Lecture 51/52 - Epidemiology 3 & 4 (studies) Flashcards
what are the basics for case control studies
- use source population as starting point
- identify the group of cases with disease
- identify the controls
- compare proportion of exposed among cases and controls
- no measures of disease frequency
why is incidence not measured with case-control design
- proportion of cases in entire population is unknown
2 controls are representative of population at risk - # of cases and controls are chosen by investigator
how are case-control studies structured
- health outcome of cases
- how controls are sampled
advantages for case control designs
- more efficient w// fewer participants
- rapid results
- optimal for rare disease
- cost effective
disadvantages for case control designs
- temporality issues
- information not collected for study purposes
- susceptible to bias
- cannot be used to estimate true risk
cross-sectional study
measurement occurs on a single occasion or within short period of time
what are the bascis of cross-sectional studies
- exposure and outcome status ascerned at same point
- individual-level data
- exposure and outcome for same unit
- first step in assessing clinical problem
- used to estimate population parameters
Descriptive cross-sectional study
characterize the prevalence of a disease in a specific population
analytical cross-sectional study
compare disease differences between exposed and unexposed groups
cross-sectional study advantages
- faster and lower cost
- easily leverage existing data
- reasonably generalize broader population
- can do repeatedly for estimation of time trends
what are the potentials for bias in cross-sectional studies
- over-representation of cases with long duration of illness
- under-representation of cases with short duration of illness
why might you use a cross-sectional design?
- first step in assessing a clinical problem
- to estimate population parameters
ecologic studies
comparison of population-level estimates of exposure and outcomes
ecologic fallacy
- relationships or processes observed at group level are also present at individual level
- attribution of effect to the population when a specific subgroup has the outcome
ecologic study strengths
- faster and lower cost
- usually leverages existing data
- can provide insight into ecological effects or population-level differences
- hypothesis-generating
ecologic study limitations
- confounding factors difficult to control
- cannot infer exposure-outcome association at individual level
- cannot determine temporality of association
association
statistical relationship between two or more events, characteristics, etc.
causation
change in one variable is responsible, directly or indirectly, for an observed change in another
“risk factor”
a factor that changes the risk of developing the disease
what could association between exposure and outcome be due to
- chance
- bias
- confounding
- invetigator error
- true
Rothman’s Causal Pie
each pie is a theorhetical causal mechanism for a given disease
sufficient cause
one or more factors that inevitably produce disease with a set of minimal conditions
component cause
factor which contributes to disease
necessary cause
factor that must be present for disease to occur
Bradford Hill’s Criteria for Causal Inference
- temporality
- strength of association
3 consistency - biological gradient
- specificity
- plausibility
- coherence
- experimental evidence
- analogy
1-4 = strong
5-9 = weak
temporality
- cause must precede an effect in time
- criterion is inarguable
- based on temporal sequence
strength of association
stronger the relationship between the independent variable and the dependent variable, the less likely that the relationship is due to something else or by chance
what are the two types of errors in epidemiologic studies
- systematic error (validity)
- random error (precision)
what is internal validity
validity of the interferences drawn as they pertain to the members of the source population
what is external validity
validity of the inferences as they pertain to individuals outside the source population
what are the 3 general types of bias
- selection
- information
- confounding
selection bias
- stems from procedures used to select participants and factors that influence participation
- occurs when the association between exposure and disease is different for participants compared to non
what are common sources of selection bias
- volunteers
- healthy-worker effect
- disproportionate loss to follow-up in cohort stuies
information bias
occurs when information that an investigator collects about or from study participants is erroneous
“misclassified”
differential misclassification
misclassification of exposure related to disease status or vice versa
nondifferential misclassification
misclassification of exposure is NOT related to disease staus or vice versa
a cofounder must be
- associated with disease as a cause of disease or proxy for a cause
- associated with exposure but not an effect
define cofounder
extraneous factors responsible for differences in the disease frequency between exposed and unexposed
