Cross-Sectional Prevalence Studies Zuber D. Mulla

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Cross-Sectional Prevalence Studies

Zuber D. Mulla

Objectives 1. Appreciate that both exposure and outcome status are measured at the same point in time in a cross-sectional study.

2. Calculate and interpret the prevalence ratio and prevalence odds ratio. 3. List the main advantages and disadvantages of a cross-sectional design.

Branches of Epidemiology • Descriptive • Analytic Epidemiology in Medicine by Hennekens & Buring, 1987

Descriptive Epidemiology • Concerned with distribution of disease • Propose hypotheses

Analytic Epidemiology • Focuses on causes of diseases • Tests hypotheses

Overview of Study Designs • Descriptive • Individuals (case series) • Populations (correlational studies)

• Analytic • Observational studies • Intervention studies

Overview of Study • Analytic – Observational studies • Case-control

Designs

–Retrospective case-control –Prospective case-control –Nested case-control –Density sampling case-control –Case-cohort

• Cohort (retrospective or prospective) • Cross-sectional prevalence survey

Overview of Study Designs • Analytic –Intervention studies • Nonrandomized controlled clinical trial

• Randomized controlled clinical trial

Independent Variable • • • • • • •

X variable Exposure Risk factor Explanatory Covariate Predictor Regressor

Dependent Variable • Y variable • Outcome • Response • Regressand • Endpoint

Cross-Sectional Studies

• Exposure (independent variable) and the outcome (dependent variable) assessed at the same point in time • No follow-up of subjects • (Panel study)

Cross-Sectional Prevalence Studies • Ideal for chronic diseases

• A disease of short duration, in general, not suitable for a crosssectional study because few individuals would have the disease at any one point in time

Example • You identify a random sample of adults using random digit dialing • Exposure: Obesity (BMI ≥ 30) • Outcome: Depression • Does prevalence of depression vary by obesity status?

Calculating a Prevalence Ratio (PR) Not Depressed depressed

Obese

A

B

A+B

Not obese

C

D

C+D

PR = Prevalence of Depression in Obese divided by Prevalence of Depression in Non-obese

A A+B PR = C C+D

Interpretation • PR=1.30 • Obese individuals were 30% more likely than non-obese individuals to have depression.

Advantage • No follow-up • May be quicker to conduct

Disadvantage • Time sequence/Temporality (what came first?) may be not intact: did the exposure really precede the outcome? • For exposures that do not change over time such as race or blood type, no problem.

What came first? Obese

Depression

Depression

Obese

PR vs. Prevalence OR • You can also calculate an odds ratio from a cross-sectional study. • Same formula as before: AD / BC • Logistic regression yields ORs. • Binomial regression will yield RR for a cohort study and PR for a crosssectional study

NHANES • National Health and Nutrition Examination Survey • www.cdc.gov/nhanes

Cited Reference Hennekens CH, Buring JE. Epidemiology in medicine. Boston: Little, Brown and Company, 1987.

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Cross-Sectional Prevalence Studies Zuber D. Mulla

Cross-Sectional Prevalence Studies Zuber D. Mulla Objectives 1. Appreciate that both exposure and outcome status are measured at the same point in ...

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