Results

The proportion of low birth weight fathers (2.6 %) was lower than the corresponding proportion for mothers (3.3 %), while there was no difference in the risk of low birth weight for sons and daughters (table 1). The difference in mean birth weight between fathers and mothers (152 g) was larger than the difference between male and female offspring (103 g). The variance in birth weight was larger for fathers compared with mothers and larger for sons than for daughters.

The mother-father correlation in birth weight is low (table 2). The mother-child correlations are larger than the father-child correlations (table 2). There is a slight tendency that parent-daughter correlations are larger than parent-son correlations. The gender standardised (z scores) father-child and mother-child correlations (0.130 and 0.226, respectively) were almost identical to the unadjusted coefficients presented in table 2.

Figure 2 shows the almost linear increase in offspring birth weight as paternal birth weight increases, within categories of maternal birth weight. The figure omits families where the paternal birth weight is below 2500 grams. It should be noted that the lines are almost parallel, indicating little or no interaction effects between parental values (that is, the effect of the paternal birth weight is roughly the same within each category of maternal birth weight).

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Figure 2

Mean offspring birth weight (g) for categories of paternal birth weight in selected strata of maternal birth weight. Families where the parental birth weight was below 2500 grams are omitted from the figure. Maternal and paternal birth weight is categorised into 250 g groups—that is, 2500=2500–2749; 2750=2750–2999; 3000=3000–3249, etc.

For all the data, the regression of a child's birth weight on the father's birth weight gives a coefficient of 0.137 (SE 0.004), and the regression of a child's birth weight on the mother's birth weight gives a coefficient of 0.252. When including both parents in the regression the coefficients are slightly lower (0.132 and 0.249), with no significant interaction between the two.

For fathers and mothers who themselves were born with a low birth weight (less than 2500 grams), their birth weight may not always be representative for their genetic potential. When we excluded these fathers and mothers, the above regression coefficients were slightly larger (separate estimates: 0.153 and 0.281; and simultaneous estimates 0.148 and 0.278). Exactly the same results emerged when we restricted to term born mothers and fathers.

The proportion of offspring with low birth weight was 4.0% (2702 of 67 795). If the mother was above 4000 g at birth herself, the risk of a low birth weight child was 2.2% (180 of 8212) compared with 9.3% (209 of 2247) if the mother was below 2500 g at birth (relative risk 4.2). If the father was above 4000 g (regardless of maternal birth weight), the risk of a low birth weight child was 3.4% (484 of 14 086) compared with 6.4% (112 of 1758) when the father was below 2500 grams (relative risk 1.9). Table 3 shows that the risk is 8.2 times higher when both parents had low birth weight compared with the situation where both parents were above 4000 grams. Within each category of maternal birth weight, the risk of low birth weight in offspring is reduced as the paternal birth weight increases. The table reflects the independent contribution of both parents birth weights to the risk of low birth of the child.

Assuming causality, the proportion of offspring with low birth weight would be reduced from 4.0 % (p) to 3.5 % (q) if parental values were shifted from the two lowest categories to the category with birth weights between 3000 and 3499 grams, using parameters estimated from logistic regression. Thus, the population attributable risk, (p-q)/p, in such an hypothetical situation is 0.125.

The equations derived from figure 1 are given in table 4. The spousal correlation was low meaning that ρe² must be low, so that the father-child correlation under model 1 will be almost entirely explained by genetic effects. The solution for model 1 is h² = 0.254 (95% CI: 0.239, 0.270), e² = 0.746 (0.730, 0.761), ρ = 0.027 (0.018, 0.037) and t_m = 0.133 (0.120, 0.146).

The parameters in model 2 can be uniquely identified using the condition t_f ² + t_m ² = 1. The estimated parameters are then e² = 0.244 (0.236, 0.253), ρ = 0.083 (0.053, 0.116), t_m ² = 0.791 (0.762, 0.821) and t_f ² = 0.209 (0.179, 0.238).

Discussion

The main finding is that paternal birth weight has an independent contribution to offspring birth weight, whether one looks at the whole birth weight distribution or one wants to predict low birth weight in children. The models presented in table 4 explore two possible channels that the parental influence may work through. Assuming no cultural transmission on the father's side (t_f=0), model 1 demonstrates that the correlations can be explained by a parental genetic effect, leading to an estimated heritability of birth weight of h²=0.25. On the other hand, model 2 does not include any genetic effects at all (h=0), assuming that both maternal and paternal influence is only through cultural transmission, as determined by t_m and t_f. The observed correlations are equally well explained by this somewhat unrealistic scenario. The merit of the model is the division of cultural transmission among the two parents when the generational effect is assumed to be non-genetic. The model predicts that t_f ² = 0.21, meaning that 21% of the cultural transmission derives from the paternal side, perhaps a rather high part of the total. The models are both saturated (fit perfectly), and consequently no comparison of goodness of fit is possible. Thus, both models provide possible explanations for the observed data, and it seems reasonable to believe that reality is somewhere in between the two extremes.

In evaluating these results, one should note the selection of subjects to the study population. The first generation consists necessarily of survivors who have given birth to children before the age of 32, while the offspring generation is unselected with respect to future survival and fertility. It is difficult to see what kind of bias this can bring to the correlational structure. Parental age is not known to have large effects on offspring birth weight. However, it seems that there may be a stronger selection to fertility for males than for females in this group of relatively young parents, based on the observation that only 2.6% of fathers were low birth weight. This observation could be explained by selection of tall men to early fatherhood.

It is relatively well established that maternal birth weight is a good predictor of offspring birth weight.3-6 There is less agreement on the interpretation of this observation. It has been argued that pregnancy can have harmful consequences on the later reproductive potential of a female fetus, if it is exposed to adverse environmental factors.11 This may be seen as a direct effect, which is not well represented in figure 1, but which would not be possible to distinguish from the cultural transmission on the maternal side in the present dataset. The finding of a substantial correlation between the father and child speaks against this mechanism as a major explanation of the association across generations.

We have not corrected the birth weights for prematurity or for gestational age more generally. For the purpose of predicting the birth weight in the firstborn child, the information on parental birth weights will be useful together with ultrasound measurements during pregnancy, at a time when the length of the pregnancy is yet unknown. For the purpose of understanding the population variability in birth weight, correcting for gestational age may blur the picture, as gestational length is an uncertain measure. Also, gestational age is as much an outcome of pregnancy as birth weight, and it is not obvious which one of these variables may be the cause of the other.

Studies of siblings have shown correlations for birth weight of about 0.5.1 Earlier analyses of data from the Medical Birth Registry, using the MZ half-sib method2 suggested higher estimates of heritability. Siblings and parent-offspring are expected to have the same degree of correlation under polygenic inheritance. A reasonable interpretation of the higher correlation in sibs is that maternal effects, which may be determined by the maternal genotype (but is the environment seen from the fetal perspective), are responsible for a certain part, maybe 25%, of the population variance in birth weight. This proposition should be tested out in studies of other relationships, in particular half-siblings and cousins.

We assume polygenic inheritance which implies many genes, each with a small effect on the phenotype. As yet, no common allele has been found that has large influences on the variability in birth weight, although some interesting associations of specific genes are emerging.12-13 Similarly, there are few examples of common environmental factors that have large effects on birth weight. For instance, in Western societies, maternal nutrition seems to have relatively small influence on birth weight.14

The advantage of this study is that the risk of low birth weight can be studied conditional on the birth weight of both parents (table 3). In clinical practice, if low birth weight is to be predicted, the paternal birth weight should be included. It is interesting that paternal birth weight seems to be a better predictor of offspring birth weight than paternal height.15 In clinical decisions one should be more cautious in diagnosing, by ultrasound or otherwise, intrauterine growth retardation if both parents were small at birth.