Commentary: The child is the mother of the woman: Intergenerational associations in maternal anthropometry

Susan MB Morton

School of Population Health, University of Auckland, Auckland, New Zealand. E-mail: s.morton{at}auckland.ac.nz

The child is the father of the man

[William Wordsworth (1770–1850)]

Wordsworth probably never envisaged how prophetic this simple, albeit non-gender specific, statement might be in terms of succinctly summarizing the relationships that exist in anthropometric measures and reproductive outcomes across generations. The simplicity of the statement though hides the complexity of the intergenerational associations and highlights the age-old problem, put more gender specifically, of which comes first—‘the child of the mother or the mother of the child’. Whatever the starting point or measure used for determining associations between one generation and the next, inevitably that measure will itself be the result of the cumulative biological and social influences from previous generations.

There is a growing body of literature describing the intergenerational continuities in measures of size at birth, suggesting that a mother's intrauterine environment and her early development directly influence her own reproductive outcomes. This relationship was suggested over sixty years ago when a study by Kermack et al.1 postulated that the health of adults was largely determined by their health as children, and that the health of infants was in turn dependent on the health of their mothers. Many studies followed, notably those by Baird and his colleagues, which considered the perinatal outcomes of infants born in Aberdeen, largely between 1948 and 1972 in relation to the childhood social environments of their mothers.2–7 Their collective findings are illustrated by a comment from Baird in his 1949 article where he states that:

Efficient child-bearing is influenced by many factors, but none so much as the mother herself. The mother is the product of heredity and environment, and therefore so far as possible the whole woman should be studied ... to discover what psychological, social and physical influences affect reproductive performance and how they act.2

Thus, the idea that reproductive success is influenced by the social environment in childhood and lifecourse growth of a mother rather than her attained maternal adult characteristics alone is not new in epidemiology, however, appropriate intergenerational data to investigate influences on growth and reproduction over a lifecourse, with quality biological and social information across several generations, have been limited until recently.8–10

It has been common, in the absence of such lifecourse and intergenerational data, for maternal adult characteristics, such as her achieved adult height or pre-pregnancy weight, to be used as proxy measures for her lifecourse development (although often not explicitly) as their effects on reproduction in particular are elucidated. In terms of understanding the predictors of reproductive success and offspring size at birth these summary measures of a mother's lifecourse development are extremely useful and relevant.11 However, when these largely cross-sectional anthropometric measures, usually measured contemporaneously to the pregnancy, are assumed to be the point at which modifications might be made to improve foetal development and infant health, the earlier wisdom of the importance of early maternal life influences on her reproductive potential is lost. Similarly when interventions to improve adult health are based on associations between measures of size at birth and adult health, as demonstrated in the foetal origins of adult disease hypothesis, these tend to overlook the fact that size at birth itself is an outcome deserving of attention in its own right. It is the end result of a complex interaction of biological and social processes not only within pregnancy but over the lifecourse of the mother and potentially her mother in turn.

Despite the emerging availability of datasets with sufficient information across generations to explore these lifecourse and intergenerational associations, the analytical challenge remains to consider fully the interplay between the lifecourse biological and social measures over time. Very often a false dichotomy is created between what a biological variable is and what a social variable is when in reality most variables are a result of a complex interaction of the two and measurement of each at only one time point may be insufficient to capture their lifecourse influence.12

Just as the biological and social environments are difficult to separate across a lifecourse so too are the distinct influences of different periods in a woman's development that have been shown to influence her offspring size at birth. These periods are not independent and any measurements such as birthweight or adult height represent ‘snap-shots’ of an entire lifecourse development. Whilst the measurements made at each point are themselves distinct, they represent slices of a continuum of growth and development between intrauterine life and adult reproductive life. A problem in attempting to unravel the effects of these different time periods is that cross-sectional measurements made during a woman's lifecourse are often highly correlated, making interpretation complex.

Hence there are many problems in considering intergenerational associations in anthropometry and reproductive capacity, including the availability of suitable data, unravelling the influences of biological and social variables and dealing with highly correlated measures over time. As stated in a recent editorial on taking a lifecourse approach to adult disease by Kuh and Ben-Shlomo ‘The lifecourse approach is paradoxical in that it is intuitively obvious ... but empirically complex’.13

In two related articles by Emanuel et al. in this issue of the IJE the authors attempt to tease apart the complex relationships that exist in size at birth and maternal anthropometry across generations and further to disentangle the social from the biological effects. In the first article the authors compare the relative importance of maternal socioeconomic status and maternal growth measures for infant birthweight in four ethnic groups14 and in the second they consider how growth and socioeconomic status relate to maternal growth within an intergenerational context, rather than a cross-sectional one.15 These are important issues in terms of addressing the potential timing and nature of interventions to improve growth in an attempt to improve health status since measures of growth throughout the lifecourse have been, in the past as well and more recently, related to proximal and distal health outcomes. However, there are two concerns raised by the approach taken in these articles: first is the dataset that is used to address these questions ‘up to the task’, and second is the methodology that has been applied appropriate to disentangle the biological from the social effects.

Whilst the dataset used by Emanuel et al. contains some improvements on earlier attempts to consider these questions they also have some important limitations. To the authors credit their dataset considers birth weight over the normal population range as opposed to only examining associations in subgroups of infants defined to be at the greatest clinical risk because of poor intrauterine growth. However data are lacking on gestational age at delivery, which is increasingly important as a determinant of absolute size at birth as more infants survive premature delivery. In addition there is a high proportion of missing data in each of the four ethnic groups studied and the overall explanation for providing analyses broken down by ethnicity, while potentially important, is scant. Perhaps of greater concern in these two articles though is the lack of what might be termed ‘hard measures’ of maternal socioeconomic status; proxy measures—including maternal age and parity—are used in both articles. These particular variables reflect a complex mix of social and biological influences rather than social status alone and they may be considered as having more biological than social significance.

With respect to methodology, use of partial correlation coefficients to determine the degree of variance explained by each particular biological and social variable is an interesting approach to disentangling the biological from the social effects. However, variables found to be the strongest predictors are expected to be those that are measured most accurately rather than those that necessarily have the greatest impact.16 In this dataset the anthropometric measures (termed biological by the authors) are probably much more accurately represented than social status is, being largely reliant on proxy measures. It is perhaps not surprising therefore for both articles to argue that it is maternal lifetime growth that is of greatest importance in determining reproductive outcomes in future generations. However, this is a somewhat circular argument, as the authors themselves state in their discussion, it is highly likely for the differential maternal growth to be the result of differential earlier social environments.

The authors comment further that the intergenerational influence of how people grow needs to be further elucidated, however, it is worth noting that in these articles the authors have been unable to consider growth per se, which suggests a consideration of change over time. Rather they have used measures of absolute size at two distinct points in a lifecourse—at birth and at the time of application for a driver's license for the mothers and the grandmothers. Using these measures does highlight both size at birth and attained adult size as important predictors of the next generation's growth (in utero and up to adulthood) but given the paucity of information on intermediate measures of size or growth trajectories, it is not possible to determine when growth between these two temporally distinct points might be of greatest importance in future generations and hence when and if interventions might be applied.

As stated by the authors, important questions remain to be answered regarding the determinants of growth across a lifecourse. Most importantly the biological and sociological mechanisms that underlie the lifecourse and intergenerational associations in anthropometry remain elusive, as does the quantification of the genetic vs the environmental influences. Nevertheless a lifecourse and intergenerational approach to lifecourse growth challenges our ideas about the origins of reproductive health as much as it does the origins of adult health.

While cross-sectional anthropometric measures are convenient measurements by which to determine associations with later health status (including reproductive outcomes), they remain proxy markers for development up to that point, which in terms of birthweight and adult size are markers of the lifecourse development of both a mother and her mother before her. And so in the gender adapted words of Wordsworth, truly ‘the child is the mother of the woman’.


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 References
 
1 Kermack WO, McKendrick AG, McKinlay PL. Death rates in Great Britain and Sweden. Some general regularities and their significance. Lancet 1934;226:698–703 (Reprinted Int J Epidemiol 2001;30: 678–83).[CrossRef]

2 Baird D. Social factors in obstetrics. Lancet 1949;1:1079–83.[CrossRef]

3 Baird D. Preventive medicine in Obstetrics. N Engl J Med 1952;246:561–68.[ISI][Medline]

4 Baird D. The epidemiology of low birth weight: changes in incidence in Aberdeen, 1948–72. J Biosoc Sci 1974;6:323–41.[ISI][Medline]

5 Baird D. Epidemiologic patterns over time. In: Reed D, Stanley FJ (eds). The Epidemiology of Prematurity. Baltimore: Urban & Schwarzenberg, 1977, pp. 5–15.

6 Illsley R. Social class selection and class differences in relation to stillbirths and infant deaths. Br Med J 1955;2:1520–24.[ISI]

7 Illsley R. Early prediction of perinatal risk. Proc R Soc Med 1966;59:181–84.[ISI][Medline]

8 Barker DJP, Osmond C, Golding J, Kuh D, Wadsworth MEJ. Growth in utero, blood pressure in childhood and adult life, and mortality from cardiovascular disease. Br Med J 1989;298:564–67.[ISI][Medline]

9 Power C. A review of child health in the 1958 cohort: national child development study. Paediatr Perinat Epidemiol 1992;6:91–110.

10 Golding J, Pembrey M, Jones R. ALSPAC—the Avon Longitudinal Study of Parents and Children. Paediatr Perinat Epidemiol 2001;15:74–87.[CrossRef][ISI][Medline]

11 Kramer MS. Determinants of low birth weight: methodological assessment and meta-analysis. Bull World Health Organ 1987;65:663–737.[ISI][Medline]

12 Morton SMB. Lifecourse determinants of offspring size at birth: an intergenerational study of Aberdeen women (PhD Thesis). University of London, 2002.

13 Ben-Shlomo Y, Kuh D. A life course approach to chronic disease epidemiology: conceptual models, empirical challenges and interdisciplinary perspectives. Int J Epidemiol 2002;31:285–93.[Free Full Text]

14 Emanuel I, Kimpo C, Moceri V. The association of maternal growth and socioeconomic measures with infant birth weight in four ethnic groups. Int J Epidemiol 2004;33:1236–42.[Abstract/Free Full Text]

15 Emanuel I, Kimpo C, Moceri V. The association of grandmaternal and maternal factors with maternal adult stature. Int J Epidemiol2004;33:1243–48[Abstract/Free Full Text]

16 De Stavola BL, Nitsch D, dos Santos Silva I et al. Statistical issues in life course epidemiology. Am J Epidemiol 2004 (in press).





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