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Being Macrosomic at Birth is an Independent Predictor of Overweight in Children: Results from the IDEFICS Study

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Abstract

Fetal macrosomia is a risk factor for the development of obesity late in childhood. We retrospectively evaluated the relationship between maternal conditions associated with fetal macrosomia and actual overweight/obesity in the European cohort of children participating in the IDEFICS study. Anthropometric variables, blood pressure and plasma lipids and glucose were measured. Socio-demographic data, medical history and perinatal factors, familiar and gestational history, maternal and/or gestational diabetes were assessed by a questionnaire. Variables of interest were reported for 10,468 children (M/F = 5,294/5,174; age 6.0 ± 1.8 years, M ± SD). The sample was divided in four groups according to child birth weight (BW) and maternal diabetes: (1) adequate for gestational age offspring (BW between the 10th and 90th percentiles for gestational age) of mothers without diabetes (AGA-ND); (2) adequate for gestational age offspring of mothers with diabetes (AGA-D); (3) macrosomic offspring (BW > 90th percentile for gestational age) of mothers without diabetes (Macro-ND); (4) macrosomic offspring of mothers with diabetes (Macro-D). Children macrosomic at birth showed significantly higher actual values of body mass index, waist circumference, and sum of skinfold thickness. In both boys and girls, Macro-ND was an independent determinant of overweight/obesity, after the adjustment for confounders [Boys: OR = 1.7 95 % CI (1.3;2.2); Girls: OR = 1.6 95 % CI (1.3;2.0)], while Macro-D showed a significant association only in girls [OR = 2.6 95 % CI (1.1;6.4)]. Fetal macrosomia, also in the absence of maternal/gestational diabetes, is independently associated with the development of overweight/obesity during childhood. Improving the understanding of fetal programming will contribute to the early prevention of childhood overweight/obesity.

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References

  1. National Library of Medicine—Medical Subject Headings, http://www.nlm.nih.gov/cgi/mesh/2012/MB_cgi.

  2. Ornoy, A. (2011). Prenatal origin of obesity and their complications: Gestational diabetes, maternal overweight and the paradoxical effects of fetal growth restriction and macrosomia. Reproductive Toxicology, 32, 205–212.

    Article  CAS  PubMed  Google Scholar 

  3. Henriksen, T. (2008). The macrosomic foetus: A challenge in current obstetrics. Acta Obstetricia et Gynecologica Scandinavica, 87, 134–145.

    Article  PubMed  Google Scholar 

  4. Langer, O. (2000). Fetal macrosomia: Etiologic factors. Clinical Obstetrics and Gynecology, 43, 283–297.

    Article  CAS  PubMed  Google Scholar 

  5. Bérard, J., Dufour, P., Vinatier, D., Subtil, D., Vanderstichèle, S., Monnier, J. C., et al. (1998). Fetal macrosomia: Risk factors and outcome. A study of the outcome concerning 100 cases > 4500 g. European Journal of Obstetrics, Gynecology, and Reproductive Biology, 77, 51–59.

    Article  PubMed  Google Scholar 

  6. Olmos, P. R., Borzone, G. R., Olmos, R. I., Valencia, C. N., Bravo, F. A., Hodgson, M. I., et al. (2012). Gestational diabetes and pre-pregnancy overweight: Possible factors involved in newborn macrosomia. Journal Obstetrics Gynaecology Research, 38, 208–214.

    Article  Google Scholar 

  7. Van Wooten, W., & Urner, E. (2002). Macrosomia in neonates of mothers with gestational diabetes is associated with body mass index and previous gestational diabetes. Journal American Diabetic Association, 102, 241–243.

    Article  Google Scholar 

  8. Schaefer-Graf, U. M., Kjos, S. L., Kilavuz, O., Plagemann, A., Brauer, M., Dudenhausen, J. W., et al. (2003). Determinants of fetal growth at different periods of pregnancies complicated by gestational diabetes mellitus or impaired glucose tolerance. Diabetes Care, 26, 193–198.

    Article  PubMed  Google Scholar 

  9. Jolly, M. C., Sebire, N. J., Harris, J. P., Regan, L., & Robinson, S. (2003). Risk factors for macrosomia and its clinical consequences: A study of 350,311 pregnancies. European Journal of Obstetrics, Gynecology, and Reproductive Biology, 111, 9–14.

    Article  PubMed  Google Scholar 

  10. Huang, R. C., Burke, V., Newnham, J. P., Stanley, F. J., Kendall, G. E., Landau, L. I., et al. (2007). Perinatal and childhood origins of cardiovascular disease. International Journal of Obesity (London), 31, 236–244.

    Article  CAS  Google Scholar 

  11. Wang, Y., & Lobstein, T. (2006). Worldwide trends in childhood overweight and obesity. International Journal of Pediatric Obesity, 1, 11–25.

    Article  PubMed  Google Scholar 

  12. Guo, S. S., Roche, A. F., Chumlea, W. C., Gardner, J. D., & Siervogel, R. M. (1994). The predictive value of childhood body mass index values for overweight at age 35 years. American Journal of Clinical Nutrition, 59, 810–819.

    CAS  PubMed  Google Scholar 

  13. Ehrenberg, H. M., Mercer, B. M., & Catalano, P. M. (2004). The influence of obesity and diabetes on the prevalence of macrosomia. American Journal of Obstetrics and Gynecology, 191, 964–968.

    Article  CAS  PubMed  Google Scholar 

  14. Gillman, M. W., Rifas-Shiman, S., Berkey, C. S., Field, A. E., & Colditz, G. A. (2003). Maternal gestational diabetes, birth weight, and adolescent obesity. Pediatrics, 111, e221–e226.

    Article  PubMed  Google Scholar 

  15. Ahrens, W., Bammann, K., Siani, A., Buchecker, K., De Henauw, S., Iacoviello, L., et al. (2011). IDEFICS Consortium. The IDEFICS cohort: Design, characteristics and participation in the baseline survey. International Journal of Obesity (London), 35, S3–S15.

    Article  Google Scholar 

  16. Stomfai, S., Ahrens, W., Bammann, K., Kovács, E., Mårild, S., Michels, N., et al. (2011). IDEFICS Consortium. Intra- and inter-observer reliability in anthropometric measurements in children. International Journal of Obesity (London), 35, S45–S51.

    Article  Google Scholar 

  17. Cole, T. J., Bellizzi, M. C., Flegal, K. M., & Dietz, W. H. (2000). Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ, 320, 1–6.

    Article  Google Scholar 

  18. Cole, T. J., Flegal, K. M., Nicholls, D., & Jackson, A. A. (2007). Body mass index cut offs to define thinness in children and adolescents: International survey. BMJ, 335, 194.

    Article  PubMed  Google Scholar 

  19. Peplies, J., Fraterman, A., Scott, R., Russo, P., & Bammann, K. (2010). Quality management for the collection of biological samples in multicentre studies. European Journal of Epidemiology, 25, 607–617.

    Article  CAS  PubMed  Google Scholar 

  20. Peplies, J., Günther, K., Bammann, K., Fraterman, A., Russo, P., Veidebaum, T., et al. (2011). IDEFICS Consortium. Influence of sample collection and preanalytical sample processing on the analyses of biological markers in the European multicentre study IDEFICS. International Journal of Obesity (London), 35, S104–S112.

    Article  CAS  Google Scholar 

  21. Shephard, M. D., Mazzachi, B. C., & Shephard, A. K. (2007). Comparative performance of two point-of-care analysers for lipid testing. Clinical Laboratory, 53, 561–566.

    CAS  PubMed  Google Scholar 

  22. Friedewald, W. T., Levy, R. I., & Fredrickson, D. S. (1972). Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clinical Chemistry, 18, 499–502.

    CAS  PubMed  Google Scholar 

  23. Matthews, D. R., Hosker, J. P., Rudenski, A. S., Naylor, B. A., Treacher, D. F., & Turner, R. C. (1985). Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia, 28, 412–419.

    Article  CAS  PubMed  Google Scholar 

  24. International Standard Classification of Education (ISCED) UNESCO 1997. http://www.unesco.org/education/information/nfsunesco/doc/isced_1997.htm Accessed April 2010.

  25. Nesterenko, T. H., & Aly, H. (2009). Fetal and neonatal programming: Evidence and clinical implications. American Journal of Perinatology, 26, 191–198.

    Article  PubMed  Google Scholar 

  26. Huang, J. S., Lee, T. A., & Lu, M. C. (2007). Prenatal programming of childhood overweight and obesity. Maternal and Child Health Journal, 11, 461–473.

    Article  PubMed  Google Scholar 

  27. Schack-Nielsen, L., Michaelsen, K. F., Gamborg, M., Mortensen, E. L., & Sørensen, T. I. (2010). Gestational weight gain in relation to offspring body mass index and obesity from infancy through adulthood. International Journal of Obesity (London), 34, 67–74.

    Article  CAS  Google Scholar 

  28. HAPO Study Cooperative Research Group. (2009). Hyperglycemia and adverse pregnancy outcome (HAPO) study: Associations with neonatal anthropometrics. Diabetes, 58, 453–459.

    Article  Google Scholar 

  29. Phelan, S., Jankovitz, K., Hagobian, T., & Abrams, B. (2011). Reducing excessive gestational weight gain: Lessons from the weight control literature and avenues for future research. Womens Health (London England), 7, 641–661.

    Article  Google Scholar 

  30. Oken, E., & Gillman, M. W. (2003). Fetal origins of obesity. Obesity Research, 11, 496–506.

    Article  PubMed  Google Scholar 

  31. Murphy, M. J., Metcalf, B. S., Voss, L. D., Jeffery, A. N., Kirkby, J., & Mallam, K. M. (2004). EarlyBird Study (EarlyBird 6). Girls at five are intrinsically more insulin resistant than boys: The programming hypotheses revisited–the earlybird study. Pediatrics, 113, 82–86.

    Article  PubMed  Google Scholar 

  32. Zimmet, P., Alberti, K. G., Kaufmann, F., Tajima, N., Silink, M., Arslanian, S., et al. (2007). IDF consensus group. The metabolic syndrome in children and adolescents—an IDF consensus report. Pediatric Diabetes, 8, 299–306.

    Article  PubMed  Google Scholar 

  33. Goodman, E., Daniels, S. R., Meigs, J. B., & Dolan, L. M. (2007). Instability in the diagnosis of metabolic syndrome in adolescents. Circulation, 115, 2316–2322.

    Article  PubMed  Google Scholar 

  34. Plagemann, A., Harder, T., Kohlhoff, R., Rohde, W., & Dörner, G. (1997). Overweight and obesity in infants of mothers with long-term insulin-dependent diabetes or gestational diabetes. International Journal of Obesity and Related Metabolic Disorders, 21, 451–456.

    Article  CAS  PubMed  Google Scholar 

  35. Pettitt, D., Knowler, W., Bennett, P., Aleck, K., & Baird, H. (1987). Obesity in offspring of diabetic Pima Indian women despite normal birth weight. Diabetes Care, 10, 76–80.

    Article  CAS  PubMed  Google Scholar 

  36. Xita, N., & Tsatsoulis, A. (2010). Fetal origins of the metabolic syndrome. Annals of the New York Academy of Sciences, 1205, 148–155.

    Article  PubMed  Google Scholar 

  37. Yogev, Y., & Visser, G. H. A. (2009). Obesity, gestational diabetes and pregnancy outcome. Seminars in Fetal and Neonatal Medicine, 14, 77–84.

    Article  PubMed  Google Scholar 

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Acknowledgments

This study was conducted as part of the IDEFICS study (http://www.idefics.eu). We gratefully acknowledge the financial support of the European Community within the Sixth RTD Framework Programme Contract no. 016181 (FOOD) and the grant support from EU for the IDEFICS study. We are grateful for the support provided by school boards, headmasters and communities. We thank the IDEFICS children and their parents for participating in this extensive examination. The information in this document reflects the authors’ view and is provided as is.

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Epidemiology and Population Genetics, Institute of Food Sciences, National Research Council (CNR), Via Roma, 64, 83100, Avellino, Italy

    Sonia Sparano, Alfonso Siani & Paola Russo

  2. BIPS-Institute for Epidemiology and Prevention Research, Bremen, Germany

    Wolfgang Ahrens & Marc Suling

  3. Institute for Statistics, University of Bremen, Bremen, Germany

    Wolfgang Ahrens & Marc Suling

  4. Department of Public Health, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium

    Stefaan De Henauw

  5. Department of Paediatrics, Queen Silvia Children’s Hospital, University of Gothenburg, Gothenburg, Sweden

    Staffan Marild

  6. Department of Paediatrics, Medical Faculty, University of Pecs, Pecs, Hungary

    Denes Molnar

  7. Growth, Exercise, Nutrition and Development Research Group, University of Zaragoza, Zaragoza, Spain

    Luis A. Moreno

  8. Research and Education Institute of Child Health, Strovolos, Cyprus

    Michael Tornaritis

  9. National Institute for Health Development, Tallin, Estonia

    Toomas Veidebaum

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  1. Sonia Sparano
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Correspondence to Alfonso Siani.

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Sparano, S., Ahrens, W., De Henauw, S. et al. Being Macrosomic at Birth is an Independent Predictor of Overweight in Children: Results from the IDEFICS Study. Matern Child Health J 17, 1373–1381 (2013). https://doi.org/10.1007/s10995-012-1136-2

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  • DOI: https://doi.org/10.1007/s10995-012-1136-2

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