mellitus, blood hypertension, hyperthyroidism, congenital heart defects, hemolytic anemia, blood transfusion in the last six months, infections and inflammatory condition, taking birth control tablets, taking iron supplements during pregnancy and after delivery, and severe bleeding during pregnancy and after delivery. Mothers of both groups were excluded if their infants had any of the following: Gene disorders or chromosomal abnormalities, siblings or first-degree relatives diagnosed with CHD, infections and inflammation, hemolytic anemia, blood transfusion, taking iron supplements. Ultimately, 70 cases and 30 controls were selected based on the inclusion criteria. However, it should be noted that we intended for the mothers in both groups to be from a similar socioeconomic background, to minimize the effect of dietary habits on iron levels. Ethics This study was approved by the Biomedical Research Ethical Committee (BMREC) at Damascus University, and the reference number is PH-290122-30. The study was conducted according to the guidelines of the Declaration of Helsinki, and all mothers signed a written informed consent form. Covariables assessment We interviewed mothers using a standardized questionnaire before collecting samples to verify their alignment with the study criteria and gather important information. The study information consisted of socio-demographic characteristics (maternal age, gestational age, type of delivery, birth weight of infant, residence, education, and income) and maternal health factors during pregnancy (bleeding, illnesses, medication use, and supplements use). Biomarkers measurement We collected peripheral venous blood from each mother and each infant among the case and control groups. We collected blood into two tubes, an EDTA tube for the assessment of complete blood count (CBC), and a dry tube to obtain serum for the assessment of iron-related biomarkers. The iron-related biomarkers include serum ferritin (SF), serum iron (Fe), unsaturated iron binding capacity (UIBC), total iron binding capacity (TIBC), and transferrin saturation (TSAT). We used a sandwich chemical lumminimmune assay (sandwich CLIA) (Mindray, China) for measuring the concentrations of SF. We used a colorimetric assay (Biomajesty, Germany) for measuring serum iron and unsaturated iron binding capacity (UIBC). Then, we calculated TIBC by summing serum iron and UIBC and calculated TSAT by the formula: [TSAT = (Fe/TIBC) × 100]. According to WHO criteria, we determined absolute iron deficiency in mother groups at a ferritin concentration < 15 ng/ml, and iron deficiency anemia at a ferritin concentration < 15 ng/ml and hemoglobin level < 12 g/dl [11, 12]. Statistical analysis Statistical analysis of data was performed by using the SPSS version 24. We applied the Chi-square (x2) test to compare categorical variables between the two groups. Continuous variables with normal and non-normal distributions were compared between the two groups using the Student's t-test and Mann-Whitney U-test, respectively. We performed Multinominal logistic regression to estimate the odds ratio (OR) with corresponding 95% confidence intervals for total CHDs associated with maternal iron status. P-value ≤0.05 was considered statistically significant. Results General characteristics of the study sample The general demographic characteristics of the study participants are shown in Table 1. The study sample consisted of 70 mothers of CHD infants and 70 CHD infants in the case group, and 30 control mothers and 30 control infants were in the control group. There were no significant differences in maternal age, gestational age, neonatal gender, type of delivery, residence, education, and income between the two groups. The CHD infants had lower birth weights compared to the control infants (2.54kg+/-0.61 vs. 2.97kg +/-0.51). The CHD types among the case groups are shown in Table 2. Approximately two-thirds of CHD infants had cyanotic CHD (64.28%) with multiple lesion CHD being the most common type (31.42%). Iron biomarkers in mothers and infants Table 3 shows the iron biomarkers of mothers and infants in the two groups. Compared to the mothers in the control group, case mothers had lower SF (20.01 vs. 26.97ng/ml), Fe (57.86 vs. 76.03µg/dl), and TSAT (13.25 vs. 19.57%). Maternal TIBC were higher (450.53 vs. 407.77 µg/dl) among case mothers than the control mothers. We observed no significant differences in hemoglobin levels, MCV (mean corpuscular volume), MCH (mean corpuscular hemoglobin), MCHC (mean corpuscular hemoglobin concentration), and RDW (red cell distribution width) between the two mothers groups. Regarding the two infants groups, CHD infants had higher hemoglobin levels (12.23vs11.19g/dl) and RDW (16.03vs13.70%) and lower MCHC (31.83vs 34.04g/dl) than the control infants. No significant differences were found in SF, Fe, TSAT, and TIBC between the two groups. Maternal Iron Deficiency and CHD Table 4 shows that CHD mothers (OR=4.01, 95% CL: 1.08-15.5) were more likely to have absolute iron deficiency compared to the control mothers, while there was no difference in the case of iron deficiency anemia (P value=0.172). We found that the mothers of CHD infants (OR=2.91, 95% CL: 1.143-7.418) were more likely to have iron deficiency with or without anemia than the mothers of non- CHD infants. Discussion The cause of most congenital heart defects (CHDs) cases is unclear, with nearly 20% of cases being related to a specific genetic cause [5]. Recent studies suggested a relationship between environmental risk factors and CHD, including maternal nutrition deficiency during the first trimester of gestation [6]. Nutritional deficiencies have been associated with various birth defects, and most of these nutritional deficiencies could be modified [13, 14]. Iron deficiency is the most common nutrition deficiency globally, particularly among pregnant women [7]. A recent animal study revealed a potential association between maternal iron deficiency and the development of CHD in the fetus [9]. However, the clinical studies exploring this relationship are limited and controversial. A previous case-control study showed that mothers whose infants have CHD had lower iron status during pregnancy compared to control mothers [10], while another study demonstrated a correlation between high maternal iron status and the risk of having a newborn with CHD [15]. Our study revealed that the mothers whose infants have CHD had lower levels of SF, Fe, TSAT, and higher TIBC compared to the mothers in the control group. The results also suggested that the mothers of CHD infants are more likely to have iron deficiency (OR=2.91, 95% CL: 1.143-7.418). Low ferritin levels without compensation from iron supplements may indicate a significant iron deficiency. Therefore, iron deficiency in CHD mothers after delivery may be indicative of iron deficiency during pregnancy [16]. Iron is crucial in embryogenesis, and iron deficiency during early pregnancy may affect heart development through multiple possible mechanisms. First, the myocardium is a highly metabolic tissue, and cardiogenesis involves controlled, energy-dependent processes, including the proliferation, differentiation, and maturation of cardiomyocytes [17, 18]. The energy needed for cardiogenesis is primarily obtained from mitochondrial oxidative phosphorylation, which relies on iron-dependent enzyme complexes [17, 19]. Iron is a crucial component in mitochondria, as Fe-protoporphyrin, Fe-S clusters, and Rieske center are involved in the mitochondrial complexes that mediate electron transportation and energy generation [19]. Therefore, iron deficiency (ID) can reduce energy production and negatively affect cardiomyocyte differentiation and maturation, leading to congenital heart disease (CHD) [20, 21]. Second, ID has been associated with disruption of mitochondrial biogenesis, changes in mitochondrial structure, increased release of cytochrome c, and induction of apoptosis. Therefore, ID may play a role in mitochondria dysfunction [22]. This could explain previous studies suggesting that mitochondrial dysfunction and metabolic disturbance contribute to the development of CHD [23, 24]. Third, ID may reduce the activity of the iron-dependent enzyme CYP26, which could result in increased retinoic acid signaling in the second heart field. This could, in turn, activate the cardiac transcription factor GATA4 and cause premature differentiation of a group of cardiac progenitor cells, leading to CHD [9]. Furthermore, ID can lead to reduced activity of another iron-dependent enzyme, the endothelial nitric oxide synthase (eNOS) [25]. The restriction of (eNOS) activity may negatively affect the expression of cardiac-specific genes, impeding the differentiation of cardiac progenitor cells and thus the development of CHD [26]. Iron deficiency seems to be (at least partly) the missing part, that links those metabolic abnormalities previously found in the mentioned papers. This study provides evidence of a correlation between maternal iron deficiency and the risk of congenital heart disease. However, due to the delayed diagnosis of CHD cases until after birth, we collected maternal blood post-delivery, which could impact the assessment of iron levels in our study. Conclusion Our study indicates that mothers of infants with congenital heart disease (CHD) have lower iron status compared to the control mothers. Additionally, the study revealed that mothers of CHD infants are more likely to have iron deficiency. It is essential to conduct prospective clinical studies with a substantial number of pregnant women to confirm our results and gain a deeper understanding of the underlying mechanism. Abbreviations CHD (congenital heart defect) SF (serum ferritin) Fe (serum iron) TSAT (transferrin saturation) TIBC (total iron binding capacity) UIBC (unsaturated iron binding capacity) IDA (iron deficiency anemia) ID (iron deficiency) CBC (complete blood count) CLIA (chemical lumminimmune assay) MCV (mean corpuscular volume) MCH (mean corpuscular hemoglobin) MCHC (mean corpuscular hemoglobin concentration) RDW (red cell distribution width) Declarations Ethics approval and consent to participate This study was approved by the Biomedical Research Ethical Committee (BMREC) at Damascus University, and the reference number is PH-290122-30. The study was conducted according to the guidelines of the Declaration of Helsinki, and all mothers signed a written informed consent form. Consent for publication Not applicable. Availability of data and materials All materials and all data generated during this study are included in this article. Competing interests The authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contribution RQ collected the samples and analyzed the data. RA designed the study and revised it. RQ and RA both interpreted the results, wrote, and drafted the manuscript. All authors read and approved the final manuscript. Acknowledgment Not applicable. Authors ’ information RQ, master student, Department of Biochemistry and Microbiology, Faculty of Pharmacy, Damascus University, Damascus, Syria. RA, professor of Clinical Biochemistry, Department of Biochemistry and Microbiology, Faculty of Pharmacy, Damascus University, Damascus, Syria. References Lastivka IV, Pishak VP, Ryznychuk МО, Khmara ТV. Risk factor analysis for congenital heart defects in children. Regulatory Mechanisms in Biosystems. 2020;11(4):524-30. Wu W, He J, Shao X. Incidence and mortality trend of congenital heart disease at the global, regional, and national level, 1990–2017. Medicine. 2020 Jun 5;99(23):e20593. CDC.CDC-data and stat in congenital heart disease. Available from https://www.cdc.gov/ncbddd/heartdefects/data.html#:~:text=CHDs%20affect%20nearly%201%25%20of,year%20in% 20the%20United%20States.&text=The% 20prevalence%20(the%20number%20of,other %20types%20has%20remained%20stable. Accessed on 1/3/2022. Suluba E, Shuwei L, Xia Q, Mwanga A. Congenital heart diseases: genetics, non-inherited risk factors, and signaling pathways. Egyptian Journal of Medical Human Genetics. 2020 Feb 28;21(1). Peyvandi S, Baer RJ, Chambers CD, et al. Environmental and socioeconomic factors influence the live‐born incidence of congenital heart disease: a population‐based study in California. Journal of the American Heart Association. 2020 Apr 21;9(8):e015255. Kalisch-Smith JI, Ved N, Sparrow DB. Environmental Risk Factors for Congenital Heart Disease. 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Available from: https://www.who.int/docs/default-source/micronutrients/ferritin-guideline/ferritin-guidelines-brochure.pdf?sfvrsn=76a71b5a_4.Accessed on 21/5/2022. WHO. Guideline on haemoglobin cutoffs to define anaemia in individuals and populations. Available from: https://iris.who.int/bitstream/handle/10665/376196/9789240088542-eng.pdf?sequence=1. Accessed on 20/5/2022. Ibrahim SA, Al-Halim OAFA, Samy MA, Mohamadin AM. Maternal nutritional status and the risk of birth defects among Saudi women. Nutrafoods. 2013 Sep;12(3):81–8. Setright R. The role of nutritional and environmental health in'preventing birth defects. Journal of the Australian Traditional-Medicine Society. 2018 Sep;24(3):155-60. Wang M, Tian Y, Yu P, et al. Association between congenital heart defects and maternal manganese and iron concentrations: a case–control study in China. Environmental science and pollution research international. 2021 Dec 4;29(18):26950–9. Al-Naseem A, Sallam A, Choudhury S, Thachil J. Iron deficiency without anaemia: a diagnosis that matters. Clinical Medicine. 2021 Mar 1;21(2):107–13. Pohjoismäki JL, Goffart S. The role of mitochondria in cardiac development and protection. Free Radical Biology and Medicine. 2017 May 1;106:345-54. Zhao Q, Sun Q, Zhou L, Liu K, Jiao K. Complex regulation of mitochondrial function during cardiac development. Journal of the American Heart Association. 2019 Jul 2;8(13):e012731. Zhang H, Zhabyeyev P, Wang S, Oudit GY. Role of iron metabolism in heart failure: From iron deficiency to iron overload. Biochimica et Biophysica Acta (BBA)-Molecular Basis of Disease. 2019 Jul 1;1865(7):1925-37. Kasahara A, Cipolat S, Chen Y, Dorn GW, Scorrano L. Mitochondrial fusion directs cardiomyocyte differentiation via calcineurin and Notch signaling. Science. 2013 Nov 8;342(6159):734-7. Paul BT, Manz DH, Torti FM, Torti SV. Mitochondria and Iron: current questions. Expert Review of Hematology. 2016 Dec 12;10(1):65–79. Alnuwaysir RI, Hoes MF, van Veldhuisen DJ, van der Meer P, Grote Beverborg N. Iron deficiency in heart failure: mechanisms and pathophysiology. Journal of clinical medicine. 2021 Dec 27;11(1):125. Alsayed R, Quobaili FA, Srour S, Geisel J, Obeid R. Elevated dimethylglycine in blood of children with congenital heart defects and their mothers. Metabolism. 2013 Aug 1;62(8):1074-80. Xu X, Lin JH, Bais AS, et al. Mitochondrial respiration defects in single-ventricle congenital heart disease. Frontiers in Cardiovascular Medicine. 2021 Sep 23;8:734388. Corradi F, Masini G, Bucciarelli T, De Caterina R. Iron deficiency in myocardial ischaemia: molecular mechanisms and therapeutic perspectives. Cardiovascular Research. 2023 Oct;119(14):2405-20 Engineer A, Saiyin T, Greco ER, Feng Q. Say NO to ROS: Their roles in embryonic heart development and pathogenesis of congenital heart defects in maternal diabetes. Antioxidants. 2019 Oct 1;8(10):436. Benson AE, Shatzel JJ, Ryan KS, Hedges MA, et al. The incidence, complications, and treatment of iron deficiency in pregnancy. European Journal of Haematology. 2022 Oct 4;109(6). Tables Table1. General characteristics of the study participants a . Socio-demographic characteristics of mothers group, n (%) Case(N=70) Control(N=30) P value Gestational age (weeks) 0.359 < 37 (preterm birth) 12(17.1%) 3(10%) ≥ 37 (full-term birth) 58(82.9%) 27(90%) Type of delivery 0.402 Cesarean delivery 32(45.7%) 11(36.7%) Normal delivery 38(54.3%) 19(63.3%) Maternal education 0.528 No formal education 20(28.6%) 8(26.7%) Primary education 22(31.4%) 6(20%) Secondary education 15(21.4%) 10(33.3%) Tertiary education 13(18.6%) 6(20%) Income 0.819 Low 45(64.3%) 20(66.7%) Middle 25(35.7%) 10(33.3%) High - - Residence 0.532 Rural 51(72.9%) 20(66.7%) Urban 19(29.1%) 10(33.3%) Maternal age(years), mean(+/-SD) 30(+/-7) 30(+/-6) 0.657 Socio-demographic characteristics of infants groups, n (%) Case(N=70) Control(N=30) P value Neonatal gender 0.547 Male 35(50%) 17(57%) Female 35(50%) 13(43%) Infant age(months) 0.149 <6 months 33(47%) 12(40%) 6-12 months 37(53%) 18(60%) Birth weight(kg),mean(+/-SD) 2.54(+/-0.61) 2.97(+/-0.51) 0.001 a Categorical variables were compared between the two groups by Chi-square test. Continuous variables were compared between the two groups by independent t-test, and expressed by mean and SD (standard deviation). Table2. CHD types among CHD infants of the case group a . CHD types Frequency Cyanotic CHD 45 Multiple lesions CHD b 22 Transposition of the great arteries 9 Tetralogy of Fallot 8 Hypoplastic left heart syndrome 4 Pulmonary atresia 2 Acyanotic CHD 25 Ventricular septal defect 9 Patent ductus arteriosus 9 Atrial septal defect 3 Pulmonary stenosis 2 Aortic stenosis 2 a Number of total CHD infants was 70 infants. b Multiple lesions CHD refers to two different CHD lesions or more, at least one of them is a cyanotic lesion. Table3 .Iron-related biomarkers of mothers and infants of the study a . Case(N=70) Control(N=30) P value Maternal indicators, mean(+/-SD) Serum iron (µg/dl) 57.86(+/- 33.3) 76.03(+/-29.59) 0.003 TIBC (µg/dl) 450.53(+/-80.37) 407.77(+/-64.7) 0.011 TSAT (%) 13.25(+/-8.6) 19.57(+/-9.72) 0.001 Serum ferritin (ng/ml) 20.01(+/-17.83) 26.97(+/-18.10) 0.033 Hb(g/dl) 12.38(+/-1.13) 12.4(+/-0.93) 0.934 MCV(fl) 82.6(+/-6.16) 83.72(+/-4.31) 0.369 MCH(pg) 27.13(+/-2.31) 27.77(+/-1.43) 0.095 MCHC(g/dl) 32.57(+/-1.09) 32.46(+/-1.25) 0.668 RDW (%) 14.13(+/-1.47) 13.97(+/-1.21) 0.613 Infants indicators, mean(+/-SD) Serum iron (µg/dl) 55.4(+/-28.6) 61.27(+/-31.13) 0.425 TIBC (µg/dl) 362.87(+/-100) 353.2(+/-85) 0.625 TSAT (%) 16.35(+/-9) 18.25(+/-9.2) 0.425 Serum ferritin (ng/ml) 70.27(+/-93.28) 41.79(+/-81.78) 0.150 Hb(g/dl) 12.23(+/-1.55) 11.19(+/-0.55) > 0.001 MCV(fl) 76.71(+/-8.48) 74.58(+/-6.05) 0.215 MCH(pg) 24.99(+/-3.15) 24.65(+/-0.94) 0.411 MCHC(g/dl) 31.83(+/-1.75) 34.04(+/-1.74) > 0.001 RDW (%) 16.03(+/-1.83) 13.70(+/-1.22) > 0.001 We used the independent t-test for continuous variables with normal distribution, and Mann Whitney test for continuous variables with non-normal distribution. The continuous variables were expressed by mean and SD(standard deviation). TIBC (total iron binding capacity), TSAT (transferrin saturation ), Hb(hemoglobin), MCV (mean corpuscular volume), MCH(mean corpuscular hemoglobin), MCHC(mean corpuscular hemoglobin concentration), RDW(red cell distribution width) Table 4. Maternal iron deficiency and congenital heart defects a . group b Iron deficiency(ID) Iron deficiency anemia(IDA) CHD mothers(N=70) Unadjusted OR(95%CL) P value Adjusted OR(95%CL) c P value Unadjusted OR(95%CL) P value Adjusted OR(95%CL) c P value 4.09(1.08-15.5) 0.038 4.31(1.05-17.7) 0.042 2.20(0.70-6.82) 0.172 2.18(0.65-7.30) 0.207 a The correlation was performed by multinomial logistic regression models. b The reference group was the control mothers. C Adjusted for Socio-demographic characteristics (maternal age, gestational age, type of delivery, education, income, and residence) Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4777905","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":340818874,"identity":"87e2e4ee-04bb-4f0c-9ac8-3eec19848b5e","order_by":0,"name":"Raghdah Qaddour","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYHACNgYeBhsGfhAzoYB4LWkMkg0gLQbEaznMYHAAxCZGi3n78WsP3tQclt18fnXihwcGDPL8Ygfwa5E5k1NuOOdYuvG2G283SwAdZjhzdgJ+LRIMOWnSPGzWidtunN0A0pJgcJuQFv43QC3/mBM3zzi7+QdxWiTSj0nztjknbuDv3UakLRJv2CTn9qUZz7jBu80iwUCCCL/wpz+TePPNRra//+zmmz8qbOT5pQloYWDgAccFY4MEWKUEIeUgwP4AooX/ADGqR8EoGAWjYCQCAO7+Rc8CgW63AAAAAElFTkSuQmCC","orcid":"","institution":"Damascus University","correspondingAuthor":true,"prefix":"","firstName":"Raghdah","middleName":"","lastName":"Qaddour","suffix":""},{"id":340818875,"identity":"6b20f442-fced-427b-bc43-695404dbddb6","order_by":1,"name":"Ranwa Alsayed","email":"","orcid":"","institution":"Damascus University","correspondingAuthor":false,"prefix":"","firstName":"Ranwa","middleName":"","lastName":"Alsayed","suffix":""}],"badges":[],"createdAt":"2024-07-21 18:38:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4777905/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4777905/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":63826893,"identity":"0626d74f-4528-4db8-b08d-1b1884935de4","added_by":"auto","created_at":"2024-09-02 17:45:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":521139,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4777905/v1/92fc4b87-58a7-4538-bc91-3cc6aa8cf4fb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The relationship between maternal iron status and risk of congenital heart defects: a case-control study","fulltext":[{"header":"Background","content":"\u003cp\u003eCongenital heart defects (CHDs) are structural abnormalities of the heart or the great vessels of the heart. CHD develops during early fetal development and is presented at birth. CHD is considered the most common birth defect, accounting for about a third of all congenital anomalies [1]. The prevalence of CHD is between 8 and 12 cases of live births worldwide [2]. CHD is a major health problem as it is associated with lifelong illness and complication in infants with birth defects, and is the leading cause of death in children with congenital defects [1, 3]. The etiology of CHD remains elusive, with nearly 20% of CHD cases being attributed to well-known chromosomal or genetic disorders. Thus, the majority of CHD cases are thought to be multifactorial, and both genetic and environmental factors have contributed to the pathogenesis of the disease [4, 5].\u003c/p\u003e\n\u003cp\u003eEnvironmental risk factors, which affect pregnant women during the critical period of embryonic heart development (3w-8w), may lead to cardiac defects. These environmental risk factors include maternal diseases, teratogen exposure, and nutrient deficiencies [5, 6]. Iron deficiency (ID) is the most prevalent nutritional deficiency around the world, and it represents the most common contributor to anemia. Iron deficiency anemia (IDA) affects about 5\u003cspan dir=\"RTL\"\u003e0\u003c/span\u003e% of pregnant women globally [27]. Pregnancy is associated with increased iron demand due to increased blood volume in pregnant women and the growth of the fetus and placenta. Thus, pregnant women are at a high risk for developing iron deficiency [7]. Animal studies have shown that iron deficiency during pregnancy affects the growth and development of fetal\u0026nbsp;organs such as the heart\u0026nbsp;[8]. One animal study on mice has demonstrated that maternal iron deficiency\u0026nbsp;disrupts embryonic heart development [9]. However, clinical studies on the relationships between maternal iron status and CHD are limited. There was one clinical study suggesting a relationship between low iron intake during pregnancy and the risk of CHD [10]. In addition, another study found that iron levels were high among mothers of CHD infants [15].\u003c/p\u003e\n\u003cp\u003eThis study aimed to evaluate the iron status among mothers of CHD infants and their infants. Moreover, to verify the relationship between maternal iron status and the risk of congenital heart defects.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe performed a case-control study in two hospitals in Damascus City, Syria the Pediatrics\u003cspan dir=\"RTL\"\u003e\u0026rsquo;\u003c/span\u003e University Hospital, and the Heart Surgery University Hospital from November 2022 to November 2023. Cases and controls were selected from mothers whose infants aged from 1 day to 1 year. The case group included\u003cspan dir=\"RTL\"\u003e\u0026nbsp;70\u0026nbsp;\u003c/span\u003emothers whose infants have an isolated CHD and their infants (n=70), whereas the control group included 30 mothers whose infants have no congenital abnormalities and their infants (n=30).\u003c/p\u003e\n\u003cp\u003eMothers in the two groups were excluded if they had any of the following:\u003c/p\u003e\n\u003cp\u003eDiabetes mellitus, blood hypertension, hyperthyroidism, congenital heart defects, hemolytic anemia, blood transfusion in the last six months, infections and inflammatory condition, taking birth control tablets, taking iron supplements during pregnancy and after delivery, and severe bleeding during pregnancy and after delivery.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMothers of both groups were excluded if their infants had any of the following:\u003c/p\u003e\n\u003cp\u003eGene disorders or chromosomal abnormalities, siblings or first-degree relatives diagnosed with CHD, infections and inflammation, hemolytic anemia, blood transfusion, taking iron supplements. Ultimately, 70 cases and 30 controls were selected based on the inclusion criteria.\u003c/p\u003e\n\u003cp\u003eHowever, it should be noted that we intended for the mothers in both groups to be from a similar socioeconomic background, to minimize the effect of dietary habits on iron levels.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Biomedical Research Ethical Committee (BMREC) at Damascus University, and the reference number is PH-290122-30. The study was conducted according to the guidelines of the Declaration of Helsinki, and all mothers signed a written informed consent form.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCovariables assessment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe interviewed mothers using a standardized questionnaire before collecting samples to verify their alignment with the study criteria and gather important information. The study information consisted of socio-demographic characteristics (maternal age, gestational age, type of delivery, birth weight of infant, residence, education, and income) and maternal health factors during pregnancy (bleeding, illnesses, medication use, and supplements use).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiomarkers measurement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe collected peripheral venous blood from each mother and each infant among the case and control groups. We collected blood into two tubes, an EDTA tube for the assessment of complete blood count (CBC), and a dry tube to obtain serum for the assessment of iron-related biomarkers. The iron-related biomarkers include serum ferritin (SF), serum iron (Fe), unsaturated iron binding capacity (UIBC), total iron binding capacity (TIBC), and transferrin saturation (TSAT). We used a sandwich chemical lumminimmune assay (sandwich CLIA) (Mindray, China) for measuring the concentrations of SF. We used a colorimetric assay (Biomajesty, Germany) for measuring serum iron and unsaturated iron binding capacity (UIBC). Then, we calculated TIBC by summing serum iron and UIBC and calculated TSAT by the formula:\u0026nbsp;[TSAT = (Fe/TIBC) \u0026times; 100].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccording to WHO criteria, we determined absolute iron deficiency in mother groups at a ferritin concentration \u0026lt; 15 ng/ml, and iron deficiency anemia at a ferritin concentration \u0026lt; 15 ng/ml and hemoglobin level \u0026lt; 12 g/dl [11, 12].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis of data was performed by using the SPSS version 24. We applied the Chi-square (x2) test to compare categorical variables between the two groups. Continuous variables with normal and non-normal distributions were compared between the two groups using the Student\u0026apos;s t-test and Mann-Whitney U-test, respectively. We performed Multinominal logistic regression to estimate the odds ratio (OR) with corresponding 95% confidence intervals for total CHDs associated with maternal iron status. P-value \u0026le;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eGeneral characteristics of the study sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe general demographic characteristics of the study participants are shown in Table 1. The study sample consisted of 70 mothers of CHD infants and 70 CHD infants in the case group, and 30 control mothers and 30 control infants were in the control group.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere were no significant differences in maternal age, gestational age, neonatal gender, type of delivery, residence, education, and income between the two groups.\u003c/p\u003e\n\u003cp\u003eThe CHD infants had lower birth weights compared to the control infants (2.54kg+/-0.61 vs. 2.97kg +/-0.51).\u003c/p\u003e\n\u003cp\u003eThe CHD types among the case groups are shown in Table 2.\u003c/p\u003e\n\u003cp\u003eApproximately two-thirds of CHD infants had cyanotic CHD (64.28%) with multiple lesion CHD being the most common type (31.42%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIron biomarkers in mothers and infants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 shows the iron biomarkers of mothers and infants in the two groups. Compared to the mothers in the control group, case mothers had lower SF (20.01 vs. 26.97ng/ml), Fe (57.86 vs. 76.03\u0026micro;g/dl), and TSAT (13.25 vs. 19.57%). Maternal TIBC were higher (450.53 vs. 407.77 \u0026micro;g/dl) among case mothers than the control mothers.\u003c/p\u003e\n\u003cp\u003eWe observed no significant differences in hemoglobin levels, MCV (mean corpuscular volume), MCH (mean corpuscular hemoglobin), MCHC (mean corpuscular hemoglobin concentration), and RDW (red cell distribution width) between the two mothers groups.\u003c/p\u003e\n\u003cp\u003eRegarding the two infants groups, CHD infants had higher hemoglobin levels (12.23vs11.19g/dl) and RDW (16.03vs13.70%) and lower MCHC (31.83vs 34.04g/dl) than the control infants. No significant differences were found in SF, Fe, TSAT, and TIBC between the two groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaternal Iron Deficiency and CHD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 4 shows that CHD mothers (OR=4.01, 95% CL: 1.08-15.5) were more likely to have absolute iron deficiency compared to the control mothers, while there was no difference in the case of iron deficiency anemia (P value=0.172).\u003c/p\u003e\n\u003cp\u003eWe found that the mothers of CHD infants (OR=2.91, 95% CL: 1.143-7.418) were more likely to have iron deficiency with or without anemia than the mothers of non- CHD infants.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe cause of most congenital heart defects (CHDs) cases is unclear, with nearly 20% of cases being related to a specific genetic cause [5]. Recent studies suggested a relationship between environmental risk factors and CHD, including maternal nutrition deficiency during the first trimester of gestation [6]. Nutritional deficiencies have been associated with various birth defects, and most of these nutritional deficiencies could be modified [13, 14]. Iron deficiency is the most common nutrition deficiency globally, particularly among pregnant women [7].\u0026nbsp;A recent animal study revealed a potential association between maternal iron deficiency and the development of CHD in the fetus [9].\u003c/p\u003e\n\u003cp\u003eHowever, the clinical studies exploring this relationship are limited and controversial. A previous case-control study showed that mothers whose infants have CHD had lower iron status during pregnancy compared to control mothers [10], while another study demonstrated a correlation between high maternal iron status and the risk of having a newborn with CHD [15].\u003c/p\u003e\n\u003cp\u003eOur study revealed that the mothers whose infants have CHD had lower levels of SF, Fe, TSAT, and higher TIBC compared to the mothers in the control group. The results also suggested that the mothers of CHD infants are more likely to have iron deficiency (OR=2.91, 95% CL: 1.143-7.418).\u003c/p\u003e\n\u003cp\u003eLow ferritin levels without compensation from iron supplements may indicate a significant iron deficiency. Therefore, iron deficiency in CHD mothers after delivery may be indicative of iron deficiency during pregnancy [16].\u003c/p\u003e\n\u003cp\u003eIron is crucial in embryogenesis, and iron deficiency during early pregnancy may affect heart development through multiple possible mechanisms.\u003c/p\u003e\n\u003cp\u003eFirst, the myocardium is a highly metabolic tissue, and cardiogenesis involves controlled, energy-dependent processes, including the proliferation, differentiation, and maturation of cardiomyocytes [17, 18]. The energy needed for cardiogenesis is primarily obtained from mitochondrial oxidative phosphorylation, which relies on iron-dependent enzyme complexes [17, 19].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIron is a crucial component in mitochondria, as Fe-protoporphyrin, Fe-S clusters, and Rieske center are involved in the mitochondrial complexes that mediate electron transportation and energy generation [19].\u003c/p\u003e\n\u003cp\u003eTherefore, iron deficiency (ID) can reduce energy production and negatively affect cardiomyocyte differentiation and maturation, leading to congenital heart disease (CHD) [20, 21].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSecond, ID has been associated with disruption of mitochondrial biogenesis, changes in mitochondrial structure, increased release of cytochrome c, and induction of apoptosis. Therefore, ID may play a role in mitochondria dysfunction [22]. This could explain previous studies suggesting that mitochondrial dysfunction and metabolic disturbance contribute to the development of CHD [23, 24].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Third, ID may reduce the activity of the iron-dependent enzyme CYP26, which could result in increased retinoic acid signaling in the second heart field. This could, in turn, activate the cardiac transcription factor GATA4 and cause premature differentiation of a group of cardiac progenitor cells, leading to CHD [9].\u003c/p\u003e\n\u003cp\u003eFurthermore, ID can lead to reduced activity of another iron-dependent enzyme, the endothelial nitric oxide synthase (eNOS) [25].\u003c/p\u003e\n\u003cp\u003eThe restriction of (eNOS) activity may negatively affect the expression of cardiac-specific genes, impeding the differentiation of cardiac progenitor cells and thus the development of CHD [26].\u003c/p\u003e\n\u003cp\u003eIron deficiency seems to be (at least partly) the missing part, that links those metabolic abnormalities previously found in the mentioned papers.\u003c/p\u003e\n\u003cp\u003eThis study provides evidence of a correlation between maternal iron deficiency and the risk of congenital heart disease. However, due to the delayed diagnosis of CHD cases until after birth, we collected maternal blood post-delivery, which could impact the assessment of iron levels in our study.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study indicates that mothers of infants with congenital heart disease (CHD) have lower iron status compared to the control mothers. Additionally, the study revealed that mothers of CHD infants are more likely to have iron deficiency. It is essential to conduct prospective clinical studies with a substantial number of pregnant women to confirm our results and gain a deeper understanding of the underlying mechanism. \u0026nbsp;\u003c/p\u003e\n"},{"header":"Abbreviations","content":"\u003cp\u003eCHD (congenital heart defect)\u003c/p\u003e\n\u003cp\u003eSF (serum ferritin)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFe (serum iron)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTSAT (transferrin saturation)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTIBC (total iron binding capacity)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUIBC (unsaturated iron binding capacity)\u003c/p\u003e\n\u003cp\u003eIDA (iron deficiency anemia)\u003c/p\u003e\n\u003cp\u003eID (iron deficiency)\u003c/p\u003e\n\u003cp\u003eCBC (complete blood count)\u003c/p\u003e\n\u003cp\u003eCLIA (chemical lumminimmune assay)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;MCV (mean corpuscular volume)\u003c/p\u003e\n\u003cp\u003eMCH (mean corpuscular hemoglobin)\u003c/p\u003e\n\u003cp\u003eMCHC (mean corpuscular hemoglobin concentration)\u003c/p\u003e\n\u003cp\u003eRDW (red cell distribution width)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Biomedical Research Ethical Committee (BMREC) at Damascus University, and the reference number is PH-290122-30. The study was conducted according to the guidelines of the Declaration of Helsinki, and all mothers signed a written informed consent form.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll materials and all data generated during this study are included in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRQ collected the samples and analyzed the data. RA designed the study and revised it. RQ and RA both interpreted the results, wrote, and drafted the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u003c/strong\u003e\u003cstrong\u003e\u003cspan dir=\"RTL\"\u003e\u0026rsquo;\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRQ, master student, Department of Biochemistry and Microbiology, Faculty of Pharmacy, Damascus University, Damascus, Syria.\u003c/p\u003e\n\u003cp\u003eRA, professor of Clinical Biochemistry, Department of Biochemistry and Microbiology, Faculty of Pharmacy, Damascus University, Damascus, Syria.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLastivka IV, Pishak VP, Ryznychuk МО, Khmara ТV. Risk factor analysis for congenital heart defects in children. Regulatory Mechanisms in Biosystems. 2020;11(4):524-30.\u003c/li\u003e\n\u003cli\u003eWu W, He J, Shao X. Incidence and mortality trend of congenital heart disease at the global, regional, and national level, 1990\u0026ndash;2017. Medicine. 2020 Jun 5;99(23):e20593.\u003c/li\u003e\n\u003cli\u003eCDC.CDC-data and stat in congenital heart disease. Available from https://www.cdc.gov/ncbddd/heartdefects/data.html#:~:text=CHDs%20affect%20nearly%201%25%20of,year%20in%\u003cbr\u003e20the%20United%20States.\u0026amp;text=The%\u003cbr\u003e20prevalence%20(the%20number%20of,other\u003cbr\u003e%20types%20has%20remained%20stable. Accessed on 1/3/2022.\u003c/li\u003e\n\u003cli\u003eSuluba E, Shuwei L, Xia Q, Mwanga A. Congenital heart diseases: genetics, non-inherited risk factors, and signaling pathways. Egyptian Journal of Medical Human Genetics. 2020 Feb 28;21(1). \u003c/li\u003e\n\u003cli\u003ePeyvandi S, Baer RJ, Chambers CD, et al. 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Journal of clinical medicine. 2021 Dec 27;11(1):125.\u003c/li\u003e\n\u003cli\u003eAlsayed R, Quobaili FA, Srour S, Geisel J, Obeid R. Elevated dimethylglycine in blood of children with congenital heart defects and their mothers. Metabolism. 2013 Aug 1;62(8):1074-80.\u003c/li\u003e\n\u003cli\u003eXu X, Lin JH, Bais AS, et al. Mitochondrial respiration defects in single-ventricle congenital heart disease. Frontiers in Cardiovascular Medicine. 2021 Sep 23;8:734388.\u003c/li\u003e\n\u003cli\u003eCorradi F, Masini G, Bucciarelli T, De Caterina R. Iron deficiency in myocardial ischaemia: molecular mechanisms and therapeutic perspectives. Cardiovascular Research. 2023 Oct;119(14):2405-20\u003c/li\u003e\n\u003cli\u003eEngineer A, Saiyin T, Greco ER, Feng Q. Say NO to ROS: Their roles in embryonic heart development and pathogenesis of congenital heart defects in maternal diabetes. Antioxidants. 2019 Oct 1;8(10):436.\u003c/li\u003e\n\u003cli\u003eBenson AE, Shatzel JJ, Ryan KS, Hedges MA, et al. The incidence, complications, and treatment of iron deficiency in pregnancy. European Journal of Haematology. 2022 Oct 4;109(6).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"592\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable1.\u003c/strong\u003eGeneral characteristics of the study participants\u003csup\u003e\u0026nbsp;a\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eSocio-demographic characteristics of mothers group, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCase(N=70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eControl(N=30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGestational age (weeks)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.359\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 37 (preterm birth)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12(17.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3(10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge; 37 (full-term birth)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58(82.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27(90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eType of delivery\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.402\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCesarean delivery\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32(45.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11(36.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNormal delivery\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38(54.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19(63.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaternal education\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo formal education\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20(28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8(26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePrimary education\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22(31.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6(20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSecondary education\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15(21.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTertiary education\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13(18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6(20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.819\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45(64.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25(35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.532\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51(72.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19(29.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMaternal age(years), mean(+/-SD)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30(+/-7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30(+/-6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eSocio-demographic characteristics of infants groups, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCase(N=70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eControl(N=30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNeonatal \u0026nbsp; \u0026nbsp; gender\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.547\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17(57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13(43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eInfant age(months)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;6 months\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33(47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12(40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6-12 months\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37(53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18(60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBirth weight(kg),mean(+/-SD)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.54(+/-0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.97(+/-0.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003eCategorical variables were compared between the two groups by Chi-square test. Continuous variables were compared between the two groups by independent t-test, and expressed by mean and SD (standard deviation).\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"630\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable2.\u003c/strong\u003e CHD types among CHD infants of the case group\u003csup\u003ea\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003eCHD types\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eFrequency\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003eCyanotic CHD\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e45\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003eMultiple lesions CHD\u003csup\u003eb\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003eTransposition of the great arteries\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003eTetralogy of Fallot\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003eHypoplastic left heart syndrome\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003ePulmonary atresia\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003eAcyanotic CHD\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003eVentricular septal defect\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003ePatent ductus arteriosus\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003eAtrial septal defect\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003ePulmonary stenosis\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.523809523809526%\" valign=\"top\"\u003e\n \u003cp\u003eAortic stenosis\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eNumber of total CHD infants was 70 infants.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eMultiple lesions CHD refers to two different CHD lesions or more, at least one of them is a cyanotic lesion.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable3\u003c/strong\u003e.Iron-related biomarkers of mothers and infants of the study\u003csup\u003ea\u003c/sup\u003e.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eCase(N=70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eControl(N=30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eMaternal indicators, mean(+/-SD)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eSerum iron (\u0026micro;g/dl)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e57.86(+/- 33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e76.03(+/-29.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eTIBC (\u0026micro;g/dl)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e450.53(+/-80.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e407.77(+/-64.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eTSAT (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e13.25(+/-8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e19.57(+/-9.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eSerum ferritin (ng/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e20.01(+/-17.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e26.97(+/-18.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eHb(g/dl)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e12.38(+/-1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e12.4(+/-0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.934\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eMCV(fl)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e82.6(+/-6.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e83.72(+/-4.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.369\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eMCH(pg)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e27.13(+/-2.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e27.77(+/-1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eMCHC(g/dl)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e32.57(+/-1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e32.46(+/-1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.668\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eRDW (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e14.13(+/-1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e13.97(+/-1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.613\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eInfants indicators, mean(+/-SD)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eSerum iron (\u0026micro;g/dl)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e55.4(+/-28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e61.27(+/-31.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.425\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eTIBC (\u0026micro;g/dl)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e362.87(+/-100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e353.2(+/-85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.625\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eTSAT (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e16.35(+/-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e18.25(+/-9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.425\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eSerum ferritin (ng/ml)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e70.27(+/-93.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e41.79(+/-81.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eHb(g/dl)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e12.23(+/-1.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e11.19(+/-0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eMCV(fl)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e76.71(+/-8.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e74.58(+/-6.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eMCH(pg)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e24.99(+/-3.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e24.65(+/-0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e0.411\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eMCHC(g/dl)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e31.83(+/-1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e34.04(+/-1.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eRDW (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e16.03(+/-1.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e13.70(+/-1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026gt;\u003c/span\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eWe used\u0026nbsp;the independent t-test for continuous variables with normal distribution, and Mann Whitney test for continuous variables with non-normal distribution.\u003c/p\u003e\n\u003cp\u003eThe continuous variables were expressed by mean and SD(standard deviation).\u003c/p\u003e\n\u003cp\u003eTIBC (total iron binding capacity), TSAT (transferrin saturation ), Hb(hemoglobin), MCV (mean corpuscular volume), MCH(mean corpuscular hemoglobin), MCHC(mean corpuscular hemoglobin concentration), RDW(red cell distribution width)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"712\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"9\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003eMaternal iron deficiency and congenital heart defects\u003csup\u003ea\u003c/sup\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.40953716690042%\" valign=\"top\"\u003e\n \u003cp\u003egroup\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.07573632538569%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eIron deficiency(ID)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.51472650771389%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eIron deficiency anemia(IDA)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.40953716690042%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eCHD mothers(N=70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.464235624123422%\" valign=\"top\"\u003e\n \u003cp\u003eUnadjusted OR(95%CL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5736325385694245%\" valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.464235624123422%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted OR(95%CL)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.5736325385694245%\" valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.622720897615709%\" valign=\"top\"\u003e\n \u003cp\u003eUnadjusted OR(95%CL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.994389901823282%\" valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.043478260869565%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted OR(95%CL)\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.854137447405329%\" valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.107382550335572%\" valign=\"top\"\u003e\n \u003cp\u003e4.09(1.08-15.5)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.060402684563758%\" valign=\"top\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.107382550335572%\" valign=\"top\"\u003e\n \u003cp\u003e4.31(1.05-17.7)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.060402684563758%\" valign=\"top\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.100671140939598%\" valign=\"top\"\u003e\n \u003cp\u003e2.20(0.70-6.82)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.563758389261745%\" valign=\"top\"\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.604026845637584%\" valign=\"top\"\u003e\n \u003cp\u003e2.18(0.65-7.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.395973154362416%\" valign=\"top\"\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"9\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea\u003c/sup\u003eThe correlation was performed by multinomial logistic regression models.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e The reference group was the control mothers.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eC\u003c/sup\u003e Adjusted for Socio-demographic characteristics (maternal age, gestational age, type of delivery, education, income, and residence)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"maternal iron status, iron deficiency, pregnancy, congenital heart defects","lastPublishedDoi":"10.21203/rs.3.rs-4777905/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4777905/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e The cause of most congenital heart defects (CHD) cases is still unknown. A study on animals showed a link between maternal iron deficiency and congenital heart defects in mice, but this connection in humans is not yet clear. Our goal in this study was to assess the iron levels in mothers and infants with CHDs and to explore the potential relationship between maternal iron status and CHDs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e We conducted a case-control study in Damascus, Syria, including 70 cases and 30 controls. The study involved mothers whose infants were aged from 1 day to 1 year. We interviewed eligible mothers to gather information about their pregnancies and collected peripheral blood from both the mothers and their infants to analyze iron-related biomarkers. We used multinomial logistic regression to estimate the odds ratio (with 95% confidence intervals) for maternal iron status with CHDs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e The iron-related biomarkers (serum ferritin (SF), serum iron (Fe), and transferrin saturation (TSAT) showed lower levels, while total iron binding capacity (TIBC) was higher among mothers of CHD infants compared to the control group (p-value \u0026lt; 0.05). Additionally, mothers of CHD infants were at a higher risk of having iron deficiency (OR=2.91, 95% CL: 1.143-7.418) compared to the control group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e Mothers of CHD infants exhibited lower levels of SF, Fe, and TSAT, and higher TIBC compared to the control group. Furthermore, the CHD mothers were more likely to have iron deficiency compared to the control group.\u003c/p\u003e","manuscriptTitle":"The relationship between maternal iron status and risk of congenital heart defects: a case-control study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-16 16:09:20","doi":"10.21203/rs.3.rs-4777905/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"55f31982-a5bc-4d33-9c47-c154706cd961","owner":[],"postedDate":"August 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-02T17:37:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-16 16:09:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4777905","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4777905","identity":"rs-4777905","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}