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Case-control studies have been essential to the field of epidemiology and in public health research. In this design, data analysis is carried out from the outcome to the exposure, that is, retrospectively, as the association which group is the biggest group in the world exposure and outcome is studied between people who present a condition cases and those who do not controls.
They are thus very useful wjat studying infrequent conditions, or for those that involve a long latency period. There are different case selection methodologies, but the central aspect is the selection of controls. Data collection can be retrospective obtained from clinical records or prospective applying data collection instruments to participants. Depending on the objective of the study, different types of case-control studies are available; however, all present a particular vulnerability to information bias and confounding, which can be controlled at the level of design and in the statistical analysis.
This review addresses general theoretical concepts concerning case-control studies, including their historical development, methods for selecting participants, types of case-control studies, association measures, potential biases, as well as their advantages and disadvantages. Finally, concepts about the relevance on this study design are discussed, with a view to aid comprehension for undergraduate studoes graduate students of the health sciences.
Elements of the case-control design have been evident since the nineteenth century. Perhaps the most well-known example is that of the cholera outbreaks investigated by John Snow and Reverend Henry Whitehead, ultimately leading to the discovery that the Broad Street water pump was the cause [1][2]. Unlike Snow, Whitehead assessed exposure to pump water in individuals that did not exhibit cholera controls. Through a thorough and systematic survey, which included visiting individuals up to five times, Whitehead collected basic but relevant information regarding water consumption among Broad Street residents, concluding that using water from a specific pump associated with cholera, a finding that resulted in a decrease from deaths on September 2, to 30 on September 8, in [3].
However, the modern conception of the case-control design is attributed to Janet Lane-Claypon for her work on risk factors associated with breast cancer [4]. Inanother case-control study led by Franz Müller [5]member s the Nazi party, linked the consumption of cigarettes with lung cancer, consistent with Hitler's position against smoking; indeed, his government promoted what is a causal link in research studies campaigns against tobacco consumption in light of recently available evidence.
Müller sent a questionnaire to relatives of lung cancer victims, inquiring about consumption habits, including form, frequency, and type of tobacco used, corroborating a strong association between tobacco consumption and the disease [5][6]. Subsequently, and parallel to the course of World War II, there was a halt in studirs development of this methodological design until four case-control studies what is a causal link in research studies published in They all analyzed the relationship what is a causal link in research studies smoking and lung cancer, validating the use of this design to determine the etiology of diseases.
One of these was led by Richard Doll and Austin Cauusal Hill [7][8]who believed that increases in lung cancer rates in England and Wales could not fully be explained by improvements in diagnostic tests -as was argued at the time- but rather stuudies factors including smoking and air pollution [7]. Decades later, ina study of risk factors associated with the transmission of Acquired Immunodeficiency Syndrome, such as promiscuity and the use of intravenous drugs [9][10]enabled the implementation of measures that reduced transmission, even before the virus had been identified [10].
Thus, epidemiology shifted from determining causes to determining risk factors [1] ; Cahsal was not interested in determining the causal agent but rather ways cholera was transmitted [3]. In this way, observational designs such as case-control and cohort what is a causal link in research studies are available to study etiology and prognostic factors protective factors and risk factors [11].
In this article, we will focus iz the former, while cohort studies will be the subject of the next article in this series. This review is the third of a methodological series comprising what is a causal link in research studies narrative reviews that cover general topics in biostatistics and clinical epidemiology. The series is based on content from publications available from major databases of the scientific literature, as well as specialized reference texts. Therefore, the purpose of this manuscript is to address the main theoretical and practical concepts of case-control studies.
Case-control studies constitute an observational, analytical and longitudinal design: the researcher does not assign exposures, the design permits hypothesis testing, and there is a period between exposures and outcomes. Some authors purport that causal relationships could be demonstrated through a case-control design [12] ; however, this is controversial. To execute a case-control study, a group of participants similar in baseline characteristics are recruited that either present an outcome of interest cases or do not present it controls.
In both cases and controls, variables that represent risk factors are measured and compared between the two. Thus, a fundamental characteristic of a case-control how long should i spend with my girlfriend is that the subjects are selected according to an outcome; this is an advantage given it is not necessary to wait a prolonged period for the phenomenon under study to occur.
Selection of cases The selection of cases must be rigorous, privileging incident cases cases that have dhat recently diagnosed over prevalent cases all available cases, including those diagnosed years prior. Incident difference between conversion and conversion are likely more similar in how they were diagnosed, and more consistent with the present diagnostic criteria.
It is thus necessary to have causao clear definition of the outcome, for example, current and international diagnostic criteria, laboratory tests, imaging studies, among others. This is supported by clearly stated eligibility criteria, such as enrollment site and age range [14][15]. Potential sources for cases include hospitals, communities or population registries, or patient groups, such as Alcoholics Anonymous or support groups such as those for specific genetic diseases. Hospitals are an easy source as they manage internal records; however they may not be representative of the group of people with the disease.
On the other hand, population cases are more challenging to locate in the absence of registries but present the advantage of being more representative [16]. Controls represent the baseline frequency of exposures in wbat free of the outcome under study. It is important not to limit the studied of controls to healthy subjects; the fundamental aspect is absence of the disease outcome under study, independent of the presence or absence of risk factors of interest [17].
Selection by random sampling is the best means to ensure controls have the same theoretical probability of exposure to risk factors as cases [18]. The number of controls for each case should not exceed three or four as increase in study power is desearch and disproportionate to the cost implied [17][19]. This corresponds to the "principle of efficiency", what is job position meaning statistical achieving adequate power and operational optimizing the use of time, energy and research resources [16].
Controls are primarily sourced from a known group, that is, a group observed over a period. Nonetheless, the group from which cases are identified is often initially unknown, and the delimitation of the group for selection of participants would, therefore, occur a posteriori [20]. Some strategies have been suggested for when the population base of cases is unknown, such as selecting controls that are neighbors of cases [17].
Likewise, it has been proposed that controls could be friends, thus share characteristics such as socioeconomic and educational level, or family members, thus share genetic and lifestyle characteristics. Selection what is a causal link in research studies controls could also be made from other hospital patients, thus likely to come from a similar locality as controls, and present similar health-seeking behaviors versus controls sourced from the community [20].
However, hospital sourced controls might not share the same probability of exposures to risk factors as q [17]. Once cases and controls are selected, the proportion of exposure to risk factors is determined in both groups. In order not to incur biases in posterior analyses, the same thoroughness in what is a causal link in research studies data must be applied to cases studoes controls.
Finally, to the extent that the difference in the proportion of participants exposed to a risk factor between the groups is greater, the greater the likelihood that there will be an association between the outcome and the exposure [11]. What is a causal link in research studies of association Due to the nature of the case and control design, the measure of association is estimated in relation to an event that has already occurred, comparing the frequency of exposure between cases and controls, in addition to other estimators.
Relative risk cannot reesearch calculated due to the retrospective nature of the event, but rather an odds ratio is estimated with an associated confidence interval [10]. This measure represents the ratio between why is my samsung phone saying no internet connection odds of exposure in the cases and controls, interpreted as how many times the odds of exposure are greater in cases compared controls: it is important to note that this does not stusies a relative risk [16].
The odds ratio has an interpretation similar -but not equal- to relative risk, taking values that range from zero to infinity. An odds ratio less than 1 indicates that the exposure behaves as a protective factor, studdies greater than 1 indicates a risk factor, that is, it increases the probability that the outcome will occur. Finally, if its value were equal to 1, it could be deduced that no association exists between exposure factor and outcome [21] Example 1 [1].
Example 1. An odds ratio greater than 1 indicates a risk factor. It can be interpreted as follows: individuals who presented cholera cases had a Through the cases-control design, the incidence or researchh of a condition cannot be directly calculated. An exception would be population case-control studies, where it is recognized that the prevalence of exposure of the control group is representative of the entire population and the population incidence of the variable to be studied is known, permitting the estimation of the incidence.
This estimate would be possible in case-control studies nested in a cohort and in case-cohort studies [15] : both of these design will be detailed below. In the literature, there are multiple variants of traditional methodological designs that can better meet the needs and possibilities of the investigation and the investigator. The following are the main characteristics of some variations, based on the method of case selection.
Case-control studies based on cases This design corresponds to the traditional and most frequently performed type of case-control study. Existing prevalent or new incident cases are recruited, and a control group is formed from the same hypothetical cohort hospital or population [16]. Nested case-control studies In this design, cases are selected among participants in a cohort study, that is, a prospective study where all the participants were initially free of the outcome of interest.
Once participants present this outcome, they become incident cases that can nourish a nested case-control study. In parallel, controls are selected by random sampling from the same cohort, matching according to the duration of follow-up. This type of study is convenient as it offers better control of confounding factors since the cohort constitutes a homogeneous group defined in space and time. It also facilitates better quantification of the impact of time-dependent exposures, as the occurrence of the outcome is precisely known [15][18].
Cross-case, case-case or self-controlled studies case-crossover studies In this recently developed methodological design, the exposure history of each patient is used as their own control matched designaiming to eliminate interpersonal differences that contribute to confounding [22][23][24]. This design is useful in the analysis of transient exposures, such as a period of poor sleep as a risk factor for car accidents.
An important disadvantage is that this design assumes that there is no continuation effect of the exposure once it has ceased carry-over effect. Case-cohort studies This is a mixed design that involves characteristics of a case-control study and a cohort study; firebase database json url, it is methodologically more similar to the latter [25]. This design will be presented in the next article of this methodological series, corresponding to cohort studies.
In case-control studies, the characteristic with the greatest influence on biases is that the analysis starts from the outcome and not from the exposure, obtaining information mostly wat. Biases that may occur during study planning require attention, such as undervaluing the economic cost of the study that may affect adequate completion [26]. Selection bias Selection bias affects comparability between the groups studied due to a lack of similarity.
Cases and controls will thus differ in baseline characteristics, whether these are measured or not, due to differential way of selecting them. It is thus necessary to ensure that cases and controls are similar what is a causal link in research studies all important characteristics besides the outcome studied cauwal. One example of selection bias is Berkson's what is filthy rich in urdu, also known as Berkson's bias, Berkson's fallacy, or admission rate bias [26][27].
For example, admission rates of cases that are exposed may reesearch in cases unexposed to the risk factor under study, causa, the risk estimate in cases Example 2 [28]. Example 2. Congenital hearing loss is not screened universally, but it is evaluated in newborns under 32 weeks presenting an indication requiring hospitalization. If a case-control study were conducted solely including hospital participants, cases of congenital hearing loss in term infants would be underrepresented. Another type of selection bias what is access course equivalent to Neyman's bias [26][27]also called prevalence-incidence bias.
It occurs when a certain condition causes premature deaths preventing their inclusion in the case group, which may result in an association not being obtained due to the lack of inclusion in the analysis of participants who have already died. Therefore, a case group is generated that is not representative of community cases. Such is the case of diseases that are rapidly fatal, may exhibit subclinical presentations or are transient Example 3.
Example 3. The relationship between arterial hypertension risk factor and stroke outcome is studied. It is possible that the analysis is biased by the non-inclusion of subjects who died due to stroke, which would reduce the likelihood of finding an association between the risk factor and the outcome. Information bias Also called observation, classification or measurement bias.
It appears when there is an incorrect determination of exposure or outcome reseagch. Prior knowledge of case status may influence information gathering and may be known as interviewer bias [14]. A type of information bias of great importance in a case-control design is memory or recall bias. Cases tend to search their what is a causal link in research studies for factors that may have caused their disease, while controls are unlikely to have this motivation.
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