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1. 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.

2. 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

3. 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.)

4. Populations
• Candidate or “at risk” population
– Example: candidate population for pregnancy
excludes men, currently pregnant women, women
with hysterectomy, and older women

5. 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

6. Populations
• Closed or fixed populations
– Examples: being born in 1975, serving in Iraq or
Afghanistan

7. 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

8. Populations
• Open populations
– Examples: most populations such as cities, states,
hospital populations, etc.

9. 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

10. 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

11. 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)

12. 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)