measures of disease occurrence dr. kamran yazdani, md mph department of epidemiology &...

Measures of Disease Occurrence

Dr. Kamran Yazdani, MD MPHDepartment of Epidemiology & Biostatistics

School of public healthTehran University of Medical Sciences

Learning Objectives:

1. Understand ratios, proportions, and rates.2. Define, calculate, and interpret incidence.3. Understand the use of person-time

denominators.4. Distinguish between cumulative incidence

and incidence rate.5. Define, calculate, and interpret prevalence.6. Distinguish between point and period

prevalence.

Learning Objectives (cont.):

7. Understand special types of incidence and prevalence measures.

8. Understand the interrelationship between incidence, prevalence, and duration of disease.

9. Differentiate the use of incidence and prevalence measures.

The study of the distribution and determinants of health-related states and events in specified populations

and The application of this study to control of

health problems

Definition of Epidemiology

Disease distributionDescriptive Studies

Disease determinantsAnalytic Studies

Two essential components

These main tools in epidemiology are:

Measuring Tools for Describing Categorical Outcomes

• Ratio• Proportion• Rate

= 5 / 2 = 2.5 / 1

• The quotient of 2 numbers• Numerator NOT necessarily INCLUDED in the

denominator• Allows to compare quantities of different nature

Ratio

Ratio, Examples # beds per doctor

– 850 beds/10 doctors– R = 85 beds for 1 doctor

# participants per facilitator # inhabitants per latrine

Sex ratio: Male / Female Female / Male

Odds ratio Rate ratio Prevalence ratio

2--- = 0.5 = 50% 4

Proportion• The ratio of 2 numbers• Numerator NECESSARELY INCLUDED

in the denominator• Quantities have to be of same nature• Proportion always ranges between 0 and 1 • Percentage = proportion x 100

Proportion, Examples

Proportion of Myopia in a survey sample:

– 5600 samples, 168 myopic patients

– Proportion of myopics = 168/5600 = 0.03

– Percentage of myopics = 3%

Indicates the magnitude of a part, related to the total.

In epidemiology, tells us the fraction of the population that is affected.

Numerical value of a proportion: 0 to 1.0

Linked to probability theory (i.e. risk of developing disease)

For ease of usage, can multiply a proportion by 100 to get a percentage

Example: p = 0.03 = 3%

Proportions

A proportion in which TIME forms part of the denominator

Speed of occurrence of an event over time

Numerator - number EVENTS observed for a given time

Denominator- population in which the events occur

includes time

Rates

Epidemiologic rates contain the following elements:

• disease frequency (in the numerator)• unit size of population• time period during which an event

occurs

Rates

Calculate crude annual death rate in the US:

Crude death rate =(Annual death count / Reference population (during midpoint of year))

x 1,000

Death count in U.S. during 1990:2,148,463U.S. population on June 30, 1990: 248,709,873

2,148,463Crude death rate = ----------------- x 1,000 = 8.64 / 1,000 / year

248,709,873

Rates – Example

Discussion QuestionDiscussion Question

What does a crude annual death rate of8.64 per 1,000 per year mean?

Measures of Disease OcurrenceMeasures of Disease Ocurrence(frequency)(frequency)

IncidenceHow fast are new cases occurring?

PrevalenceHow much disease is present now?

Incidence

The development of new cases of a disease that occur during a specified period of time in previously disease-free or condition-free (“at risk”) individuals.

Incidence Incidence quantifies the “development” of disease --- Most fundamental measure of

disease frequency and leads to the development of the concept of risk (i.e transition from non-diseased to diseased state)

- Cumulative incidence (CI)(“Incidence proportion”)

- Incidence rate (IR)(“Incidence density”)

Cumulative Incidence (CI)PROPORTION of individuals who become diseased during a specified period of time(e.g. all new cases during 1998)

Range: 0 to 1.0

Also referred to as “incidence proportion.”

Cumulative Incidence (CI)

No. of new cases of disease during a given periodCI = --------------------------------------------------------------

Total population at risk during the given period

Example: During a 1-year period, 10 out of 100 “at risk” persons develop the disease of interest.

10CI = ----- = 0.10 or 10.0%

100

Cumulative Incidence (CI)

To accurately calculate cumulative incidence, we need to follow the entire population for the specified time interval. Often times, this does not fully occur.

Cumulative incidence provides an estimate of the probability (risk) that an individual will develop a disease during a specified period of time.

Cumulative Incidence (CI) Keep in mind that over any appreciable

period of time, it is usually technically impossible to measure risk.

This is because if a population is followed over a period of time, some people in the population will die from causes other than the outcome under study

The phenomenon of being removed from a study through death from other causes is referred to as ”competing risks”.

Cumulative Incidence (CI) When the follow-up of patients is

incomplete, we have to use the survival analysis methods:

– Life Table

– Kaplan-Meier

Cumulative Incidence Incidence proportion

Risk

CI assumes that entire population at risk followed up for specified time period

xxx

x

x

x

xx disease onset

Month 1 Month12

CI = 7/12 per year

= 0.58 per year

Incidence Rate (IR)No. new cases of disease during a given period

IR = -----------------------------------------------------------Total “person-time” of observation

Range = 0 to Infinity

Since the number of cases is divided by a measure of time of observation, rather than people, this helps address the problem of competing risks.

Incidence Rate (IR)

When we observe a group of individuals for a period of time in order to ascertain the DEVELOPMENT of an event….

- The actual time each individual is observed will most likely vary.

What is person time?


In a 2-year study of the development of disease X, why might the actual

time each individual is observed vary?


Because:• Subjects may be recruited at different times

• Subjects may emigrate

• Subjects may choose to leave study

• Subjects may die

• Subjects may get the disease we are

studying

Person-TimePerson Follow-up Time on Study Person Yrs.

1 <-------------------------------------> 2 2 <--------------------------------------D 2 3 <-----------------WD 1 4 <-------------------------------------------------------> 3 5 <-------------------------------------> 2

1995 1996 1997 1998 Jan. Jan. Jan. Jan.

Study Period: 3 YearsStudy Participants: 5Person Years of Observation: 10Average Duration of Follow-Up: 2.0 Years

No. new cases of disease during a given periodIR = ------------------------------------------------------------

Total “person-time” of observationSo,

1 caseIR = ----------- = 1 case per 10 P-Y follow-up

10 P-YWhereas,

1 caseCI = ------------ = 0.20 = 20.0%

5 persons

Incidence Rate (IR)

When we use individual data (cohort study):We use person-time as the denominator

Incidence Density

When we use aggregate data:We use the average population as the denominator

Incidence RateAssumptio: homogenous distribution of events and

losses (or additions)e.g.

Crude Death Rate

Incidence Rate (IR)

The IR of 1 case per 10 P-Y is equivalent to 0.2 cases per 2 years:which suggests a 20% risk of disease development within 2 years of follow-up.

Whereas, the CI risk estimate of 20% (1 case per 5 persons) was based on a period of 3 years of follow-up.

Comparison of IR and CI

Risk and rate are often used interchangeably by epidemiologists

but there are differences


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


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



Previously, we said that the incidence ratecan range from 0 to infinity!

How can this be?


Example100 subjects have been followed up for 2 month. 20 events have occurred during this time. What is the IR in P-Y?


Example100 subjects have been followed up for 2 month. 20 events have occurred during this time. What is the IR in P-Y?IR = (20/100) / 2 = 1 per 10 person-month

= 12 per 10 P-Y = 120%/yearTherefore, as time increases, IR approaches

infinity.

Incidence Rate (IR)

NOTE: The selection of the time unit for thedenominator is arbitrary, and is notdirectly interpretable:

Example: 100 cases / person yearcan also be expressed as:

10,000 cases / person century8.33 cases / person month1.92 cases / person week0.27 cases / person day

In general:Risk estimates derived from IR and CI calculations

will be similar when:• Follow-up loss is minimal• The disease of interest occurs infrequently.

CI is most useful if interest centers on the probability than an individual will become ill over a specified period of time.

IR is preferred if interest centers on how fast the new cases are occurring in the population.


Measures of Prevalence Prevalence

– Point prevalence Do you have health condition now?

– Period prevalence Have you had health condition during past six

months?– Lifetime prevalence

Have you ever had health condition?

Importance of Prevalence Data

Burden of illness in population– Treatment needs– Burden on social services– Burden on individual well-being

“Point” PrevalenceThe usual prevalence

Number of existing casesP = --------------------------------

Total population

At a set point in time (i.e. September 30, 1999)

“Point” Prevalence

Example:On June 30, 1999, neighborhood A has:

• population of 1,600• 29 current cases of hepatitis B

So, P = 29 / 1600 = 0.018 or 1.8%

“Period” Prevalence Number of existing cases

Pp = -------------------------------- Total population

During a time period (i.e. May 1 - July 31, 1999)Includes existing cases on May 1, and

thosenewly diagnosed until July 31.

“Period” PrevalenceExample:Between June 30 and August 30, 1999,

neighborhood A has:• average population of 1,600• 29 existing cases of hepatitis B on June 30• 6 incident (new) cases of hepatitis B

between July 1 and August 30

So, Pp = (29 + 6) / 1600 = 0.022 or 2.2%

“lifetime” Prevalence Number of existing cases

LP = -------------------------------- Total population

During any time in the past

Prevalence

In general, a person’s probability of being captured as a prevalent case is proportional to the duration of his or her disease.

Thus, a set of prevalent cases tends to be skewed toward cases with more chronic forms of the disease.


How are incidence andprevalence of disease related?


Prevalence depends on:

- Incidence rate

- Disease duration

House Guests Example

Relationship between prevalence and incidenceRelationship between prevalence and incidence

WHEN (the steady state is in effect):

a) Incidence rate (I) has been constant over time

b) The duration of disease (D) has been constant over time:

ID = P / (1 – P)

P = ID / (1 + ID)

c) If the prevalence of disease is low

(i.e. < 0.10 or 0.05): 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


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

Study design for Study design for Incidence & PrevalenceIncidence & Prevalence

Incidence (follow-up studies):- Cohort study- Clinical trial

Prevalence: - Cross-sectional- Case-Control (prevalent cases)

Uses of Incidence & Uses of Incidence & Prevalence MeasuresPrevalence Measures

Prevalence: Snap shot of disease or health event

Help health care providers plan to deliver services

Indicate groups of people who should be targeted for control measures

May signal etiologic relationships, but also reflects determinants of survival

Uses of Incidence & Uses of Incidence & Prevalence MeasuresPrevalence Measures

Incidence: Measure of choice to:--- Estimate risk of disease development--- Study etiological factors--- Evaluate primary prevention programs


Why is incidence preferred overprevalence when studying the

etiology of disease?

Because, in the formula: P = I x D

D is related to : - The subject’s constitution - Access to care

- Availability of treatment - Social support - The severity of disease


So prevalent cases reflect factors related to the incidence of disease (Etiological factors), AND factors related to the duration of disease (Prognostic factors)

Thus, they are not adequate for studies trying to elucidate Disease Etiology


PROBLEMS WITH INCIDENCE AND PROBLEMS WITH INCIDENCE AND PREVALENCE MEASURESPREVALENCE MEASURES

Problems with Numerators:

• Frequently, the diagnosis of cases is not straightforward

• Where to find the cases is not always straightforward

PROBLEMS WITH INCIDENCE AND PROBLEMS WITH INCIDENCE AND PREVALENCE MEASURESPREVALENCE MEASURES

Problems with Denominators:

• Classification of population subgroups may be ambiguous (i.e race/ethnicity)

• It is often difficult to identify and remove from the denominator persons not “at risk” of developing the disease.

Exercise

0123456789

10

Jan Feb Mar Apr May Jun Jul

Ratio males / female=? Prevalence March1 =?Proportion of women=? Prevalence March-July =?

Incidence Proportion March-July =?

Exercise

A

B

C

D

E

90 91 92 93 94 95 96 97 98 99 00 Time at risk

x

x

6.0

6.0

11.0

9.5

5.0

Total years at risk 37.5

-- time followedx disease onset ID = ?

What is the interpretation?

measures of disease occurrence dr. kamran yazdani, md mph department of epidemiology &...

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