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Monthly numbers of births are influenced by the length of the month and, thus, rates per day should be used. Comparisons of seasonality in data sets of different sizes must be based on standardized indices. Although strong seasonality exists, a poor model may incorrectly yield low seasonality measures. The standard deviation of the inter-monthly variation in the indices has been used as a seasonality measure. We introduce a new measure based on analysis of variance (ANOVA). Our methods are applied on 107,896 births in the archipelago of Aland (Finland), 1653-1950. For all subregions, the birth indices for the period 1653-1850 showed marked peaks in March to April and in September to October. The seasonality is weakest for the Main Island and strongest for the most isolated parish, Kokar, which has many local/extreme socioeconomics and genetic characteristics. For the period 1851-1950, the seasonality disappeared almost totally. The variation in the seasonality between subregions can mainly be explained by socioeconomic differences, and the temporal decrease in all regions seems to be connected to diminishing differences in living conditions. Comparisons with data from Sweden and Finland show higher seasonality in Aland. DOI: 10.1080/19485560903054788

A knowledge of the seasonal variation in births and deaths during normal years is important for analyses of the effects of wars, famines, epidemics or similar privations on these two variables. In studies of seasonality, multiple trigonometric regression models are more flexible than the simple sine curve. The seasonal variation in mortality in Iceland, 1856-1990, shows a strong secular decrease, and a connection between this and the epidemiological transition is considered. As a consequence of the severe famine in Finland in 1867-68, the mortality for the whole year 1868 was almost four times as high as during normal years, and the seasonality of the mortality was even more accentuated. The birth rate in Finland during 1868 was about 70 percent of that during normal years and showed an aberrant seasonality, with a strong trough from October 1868 to February 1869 (fewer conceptions between January and May 1868, when the food shortage was severe).

Hellin's law states that if the twinning rate is w, then the triplet rate is |w.sup.2~, the quadruplet rate is |w.sup.3~, and so forth. The opinion of today is that Hellin's law holds only approximately. In this study the inaccuracy of Hellin's law is studied and the discrepancies are explained mathematically. In our earlier studies we built linear models for the twinning rate. Because most of the mothers are younger than 40 years of age and because in this age interval the twinning rate depends linearly on age, linear regression methods have been applied. Hellin's law suggests using the square-root transformation of the triplet rate r. Statistical arguments speak in favor of using the arcsin |square root of~r transformation. We discuss both transformations. Despite the fact that Hellin's law is only approximate, the arcsin transformation proves valuable. The transformed triplet rate can be modeled in a way similar to the twinning rate. We consider secular data from Finland for 1881-1990 and from Sweden since 1751. Using Hellin's law, we compare the triplet rates and the twinning rates and study the time trends of the observed twinning and triplet rates. The data are standardized. Our theoretical results are applied to multiple maternity data for Finland. Using maternal age as the regressor, we build a linear model for the twinning rate and for the arcsin-transformed triplet rate. This analysis shows a decreasing linear time trend in the triplet series for the period 1881-1950 but not in the twinning series. The triplet rate has an increasing trend after 1960, which seems to be mainly caused by artificial induction of ovulation., Hellin (1895) established empirically that the rates of different orders of higher multiple maternities occur in definite ratios. Thus, if the rate of twin maternities in a certain population is [...]