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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Int J Cancer. Author manuscript; available in PMC Jun 1, 2012.
Published in final edited form as:
PMCID: PMC3008504
NIHMSID: NIHMS230557
Birth order and Risk of Childhood Cancer: A Pooled Analysis from Five U.S. States
Julie Von Behren,1 Logan G. Spector,2,3 Beth A. Mueller,4 Susan E. Carozza,5 Eric J. Chow,4 Erin E. Fox,6 Scott Horel,5 Kimberly J. Johnson,2 Colleen McLaughlin,7 Susan E. Puumala,2 Julie A. Ross,2,3 and Peggy Reynolds1
1Cancer Prevention Institute of California, Berkeley, CA
2 Division of Epidemiology/Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, MN
3 Masonic Cancer Center, University of Minnesota, Minneapolis, MN
4 Fred Hutchinson Cancer Research Center, Seattle, WA
5 Department of Public Health, Oregon State University, Corvallis, OR
6 Cancer Epidemiology and Surveillance Branch, Texas Department of State Health Services, Austin, TX
7 New York State Cancer Registry, New York Department of Health, Albany, NY
Correspondence to: Julie Von Behren, Cancer Prevention Institute of California, 2001 Center Street, Suite 700, Berkeley, CA, 94704 (tel: (510) 608-5188; fax: (510) 666-0693; julie.vonbehren/at/cpic.org)
The causes of childhood cancers are largely unknown. Birth order has been used as a proxy for prenatal and postnatal exposures, such as frequency of infections and in utero hormone exposures. We investigated the association between birth order and childhood cancers in a pooled case-control dataset. The subjects were drawn from population-based registries of cancers and births in California, Minnesota, New York, Texas, and Washington. We included 17,672 cases less than 15 years of age who were diagnosed from1980-2004 and 57,966 randomly selected controls born 1970-2004, excluding children with Down syndrome. We calculated odds ratios and 95% confidence intervals using logistic regression, adjusted for sex, birth year, maternal race, maternal age, multiple birth, gestational age, and birth weight. Overall, we found an inverse relationship between childhood cancer risk and birth order. For children in the fourth or higher birth order category compared to first-born children, the adjusted OR was 0.87 (95% CI: 0.81, 0.93) for all cancers combined. When we examined risks by cancer type, a decreasing risk with increasing birth order was seen in the central nervous system (CNS) tumors, neuroblastoma, bilateral retinoblastoma, Wilms tumor, and rhabdomyosarcoma. We observed increased risks with increasing birth order for acute myeloid leukemia but a slight decrease in risk for acute lymphoid leukemia. These risk estimates were based on a very large sample size which allowed us to examine rare cancer types with greater statistical power than in most previous studies, however the biologic mechanisms remain to be elucidated.
Keywords: birth order, case-control studies, child, epidemiology, neoplasms
Birth order has traditionally been used as a proxy for both prenatal and postnatal exposures in childhood cancer studies, as it provides an easily measured characteristic associated with data that are more difficult to collect retrospectively, particularly the timing and frequency of infectious exposures in early life 1. Birth order may also signify differing levels of in utero hormone exposure 2-4. Leukemia, the most common form of childhood cancer, has been the malignancy most often studied with regard to birth order but the findings have been inconsistent, demonstrating both increased and decreased risks for increasing birth order 1, 5-13. Similarly, the literature has been inconsistent with regard to birth order and other types of childhood cancers, possibly due to relatively small sample sizes 5. Our goal was to investigate the association between birth order and all types of childhood cancers in a large, pooled case-control dataset with sufficient statistical power to examine many of the rare sub-types of these diseases.
Data were combined from five previous studies in which the incident cases of childhood cancer were identified from the population-based cancer registries of five states: California, Minnesota, New York (excluding New York City), Texas, and Washington. Cases were diagnosed between 1980 and 2004. The details of each state's selection and inclusion criteria have been previously reported 14. Children up to age 14 years at diagnosis were included except in California where only cases less than 5 years of age were included (the CA study was originally designed to study early childhood cancers only). Cases were matched to birth certificates using probabilistic or sequential deterministic record linkage. Controls were randomly selected from each state's birth registry, in ratios to cases varying from 1:1 to 1:10 (differed by state). They were matched on date of birth in all states and also matched on sex in California and Texas. Any subject reported to have Down syndrome was excluded (n=100). Because subjects diagnosed before age 28 days were excluded in some of the states, this criterion was applied to all cases for consistency.
We classified the cancers according to the International Classification of Childhood Cancer (ICCC-3) and examined all groups with at least 200 cases 15. We made one exception to this rule in order to examine the 109 cases of chronic myeloproliferative diseases (CMD) because of our interest in leukemia sub-types. Wilms tumors and retinoblastoma were further examined by unilateral and bilateral occurrence. Additionally we examined the CNS tumors by type to reflect clinically relevant biological differences using categories previously developed 16. We classified pilocytic astrocytomas, astrocytomas not otherwise specified, and other grade I and II gliomas into the low grade glioma category. Malignant gliomas, anaplastic astrocytomas, and other grade III and IV gliomas were grouped into the high grade glioma category. Other separate categories included medulloblastomas, primitive neuroectodermal tumors (PNET), ependymomas, and intracranial/intraspinal germ cell tumors.
Odds ratios (OR) and 95% confidence intervals (CI) were calculated using unconditional logistic regression (SAS version 9.1). The individual matching of the California cases and controls was broken to allow the use of this procedure. The other states used frequency matching. We examined birth order in four categories: first, second, third, and fourth or more. In the multivariable analyses we adjusted for matching and pooling variables (state, sex, year of birth), maternal race, maternal age, singleton vs. multiple birth, gestational age, and birth weight (all categorized as shown in Table 2). We also stratified the analyses for the leukemia sub-types by age at diagnosis (0-4 years, 5-9 years, 10-14 years).
Table 2
Table 2
Characteristics of Cases and Controls
We included a total of 17,672 cases and 57,966controls in this study. Mothers of cases were slightly older than mothers of controls (Table 2). Cases had slightly higher birth weights and were more likely to be males than controls. Over 60% of the cases were diagnosed at less than 5 years of age.
Table 3 shows the number of cases for each type of cancer examined. Overall, the distribution of cases and controls by birth order were very similar and the median for both groups was 2. For all cancer types combined we observed a slightly decreasing risk associated with increasing birth order (Table 4 and Figure 1). For children in the highest birth order category compared to first-born children, the adjusted OR was 0.87 (95% CI: 0.81, 0.93) for all cancers. When we examined the risk by ICCC-3 groups of cancer types, the decreasing risk with increasing birth order was seen in the CNS tumors, neuroblastoma, bilateral retinoblastoma, Wilms tumor, and rhabdomyosarcoma (Table 4). For all CNS tumors combined the adjusted OR for fourth or higher birth order category was 0.77 (CI: 0.68, 0.89) (see also Figure 1). The adjusted OR for the highest birth order category compared to first born children was 0.68 (CI: 0.55, 0.84) for neuroblastoma, 0.67 (CI:0.54, 0.84) for Wilms tumor, and 0.43 (CI: 0.22, 0.84) for bilateral retinoblastoma. The point estimates for unilateral and bilateral Wilms tumor were similar, though they were only statistically significant for the unilateral tumors, which were much more common in this dataset. For acute lymphoid leukemia (ALL) there was only a modestly decreased risk associated with both the third (OR=0.90, CI: 0.82, 0.99) and fourth birth order categories (OR=0.90, CI: 0.80, 1.01) (see also Figure 1). In contrast, we observed increasing risk with increasing birth order for acute myeloid leukemia (AML) and CMD, with the adjusted ORs for the highest birth order category 1.21 (CI: 0.95, 1.55) and 1.66 (CI: 0.86, 3.20), respectively. However, these increased ORs were not statistically significant until we stratified by age group. The OR for highest birth order category and gonadal germ cell tumors was 1.54 (CI: 1.04, 2.29) but the ORs were below one for the second and third birth order categories.
Table 3
Table 3
Number of Cases by Birth order by cancer type in the pooled dataset
Table 4
Table 4
Birth order by cancer type in the pooled dataset: Adjusted Odds Ratios
Figure 1
Figure 1
Adjusted Odds ratios and 95% confidence intervals for birth order categories by cancer type.
A majority of the leukemias occurred in children under 5 years of age (70% of ALL cases, 64% of AML cases, and 61% of CMD cases). When we stratified the analyses for the leukemia subtypes by age group, we observed the increased risks for AML and CMD in the 0 to 4 year olds only (Table 5). However, we observed a slight decrease in risk associated with high birth order and ALL for the 0-4 and 10-14 year old age groups (OR=0.89 and 0.68, respectively, though these were not statistically significant).
Table 5
Table 5
Birth order by leukemia subtypes by age group: Adjusted Odds Ratios
When we examined the CNS tumors in more detail, there was little apparent variation in risk by tumor sub-types (Table 6). The high grade and low grade gliomas had very similar risk estimates. The OR for high grade glioma associated with being fourth or greater birth order was 0.74 (CI: 0.53, 1.03) and the OR for low grade glioma was 0.70 (CI: 0.57,0.87). The ORs for the highest birth category were also decreased forependymoma, intracranial and intraspinal germ cell tumors, and PNET, ranging from 0.65 to 0.76, albeit not statistically significant. The only OR for the highest birth category not decreased among the CNS tumor groups examined was for medulloblastoma (OR=1.04, CI: 0.76, 1.43).
Table 6
Table 6
Adjusted Odds Ratios for the revised CNS tumors subtypes and birth order.
Overall, we found an inverse relationship between childhood cancer risk and increasing birth order. This effect was mainly seen in the CNS tumors, neuroblastoma, Wilms tumor, rhabdomyosarcoma, and bilateral retinoblastoma. Our pooled analysis included more than 17,000 children with cancer which allowed us to examine many rare sub-types with greater statistical power than in most previous studies. In addition, we were able to control for several factors, such as birth weight and maternal age that are associated with both birth order and several childhood cancers.
We observed only a slight, non-significant decrease in risk of ALL, the most common form of childhood leukemia, with increasing birth order. Previous studies of ALL and birth order have had inconsistent results with some studies reporting increased risk for ALL with high birth order 17, 18, some finding decreased risk 7, 10, 11, and others finding no association or weak associations 8, 9, 12. In contrast to the ALL findings, we observed an increased risk with increasing birth order for the rarer types of leukemia, AML and CMD, primarily in the youngest age group. Several other studies that have examined AML separately have also found increased risk associated with increasing birth order, particularly in infants and young children 6-9, 19 although this was not reported by others 10-13.
Our results for the CNS cancers are consistent with a recent case-control study from France that found decreased risk for 3rd or higher birth order for CNS tumors (OR=0.8, 95% CI: 0.5-1.2) 20. Significantly reduced risk for low grade gliomas and high birth order was also noted in a recent California study (25% of the cases in this new CA study were also included in the pooled dataset) 16. Similarly Linet et al. reported an increased risk for CNS tumors for first born children 21. In contrast, Shaw et al. reported that second or higher birth order children were at higher risk 22. Several other studies have reported null or mixed and non-statistically significant results 23-26. Two recent studies have suggested that CNS tumor risk increases with number of siblings 27 and children in the household 28. These discrepancies may be due to relatively small sample sizes in many studies and different measures used, such as birth order vs. number of siblings.
Most previous studies of birth order and neuroblastoma have also shown that later born children are at decreased risk 29. A recent French study found decreased neuroblastoma risk with high birth order with a very similar magnitude as that in our present study (OR=0.6, 95% CI 0.4, 1.0 for third or higher birth order) 30.
Because of its rarity little is known about birth characteristics and Wilms tumors. Two previous studies of these embryonal tumors of the kidneys have reported, as did ours, that firstborn children are at increased risk, though neither of these smaller studies had statistically significant findings 31, 32.
Similarly there is very little literature on retinoblastoma and birth order. A recent report from Australia found decreased risk for children who were not firstborn (OR= 0.86, 95% CI: 0.46, 1.64) 32. It is not clear why the decreased risk we observed for increasing birth order would be for bilateral retinoblastoma only. This could be due to chance, given the large number of comparisons made and the relatively small number of retinoblastoma cases. Alternatively, families with bilateral retinoblastoma may receive genetic counseling about increased risks and opt to limit childbearing.
Birth order may be a marker of infectious exposures with later-born children presumed to be more often exposed by older siblings and exposed at earlier ages. The associations we observed between birth order and cancer risk for certain tumors suggests that the immune system may play some role in cancer risk. For example, Greaves proposed that delayed exposures to infections may cause an abnormal response after a common infection, increasing the chance of the second genetic mutation that leads to ALL 33. However, we did not observe much difference in risk for ALL associated with birth order. Any relationship between birth order and infectious exposures may be diluted if the birth interval is large or if a child acquires infections from other sources, such as day care 34-36. We were not able to account for either of these variables. We also lacked information on the number of household residents and other factors that affect children's immune systems, such as breast feeding, history of infectious illnesses, and vaccinations. Methods for improving the assessment of childhood infections are being developed, including use of clinical diagnoses via medical records 37 and daily diaries to capture sub-clinical infections, however the latter would be useful only in prospective studies 1.
Birth order may be a marker of different hormonal exposures to the fetus. These early exposures to hormones may affect future cancer development 2. It is possible that firstborn children have higher estrogen exposures that may contribute to greater risk of cancer than later born children. Estrogen levels in maternal and umbilical cord blood samples are somewhat greater in first pregnancies compared to second or third pregnancies 3, 4, 38. Birth order also has been investigated with respect to several types of adult cancers, particularly those with possible hormonal-mediated mechanisms. Higher birth order has been associated with decreased risk of testicular cancer 39, 40 and adult glioma 41. Many studies have examined birth order and breast cancer risk with mostly null findings 42.
A third possibility is that higher birth order individuals have higher levels than first born individuals of microchimerism (presence of cells or DNA from genetically distinct individuals, in this instance as acquired in utero from the mother and older siblings who may have exchanged cells with her during the earlier pregnancies). Bi-directional trafficking of cells between mother and fetus during pregnancy has been demonstrated 43 with retention of maternal cells among offspring potentially lasting decades 44. Such microchimerism may result in varying levels of disease susceptibility by birth order 45, and is one suggested mechanism 46 for an observed birth order pattern in the inheritance of chronic lymphocytic leukemia and lymphoproliferative disease 47. However, this is purely speculation, as currently there is a paucity of epidemiologic data to explore this hypothesis.
This study was limited to information collected on birth certificates. We did not have a way to assess the accuracy of the birth order data. We also were not able to control for socioeconomic status, which may be associated with both birth order and some cancers 5 although SES, as measured by years of parental education, was not associated with cancer risk for most tumors types in this dataset 48. In addition, we may have missed some cancer cases among the control subjects that could have moved out of the registry catchment areas.
In conclusion, this study had the advantage of a very large sample size drawn from population-based birth and cancer registries from five different states. We had information on many potential confounders such as maternal age, race, and birth weight. While we may have accurately identified associations of particular childhood cancers with birth order, the biologic mechanisms remain to be elucidated.
Table 1
Table 1
Details of the Five Studies included in the Pooled Analysis
Acknowledgments
We thank all of the collaborating institutions for allowing data access. Funding support was provided by the Children's Cancer Research Fund, Minneapolis, MN; National Institutes of Health training grant T32 CA099936, National Cancer Institute (N01-CN-05230 to WA, R01CA717450 to CA, R01CA92670 to TX); Fred Hutchinson Cancer Research Center; and the Centers for Disease Control and Prevention's National Program of Cancer Registries by cooperative agreement (U58DP000783-01 to NY).
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