RESUMEN
Recent wildfire events (e.g. Mediterranean region, USA, and Australia) showed that this hazard poses a serious threat for wildland-urban interface (WUI) areas around the globe. Furthermore, recent events in regions where wildfire does not constitute a frequent hazard (e.g. Siberia, Scandinavia) indicated that the spatial pattern of wildfire risk might have significantly changed. To prepare for upcoming extreme events, it is critical for decision-makers to have a thorough understanding of the vulnerability of the built environment to wildfire. Building quality and design standards are important not only because building loss is costly but also because robust buildings may offer shelter when evacuation is not possible. However, studies aiming at the analysis of wildfire vulnerability for the built environment are limited. This paper presents an innovative solution for the vulnerability assessment to wildfires, making use of an all-relevant feature selection algorithm established on statistical relationships to develop a physical vulnerability index for buildings subject to wildfire. Data from a recent and systematically documented wildfire event in Greece (Mati, 2018) are used to select and weight the relevant indicators using a permutation-based automated feature selection based on random forests. Building characteristics including the structural type, the roof type, material and shape, the inclination of the ground, the surrounding vegetation, the material of the shutters and the ground covering were selected and formed into the index. The index may be used in other places in Europe and beyond, especially where no empirical data are available supporting decision-making and risk reduction of an emerging hazard amplified by climate change.
Asunto(s)
Incendios , Incendios Forestales , Algoritmos , Cambio Climático , Conservación de los Recursos Naturales , ViviendaRESUMEN
BACKGROUND/OBJECTIVES: In small studies, a thrifty human phenotype, defined by a greater 24-hour energy expenditure (EE) decrease with fasting, is associated with less weight loss during caloric restriction. In rodents, models of diet-induced obesity often have a phenotype including a reduced EE and decreased core body temperature. We assessed whether a thrifty human phenotype associates with differences in core body temperature or body composition. SUBJECTS/METHODS: Data for this cross-sectional analysis were obtained from 77 individuals participating in one of two normal physiology studies while housed on our clinical research unit. Twenty-four-hour EE using a whole-room indirect calorimeter and 24-h core body temperature were measured during 24 h each of fasting and 200% overfeeding with a diet consisting of 50% carbohydrates, 20% protein and 30% fat. Body composition was measured by dual X-ray absorptiometry. To account for the effects of body size on EE, changes in EE were expressed as a percentage change from 24-hour EE (%EE) during energy balance. RESULTS: A greater %EE decrease with fasting correlated with a smaller %EE increase with overfeeding (r=0.27, P=0.02). The %EE decrease with fasting was associated with both fat mass and abdominal fat mass, even after accounting for covariates (ß=-0.16 (95% CI: -0.26, -0.06) %EE per kg fat mass, P=0.003; ß=-0.0004 (-0.0007, -0.00004) %EE kg(-1) abdominal fat mass, P=0.03). In men, a greater %EE decrease in response to fasting was associated with a lower 24- h core body temperature, even after adjusting for covariates (ß=1.43 (0.72, 2.15) %EE per 0.1 °C, P=0.0003). CONCLUSIONS: Thrifty individuals, as defined by a larger EE decrease with fasting, were more likely to have greater overall and abdominal adiposity as well as lower core body temperature consistent with a more efficient metabolism.
Asunto(s)
Adiposidad/fisiología , Composición Corporal/fisiología , Temperatura Corporal/fisiología , Metabolismo Energético/fisiología , Fenotipo , Absorciometría de Fotón , Tejido Adiposo , Adulto , Arizona , Restricción Calórica , Estudios Transversales , Ayuno/fisiología , Femenino , Humanos , Masculino , Reproducibilidad de los Resultados , TermogénesisRESUMEN
UNLABELLED: In this study, we compare the extent to which seven available definitions of sarcopenia and two related definitions predict the rate of falling. Our results suggest that the definitions of Baumgartner and Cruz-Jentoft best predict the rate of falls among sarcopenic versus non-sarcopenic community-dwelling seniors. INTRODUCTION: The purpose of the study is to compare the extent to which seven available definitions of sarcopenia and two related definitions predict the prospective rate of falling. METHODS: We studied a cohort of 445 seniors (mean age 71 years, 45 % men) living in the community who were followed with a detailed fall assessment for 3 years. For comparing the rate of falls in sarcopenic versus non-sarcopenic individuals, we used multivariate Poisson regression analyses adjusting for gender and treatment (original intervention tested vitamin D plus calcium against placebo). Of the seven available definitions, three were based on low lean mass alone (Baumgartner, Delmonico 1 and 2) and four required both low muscle mass and decreased performance in a functional test (Fielding, Cruz-Jentoft, Morley, Muscaritoli). The two related definitions were based on low lean mass alone (Studenski 1) and low lean mass contributing to weakness (Studenski 2). RESULTS: Among 445 participants, 231 fell, sustaining 514 falls over the 3-year follow-up. The prospective rate of falls in sarcopenic versus non-sarcopenic individuals was best predicted by the Baumgartner definition based on low lean mass alone (RR = 1.54; 95 % CI 1.09-2.18) with 11 % prevalence of sarcopenia and the Cruz-Jentoft definition based on low lean mass plus decreased functional performance (RR = 1.82; 95 % CI 1.24-2.69) with 7.1 % prevalence of sarcopenia. Consistently, fall rate was non-significantly higher in sarcopenic versus non-sarcopenic individuals based on the definitions of Delmonico 1, Fielding, and Morley. CONCLUSION: Among the definitions investigated, the Baumgartner definition and the Cruz-Jentoft definition had the highest validity for predicting the rate of falls.