2015
DOI: 10.1007/s00240-015-0784-2
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Modeling the distribution of urolithiasis prevalence under projected climate change in Iran

Abstract: Although studies support a positive correlation between temperature and stone risk, the precise relationship between these factors has not been elucidated. We modeled the current distribution of urolithiasis prevalence in Iran using 26 bioclimatic, climatic and topographic variables based on two multivariate linear regression models in geographical information system. The impact of climate change on the stone prevalence was predicted under the projections of GFDL-ESM2G, CCSM4 and HadGEM2-ES climate models by m… Show more

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Cited by 15 publications
(5 citation statements)
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“…The northwest and west areas of Iran, which were much cooler than other regions, witnessed a higher prevalence of urolithiasis during 2007–2008 [58] . The reason for it may be related to a concept of temperature threshold value [60] . The prevalence rate may be higher in the areas where temperature just reaches the threshold (i.e., 18°C in Korea), compared with those under or exceeding it [61] .…”
Section: Risk Factorsmentioning
confidence: 99%
“…The northwest and west areas of Iran, which were much cooler than other regions, witnessed a higher prevalence of urolithiasis during 2007–2008 [58] . The reason for it may be related to a concept of temperature threshold value [60] . The prevalence rate may be higher in the areas where temperature just reaches the threshold (i.e., 18°C in Korea), compared with those under or exceeding it [61] .…”
Section: Risk Factorsmentioning
confidence: 99%
“…Some recent studies show changes in the distribution of urolithiasis disease over the few last years [ 5 , 10 ]. This study explored the incidence of urolithiasis in 204 countries during the last decades.…”
Section: Discussionmentioning
confidence: 99%
“…Also, urolithiasis is the reason for 4 to 8 percent of end-stage renal disease. Some recent studies show urolithiasis disease distribution changes over the last years [ 5 ]. Various factors have been proposed for this phenomenon.…”
Section: Introductionmentioning
confidence: 99%
“…Climatic data for 2050 and 2070 were derived from two atmospheric circulation models (ACMs): Community Climate System Model Version 4 (CCSM4; see Gent et al [69]) and Meteorological Research Institute CGCM Version 3 (MRI-CGCM3; see Yukimoto et al [70]). The CCSM4 is widely used for predicting climate change effects on fauna distribution in Iran, for example, [71][72][73][74]. The MRI-CGCM3 has also been suggested as one of the best models from 37 Coupled Model Intercomparison Project phase 5 (CMIP5) General Circulation Models (GCMs) of regional climate change projections in Iran [75].…”
Section: Environmental Datamentioning
confidence: 99%