Evidence-Based Practice for Nurses

risk. People who exercised more than three times per week were 62% (1 −

0.38 = 0.62 × 100 = 62%) less likely to have HTN as compared to those

people who did not exercise at all.

Cross-sectional studies have advantages and disadvantages. Cross-sectional

studies can be used to explain current exposures and diseases in a given popula-

tion. These studies are efficient and relatively inexpensive. They can also be used

to examine a number of different phenomena, including behaviors, symptoms,

diseases, and health status. The investigator is not limited to a single exposure

and disease but can examine multiple exposures and diseases simultaneously.

The major disadvantage of cross-sectional studies is temporal ambiguity. Be-

cause data about exposure and disease status are collected at the same time, an

investigator is unable to ascertain if the exposure preceded the disease. Another

disadvantage exists because cross-sectional studies measure prevalence. Because

prevalence is a function of incidence and duration of time, it is difficult to dis-

tinguish determinants of the cause of the disease from determinants of survival

with the disease. As a result, with a cross-sectional design, the investigator is not

able to determine whether the specific exposures caused the specific diseases.

Analytic study designs are hypothesis-testing and are used to test the associa-

tion between exposure and disease. These studies include case-control studies,

cohort studies, and intervention studies.

8.6 Analytic Study Designs

By the end of this section, you will be able to:

‹ Describe analytic study designs, including case-control studies, cohort studies,

and intervention studies

‹ Calculate an odds ratio for a case-control study design

‹ Calculate relative risk for a cohort study design

Calculate the PR for the following 2 × 2 table

Preterm Labor No Preterm Labor Total

Smoking 150 150 300

No Smoking 25 275 300

Total 175 425 600

TEST YOUR KNOWLEDGE 8-5

How did you do? PR = 6.02

208 CHAPTER 8 Epidemiologic Designs: Using Data to Understand Populations