Using registry data to suggest which birth defects may be more susceptible to artifactual clusters and trends.
BACKGROUND
Some birth defects appear to be more susceptible than others to artifactual prevalence variability over time or geographically. This article uses an empirical approach to try to identify them.


METHODS
Assumption: Variation in clinical practice and other artifactual sources of variability impact observed variation in prevalence of mild cases more than severe cases for a given birth defect.


METHODS
Data were examined from Texas Birth Defects Registry deliveries from 1999-2003. For each of 312 delivery hospitals, birth prevalence for mild cases was calculated for birth defect X. The 5(th) percentile was subtracted from the 95(th) percentile to measure spread in the frequency distribution of all hospitals. That was repeated for severe cases. The ratio of the mild:severe spread was calculated for 49 defects, and the defects ranked into quintiles. That was repeated using birth prevalence based on county, and using isolated cases. The percentages of severe cases were calculated and also ranked into quintiles. A sensitivity analysis and simulation were conducted.


RESULTS
Forty-nine birth defects were ranked from those least susceptible to differences in mild:severe prevalence variability (e.g., anencephaly, hypoplastic left heart syndrome) to most susceptible (e.g., atrial septal defect, fetal alcohol syndrome). Resulting quintile ranks based on the three measures were highly correlated, whether based on all cases or isolated cases.


CONCLUSIONS
This empirical approach may be helpful for a number of public health applications. Birth defects and other health outcomes more susceptible to prevalence variability may be more likely to exhibit artifactual trends or clusters.
Langlois
Peter H
PH
Birth Defects Epidemiology and Surveillance Branch, Texas Department of State Health Services, 1100 West 49th Street, Austin, Texas 78756, USA. peter.langlois@dshs.state.tx.us
Scheuerle
Angela
A
D016477:Artifacts; D016000:Cluster Analysis; D000013:Congenital Abnormalities / Q000453:epidemiology*; D005260:Female; D005843:Geography; D006801:Humans; D015588:Observer Variation; D010818:Practice Patterns, Physicians' / Q000639:trends*; D011247:Pregnancy; D015995:Prevalence; D012042:Registries / Q000706:statistics & numerical data*; D013997:Time Factors