Top Banner
Measuring Epidemiologic Outcomes
33
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Page 1: Week 2 ppt

Measuring

Epidemiologic

Outcomes

Page 2: Week 2 ppt

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

Page 3: Week 2 ppt

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)

Page 4: Week 2 ppt

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

periodIncidence Rate =

Page 5: Week 2 ppt

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 =

Page 6: Week 2 ppt

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

Page 7: Week 2 ppt

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

Page 8: Week 2 ppt

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?

Page 9: Week 2 ppt

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 r isk = 450

Page 10: Week 2 ppt

Epidemiology (Schneider)

Diagnosed cases of Skin Cancer on Sunny Beach, 1975

Average population at r isk = 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

Page 11: Week 2 ppt

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.

Page 12: Week 2 ppt

Epidemiology (Schneider)

Risk Versus Rate

Risk and rate are often used

interchangeably by epidemiologists

but there are differences

Page 13: Week 2 ppt

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

Page 14: Week 2 ppt

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

Page 15: Week 2 ppt

Epidemiology (Schneider)

Incidence Density

ID =

Number of new cases during the time period

Total person-time of observation (often years)

Page 16: Week 2 ppt

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

Page 17: Week 2 ppt

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

Page 18: Week 2 ppt

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 =

Page 19: Week 2 ppt

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

Page 20: Week 2 ppt

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 =

Page 21: Week 2 ppt

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

Page 22: Week 2 ppt

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

Page 23: Week 2 ppt

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 =

Page 24: Week 2 ppt

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 =

Page 25: Week 2 ppt

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.)

Page 26: Week 2 ppt

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 =

Page 27: Week 2 ppt

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 =

Page 28: Week 2 ppt

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 =

Page 29: Week 2 ppt

Epidemiology (Schneider)

Chart of Early Life Mortality Measures

Page 30: Week 2 ppt

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

Page 31: Week 2 ppt

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

Page 32: Week 2 ppt

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

Page 33: Week 2 ppt

Epidemiology (Schneider)

Mortality Outcomes (cont.)

Examples

Age-specific rates

Gender-specific rates

Race-specific rates

Cause-specific rates