[Durgical](https://durgical.com/en/) › [DurgiPedia](https://durgical.com/en/durgipedia/) › [Epidemiology](https://durgical.com/en/epidemiology/) › [Bias, confounding and causation](https://durgical.com/en/epidemiology/areas/bias/) › Reverse causation

# Reverse causation

- Concept

Sometimes the exposure does not cause the disease; the disease (or its first symptoms) changes the exposure.

Updated Nov 5, 2026

## Key points

- The outcome causes the exposure, not the reverse.
- Very common in cross-sectional studies, which do not show what came first.
- Protopathic bias: a treatment started for early symptoms of an undiagnosed disease appears to cause it.
- The ‘sick quitter’ effect: people who stop drinking because of illness make moderate drinking look protective.
- Controlled with cohorts, by measuring exposure before the outcome and excluding the first years of follow-up.

## What it is

Reverse causation is present when the outcome, or an early, not yet diagnosed stage of it, brings about the exposure, rather than the other way round. It is common in cross-sectional studies, where exposure and outcome are measured together. Protopathic bias is a variant: a drug is started for the first symptoms of a disease not yet diagnosed and then appears to have caused it. It is avoided by securing temporality: measuring exposure before the outcome and excluding the first years of follow-up.

## Worked example

- Survey of 2 000 adults: 400 do not drink alcohol and 1 600 drink moderately.
- Poor health: 80 of 400 non-drinkers (20%) and 160 of 1 600 moderate drinkers (10%).
- Prevalence ratio = 20% / 10% = 2.0: not drinking seems to harm health.
- But 120 of the 400 non-drinkers are former drinkers who quit because of illness; 50 of them are in poor health.
- Lifelong non-drinkers: 400 − 120 = 280, with 80 − 50 = 30 in poor health: 30 / 280 ≈ 10.7%.
- New prevalence ratio = 10.7% / 10% ≈ 1.07.
- Reading: illness made many stop drinking; the arrow pointed the other way.

## Markers

- Temporality
- Protopathic

## In practice

- In pharmacoepidemiology a latency period (for example, the first year of use) is excluded to reduce protopathic bias.
- Before accepting that a behaviour protects, ask whether the disease could have changed that behaviour.

## Common pitfalls

- Reading a cross-sectional association as causal without thinking about its direction.
- Lumping people who were never exposed together with those who gave up the exposure because of illness.

## Memory aid

Before blaming the arrow, check which way it points.

## Test yourself

Think of the answer, then tap the question to see it.

## What is reverse causation?

An association in which the outcome, or its early stage, causes the exposure rather than the exposure causing the outcome.

## What is protopathic bias?

Blaming a disease on a drug that was in fact started for the first symptoms of that still undiagnosed disease.

## Which design is most vulnerable to reverse causation?

The cross-sectional study, because it measures exposure and outcome at the same time.

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## Connections

## Related 5

- [Cross-sectional study](https://durgical.com/en/epidemiology/cross-sectional-study/)
- [Bradford Hill criteria for causation](https://durgical.com/en/epidemiology/bradford-hill-criteria-for-causation/)
- [Chance, bias, confounding or cause](https://durgical.com/en/epidemiology/chance-bias-confounding-or-cause/)
- [Cohort study](https://durgical.com/en/epidemiology/cohort-study/)
- [Confounding](https://durgical.com/en/epidemiology/confounding/)

[← All of epidemiology](https://durgical.com/en/epidemiology/)

Educational content on epidemiological and statistical methods; the examples use made-up numbers to teach the calculation. Not a clinical or legal guide: current Colombian rules are in the official sources.

Sources: [Principles of Epidemiology | Lesson 1 - Section 7](https://archive.cdc.gov/www_cdc_gov/csels/dsepd/ss1978/lesson1/section7.html) (Centers for Disease Control and Prevention, 2012); [Bradford Hill criteria | UMC](https://who-umc.org/signal-management/bradford-hill-criteria/) (Uppsala Monitoring Centre, 2026).

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Representative model, for educational purposes only.

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License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Cite as: DurgiPedia (durgical.com), https://durgical.com/en/epidemiology/reverse-causation/