Descriptive Epidemiology Lecture Note-1

Basic Epidemiology

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EPIDEMIOLOGIC VARIABLES

In descriptive epidemiology data is organized according to time, place and person. These three characteristics are sometimes called epidemiologic variables.

Compiling data by time, place and person is done in order to:

• Become familiar with the data and the extent of the problem.

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EPIDEMIOLOGIC VARIABLES

• Provide a detailed description of the health of a population that is easily communicated.

• Identify the population at greater risk of acquiring a particular disease. This information provides important clues to the causes of a disease, and these clues can be turned into testable hypotheses.

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Some details on Epidemiologic Variables:

TIME:In Epidemiology knowing the time where the

diseases occurred will help to define:

Epidemic period Secular trends Seasonality

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How do you represent the change in disease rates over time?

• The change in disease rates over time is usually shown on a graph, with number or rate of cases or deaths on the vertical axis and the time period in a horizontal axis.

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We can thereby define: The epidemic period: is a period during which the number

of cases reported is greater than normal. The epidemic curve is generally represented by a histogram.

Secular trends: Which are long term trends in disease incidence (over years)?

Secular trends are useful to predict the future and to evaluate policies and programs.

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Seasonality: Seasonality in diseases distribution can be identified by graphing the occurrence of a disease by week or month over the course of the year.

Seasonal patterns may suggest hypotheses about how an infection is transmitted, behavioral risk factors, or other possible contributing factors.

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PLACE:• By analyzing data by place, we can get an idea

where the disease agent occurs, what may carry it, and how it spreads.

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• Where the occurrence of a diseases is associated with a place, we can infer that factors which increase the risk of a disease are present in either the persons living there (HOST FACTOR) or in the environment(ENVIRONMENTAL FACTOR), or both.

• A spot map may be used to represent the location of each case’s home or workplace, or where we believe cases were exposed.

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PERSON:• Person data may be shown in tables or graphs and

may reflect the inherit characteristics of people (age, gender, ethnic group) their acquired characteristics (educational, marital, immune or nutritional status), their activities (Occupation, leisure time activities, use of alcohol, tobacco, medication), or the condition in which they live (socio economic status, access to health)

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AGE: Age is probably the single most important “person” attribute in descriptive epidemiology. Data should be analyzed by age groups which are narrow enough (often 5 years) to detect any age related patterns.

SEX: sex related differences in diseases

incidence can provide important clues to causes of disease.

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• ETHNIC GROUP AND SOCIO ECONOMIC STATUS: These are also important variables in descriptive epidemiology.

These differences may also be related to other factors, such as living conditions, behavioral patterns, or access to health care which may also affect patterns of health and diseases.

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Measures of Disease Occurrence

• The number of cases in a given community can give more epidemiologic sense if they are related to the size of the population.

• Such tie of the number of cases with the population size can established by calculating ratios, proportions, and rates.

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Measures of Disease Occurrence

• These measures provide useful information about the probability of occurrence of health events and population at a higher risk of acquiring the disease. They are also important in designing an appropriate public health interventions.

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What is a variable?

• A VARIABLE is a characteristic of a person, object or phenomenon which can take on different values. These may be in the form of numbers (e.g., age) or non-numerical characteristics (e.g., sex).

(Handout)

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RATIOS, PROPORTIONS AND RATES:

Frequencies for specific variables may be expressed in frequency distributions for ORDINAL (with values ranked in a graded order) variables.

ORDINAL scale data may be further summarized with measures of central location and measures of dispersion.

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Many NOMINAL (with names or categories) variables have only two categories (e.g., alive or dead, sick or well, exposed or unexposed).

The frequency measures we use with such dichotomous variables are rates, ratios and proportions.

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• All the three measures use the same formula.Ratio, proportion and rates = x x 10n

y• Relate the number of cases to the size of the

population in which they occurred.

• They reflect the probability of occurrence of a particular event.

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Use of such measures:In health and public health fields:• Help to identify high risk groups which can be

targeted for special interventions. These groups can be studied to identify risk factors which are related to the occurrence of diseases.

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RATIO:• A ratio is the expression of the relationship

between a numerator and denominator which may involve either an interval in time or may be instantaneous in time. The ratio is the form:

X: Y or x x k Y

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Where X = number of events or items counted and not

necessary a portion of yY = number of events or items counted and not

necessary a population of persons exposed to the risk.

K= a base, as in the case of the rates, but usually 1 or 100 for the purpose of expressing ratios.

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In ratio, the value of x and y may be completely independent, or x may be included in y.

Example: The sex of children attending an immunization clinic could be compared in either of the following ways.

( 1) female/male (2) female/allIn the first option x (female) is completely independent

of y (male). In the second, x (female) is included in y (all).

Both examples are ratios.

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PROPORTION:• A proportion is the second type of frequency

measure used with dichotomous variables, is ratio in which x is included in y or in other words. It s an expression in which the numerator is always included in the denominator, and the base is equal to 100.

• Therefore proportion is always expressed in as a percent.

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RATE: The third type of frequency measure used with

dichotomous variables, rate, is often a proportion. With an added dimension.

Rate measures the occurrence of an event in a population over time.

A rate is often expressed in the form of: X x k

Y

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Where: X = number of times an event has occurred during a

specific interval of time. Y = number of persons exposed to the risk of the event

during the same intervalK= some round number (100, 1000, 10,000, 100,000

etc) or base depending upon the relative magnitude of x and y.

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The basic formula for a rate is as follows:

Rate = Number of cases or events occurring during a given time period X 10n Population at risk during the same period

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Notice the three most important aspects of this formula:

• The persons in the numerator must reflect the population from which the cases in the denominator arose.

• The counts in the numerator and denominator should cover the same time period.

• In theory, the persons in the denominator must be “at risk” for the event, that is, it should have been possible for them to experience the same or similar event.

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Points to consider about rates, ratios and proportions:

• When we call a measure a ratio we usually mean a non proportional ratio.

• When we call a measure a proportion we usually mean a proportional ratio that does not measure an event over time.

• When we use the term rate, we frequently refer to a proportional ratio that does measure an event in a population over time.

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INDEX: • An index is the best available approximation to the

true rate. This usually occurs when we are unable to count directly the number at risk (the denominator) and use something else which we can count to give us an impression of the number at risk.

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Example: The calculation of MMR The MMR calculated with approximation of a

denominator is not at all a rate in a strict sense, but is nevertheless a useful index which gives an impression of the risk of dying associated with pregnancy.

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Exercise

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Use of RATIOS, PROPORTIONS, and RATES

• In public health, we use ratios and proportions to characterize populations by age, sex, race, exposures and other variables.

• We also use ratios, proportions, and most important rates to describe three aspects of the human condition: morbidity (diseases), mortality (death) and natality.

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Condition: Morbidity (disease)• Ratios: Risk ratio (relative risk)

Rate ratioOdds ratio

• Proportions: Attributable proportionPoint prevalence

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• Rates: Incidence rate, Attack rate, Secondary attack rate,Person time rate, Period prevalence

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Condition: Mortality (death) • Ratios: Date to case ratio

Maternal mortality rateProportionate mortality ratioPost neonatal mortality ratio

• Proportions:Proportionate mortalityCase fatality rate

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• Rates: Crude mortality rate Case specific mortality rateSex specific morality rate Age specific morality rate Race specific morality rate Age adjusted morality rate Neonatal morality rate Infant mortality rateYears of potential life lost rate

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Condition: Natality (birth) • Ratios:

Male to female ratio at Birth

• Proportions:Low Birth Weight Ratio

• Rates: Crude Birth Rate Crude Fertility Rate Crude Rate of Natural Increase

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MORBIDITY FREQUENCY MEASURES:

• To describe the presence of disease in a population, or the probability (risk) of its occurrence, we use one of the morbidity frequency measures.

• In public health terms, disease includes illnesses, injuries, or disability.

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• Morbidity rates measure the frequency of illness within specific populations.

• In morbidity rates, time and place must always be specified

• The most commonly used morbidity rates include point prevalence, period prevalence, and incidence and attack rate.

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Frequently used measures of morbidity• INCIDENCE: Incidence is a measure of the frequency

with which an event, such as a new case of illnesses, occurs in a population over a period of time.

• These new cases of a disease occur either through the onset of the disease on current members of the population or through immigration of persons already ill in the population.

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• Incidence rates are the most common way of measuring and comparing the frequency of disease in a population.

• Incidence rate expresses the probability or risk of an illness in a population over a period of time.

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• Since incidence rate is a measure of risk, when one population has a higher incidence of diseases than another, we say that the first population is at higher risk of developing disease than the second, all other factors being equal. We can also express this by saying that the first population is a high risk group relative to the second population.

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Incidence rate: New cases occurring during a given period x 10 n

Population at risk during the same time period

Numerator (x):• Number of new cases of specified disease reported

during a given time intervalDenominator (y):• Average population during time interval Expressed per number of Risk (10n): Varies 10n where n=2,3,4,5,6

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Exercise 2

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PREVALENCE: • Prevalence, sometimes referred to as

prevalence rate, is a proportion of persons in a population who have a particular disease or attribute at a specified point in time or over a period of time.

• Prevalence measures the frequency of all current cases of diseases (old and new) and is of two types:

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The general formula of prevalence is:

Prevalence = all new and pre existing cases during a given time period x 10n

Population during the same time period

The formula for prevalence of an attribute is:Prevalence = Persons having a particular attribute during a given period of time x 10n

Population during the same time periodThe value of 10n may be 1,000, 100,000, or even 1,000,000 for rare traits

and for most diseases.

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Prevalence is commonly of TWO types:

Point Prevalence: Point Prevalence measures the frequency of all current cases of diseases (old and new) at a given instant in a time.

Point prevalence would help us to know how much of a particular disease is present in a population at a single point in time. To get a snap shot look at the population with regard to that diseases.

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Measure: (Point prevalence)Numerator (x):• Number of current cases (new and old) of a

specified disease at a given point in timeDenominator (y):• Estimated population at the same point in timeExpressed per number of Risk (10n): Varies 10n where n=2,3,4,5,6

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Period Prevalence: Period Prevalence measures the frequency of all current cases of diseases (old and new) for a prescribed period of time.

Measure: (Period prevalence)• Numerator (x):Number of current cases (new and old) of a specified disease over a

given time interval • Denominator (y):Estimated population at mid interval • Expressed per number of Risk (10n): Varies 10n where n=2,3,4,5,6

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Some points to note: • A case is counted in prevalence until death or

recovery occurs. • Prevalence is based on incidence (risk) and duration

of disease. High prevalence of a disease within a population may reflect high risk or prolonged survival without cure. Conversely low prevalence may reflect low incidence, a rapidly fatal process, or rapid recovery.

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…Some points to note:• We often use prevalence rather than

incidence to measure the occurrence of chronic diseases such as osteoarthritis which have long duration and dates of onset which are difficult to pin point.

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ATTACK RATE: Attack rate is an incidence rate usually expressed as a percent, used for particular populations (the population at risk), and observed for limited period of time, as an epidemic. The attack rate is usually expressed as a percent, so 10n equals 100.

Attack rate = Number of new cases among the population during the period x 100

Population at risk at the beginning of the period

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Measure: (Attack Rate)

Numerator (x):• Number of new cases of specified disease reported during

an epidemic period

Denominator (y):• Population at the start of the epidemic period

Expressed per number of Risk (10n): • Varies 10n where n=2,3,4,5,6

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Points to note: Attack rate is a proportion – the person in the numerator is also in the denominator. This proportion is a measure of probability or risk of becoming a case.

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Secondary Attack Rate:• A secondary attack rate is a measure of the

frequency of new cases of a disease among the contacts of known cases.

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S-Attack rate = Number cases among contacts of primary cases during the period x 10n

Total number of contacts

Numerator (x):• Number of new cases of specified disease among contacts of

known cases

Denominator (y):• Size of contact population at risk • Expressed per number of Risk (10n): • Varies 10n where n=2,3,4,5,6

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Person Time Rate:A person time rate is the type of incidence rate that directly incorporates time into the denominator. Typically, each person is observed from a set beginning point to an established end point (onset of disease, death, migration out of the study, end of the study). The numerator is still the number of new cases, but the denominator is a little different. The denominator is the sum of the time each person is observed, totaled for all persons.

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Person Time Rate = Number of cases during observation period x 10n

Time each person was observed, totaled for all persons

For example, a person enrolled in a study who develops the disease of interest 5 years later contributes 5 person years to the denominator. A person who is disease free at one year and who is then lost to follow up contributes just that one-person year to the denominator.

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• Person time rates are often used in cohort (follow up studies) studies of disease with long incubation or latency periods, such as some occupationally related diseases, AIDS and Chronic diseases.

• The attack rate is more useful when we are interested in the proportion of a population at risk who becomes ill over a brief period, particularly during the course of an epidemic. The person-time rate is more useful when we are interested in how quickly people develop illness, assuming a constant rate over time.

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Day Three

Morbidity and mortality measurements that are useful to measure strength of Association between exposure and outcomes:

• Risk Ratio or Relative Risk• Odds ratio• Attributable risk • Attributable risk proportion

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Relative Risk (RR) expresses the risk of developing a certain disease in people exposed to a certain factors as compared to the risk of disease in people not exposed to that factor.

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Since the risk of developing disease is measured by incidence rate, the relative risk is calculated as follows:

RR = Incidence rate among exposed Incidence Rate among non Exposed

The relative risk, as in all measures of associations, can also be used to compare risk of death, accident or any other possible outcome of an exposure.

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• Relative risk, compares the risk of some health-related event such as diseases or death in two groups.

• The two groups are typically differentiated by demographic factors such as sex (e.g., males versus females) or by exposure to a suspected risk factor (e.g., consumption of potato salad or not).

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• Often, you will see the group of primary interest labeled the “exposed” group, and the comparison group labeled the “unexposed” group.

• In calculating RR, we place the group that we are primarily interested in the numerator; we place the group we are comparing them with in the denominator:

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• A risk ratio of 1.0 indicates identical risk in the two groups.

• A risk ratio greater than 1.0 indicates an increased risk for the numerator group,

• While a risk ratio less than 1.0 indicates a decreased risk for the numerator group (perhaps showing a protective of the factor among the “exposed” numerator group.

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A general guideline as to how the strength of association measured

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Relative Risk (Risk Ratio) Strength of Association

1.2-1.4 Weak

1.5-2.9 Moderate

3.0-10 or more Strong


• One limitation of relative risk is that it shows the risk of developing a disease associated with an exposure only in relation to the absence of the exposure.

• It does not show the actual or absolute risk of developing a disease, which is measured by incidence rate.

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• Rate Ratio: A rate ratio compares two groups in terms of incidence rates, person-time rates, or mortality rates.

The rate ratio quantifies the relative incidence of a particular heath event into specified population (one exposed to a suspected causative agent, one unexposed) over a specified period.

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Rate Ratio: Like the risk ratio, the two groups are typically differentiated by

demographic factors or by exposure to a suspected causative agent. The rate for the group of primary interest is divided by the rate for the comparison group.

Rate ratio = Rate for group of primary interest x 1 Rate for comparison group

The interpretation of the value of rate ratio is similar to that of the risk ratio.

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Odds Ratio:

• An odds ratio is another type of measure of association, which quantifies the relationship between an exposure and health outcome from a comparative study.

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Odds ratio:The design of a case control study does not allow the

determination of incidence rate, therefore the direct calculation of relative risk is not possible in such studies.

An indirect estimate of the relative risk in case control studies is given by odds ratio (OR)

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The odds ratio is calculated using the following formula :

Odds ratio = ratio of diseased to non diseased in exposed ratio of diseased to non diseased in unexposed

Odds ratio = ad bc

a = number of persons with disease and with exposure of interest

b = number of persons without disease, but with exposure of interest

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c= number of persons with diseases, but without exposure of interest

d= number of persons without diseases, but without exposure of interest

a+c= total number of persons with disease (“cases”)b+d= total number of persons without disease (“controls”)

• Note that in the two- by-two table, under the pellagra example , the same letters (a, b, c, and d) are used to label the four cells in the table.

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• The odds ratio is some times called the cross- product ratio, because the numerator is the product of cell a and cell d, while the denominator is the product of cell b to cell c (for the denominator) creates and x or cross on the two- by-two table.

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Example of • To quantity the relationship between pellagra and

sex as shown in example in the Goldburg study, the odds ratio is calculated as:

Odds ratio: 46x 1,401 = 2.5

1,438x18

• Notice that the odds ratio of 2.5 is fairly close to the risk ratio of 2.4. That is one of the attractive features of the odds ratio.

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Example 5:

The odds ratio can be used as an estimate of relative risk only if certain conditions are met. What are those conditions?

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Attributable risk:The attributable risk (AR) measures the component of

the incidence rate of a certain outcome which can be attributed to certain exposure, assuming the exposure is a cause of the outcome.

AR= Incidence rate of outcome among exposed - Incidence rate of outcome among non exposed

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Taking the example of smoking and lung cancer:

Incidence rate of lung cancer among non smokers = Incidence rate due to all risk factors other than smoking

Incidence rate of lung cancer among smokers = Incidence rate among smokers due to smoking + Incidence rate due to all risk factors other than smoking

Incidence rate of lung cancer among smokers = AR+ Incidence rate among

non-smokers AR= Incidence rate among smokers - Incidence rate among non-smokers

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Point to note:Unlike the relative risk, which is dimensionless, as a type of incidence rate, AR is expressed per a certain population size per unit time.

While the relative risk is better for quantifying strengthen of association, the attributable risk is more useful from the public health point of view, in that it tells us how many cases of disease in exposed people could have been prevented by eliminating the exposure assuming the exposure is the causal agent for the disease.

Example 6 question 1

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Attributable Proportion

• The attributable proportion, also known as the attributable risk percent, is a measure of the public health impact of a causative factor.

• In calculating this measure, we assume that the occurrence of disease in a group not exposed to the factor under study represents the baseline or expected risk for that disease; we will attribute any risk above that level in the exposed group to their exposure.

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• Thus, the attributable proportion is the proportion of disease in an exposed group attributable to the exposure. It represents the expected reduction in disease if the exposure could be removed (or never existed).

• For two specified subpopulations, identified as exposed or unexposed to a suspected risk factor, with risk of a health event recorded over a specified period,

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Attributable Proportion= (Risk for exposed group)- (Risk for unexposed group)x 100

Risk for exposed group

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• Table : Death rates and rate ratios from lung cancer by daily cigarette consumption, Doll and Hill physician follow- up study, 1951-1961

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Cigarettes per day

Date rates per 1000 per year

Attributable proportion

0 (none smokers) 0.07

1-14 0.57

15-24 1.39

25+ 2.27

Mortality Frequency MeasuresMortality Rates• A mortality rate is a measure of the frequency of

occurrence of death in a defined population during a specified interval. For a defined population, over a specified period of time.

• When mortality rates are based on vital statistics (e.g., counts of death certificates), the denominator most commonly used is the size of the population at the middle of the time period.

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• Neonatal- birth up to 28days• Post neonatal- from 28 up to 1years period• Infant = one years old and below• Age-specific mortality rate– neonatal,– postneonatal, and – infant mortality rates.

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Infant mortality rate• The infant mortality rate is one of the most

commonly used measures for comparing health services among nations.

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Maternal mortality rate• The maternal mortality rate is really a ratio

used to measure mortality associated with pregnancy.

• The numerator is the number of deaths assigned to causes related to pregnancy during a given time period.

• The denominator is the number of live births reported during the same time period.

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Sex-specific mortality rate• A sex-specific mortality rate is a mortality rate

among either males or females. • Both numerator and denominator are limited

to the one sex.Race-specific mortality rate• A race-specific mortality rate is a mortality

rate limited to a specified racial group. • Both numerator and denominator are limited

to the specified race.89

Combinations of specific mortality rates• Mortality rates can be further refined to

combinations that are cause-specific, age-specific, sex-specific, and/or race-specific. – For example, the mortality rate attributed to HIV

among 25- to 44-year-olds in the United States in 1987 was 9,820 deaths among 77.6 million 25- to 44-yearolds, or 12.7 per 100,000. This is a cause- and age-specific mortality rate, because it is limited to one cause (HIV infection) and one age group (25 to 44 years).

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Age-adjusted mortality rates• Often, we want to compare the mortality experience of

different populations. However, since mortality rates increase with age, a higher mortality rate in one population than in another may simply reflect that the first population is older than the second.

• Statistical techniques are used to adjust or standardize the rates in the populations to be compared which eliminates the effect of different age distributions in the different populations.

• Mortality rates computed with these techniques are called age-adjusted or age-standardized mortality rates.

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Death-to-case ratio• The death-to-case ratio is the number of

deaths attributed to a particular disease during a specified time period divided by the number of new cases of that disease identified during the same time period:

• the death-to-case ratio is a ratio but not a proportion.

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Case-fatality rate

• The case-fatality rate is the proportion of persons with a particular condition (cases) who die from that condition.

• The formula is:

• the case-fatality rate is a proportion and requires that the deaths in the numerator be limited to the cases in the denominator.

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Proportionate mortality• Proportionate mortality describes the proportion of deaths in

a specified population over a period of time attributable to different causes.

• Each cause is expressed as a percentage of all deaths, and the sum of the causes must add to 100%.

• These proportions are not mortality rates, since the denominator is all deaths, not the population in which the deaths occurred.

• For a specified population over a specified period,

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Years of Potential Life Lost and YPLL Rate

• YPLL is a measure of the impact of premature mortality on a population.

• It is calculated as the sum of the differences between some predetermined end point and the ages of death for those who died before that end point.

• The two most commonly used end points are age 65 years and average life expectancy.

• Because of the way in which YPLL is calculated, this measure gives more weight to a death the earlier it occurs.

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Calculating YPLL from a line listing

1. Eliminate the records of all persons who died at or after the end point (e.g., age 65 years).

2. For each person who died before the end point, identify that individual’s YPLL by subtracting the age at death from the end point.

3. Sum the YPLL’s.

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Calculating YPLL from a frequency distribution

1. Ensure that age groups break at the end point (e.g., age 65 years). Eliminate all age groups older than the end point.

2. For each age group younger than the end point, identify the midpoint of the age group

3. For each age group younger than the end point, identify that age group’s YPLL by subtracting the midpoint from the end point.

4. Calculate age-specific YPLL by multiplying the age group’s YPLL times the number of persons in that age group.

5. Sum the age-specific YPLL’s.97

Years of Potential Life Lost Rate• The Years of Potential Life Lost Rate represents years of

potential life lost per 1,000 population below the age of 65 years (or below the average life expectancy).

• YPLL rates should be used to compare premature mortality in different populations, since YPLL does not take into account differences in population sizes.

• The formula for a YPLL rate is as follows:

• We use YPLL rates to compare YPLL in populations of different sizes. – Because different populations may also have different age

distributions, we commonly calculate age-adjusted YPLL rates to eliminate the effect of different age distributions in the populations to be compared. 98

Natality Frequency Measures

• Natality measures are used in the area of maternal and child health and less so in other areas.

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Summary• Counts of disease and other health events are

important in epidemiology. • Counts are the basis for disease surveillance

and for allocation of resources. • However, a count alone is insufficient for

describing the characteristics of a population and for determining risk.

• For these purposes we use ratios, proportions, and rates as well as measures of central location and dispersion.

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• Ratios and proportions are useful for describing the characteristics of populations.

• Proportions and rates are used for quantifying morbidity and mortality.

• From these proportions we can infer risk among different groups, detect high-risk groups, and develop hypotheses about causes—i.e., why these groups are at increased risk.

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• The two primary measures of morbidity are incidence rates and prevalence.

• Incidence rates reflect the occurrence of new disease in a population;

• Prevalence reflects the presence of disease in a population.

• To quantify the association between disease occurrence and possible risk factors or causes, we commonly use two measures, relative risk and odds ratio.

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• Mortality rates have long been the standard for measuring mortality in a population.

• Recently, years of potential life lost and years of potential life lost rates have gained in popularity because they focus on premature, and mostly preventable, mortality.

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All of these measures are used when we perform the core

epidemiologic task known as DESCRIPTIVE EPIDEMIOLOGY

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Descriptive Epidemiology Lecture Note-1

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