Week 2 ppt

Measuring
Epidemiologic
Outcomes

Epidemiology (Schneider)
Epidemiological Outcomes
 Ratio: Relationship between two numbers
 Example: males/females
 Proportion: A ratio where the numerator is included
in the denominator
 Example: males/total births
 Rate: A proportion with the specification of time
 Example: (deaths in 1999/population in 1999) x 1,000

In epidemiology, the occurrence of a disease
or condition can be measured using rates
and proportions. We use these measures to
express the extent of these outcomes in a
community or other population.
 Rates tell us how fast the disease is
occurring in a population.
 Proportions tell us what fraction of
the population is affected.
(Gordis, 2000)

Morbidity Measures
 Incidence is always calculated for a given
period of time
 An attack rate is an incidence rate calculated
for a specific disease for a limited period of
time during an epidemic
Population at risk
X 1,000
Number of new
events during a time
period
Incidence Rate =

Morbidity Measures
 Prevalence is not a rate
 Point prevalence measures the frequency of all
current events (old and new) at a given instant in
time
 Period prevalence measures the frequency of all
current events (old and new) for a prescribed
period of time
Population at risk
X 1,000
Number of existing
events, old and new
Prevalence =

Interrelationship: P ≅ ID
High prevalence may reflect:
 High risk
 Prolonged survival without cure
Low prevalence may reflect:
 Low risk
 Rapid fatal disease progression
 Rapid cure
Examples: Ebola, Common cold

Relationship Between Incidence and
Prevalence (cont.)
 Cancer of the pancreas
 Incidence low
 Duration short
 Prevalence low
 Adult onset diabetes
 Incidence low
 Duration long
 Prevalence high
 Roseola infantum
 Incidence high
 Duration short
 Prevalence low
 Essential hypertension
 Incidence high
 Duration long
 Prevalence high

Calculation Practice
Skin Cancer on Sunny Beach:
1. Point prevalence on 9/28/1974
2. Period prevalence for year 1975
3. Incidence rate for year 1975
What information will you need?

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Diagnosed cases of Skin Cancer
on Sunny Beach, 9/28/1974
Point Prevalence (9/28/1974)
= (10/450)*1000
= 22 per 1000
# of existing cases = 10
Total population at risk = 450
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Diagnosed cases of Skin Cancer
on Sunny Beach, 1975
Average population at risk = 500
Incidence rate (year 1975)
= (5/500)*1000
= 10 per 1000
Period prevalence (year
1975)
= (15/500)*1000
= 30 per 1000
# of new cases = 5

JAN
2000
MAY JULY SEPT
DEC
2000
What is the numerator for incidence in 2000?
What is the numerator for point prevalence if a survey
was done in May? July? September? December?
Number of cases of disease beginning, developing, and ending
during a period of time, January 1, 2000 – December 31, 2000.
Length of each line corresponds to duration of each case.

Risk Versus Rate
Risk and rate are often used
interchangeably by epidemiologists
but there are differences

Risk Versus Rate (cont.)
 Risk is a probability statement assuming an
individual is not removed for any other reason
during a given period of time
 As such, risk ranges from 0 to 1 (no chance to
100% probability of occurrence)
 Risk requires a reference period and reflects the
cumulative incidence of a disease over that period
 Example: 1 in a million chance of developing
cancer in a 70 year lifetime

Risk Versus Rate (cont.)
 Rates can be used to estimate risk if the time
period is short (annual) and the incidence of
disease over the interval is relatively constant
 If however, individuals are in a population for
different periods of time for any reason, then
you should estimate risk by incidence density

Incidence Density
ID =
Number of new cases
during the time period
Total person-time of
observation (often years)

ID Example
 In the Iowa Women’s Health Study (IWHS), 37,105
women contributed 276,453 person-years of
follow-up
 Because there were 1,085 incident cases, the rate
of breast cancer using the incidence density
method is:
1,085/276,453 = 392.5/100,000 person-years

ID Example (cont.)
 If each woman had been followed for the
entire 8-year period of the study, the total
person-years would have been 296,840 and
the rate would have been lower (assuming the
number of incident cancers was the same)
 The incidence density method yielded a
higher and more accurate estimate

Natality Outcomes
 Natality measures are used primarily by
demographers for population projection
Estimated mid-interval total
population
X 1,000
Number of live births
for a given time period (year)
Crude Birth Rate =

Concerns About Crude Birth Rates
 Definitions of a live birth may vary
 U.S. = “any product of conception that shows any
sign of life after complete birth (pulse, heartbeat,
respiration, crying, pulsation of umbilical cord or
movement of the voluntary muscles)”
 The denominator used for birth rates is inaccurate
because men are not part of the population-at-risk

Natality Outcomes (cont.)
Estimated # of women 15-
44 years at mid-interval
X 1,000
Number of live births for a
given time period (year)
General Fertility Rate =

Natality Outcomes (cont.)
 Total fertility rate: Same as above, but use
women 10-49 years and adjust for age cohorts
 Gross reproductive rate: Same as TFR, but use
only live births of females in numerator
 Net reproductive rate: Same as GRR, but count
only births of females who survive to
reproductive age in the numerator

Net Reproductive Rate (NRR)
 If NRR = 1,000, each generation will just
replace itself
 If NRR < 1,000, indicates a potentially
declining population
 If NRR > 1,000, indicates a potential
population increase

Mortality Measures Related to Natality
 Fetal Death Rate or Ratio: Used primarily by public
health officials to estimate the health of populations
Estimates risk of death associated with late states of gestation
Fetal deaths plus live births in
that interval
X 1,000
Number of fetal deaths 20 weeks or
more gestation in a given intervalFetal Death
Rate =

Mortality Measures Related
to Natality (cont.)
Measures fetal loss relative to live births
Number of live births reported
during the same time interval
X 1,000
more gestation in a given intervalFetal Death
Ratio =

Reflects events occurring during pregnancy and after birth
more gestation plus number of live
births during the same interval
X 1,000
more gestation plus number of
neonatal deaths (28 days or less in
age) during a given interval
Perinatal
Mortality
Rate =
to Natality (cont.)

to Natality (cont.)
Estimates events immediately after birth, primarily
congenital malformations, prematurity and low birth weight
Number of live births during
the same interval
X 1,000
Number of deaths of neonates
(28 days or less) in a given
intervalNeonatal Mortality
Rate =

to Natality (cont.)
Used for international comparisons; high rates indicate
unmet public health needs and poor socioeconomic and
environmental conditions
Number of live births during
the same interval
X 1,000
Number of deaths under 1
year during a given intervalInfant Mortality
Rate =

to Natality (cont.)
Rates reflect health care access and socioeconomic factors
Number of live births during the
same interval
X 1,000
Number of deaths assigned to
causes related to pregnancy during
a given interval
Maternal
Mortality
Rate =

Chart of Early Life Mortality Measures

Mortality Outcomes
 Crude rate:
 The number of events in a population over a
given period of time, usually a calendar year
 Crude rates reflect the probability of an event
 As the probability of death increases with age,
the crude death rate reflects the age structure
of the population

Mortality Outcomes (cont.)
Example: 1980
The larger crude death rate in Florida reflects the
larger population of elderly in that state.
Location Deaths Population
Crude Death Rate
per 1,000
Florida 111,114 10,194,000 10.9
Alaska 1,830 416,000 4.4

 Specific rate:
 Used to construct rates for specific segments
of the population so we can compare among
strata or between groups (used especially for
age, race, ethnicity, gender)
 We can also construct cause-specific rates to
compare rates among causes

 Examples
 Age-specific rates
 Gender-specific rates
 Race-specific rates
 Cause-specific rates

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