Seasonality of preterm births in Japan

Abstract

Seasonal variations in the proportion of preterm births in Japan from January 1979 to December 1983 are analysed using a traditional method of time-series analysis, which divides the variation in a series into trend, seasonal variation, other cyclic change, and remaining irregular fluctuations. It is shown that the proportion of preterm births in Japan have a clear seasonal periodicity with two peaks in summer and winter. Analysis of seasonality by period of gestation shows that interesting differences in kurtosis and skewness exist between summer and winter, i.e. the summer increase in preterm births was characterized by an increase of skewness which means an extension of the lower part of the distribution. On the other hand, the winter increase was characterized by a decrease of kurtosis which corresponds to a flat-topped distribution. This result suggests that causes of preterm births might be different between the two seasons. Theoretical simulations based on actual birth data in Japan over the period, are carried out to examine how season of conception could influence seasonal variations in the proportion of preterm births. Results show that, at least for first births, seasonality in conception rates could be one explanatory factor for the observed seasonal variation in proportions of preterm births. Another analysis reveals that conception in May and June are more likely to result in preterm births in Japan.

PIP: A time series analysis using virtually 100% complete vital statistics data was conducted to examine seasonality of premature births in Japan between 1979-1983. Developments in neonatal care have resulted in a decreasing trend in overall neonatal mortality rates (from 8.8 to 4.9% between 1980-1985), but an upward trend in premature births was observed during this time period. These rates were considerably greater in hospitals without a neonatal intensive care unit. Preterm births peaked in winter and summer (or the rainy season). Male 1st births climaxed in June and female 1st births in July, but this difference was not significant. Subsequent births had a lower peak and occurred later in the summer than 1st births. Period of gestation was used to analyze seasonality. The results showed an increase of skewness (an extension of the lower part of the distribution) for the summer increase in premature births. Yet a decrease of kurtosis (a flat-topped distribution) characterized the winter increase. The differences in the distributions are thought to mean that the cause of prematurity might be different between the 2 seasons. Also examined was season of conception data to see if season of conception could affect seasonal variations. This analysis showed that, at least for 1st births, seasonality of conception rates could account for the seasonal variation in premature births. Conception in May and June tended to result in premature births. Well planned, epidemiologic or experimental studies are needed to determine the association between specific factors and premature births so as to explain seasonality of premature births in Japan.