FIGURE 6.5 Variation in risk of late-stage cancer diagnosis for the four major cancers in Illinois. The figure shows that risk is highest for cancer patients living in Chicago. The odds of late diagnosis decrease away from Chicago, reaching their lowest levels among patients living in large towns (defined here as towns with populations ranging from 10,000 to 50,000 and not located in metropolitan areas). This figure does not control for age or race, but the study looked at the impacts of both and found that the rural-urban gradient remained consistent for breast, colorectal, and lung cancers, but disappeared for prostate cancer. SOURCE: McLafferty and Wang (2009).

FIGURE 6.5 Variation in risk of late-stage cancer diagnosis for the four major cancers in Illinois. The figure shows that risk is highest for cancer patients living in Chicago. The odds of late diagnosis decrease away from Chicago, reaching their lowest levels among patients living in large towns (defined here as towns with populations ranging from 10,000 to 50,000 and not located in metropolitan areas). This figure does not control for age or race, but the study looked at the impacts of both and found that the rural-urban gradient remained consistent for breast, colorectal, and lung cancers, but disappeared for prostate cancer. SOURCE: McLafferty and Wang (2009).

and geographical variations in the quality of health care. There is also much to be gained from comparative analyses of the spatial dimensions of health care access in different parts of the world and for different types of health challenges (e.g., heart disease, HIV/AIDS, vector-borne diseases).

How are social factors affecting the spread of diseases, such as HIV/AIDS in Sub-Saharan Africa?

HIV/AIDS is the leading cause of death in Sub-Saharan Africa, which remains the epicenter of the epidemic, accounting for 67 percent of all people living with HIV worldwide and 72 percent of all AIDS-related deaths (UNAIDS, 2008). In southern Africa, the worst-affected region, national adult prevalence exceeds 15 percent in seven countries. Women account for nearly 60 percent of HIV infections in Sub-Saharan Africa, and young women represent 67 percent of all new cases of HIV among people ages 15-24 living in developing countries (UNAIDS, 2008).

It is well established that spatial variability is a key factor in understanding HIV/AIDS; geographical concentrations of HIV/AIDS are found even in many countries with very low HIV prevalence. In the Democratic Republic of the Congo, for example, Messina et al. (In review; Figure 6.6) documented a high degree of spatial variability in HIV/AIDS cases and found that the distribution of the disease was influenced by such social factors as sexual practices, socioeconomic status, and access to transportation. Future work in this vein could describe the spatial distribution of genetic subtypes of the HIV/AIDS virus, which in turn could facilitate the effort to understand not only where imported cases originate, but where and how those cases evolve from earlier strains. Work on the impacts of socioeconomic status on the distribution of

FIGURE 6.6 HIV distribution in the Democratic Republic of the Congo, showing differential patterns for men and women. A geographically based, population-representative sampling scheme allowed Michael Emch and his colleagues to construct this visualization, which was then used to examine the impacts of social factors on the distribution of HIV/AIDS. Not surprisingly, the study found that social factors are the most important drivers of the distribution of the disease. SOURCE: Michael Emch, University of North Carolina, Chapel Hill Geography. Used with permission.

FIGURE 6.6 HIV distribution in the Democratic Republic of the Congo, showing differential patterns for men and women. A geographically based, population-representative sampling scheme allowed Michael Emch and his colleagues to construct this visualization, which was then used to examine the impacts of social factors on the distribution of HIV/AIDS. Not surprisingly, the study found that social factors are the most important drivers of the distribution of the disease. SOURCE: Michael Emch, University of North Carolina, Chapel Hill Geography. Used with permission.



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