2 resultados para Evolutionary clustering

em Research Open Access Repository of the University of East London.


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Over the last three decades, the application of evolutionary theory to the human sciences has shown remarkable growth. This growth has also been characterised by a ‘splitting’ process, with the emergence of distinct sub-disciplines, most notably: Human Behavioural Ecology (HBE), Evolutionary Psychology (EP) and studies of Cultural Evolution (CE). Multiple applications of evolutionary ideas to the human sciences are undoubtedly a good thing, demonstrating the usefulness of this approach to human affairs. However, this fracture has been associated with considerable tension, a lack of integration, and sometimes outright conflict between researchers. In recent years however, there have been clear signs of hope that a synthesis of the human evolutionary behavioural sciences is underway. Here, we briefly review the history of the debate, both its theoretical and practical causes; then provide evidence that the field is currently becoming more integrated, as the traditional boundaries between sub-disciplines become blurred. This article constitutes the first paper under the new editorship of the Journal of Evolutionary Psychology, which aims to further this integration by explicitly providing a forum for integrated work.

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Background Clustering of lifestyle risk behaviours is very important in predicting premature mortality. Understanding the extent to which risk behaviours are clustered in deprived communities is vital to most effectively target public health interventions. Methods We examined co-occurrence and associations between risk behaviours (smoking, alcohol consumption, poor diet, low physical activity and high sedentary time) reported by adults living in deprived London neighbourhoods. Associations between sociodemographic characteristics and clustered risk behaviours were examined. Latent class analysis was used to identify underlying clustering of behaviours. Results Over 90% of respondents reported at least one risk behaviour. Reporting specific risk behaviours predicted reporting of further risk behaviours. Latent class analyses revealed four underlying classes. Membership of a maximal risk behaviour class was more likely for young, white males who were unable to work. Conclusions Compared with recent national level analysis, there was a weaker relationship between education and clustering of behaviours and a very high prevalence of clustering of risk behaviours in those unable to work. Young, white men who report difficulty managing on income were at high risk of reporting multiple risk behaviours. These groups may be an important target for interventions to reduce premature mortality caused by multiple risk behaviours.