Skip to main content
Log in

Fetal Programming and the Risk of Noncommunicable Disease

  • Symposium on Chronic Noncommunicable Diseases and Children
  • Published:
The Indian Journal of Pediatrics Aims and scope Submit manuscript

Abstract

The “developmental origins of health and disease” (DOHaD) hypothesis proposes that environmental conditions during fetal and early post-natal development influence lifelong health and capacity through permanent effects on growth, structure and metabolism. This has been called ‘programming’. The hypothesis is supported by epidemiological evidence in humans linking newborn size, and infant growth and nutrition, to adult health outcomes, and by experiments in animals showing that maternal under- and over-nutrition and other interventions (e.g., glucocorticoid exposure) during pregnancy lead to abnormal metabolism and body composition in the adult offspring. Early life programming is now thought to be important in the etiology of obesity, type 2 diabetes, and cardiovascular disease, opening up the possibility that these common diseases could be prevented by achieving optimal fetal and infant development. This is likely to have additional benefits for infant survival and human capital (e.g., improved cognitive performance and physical work capacity). Fetal nutrition is influenced by the mother’s diet and body size and composition, but hard evidence that the nutrition of the human mother programmes chronic disease risk in her offspring is currently limited. Recent findings from follow-up of children born after randomised nutritional interventions in pregnancy are mixed, but show some evidence of beneficial effects on vascular function, lipid concentrations, glucose tolerance and insulin resistance. Work in experimental animals suggests that epigenetic phenomena, whereby gene expression is modified by DNA methylation, and which are sensitive to the nutritional environment in early life, may be one mechanism underlying programming.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

CHD:

Coronary Heart Disease

CVD:

Cardiovascular Disease

GDM:

Gestational Diabetes Mellitus

LMIC:

Low and Middle Income Countries

PMNS:

Pune Maternal Nutrition Study

References

  1. Barker DJP. Rise and fall of Western diseases. Nature. 1989;338:371–2.

    Article  PubMed  CAS  Google Scholar 

  2. Patel V, Chatterji S, Chisholm D, et al. Chronic diseases and injuries in India. Lancet. 2011;377:413–28.

    Article  PubMed  Google Scholar 

  3. International Diabetes Federation. Diabetes Atlas. 3rd ed. Belgium: Brussels; 2006.

    Google Scholar 

  4. Yusuf S, Hawken S, Ounpuu S, et al; INTERHEART Study Investigators. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the Interheart Study): a case control study. Lancet. 2004;364:937–52.

    Article  PubMed  Google Scholar 

  5. Forsdahl A. Are poor living conditions in childhood and adolescence an important risk factor for arteriosclerotic disease? Br J Prev Soc Med. 1977;31:91–5.

    PubMed  CAS  Google Scholar 

  6. Barker DJP, Osmond C. Infant mortality, childhood nutrition, and ischaemic heart disease in England and Wales. Lancet. 1986;i:1077–81.

    Article  Google Scholar 

  7. Osmond C, Barker DJP, Winter PD, Fall CHD, Simmonds SJ. Early growth and death from cardiovascular disease in women. Br Med J. 1993;307:1519–24.

    Article  CAS  Google Scholar 

  8. Fall CHD. Fetal and maternal nutrition. In: Stanner S, ed. Cardiovascular disease: diet, nutrition and emerging risk factors. British Nutrition Foundation Task Force. Oxford, UK: Blackwell Publishing; 2005.

    Google Scholar 

  9. Barker DJP. Mothers, babies and health in later life. London: Churchill Livingstone; 1998.

    Google Scholar 

  10. Lucas A. Programming by early nutrition in man. In: Bock GR, Whelan J, eds. Ciba Foundation Symposium 156-The childhood environment and adult disease. Chichester, UK: John Wiley & Sons, Ltd.; 1991. pp. 38–55.

    Google Scholar 

  11. Roseboom TJ, van der Meulen J, Ravelli ACJ, Osmond C, Barker DJP, Bleker OP. Effects of prenatal exposure to the Dutch famine on adult disease in later life: an overview. Mol Cell Endocrinol. 2001;185:93–8.

    Article  PubMed  CAS  Google Scholar 

  12. Freinkel N. Of pregnancy and progeny. Diabetes. 1980;29:1023–35.

    Article  PubMed  CAS  Google Scholar 

  13. Dabelea D, Hanson RL, Lindsay RS, et al. Intrauterine exposure to diabetes conveys risks for type 2 diabetes and obesity: a study of discordant sibships. Diabetes. 2000;49:2208–11.

    Article  PubMed  CAS  Google Scholar 

  14. Whincup PH, Kaye SJ, Owen CG, et al. Birthweight and risk of type 2 diabetes: a systematic review. JAMA. 2008;300:2886–97.

    Article  PubMed  CAS  Google Scholar 

  15. Huda SS, Brodie LE, Sattar N. Obesity in pregnancy: prevalence and metabolic consequences. Semin Fetal Neonatal Med. 2010;15:70–6.

    Article  PubMed  Google Scholar 

  16. Metzger BE, the HAPO Study Co-operative Research Group. Hyperglycaemia and adverse pregnancy outcome (HAPO); associations with neonatal anthropometrics. Diabetes. 2009;58:453–9.

    CAS  Google Scholar 

  17. Oken E. Maternal and child obesity: the causal link. Obstet Gyn Clin N Am. 2009;36:361–77.

    Article  Google Scholar 

  18. Gardner DS, Jackson AA, Langley-Evans SC. The effect of prenatal diet and glucocorticoids on growth and systolic blood pressure in the rat. Proc Nutr Soc. 1998;57:235–40.

    Article  PubMed  CAS  Google Scholar 

  19. Warner MJ, Ozanne SE. Mechanisms involved in the developmental programming of adult disease. Biochem J. 2010;427:333–47.

    Article  PubMed  CAS  Google Scholar 

  20. Vickers MH, Krechowec SO, Breier BH. Is later obesity programmed in utero? Curr Drug Targets. 2007;8:923–34.

    Article  PubMed  CAS  Google Scholar 

  21. Waterland RA, Garza C. Potential mechanisms of metabolic imprinting that lead to chronic disease. Am J Clin Nutr. 1999;69:179–97.

    PubMed  CAS  Google Scholar 

  22. Burdge GC, Hanson MA, Slater-Jefferies JL, Lillycrop KA. Epigenetic regulation of transcription: a mechanism for inducing variations in phenotype (fetal programming) by differences in nutrition during early life? Br J Nutr. 2007;97:1036–46.

    Article  PubMed  CAS  Google Scholar 

  23. Lillycrop KA, Phillips ES, Jackson AA, Hanson MA, Burdge GC. Dietary protein restriction of pregnant rats induces and folic acid supplementation prevents epigenetic modification of hepatic gene expression in the offspring. J Nutr. 2005;135:1382–6.

    PubMed  CAS  Google Scholar 

  24. Sinclair K, Allegrucci C, Singh R, Gardner D, Sebastian S, Bispham J. DNA methylation, insulin resistance, and blood pressure in offspring determined by maternal periconceptional B vitamin and methionine status. Proc Nat Acad Sci USA. 2007;104:19351–6.

    Article  PubMed  Google Scholar 

  25. Waterland RA, Jirtle RL. Transposable elements: targets for early nutritional effects on epigenetic gene regulation. Mol Cell Biol. 2003;23:5293–300.

    Article  PubMed  CAS  Google Scholar 

  26. Heijmans B, Tobi E, Stein A, et al. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proc Natl Acad Sci USA. 2008;105:17046–9.

    Article  PubMed  Google Scholar 

  27. Godfrey KM, Gluckman PD, Hanson MA. Developmental origins of metabolic disease: life course and intergenerational perspectives. Trends Endocrinol Metab. 2010;21:199–205.

    Article  PubMed  CAS  Google Scholar 

  28. Drake AJ, Walker BR. The intergenerational effects of fetal programming: non-genomic mechanisms for the inheritance of low birth weight and cardiovascular risk. J Endocrinol. 2004;180:1–16.

    Article  PubMed  CAS  Google Scholar 

  29. Bavdekar A, Yajnik CS, Fall CHD, et al. The insulin resistance syndrome (IRS) in eight-year-old Indian children: small at birth, big at 8 years or both? Diabetes. 1999;48:2422–9.

    Article  PubMed  CAS  Google Scholar 

  30. Krishnaveni GV, Veena SR, Wills AK, Hill JC, Karat SC, Fall CHD. Adiposity, insulin resistance and cardiovascular risk factors in 9–10 year old Indian children: relationships with birth size and postnatal growth. J Dev Orig Hlth Dis. 2010;1:403–11.

    Article  CAS  Google Scholar 

  31. Bhargava SK, Sachdev HPS, Fall CHD, et al. Relation of serial changes in childhood body mass index to impaired glucose tolerance in young adulthood. N Engl J Med. 2004;350:865–75.

    Article  PubMed  CAS  Google Scholar 

  32. Huffman MD, Prabhakaran D, Osmond C, et al. Incidence of cardiovascular risk factors in an Indian urban cohort: results from the New Delhi birth cohort. J Am Coll Cardiol. 2011;57:1765–74.

    Article  PubMed  Google Scholar 

  33. Raghupathy P, Antonisamy B, Geethanjali FS, et al. Glucose tolerance, insulin resistance and insulin secretion in young south Indian adults; relationships to parental size, neonatal size and childhood body mass index. Diabetes Res Clin Pract. 2010;87:283–92.

    Article  PubMed  CAS  Google Scholar 

  34. Krishnaveni GV, Veena SR, Hill JC, Kehoe S, Karat SC, Fall CHD. Intra-uterine exposure to maternal diabetes is associated with higher adiposity and insulin resistance and clustering of cardiovascular risk markers in Indian children. Diabetes Care. 2010;33:402–4.

    Article  PubMed  CAS  Google Scholar 

  35. Rao S, Yajnik CS, Kanade A, et al. Intake of micronutrient-rich foods in rural Indian mothers is associated with the size of their babies at birth; the Pune Maternal Nutrition Study. J Nutr. 2001;131:1217–24.

    PubMed  CAS  Google Scholar 

  36. Yajnik CS, Fall CHD, Coyaji KJ, et al. Neonatal anthropometry: the thin-fat Indian baby; the Pune Maternal Nutrition Study. Int J Obes. 2003;27:173–80.

    Article  CAS  Google Scholar 

  37. Modi N, Thomaa EL, Uthaya SN, Umranikar S, Bell JD, Yajnik CS. Whole body magnetic resonance imaging of healthy newborn infants demonstrates increased central adiposity in Asian Indians. Ped Res. 2009;65:584–7.

    Article  Google Scholar 

  38. Yajnik CS, Deshpande SS, Panchanadikar AV, et al. Maternal total homocysteine concentration and neonatal size in India. Asia Pacific J Clin Nutr. 2005;14:179–81.

    CAS  Google Scholar 

  39. Stein AD, Wang M, Ramirez-Zea M, et al. Exposure to a nutrition supplement intervention in early childhood and risk factors for cardiovascular disease in adulthood; evidence from Guatemala. Am J Epidemiol. 2006;164:1160–70.

    Article  PubMed  Google Scholar 

  40. Hawkesworth S, Walker CG, Sawo Y, et al. Nutritional supplementation during pregnancy and offspring cardiovascular risk in the Gambia. Am J Clin Nutr. 2011;94:1853S–60S.

    Article  PubMed  CAS  Google Scholar 

  41. Kinra S, Rameshwar Sarma KV, Ghafoorunissa, et al. Effect of integration of supplemental nutrition with public health programmes in pregnancy and early childhood on cardiovascular risk in rural Indian adolescents: long term follow-up of Hyderabad nutrition trial. BMJ. 2008;337:a605.

    Article  PubMed  Google Scholar 

  42. Vaidya A, Saville N, Shreshta BP, Costello AM, Manandhar DS, Osrin D. Effects of antenatal multiple micronutrient supplementation on children’s weight and size at 2 years of age in Nepal: follow-up of a double-blind randomised controlled trial. Lancet. 2008;371:492–9.

    Article  PubMed  CAS  Google Scholar 

  43. Stewart CP, Christian P, LeClerq SC, West KP, Khatry SK. Antenatal supplementation with folic acid + iron + zinc improves linear growth and reduces peripheral adiposity in school-age children in rural Nepal. Am J Clin Nutr. 2009;90:132–40.

    Article  PubMed  CAS  Google Scholar 

  44. Iannotti LL, Zavaleta N, Leon Z, Shankar AH, Caulfield LE. Maternal zinc supplementation and growth in Peruvian infants. Am J Clin Nutr. 2008;88:154–60.

    PubMed  CAS  Google Scholar 

  45. Watkins AJ, Fleming TP. Blastocyst environment and its influence on offspring cardiovascular health; the heart of the matter. J Anat. 2009;215:52–9.

    Article  PubMed  Google Scholar 

  46. Oken E, Levitan EB, Gillman MW. Maternal smoking during pregnancy and child overweight: systematic review and meta-analysis. Int J Obes. 2008;32:201–10.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The author would like to thank the Indian scientists with whom she work, including those at the KEM Hospital, Pune; Holdsworth Memorial Hospital, Mysore; New Delhi Birth Cohort Study, New Delhi; Christian Medical College, Vellore; and Centre for the Study of Social Change, Mumbai; and also the Indian society for research into the developmental origins of health and disease, Sneha-India. The research described is funded by the Indian Council of Medical Research; Medical Research Council, UK; Wellcome Trust, UK; Parthenon Trust, Switzerland; and ICICI Foundation, India. The manuscript was produced with the assistance of Jane Pearce.

Conflict of Interest

None.

Role of Funding Source

The work was funded by the Medical Research Council, UK, the Wellcome Trust, UK and the Parthenon Trust (Switzerland). The funders played no role in the data analysis and interpretation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Caroline H. D. Fall.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fall, C.H.D. Fetal Programming and the Risk of Noncommunicable Disease. Indian J Pediatr 80 (Suppl 1), 13–20 (2013). https://doi.org/10.1007/s12098-012-0834-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12098-012-0834-5

Keywords

Navigation