2 resultados para sudden infant death syndrome

em CentAUR: Central Archive University of Reading - UK


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Many time series are measured monthly, either as averages or totals, and such data often exhibit seasonal variability-the values of the series are consistently larger for some months of the year than for others. A typical series of this type is the number of deaths each month attributed to SIDS (Sudden Infant Death Syndrome). Seasonality can be modelled in a number of ways. This paper describes and discusses various methods for modelling seasonality in SIDS data, though much of the discussion is relevant to other seasonally varying data. There are two main approaches, either fitting a circular probability distribution to the data, or using regression-based techniques to model the mean seasonal behaviour. Both are discussed in this paper.

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This study compares the infant mortality profiles of 128 infants from two urban and two rural cemetery sites in medieval England. The aim of this paper is to assess the impact of urbanization and industrialization in terms of endogenous or exogenous causes of death. In order to undertake this analysis, two different methods of estimating gestational age from long bone lengths were used: a traditional regression method and a Bayesian method. The regression method tended to produce more marked peaks at 38 weeks, while the Bayesian method produced a broader range of ages and were more comparable with the expected "natural" mortality profiles. At all the sites, neonatal mortality (28-40 weeks) outweighed post-neonatal mortality (41-48 weeks) with rural Raunds Furnells in Northamptonshire, showing the highest number of neonatal deaths and post-medieval Spitalfields, London, showing a greater proportion of deaths due to exogenous or environmental factors. Of the four sites under study, Wharram Percy in Yorkshire showed the most convincing "natural" infant mortality profile, suggesting the inclusion of all births (i.e., stillbirths and unbaptised infants).