Maternal obesity, interpregnancy weight changes and congenital heart defects in the offspring: a nationwide cohort study

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Methods A nationwide cohort study of all singleton pregnancies in Denmark from 2008 to 2018. Data were retrieved from the Danish Foetal Medicine Database, which included both pre- and postnatal diagnoses of CHDs. Children or foetuses with chromosomal aberrations were excluded. Relative risks were calculated using log-linear Poisson models for CHDs overall, severe CHDs and for five of the most prevalent subtypes of CHDs. Results Of the 547 178 pregnancies included in the cohort, 5 498 had CHDs (1.0%). Risk of CHDs became gradually higher with higher maternal BMI; for BMI 30-34.9 kg/m 2 , adjusted relative risk (aRR) 1.23 (95% CI 1.12–1.36), for BMI 35-39.9 kg/m 2 , aRR 1.26 (95% CI 1.09–1.46) and for BMI ≥ 40 kg/m 2 , aRR 1.81 (95% CI 1.50–2.15). Data was adjusted for maternal age, smoking status and year of estimated due date. The same pattern was seen for the subgroup of severe CHDs. Among the atrioventricular septal defects (n = 245), a particularly strong association with maternal BMI ≥ 40 kg/m 2 was seen, aRR 4.19 (95% CI 2.13–7.42). 107 627 women were identified with their first and second pregnancies in the cohort. Interpregnancy BMI change was associated, albeit not statistically significant, with risk of CHDs in the second pregnancy when adjusting for maternal age and BMI, with an aRR 1.27 (95% CI 0.96–1.64) among persons with a BMI increase of ≥ 4 kg/m 2 . Conclusion Risk of foetal CHDs became gradually higher with higher maternal BMI, but only a non-significant association was seen for interpregnancy weight changes and risk of CHDs. Health sciences/Risk factors Health sciences/Diseases atrioventricular septum defect coarctation of the aorta epidemiological study maternal BMI prenatal congenital heart defects register-based study severe congenital heart defects The Danish Foetal Medicine database Tetralogy of Fallot transposition of the great arteries univentricular heart Figures Figure 1 Figure 2 Introduction Obesity among women of reproductive age has been increasing over the last three decades.( 1 ) Centers for Disease Control and Prevention estimated that 40% of women aged 20–39 years old in the United States were obese (body mass index [BMI] ≥ 30 kg/m 2 ) in 2017–2018.( 2 ) Maternal obesity is a risk factor for adverse pregnancy outcomes as well as for long-term health consequences for both the mother and child.( 3 , 4 ) Furthermore, maternal obesity is associated with a higher risk of having a child with congenital malformations.( 5 ) Congenital heart defects (CHDs) remain the leading cause of infant death from congenital malformations in the United States.( 6 ) Believed to be the most common congenital malformations, CHDs have a global prevalence of nine per 1000 live births with geographical differences.( 7 ) The causes of CHDs are unknown in most cases, but are associated with maternal age, chronic conditions, viral infections and foetal exposures to teratogenic drugs.( 8 – 11 ) With improvements in genetic and genomic analytical techniques an increasing number of genetic associations/causes have been identified in up to 30% of the cases.( 12 ) The association between maternal obesity and infants born with congenital malformations has been reported to include CHDs. However, none of the large studies have included the proportion of CHDs that are identified and terminated in pregnancy. During the last two decades, the prenatal identification of CHDs has increased dramatically, consequently, an analysis of the association between maternal risk factors and CHDs should include data on prenatally identified cases. Meta-analyses suggest a moderate association between maternal obesity (BMI ≥ 30 kg/m 2 ) and CHDs in the offspring with an OR 1.2 (95% CI 1.1–1.2)( 13 ) or an OR 1.3 (95% CI 1.2–1.4).( 14 ) A recent systematic review on the topic demonstrated great heterogeneity among the studies with respect to design, exposure definition, outcome definition, choice of covariates, and only populations of Northern European or Chinese descent were examined to a reasonable extent.( 15 ) Some studies have found an association between maternal interpregnancy BMI changes and adverse pregnancy- and perinatal outcomes that were linearly related to the amount of weight gain.( 16 , 17 ) So far, a few small studies suggest that this might be relevant for certain congenital malformations (spina bifida, gastroschisis and oral cleft),( 16 , 18 – 20 ) however, no data is available in these studies for foetal CHDs. It is of great importance to identify any modifiable risk factors for CHDs. If weight gain, defined as interpregnancy BMI change, is associated with CHDs, this could be added to the aetiology of the association and the justification of preventive initiatives as to stress weight stability, and for some women weight loss. The hypothesis of the study was that high maternal BMI was associated with higher risk of foetal CHDs when the study population comprised all CHDs found among live births, stillbirths, abortions and terminated pregnancies in Denmark. Furthermore, interpregnancy maternal BMI changes were hypothesized to influence the risk of foetal CHDs. This study aims to assess the risk of foetal CHDs, severe CHDs or five of the most frequently identified subtypes of CHDs according to early-pregnancy BMI. The study also investigates if changes in maternal BMI from the beginning of the first pregnancy to the beginning of the second pregnancy were associated with risk of CHDs in the second pregnancy. Materials and Methods This cohort study was performed on prospectively collected data retrieved from a nationwide cohort based on The Danish Foetal Medicine Database.( 21 ) The Danish Foetal Medicine Database includes data on pregnancies with prenatal screening results from all obstetric and gynaecological departments in Denmark from January 1, 2008.( 21 ) All women in Denmark are offered a first trimester screening for chromosomal abnormalities (gestational week 12) and a second trimester anomaly scan, for which the uptake rate is high; 95% of pregnant women participate. The database does not include data on outcomes of pregnancies before the first trimester scan. The primary source of information is the local foetal medicine databases used nationwide in which sonographers and maternal-foetal medicine specialists add data from all examinations. The Danish Foetal Medicine Database includes data on maternal characteristics including weight and height, data from ultrasound examinations and pregnancy outcomes.( 21 ) Furthermore, the database includes data from other Danish registers: the Danish Cytogenetic Central Register,( 22 ) the Danish National Patient Register,( 23 ) and the Danish Medical Birth Register.( 24 ) All Danish residents are assigned a unique personal identification number enabling linkage of data between national registers and other data sources.( 25 ) In Denmark, health care is free and it is standard practice to offer genetic testing by chorionic villus sampling or amniocentesis when a CHD is diagnosed prenatally.( 26 ) The prenatal detection rate and accuracy of major CHD is high and the majority of parents opt for further testing.( 27 , 28 ) A gradual transition from conventional karyotyping to chromosomal microarray was observed over the course of the study period. Postnatal genetic testing primarily by chromosomal microarray is performed in all children with syndromic suspicion. The Danish Foetal Medicine database is updated once a year with information on postnatal diagnosed congenital malformations and karyotypes.( 21 ) The International Classification of Diseases, 10th revision code system (ICD-10) is used to code malformations in the foetus and in the infant.( 21 ) The cohort included singleton pregnancies in Denmark with an estimated due date, from ultrasound scan, between June 1, 2008 and June 1, 2018. Each woman can have multiple pregnancies during the study period. Pregnancies with a foetus or child with a chromosomal aberration were excluded from the cohort. Only pregnant women with a registered early-pregnancy weight and a height from 120 through 200 cm were included. Maternal BMI was calculated as weight in kilograms divided by the square of the height in meters (kg/m 2 ) and BMI values are reported in that unit. Extreme observations defined as BMI 60 were excluded to avoid registration errors. We identified foetuses and infants with CHDs (Table S1 ) by using either the prenatal or/and the postnatal diagnoses. In all live births, postnatal CHD diagnoses were considered gold standard. The CHD diagnoses were defined by the European Surveillance of Congenital Anomalies (EUROCAT)( 29 ) (Table S1 ). Severe CHDs include the following 17 diagnoses: truncus arteriosus, double outlet right ventricle, transposition of the great arteries (TGA), univentricular heart (UVH), atrioventricular septum defect (AVSD), Tetralogy of Fallot (ToF), pulmonary atresia, tricuspid valve stenosis, Epstein’s anomaly, hypoplastic right heart syndrome, aortic valve stenosis, mitral valve stenosis, mitral insufficiency, hypoplastic left heart syndrome, coarctation of the aorta (CoA), aortic atresia, and total anomalous pulmonary venous return. Irrespective of the number of CHD diagnoses in a particular patient, the patient was only registered once as having CHDs. Furthermore, offspring with five of the most frequent subtypes of severe CHDs were identified (Table S2). These were ranked as defined by Lytzen et al.( 27 ) with the most severe first (UVH > TGA > AVSD > CoA > ToF). If offspring had combinations of these subtypes, they were only registered once with the most severe diagnosis. ICD-10 codes for severe CHDs have been validated against hospital records with very good agreement in the Danish National Patient Register.( 30 ) Prenatal diagnoses of 12 severe CHDs have been shown to have a very high diagnostic precision.( 28 ) For the calculations of interpregnancy BMI changes, a sub-cohort including women with first and second pregnancies and more than 50 weeks between estimated due dates was compiled. Maternal height was defined as the height registered in the first pregnancy. Interpregnancy BMI changes were calculated as the difference between BMI at the beginning of the first and BMI at the beginning of the second pregnancy. Differences were categorized into six groups < -2; -2 to < -1; -1 to < 1; 1 to < 2; 2 to < 4; and ≥ 4 BMI units. The category − 1 to < 1 was defined as stable weight and used as reference. Associations between maternal BMI and offspring risk of CHDs were calculated as relative risks (RRs) with 95% CI using log-linear Poisson regression models. The models were adjusted for maternal age (< 20, 20–24, 25–29, 30–34, 35–39, ≥ 40 years), maternal smoking status (yes/no/stopped), and year of estimated due date (1-year groups). The model was not adjusted for potential multiple pregnancies for each woman during the study period. Associations between interpregnancy BMI changes and risk of CHDs were calculated as RRs with 95% CI using log-linear Poisson regression models. Maternal BMI in first pregnancy and maternal age at second pregnancy were considered possible confounders and were adjusted for in the multivariate model. Statistical analyses were run in R version 4.2.1. Statens Serum Institut has approval from the Danish Data Protection Agency to conduct register-based studies, and the project has been approved (journal no. 19/03354 and 20/09279). The cohort study adhered to the STROBE guidelines. During the preparation of this work the author used ChatGPT in order to improve language and readability. The authors reviewed and edited the content as needed and take full responsibility for the content of the publication. Results The study cohort consisted of 547 178 singleton pregnancies with estimated due dates between June 1, 2008 and June 1, 2018 when pregnancies with chromosomal aberrations and missing data were excluded as detailed in Fig. 1 . A total of 5 498 (1.0%) offspring had CHDs. Of these 1 227 were defined as severe CHDs (0.2%). Clinical and demographic data are available in Table 1. Information on parity was not registered and therefore missing in the dataset from 2008–2011 corresponding to 25% of the pregnancies. The study cohort comprised 534 478 live births (97.7%), 1 623 stillbirths (0.3%), 5 073 abortions or terminated pregnancies (0.9%), and 6 004 pregnancies with missing outcomes (1.1%). In total, 35% of the women had an early-pregnancy BMI ≥ 25, and 13% were obese (BMI ≥ 30). The distribution of maternal BMI among the different groups and covariates can be seen in Table 1. Maternal overweight was associated significantly with higher risk of CHDs in the offspring increasing with higher maternal BMI: for BMI 25-29.9, adjusted relative risk (aRR) 1.17 (95% CI 1.09–1.25), for BMI 30-34.9, aRR 1.23 (95% CI 1.12–1.36), for BMI 35-39.9, aRR 1.26 (95% CI 1.09–1.46) and for BMI ≥ 40, aRR 1.81 (95% CI 1.50–2.15) compared to women with an early-pregnancy BMI 18.5–24.9 (Table 2). Similar results were seen for maternal BMI and severe CHDs: for BMI 25-29.9, aRR 1.20 (95% CI 1.04–1.38), for BMI 30-34.9, aRR 1.28 (95% CI 1.04–1.56), for BMI 35-39.9, aRR 1.47 (95% CI 1.09–1.96) and for BMI ≥ 40, aRR 1.85 (95% CI 1.23–2.67) compared to women with an early-pregnancy BMI 18.5–24.9 (Table 2). A marginally higher risk of CHDs, when only including live births compared to all pregnancies, was seen for maternal BMI ≥ 30 (aRR 1.24–1.87; data available in Table S3). The proportion of CHD cases with one of the five specific CHD diagnoses were as follows: univentricular heart (UVH; 4.4%), transposition of the great arteries (TGA; 3.2%), atrioventricular septum defect (AVSD; 4.5%), coarctation of the aorta (CoA; 4.6%), and Tetralogy of Fallot (ToF; 2.3%). The association between maternal BMI and these specific five CHD diagnoses are shown in Fig. 2 . No significant associations were seen for UVH, TGA, CoA and ToF. However, maternal BMI ≥ 30 was associated with a significantly higher risk of AVSD in the offspring (Fig. 2 ). The sub-cohort included 107 627 women who had a first and second consecutive singleton pregnancies between June 1, 2008 and June 1, 2018 (Table 3). Mean BMI in first pregnancy was 24.9 vs. 25.8 in second pregnancy. In total, 998 had an offspring with CHDs (0.9%) in their second pregnancy. The prevalence of CHDs in the second pregnancy became higher with increased weight gain between pregnancies (0.8–1.3%). Increase in maternal BMI between pregnancies were significantly associated with higher risk of CHDs in second pregnancy. However, when adjusted for maternal age in the second pregnancy and maternal BMI in the first pregnancy, only a non-significant association remained towards higher risks of any CHDs with weight gain between pregnancies (Table 3). Discussion When including both pre- and postnatally diagnosed CHDs for all pregnancies, this study showed a dose-response association between high maternal BMI and risk of CHDs in the offspring. However, only a non-significant association was seen between interpregnancy BMI changes between first and second pregnancies and risk of foetal CHDs in the second pregnancies. This prospective nationwide cohort included 547 178 live births, stillbirths, abortions and terminated pregnancies in Denmark from 2008 to 2018 and showed that maternal overweight and obesity were significantly associated with a moderately higher risk of CHDs (aRR 1.17–1.81) and severe CHDs (aRR 1.20–1.85) in the offspring compared to women with a BMI in the normal range (BMI 18.5–24.9). The study validates previous findings of an association between high maternal BMI and risk of CHDs in the offspring( 13 , 14 , 31 , 32 ) and thereby rejects any hypothesis of this association to be caused by lower prenatal detection rates of CHDs in pregnant women with obesity. Most other studies have been limited to live births.( 15 , 31 ) A large nationwide Swedish study with two million live born children found an association between high maternal BMI and CHDs (BMI 30-34.9: OR 1.2, 95% CI 1.2–1.3; BMI ≥ 40: OR 1.6, 95% CI 1.4–1.8).( 31 ) When restricting our analysis to live births (Table S3), we found significant associations of a similar magnitude between maternal BMI ≥ 25 and foetal CHDs. Results from five specific subtypes of CHDs (UVH, TGA, AVSD, CoA and ToF) showed no significant association with maternal BMI except for AVSD (Fig. 2 ), which was significantly associated with increased risks when maternal BMI ≥ 30 (BMI 30 to ≥ 40: aRR = 1.65–4.19). Persson et al. found a non-significant association between maternal BMI and AVSD in women with BMI ≥ 30,( 5 ) and the same pattern was observed in other studies.( 9 , 33 , 34 ) The lack of statistical significance in other studies might be due to few cases in each BMI group or different study designs. We examined the interpregnancy weight changes between the first and second pregnancies in 107 627 women and found a non-significant association towards higher risks of CHDs in second pregnancies preceded by a substantial BMI gain but this was not significant when data was adjusted for maternal BMI in first pregnancy and maternal age in second pregnancy (Table 3) as a result of the correlation between maternal BMI and interpregnancy weight changes. The investigations of the association between interpregnancy weight changes and risk of foetal CHDs are sparse.( 16 ) A few studies have looked at other congenital malformations and found a RR 2.3 for isolated cleft palate when maternal BMI increased ≥ 3 BMI units,( 20 ) an association between spina bifida and interpregnancy BMI gain,( 18 ) and a significant decrease in OR 0.62 (95% CI 0.42–0.94) for gastroschisis when maternal BMI increased with ≥ 3 BMI units.( 19 ) Clinical Implications Lifestyle interventions to reduce risk of foetal CHDs have been suggested to be introduced before or between pregnancies.( 35 ) Although our results only indicate a trend between interpregnancy weight changes and risk of CHDs, it does not dismiss a positive effect of weight reduction in women with obesity before pregnancy. In a setting with pre-pregnancy counselling, it is still important to advise women about the importance of BMI as a risk factor for congenital malformations,( 5 ) obstetric and perinatal complications.( 3 , 4 ) Research Implications Prenatal detection rates of congenital malformations decreases with increasing maternal BMI since image quality is lower in women with obesity.( 36 , 37 ) Consequently, studies only including live births could be biased towards a higher postnatal prevalence of CHDs in women with obesity if severe foetal CHDs were not diagnosed and possibly terminated during pregnancy (Table 1). Thus, this phenomenon may at least partly explain an association between high BMI and prevalence of CHDs in live borns.( 5 ) Prenatal detection rates of CHDs have improved substantially in the last decades, and in countries with prenatal screening with high detection rate of CHDs as in Denmark,( 28 ) it is more important to include terminated pregnancies in prevalence and association studies as the rate of terminated pregnancies with the most severe CHDs likely will be higher as seen in Table 1. This study confirms the association between high maternal BMI and risk of foetal CHDs. Knowledge about the aetiology is still limited( 35 ) and future research should focus on combinations of other related maternal metabolic disorders linked to insulin resistance as suggested in a recent review.( 15 ) Strengths and Limitations The strength of this study is the large size of the cohort and prospectively, nationwide data collection including prenatal information. Some limitation must be considered. The database did not include data on pregestational diabetes, which is known to be strongly associated with CHDs, and therefore this confounder was not included as a covariate in the analyses.( 15 , 38 ) Persson et al. excluded all women with pregestational diabetes and found a moderate association similar to the results of the present study.( 31 ) Nor did the data include information about family history of CHDs,( 39 ) maternal infections or teratogenic medicine intake in pregnancy that have been associated with higher risk of CHDs.( 8 ) Since the study draws conclusions from register data, there is a risk of reporting bias and all CHD diagnoses are not validated against hospital records. Conclusion This study found that risk of foetal CHDs becomes gradually higher with higher maternal BMI when including live births, stillbirths, aborted and terminated pregnancies, however, only a non-significant association was found between interpregnancy maternal BMI changes and risk of foetal CHDs. Declarations Competing interest statement: The authors report no conflict of interest Acknowledgements The study group wishes to thank sonographers and medical doctors, who have and continuously are collecting data for the Danish Foetal Medicine Database. An earlier version of the article is available at a preprint server, MedRxiv (doi: https://doi.org/10.1101/2023.02.12.23285811). This study was supported by The Danish Children Heart Foundation (18-R109-A5193-26043), The A.P. Moller Foundation (19-L-0096), and Aase and Ejnar Danielsen's Foundation (19-10-0493). This research has been conducted using the Danish National Biobank resource supported by the Novo Nordisk Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Author Contributions GH was responsible for designing the study, writing the protocol, funding acquisition, analysing data, interpreting results and writing the original draft. INT contributed to the design of the study, funding acquisition, writing the protocol, interpreting results and commented on the original draft. PLH contributed to the design of the study, writing the protocol, analysing and interpreting results, creating figures and commented on the original draft. LK contributed to the design of the study, funding acquisition and commented on the original draft. CMH conducted the data analyses and commented on the original draft. TIAS contributed to the design of the study and commented on the original draft. MC contributed to the design of the study, funding acquisition, writing the protocol, interpreting results and writing the original draft. 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Tables Tables 1 to 3 are available in the Supplementary Files section Additional Declarations There is NO conflict of interest to disclose Supplementary Files SupplementaryInformation.pdf Table1.xlsx Table2.xlsx Table3.xlsx Cite Share Download PDF Status: Published Journal Publication published 11 May, 2024 Read the published version in International Journal of Obesity → Version 1 posted Editorial decision: revise 09 Nov, 2023 Review # 2 received at journal 06 Nov, 2023 Review # 1 received at journal 23 Oct, 2023 Reviewer # 2 agreed at journal 23 Oct, 2023 Reviewer # 1 agreed at journal 23 Oct, 2023 Reviewers invited by journal 16 Oct, 2023 Submission checks completed at journal 16 Oct, 2023 First submitted to journal 13 Oct, 2023 Editor assigned by journal 13 Oct, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Hedermann","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAmklEQVRIiWNgGAWjYDACZh4Ghg8MDEAyjQQtjDNI0wJUDLKIgXgt8u68Bz/b/KmTYWBPSyBOi+FhvmTp3LbDPAw8zw4QqaWZx4w5t+EAD4NEegMJWiz+1JGgRZ4ZqIWBDRgCEmlEOsyAmcdYshfoFzaeZwlE2tJ/xvDDjz919vzsaQZE2gJzDRtx6kG2NBCtdBSMglEwCkYsAAAxNyE6PvuSlwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-8853-0986","institution":"Statens Serum Institut","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Gitte","middleName":"","lastName":"Hedermann","suffix":""},{"id":240597866,"identity":"5c778315-7b87-4ec8-8336-8e81680dfd5d","order_by":1,"name":"Ida Thagaard","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ida","middleName":"","lastName":"Thagaard","suffix":""},{"id":240597867,"identity":"7216e5f2-7946-4c24-8f2a-09a018ae72ed","order_by":2,"name":"Paula Hedley","email":"","orcid":"","institution":"Statens Serum Instiut","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Paula","middleName":"","lastName":"Hedley","suffix":""},{"id":240597868,"identity":"551ea2a2-a3a3-4d15-b10b-b4065b945311","order_by":3,"name":"Lone Krebs","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lone","middleName":"","lastName":"Krebs","suffix":""},{"id":240597869,"identity":"1f8a7071-952b-4ad4-be9b-abe84b661d0b","order_by":4,"name":"Christian Hagen","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Christian","middleName":"","lastName":"Hagen","suffix":""},{"id":240597870,"identity":"21b8c5d1-302f-4ce8-9e84-6803a7002809","order_by":5,"name":"Thorkild Sorensen","email":"","orcid":"https://orcid.org/0000-0003-4821-430X","institution":"Faculty of Health and Medical Sciences, University of Copenhagen","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Thorkild","middleName":"","lastName":"Sorensen","suffix":""},{"id":240597871,"identity":"414022c3-ed4d-483d-9cf0-4aaca222f872","order_by":6,"name":"Michael Christiansen","email":"","orcid":"","institution":"Statens Serum Institut","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Christiansen","suffix":""},{"id":240597873,"identity":"9eb93067-069e-409a-8d02-77c05839df84","order_by":7,"name":"Charlotte Ekelund","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Charlotte","middleName":"","lastName":"Ekelund","suffix":""}],"badges":[],"createdAt":"2023-10-13 13:37:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3442362/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3442362/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41366-024-01531-5","type":"published","date":"2024-05-11T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":44867727,"identity":"d35cd7c8-5856-40c9-8f49-cbdbc6cd229c","added_by":"auto","created_at":"2023-10-18 15:50:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1259345,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eFlowchart\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eAbbreviations: BMI, body mass index; CHDs, congenital heart defects\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3442362/v1/e83a31caece4040f97e12cdb.png"},{"id":44867726,"identity":"06ea7b0f-94cd-4855-b858-f2ba0dd3b19d","added_by":"auto","created_at":"2023-10-18 15:50:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":50171,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eCrude relative risks for five subtypes of congenital heart defects by maternal BMI, singleton pregnancies in Denmark 2008-2018\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eBMI 18.5-24.9 kg/m\u003csup\u003e2\u003c/sup\u003e was considered as the normal range and used as a reference.\u003c/p\u003e\n\u003cp\u003eAbbreviations: CHDs, congenital heart defects; CI, confidence interval; RR, relative risk; N, number of events\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3442362/v1/e329bc83667590eb39f65431.png"},{"id":56323583,"identity":"86b42e6e-0836-4816-81fe-943d39e2eebe","added_by":"auto","created_at":"2024-05-12 07:05:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":941348,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3442362/v1/81a395b7-14f5-402a-8719-1a6bfddc6175.pdf"},{"id":44867728,"identity":"64a30e7a-9422-4dc0-a80f-639b91d92806","added_by":"auto","created_at":"2023-10-18 15:50:54","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":124275,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementaryInformation.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3442362/v1/c924ce67ac93ba35fff04eeb.pdf"},{"id":44867725,"identity":"d57ce84f-bda7-44e9-be35-4ce638612404","added_by":"auto","created_at":"2023-10-18 15:50:53","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":12845,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3442362/v1/23b579249b9d1e0508afd2d7.xlsx"},{"id":44867724,"identity":"77e66d2d-286f-467f-aec2-02ef60248492","added_by":"auto","created_at":"2023-10-18 15:50:53","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":10879,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3442362/v1/02f54b1ef587fb4b60af24e2.xlsx"},{"id":44867730,"identity":"fe395485-7e0e-4b04-8e38-ef4f851f483a","added_by":"auto","created_at":"2023-10-18 15:50:54","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":10783,"visible":true,"origin":"","legend":"","description":"","filename":"Table3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3442362/v1/7a59f866f52794c4cb0dfd7b.xlsx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Maternal obesity, interpregnancy weight changes and congenital heart defects in the offspring: a nationwide cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eObesity among women of reproductive age has been increasing over the last three decades.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Centers for Disease Control and Prevention estimated that 40% of women aged 20\u0026ndash;39 years old in the United States were obese (body mass index [BMI]\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e) in 2017\u0026ndash;2018.(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Maternal obesity is a risk factor for adverse pregnancy outcomes as well as for long-term health consequences for both the mother and child.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) Furthermore, maternal obesity is associated with a higher risk of having a child with congenital malformations.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eCongenital heart defects (CHDs) remain the leading cause of infant death from congenital malformations in the United States.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) Believed to be the most common congenital malformations, CHDs have a global prevalence of nine per 1000 live births with geographical differences.(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) The causes of CHDs are unknown in most cases, but are associated with maternal age, chronic conditions, viral infections and foetal exposures to teratogenic drugs.(\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) With improvements in genetic and genomic analytical techniques an increasing number of genetic associations/causes have been identified in up to 30% of the cases.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe association between maternal obesity and infants born with congenital malformations has been reported to include CHDs. However, none of the large studies have included the proportion of CHDs that are identified and terminated in pregnancy. During the last two decades, the prenatal identification of CHDs has increased dramatically, consequently, an analysis of the association between maternal risk factors and CHDs should include data on prenatally identified cases. Meta-analyses suggest a moderate association between maternal obesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e) and CHDs in the offspring with an OR 1.2 (95% CI 1.1\u0026ndash;1.2)(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) or an OR 1.3 (95% CI 1.2\u0026ndash;1.4).(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) A recent systematic review on the topic demonstrated great heterogeneity among the studies with respect to design, exposure definition, outcome definition, choice of covariates, and only populations of Northern European or Chinese descent were examined to a reasonable extent.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eSome studies have found an association between maternal interpregnancy BMI changes and adverse pregnancy- and perinatal outcomes that were linearly related to the amount of weight gain.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) So far, a few small studies suggest that this might be relevant for certain congenital malformations (spina bifida, gastroschisis and oral cleft),(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) however, no data is available in these studies for foetal CHDs. It is of great importance to identify any modifiable risk factors for CHDs. If weight gain, defined as interpregnancy BMI change, is associated with CHDs, this could be added to the aetiology of the association and the justification of preventive initiatives as to stress weight stability, and for some women weight loss.\u003c/p\u003e \u003cp\u003eThe hypothesis of the study was that high maternal BMI was associated with higher risk of foetal CHDs when the study population comprised all CHDs found among live births, stillbirths, abortions and terminated pregnancies in Denmark. Furthermore, interpregnancy maternal BMI changes were hypothesized to influence the risk of foetal CHDs.\u003c/p\u003e \u003cp\u003eThis study aims to assess the risk of foetal CHDs, severe CHDs or five of the most frequently identified subtypes of CHDs according to early-pregnancy BMI. The study also investigates if changes in maternal BMI from the beginning of the first pregnancy to the beginning of the second pregnancy were associated with risk of CHDs in the second pregnancy.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eThis cohort study was performed on prospectively collected data retrieved from a nationwide cohort based on The Danish Foetal Medicine Database.(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) The Danish Foetal Medicine Database includes data on pregnancies with prenatal screening results from all obstetric and gynaecological departments in Denmark from January 1, 2008.(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) All women in Denmark are offered a first trimester screening for chromosomal abnormalities (gestational week 12) and a second trimester anomaly scan, for which the uptake rate is high; 95% of pregnant women participate. The database does not include data on outcomes of pregnancies before the first trimester scan. The primary source of information is the local foetal medicine databases used nationwide in which sonographers and maternal-foetal medicine specialists add data from all examinations. The Danish Foetal Medicine Database includes data on maternal characteristics including weight and height, data from ultrasound examinations and pregnancy outcomes.(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) Furthermore, the database includes data from other Danish registers: the Danish Cytogenetic Central Register,(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) the Danish National Patient Register,(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) and the Danish Medical Birth Register.(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) All Danish residents are assigned a unique personal identification number enabling linkage of data between national registers and other data sources.(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) In Denmark, health care is free and it is standard practice to offer genetic testing by chorionic villus sampling or amniocentesis when a CHD is diagnosed prenatally.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) The prenatal detection rate and accuracy of major CHD is high and the majority of parents opt for further testing.(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) A gradual transition from conventional karyotyping to chromosomal microarray was observed over the course of the study period. Postnatal genetic testing primarily by chromosomal microarray is performed in all children with syndromic suspicion. The Danish Foetal Medicine database is updated once a year with information on postnatal diagnosed congenital malformations and karyotypes.(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) The International Classification of Diseases, 10th revision code system (ICD-10) is used to code malformations in the foetus and in the infant.(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe cohort included singleton pregnancies in Denmark with an estimated due date, from ultrasound scan, between June 1, 2008 and June 1, 2018. Each woman can have multiple pregnancies during the study period. Pregnancies with a foetus or child with a chromosomal aberration were excluded from the cohort. Only pregnant women with a registered early-pregnancy weight and a height from 120 through 200 cm were included. Maternal BMI was calculated as weight in kilograms divided by the square of the height in meters (kg/m\u003csup\u003e2\u003c/sup\u003e) and BMI values are reported in that unit. Extreme observations defined as BMI\u0026thinsp;\u0026lt;\u0026thinsp;12 and BMI\u0026thinsp;\u0026gt;\u0026thinsp;60 were excluded to avoid registration errors.\u003c/p\u003e \u003cp\u003eWe identified foetuses and infants with CHDs (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) by using either the prenatal or/and the postnatal diagnoses. In all live births, postnatal CHD diagnoses were considered gold standard. The CHD diagnoses were defined by the European Surveillance of Congenital Anomalies (EUROCAT)(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Severe CHDs include the following 17 diagnoses: truncus arteriosus, double outlet right ventricle, transposition of the great arteries (TGA), univentricular heart (UVH), atrioventricular septum defect (AVSD), Tetralogy of Fallot (ToF), pulmonary atresia, tricuspid valve stenosis, Epstein\u0026rsquo;s anomaly, hypoplastic right heart syndrome, aortic valve stenosis, mitral valve stenosis, mitral insufficiency, hypoplastic left heart syndrome, coarctation of the aorta (CoA), aortic atresia, and total anomalous pulmonary venous return. Irrespective of the number of CHD diagnoses in a particular patient, the patient was only registered once as having CHDs. Furthermore, offspring with five of the most frequent subtypes of severe CHDs were identified (Table S2). These were ranked as defined by Lytzen et al.(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) with the most severe first (UVH\u0026thinsp;\u0026gt;\u0026thinsp;TGA\u0026thinsp;\u0026gt;\u0026thinsp;AVSD\u0026thinsp;\u0026gt;\u0026thinsp;CoA\u0026thinsp;\u0026gt;\u0026thinsp;ToF). If offspring had combinations of these subtypes, they were only registered once with the most severe diagnosis. ICD-10 codes for severe CHDs have been validated against hospital records with very good agreement in the Danish National Patient Register.(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) Prenatal diagnoses of 12 severe CHDs have been shown to have a very high diagnostic precision.(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eFor the calculations of interpregnancy BMI changes, a sub-cohort including women with first and second pregnancies and more than 50 weeks between estimated due dates was compiled. Maternal height was defined as the height registered in the first pregnancy. Interpregnancy BMI changes were calculated as the difference between BMI at the beginning of the first and BMI at the beginning of the second pregnancy. Differences were categorized into six groups \u0026lt; -2; -2 to \u0026lt; -1; -1 to \u0026lt;\u0026thinsp;1; 1 to \u0026lt;\u0026thinsp;2; 2 to \u0026lt;\u0026thinsp;4; and \u0026ge;\u0026thinsp;4 BMI units. The category \u0026minus;\u0026thinsp;1 to \u0026lt;\u0026thinsp;1 was defined as stable weight and used as reference.\u003c/p\u003e \u003cp\u003eAssociations between maternal BMI and offspring risk of CHDs were calculated as relative risks (RRs) with 95% CI using log-linear Poisson regression models. The models were adjusted for maternal age (\u0026lt;\u0026thinsp;20, 20\u0026ndash;24, 25\u0026ndash;29, 30\u0026ndash;34, 35\u0026ndash;39, \u0026ge;\u0026thinsp;40 years), maternal smoking status (yes/no/stopped), and year of estimated due date (1-year groups). The model was not adjusted for potential multiple pregnancies for each woman during the study period. Associations between interpregnancy BMI changes and risk of CHDs were calculated as RRs with 95% CI using log-linear Poisson regression models. Maternal BMI in first pregnancy and maternal age at second pregnancy were considered possible confounders and were adjusted for in the multivariate model. Statistical analyses were run in R version 4.2.1. Statens Serum Institut has approval from the Danish Data Protection Agency to conduct register-based studies, and the project has been approved (journal no. 19/03354 and 20/09279). The cohort study adhered to the STROBE guidelines.\u003c/p\u003e \u003cp\u003eDuring the preparation of this work the author used ChatGPT in order to improve language and readability. The authors reviewed and edited the content as needed and take full responsibility for the content of the publication.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study cohort consisted of 547 178 singleton pregnancies with estimated due dates between June 1, 2008 and June 1, 2018 when pregnancies with chromosomal aberrations and missing data were excluded as detailed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 5 498 (1.0%) offspring had CHDs. Of these 1 227 were defined as severe CHDs (0.2%). Clinical and demographic data are available in Table\u0026nbsp;1. Information on parity was not registered and therefore missing in the dataset from 2008\u0026ndash;2011 corresponding to 25% of the pregnancies. The study cohort comprised 534 478 live births (97.7%), 1 623 stillbirths (0.3%), 5 073 abortions or terminated pregnancies (0.9%), and 6 004 pregnancies with missing outcomes (1.1%). In total, 35% of the women had an early-pregnancy BMI\u0026thinsp;\u0026ge;\u0026thinsp;25, and 13% were obese (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30). The distribution of maternal BMI among the different groups and covariates can be seen in Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMaternal overweight was associated significantly with higher risk of CHDs in the offspring increasing with higher maternal BMI: for BMI 25-29.9, adjusted relative risk (aRR) 1.17 (95% CI 1.09\u0026ndash;1.25), for BMI 30-34.9, aRR 1.23 (95% CI 1.12\u0026ndash;1.36), for BMI 35-39.9, aRR 1.26 (95% CI 1.09\u0026ndash;1.46) and for BMI\u0026thinsp;\u0026ge;\u0026thinsp;40, aRR 1.81 (95% CI 1.50\u0026ndash;2.15) compared to women with an early-pregnancy BMI 18.5\u0026ndash;24.9 (Table\u0026nbsp;2). Similar results were seen for maternal BMI and severe CHDs: for BMI 25-29.9, aRR 1.20 (95% CI 1.04\u0026ndash;1.38), for BMI 30-34.9, aRR 1.28 (95% CI 1.04\u0026ndash;1.56), for BMI 35-39.9, aRR 1.47 (95% CI 1.09\u0026ndash;1.96) and for BMI\u0026thinsp;\u0026ge;\u0026thinsp;40, aRR 1.85 (95% CI 1.23\u0026ndash;2.67) compared to women with an early-pregnancy BMI 18.5\u0026ndash;24.9 (Table\u0026nbsp;2). A marginally higher risk of CHDs, when only including live births compared to all pregnancies, was seen for maternal BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 (aRR 1.24\u0026ndash;1.87; data available in Table S3).\u003c/p\u003e \u003cp\u003eThe proportion of CHD cases with one of the five specific CHD diagnoses were as follows: univentricular heart (UVH; 4.4%), transposition of the great arteries (TGA; 3.2%), atrioventricular septum defect (AVSD; 4.5%), coarctation of the aorta (CoA; 4.6%), and Tetralogy of Fallot (ToF; 2.3%). The association between maternal BMI and these specific five CHD diagnoses are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. No significant associations were seen for UVH, TGA, CoA and ToF. However, maternal BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 was associated with a significantly higher risk of AVSD in the offspring (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe sub-cohort included 107 627 women who had a first and second consecutive singleton pregnancies between June 1, 2008 and June 1, 2018 (Table\u0026nbsp;3). Mean BMI in first pregnancy was 24.9 vs. 25.8 in second pregnancy. In total, 998 had an offspring with CHDs (0.9%) in their second pregnancy. The prevalence of CHDs in the second pregnancy became higher with increased weight gain between pregnancies (0.8\u0026ndash;1.3%). Increase in maternal BMI between pregnancies were significantly associated with higher risk of CHDs in second pregnancy. However, when adjusted for maternal age in the second pregnancy and maternal BMI in the first pregnancy, only a non-significant association remained towards higher risks of any CHDs with weight gain between pregnancies (Table\u0026nbsp;3).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWhen including both pre- and postnatally diagnosed CHDs for all pregnancies, this study showed a dose-response association between high maternal BMI and risk of CHDs in the offspring. However, only a non-significant association was seen between interpregnancy BMI changes between first and second pregnancies and risk of foetal CHDs in the second pregnancies.\u003c/p\u003e \u003cp\u003eThis prospective nationwide cohort included 547 178 live births, stillbirths, abortions and terminated pregnancies in Denmark from 2008 to 2018 and showed that maternal overweight and obesity were significantly associated with a moderately higher risk of CHDs (aRR 1.17\u0026ndash;1.81) and severe CHDs (aRR 1.20\u0026ndash;1.85) in the offspring compared to women with a BMI in the normal range (BMI 18.5\u0026ndash;24.9). The study validates previous findings of an association between high maternal BMI and risk of CHDs in the offspring(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) and thereby rejects any hypothesis of this association to be caused by lower prenatal detection rates of CHDs in pregnant women with obesity. Most other studies have been limited to live births.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) A large nationwide Swedish study with two million live born children found an association between high maternal BMI and CHDs (BMI 30-34.9: OR 1.2, 95% CI 1.2\u0026ndash;1.3; BMI\u0026thinsp;\u0026ge;\u0026thinsp;40: OR 1.6, 95% CI 1.4\u0026ndash;1.8).(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) When restricting our analysis to live births (Table S3), we found significant associations of a similar magnitude between maternal BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 and foetal CHDs. Results from five specific subtypes of CHDs (UVH, TGA, AVSD, CoA and ToF) showed no significant association with maternal BMI except for AVSD (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), which was significantly associated with increased risks when maternal BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 (BMI 30 to \u0026ge;\u0026thinsp;40: aRR\u0026thinsp;=\u0026thinsp;1.65\u0026ndash;4.19). Persson et al. found a non-significant association between maternal BMI and AVSD in women with BMI\u0026thinsp;\u0026ge;\u0026thinsp;30,(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) and the same pattern was observed in other studies.(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) The lack of statistical significance in other studies might be due to few cases in each BMI group or different study designs. We examined the interpregnancy weight changes between the first and second pregnancies in 107 627 women and found a non-significant association towards higher risks of CHDs in second pregnancies preceded by a substantial BMI gain but this was not significant when data was adjusted for maternal BMI in first pregnancy and maternal age in second pregnancy (Table\u0026nbsp;3) as a result of the correlation between maternal BMI and interpregnancy weight changes. The investigations of the association between interpregnancy weight changes and risk of foetal CHDs are sparse.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) A few studies have looked at other congenital malformations and found a RR 2.3 for isolated cleft palate when maternal BMI increased\u0026thinsp;\u0026ge;\u0026thinsp;3 BMI units,(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) an association between spina bifida and interpregnancy BMI gain,(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) and a significant decrease in OR 0.62 (95% CI 0.42\u0026ndash;0.94) for gastroschisis when maternal BMI increased with \u0026ge;\u0026thinsp;3 BMI units.(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eClinical Implications\u003c/h2\u003e \u003cp\u003eLifestyle interventions to reduce risk of foetal CHDs have been suggested to be introduced before or between pregnancies.(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) Although our results only indicate a trend between interpregnancy weight changes and risk of CHDs, it does not dismiss a positive effect of weight reduction in women with obesity before pregnancy. In a setting with pre-pregnancy counselling, it is still important to advise women about the importance of BMI as a risk factor for congenital malformations,(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) obstetric and perinatal complications.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eResearch Implications\u003c/h2\u003e \u003cp\u003ePrenatal detection rates of congenital malformations decreases with increasing maternal BMI since image quality is lower in women with obesity.(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) Consequently, studies only including live births could be biased towards a higher postnatal prevalence of CHDs in women with obesity if severe foetal CHDs were not diagnosed and possibly terminated during pregnancy (Table\u0026nbsp;1). Thus, this phenomenon may at least partly explain an association between high BMI and prevalence of CHDs in live borns.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Prenatal detection rates of CHDs have improved substantially in the last decades, and in countries with prenatal screening with high detection rate of CHDs as in Denmark,(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) it is more important to include terminated pregnancies in prevalence and association studies as the rate of terminated pregnancies with the most severe CHDs likely will be higher as seen in Table\u0026nbsp;1.\u003c/p\u003e \u003cp\u003eThis study confirms the association between high maternal BMI and risk of foetal CHDs. Knowledge about the aetiology is still limited(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e) and future research should focus on combinations of other related maternal metabolic disorders linked to insulin resistance as suggested in a recent review.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThe strength of this study is the large size of the cohort and prospectively, nationwide data collection including prenatal information. Some limitation must be considered. The database did not include data on pregestational diabetes, which is known to be strongly associated with CHDs, and therefore this confounder was not included as a covariate in the analyses.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) Persson et al. excluded all women with pregestational diabetes and found a moderate association similar to the results of the present study.(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) Nor did the data include information about family history of CHDs,(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e) maternal infections or teratogenic medicine intake in pregnancy that have been associated with higher risk of CHDs.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) Since the study draws conclusions from register data, there is a risk of reporting bias and all CHD diagnoses are not validated against hospital records.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study found that risk of foetal CHDs becomes gradually higher with higher maternal BMI when including live births, stillbirths, aborted and terminated pregnancies, however, only a non-significant association was found between interpregnancy maternal BMI changes and risk of foetal CHDs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interest statement:\u003c/strong\u003e The authors report no conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study group wishes to thank sonographers and medical doctors, who have and continuously are collecting data for the Danish Foetal Medicine Database.\u003cbr\u003e\u0026nbsp;An earlier version of the article is available at a preprint server, MedRxiv (doi: https://doi.org/10.1101/2023.02.12.23285811).\u0026nbsp;\u003cbr\u003e\u0026nbsp;This study was supported by The Danish Children Heart Foundation (18-R109-A5193-26043), The A.P. Moller Foundation (19-L-0096), and Aase and Ejnar Danielsen\u0026apos;s Foundation (19-10-0493). This research has been conducted using the Danish National Biobank resource supported by the Novo Nordisk Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGH was responsible for designing the study, writing the protocol, funding acquisition, analysing data, interpreting results and writing the original draft. INT contributed to the design of the study, funding acquisition, writing the protocol, interpreting results and commented on the original draft. PLH contributed to the design of the study, writing the protocol, analysing and interpreting results, creating figures and commented on the original draft. LK contributed to the design of the study, funding acquisition and commented on the original draft. CMH conducted the data analyses and commented on the original draft. TIAS contributed to the design of the study and commented on the original draft. MC contributed to the design of the study, funding acquisition, writing the protocol, interpreting results and writing the original draft. CKE contributed to the design of the study, funding acquisition, writing the protocol, analysing data, interpreting results and writing the original draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset analysed during the current study is available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePoston L, Caleyachetty R, Cnattingius S, Corvalan C, Uauy R, Herring S, et al. Preconceptional and maternal obesity: epidemiology and health consequences. Lancet Diabetes Endocrinol. 2016;4(12):1025\u0026ndash;1036.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of Obesity and Severe Obesity Among Adults: United States, 2017\u0026ndash;2018. NCHS Data Brief. 2020(360):1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGodfrey KM, Reynolds RM, Prescott SL, Nyirenda M, Jaddoe VW, Eriksson JG, et al. Influence of maternal obesity on the long-term health of offspring. Lancet Diabetes Endocrinol. 2017;5(1):53\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCatalano PM, Shankar K. Obesity and pregnancy: mechanisms of short term and long term adverse consequences for mother and child. BMJ. 2017;356:j1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePersson M, Cnattingius S, Villamor E, Soderling J, Pasternak B, Stephansson O, et al. Risk of major congenital malformations in relation to maternal overweight and obesity severity: cohort study of 1.2 million singletons. BMJ. 2017;357:j2563.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenjamin EJ, Virani SS, Callaway CW, Chamberlain AM, Chang AR, Cheng S, et al. Heart Disease and Stroke Statistics-2018 Update: A Report From the American Heart Association. Circulation. 2018;137(12):e67-e492.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Y, Chen S, Zuhlke L, Black GC, Choy MK, Li N, et al. Global birth prevalence of congenital heart defects 1970\u0026ndash;2017: updated systematic review and meta-analysis of 260 studies. Int J Epidemiol. 2019;48(2):455\u0026ndash;463.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJenkins KJ, Correa A, Feinstein JA, Botto L, Britt AE, Daniels SR, et al. Noninherited risk factors and congenital cardiovascular defects: current knowledge: a scientific statement from the American Heart Association Council on Cardiovascular Disease in the Young: endorsed by the American Academy of Pediatrics. Circulation. 2007;115(23):2995\u0026ndash;3014.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu S, Joseph KS, Lisonkova S, Rouleau J, Van den Hof M, Sauve R, et al. Association between maternal chronic conditions and congenital heart defects: a population-based cohort study. Circulation. 2013;128(6):583\u0026ndash;589.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYe Z, Wang L, Yang T, Chen L, Wang T, Chen L, et al. Maternal Viral Infection and Risk of Fetal Congenital Heart Diseases: A Meta-Analysis of Observational Studies. J Am Heart Assoc. 2019;8(9):e011264.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMamasoula C, Bigirumurame T, Chadwick T, Addor MC, Cavero-Carbonell C, Dias CM, et al. Maternal age and the prevalence of congenital heart defects in Europe, 1995\u0026ndash;2015: A register-based study. Birth Defects Res. 2023;115(6):583\u0026ndash;594.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePierpont ME, Brueckner M, Chung WK, Garg V, Lacro RV, McGuire AL, et al. Genetic Basis for Congenital Heart Disease: Revisited: A Scientific Statement From the American Heart Association. Circulation. 2018;138(21):e653-e711.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu Y, Chen Y, Feng Y, Yu D, Mo X. Association between maternal body mass index and congenital heart defects in infants: A meta-analysis. Congenit Heart Dis. 2018;13(2):271\u0026ndash;281.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng Z, Yang T, Chen L, Wang L, Zhang S, Wang T, et al. Increased maternal Body Mass Index is associated with congenital heart defects: An updated meta-analysis of observational studies. Int J Cardiol. 2018;273:112\u0026ndash;120.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHedermann G, Hedley PL, Thagaard IN, Krebs L, Ekelund CK, Sorensen TIA, et al. Maternal obesity and metabolic disorders associate with congenital heart defects in the offspring: A systematic review. PLoS One. 2021;16(5):e0252343.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBogaerts A, Van den Bergh BRH, Ameye L, Witters I, Martens E, Timmerman D, et al. Interpregnancy weight change and risk for adverse perinatal outcome. Obstet Gynecol. 2013;122(5):999\u0026ndash;1009.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVillamor E, Cnattingius S. Interpregnancy weight change and risk of adverse pregnancy outcomes: a population-based study. The Lancet. 2006;368(9542):1164\u0026ndash;1170.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenjamin RH, Ethen MK, Canfield MA, Hua F, Mitchell LE. Association of interpregnancy change in body mass index and spina bifida. Birth Defects Res. 2019;111(18):1389\u0026ndash;1398.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenjamin RH, Ethen MK, Canfield MA, Mitchell LE. Change in prepregnancy body mass index and gastroschisis. Ann Epidemiol. 2020;41:21\u0026ndash;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVillamor E, Sparen P, Cnattingius S. Risk of oral clefts in relation to prepregnancy weight change and interpregnancy interval. Am J Epidemiol. 2008;167(11):1305\u0026ndash;1311.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEkelund CK, Kopp TI, Tabor A, Petersen OB. The Danish Fetal Medicine database. Clin Epidemiol. 2016;8:479\u0026ndash;483.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVidebech P, Nielsen J. Electronic data processing in the Danish cytogenetic central register and EDP problems of registers in general. Clin Genet. 1979;15(2):137\u0026ndash;146.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLynge E, Sandegaard JL, Rebolj M. The Danish National Patient Register. Scand J Public Health. 2011;39(7 Suppl):30\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnudsen LB, Olsen J. The Danish Medical Birth Registry. Dan Med Bull. 1998;45(3):320\u0026ndash;323.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePedersen CB, Gotzsche H, Moller JO, Mortensen PB. The Danish Civil Registration System. A cohort of eight million persons. Dan Med Bull. 2006;53(4):441\u0026ndash;449.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVedel C, Hjortshoj TD, Jorgensen DS, Tabor A, Rode L, Sundberg K, et al. Prevalence of chromosomal disorders in cases with congenital heart defect: registry-based study from Denmark between 2008 and 2018. Ultrasound Obstet Gynecol. 2023;61(1):40\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLytzen R, Vejlstrup N, Bjerre J, Petersen OB, Leenskjold S, Dodd JK, et al. Live-Born Major Congenital Heart Disease in Denmark: Incidence, Detection Rate, and Termination of Pregnancy Rate From 1996 to 2013. JAMA Cardiology. 2018;3(9):829\u0026ndash;837.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVedel C, Tabor A, Jorgensen FS, Rode L, Sundberg K, Vejlstrup N, et al. Prenatal detection rate of major congenital heart defects in Copenhagen from 2015 to 2018. Ultrasound Obstet Gynecol. 2021;58(2):324\u0026ndash;325.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreenlees R, Neville A, Addor MC, Amar E, Arriola L, Bakker M, et al. Paper 6: EUROCAT member registries: organization and activities. Birth Defects Res A Clin Mol Teratol. 2011;91 Suppl 1:S51-S100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgergaard P, Hebert A, Bjerre J, Sorensen KM, Olesen C, Ostergaard JR. Children diagnosed with congenital cardiac malformations at the national university departments of pediatric cardiology: positive predictive values of data in the Danish National Patient Registry. Clin Epidemiol. 2011;3:61\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePersson M, Razaz N, Edstedt Bonamy AK, Villamor E, Cnattingius S. Maternal Overweight and Obesity and Risk of Congenital Heart Defects. J Am Coll Cardiol. 2019;73(1):44\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCai GJ, Sun XX, Zhang L, Hong Q. Association between maternal body mass index and congenital heart defects in offspring: a systematic review. Am J Obstet Gynecol. 2014;211(2):91\u0026ndash;117.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlock SR, Watkins SM, Salemi JL, Rutkowski R, Tanner JP, Correia JA, et al. Maternal pre-pregnancy body mass index and risk of selected birth defects: evidence of a dose-response relationship. Paediatr Perinat Epidemiol. 2013;27(6):521\u0026ndash;531.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgopian AJ, Moulik M, Gupta-Malhotra M, Marengo LK, Mitchell LE. Descriptive epidemiology of non-syndromic complete atrioventricular canal defects. Paediatr Perinat Epidemiol. 2012;26(6):515\u0026ndash;524.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHelle E, Priest JR. Maternal Obesity and Diabetes Mellitus as Risk Factors for Congenital Heart Disease in the Offspring. J Am Heart Assoc. 2020;9(8):e011541.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBest KE, Tennant PW, Bell R, Rankin J. Impact of maternal body mass index on the antenatal detection of congenital anomalies. BJOG. 2012;119(12):1503\u0026ndash;1511.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUhden M, Knippel AJ, Stressig R, Hammer R, Siegmann H, Froehlich S, et al. Impact of maternal obesity and maternal overweight on the detection rate of fetal heart defects and the image quality of prenatal echocardiography. Ultraschall Med. 2011;32 Suppl 2:E108-114.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOyen N, Diaz LJ, Leirgul E, Boyd HA, Priest J, Mathiesen ER, et al. Prepregnancy Diabetes and Offspring Risk of Congenital Heart Disease: A Nationwide Cohort Study. Circulation. 2016;133(23):2243\u0026ndash;2253.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrodwall K, Greve G, Leirgul E, Tell GS, Vollset SE, Oyen N. Recurrence of congenital heart defects among siblings-a nationwide study. Am J Med Genet A. 2017;173(6):1575\u0026ndash;1585.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-obesity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ijo","sideBox":"Learn more about [International Journal of Obesity](http://www.nature.com/ijo/)","snPcode":"41366","submissionUrl":"https://mts-ijo.nature.com/cgi-bin/main.plex","title":"International Journal of Obesity","twitterHandle":"@intjobesity","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"atrioventricular septum defect, coarctation of the aorta, epidemiological study, maternal BMI, prenatal congenital heart defects, register-based study, severe congenital heart defects, The Danish Foetal Medicine database, Tetralogy of Fallot, transposition of the great arteries, univentricular heart","lastPublishedDoi":"10.21203/rs.3.rs-3442362/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3442362/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eObjective\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo evaluate the association between maternal BMI and congenital heart defects (CHDs) in the offspring when including live births, stillbirths, aborted and terminated pregnancies and to investigate if maternal interpregnancy weight changes between the first and second pregnancy influences risk of foetal CHDs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA nationwide cohort study of all singleton pregnancies in Denmark from 2008 to 2018. Data were retrieved from the Danish Foetal Medicine Database, which included both pre- and postnatal diagnoses of CHDs. Children or foetuses with chromosomal aberrations were excluded. Relative risks were calculated using log-linear Poisson models for CHDs overall, severe CHDs and for five of the most prevalent subtypes of CHDs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOf the 547 178 pregnancies included in the cohort, 5 498 had CHDs (1.0%). Risk of CHDs became gradually higher with higher maternal BMI; for BMI 30-34.9 kg/m\u003csup\u003e2\u003c/sup\u003e, adjusted relative risk (aRR) 1.23 (95% CI 1.12\u0026ndash;1.36), for BMI 35-39.9 kg/m\u003csup\u003e2\u003c/sup\u003e, aRR 1.26 (95% CI 1.09\u0026ndash;1.46) and for BMI\u0026thinsp;\u0026ge;\u0026thinsp;40 kg/m\u003csup\u003e2\u003c/sup\u003e, aRR 1.81 (95% CI 1.50\u0026ndash;2.15). Data was adjusted for maternal age, smoking status and year of estimated due date. The same pattern was seen for the subgroup of severe CHDs. Among the atrioventricular septal defects (n\u0026thinsp;=\u0026thinsp;245), a particularly strong association with maternal BMI\u0026thinsp;\u0026ge;\u0026thinsp;40 kg/m\u003csup\u003e2\u003c/sup\u003e was seen, aRR 4.19 (95% CI 2.13\u0026ndash;7.42). 107 627 women were identified with their first and second pregnancies in the cohort. Interpregnancy BMI change was associated, albeit not statistically significant, with risk of CHDs in the second pregnancy when adjusting for maternal age and BMI, with an aRR 1.27 (95% CI 0.96\u0026ndash;1.64) among persons with a BMI increase of \u0026ge;\u0026thinsp;4 kg/m\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eRisk of foetal CHDs became gradually higher with higher maternal BMI, but only a non-significant association was seen for interpregnancy weight changes and risk of CHDs.\u003c/p\u003e","manuscriptTitle":"Maternal obesity, interpregnancy weight changes and congenital heart defects in the offspring: a nationwide cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-10-18 15:50:49","doi":"10.21203/rs.3.rs-3442362/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2023-11-09T14:42:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2023-11-06T16:18:11+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2023-10-23T19:03:16+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2023-10-23T14:12:46+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2023-10-23T11:31:05+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2023-10-16T20:31:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-10-16T16:45:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Obesity","date":"2023-10-13T13:34:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-10-13T13:34:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-obesity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"ijo","sideBox":"Learn more about [International Journal of Obesity](http://www.nature.com/ijo/)","snPcode":"41366","submissionUrl":"https://mts-ijo.nature.com/cgi-bin/main.plex","title":"International Journal of Obesity","twitterHandle":"@intjobesity","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"40fd5655-2995-40e0-9fef-b99082e5f234","owner":[],"postedDate":"October 18th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":25425749,"name":"Health sciences/Risk factors"},{"id":25425750,"name":"Health sciences/Diseases"}],"tags":[],"updatedAt":"2024-05-12T07:05:10+00:00","versionOfRecord":{"articleIdentity":"rs-3442362","link":"https://doi.org/10.1038/s41366-024-01531-5","journal":{"identity":"international-journal-of-obesity","isVorOnly":false,"title":"International Journal of Obesity"},"publishedOn":"2024-05-11 04:00:00","publishedOnDateReadable":"May 11th, 2024"},"versionCreatedAt":"2023-10-18 15:50:49","video":"","vorDoi":"10.1038/s41366-024-01531-5","vorDoiUrl":"https://doi.org/10.1038/s41366-024-01531-5","workflowStages":[]},"version":"v1","identity":"rs-3442362","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3442362","identity":"rs-3442362","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}