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# Age, period and cohort effects; reading trends

- Concept

A rate changes because of people's age, because of something that happened in a given year, or because of the generation they were born in.

Updated Nov 13, 2026

## Key points

- Age effect: risk changes with age in every generation.
- Period effect: a simultaneous change at all ages at one time (a new diagnostic test, an epidemic, a war).
- Cohort effect: the change appears first in the young and moves with that generation as it ages.
- A cross-section (all ages in one year) can give a misleading age curve if there is a cohort effect.
- Age, period and cohort are linked (cohort = period − age): they cannot be fully separated without assumptions.
- Artefactual changes: ICD revisions, new diagnostic criteria, screening, changes in registries or censuses.

## What it is

Trends in a rate break down into three effects: age (risk changes as people grow older), period (something affects all ages at once in a given year) and cohort (a generation born in certain years carries its own exposure throughout life). Before accepting that a trend is real, artefactual changes must be ruled out: new classification codes, better diagnostic methods, screening or errors in denominators.

## Worked example

- Rate of a cancer per 100,000 in 2000, 2010 and 2020. Age 40–49: 10, 20, 20. Age 50–59: 20, 20, 40.
- Age 60–69: 40, 40, 40. In every year the rate rises with age: an age effect.
- The rise appears in 2010 only at 40–49 and in 2020 at 50–59: always in people born in 1961–1970.
- That generation has double the previous one's rate at the same age: 20 against 10, and 40 against 20.
- A period effect would have raised all ages in the same year; that does not happen here.
- Reading: a cohort effect; look for a new exposure in that generation. Around 2030 the rise would be expected at 60–69.

## Three effects in a trend

| Effect | How it shows in the table | Example |
| --- | --- | --- |
| Age | Rises or falls down each year's column | Cancer more common with age |
| Period | All ages change in the same year | A new test that finds more cases at all ages |
| Cohort | The change follows one generation diagonally | Generations that took up smoking in large numbers |
| Artefact | A sudden jump that coincides with a recording change | A change of ICD version |

## Markers

- Age
- Period
- Cohort
- Trend

## In practice

- Before announcing an epidemic, check whether the case definition, code, diagnostic test or screening changed.
- Rising incidence with stable mortality suggests more diagnosis (overdiagnosis) rather than more disease.
- Use age-adjusted rates to compare years: the population is ageing.

## Common pitfalls

- Reading the age curve of a single year as the story of one person growing older.
- Comparing rates without checking whether the denominator changed (new census, migration).
- Blaming chance for a jump that coincides with an ICD change or a new surveillance system.

## Memory aid

Age is what happens to everyone on their birthdays; period, what happens to everyone in one year; cohort, what a generation brings with it.

## Test yourself

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

## What pattern in an age-by-year table shows a cohort effect?

A change that appears first in the youngest and moves diagonally to older ages with the same generation.

## What pattern shows a period effect?

A simultaneous change at all ages in the same year.

## A cancer's incidence doubles after screening starts and mortality does not change. What does it suggest?

A rise that is largely artefactual from detection (including overdiagnosis), not more disease.

## Why can the three effects not be fully separated?

Because they are linearly dependent: year of birth is calendar year minus age.

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## Connections

## Related 6

- [Standardisation of rates](https://durgical.com/en/epidemiology/standardisation-of-rates/)
- [Mortality rates: crude and specific](https://durgical.com/en/epidemiology/mortality-rates-crude-and-specific/)
- [Incidence](https://durgical.com/en/epidemiology/incidence/)
- [Overdiagnosis](https://durgical.com/en/epidemiology/overdiagnosis/)
- [Public health surveillance](https://durgical.com/en/epidemiology/public-health-surveillance/)
- [Migrant studies](https://durgical.com/en/epidemiology/migrant-studies/)

[← 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: [Gen X Projected to Experience Greater Increases in Cancer Incidence than Previous Generations](https://dceg.cancer.gov/news-events/news/2024/generation-cancer-incidence) (National Cancer Institute, Division of Cancer Epidemiology and Genetics, 2024); [SEER Cancer Statistics Review 1975-2016: Introduction](https://seer.cancer.gov/archive/csr/1975_2016/results_merged/sect_01_overview.pdf) (National Cancer Institute, 2019); [Age adjustment](https://www.cdc.gov/nchs/hus/sources-definitions/age-adjustment.htm) (National Center for Health Statistics, Centers for Disease Control and Prevention, 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/age-period-and-cohort-effects-reading-trends/