Confounding and effect modification

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Confounding and effect modification

• Preben Aavitsland

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Can we believe the result?
Rice
Salmonellosis
OR 3.9
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Systematic error

• Does not decrease with increasing sample size
• Selection bias
• Information bias
• Confounding

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Confunding - 1
Mixing of the effect of the exposure on disease
with the effect of another factor that is
associated with the exposure.
Exposure
Disease
Confounder
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Confounding - 2

• Key term in epidemiology
• Most important explanation for associations
• Always look for confounding factors

Surgeon
Post op inf.
Op theatre I
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Criteria for a confounder
1 A confounder must be a cause of the disease (or
a marker for a cause) 2 A confounder must be
associated with the exposure in the source
population 3 A confounder must not be affected by
the exposure or the disease
Umbrella
Less tub.
2
1
Class
3
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Downs syndrome by birth order
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Find confounders
Second, third and fourth child are more often
affected by Downs syndrome.
Many children
Downs
Maternal age
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Downs syndrome by maternal age
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Downs syndrome by birth order and maternal age
groups
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Find confounders
The Norwegian comedian Marve Fleksnes once
stated I am probably allergic to leather because
every time I go to bed with my shoes on, I wake
up with a headache the next morning.
Sleep shoes
Headache
Alcohol
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Find confounders
A study has found that small hospitals have
lower rates of nosocomial infections than the
large university hospitals. The local politicians
use this as an argument for the higher quality of
local hospitals.
Small hosp
Few infections
Well patients
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Controlling confounding

• In the design
• Restriction of the study
• Matching
• Before data collection!

• In the analysis
• Restriction of the analysis
• Stratification
• Multivariable regression
• After data collection!

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Restriction
Restriction of the study or the analysis to a
subgroup that is homogenous for the possible
confounder. Always possible, but reduces the size
of the study.
Umbrella
Less tub.
Lower class
Class
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Restriction
We study only mothers of a certain age
Many children
Downs
35 year old mothers
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Matching
Selection of controls to be identical to the
cases with respect to distribution of one or more
potential confounders.
Many children
Downs
Maternal age
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Disadvantages of matching

• Breaks the rule Control group should be
  representative of source population
• Therefore Special matched analysis needed
• More complicated analysis
• Cannot study whether matched factor has a causal
  effect
• More difficult to find controls

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Why match?

• Random sample from source population may not be
  possible
• Quick and easy way to get controls
• Matched on social factors Friend controls,
  family controls, neighbourhood controls
• Matched on time Density case-control studies
• Can improve efficiency of study
• Can control for confounding due to factors that
  are difficult to measure

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Should we match?

• Probably not, but may
• If there are many possible confounders that you
  need to stratify for in analysis

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Stratified analysis

• Calculate crude odds ratio with whole data set
• Divide data set in strata for the potential
  confounding variable and analyse these separately
• Calculate adjusted (ORmh) odds ratio
• If adjusted OR differs (gt 10-20) from crude OR,
  then confounding is present and adjusted OR
  should be reported

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Procedure for analysis

• When two (or more) exposures seem to be
  associated with disease
• Choose one exposure which will be of interest
• Stratify by the other variable
• Meaning. Making one two by two table for those
  with and one for those without the other variable
  (for example, one table for men and one for
  women)
• Repeat the procedure, but change the variables

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Example

• Salmonella after wedding dinner
• Disease seems to be associated with both chicken
  and rice
• But many had both chicken and rice

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Confounding
Is rice a confounder for the chicken ?
salmonellosis association? Stratify Make one 2x2
table for rice-eaters and one for non-rice-eaters
(e.g. in Episheet)
Chicken
Salmonellosis
Rice
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No confounding
Because OR for chicken alone ORmh for chicken
controlled for rice
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Confounding
Is chicken a confounder for the rice ?
salmonellosis association? Stratify Make one 2x2
table for chicken-eaters and one for
non-chicken-eaters (e.g. in Episheet)
Rice
Salmonellosis
Chicken
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Confounding

• Because
• OR for rice alone ORmh for rice controlled
  for chicken

Not 3,9
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Conclusion

• Chicken is associated with salmonellosis
• Rice is not associated with salmonellosis
• confounding by chicken because many
  chicken-eaters also had rice
• rice only appeared to be associated with
  salmonellosis
• Stratification was needed to find confounding
• Compare crude OR to adjusted OR (ORmh)
• If gt 10-20 difference ? confounding!

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Multivariable regression

• Analyse the data in a statistical model that
  includes both the presumed cause and possible
  confounders
• Measure the odds ratio OR for each of the
  exposures, independent from the others
• Logistic regression is the most common model in
  epidemiology
• But explore the data first with stratification!

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Controlling confounding

• In the design
• Restriction of the study
• Matching

• In the analysis
• Restriction of the analysis
• Stratification
• Multivariable methods

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Effect modification

• Definition The association between exposure and
  disease differ in strata of the population
• Example Tetracycline discolours teeth in
  children, but not in adults
• Example Measles vaccine protects in children gt
  15 months, but not in children lt 15 months
• Rare occurence