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.

Audit of selective and non-selective non-steroidal anti-inflammatory drug use in rural general practice

Aim: To identify the demographics and risk factors in a selected patient population prescribed non-selective and cyclo-oxygenase-2 (COX- 2) selective non-steroidal anti-inflammatory drugs (NSAIDs). Method: A structured clinical self-audit form was distributed in January to March 2001 to 155 interested general practitioners (GPs) in rural Queensland. Results: Seventy one GPs participated in the audit and contributed 1417 patient records - 790 patients had received nonselective NSAIDs and 627 had received COX-2 inhibitors (celecoxib or rofecoxib). Patients who received COX-2 inhibitors were significantly older, more likely to have clinically important concomitant illness, and more likely to be taking medication known to interact with NSAIDs. They were also twice as likely to have two or more risk factors for adverse effects. The most common reasons for switching from an NSAID to a COX-2 inhibitor were reported to be a previous side effect from an NSAID (primarily related to gastrointestinal effects) or the doctor's perception of the superior efficacy of COX-2 inhibitor therapy. Conclusions: This study has shown that COX-2 inhibitors were used in a distinctly different patient population compared to non-selective NSAIDs. There were significant variations in the demographics and number of risk factors - for example, cardiovascular and renal - between the two identified populations. These differences may be due to doctors selecting COX-2 inhibitors for patients at high risk of gastrointestinal complications. However, the prescribing pattern may also be partly due to misconceptions about the relative safety and efficacy of COX-2 inhibitor drugs.

Family average income and body mass index above the healthy weight range among urban and rural residents in regional Mainland China

Objective: To explore the relationship between family average income (FAI; an index of socio-economic status) and body mass index (BMI; a widely used, inexpensive indicator of weight status) above the healthy weight range in a region of Mainland China. Design: Population-based cross-sectional study, conducted between October 1999 and March 2000 on a sample of regular local residents aged 35 years or older who were selected by random cluster sampling. Setting: Forty-five administrative villages selected from three urban districts and two rural counties of Nanjing municipality, Mainland China, with a regional population of 5.6 million. Subjects: In total, 29 340 subjects participated; 67.7% from urban and 32.3% from rural areas; 49.8% male and 50.2% female. The response rate among eligible participants was 90.1%. Results: The proportion of participants classified as overweight was 30.5%, while 7.8% were identified as obese. After adjusting for possible confounding variables (age, gender, area of residence, educational level, occupational and leisure-time physical activity, daily vegetable consumption and frequency of red meat intake), urban participants were more likely to be overweight or obese relative to their rural counterparts, more women than men were obese, and participants in the lowest FAI tertile were the least likely to be above the healthy weight range. Conclusions: The proportion of adults with BMI above the healthy weight range was positively related to having a higher socio-economic status (indexed by FAI) in a regional Chinese population.

Violence against young Australian women and association with reproductive events: a cross-sectional analysis of a national population sample

Objective: This study aimed to investigate associations between violence and younger women's reproductive events using Survey 1 (1996) data of the Younger cohort of the Australian Longitudinal Study of Women's Health (ALSWH). Methods: Multinomial regression, using composite variables for both violence and reproductive events, adjusting for socioeconomic variables and weighted for rural and remote areas. Results: 23.8% of 14,784 women aged 18 to 23 years reported violence; 12.6% reported non-partner violence in the previous year; and 11.2% reported ever having had a violent relationship with a partner. Of the latter group, 43% (4.8% overall) also reported violence in the past year. Compared with women reporting no violence, women reporting partner but not recent violence (OR 2.55, 95% Cl 2.10-3.09) or partner and recent violence (OR 3.96, 95% Cl 3.18-4.93) were significantly more likely to have had one or more pregnancies. Conversely, having had a pregnancy (2,561) was associated with an 80% increase in prevalence of any violence and a 230% increase in partner violence. Among women who had a pregnancy, having had a miscarriage or termination was associated with violence. Partner and recent violence is strongly associated with having had a miscarriage, whether alone (OR = 2.85, 95% Cl 1.74-4.66), with a termination (OR = 4.60, 2.26-9.35), or with birth, miscarriage and a termination (OR 4.12, 1.89-9.00). Conclusions and implications: Violence among young women of childbearing age is a factor for which doctors should be vigilant, well-trained and supported to identify and manage effectively.

Mental health literacy in rural Queensland: results of a community survey

Objectives: The aim of this study was to assess the awareness of, and attitudes to, mental health issues in rural dwelling Queensland residents. A secondary objective was to provide baseline data of mental health literacy prior to the implementation of Australian Integrated Mental Health Initiative - a health promotion strategy aimed at improving the health outcomes of people with chronic or recurring mental disorders. Method: In 2004 a random sample of 2% (2132) of the estimated adult population in each of eight towns in rural Queensland was sent a postal survey and invited to participate in the project. A series of questions were asked based on a vignette describing a person suffering major depression. In addition, questions assessed respondents' awareness and perceptions of community mental health agencies. Results: Approximately one-third (36%) of those surveyed completed and returned the questionnaire. While a higher proportion of respondents (81%) correctly identified and labelled the problem in the vignette as depression than previously reported in Australian community surveys, the majority of respondents (66%) underestimated the prevalence of mental health problems in the community. Furthermore, a substantial number of respondents (37%) were unaware of agencies in their community to assist people with mental health issues while a majority of respondents (57.6%) considered that the services offered by those agencies were poor. Conclusion: While mental health literacy in rural Queensland appears to be comparable to other Australian regions, several gaps in knowledge were identified. This is in spite of recent widespread coverage of depression in the media and thus, there is a continuing need for mental health education in rural Queensland.

Testing alternative models for the conservation of koalas in fragmented rural-urban landscapes

Predicting the various responses of different species to changes in landscape structure is a formidable challenge to landscape ecology. Based on expert knowledge and landscape ecological theory, we develop five competing a priori models for predicting the presence/absence of the Koala (Phascolarctos cinereus) in Noosa Shire, south-east Queensland (Australia). A priori predictions were nested within three levels of ecological organization: in situ (site level) habitat (< 1 ha), patch level (100 ha) and landscape level (100-1000 ha). To test the models, Koala surveys and habitat surveys (n = 245) were conducted across the habitat mosaic. After taking into account tree species preferences, the patch and landscape context, and the neighbourhood effect of adjacent present sites, we applied logistic regression and hierarchical partitioning analyses to rank the alternative models and the explanatory variables. The strongest support was for a multilevel model, with Koala presence best predicted by the proportion of the landscape occupied by high quality habitat, the neighbourhood effect, the mean nearest neighbour distance between forest patches, the density of forest patches and the density of sealed roads. When tested against independent data (n = 105) using a receiver operator characteristic curve, the multilevel model performed moderately well. The study is consistent with recent assertions that habitat loss is the major driver of population decline, however, landscape configuration and roads have an important effect that needs to be incorporated into Koala conservation strategies.