Abstract: Many studies have suggested that socio-economic factors are strong modifiers of human vulnerability to air pollution effects. Most of these studies were performed in developed countries, specifically in the US and Europe. Only a few studies have been performed in developing countries, and analyzed small regions (city level) with no spatial disaggregation. The aim of this study was to assess the association between vehicle emissions and cardiorespiratory disease risk in Brazil and its modification by spatial clustering of socio-economic conditions. We used a quantile regression model to estimate the risk and a geostatistical approach (K means) to execute spatial cluster analysis. We performed the risk analysis in three stages. First, we analyzed the entire study area (primary analysis), and then we conducted a spatial cluster analysis based on various municipal-level socio-economic factors, followed by a sensitivity analysis. We studied 5444 municipalities in Brazil between 2008 and 2012. Our findings showed a significant association between cardiorespiratory disease risk and vehicular emissions. We found that a 15% increase in air pollution is associated with a 6% increase in hospital admissions rates. The results from the spatial cluster analysis revealed two groups of municipalities with distinct sets of socio-economic factors and risk levels of cardiorespiratory disease related to exposure to vehicular emissions. For example, for vehicle emissions of PM in 2008, we found a relative risk of 4.18 (95% CI: 3.66, 4.93) in the primary analysis; in Group 1, the risk was 0.98 (95% CI: 0.10, 2.05) while in Group 2, the risk was 5.56 (95% CI: 4.46, 6.25). The risk in Group 2 was 480% higher than the risk in Group 1, and 35% higher than the risk in the primary analysis. Group 1 had higher values (3rd quartile) for urbanization rate, highway density, and GDP; very high values (>/=3rd quartile) for population density; median values for distance from the capital; and lower values (1st quartile) for rural population density. Group 2 had lower values (1st quartile) urbanization rate; median values for highway density, GDP, and population density; between median and third quartile values for distance from the capital; and higher values (3rd quartile) for rural population density. Our findings suggest that socio-economic factors are important modifiers of the human risk of cardiorespiratory disease due to exposure to vehicle emissions in Brazil. Our study provides support for creating effective public policies related to environmental health that are targeted to high-risk populations.

Abstract: PURPOSE: Recent studies have focused on surgeons' nontechnical skills in the operating room (OR), especially leadership. In an attempt to identify trainee preferences, we explored junior residents' opinions about the OR leadership style of teaching faculty. METHODS: Overall, 20 interns and 20 mid-level residents completed a previously validated survey on the style of leadership they encountered, the style they preferred to receive, and the style they personally employed in the OR. In all, 4 styles were explored; authoritative: leader makes decisions and communicates them firmly; explanatory: leader makes decisions promptly, but explains them fully; consultative: leader consults with trainees when important decisions are made, and delegative: leader puts the problem before the group and makes decisions by majority opinion. Comparisons were completed using chi-square analysis. RESULTS: Junior resident preference for leadership style of attending surgeons in the OR differed from what they encountered. Overall, 62% of residents encountered an authoritative leadership style; however, only 9% preferred this (p < 0.001). Instead, residents preferred explanatory (53%) or consultative styles (41%). Preferences differed by postgraduate year. Although 40% of interns preferred a consultative style, 50% of mid-level residents preferred explanatory leadership. CONCLUSIONS: Junior resident preference of leadership style in the OR differs from what they actually encounter. This has the potential to create unwanted tension and may erode team performance. Awareness of this difference provides an opportunity for an educational intervention directed at both attendings and trainees.

Abstract: Empirical models describe soil-plant transfers to explain the variations in the occurrence of potentially toxic elements (PTE) in soils and to estimate the Bioconcentration Factor (BCF). In this study, results were selected based on data in the literature on soils of humid tropical and temperate regions to evaluate soil-plant transfer models, to calculate the BCF and to derive risk concentrations of Cu, Cr, Pb, Ni and Zn present in the exposure pathway leading to the consumption of contaminated vegetables. The Cetesb (Environmental Agency of the State of Sao Paulo, Brazil) mathematical model was used to derive the risk posed by soil concentrations in urban and rural exposure scenarios. The results of the pseudo total contents of PTE in the soil and the contents absorbed by plants were compared and the BCFs were calculated by the use of geometric means, including a correction factor appropriate to each particular type of soil. Differences were observed between BCFs calculated for each climate region: humid tropical (HTR) and temperate (TE), which the first one presented the highest values to BCF in leaves and the lowest BCF values for root, except Ni, compared to second one. The soil concentrations with the highest risk were found in humid tropical regions as compared with those found in temperate regions, except for Ni. The obtained BCFs may contribute to any future revisions of guideline values as well as help other state environmental agencies to establish their own guideline values.