from association to causation

From Association to Causation: Deriving Inferences from

Epidemiologic Studies

Najibullah Safi, MD, MSc. HPMNPO/PHC – WHO Country Office

Afghanistan

04/11/2023 2

Presentation outline

• Approaches for studying diseases etiology• Ecologic studies• Type of association• Type of causal relationships

04/11/2023 3

Approaches for studying diseases etiology

• Expose animals to risk factors such as carcinogens in control lab – Control the exposure dose – Control other environmental conditions and

genetic factors – Keep lost to follow-up to minimum

• Can we extrapolate data across species and from animal to human population?

04/11/2023 4

Approaches to etiology in human population

• Epidemiology build on unplanned or natural experiments – People exposed to risk for non-study purposes • e.g. exposure to atomic bomb radiation in Hiroshima

and Nagasaki 1945

04/11/2023 5

Approaches to etiology in human population cont.

• Sequences of studies in human populationClinical observation

Available data

Case control studies

Cohort studies

Randomized trials

04/11/2023 6

Approaches to etiology in human population cont.

• Conceptually, a two step process is followed in carrying out studies and evaluating evidence– Determining association between an exposure or

characteristics and the risk of a disease• Studies of group characteristics: ecological studies• Studies of individual characteristics: case control and

cohort

– If association exist – determine whether the observed association is likely to be a causal one

04/11/2023 7

Ecologic studies

• Studies of group characteristics

04/11/2023 8

Ecologic studies cont.

• Higher the average dietary fat consumption for a country, the higher breast cancer incidence

• No information on individuals (outcome - breast cancer vs. exposure - high dietary fat intake)

• Ascribing to members of a group, characteristics that they in fact do not possess as individuals (ecologic fallacy)

04/11/2023 9

Ecologic studies cont.

What is the problem? The authors wrote: “the observed association is between pregnancy during an influenza epidemic and subsequent leukemia in the offspring of that pregnancy. It is not known if the mothers of any of these children actually had influenza during their pregnancy”.

04/11/2023 10

Type of association

(Non-causal)

04/11/2023 11

Type of association cont.

• McMahon’s study: observed association of coffee consumption with risk of pancreatic cancer

Coffee Drinking

Pancreatic Cancer

Causal association

Coffee Drinking

Smoking

Pancreatic Cancer

Non-causal association (due to confounding

04/11/2023 12

Types of causal relationships

04/11/2023 13

Types of causal relationships cont.

• Necessary and sufficient – Without that factor the diseases never develops,

and in its presence the disease always develops – This situation rarely occurred

Factor A Disease

04/11/2023 14


• Necessary, but not sufficient – Factor is necessary but not sufficient to produce

the disease e.g. Tubercle bacillus – Multiple factors are required, often in a specific

temporal sequence

Factor A+

Factor B+

Factor C

Disease

04/11/2023 15


• Sufficient, but not necessary– The factor alone can produce the disease, but so

can other factors • Radiation, benzene – either can produce leukemia• Cancer does not develop in everyone who has

experienced radiation or benzene exposure

Factor Aor

Factor Bor

Factor C

Disease

04/11/2023 16


• Neither sufficient nor necessary– More complex model – Probably most accurately represents the causal

relationships that operate in most chronic diseases

Factor A + Factor Bor

Factor C + Factor Dor

Factor E + Factor F

Disease

04/11/2023 17

Evidence for a causal relationship

• Infectious diseases: Henle assumptions 1840 – which was expanded by Koch in 1880s: – The organism is always found with the disease– The organism is not found with any other disease – The organism, isolated from one who has the

disease, and cultured through several generations, produces the disease (in experimental animals)

• NCDs, no organism to detect and culture --- causal relationship more complex

04/11/2023 18

Guidelines for judging whether an association is causal

1. Temporal relationship 2. Strength of association3. Dose response relationship4. Replication of findings 5. Biologic plausibility 6. Consideration of alternate explanations7. Cessation of exposure 8. Consistency with other knowledge 9. Specificity of the association

04/11/2023 19

Temporal relationship

• Exposure to the factor must occurred before the disease developed

• It is easy to establish a temporal relationship in a prospective cohort study than case control and retrospective cohort

• Length of the interval between the exposure and disease (asbestos in lung cancer)

04/11/2023 20

Temporal relationship cont.

04/11/2023 21



04/11/2023 22

Strength of association

• Strength of association is measured by Relative Risk or Odds Ratio

• The stronger the association, the more likely the relation is causal

04/11/2023 23



04/11/2023 24

Dose response relationship

• As the dose of exposure increase, the risk of disease also increases

• If a dose response relationship is present, it is strong evidence for a causal relationship

• Absence of dose response relationship does not necessarily rule out a causal relationship

• In some cases a threshold may exist

04/11/2023 25

Dose response relationship cont.

04/11/2023 26



04/11/2023 27

Replication of findings

• If the relationship is causal, we would expect to find it consistently in different studies and in different population

• It is expected to be present in subgroups of the population

04/11/2023 28



04/11/2023 29

Biologic plausibility

• Coherence with the current body of biologic knowledge

• Sometimes, epidemiological observation preceded biologic knowledge – E.g. Gregg’s observation on Rubella and congenital

cataracts preceded any knowledge of teratogenic viruses

• If epidemiological findings are not consistent with the existing knowledge – interpreting the meaning of observed association might be difficult

04/11/2023 30



04/11/2023 31

Consideration of alternate explanations

• Explanation of a relationship as causal or due to confounding

• The extent to which the investigators have taken other possible explanations into account and the extent to which they have ruled out such explanations are important considerations

04/11/2023 32



04/11/2023 33

Cessation of exposure

• If a factor is a cause of a diseases, the risk of the disease to decline when exposure to the factor is reduced or eliminated

04/11/2023 34

Cessation of exposure cont.

Eosinophilia myalgia syndrome caused by L-tryptophan

04/11/2023 35



04/11/2023 36

Consistency with other knowledge

• If a relationship is causal, we would expect the findings to be consistent with other data

04/11/2023 37



04/11/2023 38

Specificity of the association

• An association is specific when a certain exposure is associated with only one disease – The weakest point of the guideline – should be

removed – Smoking is linked with lung, pancreatic & bladder

cancers; hearth disease, emphysema … – When specificity of an association is found, it

provides additional support for a causal inference– With a dose response relationship, absence of

specificity in no way negates a causal relationship

04/11/2023 39

More on causal inferences

• Bias• Confounding • Interaction

04/11/2023 40

Thanks, any questi ons or comment

from association to causation

Documents