Dideriksenstensgaard7694

for a simpler interpretation. Reduced GLS was defined as  less then  18%, and normal GLS was defined as ≥ 18%. Of 690 study subjects (mean age, 58 years and females, 51.2%), 208 (30.1%) had reduced GLS. Subjects with reduced GLS were more frequently male, and had more cardiovascular risk factors than those with normal GLS. In multivariable binary logistic regression analysis, male sex (odds ratio [OR] 3.02; 95% confidence interval [CI] 2.02‒4.50; P  less then  0.001), hypertension (OR 1.52; 95% CI 1.02‒2.28; P = 0.043) and cigarette smoking (OR 1.80; 95% CI 1.14‒2.85; P = 0.012) were independently associated with reduced GLS. The greater the number of these 3 risk factors (male sex, hypertension and cigarette smoking), the higher the probability of having reduced GLS (P  less then  0.001). In subjects without overt cardiovascular disease who had normal LVEF, a relevant proportion (30.1%) of subjects had reduced GLS. Male sex, hypertension and cigarette smoking were independently associated with reduced GLS. GLS measurement should be emphasized for subjects with these clinical characteristics.Nowadays, academics have paid special attention to global warming, because it has several issues such as urban heat island (UHI) related to the quality of life. For this purpose, a spatial decision support system (SDSS) has been developed to investigate the effect of parcels' roof covering type on surface heat island (SHI) values and its variation at the neighborhood scale in Tehran, Iran. This SDSS, as the innovation of the present research, consists of two main steps including estimating the UHI value in the study area and adopting the optimum set of parcels to change their roofs' cover with three types of vegetation, high-albedo material, and flagstone. The first step is accomplished by aggregating various indices related to land cover obtained from Landsat 8 images. The aggregation is done by linear regression method (LRM) with an RMSE and R2 equal to 0.942 and 0.897, respectively. Then, the genetic algorithm was used to select the optimal subset, including 10% of the parcels in the area, to change their roof covering type based on minimizing the UHI's variation. The standard deviation obtained after the changes improved from 13.222 to 10.781 °C. The results indicate that to control UHI in the center of the region, it is necessary to inhibit UHI effects at the boundary of the study area with vegetation roof covering since flagstone and high-albedo materials have local effects on controlling the UHI effects.