2 resultados para Logistic regression model
em Publishing Network for Geoscientific
Resumo:
Interannual environmental variability in Peru is dominated by the El Niño Southern Oscillation (ENSO). The most dramatic changes are associated with the warm El Niño (EN) phase (opposite the cold La Niña phase), which disrupts the normal coastal upwelling and affects the dynamics of many coastal marine and terrestrial resources. This study presents a trophic model for Sechura Bay, located at the northern extension of the Peruvian upwelling system, where ENSO-induced environmental variability is most extreme. Using an initial steady-state model for the year 1996, we explore the dynamics of the ecosystem through the year 2003 (including the strong EN of 1997/98 and the weaker EN of 2002/03). Based on support from literature, we force biomass of several non-trophically-mediated 'drivers' (e.g. Scallops, Benthic detritivores, Octopus, and Littoral fish) to observe whether the fit between historical and simulated changes (by the trophic model) is improved. The results indicate that the Sechura Bay Ecosystem is a relatively inefficient system from a community energetics point of view, likely due to the periodic perturbations of ENSO. A combination of high system productivity and low trophic level target species of invertebrates (i.e. scallops) and fish (i.e. anchoveta) results in high catches and an efficient fishery. The importance of environmental drivers is suggested, given the relatively small improvements in the fit of the simulation with the addition of trophic drivers on remaining functional groups' dynamics. An additional multivariate regression model is presented for the scallop Argopecten purpuratus, which demonstrates a significant correlation between both spawning stock size and riverine discharge-mediated mortality on catch levels. These results are discussed in the context of the appropriateness of trophodynamic modeling in relatively open systems, and how management strategies may be focused given the highly environmentally influenced marine resources of the region.
Resumo:
This cross-sectional study was conducted in southern Minas Gerais, in two counties: São Gonçalo do Sapucaí and Silvianópolis. Presented as objective to verify the important variables associated with the occurrence of symptoms of subacute intoxication related to pesticides exposure. A questionnaire was dedicated to a sample of 412 workers. An analysis of non-conditional logistic regression was applied gradually. The likelihood ratio method was used to define the significant variables in the final model. Of the analysed population, 59.2% reported symptoms typical of subacute intoxication. Of the respondents, 91.5% reported knowing the deleterious effects associated with exposure to pesticides. The adjusted model was found with the significant variables: being male that presented Prevalence Odds Ratio (POR) adjusted . PORof 0.54 (95% CI 0.36 to 0.81), already hospitalized for poisoning with pesticides, POR of 3.26 (95% CI 1.08 to 9.82), living in the rural area of residence., POR of 2.17 (95% CI 1.20 to 3.93) and type of employment relationship or temporary employment, POR of 2.32 (95% CI 1.08 to 4.95).