1. Birth Weight and Childhood Cancer and Leukemia Update from the I4C Environmental Working Group on Birth Weight and Childhood Cancer Ora Paltiel, Hadassah-Hebrew University, School of Pubic Health, Jerusalem, Israel Barcelona, Sept 2011

2. Background- Big babies and leukemia

4. Data from 31 studies, mostly case control, JPS and Danish registry study included

5. High Birth weight (categorical) and childhood leukemia

6. Birth weight per kg and childhood leukemia: International Journal of Cancer Volume 124, Issue 11, pages 2658- 2670, Volume 124, Issue 11, Samuelsen (Epidemiology 2009) Norwegian Cancer Registry including 1,842,113 live-born infants born 1967 -1998 demonstrated an increase in leukemia risk of 29% per 1000g increase in birth weight, increase for all cancers was 23% after adjustment for gestational age

7. High Birth weight and childhood ALL International Journal of Cancer Volume 124, Issue 11, pages 2658-2670, 18 DEC 2008 DOI: 10.1002/ijc.24225 http://onlinelibrary.wiley.com/doi/10.1002/ijc.24225/full#fig2 Volume 124, Issue 11, http://onlinelibrary.wiley.com/doi/10.1002/ijc.24225/full#fig2

8. Birth weight and childhood AML International Journal of Cancer Volume 124, Issue 11, pages 2658-2670, 18 DEC 2008 DOI: 10.1002/ijc.24225 http://onlinelibrary.wiley.com/doi/10.1002/ijc.24225/full#fig3 Volume 124, Issue 11, http://onlinelibrary.wiley.com/doi/10.1002/ijc.24225/full#fig3

9. Beyond birth weight… fetal growth and leukemia Milne (AM J Epid 2009) showed an increased risk of childhood ALL for every 1-standard deviation increase in "proportion of optimal birth weight" (OR 1.18, 95%CI :1.04- 1.34) derived from a regression equation including gestational age, maternal height, parity and infant sex

10. Birth certificate data of 2,254 children with cancer <5 years old at diagnosis and registered at Texas Cancer Registry 1995-2003 were compared to 11,734 age-matched controls. Using model diagnostics, the model containing BW corrected-for-gestational age was a better predictor than the model with BW alone

11. Determinants of birth weight Gestational age Birth length Child gender Altitude Birth order SES ethnicity Smoking Gestational diabetes Maternal height Pre-pregnancy BMI Gestational weight gain

13. New case for action…. Prevalence of obesity in 20-29 yo females US 1960-2004 Prevalence of obesity among pregnant women

14. The I4C provides a unique opportunity to examine the relations using rich prospectively collected data, taking into account a large variety of covariates and modifiers of BW. The temporal and geographical diversity of cohorts participating in the I4C will allow the analysis of secular trends in the BW- cancer association as well as geographic/ ethnic variations in this relation.

15. Aim Of I4C study To investigate the association between birth weight (BW) and other measures of fetal growth and childhood cancer, specifically leukemia, with specific attention to determinants of BW such as maternal obesity, weight gain in pregnancy, pregnancy complications, in a pooled analysis of childhood cancer cohorts.

16. Specific objectives 1.To examine the pattern of the association between BW and other measures of fetal growth and the risk of childhood AML, ALL, all leukemia, other cancers: U, linear, threshold effect, and examining BW both as a continuous and categorical variable 2.To examine these associations in specific age groups: Infant (up to age 1 year); Early childhood (1-4); Later childhood (5-9); Early adolescence (10-14), controlling for and in strata of maternal prepregnancy BMI, and weight gain during pregnancy.

17. 3.To determine whether the associations are consistent over time, and across ethnicities/geography groups using data from the various cohorts with inception times in different epochs. eg CPP 1959-65, JPS 64-76, other cohorts in the 80s,90s, 2000 4. To investigate the hypothesis that diabetes in the mother, especially type 2DM and gestational DM increases the risk of cancer and no such association is seen for paternal diabetes. Specific objectives cont’d

18. Feasibility The basic data on BW, gender, birth order and cancer incidence are available in all cohorts. In JPS data on gestational age, pre-pregnancy BMI and weight gain during pregnancy are only available for subcohort

19. Participating cohorts TIHS JPS ALSPAC CPP MoBa DNBC

20. Table 1: Participating cohort sample size and number of cancer and ALL cases. CohortTotal number live births Total number of cancer cases Number of ALL % (n/N) With BW >4000g ALSPAC14 06224313% (1787/14082) TIHS10 62831310% (1080/10628) JPS ( Perinatal Study)92 408166266% (5839/91917) CPP (Collaborative Perinatal Project) 58 000501112% (6413/55760) DNBC?15158? MoBa108 48710633? TOTAL 283 585528134 (8.6%) 15 119/175098

21. Next steps in analysis Analyse BW as continuous and categorical variable Add more covariates to analysis Stratify analysis by maternal pre-pregnancy BMI and weight Stratify by weight gain in pregnancy Use more sensitive indicators of fetal growth

22. Methods for incorporating fetal growth characteristics in analysis appropriateness of fetal growth measured as: Z-score of birth weight for gestation, proportion of optimal birth weight,

23. Dreams Add more cohorts Especially first year of life Eventually add cohorts with biosamples to broaden biologic and genetic hypotheses

24. Gabriella Tikellis Working group members Ora Paltiel JPS; Manolis Kogevinas, CREAL, Gabriella Tikellis MCRI, Martine Vrijheid CREAL; Martha Linet NCI, Terry Dwyer MCRI, Jorn Olson Statens Serum Institut and others All participating cohorts Mothers and babies

25. Thanks for listening