Kvinnlig Könsstympning : Litteraturstudie om praktisk handläggning och komplikationsrisker vid förlossning

Today around 28 000 women originally from countries where FGM is practised, are living in Sweden. Many of them are at childbearing age which means that knowledge about FGM and its consequences is of outmost importance during delivery. The aim of this study is to describe current research on how to manage the delivery, regarding deinfibulation and the following stitching as well as the risk of complications when the labouring woman is mutilated. This review of literature is based on 12 scientific articles published between years 1989 – 2005. Five different databases have been searched with use of a large number of keywords.The review found that no scientific research has been carried out that describes how deinfibulation and following stitching should be managed when the woman is mutilated. All available articles within this area are referring to best practice only. The review also found that the conclusions of the studies are contradictory. The majority, however, show an increased frequency for prolonged labour that could be related to FGM. The three largest studies also show an increased rate of caesarean section among mutilated women. In the few studies that examine haemorrhage, the majorities show an increased tendency to bleed, that could be related to FGM. Several articles emphasize the importance of good routines for deinfibulation to reduce the risk for complications.In summary it can be established that due to methodological problems in many studies, no reliable conclusion can be made that the researched complications exists to a greater extent when the woman is mutilated

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.