Analysis of seasonal variation of birth defects in Atlanta.
BACKGROUND
Compared with analyses of temporal trends, analyses of seasonal variations in the prevalence of birth defects have been more limited and have provided less consistent information. Possible reasons for this lack of consistency in findings include differences in populations, underlying factors, seasons or climates, and methods of ascertainment and analysis between studies. This study examines possible seasonal variation in the prevalence of selected birth defects in a defined study population using graphical displays and three statistical methods.


METHODS
Cases were infants and fetal deaths in nine birth defect groups born to residents of mothers in five counties of metropolitan Atlanta during the period of 1978-2001 and ascertained by the Metropolitan Atlanta Congenital Defects Program. These birth defect groups were anencephaly, spina bifida, total neural tube defects, cleft palate, cleft lip with or without cleft palate, anomalies of the pulmonary valve, anomalies of the aortic valve, hypoplastic left heart syndrome, and congenital dislocation of the hip. We pooled monthly case counts and calculated monthly rates for each of these birth defect groups for five different birth periods: 1978-2001, 1978-1989, 1990-2001, 1990-1994, and 1995-2001. We applied the Cochran-Armitage test for trend to rule out homogeneity in pooled monthly rates. Data for each defect group were examined for possible seasonal (i.e., cyclical) variation overall and within the cited birth periods using the Hewitt-Rogerson test and the Walter-Elwood test.


RESULTS
Graphical analyses of the pooled monthly rates showed no apparent seasonal patterns for any of the nine defect groups examined. Statistical tests for seasonality suggested possible seasonality for three defect groups: the Hewitt-Rogerson test was statistically significant for anencephaly (peak March-August, p = 0.048),while the Walter-Elwood test was significant for anomalies of the pulmonary valve (peak September, p = 0.02), and anomalies of the aortic valve (peak July, p = 0.039). With both methods, the results appeared to be influenced by the choice of time (i.e., birth) period. Results for anomalies of the pulmonary valve were statistically significant and more consistent with all tests in most of the time periods examined.


CONCLUSIONS
Graphical analyses and basic statistical tests for seasonality showed no consistent evidence of seasonality for any of the nine defect groups examined, except for anomalies of the pulmonary valve. The two basic statistical methods coupled by a trend test for exploring seasonal patterns of the prevalence of birth defects can be useful for preliminary analyses of possible seasonal patterns. However, these methods have some limitations: (1) an assumption of no strong temporal trend over the study years, and (2) the results can vary by time period chosen. For specific hypotheses regarding seasonality, a more robust analytical approach such as time-series analysis might be more appropriate.
Siffel
Csaba
C
Division of Birth Defects and Developmental Disabilities, National Center on Birth Defects and Developmental Disabilities, Coordinating Center for Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA. csiffel@cdc.gov
Alverson
C J
CJ
Correa
Adolfo
A
D000757:Anencephaly / Q000453:epidemiology; D001011:Aorta / Q000473:pathology; D001021:Aortic Valve / Q000002:abnormalities; D002971:Cleft Lip / Q000453:epidemiology; D002972:Cleft Palate / Q000453:epidemiology; D000013:Congenital Abnormalities / Q000175:diagnosis* / Q000453:epidemiology*; D005260:Female; D005845:Georgia; D006615:Hip / Q000002:abnormalities; D006801:Humans; D018636:Hypoplastic Left Heart Syndrome / Q000453:epidemiology; D015994:Incidence; D007231:Infant, Newborn; D015233:Models, Statistical; D009436:Neural Tube Defects / Q000453:epidemiology; D011247:Pregnancy; D011664:Pulmonary Valve / Q000002:abnormalities; D012044:Regression Analysis; D012621:Seasons; D012984:Software; D016135:Spinal Dysraphism / Q000453:epidemiology; D013997:Time Factors