Skip to main content
Social Sci LibreTexts

8.3: Physical and Mental Health

  • Page ID
    212711
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    \( \newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\)

    ( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\id}{\mathrm{id}}\)

    \( \newcommand{\Span}{\mathrm{span}}\)

    \( \newcommand{\kernel}{\mathrm{null}\,}\)

    \( \newcommand{\range}{\mathrm{range}\,}\)

    \( \newcommand{\RealPart}{\mathrm{Re}}\)

    \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\)

    \( \newcommand{\Argument}{\mathrm{Arg}}\)

    \( \newcommand{\norm}[1]{\| #1 \|}\)

    \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\)

    \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\AA}{\unicode[.8,0]{x212B}}\)

    \( \newcommand{\vectorA}[1]{\vec{#1}}      % arrow\)

    \( \newcommand{\vectorAt}[1]{\vec{\text{#1}}}      % arrow\)

    \( \newcommand{\vectorB}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vectorC}[1]{\textbf{#1}} \)

    \( \newcommand{\vectorD}[1]{\overrightarrow{#1}} \)

    \( \newcommand{\vectorDt}[1]{\overrightarrow{\text{#1}}} \)

    \( \newcommand{\vectE}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash{\mathbf {#1}}}} \)

    \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \)

    \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)

    \(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)

    Physical and Mental Health

    Another way of gathering data about the overall health and well-being of an individual or a group of people is to survey them. Geographers use survey methods to gather information about a wide range of topics. Well done surveys are complex to plan, perform and analyze; so researchers must exercise extreme caution when using survey data, especially when the survey data was collected by others. The world’s largest telephone survey is done by the Centers for Disease Control and Prevention (CDC) with the aid of local health departments. This survey is called the Behavioral Risk Factor Surveillance System (BRFSS) and it provides a substantial amount of quality data about the health and health care of Americans. A number of questions are useful in measuring the quality of life of people around the US. The CDC makes this data available in a variety of formats, including format useable in a GIS, allowing health geographers easy access to exceptionally high-quality data sets necessary to solve numerous health-related problems.

    An outstanding source of data and maps about American’s Health:

    Centers for Disease Control

    Behavioral Risk Factor Surveillance System

    Healthy Days

    A couple of the most basic questions asked by the CDC on the BRFSS are “Would you say that in general your health is _______? (Excellent, Very good, good, fair, poor) and “How many days in the past 30 days was your physical health poor?” (numeric answer, none, not sure, refuse to answer). Similar questions are asked about mental health. The answers to these questions can be mapped at various scales (county, city, state, etc.) to paint a compelling picture of a region’s health. Hundreds of researchers, and dozens of organizations working to improve the health and well-being of communities, use this data.

    Poor health days per month U.S (2010).png

    Figure: US Map - Eastern Appalachia and parts of the South report five times as many poor health days as some counties in the Upper Midwest. What are the costs to employers and taxpayers? Source: CDC / County Health

    Survey results indicate a wide variation in the number of days people are sick over the course of any 30-day period in the US. In some places, people on average have less than two “sick days” per month. In other places, especially the Deep South and Appalachia, people are sick, on average, about seven days per month. While a few days difference may not seem noteworthy, multiplied by millions of people that live in most states, it is a huge difference. Chronic illness has significant implications for the economy of a region at the very least. Imagine for a moment how a company looking to open a factory in Appalachia would evaluate the health indicator data for a county where people are sick about three months out of every year? How much money would the factory stand to lose in a location like this? The unhealthy conditions of Americans living in poverty are not only a humanitarian concern but a significant economic drain on the entire US economy because the poor health of Americans in other regions of the country is often passed on to the rest of the country via external costs -like extra taxes and increased health insurance costs.

    Population Receiving Government Disability Payments U.S.png

    Figure : US Map - Many poor counties have over 10% of their population receiving disability payments from the US government. Age is partly a factor, but unhealthy lifestyles cost American taxpayers billions annually, while contributing to a cycle of poverty. Source: Social Security

    One of the key outcomes of poor health is disability. Over 10 million Americans were receiving disability payments at the end of 2017. On average, the monthly benefit paid to claimants was around $1,200. The program began in 1957, but expanded rapidly in the 1990s, after cuts to other welfare payments eliminated cash payments to the able-bodied poor, many of whom were economically struggling parents of small children.

    The Truth Initiative is a nonprofit organization dedicated to eliminating tobacco use.

    The article linked below discusses the difference in health outcomes for states with prevalent tobacco use:


    8.3: Physical and Mental Health is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by LibreTexts.

    • Was this article helpful?