Characteristics and birth outcomes: Women receiving no prenatal care in the United States, 1995–1997

Although prenatal care is an established mechanism for identifying and managing risk factors impacting pregnancy outcomes, about 70,000 women in the United States receive no prenatal care annually. It was hypothesized that women who receive no care comprise clusters (subgroups) with distinctive soci...

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Bibliographic Details
Main Author Taylor, Cathy R
Format Dissertation
LanguageEnglish
Published ProQuest Dissertations & Theses 01.01.2002
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Summary:Although prenatal care is an established mechanism for identifying and managing risk factors impacting pregnancy outcomes, about 70,000 women in the United States receive no prenatal care annually. It was hypothesized that women who receive no care comprise clusters (subgroups) with distinctive sociodemographic characteristics and that differences in birth outcomes exist among the clusters. A population-based, non-experimental, retrospective design, and secondary data were used to identify White, Black, and Hispanic (n = 126,220) women delivering a live, singleton infant and reporting no prenatal care between 1995 and 1997. Cluster analysis was used to cluster (group) no care women with similar maternal characteristics, and prospective cluster assignment was evaluated using discriminant analysis. Birth outcome frequencies were calculated for the total population receiving any care and the no care clusters. Birth outcome differences were assessed for the total population and the clusters using chi square analysis. Logistic regression was used to assess risk for negative birth outcomes among the clusters. Six clusters emerged. Replicability of cluster assignment was confirmed using discriminant analysis. Women in Cluster I (n = 7,832) were older, White, married, highly educated, with high risks. Women in Cluster 2 (n = 2,222) were young, foreign-born Hispanic, with no education, and low risks. Women in Cluster 3 (n = 9,155) were young, foreign-born Hispanic, with elementary education, and low risks. Women in Cluster 4 (n = 62,014) were young, Black, with <12 th grade education, and the highest risks. Women in Cluster 5 ( n = 22,051) were young, White, primiparas, with >12th grade education, and high risks. Women in Cluster 6 (n = 2,946) were very young and Hispanic with <9th grade education and high risks. Birth outcomes varied significantly among clusters. Cluster 4 had the worst outcomes; Cluster 3 had the best outcomes. Outcomes were two to four times worse for the clusters compared to women receiving any care. Interventions should target reducing the proportion of women receiving no care and should be tailored to specific no care subgroups. Cluster analysis offers an effective alternative for grouping characteristics for use in public health education, intervention, and outreach.
ISBN:9780493869162
0493869166