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ORIGINAL RESEARCH |
From the *Department of Epidemiology and Department of Maternal and Child Health, University of Alabama at Birmingham, Birmingham, Alabama; and Department of Obstetrics and Gynecology, Northwestern University, Chicago, Illinois.
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ABSTRACT |
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METHODS: We analyzed 22,463,141 singleton deliveries at 20 weeks or more of gestation in the United States from 1989 through 2000. Adjusted odds ratios generated from logistic regression models were used to approximate relative risk for neonatal morbidity in women with 1–4 (moderate parity or type I; referent group), 5–9 (high parity or type II), 10–14 (very high parity or type III) and 15 or more (extremely high parity or type IV) prior live births. Main outcome measures included low and very low birth weight, preterm and very preterm birth, and small and large for gestational age delivery.
RESULTS: The overall crude rates for low birth weight, very low birth weight, preterm birth, very preterm birth, and small and large for gestational age were 55, 11, 97, 19, 83, and 129 per 1,000 live births, respectively. The adjusted odds ratios for low birth weight, very low birth weight, preterm, and very preterm delivery increased consistently and in a dose–effect fashion with ascending parity (P for trend < .001). In the case of large for gestational age delivery, the adjusted odds ratio showed an inverted-U pattern, being highest among women in the type III parity cluster. The findings with respect to small for gestational age were inconclusive.
CONCLUSION: High parity is a risk factor for adverse fetal outcomes. However, the impact of heightened parity is more manifest as shortened gestation rather than physical size restriction. These findings could prove beneficial for counseling women of high parity.
LEVEL OF EVIDENCE: II-3
Low birth weight is a composite of 2 fetal morbidity indices: small for gestational age and preterm. Small for gestational age is closely associated with adverse perinatal outcomes22,23 and bears an increased risk for subsequent infant morbidity, including developmental disorders, psychomotor handicap, and learning disabilities. Preterm birth is a significant cause of infant morbidity and mortality, especially in developed countries.16
The need for additional data on outcomes associated with high parity, especially in developed countries with high-quality obstetric care, has been mentioned by several authors.2,3,8,27,28 However, early studies exploring this subject were not without limitations. Several were hospital-based,14,28–30 and others failed to account for strong confounders, notably maternal age,3,14,31 or were simply underpowered.7,8
We therefore sought to examine the association between liveborn parity and fetal growth outcomes (namely, low birth weight [LBW], very low birth weight [VLBW], small for gestational age [SGA], large for gestational age [LGA], and preterm and very preterm birth) using a large population-based sample. We expanded parity groupings to include liveborn parity of 15 and beyond, a group we denote as "extremely high parity" women. We hypothesized that if increasing liveborn parity is associated with adverse fetal growth outcomes, then such a relationship will manifest at such extreme degrees of parity.
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METHODS |
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The primary aim of this study was to investigate the relationship between maternal parity status and fetal growth patterns (LBW, VLBW, preterm, very preterm, SGA, and LGA) in singleton gestations. We defined maternal parity as the total number of live deliveries the mother had experienced. For the purpose of this study we further classified mothers into four parity groups: moderate parity or type I (1–4 previous live births), high parity or type II (5–9 previous live births), very high parity or type III (10–14 previous live births), and extremely high parity or type IV (
15 previous live deliveries). We excluded mothers with no previous live birth and those with multiple gestations, because these conditions have their own peculiar obstetric risks.
The components of fetal growth analyzed in this study were: preterm and very preterm delivery (< 37 and < 33 weeks gestation, respectively), LBW and VLBW (< 2,500 g and < 1,500 g, respectively), and small and LGA (<10th and > 90th percentile of birth weight for gestational age, respectively). In classifying neonates as small or LGA, we used population-based national reference curves for singletons as appropriate.34
The interval between the first day of the last menstrual period (LMP) and the date of birth was used to compute gestational age in completed weeks. Records missing the date of the LMP were imputed by the National Center for Health Statistics when there was a valid month and year. Clinical estimate of gestation was used in the computation of gestational age in cases where the date of the LMP was not reported or where the LMP date was inconsistent with the birth weight.32 Approximately, 4–5% of the gestational ages during the period were based on clinical estimate of gestation. We restricted our analyses to live births within 20–44 gestational weeks.
We compared the following sociodemographic characteristics between mothers in the 4 parity groups: maternal age, race, educational level attained, marital status, reported use of tobacco during pregnancy, and adequacy of prenatal care. Adequacy of prenatal care was assessed using the revised graduated index algorithm.35,36 This index assesses the adequacy of care based on the trimester prenatal care began, number of visits, and the gestational age of the infant at birth. In this study, inadequate prenatal care use refers to women who either had no prenatal care at all, had prenatal care but the level was considered suboptimal, or had missing prenatal care information. The accuracy of all these sociodemographic variables on the birth certificate has been previously validated.37,38
Because a woman might have more than 1 live birth during the period of study, we matched siblings by using 4 distinct maternal characteristics: maternal race, ethnicity, maternal place of birth and the computed maternal ages in subsequent years within the study period, as previously reported.39 A variant of this algorithm has been previously validated and found by us and other investigators to be accurate.39,40
We estimated the risk for each of the fetal growth indices within parity subgroups using logistic regression that generated adjusted odds ratios that we used to approximate the relative risk. To control for intracluster correlations among siblings, we applied the generalized estimating equations41 using the PROC GENMOD in SAS 9.1 (SAS, Cary, NC). We constructed 2 models in deriving the adjusted relative risk: in the first, adjusted estimates were generated by taking into account the confounding effects of maternal education, maternal age, maternal race, year of birth, marital status, adequacy of prenatal care, and maternal smoking during pregnancy. In the second, we included a composite variable for maternal complications in addition to the aforementioned confounders. Using the maternal characteristics as covariates, we also generated propensity scores42 for each individual and included these scores in the logistic models. The propensity score in this case represented each mother's probability, on the basis of her covariate values, of belonging to a specific parity subgroup. We applied this "quasi randomized" technique to reduce bias and increase the precision of our estimates.43 Further, we used the 
2 statistic to assess linear trend.44 All tests of hypothesis were 2-tailed, with a type 1 error rate fixed at 5%. This study was approved by the Institutional Review Board at the University of Alabama at Birmingham.
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RESULTS |
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Table 2 compares the distribution of relatively common medical complications experienced during pregnancy across the 4 parity subgroups. The rates of diabetes, hypertension, placenta previa, and placental abruption increased with increasing parity in a dose-dependent pattern (P for trend < .001). However, the occurrence of preeclampsia was U-shaped, being lowest in type II (2%) and highest in type IV subgroup (3.5%).
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Overall, a total of 1,244,998 LBW, 247,580 VLBW, 2,140,024 preterm, 409,082 very preterm, and 1,838,712 SGA deliveries occurred during the study period. The overall crude rate for LBW, VLBW, preterm birth, very preterm birth, and SGA were 55 of 1000, 11 of 1000, 97 of 1000, 19 of 1000 and 83 of 1000 live births, respectively. A total of 2,851,363 LGA babies were also recorded during the same period, resulting in the crude rate for LGA delivery (129/1,000) being higher than the rates of the other fetal growth indices. Figure 1 displays the crude rates of these morbidity indices by parity subtype. With the exception of SGA and LGA, a linear increase in the crude rate for all growth indices is evident with increasing parity.
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We present adjusted estimates for the association between fetal growth indices and parity status (with mothers in the type I parity group as the referent category) in Table 3. In the lower half of the table we included maternal complications as possible confounders in addition to the sociodemographic variables listed in the footnote to the table. The estimates generated from both models were similar and the adjusted odds ratios for LBW, VLBW, and preterm and very preterm delivery were uniformly higher in mothers belonging to the 3 upper parity classes (types II–IV) as compared with their counterparts in the type I parity subgroup. Further, there was a significant dose–response relationship, with increasing parity for the aforementioned growth indices (LBW, VLBW, and preterm and very preterm) (P for trend < .001). However, the adjusted odds ratio for SGA delivery among mothers in the type III group was lower than that of mothers in the referent category, whereas mothers in the extremely high parity subgroup (type IV) had comparable risk of having an SGA baby compared with their counterparts in the referent category. In the case of LGA delivery, the adjusted odds ratio showed an inverted-U pattern, being highest among women in the type III parity cluster.
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DISCUSSION |
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Our analysis suggests that shortened gestation rather than physical size restriction (SGA) was the component of fetal growth affected by heightened parity. Just as in the case of LBW, positive and null associations2,6,9,20,21 between preterm delivery and increased parity occur in the literature. Schram et al17 attempted to explain the connection between repeated births and preterm delivery by observing that preterm labor in grand multiparas was related to an increased level of domestic work and responsibilities. Other authors postulated that the preponderance of serious placental complications might be responsible.7 Placental abruption and placenta previa both showed a significant increase with ascending parity in a consistent manner. However, when we adjusted for pregnancy complications including placental pathologies (Model II) the results remained unchanged, an indication that placental complications alone do not explain the heightened risk for preterm delivery among women with excessive parity.
Our study does not find a definite and consistent relationship between parity status and SGA. Rather than SGA, the literature suggests an excess of macrosomic babies among grand multiparas.5,6,8,27,45–47 The higher incidence of macrosomic deliveries among grand multiparas45 has been attributed to the increased frequency of diabetes mellitus17 and the tendency among these mothers to have a high maternal body mass index.45 We found an increase in LGA babies (our indicator for infant macrosomia) in women with parity beyond type I, although a consistent dose–effect pattern was not evident. This finding supports the dominant view that parity is an independent risk factor for infant macrosomia.8,29,47
Women of advanced parity are likely to be of advanced age as well, so that the results observed in our study might reflect the effect of older age rather than parity alone, because it is known that fetal growth and maturity are impaired among older women.48 The fact that both models on which our results are based included maternal age as a covariate counters the possibility that maternal age could have explained our findings.
A shortcoming in this study was the limitation in the array of information available. Although one of the merits of our analysis is the ability to control for several confounding characteristics, it is worth mentioning that our data did not provide information on negative behaviors49 or psychosocial stressors, both of which have been associated with adverse birth outcomes.50 Another limitation of this analysis is our inability to account for the contribution of shorter interpregnancy intervals to higher parity and adverse birth outcomes because the data set for this study did not provide specific information in this regard.
A strength of this paper is the ample sample size that provided an acceptable level of precision in estimates. Also, the population-wide nature of the study minimizes biases that might have been induced as a result of selective inclusion of certain population subgroups that have risk profiles that may not be representative of the entire population. To that extent, our findings are therefore generalizable to women of high parity.
In summary, we found the risk for LBW, VLBW, and preterm and very preterm birth to be elevated in a dose–effect fashion among women who experienced 5 or more live births. These women also had a greater-than-expected incidence of macrosomic babies. These findings could prove useful to care providers for periconceptional counseling of women with high parity.
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Footnotes |
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Address reprint requests to: Hamisu Salihu MD, PhD, Department of Maternal and Child Health, University of Alabama at Birmingham, 1665 University Boulevard, Room 320, Birmingham, Alabama 35294; e-mail: hsalihu{at}uab.edu.
Received November 29, 2004. Received in revised form January 5, 2005. Accepted January 13, 2005.
doi:10.1097/01.AOG.0000157444.74674.75
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