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Epidemiologic studies that are concerned with characterizing the amount and distribution of health and disease within a population.
Variables of Descriptive Epidemiology
- Socioeconomic Status
- Cyclic fluctuation
- Point epidemic
- Secular trends
- Temporal Clustering
- Within Country
- Localized/spatial clustering
Perhaps the most important factor to consider when describing occurrence of a disease or illness.
Age and Cancer
- 2.5 per 100,000 cases ages 5-14
- 1637 per 100,000 cases over age 85
Age and Vehicle accidents
Highest ages 15-24 and over age 75
First Year of Life
Risk of death from all causes is higher in the first year of life than any othe rage until age 55
Cervical carcinoma and age
Peak 25-29 sharp decline after 50
Epidemiologic studies have shown sex differences in a wide scope of health phenomena including morbidity and mortality.
Females vs. Males
- More males are born each year and more males die every year.
- Females outlive males 5-7 years.
- Risk of cancer in males is greater.
- Somewhat amibiguous classifications
- Tends to overlap with nativity and religion
- Some scientists propose that it is a social construct rather than a biological construct
- Used to track various health outcomes.
Race/Ethnic major categories used in Census
- Black or African American
- American Indian and Alaska Native
- Native Hawaiian and other Pacific Islander
Place of origin of the individual or his or her relatives.
Descriptive term for a person's position in society
SES is a composite measure of the following dimensions:
- A person's income level
- Education level
- Type of occupation
Climate, cultural factors, national dietary habits, and access to health care.
National (within country)
Regional differences may affect the prevalence and incidence of disease.
Urban and rural sections of the US show variations in morbidity and mortality related to environmental and lifestyle isues.
Localized patterns of disease
Associated with specific environmental conditions that may exist in a particular geographic area.
An increase or decrease in the frequence of a disease or health condition in a population over a period of years or within each year
Response of a group of people circumscribed in place to a common source of infection, contamination, or other etiologic factor to which they were exposed almost simultaneously.
Gradual changes in disease frequency over long time periods
Association between common exposure to an etiologic agent at the same time and the development of mrobidity or mortality in a group or population.
Accounts of a single occurrence of a note-worthy health related incident or of a small collection of such events.
A larger collection of cases of a disease, often grouped consecutively and listing common features.
A type of prevalence study that examines the relationship between diseases and other variables of interest as they exist in a defined population at one particular time.
Uses of descriptive epidmiology
- 1. prevention of disease
- 2. Design of interventions
- 3. conduct of additional research
X does not cause y
X causes Y
If the value of one variable increases, the value of the other variable increases as well.
If the value of one variable increases, the value of the other variable decreases.
Pearson Correlation Coefficient (r)
- Measure of assocation used with continuous variables
- Varies from -1 to +1
- As r approaches either -1 or +1 the association is stronger
One that can have an infinite number of values within a specified range (ht and wt)
Types of Associations
- No association
- Causally Associated
- Noncausally associated
The plot of a dose-response relationship, which is a type of correlative association between an exposure and an effect.
The lowest dose at which a particular response occurs
One that has several peaks in the frequency of a condition
- A graphic plotting of the distribution of cases by time of onset.
- Aids in identifying the cause of a disease outbreak.
- Another method for demonstrating associations
- A type of table that tabulates data according to two dimensions
Hypotheses: Where They Come From
- Method of difference
- Method of concomitant variation
Method of Difference
All of the factors in two or more domains are the same except for a single factor, which is hypothesized to be the "cause" of a disease.
Method of Concomitant Variation
A type of association in which the frequency o fan outcome increases with the frequency of exposure to a factor, the hypothesized cause of the outcome
Refers to the process of defining measurement procedures for the variables used in a study
Causality in Epidemiologic Studies
- One of the central concerns of epidemiology is to be able to assert that a causal association exists between an exposure factor and disease.
- Complex issue
- Several criteria must be satisfied in order to asser that a causal association exists.
Hill's Criteria of Causality
- 1. Strength
- 2. Consistency
- 3. Specificity
- 4. Temporality
- 5. Biological gradient
- 6. Plausibility
- 7. Coherence
- 8. Analogy
Strong associations give support to a causal relationsihp between factor and disease
An association has been observed repeatedly
Association is constrained to a particular disease-exposure relationship
The cause must be observed before the effect
Also known as dose-response curve, shows a linear trend in the association between exposure and disease
The association must be biologically plausible from the standpoint of ceontemporary biological knowledge
The cause-and-effect interpretation of our data should not seriously conflict with the generally known facts of the natural history and biology of the disease
Relates to the correspondence between known associations and one tha tis being evaluated for causality
- Subjects are defined on the basis of the presence of absence of an outcome of interest.
- Cases are those individuals who have the outcome or disease of interest, whereas controls do not.
Matched Case-Control Study
Is one in which the cases and controls have been matched according to one o rmore criteria such as sex, age, race, or other variables.
Defined as a population group, or subset thereof, tha tis followed over a period of time
Types of Cohort Studies
- Historical Prospective
A study in which the units of analysis are populations or groups rathe rthan individuals
Ecologic comparison study
Involves an assessment of th eassociation between expousre rates and disease rates during the same time period
An association betwen two variables measure at the group level.
An investiagion involving intentional change in some aspect of the status of the subject
- Does not have control over the exposure factor
- Usually is unable to assign subjects randomly to study conditions
- Controls who is exposed to a factor of interest
- Assigns subjects randomly to study groups
Subjects ar eclassified according to their exposure to a factor of interest and then are observed over time to document the occurrence of new cases of disease or other health events
- Makes use of historical data to determine exposure level at some baseline in the past
- Follow-up for a subsequent occurrences of disease between baseline and present is performed
Historical Prospective Study
Combines retrospective and prospective approaches
An erroneous inference that may occur because an association observed between variables on an aggregate level doe snot necessarily represent or reflect the assocation that exists at an individual level
Advantages of Ecologic Studies
- May provide information about the context of health
- Can be performed when individual level measurements are not available
- Can be conducted rapidly and with minimal resources
Disadvantages of Ecologic Studies
- Ecologic fallacy
- Imprecise measurement of exposure
- A measure of the association between frequency of exposure and frequency of outcome used in case-control study.
Advantages of Case Control Study
- Can be used to study low-prevalence conditions
- relatively quick and easy to complete
- Usually inexpensive
- Involve smaller number of subjects
Disadvantages of Case Control Study
- Measurement of exposure may be inaccurate
- representativeness of cases and controls may be unknown
- Provide indirect estiamates of risk
- The temporal relationship between expousre factor and outcome cannot always be ascertained
The ratio of the incidence rate of a disease or health outcome in an exposed group to the incidence rate of the disease or condition in a non-exposed group
Population Risk Difference
Inidence in the total population- incidence in the nonexposed segment
Advantages of Cohort Studies
- Permit direct observation of risk
- Exposure factor is well defined
- Can study expousres that are uncommon in the population
- The temporal relationship between factor and outcome is known
Disadvantages of Cohort Studies
- Expensive and time consuming
- Complicated and difficult to carry out
- Subjects may be lost to follow-up during the course of the study
- Exposures can be mis classified
Randomized Control Trial
Subjects in a population are randomly allocated into groups, usualy called study and control groups, to receive or not to receive an experimental preventative or therapeutic procedure, maneuver, or intervention
Systematic devation of results or inferences from truth
Types of Bias
- Hawthorne effect
- Recall bias
- Selection bias
- Healthy worker effect
Participant's behavioral changes as a result of their knowledge of being in a study
Cases may remember an exposure more clearly than controls
Distortions that result from procedures used to select subjects and from factors that influence participation in the study
healthy worker effect
the observation that employed populations tend to have a lower mortality experience than the general population
the distortion of a measure of the effect of an exposure on an outcome due to the association of the exposure with other factors that influence the occurrence of the outcome
Which of the Hill's criteria doesn't really belong?
Direct causal relationship
- X causes Y
- Example: Delta F508 causes Cystic Fibrosis
Indirect Causal relationship
- X causes Y causes Z
- High cholesterol causes artery thickening which caueses hemostatic factors which can lead to MI
Sufficient but not necessary
- Factor can produce disease, but is not necessary
- Radiation exposure and leukemia
Necessary but not sufficient
- Multiple factors, including main factor, required
- Example: Development of TB and immunosuppression to cause disase
- Bacteria still necessary, but not sufficient to cause disease.
Necessary and Sufficient
- Without factor, disease doesn't develop
Neither sufficient nor necessary
- Complex models of disease etiology
- High fat diet and heart disease
Four Types of Causal Factors
- Necessary and Sufficient
- Necessary but not sufficient
- Sufficient but not necessary
- Neither sufficient nor necessary
Web of Causation
Model of multifactorial causality