Centile charts of birthweight for gestational age are a valuable tool in many epidemiological studies as well as providing important information to clinicians as to which babies may be at higher risk of neonatal or postnatal morbidity . It is therefore essential that the charts used are representative of the population to which they are applied. A number of standards are available based on births occurring in various European countries; mostly using data from the 1980s and the 1990s .
There are clear differences between the centiles calculated here from recent data and those in current use in Scotland which are based on data from 1975–1989. For term babies the median birthweight in all sex and parity groupings is shown to be higher than it was previously. This increase in birthweight is also reflected in the other centiles. For babies born at very low gestational ages the median birthweight is now less than it was, possibly reflecting the increased survival rate in pre-term births . The centiles for lower gestational ages are also much closer together than in the existing charts. One possible explanation for such a marked difference at lower gestations in particular may be poor estimation of gestational age, particularly in the 1970s, as was found in data for England and Wales analysed by Milner and Richards in 1974 .
In recent years a number of centiles charts  have been constructed using the method developed by Gardosi . This method aims to give a fetal weight standard and requires only data for term births from the population of interest. Whilst it is desirable in principle to look at fetal weights the assumptions which are being made with this method cannot be substantiated with reference to our data which consists only of actual birthweights. It is therefore not possible to assess the goodness of fit of the centiles calculated in this way.
As well as modelling the median birthweight the LMS method also models the coefficient of variation S and the power L which is used to transform the birthweights to achieve normality. Within each of the sex and parity groupings it is seen that the coefficient of variation decreases with increased gestational age showing that the birthweights are more variable at lower gestational ages. This contrasts with the assumption used in Gardosi's methodology for fetal weights that the coefficient of variation is constant.
It is important in constructing charts of this type to test the adequacy of the model fitted both with reference to the raw data used to construct the charts and to the assumptions on which the model relies [20, 21].
Comparing the new centiles to the empirical centiles suggests that the LMS method is a reasonable fit to the data. It can be shown that, in general, the standard errors of empirical centiles are larger than those for the centiles calculated using the normal distribution. The latter method is therefore more efficient. This is only true if the assumption of normality is reasonable which is not the case for birthweight and therefore some transformation of the data is required. A value of 1 for L indicates no transformation required with a value less than 1 adjusting for positive skewness and a value greater than 1 for negative skewness. For each sex and parity grouping the values of L suggest that the birthweights are negatively skewed for low gestational ages and positively skewed for higher gestational ages. The values of L suggest the extent of skewness at each gestational age is not high.
Normal probability plots of the z-scores for each grouping and for each gestational age within each grouping show that the LMS method has largely succeeded in achieving normality. There is some suggestion in the plot of heavier tails however the percentages in the tails are close to what is expected.
An important question in constructing centile charts of any data is which cases to include in the calculations and which to omit. Many previous studies into centile charts have used live births only because of the difficulty of accurately assessing the gestational age of stillbirths. The argument in the past has been that a baby which is stillborn may have died some time before delivery and therefore the weight may not be a true reflection of the gestational age at which delivery occurs. This is not often the case now. Fetal death is almost always recognized very quickly, and most women prefer to be delivered as soon as possible once it is realized that this has happened. This was argued by Tin looking at the problems of estimating centiles for babies born before 32 weeks gestational age, In this paper it was suggested that not all stillbirths should be excluded, arguing that by doing so centiles at gestational ages less than 28 weeks have been largely overestimated.
For babies born within ten weeks of term the difference in centiles including and excluding stillbirths are negligible because the numbers of stillbirths are relatively small. Omitting stillbirths at low gestations of 24–27 weeks gestation causes bias in the centiles possibly because very small babies at any specified gestation are much more likely to be treated as "effectively" stillborn than larger babies of the same gestation when pregnancy ends as soon as this.
Information on ethnicity is poorly recorded on the SMR02 forms therefore no attempt was made to produce separate centiles for different ethnic groups. From the 2001 census it is known that the minority ethnic population was just over 100,000 in that year which is 2% of the total population of Scotland. The percentage is similar for women of child bearing age. Ethnicity is not therefore a major consideration for the Scottish data.
Other studies have followed the convention of excluding babies with major congenital malformations  and this has been used in this study. However with such a large data set the exclusion has made little difference to the centiles. Other studies [1, 23] have also identified outliers at each gestational age using the criterion outlined by Tukey. From visual inspection of the charts with and without the outliers, it is clear that the points identified in this study are most likely to be due to transcription errors. The excluded points do not therefore raise any concerns about the accuracy with which gestational age is measured.
Other factors are known to have a significant effect on birthweight and a number of customised charts have been developed in recent years. It can be desirable to take into account physiological factors such as the height of the mother which contribute to the natural variation in birthweights but not potential risk factors such as whether or not the mother smokes. The distinction between the two types of factor may not always be clear cut however. For example height and weight of the mother may in part be determined by risk factors such as social deprivation or nutrition. There is therefore an important role in epidemiological studies into adverse perinatal outcomes for charts such as the ones described here which will allow both the effect of infant's size and the size of the mother to be separated.