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Confounding and effect modification. Preben Aavitsland. Can we believe the result?. Rice. Salmonellosis. OR = 3.9. Systematic error. Does not decrease with increasing sample size Selection bias Information bias Confounding. Confunding - 1.

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can we believe the result
Can we believe the result?

Rice

Salmonellosis

OR = 3.9

systematic error
Systematic error
  • Does not decrease with increasing sample size
  • Selection bias
  • Information bias
  • Confounding
confunding 1
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

confounding 2
Confounding - 2
  • Key term in epidemiology
  • Most important explanation for associations
  • Always look for confounding factors

Surgeon

Post op inf.

Op theatre I

criteria for a confounder
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

find confounders
Find confounders

“Second, third and fourth child are more often affected by Downs’ syndrome.”

Many children

Downs’

Maternal age

find confounders11
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

find confounders12
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

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!

Controlling confounding
restriction
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

restriction15
Restriction

We study only mothers of a certain age

Many children

Downs’

35 year old mothers

matching
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

disadvantages of matching
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
why match
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
should we match
Should we match?
  • Probably not, but may:
  • If there are many possible confounders that you need to stratify for in analysis
stratified analysis
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 (> 10-20%) from crude OR, then confounding is present and adjusted OR should be reported
procedure for analysis
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
example
Example
  • Salmonella after wedding dinner
  • Disease seems to be associated with both chicken and rice
  • But many had both chicken and rice
confounding
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

no confounding
No confounding

Because:

OR for chicken alone = ORmh for chicken ”controlled for rice”

confounding25
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

confounding26
Confounding

Because:

OR for rice alone = ORmh for rice ”controlled for chicken”

Not 3,9

conclusion
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 > 10-20% difference  confounding!
multivariable regression
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!
controlling confounding29
In the design

Restriction of the study

Matching

In the analysis

Restriction of the analysis

Stratification

Multivariable methods

Controlling confounding
effect modification
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 > 15 months, but not in children < 15 months
  • Rare occurence