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Measures of effect in epidemiological research
Giovanni Tripepi1, Kitty J Jager, Friedo W Dekker
1CNR-IBIM, Clinical Epidemiology and Physiopathology of Renal Diseases and Hypertension, Reggio Calabria, Italy. gtripepi@ibim.cnr.it
Nephron. Clinical Practice
|April 22, 2010
Summary
Understanding risk factor-outcome relationships is key in research. Relative measures like risk ratio and absolute measures like risk difference quantify these associations, with choices depending on study goals.
Area of Science:
- Epidemiology
- Biostatistics
Background:
- Assessing risk factor-outcome relationships is crucial for etiological and prognostic research.
- Quantifying the strength of these relationships requires specific statistical measures.
- Measures are categorized as relative or absolute, each serving distinct analytical purposes.
Purpose of the Study:
- To explain the different types of measures used to quantify risk factor-outcome relationships.
- To differentiate between relative and absolute measures.
- To guide the selection of appropriate measures based on research objectives.
Main Methods:
- Discussion of relative measures including risk ratio, incidence rate ratio, and odds ratio.
- Explanation of absolute measures including risk difference (attributable risk) and rate difference (attributable rate).
- Description of how absolute measures are calculated by subtracting outcomes in unexposed from exposed groups.
Main Results:
- Relative measures (risk ratio, incidence rate ratio, odds ratio) assess the magnitude of association.
- Absolute measures (risk difference, rate difference) quantify the excess risk or rate attributable to a factor.
- The choice between relative and absolute measures is dictated by the specific research question and study aim.
Conclusions:
- Relative measures are predominantly utilized in etiological research to understand disease causation.
- Absolute measures are primarily employed in public health research for assessing population impact and intervention planning.
- Appropriate selection of risk-outcome measures enhances the validity and applicability of research findings.
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