Deborah Rosenberg1, Arden Handler, Sylvia Furner. 1. Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, Illinois 60612, USA. drose@uic.edu
Abstract
OBJECTIVES: The objectives of this study were: to 1) define patterns of prenatal care utilization using cluster analysis, 2) describe two alternative cluster solutions and compare these groupings to the Adequacy of Prenatal Care Utilization Index (APNCU), 3) compare the cluster solutions and the APNCU with respect to maternal age and prematurity, and 4) discuss advantages and disadvantages of using cluster analysis to study prenatal care. METHODS: The study sample included 3544 women in the 1988 National Maternal and Infant Health Survey for whom complete prenatal care visit data were available. Clustering was carried out in two stages, first employing nearest centroid sorting (the k means method), a nonhierarchical approach, and then using Ward's Minimum Variance Method, a hierarchical clustering technique. RESULTS: Patterns of prenatal care defined by cluster analysis varied by timing of the first visit, total number of visits, and the rate of accumulation of visits, but this variation was different compared to that seen for the APNCU. While the cluster solutions and the APNCU identified a similar normative pattern of care, other patterns identified were quite different. In particular, the six-cluster solution differentiated among women who entered care at similar times, but accumulated visits at differing rates and experienced differing rates of preterm delivery. CONCLUSION: Cluster analysis is a new tool for studying prenatal care. Further studies are needed to refine the method and test whether the alternative perspective it provides will lead to new findings concerning the relationship of prenatal care and birth outcomes.
OBJECTIVES: The objectives of this study were: to 1) define patterns of prenatal care utilization using cluster analysis, 2) describe two alternative cluster solutions and compare these groupings to the Adequacy of Prenatal Care Utilization Index (APNCU), 3) compare the cluster solutions and the APNCU with respect to maternal age and prematurity, and 4) discuss advantages and disadvantages of using cluster analysis to study prenatal care. METHODS: The study sample included 3544 women in the 1988 National Maternal and Infant Health Survey for whom complete prenatal care visit data were available. Clustering was carried out in two stages, first employing nearest centroid sorting (the k means method), a nonhierarchical approach, and then using Ward's Minimum Variance Method, a hierarchical clustering technique. RESULTS: Patterns of prenatal care defined by cluster analysis varied by timing of the first visit, total number of visits, and the rate of accumulation of visits, but this variation was different compared to that seen for the APNCU. While the cluster solutions and the APNCU identified a similar normative pattern of care, other patterns identified were quite different. In particular, the six-cluster solution differentiated among women who entered care at similar times, but accumulated visits at differing rates and experienced differing rates of preterm delivery. CONCLUSION: Cluster analysis is a new tool for studying prenatal care. Further studies are needed to refine the method and test whether the alternative perspective it provides will lead to new findings concerning the relationship of prenatal care and birth outcomes.