measuring epidemiologic outcomes. epidemiology (schneider) epidemiological outcomes ratio:...
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Measuring
Epidemiologic
Outcomes
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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
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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)
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Epidemiology (Schneider)
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 riskX 1,000
Number of new events during a time period
Incidence Rate =
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Epidemiology (Schneider)
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 riskX 1,000
Number of existing events, old and new
Prevalence =
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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
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Epidemiology (Schneider)
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
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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?
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Epidemiology (Schneider)
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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Epidemiology (Schneider)
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
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Epidemiology (Schneider)
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.
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Epidemiology (Schneider)
Risk Versus Rate
Risk and rate are often used
interchangeably by epidemiologists
but there are differences
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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
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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
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Epidemiology (Schneider)
Incidence Density
ID =
Number of new cases during the time period
Total person-time of observation (often years)
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Epidemiology (Schneider)
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
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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
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Epidemiology (Schneider)
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 =
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Epidemiology (Schneider)
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
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Epidemiology (Schneider)
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 =
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Epidemiology (Schneider)
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
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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
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Epidemiology (Schneider)
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 =
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Epidemiology (Schneider)
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
Number of fetal deaths 20 weeks or more gestation in a given intervalFetal Death
Ratio =
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Epidemiology (Schneider)
Reflects events occurring during pregnancy and after birth
Number of fetal deaths 20 weeks or more gestation plus number of live births during the same interval
X 1,000
Number of fetal deaths 20 weeks or more gestation plus number of
neonatal deaths (28 days or less in age) during a given interval
Perinatal Mortality Rate =
Mortality Measures Related to Natality (cont.)
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Epidemiology (Schneider)
Mortality Measures Related 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 =
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Epidemiology (Schneider)
Mortality Measures Related 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 =
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Epidemiology (Schneider)
Mortality Measures Related 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 =
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Epidemiology (Schneider)
Chart of Early Life Mortality Measures
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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
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Epidemiology (Schneider)
Mortality Outcomes (cont.)Example: 1980
The larger crude death rate in Florida reflects the larger population of elderly in that state.
Location Deaths PopulationCrude Death
Rate per 1,000
Florida 111,114 10,194,000 10.9
Alaska 1,830 416,000 4.4
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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
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Epidemiology (Schneider)
Mortality Outcomes (cont.)
Examples Age-specific rates
Gender-specific rates
Race-specific rates
Cause-specific rates