Using Administrative Data To Monitor Access, Identify Disparities, and Assess Performance of the Safety Net: Figure 1

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Figure 1. Percent of Births with Late/No Prenatal Care, New York City, 1997-1998

Scatter diagram of ZIP codes areas, with Percent of Population Below Poverty on one axis and Percent of Births Late/No Prenatal Care on the other axis. Go to Text Description [D] for details.

Key: Each square represents a ZIP code area.

[D] Scatter diagram of ZIP codes areas, with Percent of Population Below Poverty on one axis and Percent of Births Late/No Prenatal Care on the other axis.

ZIP code-level analysis often can provide findings of significant interest to planners and policymakers as well. Combining birth data with information on characteristics of ZIP codes can help produce charts and maps that are very intuitive to policymakers. For example, simply examining area income reveals a relatively strong association between area income and rates of late/no prenatal care. Displaying these data in a graphic format often has more power than mere tables with numbers or more complex multivariate analyses, which may be confusing to some readers.

In Figure 1, the relationship between income and rates of late/no prenatal care in New York City is apparent, even to observers without statistical backgrounds. It is easy to see that higher rates tend to be in low-income areas, with generally lower rates in high-income areas.

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