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Birth Weight and Childhood Cancer and Leukemia

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. Background- Big babies and leukemia.

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Birth Weight and Childhood Cancer and Leukemia

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

  2. Background- Big babies and leukemia

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

  4. High Birth weight (categorical) and childhood leukemia

  5. Birth weight per kg and childhood leukemia: International Journal of CancerVolume 124, Issue 11, pages 2658-2670, 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

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

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

  8. 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

  9. 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

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

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

  12. 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.

  13. 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.

  14. Specific objectives • 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 • 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.

  15. Specific objectives cont’d • 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.

  16. 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

  17. Participating cohorts MoBa DNBC ALSPAC CPP JPS TIHS

  18. Table 1: Participating cohort sample size and number of cancer and ALL cases.

  19. 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

  20. 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,

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

  22. 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

  23. Thanks for listening

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