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A new method for classifying patterns of prenatal care utilization using cluster analysis
Deborah Rosenberg1, Arden Handler, Sylvia Furner
1Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, Illinois 60612, USA. drose@uic.edu
Maternal and Child Health Journal
|May 6, 2004
Summary
Cluster analysis reveals distinct prenatal care patterns beyond the Adequacy of Prenatal Care Utilization Index (APNCU). This method offers new insights into prenatal care utilization and its relationship with birth outcomes.
Area of Science:
- Maternal and Child Health
- Biostatistics
- Public Health
Background:
- Prenatal care utilization is crucial for maternal and infant health outcomes.
- Existing measures like the Adequacy of Prenatal Care Utilization Index (APNCU) may not capture the full complexity of care patterns.
Purpose of the Study:
- To define patterns of prenatal care utilization using cluster analysis.
- To compare cluster solutions with the APNCU regarding maternal age and prematurity.
- To evaluate the utility of cluster analysis in studying prenatal care.
Main Methods:
- Utilized cluster analysis (k-means and Ward's method) on data from 3544 women in the 1988 National Maternal and Infant Health Survey.
- Compared identified clusters with the APNCU.
Main Results:
- Cluster analysis identified distinct prenatal care patterns based on timing, total visits, and visit accumulation rates.
- While a normative pattern was similar to APNCU, other identified patterns differed significantly.
- A six-cluster solution distinguished women with similar entry times but varying visit accumulation and preterm delivery rates.
Conclusions:
- Cluster analysis offers a novel approach to understanding prenatal care utilization.
- Further research is needed to refine this method and explore its potential for uncovering new relationships between prenatal care and birth outcomes.