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Birth Defects

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Last Edited: 7/11/11

Birth Defects: Measurement and Limitations

To understand how often birth defects happen in a population, it is important to monitor the occurence of birth defects at the time of birth (birth defects prevalence).  Although there are many types of birth defects, on this website we provide counts and rates for a select group of 12 birth defects.

Learn more about birth defect data sources and limitations.

This section contains the following topics:


Data Sources

California Birth Defects Monitoring Program Registry Data

Established in 1982, the California Birth Defects Monitoring Program (CBDMP) Registry collects information on birth defects during the first year of life from hospitals, laboratories, and genetic centers.  CBDMP actively reviews medical records to identify and describe major structural and chromosomal defects in a subset of California's population.  CBDMP also collects demographic information including race, ethnicity, geographic location, mother's age, and single and multiple births.

CBDMP also collects data on total live births and fetal deaths.  This data was used in the denominator to calculate birth defect prevalence rates displayed in this portal.

 

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Statistical Concepts

5-year Average

Given that birth defects are a rare event, we calculated a 5-year average for each birth defect by county.  This is done by counting the total number of a particular birth defect (e.g. anencephaly) over a five year period (e.g. 2000-2004), and dividing by five.

 

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5-year Prevalence Rate

The 5-year prevalence rate for each birth defect is calculated by taking the total number of a particular birth defect over a five year period (e.g. 2000-2004) in a county, and dividing by the total number of live births in that county for that same time period.  We also calculated 5-year prevalence rates for specific demographic groups: infant sex, maternal age, and maternal race/ethnicity.  The rates are then multiplied by 10,000 and expressed as X birth defects per 10,000 live births.

 

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Confidence Intervals

Given the data at hand, to understand the range of possible values for the true prevalence rate, we calculate the 95% confidence interval for each rate.  Statisticians have developed a large number of methods for calculating these confidence intervals.  Usually the result is the same no matter which method is used, although when numbers of events are small, the results may differ.

The Wilson's score method applies specifically to the situation of binomial processes such as birth defects incidence in a population.  We have chosen to use this method for calculating confidence intervals for birth defects prevalence, but it is important that users understand that others in the field may not be using the same method.

 

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Common Limitations with the Data

Lack of Statewide Data

CBDMP expanded data collection from 1983-1990, eventually monitoring all 58 California counties.  However, due to significant budget constraints monitoring has been scaled back to include a subset of the population, until recently about 40% of annual births in California. Currently, they are collecting data in the Central Valley (since 1987), San Diego County (since 2001), and Orange County (since 2003).  Monitoring was conducted in Riverside and San Bernardino Counties (2005-2007) but has recently been discontinued. There is limited data collection in Los Angeles, San Francisco, Santa Clara and Sacramento Counties to insure more complete ascertainment of children receiving care in tertiary care centers outside of the Program’s reporting counties.  

Since 1987, they have consistently monitored the following eight counties located in the Central Valley:

  • Fresno
  • Kern
  • Kings
  • Madera
  • Merced
  • San Joaquin
  • Stanislaus
  • Tulare

Although this subset represents the state's geographic, environmental, and racial/ethnic diversity, we are unable to provide statewide data for birth defects.

On this portal, we only provide data for these eight Central Valley counties.

 

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Exclusion of Data for Some Birth Years

There are nuances to the data collected at the county-level.  Specifically, single gene disorders and abnormal chromosomes (other than Trisomy 13, 18, and 21) were excluded for certain birth years.  The table below describes during which birth years the exclusions took place by county.

County
Birth years that exclude single gene disorders and abnormal chromosomes other than Trisomy 13, 18, 21
Fresno
2001-2003
Kern
2001-2003
Kings
2001-2003
Madera
2001-2003
Merced
2001-2006
San Joaquin
2001-2006
Stanislaus
2001-2006
Tulare
2001-2003

 

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 Multiple Birth Defects in the Same Baby

A baby can have more than one birth defect and can be counted as a separate case for each defect (i.e. child with cleft lip and spina bifida will be counted as a case of cleft lip, and again as a case of spina bifida).  Therefore, the defect data do not necessarily represent mutually exclusive cases.  It is important to recognize that adding up the number of defects will not yield the number of babies with defects.

 

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Potential for Race/Ethnicity Misclassification

The concepts of race and ethnicity are difficult to define.  Although birth defects data include information on maternal race and ethnicity, we know that these data are not necessarily recorded consistently and may not reflect peoples' self-identification of their race/ethnicity, much less capture their experiences with respect to discrimination, acculturation, or vulnerability to health problems.  When using race/ethnicity information from these data sources, these limitations should be kept in mind.


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