Journal of Perinatology (2015) 35, 198–203 © 2015 Nature America, Inc. All rights reserved 0743-8346/15 www.nature.com/jp
ORIGINAL ARTICLE
A spectrum project: preterm birth and small-for-gestational age among infants with birth defects F Miquel-Verges1, BS Mosley2, AS Block2 and CA Hobbs2 OBJECTIVE: The aim of this study is to investigate the association between birth defects (BDs), prematurity and small-forgestational age (SGA) in a population-based sample. STUDY DESIGN: Participants were singleton live births enrolled in the National Birth Defects Prevention Study, including 18 737 case infants with one or more BD and 7999 controls. Logistic regression models to evaluate associations between BDs, prematurity and fetal growth were computed while adjusting for covariates. RESULT: Cases were significantly more likely to be born prematurely than controls, particularly at 24 to 28 weeks of gestation. The highest odds ratios for preterm birth were found for intestinal atresia, anencephaly, gastroschisis and esophageal atresia. Infants with BDs were also significantly more likely to be SGA than controls (17.2 and 7.8%). CONCLUSION: Infants with BDs are more likely than controls to be born prematurely and SGA. Findings from this study present additional evidence demonstrating a complex interaction between the development of BDs, prematurity and intrauterine growth. Journal of Perinatology (2015) 35, 198–203; doi:10.1038/jp.2014.180; published online 2 October 2014
INTRODUCTION Birth defects (BDs) and prematurity are the leading causes of infant mortality in the United States.1 It is estimated that 11.72% of infants are born prematurely, at o 37 weeks of completed gestation.2 The risk of premature birth is significantly higher for infants with BDs than for those without BDs.3–6 Also, infants with BDs are more likely to have low birth weight than infants without BDs.7 BDs represent significant challenges in medical care but when compounded by prematurity and/or poor growth, the ability to intervene clinically is often limited and resource utilization, morbidity and mortality are increased.4 The etiology of most nonsyndromic BDs is unknown and may share risk factors with preterm birth and intrauterine growth restriction.8,9 Genetic factors as well as maternal characteristics and environmental exposures likely contribute to the occurrence of BDs and preterm birth.10 Maternal characteristics associated with BDs and/or preterm birth include maternal diabetes mellitus, obesity, tobacco use and poor folic acid intake.11–14 Restricted growth during fetal life is a risk factor for morbidity and mortality in preterm newborns who may or may not have BDs.15 Infants with a birth weight of o10th percentile for gestational age are classified as small-for-gestational age (SGA). An increased risk for preterm birth and intrauterine growth restriction has been associated with individual BDs, including heart defects, brain defects, renal agenesis, intestinal atresia, tracheoesophageal fistula, esophageal atresia, anorectal atresia, omphalocele, biliary atresia, limb reduction defects and gastroschisis.3,5 Previous studies have reported secondary analysis of BD registry data and few have been able to adjust for maternal covariates such as maternal body mass index, diabetes, folic acid intake and maternal tobacco use.
The current study investigated the association between a spectrum of BDs, preterm birth and intrauterine growth restriction in a large case–control population-based sample in which maternal reports of covariates were obtained through detailed and structured interviews. By better understanding the relationship between BDs, intrauterine growth and preterm birth, we may find common and overlapping risk factors, the identification of which are crucial to developing effective interventions in the preconception and prenatal period. METHODS Study population Eligible case and control study participants were enrolled in the National Birth Defects Prevention Study (NBDPS) and born between October 1997 and 31 December 2007. The NBDPS is a multi-site, population-based, case– control study conducted in the United States between 1997 and June 2013, with the primary goal of identifying etiologic factors for nonsyndromic structural BDs. The study population and eligibility criteria for the NBDPS have been previously outlined.16 Briefly, subjects with 1 or more of over 30 eligible BDs were identified through population-based BD surveillance registries in 10 states (Arkansas, California, Iowa, Georgia, Massachusetts, New Jersey, New York, North Carolina, Texas and Utah) using uniform diagnostic criteria. Clinical data were abstracted by trained surveillance program staff members. BD cases were reviewed by clinical geneticists to determine eligibility. Infants with chromosomal abnormalities or single gene disorders were excluded. Controls were live-born infants without BDs, who were randomly selected either from each Center’s live birth population through birth certificates or birth hospital delivery records. Mothers of case and control infants were interviewed by telephone using a computerized automated telephone interview between 6 weeks and 24 months following completion of pregnancy. The computerized
1 Neonatology Section, College of Medicine, University of Arkansas for Medical Sciences, Arkansas Children’s Hospital Research Institute, Little Rock, AR, USA and 2Birth Defects Research Section, Department of Pediatrics, College of Medicine, University of Arkansas for Medical Sciences, Arkansas Children’s Hospital Research Institute, Little Rock, AR, USA. Correspondence: Dr CA Hobbs, Department of Pediatrics, College of Medicine, University of Arkansas for Medical Sciences, 13 Children’s Way, Slot 512-40, Little Rock, 72202, AR, USA. E-mail: [email protected] Received 16 April 2014; revised 17 July 2014; accepted 5 August 2014; published online 2 October 2014
Preterm and SGA among infants with birth defects F Miquel-Verges et al automated telephone interview ascertains information regarding maternal demographics, medical history, prenatal care and pregnancy history, environmental history and family history of BDs. Mothers of cases and controls spoke English or Spanish. Institutional review boards for participating Centers and from the Centers for Disease Control and Prevention approved the study. All subjects gave written informed consent. For minors, written informed consent was obtained from their legal guardian for DNA collection.
Classification of BDs As with previous NBDPS papers,12,13 cases included in this study have one or more eligible BD. BDs were categorized as previously described in NBDPS studies.17 Only BD categories with 100 or more eligible cases with completed interviews were evaluated. Categories included are neural tube defects, hydrocephaly, holoprosencephaly, congenital cataract, anotia or microtia, glaucoma or anterior chamber defects, seven different heart defect phenotypes (conotruncal heart defects, septal heart defects, right and left obstructive heart defects, atrioventricular septal heart defects, anomalous pulmonary venous return and single ventricle), choanal atresia, oral clefts, esophageal atresia, intestinal atresia or stenosis, anorectal atresia or stenosis, hypospadias, biliary atresia, craniosynostosis, diaphragmatic hernia, gastroschisis and omphalocele. Subjects affected by BDs were classified as having isolated or multiple defects by clinical geneticists. Subjects classified as having an isolated BD had: (a) one major defect, (b) one major and ⩾ 1 minor defects, (c) major defects that affect one organ system only or (d) a major defect with a well-described sequence of related defects without any other unrelated major defects. Those with multiple BDs had either ⩾ 2 major unrelated defects in different organ systems or multiple associated major defects that were not associated with any known syndrome.18 Congenital heart defects (CHDs) were classified as simple (well-defined, pure heart defect), associated (combination of two or more simple heart defects that occur frequently together but cannot be easily categorized under one of their components) and complex (heart phenotypes characterized by independent defects in multiple cardiac structures). Simple and associated CHDs were included in this analysis whereas complex CHDs were excluded.19
Growth parameters Gestational age and birth weight measures were obtained from each subject's clinical records. Week of gestational age at birth was based upon the following hierarchical system: (1) ultrasound performed before 14 weeks of gestation; (2) ultrasound between 14 and 27 weeks gestation; (3) standard neonatal exam and (4) last menstrual cycle. Infants born between 24 and 42 weeks of gestation were included in the analyses and categorized as follows: 24 to 28 weeks of gestation, 29 to 33 weeks, 34 to 36 weeks and 37 to 42 (up to 42) weeks. For comparison, those born between 37 and 42 weeks were considered the referent category. Intrauterine fetal growth was categorized using United States national standards for sex and gestational age-specific birth weights.20 Each infant was classified as: SGA (o 10th percentile), appropriate for gestational age (10 to 90th percentile) or large-for-gestational age (490th percentile).
Statistical analysis All analysis were limited to participants who had completed interviews. Descriptive statistics for sample characteristics were compared using χ2tests or t-tests. These factors included maternal race/ethnicity, education, age, infant sex, parity, maternal body mass index prior to pregnancy, diabetes, dietary folate intake prior to pregnancy, periconception folic acid supplement use and smoking or alcoholic drinking at any point from 3 months before pregnancy to delivery. Multiple logistic regression models were computed to model prematurity as a function of case–control status and maternal and infant covariates. Available maternal and infant characteristics determined to be statistically significant (α = 0.05) in the bivariate analyses and/or associated with prematurity or BDs in previously published research were included as covariates. Prematurity results were stratified by isolated and multiple defect groups. Infants born large-for-gestational age were excluded from the fetal growth/SGA analysis. All analyses were performed in SAS (version 9.2; SAS, Gary, NC, USA). © 2015 Nature America, Inc.
RESULTS Between 1997 and 2007, among live-born, singleton infants there were 19 197 with eligible BDs and 8164 controls. Interview participation rates for cases and controls were above 70%. Further review required the exclusion of 68 infants who did not have final review by clinical geneticist or were identified during final review to have a probable or certain syndrome; 17 mothers with known viral infections (14 cases, 3 controls); 169 infants for whom the gestational age was missing (167 cases, 2 controls) and 849 infants for whom the documented gestational age was o 24 weeks (440 cases, 11 controls) or more than 42 weeks (243 cases, 155 controls). Our final study population consisted of 18 737 cases and 7 999 controls. Maternal and infant characteristics are presented in Table 1. Mothers of cases and controls were primarily white, nonHispanic (59%) with an average age at delivery of 26.9 years. The distribution of obesity and diabetes mellitus varied between mothers of cases and controls; mothers of cases were more likely to be obese, have Type 1 or 2 diabetes mellitus and smoke tobacco. Infants with BDs were more likely to be male. Distribution of gestational age at birth and birth weight is shown in Table 2. Infants with BDs were significantly more likely to be born preterm than controls, particularly at earlier gestational ages. Among cases, 2.1 and 6.3% of infants were born at 24 to 28 weeks and 29 to 33 weeks, respectively. Whereas among control infants, 0.4 and 1.5% were born at these earlier gestational ages (P o0.001). Overall, 22.5% of cases were born prematurely whereas only 8.3% of controls were born before 37 weeks of gestation. Infants with BDs were significantly more likely to be SGA than controls (17.2% vs 7.8%, respectively). When controlling for potential confounders and comparing three categories of preterm births to full-term births, the odds of being born very preterm (24 to 28 weeks) appear to increase across all selected defects where data were available (Table 3). Because adjusted results were similar to crude results (within 10%), only the adjusted results are presented. Infants with septal heart defects (odds ratio (OR), 12.8; 95% confidence interval (CI), 8.5 to 19.3), intestinal atresia/stenosis (OR, 13.2; 95% CI, 6.6 to 26.7) and esophageal atresia (OR, 11.1; 95% CI, 5.2 to 23.7) had the highest odds of being born between 24 to 28 weeks when compared with controls. Those infants with gastroschisis (OR, 19.5; 95% CI, 14.0 to 27.0), intestinal atresia/ stenosis (OR, 22.0; 95% CI, 15.8 to 30.7), anencephaly (OR, 14.6; 95% CI, 7.4 to 28.9), esophageal atresia (OR, 12.8; 95% CI, 8.9 to 18.5), hydrocephaly (OR, 8.3; 95% CI, 5.4 to 12.7) or choanal atresia (OR, 9.6; CI, 4.7 to 19.5) were more likely to be born between 29 and 33 weeks gestation when compared with controls. The odds of prematurity in the 34 to 36 week period were highest among the same five BD: gastroschisis (OR, 16.6; 95% CI, 13.6 to 20.2), intestinal atresia/stenosis (OR, 10.3; 95% CI, 8.2 to 12.9), anencephaly (OR, 6.6; 95% CI, 4.1 to 10.6), esophageal atresia (OR, 5.7; 95% CI, 4.5 to 7.4) and hydrocephaly (OR, 5.3; 95% CI, 4.0 to 7.1). Infants with gastroschisis and intestinal atresia/stenosis were more likely to be born prematurely than infants with any other BD studied (data not shown). Of the 852 infants with gastroschisis, 14 (1.6%) were born between 24 and 28 weeks, 112 (13.1%) between 29 and 33 weeks, 399 (46.8%) between 34 and 36 weeks and only 327 (38.3%) were born at term. Similarly, of the 465 infants with intestinal atresia, 13 (2.7%) were born between 24 and 28 weeks, 78 (16.7%) between 29 and 33 weeks, 154 (33.1%) between 34 and 36 weeks, and only 220 (47.3%) were born at term. Across all BD categories studied, odds of prematurity were higher for infants with multiple defects when compared with isolated defects, except for glaucoma and anterior chamber defects (Supplementary Table 1). Overall, those with any isolated BD had 2.8 (95% CI, 2.6 to 3.1) times the odds of being born Journal of Perinatology (2015), 198 – 203
199
Preterm and SGA among infants with birth defects F Miquel-Verges et al
200 Table 1. Demographic and maternal characteristics of study participants with and without birth defects, National Birth Defect Prevention Study, 1997 to 2007
Table 2.
Gestational age and fetal growth at birth among cases and
controls Cases
Birth defects
No.
Percent
Without birth defects a
Bivariate analysisb
a
No. Percent
Total subjects
18 737
Maternal race/ethnicity White, non-Hispanic Black, non-Hispanic Hispanic Other races
11 085 1802 4432 1375
59.3 9.6 23.7 7.4
4684 875 1824 590
58.7 11.0 22.9 7.4
P = 0.0780
3367 4820
18.2 26.1
1348 1913
17.1 24.2
Po0.0001
5078 5235
27.4 28.3
2156 2476
27.3 31.4
Maternal age o20 Years 2543 20–29 Years 9498 30–39 Years 6284 40+ Years 412 Mean age: years (s.d.) 27.0
13.6 50.7 33.5 2.2 (6.3)
1071 4159 2658 111 26.8
13.4 52.0 33.2 1.4 (6.1)
Maternal education Less than high school High school degree/ equivalent 13–15 Years ⩽ 16 Years
7999
P = 0.0001
P = 0.1141
Infant sex Male Female
11 427 7950
59.0 41.0
4056 3937
50.7 49.3
Po0.0001
Parity Primiparity Multiparity
7940 10 736
42.5 57.5
3173 4807
39.8 60.2
Po0.0001
1008 9313 4090
5.6 52.1 22.9
415 4221 1738
5.4 55.1 22.7
Po0.0001
3477 25.5
19.4 (6.2)
1289 25.0
16.8 (5.7)
16 757 447 1465
89.8 2.4 7.8
7393 56 528
92.7 0.7 6.6
Po0.0001
5333
28.7
1988
25.0
Po0.0001
4781 4308 4194
25.7 23.1 22.5
1987 1988 1988
25.0 25.0 25.0
Folic acid supplement use Yes, B1-P1 9298 No, B1-P1 9332
49.9 50.1
4062 3891
51.1 48.9
P = 0.0816
Maternal smoking, B3-P9 Yes 4107 No 14 429
22.2 77.8
1530 6382
19.3 80.7
Po0.0001
Maternal drinking, B3-P9 Yes 8286 No 10 208
44.8 55.2
3620 4279
45.8 54.2
P = 0.1255
Maternal diabetes None Type 1 or 2 Gestational Maternal dietary folate 25th Percentile or less 26–50th Percentile 51–75th Percentile ⩾ 75th Percentile
Po0.0001
Abbreviations: B1, 1 month before pregnancy; B3, 3 months before pregnancy; BMI, body mass index; P1, first month of pregnancy; P9, 9th month of pregnancy. aPercentages reflect the exclusion of missing data for each characteristic. bBivariate analysis reflect P-values from Student's t-test for continuous data (maternal age and BMI) and χ2-test for categorical data (all variables). c1508 hypospadias cases included in male birth defect counts.
Journal of Perinatology (2015), 198 – 203
Gestational age at birth 24–28 Weeks 29–33 Weeks 34–36 Weeks 37–41 Weeks
%
No.
Bivariate analysis
%
389 2.1 31 0.4 P o0.0001 1185 6.3 122 1.5 2640 14.1 508 6.4 14 523 77.5 7338 91.7
Fetal growth at birtha Small for gestation 3194 17.2 622 7.8 P o0.0001 Appropriate for gestation 13 966 75.1 6602 82.8 Large for gestation 1429 7.7 750 9.4 a Percentages reflect the exclusion of missing data for fetal growth (148 cases, 25 controls).
c
Maternal BMI Underweight: o 18.5 Normal: 18.5 to o25 Overweight: 25 to o30 Obese: ⩽ 30 Mean BMI value (s.d.)
No.
Controls
premature as healthy controls, whereas the adjusted odds ratio comparing those with multiple BDs to controls was 5.9 (95% CI, 5.2 to 6.6). Table 4 illustrates the association of fetal growth and selected BDs. Large-for-gestational age cases and controls were removed from this analysis. Overall, infants with BDs studied were roughly twice as likely to be born SGA than infants without BDs when controlling for potential confounders. The largest odds ratio for being SGA was among infants with anencephaly, (OR, 55.3; 95% CI, 33.5 to 91.1), esophageal atresia (OR, 5.2; 95% CI, 4.1 to 6.6), gastroschisis (OR, 4.6; 95% CI, 3.8 to 5.5) and hypospadias (OR, 3.7; 95% CI, 3.1 to 4.5). As with the BD and prematurity analysis, infants with multiple BDs were more likely than those with isolated BDs to be SGA (data not shown). DISCUSSION Our findings from the largest population-based case–control study of BDs conducted in the United States confirms findings from other studies that fetuses with major BDs are more likely to be born prematurely and SGA than fetuses without BDs.3,11,21,22 The NBDPS clinical and interview data allowed for closer evaluation of the association between BDs and all degrees of prematurity while controlling for important maternal covariates. Previous published studies were based only on abstracted medical records collected by population-based registries,3 or data from research networks. Unlike previous studies, NBDPS clinical algorithms applied by board-certified clinical dysmorphologists ensured application of uniform diagnostic criteria, and interviews with mothers of infants with BDs allowed for more comprehensive information about maternal preconceptional and prenatal exposures. Among the spectrum of BDs included in the current study cases were at least twice as likely to be born prematurely than controls, across all gestational ages. The relationship between BDs and preterm birth was strongest among infants with gastroschisis, intestinal atresia or stenosis, omphalocele, esophageal atresia and septal heart defects. These findings are consistent with previous studies that have shown a particularly strong association between esophageal and intestinal atresias and premature birth.3 Poor intrauterine growth is a known risk factor for morbidity and mortality in the neonatal period, particularly for premature infants.15,23 Infants with BDs are more likely to be SGA than infants without BDs.24 The relationship is particularly strong for anencephaly, esophageal atresia, intestinal atresia and gastroschisis. Our data confirm previous findings that infants with CHDs, the most © 2015 Nature America, Inc.
Preterm and SGA among infants with birth defects F Miquel-Verges et al
201 Table 3.
Adjusted odds ratios of the association of select birth defect phenotypes and various levels of prematurity 37–41 Weeks
Controls Total all select birth defects Anencephaly Spina bifida Hydrocephaly Holoprosencephaly Cataracts Anotia/microtia Glaucoma/ anterior chamber defects Conotruncal CHD Septal CHD Right ventricular obstructive CHD Left ventricular obstructive CHD Atrioventricular septal defects Anomalous pulmonary venous return Single ventricle Choanal atresia Cleft palate w/o cleft lip Cleft lip w or w/o cleft palate Esophageal atresia Intestinal atresia/stenosis Anorectal atresia/stenosis Hypospadiasb Biliary atresia Craniosynostosis Diaphragmatic hernia Gastroschisis Omphalocele
34–36 Weeks
No.
No.
6913 13 666 60 595 198 72 183 350 104 1389 2371 952 1144 175 205 192 72 883 1702 272 220 494 1100 94 830 425 327 167
477 2485 27 95 74 14 19 44 8 187 487 157 132 34 23 29 15 116 177 103 154 87 183 19 81 70 399 42
aOR (95% CI) 1 2.6 6.6 2.3 5.3 2.4 1.5 1.6 1.1 1.9 2.7 2.3 1.7 2.6 1.6 1.9 3.2 1.9 1.5 5.7 10.3 2.5 2.7 3.0 1.5 2.4 16.6 3.8
(reference) (2.3, 2.9) (4.1, 10.6) (1.8, 3.0) (4.0, 7.1) (1.3, 4.3) (0.9, 2.4) (1.1, 2.3) (0.5, 2.3) (1.6, 2.3) (2.4, 3.1) (1.9, 2.8) (1.4, 2.1) (1.8, 3.9) (1.0, 2.5) (1.2, 2.9) (1.8, 5.6) (1.5, 2.3) (1.2, 1.8) (4.5, 7.4) (8.2, 12.9) (1.9, 3.2) (2.1, 3.3) (1.8, 5.0) (1.1, 1.9) (1.8, 3.1) (13.6, 20.2) (2.7, 5.4)
29–33 Weeks No. 117 1102 12 22 34 7 5 20 3 56 319 86 50 16 5 9 10 53 63 54 78 40 124 6 31 35 112 23
aOR (95% CI) 1 4.7 14.6 2.1 8.3 5.5 1.7 3.6
(reference) (3.9, 5.7) (7.4, 28.9) (1.3, 3.4) (5.4, 12.7) (2.4, 12.6) (0.7, 4.3) (2.2, 6.1)
2.2 7.0 5.2 2.6 4.7 1.4 2.2 9.6 3.6 2.2 12.8 22.0 4.2 6.6 3.5 2.4 5.1 19.5 7.8
(1.6, 3.1) (5.6, 8.8) (3.9, 7.0) (1.8, 3.7) (2.6, 8.2) (0.5, 3.5) (1.1, 4.7) (4.7, 19.5) (2.6, 5.1) (1.6, 3.0) (8.9, 18.5) (15.8, 30.7) (2.9, 6.2) (4.7, 9.2) (1.5, 8.2) (1.6, 3.6) (3.4, 7.6) (14.0, 27.0) (4.8, 12.7)
a
24–28 Weeks No. 29 361 8 7 7 2 9 2 1 27 146 37 11 3 4 3 1 7 18 11 13 12 39 1 8 7 14 8
aOR (95% CI) 1 6.2 29.8 3.1 7.7
(reference) (4.2, 9.1) (11.4, 77.9) (1.3, 7.3) (3.2, 18.6) a
10.8 (4.9, 24.0) a a
4.6 12.8 9.3 2.3
(2.7, (8.5, (5.6, (1.1, a
8.0) 19.3) 15.4) 4.8)
a a a
2.0 2.6 11.1 13.2 5.6 8.7
(0.8, (1.4, (5.2, (6.6, (2.7, (4.6,
4.7) 4.8) 23.7) 26.7) 11.3) 16.3)
2.4 3.8 9.1 12.6
(1.1, (1.6, (4.3, (5.4,
5.5) 9.1) 19.4) 29.6)
a
Abbreviations: aOR, adjusted odds ratio; CI, confidence interval; CHD, congenital heart defect. aOdds ratio not reported due to cell count o5. bHypospadias models included male infants only. Covariates: maternal race/ethnicity, education, infant sex, parity, maternal body mass index, type 1/2 diabetes, dietary folate, smoking during pregnancy and study center. Referent category: infants born between 37 and 41 weeks.
prevalent BDs, are twice as likely to be SGA than those without BDs.25 Multiple factors may help to explain the association between BD, prematurity and SGA. The BD may cause poor intrauterine growth and/or preterm birth. For example, esophageal and intestinal atresia are associated with polyhydramnios that may lead to preterm labor and increase the risk of prematurity. Obstetrical complications, such as polyhydramnios, may be more likely to cause preterm labor during the last trimester than during the mid-trimester when very early births (23 to 28 weeks of gestation) occur.3 Another factor that may increase the likelihood of prematurity among fetuses with BDs is increased medical surveillance for fetuses prenatally diagnosed with a serious BD. For example, it is well established that gastroschisis is associated with a risk of intrauterine hypoxia and later-term fetal death.26 For infants with gastroschisis, planned preterm delivery has been advocated before development of bowel dilation, bowel complications and fetal death.26 The obstetrical management of affected pregnancies requires increased surveillance that may lead to increased intervention resulting in a greater number of infants with gastroschisis being delivered between 34 and 36 weeks gestation (late prematurity). For some infants born prematurely, increased medical surveillance in the nursery may increase the detection of BDs. For example, premature infants are more likely to have echocardiograms than term infants increasing the likelihood of being diagnosed with small septal defects. A third factor that may account for an association between BDs and prematurity and SGA is a common etiologic pathway for BDs, © 2015 Nature America, Inc.
poor intrauterine growth and preterm birth. We and many others hypothesize that a complex interplay between genetic, epigenetic and environmental factors causes BDs, prematurity and intrauterine growth restriction. Supporting evidence has suggested that the factors involved may vary by BD phenotype. Vascular compromise has been implicated in the development of a number of BDs, including neural tube, heart, limb and abdominal defects, and also in the development of intrauterine growth retardation.27–29 Micronutrients may also have a role in the complex relationship between the development of a BD and intrauterine growth. Maternal folate metabolism is associated with neural tube, cardiac and limb defects,30–34 and at least in some studies, with prematurity3,21 and low birth weight.11,24 Other micronutrients, including thiamin, riboflavin, vitamin A, vitamin E and zinc, have been implicated in both the risk of preterm delivery and BDs.35,36 Diabetes mellitus is known to increase the32 risk of some BDs, including both cardiac and noncardiac defects such as anencephaly, anotia/microtia, cleft lip and palate, limb anomalies, renal agenesis and anorectal atresia.13,37–40 Maternal obesity has been shown to increase the risk of spina bifida, heart defects, anorectal atresia, hypospadias, limb reduction defects, diaphragmatic hernia and omphalocele and has also been associated with increased risk of premature birth.12,14 Maternal exposure to tobacco increases the risk of some BDs and prematurity and SGA.41,42 Poor fetal growth increases the morbidity and mortality of infants with BDs.43 The outcomes and survival of infants with CHDs is significantly worse for those born preterm, particularly at earlier gestational ages.43 The neonatal course and long-term outcomes of infants with BDs requiring surgeries and lengthy Journal of Perinatology (2015), 198 – 203
Preterm and SGA among infants with birth defects F Miquel-Verges et al
202 Table 4.
Association of select birth defect phenotypes and small-for-gestational agea No. Appropriate for gestational age
Controls Total all birth defects Anencephaly Spina bifida Hydrocephaly Holoprosencephaly Cataracts Anotia/microtia Glaucoma/anterior chamber defects Conotruncal CHD Septal CHD Right ventricular obstructive CHD Left ventricular obstructive CHD Atrioventricular septal defects Anomalous pulmonary venous return Single ventricle Choanal atresia Cleft palate w/o cleft lip Cleft lip w or w/o cleft palate Esophageal atresia Intestinal atresia/stenosis Anorectal atresia/stenosis Hypospadiasb Biliary atresia Craniosynostosis Diaphragmatic hernia Gastroschisis Omphalocele
6212 13 133 22 558 215 64 165 304 89 1225 2489 944 1052 170 177 175 73 798 1523 297 369 472 1012 95 721 411 545 184
Small-for-gestational age No.
aOR (95% CI)
588 2995 83 104 37 22 25 76 17 314 546 171 181 42 41 40 18 175 265 133 73 122 326 11 80 87 291 40
1 [reference] 2.4 (2.2, 2.7) 55.3 (33.5, 91.1) 2.1 (1.7, 2.7) 1.7 (1.2, 2.5) 3.5 (2.1, 5.8) 1.6 (1.0, 2.5) 2.7 (2.0, 3.5) 2.2 (1.3, 3.7) 2.8 (2.4, 3.3) 2.3 (2.0, 2.6) 2.0 (1.7, 2.4) 2.1 (1.7, 2.5) 2.7 (1.9, 3.9) 2.6 (1.8, 3.7) 2.5 (1.7, 3.6) 3.0 (1.8, 5.2) 2.5 (2.0, 3.0) 1.9 (1.6, 2.2) 5.2 (4.1, 6.6) 2.0 (1.5, 2.6) 2.7 (2.2, 3.4) 3.7 (3.1, 4.5) 1.1 (0.6, 2.2) 1.4 (1.1, 1.8) 2.3 (1.8, 3.0) 4.6 (3.8, 5.5) 2.2 (1.5, 3.2)
Abbreviations: aOR, adjusted odds ratio; CI, confidence intervals; CHD, congenital heart defect; w or w/o, with or without. aInfants large-for-gestational age were excluded from these analyses. bHypospadias models included male infants only. Covariates: maternal race/ethnicity, education, infant sex, parity, maternal body mass index, type 1/2 diabetes, dietary folate, smoking during pregnancy and study center.
hospitalizations are complicated by low birth weight. At 18 to 22 months' corrected age, infants with extremely low birth weight and congenital anomalies are at a significantly higher risk of poor growth, requiring in-hospital care and neurodevelopmental impairment than those extremely low birth weight infants without anomalies.44 Several limitations of this study must be considered. Some phenotypes with smaller sample sizes, such as anencephaly, restricted our ability to evaluate associations between BDs and SGA. Information regarding indications for premature delivery was unavailable and limited our ability to interpret our findings within the context of medically necessary deliveries and relevant common etiologic pathways. Another limitation is that information regarding smoking and alcohol use relies on maternal reporting of both the magnitude and precise timing of exposure. Non-differential measurement error in reporting may lead to misclassification of exposure status, and attenuate the results toward the null. CONCLUSION Infants with BDs are significantly more likely than infants without BDs to be SGA and born prematurely, particularly at very early gestational ages. This study adds to the evidence suggesting a complex interaction between the development of a BD, prematurity and intrauterine growth. Identification of common risk factors to the development of BDs and poor intrauterine growth may contribute to the understanding of the pathophysiology of Journal of Perinatology (2015), 198 – 203
these conditions and provide a basis for preconception care and counseling. Future research should aim to identify common pathways and develop interventions to decrease the incidence of the two principal causes of infant mortality. CONFLICT OF INTEREST The authors declare no conflict of interest.
ACKNOWLEDGEMENTS We thank the generous participation of the numerous families who made this research study possible. This research was supported by the Centers for Disease Control and Prevention (5U01DD000491) and the Arkansas Biosciences Institute.
DISCLAIMER The manuscript's contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention or the California Department of Public Health.
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Preterm and SGA among infants with birth defects F Miquel-Verges et al
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27 Sadler TW, Rasmussen SA. Examining the evidence for vascular pathogenesis of selected birth defects. Am J Med Genet A 2010; 152A(10): 2426–2436. 28 Menon R, Pearce B, Velez DR, Merialdi M, Williams SM, Fortunato SJ et al. Racial disparity in pathophysiologic pathways of preterm birth based on genetic variants. Reprod Biol Endocrinol 2009; 7: 62. 29 Carmichael SL, Shaw GM, Iovannisci DM, Yang W, Finnell RH, Cheng S et al. Risks of human limb deficiency anomalies associated with 29 SNPs of genes involved in homocysteine metabolism, coagulation, cell-cell interactions, inflammatory response, and blood pressure regulation. Am J Med Genet A 2006; 140(22): 2433–2440. 30 Hobbs CA, Cleves MA, Karim MA, Zhao W, MacLeod SL. Maternal folate-related gene environment interactions and congenital heart defects. Obstet Gynecol 2010; 116(2 Pt 1): 316–322. 31 Hobbs CA, Cleves MA, Melnyk S, Zhao W, James SJ. Congenital heart defects and abnormal maternal biomarkers of methionine and homocysteine metabolism. Am J Clin Nutr 2005; 81(1): 147–153. 32 Hobbs CA, Cleves MA, MacLeod SL, Erickson SW, Tang X, Li J et al. Conotruncal heart defects and common variants in maternal and fetal genes in folate, homocysteine and transsulfuration pathways. Birth Defects Res A Clin Mol Teratol 2014; 100(2): 116–126. 33 Zhao W, Mosley BS, Cleves MA, Melnyk S, James SJ, Hobbs CA. Neural tube defects and maternal biomarkers of folate, homocysteine, and glutathione metabolism. BMC Med Genet 2006; 76(4): 230–236. 34 Cleves MA, Hobbs CA, Zhao W, Krakowiak PA, MacLeod SL. National Birth Defects Prevention S Association between selected folate pathway polymorphisms and nonsyndromic limb reduction defects: a case-parental analysis. Paediatr Perinat Epidemiol 2011; 25(2): 124–134. 35 Carmichael SL, Yang W, Shaw GM. National Birth Defects Prevention S Maternal dietary nutrient intake and risk of preterm delivery. Am J Perinatol 2013; 30(7): 579–588. 36 Chandler AL, Hobbs CA, Mosley BS, Berry RJ, Canfield MA, Qi YP et al. Neural tube defects and maternal intake of micronutrients related to one-carbon metabolism or antioxidant activity. Birth Defects Res A Clin Mol Teratol 2012; 94(11): 864–874. 37 Werler MM, Louik C, Shapiro S, Mitchell AA. Prepregnant weight in relation to risk of neural tube defects. JAMA 1996; 275(14): 1089–1128. 38 Agopian AJ, Tinker SC, Lupo PJ, Canfield MA, Mitchell LE. National Birth Defects Prevention Study. Proportion of neural tube defects attributable to known risk factors. Birth Defects Res A Clin Mol Teratol 2013; 97(1): 42–46. 39 Parker SE, Werler MM, Shaw GM, Anderka M, Yazdy MM. National Birth Defects Prevention Study. Dietary glycemic index and the risk of birth defects. Am J Epidemiol 2012; 176(12): 1110–1120. 40 Patel SS, Burns TL, Botto LD, Riehle-Colarusso TJ, Lin AE, Shaw GM et al. Analysis of selected maternal exposures and non-syndromic atrioventricular septal defects in the National Birth Defects Prevention Study, 1997-2005. Am J Med Genet A 2012; 158A(10): 2447–2455. 41 DiFranza JR, Lew RA. Effect of maternal cigarette smoking on pregnancy complications and sudden infant death syndrome. J Fam Pract 1995; 40(4): 385–394. 42 Hoyt AT, Browne M, Richardson S, Romitti P, Druschel C. The National Birth Defects Prevention Study. Maternal caffeine consumption and small for gestational age births: results from a population-based case-control study. Matern Child Health J 2013; 18(6): 1540–1551. 43 Pappas A, Shankaran S, Hansen NI, Bell EF, Stoll BJ, Laptook AR et al. Outcome of extremely preterm infants ( o 1,000 g) with congenital heart defects from the National Institute of Child Health and Human Development Neonatal Research Network. Pediatr Cardiol 2012; 33(8): 1415–1426. 44 Walden RV, Taylor SC, Hansen NI, Poole WK, Stoll BJ, Abuelo D et al. Major congenital anomalies place extremely low birth weight infants at higher risk for poor growth and developmental outcomes. Pediatrics 2007; 120(6): e1512–e1519.
Supplementary Information accompanies the paper on the Journal of Perinatology website (http://www.nature.com/jp)
© 2015 Nature America, Inc.
Journal of Perinatology (2015), 198 – 203
ORIGINAL ARTICLE
A spectrum project: preterm birth and small-for-gestational age among infants with birth defects F Miquel-Verges1, BS Mosley2, AS Block2 and CA Hobbs2 OBJECTIVE: The aim of this study is to investigate the association between birth defects (BDs), prematurity and small-forgestational age (SGA) in a population-based sample. STUDY DESIGN: Participants were singleton live births enrolled in the National Birth Defects Prevention Study, including 18 737 case infants with one or more BD and 7999 controls. Logistic regression models to evaluate associations between BDs, prematurity and fetal growth were computed while adjusting for covariates. RESULT: Cases were significantly more likely to be born prematurely than controls, particularly at 24 to 28 weeks of gestation. The highest odds ratios for preterm birth were found for intestinal atresia, anencephaly, gastroschisis and esophageal atresia. Infants with BDs were also significantly more likely to be SGA than controls (17.2 and 7.8%). CONCLUSION: Infants with BDs are more likely than controls to be born prematurely and SGA. Findings from this study present additional evidence demonstrating a complex interaction between the development of BDs, prematurity and intrauterine growth. Journal of Perinatology (2015) 35, 198–203; doi:10.1038/jp.2014.180; published online 2 October 2014
INTRODUCTION Birth defects (BDs) and prematurity are the leading causes of infant mortality in the United States.1 It is estimated that 11.72% of infants are born prematurely, at o 37 weeks of completed gestation.2 The risk of premature birth is significantly higher for infants with BDs than for those without BDs.3–6 Also, infants with BDs are more likely to have low birth weight than infants without BDs.7 BDs represent significant challenges in medical care but when compounded by prematurity and/or poor growth, the ability to intervene clinically is often limited and resource utilization, morbidity and mortality are increased.4 The etiology of most nonsyndromic BDs is unknown and may share risk factors with preterm birth and intrauterine growth restriction.8,9 Genetic factors as well as maternal characteristics and environmental exposures likely contribute to the occurrence of BDs and preterm birth.10 Maternal characteristics associated with BDs and/or preterm birth include maternal diabetes mellitus, obesity, tobacco use and poor folic acid intake.11–14 Restricted growth during fetal life is a risk factor for morbidity and mortality in preterm newborns who may or may not have BDs.15 Infants with a birth weight of o10th percentile for gestational age are classified as small-for-gestational age (SGA). An increased risk for preterm birth and intrauterine growth restriction has been associated with individual BDs, including heart defects, brain defects, renal agenesis, intestinal atresia, tracheoesophageal fistula, esophageal atresia, anorectal atresia, omphalocele, biliary atresia, limb reduction defects and gastroschisis.3,5 Previous studies have reported secondary analysis of BD registry data and few have been able to adjust for maternal covariates such as maternal body mass index, diabetes, folic acid intake and maternal tobacco use.
The current study investigated the association between a spectrum of BDs, preterm birth and intrauterine growth restriction in a large case–control population-based sample in which maternal reports of covariates were obtained through detailed and structured interviews. By better understanding the relationship between BDs, intrauterine growth and preterm birth, we may find common and overlapping risk factors, the identification of which are crucial to developing effective interventions in the preconception and prenatal period. METHODS Study population Eligible case and control study participants were enrolled in the National Birth Defects Prevention Study (NBDPS) and born between October 1997 and 31 December 2007. The NBDPS is a multi-site, population-based, case– control study conducted in the United States between 1997 and June 2013, with the primary goal of identifying etiologic factors for nonsyndromic structural BDs. The study population and eligibility criteria for the NBDPS have been previously outlined.16 Briefly, subjects with 1 or more of over 30 eligible BDs were identified through population-based BD surveillance registries in 10 states (Arkansas, California, Iowa, Georgia, Massachusetts, New Jersey, New York, North Carolina, Texas and Utah) using uniform diagnostic criteria. Clinical data were abstracted by trained surveillance program staff members. BD cases were reviewed by clinical geneticists to determine eligibility. Infants with chromosomal abnormalities or single gene disorders were excluded. Controls were live-born infants without BDs, who were randomly selected either from each Center’s live birth population through birth certificates or birth hospital delivery records. Mothers of case and control infants were interviewed by telephone using a computerized automated telephone interview between 6 weeks and 24 months following completion of pregnancy. The computerized
1 Neonatology Section, College of Medicine, University of Arkansas for Medical Sciences, Arkansas Children’s Hospital Research Institute, Little Rock, AR, USA and 2Birth Defects Research Section, Department of Pediatrics, College of Medicine, University of Arkansas for Medical Sciences, Arkansas Children’s Hospital Research Institute, Little Rock, AR, USA. Correspondence: Dr CA Hobbs, Department of Pediatrics, College of Medicine, University of Arkansas for Medical Sciences, 13 Children’s Way, Slot 512-40, Little Rock, 72202, AR, USA. E-mail: [email protected] Received 16 April 2014; revised 17 July 2014; accepted 5 August 2014; published online 2 October 2014
Preterm and SGA among infants with birth defects F Miquel-Verges et al automated telephone interview ascertains information regarding maternal demographics, medical history, prenatal care and pregnancy history, environmental history and family history of BDs. Mothers of cases and controls spoke English or Spanish. Institutional review boards for participating Centers and from the Centers for Disease Control and Prevention approved the study. All subjects gave written informed consent. For minors, written informed consent was obtained from their legal guardian for DNA collection.
Classification of BDs As with previous NBDPS papers,12,13 cases included in this study have one or more eligible BD. BDs were categorized as previously described in NBDPS studies.17 Only BD categories with 100 or more eligible cases with completed interviews were evaluated. Categories included are neural tube defects, hydrocephaly, holoprosencephaly, congenital cataract, anotia or microtia, glaucoma or anterior chamber defects, seven different heart defect phenotypes (conotruncal heart defects, septal heart defects, right and left obstructive heart defects, atrioventricular septal heart defects, anomalous pulmonary venous return and single ventricle), choanal atresia, oral clefts, esophageal atresia, intestinal atresia or stenosis, anorectal atresia or stenosis, hypospadias, biliary atresia, craniosynostosis, diaphragmatic hernia, gastroschisis and omphalocele. Subjects affected by BDs were classified as having isolated or multiple defects by clinical geneticists. Subjects classified as having an isolated BD had: (a) one major defect, (b) one major and ⩾ 1 minor defects, (c) major defects that affect one organ system only or (d) a major defect with a well-described sequence of related defects without any other unrelated major defects. Those with multiple BDs had either ⩾ 2 major unrelated defects in different organ systems or multiple associated major defects that were not associated with any known syndrome.18 Congenital heart defects (CHDs) were classified as simple (well-defined, pure heart defect), associated (combination of two or more simple heart defects that occur frequently together but cannot be easily categorized under one of their components) and complex (heart phenotypes characterized by independent defects in multiple cardiac structures). Simple and associated CHDs were included in this analysis whereas complex CHDs were excluded.19
Growth parameters Gestational age and birth weight measures were obtained from each subject's clinical records. Week of gestational age at birth was based upon the following hierarchical system: (1) ultrasound performed before 14 weeks of gestation; (2) ultrasound between 14 and 27 weeks gestation; (3) standard neonatal exam and (4) last menstrual cycle. Infants born between 24 and 42 weeks of gestation were included in the analyses and categorized as follows: 24 to 28 weeks of gestation, 29 to 33 weeks, 34 to 36 weeks and 37 to 42 (up to 42) weeks. For comparison, those born between 37 and 42 weeks were considered the referent category. Intrauterine fetal growth was categorized using United States national standards for sex and gestational age-specific birth weights.20 Each infant was classified as: SGA (o 10th percentile), appropriate for gestational age (10 to 90th percentile) or large-for-gestational age (490th percentile).
Statistical analysis All analysis were limited to participants who had completed interviews. Descriptive statistics for sample characteristics were compared using χ2tests or t-tests. These factors included maternal race/ethnicity, education, age, infant sex, parity, maternal body mass index prior to pregnancy, diabetes, dietary folate intake prior to pregnancy, periconception folic acid supplement use and smoking or alcoholic drinking at any point from 3 months before pregnancy to delivery. Multiple logistic regression models were computed to model prematurity as a function of case–control status and maternal and infant covariates. Available maternal and infant characteristics determined to be statistically significant (α = 0.05) in the bivariate analyses and/or associated with prematurity or BDs in previously published research were included as covariates. Prematurity results were stratified by isolated and multiple defect groups. Infants born large-for-gestational age were excluded from the fetal growth/SGA analysis. All analyses were performed in SAS (version 9.2; SAS, Gary, NC, USA). © 2015 Nature America, Inc.
RESULTS Between 1997 and 2007, among live-born, singleton infants there were 19 197 with eligible BDs and 8164 controls. Interview participation rates for cases and controls were above 70%. Further review required the exclusion of 68 infants who did not have final review by clinical geneticist or were identified during final review to have a probable or certain syndrome; 17 mothers with known viral infections (14 cases, 3 controls); 169 infants for whom the gestational age was missing (167 cases, 2 controls) and 849 infants for whom the documented gestational age was o 24 weeks (440 cases, 11 controls) or more than 42 weeks (243 cases, 155 controls). Our final study population consisted of 18 737 cases and 7 999 controls. Maternal and infant characteristics are presented in Table 1. Mothers of cases and controls were primarily white, nonHispanic (59%) with an average age at delivery of 26.9 years. The distribution of obesity and diabetes mellitus varied between mothers of cases and controls; mothers of cases were more likely to be obese, have Type 1 or 2 diabetes mellitus and smoke tobacco. Infants with BDs were more likely to be male. Distribution of gestational age at birth and birth weight is shown in Table 2. Infants with BDs were significantly more likely to be born preterm than controls, particularly at earlier gestational ages. Among cases, 2.1 and 6.3% of infants were born at 24 to 28 weeks and 29 to 33 weeks, respectively. Whereas among control infants, 0.4 and 1.5% were born at these earlier gestational ages (P o0.001). Overall, 22.5% of cases were born prematurely whereas only 8.3% of controls were born before 37 weeks of gestation. Infants with BDs were significantly more likely to be SGA than controls (17.2% vs 7.8%, respectively). When controlling for potential confounders and comparing three categories of preterm births to full-term births, the odds of being born very preterm (24 to 28 weeks) appear to increase across all selected defects where data were available (Table 3). Because adjusted results were similar to crude results (within 10%), only the adjusted results are presented. Infants with septal heart defects (odds ratio (OR), 12.8; 95% confidence interval (CI), 8.5 to 19.3), intestinal atresia/stenosis (OR, 13.2; 95% CI, 6.6 to 26.7) and esophageal atresia (OR, 11.1; 95% CI, 5.2 to 23.7) had the highest odds of being born between 24 to 28 weeks when compared with controls. Those infants with gastroschisis (OR, 19.5; 95% CI, 14.0 to 27.0), intestinal atresia/ stenosis (OR, 22.0; 95% CI, 15.8 to 30.7), anencephaly (OR, 14.6; 95% CI, 7.4 to 28.9), esophageal atresia (OR, 12.8; 95% CI, 8.9 to 18.5), hydrocephaly (OR, 8.3; 95% CI, 5.4 to 12.7) or choanal atresia (OR, 9.6; CI, 4.7 to 19.5) were more likely to be born between 29 and 33 weeks gestation when compared with controls. The odds of prematurity in the 34 to 36 week period were highest among the same five BD: gastroschisis (OR, 16.6; 95% CI, 13.6 to 20.2), intestinal atresia/stenosis (OR, 10.3; 95% CI, 8.2 to 12.9), anencephaly (OR, 6.6; 95% CI, 4.1 to 10.6), esophageal atresia (OR, 5.7; 95% CI, 4.5 to 7.4) and hydrocephaly (OR, 5.3; 95% CI, 4.0 to 7.1). Infants with gastroschisis and intestinal atresia/stenosis were more likely to be born prematurely than infants with any other BD studied (data not shown). Of the 852 infants with gastroschisis, 14 (1.6%) were born between 24 and 28 weeks, 112 (13.1%) between 29 and 33 weeks, 399 (46.8%) between 34 and 36 weeks and only 327 (38.3%) were born at term. Similarly, of the 465 infants with intestinal atresia, 13 (2.7%) were born between 24 and 28 weeks, 78 (16.7%) between 29 and 33 weeks, 154 (33.1%) between 34 and 36 weeks, and only 220 (47.3%) were born at term. Across all BD categories studied, odds of prematurity were higher for infants with multiple defects when compared with isolated defects, except for glaucoma and anterior chamber defects (Supplementary Table 1). Overall, those with any isolated BD had 2.8 (95% CI, 2.6 to 3.1) times the odds of being born Journal of Perinatology (2015), 198 – 203
199
Preterm and SGA among infants with birth defects F Miquel-Verges et al
200 Table 1. Demographic and maternal characteristics of study participants with and without birth defects, National Birth Defect Prevention Study, 1997 to 2007
Table 2.
Gestational age and fetal growth at birth among cases and
controls Cases
Birth defects
No.
Percent
Without birth defects a
Bivariate analysisb
a
No. Percent
Total subjects
18 737
Maternal race/ethnicity White, non-Hispanic Black, non-Hispanic Hispanic Other races
11 085 1802 4432 1375
59.3 9.6 23.7 7.4
4684 875 1824 590
58.7 11.0 22.9 7.4
P = 0.0780
3367 4820
18.2 26.1
1348 1913
17.1 24.2
Po0.0001
5078 5235
27.4 28.3
2156 2476
27.3 31.4
Maternal age o20 Years 2543 20–29 Years 9498 30–39 Years 6284 40+ Years 412 Mean age: years (s.d.) 27.0
13.6 50.7 33.5 2.2 (6.3)
1071 4159 2658 111 26.8
13.4 52.0 33.2 1.4 (6.1)
Maternal education Less than high school High school degree/ equivalent 13–15 Years ⩽ 16 Years
7999
P = 0.0001
P = 0.1141
Infant sex Male Female
11 427 7950
59.0 41.0
4056 3937
50.7 49.3
Po0.0001
Parity Primiparity Multiparity
7940 10 736
42.5 57.5
3173 4807
39.8 60.2
Po0.0001
1008 9313 4090
5.6 52.1 22.9
415 4221 1738
5.4 55.1 22.7
Po0.0001
3477 25.5
19.4 (6.2)
1289 25.0
16.8 (5.7)
16 757 447 1465
89.8 2.4 7.8
7393 56 528
92.7 0.7 6.6
Po0.0001
5333
28.7
1988
25.0
Po0.0001
4781 4308 4194
25.7 23.1 22.5
1987 1988 1988
25.0 25.0 25.0
Folic acid supplement use Yes, B1-P1 9298 No, B1-P1 9332
49.9 50.1
4062 3891
51.1 48.9
P = 0.0816
Maternal smoking, B3-P9 Yes 4107 No 14 429
22.2 77.8
1530 6382
19.3 80.7
Po0.0001
Maternal drinking, B3-P9 Yes 8286 No 10 208
44.8 55.2
3620 4279
45.8 54.2
P = 0.1255
Maternal diabetes None Type 1 or 2 Gestational Maternal dietary folate 25th Percentile or less 26–50th Percentile 51–75th Percentile ⩾ 75th Percentile
Po0.0001
Abbreviations: B1, 1 month before pregnancy; B3, 3 months before pregnancy; BMI, body mass index; P1, first month of pregnancy; P9, 9th month of pregnancy. aPercentages reflect the exclusion of missing data for each characteristic. bBivariate analysis reflect P-values from Student's t-test for continuous data (maternal age and BMI) and χ2-test for categorical data (all variables). c1508 hypospadias cases included in male birth defect counts.
Journal of Perinatology (2015), 198 – 203
Gestational age at birth 24–28 Weeks 29–33 Weeks 34–36 Weeks 37–41 Weeks
%
No.
Bivariate analysis
%
389 2.1 31 0.4 P o0.0001 1185 6.3 122 1.5 2640 14.1 508 6.4 14 523 77.5 7338 91.7
Fetal growth at birtha Small for gestation 3194 17.2 622 7.8 P o0.0001 Appropriate for gestation 13 966 75.1 6602 82.8 Large for gestation 1429 7.7 750 9.4 a Percentages reflect the exclusion of missing data for fetal growth (148 cases, 25 controls).
c
Maternal BMI Underweight: o 18.5 Normal: 18.5 to o25 Overweight: 25 to o30 Obese: ⩽ 30 Mean BMI value (s.d.)
No.
Controls
premature as healthy controls, whereas the adjusted odds ratio comparing those with multiple BDs to controls was 5.9 (95% CI, 5.2 to 6.6). Table 4 illustrates the association of fetal growth and selected BDs. Large-for-gestational age cases and controls were removed from this analysis. Overall, infants with BDs studied were roughly twice as likely to be born SGA than infants without BDs when controlling for potential confounders. The largest odds ratio for being SGA was among infants with anencephaly, (OR, 55.3; 95% CI, 33.5 to 91.1), esophageal atresia (OR, 5.2; 95% CI, 4.1 to 6.6), gastroschisis (OR, 4.6; 95% CI, 3.8 to 5.5) and hypospadias (OR, 3.7; 95% CI, 3.1 to 4.5). As with the BD and prematurity analysis, infants with multiple BDs were more likely than those with isolated BDs to be SGA (data not shown). DISCUSSION Our findings from the largest population-based case–control study of BDs conducted in the United States confirms findings from other studies that fetuses with major BDs are more likely to be born prematurely and SGA than fetuses without BDs.3,11,21,22 The NBDPS clinical and interview data allowed for closer evaluation of the association between BDs and all degrees of prematurity while controlling for important maternal covariates. Previous published studies were based only on abstracted medical records collected by population-based registries,3 or data from research networks. Unlike previous studies, NBDPS clinical algorithms applied by board-certified clinical dysmorphologists ensured application of uniform diagnostic criteria, and interviews with mothers of infants with BDs allowed for more comprehensive information about maternal preconceptional and prenatal exposures. Among the spectrum of BDs included in the current study cases were at least twice as likely to be born prematurely than controls, across all gestational ages. The relationship between BDs and preterm birth was strongest among infants with gastroschisis, intestinal atresia or stenosis, omphalocele, esophageal atresia and septal heart defects. These findings are consistent with previous studies that have shown a particularly strong association between esophageal and intestinal atresias and premature birth.3 Poor intrauterine growth is a known risk factor for morbidity and mortality in the neonatal period, particularly for premature infants.15,23 Infants with BDs are more likely to be SGA than infants without BDs.24 The relationship is particularly strong for anencephaly, esophageal atresia, intestinal atresia and gastroschisis. Our data confirm previous findings that infants with CHDs, the most © 2015 Nature America, Inc.
Preterm and SGA among infants with birth defects F Miquel-Verges et al
201 Table 3.
Adjusted odds ratios of the association of select birth defect phenotypes and various levels of prematurity 37–41 Weeks
Controls Total all select birth defects Anencephaly Spina bifida Hydrocephaly Holoprosencephaly Cataracts Anotia/microtia Glaucoma/ anterior chamber defects Conotruncal CHD Septal CHD Right ventricular obstructive CHD Left ventricular obstructive CHD Atrioventricular septal defects Anomalous pulmonary venous return Single ventricle Choanal atresia Cleft palate w/o cleft lip Cleft lip w or w/o cleft palate Esophageal atresia Intestinal atresia/stenosis Anorectal atresia/stenosis Hypospadiasb Biliary atresia Craniosynostosis Diaphragmatic hernia Gastroschisis Omphalocele
34–36 Weeks
No.
No.
6913 13 666 60 595 198 72 183 350 104 1389 2371 952 1144 175 205 192 72 883 1702 272 220 494 1100 94 830 425 327 167
477 2485 27 95 74 14 19 44 8 187 487 157 132 34 23 29 15 116 177 103 154 87 183 19 81 70 399 42
aOR (95% CI) 1 2.6 6.6 2.3 5.3 2.4 1.5 1.6 1.1 1.9 2.7 2.3 1.7 2.6 1.6 1.9 3.2 1.9 1.5 5.7 10.3 2.5 2.7 3.0 1.5 2.4 16.6 3.8
(reference) (2.3, 2.9) (4.1, 10.6) (1.8, 3.0) (4.0, 7.1) (1.3, 4.3) (0.9, 2.4) (1.1, 2.3) (0.5, 2.3) (1.6, 2.3) (2.4, 3.1) (1.9, 2.8) (1.4, 2.1) (1.8, 3.9) (1.0, 2.5) (1.2, 2.9) (1.8, 5.6) (1.5, 2.3) (1.2, 1.8) (4.5, 7.4) (8.2, 12.9) (1.9, 3.2) (2.1, 3.3) (1.8, 5.0) (1.1, 1.9) (1.8, 3.1) (13.6, 20.2) (2.7, 5.4)
29–33 Weeks No. 117 1102 12 22 34 7 5 20 3 56 319 86 50 16 5 9 10 53 63 54 78 40 124 6 31 35 112 23
aOR (95% CI) 1 4.7 14.6 2.1 8.3 5.5 1.7 3.6
(reference) (3.9, 5.7) (7.4, 28.9) (1.3, 3.4) (5.4, 12.7) (2.4, 12.6) (0.7, 4.3) (2.2, 6.1)
2.2 7.0 5.2 2.6 4.7 1.4 2.2 9.6 3.6 2.2 12.8 22.0 4.2 6.6 3.5 2.4 5.1 19.5 7.8
(1.6, 3.1) (5.6, 8.8) (3.9, 7.0) (1.8, 3.7) (2.6, 8.2) (0.5, 3.5) (1.1, 4.7) (4.7, 19.5) (2.6, 5.1) (1.6, 3.0) (8.9, 18.5) (15.8, 30.7) (2.9, 6.2) (4.7, 9.2) (1.5, 8.2) (1.6, 3.6) (3.4, 7.6) (14.0, 27.0) (4.8, 12.7)
a
24–28 Weeks No. 29 361 8 7 7 2 9 2 1 27 146 37 11 3 4 3 1 7 18 11 13 12 39 1 8 7 14 8
aOR (95% CI) 1 6.2 29.8 3.1 7.7
(reference) (4.2, 9.1) (11.4, 77.9) (1.3, 7.3) (3.2, 18.6) a
10.8 (4.9, 24.0) a a
4.6 12.8 9.3 2.3
(2.7, (8.5, (5.6, (1.1, a
8.0) 19.3) 15.4) 4.8)
a a a
2.0 2.6 11.1 13.2 5.6 8.7
(0.8, (1.4, (5.2, (6.6, (2.7, (4.6,
4.7) 4.8) 23.7) 26.7) 11.3) 16.3)
2.4 3.8 9.1 12.6
(1.1, (1.6, (4.3, (5.4,
5.5) 9.1) 19.4) 29.6)
a
Abbreviations: aOR, adjusted odds ratio; CI, confidence interval; CHD, congenital heart defect. aOdds ratio not reported due to cell count o5. bHypospadias models included male infants only. Covariates: maternal race/ethnicity, education, infant sex, parity, maternal body mass index, type 1/2 diabetes, dietary folate, smoking during pregnancy and study center. Referent category: infants born between 37 and 41 weeks.
prevalent BDs, are twice as likely to be SGA than those without BDs.25 Multiple factors may help to explain the association between BD, prematurity and SGA. The BD may cause poor intrauterine growth and/or preterm birth. For example, esophageal and intestinal atresia are associated with polyhydramnios that may lead to preterm labor and increase the risk of prematurity. Obstetrical complications, such as polyhydramnios, may be more likely to cause preterm labor during the last trimester than during the mid-trimester when very early births (23 to 28 weeks of gestation) occur.3 Another factor that may increase the likelihood of prematurity among fetuses with BDs is increased medical surveillance for fetuses prenatally diagnosed with a serious BD. For example, it is well established that gastroschisis is associated with a risk of intrauterine hypoxia and later-term fetal death.26 For infants with gastroschisis, planned preterm delivery has been advocated before development of bowel dilation, bowel complications and fetal death.26 The obstetrical management of affected pregnancies requires increased surveillance that may lead to increased intervention resulting in a greater number of infants with gastroschisis being delivered between 34 and 36 weeks gestation (late prematurity). For some infants born prematurely, increased medical surveillance in the nursery may increase the detection of BDs. For example, premature infants are more likely to have echocardiograms than term infants increasing the likelihood of being diagnosed with small septal defects. A third factor that may account for an association between BDs and prematurity and SGA is a common etiologic pathway for BDs, © 2015 Nature America, Inc.
poor intrauterine growth and preterm birth. We and many others hypothesize that a complex interplay between genetic, epigenetic and environmental factors causes BDs, prematurity and intrauterine growth restriction. Supporting evidence has suggested that the factors involved may vary by BD phenotype. Vascular compromise has been implicated in the development of a number of BDs, including neural tube, heart, limb and abdominal defects, and also in the development of intrauterine growth retardation.27–29 Micronutrients may also have a role in the complex relationship between the development of a BD and intrauterine growth. Maternal folate metabolism is associated with neural tube, cardiac and limb defects,30–34 and at least in some studies, with prematurity3,21 and low birth weight.11,24 Other micronutrients, including thiamin, riboflavin, vitamin A, vitamin E and zinc, have been implicated in both the risk of preterm delivery and BDs.35,36 Diabetes mellitus is known to increase the32 risk of some BDs, including both cardiac and noncardiac defects such as anencephaly, anotia/microtia, cleft lip and palate, limb anomalies, renal agenesis and anorectal atresia.13,37–40 Maternal obesity has been shown to increase the risk of spina bifida, heart defects, anorectal atresia, hypospadias, limb reduction defects, diaphragmatic hernia and omphalocele and has also been associated with increased risk of premature birth.12,14 Maternal exposure to tobacco increases the risk of some BDs and prematurity and SGA.41,42 Poor fetal growth increases the morbidity and mortality of infants with BDs.43 The outcomes and survival of infants with CHDs is significantly worse for those born preterm, particularly at earlier gestational ages.43 The neonatal course and long-term outcomes of infants with BDs requiring surgeries and lengthy Journal of Perinatology (2015), 198 – 203
Preterm and SGA among infants with birth defects F Miquel-Verges et al
202 Table 4.
Association of select birth defect phenotypes and small-for-gestational agea No. Appropriate for gestational age
Controls Total all birth defects Anencephaly Spina bifida Hydrocephaly Holoprosencephaly Cataracts Anotia/microtia Glaucoma/anterior chamber defects Conotruncal CHD Septal CHD Right ventricular obstructive CHD Left ventricular obstructive CHD Atrioventricular septal defects Anomalous pulmonary venous return Single ventricle Choanal atresia Cleft palate w/o cleft lip Cleft lip w or w/o cleft palate Esophageal atresia Intestinal atresia/stenosis Anorectal atresia/stenosis Hypospadiasb Biliary atresia Craniosynostosis Diaphragmatic hernia Gastroschisis Omphalocele
6212 13 133 22 558 215 64 165 304 89 1225 2489 944 1052 170 177 175 73 798 1523 297 369 472 1012 95 721 411 545 184
Small-for-gestational age No.
aOR (95% CI)
588 2995 83 104 37 22 25 76 17 314 546 171 181 42 41 40 18 175 265 133 73 122 326 11 80 87 291 40
1 [reference] 2.4 (2.2, 2.7) 55.3 (33.5, 91.1) 2.1 (1.7, 2.7) 1.7 (1.2, 2.5) 3.5 (2.1, 5.8) 1.6 (1.0, 2.5) 2.7 (2.0, 3.5) 2.2 (1.3, 3.7) 2.8 (2.4, 3.3) 2.3 (2.0, 2.6) 2.0 (1.7, 2.4) 2.1 (1.7, 2.5) 2.7 (1.9, 3.9) 2.6 (1.8, 3.7) 2.5 (1.7, 3.6) 3.0 (1.8, 5.2) 2.5 (2.0, 3.0) 1.9 (1.6, 2.2) 5.2 (4.1, 6.6) 2.0 (1.5, 2.6) 2.7 (2.2, 3.4) 3.7 (3.1, 4.5) 1.1 (0.6, 2.2) 1.4 (1.1, 1.8) 2.3 (1.8, 3.0) 4.6 (3.8, 5.5) 2.2 (1.5, 3.2)
Abbreviations: aOR, adjusted odds ratio; CI, confidence intervals; CHD, congenital heart defect; w or w/o, with or without. aInfants large-for-gestational age were excluded from these analyses. bHypospadias models included male infants only. Covariates: maternal race/ethnicity, education, infant sex, parity, maternal body mass index, type 1/2 diabetes, dietary folate, smoking during pregnancy and study center.
hospitalizations are complicated by low birth weight. At 18 to 22 months' corrected age, infants with extremely low birth weight and congenital anomalies are at a significantly higher risk of poor growth, requiring in-hospital care and neurodevelopmental impairment than those extremely low birth weight infants without anomalies.44 Several limitations of this study must be considered. Some phenotypes with smaller sample sizes, such as anencephaly, restricted our ability to evaluate associations between BDs and SGA. Information regarding indications for premature delivery was unavailable and limited our ability to interpret our findings within the context of medically necessary deliveries and relevant common etiologic pathways. Another limitation is that information regarding smoking and alcohol use relies on maternal reporting of both the magnitude and precise timing of exposure. Non-differential measurement error in reporting may lead to misclassification of exposure status, and attenuate the results toward the null. CONCLUSION Infants with BDs are significantly more likely than infants without BDs to be SGA and born prematurely, particularly at very early gestational ages. This study adds to the evidence suggesting a complex interaction between the development of a BD, prematurity and intrauterine growth. Identification of common risk factors to the development of BDs and poor intrauterine growth may contribute to the understanding of the pathophysiology of Journal of Perinatology (2015), 198 – 203
these conditions and provide a basis for preconception care and counseling. Future research should aim to identify common pathways and develop interventions to decrease the incidence of the two principal causes of infant mortality. CONFLICT OF INTEREST The authors declare no conflict of interest.
ACKNOWLEDGEMENTS We thank the generous participation of the numerous families who made this research study possible. This research was supported by the Centers for Disease Control and Prevention (5U01DD000491) and the Arkansas Biosciences Institute.
DISCLAIMER The manuscript's contents are solely the responsibility of the authors and do not necessarily represent the official views of the Centers for Disease Control and Prevention or the California Department of Public Health.
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Journal of Perinatology (2015), 198 – 203
