The incidence of both spontaneous and induced moderately preterm births (32 0/7–35 6/7 weeks of gestation) has risen in the last decades from 6% to 9% of all life births worldwide and accounts for 70–85% of all preterm-born children.1 Moderately preterm–born children have more developmental and behavioral problems in kindergarten and primary school,2–6 increased special educational needs,4,7 and more social disabilities as adults than term-born children.8 Because of the large share of moderately preterm–born children within all life births, even slightly increased risks of long-term developmental problems in this group have important economic and social implications.9
Several preexisting maternal and pregnancy-related factors have been shown to increase the risk of moderately preterm birth, neonatal mortality, and early neonatal morbidity before discharge.10–13 It is unknown whether these same factors also increase the risk of developmental delay in early childhood for this particular group. Knowledge on this subject may help optimize antenatal obstetric care and may also be helpful for obstetricians who need to counsel parents in case of considering induced moderately preterm delivery. The same knowledge may also help pediatricians to identify those children within the large moderately preterm group who may have an increased risk of developmental delay in early childhood and who could, therefore, benefit from more structured follow-up assessments.
The aim of this study was to estimate, for moderately preterm–born children, which preexisting maternal and pregnancy-related factors were associated with developmental delay in early childhood.
MATERIALS AND METHODS
This study was part of the Longitudinal Preterm Outcome Project (LOLLIPOP) on growth and development of preterm children.6,14 In a community-based cohort of 45,455 children born in 2002 and 2003, all children with a gestational age between 32 0/7 and 35 6/7 weeks of gestation were sampled. We based the size of our cohort on estimates of the numbers needed to compile growth curves for Dutch preterm-born children.14
All children were included during their regular visit to a preventive child health care center at the age of 43–49 months (uncorrected age, inclusion from October 2005 to September 2007). At this age, 95–97% of all Dutch children are routinely seen at a preventive child health care center.15 Children with major congenital malformations, congenital infections, and syndromes were excluded.
Eventually 960 moderately preterm–born children included in the growth part of the Longitudinal Preterm Outcome Project study also participated in the developmental part of the Longitudinal Preterm Outcome Project study. The institutional medical ethical review board at Groningen approved the entire study and we obtained written informed consent from all parents. Further details on the Longitudinal Preterm Outcome Project study were provided previously.6,14
Before their planned visit to the preventive child health care center, parents were asked to fill out the Dutch version of the 48-month Ages and Stages Questionnaire, a parent-completed developmental screening tool.16 Reliability and validity of the Ages and Stages Questionnaire has been documented in several studies.16,17 The Ages and Stages Questionnaire measures development in five domains: communication, fine motor, gross motor, problem-solving ability, and personal–social functioning. The scores on each domain add up to an Ages and Stages Questionnaire total score.17 An Ages and Stages Questionnaire total score of more than two standard deviations below the mean of the Dutch reference group was considered to indicate developmental delay (dichotomous yes or no). We set the time window for the parents to have completed the Ages and Stages Questionnaire between 43 and 49 months (3 months on either side of the median).6
We expressed gestational age in completed weeks of gestation. We collected the data on preexisting maternal and pregnancy-related factors of children participating in this part of the Longitudinal Preterm Outcome Project study in a controlled manner from the hospital records of both mothers and children, preventive child health care center records, the Dutch Central Perinatal Registration, and a parental questionnaire at age 4 years. We crosschecked data from different sources whenever possible. Pregnancy-related factors were divided into three categories; maternal, fetal, and delivery-related. This led to a final categorization of all factors into one of four categories: maternal preexisting, maternal pregnancy-related, fetal, and delivery-related factors. Because preexisting diabetes was very rare in our sample, we pragmatically included preexisting diabetes into the corresponding pregnancy-related category gestational diabetes. Within the category of fetal factors, small for gestational age (SGA), as a proxy for intrauterine growth restriction (IUGR), was defined as a birth weight below the 10th percentile of the Dutch Kloosterman growth charts.18 All variables are specified in Table 1.
Data on sociodemographic and lifestyle variables were collected from the general questionnaire and crosschecked with medical data. These data included multiparity, socioeconomic status, ethnicity, smoking, and alcohol consumption during pregnancy (Table 1). For socioeconomic status, we computed a composite continuous score based on the average of the following five indicators: educational level of both parents, occupational level of both parents, and family income.19 Low socioeconomic status was defined as the lowest 25% of the continuous socioeconomic status score; the middle 50% and highest 25% were combined into nonlow socioeconomic status.
We first calculated the prevalence rates of all preexisting and pregnancy-related (maternal, fetal, delivery-related) and sociodemographic and lifestyle variables in our cohort of children with and without abnormal Ages and Stages Questionnaire scores. Second, we analyzed the association of all preexisting and pregnancy-related variables with rates of abnormal Ages and Stages Questionnaire scores in univariable logistic regression analyses. Furthermore, we calculated attributable risks. Third, we constructed a multivariable model including all variables with P values <.20. (in univariable analyses) in the model. In this model, we combined induction of birth for solely fetal reasons with induction for “combined fetal and maternal reasons.” Together they formed a new variable, “fetal indication.” Finally, we adjusted for differences in sociodemographic and lifestyle parameters with a P value <.20 in univariable analyses. We constructed one additional model. In this additional model, we removed SGA as a variable from the model. We chose to do so because nonreassuring fetal parameters (signs of fetal distress) leading to induced moderately preterm birth are often found in growth-restricted fetuses. This implies that SGA and induced birth for fetal indication may be partial proxies.
All regression analyses were done using multilevel techniques to account for the clustering of risk factors in members of multiples.20 All analyses were done using SAS 9.2. The threshold for statistical significance was set at P<.05.
A total of 927 (97%) of the 960 Ages and Stages Questionnaire were completed within the set timeframe. For 10% (n=93) of these children, we were unable to retrieve data on antenatal factors as a result of logistic reasons and missing records. The final sample, therefore, consisted of 834 children. The children not included in the final sample (n=126) more often had mothers who were non-Dutch (15.0% compared with 5.4%, P<.001). They did not differ significantly on sex, gestational age, SGA, maternal education, or percentage of multiples (results not shown).
Prevalence rates of all factors are shown in Table 1. For 72% of the cohort, birth occurred after spontaneous rupture of membranes or spontaneous onset of labor, whereas 24% were induced births for fetal, maternal, or both indications, and 4% were elective births. Seventy-two children (8.6%) had an abnormal Ages and Stages Questionnaire score. Prevalence rates of abnormal Ages and Stages Questionnaire scores for children with and without antenatal factors are shown in Table 2.
We present the results of the univariable analyses in Table 3. With regard to both preexisting and pregnancy-related maternal factors, only prepregnancy obesity was associated with increased risk of developmental delay at age 4 years. Furthermore, the fetal factors, SGA and male sex, as well as the delivery-related factors cesarean delivery and “fetal indication” were associated with an increased risk of developmental delay. Several other factors in all four categories had borderline positive or negative associations with developmental delay and were, therefore, also included in the multivariable models.
Attributable risk for developmental delay for SGA (as a proxy for IUGR) was 14.2% (SGA 21.9%, no SGA 7.7%, P<.05), for preexisting maternal obesity 10.5% (obesity 18.0%, no obesity 7.5%, P<.01), for multiple pregnancy 4.2% (multiple 12.0%, singleton 7.8%, P<.05), and for male sex 9.3% (male 13.0%, female 3.8%, P<.001).
Table 3 contains the results of the unadjusted and adjusted multivariable multilevel models. In the unadjusted model (Model 1), prepregnancy obesity, SGA, and male sex remained associated with an increased risk of developmental delay with statistical significance, and being one of multiple was also associated with an increased risk of developmental delay. Adjustment for sociodemographic and lifestyle factors hardly influenced the strength of the associations (Model 2). Repeating the analyses excluding SGA did not influence the results either (results not shown).
In this cohort of moderately preterm–born children, SGA, prepregnancy obesity, being one of a multiple, and male sex increased the risk of developmental delay in early childhood. We did not find an association between any pregnancy-related maternal factors or delivery-related factors and risk of developmental delay.
The association between SGA and developmental risk is also in line with other studies both in full-term-born and early preterm–born children.20–22 Although SGA remains only a proxy for IUGR,22,23 many of those born SGA will have had chronic deficits in nutritional and oxygen needs during the fetal period.22 These chronic deficits may alter brain structure permanently, thus compromising development.
The association between maternal prepregnancy obesity and developmental risk is also in line with a study on early preterms20 and consistent with findings from an experimental animal model.24 This may indicate that maternal obesity not only increases the risk of preterm birth,25 but also increases the risk of adverse development later on. The third fetal factor that increased the risk of developmental delay in our cohort was multiple pregnancies. Twins are known to have poorer developmental outcomes than singletons, but it has been argued that this is solely the result of higher rates of IUGR and preterm births in multiples.26 In our cohort, results for multiples were not explained by IUGR or by gestational age within the moderately preterm range.
The final factor strongly associated with developmental risk was male sex. It has been postulated that early preterm–born boys have a higher biological baseline risk for developmental delay as well as a higher risk of postnatal complications that also leads to developmental delay.27 Our findings suggest that this male disadvantage also holds true for moderately preterm–born boys.
In our multivariable models, we found no association between any maternal pregnancy-related or delivery-related factors and risk of developmental delay, which is in line with a study on early preterms.20 We found several delivery-related factors (cesarean delivery, breech presentation, assisted delivery, fetal indication) that showed significant or nearly significant associations with developmental delay in the univariable analyses to lose significance in the multivariable models, including the model without SGA as a variable. It implies that predominantly fetal factors, and not the final indication for earlier delivery or mode of delivery, is associated with the increased risk of developmental delay. It is reassuring that we could not demonstrate an association between prolonged premature rupture of membranes and risk of developmental delay. Even so, this lack of association has to be interpreted with caution, because we did not have data on placenta histology.
The strengths of our study are its community-based approach, the large number of children that participated, and the data collection from various sources. We also recognize some limitations. We measured developmental outcome with a parent-completed screening tool instead of submitting the children to extensive neuropsychologic tests. Nevertheless, developmental screeners are considered to be reliable measures for identifying developmental problems in high-risk populations.28 Furthermore, many etiologic factors and phenotypic entities within the complex “preterm birth syndrome” are intricately entwined, making it difficult to assess separate variables in the cascade leading to moderately preterm birth.29,30 Our study may also have been underpowered to find associations for some of the rarer antenatal factors. Finally, children who were not included in the analyses more frequently had mothers born outside The Netherlands. Because of the universal access to care in The Netherlands, we think that this difference will not have influenced our results, but it might reduce the generalizability of our results.
Our study may have important implications. Until recently, perinatal care focused on secondary prevention of preterm birth, including moderately preterm birth, in high-risk pregnancies and the reduction of early neonatal morbidity after preterm birth. Most moderately preterm deliveries, however, are spontaneous without any evidence of fetal compromise and few or no postnatal complications. Therefore, more focus should be placed on primary prevention of spontaneous preterm birth as outlined in the guidelines of the Royal College of Obstetrics and Gynaecology.31 These guidelines include issues on increasing health and healthy lifestyles in fertile women in general to reduce both IUGR and the risk of preterm delivery.32 Our study however cannot answer the question whether earlier delivery within the moderately preterm range, aiming at preventing more severe IUGR, may be feasible.33
Of all the preexisting maternal and pregnancy-related factors studied, only SGA, maternal prepregnancy obesity, being one of a multiple, and male sex were associated with the risk of developmental delay in early childhood after moderately preterm birth. Current efforts to prevent IUGR, efforts to reduce weight in fertile women by intervening in preconception lifestyle, and efforts to reduce rates of multiple pregnancies in assisted reproduction should be continued and where possible be reinforced. They may all contribute toward more favorable developmental outcomes in moderately preterm–born children.
1. Shapiro Mendoza CK, Lackritz EM. Epidemiology of late and moderate preterm birth. Semin Fetal Neonatal Med 2012;17:120–5.
2. McGowan JE, Alderdice FA, Holmes VA, Johnston L. Early childhood development of late-preterm infants: a systematic review. Pediatrics 2011;127:1111–24.
3. Jain L. School outcome in late preterm infants: a cause for concern. J Pediatr 2008;153:5–6.
4. Chyi LJ, Lee HC, Hintz SR, Gould JB, Sutcliffe TL. School outcomes of late preterm infants: special needs and challenges for infants born at 32 to 36 weeks gestation. J Pediatr 2008;153:25–31.
5. Lipkind HS, Slopen ME, Pfeiffer MR, McVeigh KH. School-age outcomes of late preterm infants in New York City. Am J Obstet Gynecol 2012;206:222.e1–6.
6. Kerstjens JM, de Winter AF, Bocca-Tjeertes IF, ten Vergert EM, Reijneveld SA, Bos AF. Developmental delay in moderately preterm–born children at school-entry. J Pediatr 2011;159:92–8.
7. MacKay DF, Smith GC, Dobbie R, Pell JP. Gestational age at delivery and special educational need: retrospective cohort study of 407,503 schoolchildren. PLoS Med 2010;8:e1000289.
8. Moster D, Lie RT, Markestad T. Long-term medical and social consequences of preterm birth. N Engl J Med 2008;359:262–73.
9. Petrou S, Khan K. Economic costs associated with moderate and late preterm birth: primary and secondary evidence. Semin Fetal Neonatal Med 2012;17:170–8.
10. Dimitriou G, Fouzas S, Georgakis V, Vervenioti A, Papadopoulos VG, Decacalas G, et al.. Determinants of morbidity in late preterm infants. Early Hum Dev 2010;86:587–91.
11. Bastek JA, Sammel MD, Paré E, Srinivas SK, Posencheg MA, Elovitz MA. Adverse neonatal outcomes: examining the risks between preterm, late preterm, and term infants. Am J Obstet Gynecol 2008;199:367.e1–8.
12. Sibai BM. Preeclampsia as a cause of preterm and late preterm (near-term) births. Semin Perinatol 2006;30:16–9.
13. Khatibi A, Brantsaeter A-L, Sengpiel V, Kacerovsky M, Magnus P, Morken NH, et al.. Prepregnancy maternal body mass index and preterm delivery. Am J Obstet Gynecol 2012;207:212.e1–7.
14. Bocca-Tjeertes IF, Kerstjens JM, Reijneveld SA, de Winter AF, Bos AF. Growth and predictors of growth restraint in moderately preterm children aged 0 to 4 years. Pediatrics 2011;128:e1187–94.
15. Crone M, Vogels A, Hoekstra F. A comparison of four scoring methods based on the parent-rated Strengths and Difficulties Questionnaire as used in the Dutch preventive child health care system. BMC Public Health 2008;8:106.
16. Squires J, Bricker D, Potter L. Ages and stages questionnaires user's guide. 2nd ed. Baltimore (MD): Paul Brookes Publishing; 1999.
17. Kerstjens JM, Bos AF, ten Vergert EMJ, de Meer G, Butcher PR, Reijneveld SA. Support for the global feasibility of the ages and stages questionnaire as developmental screener. Early Hum Dev 2009;85:443–7.
18. Kloosterman GJ. On intrauterine growth: the significance of prenatal care. Int J Gynaecol Obstet 1970;8:895–912.
19. Ganzeboom HBG, Treiman DJ. Internationally comparable measures of occupational status for the 1988 International Standard Classification of Occupations. Soc Sci Res 1996;25:201–39.
20. Helderman JB, O’Shea TM, Kuban KC, Allred EN, Hecht JL, Dammann O, et al.. Antenatal antecedents of cognitive impairment at 24 months in extremely low gestational age newborns. Pediatrics 2012;129:494–502.
21. Teune MJ, van Wassenaer AG, van Dommelen P, Mol BW, Opmeer BC; Dutch POPS-19 Collaborative Study Group. Perinatal risk indicators for long-term neurological morbidity among preterm neonates. Am J Obstet Gynecol 2011;204:396.e1–396.e14.
22. Strauss RS. Adult functional outcome of those born small for gestational age: twenty-six-year follow-up of the 1970 British Birth Cohort. JAMA 2000;283:625–32.
23. Bamberg C, Kalache KD. Prenatal diagnosis of fetal growth restriction. Semin Fetal Neonatal Med 2004;9:387–94.
24. Tozuka Y, Kumon M, Wada E, et al.. Maternal obesity impairs hippocampal BDNF production and spatial learning performance in young mouse offspring. Neurochem Int 2010;57:235–47.
25. Djelantik AA, Kunst AE, van der Wal MF, Smit HA, Vrijkotte TG. Contribution of overweight and obesity to the occurrence of adverse pregnancy outcomes in a multi-ethnic cohort: population attributive fractions for Amsterdam. BJOG 2012;119:283–90.
26. Cooke RWI. Does neonatal and infant neurodevelopmental morbidity of multiples and singletons differ? Semin Fetal Neonatal Med 2010;15:362–6.
27. Hintz SR, Kendrick DE, Vohr BR, Kenneth Poole W, Higgins RD; NICHD Neonatal Research Network. Gender differences in neurodevelopmental outcomes among extremely preterm, extremely-low-birthweight infants. Acta Paediatr 2006;95:1239–48.
28. Glascoe F. Screening for developmental and behavioral problems. Ment Retard Dev Disabil Res Rev 2005;11:173–9.
29. Goldenberg RL, Gravett MG, Iams J, Papageorghiou AT, Waller SA, Kramer M, et al.. The preterm birth syndrome: issues to consider in creating a classification system. Obstet Gynecol 2012;206:113–8.
30. Kramer MS, Papageorghiou A, Culhane J, Bhutta Z, Goldernberg RL, Gravett M, et al.. Challenges in defining and classifying the preterm birth syndrome. Obstet Gynecol 2012;206:108–12.
31. Rattihalli R, Smith L, Field D. Prevention of preterm births: are we looking in the wrong place? the case for primary prevention. Arch Dis Child Fetal Neonatal Ed 2012;97:F160–1.
32. Krans EE, Davis MM. Preventing Low Birthweight: 25 years, prenatal risk, and the failure to reinvent prenatal care. Am J Obstet Gynecol 2012;206:398–403.
33. Walker D, Marlow N, Upstone L, Gross H, Hornbuckle J, Vail A, et al.. The growth restriction intervention trial: long-term outcomes in a randomized trial of timing of delivery in fetal growth restriction. Am J Obstet Gynecol 2011;204:34.e1–9.