ConclusionEpidemiology and what
matters most
Epidemiology matters: a new introduction to methodological foundations
Chapter 14
Epidemiology Matters – Chapter 14
1. Seven steps of an epidemiological study
2. Balancing comparability and external validity
3. Small effects, big implications
4. Consequentialist epidemiology implications
5. Causal explanation versus intervention
6. Summary
Epidemiology Matters – Chapter 14
1. Seven steps of an epidemiological study
2. Balancing comparability and external validity
3. Small effects, big implications
4. Consequentialist epidemiology implications
5. Causal explanation versus intervention
6. Summary
4Epidemiology Matters – Chapter 1
Seven steps
1. Define the population of interest
2. Conceptualize and create measures of exposures and health indicators
3. Take a sample of the population
4. Estimate measures of association between exposures and health indicators
of interest
5. Rigorously evaluate whether the association observed suggests a causal
association
6. Assess the evidence for causes working together, i.e., interaction
7. Assess the extent to which the result matters, is externally valid, to other
populations
Epidemiology Matters – Chapter 14
1. Seven steps of an epidemiological study
2. Balancing comparability and external validity
3. Small effects, big implications
4. Consequentialist epidemiology implications
5. Causal explanation versus intervention
6. Summary
Epidemiology Matters – Chapter 14
Comparability and external validity
All epidemiologic studies should be conducted with a clear intent to improve the health of populationsHowever no one study can stand alone without an evidence base, no one study will settle a causal question, no one study will be the last word on any issue
Epidemiology Matters – Chapter 14
Comparability and external validity
Comparability: achieving within study sample ensures causal effect estimate(s) are internally validChapter 10: Randomization, matching, and stratification are foundational approaches to achieve comparability of study sample
Epidemiology Matters – Chapter 14
Comparability and external validity
External validity: extent to which our findings are generalizable to a
base population. This requires an understanding of factors that together
are involved in producing a causal estimate
Chapter 7: most causes of disease do not act in isolation, i.e., interaction
Chapter 11: assess interaction in data - evident when risk of disease
among exposed to two potential causes > additive effect of each cause
Chapter 12: relation between exposure and health indicator is externally
valid to another population to the extent that interacting causes with
exposure are distributed similarly
Epidemiology Matters – Chapter 14
1. Seven steps of an epidemiological study
2. Balancing comparability and external validity
3. Small effects, big implications
4. Consequentialist epidemiology implications
5. Causal explanation versus intervention
6. Summary
Epidemiology Matters – Chapter 14
Small effects, big implications
Does the causal effect obtained in a study have consequence for the populations in which burden of disease is greatest?Are the effect estimates obtained in study translatable to actual cases of illness and disease potentially prevented by intervention?To answer: compare effect estimate magnitude to prevalence of exposures of interest; small magnitude of effect may translate to large public health benefits
Epidemiology Matters – Chapter 14
Small effects, big implicationsexample
Question: intervening to prevent occurrence of disease in Farrlandia, an overall population risk of 6/100, over 5 yearsTwo exposures associated with disease:
Exposure A associated with increased risk ratio of 1.2 disease onset
Exposure B associated with 5-fold increase disease riskWhich exposure should we invest public health time and money in preventing? Answer may depend on the prevalence of these exposures
Epidemiology Matters – Chapter 14
Small effects, big implicationsexample
Exposure A Exposure B
Interpretation: Exposure A has prevalence of
80% (800/1000). A risk ratio of 1.2 and 5 year
risk of 6%. Exposure to A caused 45 cases.
Interpretation: Exposure B has prevalence of
5%. A risk ratio of 5.0 and 5 year risk of 6%.
Exposure to B caused 12 cases.
Even though Exposure A has weaker overall effect on disease compared with Exposure
B , it is responsible for almost four times disease more because it is more prevalent in
population
Epidemiology Matters – Chapter 14
1. Seven steps of an epidemiological study
2. Balancing comparability and external validity
3. Small effects, big implications
4. Consequentialist epidemiology implications
5. Causal explanation versus intervention
6. Summary
Epidemiology Matters – Chapter 14
Consequentialist epidemiology
The ultimate purpose of epidemiology, the quantitative science of public health, is to understand the causes of human disease and improve health of the populations where the burden of disease is greatest
Health is not distributed equally across populations, a consequentialist epidemiologists engages in science beyond local borders
Epidemiology Matters – Chapter 14
ImplicationsTo study under 5 mortality in US
• Sample the population (Chapter 4)
• Measure potential causes of interest (Chapter 5)
• Estimate associations of effect of potential causes
on child mortality (Chapter 6)
• Assess associations for internal validity (Chapter 8)
• Assess interaction (Chapter 11)
• Consider the conditions for external validity across
populations (Chapter 12)
An epidemiology of consequence makes sure to study
child mortality in resource poor versus resource rich
settings
Epidemiology Matters – Chapter 14
1. Seven steps of an epidemiological study
2. Balancing comparability and external validity
3. Small effects, big implications
4. Consequentialist epidemiology implications
5. Causal explanation versus intervention
6. Summary
Epidemiology Matters – Chapter 14
Causal explanation and interventions
Effects of causes are not necessarily equal to the effects of interventions on those causes Epidemiologic studies can isolate specific effects of exposures by creating comparable exposed and unexposed groupsHowever, exposures cannot be removed in isolation, resulting in alterations to changing distribution of component causes once causes are manipulatedThis can have unintended consequences including increasing another adverse outcome
Epidemiology Matters – Chapter 14
1. Seven steps of an epidemiological study
2. Balancing comparability and external validity
3. Small effects, big implications
4. Consequentialist epidemiology implications
5. Causal explanation versus intervention
6. Summary
19Epidemiology Matters – Chapter 1
Seven steps
1. Define the population of interest
2. Conceptualize and create measures of exposures and health indicators
3. Take a sample of the population
4. Estimate measures of association between exposures and health indicators
of interest
5. Rigorously evaluate whether the association observed suggests a causal
association
6. Assess the evidence for causes working together, i.e., interaction
7. Assess the extent to which the result matters, is externally valid, to other
populations
20Epidemiology Matters – Chapter 1
epidemiologymatters.org
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