5.3.2.1 Antenatal detection o f restricted fetal growth
In this study population, only 28% (22/79) o f SGA infants were identified as having poor fetal growth antenatally. Unfortunately, no data are available regarding the specificity and sensitivity o f antenatal ultrasound screening to detect SGA fetuses at the two recruitment centres. Nevertheless, the proportion o f SGA infants identified antenatally in this study was similar to that reported in an earlier perinatal review (de Courcey-Wheeler et al. 1995). Despite increasing technological advancement in ultrasonography and its use for the assessment o f fetal growth, antenatal detection of SGA fetuses has been reported to be poor (Neilson and Alfirevic, 1998; Neilson and Alfirevic, 1998). Hence most o f the SGA infants were identified fi*om anthropometric measurements made after delivery.
5.3.2.2 Postnatal identification
Since the optimal method o f identifying SGA infants postnatally remains unclear, two methods to classify infants’ size at birth were used, namely the CGF (Freeman et al. 1995) and GROW (Wilcox et al. 1993) algorithms. There was generally reasonable agreement between these two methods (Lum et al. 1999), with any discrepancies falling between the 11 - 15*^ centiles on one or other program. By including infants who were identified as SGA by either method, it was hoped that misclassification would have been avoided. Furthermore, in order to maintain a clear dichotomy between the SGA and AGA groups, infants whose birthweight centile fell between 15^*’ - 20^^ centile according to CGF charts were not recruited into either group. However, it is recognised that the relationship between morbidity and birthweight is not a dichotomy but a continuous distribution, as it is dependent on the exposure to risk factors such as smoking, nutrition and poor socio-economic status (Kramer, 1987).
While it may be argued that birthweight centiles should be considered as a continuous variable rather than dichotomised into SGA and AGA groups, the latter option was chosen as the most cost-effective study design available. As we were interested in examining the implications o f more severe growth restriction after allowing for some potentially confounding factors, we considered it advisable to actively recruit larger numbers o f infants o f low birthweight for gestation than would have been possible had we simply recruited a general population sample (Section 5.3.1.1). As these tests are time consuming and require sedation and furthermore as SGA infants tend to be disproportionately exposed to matemal smoking, we actively recmited SGA infants to ensure that the study had adequate power to detect clinically important differences and to adjust for recognised confounding factors. As this was the recmitment strategy, we therefore analysed all data accordingly using a dichotomous variable to express birthweight status. Using this option allowed comparison to be made between the two extremes o f population with a clear gap (CGF 15-20**' centile) between the two groups.
However, we have also undertaken analyses using ‘Birthweight SD score’ as a continuous variable and found that the conclusions o f the study are similar irrespective o f whether birthweight status is expressed as continuous or dichotomous (Figures 5.2 and 5.3). Thus, as for the dichotomous analysis presented in sections 4.6.4 and 4.6.5, univariate analysis revealed a significant relationship between both FEVo.4 (Figure 5.2) and MEF25 (Figure 5.3) and birthweight SD score, whereas this relationship only remained significant for FEV0.4 after adjusting for known confounders (see Table 4.20 and Table 4.21).
Figure 5.2 FEV0 .4 plotted against birthweight SD score according to
maternal smoking status
3001 V £ •3 •2 0 1 2 -4 1 ^ smoking V non-smoking Birthweight SD score
Figure 5.3 MEF25 plotted against birthweight SD score according to maternal smoking status
400 300 200 wo (N a . i g X 100 V V V V V % V 7V yv 7 W -4 -3 -2 -1 0 Birthweight SD score ^ smoking 7 non-smoking 185
5,3,2,3 CGF or GROW?
There was no ‘reference’ birthweight standard for the local population with which to compare birthweight status of infants recruited to this study. Thus the widely used population based CGF reference standard for the UK (Cole et al. 1995) was used in conjunction with the assumption that an SGA infant is one whose birthweight lies below the 3*^*^ or the 10^^ centile. However, some infants may be poorly grown, but on the basis o f their birthweight, may appear to be o f appropriate size for their gestational age. The GROW program, which calculates an individualised birthweight ratio from the relative contributions o f gestation, matemal weight, infant sex, matemal height, parity and ethnic origin, was therefore used to provide a measure o f the difference between the actual birthweight and the predicted birthweight o f the infant (Wilcox et al. 1993).
Although there was reasonable agreement between these two methods o f birthweight classification ( Figure 4.4 and Figure 4.5), these methods are not interchangeable as shown by the wide limits o f agreement according to the method by Bland and Altman (Bland and Altman, 1986). Centiles derived from the CGF were on average 3 centiles (95% Cl: 2.2, 3.7) higher than GROW among SGA infants and 5.3 centiles (3.1, 7.4) higher than GROW among AGA infants.
Nevertheless, recent studies examining perinatal outcome in SGA births as defined by customised (GROW) versus population based birthweight standards have reported that the former method has an improved capacity to identify adverse effects related to fetal growth restriction such as stillbirth, neonatal death and Apgar score less than four at five minutes (de Jong et al. 1998; Clausson B et al. 2001).
53,2,4 Practical difficulties in calculating birthweight centiles
There are additional practical difficulties in attempting to use either o f these methods. The calculation o f birthweight centiles using the CGF algorithm is based on infant’s sex, gestational age and birthweight. As these factors are routinely recorded for each birth, and centile charts published by CGF are widely available.
this method o f birthweight centile estimation is readily accessible for use in postnatal wards. By contrast, for birthweight centiles calculated using the GROW algorithm, information on matemal height, booking weight, ethnic group and parity are needed together with the GROW software to calculate an individualised birthweight centile. This information was not routinely recorded in the obstetric records, specifically details o f matemal height and booking weight were often missing. When matemal booking weight was available, the gestational age at which this was recorded varied fi*om nine to 20 weeks. Thus, classification o f infants using the GROW program was not feasible as a routine procedure to identify and recmit eligible SGA infants from postnatal wards. Hence some o f the SGA infants who might have been identified as such according to GROW algorithm but who were above the 10^ centile according to CGF algorithm might have been missed and hence not approached for recmitment to this study.
During the first year o f this study, the identification o f eligible infants for recmitment was based on using the CGF paper charts rather than software on the postnatal ward. While the resolution o f the CGF chart was adequate for the estimation o f birthweight centile up to 40 weeks gestation, it was much harder to use reliably for infants delivered after this gestation, due to the smaller scale o f the chart (Appendix L). As a result, five infants who attended for respiratory function tests were later calculated to have birthweight between 15*^ - 20* centile according to the CGF algorithm and were therefore excluded from the study. In order to minimise this potential source of error, software produced by the Child Growth Foundation was subsequently used to identify eligible infants for recmitment. This meant that access to a computer and appropriate software was required for both methods.
As race and ethnic group have significant effects on birthweight (Zhang and Harville, 1998; Pang et al. 2000), birthweight standards such as the CGF method, derived fi"om predominantly ‘Caucasian’ populations cannot be used for all racial/ethnic groups. Nevertheless, Gardosi et al. suggests that differences between the ethnic groups disappear when matemal size is also taken into consideration as proposed in the GROW program (Gardosi et al. 1992). However, this information was lacking in more than half o f the eligible study population. Furthermore, the time o f the
woman’s first antenatal visit may vary greatly and the measurement o f matemal weight and height is no longer routinely performed in many maternity units.