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POSTER TEMPLATE BY: www.PosterPresentations.com Tuberculosis: Environmental and Individual Indicators: A Work in Progress Justin Beatty, Department of.

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Presentation on theme: "POSTER TEMPLATE BY: www.PosterPresentations.com Tuberculosis: Environmental and Individual Indicators: A Work in Progress Justin Beatty, Department of."— Presentation transcript:

1 POSTER TEMPLATE BY: www.PosterPresentations.com Tuberculosis: Environmental and Individual Indicators: A Work in Progress Justin Beatty, Department of Biological Sciences, College of Arts and Sciences and Honors College Mentored by Dr. Joseph Oppong, Department of Geography, College of Arts and Sciences Why Tuberculosis? Tuberculosis infects one-third of the world’s population and causes more than three million deaths every year. Abstract Throughout the United States, tuberculosis has become a growing problem. This is particularly true in the African American community. But why are African Americans being hit so hard by this disease? The objective of my research is to determine the correlations between individual indicators (age, gender, ethnicity, recent immigration), environmental indicators (dwelling crowding, population density, poverty, building size and age, exposure to recent immigrants) and rates of infection with tuberculosis. This will be accomplished by using a geographical information system, with zip codes as the unit of analysis. The research sheds light on the nature of the relationship between these factors and the higher risk of infection among African Americans. It suggests that the greater risk of infection among African Americans may be due to a higher occurrence of environmental risk factors (poverty, crowding, population density, and exposure to recent immigrants) in the African American community. Why Tuberculosis? References Images 1.http://blog.seattlepi.nwsource.com/healthcare/archives/131972.asp?from=blog_last3http://blog.seattlepi.nwsource.com/healthcare/archives/131972.asp?from=blog_last3 2.http://www.ij-healthgeographics.com/content/3/1/23/figure/F2http://www.ij-healthgeographics.com/content/3/1/23/figure/F2 3.http://earthtrends.wri.org/updates/node/177http://earthtrends.wri.org/updates/node/177 4.http://www.nature.com/nri/journal/v6/n9/fig_tab/nri1920_F1.htmlhttp://www.nature.com/nri/journal/v6/n9/fig_tab/nri1920_F1.html Text 1.Chan-Yeung, M, et al. Socio-demographic and geographic indicators and distribution of tuberculosis in Hong Kong: a spatial analysis. International Journal of Tuberculosis and Lung Disease. 2005; 9: 1320-1326. 2.Wanyeki, Ian, et al. Dwellings, crowding, and tuberculosis in Montreal. Social Science and Medicine. 2006; 63: 501-511. 3.Acevedo-Garcia, Dolores. Zip code-level risk factors for tuberculosis: neighborhood environment and residential segregation in New Jersey, 1985-1992. American Journal of Public Health. 2001; 91: 734-741. Methodology And a Local Problem What Can Be Done? My hope is that through a greater understanding of the nature of tuberculosis and how it is spread, we may better equip ourselves to slow the tidal wave. But what can be done now? By educating people about the seriousness of this disease and the factors that contribute to its spread, I believe that we can make an immediate impact. Furthermore, it is my hope that through recognition, more volunteers will devote time abroad to children like the boy shown here from Cape Town, South Africa, who have no hope without our help. tb flies. Acknowledgments I would like to thank the following individuals for making this research experience possible: Dr. Wendy Wilkins, Provost and Vice President for Academic Affairs Dr. Gloria Cox, Dean, Honors College Dr. Warren Burggren, Dean, College of Arts and Sciences Dr. Joseph Oppong, Department of Geography A Global Problem… This research will examine the following variables in each zip code in Tarrant County, searching for correlations between each variable. Dependent variable  Tuberculosis infection Independent variables  Age  Gender  Ethnicity Variables of unknown relationship  Dwelling crowding  Population density  Poverty  Building size  Building age  Recent immigration  Exposure to recent immigrants  HIV Infection


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