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Epidemiology
L K Atuhaire
Definition
Epidemiology is the study of the distribution
and determinants of health-related states or
events in specified populations, and the
application of this study to the control of
health problems.
Distribution
Epidemiology is concerned with the frequency
and pattern of health events in a population.
Frequency
Frequency refers not only to the number of
health events such as the number of cases of
meningitis or diabetes in a population, but
also to the relationship of that number to the
size of the population. The resulting rate
allows epidemiologists to compare disease
occurrence across different populations.
Pattern
 Pattern refers to the occurrence of health-related
events by time, place, and person.
 Time patterns may be annual, seasonal, weekly, daily,
hourly, weekday versus weekend, or any other
breakdown of time that may influence disease or
injury occurrence.
 Place patterns include geographic variation,
urban/rural differences, and location of work sites or
schools.
Pattern
Personal characteristics include demographic
factors which may be related to risk of illness,
injury, or disability such as age, sex, marital
status, and socioeconomic status, as well as
behaviors and environmental exposures .
Descriptive Epidemiology
Characterizing health events by time, place,
and person are activities of descriptive
epidemiology
Sources of Data for Descriptive Epidemiology
 Population Census
 Surveys
 Administrative sources
 Health Unit records
 Surveillance/Notification
 Register(e.g Cancer register)
Determinants
Epidemiology is also used to search for
determinants, which are the causes and other
factors that influence the occurrence of
disease and other health-related events.
Epidemiologists assume that illness does not
occur randomly in a population, but happens
only when the right accumulation of risk
factors or determinants exists in an individual.
Analytical Epidemiology
To search for these determinants,
epidemiologists use analytic epidemiology or
epidemiologic studies to provide the Why
and How of such events.
Analytical Epidemiology
 They assess whether groups with different rates
of disease differ in their demographic
characteristics, genetic or immunologic make-
up, behaviors, environmental exposures, or
other so-called potential risk factors.
 Ideally, the findings provide sufficient evidence
to direct prompt and effective public health
control and prevention measures.
Scope
Epidemiology was originally focused
exclusively on epidemics of communicable
diseases but was subsequently expanded to
address endemic communicable diseases and
non-communicable infectious diseases.
Scope
By the middle of the 20th Century, additional
epidemiologic methods had been developed
and applied to chronic diseases, injuries, birth
defects, maternal-child health, occupational
health, and environmental health.
History
Circa 400 B.C. Hippocrates
Hippocrates attempted to explain disease
occurrence from a rational rather than a
supernatural viewpoint. In his essay entitled
On Airs, Waters, and Places, Hippocrates
suggested that environmental and host factors
such as behaviors might influence the
development of disease
John Gaunt 1662
Another early contributor to epidemiology
was John Gaunt, of London who published a
landmark analysis of mortality data in 1662.
This publication was the first to quantify
patterns of birth, death, and disease
occurrence, noting disparities between males
and females, high infant mortality, urban/rural
differences, and seasonal variations.
William Farr 1800
William Farr built upon Gaunts work by systematically
collecting and analyzing Britains mortality statistics.
Farr, considered the father of modern vital statistics and
surveillance, developed many of the basic practices
used today in vital statistics and disease classification.
He concentrated his efforts on collecting vital statistics,
assembling and evaluating those data, and reporting
to responsible health authorities and the general
public.
John Snow 1854
In the mid-1800s, an anesthesiologist named John
Snow was conducting a series of investigations
in London that warrant his being considered the
father of field epidemiology.
Twenty years before the development of the
microscope, Snow conducted studies of cholera
outbreaks both to discover the cause of disease
and to prevent its recurrence.
19th and 20th centuries
In the mid- and late-1800s, epidemiological
methods began to be applied in the
investigation of disease occurrence.
At that time, most investigators focused on
acute infectious diseases.
In the 1930s and 1940s, epidemiologists
extended their methods to noninfectious
diseases.
19th and 20th centuries
 The period since World War II has seen an
explosion in the development of research
methods and the theoretical underpinnings of
epidemiology
 Epidemiology has been applied to the entire
range of health-related outcomes, behaviors,
and even knowledge and attitudes.
19th and 20th centuries
The studies by Doll and Hill linking lung cancer
to smoking6and the study of cardiovascular
disease among residents of Framingham,
Massachusetts are two examples of how
pioneering researchers have applied
epidemiologic methods to chronic disease
since World War II.
19th and 20th centuries
During the 1960s and early 1970s health
workers applied epidemiologic methods to
eradicate naturally occurring smallpox
worldwide.
This was an achievement in applied
epidemiology of unprecedented proportions.
19th and 20th centuries
In the 1980s, epidemiology was extended to
the studies of injuries and violence. In the
1990s, the related fields of molecular and
genetic epidemiology (expansion of
epidemiology to look at specific pathways,
molecules and genes that influence risk of
developing disease) took root.
19th and 20th centuries
Meanwhile, infectious diseases continued to
challenge epidemiologists as new infectious
agents emerged (Ebola virus, Human
Immunodeficiency virus (HIV)/ Acquired
Immunodeficiency Syndrome (AIDS)), were
identified (Legionella, Severe Acute
Respiratory Syndrome (SARS)), or changed
(drug-resistant Mycobacterium tuberculosis,
Avian influenza
Uses
Much epidemiologic research is devoted to searching
for causal factors that influence ones risk of disease.
Ideally, the goal is to identify a cause so that
appropriate public health action might be taken.
One can argue that epidemiology can never prove a
causal relationship between an exposure and a
disease, since much of epidemiology is based on
ecologic reasoning. Nevertheless, epidemiology
often provides enough information to support
effective action.
Analytic studies
Surveillance and field investigations are usually
sufficient to identify causes, modes of transmission,
and appropriate control and prevention measures.
But sometimes analytic studies employing more
rigorous methods are needed.
Often the methods are used in combination  with
surveillance and field investigations providing clues
or hypotheses about causes and modes of
transmission, and analytic studies evaluating the
credibility of those hypotheses.
Comparison !
 The key feature of analytic epidemiology is a
comparison group.
 When investigators find that persons with a
particular characteristic are more likely than
those without the characteristic to contract a
disease, the characteristic is said to be
associated with the disease.
Common factors
The characteristic may be a:
 Demographic factor such as age, race, or sex;
 Constitutional factor such as blood group or
immune status;
 Behavior or act such as smoking or having
eaten salsa; or
 Circumstance such as living near a toxic waste
site.
Importance
 Identifying factors associated with disease
help health officials appropriately target public
health prevention and control activities.
 It also guides additional research into the
causes of disease.
Importance
 Thus, analytic epidemiology is concerned with the
search for causes and effects, or the why and the how.
 Epidemiologists use analytic epidemiology to quantify
the association between exposures and outcomes and
to test hypotheses about causal relationships.
 It has been said that epidemiology by itself can never
prove that a particular exposure caused a particular
outcome. Often, however, epidemiology provides
sufficient evidence to take appropriate control and
prevention measures
Scope
Epidemiologic studies fall into two categories:
experimental and observational.
Experimental Studies
 In an experimental study, the investigator
determines through a controlled process the
exposure for each individual (clinical trial) or
community (community trial), and then tracks the
individuals or communities over time to detect the
effects of the exposure.
 For example, in a clinical trial of a new vaccine, the
investigator may randomly assign some of the
participants to receive the new vaccine, while others
receive a placebo shot.
Experimental Studies
 The investigator then tracks all participants,
observes who gets the disease that the new vaccine
is intended to prevent, and compares the two
groups (new vaccine vs. placebo) to see whether the
vaccine group has a lower rate of disease.
 Similarly, in a trial to prevent onset of diabetes
among high-risk individuals, investigators randomly
assigned enrollees to one of three groups 
placebo, an anti-diabetes drug, or lifestyle
intervention.
Experimental Studies
 At the end of the follow-up period,
investigators found the lowest incidence of
diabetes in the lifestyle intervention group,
the next lowest in the anti-diabetic drug
group, and the highest in the placebo group
Observational studies
In an observational study, the epidemiologist
simply observes the exposure and disease status
of each study participant. John Snows studies of
cholera in London were observational studies.
The two most common types of observational
studies are cohort studies and case-control
studies; a third type is cross-sectional studies.
Cohort Study
A cohort study is similar in concept to the experimental
study. In a cohort study the epidemiologist records
whether each study participant is exposed or not, and
then tracks the participants to see if they develop the
disease of interest.
Note that this differs from an experimental study
because, in a cohort study, the investigator observes
rather than determines the participants exposure
status.
Cohort Study
After a period of time, the investigator compares the
disease rate in the exposed group with the disease
rate in the unexposed group.
The unexposed group serves as the comparison group,
providing an estimate of the baseline or expected
amount of disease occurrence in the community.
If the disease rate is substantively different in the
exposed group compared to the unexposed group, the
exposure is said to be associated with illness.
Cohort Study
The length of follow-up varies considerably. In an
attempt to respond quickly to a public health concern
such as an outbreak, public health departments tend
to conduct relatively brief studies.
On the other hand, research and academic
organizations are more likely to conduct studies of
cancer, cardiovascular disease, and other chronic
diseases which may last for years and even decades.
Cohort Study
These studies are sometimes called follow-up or
prospective cohort studies, because
participants are enrolled as the study begins
and are then followed prospectively over time
to identify occurrence of the outcomes of
interest
Cohort Study
Advantages
 Useful when exposure of interest is rare
 Can examine multiple effects eg diseases of a single
exposure
 Can elucidate temporal relationship between
exposure and disease thereby getting closer to
causation
 Allows direct measurement of incidence of disease
 Minimizes bias in ascertainment of exposure
Cohort Study
Disadvantages
 Inefficient for studying rare diseases
 Generally requires a large number of subjects.
 Expensive and time consuming
 Subjects can be lost to follow-up or drop out
of study leading to bias
Retrospective cohort study
An alternative type of cohort study is a retrospective
cohort study. In this type of study both the exposure
and the outcomes have already occurred. Just as in a
prospective cohort study, the investigator calculates
and compares rates of disease in the exposed and
unexposed groups. Retrospective cohort studies are
commonly used in investigations of disease in groups
of easily identified people such as workers at a
particular factory or attendees at a wedding.
Case-control study
In a case-control study, investigators start by
enrolling a group of people with disease (at CDC
such persons are called case-patients rather
than cases, because case refers to occurrence of
disease, not a person).
As a comparison group, investigator then enrolls
a group of people without disease (controls).
Case-control study
Investigators then compare previous exposures
between the two groups. The control group
provides an estimate of the baseline or expected
amount of exposure in that population.
If the amount of exposure among the case group
is substantially higher than the amount you would
expect based on the control group, then illness is
said to be associated with that exposure.
Case-control study
The key in a case-control study is to identify an
appropriate control group, comparable to the
case group in most respects, in order to provide
a reasonable estimate of the baseline or
expected exposure
Case-control study
Advantages
 Useful for studying rare disease
 Useful for studying diseases with long latency
periods
 Can explore several potential risk factors
exposures for disease simultaneously
 Can use existing data sources
 Cheap, quick, and easy to conduct
Case-control study
Disadvantages
 Prone to methodological errors and biases
 Dependent on high quality records
 Difficult to select an appropriate control group
 More difficult statistical methods required for
proper analysis
Cross-sectional study
In this third type of observational study, a sample of persons
from a population is enrolled and their exposures and health
outcomes are measured simultaneously.
The cross-sectional study tends to assess the presence
(prevalence) of the health outcome at that point of time
without regard to duration.
For example, in a cross-sectional study of diabetes, some of the
enrollees with diabetes may have lived with their diabetes for
many years, while others may have been recently diagnosed.
Cross-sectional study
From an analytic viewpoint the cross-sectional
study is weaker than either a cohort or a case-
control study because a cross-sectional study
usually cannot disentangle risk factors for
occurrence of disease (incidence) from risk
factors for survival with the disease. (Incidence
and prevalence are discussed in more detail in
Lesson 3.)
Cross-sectional study
On the other hand, a cross-sectional study is a
perfectly fine tool for descriptive epidemiology
purposes.
Cross-sectional studies are used routinely to document
the prevalence in a community of health behaviors
(prevalence of smoking), health states (prevalence of
vaccination against measles), and health outcomes,
particularly chronic conditions (hypertension,
diabetes).
Cross-sectional study
Advantages
 Often based on a sample of the general
population not just people seeking medical
care
 Can be carried out over a relatively short
period of time
Cross-sectional study
Disadvantages
 Difficult to separate cause and effect because
measurement of exposure and disease are made at
one point in time so it may not be possible to
determine which came first
 Are biased toward detecting cases with disease of long
duration and can involve misclassications of cases in
remission or under effective medical treatment
 Snapshot in time can be misleading in a variety of
other ways
Exercise
Classify each of the following studies as:
A. Experimental
B. Observational cohort
C. Observational case - control
D. Observational cross - sectional
E. Not an analytical or epidemiologic study
_____ 1. Representative sample of residents were telephoned and asked how much they exercise each week and
whether they currently have (have ever been diagnosed with) heart disease.
_____ 2. Occurrence of cancer was identified between April 1991 and July 2002 for 50,000 troops who served in
the first Gulf War (ended April 1991) and 50,000 troops who served elsewhere during the same period.
_____ 3. Persons diagnosed with new-onset Lyme disease were asked how often they walk through woods, use
insect repellant, wear short sleeves and pants, etc. Twice as many patients without Lyme disease from the same
physicians practice were asked the same questions, and the responses in the two groups were compared.
_____ 4. Subjects were children enrolled in a health maintenance organization. At 2 months, eachchild was
randomly given one of two types of a new vaccine against rotavirus infection. Parents were called by a nurse two
weeks later and asked whether the children had experienced any of a list of side-effects.

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Lectures to biostatistics day_2 (2).pptx

  • 2. Definition Epidemiology is the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to the control of health problems.
  • 3. Distribution Epidemiology is concerned with the frequency and pattern of health events in a population.
  • 4. Frequency Frequency refers not only to the number of health events such as the number of cases of meningitis or diabetes in a population, but also to the relationship of that number to the size of the population. The resulting rate allows epidemiologists to compare disease occurrence across different populations.
  • 5. Pattern Pattern refers to the occurrence of health-related events by time, place, and person. Time patterns may be annual, seasonal, weekly, daily, hourly, weekday versus weekend, or any other breakdown of time that may influence disease or injury occurrence. Place patterns include geographic variation, urban/rural differences, and location of work sites or schools.
  • 6. Pattern Personal characteristics include demographic factors which may be related to risk of illness, injury, or disability such as age, sex, marital status, and socioeconomic status, as well as behaviors and environmental exposures .
  • 7. Descriptive Epidemiology Characterizing health events by time, place, and person are activities of descriptive epidemiology
  • 8. Sources of Data for Descriptive Epidemiology Population Census Surveys Administrative sources Health Unit records Surveillance/Notification Register(e.g Cancer register)
  • 9. Determinants Epidemiology is also used to search for determinants, which are the causes and other factors that influence the occurrence of disease and other health-related events. Epidemiologists assume that illness does not occur randomly in a population, but happens only when the right accumulation of risk factors or determinants exists in an individual.
  • 10. Analytical Epidemiology To search for these determinants, epidemiologists use analytic epidemiology or epidemiologic studies to provide the Why and How of such events.
  • 11. Analytical Epidemiology They assess whether groups with different rates of disease differ in their demographic characteristics, genetic or immunologic make- up, behaviors, environmental exposures, or other so-called potential risk factors. Ideally, the findings provide sufficient evidence to direct prompt and effective public health control and prevention measures.
  • 12. Scope Epidemiology was originally focused exclusively on epidemics of communicable diseases but was subsequently expanded to address endemic communicable diseases and non-communicable infectious diseases.
  • 13. Scope By the middle of the 20th Century, additional epidemiologic methods had been developed and applied to chronic diseases, injuries, birth defects, maternal-child health, occupational health, and environmental health.
  • 14. History Circa 400 B.C. Hippocrates Hippocrates attempted to explain disease occurrence from a rational rather than a supernatural viewpoint. In his essay entitled On Airs, Waters, and Places, Hippocrates suggested that environmental and host factors such as behaviors might influence the development of disease
  • 15. John Gaunt 1662 Another early contributor to epidemiology was John Gaunt, of London who published a landmark analysis of mortality data in 1662. This publication was the first to quantify patterns of birth, death, and disease occurrence, noting disparities between males and females, high infant mortality, urban/rural differences, and seasonal variations.
  • 16. William Farr 1800 William Farr built upon Gaunts work by systematically collecting and analyzing Britains mortality statistics. Farr, considered the father of modern vital statistics and surveillance, developed many of the basic practices used today in vital statistics and disease classification. He concentrated his efforts on collecting vital statistics, assembling and evaluating those data, and reporting to responsible health authorities and the general public.
  • 17. John Snow 1854 In the mid-1800s, an anesthesiologist named John Snow was conducting a series of investigations in London that warrant his being considered the father of field epidemiology. Twenty years before the development of the microscope, Snow conducted studies of cholera outbreaks both to discover the cause of disease and to prevent its recurrence.
  • 18. 19th and 20th centuries In the mid- and late-1800s, epidemiological methods began to be applied in the investigation of disease occurrence. At that time, most investigators focused on acute infectious diseases. In the 1930s and 1940s, epidemiologists extended their methods to noninfectious diseases.
  • 19. 19th and 20th centuries The period since World War II has seen an explosion in the development of research methods and the theoretical underpinnings of epidemiology Epidemiology has been applied to the entire range of health-related outcomes, behaviors, and even knowledge and attitudes.
  • 20. 19th and 20th centuries The studies by Doll and Hill linking lung cancer to smoking6and the study of cardiovascular disease among residents of Framingham, Massachusetts are two examples of how pioneering researchers have applied epidemiologic methods to chronic disease since World War II.
  • 21. 19th and 20th centuries During the 1960s and early 1970s health workers applied epidemiologic methods to eradicate naturally occurring smallpox worldwide. This was an achievement in applied epidemiology of unprecedented proportions.
  • 22. 19th and 20th centuries In the 1980s, epidemiology was extended to the studies of injuries and violence. In the 1990s, the related fields of molecular and genetic epidemiology (expansion of epidemiology to look at specific pathways, molecules and genes that influence risk of developing disease) took root.
  • 23. 19th and 20th centuries Meanwhile, infectious diseases continued to challenge epidemiologists as new infectious agents emerged (Ebola virus, Human Immunodeficiency virus (HIV)/ Acquired Immunodeficiency Syndrome (AIDS)), were identified (Legionella, Severe Acute Respiratory Syndrome (SARS)), or changed (drug-resistant Mycobacterium tuberculosis, Avian influenza
  • 24. Uses Much epidemiologic research is devoted to searching for causal factors that influence ones risk of disease. Ideally, the goal is to identify a cause so that appropriate public health action might be taken. One can argue that epidemiology can never prove a causal relationship between an exposure and a disease, since much of epidemiology is based on ecologic reasoning. Nevertheless, epidemiology often provides enough information to support effective action.
  • 25. Analytic studies Surveillance and field investigations are usually sufficient to identify causes, modes of transmission, and appropriate control and prevention measures. But sometimes analytic studies employing more rigorous methods are needed. Often the methods are used in combination with surveillance and field investigations providing clues or hypotheses about causes and modes of transmission, and analytic studies evaluating the credibility of those hypotheses.
  • 26. Comparison ! The key feature of analytic epidemiology is a comparison group. When investigators find that persons with a particular characteristic are more likely than those without the characteristic to contract a disease, the characteristic is said to be associated with the disease.
  • 27. Common factors The characteristic may be a: Demographic factor such as age, race, or sex; Constitutional factor such as blood group or immune status; Behavior or act such as smoking or having eaten salsa; or Circumstance such as living near a toxic waste site.
  • 28. Importance Identifying factors associated with disease help health officials appropriately target public health prevention and control activities. It also guides additional research into the causes of disease.
  • 29. Importance Thus, analytic epidemiology is concerned with the search for causes and effects, or the why and the how. Epidemiologists use analytic epidemiology to quantify the association between exposures and outcomes and to test hypotheses about causal relationships. It has been said that epidemiology by itself can never prove that a particular exposure caused a particular outcome. Often, however, epidemiology provides sufficient evidence to take appropriate control and prevention measures
  • 30. Scope Epidemiologic studies fall into two categories: experimental and observational.
  • 31. Experimental Studies In an experimental study, the investigator determines through a controlled process the exposure for each individual (clinical trial) or community (community trial), and then tracks the individuals or communities over time to detect the effects of the exposure. For example, in a clinical trial of a new vaccine, the investigator may randomly assign some of the participants to receive the new vaccine, while others receive a placebo shot.
  • 32. Experimental Studies The investigator then tracks all participants, observes who gets the disease that the new vaccine is intended to prevent, and compares the two groups (new vaccine vs. placebo) to see whether the vaccine group has a lower rate of disease. Similarly, in a trial to prevent onset of diabetes among high-risk individuals, investigators randomly assigned enrollees to one of three groups placebo, an anti-diabetes drug, or lifestyle intervention.
  • 33. Experimental Studies At the end of the follow-up period, investigators found the lowest incidence of diabetes in the lifestyle intervention group, the next lowest in the anti-diabetic drug group, and the highest in the placebo group
  • 34. Observational studies In an observational study, the epidemiologist simply observes the exposure and disease status of each study participant. John Snows studies of cholera in London were observational studies. The two most common types of observational studies are cohort studies and case-control studies; a third type is cross-sectional studies.
  • 35. Cohort Study A cohort study is similar in concept to the experimental study. In a cohort study the epidemiologist records whether each study participant is exposed or not, and then tracks the participants to see if they develop the disease of interest. Note that this differs from an experimental study because, in a cohort study, the investigator observes rather than determines the participants exposure status.
  • 36. Cohort Study After a period of time, the investigator compares the disease rate in the exposed group with the disease rate in the unexposed group. The unexposed group serves as the comparison group, providing an estimate of the baseline or expected amount of disease occurrence in the community. If the disease rate is substantively different in the exposed group compared to the unexposed group, the exposure is said to be associated with illness.
  • 37. Cohort Study The length of follow-up varies considerably. In an attempt to respond quickly to a public health concern such as an outbreak, public health departments tend to conduct relatively brief studies. On the other hand, research and academic organizations are more likely to conduct studies of cancer, cardiovascular disease, and other chronic diseases which may last for years and even decades.
  • 38. Cohort Study These studies are sometimes called follow-up or prospective cohort studies, because participants are enrolled as the study begins and are then followed prospectively over time to identify occurrence of the outcomes of interest
  • 39. Cohort Study Advantages Useful when exposure of interest is rare Can examine multiple effects eg diseases of a single exposure Can elucidate temporal relationship between exposure and disease thereby getting closer to causation Allows direct measurement of incidence of disease Minimizes bias in ascertainment of exposure
  • 40. Cohort Study Disadvantages Inefficient for studying rare diseases Generally requires a large number of subjects. Expensive and time consuming Subjects can be lost to follow-up or drop out of study leading to bias
  • 41. Retrospective cohort study An alternative type of cohort study is a retrospective cohort study. In this type of study both the exposure and the outcomes have already occurred. Just as in a prospective cohort study, the investigator calculates and compares rates of disease in the exposed and unexposed groups. Retrospective cohort studies are commonly used in investigations of disease in groups of easily identified people such as workers at a particular factory or attendees at a wedding.
  • 42. Case-control study In a case-control study, investigators start by enrolling a group of people with disease (at CDC such persons are called case-patients rather than cases, because case refers to occurrence of disease, not a person). As a comparison group, investigator then enrolls a group of people without disease (controls).
  • 43. Case-control study Investigators then compare previous exposures between the two groups. The control group provides an estimate of the baseline or expected amount of exposure in that population. If the amount of exposure among the case group is substantially higher than the amount you would expect based on the control group, then illness is said to be associated with that exposure.
  • 44. Case-control study The key in a case-control study is to identify an appropriate control group, comparable to the case group in most respects, in order to provide a reasonable estimate of the baseline or expected exposure
  • 45. Case-control study Advantages Useful for studying rare disease Useful for studying diseases with long latency periods Can explore several potential risk factors exposures for disease simultaneously Can use existing data sources Cheap, quick, and easy to conduct
  • 46. Case-control study Disadvantages Prone to methodological errors and biases Dependent on high quality records Difficult to select an appropriate control group More difficult statistical methods required for proper analysis
  • 47. Cross-sectional study In this third type of observational study, a sample of persons from a population is enrolled and their exposures and health outcomes are measured simultaneously. The cross-sectional study tends to assess the presence (prevalence) of the health outcome at that point of time without regard to duration. For example, in a cross-sectional study of diabetes, some of the enrollees with diabetes may have lived with their diabetes for many years, while others may have been recently diagnosed.
  • 48. Cross-sectional study From an analytic viewpoint the cross-sectional study is weaker than either a cohort or a case- control study because a cross-sectional study usually cannot disentangle risk factors for occurrence of disease (incidence) from risk factors for survival with the disease. (Incidence and prevalence are discussed in more detail in Lesson 3.)
  • 49. Cross-sectional study On the other hand, a cross-sectional study is a perfectly fine tool for descriptive epidemiology purposes. Cross-sectional studies are used routinely to document the prevalence in a community of health behaviors (prevalence of smoking), health states (prevalence of vaccination against measles), and health outcomes, particularly chronic conditions (hypertension, diabetes).
  • 50. Cross-sectional study Advantages Often based on a sample of the general population not just people seeking medical care Can be carried out over a relatively short period of time
  • 51. Cross-sectional study Disadvantages Difficult to separate cause and effect because measurement of exposure and disease are made at one point in time so it may not be possible to determine which came first Are biased toward detecting cases with disease of long duration and can involve misclassications of cases in remission or under effective medical treatment Snapshot in time can be misleading in a variety of other ways
  • 52. Exercise Classify each of the following studies as: A. Experimental B. Observational cohort C. Observational case - control D. Observational cross - sectional E. Not an analytical or epidemiologic study _____ 1. Representative sample of residents were telephoned and asked how much they exercise each week and whether they currently have (have ever been diagnosed with) heart disease. _____ 2. Occurrence of cancer was identified between April 1991 and July 2002 for 50,000 troops who served in the first Gulf War (ended April 1991) and 50,000 troops who served elsewhere during the same period. _____ 3. Persons diagnosed with new-onset Lyme disease were asked how often they walk through woods, use insect repellant, wear short sleeves and pants, etc. Twice as many patients without Lyme disease from the same physicians practice were asked the same questions, and the responses in the two groups were compared. _____ 4. Subjects were children enrolled in a health maintenance organization. At 2 months, eachchild was randomly given one of two types of a new vaccine against rotavirus infection. Parents were called by a nurse two weeks later and asked whether the children had experienced any of a list of side-effects.