Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-28T05:50:53.308Z Has data issue: false hasContentIssue false
  • English
  • Français

Grandparental morbidity and mortality patterns are associated with infant birth weight in the Lifeways cross-generation cohort study 2001–2010

Published online by Cambridge University Press:  05 July 2012

A. Shrivastava ,
C. Murrin ,
J. O'Brien ,
K. Viljoen ,
P. Heavey ,
T. Grant  and
C. C. Kelleher
A. Shrivastava
Affiliation:
Lifeways Cross-Generation Cohort Study Steering Group, Health Research Board Centre for Health and Diet Research, School of Public Health, Physiotherapy and Population Science, University College Dublin, Belfield, Dublin, Republic of Ireland
C. Murrin
Affiliation:
Lifeways Cross-Generation Cohort Study Steering Group, Health Research Board Centre for Health and Diet Research, School of Public Health, Physiotherapy and Population Science, University College Dublin, Belfield, Dublin, Republic of Ireland
J. O'Brien
Affiliation:
Lifeways Cross-Generation Cohort Study Steering Group, Health Research Board Centre for Health and Diet Research, School of Public Health, Physiotherapy and Population Science, University College Dublin, Belfield, Dublin, Republic of Ireland
K. Viljoen
Affiliation:
Lifeways Cross-Generation Cohort Study Steering Group, Health Research Board Centre for Health and Diet Research, School of Public Health, Physiotherapy and Population Science, University College Dublin, Belfield, Dublin, Republic of Ireland
P. Heavey
Affiliation:
Lifeways Cross-Generation Cohort Study Steering Group, Health Research Board Centre for Health and Diet Research, School of Public Health, Physiotherapy and Population Science, University College Dublin, Belfield, Dublin, Republic of Ireland
T. Grant
Affiliation:
Lifeways Cross-Generation Cohort Study Steering Group, Health Research Board Centre for Health and Diet Research, School of Public Health, Physiotherapy and Population Science, University College Dublin, Belfield, Dublin, Republic of Ireland
C. C. Kelleher*
Affiliation:
Lifeways Cross-Generation Cohort Study Steering Group, Health Research Board Centre for Health and Diet Research, School of Public Health, Physiotherapy and Population Science, University College Dublin, Belfield, Dublin, Republic of Ireland
*
*Address for correspondence: Professor C. C. Kelleher, Chair of Public Health Medicine, Dean of Public Health and Head, School of Public Health, Physiotherapy and Population Science, University College Dublin, Woodview House, Belfield, Dublin 4, Republic of Ireland. (Email cecily.kelleher@ucd.ie)
Get access Rights & Permissions [Opens in a new window]

Abstract

The association of infants’ birth weight with maternal cardiovascular morbidity (CVD) and mortality substantiates the foetal origins hypothesis. Few studies to date have investigated grandparent–infant risk association. We prospectively examined this relationship in the Lifeways three-generation familial cohort, contrasting lineage and gender differences to understand mechanisms of intergenerational risk transmission. In 2001, a cohort of 1082 families was established at antenatal stage. A total of 539 families (n = 539 infants) had both a participating grandparent (n = 1054) and information on infants’ gestational age. At baseline, grandparents provided their diagnosed CVD status and 79% also underwent a cardiovascular risk factors assessment. In 2005, general practitioners provided an update for 61% grandparents. In 2010, a search of civil register confirmed 77 grandparental deaths in 539 families. Grandchildren's birth weight and grandparental cardiovascular risk factors associations were examined with linear regressions. Grandparental CVD associations were analysed using ANCOVA. Cox proportional hazard ratios (HR) were calculated for all-cause mortality associations. Models were adjusted for infants’, mothers’ and grandparents’ demographic, anthropometric and socio-behavioural characteristics, as appropriate. The paternal grandfathers’ (PGF) systolic blood pressure (mmHg) [β (95% CI) = 6.6 (0.8 – 12.5); P = 0.03] and paternal grandmothers’ serum triglycerides (mmol/l) [β (95% CI) = 78.8 (7.0 – 150.7); P = 0.03] were linearly predictive of infants’ birth weight, which was not observed for maternal grandparents. Mean birth weight for infants of maternal grandmothers with diabetes {−272.7 [(−499.7) − (−45.6)] g; P = 0.02} or stroke {−292.1 [(−544.5) − (−39.6)] g; P = 0.02} was lower than those without diabetes or stroke, a pattern not observed for paternal grandparents. Whereas PGFs’ mortality was significantly associated with infants’ high birth weight (⩾4000 g) [HR (95% CI) = 4.9 (1.2 – 19.9); P = 0.03], maternal grandparents’ mortality showed a converse pattern with infants’ low birth weight (<2500 g) [HR (95% CI) = 1.7 (0.4 – 8.2); P = 0.7], although not statistically significant. These findings suggest that intergenerational transmission of risk differs in maternal and paternal lines.

Keywords

birth weightcardiovascularintergenerationalmortalitysex specific
Type
Original Article
Information
Journal of Developmental Origins of Health and Disease , Volume 3 , Issue 6 , December 2012 , pp. 458 - 468
Copyright
Copyright © Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2012 

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

1.Osmond, C, Barker, DJ. Fetal, infant, and childhood growth are predictors of coronary heart disease, diabetes, and hypertension in adult men and women. Environ Health Perspect. 2000; 108 (Suppl 3), 545–553.Google Scholar
2.Whincup, PH, Kaye, SJ, Owen, CG, et al. Birth weight and risk of type 2 diabetes. JAMA. 2008; 300, 2886–2897.Google Scholar
3.Hanson, M, Godfrey, KM, Lillycrop, KA, Burdge, GC, Gluckman, PD. Developmental plasticity and developmental origins of non-communicable disease: theoretical considerations and epigenetic mechanisms. Prog Biophys Mol Biol. 2011; 106, 272–280.Google Scholar
4.Hattersley, AT, Tooke, JE. The fetal insulin hypothesis: an alternative explanation of the association of low birthweight with diabetes and vascular disease. Lancet. 1999; 353, 1789–1792.Google Scholar
5.Bergvall, N, Cnattingius, S. Familial (shared environmental and genetic) factors and the foetal origins of cardiovascular diseases and type 2 diabetes: a review of the literature. J Intern Med. 2008; 264, 205–223.Google Scholar
6.Friedlander, Y, Paltiel, O, Manor, O, et al. Birthweight of offspring and mortality of parents: the Jerusalem perinatal study cohort. Ann Epidemiol. 2007; 17, 914–922.Google Scholar
7.Hypponen, E, Smith, GD, Power, C. Parental diabetes and birth weight of offspring: intergenerational cohort study. BMJ. 2003; 326, 19–20.Google Scholar
8.Pell, JP, Smith, GC, Dominiczak, A, et al. Family history of premature death from ischaemic heart disease is associated with an increased risk of delivering a low birth weight baby. Heart. 2003; 89, 1249–1250.Google Scholar
9.Pell, JP, Smith, GCS, Wash, D. Pregnancy complications and subsequent maternal cerebrovascular events: a retrospective cohort study of 119,668 births. Am J of Epidemiol. 2004; 159, 336–342.Google Scholar
10.Smith, GCS, Pell, JP, Walsh, D. Pregnancy complications and maternal risk of ischaemic heart disease: a retrospective cohort study of 129,290 births. Lancet. 2001; 357, 2002–2006.Google Scholar
11.Andersen, AM, Osler, M. Birth dimensions, parental mortality, and mortality in early adult age: a cohort study of Danish men born in 1953. Int J Epidemiol. 2004; 33, 92–99.CrossRefGoogle ScholarPubMed
12.Friedlander, Y, Manor, O, Paltiel, O, et al. Birth weight of offspring, maternal pre-pregnancy characteristics, and mortality of mothers: the Jerusalem perinatal study cohort. Ann Epidemiol. 2009; 19, 112–117.Google Scholar
13.Wannamethee, SG, Lawlor, DA, Whincup, PH, et al. Birthweight of offspring and paternal insulin resistance and paternal diabetes in late adulthood: cross sectional survey. Diabetologia. 2004; 47, 12–18.CrossRefGoogle ScholarPubMed
14.Davey Smith, G, Hart, C, Ferrell, C, et al. Birth weight of offspring and mortality in the Renfrew and Paisley study: prospective observational study. Br Med J. 1997; 315, 1189–1193.CrossRefGoogle ScholarPubMed
15.Davey Smith, G, Hypponen, E, Power, C, Lawlor, DA. Offspring birth weight and parental mortality: prospective observational study and meta-analysis. Am J Epidemiol. 2007; 166, 160–169.Google Scholar
16.Davey Smith, G, Sterne, JA, Tynelius, P, Rasmussen, F. Birth characteristics of offspring and parental diabetes: evidence for the fetal insulin hypothesis. J Epidemiol Community Health. 2004; 58, 126–128.Google Scholar
17.Hennessy, E, Alberman, E. Intergenerational influences affecting birth outcome. I. Birthweight for gestational age in the children of the 1958 British Birth Cohort. Paediatr Perinat Epidemiol. 1998; 12(S1), 45–60.Google Scholar
18.Horta, BL, Gigante, DP, Osmond, C, Barros, FC, Victora, CG. Intergenerational effect of weight gain in childhood on offspring birthweight. Int J Epidemiol. 2009; 38, 724–732.Google Scholar
19.Brion, M-JA, Ness, AR, Rogers, I, et al. Maternal macronutrient and energy intakes in pregnancy and offspring intake at 10 y: exploring parental comparisons and prenatal effects. Am J Clin Nutr. 2010; 91, 748–756.Google Scholar
20.Al Mamun, A, O'Callaghan, FV, Alati, R, et al. Does maternal smoking during pregnancy predict the smoking patterns of young adult offspring? A birth cohort study. Tob Control. 2006; 15, 452–457.Google Scholar
21.McConnell, JML. A mitochondrial component of developmental programming. In Developmental Origins of Health and Disease (eds. Gluckman PD, Hanson MA), 2006 pp. 75–81. Cambridge University Press, Cambridge.Google Scholar
22.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.Google Scholar
23.Drake, AJ, Liu, L. Intergenerational transmission of programmed effects: public health consequences. Trends Endocrinol Metab. 2010; 21, 206–213.Google Scholar
24.Gluckman, PD, Hanson, MA, Beedle, AS. Non-genomic transgenerational inheritance of disease risk. Bioessays. 2007; 29, 145–154.Google Scholar
25.Kuzawa, CW. Fetal origins of developmental plasticity: are fetal cues reliable predictors of future nutritional environments? Am J Hum Biol. 2005; 17, 5–21.Google Scholar
26.Kuzawa, CW. Developmental origins of life history: growth, productivity, and reproduction. Am J Hum Biol. 2007; 19, 654–661.Google Scholar
27.Smith, GCS, Wood, AM, White, IR, Pell, JP, Hattie, J. Birth weight and the risk of cardiovascular disease in the maternal grandparents. Am J Epidemiol. 2010; 171, 736–744.Google Scholar
28.Manor, O, Koupil, I. Birth weight of infants and mortality in their parents and grandparents: the Uppsala Birth Cohort Study. Int J Epidemiol. 2010; 39, 1264–1276.Google Scholar
29.McCarron, P, Davey Smith, G, Hattersley, AT. Type 2 diabetes in grandparents and birth weight in offspring and grandchildren in the ALSPAC study. J Epidemiol Community Health. 2004; 58, 517–522.Google Scholar
30.Naess, O, Hoff, DA, Lie, RT, et al. Differential associations between grandparental and parental cardiovascular disease and offspring birthweight. A multigenerational family based study of the cohort of Norway (CONOR) [abstract]. Longit Life Course Stud. 2010; 1 (Suppl 3), 262.Google Scholar
31.O'Mahony, D, Fallon, UB, Hannon, F, et al. The Lifeways Cross-generation Study: design, recruitment and data management considerations. Ir Med J. 2007; 100 (Suppl 8), 3–6.Google Scholar
32.Pembrey, ME, Bygren, LO, Kaati, G, et al. Sex-specific, male-line transgenerational responses in humans. Eur J Hum Genet. 2006; 14, 159–166.Google Scholar
33.Kelleher, CC, Fallon, UB, Fitzsimon, N, et al. The risk factor profile of grandparents. Ir Med J. 2007; 100 (Suppl 8), 15–19.Google Scholar
34.Niedhammer, I, O'Mahony, D, Daly, S, Morrison, JJ, Kelleher, CC. Occupational predictors of pregnancy outcomes in Irish working women in the Lifeways cohort. BJOG. 2009; 116, 943–952.Google Scholar
35.Niedhammer, I, Murrin, C, O'Mahony, D, et al. Explanations for social inequalities in preterm delivery in the prospective Lifeways cohort in the Republic of Ireland. Eur J Public Health. 2011 [Epub ahead of print]. doi: 10.1093/eurpub/ckr089.Google Scholar
36.Murrin, C, Segonds-Pichon, A, Fallon, UB, et al. Self-reported pre-pregnancy maternal body mass index and infant birth-weight. Ir Med J. 2007; 100 (Suppl 8), 20–23.Google Scholar
37.Susser, E, Susser, M. Familial aggregation studies. A note on their epidemiologic properties. Am J Epidemiol. 1989; 129, 23–30.CrossRefGoogle ScholarPubMed
38.Howell, DC. The treatment of missing data. In The SAGE Handbook of Social Science Methodology (eds. Outhwaite W, Turner SP), 2007; pp. 208–224. SAGE Publications Ltd, London.Google Scholar
39.Barker, DJP. Developmental origins of chronic disease: The Richard Doll lecture. Public Health. 2012 [Epub ahead of print]. doi: 10.1016/j.puhe.2011.11.014.CrossRefGoogle Scholar
40.Moore, T, Haig, D. Genomic imprinting in mammalian development: a parental tug-of-war. Trends Genet. 1991; 7, 45–49.Google Scholar
41.Ong, KK, Dunger, DB. Birth weight, infant growth and insulin resistance. Eur J Endocrinol. 2004; 151(Suppl 3), U131–U139.Google Scholar
42.Murrin, CM, Kelly, GE, Tremblay, RE, Kelleher, CC. Body mass index and height over three generations: evidence from the Lifeways cross-generational cohort study. BMC Public Health. 2012; 12, 81. [Epub ahead of print], doi 10.1186/1471-2458-1112-1181.Google Scholar
43.Pilote, L, Dasgupta, K, Guru, V, et al. A comprehensive view of sex-specific issues related to cardiovascular disease. CMAJ. 2007; 176, S1–S44.Google Scholar
44.Fox, M, Sear, R, Beise, J, et al. Grandma plays favourites: X-chromosome relatedness and sex-specific childhood mortality. Proc Biol Sci. 2010; 277, 567–573.Google Scholar
45.Rothman, KJ. No adjustments are needed for multiple comparisons. Epidemiology. 1990, 43–46.Google Scholar
46.Savitz, DA, Olshan, AF. Multiple comparisons and related issues in the interpretation of epidemiologic data. Am J of Epidemiol. 1995; 142, 904–908.Google Scholar
47.Hill, AB. The environment and disease: association or causation? Proc R Soc Med. 1965; 58, 295–300.Google Scholar