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Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging
09:56

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Published on: April 30, 2019

Visualization and interpretation of birth defects data using linked micromap plots.

Samson Y Gebreab1, Robert R Gillies, Ronald G Munger

  • 1Department of Watershed Sciences, Utah State University, 5210 Old Main Hill, Logan, Utah 84322-5210, USA.

Birth Defects Research. Part A, Clinical and Molecular Teratology
|December 1, 2007
PubMed
Summary

Linked micromap (LM) plots effectively visualize birth defect data, revealing geographic patterns and risk factor associations. Integrating LM plots into surveillance systems enhances data presentation and interpretation for birth defects.

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Area of Science:

  • Public Health
  • Biostatistics
  • Geographic Information Systems

Background:

  • Birth defects surveillance systems are crucial for monitoring and disseminating information.
  • Current reliance on tabular methods for summarizing birth defect data limits comprehensive understanding.
  • Linked micromap (LM) plots offer an innovative approach to present birth defect data in a combined geographical and statistical context.

Purpose of the Study:

  • To evaluate the effectiveness of linked micromap (LM) plots for presenting birth defect data.
  • To explore the spatial patterns and demographic/behavioral risk factor associations of oral clefts using LM plots.

Main Methods:

  • LM plots were created for oral cleft data at national (USA states) and sub-state (Utah counties) levels.
  • Data visualization incorporated demographic and behavioral risk factors, including maternal smoking rates and ethnicity.
  • Geographic and statistical analyses were performed using the generated LM plots.

Main Results:

  • National LM plots revealed higher oral cleft occurrence in the Southwest and Midwest USA, with lower rates in the East.
  • Associations were observed between oral cleft occurrence, maternal smoking rates, and the proportion of American Indian/Alaska Native populations.
  • LM plots for Utah counties did not show a clear geographic pattern, potentially due to limited case numbers.

Conclusions:

  • LM plots are effective tools for representing complex and large-volume birth defect data.
  • Integrating LM plots into existing birth defect surveillance systems can significantly improve data presentation and interpretation.
  • This visualization method aids in identifying geographic disparities and potential risk factors for birth defects.