2 research outputs found
Effect of GDP Per Capita On Dietary Decisions Internationally
No full textThe goal of this project is to analyse and understand how GDP per capita affects an individual’s dietary decisions. A total of nine countries were used in this project which included, China, Japan, United States, Iceland, United Kingdom, France, New Zealand, Canada, and South Korea. The dependent variable being analysed was the % vegetarian population in each country and the independent variables included nominal GDP, GDP per capita, annual GDP growth rate, population size, meat consumption (kg/capita), and unemployment rate. To analyse the data a regression analysis was done. Degrees of freedom was 182 with all the independent variables, with the exception of GDP per capita, showing a negative relationship to the dependent variable. To account for heterogeneity of each country a fixed effect regression model was done which showed GDP per capita having a negative relationship with the % vegetarian population in each country, and it was statistically significant at the 1% level. Omitting all other independent variables, GDP per capita was analysed for its role on dietary decisions. A regression model without fixed effect was compared to a regression with fixed effect. Results concluded that other factors such as culture or geographic location play a much bigger role in an individual’s dietary decision
Identification of Toxicity Parameters Associated with Combustion Produced Soot Surface Chemistry and Particle Structure by in Vitro Assays
No full textAir pollution has become the world’s single biggest environmental health risk of the past decade, causing millions of yearly deaths worldwide. One of the dominant air pollutants is fine particulate matter (PM2.5), which is a product of combustion. Exposure to PM2.5 has been associated with decreased lung function, impaired immunity, and exacerbations of lung disease. Accumulating evidence suggests that many of the adverse health effects of PM2.5 exposure are associated with lung inflammation and oxidative stress. While the physical structure and surface chemistry of PM2.5 are surrogate measures of particle oxidative potential, little is known about their contributions to negative health effects. In this study, we used functionalized carbon black particles as surrogates for atmospherically aged combustion-formed soot to assess the effects of PM2.5 surface chemistry in lung cells. We exposed the BEAS-2B lung epithelial cell line to different soot at a range of concentrations and assessed cell viability, inflammation, and oxidative stress. Our results indicate that exposure to soot with varying particle surface composition results in differential cell viability rates, the expression of pro-inflammatory and oxidative stress genes, and protein carbonylation. We conclude that particle surface chemistry, specifically oxygen content, in soot modulates lung cell inflammatory and oxidative stress responses
