Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees : the PredictAL study

Background: Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. Methods: A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score >= 8 in men and >= 5 in women. Results: 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). Conclusions: The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.

Comparação entre sistemas de saúde oral de 8 países da união europeia e intervenções por estes desenvolvidas no seguimento das linhas de atuação definidas pela Organização Mundial de Saúde para o ano 2020

RESUMO - Hoje, facilmente se poderá constatar que as doenças orais possuem uma expressiva influência perante a saúde geral, não apenas pela presença da condição por si só, mas também a nível pessoal, social e económico. O seu reflexo traduz-se em parte, no absentismo escolar e laboral, diminuição considerável de produtividade e eficiência, falta de atenção e objetividade. Pelo que é então considerado, um grave problema de saúde pública, afetando de forma mais expressiva, grupos socioeconomicamente desfavorecidos. O acompanhamento e análise do desenvolvimento de iniciativas internacionais, no que ao seguimento das recomendações da Organização Mundial de Saúde diz respeito, poderá ser um ótimo beneficio e impulso para a identificação e aplicação de novos planos de ação. O presente projeto, pretendeu contribuir para a identificação de duas propostas de intervenção em saúde oral ajustadas ao alcance das recomendações da OMS que simultaneamente possam sejam proveitosas para a resolução dos problemas de saúde oral nacionais. Foi realizado um estudo observacional, descritivo e retrospetivo onde foram recolhidos dados acerca de 8 Sistemas de Saúde Oral europeus, previamente selecionados segundo critérios específicos, e iniciativas de saúde oral por eles desenvolvidas. Por fim, foram eleitas duas iniciativas de interesse, possíveis de aplicação futura. Os resultados do estudo apontam para a existência de diferentes iniciativas, enquadradas com as recomendações da OMS. De entre as mesmas, destaca-se uma implementada em 2009, na Suécia, que estando essencialmente assente num acessível subsidio anual fixo pago por cada indivíduo adulto, procura fundamentalmente preservar os esforços de prevenção aplicados nas últimas décadas.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.