8.1: Chapter Introduction and Objectives
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)Chapter Introduction & Objectives
Chapter 8: Geography of Health & Disease
- Analyze key health metrics such as infant mortality rate and life expectancy to understand regional health disparities.
- Examine the geographical distribution and impact of major diseases, including COVID-19, influenza, malaria, and cancer.
- Assess the influence of demographic factors and the built environment on health outcomes and access to healthcare.
- Evaluate the geography of care, focusing on the availability and accessibility of medical facilities and healthcare systems.
- Investigate the intersection of health and geography in the context of women's reproductive rights, public spaces, and regional health policies.
Introduction to the Geography of Health and Disease
In our exploration of cultural geography, we delve into the intricate and multifaceted relationship between geography and health. This chapter, The Geography of Health and Disease, will illuminate how the physical and social environments influence health outcomes and the distribution of diseases. Through this lens, we will understand the profound impacts of place, space, and scale on health metrics and care.
We'll begin by examining key health metrics that provide insight into the well-being of populations. Metrics such as the infant mortality rate and life expectancy offer a window into the health disparities across different regions. We'll discuss tools like Measure of America and County Health Rankings, which help us analyze and compare health outcomes across the United States.
Our discussion will extend to both physical and mental health, understanding how geography shapes the prevalence and management of various health conditions. The concept of "Tobacco Nation" will serve as a case study in understanding how lifestyle choices and health policies can vary dramatically by region.
The geography of disease is a critical aspect of our study. We'll trace the spread and impact of major diseases such as COVID-19, influenza, malaria, and cancer. Each of these diseases has a unique geographical footprint, influenced by factors such as climate, socioeconomic conditions, and public health infrastructure.
We'll also explore the geography of care, focusing on access to medical facilities and the regional variations in health care systems. Issues like affordable healthcare and women's reproductive rights will be discussed, highlighting the inequalities and challenges faced by different populations.
Demographic factors such as the demographic transition, sex ratio, and gendered landscapes play a significant role in health outcomes. We'll examine how these factors intersect with geography to create distinct health landscapes.
Finally, we'll consider how the built environment, including housing, public spaces, and even gas stations, impacts health. These elements of our everyday surroundings can have profound effects on physical activity levels, exposure to pollutants, and overall well-being.
By the end of this chapter, students will have a comprehensive understanding of how geographical factors shape health and disease. This knowledge is crucial for addressing public health challenges and creating healthier, more equitable communities.
Everybody gets sick and everyone eventually dies but, where you live is an important factor in how often and from what causes your health will suffer. Geography offers a powerful set of tools to investigate the spatial patterns of health and health care.
Figure Lithographic Map - John Snow mapped locations where cholera victims lived in London in an effort to isolate the source of the cause of the disease. Source: Wikimedia
The application of geographic techniques in the quest to address health crises is one of the earliest and most famous uses of spatial statistics to solve a pressing medical problem. In London in 1854, there was a severe outbreak of cholera, a gastrointestinal illness generally caused by drinking water contaminated by human feces. Back then, nobody quite understood that microscopic organisms, like bacteria, were capable of causing such violent illnesses. Instead, most medical experts believed that a kind of poisonous air, called miasma, was responsible for infectious diseases like cholera and the plague. The fear of miasma drove thousands, especially the wealthy, to seek healthy air in mountain or coastal resort towns. John Snow, a physician from London, worked in a neighborhood where there were many cases of cholera during the 1854 outbreak. Snow suspected that the miasmic air could not be the cause of cholera because other neighborhoods had similar air quality characteristics, but not the same rate of cholera. Instead, Snow guessed that the water supply was somehow contaminated, although he could not identify the “poison” in the water, even with a microscope. In order to test his theory, Snow first made a mental map of the locations where people had contracted cholera. He realized that cholera cases were spatially clustered around one public water well. Snow then hypothesized that if the handle to the water pump at the geographic center of the cholera outbreak was removed, then local residents would be forced to get water elsewhere, and the incidence of cholera would begin to subside. To test his hypothesis, Snow convinced local authorities to remove the well’s pump handle and indeed the cholera epidemic lessened. Snow later made a physical point map indicating the location of the cholera patients’ residences and the poisoned well. Snow’s effort can be quickly replicated today using GIS and the results of simple statistical analyses of Snow’s data points to the remarkable accuracy of his initial hypothesis. More importantly, Snow’s map overturned centuries of bad science on disease while paving the way for the adoption of the germ theory of disease that is widely accepted today.
Figure London, England. This memorial water pump commemorates John Snow's scientific breakthrough in the diagnosis of Cholera. Note: the missing pump handle. Wikimedia
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