Commentary: On the paradoxes of birthweight

Allen J Wilcox

Epidemiology Branch, National Institute of Environmental Health Sciences, PO Box 12233, Durham NC 27709, USA. E-mail: wilcox{at}niehs.nih.gov

Is there any epidemiological variable so much discussed and so little understood as birthweight? In the US, there has been a long-standing preoccupation with birthweight and infant health, while Europeans have led the way in studies of birthweight and the subsequent health of adults. In either case, the implied message is that a pregnant woman’s nutrition affects her baby’s weight at birth, and that birthweight in turn affects health. The irony, of course, is that a mother’s nutrition during pregnancy has little effect on birthweight—especially in countries where birthweight is most often studied.1

This is not to say that birthweight is static. Many conditions are linked to birthweight—a mother’s cigarette smoking, her height, parity, and ethnicity, to name a few. Such factors typically produce birthweight differences in the range of 100–200 g. In this issue of the International Journal of Epidemiology, Melve and Skjaerven remind us that one of the most powerful predictors of birthweight is the weight of the baby’s previous sibling.2 The authors demonstrate this by linking data from women’s first and second births. When the weights of first babies are categorized into their highest and lowest quartiles, second babies differ by 650 g. This is a huge difference (well over a standard deviation of the birthweight distribution). Still, it is not surprising that sibling weights would be highly correlated. There is no better way to hold constant the social, genetic, and physical determinants of birthweight than by keeping parentage constant.

To what degree is this sibling correlation explained by social determinants? Social factors must contribute something, although this may be hard to show. Melve and Skjaerven address this question to a limited extent, using mother’s education as a surrogate for social factors. Birthweight goes up by about 100 g with better education of the mother. In these data, stratifying by education has virtually no effect on the correlation of birthweight between siblings (Table 1).

The more interesting question is whether birthweight matters at all. Does it matter whether mean birthweight changes by 100 g, or even by 650 g? Many researchers would say yes, of course. Small babies are at high risk. Shifting the distribution so that more babies are in the higher-risk weights must be a bad thing. Mustn’t it?

The answer is ‘not necessarily’, and this is where things get interesting. Consider the Norwegian data. Assuming weight-specific mortality rates are constant, the downward shift of the birthweight distribution by 650 g should increase perinatal mortality by fourfold. But in fact the 650 g shift is accompanied by a mortality increase of only twofold (Table 2). How is this possible? How can such a large decrease in birthweight produce only half the expected increase in mortality?

It happens because weight-specific mortality rates are not constant. In the Norwegian data, the rates are dramatically different for the two groups—paradoxically, to the advantage of the lighter distribution of babies (Figure 2).

This paradox is an old story in perinatal epidemiology, one that has been discussed at length elsewhere.3 The contribution of Melve and Skjaerven is to show that these seemingly paradoxical differences in weight-specific rates are not explained by social class factors, as some have suggested.4

But the larger question is still this: does birthweight really matter? If a particular factor reduces birthweights, does it necessarily damage perinatal health? The simple answer is no. Altitude is a common example.5 The picture is slightly more complicated for the numerous factors that decrease mean birthweight and also increase perinatal mortality, but even under these conditions, the two effects can be read as independent.3

There of course is no evidence that birthweight itself is on the causal pathway between risk factors and perinatal mortality. Differences in mean weight generally reveal little about perinatal health. We should stop worrying about whether populations (for example ethnic groups) differ in mean birthweight, and ask instead whether these groups differ in perinatal mortality or morbidity. Birthweight is a distraction.

And while we are at it, it is reasonable to question whether birthweight is only incidental on the causal pathway to adult health. The links between birthweight and outcomes in the adult are worth attention,6 but we should not forget that a causal role for fetal growth is just one hypothesis.

Factors that reduce birthweight can increase perinatal mortality, and often do. Smoking is the classic example. But the two effects of smoking (a decrease in birthweight, an increase in mortality) are best understood as independent phenomena.5 This appears to be true for any variable that affects the distribution of birthweights.3 For those who still believe otherwise, Melve and Skjaerven’s data provide one more reason why it is unwise to depend on birthweight when assessing perinatal health.


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1 Rush D. Maternal nutrition and perinatal survival. J Health Popul Nutr 2001;19:S217–64.[Medline]

2 Melve KK, Skjaerven R. Birthweight and perinatal mortality: paradoxes, social class, and sibling dependencies. Int J Epidemiol 2003;32:625–32.[Abstract/Free Full Text]

3 Wilcox AJ. On the importance—and the unimportance—of birthweight. Int J Epidemiol 2001;30:1233–41.[Abstract/Free Full Text]

4 Carlson E, Hoem JM. Low-weight neonatal survival paradox in the Czech Republic. Am J Epidemiol 1999;149:447–53.[Abstract]

5 Wilcox AJ. Birthweight and perinatal mortality: the effect of maternal smoking. Am J Epidemiol 1993;137:1098–104.[Abstract]

6 Barker DJ. Fetal origins of coronary heart disease. BMJ 1995;311:171–74.[Free Full Text]