Seasonality of Poor Pregnancy Outcomes

background Seasonal variation in poor pregnancy outcomes has not received the same level of research attention and rigor as has thewell-established seasonal variation in births. methods In this analysis of data from the 2001-2005 North Carolina Detailed Birth Record, we use season of conception as a proxy forenvironmental or other risk factors. We model the continuous pregnancy outcome of birth weight percentile for gestational age by use of linear regression. We use logistic regression to model the binary pregnancy outcomes of low birth weight (<2500 g), preterm birth (<37weeks), and small for gestational age (<10th percentile of birth weight for gestational age). results We found significant seasonal patterns in poor pregnancy outcomes. Our results suggest that, in North Carolina, seasonal pat-terns are most pronounced among non-Hispanic white women living in urban areas. limitations The present study is limited by the restricted set of maternal and pregnancy variables available in this data set. Richer data,potentially including psychosocial and activity measures of the women, would allow us to more ably discern what is driving the seasonal patterns we observed. The pronounced increased risk associated with a spring season of conception provides an important clue for deter-mining the true causative factors. conclusions Poor pregnancy outcomes in North Carolina follow a clear seasonal pattern based on timing of conception, with patterns most pronounced among non-Hispanic white women living in urban areas. These seasonal patterns are suggestive of causative environmental factors and certainly warrant additional research.