RESUMO
There is increasing evidence from across the globe that climate change results in changes in the frequency, location, and impact of natural hazards. Much of this evidence is conceptual, inferential, or simply assumed. To provide objective support to confirm these hypotheses, we constructed county-level time-series datasets (2000-2019) for nine natural hazards for the entire United States. Hazards considered for this study included hurricanes, tropical storms, landslides, wildfires, earthquakes, drought, inland flooding, coastal flooding, and tornadoes. Geospatial analysis techniques were used to calculate the percentage (range: 0-100) of land area in each county exposed to each natural hazard for all the years that hazard data were available. The best available data were acquired from publicly accessible sources. Cumulative distribution functions were calculated for each hazard in five-year intervals to test for statistically significant changes in distribution patterns across the five-year time periods using the Kolmogorov-Smirnov test. There were significant changes in hurricanes, tropical storms, and drought over the two decades; changes in tornadoes, landslides, and wildfires were not significant in terms of frequency, likely due to the site-specific nature of their occurrences. The intensity and spatial distribution and an emerging hot spot and spatial trend analyses and an emerging hot spot and spatial trend analyses were also completed (except for flooding events and earthquakes due to insufficient data). All datasets provide empirical support for earlier inferences concerning the connections between the hazards and climate change. Analyses showed apparent changes in the frequency and intensity of hurricanes, tropical storms, and drought-related to climate change factors. Internal and coastal flooding also demonstrated these connections, although the length of the dataset did not permit significant testing but shows significant hot spots and trending locations. Tornadoes, landslides, and wildfires showed significant hot spots and trending locations, but the specific locational nature of the data did not show significant changes in frequency. Earthquakes showed no significant changes over the time period.
RESUMO
The aim of this investigation was to study the influence of genetic polymorphisms of biotransformation enzymes and dopamine receptors on neurobehavioral effects in referents (n = 53), solvent-workers (n = 144), and chronic toxic encephalopathy (CTE) patients (n = 33). All participants were interviewed for exposure data and confounding factors and underwent a clinical examination. Neurobehavioral complaints (neurotoxicity symptom checklist-60) and effects [simple reaction time (SRT), symbol digit substitution (SDS), hand-eye coordination (HEC), and digit span backwards (DSB)] were evaluated with a computer assisted test battery. The following genotypes were determined: GSTM1, GSTT1, GSTP1, DRD2 Taq1A, DRD2 Taq1B, and DRD2-141Cdel. Neurotoxic effects and complaints were significantly higher in CTE patients and were related to both duration and level of exposure. An equal distribution of genotypes was found between all groups. Logistic regression analysis revealed that GSTT1 was negatively associated with sleep and sensorimotor complaints. GSTM1 had a protecting influence on the relationship between logDSB and the cumulative exposure index and between logSRT and cumulative exposure index and degree of exposure, respectively. This effect was also found when correcting for age, education level, alcohol consumption, and smoking. DRD2-141Cdel polymorphisms had a negative influence on the relationship between logSDS and the total exposure time. GSTT1 might be protective against sleep and sensorimotor complaints, whereas GSTM1 seems to decrease sustained attention and short-term memory problems in relation to solvent exposure. Individuals possessing DRD2-141Cdel variant experienced more visuomotor problems.
