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Can the gap in Aboriginal outcomes be explained by DOHaD

Part of: DOHaD in Indigenous Populations

Published online by Cambridge University Press:  06 February 2019

E. C. McEwen ,
T. J. Boulton  and
R. Smith
E. C. McEwen
Affiliation:
School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia Mothers and Babies Research Center, Priority Center in Reproduction, Hunter Medical Research Institute, University of Newcastle, Newcastle, NSW, Australia
T. J. Boulton
Affiliation:
School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
R. Smith
Affiliation:
School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia Mothers and Babies Research Center, Priority Center in Reproduction, Hunter Medical Research Institute, University of Newcastle, Newcastle, NSW, Australia
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Abstract

In Australia, there are two distinct populations, each with vastly disparate health outcomes: Aboriginal and Torres Strait Islander People and non-Aboriginal Australians. Aboriginal Australians have significantly higher rates of health and socioeconomic disadvantage, and Aboriginal babies are also more likely to be born low birth weight or growth restricted. The Developmental Origins of Health and Disease (DOHaD) hypothesis advocates that a sub-optimal intrauterine environment, often manifested as diminished foetal growth, during critical periods of foetal development has the potential to alter the risk of non-communicable disease in the offspring. A better understanding of the role of the intrauterine environment and subsequent developmental programming, in response to both transgenerational and immediate stimuli, in Aboriginal Australians remains a relatively unexplored field and may provide insights into the prevailing health disparities between Aboriginal and non-Aboriginal children. This narrative review explores the role of DOHaD in explaining the ongoing disadvantage experienced by Aboriginal People in today’s society through a detailed discussion of the literature on the association between foetal growth, as a proxy for the quality of the intrauterine environment, and outcomes in the offspring including perinatal health, early life development and childhood education. The literature largely supports this hypothesis and this review therefore has potential implications for policy makers not only in Australia but also in other countries that have minority and Indigenous populations who suffer disproportionate disadvantage such as the United States, Canada and New Zealand.

Keywords

AboriginalAEDCbirth weightDOHaD, educationdevelopmentepigeneticsfoetal growthIndigenousNAPLANperinatal mortalitypregnancy
Type
Review
Information
Journal of Developmental Origins of Health and Disease , Volume 10 , Special Issue 1: Themed Issue: Canada / Indigenous Populations , February 2019 , pp. 5 - 16
Copyright
© Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2019. 

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References

1. Malaspinas, AS, Westaway, MC, Muller, C, et al. A genomic history of Aboriginal Australia. Nature. 2016; 538, 207–214.Google Scholar
2. Clarkson, C, Jacobs, Z, Marwick, B, et al. Human occupation of northern Australia by 65,000 years ago. Nature. 2017; 547, 306–310.Google Scholar
3. Aboriginal Children, Health and History: Beyond Social Determinants. (ed. Boulton J), 2016; Routledge: NY.Google Scholar
4. Australian Bureau of Statistics. Estimates and Projections, Aboriginal and Torres Strait Islander Australians, 2001 to 2026, 2014. Australian Bureau of Statistics (ABS): Canberra; (cat. no. 3238.0).Google Scholar
5. SCRGSP. Overcoming Indigenous Disadvantage: Key Indicators. 2014. Productivity Commission: Canberra.Google Scholar
6. Australian Bureau of Statistics. Estimates of Aboriginal and Torres Strait Islander Australians, June 2011, 2013. Australian Bureau of Statistics (ABS): Canberra; (cat. no. 3238).Google Scholar
7. Australian Bureau of Statistics. Life Tables for Aboriginal and Torres Strait Islander Australians, 2010–2012, 2013. Australian Bureau of Statistics (ABS): Canberra; (cat. no. 3302.0.55.003).Google Scholar
8. Zhao, Y, You, J, Wright, J, Guthridge, SL, Lee, AH. Health inequity in the Northern Territory, Australia. Int J Equity Health. 2013; 12, 79.Google Scholar
9. Anderson, I, Robson, B, Connolly, M, et al. Indigenous and tribal peoples’ health (The Lancet-Lowitja Institute Global Collaboration): a population study. Lancet. 2016; 388, 131–157.Google Scholar
10. Australian Bureau of Statistics. Labour Force Characteristics of Aboriginal and Torres Strait Islander Australians, Estimates from the Labour Force Survey, 2011. Australian Bureau of Statistics (ABS): Canberra; (cat. no 6287).Google Scholar
11. Australian Bureau of Statistics. Prisoners in Australia, 2015, 2014. Australian Bureau of Statistics (ABS): Canberra; (cat. no. 4517).Google Scholar
12. Australian Bureau of Statistics. Recorded Crime – Victims, Australia, 2014, 2015. Australian Bureau of Statistics (ABS): Canberra; (cat. no. 4510).Google Scholar
13. Panaretto, K, Lee, H, Mitchell, M, et al. Risk factors for preterm, low birth weight and small for gestational age birth in urban Aboriginal and Torres Strait Islander women in Townsville. Aust N Z J Public Health. 2006; 30, 163–170.Google Scholar
14. Hilder, L, Zhichao, Z, Parker, M, Jahan, S, Chambers, GM. Australia’s mothers and babies 2012. Perinatal statistics series no 30. 2014. AIHW: Canberra.Google Scholar
15. McEwen, EC, Guthridge, SL, He, VY, McKenzie, JW, Boulton, TJ, Smith, R. What birthweight percentile is associated with optimal perinatal mortality and childhood education outcomes? Am J Obstet Gynecol. 2018; 218, S712–S724.Google Scholar
16. Shah, PS, Zao, J, Al-Wassia, H, Shah, V. Pregnancy and neonatal outcomes of aboriginal women: a systematic review and meta-analysis. Women’s Health Issues. 2011; 21, 28–39.Google Scholar
17. Rudd K. Prime Minister Kevin Rudd, MP – Apology to Australia’s Indigenous peoples [speech transcript]; 2008 Canberra: Department of Parliamentary Services [Available from: http://www.australia.gov.au/about-australia/our-country/our-people/apology-to-australias-indigenous-peoples.Google Scholar
18. NAPLAN. Achievement in Reading, Persuasive Writing, Language Conventions and Numeracy: National Report for 2017, 2017. ACARA: Sydney.Google Scholar
19. Australian Institute of Health and Welfare. A picture of Australia’s children. cat. no. PHE 58. 2005. AIHW: Canberra.Google Scholar
20. Janus, M, Duku, E. The school entry gap: socioeconomic, family, and health factors associated with children’s school readiness to learn. Early Educ Dev. 2007; 18, 375–403.Google Scholar
21. Sum, A, Khatiwada, I, McLaughlin, J, Palma, S. The Consequences of Dropping Out of High School. 2009.Google Scholar
22. Gluckman, PD, Hanson, MA, Buklijas, T. A conceptual framework for the developmental origins of health and disease. J Dev Orig Health Dis. 2010; 1, 6–18.Google Scholar
23. Wadhwa, PD, Buss, C, Entringer, S, Swanson, JM. Developmental origins of health and disease: brief history of the approach and current focus on epigenetic mechanisms. Semin Reprod Med. 2009; 27, 358–368.Google Scholar
24. Hales, CN, Barker, DJ. Type 2 (non-insulin-dependent) diabetes mellitus: the thrifty phenotype hypothesis. Diabetologia. 1992; 35, 595–601.Google Scholar
25. Francis, JH, Permezel, M, Davey, MA. Perinatal mortality by birthweight centile. Aust N Z J Obstet Gynecol. 2014; 54, 354–359.Google Scholar
26. Vasak, B, Koenen, SV, Koster, MP, et al. Human fetal growth is constrained below optimal for perinatal survival. Ultrasound Obstet Gynecol. 2015; 45, 162–167.Google Scholar
27. Vashevnik, S, Walker, S, Permezel, M. Stillbirths and neonatal deaths in appropriate, small and large birthweight for gestational age fetuses. Aust N Z J Obstet Gynaecol. 2007; 47, 302–306.Google Scholar
28. Steer, P. The management of large and small for gestational age fetuses. Semin Perinatol. 2004; 28, 59–66.Google Scholar
29. Dobbins, TA, Sullivan, EA, Roberts, CL, Simpson, JM. Australian national birthweight percentiles by sex and gestational age, 1998-2007. Med J Aust. 2012; 197, 291–294.Google Scholar
30. Royal College of Obstetricians and Gynaecologists. Small for Gestational Age Fetus: Investigation and Management. Greentop Guideline no. 31. 2013. RCOG: London.Google Scholar
31. Raznahan, A, Greenstein, D, Lee, NR, Clasen, LS, Giedd, JN. Prenatal growth in humans and postnatal brain maturation into late adolescence. Proc Natl Acad Sci USA. 2012; 109, 11366–11371.Google Scholar
32. Matte, TD, Bresnahan, M, Begg, MD, Susser, E. Influence of variation in birth weight within normal range and within sibships on IQ at age 7 years: cohort study. BMJ. 2001; 323, 310–314.Google Scholar
33. Roberts, CL, Lancaster, PA. Australian national birthweight percentiles by gestational age. Med J Aust. 1999; 170, 114–118.Google Scholar
34. Coory, M. An investigation into the disparity between Australian Aboriginal and Caucasian perinatal mortality rates. Ann Epidemiol. 1995; 5, 393–399.Google Scholar
35. Jasienska, G. Low birth weight of contemporary African Americans: an intergenerational effect of slavery? Am J Hum Biol. 2009; 21, 16–24.Google Scholar
36. Mohsin, M, Wong, F, Bauman, A, Bai, J. Maternal and neonatal factors influencing premature birth and low birth weight in Australia. J Biosoc Sci. 2003; 35, 161–174.Google Scholar
37. Kramer, MS, Ananth, CV, Platt, RW, Joseph, KS. US Black vs White disparities in foetal growth: physiological or pathological? Int J Epidemiol. 2006; 35, 1187–1195.Google Scholar
38. Currie, J, Moretti, E. Biology as destiny? Short- and long-run determinants of intergenerational transmission of birth weight. J Labor Econ. 2007; 25, 231–263.Google Scholar
39. Millennium Development Goals Report 215; 2015. United Nations: New York.Google Scholar
40. Closing the Gap: Prime Minister’s Report 2017. 2017 Australian Government Department of the Prime Minister and Cabinet: Canberra.Google Scholar
41. Ibiebele, I, Coory, M, Boyle, FM, Humphrey, M, Vlack, S, Flenady, V. Stillbirth rates among Indigenous and non-Indigenous women in Queensland, Australia: is the gap closing? BJOG. 2015; 122, 1476–1483.Google Scholar
42. Mohsin, M, Bauman, AE, Jalaludin, B. The influence of antenatal and maternal factors on stillbirths and neonatal deaths in New South Wales, Australia. J Biosoc Sci. 2006; 38, 643–657.Google Scholar
43. Kramer, MS. Determinants of low birth weight: methodological assessment and meta-analysis. Bull World Health Organ. 1987; 65, 663–737.Google Scholar
44. Kliewer, EV, Stanley, FJ. Stillbirths, neonatal and post-neonatal mortality by race, birthweight and gestational age. J Paediatr Child Health. 1993; 29, 43–50.Google Scholar
45. Groom, KM, Poppe, KK, North, RA, McCowan, LME. Small-for-gestational-age infants classified by customized or population birthweight centiles: impact of gestational age at delivery. Am J Obstet Gynecol. 2007; 197, 239.e1–.e5.Google Scholar
46. Moraitis, AA, Wood, AM, Fleming, M, Smith, GC. Birth weight percentile and the risk of term perinatal death. Obstet Gynecol. 2014; 124(2 Pt 1), 274–283.Google Scholar
47. Morales-Roselló, J, Khalil, A, Morlando, M, Papageorghiou, A, Bhide, A, Thilaganathan, B. Changes in fetal Doppler indices as a marker of failure to reach growth potential at term. Ultrasound Obstet Gynecol. 2014; 43, 303–310.Google Scholar
48. Ruan, S, Abdel-Latif, ME, Bajuk, B, et al. The associations between ethnicity and outcomes of infants in neonatal intensive care units. Arch Dis Child Fetal Neonatal Ed. 2011; 97, 133–138.Google Scholar
49. Alexander, GR, Tompkins, ME, Altekruse, JM, Hornung, CA. Racial differences in the relation of birth weight and gestational age to neonatal mortality. Public Health Rep. 1985; 100, 539–547.Google Scholar
50. Binkin, NJ, Williams, RL, Hogue, CJ, Chen, PM. Reducing black neonatal mortality. Will improvement in birth weight be enough? JAMA. 1985; 253, 372–375.Google Scholar
51. Thomson, M. Heavy birthweight in Native Indians of British Columbia. Can J Pub Health. 1990; 81, 443–446.Google Scholar
52. Maiti, K, Sultana, Z, Aitken, RJ, et al. Evidence that fetal death is associated with placental aging. Am J Obstet Gynecol. 2017; 217, 441.e1–14.Google Scholar
53. Janus, M, Offord, D. Reporting on readiness to learn in Canada. ISUMA Can J Policy Res. 2000; 1, 71–75.Google Scholar
54. Janus, M, Offord, DR. Development and psychometric properties of the Early Development Instrument (EDI): a measure of children’s school readiness. Can J Behav Sci. 2007; 39, 1–22.Google Scholar
55. Australian Early Development Census: 2012 Summary Report. 2013 Department of Education: Canberra.Google Scholar
56. Brinkman, S, Gregory, T, Harris, J, Hart, B, Blackmore, S, Janus, M. Associations between the early development instrument at age 5, and reading and numeracy skills at ages 8, 10 and 12: a prospective linked data study. Child Indic Res. 2013; 6, 695–708.Google Scholar
57. Cordova-Palomera, A, Fatjo-Vilas, M, Falcon, C, et al. Birth weight and adult iq, but not anxious-depressive psychopathology, are associated with cortical surface area: a study in twins. PLoS One. 2015; 10, e0129616.Google Scholar
58. Walhovd, KB, Fjell, AM, Brown, TT, et al. Long-term influence of normal variation in neonatal characteristics on human brain development. Proc Natl Acad Sci USA. 2012; 109, 20089–20094.Google Scholar
59. Matthews, SG. Early programming of the hypothalamo–pituitary–adrenal axis. Trends Endocrinol Metab. 2002; 13, 373–380.Google Scholar
60. Phillips, DI. Programming of the stress response: a fundamental mechanism underlying the long-term effects of the fetal environment? J Intern Med. 2007; 261, 453–460.Google Scholar
61. Simonetta, G, Rourke, AK, Owens, JA, Robinson, JS, McMillen, IC. Impact of placental restriction on the development of the sympathoadrenal system. Pediatr Res. 1997; 42, 805–811.Google Scholar
62. Austin, PC, Brunner, LJ. Inflation of the type I error rate when a continuous confounding variable is categorized in logistic regression analyses. Stat Med. 2004; 23, 1159–1178.Google Scholar
63. Hernandez-Andrade, E, Cortes-Camberos, AJ, Diaz, NF, et al. Altered levels of brain neurotransmitter from new born rabbits with intrauterine restriction. Neurosci Lett. 2015; 584, 60–65.Google Scholar
64. Radlowski, EC, Conrad, MS, Lezmi, S, et al. A neonatal piglet model for investigating brain and cognitive development in small for gestational age human infants. PLoS One. 2014; 9, e91951.Google Scholar
65. Duncan, JR, Cock, ML, Loeliger, M, Louey, S, Harding, R, Rees, SM. Effects of exposure to chronic placental insufficiency on the postnatal brain and retina in sheep. J Neuropathol Exp Neurol. 2004; 63, 1131–1143.Google Scholar
66. Mallard, C, Loeliger, M, Copolov, D, Rees, S. Reduced number of neurons in the hippocampus and the cerebellum in the postnatal guinea-pig following intrauterine growth-restriction. Neuroscience. 2000; 100, 327–333.Google Scholar
67. Kelly, YJ, Nazroo, JY, McMunn, A, Boreham, R, Marmot, M. Birthweight and behavioural problems in children: a modifiable effect? Int J Epidemiol. 2001; 30, 88–94.Google Scholar
68. Costello, EJ, Worthman, C, Erkanli, A, Angold, A. Prediction from low birth weight to female adolescent depression: a test of competing hypotheses. Arch Gen Psychiatry. 2007; 64, 338–344.Google Scholar
69. Grunau, RE, Whitfield, MF, Fay, TB. Psychosocial and academic characteristics of extremely low birth weight (< or=800 g) adolescents who are free of major impairment compared with term-born control subjects. Pediatrics. 2004; 114, e725–e732.Google Scholar
70. Liu, X, Sun, Z, Neiderhiser, JM, Uchiyama, M, Okawa, M. Low birth weight, developmental milestones, and behavioral problems in Chinese children and adolescents. Psychiatry Res. 2001; 101, 115–129.Google Scholar
71. Heinonen, K, Raikkonen, K, Pesonen, AK, et al. Behavioural symptoms of attention deficit/hyperactivity disorder in preterm and term children born small and appropriate for gestational age: a longitudinal study. BMC Pediatr. 2010; 10, 91.Google Scholar
72. Guthridge, S, Li, L, Silburn, S, Li, SQ, McKenzie, J, Lynch, J. Early influences on developmental outcomes among children, at age 5, in Australia’s Northern Territory. Early Child Res Q.Google Scholar
73. Khambalia, AZ, Algert, CS, Bowen, JR, Collie, RJ, Roberts, CL. Long‐term outcomes for large for gestational age infants born at term. J Paediatr Child Health. 2017; 53, 876–881.Google Scholar
74. Hanly, M, Falster, K, Chambers, G, et al. Gestational age and child development at age five in a population-based cohort of Australian Aboriginal and Non-Aboriginal children. Paediatr Perinat Epidemiol. 2018; 32, 114–125.Google Scholar
75. Sommerfelt, K, Andersson, HW, Sonnander, K, et al. Behavior in term, small for gestational age preschoolers. Early Hum Dev. 2001; 65, 107–121.Google Scholar
76. Malacova, E, Li, J, Blair, E, Leonard, H, de Klerk, N, Stanley, F. Association of birth outcomes and maternal, school, and neighborhood characteristics with subsequent numeracy achievement. Am J Epidemiol. 2008; 168, 21–29.Google Scholar
77. Hanushek, EA, Woessmann, L. Knowledge capital, growth, and the East Asian miracle. Science. 2016; 351, 344–345.Google Scholar
78. Guthridge, S, Li, L, Silburn, S, Li, SQ, McKenzie, J, Lynch, J. Impact of perinatal health and socio-demographic factors on school education outcomes: a population study of Indigenous and non-Indigenous children in the Northern Territory. J Paediatr Child Health. 2015; 51, 778–786.Google Scholar
79. Pearce, MS, Mann, KD, Singh, G, Sayers, SM. Birth weight and cognitive function in early adulthood: the Australian Aboriginal birth cohort study. J Dev Orig Health Dis. 2014; 5, 240–247.Google Scholar
80. Malacova, E, Li, J, Blair, E, Mattes, E, de Klerk, N, Stanley, F. Neighbourhood socioeconomic status and maternal factors at birth as moderators of the association between birth characteristics and school attainment: a population study of children attending government schools in Western Australia. J Epidemiol Community Health. 2009; 63, 842–849.Google Scholar
81. Low, JA, Galbraith, RS, Muir, D, Killen, H, Pater, B, Karchmar, J. Intrauterine growth retardation: a study of long-term morbidity. Am J Obstet Gynecol. 1982; 142(6 Pt 1), 670–677.Google Scholar
82. Westwood, M, Kramer, MS, Munz, D, Lovett, JM, Watters, GV. Growth and development of full-term nonasphyxiated small-for-gestational-age newborns: follow-up through adolescence. Pediatrics. 1983; 71, 376–382.Google Scholar
83. Boomsma, DI, van Baal, GC. Genetic influences on childhood IQ in 5‐ and 7‐year‐old Dutch twins. Dev Neuropsychol. 1998; 14, 115–126.Google Scholar
84. Boomsma, DI, van Beijsterveldt, CE, Rietveld, MJ, Bartels, M, van Baal, GC. Genetics mediate relation of birth weight to childhood IQ. BMJ. 2001; 323, 1426–1427.Google Scholar
85. Keltikangas-Jarvinen, L, Elovainio, M, Kivimaki, M, Raitakari, OT, Viikari, JS, Lehtimaki, T. Dopamine receptor D2 gene Taq1A (C32806T) polymorphism modifies the relationship between birth weight and educational attainment in adulthood: 21-year follow-up of the Cardiovascular Risk in Young Finns study. Pediatrics. 2007; 120, 756–761.Google Scholar
86. Newcombe, R, Milne, BJ, Caspi, A, Poulton, R, Moffitt, TE. Birthweight predicts IQ: fact or artefact? Twin Res Hum Genet. 2007; 10, 581–586.Google Scholar
87. Deary, IJ, Spinath, FM, Bates, TC. Genetics of intelligence. Eur J Hum Genet. 2006; 14, 690–700.Google Scholar
88. Petersen, I, Jensen, VM, McGue, M, Bingley, P, Christensen, K. No evidence of genetic mediation in the association between birthweight and academic performance in 2,413 Danish adolescent twin pairs. Twin Res Hum Genet. 2009; 12, 564–572.Google Scholar
89. Eriksen, W, Sundet, JM, Tambs, K. Birth weight standardized to gestational age and intelligence in young adulthood: a register-based birth cohort study of male siblings. Am J Epidemiol. 2010; 172, 530–536.Google Scholar
90. Strohmaier, J, van Dongen, J, Willemsen, G, et al. Low birth weight in MZ twins discordant for birth weight is associated with shorter telomere length and lower IQ, but not anxiety/depression in later life. Twin Res Hum Genet. 2015; 18, 198–209.Google Scholar
91. Delisle, H. Programming of chronic disease by impaired fetal nutrition: evidence and implications for policy and intervention strategies. 2002. WHO: Switzerland.Google Scholar
92. Australian Institute of Health and Welfare. SCSEEC successful school attendance strategies evidence-based project: summary report. 2014. AIHW: Canberra.Google Scholar
93. Chaudhari, S, Otiv, M, Khairnar, B, Pandit, A, Hoge, M, Sayyad, M. Pune low birth weight study - birth to adulthood - cognitive development. Indian Pediatr. 2013; 50, 853–857.Google Scholar
94. Lin, MJ, Liu, JT, Chou, SY. As low birth weight babies grow, can well-educated parents buffer this adverse factor? A research note. Demography. 2007; 44, 335–343.Google Scholar
95. Okbay, A, Beauchamp, JP, Fontana, MA, et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature. 2016; 533, 539–542.Google Scholar
96. Horikoshi, M, Beaumont, RN, Day, FR, et al. Genome-wide associations for birth weight and correlations with adult disease. Nature. 2016; 538, 248–252.Google Scholar