birth order and risk of childhood cancer

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Birth order and risk of childhood cancer: a pooled analysisfrom five US States

Julie Von Behren1, Logan G. Spector2,3, Beth A. Mueller4, Susan E. Carozza5, Eric J. Chow4, Erin E. Fox6, Scott Horel5,

Kimberly J. Johnson2, Colleen McLaughlin7, Susan E. Puumala2, Julie A. Ross2,3 and Peggy Reynolds1

1 Cancer Prevention Institute of California, Berkeley, CA2 Division of Epidemiology/Clinical Research, Department of Pediatrics, University of Minnesota, Minneapolis, MN3 Masonic Cancer Center, University of Minnesota, Minneapolis, MN4 Dept. of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA5 Department of Public Health, Oregon State University, Corvallis, OR6 Cancer Epidemiology and Surveillance Branch, Texas Department of State Health Services, Austin, TX7 New York State Cancer Registry, New York Department of Health, Albany, NY

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 ofcancers and births in California, Minnesota, New York, Texas and Washington. We included 17,672 cases


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where only cases


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When we examined the CNS tumors in more detail, there

was little apparent variation in risk by tumor subtypes (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 forthe highest birth category were also decreased forependymoma,

intracranial and intraspinal germ cell tumors and PNET, rang-

ing 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).

DiscussionOverall, 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, rhab-

domyosarcoma and bilateral retinoblastoma. Our pooledanalysis included more than 17,000 children with cancer,

which allowed us to examine many rare subtypes 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, nonsignificant 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 report-

ing increased risk for ALL with high birth order,17,18 some

finding decreased risk7,10,11 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

children69,19 although this was not reported by others.1013

Our results for the CNS cancers are consistent with a

recent case-control study from France that found decreased

risk for third or higher birth order for CNS tumors (OR

0.8, 95% CI: 0.51.2).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 werealso included in the pooled dataset).16 Similarly Linet et al.

reported an increased risk for CNS tumors for first born chil-

dren.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-statisti-

cally significant results.2326 Two recent studies have sug-

gested that CNS tumor risk increases with number of sib-

lings27 and children in the household.28 These discrepancies

may be because of relatively small sample sizes in many stud-

ies and different measures used, such as birth order vs. num-

ber of siblings.

Table 2. Characteristics of cases and controls

Cases N (%) Controls N (%)

Maternal age (years)


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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 character-

istics 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, although neitherof 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 rela-

tively 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 secondgenetic 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.3436 We were not able to account for either of these var-

iables. We also lacked information on the number of house-

hold residents and other factors that affect childrens 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

Table 3. Number of cases by birth order by cancer type in the pooled dataset

Birth order

Cancer Type First Second Third Fourth or higher Total Cases

Leukemia 2342 1902 965 630 5839

Lymphoid leukemia 1918 1539 752 490 4699

Acute myeloid leukemia 315 264 154 109 842

Chronic myeloproliferative diseases 35 33 24 17 109

Lymphoma 613 490 224 172 1499

Hodgkin lymphoma 195 148 77 57 477

Non-Hodgkin lymphoma 252 191 89 60 592

Burkitt lymphoma 93 79 27 29 228

CNS 1566 1285 556 333 3740

Ependymoma and choroid plexus 168 132 51 32 383

Astrocytoma 703 573 235 139 1650

Intracranial embryonal 370 285 145 88 888

Other gliomas 193 183 79 38 493Neuroblastoma 628 469 252 121 1470

Retinoblastoma 271 225 119 64 679

Wilms tumor 518 379 163 108 1168

Hepatoblastoma 126 76 40 31 273

Bone tumors 225 187 86 52 550

Osteosarcoma 116 98 41 24 279

Ewing sarcoma 79 76 35 22 212

Soft Tissue Sarcoma 437 332 171 114 1054

Rhabdomyosarcoma 261 178 82 59 580

Germ Cell Tumors 233 178 76 73 560

Gonadal Germ Cell Tumors 111 80 43 40 274

Epidemiology

Int. J. Cancer: 000, 000000 (2010) VC 2010 UICC

4 Birth order and risk of childhood cancer


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clinical diagnoses via medical records37 and daily diaries to

capture subclinical infections, however the latter would beuseful only in prospective studies.1

Birth order may be a marker of different hormonal expo-

sures 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 with second

or third pregnancies.3,4,38 Birth order also has been investi-

gated with respect to several types of adult cancers, particu-

larly 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 haveexamined 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 microchimer-

ism (presence of cells or DNA from genetically distinct indi-

viduals, in this instance as acquired in utero from the mother

and older siblings who may have exchanged cells with her

during the earlier pregnancies). Bidirectional trafficking of

cells between mother and fetus during pregnancy has been

demonstrated43 with retention of maternal cells among off-

spring potentially lasting decades.44 Such microchimerism

Table 4. Birth order by cancer type in the pooled dataset: Adjusted odds ratios

Birth Order

First Second OR1 (95% CI) Third OR1 (95% CI) Fourth or higher OR1 (95% CI)

All cancers combined Ref 0.96 (0.92, 1.01) 0.90 (0.85, 0.96) 0.87 (0.81, 0.93)

Leukemia Ref 0.97 (0.91, 1.04) 0.96 (0.88, 1.04) 0.94 (0.85, 1.04)

Lymphoid leukima Ref 0.96 (0.89, 1.03) 0.90 (0.82, 0.99) 0.90 (0.80, 1.01)

Acute myeloid leukemia Ref 1.04 (0.88, 1.24) 1.17 (0.95, 1.44) 1.21 (0.95, 1.55)

Chronic myeloproliferative diseases Ref 1.09 (0.66, 1.81) 1.65 (0.95, 2.88) 1.66 (0.86, 3.20)

Lymphoma Ref 0.98 (0.86, 1.11) 0.92 (0.78, 1.08) 1.07 (0.88, 1.30)

Hodgkin lymphoma Ref 0.96 (0.76, 1.21) 1.07 (0.80, 1.43) 1.26 (0.90, 1.78)

Non-Hodgkin lymphoma Ref 0.90 (0.74, 1.11) 0.86 (0.67, 1.12) 0.83 (0.60, 1.14)

Burkitt lymphoma Ref 1.02 (0.75, 1.40) 0.72 (0.47, 1.13) 1.18 (0.75, 1.85)

CNS Ref 1.01 (0.93, 1.09) 0.85 (0.77, 0.95) 0.77 (0.68, 0.89)

Ependymoma and choroid plexus Ref 0.97 (0.77, 1.23) 0.71 (0.51, 0.99) 0.62 (0.41, 0.95)

Astrocytoma Ref 0.98 (0.87, 1.10) 0.79 (0.67, 0.92) 0.72 (0.59, 0.88)

Intracranial embryonal Ref 0.99 (0.84, 1.16) 0.96 (0.78, 1.18) 0.93 (0.72, 1.20)

Other gliomas Ref 1.21 (0.97, 1.50) 1.05 (0.79, 1.39) 0.76 (0.52, 1.10)

Neuroblastoma Ref 0.91 (0.80, 1.03) 0.91 (0.78, 1.07) 0.68 (0.55, 0.84)

Retinoblastoma Ref 1.09 (0.91, 1.31) 1.09 (0.87, 1.37) 0.89 (0.66, 1.19)

Unilateral Ref 1.25 (0.99, 1.58) 1.33 (1.00, 1.77) 1.19 (0.83, 1.70)

Bilateral Ref 0.87 (0.61, 1.24) 0.63 (0.38, 1.03) 0.43 (0.22, 0.84)

Wilms tumor Ref 0.84 (0.73, 0.97) 0.69 (0.57, 0.83) 0.67 (0.54, 0.84)

Unilateral Ref 0.87 (0.74, 1.01) 0.74 (0.60, 0.90) 0.66 (0.52, 0.86)

Bilateral Ref 0.84 (0.51, 1.39) 0.69 (0.36, 1.33) 0.58 (0.26, 1.30)

Hepatoblastoma Ref 0.79 (0.58, 1.06) 0.72 (0.49, 1.06) 0.93 (0.61, 1.43)

Bone tumors Ref 0.98 (0.80, 1.21) 0.85 (0.64, 1.11) 0.76 (0.54, 1.07)

Osteosarcoma Ref 1.06 (0.79, 1.41) 0.79 (0.53, 1.18) 0.64 (0.38, 1.09)

Ewing sarcoma Ref 1.08 (0.78, 1.51) 1.00 (0.66, 1.54) 0.99 (0.59, 1.66)

Soft Tissue Sarcoma Ref 0.91 (0.79, 1.06) 0.91 (0.75, 1.10) 0.91 (0.72, 1.14)

Rhabdomyosarcoma Ref 0.82 (0.67, 1.00) 0.70 (0.54, 0.91) 0.75 (0.56, 1.03)

Germ Cell Tumors Ref 0.95 (0.77, 1.17) 0.81 (0.62, 1.07) 1.26 (0.94, 1.68)

Gonadal Germ Cell Tumors Ref 0.89 (0.66, 1.21) 0.98 (0.67, 1.42) 1.54 (1.04, 2.29)

1Adjusted for matching and pooling variables (state, sex, year of birth), maternal race, maternal age category, singleton vs. multiple birth,gestational age and birth weight.


Von Behren et al. 5


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may result in varying levels of disease susceptibility by birth

order,45 and is one suggested mechanism46 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 epide-

miologic 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

Figure 1. Adjusted odds ratios and 95% confidence intervals for birth order categories by cancer type.

Table 5. Birth order by leukemia subtypes by age group: Adjusted1 odds ratios

Leukemia subtypes by age group First Second Third Fourth or higher

Ages 04 years

Lymphoid leukemia-N 1348 1107 523 352

OR (95% CI) Ref 0.98 (0.90, 1.07) 0.88 (0.79, 0.99) 0.89 (0.78, 1.02)

Acute myeloid leukemia-N 190 172 103 78

OR (95% CI) Ref 1.16 (0.93, 1.44) 1.32 (1.02, 1.70) 1.42 (1.06, 1.90)

Chronic myeloproliferative diseases-N 18 21 17 11

OR (95% CI) Ref 1.33 (0.69, 2.55) 2.41 (1.21, 4.79) 2.38 (1.05, 5.41)

Ages 59 yearsLymphoid leukemia-N 365 284 151 97

OR (95% CI) Ref 0.97 (0.82, 1.14) 1.05 (0.86, 1.29) 1.18 (0.92, 1.50)


OR (95% CI) Ref 0.71 (0.47, 1.08) 0.85 (0.52, 1.40) 0.82 (0.45, 1.53)

Chronic myeloproliferative diseases-N 9 3 5 1

OR (95% CI) Ref Not run. Total N18 cases

Ages 1014 years

Lymphoid leukemia-N 205 148 78 41

OR (95% CI) Ref 0.82 (0.65, 1.04) 0.91 (0.68, 1.22) 0.68 (0.46, 1.02)


OR (95% CI) Ref 1.05 (0.71, 1.55) 1.12 (0.68, 1.83) 1.07 (0.58, 1.97)Chronic myeloproliferative diseases-N 8 9 2 5

OR (95% CI) Ref Not run. Total N24 cases

1Adjusted for matching and pooling variables (state, sex, year of birth), maternal race, maternal age category, singleton vs. multiple birth,gestational age and birth weight.

Epidemiology




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the birth order data. We also were not able to control for soci-

oeconomic status, which may be associated with both birth

order and some cancers5 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 infor-

mation 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.

AcknowledgementsWe thank all of the collaborating institutions for allowing data access.

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Table 6. Adjusted1 odds ratios for the revised CNS tumors subtypes and birth order

CNS Tumor Type First Second Third Fourth 1

Ependymoma-N 141 107 43 28

OR (95% CI) Ref 0.94 (0.721.22) 0.71 (0.501.02) 0.65 (0.411.01)

High Grade Gliomas-N 252 246 114 49

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Low Grade Gliomas-N 678 542 211 132

OR (95% CI) Ref 0.95 (0.841.08) 0.73 (0.620.86) 0.70 (0.570.87)

Medulloblastoma-N 225 203 95 56

OR (95% CI) Ref 1.18 (0.971.44) 1.05 (0.821.36) 1.04 (0.761.43)

Primitive Neuroectodermal Tumors-N 145 82 51 32

OR (95% CI) Ref 0.69 (0.520.92) 0.82 (0.591.16) 0.76 (0.501.16)

Intracranial and Intraspinal Germ Cell tumors-N 26 33 11 7

OR (95% CI) Ref 0.93 (0.611.43) 0.72 (0.401.29) 0.74 (0.361.52)

1Adjusted for state, birth year (quartiles), childs sex, maternal race, maternal age, gestational age, plurality and birth weight.


Von Behren et al. 7


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