Populations• Populations in epidemiology

– Group of people for whom we are interested in the occurrence of disease or the effect of an exposure on disease

– Defined by: geography, occupation, demographic characteristics (age, race/ethnicity, gender), time etc.

Populations• Populations in epidemiology

– Examples:• Residents of NYC on 9/11/2001• Women of childbearing age in Alameda County 1980-2000• Live singleton births in Bangladesh in 2005

Populations• Total population

– Includes everyone in a particular population• Candidate or “at risk” population

– People in the total population who could get the disease/condition of interest

– Excludes those who have the disease or who are immune (or do not have the necessary organ or physiological function, etc.)

Populations• Candidate or “at risk” population

– Example: candidate population for pregnancy excludes men, currently pregnant women, women with hysterectomy, and older women

Populations• Closed or fixed populations

– Membership is permanent and defined by some life event

– Add no new members and only lose members to death

– The size of the population will eventually reach 0 because everyone ultimately dies

Populations• Closed or fixed populations

– Examples: being born in 1975, serving in Iraq or Afghanistan

Populations• Open populations

– Gain members over time through immigration or birth– Lose members through emigration or death– Sometimes called dynamic, but a misnomer b/c both

open and closed populations are changing– If membership can be lost due to events other than

death, then the population is open

Populations• Open populations

– Examples: most populations such as cities, states, hospital populations, etc.

Populations• Steady state populations – a type of open

population– When the number of persons entering the population

is balanced by the number exiting over a period of time

– Example: a city where the number of people moving out or dying is approximately equal to the number moving in or being born between over a given time interval

– Example: population of women in the maternity ward at Alta Bates hospital

Populations• Distinctions can depend on measurement of

time or disease– Example: a population that starts a new drug could

be considered closed if only the population starting at a particular time is included but if new users of the drug are allowed to enter the population it could be considered open

Populations• Relevance

– Population properties are important to consider in study planning• Example: when studying a particular outcome (e.g.,

pregnancy) need to make sure you study a population “at- risk” of that outcome (e.g., women of certain ages)

• Example: should define your study population so that you can address your study question in that population (e.g., differences in PTSD between OEF/OIF Veterans and civilians vs differences in PTSD among OEF/OIF Veterans)

Populations• Example: studying exposure to a fixed event (e.g., hurricane

Katrina) population of interest is fixed/closed and a study would need to be designed to capture that population appropriately

• Example: a population of interest may be open (e.g., tourists visiting a given city) and a study would need to be designed to capture that population appropriately

– Important to consider in calculation and interpretation of measures of disease (more later in relations between measures)