Literature DB >> 1544764

Seasonality of preterm births in Japan.

S Matsuda1, H Kahyo.   

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.

Entities:  

Keywords:  Age Factors; Asia; Climate; Demographic Factors; Developed Countries; Eastern Asia; Environment; Epidemiologic Methods; Fertilization; Fetus; Gestational Age; Infant; Infant Mortality; Infant, Premature--changes; Japan; Methodological Studies; Models, Theoretical; Mortality; Neonatal Mortality; Population; Population Characteristics; Population Dynamics; Population Statistics; Pregnancy; Reproduction; Research Methodology; Seasonal Variation; Time Factors; Vital Statistics; Youth

Mesh:

Year:  1992        PMID: 1544764     DOI: 10.1093/ije/21.1.91

Source DB:  PubMed          Journal:  Int J Epidemiol        ISSN: 0300-5771            Impact factor:   7.196


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