Clustering in perinatal data can violate assumptions of independence, an important consideration for data analysis. Few published studies report on the extent of repeat births in routinely collected Australian perinatal data and the implications thereof for analysis and interpretation. This paper reports on a case study that examined the extent and implications of clustering in the Northern Territory Midwives Collection (NTMC) for the period 2003-2005. Data were obtained on 7,741 individual mothers giving birth to 8,707 babies in public hospitals during 2003-2005. Clusters of multiple pregnancies and repeat births were identified and the design effects for birth weight of Aboriginal and non-Aboriginal newborns were calculated. Of the mothers, 46.1% were Aboriginal. Of these, 13.2% had repeat singleton births; 0.4% had multiple pregnancies, and 0.3% had both. Of non-Aboriginal mothers, 8.7% had repeat singleton births; 1.2% had multiple pregnancies; and 0.3% had both. The design effect was 1.07 for Aboriginal newborns and 1.04 for non-Aboriginal newborns. The design effects indicate that the correct variance accounting for clustering is 4-7% larger than the incorrect variance ignoring clustering when three consecutive years of NT data are considered and an intracluster correlation coefficient of 0.48 is assumed for birth weight between twin and non-twin siblings. Depending on the outcome of interest, the impact of clustering should be considered in multivariate analysis of perinatal data, especially when such analyses involve more than one year's data, include large proportions of Aboriginal mothers and newborns, and groups with different rates of repeat births.
- Cluster analysis
- Indigenous population