Related Experiment Videos
Sex ratios among infants with birth defects, National Birth Defects Prevention Study, 1997-2009
Adrian M Michalski1, Sandra D Richardson, Marilyn L Browne
1New York State Department of Health, Congenital Malformations Registry, Albany, New York.
Insights
This study analyzed sex ratios in infants with birth defects, finding significant differences for specific congenital anomalies. These sex differences in birth defects may offer insights into their causes and classification.
Area of Science:
- Pediatric Epidemiology
- Congenital Anomalies Research
- Sex Differences in Health
Background:
- Population-based studies on sex differences in infant birth defects are limited.
- Understanding these differences is crucial for etiological insights and classification.
- Previous research has not comprehensively analyzed sex ratios across diverse congenital anomalies and demographic groups.
Purpose of the Study:
- To estimate sex ratios for isolated and multiple congenital anomalies.
- To examine sex ratio variations by race/ethnicity for specific birth defects.
- To identify patterns in sex differences that may inform etiology and classification.
Main Methods:
- Analysis of 25,952 clinically reviewed case infants from the National Birth Defects Prevention Study (1997-2009).
- Calculation of male-female sex ratios and 95% confidence intervals.
- Stratification of analyses by defect type (cardiac vs. non-cardiac, isolated vs. multiple) and race/ethnicity.
Main Results:
- Significant male preponderance observed in isolated non-cardiac defects like craniosynostosis (2.12) and cleft lip (1.78-2.01).
- Notable female preponderance in defects such as choanal atresia (0.45) and cloacal exstrophy (0.46).
- Highest sex ratios for isolated cardiac defects included aortic stenosis (2.88) and coarctation of the aorta (2.51); lowest for multiple VSDs (0.52).
- Observed variations in sex differences across different race/ethnicity groups for certain defects.
Conclusions:
- Sex differences in specific congenital anomalies are evident and vary by defect type and presence of multiple anomalies.
- Observed patterns in sex ratios suggest potential etiological factors.
- Findings support the utility of considering sex and race/ethnicity in birth defect classification and research.
Abstract:
A small number of population-based studies have examined sex differences among infants with birth defects. This study presents estimates of sex ratio for both isolated cases and those with multiple congenital anomalies, as well as by race/ethnicity. Male-female sex ratios and their 95% confidence intervals were calculated for 25,952 clinically reviewed case infants included in the National Birth Defects Prevention Study (1997-2009), a large population-based case-control study of birth defects. The highest elevations in sex ratios (i.e., male preponderance) among isolated non-cardiac defects were for craniosynostosis (2.12), cleft lip with cleft palate (2.01), and cleft lip without cleft palate (1.78); the lowest sex ratios (female preponderance) were for choanal atresia (0.45), cloacal exstrophy (0.46), and holoprosencephaly (0.64). Among isolated cardiac defects, the highest sex ratios were for aortic stenosis (2.88), coarctation of the aorta (2.51), and d-transposition of the great arteries (2.34); the lowest were multiple ventricular septal defects (0.52), truncus arteriosus (0.63), and heterotaxia with congenital heart defect (0.64). Differences were observed by race/ethnicity for some but not for most types of birth defects. The sex differences we observed for specific defects, between those with isolated versus multiple defects, as well as by race/ethnicity, demonstrate patterns that may suggest etiology and improve classification.
Related Concept Videos
The Ratio of X Chromosome to Autosomes
Normal male Drosophila has a ratio of one X chromosome to two sets of autosomes. In contrast, normal female...
Probability Laws
Teratogenicity
Odds Ratio
Sex-linked Disorders
Testing a Claim about Population Proportion
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...