Biostatistics For Dummies, 2nd Edition (Monika Wahi, John Pezzullo)

96 PART 2 Examining Tools and Processes

include very large sample sizes — but they still use the same 2x2 table for inter-

pretation. Figure 7-6 offers an example of what a 2x2 table for a cohort study

might look like where the exposure is high alcohol intake and the outcome is HTN.

As shown in Figure 7-6, the total number of participants is large. This cohort of

600 participants could have been naturally sampled from the population, or they

could be stratified by exposure, meaning that the study design could require a cer-

tain number of participants to be exposed and to be unexposed. Imagine that you

insisted that 300 of your participants have high alcohol intake, and 300 have low

alcohol intake. It may be harder to recruit for the study, but you would be sure to

have enough exposed participants for your statistics to work out. In the case of

Figure 7-6, 210 exposed and 390 unexposed participants were enrolled.

In cohort studies, all the participants are examined upon entering the study, and

those with the outcome are not allowed to participate. Therefore, at the beginning

of the study, all 600 of the participants did not have the outcome, which is HTN.

A cohort study is essentially a series of cross-sectional studies on the same cohort

called waves. The first wave is baseline, when the participants enter the study (all

of whom do not have the outcome). Baseline values of important variables are

measured (and criteria about baseline values may be used to set inclusion criteria,

such as minimum age for the study). Subsequent waves of cross-sectional data

collection take place at regular time intervals (such as every year or every two

years). Changes in measured baseline values are tracked over time, and subgroups

of the cohort are compared in terms of outcome status. Figure 7-6 shows the

exposure status from baseline, and the outcome status from the first wave.

Because the exposure is measured in a cohort study before any participants get the

outcome, it is considered the highest level of evidence among the observational

study designs. It is far less biased than the case-control study design. Several

measures of relative risk can be used to interpret a cohort study, including the OR,

risk ratio, and incidence rate (see Chapter 14).

FIGURE 7-6:

Example of a

typical cohort

study 2x2 table.