Measuring
Epidemiologic
Outcomes
Epidemiological Outcomes

Ratio: Relationship between two numbers
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Proportion: A ratio where the numerator is included
in the denominator


Example: males/females
Example: males/total births
Rate: A proportion with the specification of time

Example: (deaths in 1999/population in 1999) x 1,000
Epidemiology (Schneider)
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)
Epidemiology (Schneider)
Morbidity Measures
Incidence Rate =
Number of new
events during a time
period
Population at risk
X 1,000

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
Epidemiology (Schneider)
Morbidity Measures
Prevalence =
Number of existing
events, old and new
Population at risk
X 1,000

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
Epidemiology (Schneider)
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
Epidemiology (Schneider)
Relationship Between Incidence and
Prevalence (cont.)


Cancer of the pancreas

Roseola infantum

Incidence low

Incidence high

Duration short

Duration short

Prevalence low

Prevalence low
Adult onset diabetes

Essential hypertension

Incidence low

Incidence high

Duration long

Duration long

Prevalence high

Prevalence high
Epidemiology (Schneider)
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?
Epidemiology (Schneider)
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Diagnosed cases of Skin Cancer
on Sunny Beach, 9/28/1974
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# of existing cases = 10
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Total population at risk = 450

Point Prevalence (9/28/1974)
= (10/450)*1000
= 22 per 1000
Epidemiology (Schneider)
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Diagnosed cases of Skin Cancer
on Sunny Beach, 1975

Average population at risk = 500
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# of new cases = 5
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Incidence rate (year 1975)
= (5/500)*1000
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= 10 per 1000
Period prevalence (year 1975)
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= (15/500)*1000
= 30 per 1000
Epidemiology (Schneider)



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.
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?
Epidemiology (Schneider)
Risk Versus Rate
Risk and rate are often used
interchangeably by epidemiologists
but there are differences
Epidemiology (Schneider)
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
Epidemiology (Schneider)
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
Epidemiology (Schneider)
Incidence Density
ID =
Epidemiology (Schneider)
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
Epidemiology (Schneider)
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
Epidemiology (Schneider)
Natality Outcomes

Natality measures are used primarily by
demographers for population projection
Number of live births
Crude Birth Rate =
Epidemiology (Schneider)
for a given time period (year)
Estimated mid-interval total
population
X 1,000
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
Epidemiology (Schneider)
Natality Outcomes (cont.)
Number of live births for a
given time period (year)
General Fertility Rate =
Estimated # of women 1544 years at mid-interval
Epidemiology (Schneider)
X 1,000
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
Epidemiology (Schneider)
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
Epidemiology (Schneider)
Mortality Measures Related to Natality

Fetal Death Rate or Ratio: Used primarily by public
health officials to estimate the health of populations
Fetal Death
Rate =
Number of fetal deaths 20 weeks or
more gestation in a given interval X 1,000
Fetal deaths plus live births in
that interval
Estimates risk of death associated with late states of gestation
Epidemiology (Schneider)
Mortality Measures Related
to Natality (cont.)
Fetal Death
Ratio =
Number of fetal deaths 20 weeks or
more gestation in a given interval
X 1,000
Number of live births reported
during the same time interval
Measures fetal loss relative to live births
Epidemiology (Schneider)
Mortality Measures Related
to Natality (cont.)
Perinatal
Mortality
Rate =
Number of fetal deaths 20 weeks or
more gestation plus number of
neonatal deaths (28 days or less in
age) during a given interval
Number of fetal deaths 20 weeks or
more gestation plus number of live
births during the same interval
X 1,000
Reflects events occurring during pregnancy and after birth
Epidemiology (Schneider)
Mortality Measures Related
to Natality (cont.)
Number of deaths of neonates
Neonatal Mortality (28 days or less) in a given interval
X 1,000
Rate =
Number of live births during
the same interval
Estimates events immediately after birth, primarily
congenital malformations, prematurity and low birth weight
Epidemiology (Schneider)
Mortality Measures Related
to Natality (cont.)
Infant Mortality
Rate =
Number of deaths under 1
year during a given interval
Number of live births during
the same interval
X 1,000
Used for international comparisons; high rates indicate
unmet public health needs and poor socioeconomic and
environmental conditions
Epidemiology (Schneider)
Mortality Measures Related
to Natality (cont.)
Maternal
Mortality
Rate =
Number of deaths assigned to
causes related to pregnancy during
a given interval
X 1,000
Number of live births during the
same interval
Rates reflect health care access and socioeconomic factors
Epidemiology (Schneider)
Chart of Early Life Mortality Measures
Epidemiology (Schneider)
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
Epidemiology (Schneider)
Mortality Outcomes (cont.)
Example: 1980
Location
Deaths
Crude Death Rate
Population
per 1,000
Florida
111,114
10,194,000
10.9
Alaska
1,830
416,000
4.4
The larger crude death rate in Florida reflects the
larger population of elderly in that state.
Epidemiology (Schneider)
Mortality Outcomes (cont.)

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
Epidemiology (Schneider)
Mortality Outcomes (cont.)

Examples

Age-specific rates

Gender-specific rates

Race-specific rates

Cause-specific rates
Epidemiology (Schneider)