Section outline

  • Lecture: Basic measurement issues in health disparities research

    How do we describe the magnitude of health disparities, or decide whether health disparities are getting smaller or larger?  Although it may sound simple, there are many different approaches to quantifying disparities, and sometimes they give very different insights.  In this class we will compare some approaches, such as focusing on absolute versus relative inequalities and how to choose a reference category. We will also address some basic concepts in measurement of variables in health disparities research.  Rigorous, reproducible measurement protocols are essential to scientific progress, but many key variables in health disparities research are controversial to define or difficult to measure, such as segregation, racism, or social capital.  We will discuss some strategies to overcoming these measurement challenges and to give health disparities research a strong scientific grounding.

    Faculty:  Patience Afulani

    Location (Access restricted to registered students): Zoom URL

    • Session Slides:

    • Afulani-Health disparities measurement-2-11-21 File
    • Methodological Issues in Measuring Health Disparities File

    • Session Audio/Video Recording (Access restricted to registered students):

    • Watch -Live Lecture Media Resource
      Not available unless: You belong to Registered Students Only

    • Required Reading:

    • Krieger EverydayDiscrimination File
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    • A paper describing the validation of a measure of everyday discrimination
    • Stewart- Can we afford to ignore measurement File
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    • A commentary highlighting the relevance of thinking about measurement issues in health disparities research
    • Measures Epi File
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    • An exploration of use of relative vs. absolute measures of inequality

    • Optional Reading:


    • Atkins Racism File
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    • A paper that summarizes available scales to measure racism
    • discrimination resource dec. 2020 File
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    • Afulani et al-2017-Kenya validation File
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    • Keppel Measurement File
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    • Assignment:

       Hi everyone, homework this week has three parts. Please post to the forum by 8:45am on the day of class. 

      Part 1:

      1. Choose a paper describing the development or validation of a measure of relevance in health disparities research (please give the full citation and/or upload the paper if that's possible). Examples to get you thinking are measures of discrimination, self reported health outcomes, and measures of experiences of care.. 

      2. What was the definition of the construct?

      3. How did the authors provide evidence on the validity of the measure? Could you think of additional approaches to validating the measure?

      4. How did the authors provide evidence on the reliability of the measure? Could you think of additional approaches to evaluating the reliability of the measure?

      5. Are there limitations in how you would use this measure based on the population(s) with whom the measure was validated?

      6. Describe the implications of a lack of measurement validity or reliability for future research applications.

      Part 2:

      1. Find a paper describing a health disparity (please give the full citation or, even better, upload the paper so everyone else can look at it too)

      2. Summarize the construct and measurement of the dimension of disparity (e.g., racial inequalities?, SES inequalities?) and the outcome measured (e.g., self-rated health).

      3. What is the reference category used for the disparity measure (ie, who is the comparison group)? Why does this reference category make sense (or not) for this research question?

      4. How is the disparity quantified or measured? Is this an absolute or relative measure or are both provided? Describe which type of measure you would prefer for this research area, or, if both, why.

      Part 3:

      1. Read someone else's response to part 1 above (identifying a construct) and comment, specifically noting whether you can see any additional implications of measurement quality for future research or whether you agree with those noted by your classmate.