(correlational) studies, and cross-sectional studies. These designs are called descriptive study designs

because they focus on describing health in populations. (We explain what this means in “Describing

What We See.”) In contrast to descriptive study designs, there are only two types of analytic study

designs: longitudinal cohort studies and case-control studies. Unlike descriptive studies, analytic

studies are designed specifically for causal inference. These are described in more detail in the

section, “Getting Analytical.”

Describing what we see

As shown in Figure 7-1, there are two types of observational studies: descriptive and analytic.

Descriptive study designs focus on describing patterns of human health and disease in populations,

usually as part of surveillance, which is the act of quantifying patterns of health and disease in

populations. Cross-sectional is one descriptive study design used in surveillance to produce incidence

and prevalence rates of conditions or behaviors (see Chapter 14). For example, results from cross-

sectional surveillance studies tell us that approximately 25 percent of women aged 15 to 44 who

currently use contraception in the United States choose the birth control pill as their method of choice.

While descriptive study designs are necessary in a practical sense, they are poor at developing

evidence for causal inference, so they are considered inferior to analytic study designs.

Getting analytical

Analytic designs include longitudinal cohort studies and case-control studies. These are the strongest

observational study designs for causal inference. Longitudinal cohort studies are used to study causes

of more common conditions, like hypertension (HTN). It is called longitudinal because follow-up

data are collected over years to see which members of the sample, or cohort, eventually get the

outcome, and which members do not. (In a cohort study, none of the participants has the condition, or

outcome, when they enter the study.) The cohort study design is described in more detail under the

section, “Following a cohort over time.”

Case-control studies are used when the outcome is not that common, such as liver cancer. In the case of

rare conditions, first a group of individuals known to have the rare condition (cases) is identified and

enrolled in the study. Then, a comparable group of individuals known to not have the rare condition is

enrolled in the study as controls. The case-control study design is described in greater detail under the

section “Going from case series to case-control.”

Going from observational to experimental

You may notice in Figure 7-1 that observational studies (which are either descriptive or analytic)

comprise most of the figure. Experimental studies — where participants are assigned to engage in

certain behaviors or interventions — are less common than observational studies because they have

ethical concerns, and are often expensive and complex. However, experimental studies benefit from

generating the highest level of evidence for causal inference — much higher than observational

studies.

Climbing the Evidence Pyramid

Each of the study designs discussed in the previous sections generates a particular level of evidence

for causal inference. These levels of evidence may be arranged in a pyramid. As shown in Figure 7-2,

the study designs with the strongest evidence for causal inference are at the top of the pyramid, and