Periodontal treatment needs in a native island community in Colombia determined with CPITN

Aims: To identify the prevalence and different degrees of periodontal disease in an isolated community (Isla Grande, Colombia) with no dental services and low educational level with the use of CPITN, and to establish periodontal treatment needs in different age groups. Results: Of 116 people examined, 0.9% were in periodontal health (CPITN value 0), 18.1% had gingival bleeding (CPITN value 1), 51.7% had supra or subgingival calculus (CPITN value 2),18.1% presented pockets 3.5-5.0mm deep (CPITN value 3), and 11.2% had pathological pockets of 5.5mm or deeper (CPITN value 4). No clear differences were observed between sexes. Conclusions: This study shows that 81% of the sample has some type of periodontal treatment need, with 69.8% of them requiring periodontal treatment that may be supplied by a hygienist and 11.2% requiring specialised treatment. Implementation of oral health education and oral prevention programmes was recommended to the authorities for this community.

Regional patterns of agricultural land use and deforestation in Colombia

An expanding human population and associated demands for goods and services continues to exert an increasing pressure on ecological systems. Although the rate of expansion of agricultural lands has slowed since 1960, rapid deforestation still occurs in many tropical countries, including Colombia. However, the location and extent of deforestation and associated ecological impacts within tropical countries is often not well known. The primary aim of this study was to obtain an understanding of the spatial patterns of forest conversion for agricultural land uses in Colombia. We modeled native forest conversion in Colombia at regional and national-levels using logistic regression and classification trees. We investigated the impact of ignoring the regional variability of model parameters, and identified biophysical and socioeconomic factors that best explain the current spatial pattern and inter-regional variation in forest cover. We validated our predictions for the Amazon region using MODIS satellite imagery. The regional-level classification tree that accounted for regional heterogeneity had the greatest discrimination ability. Factors related to accessibility (distance to roads and towns) were related to the presence of forest cover, although this relationship varied regionally. In order to identify areas with a high risk of deforestation, we used predictions from the best model, refined by areas with rural population growth rates of > 2%. We ranked forest ecosystem types in terms of levels of threat of conversion. Our results provide useful inputs to planning for biodiversity conservation in Colombia, by identifying areas and ecosystem types that are vulnerable to deforestation. Several of the predicted deforestation hotspots coincide with areas that are outstanding in terms of biodiversity value.