Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-19T03:50:18.608Z Has data issue: false hasContentIssue false
  • English
  • Français

Birthweight-for-gestational-age z-scores are associated with early childhood cardiometabolic health in the Peri/Postnatal Epigenetic Twin Study

Published online by Cambridge University Press:  23 August 2021

Deborah N. Ashtree Open the ORCID record for Deborah N. Ashtree [Opens in a new window] ,
Mihiri J. Silva ,
Cong Sun ,
Jeffrey M. Craig  and
Katrina J. Scurrah
Deborah N. Ashtree
Affiliation:
Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Parkville, Australia Twins Research Australia, Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Parkville, Australia
Mihiri J. Silva
Affiliation:
Inflammatory Origins, Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, Australia Melbourne Dental School, University of Melbourne, Parkville, Australia Melbourne Medical School, University of Melbourne, Royal Children’s Hospital, Parkville, Australia
Cong Sun
Affiliation:
Epigenetics, Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, Australia
Jeffrey M. Craig
Affiliation:
Epigenetics, Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, Australia IMPACT – the Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Faculty of Health, Deakin University, Waurn Ponds, Australia
Katrina J. Scurrah*
Affiliation:
Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Parkville, Australia Twins Research Australia, Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Parkville, Australia
*
Address for correspondence: Dr Katrina J. Scurrah, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria, Australia. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Birthweight has been consistently related to risk of cardiometabolic disorders in later life. Twins are at higher risk of low birthweight than singletons, so understanding the links between birthweight and cardiometabolic health may be particularly important for twins. However, evidence for the association of birthweight with childhood markers of cardiometabolic health in twins is currently lacking. Previous studies have often failed to appropriately adjust for gestational age or fully implement twin regression models. Therefore, we aimed to evaluate the association of birthweight-for-gestational-age z-scores with childhood cardiometabolic health in twins, using within-between regression models. The Peri/Postnatal Epigenetic Twins Study is a Melbourne-based prospective cohort study of 250 twin pairs. Birthweight was recorded at delivery, and childhood anthropometric measures were taken at 18-month and 6-year follow-up visits. Associations of birthweight with markers of cardiometabolic health were assessed at the individual, between- and within-pair level using linear regression with generalised estimating equations. Birthweight-for-gestational-age z-scores were associated with height, weight and BMI at 18 months and 6 years, but not with blood pressure (twins-as-individual SBP: β = 0.15, 95% CI: −0.81, 1.11; twins-as-individual DBP: β = 0.22, 95% CI: −0.34, 0.77). We found little evidence to indicate that the within-between models improved on the twins-as-individuals models. Birthweight was associated with childhood anthropometric measures, but not blood pressure, after appropriately adjusting for gestational age. These associations were consistent across the within-between and twins-as-individuals models. After adjusting for gestational age, results from the twins-as-individuals models are consistent with singleton studies, so these results can be applied to the general population.

Keywords

Birthweightadiposityblood pressurecardiometabolic healthtwins
Type
Original Article
Information
Journal of Developmental Origins of Health and Disease , Volume 13 , Issue 4 , August 2022 , pp. 514 - 522
Copyright
© The Author(s), 2021. Published by Cambridge University Press in association with International Society for Developmental Origins of Health and Disease

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

World Health Organization. Cardiovascular diseases (CVDs). https://www.who.int/en/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds).Google Scholar
Barker, DJ, Winter, PD, Osmond, C, Margetts, B, Simmonds, SJ. Weight in infancy and death from ischaemic heart disease. Lancet. 1989; 2, 577–580.CrossRefGoogle ScholarPubMed
Law, CM, Shiell, AW. Is blood pressure inversely related to birth weight? The strength of evidence from a systematic review of the literature. J Hypertens. 1996; 14, 935–941.CrossRefGoogle ScholarPubMed
Newsome, CA, Shiell, AW, Fall, CHD, et al. Is birth weight related to later glucose and insulin metabolism?—a systematic review. Diabetic Med. 2003; 20, 339–348.CrossRefGoogle ScholarPubMed
Yu, ZB, Han, SP, Zhu, GZ, et al. Birth weight and subsequent risk of obesity: a systematic review and meta-analysis. Obes Rev. 2011; 12, 525–542.CrossRefGoogle ScholarPubMed
Joshi, SM, Katre, PA, Kumaran, K, et al. Tracking of cardiovascular risk factors from childhood to young adulthood – the Pune Children’s study. Int J Cardiol. 2014; 175, 176–178.CrossRefGoogle ScholarPubMed
Yan, Y, Hou, D, Liang, Y, et al. Tracking body mass index from childhood to adulthood for subclinical cardiovascular diseases at adulthood. J Am Coll Cardiol. 2016; 67, 1006–1007.CrossRefGoogle ScholarPubMed
Bloetzer, C, Bovet, P, Suris, J-C, et al. Screening for cardiovascular disease risk factors beginning in childhood. Public Health Rev. 2015; 36, 9.CrossRefGoogle ScholarPubMed
Ashtree, DN, McGuinness, AJ, Plummer, M, et al. Developmental origins of cardiometabolic health outcomes in twins: a systematic review and meta-analysis. Nutr Metab Cardiovasc Dis. 2020; 30, 1609–1621.CrossRefGoogle ScholarPubMed
Harrison, MS, Eckert, LO, Cutland, C, et al. Pathways to preterm birth: case definition and guidelines for data collection, analysis, and presentation of immunization safety data. Vaccine. 2016; 34, 6093–6101.CrossRefGoogle ScholarPubMed
Morley, R, Dwyer, T, Carlin, JB. Studies of twins: can they shed light on the fetal origins of adult disease hypothesis? Twin Res. 2003; 6, 520–525.CrossRefGoogle ScholarPubMed
Tudehope, D, Vento, M, Bhutta, Z, Pachi, P. Nutritional requirements and feeding recommendations for small for gestational age infants. J Pediatr. 2013; 162, S81–S89.CrossRefGoogle ScholarPubMed
Koullali, B, Oudijk, MA, Nijman, TAJ, Mol, BWJ, Pajkrt, E. Risk assessment and management to prevent preterm birth. Semin Fetal Neonatal Med. 2016; 21, 80–88.CrossRefGoogle ScholarPubMed
Lee, AC, Kozuki, N, Cousens, S, et al. Estimates of burden and consequences of infants born small for gestational age in low and middle income countries with INTERGROWTH-21st standard: analysis of CHERG datasets. BMJ. 2017; 358, J3677.Google Scholar
Katz, J. Lee, AC, Kozuki, N, et al. Mortality risk in preterm and small-for-gestational-age infants in low-income and middle-income countries: A pooled country analysis. Lancet. 2013; 382, 417–425.CrossRefGoogle ScholarPubMed
Li, Z, Umstad, MP, Hilder, L, Xu, F, Sullivan, EA. Australian national birthweight percentiles by sex and gestational age for twins, 2001–2010. BMC Pediatr. 2015; 15, 148.CrossRefGoogle ScholarPubMed
Cole, TJ, Freeman, JV, Preece, MA. British 1990 growth reference centiles for weight, height, body mass index and head circumference fitted by maximum penalized likelihood. Stat Med. 1998; 17, 407–429.3.0.CO;2-L>CrossRefGoogle ScholarPubMed
Vidmar, SI, Cole, TJ, Pan, H. Standardizing anthropometric measures in children and adolescents with functions for Egen: update. Stata J. 2013; 13, 366–378.CrossRefGoogle Scholar
Simes, RJ. An improved Bonferroni procedure for multiple tests of significance. Biometrika. 1986; 73, 751–754.CrossRefGoogle Scholar
Seaman, SR, White, IR. Review of inverse probability weighting for dealing with missing data. Stat Methods Med Res. 2013; 22, 278–295.CrossRefGoogle ScholarPubMed
Dwyer, T, Blizzard, L, Morley, R, Ponsonby, AL. Within pair association between birth weight and blood pressure at age 8 in twins from a cohort study. BMJ. 1999; 319, 1325.CrossRefGoogle ScholarPubMed
Oberg, S, Ge, D, Cnattingius, S, et al. Ethnic differences in the association of birth weight and blood pressure: the Georgia cardiovascular twin study. Am J Hypertens. 2007; 20, 1235–1241.CrossRefGoogle ScholarPubMed
Baird, J, Osmond, C, MacGregor, A, et al. Testing the fetal origins hypothesis in twins: the Birmingham twin study. Diabetologia. 2001; 44, 33–39.CrossRefGoogle ScholarPubMed
Loos, RJ, Fagard, R, Beunen, G, Derom, C, Vlietinck, R. Birth weight and blood pressure in young adults. Circulation. 2001; 104, 1633–1638.CrossRefGoogle ScholarPubMed
McNeill, G, Tuya, C, Campbell, DM, et al. Blood pressure in relation to birth weight in twins and singleton controls matched for gestational age. Am J Epidemiol. 2003; 58, 150–155.CrossRefGoogle Scholar
Jelenkovic, A, Yokoyama, Y, Sund, R, et al. Association between birthweight and later body mass index: an individual-based pooled analysis of 27 twin cohorts participating in the CODATwins project. Int J Epidemiol. 2017; 46, 1488–1498.CrossRefGoogle ScholarPubMed
Kwok, MK, Yeung, SLA, Leung, GM, Mary Schooling, C. Birth weight and adult cardiovascular risk factors using multiple birth status as an instrumental variable in the 1958 British Birth Cohort. Prev Med. 2016; 84, 69–75.CrossRefGoogle ScholarPubMed
Skidmore, PM, Cassidy, A, Swaminathan, R, et al. An obesogenic postnatal environment is more important than the fetal environment for the development of adult adiposity: a study of female twins. Am J Clin Nutr. 2009; 90, 401–406.CrossRefGoogle Scholar
Loos, RJ, Beunen, G, Fagard, R, Derom, C, Vlietinck, R. Birth weight and body composition in young adult men—a prospective twin study. Int J Obes Relat Metab Disord. 2001; 25, 1537–1545.CrossRefGoogle ScholarPubMed
Freedman, DS, Katzmarzyk, PT, Dietz, WH, Srinivasan, SR, Berenson, GS. Relation of body mass index and skinfold thicknesses to cardiovascular disease risk factors in children: the Bogalusa Heart Study. Am J Clin Nutr. 2009; 90, 210–216.CrossRefGoogle ScholarPubMed
de Hollander, EL, Bemelmans, WJE, de Groot, LCPGM. Associations between changes in anthropometric measures and mortality in old age: a role for mid-upper arm circumference? J Am Med Dir Assoc. 2013; 14, 187–193.CrossRefGoogle ScholarPubMed
Pomeroy, E, Stock, JT, Cole, TJ, O’Callaghan, M, Wells, JCK. Relationships between neonatal weight, limb lengths, skinfold thicknesses, body breadths and circumferences in an Australian cohort. PloS One. 2014; 9, e105108.CrossRefGoogle Scholar
van Wyk, L, Boers, KE, van Wassenaer-Leemhuis, AG, et al. Postnatal catch-up growth after suspected fetal growth restriction at term. Front Endocrinol. 2019; 10, 274.CrossRefGoogle ScholarPubMed
Perng, W, Hajj, H, Belfort, MB, et al. Birth size, early life weight gain, and Midchildhood cardiometabolic health. J Pediatr. 2016; 173, 122–130.CrossRefGoogle ScholarPubMed
Wu, D, Zhu, J, Wang, X, et al. Rapid BMI increases and persistent obesity in small-for-gestational-age infants. Front Pediatr. 2021; 9, 625853.CrossRefGoogle ScholarPubMed
Ranganathan, P, Pramesh, CS, Buyse, M. Common pitfalls in statistical analysis: the perils of multiple testing. Perspect Clin Res. 2016; 7, 106–107.CrossRefGoogle Scholar
Supplementary material: File

Ashtree et al. supplementary material

Ashtree et al. supplementary material

Download Ashtree et al. supplementary material(File)
File 44.7 KB