Dose Effect

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Explained

So far we have only considered that persons could be either exposed or not, but exposure can frequently be quantified and a gradient established. Examples may include the number of glasses (or volume) of water consumed per day, the number of pizza slices eaten, or the degree of completion of a vaccination course etc. The risk of illness can then be calculated according to amount drunk, eaten or completed.

Amount drunk Exposed Cases Risk (%) RR
None 100 5 5 ref
1 glass 100 11 11 2.2
2 glasses 100 16 16 3.2
3 glasses 100 22 22 4.4
≥4 glasses 100 28 28 5.7
500 82 82 c


The Χ2 test for trend across these strata = 23.24, p≤0.001 - indicating that there is a trend across the exposure strata.

If instead a case control study had been conducted (note the similarity between the OR and the RR above):

Amount drunk Exposed Cases OR
None 5 30 ref
1 glass 11 30 2.2
2 glasses 16 30 3.2
3 glasses 22 30 4.4
≥4 glasses 28 30 5.6
82 150


For which the Χ2 test for trend = 12.77, p≤0.001

In the above examples, the risk of disease occurring increases with the amount of water consumed (i.e. with the dose of water). This is frequently called a dose response or a dose effect relationship.

To compute the risk ratio or the odds ratio the same reference level of exposure is used. Here the non exposed group is used as a reference. Alternatively the group with the lowest incidence could be used.

Dose response is particularly interesting when in an outbreak (often in water borne or a food borne outbreak) everybody is exposed to the same factor but the level of exposure differs among individuals. Choosing the lowest category of exposure as a reference still allows identification of a food item or a beverage as the vehicle for the outbreak. To test that the trend observed in risk or odds ratio differs from no trend, we can use a chi square for trend [1], [2], [3]. Dose response is also an important criterion to consider when providing evidence for causality proposed by Bradford Hill [4].

References

  1. J.J.Schlesselman. Case-control studies: design, conduct, analysis. New York: Oxford University Press; 1982.
  2. B.R.Kirkwood, J.A.C.Sterne. Medical Statistics. Second ed. Massachusetts: Blackwell Science Ltd; 2003.
  3. K.J.Rothman, S.Greenland, T.L.Lash. Modern Epidemiology. Third ed. Philadelphia, USA: Lipincott Williams and Wilkins; 2008.
  4. A.Bradford Hill. The Environment and Disease: Association or Causation? Proceedings of the Royal Society of Medicine 1965;58:295-300.