2 resultados para annual speed change
em Université de Lausanne, Switzerland
Resumo:
Molecular evidence suggests that levels of vitamin D are associated with kidney function loss. Still, population-based studies are limited and few have considered the potential confounding effect of baseline kidney function. This study evaluated the association of serum 25-hydroxyvitamin D with change in eGFR, rapid eGFR decline, and incidence of CKD and albuminuria. Baseline (2003-2006) and 5.5-year follow-up data from a Swiss adult general population were used to evaluate the association of serum 25-hydroxyvitamin D with change in eGFR, rapid eGFR decline (annual loss >3 ml/min per 1.73 m(2)), and incidence of CKD and albuminuria. Serum 25-hydroxyvitamin D was measured at baseline using liquid chromatography-tandem mass spectrometry. eGFR and albuminuria were collected at baseline and follow-up. Multivariate linear and logistic regression models were used considering potential confounding factors. Among the 4280 people included in the analysis, the mean±SD annual eGFR change was -0.57±1.78 ml/min per 1.73 m(2), and 287 (6.7%) participants presented rapid eGFR decline. Before adjustment for baseline eGFR, baseline 25-hydroxyvitamin D level was associated with both mean annual eGFR change and risk of rapid eGFR decline, independently of baseline albuminuria. Once adjusted for baseline eGFR, associations were no longer significant. For every 10 ng/ml higher baseline 25-hydroxyvitamin D, the adjusted mean annual eGFR change was -0.005 ml/min per 1.73 m(2) (95% confidence interval, -0.063 to 0.053; P=0.87) and the risk of rapid eGFR decline was null (odds ratio, 0.93; 95% confidence interval, 0.79 to 1.08; P=0.33). Baseline 25-hydroxyvitamin D level was not associated with incidence of CKD or albuminuria. The association of 25-hydroxyvitamin D with eGFR decline is confounded by baseline eGFR. Sufficient 25-hydroxyvitamin D levels do not seem to protect from eGFR decline independently from baseline eGFR.
Resumo:
Mountain regions worldwide are particularly sensitive to on-going climate change. Specifically in the Alps in Switzerland, the temperature has increased twice as fast than in the rest of the Northern hemisphere. Water temperature closely follows the annual air temperature cycle, severely impacting streams and freshwater ecosystems. In the last 20 years, brown trout (Salmo trutta L) catch has declined by approximately 40-50% in many rivers in Switzerland. Increasing water temperature has been suggested as one of the most likely cause of this decline. Temperature has a direct effect on trout population dynamics through developmental and disease control but can also indirectly impact dynamics via food-web interactions such as resource availability. We developed a spatially explicit modelling framework that allows spatial and temporal projections of trout biomass using the Aare river catchment as a model system, in order to assess the spatial and seasonal patterns of trout biomass variation. Given that biomass has a seasonal variation depending on trout life history stage, we developed seasonal biomass variation models for three periods of the year (Autumn-Winter, Spring and Summer). Because stream water temperature is a critical parameter for brown trout development, we first calibrated a model to predict water temperature as a function of air temperature to be able to further apply climate change scenarios. We then built a model of trout biomass variation by linking water temperature to trout biomass measurements collected by electro-fishing in 21 stations from 2009 to 2011. The different modelling components of our framework had overall a good predictive ability and we could show a seasonal effect of water temperature affecting trout biomass variation. Our statistical framework uses a minimum set of input variables that make it easily transferable to other study areas or fish species but could be improved by including effects of the biotic environment and the evolution of demographical parameters over time. However, our framework still remains informative to spatially highlight where potential changes of water temperature could affect trout biomass. (C) 2015 Elsevier B.V. All rights reserved.-