Flood Risk Assessment in Coastal Drainage Basins through a Multivariate Analysis within a GIS-Based Model

This paper presents a GIS-based multicriteria flood risk assessment and mapping approach applied to coastal drainage basins where hydrological data are not available. It involves risk to different types of possible processes: coastal inundation (storm surge), river, estuarine and flash flood, either at urban or natural areas, and fords. Based on the causes of these processes, several environmental indicators were taken to build-up the risk assessment. Geoindicators include geological-geomorphologic proprieties of Quaternary sedimentary units, water table, drainage basin morphometry, coastal dynamics, beach morphodynamics and microclimatic characteristics. Bioindicators involve coastal plain and low slope native vegetation categories and two alteration states. Anthropogenic indicators encompass land use categories properties such as: type, occupation density, urban structure type and occupation consolidation degree. The selected indicators were stored within an expert Geoenvironmental Information System developed for the State of Sao Paulo Coastal Zone (SIIGAL), which attributes were mathematically classified through deterministic approaches, in order to estimate natural susceptibilities (Sn), human-induced susceptibilities (Sa), return period of rain events (Ri), potential damages (Dp) and the risk classification (R), according to the equation R=(Sn.Sa.Ri).Dp. Thematic maps were automatically processed within the SIIGAL, in which automata cells (""geoenvironmental management units"") aggregating geological-geomorphologic and land use/native vegetation categories were the units of classification. The method has been applied to the Northern Littoral of the State of Sao Paulo (Brazil) in 32 small drainage basins, demonstrating to be very useful for coastal zone public politics, civil defense programs and flood management.

Risk factors for dengue virus infection in rural Amazonia: Population-based cross-sectional surveys

A comparison of dengue virus (DENV) antibody levels in paired serum samples collected from predominantly DENV-naive residents in an agricultural settlement in Brazilian Amazonia (baseline seroprevalence, 18.3%) showed a seroconversion rate of 3.67 episodes/100 person-years at risk during 12 months of follow-up. Multivariate analysis identified male sex, poverty, and migration from extra-Amazonian states as significant predictors of baseline DENY seropositivity, whereas male sex, a history of clinical diagnosis of dengue fever, and travel to an urban area predicted subsequent seroconversion. The laboratory surveillance of acute febrile illnesses implemented at the study site and in a nearby town between 2004 and 2006 confirmed 11. DENV infections among 102 episodes studied with DENV IgM detection, reverse transcriptase-polymerise chain reaction, and virus isolation; DENV-3 was isolated. Because DENV exposure is associated with migration or travel, personal protection measures when visiting high-risk urban areas may reduce the incidence of DENV infection in this rural population.

Pooled analysis of recent studies on magnetic fields and childhood leukaemia

BACKGROUND: Previous pooled analyses have reported an association between magnetic fields and childhood leukaemia. We present a pooled analysis based on primary data from studies on residential magnetic fields and childhood leukaemia published after 2000. METHODS: Seven studies with a total of 10 865 cases and 12 853 controls were included. The main analysis focused on 24-h magnetic field measurements or calculated fields in residences. RESULTS: In the combined results, risk increased with increase in exposure, but the estimates were imprecise. The odds ratios for exposure categories of 0.1-0.2 mu T, 0.2-0.3 mu T and >= 0.3 mu T, compared with <0.1 mu T, were 1.07 (95% Cl 0.81-1.41), 1.16 (0.69-1.93) and 1.44 (0.88-2.36), respectively. Without the most influential study from Brazil, the odds ratios increased somewhat. An increasing trend was also suggested by a nonparametric analysis conducted using a generalised additive model. CONCLUSIONS: Our results are in line with previous pooled analyses showing an association between magnetic fields and childhood leukaemia. Overall, the association is weaker in the most recently conducted studies, but these studies are small and lack methodological improvements needed to resolve the apparent association. We conclude that recent studies on magnetic fields and childhood leukaemia do not alter the previous assessment that magnetic fields are possibly carcinogenic. British Journal of Cancer (2010) 103, 1128-1135. doi: 10.1038/sj.bjc.6605838 www.bjcancer.com (c) 2010 Cancer Research UK

Electronegative Low-Density Lipoprotein is Associated with Dense Low-Density Lipoprotein in Subjects with Different Levels of Cardiovascular Risk

Dyslipidemias and physicochemical changes in low-density lipoprotein (LDL) are very important factors for the development of coronary artery disease (CAD). However, pathophysiological properties of electronegative low-density lipoprotein [LDL(-)] remain a controversial issue. Our objective was to investigate LDL(-) content in LDL and its subfractions (phenotypes A and B) of subjects with different cardiovascular risk. Seventy-three subjects were randomized into three groups: normolipidemic (N; n = 30) and hypercholesterolemic (HC; n = 33) subjects and patients with CAD (n = 10). After fasting, blood samples were collected and total, dense and light LDL were isolated. LDL(-) content in total LDL and its subfractions was determined by ELISA. LDL(-) content in total LDL was lower in the N group as compared to the HC (P < 0.001) and CAD (P = 0.006) groups. In the total sample and in those of the N, HC, and CAD groups, LDL(-) content in dense LDL was higher than in light LDL (P = 0.001, 0.001, 0.001, and 0.033, respectively) The impact of LDL(-) on cardiovascular risk was reinforced when LDL(-) content in LDL showed itself to have a positive association with total cholesterol (beta = 0.003; P < 0.001), LDL-C (beta = 0.003; p < 0.001), and non-HDL-C (beta = 0.003; P < 0.001) and a negative association with HDL-C (beta = -0.32; P = 0.04). Therefore, LDL(-) is an important biomarker that showed association with the lipid profile and the level of cardiovascular risk.