instructor resource chapter 10 copyright © scott b. patten, 2015. permission granted for classroom...
TRANSCRIPT
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Instructor Resource
Chapter 10
Copyright © Scott B. Patten, 2015.
Permission granted for classroom use with Epidemiology for Canadian Students: Principles, Methods & Critical Appraisal (Edmonton: Brush Education Inc. www.brusheducation.ca).
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Chapter 10. Cross-sectional studies
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Objectives
• Define cross-sectional studies.• Differentiate between the potential descriptive and
analytical goals of cross-sectional studies.• Describe the following measures of association:
prevalence differences, prevalence ratios, prevalence odds ratios, and specific types of linear equations.• Explain how to interpret measures of association
calculated from cross-sectional data.• List strengths and weaknesses of cross-sectional
studies.
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Critical appraisal
• This chapter is our first examination of a specific study design.• Identification of study designs is a key step in
critical appraisal of research reports.• Critical appraisal is more than just reading a study
and intuitively trying to identify problems with it.• Critical appraisal involves asking and answering a
series of key questions.• An early step in critical appraisal should be
identification of the study design.
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Strategies for classifying study design
• A common (but sometimes problematic) approach to classifying studies is based on the motivations of the investigators.• This approach asks the question: did these
investigators have descriptive or analytical goals?• The problem is that studies can have mixed goals
and motivations may not be clearly stated.• A more reliable procedure for study-design
classification is based on actual features of the study.
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What is a cross-sectional study?• Cross-sectional studies are studies in which all data
are collected at a single point in time. • Prevalence studies are usually cross-sectional.
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What is a cross-sectional study? (continued)• Obviously, no study can occur exactly in a single
instant. • A prevalence study may take months or even years
to conduct. • Conceptually, however, these studies take place at a
point in time: the study design neither to looks back into the past (retrospectively), nor forward into the future (prospectively).• Note that a cross-sectional study can look back in
time with its questions (e.g., it may ask adults questions about abuse when they were children), but the design is neither retrospective nor prospective.
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Examples of cross-sectional studies• The Canadian Community Health Survey• general health “iterations”• specialized “iterations”: e.g., nutrition, aging
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More examples
• See abstracts at: • http://www.ncbi.nlm.nih.gov/pubmed/24044468• http://www.ncbi.nlm.nih.gov/pubmed/26001869• http://www.ncbi.nlm.nih.gov/pubmed/25935425• http://www.ncbi.nlm.nih.gov/pubmed/25929819
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How cross-sectional studies look at associations• For the next few slides, consider the classic 2 x 2 contingency table:
Disease No Disease
Exposed a b
Nonexposed c d
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Prevalence differences
Prevalence Differenc e=𝑎
𝑎+𝑏−
𝑐𝑐+𝑑
Key point: A prevalence difference is an example of a measure of association because it embodies a comparison between 2 simpler parameters, which are prevalence in exposed and nonexposed groups.
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Prevalence ratios
Prevalence R atio=
𝑎𝑎+𝑏𝑐
𝑐+𝑑
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Prevalence odds ratios
R
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Specific types of linear equationsPrevalence=α+ β 𝑋𝑒
where Xe is a variable with two values: 1 = exposed, 0 = nonexposed
This equation states that in the nonexposed,prevalence is and in the exposed it is +
Can you see that is a prevalence difference?
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Strengths of the cross-sectional study designCross-sectional studies:• provide valuable snapshots of disease• describe disease occurrence across multiple
variables: they can examine multiple diseases and exposures• are cost efficient: these studies are often relatively
inexpensive and practical• are invulnerable to attrition
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Weaknesses of the cross-sectional study designCross-sectional studies:• lack causal inference: temporality is usually unclear• provide no determination of risk• are inefficient for rare diseases• are insensitive to time-dependent frequency
changes
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End