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<!doctype html><html lang="en" class="js-disabled"><head><meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1"/><title>Period versus cohort measures: what’s the difference? - Our World in Data</title><meta name="description" content="What do the terms “period” and “cohort” mean in statistics? 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How do they differ, and why does it matter?"/><meta name="twitter:image" content="https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/eef226b0-954a-4c7c-5d78-14eaf8bcb100/public"/><link rel="modulepreload" href="/assets/owid.mjs"/><link rel="preload" href="https://cdnjs.cloudflare.com/polyfill/v3/polyfill.min.js?version=4.8.0&features=es2021,es2022,es2023,IntersectionObserver,IntersectionObserverEntry" as="script" data-cloudflare-disable-early-hints="true"/><link rel="preload" href="/assets/owid.css" as="style"/><link rel="stylesheet" href="/assets/owid.css"/><meta name="citation_title" content="Period versus cohort measures: what’s the difference?"/><meta name="citation_fulltext_html_url" content="https://ourworldindata.org/period-versus-cohort-measures-whats-the-difference"/><meta name="citation_fulltext_world_readable" content=""/><meta name="citation_publication_date" content="2023/11/27"/><meta name="citation_journal_title" content="Our World in Data"/><meta name="citation_journal_abbrev" content="Our World in Data"/><meta name="citation_author" content="Saloni Dattani"/><script>window._OWID_GDOC_PROPS = {"slug":"period-versus-cohort-measures-whats-the-difference","published":true,"createdAt":"2023-09-24T08:46:07.000Z","publishedAt":"2023-11-27T11:46:31.000Z","updatedAt":"2023-12-28T16:31:04.000Z","revisionId":"ALBJ4LsDb9j226A4NubA64m9LSK4CmNsCGeLPQbRpobHxRTi1ZNdQxm2ZRwFkcjDCmxalG-YgnclB4gfUBu40Q","markdown":"Several concepts in demography can be calculated either as a “cohort” or as a “period” measure. These terms are often used to describe life expectancy, but also apply to measures such as fertility rates or the age of death.\n\nHow do these terms differ, and why does it matter?\n\nIn this article, I will explain the difference between period and cohort measures. I will also give some examples of what they are used for, and describe how they are calculated and interpreted.\n\nTo do this, we’ll look at three different uses of period and cohort: data, effects and measures.\n\n# Period versus cohort data\n\nLet’s start by looking at period and cohort _data_. These will help to develop an intuition about what the terms mean.\n\n**Period data** refers to data collected from groups of people at_ a given time_.\n\nFor example, data could be collected for the year 2019, across the population who live in the United Kingdom that year. If the data is collected again the next year, the people included in the data could be different, due to births and migrations.\n\n**Cohort data** refers to data on _the same group of people_ – a cohort – who have been tracked _over time_.\n\nFor example, data might be collected for people born in the United Kingdom in 2019, with more data collected from them as they grow older.1\n\nYou can see a comparison between them in the visualization below.2\n\n<Image filename=\"period-vs-cohort-visual.png\"/>\n\nSo, period data comes from a group of people at a particular time, while cohort data is collected from the same group of people across time.\n\n# Period versus cohort effects\n\nNow let’s turn to period and cohort _effects_.\n\n**Period effects** are caused by events that affect many people at a particular time.\n\nFor example, the two World Wars and the [Spanish flu pandemic in 1918](https://ourworldindata.org/spanish-flu-largest-influenza-pandemic-in-history) each caused a surge in death rates across the population at that particular time, especially among young and middle aged adults.\n\nYou can see their effects in the chart of annual change in mortality rates in England and Wales below.\n\nPeriod effects are shown as red vertical lines or streaks, which means they affected many age groups during those specific years.\n\n<Image filename=\"period-vs-cohort-lexis-plot-uk.png\"/>\n\n**Cohort effects** are different – they are generational effects that carry forward as people age. They come from experiences that people had at a particular time, which continued to affect them later on.\n\nYou can see cohort effects in the chart above as well – they are the diagonal lines.\n\nFor example, there is a clear red diagonal line that starts in 1918. The line shows us that people born during the 1918 Spanish flu pandemic had higher risks of death across their whole lifetimes than people born just before or after it.3\n\n# Period versus cohort measures\n\nNow we know what period and cohort _effects_ and _data_ mean.\n\nBut what about the difference between period and cohort measures?\n\nAs an example, let’s look at life expectancy. This time, we’ll start with the **cohort** measure of life expectancy, which is more straightforward.\n\n## Cohort life expectancy\n\n**Cohort life expectancy** is a measure of the average lifespan that people have had. It can be calculated for a birth cohort by tracking people born in a given year across their lives.\n\nThis calculation is straightforward, but it requires data to be collected across a very long time frame.\n\nIt means we need to wait for decades – until everyone in the birth cohort has died – so that we can calculate their average lifespan.4\n\n## Period life expectancy\n\nAnother way to calculate life expectancy is with **period life expectancy**.\n\nIt is a metric that summarizes the death rates across the population _in a given year_.\n\nRather than tracking a group of people over their lives, it involves creating a ‘synthetic cohort’ that we walk through the death rates that are seen in each age group within _one particular year_.\n\nIt assumes that death rates in each age group this year are equivalent to the death rate of this year’s newborns when they reach those same ages. For example, that the death rate among fifty year olds in a particular year is a good proxy for the death rate of newborns fifty years later.\n\nI’ll describe an example. Imagine there are 1,000 infants (under one year old)5, and in a particular year, infants had a death rate of 5 per 1,000. This tells us that 995 of them would survive to the age of one.\n\nNow, imagine these 995 have reached the age of one. Based on the death rate among one year olds _in the same year_, we can now estimate how many might survive to the age of two.\n\nWe can then carry on this calculation for the entire hypothetical cohort of 1,000 infants. Along with this, we can keep track of how many years each of them survived.\n\nThen, we can calculate the average number of years lived by the entire group of 1,000 hypothetical infants. This is equal to the period life expectancy at birth.\n\nThis means period life expectancy is a summary measure of death rates in one particular year, rather than a prediction of how long people will actually live.6\n\nThis means that, for a given year, it represents the average lifespan for a hypothetical group of people, if they experienced the same age-specific death rates throughout their whole lives as the age-specific death rates seen in one particular year.\n\nIn the chart below, you can see a comparison between period and cohort life expectancy.\n\n<Chart url=\"https://ourworldindata.org/grapher/period-versus-cohort-life-expectancy\"/>\n\nAs you can see, cohort life expectancy (the actual average lifespan) is higher than period life expectancy. This is because period life expectancy is calculated by assuming people will experience the current year’s mortality rates at each age at the corresponding ages in their lifetime.\n\nBut in reality, mortality rates declined throughout the 20th century, so people actually lived longer than what’s implied by period life expectancy.7\n\nAnother reason for the difference is that period life expectancy is partly a reflection of conditions _of the past_ that continue to affect older generations’ death rates today.8\n\nYou can also see that the trendline of cohort life expectancy ends decades ago. It can only be measured retrospectively, because researchers need to wait for data on deaths of the population who were born more recently.\n\n## Ages at death, death rates, and other measures\n\nWe can also calculate other metrics using either period or cohort measures.\n\nFor example, we might be interested in the **modal age at death**, which is the most common age at which people die in a given year.9\n\nThe modal age at death can be measured as a period indicator – where it refers to the most common age at which people died in 2019, for example. Or as a cohort rate – where it refers to the most common age at which people died, among those born in the same year.\n\nMany other measures can also be described with period or cohort data.\n\nThis includes the **age-specific mortality profiles**, which are the death rates across age groups.\n\nAge-specific mortality profiles can be calculated from a time period, for example, death rates in different age groups during a particular year.\n\nOr they can be tracked for a cohort, where they refer to the death rates at different ages of a given birth cohort as they have grown older over time.\n\nIn the chart, you can see a comparison between period and cohort age mortality profiles. The horizontal axis shows the age, and the vertical axis shows the share of people of that age who died that year.\n\nThe data comes from France and covers the entire population.10\n\n<Image filename=\"period-vs-cohort-age-mortality.png\"/>\n\nAs you can see, _period_ mortality profiles show death rates across age groups in a particular year. Death rates were elevated in 1918 and 1940, across youth and middle aged adults, due to the two World Wars and the 1918 Spanish flu pandemic.\n\nThis period measure is useful because it tells us how different age groups were affected during a specific period in time.\n\nThe _cohort_ mortality profile shows death rates for people born in different cohorts, at different ages of their lives. You can see elevated death in those born in 1910, 1918 and 1920, across their youth and middle-age, due to the two World Wars and the 1918 Spanish flu pandemic.\n\nThis cohort measure is useful because it tells us how different generations experienced these events, and how mortality rates varied across their lifespans.\n\nPeriod and cohort measures are also used for other topics, such as fertility rates, not only mortality data.11\n\n# What are period and cohort measures used for?\n\nPeriod and cohort measures are used for different purposes.\n\nThe most appropriate choice depends on what you’re interested in and what data is available.\n\n**Period measures** summarize data from a particular point in time. They can therefore be useful to understand the impact of immediate events, such as pandemics and wars. They can help answer the question: during these periods, which age groups were more likely to die?\n\n**Cohort measures** track changes as people grow older. They can be used to understand death rates among a birth cohort as the group grows older.\n\nThey can also help to understand the historical experience that people have had. For cohorts born during the 1918 Spanish flu pandemic, for example, they can help us understand how it impacted their long-term survival.\n\nOf course, cohort data is only available in retrospect and we need to wait many decades before full data becomes available. It is also more difficult to collect data across many years, decades, or even over a century and therefore is only available for relatively few populations.\n\nIn the visualization below, you can see a summary of the main points in this article.\n\n<Image filename=\"period-vs-cohort-explanation.png\"/>\n\n<Callout title=\"Acknowledgements\"/>\n\nThis visualization was inspired by a diagram in the Office for Budget Responsibility’s report.\n\nOffice for Budget Responsibility. (2018, July). Period and cohort measures of fertility and mortality. [https://obr.uk/box/period-cohort-measures-of-fertility-and-mortality/](https://obr.uk/box/period-cohort-measures-of-fertility-and-mortality/)\n\nSee also:\n\nWilson, C., Sobotka, T., Williamson, L., & Boyle, P. (2013). Migration and Intergenerational Replacement in Europe. Population and Development Review, 39(1), 131–157. [https://doi.org/10.1111/j.1728-4457.2013.00576.x](https://doi.org/10.1111/j.1728-4457.2013.00576.x)\n\nIn the Human Mortality Database, researchers have a threshold to wait until 99% of the relevant exposure data from a given cohort is available until making cohort estimates.\n\nSee section 7.2.2 in the Human Mortality Database full protocol v6.\n\nWilmoth, J. R., Andreev, K., Jdanov, D., Glei, D. A., Riffe, T., Boe, C., Bubenheim, M., Philipov, D., Shkolnikov, V., Vachon, P., Winant, C., & Barbieri, M. (2021). Methods protocol for the human mortality database (v6). [https://www.mortality.org/File/GetDocument/Public/Docs/MethodsProtocolV6.pdf](https://www.mortality.org/File/GetDocument/Public/Docs/MethodsProtocolV6.pdf)\n\nCanudas-Romo, V., & Schoen, R. (2005). Age-specific contributions to changes in the period and cohort life expectancy. Demographic Research, 13, 63–82. [https://doi.org/10.4054/DemRes.2005.13.3](https://doi.org/10.4054/DemRes.2005.13.3)\n\nVaupel, J. W. (2002). Life expectancy at current rates vs. Current conditions: A reflexion stimulated by Bongaarts and Feeney’s “How long do we live?” Demographic Research, 7, 365–378. [https://doi.org/10.4054/DemRes.2002.7.8](https://doi.org/10.4054/DemRes.2002.7.8)\n\nOeppen, J., & Vaupel, J. W. (2002). Broken Limits to Life Expectancy. Science, 296(5570), 1029–1031. [https://doi.org/10.1126/science.1069675](https://doi.org/10.1126/science.1069675)\n\nWe usually talk about birth cohorts – people born in the same year – but the term can be used for many kinds of groups: immigration cohorts, marriage cohorts, stroke survivors, university alumni, and so on. In this article, we’ll focus on birth cohorts.\n\nGuillot, M. (2011). Period Versus Cohort Life Expectancy. In R. G. Rogers & E. M. Crimmins (Eds.), International Handbook of Adult Mortality (Vol. 2, pp. 533–549). Springer Netherlands. [https://doi.org/10.1007/978-90-481-9996-9_25](https://doi.org/10.1007/978-90-481-9996-9_25)\n\nFor example, researchers can measure the **total fertility rate** (TFR) as a period measure. It represents the average fertility for a hypothetical group of women in a given year, if they experienced the same age-specific fertility rates throughout their whole lives as the age-specific fertility rates seen in that particular year.\n\nBut TFR can also be measured as a cohort measure – where it represents the average number of children born to women in that cohort by the end of their reproductive lives.\n\nThis distinction is important because period TFR can be influenced by the timing of childbearing and can therefore fluctuate due to trends such as women choosing to have children later in life.\n\nBongaarts, J., & Feeney, G. (1998). On the Quantum and Tempo of Fertility. Population and Development Review, 24(2), 271. [https://doi.org/10.2307/2807974](https://doi.org/10.2307/2807974)\n\nIn addition, demographers can also calculate hybrid measures from both period and cohort.\n\nSee for an example: Wilson, C., Sobotka, T., Williamson, L., & Boyle, P. (2013). Migration and Intergenerational Replacement in Europe. Population and Development Review, 39(1), 131–157. [https://doi.org/10.1111/j.1728-4457.2013.00576.x](https://doi.org/10.1111/j.1728-4457.2013.00576.x)\n\nJones, P. M., Minton, J., & Bell, A. (2023). Methods for disentangling period and cohort changes in mortality risk over the twentieth century: Comparing graphical and modelling approaches. Quality & Quantity, 57(4), 3219–3239. [https://doi.org/10.1007/s11135-022-01498-3](https://doi.org/10.1007/s11135-022-01498-3)\n\nVaupel, J. W. (2002). Life expectancy at current rates vs. Current conditions: A reflexion stimulated by Bongaarts and Feeney’s “How long do we live?” Demographic Research, 7, 365–378. [https://www.demographic-research.org/volumes/vol7/8/7-8.pdf](https://www.demographic-research.org/volumes/vol7/8/7-8.pdf)\n\nMissov, T. I., Lenart, A., Nemeth, L., Canudas-Romo, V., & Vaupel, J. W. (2015). The Gompertz force of mortality in terms of the modal age at death. Demographic Research, 32, 1031–1048. [https://doi.org/10.4054/DemRes.2015.32.36](https://doi.org/10.4054/DemRes.2015.32.36)\n\nHoriuchi, S., Ouellette, N., Cheung, S. L. K., & Robine, J.-M. (2013). Modal age at death: Lifespan indicator in the era of longevity extension. _Vienna Yearbook of Population Research_, 37–69. [https://www.jstor.org/stable/43050796](https://www.jstor.org/stable/43050796)\n\nMissov, T. I., Lenart, A., Nemeth, L., Canudas-Romo, V., & Vaupel, J. W. (2015). The Gompertz force of mortality in terms of the modal age at death. Demographic Research, 32, 1031–1048. [https://doi.org/10.4054/DemRes.2015.32.36](https://doi.org/10.4054/DemRes.2015.32.36)\n\nIn demography, it’s common to describe population sizes in 100,000 people instead. However, I’ve used 1,000 in this hypothetical example to make the numbers more digestible.\n\nTo recreate this chart, or create it for other countries, the [scripts](https://github.com/owid/notebooks/tree/main/SaloniDattani/Life-expectancy/Period-vs-cohort-age-mortality) are available online.","publicationContext":"listed","breadcrumbs":[{"label":"Life Expectancy","href":"https://ourworldindata.org/life-expectancy"}],"manualBreadcrumbs":null,"tags":[{"id":7,"name":"Life Expectancy","slug":"life-expectancy"}],"errors":[],"donors":["A Burrows","A Francois","A Neves","A.W. 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(2023) Methods for disentangling period and cohort changes in mortality risk over the twentieth century: Comparing graphical and modelling approaches.\n\nIt shows the annual change in mortality rates on a Lexis plot, using national mortality data from England and Wales across the 20th century.","originalWidth":1424,"updatedAt":1697210163017,"originalHeight":694,"cloudflareId":"2a5670da-015d-48f3-f50a-71315420c900","hash":null,"userId":50,"replacedBy":null,"version":0},"period-vs-cohort-age-mortality.png":{"id":459,"googleId":"1qd3j7KjSE-AZv9QUBRFG1JJUYIIcklG6","filename":"period-vs-cohort-age-mortality.png","defaultAlt":"A comparison between period and cohort age-specific mortality rates, using national mortality data from France.","originalWidth":10905,"updatedAt":1702033796986,"originalHeight":7135,"cloudflareId":"3ea05ad4-8746-424b-b6e1-e95951212e00","hash":null,"userId":50,"replacedBy":null,"version":0},"period-vs-cohort-explanation.png":{"id":457,"googleId":"1CqzRnK9YoddGYHWaamUPP5hCMmbK_fy4","filename":"period-vs-cohort-explanation.png","defaultAlt":"A visual explanation of the difference between period and cohort measures, with a few examples.","originalWidth":10768,"updatedAt":1702033749510,"originalHeight":11965,"cloudflareId":"cea9e4f1-220c-4892-651c-a528b5f16500","hash":null,"userId":61,"replacedBy":null,"version":0}},"linkedAuthors":[{"slug":"saloni-dattani","name":"Saloni Dattani","featuredImage":"saloni-owid.jpeg","updatedAt":"2024-05-24 15:38:42"}],"linkedCharts":{"period-versus-cohort-life-expectancy":{"configType":"grapher","originalSlug":"period-versus-cohort-life-expectancy","title":"Period versus cohort life expectancy","tab":"chart","resolvedUrl":"https://ourworldindata.org/grapher/period-versus-cohort-life-expectancy","thumbnail":"https://ourworldindata.org/grapher/period-versus-cohort-life-expectancy.png","tags":[]}},"linkedIndicators":{},"linkedDocuments":{},"latestDataInsights":[],"linkedChartViews":{},"relatedCharts":[],"content":{"toc":[{"slug":"cohort-life-expectancy","text":"Cohort life expectancy","title":"Cohort life expectancy","supertitle":"","isSubheading":false},{"slug":"period-life-expectancy","text":"Period life expectancy","title":"Period life expectancy","supertitle":"","isSubheading":false},{"slug":"ages-at-death-death-rates-and-other-measures","text":"Ages at death, death rates, and other measures","title":"Ages at death, death rates, and other measures","supertitle":"","isSubheading":false}],"body":[{"type":"text","value":[{"text":"Several concepts in demography can be calculated either as a “cohort” or as a “period” measure. These terms are often used to describe life expectancy, but also apply to measures such as fertility rates or the age of death.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"How do these terms differ, and why does it matter?","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"In this article, I will explain the difference between period and cohort measures. I will also give some examples of what they are used for, and describe how they are calculated and interpreted.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"To do this, we’ll look at three different uses of period and cohort: data, effects and measures.","spanType":"span-simple-text"}],"parseErrors":[]},{"text":[{"text":"Period versus cohort data","spanType":"span-simple-text"}],"type":"heading","level":1,"parseErrors":[]},{"type":"text","value":[{"text":"Let’s start by looking at period and cohort ","spanType":"span-simple-text"},{"children":[{"text":"data","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":". These will help to develop an intuition about what the terms mean.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"children":[{"text":"Period data","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":" refers to data collected from groups of people at","spanType":"span-simple-text"},{"children":[{"text":" a given time","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":".","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"For example, data could be collected for the year 2019, across the population who live in the United Kingdom that year. If the data is collected again the next year, the people included in the data could be different, due to births and migrations.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"children":[{"text":"Cohort data","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":" refers to data on ","spanType":"span-simple-text"},{"children":[{"text":"the same group of people","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":" – a cohort – who have been tracked ","spanType":"span-simple-text"},{"children":[{"text":"over time","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":".","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"For example, data might be collected for people born in the United Kingdom in 2019, with more data collected from them as they grow older.","spanType":"span-simple-text"},{"url":"#note-1","children":[{"children":[{"text":"1","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"}],"parseErrors":[]},{"type":"text","value":[{"text":"You can see a comparison between them in the visualization below.","spanType":"span-simple-text"},{"url":"#note-2","children":[{"children":[{"text":"2","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"}],"parseErrors":[]},{"size":"narrow","type":"image","filename":"period-vs-cohort-visual.png","parseErrors":[]},{"type":"text","value":[{"text":"So, period data comes from a group of people at a particular time, while cohort data is collected from the same group of people across time.","spanType":"span-simple-text"}],"parseErrors":[]},{"text":[{"text":"Period versus cohort effects","spanType":"span-simple-text"}],"type":"heading","level":1,"parseErrors":[]},{"type":"text","value":[{"text":"Now let’s turn to period and cohort ","spanType":"span-simple-text"},{"children":[{"text":"effects","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":".","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"children":[{"text":"Period effects","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":" are caused by events that affect many people at a particular time.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"For example, the two World Wars and the ","spanType":"span-simple-text"},{"url":"https://ourworldindata.org/spanish-flu-largest-influenza-pandemic-in-history","children":[{"text":"Spanish flu pandemic in 1918","spanType":"span-simple-text"}],"spanType":"span-link"},{"text":" each caused a surge in death rates across the population at that particular time, especially among young and middle aged adults.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"You can see their effects in the chart of annual change in mortality rates in England and Wales below.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Period effects are shown as red vertical lines or streaks, which means they affected many age groups during those specific years.","spanType":"span-simple-text"}],"parseErrors":[]},{"size":"narrow","type":"image","caption":[{"text":"The annual change in death rates in each age group, compared to the previous year. Red represents a rise in mortality rates compared to the previous year, while blue represents a decline. Red is often followed by blue, as a sudden rise in death rates may be followed by a return to previous trends. This figure comes from a study by Phil Mike Jones et al. (2023).","spanType":"span-simple-text"},{"url":"#note-3","children":[{"children":[{"text":"3","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"}],"filename":"period-vs-cohort-lexis-plot-uk.png","parseErrors":[]},{"type":"text","value":[{"children":[{"text":"Cohort effects","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":" are different – they are generational effects that carry forward as people age. They come from experiences that people had at a particular time, which continued to affect them later on.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"You can see cohort effects in the chart above as well – they are the diagonal lines.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"For example, there is a clear red diagonal line that starts in 1918. The line shows us that people born during the 1918 Spanish flu pandemic had higher risks of death across their whole lifetimes than people born just before or after it.","spanType":"span-simple-text"},{"url":"#note-3","children":[{"children":[{"text":"3","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"}],"parseErrors":[]},{"text":[{"text":"Period versus cohort measures","spanType":"span-simple-text"}],"type":"heading","level":1,"parseErrors":[]},{"type":"text","value":[{"text":"Now we know what period and cohort ","spanType":"span-simple-text"},{"children":[{"text":"effects","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":" and ","spanType":"span-simple-text"},{"children":[{"text":"data","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":" mean.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"But what about the difference between period and cohort measures?","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"As an example, let’s look at life expectancy. This time, we’ll start with the ","spanType":"span-simple-text"},{"children":[{"text":"cohort","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":" measure of life expectancy, which is more straightforward.","spanType":"span-simple-text"}],"parseErrors":[]},{"text":[{"text":"Cohort life expectancy","spanType":"span-simple-text"}],"type":"heading","level":2,"parseErrors":[]},{"type":"text","value":[{"children":[{"text":"Cohort life expectancy","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":" is a measure of the average lifespan that people have had. It can be calculated for a birth cohort by tracking people born in a given year across their lives.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"This calculation is straightforward, but it requires data to be collected across a very long time frame.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"It means we need to wait for decades – until everyone in the birth cohort has died – so that we can calculate their average lifespan.","spanType":"span-simple-text"},{"url":"#note-4","children":[{"children":[{"text":"4","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"}],"parseErrors":[]},{"text":[{"text":"Period life expectancy","spanType":"span-simple-text"}],"type":"heading","level":2,"parseErrors":[]},{"type":"text","value":[{"text":"Another way to calculate life expectancy is with ","spanType":"span-simple-text"},{"children":[{"text":"period life expectancy","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":".","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"It is a metric that summarizes the death rates across the population ","spanType":"span-simple-text"},{"children":[{"text":"in a given year","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":".","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Rather than tracking a group of people over their lives, it involves creating a ‘synthetic cohort’ that we walk through the death rates that are seen in each age group within ","spanType":"span-simple-text"},{"children":[{"text":"one particular year","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":".","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"It assumes that death rates in each age group this year are equivalent to the death rate of this year’s newborns when they reach those same ages. For example, that the death rate among fifty year olds in a particular year is a good proxy for the death rate of newborns fifty years later.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"I’ll describe an example. Imagine there are 1,000 infants (under one year old)","spanType":"span-simple-text"},{"url":"#note-5","children":[{"children":[{"text":"5","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"},{"text":", and in a particular year, infants had a death rate of 5 per 1,000. This tells us that 995 of them would survive to the age of one.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Now, imagine these 995 have reached the age of one. Based on the death rate among one year olds ","spanType":"span-simple-text"},{"children":[{"text":"in the same year","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":", we can now estimate how many might survive to the age of two.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"We can then carry on this calculation for the entire hypothetical cohort of 1,000 infants. Along with this, we can keep track of how many years each of them survived.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Then, we can calculate the average number of years lived by the entire group of 1,000 hypothetical infants. This is equal to the period life expectancy at birth.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"This means period life expectancy is a summary measure of death rates in one particular year, rather than a prediction of how long people will actually live.","spanType":"span-simple-text"},{"url":"#note-6","children":[{"children":[{"text":"6","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"}],"parseErrors":[]},{"type":"text","value":[{"text":"This means that, for a given year, it represents the average lifespan for a hypothetical group of people, if they experienced the same age-specific death rates throughout their whole lives as the age-specific death rates seen in one particular year.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"In the chart below, you can see a comparison between period and cohort life expectancy.","spanType":"span-simple-text"}],"parseErrors":[]},{"url":"https://ourworldindata.org/grapher/period-versus-cohort-life-expectancy","tabs":["all"],"type":"chart","title":"Period versus cohort life expectancy in France","parseErrors":[]},{"type":"text","value":[{"text":"As you can see, cohort life expectancy (the actual average lifespan) is higher than period life expectancy. This is because period life expectancy is calculated by assuming people will experience the current year’s mortality rates at each age at the corresponding ages in their lifetime.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"But in reality, mortality rates declined throughout the 20th century, so people actually lived longer than what’s implied by period life expectancy.","spanType":"span-simple-text"},{"url":"#note-7","children":[{"children":[{"text":"7","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"}],"parseErrors":[]},{"type":"text","value":[{"text":"Another reason for the difference is that period life expectancy is partly a reflection of conditions ","spanType":"span-simple-text"},{"children":[{"text":"of the past","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":" that continue to affect older generations’ death rates today.","spanType":"span-simple-text"},{"url":"#note-8","children":[{"children":[{"text":"8","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"}],"parseErrors":[]},{"type":"text","value":[{"text":"You can also see that the trendline of cohort life expectancy ends decades ago. It can only be measured retrospectively, because researchers need to wait for data on deaths of the population who were born more recently.","spanType":"span-simple-text"}],"parseErrors":[]},{"text":[{"text":"Ages at death, death rates, and other measures","spanType":"span-simple-text"}],"type":"heading","level":2,"parseErrors":[]},{"type":"text","value":[{"text":"We can also calculate other metrics using either period or cohort measures.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"For example, we might be interested in the ","spanType":"span-simple-text"},{"children":[{"text":"modal age at death","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":", which is the most common age at which people die in a given year.","spanType":"span-simple-text"},{"url":"#note-9","children":[{"children":[{"text":"9","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"}],"parseErrors":[]},{"type":"text","value":[{"text":"The modal age at death can be measured as a period indicator – where it refers to the most common age at which people died in 2019, for example. Or as a cohort rate – where it refers to the most common age at which people died, among those born in the same year.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Many other measures can also be described with period or cohort data.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"This includes the ","spanType":"span-simple-text"},{"children":[{"text":"age-specific mortality profiles","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":", which are the death rates across age groups.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Age-specific mortality profiles can be calculated from a time period, for example, death rates in different age groups during a particular year.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Or they can be tracked for a cohort, where they refer to the death rates at different ages of a given birth cohort as they have grown older over time.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"In the chart, you can see a comparison between period and cohort age mortality profiles. The horizontal axis shows the age, and the vertical axis shows the share of people of that age who died that year.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"The data comes from France and covers the entire population.","spanType":"span-simple-text"},{"url":"#note-10","children":[{"children":[{"text":"10","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"}],"parseErrors":[]},{"size":"wide","type":"image","filename":"period-vs-cohort-age-mortality.png","parseErrors":[]},{"type":"text","value":[{"text":"As you can see, ","spanType":"span-simple-text"},{"children":[{"text":"period","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":" mortality profiles show death rates across age groups in a particular year. Death rates were elevated in 1918 and 1940, across youth and middle aged adults, due to the two World Wars and the 1918 Spanish flu pandemic.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"This period measure is useful because it tells us how different age groups were affected during a specific period in time.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"The ","spanType":"span-simple-text"},{"children":[{"text":"cohort","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":" mortality profile shows death rates for people born in different cohorts, at different ages of their lives. You can see elevated death in those born in 1910, 1918 and 1920, across their youth and middle-age, due to the two World Wars and the 1918 Spanish flu pandemic.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"This cohort measure is useful because it tells us how different generations experienced these events, and how mortality rates varied across their lifespans.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Period and cohort measures are also used for other topics, such as fertility rates, not only mortality data.","spanType":"span-simple-text"},{"url":"#note-11","children":[{"children":[{"text":"11","spanType":"span-simple-text"}],"spanType":"span-superscript"}],"spanType":"span-ref"}],"parseErrors":[]},{"text":[{"text":"What are period and cohort measures used for?","spanType":"span-simple-text"}],"type":"heading","level":1,"parseErrors":[]},{"type":"text","value":[{"text":"Period and cohort measures are used for different purposes.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"The most appropriate choice depends on what you’re interested in and what data is available.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"children":[{"text":"Period measures","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":" summarize data from a particular point in time. They can therefore be useful to understand the impact of immediate events, such as pandemics and wars. They can help answer the question: during these periods, which age groups were more likely to die?","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"children":[{"text":"Cohort measures","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":" track changes as people grow older. They can be used to understand death rates among a birth cohort as the group grows older.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"They can also help to understand the historical experience that people have had. For cohorts born during the 1918 Spanish flu pandemic, for example, they can help us understand how it impacted their long-term survival.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Of course, cohort data is only available in retrospect and we need to wait many decades before full data becomes available. It is also more difficult to collect data across many years, decades, or even over a century and therefore is only available for relatively few populations.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"In the visualization below, you can see a summary of the main points in this article.","spanType":"span-simple-text"}],"parseErrors":[]},{"size":"narrow","type":"image","filename":"period-vs-cohort-explanation.png","parseErrors":[]},{"text":[{"type":"text","value":[{"text":"Ilya Kashnitsky, Edouard Mathieu, Max Roser, and Fiona Spooner provided valuable feedback on this article.","spanType":"span-simple-text"}],"parseErrors":[]}],"type":"callout","title":"Acknowledgements","parseErrors":[]}],"refs":{"errors":[],"definitions":{"1720d18fa342c20fd81450476e6a49979e89802f":{"id":"1720d18fa342c20fd81450476e6a49979e89802f","index":1,"content":[{"type":"text","value":[{"text":"This visualization was inspired by a diagram in the Office for Budget Responsibility’s report.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Office for Budget Responsibility. (2018, July). Period and cohort measures of fertility and mortality. ","spanType":"span-simple-text"},{"url":"https://obr.uk/box/period-cohort-measures-of-fertility-and-mortality/","children":[{"text":"https://obr.uk/box/period-cohort-measures-of-fertility-and-mortality/","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]},{"type":"text","value":[{"text":"See also:","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Wilson, C., Sobotka, T., Williamson, L., & Boyle, P. (2013). Migration and Intergenerational Replacement in Europe. Population and Development Review, 39(1), 131–157. ","spanType":"span-simple-text"},{"url":"https://doi.org/10.1111/j.1728-4457.2013.00576.x","children":[{"text":"https://doi.org/10.1111/j.1728-4457.2013.00576.x","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]}],"parseErrors":[]},"17b4c013ef49ea89a03b092d68b93253a639077d":{"id":"17b4c013ef49ea89a03b092d68b93253a639077d","index":3,"content":[{"type":"text","value":[{"text":"In the Human Mortality Database, researchers have a threshold to wait until 99% of the relevant exposure data from a given cohort is available until making cohort estimates.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"See section 7.2.2 in the Human Mortality Database full protocol v6.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Wilmoth, J. R., Andreev, K., Jdanov, D., Glei, D. A., Riffe, T., Boe, C., Bubenheim, M., Philipov, D., Shkolnikov, V., Vachon, P., Winant, C., & Barbieri, M. (2021). Methods protocol for the human mortality database (v6). ","spanType":"span-simple-text"},{"url":"https://www.mortality.org/File/GetDocument/Public/Docs/MethodsProtocolV6.pdf","children":[{"text":"https://www.mortality.org/File/GetDocument/Public/Docs/MethodsProtocolV6.pdf","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]}],"parseErrors":[]},"3628c6f46204f4643e358e1d0c65a57ac5e1f539":{"id":"3628c6f46204f4643e358e1d0c65a57ac5e1f539","index":6,"content":[{"type":"text","value":[{"text":"Canudas-Romo, V., & Schoen, R. (2005). Age-specific contributions to changes in the period and cohort life expectancy. Demographic Research, 13, 63–82. ","spanType":"span-simple-text"},{"url":"https://doi.org/10.4054/DemRes.2005.13.3","children":[{"text":"https://doi.org/10.4054/DemRes.2005.13.3","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]},{"type":"text","value":[{"text":"Vaupel, J. W. (2002). Life expectancy at current rates vs. Current conditions: A reflexion stimulated by Bongaarts and Feeney’s “How long do we live?” Demographic Research, 7, 365–378. ","spanType":"span-simple-text"},{"url":"https://doi.org/10.4054/DemRes.2002.7.8","children":[{"text":"https://doi.org/10.4054/DemRes.2002.7.8","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]},{"type":"text","value":[{"text":"Oeppen, J., & Vaupel, J. W. (2002). Broken Limits to Life Expectancy. Science, 296(5570), 1029–1031. ","spanType":"span-simple-text"},{"url":"https://doi.org/10.1126/science.1069675","children":[{"text":"https://doi.org/10.1126/science.1069675","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]}],"parseErrors":[]},"493ca88c7cd30c294632201c3fd10f4fdb5c2b8e":{"id":"493ca88c7cd30c294632201c3fd10f4fdb5c2b8e","index":0,"content":[{"type":"text","value":[{"text":"We usually talk about birth cohorts – people born in the same year – but the term can be used for many kinds of groups: immigration cohorts, marriage cohorts, stroke survivors, university alumni, and so on. In this article, we’ll focus on birth cohorts.","spanType":"span-simple-text"}],"parseErrors":[]}],"parseErrors":[]},"53fabe58cf039199feffee485eb79eb2efbbd307":{"id":"53fabe58cf039199feffee485eb79eb2efbbd307","index":5,"content":[{"type":"text","value":[{"text":"Guillot, M. (2011). Period Versus Cohort Life Expectancy. In R. G. Rogers & E. M. Crimmins (Eds.), International Handbook of Adult Mortality (Vol. 2, pp. 533–549). Springer Netherlands. ","spanType":"span-simple-text"},{"url":"https://doi.org/10.1007/978-90-481-9996-9_25","children":[{"text":"https://doi.org/10.1007/978-90-481-9996-9_25","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]}],"parseErrors":[]},"8e8480be906a5d9464ab2ff2623f89ae61151b25":{"id":"8e8480be906a5d9464ab2ff2623f89ae61151b25","index":10,"content":[{"type":"text","value":[{"text":"For example, researchers can measure the ","spanType":"span-simple-text"},{"children":[{"text":"total fertility rate","spanType":"span-simple-text"}],"spanType":"span-bold"},{"text":" (TFR) as a period measure. It represents the average fertility for a hypothetical group of women in a given year, if they experienced the same age-specific fertility rates throughout their whole lives as the age-specific fertility rates seen in that particular year.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"But TFR can also be measured as a cohort measure – where it represents the average number of children born to women in that cohort by the end of their reproductive lives.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"This distinction is important because period TFR can be influenced by the timing of childbearing and can therefore fluctuate due to trends such as women choosing to have children later in life.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"Bongaarts, J., & Feeney, G. (1998). On the Quantum and Tempo of Fertility. Population and Development Review, 24(2), 271. ","spanType":"span-simple-text"},{"url":"https://doi.org/10.2307/2807974","children":[{"text":"https://doi.org/10.2307/2807974","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]},{"type":"text","value":[{"text":"In addition, demographers can also calculate hybrid measures from both period and cohort.","spanType":"span-simple-text"}],"parseErrors":[]},{"type":"text","value":[{"text":"See for an example: Wilson, C., Sobotka, T., Williamson, L., & Boyle, P. (2013). Migration and Intergenerational Replacement in Europe. Population and Development Review, 39(1), 131–157. ","spanType":"span-simple-text"},{"url":"https://doi.org/10.1111/j.1728-4457.2013.00576.x","children":[{"text":"https://doi.org/10.1111/j.1728-4457.2013.00576.x","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]}],"parseErrors":[]},"913e03025c978846be1c255bc68bec4068b89343":{"id":"913e03025c978846be1c255bc68bec4068b89343","index":2,"content":[{"type":"text","value":[{"text":"Jones, P. M., Minton, J., & Bell, A. (2023). Methods for disentangling period and cohort changes in mortality risk over the twentieth century: Comparing graphical and modelling approaches. Quality & Quantity, 57(4), 3219–3239. ","spanType":"span-simple-text"},{"url":"https://doi.org/10.1007/s11135-022-01498-3","children":[{"text":"https://doi.org/10.1007/s11135-022-01498-3","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]}],"parseErrors":[]},"944c853b7ceb0a1039727afbab5c500b5fdad4ba":{"id":"944c853b7ceb0a1039727afbab5c500b5fdad4ba","index":7,"content":[{"type":"text","value":[{"text":"Vaupel, J. W. (2002). Life expectancy at current rates vs. Current conditions: A reflexion stimulated by Bongaarts and Feeney’s “How long do we live?” Demographic Research, 7, 365–378. ","spanType":"span-simple-text"},{"url":"https://www.demographic-research.org/volumes/vol7/8/7-8.pdf","children":[{"text":"https://www.demographic-research.org/volumes/vol7/8/7-8.pdf","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]},{"type":"text","value":[{"text":"Missov, T. I., Lenart, A., Nemeth, L., Canudas-Romo, V., & Vaupel, J. W. (2015). The Gompertz force of mortality in terms of the modal age at death. Demographic Research, 32, 1031–1048. ","spanType":"span-simple-text"},{"url":"https://doi.org/10.4054/DemRes.2015.32.36","children":[{"text":"https://doi.org/10.4054/DemRes.2015.32.36","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]}],"parseErrors":[]},"ae2a54df83436cd27489a05cf31eb0945af1564e":{"id":"ae2a54df83436cd27489a05cf31eb0945af1564e","index":8,"content":[{"type":"text","value":[{"text":"Horiuchi, S., Ouellette, N., Cheung, S. L. K., & Robine, J.-M. (2013). Modal age at death: Lifespan indicator in the era of longevity extension. ","spanType":"span-simple-text"},{"children":[{"text":"Vienna Yearbook of Population Research","spanType":"span-simple-text"}],"spanType":"span-italic"},{"text":", 37–69. ","spanType":"span-simple-text"},{"url":"https://www.jstor.org/stable/43050796","children":[{"text":"https://www.jstor.org/stable/43050796","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]},{"type":"text","value":[{"text":"Missov, T. I., Lenart, A., Nemeth, L., Canudas-Romo, V., & Vaupel, J. W. (2015). The Gompertz force of mortality in terms of the modal age at death. Demographic Research, 32, 1031–1048. ","spanType":"span-simple-text"},{"url":"https://doi.org/10.4054/DemRes.2015.32.36","children":[{"text":"https://doi.org/10.4054/DemRes.2015.32.36","spanType":"span-simple-text"}],"spanType":"span-link"}],"parseErrors":[]}],"parseErrors":[]},"b90e972bc0a76433138b469a8da24af712803012":{"id":"b90e972bc0a76433138b469a8da24af712803012","index":4,"content":[{"type":"text","value":[{"text":"In demography, it’s common to describe population sizes in 100,000 people instead. However, I’ve used 1,000 in this hypothetical example to make the numbers more digestible.","spanType":"span-simple-text"}],"parseErrors":[]}],"parseErrors":[]},"d8a70cff578f8e5a3b5827ebf38a44aa6623ea14":{"id":"d8a70cff578f8e5a3b5827ebf38a44aa6623ea14","index":9,"content":[{"type":"text","value":[{"text":"To recreate this chart, or create it for other countries, the ","spanType":"span-simple-text"},{"url":"https://github.com/owid/notebooks/tree/main/SaloniDattani/Life-expectancy/Period-vs-cohort-age-mortality","children":[{"text":"scripts","spanType":"span-simple-text"}],"spanType":"span-link"},{"text":" are available online.","spanType":"span-simple-text"}],"parseErrors":[]}],"parseErrors":[]}}},"type":"article","title":"Period versus cohort measures: what’s the difference?","authors":["Saloni Dattani"],"excerpt":"What do the terms “period” and “cohort” mean in statistics? How do they differ, and why does it matter?","dateline":"November 27, 2023","subtitle":"What do the terms “period” and “cohort” mean in statistics? How do they differ, and why does it matter?","featured-image":"period-vs-cohort-thumbnail.png"},"id":"1adfde5rHHzV0zAzAKjM_J8ejdRJYte2996aRC-r4u8A"}</script><script> function setJSEnabled(enabled) { var elem = window.document.documentElement; if (enabled) { elem.classList.remove("js-disabled"); elem.classList.add("js-enabled"); } else { elem.classList.remove("js-enabled"); elem.classList.add("js-disabled"); } } if ("noModule" in HTMLScriptElement.prototype) { setJSEnabled(true); } else { setJSEnabled(false); } window.onerror = function (err, url) { var isOurSyntaxError = typeof err === "string" && err.indexOf("SyntaxError") > -1 && url.indexOf("https://ourworldindata.org") > -1; if (isOurSyntaxError) { console.error("Caught global syntax error", err, url); setJSEnabled(false); } }</script><script>/* Prepare Google Tag Manager */ window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} 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href="/">Home</a><span class="separator"><svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="angle-right" class="svg-inline--fa fa-angle-right " role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 320 512"><path fill="currentColor" d="M278.6 233.4c12.5 12.5 12.5 32.8 0 45.3l-160 160c-12.5 12.5-32.8 12.5-45.3 0s-12.5-32.8 0-45.3L210.7 256 73.4 118.6c-12.5-12.5-12.5-32.8 0-45.3s32.8-12.5 45.3 0l160 160z"></path></svg></span><a href="https://ourworldindata.org/life-expectancy" data-track-note="breadcrumb">Life Expectancy</a></div></div><header class="centered-article-header align-center grid grid-cols-8 span-cols-8 col-start-4 grid-md-cols-6 span-md-cols-12 col-md-start-2"><div class="centered-article-header__title-container col-start-2 span-cols-6 span-md-cols-6 col-md-start-1"><h1 class="centered-article-header__title">Period versus cohort measures: what’s the difference?</h1></div><h2 class="centered-article-header__subtitle col-start-2 span-cols-6 span-md-cols-6 col-md-start-1">What do the terms “period” and “cohort” mean in statistics? How do they differ, and why does it matter?</h2><div class="centered-article-header__meta-container col-start-2 span-cols-6 span-md-cols-6 col-md-start-1 grid grid-cols-2 "><div class="span-cols-1 span-sm-cols-2"><div class="centered-article-header__byline">By: <a href="/team/saloni-dattani">Saloni Dattani</a></div><div class="centered-article-header__dateline body-3-medium-italic">November 27, 2023</div></div><div class="centered-article-header__links span-cols-1 span-sm-cols-2"><a href="#article-citation" class="body-1-regular display-block"><svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="book" class="svg-inline--fa fa-book " role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><path fill="currentColor" d="M96 0C43 0 0 43 0 96L0 416c0 53 43 96 96 96l288 0 32 0c17.7 0 32-14.3 32-32s-14.3-32-32-32l0-64c17.7 0 32-14.3 32-32l0-320c0-17.7-14.3-32-32-32L384 0 96 0zm0 384l256 0 0 64L96 448c-17.7 0-32-14.3-32-32s14.3-32 32-32zm32-240c0-8.8 7.2-16 16-16l192 0c8.8 0 16 7.2 16 16s-7.2 16-16 16l-192 0c-8.8 0-16-7.2-16-16zm16 48l192 0c8.8 0 16 7.2 16 16s-7.2 16-16 16l-192 0c-8.8 0-16-7.2-16-16s7.2-16 16-16z"></path></svg>Cite this article</a><a href="#article-licence" class="body-3-medium display-block"><svg aria-hidden="true" focusable="false" data-prefix="fab" data-icon="creative-commons" class="svg-inline--fa fa-creative-commons " role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><path fill="currentColor" d="M245.83 214.87l-33.22 17.28c-9.43-19.58-25.24-19.93-27.46-19.93-22.13 0-33.22 14.61-33.22 43.84 0 23.57 9.21 43.84 33.22 43.84 14.47 0 24.65-7.09 30.57-21.26l30.55 15.5c-6.17 11.51-25.69 38.98-65.1 38.98-22.6 0-73.96-10.32-73.96-77.05 0-58.69 43-77.06 72.63-77.06 30.72-.01 52.7 11.95 65.99 35.86zm143.05 0l-32.78 17.28c-9.5-19.77-25.72-19.93-27.9-19.93-22.14 0-33.22 14.61-33.22 43.84 0 23.55 9.23 43.84 33.22 43.84 14.45 0 24.65-7.09 30.54-21.26l31 15.5c-2.1 3.75-21.39 38.98-65.09 38.98-22.69 0-73.96-9.87-73.96-77.05 0-58.67 42.97-77.06 72.63-77.06 30.71-.01 52.58 11.95 65.56 35.86zM247.56 8.05C104.74 8.05 0 123.11 0 256.05c0 138.49 113.6 248 247.56 248 129.93 0 248.44-100.87 248.44-248 0-137.87-106.62-248-248.44-248zm.87 450.81c-112.54 0-203.7-93.04-203.7-202.81 0-105.42 85.43-203.27 203.72-203.27 112.53 0 202.82 89.46 202.82 203.26-.01 121.69-99.68 202.82-202.84 202.82z"></path></svg>Reuse our work freely</a></div></div></header><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Several concepts in demography can be calculated either as a “cohort” or as a “period” measure. These terms are often used to describe life expectancy, but also apply to measures such as fertility rates or the age of death.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>How do these terms differ, and why does it matter?</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>In this article, I will explain the difference between period and cohort measures. I will also give some examples of what they are used for, and describe how they are calculated and interpreted.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>To do this, we’ll look at three different uses of period and cohort: data, effects and measures.</span></p><h1 class="h1-semibold article-block__heading col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2" id="period-versus-cohort-data"><span>Period versus cohort data</span><a class="deep-link" href="#period-versus-cohort-data"></a></h1><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Let’s start by looking at period and cohort </span><em><span>data</span></em><span>. These will help to develop an intuition about what the terms mean.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><strong><span>Period data</span></strong><span> refers to data collected from groups of people at</span><em><span> a given time</span></em><span>.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>For example, data could be collected for the year 2019, across the population who live in the United Kingdom that year. If the data is collected again the next year, the people included in the data could be different, due to births and migrations.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><strong><span>Cohort data</span></strong><span> refers to data on </span><em><span>the same group of people</span></em><span> – a cohort – who have been tracked </span><em><span>over time</span></em><span>.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>For example, data might be collected for people born in the United Kingdom in 2019, with more data collected from them as they grow older.</span><a href="#note-1" class="ref"><sup><span>1</span></sup></a></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>You can see a comparison between them in the visualization below.</span><a href="#note-2" class="ref"><sup><span>2</span></sup></a></p><figure class="article-block__image article-block__image--narrow col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 col-sm-start-2 span-sm-cols-12"><div class="image"><picture><source srcSet="https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/16bf47e1-8fc7-4370-1735-3055de515900/w=48 48w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/16bf47e1-8fc7-4370-1735-3055de515900/w=100 100w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/16bf47e1-8fc7-4370-1735-3055de515900/w=350 350w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/16bf47e1-8fc7-4370-1735-3055de515900/w=850 850w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/16bf47e1-8fc7-4370-1735-3055de515900/w=1350 1350w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/16bf47e1-8fc7-4370-1735-3055de515900/w=10422 10422w" type="image/png" sizes="(max-width: 960px) 95vw, (min-width: 960px) 853px"/><img src="https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/16bf47e1-8fc7-4370-1735-3055de515900/w=10422" alt="A brief visual explanation of the difference between period and cohort measures." class="lightbox-image" loading="lazy" data-filename="period-vs-cohort-visual.png" width="10422" height="4712"/></picture><div class="article-block__image-download-button-container"><button aria-label="Download period-vs-cohort-visual.png" class="article-block__image-download-button"><div class="article-block__image-download-button-background-layer"><svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="download" class="svg-inline--fa fa-download article-block__image-download-button-icon" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M288 32c0-17.7-14.3-32-32-32s-32 14.3-32 32l0 242.7-73.4-73.4c-12.5-12.5-32.8-12.5-45.3 0s-12.5 32.8 0 45.3l128 128c12.5 12.5 32.8 12.5 45.3 0l128-128c12.5-12.5 12.5-32.8 0-45.3s-32.8-12.5-45.3 0L288 274.7 288 32zM64 352c-35.3 0-64 28.7-64 64l0 32c0 35.3 28.7 64 64 64l384 0c35.3 0 64-28.7 64-64l0-32c0-35.3-28.7-64-64-64l-101.5 0-45.3 45.3c-25 25-65.5 25-90.5 0L165.5 352 64 352zm368 56a24 24 0 1 1 0 48 24 24 0 1 1 0-48z"></path></svg><span class="article-block__image-download-button-text">Download image</span></div></button></div></div></figure><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>So, period data comes from a group of people at a particular time, while cohort data is collected from the same group of people across time.</span></p><h1 class="h1-semibold article-block__heading col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2" id="period-versus-cohort-effects"><span>Period versus cohort effects</span><a class="deep-link" href="#period-versus-cohort-effects"></a></h1><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Now let’s turn to period and cohort </span><em><span>effects</span></em><span>.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><strong><span>Period effects</span></strong><span> are caused by events that affect many people at a particular time.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>For example, the two World Wars and the </span><a href="https://ourworldindata.org/spanish-flu-largest-influenza-pandemic-in-history" class="span-link" target="_blank" rel="noopener"><span>Spanish flu pandemic in 1918</span></a><span> each caused a surge in death rates across the population at that particular time, especially among young and middle aged adults.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>You can see their effects in the chart of annual change in mortality rates in England and Wales below.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Period effects are shown as red vertical lines or streaks, which means they affected many age groups during those specific years.</span></p><figure class="article-block__image article-block__image--narrow col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 col-sm-start-2 span-sm-cols-12"><div class="image"><picture><source srcSet="https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/2a5670da-015d-48f3-f50a-71315420c900/w=48 48w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/2a5670da-015d-48f3-f50a-71315420c900/w=100 100w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/2a5670da-015d-48f3-f50a-71315420c900/w=350 350w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/2a5670da-015d-48f3-f50a-71315420c900/w=850 850w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/2a5670da-015d-48f3-f50a-71315420c900/w=1350 1350w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/2a5670da-015d-48f3-f50a-71315420c900/w=1424 1424w" type="image/png" sizes="(max-width: 960px) 95vw, (min-width: 960px) 853px"/><img src="https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/2a5670da-015d-48f3-f50a-71315420c900/w=1424" alt="A figure from the paper by Phil Mike Jones et al. (2023) Methods for disentangling period and cohort changes in mortality risk over the twentieth century: Comparing graphical and modelling approaches. It shows the annual change in mortality rates on a Lexis plot, using national mortality data from England and Wales across the 20th century." class="lightbox-image" loading="lazy" data-filename="period-vs-cohort-lexis-plot-uk.png" width="1424" height="694"/></picture><div class="article-block__image-download-button-container"><button aria-label="Download period-vs-cohort-lexis-plot-uk.png" class="article-block__image-download-button"><div class="article-block__image-download-button-background-layer"><svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="download" class="svg-inline--fa fa-download article-block__image-download-button-icon" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M288 32c0-17.7-14.3-32-32-32s-32 14.3-32 32l0 242.7-73.4-73.4c-12.5-12.5-32.8-12.5-45.3 0s-12.5 32.8 0 45.3l128 128c12.5 12.5 32.8 12.5 45.3 0l128-128c12.5-12.5 12.5-32.8 0-45.3s-32.8-12.5-45.3 0L288 274.7 288 32zM64 352c-35.3 0-64 28.7-64 64l0 32c0 35.3 28.7 64 64 64l384 0c35.3 0 64-28.7 64-64l0-32c0-35.3-28.7-64-64-64l-101.5 0-45.3 45.3c-25 25-65.5 25-90.5 0L165.5 352 64 352zm368 56a24 24 0 1 1 0 48 24 24 0 1 1 0-48z"></path></svg><span class="article-block__image-download-button-text">Download image</span></div></button></div></div><figcaption class="article-block__image-caption col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>The annual change in death rates in each age group, compared to the previous year. Red represents a rise in mortality rates compared to the previous year, while blue represents a decline. Red is often followed by blue, as a sudden rise in death rates may be followed by a return to previous trends. This figure comes from a study by Phil Mike Jones et al. (2023).</span><a href="#note-3" class="ref"><sup><span>3</span></sup></a></figcaption></figure><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><strong><span>Cohort effects</span></strong><span> are different – they are generational effects that carry forward as people age. They come from experiences that people had at a particular time, which continued to affect them later on.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>You can see cohort effects in the chart above as well – they are the diagonal lines.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>For example, there is a clear red diagonal line that starts in 1918. The line shows us that people born during the 1918 Spanish flu pandemic had higher risks of death across their whole lifetimes than people born just before or after it.</span><a href="#note-3" class="ref"><sup><span>3</span></sup></a></p><h1 class="h1-semibold article-block__heading col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2" id="period-versus-cohort-measures"><span>Period versus cohort measures</span><a class="deep-link" href="#period-versus-cohort-measures"></a></h1><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Now we know what period and cohort </span><em><span>effects</span></em><span> and </span><em><span>data</span></em><span> mean.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>But what about the difference between period and cohort measures?</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>As an example, let’s look at life expectancy. This time, we’ll start with the </span><strong><span>cohort</span></strong><span> measure of life expectancy, which is more straightforward.</span></p><h2 class="h2-bold article-block__heading col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2" id="cohort-life-expectancy"><span>Cohort life expectancy</span><a class="deep-link" href="#cohort-life-expectancy"></a></h2><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><strong><span>Cohort life expectancy</span></strong><span> is a measure of the average lifespan that people have had. It can be calculated for a birth cohort by tracking people born in a given year across their lives.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>This calculation is straightforward, but it requires data to be collected across a very long time frame.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>It means we need to wait for decades – until everyone in the birth cohort has died – so that we can calculate their average lifespan.</span><a href="#note-4" class="ref"><sup><span>4</span></sup></a></p><h2 class="h2-bold article-block__heading col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2" id="period-life-expectancy"><span>Period life expectancy</span><a class="deep-link" href="#period-life-expectancy"></a></h2><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Another way to calculate life expectancy is with </span><strong><span>period life expectancy</span></strong><span>.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>It is a metric that summarizes the death rates across the population </span><em><span>in a given year</span></em><span>.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Rather than tracking a group of people over their lives, it involves creating a ‘synthetic cohort’ that we walk through the death rates that are seen in each age group within </span><em><span>one particular year</span></em><span>.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>It assumes that death rates in each age group this year are equivalent to the death rate of this year’s newborns when they reach those same ages. For example, that the death rate among fifty year olds in a particular year is a good proxy for the death rate of newborns fifty years later.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>I’ll describe an example. Imagine there are 1,000 infants (under one year old)</span><a href="#note-5" class="ref"><sup><span>5</span></sup></a><span>, and in a particular year, infants had a death rate of 5 per 1,000. This tells us that 995 of them would survive to the age of one.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Now, imagine these 995 have reached the age of one. Based on the death rate among one year olds </span><em><span>in the same year</span></em><span>, we can now estimate how many might survive to the age of two.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>We can then carry on this calculation for the entire hypothetical cohort of 1,000 infants. Along with this, we can keep track of how many years each of them survived.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Then, we can calculate the average number of years lived by the entire group of 1,000 hypothetical infants. This is equal to the period life expectancy at birth.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>This means period life expectancy is a summary measure of death rates in one particular year, rather than a prediction of how long people will actually live.</span><a href="#note-6" class="ref"><sup><span>6</span></sup></a></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>This means that, for a given year, it represents the average lifespan for a hypothetical group of people, if they experienced the same age-specific death rates throughout their whole lives as the age-specific death rates seen in one particular year.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>In the chart below, you can see a comparison between period and cohort life expectancy.</span></p><div class="article-block__chart col-start-4 span-cols-8 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2 full-width-on-mobile"><figure class="grapherPreview chart" data-grapher-src="https://ourworldindata.org/grapher/period-versus-cohort-life-expectancy" data-grapher-config="{"hideRelativeToggle":true,"hideTimeline":true,"hideFacetControl":true,"hideEntityControls":true,"hideZoomToggle":true,"hideNoDataAreaToggle":true,"hideFacetYDomainToggle":true,"hideXScaleToggle":true,"hideYScaleToggle":true,"hideMapProjectionMenu":true,"hideTableFilterToggle":true,"map":{"hideTimeline":true},"hideRelatedQuestion":true,"hideShareButton":true,"hideExploreTheDataButton":false,"title":"Period versus cohort life expectancy in France","forceHideAnnotationFieldsInTitle":{"entity":true,"time":true,"changeInPrefix":true}}" style="width:100%;border:0px none"><a href="https://ourworldindata.org/grapher/period-versus-cohort-life-expectancy" target="_blank" rel="noopener"><picture><source id="grapher-preview-source" srcSet="https://ourworldindata.org/grapher/period-versus-cohort-life-expectancy.png?imWidth=850 850w, https://ourworldindata.org/grapher/period-versus-cohort-life-expectancy.png?imWidth=1700 1700w" sizes="(max-width: 850px) 100vw, 850px"/><img class="GrapherImage" src="https://ourworldindata.org/grapher/period-versus-cohort-life-expectancy.png" alt="Period versus cohort life expectancy in France" width="850" height="600" loading="lazy" data-no-lightbox="true"/></picture></a></figure></div><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>As you can see, cohort life expectancy (the actual average lifespan) is higher than period life expectancy. This is because period life expectancy is calculated by assuming people will experience the current year’s mortality rates at each age at the corresponding ages in their lifetime.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>But in reality, mortality rates declined throughout the 20th century, so people actually lived longer than what’s implied by period life expectancy.</span><a href="#note-7" class="ref"><sup><span>7</span></sup></a></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Another reason for the difference is that period life expectancy is partly a reflection of conditions </span><em><span>of the past</span></em><span> that continue to affect older generations’ death rates today.</span><a href="#note-8" class="ref"><sup><span>8</span></sup></a></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>You can also see that the trendline of cohort life expectancy ends decades ago. It can only be measured retrospectively, because researchers need to wait for data on deaths of the population who were born more recently.</span></p><h2 class="h2-bold article-block__heading col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2" id="ages-at-death-death-rates-and-other-measures"><span>Ages at death, death rates, and other measures</span><a class="deep-link" href="#ages-at-death-death-rates-and-other-measures"></a></h2><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>We can also calculate other metrics using either period or cohort measures.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>For example, we might be interested in the </span><strong><span>modal age at death</span></strong><span>, which is the most common age at which people die in a given year.</span><a href="#note-9" class="ref"><sup><span>9</span></sup></a></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>The modal age at death can be measured as a period indicator – where it refers to the most common age at which people died in 2019, for example. Or as a cohort rate – where it refers to the most common age at which people died, among those born in the same year.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Many other measures can also be described with period or cohort data.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>This includes the </span><strong><span>age-specific mortality profiles</span></strong><span>, which are the death rates across age groups.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Age-specific mortality profiles can be calculated from a time period, for example, death rates in different age groups during a particular year.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Or they can be tracked for a cohort, where they refer to the death rates at different ages of a given birth cohort as they have grown older over time.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>In the chart, you can see a comparison between period and cohort age mortality profiles. The horizontal axis shows the age, and the vertical axis shows the share of people of that age who died that year.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>The data comes from France and covers the entire population.</span><a href="#note-10" class="ref"><sup><span>10</span></sup></a></p><figure class="article-block__image article-block__image--wide col-start-4 span-cols-8 col-md-start-2 span-md-cols-12"><div class="image"><picture><source srcSet="https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/3ea05ad4-8746-424b-b6e1-e95951212e00/w=48 48w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/3ea05ad4-8746-424b-b6e1-e95951212e00/w=100 100w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/3ea05ad4-8746-424b-b6e1-e95951212e00/w=350 350w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/3ea05ad4-8746-424b-b6e1-e95951212e00/w=850 850w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/3ea05ad4-8746-424b-b6e1-e95951212e00/w=1350 1350w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/3ea05ad4-8746-424b-b6e1-e95951212e00/w=10905 10905w" type="image/png" sizes="(max-width: 960px) 95vw, (min-width: 960px) 853px"/><img src="https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/3ea05ad4-8746-424b-b6e1-e95951212e00/w=10905" alt="A comparison between period and cohort age-specific mortality rates, using national mortality data from France." class="lightbox-image" loading="lazy" data-filename="period-vs-cohort-age-mortality.png" width="10905" height="7135"/></picture><div class="article-block__image-download-button-container"><button aria-label="Download period-vs-cohort-age-mortality.png" class="article-block__image-download-button"><div class="article-block__image-download-button-background-layer"><svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="download" class="svg-inline--fa fa-download article-block__image-download-button-icon" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M288 32c0-17.7-14.3-32-32-32s-32 14.3-32 32l0 242.7-73.4-73.4c-12.5-12.5-32.8-12.5-45.3 0s-12.5 32.8 0 45.3l128 128c12.5 12.5 32.8 12.5 45.3 0l128-128c12.5-12.5 12.5-32.8 0-45.3s-32.8-12.5-45.3 0L288 274.7 288 32zM64 352c-35.3 0-64 28.7-64 64l0 32c0 35.3 28.7 64 64 64l384 0c35.3 0 64-28.7 64-64l0-32c0-35.3-28.7-64-64-64l-101.5 0-45.3 45.3c-25 25-65.5 25-90.5 0L165.5 352 64 352zm368 56a24 24 0 1 1 0 48 24 24 0 1 1 0-48z"></path></svg><span class="article-block__image-download-button-text">Download image</span></div></button></div></div></figure><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>As you can see, </span><em><span>period</span></em><span> mortality profiles show death rates across age groups in a particular year. Death rates were elevated in 1918 and 1940, across youth and middle aged adults, due to the two World Wars and the 1918 Spanish flu pandemic.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>This period measure is useful because it tells us how different age groups were affected during a specific period in time.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>The </span><em><span>cohort</span></em><span> mortality profile shows death rates for people born in different cohorts, at different ages of their lives. You can see elevated death in those born in 1910, 1918 and 1920, across their youth and middle-age, due to the two World Wars and the 1918 Spanish flu pandemic.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>This cohort measure is useful because it tells us how different generations experienced these events, and how mortality rates varied across their lifespans.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Period and cohort measures are also used for other topics, such as fertility rates, not only mortality data.</span><a href="#note-11" class="ref"><sup><span>11</span></sup></a></p><h1 class="h1-semibold article-block__heading col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2" id="what-are-period-and-cohort-measures-used-for"><span>What are period and cohort measures used for?</span><a class="deep-link" href="#what-are-period-and-cohort-measures-used-for"></a></h1><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Period and cohort measures are used for different purposes.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>The most appropriate choice depends on what you’re interested in and what data is available.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><strong><span>Period measures</span></strong><span> summarize data from a particular point in time. They can therefore be useful to understand the impact of immediate events, such as pandemics and wars. They can help answer the question: during these periods, which age groups were more likely to die?</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><strong><span>Cohort measures</span></strong><span> track changes as people grow older. They can be used to understand death rates among a birth cohort as the group grows older.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>They can also help to understand the historical experience that people have had. For cohorts born during the 1918 Spanish flu pandemic, for example, they can help us understand how it impacted their long-term survival.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Of course, cohort data is only available in retrospect and we need to wait many decades before full data becomes available. It is also more difficult to collect data across many years, decades, or even over a century and therefore is only available for relatively few populations.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>In the visualization below, you can see a summary of the main points in this article.</span></p><figure class="article-block__image article-block__image--narrow col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 col-sm-start-2 span-sm-cols-12"><div class="image"><picture><source srcSet="https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/cea9e4f1-220c-4892-651c-a528b5f16500/w=48 48w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/cea9e4f1-220c-4892-651c-a528b5f16500/w=100 100w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/cea9e4f1-220c-4892-651c-a528b5f16500/w=350 350w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/cea9e4f1-220c-4892-651c-a528b5f16500/w=850 850w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/cea9e4f1-220c-4892-651c-a528b5f16500/w=1350 1350w, https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/cea9e4f1-220c-4892-651c-a528b5f16500/w=10768 10768w" type="image/png" sizes="(max-width: 960px) 95vw, (min-width: 960px) 853px"/><img src="https://ourworldindata.org/cdn-cgi/imagedelivery/qLq-8BTgXU8yG0N6HnOy8g/cea9e4f1-220c-4892-651c-a528b5f16500/w=10768" alt="A visual explanation of the difference between period and cohort measures, with a few examples." class="lightbox-image" loading="lazy" data-filename="period-vs-cohort-explanation.png" width="10768" height="11965"/></picture><div class="article-block__image-download-button-container"><button aria-label="Download period-vs-cohort-explanation.png" class="article-block__image-download-button"><div class="article-block__image-download-button-background-layer"><svg aria-hidden="true" focusable="false" data-prefix="fas" data-icon="download" class="svg-inline--fa fa-download article-block__image-download-button-icon" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M288 32c0-17.7-14.3-32-32-32s-32 14.3-32 32l0 242.7-73.4-73.4c-12.5-12.5-32.8-12.5-45.3 0s-12.5 32.8 0 45.3l128 128c12.5 12.5 32.8 12.5 45.3 0l128-128c12.5-12.5 12.5-32.8 0-45.3s-32.8-12.5-45.3 0L288 274.7 288 32zM64 352c-35.3 0-64 28.7-64 64l0 32c0 35.3 28.7 64 64 64l384 0c35.3 0 64-28.7 64-64l0-32c0-35.3-28.7-64-64-64l-101.5 0-45.3 45.3c-25 25-65.5 25-90.5 0L165.5 352 64 352zm368 56a24 24 0 1 1 0 48 24 24 0 1 1 0-48z"></path></svg><span class="article-block__image-download-button-text">Download image</span></div></button></div></div></figure><div class="article-block__callout col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><h4 class="h4-semibold">Acknowledgements</h4><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Ilya Kashnitsky, Edouard Mathieu, Max Roser, and Fiona Spooner provided valuable feedback on this article.</span></p></div><section class="footnote-container grid grid-cols-12-full-width col-start-1 col-end-limit"><div class="col-start-4 span-cols-8 col-md-start-3 span-md-cols-10 col-sm-start-2 span-sm-cols-12"><h3 id="article-endnotes">Endnotes</h3><ol class="footnote-list"><li id="note-1" class="footnote-list__footnote"><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>We usually talk about birth cohorts – people born in the same year – but the term can be used for many kinds of groups: immigration cohorts, marriage cohorts, stroke survivors, university alumni, and so on. In this article, we’ll focus on birth cohorts.</span></p></li><li id="note-2" class="footnote-list__footnote"><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>This visualization was inspired by a diagram in the Office for Budget Responsibility’s report.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Office for Budget Responsibility. (2018, July). Period and cohort measures of fertility and mortality. </span><a href="https://obr.uk/box/period-cohort-measures-of-fertility-and-mortality/" class="span-link" target="_blank" rel="noopener"><span>https://obr.uk/box/period-cohort-measures-of-fertility-and-mortality/</span></a></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>See also:</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Wilson, C., Sobotka, T., Williamson, L., & Boyle, P. (2013). Migration and Intergenerational Replacement in Europe. Population and Development Review, 39(1), 131–157. </span><a href="https://doi.org/10.1111/j.1728-4457.2013.00576.x" class="span-link" target="_blank" rel="noopener"><span>https://doi.org/10.1111/j.1728-4457.2013.00576.x</span></a></p></li><li id="note-3" class="footnote-list__footnote"><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Jones, P. M., Minton, J., & Bell, A. (2023). Methods for disentangling period and cohort changes in mortality risk over the twentieth century: Comparing graphical and modelling approaches. Quality & Quantity, 57(4), 3219–3239. </span><a href="https://doi.org/10.1007/s11135-022-01498-3" class="span-link" target="_blank" rel="noopener"><span>https://doi.org/10.1007/s11135-022-01498-3</span></a></p></li><li id="note-4" class="footnote-list__footnote"><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>In the Human Mortality Database, researchers have a threshold to wait until 99% of the relevant exposure data from a given cohort is available until making cohort estimates.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>See section 7.2.2 in the Human Mortality Database full protocol v6.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Wilmoth, J. R., Andreev, K., Jdanov, D., Glei, D. A., Riffe, T., Boe, C., Bubenheim, M., Philipov, D., Shkolnikov, V., Vachon, P., Winant, C., & Barbieri, M. (2021). Methods protocol for the human mortality database (v6). </span><a href="https://www.mortality.org/File/GetDocument/Public/Docs/MethodsProtocolV6.pdf" class="span-link" target="_blank" rel="noopener"><span>https://www.mortality.org/File/GetDocument/Public/Docs/MethodsProtocolV6.pdf</span></a></p></li><li id="note-5" class="footnote-list__footnote"><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>In demography, it’s common to describe population sizes in 100,000 people instead. However, I’ve used 1,000 in this hypothetical example to make the numbers more digestible.</span></p></li><li id="note-6" class="footnote-list__footnote"><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Guillot, M. (2011). Period Versus Cohort Life Expectancy. In R. G. Rogers & E. M. Crimmins (Eds.), International Handbook of Adult Mortality (Vol. 2, pp. 533–549). Springer Netherlands. </span><a href="https://doi.org/10.1007/978-90-481-9996-9_25" class="span-link" target="_blank" rel="noopener"><span>https://doi.org/10.1007/978-90-481-9996-9_25</span></a></p></li><li id="note-7" class="footnote-list__footnote"><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Canudas-Romo, V., & Schoen, R. (2005). Age-specific contributions to changes in the period and cohort life expectancy. Demographic Research, 13, 63–82. </span><a href="https://doi.org/10.4054/DemRes.2005.13.3" class="span-link" target="_blank" rel="noopener"><span>https://doi.org/10.4054/DemRes.2005.13.3</span></a></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Vaupel, J. W. (2002). Life expectancy at current rates vs. Current conditions: A reflexion stimulated by Bongaarts and Feeney’s “How long do we live?” Demographic Research, 7, 365–378. </span><a href="https://doi.org/10.4054/DemRes.2002.7.8" class="span-link" target="_blank" rel="noopener"><span>https://doi.org/10.4054/DemRes.2002.7.8</span></a></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Oeppen, J., & Vaupel, J. W. (2002). Broken Limits to Life Expectancy. Science, 296(5570), 1029–1031. </span><a href="https://doi.org/10.1126/science.1069675" class="span-link" target="_blank" rel="noopener"><span>https://doi.org/10.1126/science.1069675</span></a></p></li><li id="note-8" class="footnote-list__footnote"><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Vaupel, J. W. (2002). Life expectancy at current rates vs. Current conditions: A reflexion stimulated by Bongaarts and Feeney’s “How long do we live?” Demographic Research, 7, 365–378. </span><a href="https://www.demographic-research.org/volumes/vol7/8/7-8.pdf" class="span-link" target="_blank" rel="noopener"><span>https://www.demographic-research.org/volumes/vol7/8/7-8.pdf</span></a></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Missov, T. I., Lenart, A., Nemeth, L., Canudas-Romo, V., & Vaupel, J. W. (2015). The Gompertz force of mortality in terms of the modal age at death. Demographic Research, 32, 1031–1048. </span><a href="https://doi.org/10.4054/DemRes.2015.32.36" class="span-link" target="_blank" rel="noopener"><span>https://doi.org/10.4054/DemRes.2015.32.36</span></a></p></li><li id="note-9" class="footnote-list__footnote"><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Horiuchi, S., Ouellette, N., Cheung, S. L. K., & Robine, J.-M. (2013). Modal age at death: Lifespan indicator in the era of longevity extension. </span><em><span>Vienna Yearbook of Population Research</span></em><span>, 37–69. </span><a href="https://www.jstor.org/stable/43050796" class="span-link" target="_blank" rel="noopener"><span>https://www.jstor.org/stable/43050796</span></a></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Missov, T. I., Lenart, A., Nemeth, L., Canudas-Romo, V., & Vaupel, J. W. (2015). The Gompertz force of mortality in terms of the modal age at death. Demographic Research, 32, 1031–1048. </span><a href="https://doi.org/10.4054/DemRes.2015.32.36" class="span-link" target="_blank" rel="noopener"><span>https://doi.org/10.4054/DemRes.2015.32.36</span></a></p></li><li id="note-10" class="footnote-list__footnote"><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>To recreate this chart, or create it for other countries, the </span><a href="https://github.com/owid/notebooks/tree/main/SaloniDattani/Life-expectancy/Period-vs-cohort-age-mortality" class="span-link" target="_blank" rel="noopener"><span>scripts</span></a><span> are available online.</span></p></li><li id="note-11" class="footnote-list__footnote"><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>For example, researchers can measure the </span><strong><span>total fertility rate</span></strong><span> (TFR) as a period measure. It represents the average fertility for a hypothetical group of women in a given year, if they experienced the same age-specific fertility rates throughout their whole lives as the age-specific fertility rates seen in that particular year.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>But TFR can also be measured as a cohort measure – where it represents the average number of children born to women in that cohort by the end of their reproductive lives.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>This distinction is important because period TFR can be influenced by the timing of childbearing and can therefore fluctuate due to trends such as women choosing to have children later in life.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>Bongaarts, J., & Feeney, G. (1998). On the Quantum and Tempo of Fertility. Population and Development Review, 24(2), 271. </span><a href="https://doi.org/10.2307/2807974" class="span-link" target="_blank" rel="noopener"><span>https://doi.org/10.2307/2807974</span></a></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>In addition, demographers can also calculate hybrid measures from both period and cohort.</span></p><p class="article-block__text col-start-5 span-cols-6 col-md-start-3 span-md-cols-10 span-sm-cols-12 col-sm-start-2"><span>See for an example: Wilson, C., Sobotka, T., Williamson, L., & Boyle, P. (2013). Migration and Intergenerational Replacement in Europe. Population and Development Review, 39(1), 131–157. </span><a href="https://doi.org/10.1111/j.1728-4457.2013.00576.x" class="span-link" target="_blank" rel="noopener"><span>https://doi.org/10.1111/j.1728-4457.2013.00576.x</span></a></p></li></ol></div></section><section id="article-citation" class="grid grid-cols-12-full-width col-start-1 col-end-limit"><div class="col-start-4 span-cols-8 col-md-start-3 span-md-cols-10 col-sm-start-2 span-sm-cols-12"><h3 class="align-center">Cite this work</h3><p>Our articles and data visualizations rely on work from many different people and organizations. When citing this article, please also cite the underlying data sources. This article can be cited as:</p><div><div class="wp-code-snippet wp-code-snippet--dark"><pre class="wp-block-code"><code class="wp-code-snippet__code">Saloni Dattani (2023) - “Period versus cohort measures: what’s the difference?” Published online at OurWorldinData.org. Retrieved from: 'https://ourworldindata.org/period-versus-cohort-measures-whats-the-difference' [Online Resource]</code></pre></div></div><p>BibTeX citation</p><div><div class="wp-code-snippet wp-code-snippet--dark"><pre class="wp-block-code"><code class="wp-code-snippet__code">@article{owid-period-versus-cohort-measures-whats-the-difference, author = {Saloni Dattani}, title = {Period versus cohort measures: what’s the difference?}, journal = {Our World in Data}, year = {2023}, note = {https://ourworldindata.org/period-versus-cohort-measures-whats-the-difference} }</code></pre></div></div></div></section><section id="article-licence" class="grid grid-cols-12-full-width col-start-1 col-end-limit"><div class="col-start-4 span-cols-8 col-md-start-3 span-md-cols-10 col-sm-start-2 span-sm-cols-12"><img src="https://ourworldindata.org/owid-logo.svg" class="img-raw" alt="Our World in Data logo" width="104" height="57"/><h3>Reuse this work freely</h3><p>All visualizations, data, and code produced by Our World in Data are completely open access under the <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" rel="noopener">Creative Commons BY license</a>. 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