DESCRIPTIVE STUDIES Ahmed Mandil Prof of Epidemiology KSU

DESCRIPTIVE STUDIES Ahmed Mandil Prof of Epidemiology KSU College of Medicine

Headlines • • • Introduction General concepts Descriptive versus analytical epidemiology Types of study designs in health research Cross-sectional studies Measures

X &Y notations • X = independent variable (exposures, causes, risk factors) • Smoking, obesity, asbestos, environmental factor, etc • Y = dependent variable (outcomes, effects, diseases, injuries, disabilities, complications, mortalities) • Respiratory systems cancers (larynx, trachea, lung, etc); diabetes; asbestosis (types of pneumoconiosis), etc

Types of Quantitative Research Designs – Descriptive X? Y? • What is X, Y? – Correlational • Is there a relationship between X and Y? – Analytical ΔX ΔY? • Does a change in X cause a change in Y?

Are exposure and outcome linked (association, causation) ? Exposure Outcome

Basic Questions in Health Research To link exposure and outcome, we ask: – What is the exposure? – Who are the exposed? – What are the potential outcomes ? – What approach will we take to study the relationship between exposure and outcome ?

Data Collection Methods • Primary: where the investigator is the first to collect the data. Sources include: medical examinations, interviews, observations, etc. Merits: less measurement error, suits objectives of the study better. Disadvantage: costly, may not be feasible. • Secondary: where the data is collected by OTHERS, for other purposes that those of the current study. Sources include: individual records (medical / employment); group records (census data, vital statistics)

Descriptive versus Analytical Epidemiology DESCRIPTIVE EPIDEMIOLOGY ANALYTIC EPIDEMIOLOGY Examining the distribution of a disease in a population, and observing the basic features of its distribution in terms of time, place, and person. Typical study design: community health survey (approximate synonyms cross-sectional study, descriptive study) Triad: person, place, time Testing a specific hypothesis about the relationship of a disease to a putative cause, by conducting an epidemiologic study that relates the exposure of interest to the disease of interest. Typical study designs: cohort case-control Triad: agent, host, environment

Study Designs in Health Research • Qualitative – Focus group discussions – Key informant studies – Ethnographic studies – Bibliographic studies – Others • Quantitative – Observational • Descriptive, e. g. crosssectional (surveys) • Analytical, e. g. casecontrol; cohort – Experimental (also analytical) • Randomized Clinical Trials • Community Intervention Studies

Observational Studies • Non-experimental • Observational because there is no investigator(s) intervention • Exposures occur in a “non-controlled” environment • Individuals can be observed currently (snap shot), prospectively, retrospectively, or a combination

Observational Designs (3 Broad Types) • Exploratory: used when the state of knowledge about the phenomenon is poor: small scale; of limited duration. • Descriptive: used to formulate a certain hypothesis: small / large scale. Examples: casestudies; cross-sectional studies • Analytical: used to test hypotheses: small / large scale. Examples: case-control, cross-sectional, cohort.

Cross-sectional studies An “observational” design that surveys exposures and outcomes at a specified point in time (a cross-section of the population) time Study only exists at this point in time

Cross-Sectional Design exposure present, outcome present Study population exposure absent, outcome present exposure present, outcome absent exposure absent, outcome absent time Study only exists at this point in time

Cross-sectional Studies • Often used to study conditions that are relatively frequent with long duration of expression (nonfatal, chronic conditions) • It measures prevalence, not incidence of disease • Example: community-based surveys • Not suitable for studying rare or highly fatal diseases or a disease with short duration of expression

Cross-sectional Studies: Advantages • Feasible; quick; economic; allows study of several diseases / exposures; useful for estimation of the population burden, health planning and priority setting of health problems

Cross-sectional studies: Disadvantages • Weakest observational designs (measure prevalence, not incidence of disease) • The temporal sequence of exposure and outcome may be difficult or impossible to determine (temporal ambiguity) • Usually don’t know when outcome (e. g. disease) occurred • Not suitable for study of rare events and quickly emerging diseases

Measures (I) • Frequency measures (for estimation of the magnitude of the problem / outcome): incidence (cohort studies), prevalence (cross-sectional studies) • Effect measures (for quantification of the magnitude of association between the exposure and outcome): risk ratio or relative risk (cohort studies); odds ratio (estimates the RR in both cross-sectional and case control studies)

Measures (II) Impact fractions (to estimate the proportion of the outcome attributed to the exposure): – Attributable fractions (for causal associations) – Prevented fractions (for preventive associations)

Headlines • • • Introduction General concepts Descriptive versus analytical epidemiology Types of study designs in health research Cross-sectional studies Measures

References • Last J. A dictionary of epidemiology. 5 th edition. Oxford: Oxford University Press, 2008. • Holzemer WL. Advanced Quantitative Methods. University of California, San Franciso, USA. • Songer T. Study designs in epidemiological research. In: South Asian Cardiovascular Research Methodology Workshop. Aga-Khan and Pittsburgh universities. • Kelsey JL, Thompson WD, Evans AL. Methods in observational epidemiology. New York: Oxford University Press.