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((Short description|Form of longitudinal study))
((for multi|analysis of cohorts in community health and business data sets|Cohort analysis|other uses|Cohort (disambiguation)))
((Use dmy dates|date=March 2020))
A '''cohort study''' is a particular form of [[longitudinal study]] that samples a [[Cohort (statistics)|cohort]] (a group of people who share a defining characteristic, typically those who experienced a common event in a selected period, such as birth or graduation), performing a [[Cross-sectional data|cross-section]] at intervals through time. It is a type of [[panel study]] where the individuals in the panel share a common characteristic.

Cohort studies represent one of the fundamental designs of [[epidemiology]] which are used in research in the fields of [[medicine]], [[pharmacy]], [[nursing]], [[Psychological research|psychology]], [[social science]], and in any field reliant on 'difficult to reach' answers that are based on evidence ([[statistics]]). In medicine for instance, while clinical trials are used primarily for assessing the safety of newly developed pharmaceuticals before they are approved for sale, epidemiological analysis on how risk factors affect the incidence of diseases is often used to identify the causes of diseases in the first place, and to help provide pre-clinical justification for the plausibility of protective factors (treatments).

==Comparison with controlled trials==
Cohort studies differ from clinical trials in that no intervention, treatment, or exposure is administered to participants in a cohort design; and no control group is defined. Rather, cohort studies are largely about the life histories of segments of populations and the individual people who constitute these segments.<ref>((cite web|url=http://www.socialresearchmethods.net/tutorial/Cho2/cohort.html|title=Cohort Studies|publisher=Web Center for Social Research Methods|archive-url=https://web.archive.org/web/20110909043451/http://www.socialresearchmethods.net/tutorial/Cho2/cohort.html|archive-date=2011-09-09))</ref><ref>((cite book|url=http://www.oup.com/us/catalog/general/subject/Medicine/EpidemiologyBiostatistics/?view=usa&ci=9780195314502|title=A Dictionary of Epidemiology|publisher=Oxford University Press|year=2008|editor-last=Porta|editor-first=Miquel|edition=5th|location=New York))</ref> Exposures or protective factors are identified as preexisting characteristics of participants. The study is controlled by including other common characteristics of the cohort in the statistical analysis. Both exposure/treatment and control variables are measured at baseline. Participants are then followed over time to observe the incidence rate of the disease or outcome in question. Regression analysis can then be used to evaluate the extent to which the exposure or treatment variable contributes to the incidence of the disease, while accounting for other variables that may be at play.((cn|date=May 2023))

[[Randomized controlled trial|Double-blind randomized controlled trial]]s (RCTs) are generally considered superior methodology in the [[hierarchy of evidence]] in treatment, because they allow for the most control over other variables that could affect the outcome, and the randomization and blinding processes reduce bias in the study design. This minimizes the chance that results will be influenced by [[confounding]] variables, particularly ones that are unknown. However, educated hypotheses based on prior research and background knowledge are used to select variables to be included in the regression model for cohort studies, and statistical methods can be used to identify and account for potential confounders from these variables. Bias can also be mitigated in a cohort study when selecting participants for the cohort. It is also important to note that RCTs may not be suitable in all cases; such as when the outcome is a negative health effect and the exposure is hypothesized to be a risk factor for the outcome. Ethical standards, and morality, would prevent the use of risk factors in RCTs. The natural or incidental exposure to these risk factors (e.g. time spent in the sun), or self-administered exposure (e.g. smoking), can be measured without subjecting participants to risk factors outside of their individual lifestyles, habits, and choices.

== Types ==
Cohort studies can be [[Retrospective cohort study|retrospective]] (looking back in time, thus using existing data such as medical records or claims database) or [[Prospective cohort study|prospective]] (requiring the collection of new data).<ref>((cite web|url=http://www.ehib.org/faq.jsp?faq_key=37|title=FAQ: What is a cohort study?|date=2 June 2001|publisher=California Department of Public Health, Environmental Health Investigations Branch|access-date=10 September 2010|archive-url=https://web.archive.org/web/20110726020518/http://www.ehib.org/faq.jsp?faq_key=37|archive-date=26 July 2011|url-status=dead))</ref> Retrospective cohort studies restrict the investigators' ability to reduce confounding and bias because collected information is restricted to data that already exists. There are advantages to this design, however, as retrospective studies are much cheaper and faster because the data has already been collected and stored.

A [[cohort (statistics)|cohort]] is a group of people who share a common characteristic or experience within a defined period (e.g., are currently living, are exposed to a drug or vaccine or pollutant, or undergo a certain medical procedure). Thus a group of people who were born on a day or in a particular period, say 1948, form a birth cohort. The comparison group may be the general population from which the cohort is drawn, or it may be another cohort of persons thought to have had little or no exposure to the substance under investigation, but otherwise similar. Alternatively, subgroups within the cohort may be compared with each other.

==Application==

In medicine, a cohort study is often undertaken to obtain evidence to try to refute the existence of a suspected association between cause and effect; failure to refute a hypothesis often strengthens confidence in it. Crucially, the cohort is identified before the appearance of the disease under investigation. The study groups follow a group of people who do not have the disease for a period of time and see who develops the disease (new incidence). The cohort cannot therefore be defined as a group of people who already have the disease. Prospective (longitudinal) cohort studies between exposure and disease strongly aid in studying causal associations, though distinguishing true causality usually requires further corroboration from further experimental trials.

The advantage of prospective cohort study data is that it can help determine risk factors for contracting a new disease because it is a longitudinal observation of the individual through time, and the collection of data at regular intervals, so recall error is reduced. However, cohort studies are expensive to conduct, are sensitive to [[Attrition (medicine, epidemiology)|attrition]] and take a long follow-up time to generate useful data. Nevertheless, the results that are obtained from long-term cohort studies are of substantially superior quality to those obtained from retrospective/cross-sectional studies. Prospective cohort studies are considered to yield the most reliable results in observational epidemiology. They enable a wide range of exposure-disease associations to be studied.

Some cohort studies track groups of children from their birth, and record a wide range of information (exposures) about them. The value of a cohort study depends on the researchers' capacity to stay in touch with all members of the cohort. Some studies have continued for decades.

In a cohort study, the population under investigation consists of individuals who are at risk of developing a specific disease or health outcome.<ref>((cite book |editor-first1=Lorna |editor-last1=Fewtrell |editor-first2=Jamie |editor-last2=Bartram |title=Water Quality: Guidelines, Standards, and Health : Assessment of Risk and Risk Management for Water-related Infectious Disease |first1=Ursula J. |last1=Blumenthal |first2=Jay M. |last2=Fleisher |first3=Steve A. |last3=Esrey |first4=Anne |last4=Peasey |chapter=Chapter 7: Epidemiology: a tool for the assessment of risk |publisher=IWA Publishing |year=2001 |chapter-url=https://www.who.int/water_sanitation_health/dwq/iwachap7.pdf |pages=143–144))</ref>

==Examples==
((Cleanup|section|date=July 2011))

An example of an epidemiological question that can be answered using a cohort study is whether exposure to X (say, smoking) associates with outcome Y (say, lung cancer). For example, in 1951, the [[British Doctors Study]] was started. Using a cohort which included both smokers (the exposed group) and non-smokers (the unexposed group). The study continued through 2001. By 1956, the study provided convincing proof of the association between smoking and the incidence of lung cancer. In a cohort study, the groups are ''matched'' in terms of many other variables such as economic status and other health status so that the variable being assessed, the [[independent variable]] (in this case, smoking) can be isolated as the cause of the [[dependent variable]] (in this case, lung cancer). In this example, a [[Statistical significance|statistically significant]] increase in the incidence of lung cancer in the smoking group as compared to the non-smoking group is evidence in favor of the hypothesis. However, rare outcomes, such as lung cancer, are generally not studied with the use of a cohort study, but are rather studied with the use of a [[case-control]] study.

Cohort Succession can explain most change in literature, art, intellectualism, political opinions, and phonology.<ref>((cite journal |last1=Underwood |first1=Ted |last2=Kiley |first2=Kevin |last3=Shang |first3=Wenyi |last4=Vaisey |first4=Stephen |title=Cohort Succession Explains Most Change in Literary Culture |journal=Sociological Science |date=2022 |volume=9 |pages=184–205 |doi=10.15195/v9.a8 |url=https://sociologicalscience.com/articles-v9-8-184/ |access-date=11 May 2022 |doi-access=free ))</ref>

Shorter term studies are commonly used in medical research as a form of [[clinical trial]], or means to test a particular hypothesis of clinical importance. Such studies typically follow two groups of patients for a period of time and compare an endpoint or outcome measure between the two groups.

[[Randomized controlled trial]]s, or RCTs, are a superior methodology in the hierarchy of evidence, because they limit the potential for bias by randomly assigning one patient pool to an intervention and another patient pool to non-intervention (or placebo). This minimizes the chance that the incidence of confounding variables will differ between the two groups. Nevertheless, it is sometimes not practical or ethical to perform RCTs to answer a clinical question. To take our example, if we already had reasonable evidence that smoking causes lung cancer then persuading a pool of non-smokers to take up smoking in order to test this hypothesis would generally be considered quite unethical.

Two examples of cohort studies that have been going on for more than 50 years are the [[Framingham Heart Study]] and the [[National Child Development Study]] (NCDS), the most widely researched of the [[British birth cohort studies]]. Key findings of NCDS and a detailed profile of the study appear in the ''International Journal of Epidemiology''.<ref>((cite journal |vauthors=Power C, Elliott J|title=Cohort profile: 1958 British Cohort Study |journal=International Journal of Epidemiology |volume=35 |issue=1 |pages=34–41 |year=2006 |doi=10.1093/ije/dyi183 |pmid=16155052|doi-access=free ))</ref>

The [[Dunedin Longitudinal Study]], started in 1975, has been studying the thousand people born in [[Dunedin]], New Zealand, in 1972–1973. The subjects are interviewed regularly, with Phase 45 starting in 2017.

<!-- This paragraph following trails off in the middle of a sentence! Needs to be fixed...
The ''International Journal of Epidemiology''<ref>((cite journal |first1=Richard J |last1=Pinder |first2=Neil |last2=Greenberg |first3=Edward J |last3=Boyko |first4=Gary D |last4=Gackstetter |first5=Tomoko I |last5=Hooper |first6=Dominic |last6=Murphy |first7=Margaret AK |last7=Ryan |first8=Besa |last8=Smith |first9=Tyler C |last9=Smith |first10=Timothy S |last10=Wells |first11=Simon |last11=Wessely |title=Profile of two cohorts: UK and US prospective studies of military health   |journal=[[International Journal of Epidemiology]] |year=2012 |volume=41 |number=5 |pages=1272–1282 |publisher=[[Oxford University Press]] |doi=10.1093/ije/dyr096))</ref> comparison of two Cohorts, [[Millennium Cohort Study (United States)]] and The King's Cohort (United Kingdom)

-->
The largest cohort study in women is the [[Nurses' Health Study]]. Started in 1976, it is tracking over 120,000 nurses and has been analyzed for many different conditions and outcomes.

The largest cohort study in Africa is the [[Birth to Twenty]] Study, which began in 1990 and tracks a cohort of over 3,000 children born in the weeks following [[Nelson Mandela]]'s release from prison.

Other famous examples are the [[Grant Study]] tracking a number of Harvard graduates from ca. 1950.77, the [[Whitehall Study]] tracking 10,308 British civil servants, and the [[Caerphilly Heart Disease Study]], which since 1979 has studied a representative sample of 2,512 men, drawn from the Welsh town of Caerphilly.<ref>((Cite journal|pmc=1052363|year=1984|title=Caerphilly and Speedwell collaborative heart disease studies. The Caerphilly and Speedwell Collaborative Group|journal=Journal of Epidemiology and Community Health|volume=38|issue=3|pages=259–262|pmid=6332166|doi=10.1136/jech.38.3.259)).</ref>

The ASPREE-XT study is designed to determine whether there are long-lasting effects of an average of four–five years of treatment with daily low-dose aspirin, with outcome measures including cancer mortality.<ref>((Cite web|url=https://aspree.org/aus/for-clinicans/about-aspree-xt/|title=ASPREE Australia ((!)) ABOUT ASPREE-XT - ASPREE Australia|date=2019-07-21|access-date=2019-07-21|archive-url=https://web.archive.org/web/20190721044912/https://aspree.org/aus/for-clinicans/about-aspree-xt/|archive-date=21 July 2019))</ref> As of September 2018, there were 16,703 ASPREE-XT participants in Australia.<ref>((Cite web|date=September 16, 2018|title=Daily low-dose aspirin found to have no effect on healthy life span in older people|url=https://www.nih.gov/news-events/news-releases/daily-low-dose-aspirin-found-have-no-effect-healthy-life-span-older-people|access-date=22 March 2021|website=National Institutes of Health News Releases))</ref> It has been proposed that the existing ASPREE-XT study could provide a platform for a future multigenerational research study.<ref>((Cite journal|last1=Nunn|first1=Jack S.|last2=Sulovski|first2=Merrin|last3=Tiller|first3=Jane|last4=Holloway|first4=Bruce|last5=Ayton|first5=Darshini|last6=Lacaze|first6=Paul|date=2021-05-03|title=Involving elderly research participants in the co-design of a future multi-generational cohort study|journal=Research Involvement and Engagement|volume=7|issue=1|pages=23|doi=10.1186/s40900-021-00271-4|pmid=33941290|pmc=8094476|issn=2056-7529|doi-access=free))</ref>

==Variations==
[[Image:ExplainingCaseControlSJW-en.svg|360px|Comparison of timelines of case-control and cohort studies. "OR" stands for "odds ratio" and "RR" stands for "relative risk".|thumb]]
The diagram indicates the starting point and direction of cohort and case-control studies.
In case-control studies the analysis proceeds from documented disease and investigations are made to arrive at the possible causes of the disease. In cohort studies the assessment starts with the putative cause of disease, and observations are made of the occurrence of disease relative to the hypothesized causal agent'''.<ref name="gfmer.ch">((cite book |editor-first=Aldo |editor-last=Campana |first=O. |last=Meirik |title=Reproductive Health |chapter-url=http://www.gfmer.ch/Books/Reproductive_health/Cohort_and_case_control_studies.html |chapter=Cohort and Case-Control Studies |publisher=Geneva Foundation for Medical Education and Research))</ref>'''

===Current and historical cohorts===
((main|Retrospective cohort study))

A current cohort study represents a true prospective study where the data concerning exposure are assembled prior to the occurrence of the fact to be studied, for instance a disease. An example of a current cohort study is the Oxford Family Planning Association Study in the United Kingdom, which aimed to provide a balanced view of the beneficial and harmful effects of different methods of contraception. This study has provided a large amount of information on the efficacy and safety of contraceptive methods, and in particular oral contraceptives (OCs), diaphragms and intrauterine device (IUDs).<ref>((Cite journal|last1=Vessey|first1=M. P.|last2=Lawless|first2=M.|date=1984|title=The Oxford-Family Planning Association contraceptive study|journal=Clinics in Obstetrics and Gynaecology|volume=11|issue=3|pages=743–757|doi=10.1016/S0306-3356(21)00625-7|issn=0306-3356|pmid=6509857))</ref>

In a historical cohort study the data concerning exposure and occurrence of a disease, births, a political attitude or any other categorical variable are collected after the events have taken place, and the subjects (those exposed and unexposed to the agent under study) are assembled from existing records or health care registers.

A "[[prospective cohort]]" defines the groups before the study is done, while historical studies, which are sometimes referred to as "[[retrospective cohort]]", defines the grouping after the data is collected. Examples of a [[retrospective cohort]] are ''Long-Term Mortality after Gastric Bypass Surgery''<ref name="pmid17715409">((cite journal |author=Adams TD |title=Long-term mortality after gastric bypass surgery |journal=N. Engl. J. Med. |volume=357 |issue=8 |pages=753–61 |year=2007 |pmid=17715409 |doi=10.1056/NEJMoa066603 |name-list-style=vanc|author2=Gress RE |author3=Smith SC |display-authors=3 |last4=Halverson |first4=R. Chad |last5=Simper |first5=Steven C. |last6=Rosamond |first6=Wayne D. |last7=Lamonte |first7=Michael J. |last8=Stroup |first8=Antoinette M. |last9=Hunt |first9=Steven C.|s2cid=8710295 |url=http://pdfs.semanticscholar.org/2908/f0ef315574fb7fa5a7941c97091a7fddd012.pdf |archive-url=https://web.archive.org/web/20190220132224/http://pdfs.semanticscholar.org/2908/f0ef315574fb7fa5a7941c97091a7fddd012.pdf |url-status=dead |archive-date=2019-02-20 ))</ref> and ''[[The Lothian Birth Cohort Studies]]''.<ref>((cite web|url=http://www.psy.ed.ac.uk/research/lbc/LBC.html|title=The Lothian Birth Cohort Studies|access-date=8 May 2011|publisher=University of Edinburgh |archive-url=https://web.archive.org/web/20091022052040/http://www.psy.ed.ac.uk/research/lbc/LBC.html |archive-date=2009-10-22))</ref>

Although historical studies are sometimes referred to as retrospective study, it a misnomer as the methodological principles of historical cohort studies and prospective studies are the same.<ref name="gfmer.ch" />

===Nested case-control study===
((main|Nested case-control study))
A nested case-control study is a case control nested inside of a cohort study. The procedure begins like a normal cohort study, however, as participants develop the outcome of interest they are selected as cases. Once the cases are identified, controls are selected and matched to each case. The process for selecting and matching cases is identical to a normal case control study. An example of a [[nested case-control study]] is ''Inflammatory markers and the risk of coronary heart disease in men and women'', which was a case control analyses extracted from the [[Framingham Heart Study]] cohort.<ref name="pmid15602020">((cite journal |last1=Pai |first1=JK |title=Inflammatory markers and the risk of coronary heart disease in men and women |journal=N. Engl. J. Med. |volume=351 |issue=25 |pages=2599–2610 |year=2004 |pmid=15602020 |doi=10.1056/NEJMoa040967 |last2=Pischon |first2=T |last3=Ma |first3=J |display-authors=3 |last4=Manson |first4=Joann E. |last5=Hankinson |first5=Susan E. |last6=Joshipura |first6=Kaumudi |last7=Curhan |first7=Gary C. |last8=Rifai |first8=Nader |last9=Cannuscio |first9=Carolyn C.|s2cid=16142059 |doi-access=free ))</ref>

Nested case-controls have the advantage of reducing the number of participants that require details follow up or diagnostic testing to assess outcome or exposure status. However, this will also reduce the power of the study, when compared to larger cohort the study population is drawn from.

===Household panel survey===
Panel surveys are another important sub-type of [[longitudinal study]]. They differ from cohort studies by starting with representative cross-sectional samples, rather than cohorts defined by an event. Household panel draw representative samples of households and survey them, following all individuals through time on a usually annual basis. Examples include the US [[Panel Study of Income Dynamics]] (since 1968), the ''German'' [[Socio-Economic Panel]] (since 1984), the [[British Household Panel Survey]] (since 1991) and (since 2009) its successor [[Understanding Society: the UK Household Longitudinal Study]], the [[Household, Income and Labour Dynamics in Australia Survey]] (since 2001) and the [[European Community Household Panel]] (1994–2001).

===Cohort analysis in business===

For an example in business analysis, see [[cohort analysis]].

==See also==
* [[Cohort (statistics)]]
* [[Community of position]]
* [[Panel analysis]]
* [[Panel data]]

==References==
((reflist|30em))

==External links==
* [https://web.archive.org/web/20060310202137/http://clio.stanford.edu:7080/cocoon/cliomods/trailmaps/design/design/prospectiveCohort/index.html Prospective cohorts]
* [https://web.archive.org/web/20060310202147/http://clio.stanford.edu:7080/cocoon/cliomods/trailmaps/design/design/retrospectiveCohort/index.html Retrospective cohorts]
* [https://web.archive.org/web/20100414204016/http://www.esds.ac.uk/longitudinal/resources/international.asp Birth cohort study timelines (ESDS Longitudinal)]
* [http://www.cls.ioe.ac.uk Centre for Longitudinal Studies]

((Statistics|collection))
((Medical research studies))

((DEFAULTSORT:Cohort Study))
[[Category:Epidemiology]]
[[Category:Cohort studies|*]]
[[Category:Cohort study methods|*]]
[[Category:Research]]
[[Category:Nursing research]]

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