1. Measuring Epidemiologic Outcomes
Data Sets and Outcome Measures - Part 2

2. 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

3. Rates tell us how fast the disease is occurring in a population.
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)

4. Number of new events during a time period
Morbidity Measures
Number of new events during a time period
X 1,000
Incidence Rate =
Population at risk
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

5. Number of existing events, old and new
Morbidity Measures
Population at risk
X 1,000
Number of existing events, old and new
Prevalence =
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

6. 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

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

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

9. Diagnosed cases of Skin Cancer
on Sunny Beach, 9/28/1974            
# of existing cases = 10
Total population at risk = 450          
Point Prevalence (9/28/1974)
= (10/450)*1000
= 22 per 1000  

10. Diagnosed cases of Skin Cancer Average population at risk = 500
on Sunny Beach, 1975
Average population at risk = 500             
# of new cases = 5  
Incidence rate (year 1975)
= (5/500)*1000
= 10 per 1000            
Period prevalence (year 1975)
= (15/500)*1000
= 30 per 1000  

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

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

13. 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

14. 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

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

16. 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

17. 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

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

19. 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

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

21. Natality Outcomes (cont.)
Total fertility rate: Same as above, but use women 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

22. 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

23. 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

24. 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

25. 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
X 1,000
Number of fetal deaths 20 weeks or more gestation plus number of live births during the same interval
Reflects events occurring during pregnancy and after birth

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

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

28. 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

29. Chart of Early Life Mortality Measures

30. 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

31. Mortality Outcomes (cont.)
Example: 1980
Location
Deaths
Population
Crude Death Rate 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.

32. 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

33. Mortality Outcomes (cont.)
Examples
Age-specific rates
Gender-specific rates
Race-specific rates
Cause-specific rates