EpidemiologyThe Basics Only…

Adapted with permission from a class presentation developed by Dr. Charles Lynch – University of Iowa, Iowa City

Epidemiology

• Study of the distribution and determinants of health-related states or events in specified human populations and the application of this study to control of health problems.

Epidemiology Objectives

• Identify etiology of disease

• Determine extent of disease

• Study natural history

• Evaluate new modes of health care delivery and new preventive and therapeutic measures

• Provide foundation for developing public policy

Usual Pattern of Reasoning

• Develop a hypothesis

• Test the hypothesis on an exposed human population and include an appropriate comparison group

• Systematically collect and analyze data to determine whether a statistical association exists

Usual Pattern of Reasoning

• Assess validity of any observed statistical association by excluding possible alternative explanations such as– Chance (random error)– Bias (systematic error)– Confounding (effects of additional variables)

– Describe interaction

Usual Pattern of Reasoning

• Judge whether the observed association represents a cause-effect relationship between exposure and disease

VALIDITYDefinition

The degree to which a measurement or study

reaches a correct conclusion

TYPES OF VALIDITYDefinitions

• Internal: Do the results of an investigation accurately reflect the true situation of the study participants?

• External (i.e., generalizability): Are the results of a study applicable to other populations?

Internal and External Validity

• Internal validity- – must be the primary study objective

because you would not want to generalize an invalid result

Epidemiologic Study Cycle

Descriptive Studies - dataaggregation and analysis

Analysis of results suggests further descriptive study of hypotheses and new hypotheses

Analytic Studies to test hypotheses

Form hypothesis

Types of Studies

• Observational– Descriptive

• Study of the amount and distribution of disease within a population by person, place, and time

– Analytic• Study of the determinants of disease or reasons

for relatively high or low frequency in specific groups

Descriptive

• Undertaken when little is known of the epidemiology of a disease

• Provides information on patterns of disease occurrence in populations by characteristics such as age, race, marital status, social class, occupation, geographic area, and time occurrence

Descriptive

• Usually uses routinely collected data

IMPORTANT DIFFERENCE

• Used to generate the hypothesis NOT test the hypothesis

Descriptive

• Populations – Correlational– Ecologic– Aggregate

• Individuals– Case report (describes

single patient)– Case series (describes

characteristics of a number of patients)

Analytic

• Designed to test causal hypotheses that usually have been generated from descriptive studies

• Collection of new data

• More definitive conclusions about causation

Types of Studies for Testing Hypotheses

Observational– Cross-sectional– Case-Control– Cohort (prospective, retrospective

Intervention (experimental, clinical trials)

Experimental Versus Observational Study Design

E xp erim en ta l S tu d y

G rou p A G rou p B

R an d om A lloca tion

P op u la tion

O b serva tion a l S tu d y

G rou p A G rou p B

O th er-th an -ran d omA lloca tion

(e .g . S e lf-S e lec tion )

P op u la tion

Clinical Observations

Available Data

Case-Control Studies

Cohort Studies

Randomized Trials

DescriptiveStudies

Sequence of Studies in Human Populations

Design of a Randomized Clinical Trial

Im p roved N ot Im p roved

N ewTrea tm en t

Im p roved N ot Im p roved

C u rren tTrea tm en t

R an d om ized

D efin ed P op u la tion

Clinical Applications of Various Types of Studies

Type of Study Application to Clinical Practice

Etiologic Can risk be reduced among susceptible persons?

Diagnostic Can accuracy and timeliness of diagnosis be improved?

Prognostic Can prognosis be determined more definitively?

Therapeutic Can treatment be improved?

Case Reports• Describe the experience of a single

patient• Generally provide detailed

documentation of a unique medical occurrence

• May lead to the generation of a new hypothesis

• Traditionally, a common type of study published in medical journals

• Chief limitation: Sample size of 1

Case Series• Collections of individual case

reports• Often used as an early means to

identify the beginning or presence of an epidemic

• May lead to the generation of a new hypothesis

• Chief limitation: Lack of an appropriate comparison group

Descriptive Studies of Population Groups

• Also called– Correlational studies– Ecologic studies– Aggregate studies

• Studies in which the unit of analysis is some aggregate of individuals rather than an individual person

CHANCEDefinition of P-value

The probability that an effect at least as extreme as that observed in a particular study could have occurred by chance alone, given that there is truly no relationship between exposure and disease.

CHANCEP-value

• If p-value < 0.05: Since there is less than a 5% probability (1 in 20 chance) of observing a result as extreme as that observed due solely to chance, we generally consider the association between the exposure and disease to be statistically significant.

CHANCEP-value

• If p-value > 0.05 - by convention:–We generally consider that

chance cannot be excluded as a likely explanation

–Findings are stated to be not statistically significant at that level

BIASDefinition

Any systematic error in the design, conduct, or analysis of a study that results in a mistaken estimate of an exposure’s effect

on the risk of disease.

CONFOUNDING: ANOTHER TYPE OF BIAS

Definition• A variable that:

– Is causally related to (or at least associated with) the disease under study (or, as often occurs in practice, serves as a proxy measure for unknown or unmeasured causes), and

– Is associated with the exposure under study in the study population but is not a consequence of this exposure