2. Quantitative Methods for Public Health

How much of your daily public health work is informed by data? Do you know the difference between quantitative and qualitative data?

Data provides evidence to support programs and policies that are designed to improve individual and population health. There are two kinds of data:

  • Quantitative data is information in numeric form (i.e., things that can be counted, measured, or compared on a numerical scale)
  • Qualitative data is descriptive (i.e., things that can be observed, but not measured)

Both types of data are important to public health work.

 

After completing this section, you will be able to:

  • Name four key uses of data
  • List some characteristics of useful data
  • Calculate the incidence and prevalence of a given disease and population
  • Distinguish between absolute and relative measures of association
  • Compute the risk difference and risk ratio for a given disease and sleep characteristic
  • Describe the difference between association and causation of disease
  • Define confidence interval estimates

Recording 2A

Listen to this recording (approximately 22 minutes).

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Action Item

Data Sources

What health data sources are available to you? What data points do you contribute to local or state data collection systems?

Review the data resources listed on the last page of this training. Consider bookmarking them on your computer.

 Recording 2B

Listen to this recording (approximately 12 minutes).

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Recording 2C

Listen to this recording (approximately 13 minutes).

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Action Item

Absolute vs. Relative Measures of Association

We often want to compare estimates of prevalence or incidence between groups (e.g., those who follow a healthy diet versus those that follow an unhealthy diet).  Remember, there are two types of comparisons:

  1. Absolute comparisons look at differences (e.g., differences in prevalence or differences in cumulative incidence)
  2. Relative comparisons look at ratios (e.g., ratios of prevalence or ratios of risk)

Once we have these measures, we then need to determine if they suggest a difference in prevalence or incidence between groups, and there are statistical approaches to these assessments.

  • The null value (or the "no difference" value) of an absolute measure is zero (i.e., if the 2 risks are equal, the difference will be zero)
  • The null value (or the "no difference" value) of a relative measure is one (i.e., if the 2 risks are equal, the ratio will be one)

Which is best to use when determining risk for students in a school setting? It depends on the question you ask.

Use absolute measures for questions like:

  • How much impact would a prevention program have?
  • How many students would benefit?

Use relative measures for questions like:

  • How much more likely are students with the risk factor/exposure to develop a disease compared to those without the risk factor/exposure?

 

Recording 2D

Listen to this recording (approximately 7 minutes).

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Recording 2E

Listen to this recording (approximately 11 minutes).

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