Introduction to Epidemiology Flashcards

1
Q

What is epidemiology?

A

Dynamic study of the determinants, occurrence, distribution, control and pattern of health and disease in a population

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2
Q

How is epidemiology a quantitative discipline?

A
  1. Measures of frequency
    e.g. Counts and rates
  2. Measures of association
    e.g. Relative risk, Odds ratio
  3. Statistical inference
    e.g. P-value, Confidence limits
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3
Q

What are the roles of an epidemiologist?

A

communities diagnostician
> carries out investigations
> investigations
> predict trend
> control
> prevention

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4
Q

Epidemiology describes?

A
  1. health events
  2. cause and risk factors of disease
  3. clinical pattern of disease
    - Identify syndromes
  4. Identify control and/or preventive measures
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5
Q

What are the kinds of epidemiology?

A
  1. descriptive
  2. analytic
  3. experimental
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6
Q

Descriptive epidemiology?

A

study of the occurrence and distribution of disease

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7
Q

Analystic epidemiology?

A

Further studies to determine the validity of a hypothesis concerning the occurrence of disease

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8
Q

Experimental epidemiology?

A

Deliberate manipulation of the cause is predictably followed by an alteration in the effect not due to chance

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9
Q

Descriptive epidemiologic design strategies?

A
  1. Populations
    - Correlational studies
  2. Individual
    i. Case report
    ii. Case series
    iii. Cross sectional studies
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10
Q

Analytical epidemiologic studies?

A
  1. observational
    i. case control
    ii. cohort
    - retrospective and prospective
  2. interventional/experimental
    i. Randomized controlled trial
    ii. Field trial
    iii. Clinical trial
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11
Q

Descriptive vs. Analytic Epidemiology?

A
  1. descriptive is used when little is known about the disease whereas analytical is used when insight of disease is available
  2. descriptive relies of pre-existing data whereas analytical relies of development of new data
  3. descriptive deals with who, where, when whereas analytical deals with the why
  4. descriptive illustrates potential associations whereas analytical evaluates the causality of associations
  5. descriptive is relatively inexpensive and less time consuming than analytic studies
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12
Q

Descriptive studies describe patterns of disease occurrence in terms of?

A
  1. Who gets sick and/or who does not
  2. Where rates are highest and lowest
  3. Temporal patterns of disease
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13
Q

Data provided from descriptive studies are useful for?

A
  1. Public health administrators
    - for allocation of resources
  2. Epidemiologists
    - first step in risk factor determination
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14
Q

Name descriptive studies?

A
  1. correlational studies
  2. case reports
  3. case series
  4. cross sectional studies
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15
Q

What are correlational (ecologic) studies?

A

a type of research design that looks at relationships between 2 or more variables
- they are non-experimental meaning that the experimenter does not manipulate or control any of the variables

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16
Q

Describe correlational studies?

A
  • Uses measures that represent characteristics of entire populations
  • It describes outcomes in relation to age, time, utilization of services, or exposures
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17
Q

Advantages of correlational studies?

A
  1. We can generate hypotheses for case-control studies and environmental studies
  2. We can target high-risk populations, time-periods, or geographic regions for future studies
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18
Q

Limitations of correlational studies?

A
  1. Because data are for groups, we cannot link disease and exposure in individual
  2. We cannot control for potential confounders
  3. Data represent average exposures rather than individual exposures, so we cannot determine a dose-response relationship
  4. Caution must be taken to avoid drawing inappropriate conclusions, or ecological fallacy
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19
Q

What is the function of correlation (ecologic) studies?

A

Used as first step in determining association
- plot : disease (population) burden [ Y axis ] vs. prevalence of “risk factor” [ X axis ]
e.g. smoking vs. lung cancer

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20
Q

What is correlation coefficient?

A

correlation coefficient : r ; + 1 to -1
- Quantifies linear relationship between exposure & disease

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21
Q

What are case reports (case series)?

A

Report of a single individual or a group of individuals with the same diagnosis

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22
Q

Advantages of case reports?

A

We can aggregate cases from disparate sources to generate hypotheses and describe new syndromes
Example: hepatitis, AIDS

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23
Q

Limitations of case reports?

A
  1. We cannot test for statistical association because there is no relevant comparison group
  2. Based on individual exposure {may simply be coincidental}
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24
Q

What are cross-sectional studies (prevalence studies)?

A

Measures disease and exposure simultaneously in a well-defined population

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25
Q

Advantages of cross-sectional studies?

A
  1. They cut across the general population, not simply those seeking medical care
  2. Good for identifying prevalence of common outcomes, such as arthritis, blood pressure or allergies
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26
Q

Limitations of cross-sectional studies?

A
  1. Cannot determine whether exposure preceded disease
  2. It considers prevalent rather than incident cases, results will be influenced by survival factors
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27
Q

Describe the use of cross-sectional studies?

A

Can be used as a type of analytic study for testing hypothesis, when;
1. Current values of exposure variables are unalterable over time
2. Represents value present at initiation of disease
E.g. eye colour or blood group
3. If risk factor is subject to alterations by disease, only hypothesis formulation can be done

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28
Q

What are the key questions in descriptive studies?

A

What (case definition)
Who (person)
Where (place)
When (time)
How many (measures)
Why now?
Why here?
Why in this group?

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29
Q

What are the key questions in analystical studies?

A

Why (Causes)
How (Causes)

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30
Q

What are the three categories of descriptive epidemiologic clues?

A

Person: Who is getting sick?
Place: Where is the sickness occurring?
Time: When is the sickness occurring?

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31
Q

What are the trends under time?

A
  1. secular
  2. periodic
  3. seasonal
  4. epidemic
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32
Q

What is the secular trend?

A

The long-time trend of disease occurrence

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33
Q

What are the possible reasons for changes in trends?

A
  1. artifactual
  2. real
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34
Q

Artifactual reasons for changes in trends?

A

Errors in numerator due to
1. Changes in the recognition of disease
2. Changes in the rules and procedures for classification of causes of death
3. Changes in the classification code of causes of death
4. Changes in accuracy of reporting age at death
5. Errors in the denominator due to error in the enumeration of the population

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35
Q

Real reasons for changes in trends?

A
  1. Changes in age distribution of the population
  2. Changes in survivorship
    Changes in incidence of disease resulting from
    - Genetic factors
    - Environmental factors
36
Q

What are cyclic trends?

A

recurrent alterations in occurrence , interval or frequency of disease

37
Q

Types of cyclic trends?

A
  1. Secular cyclicity
    - Levels of immunizations
    - Build up of susceptibles
    e.g. Hep A-7 yr cycle,Measles-2yr cycle
  2. Short term cyclicity
    e.g. Chickenpox ,salmonella (yearly basis)
38
Q

What is a periodic trend?

A

Temporal interruption of the general trend of secular variation

39
Q

What is a seasonal trend?

A

A cyclic variation in disease frequency by time of year & season
- Seasonal fluctuations in,
1. Environmental factors
2. Occupational activities
3. Recreational activities

40
Q

What is an epidemic trend?

A

An increase in incidence above the expected in a defined geographic area within a defined time period

41
Q

What is an endemic?

A

The habitual presence (or usual occurrence) of a disease within a given geographic area

42
Q

What is an epidemic?

A

The occurrence of an infectious disease clearly in excess of normal expectancy, and generated from a common or propagated source

43
Q

What is a pandemic?

A

A worldwide epidemic affecting an exceptionally high proportion of the global population

44
Q

What is time clustering?

A

A group of cases occur close together & have a well aligned distribution pattern {in terms of time and place}
Note: Cluster analysis used for rare or special disease events

45
Q

What is the Poisson model of time/place clustering analysis?

A

Poisson probability distribution is an inferential statistics probability measure that describes objects/events as they are distributed geographically

46
Q

How is the Poisson model carried out?

A
  1. Geographical area divided into a series of equal square areas.
  2. Randomization i.e. each case has equal probability of falling into each square
  3. If clustering occurs, probability of cause-effect relationship goes up & vice versa.
47
Q

Describe a person under descriptive epidemiology?

A

Age Sex
Occupation Immunization status Underlying disease Medication Nutritional status Socioeconomic factors Crowding
Hobbies
Travel
Personal Habits Stress
Family unit School Genetics Religion

48
Q

How to determine distribution of disease in populations?
=Equation

A

event count/group at risk

49
Q

Describe patterns of disease occurrence by person?

A

age , race / ethnicity , gender , occupation , education , marital status , genetic marker , sexual preference

50
Q

Describe patterns of disease occurrence by place?

A

residence (urban vs. rural) , worksite , social event

51
Q

Describe patterns of disease occurrence by time?

A

week , month , year ; sporadic , seasonal trends, incubation period ; latency

52
Q

What are the sources of information?

A

Census data
Vital statistical records
Employment health examinations
Clinical records from hospitals
National figures on food consumption , medications, health events etc

53
Q

Describe the epidemiologic approach?

A
  1. identify a problem
    - clinical suspicion ; case series ; review of medical literature
  2. formulate a hypothesis
    - good hypotheses are: Specific, Measurable, and Plausible
  3. test that hypothesis
    - assumptions vs. type of data
  4. always question the validity of the results
    - chance, bias and causality
54
Q

Describe the threats to the epidemiologic study?

A
  1. Chance
    - role of random error in outcome measure(s) ( p - value ; power of the study and the confidence interval )
    - largely determined by sample size
  2. Bias
    - role of systematic error in outcome measure(s)
55
Q

Describe the types of bias?

A

Selection bias - subjects not representative
Information bias - error(s) in subject data / classification
Confounding - 3rd variable (causal) assoc. w/ both X and Y

56
Q

What is a hypothesis?

A

an educated guess or an unproven idea based on observation or reasoning, that can be proven or disproven through investigation

57
Q

What goes into a hypothesis?

A
  1. characteristics of the disease
    - the illness
    - established modes of transmission
  2. distribution
    - in time, by place, by person
58
Q

What are morbidity and mortality measures?

A
  1. morbidity - Refers to the presence of disease in a population
  2. mortality - Refers to the occurrence of death in a population
59
Q

How do we determine disease frequency for a population?

A

rate - Frequency of defined events in specified population for given time period
- Rates allow comparisons between two or more populations of different sizes or of a population over time

60
Q

What is prevalence and incidence?

A
  1. Prevalence - the number of existing cases of disease in the population during a defined period
  2. incidence - the number of new cases of disease that develop in the population during a defined period.
61
Q

What is an incident rate?

A

a measure of the probability of the event among persons at risk
- IR = # new cases during time period/specified population at risk x K

62
Q

What is a mortality rate?

A
  • A special type of incidence rate
  • Number of deaths occurring in a specified population in a given time period
63
Q

Describe the use of mortality rates?

A

Mortality rates are used to estimate disease frequency when:
1. incidence data are not available,
2. case-fatality rates are high,
3. goal is to reduce mortality among screened or targeted populations

64
Q

Give examples of mortality rates?

A
  1. crude mortality
  2. cause-specific mortality
  3. case-fatality
  4. maternal mortality
  5. infant mortality
  6. neonatal mortality
65
Q

What is crude mortality?

A

death rate in an entire population
- Rates can also be calculated for sub-groups within the population

66
Q

What is cause-specific mortality?

A

rate at which deaths occur for a specific cause

67
Q

What is case-fatality?

A

Rate at which deaths occur from a disease among those with the disease

68
Q

What is maternal mortality?

A

Ratio of death from childbearing for a given time period per number of live births during same time period

69
Q

What is infant mortality?

A

Rate of death for children less than 1 year per number of live births

70
Q

What is neonatal mortality?

A

Rate of death for children less than 28 days of age per number of live births

71
Q

What is prevalanece?

A
  • Existing cases in a specified population during a specified time period (both new and ongoing cases)
  • Prevalence is a measure of burden of disease or health problem in a population
  • PR = # existing cases during time period/population at same point in time x K
72
Q

Describe the factors that increase prevalanece?

A
  1. longer duration of disease
  2. prolongation of life of patients without cure
  3. increase in new cases (increase in incidence)
  4. in-migration of cases
  5. out-migration of healthy people
  6. in-migration of susceptible people
  7. improved diagnostic facilities
  8. better reporting
73
Q

Describe the factors that decrease prevalence?

A
  1. shorter duration of disease
  2. high case fatality rate from disease
  3. decrease in new cases (decrease in incidence)
  4. in-migration of healthy people
  5. out-migration of cases
  6. improved cure rate of cases
74
Q

What are the basic measures of association?

A
  1. relative risk
  2. odds ratio
75
Q

Describe the function of basic measures of association?

A
  • We often need to know the relationship between an outcome and certain factors (e.g., age, sex, race, smoking status, etc.)
  • Used to guide planning and intervention strategies
76
Q

What is relative risk?

A
  • Ratio of the incidence rates between two groups
  • Can only be calculated from prospective studies (cohort studies)
  • RR = incidence rate among exposed/incidence rate among non-exposed
77
Q

Describe the various interpretations of relative risk?

A
  1. RR > 1: Increased risk of outcome among “exposed” group
  2. RR < 1: Decreased risk, or protective effects, among “exposed” group
  3. RR = 1: No association between exposure and outcome
78
Q

What is probabilty?

A

Chance or risk of an event occurring (a proportion)
Probability = no. of times an event occurs/no. of times an event can occur

79
Q

What are odds?

A

ratio of the probability of an event occurring to the probability of an event not occurring
- Odds = P/(1-P)

80
Q

What is odds ratio?

A

The odds ratio (OR) is a ratio of two odds

81
Q

Which study designs can odds ratio be calculated for?

A
  1. Cross-sectional
  2. Cohort
    - OR is a ratio of the odds of the outcome in exposed persons to the odds of the outcome in non- exposed persons
  3. Case-control
    - OR is a ratio of the odds of exposure in cases to the odds of exposure in controls.
82
Q

Describe the various approaches to odds ratio?

A
  1. Cross product/odds ratio
    - 2 x 2 contingency table (ad/bc)
  2. Prevalence odds ratio
    - cross sectional studies
  3. Exposure odds ratio( odds of exposure in diseased vs. non-diseased)
    - In rare cases or exotic diseases
  4. Disease odds/Rate odds ratio(odds of getting a disease if exposed or unexposed)
    - Cohort & cross sectional
  5. Risk odds ratio
    - Cross sectional, cohort & case control
83
Q

Describe the various interpretations of odds ratio?

A
  1. OR > 1: Increased odds of exposure among those with outcome
  2. OR < 1: Decreased odds, or protective effects, among those with outcome
  3. OR = 1: No association between exposure and outcome
84
Q

What are confidence intervals?

A

A confidence interval is a range of values that is likely (e.g., 95%) to contain the true value in the underlying population

85
Q

What are the 10 steps of outbreak investigation?

A
86
Q

Objectives of descriptive epidemiology?

A
  1. To evaluate trends in health and disease and allow comparisons among countries and subgroups within countries
  2. To provide a basis for planning, provision and evaluation of services
  3. To identify problems to be studied by analytic methods and to test hypotheses related to those problems