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What Is a Case-Control Study? | Definition & Examples

Published on February 4, 2023 by Tegan George . Revised on June 22, 2023.

A case-control study is an experimental design that compares a group of participants possessing a condition of interest to a very similar group lacking that condition. Here, the participants possessing the attribute of study, such as a disease, are called the “case,” and those without it are the “control.”

It’s important to remember that the case group is chosen because they already possess the attribute of interest. The point of the control group is to facilitate investigation, e.g., studying whether the case group systematically exhibits that attribute more than the control group does.

Table of contents

When to use a case-control study, examples of case-control studies, advantages and disadvantages of case-control studies, other interesting articles, frequently asked questions.

Case-control studies are a type of observational study often used in fields like medical research, environmental health, or epidemiology. While most observational studies are qualitative in nature, case-control studies can also be quantitative , and they often are in healthcare settings. Case-control studies can be used for both exploratory and explanatory research , and they are a good choice for studying research topics like disease exposure and health outcomes.

A case-control study may be a good fit for your research if it meets the following criteria.

  • Data on exposure (e.g., to a chemical or a pesticide) are difficult to obtain or expensive.
  • The disease associated with the exposure you’re studying has a long incubation period or is rare or under-studied (e.g., AIDS in the early 1980s).
  • The population you are studying is difficult to contact for follow-up questions (e.g., asylum seekers).

Retrospective cohort studies use existing secondary research data, such as medical records or databases, to identify a group of people with a common exposure or risk factor and to observe their outcomes over time. Case-control studies conduct primary research , comparing a group of participants possessing a condition of interest to a very similar group lacking that condition in real time.

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Case-control studies are common in fields like epidemiology, healthcare, and psychology.

You would then collect data on your participants’ exposure to contaminated drinking water, focusing on variables such as the source of said water and the duration of exposure, for both groups. You could then compare the two to determine if there is a relationship between drinking water contamination and the risk of developing a gastrointestinal illness. Example: Healthcare case-control study You are interested in the relationship between the dietary intake of a particular vitamin (e.g., vitamin D) and the risk of developing osteoporosis later in life. Here, the case group would be individuals who have been diagnosed with osteoporosis, while the control group would be individuals without osteoporosis.

You would then collect information on dietary intake of vitamin D for both the cases and controls and compare the two groups to determine if there is a relationship between vitamin D intake and the risk of developing osteoporosis. Example: Psychology case-control study You are studying the relationship between early-childhood stress and the likelihood of later developing post-traumatic stress disorder (PTSD). Here, the case group would be individuals who have been diagnosed with PTSD, while the control group would be individuals without PTSD.

Case-control studies are a solid research method choice, but they come with distinct advantages and disadvantages.

Advantages of case-control studies

  • Case-control studies are a great choice if you have any ethical considerations about your participants that could preclude you from using a traditional experimental design .
  • Case-control studies are time efficient and fairly inexpensive to conduct because they require fewer subjects than other research methods .
  • If there were multiple exposures leading to a single outcome, case-control studies can incorporate that. As such, they truly shine when used to study rare outcomes or outbreaks of a particular disease .

Disadvantages of case-control studies

  • Case-control studies, similarly to observational studies, run a high risk of research biases . They are particularly susceptible to observer bias , recall bias , and interviewer bias.
  • In the case of very rare exposures of the outcome studied, attempting to conduct a case-control study can be very time consuming and inefficient .
  • Case-control studies in general have low internal validity  and are not always credible.

Case-control studies by design focus on one singular outcome. This makes them very rigid and not generalizable , as no extrapolation can be made about other outcomes like risk recurrence or future exposure threat. This leads to less satisfying results than other methodological choices.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Student’s  t -distribution
  • Normal distribution
  • Null and Alternative Hypotheses
  • Chi square tests
  • Confidence interval
  • Quartiles & Quantiles
  • Cluster sampling
  • Stratified sampling
  • Data cleansing
  • Reproducibility vs Replicability
  • Peer review
  • Prospective cohort study

Research bias

  • Implicit bias
  • Cognitive bias
  • Placebo effect
  • Hawthorne effect
  • Hindsight bias
  • Affect heuristic
  • Social desirability bias

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A case-control study differs from a cohort study because cohort studies are more longitudinal in nature and do not necessarily require a control group .

While one may be added if the investigator so chooses, members of the cohort are primarily selected because of a shared characteristic among them. In particular, retrospective cohort studies are designed to follow a group of people with a common exposure or risk factor over time and observe their outcomes.

Case-control studies, in contrast, require both a case group and a control group, as suggested by their name, and usually are used to identify risk factors for a disease by comparing cases and controls.

A case-control study differs from a cross-sectional study because case-control studies are naturally retrospective in nature, looking backward in time to identify exposures that may have occurred before the development of the disease.

On the other hand, cross-sectional studies collect data on a population at a single point in time. The goal here is to describe the characteristics of the population, such as their age, gender identity, or health status, and understand the distribution and relationships of these characteristics.

Cases and controls are selected for a case-control study based on their inherent characteristics. Participants already possessing the condition of interest form the “case,” while those without form the “control.”

Keep in mind that by definition the case group is chosen because they already possess the attribute of interest. The point of the control group is to facilitate investigation, e.g., studying whether the case group systematically exhibits that attribute more than the control group does.

The strength of the association between an exposure and a disease in a case-control study can be measured using a few different statistical measures , such as odds ratios (ORs) and relative risk (RR).

No, case-control studies cannot establish causality as a standalone measure.

As observational studies , they can suggest associations between an exposure and a disease, but they cannot prove without a doubt that the exposure causes the disease. In particular, issues arising from timing, research biases like recall bias , and the selection of variables lead to low internal validity and the inability to determine causality.

Sources in this article

We strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below.

George, T. (2023, June 22). What Is a Case-Control Study? | Definition & Examples. Scribbr. Retrieved February 15, 2024, from https://www.scribbr.com/methodology/case-control-study/
Schlesselman, J. J. (1982). Case-Control Studies: Design, Conduct, Analysis (Monographs in Epidemiology and Biostatistics, 2) (Illustrated). Oxford University Press.

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What Is A Case Control Study?

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BA (Hons) Psychology, Princeton University

Julia Simkus is a graduate of Princeton University with a Bachelor of Arts in Psychology. She is currently studying for a Master's Degree in Counseling for Mental Health and Wellness in September 2023. Julia's research has been published in peer reviewed journals.

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A case-control study is a research method where two groups of people are compared – those with the condition (cases) and those without (controls). By looking at their past, researchers try to identify what factors might have contributed to the condition in the ‘case’ group.

A case-control study looks at people who already have a certain condition (cases) and people who don’t (controls). By comparing these two groups, researchers try to figure out what might have caused the condition. They look into the past to find clues, like habits or experiences, that are different between the two groups.

The “cases” are the individuals with the disease or condition under study, and the “controls” are similar individuals without the disease or condition of interest.

The controls should have similar characteristics (i.e., age, sex, demographic, health status) to the cases to mitigate the effects of confounding variables .

Case-control studies identify any associations between an exposure and an outcome and help researchers form hypotheses about a particular population.

Researchers will first identify the two groups, and then look back in time to investigate which subjects in each group were exposed to the condition.

If the exposure is found more commonly in the cases than the controls, the researcher can hypothesize that the exposure may be linked to the outcome of interest.

Case Control Study

Figure: Schematic diagram of case-control study design. Kenneth F. Schulz and David A. Grimes (2002) Case-control studies: research in reverse . The Lancet Volume 359, Issue 9304, 431 – 434

Quick, inexpensive, and simple

Because these studies use already existing data and do not require any follow-up with subjects, they tend to be quicker and cheaper than other types of research. Case-control studies also do not require large sample sizes.

Beneficial for studying rare diseases

Researchers in case-control studies start with a population of people known to have the target disease instead of following a population and waiting to see who develops it. This enables researchers to identify current cases and enroll a sufficient number of patients with a particular rare disease.

Useful for preliminary research

Case-control studies are beneficial for an initial investigation of a suspected risk factor for a condition. The information obtained from cross-sectional studies then enables researchers to conduct further data analyses to explore any relationships in more depth.

Limitations

Subject to recall bias.

Participants might be unable to remember when they were exposed or omit other details that are important for the study. In addition, those with the outcome are more likely to recall and report exposures more clearly than those without the outcome.

Difficulty finding a suitable control group

It is important that the case group and the control group have almost the same characteristics, such as age, gender, demographics, and health status.

Forming an accurate control group can be challenging, so sometimes researchers enroll multiple control groups to bolster the strength of the case-control study.

Do not demonstrate causation

Case-control studies may prove an association between exposures and outcomes, but they can not demonstrate causation.

A case-control study is an observational study where researchers analyzed two groups of people (cases and controls) to look at factors associated with particular diseases or outcomes.

Below are some examples of case-control studies:
  • Investigating the impact of exposure to daylight on the health of office workers (Boubekri et al., 2014).
  • Comparing serum vitamin D levels in individuals who experience migraine headaches with their matched controls (Togha et al., 2018).
  • Analyzing correlations between parental smoking and childhood asthma (Strachan and Cook, 1998).
  • Studying the relationship between elevated concentrations of homocysteine and an increased risk of vascular diseases (Ford et al., 2002).
  • Assessing the magnitude of the association between Helicobacter pylori and the incidence of gastric cancer (Helicobacter and Cancer Collaborative Group, 2001).
  • Evaluating the association between breast cancer risk and saturated fat intake in postmenopausal women (Howe et al., 1990).

Frequently asked questions

1. what’s the difference between a case-control study and a cross-sectional study.

Case-control studies are different from cross-sectional studies in that case-control studies compare groups retrospectively while cross-sectional studies analyze information about a population at a specific point in time.

In  cross-sectional studies , researchers are simply examining a group of participants and depicting what already exists in the population.

2. What’s the difference between a case-control study and a longitudinal study?

Case-control studies compare groups retrospectively, while longitudinal studies can compare groups either retrospectively or prospectively.

In a  longitudinal study , researchers monitor a population over an extended period of time, and they can be used to study developmental shifts and understand how certain things change as we age.

In addition, case-control studies look at a single subject or a single case, whereas longitudinal studies can be conducted on a large group of subjects.

3. What’s the difference between a case-control study and a retrospective cohort study?

Case-control studies are retrospective as researchers begin with an outcome and trace backward to investigate exposure; however, they differ from retrospective cohort studies.

In a  retrospective cohort study , researchers examine a group before any of the subjects have developed the disease, then examine any factors that differed between the individuals who developed the condition and those who did not.

Thus, the outcome is measured after exposure in retrospective cohort studies, whereas the outcome is measured before the exposure in case-control studies.

Boubekri, M., Cheung, I., Reid, K., Wang, C., & Zee, P. (2014). Impact of windows and daylight exposure on overall health and sleep quality of office workers: a case-control pilot study. Journal of Clinical Sleep Medicine: JCSM: Official Publication of the American Academy of Sleep Medicine, 10 (6), 603-611.

Ford, E. S., Smith, S. J., Stroup, D. F., Steinberg, K. K., Mueller, P. W., & Thacker, S. B. (2002). Homocyst (e) ine and cardiovascular disease: a systematic review of the evidence with special emphasis on case-control studies and nested case-control studies. International journal of epidemiology, 31 (1), 59-70.

Helicobacter and Cancer Collaborative Group. (2001). Gastric cancer and Helicobacter pylori: a combined analysis of 12 case control studies nested within prospective cohorts. Gut, 49 (3), 347-353.

Howe, G. R., Hirohata, T., Hislop, T. G., Iscovich, J. M., Yuan, J. M., Katsouyanni, K., … & Shunzhang, Y. (1990). Dietary factors and risk of breast cancer: combined analysis of 12 case—control studies. JNCI: Journal of the National Cancer Institute, 82 (7), 561-569.

Lewallen, S., & Courtright, P. (1998). Epidemiology in practice: case-control studies. Community eye health, 11 (28), 57–58.

Strachan, D. P., & Cook, D. G. (1998). Parental smoking and childhood asthma: longitudinal and case-control studies. Thorax, 53 (3), 204-212.

Tenny, S., Kerndt, C. C., & Hoffman, M. R. (2021). Case Control Studies. In StatPearls . StatPearls Publishing.

Togha, M., Razeghi Jahromi, S., Ghorbani, Z., Martami, F., & Seifishahpar, M. (2018). Serum Vitamin D Status in a Group of Migraine Patients Compared With Healthy Controls: A Case-Control Study. Headache, 58 (10), 1530-1540.

Further Information

  • Schulz, K. F., & Grimes, D. A. (2002). Case-control studies: research in reverse. The Lancet, 359(9304), 431-434.
  • What is a case-control study?

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  • Knowledge Base
  • Methodology
  • What Is a Case-Control Study? | Definition & Examples

What Is a Case-Control Study? | Definition & Examples

Published on 4 February 2023 by Tegan George .

A case-control study is an experimental design that compares a group of participants possessing a condition of interest to a very similar group lacking that condition. Here, the participants possessing the attribute of study, such as a disease, are called the ‘case’, and those without it are the ‘control’.

It’s important to remember that the case group is chosen because they already possess the attribute of interest. The point of the control group is to facilitate investigation, e.g., studying whether the case group systematically exhibits that attribute more than the control group does.

Table of contents

When to use a case-control study, examples of case-control studies, advantages and disadvantages of case-control studies, frequently asked questions.

Case-control studies are a type of observational study often used in fields like medical research, environmental health, or epidemiology. While most observational studies are qualitative in nature, case-control studies can also be quantitative , and they often are in healthcare settings. Case-control studies can be used for both exploratory and explanatory research , and they are a good choice for studying research topics like disease exposure and health outcomes.

A case-control study may be a good fit for your research if it meets the following criteria.

  • Data on exposure (e.g., to a chemical or a pesticide) are difficult to obtain or expensive.
  • The disease associated with the exposure you’re studying has a long incubation period or is rare or under-studied (e.g., AIDS in the early 1980s).
  • The population you are studying is difficult to contact for follow-up questions (e.g., asylum seekers).

Retrospective cohort studies use existing secondary research data, such as medical records or databases, to identify a group of people with a common exposure or risk factor and to observe their outcomes over time. Case-control studies conduct primary research , comparing a group of participants possessing a condition of interest to a very similar group lacking that condition in real time.

Prevent plagiarism, run a free check.

Case-control studies are common in fields like epidemiology, healthcare, and psychology.

You would then collect data on your participants’ exposure to contaminated drinking water,   focusing on variables such as the source of said water and the duration of exposure,   for both groups. You could then compare the two to determine if there is a relationship between drinking water contamination and the risk of developing a gastrointestinal illness. Example: Healthcare case-control study You are interested in the relationship between the dietary intake of a particular vitamin (e.g., vitamin D) and the risk of developing osteoporosis later in life. Here, the case group would be individuals who have been diagnosed with osteoporosis, while the control group would be individuals without osteoporosis.

You would then collect information on dietary intake of vitamin D for both the cases and controls and compare the two groups to determine if there is a relationship between vitamin D intake and the risk of developing osteoporosis. Example: Psychology case-control study You are studying the relationship between early-childhood stress and the likelihood of later developing post-traumatic stress disorder (PTSD). Here, the case group would be individuals who have been diagnosed with PTSD, while the control group would be individuals without PTSD.

Case-control studies are a solid research method choice, but they come with distinct advantages and disadvantages.

Advantages of case-control studies

  • Case-control studies are a great choice if you have any ethical considerations about your participants that could preclude you from using a traditional experimental design .
  • Case-control studies are time efficient and fairly inexpensive to conduct because they require fewer subjects than other research methods .
  • If there were multiple exposures leading to a single outcome, case-control studies can incorporate that. As such, they truly shine when used to study rare outcomes or outbreaks of a particular disease .

Disadvantages of case-control studies

  • Case-control studies, similarly to observational studies, run a high risk of research biases . They are particularly susceptible to observer bias , recall bias , and interviewer bias.
  • In the case of very rare exposures of the outcome studied, attempting to conduct a case-control study can be very time consuming and inefficient .
  • Case-control studies in general have low internal validity  and are not always credible.

Case-control studies by design focus on one singular outcome. This makes them very rigid and not generalisable , as no extrapolation can be made about other outcomes like risk recurrence or future exposure threat. This leads to less satisfying results than other methodological choices.

A case-control study differs from a cohort study because cohort studies are more longitudinal in nature and do not necessarily require a control group .

While one may be added if the investigator so chooses, members of the cohort are primarily selected because of a shared characteristic among them. In particular, retrospective cohort studies are designed to follow a group of people with a common exposure or risk factor over time and observe their outcomes.

Case-control studies, in contrast, require both a case group and a control group, as suggested by their name, and usually are used to identify risk factors for a disease by comparing cases and controls.

A case-control study differs from a cross-sectional study because case-control studies are naturally retrospective in nature, looking backward in time to identify exposures that may have occurred before the development of the disease.

On the other hand, cross-sectional studies collect data on a population at a single point in time. The goal here is to describe the characteristics of the population, such as their age, gender identity, or health status, and understand the distribution and relationships of these characteristics.

Cases and controls are selected for a case-control study based on their inherent characteristics. Participants already possessing the condition of interest form the “case,” while those without form the “control.”

Keep in mind that by definition the case group is chosen because they already possess the attribute of interest. The point of the control group is to facilitate investigation, e.g., studying whether the case group systematically exhibits that attribute more than the control group does.

The strength of the association between an exposure and a disease in a case-control study can be measured using a few different statistical measures , such as odds ratios (ORs) and relative risk (RR).

No, case-control studies cannot establish causality as a standalone measure.

As observational studies , they can suggest associations between an exposure and a disease, but they cannot prove without a doubt that the exposure causes the disease. In particular, issues arising from timing, research biases like recall bias , and the selection of variables lead to low internal validity and the inability to determine causality.

Sources for this article

We strongly encourage students to use sources in their work. You can cite our article (APA Style) or take a deep dive into the articles below.

George, T. (2023, February 04). What Is a Case-Control Study? | Definition & Examples. Scribbr. Retrieved 15 February 2024, from https://www.scribbr.co.uk/research-methods/case-control-studies/
Schlesselman, J. J. (1982). Case-Control Studies: Design, Conduct, Analysis (Monographs in Epidemiology and Biostatistics, 2) (Illustrated). Oxford University Press.

Is this article helpful?

Tegan George

Tegan George

Other students also liked, what is an observational study | guide & examples, control groups and treatment groups | uses & examples, cross-sectional study | definitions, uses & examples.

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Case-control and Cohort studies: A brief overview

Posted on 6th December 2017 by Saul Crandon

Man in suit with binoculars

Introduction

Case-control and cohort studies are observational studies that lie near the middle of the hierarchy of evidence . These types of studies, along with randomised controlled trials, constitute analytical studies, whereas case reports and case series define descriptive studies (1). Although these studies are not ranked as highly as randomised controlled trials, they can provide strong evidence if designed appropriately.

Case-control studies

Case-control studies are retrospective. They clearly define two groups at the start: one with the outcome/disease and one without the outcome/disease. They look back to assess whether there is a statistically significant difference in the rates of exposure to a defined risk factor between the groups. See Figure 1 for a pictorial representation of a case-control study design. This can suggest associations between the risk factor and development of the disease in question, although no definitive causality can be drawn. The main outcome measure in case-control studies is odds ratio (OR) .

case control study or

Figure 1. Case-control study design.

Cases should be selected based on objective inclusion and exclusion criteria from a reliable source such as a disease registry. An inherent issue with selecting cases is that a certain proportion of those with the disease would not have a formal diagnosis, may not present for medical care, may be misdiagnosed or may have died before getting a diagnosis. Regardless of how the cases are selected, they should be representative of the broader disease population that you are investigating to ensure generalisability.

Case-control studies should include two groups that are identical EXCEPT for their outcome / disease status.

As such, controls should also be selected carefully. It is possible to match controls to the cases selected on the basis of various factors (e.g. age, sex) to ensure these do not confound the study results. It may even increase statistical power and study precision by choosing up to three or four controls per case (2).

Case-controls can provide fast results and they are cheaper to perform than most other studies. The fact that the analysis is retrospective, allows rare diseases or diseases with long latency periods to be investigated. Furthermore, you can assess multiple exposures to get a better understanding of possible risk factors for the defined outcome / disease.

Nevertheless, as case-controls are retrospective, they are more prone to bias. One of the main examples is recall bias. Often case-control studies require the participants to self-report their exposure to a certain factor. Recall bias is the systematic difference in how the two groups may recall past events e.g. in a study investigating stillbirth, a mother who experienced this may recall the possible contributing factors a lot more vividly than a mother who had a healthy birth.

A summary of the pros and cons of case-control studies are provided in Table 1.

case control study or

Table 1. Advantages and disadvantages of case-control studies.

Cohort studies

Cohort studies can be retrospective or prospective. Retrospective cohort studies are NOT the same as case-control studies.

In retrospective cohort studies, the exposure and outcomes have already happened. They are usually conducted on data that already exists (from prospective studies) and the exposures are defined before looking at the existing outcome data to see whether exposure to a risk factor is associated with a statistically significant difference in the outcome development rate.

Prospective cohort studies are more common. People are recruited into cohort studies regardless of their exposure or outcome status. This is one of their important strengths. People are often recruited because of their geographical area or occupation, for example, and researchers can then measure and analyse a range of exposures and outcomes.

The study then follows these participants for a defined period to assess the proportion that develop the outcome/disease of interest. See Figure 2 for a pictorial representation of a cohort study design. Therefore, cohort studies are good for assessing prognosis, risk factors and harm. The outcome measure in cohort studies is usually a risk ratio / relative risk (RR).

case control study or

Figure 2. Cohort study design.

Cohort studies should include two groups that are identical EXCEPT for their exposure status.

As a result, both exposed and unexposed groups should be recruited from the same source population. Another important consideration is attrition. If a significant number of participants are not followed up (lost, death, dropped out) then this may impact the validity of the study. Not only does it decrease the study’s power, but there may be attrition bias – a significant difference between the groups of those that did not complete the study.

Cohort studies can assess a range of outcomes allowing an exposure to be rigorously assessed for its impact in developing disease. Additionally, they are good for rare exposures, e.g. contact with a chemical radiation blast.

Whilst cohort studies are useful, they can be expensive and time-consuming, especially if a long follow-up period is chosen or the disease itself is rare or has a long latency.

A summary of the pros and cons of cohort studies are provided in Table 2.

case control study or

The Strengthening of Reporting of Observational Studies in Epidemiology Statement (STROBE)

STROBE provides a checklist of important steps for conducting these types of studies, as well as acting as best-practice reporting guidelines (3). Both case-control and cohort studies are observational, with varying advantages and disadvantages. However, the most important factor to the quality of evidence these studies provide, is their methodological quality.

  • Song, J. and Chung, K. Observational Studies: Cohort and Case-Control Studies .  Plastic and Reconstructive Surgery.  2010 Dec;126(6):2234-2242.
  • Ury HK. Efficiency of case-control studies with multiple controls per case: Continuous or dichotomous data .  Biometrics . 1975 Sep;31(3):643–649.
  • von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.   Lancet 2007 Oct;370(9596):1453-14577. PMID: 18064739.

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Very well presented, excellent clarifications. Has put me right back into class, literally!

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Very clear and informative! Thank you.

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very informative article.

' src=

Thank you for the easy to understand blog in cohort studies. I want to follow a group of people with and without a disease to see what health outcomes occurs to them in future such as hospitalisations, diagnoses, procedures etc, as I have many health outcomes to consider, my questions is how to make sure these outcomes has not occurred before the “exposure disease”. As, in cohort studies we are looking at incidence (new) cases, so if an outcome have occurred before the exposure, I can leave them out of the analysis. But because I am not looking at a single outcome which can be checked easily and if happened before exposure can be left out. I have EHR data, so all the exposure and outcome have occurred. my aim is to check the rates of different health outcomes between the exposed)dementia) and unexposed(non-dementia) individuals.

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Very helpful information

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Thanks for making this subject student friendly and easier to understand. A great help.

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Thanks a lot. It really helped me to understand the topic. I am taking epidemiology class this winter, and your paper really saved me.

Happy new year.

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Wow its amazing n simple way of briefing ,which i was enjoyed to learn this.its very easy n quick to pick ideas .. Thanks n stay connected

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Saul you absolute melt! Really good work man

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am a student of public health. This information is simple and well presented to the point. Thank you so much.

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very helpful information provided here

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really thanks for wonderful information because i doing my bachelor degree research by survival model

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Quite informative thank you so much for the info please continue posting. An mph student with Africa university Zimbabwe.

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Thank you this was so helpful amazing

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Apreciated the information provided above.

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So clear and perfect. The language is simple and superb.I am recommending this to all budding epidemiology students. Thanks a lot.

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Great to hear, thank you AJ!

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I have recently completed an investigational study where evidence of phlebitis was determined in a control cohort by data mining from electronic medical records. We then introduced an intervention in an attempt to reduce incidence of phlebitis in a second cohort. Again, results were determined by data mining. This was an expedited study, so there subjects were enrolled in a specific cohort based on date(s) of the drug infused. How do I define this study? Thanks so much.

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thanks for the information and knowledge about observational studies. am a masters student in public health/epidemilogy of the faculty of medicines and pharmaceutical sciences , University of Dschang. this information is very explicit and straight to the point

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Very much helpful

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Case-control study: comparative studies

How to use a case-control study to evaluate your digital health product.

This page is part of a collection of guidance on evaluating digital health products .

A case-control study is a type of observational study. It looks at 2 sets of participants. One group has the condition you are interested in (the cases) and one group does not have it (the controls).

In other respects, the participants in both groups are similar. You can then look at a particular factor that might have caused the condition, such as your digital product, and compare participants from the 2 groups in relation to that.

A case-control study is an observational study because you observe the effects on existing groups rather than designing an experiment where participants are allocated into different groups.

What to use it for

A case-control study can help you to find out if your digital product or service achieves its aims, so it can be useful when you have developed your product (summative evaluation).

It can be a useful method when it would be difficult or impossible to randomise participants, for example, if your product aims to help people with rare health conditions.

Case-control studies have many benefits.

  • help to estimate the effects of your digital product when randomisation is not possible
  • use existing data, which could be cheaper and easier
  • operate with fewer participants compared to other designs

There can also be drawbacks of a case-control study.

For example:

  • you need to pay careful attention to factors that may influence your results, confounding factors and biases – see explanation in ‘How to carry out a case-control study’ below
  • there may be challenges when accessing pre-existing data
  • you cannot draw definitive answers about the effects of your product as you haven’t randomly selected participants for your evaluation

How to carry out a case-control study

In a traditional case-control design, cases and controls are looked at retrospectively – that is, the health condition and the factor that might have caused it have already occurred when you start the study.

Sources of cases and controls typically include:

  • routinely collected data at medical facilities
  • disease registries
  • cross-sectional surveys

Some researchers use the term prospective case-control study when, for example, a prospective group exposed to an intervention is compared to a retrospective control.

Choosing your control

Selecting an appropriate control is an important part of a case-control study. The comparison group should be as similar as possible to the source population that produced the cases. This means the participants will be similar to each other in terms of factors that may influence the outcomes you’re looking at. Ideally, they will only differ in whether they received your digital product (cases) or not (controls).

There are 2 main types of case-control design: matched and unmatched.

Essentially, in an unmatched case-control design, a shared control group is selected for all cases at random given certain attributes. In a matched case-control design, controls are selected case-by-case based on specified characteristics. You should pick characteristics that have an effect on the usage of digital devices and services.

Commonly used matching factors include:

  • socio-economic status

However, think about other characteristics and attributes that might influence the use of your product, and the subsequent outcomes.

Confounding variables and biases

Confounding variables (variables other than the one you are interested in that may influence the results) and biases (errors that influence the sample selected and results observed) are important to consider when conducting any research. This is especially important in designs that are non-randomised.

  • selection bias can happen when participants are assigned without randomisation
  • attribution bias may occur when patients with unfavourable outcomes are less likely to attend follow-ups

Analysing your data

The analysis most commonly used in case-control studies is an odds ratio, which is the chance (odds) of the outcomes occurring in the case group versus the control group.

Example: Can telemedicine help with post-bariatric surgery care? A case-control design

In 2019, Wang and colleagues published a paper entitled Exploring the Effects of Telemedicine on Bariatric Surgery Follow-up: a Matched Case Control Study .

The study showed that people who go through bariatric surgery have better outcomes if they attend their follow-up appointments after surgery in comparison to those who do not. However, attending appointments can be challenging for people who live in remote areas. In Ontario, Canada, telemedicine suites were set up to enable healthcare provider-patient videoconferencing.

The researchers used a matched case-control study to investigate if telemedicine videoconferencing can support post-surgery appointment attendance rates in people who live further away from the hospital sites. They used the existing data from the bariatric surgery hospital programme to identify eligible patients.

All patients attending the bariatric surgery were offered telemedicine services. The cases were the participants who used telemedicine services; they were compared to those who did not (the controls).

Cases and controls were matched on various characteristics, specifically:

  • time since bariatric surgery
  • body mass index ( BMI )
  • travel distance from the hospital site

Researchers measured:

  • the percentage of appointments attended
  • rates of dropout
  • pre-and post-surgery weight and BMI
  • various physical and psychological outcomes

They also calculated rurality index to classify patients into urban, non-urban and rural areas. These variables were used to compare cases (those who used telemedicine) and controls (those who did not).

During the study period, they identified that 487 patients of 1,262 who received bariatric surgery used telemedicine services. Of those, 192 agreed to participate in the study.

They found that patients who used telemedicine did as well as patients who attended in person, both in terms of appointment attendance rates and in terms of physical and psychological outcomes.

Moreover, the researchers found that the cases (telemedicine users) came from more rural areas than the controls. The authors argued that this demonstrated that telemedicine can help overcome the known challenges for patients in more rural areas to attend appointments.

Randomising patients to telemedicine or withdrawing the telemedicine would be difficult, undesirable and possibly unethical. Case-control was a good alternative to assess the potential impact on patient outcomes in a service that is already up and running.

More information and resources

A 2003 study by Mann provides an accessible overview of observational research methods, including an explanation of biases and confounding variables.

On the website for Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ), there is a checklist of items that should be included in reports of case-control studies .

A 2016 study by Pearce offers considerations for the analysis of a matched case-control study.

Examples of case-control studies in digital health

In a 2020 study by Heuvel and others , researchers assessed a new digital health tool to monitor women at increased risk of preeclampsia at home. They investigated if the digital tool allows for fewer antenatal visits without compromising women’s safety, and whether it positively affects pregnancy outcomes. This study used a prospective case group compared to a retrospective control group.

In a 2019 study by Depp and others , the research team examined whether schizophrenia symptoms were associated with mobility (measured using GPS sensors). They compared participants with schizophrenia to healthy controls and they found that less mobility was associated with greater symptoms of schizophrenia.

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Quantitative study designs: Case Control

Quantitative study designs.

  • Introduction
  • Cohort Studies
  • Randomised Controlled Trial

Case Control

  • Cross-Sectional Studies
  • Study Designs Home

In a Case-Control study there are two groups of people: one has a health issue (Case group), and this group is “matched” to a Control group without the health issue based on characteristics like age, gender, occupation. In this study type, we can look back in the patient’s histories to look for exposure to risk factors that are common to the Case group, but not the Control group. It was a case-control study that demonstrated a link between carcinoma of the lung and smoking tobacco . These studies estimate the odds between the exposure and the health outcome, however they cannot prove causality. Case-Control studies might also be referred to as retrospective or case-referent studies. 

Stages of a Case-Control study

This diagram represents taking both the case (disease) and the control (no disease) groups and looking back at their histories to determine their exposure to possible contributing factors.  The researchers then determine the likelihood of those factors contributing to the disease.

case control study or

(FOR ACCESSIBILITY: A case control study is likely to show that most, but not all exposed people end up with the health issue, and some unexposed people may also develop the health issue)

Which Clinical Questions does Case-Control best answer?

Case-Control studies are best used for Prognosis questions.

For example: Do anticholinergic drugs increase the risk of dementia in later life? (See BMJ Case-Control study Anticholinergic drugs and risk of dementia: case-control study )

What are the advantages and disadvantages to consider when using Case-Control?

* Confounding occurs when the elements of the study design invalidate the result. It is usually unintentional. It is important to avoid confounding, which can happen in a few ways within Case-Control studies. This explains why it is lower in the hierarchy of evidence, superior only to Case Studies.

What does a strong Case-Control study look like?

A strong study will have:

  • Well-matched controls, similar background without being so similar that they are likely to end up with the same health issue (this can be easier said than done since the risk factors are unknown). 
  • Detailed medical histories are available, reducing the emphasis on a patient’s unreliable recall of their potential exposures. 

What are the pitfalls to look for?

  • Poorly matched or over-matched controls.  Poorly matched means that not enough factors are similar between the Case and Control. E.g. age, gender, geography. Over-matched conversely means that so many things match (age, occupation, geography, health habits) that in all likelihood the Control group will also end up with the same health issue! Either of these situations could cause the study to become ineffective. 
  • Selection bias: Selection of Controls is biased. E.g. All Controls are in the hospital, so they’re likely already sick, they’re not a true sample of the wider population. 
  • Cases include persons showing early symptoms who never ended up having the illness. 

Critical appraisal tools 

To assist with critically appraising case control studies there are some tools / checklists you can use.

CASP - Case Control Checklist

JBI – Critical appraisal checklist for case control studies

CEBMA – Centre for Evidence Based Management  – Critical appraisal questions (focus on leadership and management)

STROBE - Observational Studies checklists includes Case control

SIGN - Case-Control Studies Checklist

NCCEH - Critical Appraisal of a Case Control Study for environmental health

Real World Examples

Smoking and carcinoma of the lung; preliminary report

  • Doll, R., & Hill, A. B. (1950). Smoking and carcinoma of the lung; preliminary report.  British Medical Journal ,  2 (4682), 739–748. Retrieved from  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2038856/
  • Key Case-Control study linking tobacco smoking with lung cancer
  • Notes a marked increase in incidence of Lung Cancer disproportionate to population growth.
  • 20 London Hospitals contributed current Cases of lung, stomach, colon and rectum cancer via admissions, house-physician and radiotherapy diagnosis, non-cancer Controls were selected at each hospital of the same-sex and within 5 year age group of each.
  • 1732 Cases and 743 Controls were interviewed for social class, gender, age, exposure to urban pollution, occupation and smoking habits.
  • It was found that continued smoking from a younger age and smoking a greater number of cigarettes correlated with incidence of lung cancer.

Anticholinergic drugs and risk of dementia: case-control study

  • Richardson, K., Fox, C., Maidment, I., Steel, N., Loke, Y. K., Arthur, A., . . . Savva, G. M. (2018). Anticholinergic drugs and risk of dementia: case-control study. BMJ , 361, k1315. Retrieved from  http://www.bmj.com/content/361/bmj.k1315.abstract .
  • A recent study linking the duration and level of exposure to Anticholinergic drugs and subsequent onset of dementia.
  • Anticholinergic Cognitive Burden (ACB) was estimated in various drugs, the higher the exposure (measured as the ACB score) the greater likeliness of onset of dementia later in life.
  • Antidepressant, urological, and antiparkinson drugs with an ACB score of 3 increased the risk of dementia. Gastrointestinal drugs with an ACB score of 3 were not strongly linked with onset of dementia.
  • Tricyclic antidepressants such as Amitriptyline have an ACB score of 3 and are an example of a common area of concern.

Omega-3 deficiency associated with perinatal depression: Case-Control study 

  • Rees, A.-M., Austin, M.-P., Owen, C., & Parker, G. (2009). Omega-3 deficiency associated with perinatal depression: Case control study. Psychiatry Research , 166(2), 254-259. Retrieved from  http://www.sciencedirect.com/science/article/pii/S0165178107004398 .
  • During pregnancy women lose Omega-3 polyunsaturated fatty acids to the developing foetus.
  • There is a known link between Omgea-3 depletion and depression
  • Sixteen depressed and 22 non-depressed women were recruited during their third trimester
  • High levels of Omega-3 were associated with significantly lower levels of depression.
  • Women with low levels of Omega-3 were six times more likely to be depressed during pregnancy.

References and Further Reading

Doll, R., & Hill, A. B. (1950). Smoking and carcinoma of the lung; preliminary report. British Medical Journal, 2(4682), 739–748. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2038856/

Greenhalgh, Trisha. How to Read a Paper: the Basics of Evidence-Based Medicine, John Wiley & Sons, Incorporated, 2014. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/deakin/detail.action?docID=1642418 .

Himmelfarb Health Sciences Library. (2019). Study Design 101: Case-Control Study. Retrieved from https://himmelfarb.gwu.edu/tutorials/studydesign101/casecontrols.cfm   

Hoffmann, T., Bennett, S., & Del Mar, C. (2017). Evidence-Based Practice Across the Health Professions (Third edition. ed.): Elsevier. 

Lewallen, S., & Courtright, P. (1998). Epidemiology in practice: case-control studies. Community Eye Health, 11(28), 57.  https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1706071/  

Pelham, B. W. a., & Blanton, H. (2013). Conducting research in psychology : measuring the weight of smoke /Brett W. Pelham, Hart Blanton (Fourth edition. ed.): Wadsworth Cengage Learning. 

Rees, A.-M., Austin, M.-P., Owen, C., & Parker, G. (2009). Omega-3 deficiency associated with perinatal depression: Case control study. Psychiatry Research, 166(2), 254-259. Retrieved from http://www.sciencedirect.com/science/article/pii/S0165178107004398

Richardson, K., Fox, C., Maidment, I., Steel, N., Loke, Y. K., Arthur, A., … Savva, G. M. (2018). Anticholinergic drugs and risk of dementia: case-control study. BMJ, 361, k1315. Retrieved from http://www.bmj.com/content/361/bmj.k1315.abstract

Statistics How To. (2019). Case-Control Study: Definition, Real Life Examples. Retrieved from https://www.statisticshowto.com/case-control-study/  

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The clinical and neuroimaging differences between vascular parkinsonism and Parkinson's disease: a case-control study

Affiliations.

  • 1 Department of Neurology, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
  • 2 Department of Radiology, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
  • 3 Department of Neurology, Faculty of Medicine, Ain Shams University, Cairo, Egypt. [email protected].
  • PMID: 38321372
  • PMCID: PMC10845551
  • DOI: 10.1186/s12883-024-03556-9

Background: Parkinson's disease (PD) and vascular parkinsonism (VaP) have highly overlapping phenotypes, and different prognosis. This study comprehensively investigated the clinical, brain MRI and transcranial sonography differences between VaP and PD.

Methods: Forty-eight patients with PD, 27 patients with VaP, and 29 healthy controls were compared. All patients were assessed using the MDS-UPDRS, Berg Balance Scale (BBS), Ten-Meter Walking Test (10-MWT), Time Up and Go Test, and Non-Motor Symptoms Scale. Beck Depression Inventory, PD questionnaire- 39, international urine incontinence scale, cognitive assessment scales, MRI brain and transcranial colour-coded doppler. The study was registered on clinical-Trial.gov ( NCT04308135 ) on 03/12/2020.

Results: VaP patients showed significantly older age of onset, shorter disease duration, lower drug doses and levodopa responsiveness, higher On and Off axial scores, On and Off BBS, higher On scores for PIGD, rigidity, bradykinesia and total motor MDS-UPDRS, lower On and Off tremor, lower-half predominance, lower asymmetrical presentation and symmetric index than PD patients. VaP patients had worse non-motor symptoms Scale (NMSS) than controls except for perceptual problems/hallucinations but better symptoms than PD patients except for urinary dysfunction. Quality of life (QoL) was impaired in VaP patients and was correlated with motor function and NMSs. The VaP group had significantly higher white matter lesions and brain atrophy, with lower hyperechogenicity of the substantia nigra and more impaired cerebral vascular resistance and vasoreactivity than the PD group.

Conclusions: VaP has a characteristic motor and non-motor profile, with impaired QoL, white matter, and transcranial sonography abnormalities that differentiate it from PD. Further studies are warranted to explore the role of vascular lesions in the pathogenesis of VaP.

Trial registration: The registered identifier NCT04308135 on clinical-Trial.gov. Registered on 03/12/2020.

Keywords: Brain MRI; Non-motor; Parkinson’s disease; Quality of life; TCCD; Vascular parkinsonism.

© 2024. The Author(s).

  • Case-Control Studies
  • Parkinson Disease*
  • Postural Balance
  • Quality of Life / psychology
  • Time and Motion Studies
  • Ultrasonography, Doppler, Transcranial

Associated data

  • ClinicalTrials.gov/NCT04308135

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  • Indian J Dermatol
  • v.61(2); Mar-Apr 2016

Methodology Series Module 2: Case-control Studies

Maninder singh setia.

Epidemiologist, MGM Institute of Health Sciences, Navi Mumbai, Maharashtra, India

Case-Control study design is a type of observational study. In this design, participants are selected for the study based on their outcome status. Thus, some participants have the outcome of interest (referred to as cases), whereas others do not have the outcome of interest (referred to as controls). The investigator then assesses the exposure in both these groups. The investigator should define the cases as specifically as possible. Sometimes, definition of a disease may be based on multiple criteria; thus, all these points should be explicitly stated in case definition. An important aspect of selecting a control is that they should be from the same ‘study base’ as that of the cases. We can select controls from a variety of groups. Some of them are: General population; relatives or friends; and hospital patients. Matching is often used in case-control control studies to ensure that the cases and controls are similar in certain characteristics, and it is a useful technique to increase the efficiency of the study. Case-Control studies can usually be conducted relatively faster and are inexpensive – particularly when compared with cohort studies (prospective). It is useful to study rare outcomes and outcomes with long latent periods. This design is not very useful to study rare exposures. Furthermore, they may also be prone to certain biases – selection bias and recall bias.

Introduction

Case-Control study design is a type of observational study design. In an observational study, the investigator does not alter the exposure status. The investigator measures the exposure and outcome in study participants, and studies their association.

In a case-control study, participants are selected for the study based on their outcome status. Thus, some participants have the outcome of interest (referred to as cases), whereas others do not have the outcome of interest (referred to as controls). The investigator then assesses the exposure in both these groups. Thus, by design, in a case-control study the outcome has to occur in some of the participants that have been included in the study.

As seen in Figure 1 , at the time of entry into the study (sampling of participants), some of the study participants have the outcome (cases) and others do not have the outcome (controls). During the study procedures, we will examine the exposure of interest in cases as well as controls. We will then study the association between the exposure and outcome in these study participants.

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Example of a case-control study

Examples of Case-Control Studies

Smoking and lung cancer study.

In their landmark study, Doll and Hill (1950) evaluated the association between smoking and lung cancer. They included 709 patients of lung carcinoma (defined as cases). They also included 709 controls from general medical and surgical patients. The selected controls were similar to the cases with respect to age and sex. Thus, they included 649 males and 60 females in cases as well as controls.

They found that only 0.3% of males were non-smokers among cases. However, the proportion of non-smokers among controls was 4.2%; the different was statistically significant ( P = 0.00000064). Similarly they found that about 31.7% of the female were non-smokers in cases compared with 53.3% in controls; this difference was also statistically significant (0.01< p <0.02).

Melanoma and tanning (Lazovic et al ., 2010)

The authors conducted a case-control study to study the association between melanoma and tanning. The 1167 cases - individuals with invasive cutaneous melanoma – were selected from Minnesota Cancer Surveillance System. The 1101 controls were selected randomly from Minnesota State Driver's License list; they were matched for age (+/- 5 years) and sex.

The data were collected by self administered questionnaires and telephone interviews. The investigators assessed the use of tanning devices (using photographs), number of years, and frequency of use of these devices. They also collected information on other variables (such as sun exposure; presence of freckles and moles; and colour of skin, hair, among other exposures.

They found that melanoma was higher in individuals who used UVB enhances and primarily UVA-emitting devices. The risk of melanoma also increased with increase in years of use, hours of use, and sessions.

Risk factors for erysipelas (Pitché et al, 2015)

Pitché et al (2015) conducted a case-control study to assess the factors associated with leg erysipelas in sub-Saharan Africa. This was a multi-centre study; the cases and controls were recruited from eight countries in sub-Saharan Africa.

They recruited cases of acute leg cellulitis in these eight countries. They recruited two controls for each case; these were matched for age (+/- 5 years) and sex. Thus, the final study has 364 cases and 728 controls. They found that leg erysipelas was associated with obesity, lympoedema, neglected traumatic wound, toe-web intertrigo, and voluntary cosmetic depigmentation.

We have provided details of all the three studies in the bibliography. We strongly encourage the readers to read the papers to understand some practical aspects of case-control studies.

Selection of Cases and Controls

Selection of cases and controls is an important part of this design. Wacholder and colleagues (1992 a, b, and c) have published wonderful manuscripts on design and conduct of case-control of studies in the American Journal of Epidemiology. The discussion in the next few sections is based on these manuscripts.

Selection of case

The investigator should define the cases as specifically as possible. Sometimes, definition of a disease may be based on multiple criteria; thus, all these points should be explicitly stated in case definition.

For example, in the above mentioned Melanoma and Tanning study, the researchers defined their population as any histologic variety of invasive cutaneous melanoma. However, they added another important criterion – these individuals should have a driver's license or State identity card. This probably is not directly related to the clinic condition, so why did they add this criterion? We will discuss this in detail in the next few paragraphs.

Selection of a control

The next important point in designing a case-control study is the selection of control patients.

In fact, Wacholder and colleagues have extensively discussed aspects of design of case control studies and selection of controls in their article.

According to them, an important aspect of selecting a control is that they should be from the same ‘study base’ as that of the cases. Thus, the pool of population from which the cases and controls will be enrolled should be same. For instance, in the Tanning and Melanoma study, the researchers recruited cases from Minnesota Cancer Surveillance System; however, it was also required that these cases should either have a State identity card or Driver's license. This was important since controls were randomly selected from Minnesota State Driver's license list (this also included the list of individuals who have the State identity card).

Another important aspect of a case-control study is that we should measure the exposure similarly in cases and controls. For instance, if we design a research protocol to study the association between metabolic syndrome (exposure) and psoriasis (outcome), we should ensure that we use the same criteria (clinically and biochemically) for evaluating metabolic syndrome in cases and controls. If we use different criteria to measure the metabolic syndrome, then it may cause information bias.

Types of Controls

We can select controls from a variety of groups. Some of them are: General population; relatives or friends; or hospital patients.

Hospital controls

An important source of controls is patients attending the hospital for diseases other than the outcome of interest. These controls are easy to recruit and are more likely to have similar quality of medical records.

However, we have to be careful while recruiting these controls. In the above example of metabolic syndrome and psoriasis, we recruit psoriasis patients from the Dermatology department of the hospital as controls. We recruit patients who do not have psoriasis and present to the Dermatology as controls. Some of these individuals have presented to the Dermatology department with tinea pedis. Do we recruit these individuals as controls for the study? What is the problem if we recruit these patients? Some studies have suggested that diabetes mellitus and obesity are predisposing factors for tinea pedis. As we know, fasting plasma glucose of >100 mg/dl and raised trigylcerides (>=150 mg/dl) are criteria for diagnosis of metabolic syndrome. Thus, it is quite likely that if we recruit many of these tinea pedis patients, the exposure of interest may turn out to be similar in cases and controls; this exposure may not reflect the truth in the population.

Relative and friend controls

Relative controls are relatively easy to recruit. They can be particularly useful when we are interested in trying to ensure that some of the measurable and non-measurable confounders are relatively equally distributed in cases and controls (such as home environment, socio-economic status, or genetic factors).

Another source of controls is a list of friends referred by the cases. These controls are easy to recruit and they are also more likely to be similar to the cases in socio-economic status and other demographic factors. However, they are also more likely to have similar behaviours (alcohol use, smoking etc.); thus, it may not be prudent to use these as controls if we want to study the effect of these exposures on the outcome.

Population controls

These controls can be easily conducted the list of all individuals is available. For example, list from state identity cards, voter's registration list, etc., In the Tanning and melanoma study, the researchers used population controls. They were identified from Minnesota state driver's list.

We may have to use sampling methods (such as random digit dialing or multistage sampling methods) to recruit controls from the population. A main advantage is that these controls are likely to satisfy the ‘study-base’ principle (described above) as suggested by Wacholder and colleagues. However, they can be expensive and time consuming. Furthermore, many of these controls will not be inclined to participate in the study; thus, the response rate may be very low.

Matching in a Case-Control Study

Matching is often used in case-control control studies to ensure that the cases and controls are similar in certain characteristics. For example, in the smoking and lung cancer study, the authors selected controls that were similar in age and sex to carcinoma cases. Matching is a useful technique to increase the efficiency of study.

’Individual matching’ is one common technique used in case-control study. For example, in the above mentioned metabolic syndrome and psoriasis, we can decide that for each case enrolled in the study, we will enroll a control that is matched for sex and age (+/- 2 years). Thus, if 40 year male patient with psoriasis is enrolled for the study as a case, we will enroll a 38-42 year male patient without psoriasis (and who will not be excluded for other reason) as controls.

If the study has used ‘individual matching’ procedures, then the data should also reflect the same. For instance, if you have 45 males among cases, you should also have 45 males among controls. If you show 60 males among controls, you should explain the discrepancy.

Even though matching is used to increase the efficiency in case-control studies, it may have its own problems. It may be difficult to fine the exact matching control for the study; we may have to screen many potential enrollees before we are able to recruit one control for each case recruited. Thus, it may increase the time and cost of the study.

Nonetheless, matching may be useful to control for certain types of confounders. For instance, environment variables may be accounted for by matching controls for neighbourhood or area of residence. Household environment and genetic factors may be accounted for by enrolling siblings as controls.

If we use controls from the past (time period when cases did not occur), then the controls are sometimes referred to historic controls. Such controls may be recruited from past hospital records.

Strengths of a Case-Control Study

  • Case-Control studies can usually be conducted relatively faster and are inexpensive – particularly when compared with cohort studies (prospective)
  • It is useful to study rare outcomes and outcomes with long latent periods. For example, if we wish to study the factors associated with melanoma in India, it will be useful to conduct a case-control study. We will recruit cases of melanoma as cases in one study site or multiple study sites. If we were to conduct a cohort study for this research question, we may to have follow individuals (with the exposure under study) for many years before the occurrence of the outcome
  • It is also useful to study multiple exposures in the same outcome. For example, in the metabolic syndrome and psoriasis study, we can study other factors such as Vitamin D levels or genetic markers
  • Case-control studies are useful to study the association of risk factors and outcomes in outbreak investigations. For instance, Freeman and colleagues (2015) in a study published in 2015 conducted a case-control study to evaluate the role of proton pump inhibitors in an outbreak of non-typhoidal salmonellosis.

Limitations of a Case-control Study

  • The design, in general, is not useful to study rare exposures. It may be prudent to conduct a cohort study for rare exposures

Since the investigator chooses the number of cases and controls, the proportion of cases may not be representative of the proportion in the population. For instance if we choose 50 cases of psoriasis and 50 controls, the prevalence of proportion of psoriasis cases in our study will be 50%. This is not true prevalence. If we had chosen 50 cases of psoriasis and 100 controls, then the proportion of the cases will be 33%.

  • The design is not useful to study multiple outcomes. Since the cases are selected based on the outcome, we can only study the association between exposures and that particular outcome
  • Sometimes the temporality of the exposure and outcome may not be clearly established in case-control studies
  • The case-control studies are also prone to certain biases

If the cases and controls are not selected similarly from the study base, then it will lead to selection bias.

  • Odds Ratio: We are able to calculate the odds ratios (OR) from a case-control study. Since we are not able to measure incidence data in case-control study, an odds ratio is a reasonable measure of the relative risk (under some assumptions). Additional details about OR will be discussed in the biostatistics section.

The OR in the above study is 3.5. Since the OR is greater than 1, the outcome is more likely in those exposed (those who are diagnosed with metabolic syndrome) compared with those who are not exposed (those who do are not diagnosed with metabolic syndrome). However, we will require confidence intervals to comment on further interpretation of the OR (This will be discussed in detail in the biostatistics section).

  • Other analysis : We can use logistic regression models for multivariate analysis in case-control studies. It is important to note that conditional logistic regressions may be useful for matched case-control studies.

Calculating an Odds Ratio (OR)

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Hypothetical study of metabolic syndrome and psoriasis

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Additional Points in A Case-Control Study

How many controls can i have for each case.

The most optimum case-to-control ratio is 1:1. Jewell (2004) has suggested that for a fixed sample size, the chi square test for independence is most powerful if the number of cases is same as the number of controls. However, in many situations we may not be able recruit a large number of cases and it may be easier to recruit more controls for the study. It has been suggested that we can increase the number of controls to increase statistical power (if we have limited number of cases) of the study. If data are available at no extra cost, then we may recruit multiple controls for each case. However, if it is expensive to collect exposure and outcome information from cases and controls, then the optimal ratio is 4 controls: 1 case. It has been argued that the increase in statistical power may be limited with additional controls (greater than four) compared with the cost involved in recruiting them beyond this ratio.

I have conducted a randomised controlled trial. I have included a group which received the intervention and another group which did not receive the intervention. Can I call this a case-control study?

A randomised controlled trial is an experimental study. In contrast, case-control studies are observational studies. These are two different groups of studies. One should not use the word case-control study for a randomised controlled trial (even though you have a control group in the study). Every study with a control group is not a case-control study. For a study to be classified as a case-control study, the study should be an observational study and the participants should be recruited based on their outcome status (some have the disease and some do not).

Should I call case-control studies prospective or retrospective studies?

In ‘The Dictionary of Epidemiology’ by Porta (2014), the authors have suggested that even though the term ‘retrospective’ was used for case-control studies, the study participants are often recruited prospectively. In fact, the study on risk factors for erysipelas (Pitché et al ., 2015) was a prospective case case-control study. Thus, it is important to remember that the nature of the study (case-control or cohort) depends on the sampling method. If we sample the study participants based on exposure and move towards the outcome, it is a cohort study. However, if we sample the participants based on the outcome (some with outcome and some do not) and study the exposures in both these groups, it is a case-control study.

In case-control studies, participants are recruited on the basis of disease status. Thus, some of participants have the outcome of interest (referred to as cases), whereas others do not have the outcome of interest (referred to as controls). The investigator then assesses the exposure in both these groups. Case-control studies are less expensive and quicker to conduct (compared with prospective cohort studies at least). The measure of association in this type of study is an odds ratio. This type of design is useful for rare outcomes and those with long latent periods. However, they may also be prone to certain biases – selection bias and recall bias.

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  • Proton pump inhibitors and the risk of inflammatory bowel disease: a Mendelian randomisation study
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  • Hongjin An 1 ,
  • Min Zhong 1 ,
  • http://orcid.org/0000-0002-5736-1283 Huatian Gan 2 , 3
  • 1 Department of Gastroenterology and Hepatology, West China Hospital, Sichuan University , Chengdu , China
  • 2 Department of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University , Chengdu , China
  • 3 Department of Gastroenterology and Laboratory of Inflammatory Bowel Disease, the Center for Inflammatory Bowel Disease, Clinical Institute of Inflammation and Immunology, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University , Chengdu , China
  • Correspondence to Dr Huatian Gan, West China Hospital of Sichuan University, Chengdu, Sichuan, China; ganhuatian123{at}163.com

https://doi.org/10.1136/gutjnl-2024-331904

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  • INFLAMMATORY BOWEL DISEASE

We read with great interest the population-based cohort study by Abrahami D et al , 1 in which they found that the use of proton pump inhibitors (PPIs) was not associated with an increased risk of inflammatory bowel disease (IBD). However, the assessment of causality in observational studies is often challenging due to the presence of multiple confounding factors. The existence of a causal relationship between PPIs and IBD remains unclear at present. Mendelian randomisation (MR) is a method of generating more reliable evidence using exposure-related genetic variants to assess causality, limiting the bias caused by confounders. 2 Therefore, we used a two-sample MR analysis to investigate the association between the use of PPIs and IBD including Crohn’s disease (CD) and ulcerative colitis (UC).

Supplemental material

Here, we mainly used the inverse-variance weighted 8 method for MR analysis with weighted median, 9 MR-Egger 10 and MR-PRESSO 5 as complementary approaches. Furthermore, we applied a series of sensitivity analyses to ensure the robustness of our results, with Cochran’s Q test to assess heterogeneity and the intercept of an MR-Egger regression to assess horizontal pleiotropy. The genetic prediction of omeprazole, esomeprazole, lansoprazole and rabeprazole use, as depicted in figure 1 , demonstrated no significant association with an increased risk of IBD after excluding pleiotropic SNPs (omeprazole, OR, 1.05; 95% CI, 0.88 to 1.25; p=0.587; esomeprazole, OR, 0.99; 95% CI, 0.92 to 1.07; p=0.865; lansoprazole, OR, 1.06; 95% CI, 0.89 to 1.26; p=0.537; and rabeprazole, OR, 1.00; 95% CI, 0.95 to 1.04; p=0.862). The IBD subtype analyses also did not reveal any evidence of an increased risk of CD or UC associated with the use of PPIs ( figure 1 ). These findings were robustly confirmed through complementary approaches employing rigorous methodologies that consistently yielded similar point estimates ( figure 1 ). Further sensitivity analyses showed the absence of heterogeneity (All P heterogeneity >0.05) and pleiotropy (All P pleiotropy >0.05), again demonstrating the robustness of the conclusions ( figure 1 ).

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Mendelian randomisation estimates the associations between the use of different types of proton pump inhibitors and inflammatory bowel disease. IBD, inflammatory bowel disease; CD, Crohn’s disease; UC, ulcerative colitis; PPIs, proton pump inhibitors; IVW, inverse-variance weighted; MR, Mendelian randomisation.

In conclusion, the MR results corroborate Abrahami D et al ’s findings that PPIs were not associated with an increased risk of IBD. Nonetheless, further research is needed to elucidate the effects of more types, drug dosage, frequency and duration on IBD.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

  • Abrahami D ,
  • Pradhan R ,
  • Yin H , et al
  • Kathiresan S
  • Fang H , et al
  • van Sommeren S ,
  • Huang H , et al
  • Verbanck M ,
  • Neale B , et al
  • Tilling K ,
  • Davey Smith G
  • Brion M-JA ,
  • Shakhbazov K ,
  • Visscher PM
  • Burgess S ,
  • Timpson NJ , et al
  • Davey Smith G ,
  • Haycock PC , et al

Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

  • Data supplement 1

HA and MZ contributed equally.

Contributors All authors conceived and designed the study. HA and MZ did the statistical analyses and wrote the manuscript. HG revised the manuscript and is the guarantor. HA and MZ have contributed equally to this study.

Funding The present work was supported by the National Natural Science Foundation of China (No. 82070560) and 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan (No. ZYGD23013).

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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Reproductive rights in America

Research at the heart of a federal case against the abortion pill has been retracted.

Selena Simmons-Duffin

Selena Simmons-Duffin

case control study or

The Supreme Court will hear the case against the abortion pill mifepristone on March 26. It's part of a two-drug regimen with misoprostol for abortions in the first 10 weeks of pregnancy. Anna Moneymaker/Getty Images hide caption

The Supreme Court will hear the case against the abortion pill mifepristone on March 26. It's part of a two-drug regimen with misoprostol for abortions in the first 10 weeks of pregnancy.

A scientific paper that raised concerns about the safety of the abortion pill mifepristone was retracted by its publisher this week. The study was cited three times by a federal judge who ruled against mifepristone last spring. That case, which could limit access to mifepristone throughout the country, will soon be heard in the Supreme Court.

The now retracted study used Medicaid claims data to track E.R. visits by patients in the month after having an abortion. The study found a much higher rate of complications than similar studies that have examined abortion safety.

Sage, the publisher of the journal, retracted the study on Monday along with two other papers, explaining in a statement that "expert reviewers found that the studies demonstrate a lack of scientific rigor that invalidates or renders unreliable the authors' conclusions."

It also noted that most of the authors on the paper worked for the Charlotte Lozier Institute, the research arm of anti-abortion lobbying group Susan B. Anthony Pro-Life America, and that one of the original peer reviewers had also worked for the Lozier Institute.

The Sage journal, Health Services Research and Managerial Epidemiology , published all three research articles, which are still available online along with the retraction notice. In an email to NPR, a spokesperson for Sage wrote that the process leading to the retractions "was thorough, fair, and careful."

The lead author on the paper, James Studnicki, fiercely defends his work. "Sage is targeting us because we have been successful for a long period of time," he says on a video posted online this week . He asserts that the retraction has "nothing to do with real science and has everything to do with a political assassination of science."

He says that because the study's findings have been cited in legal cases like the one challenging the abortion pill, "we have become visible – people are quoting us. And for that reason, we are dangerous, and for that reason, they want to cancel our work," Studnicki says in the video.

In an email to NPR, a spokesperson for the Charlotte Lozier Institute said that they "will be taking appropriate legal action."

Role in abortion pill legal case

Anti-abortion rights groups, including a group of doctors, sued the federal Food and Drug Administration in 2022 over the approval of mifepristone, which is part of a two-drug regimen used in most medication abortions. The pill has been on the market for over 20 years, and is used in more than half abortions nationally. The FDA stands by its research that finds adverse events from mifepristone are extremely rare.

Judge Matthew Kacsmaryk, the district court judge who initially ruled on the case, pointed to the now-retracted study to support the idea that the anti-abortion rights physicians suing the FDA had the right to do so. "The associations' members have standing because they allege adverse events from chemical abortion drugs can overwhelm the medical system and place 'enormous pressure and stress' on doctors during emergencies and complications," he wrote in his decision, citing Studnicki. He ruled that mifepristone should be pulled from the market nationwide, although his decision never took effect.

case control study or

Matthew Kacsmaryk at his confirmation hearing for the federal bench in 2017. AP hide caption

Matthew Kacsmaryk at his confirmation hearing for the federal bench in 2017.

Kacsmaryk is a Trump appointee who was a vocal abortion opponent before becoming a federal judge.

"I don't think he would view the retraction as delegitimizing the research," says Mary Ziegler , a law professor and expert on the legal history of abortion at U.C. Davis. "There's been so much polarization about what the reality of abortion is on the right that I'm not sure how much a retraction would affect his reasoning."

Ziegler also doubts the retractions will alter much in the Supreme Court case, given its conservative majority. "We've already seen, when it comes to abortion, that the court has a propensity to look at the views of experts that support the results it wants," she says. The decision that overturned Roe v. Wade is an example, she says. "The majority [opinion] relied pretty much exclusively on scholars with some ties to pro-life activism and didn't really cite anybody else even or really even acknowledge that there was a majority scholarly position or even that there was meaningful disagreement on the subject."

In the mifepristone case, "there's a lot of supposition and speculation" in the argument about who has standing to sue, she explains. "There's a probability that people will take mifepristone and then there's a probability that they'll get complications and then there's a probability that they'll get treatment in the E.R. and then there's a probability that they'll encounter physicians with certain objections to mifepristone. So the question is, if this [retraction] knocks out one leg of the stool, does that somehow affect how the court is going to view standing? I imagine not."

It's impossible to know who will win the Supreme Court case, but Ziegler thinks that this retraction probably won't sway the outcome either way. "If the court is skeptical of standing because of all these aforementioned weaknesses, this is just more fuel to that fire," she says. "It's not as if this were an airtight case for standing and this was a potentially game-changing development."

Oral arguments for the case, Alliance for Hippocratic Medicine v. FDA , are scheduled for March 26 at the Supreme Court. A decision is expected by summer. Mifepristone remains available while the legal process continues.

  • Abortion policy
  • abortion pill
  • judge matthew kacsmaryk
  • mifepristone
  • retractions
  • Abortion rights
  • Supreme Court

Study Design 101: Case Control Study

  • Case Report
  • Case Control Study
  • Cohort Study
  • Randomized Controlled Trial
  • Practice Guideline
  • Systematic Review
  • Meta-Analysis
  • Helpful Formulas
  • Finding Specific Study Types

A study that compares patients who have a disease or outcome of interest (cases) with patients who do not have the disease or outcome (controls), and looks back retrospectively to compare how frequently the exposure to a risk factor is present in each group to determine the relationship between the risk factor and the disease.

Case control studies are observational because no intervention is attempted and no attempt is made to alter the course of the disease. The goal is to retrospectively determine the exposure to the risk factor of interest from each of the two groups of individuals: cases and controls. These studies are designed to estimate odds.

Case control studies are also known as "retrospective studies" and "case-referent studies."

  • Good for studying rare conditions or diseases
  • Less time needed to conduct the study because the condition or disease has already occurred
  • Lets you simultaneously look at multiple risk factors
  • Useful as initial studies to establish an association
  • Can answer questions that could not be answered through other study designs

Disadvantages

  • Retrospective studies have more problems with data quality because they rely on memory and people with a condition will be more motivated to recall risk factors (also called recall bias).
  • Not good for evaluating diagnostic tests because it's already clear that the cases have the condition and the controls do not
  • It can be difficult to find a suitable control group

Design pitfalls to look out for

Care should be taken to avoid confounding, which arises when an exposure and an outcome are both strongly associated with a third variable. Controls should be subjects who might have been cases in the study but are selected independent of the exposure. Cases and controls should also not be "over-matched."

Is the control group appropriate for the population? Does the study use matching or pairing appropriately to avoid the effects of a confounding variable? Does it use appropriate inclusion and exclusion criteria?

Fictitious Example

There is a suspicion that zinc oxide, the white non-absorbent sunscreen traditionally worn by lifeguards is more effective at preventing sunburns that lead to skin cancer than absorbent sunscreen lotions. A case-control study was conducted to investigate if exposure to zinc oxide is a more effective skin cancer prevention measure. The study involved comparing a group of former lifeguards that had developed cancer on their cheeks and noses (cases) to a group of lifeguards without this type of cancer (controls) and assess their prior exposure to zinc oxide or absorbent sunscreen lotions.

This study would be retrospective in that the former lifeguards would be asked to recall which type of sunscreen they used on their face and approximately how often. This could be either a matched or unmatched study, but efforts would need to be made to ensure that the former lifeguards are of the same average age, and lifeguarded for a similar number of seasons and amount of time per season.

Real-life Examples

Boubekri, M., Cheung, I., Reid, K., Wang, C., & Zee, P. (2014). Impact of windows and daylight exposure on overall health and sleep quality of office workers: a case-control pilot study. Journal of Clinical Sleep Medicine : JCSM : Official Publication of the American Academy of Sleep Medicine, 10 (6), 603-611. https://doi.org/10.5664/jcsm.3780

This pilot study explored the impact of exposure to daylight on the health of office workers (measuring well-being and sleep quality subjectively, and light exposure, activity level and sleep-wake patterns via actigraphy). Individuals with windows in their workplaces had more light exposure, longer sleep duration, and more physical activity. They also reported a better scores in the areas of vitality and role limitations due to physical problems, better sleep quality and less sleep disturbances.

Togha, M., Razeghi Jahromi, S., Ghorbani, Z., Martami, F., & Seifishahpar, M. (2018). Serum Vitamin D Status in a Group of Migraine Patients Compared With Healthy Controls: A Case-Control Study. Headache, 58 (10), 1530-1540. https://doi.org/10.1111/head.13423

This case-control study compared serum vitamin D levels in individuals who experience migraine headaches with their matched controls. Studied over a period of thirty days, individuals with higher levels of serum Vitamin D was associated with lower odds of migraine headache.

Related Formulas

  • Odds ratio in an unmatched study
  • Odds ratio in a matched study

Related Terms

A patient with the disease or outcome of interest.

Confounding

When an exposure and an outcome are both strongly associated with a third variable.

A patient who does not have the disease or outcome.

Matched Design

Each case is matched individually with a control according to certain characteristics such as age and gender. It is important to remember that the concordant pairs (pairs in which the case and control are either both exposed or both not exposed) tell us nothing about the risk of exposure separately for cases or controls.

Observed Assignment

The method of assignment of individuals to study and control groups in observational studies when the investigator does not intervene to perform the assignment.

Unmatched Design

The controls are a sample from a suitable non-affected population.

Now test yourself!

1. Case Control Studies are prospective in that they follow the cases and controls over time and observe what occurs.

a) True b) False

2. Which of the following is an advantage of Case Control Studies?

a) They can simultaneously look at multiple risk factors. b) They are useful to initially establish an association between a risk factor and a disease or outcome. c) They take less time to complete because the condition or disease has already occurred. d) b and c only e) a, b, and c

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Physics > Fluid Dynamics

Title: precision air flow control via ehd actuator: a co-simulation and control design case study.

Abstract: A Dielectric Barrier Discharge (DBD) plasma actuator for controlling airflow is proposed. It consists of diverging and converging nozzles, two concentric cylinders and an actuator mounted in-between the two cylinders. The actuator employs electrohydrodynamic (EHD) body force to induce an air jet within the air gap between the two cylinders, effectively creating a suction area while passing through the diverging nozzle, due to the Coanda effect. While merging with the air stream inside the inner cylinder, the Coanda jet effectively enhances amplification of the airflow. The outflow rate is measured by a velocity sensor at the outlet and controlled by the plasma actuator. The control strategy is based on the Active Disturbance Rejection Control (ADRC) and compared to the baseline PID controller. The actuator was modelled by seamlessly linking two modeling platforms for a co-simulation study. The CFD simulation of the plasma and airflow was carried out in the COMSOL multi-physics commercial software, and the control was implemented in the Simulink. The DBD plasma model was based on the two-species model of discharge, and the electric body force, calculated from the plasma simulation, was used in the Navier-Stokes equation for the turbulent flow simulation. The plasma-air flow system was analyzed using the input (the actuator voltage) and output (the outlet flow rate) data for the control design. Finally, the performance of the system of air flow control device was tested and discussed in the co-simulation process.

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CDC plans to drop five-day covid isolation guidelines

case control study or

Americans who test positive for the coronavirus no longer need to routinely stay home from work and school for five days under new guidance planned by the Centers for Disease Control and Prevention.

The agency is loosening its covid isolation recommendations for the first time since 2021 to align it with guidance on how to avoid transmitting flu and RSV, according to four agency officials and an expert familiar with the discussions.

CDC officials acknowledged in internal discussions and in a briefing last week with state health officials how much the covid-19 landscape has changed since the virus emerged four years ago, killing nearly 1.2 million people in the United States and shuttering businesses and schools. The new reality — with most people having developed a level of immunity to the virus because of prior infection or vaccination — warrants a shift to a more practical approach, experts and health officials say.

“Public health has to be realistic,” said Michael T. Osterholm, an infectious-disease expert at the University of Minnesota. “In making recommendations to the public today, we have to try to get the most out of what people are willing to do. … You can be absolutely right in the science and yet accomplish nothing because no one will listen to you.”

The CDC plans to recommend that people who test positive for the coronavirus use clinical symptoms to determine when to end isolation. Under the new approach, people would no longer need to stay home if they have been fever-free for at least 24 hours without the aid of medication and their symptoms are mild and improving, according to three agency officials who spoke on the condition of anonymity to share internal discussions.

Here is the current CDC guidance on isolation and precautions for people with covid-19

The federal recommendations follow similar moves by Oregon and California . The White House has yet to sign off on the guidance that the agency is expected to release in April for public feedback, officials said. One agency official said the timing could “move around a bit” until the guidance is finalized.

Work on revising isolation guidance has been underway since last August but was paused in the fall as covid cases rose. CDC director Mandy Cohen sent staff a memo in January that listed “Pan-resp guidance-April” as a bullet point for the agency’s 2024 priorities.

Officials said they recognized the need to give the public more practical guidelines for covid-19, acknowledging that few people are following isolation guidance that hasn’t been updated since December 2021. Back then, health officials cut the recommended isolation period for people with asymptomatic coronavirus from 10 days to five because they worried essential services would be hobbled as the highly transmissible omicron variant sent infections surging. The decision was hailed by business groups and slammed by some union leaders and health experts.

Covid is here to stay. How will we know when it stops being special?

The plan to further loosen isolation guidance when the science around infectiousness has not changed is likely to prompt strong negative reaction from vulnerable groups, including people older than 65, those with weak immune systems and long-covid patients, CDC officials and experts said.

Doing so “sweeps this serious illness under the rug,” said Lara Jirmanus, a clinical instructor at Harvard Medical School and a member of the People’s CDC, a coalition of health-care workers, scientists and advocates focused on reducing the harmful effects of covid-19.

Public health officials should treat covid differently from other respiratory viruses, she said, because it’s deadlier than the flu and increases the risk of developing long-term complications . As many as 7 percent of Americans report having suffered from a slew of lingering covid symptoms, including fatigue, difficulty breathing, brain fog, joint pain and ongoing loss of taste and smell, according to the CDC.

The new isolation recommendations would not apply to hospitals and other health-care settings with more vulnerable populations, CDC officials said.

While the coronavirus continues to cause serious illness, especially among the most vulnerable people, vaccines and effective treatments such as Paxlovid are available. The latest versions of coronavirus vaccines were 54 percent effective at preventing symptomatic infection in adults, according to data released Feb. 1, the first U.S. study to assess how well the shots work against the most recent coronavirus variant. But CDC data shows only 22 percent of adults and 12 percent of children had received the updated vaccine as of Feb. 9, despite data showing the vaccines provide robust protection against serious illness .

Coronavirus levels in wastewater i ndicate that symptomatic and asymptomatic infections remain high. About 20,000 people are still hospitalized — and about 2,300 are dying — every week, CDC data show. But the numbers are falling and are much lower than when deaths peaked in January 2021 when almost 26,000 people died of covid each week and about 115,000 were hospitalized.

The lower rates of hospitalizations were among the reasons California shortened its five-day isolation recommendation last month , urging people to stay home until they are fever-free for 24 hours and their symptoms are mild and improving. Oregon made a similar move last May.

California’s state epidemiologist Erica Pan said the societal disruptions that resulted from strict isolation guidelines also helped spur the change. Workers without sick leave and those who can’t work from home if they or their children test positive and are required to isolate bore a disproportionate burden. Strict isolation requirements can act as a disincentive to test when testing should be encouraged so people at risk for serious illness can get treatment, she said.

Giving people symptom-based guidance, similar to what is already recommended for flu, is a better way to prioritize those most at risk and balance the potential for disruptive impacts on schools and workplaces, Pan said. After Oregon made its change, the state has not experienced any disproportionate increases in community transmission or severity, according to data shared last month with the national association representing state health officials.

California still recommends people with covid wear masks indoors when they are around others for 10 days after testing positive — even if they have no symptoms — or becoming sick. “You may remove your mask sooner than 10 days if you have two sequential negative tests at least one day apart,” the California guidance states.

It’s not clear whether the updated CDC guidance will continue to recommend masking for 10 days.

Health officials from other states told the CDC last week that they are already moving toward isolation guidelines that would treat the coronavirus the same as flu and RSV, with additional precautions for people at high risk, said Anne Zink, an emergency room physician and Alaska’s chief medical officer.

Many other countries, including the United Kingdom, Denmark, Finland, Norway and Australia, made changes to isolation recommendations in 2022. Of 16 countries whose policies California officials reviewed, only Germany and Ireland still recommend isolation for five days, according to a presentation the California public health department gave health officials from other states in January. The Singapore ministry of health, in updated guidance late last year, said residents could “return to normal activities” once coronavirus symptoms resolve.

Even before the Biden administration ended the public health emergency last May, much of the public had moved on from covid-19, with many people having long given up testing and masking, much less isolating when they come down with covid symptoms.

Doctors say the best way for sick people to protect their communities is to mask or avoid unnecessary trips outside the home.

“You see a lot of people with symptoms — you don’t know if they have covid or influenza or RSV — but in all three of those cases, they probably shouldn’t be at Target, coughing, and looking sick,” said Eli Perencevich, an internal medicine professor at the University of Iowa.

Coronavirus: What you need to know

New covid variant: The United States is in the throes of another covid-19 uptick and coronavirus samples detected in wastewater suggests infections could be as rampant as they were last winter. JN.1, the new dominant variant , appears to be especially adept at infecting those who have been vaccinated or previously infected. Here’s how this covid surge compares with earlier spikes .

Covid ER visits rise: Covid-19, flu and RSV are rebounding in the United States ahead of the end-of-year holidays, with emergency room visits for the three respiratory viruses collectively reaching their highest levels since February.

New coronavirus booster: The Centers for Disease Control and Prevention recommends that anyone 6 months or older get an updated coronavirus shot , but the vaccine rollout has seen some hiccups , especially for children . Here’s what you need to know about the new coronavirus vaccines , including when you should get it.

  • CDC plans to drop five-day covid isolation guidelines February 13, 2024 CDC plans to drop five-day covid isolation guidelines February 13, 2024
  • Is this covid surge really the second biggest? Here’s what data shows. January 12, 2024 Is this covid surge really the second biggest? Here’s what data shows. January 12, 2024
  • Covid kills nearly 10,000 in a month as holidays fuel spread, WHO says January 11, 2024 Covid kills nearly 10,000 in a month as holidays fuel spread, WHO says January 11, 2024

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COMMENTS

  1. Case-control study

    A case-control study (also known as case-referent study) is a type of observational study in which two existing groups differing in outcome are identified and compared on the basis of some supposed causal attribute.

  2. What Is a Case-Control Study?

    Case-control studies are a type of observational study often used in fields like medical research, environmental health, or epidemiology. While most observational studies are qualitative in nature, case-control studies can also be quantitative, and they often are in healthcare settings.

  3. Case Control Studies

    A case-control study is a type of observational study commonly used to look at factors associated with diseases or outcomes. [1] The case-control study starts with a group of cases, which are the individuals who have the outcome of interest.

  4. Case Control Studies

    A case-control study is a type of observational study commonly used to look at factors associated with diseases or outcomes. The case-control study starts with a group of cases, which are the individuals who have the outcome of interest.

  5. Case Control Study: Definition, Benefits & Examples

    A case control study is a retrospective, observational study that compares two existing groups. Researchers form these groups based on the existence of a condition in the case group and the lack of that condition in the control group.

  6. Epidemiology in Practice: Case-Control Studies

    A case-control study is designed to help determine if an exposure is associated with an outcome (i.e., disease or condition of interest). In theory, the case-control study can be described simply. First, identify the cases (a group known to have the outcome) and the controls (a group known to be free of the outcome).

  7. A Practical Overview of Case-Control Studies in Clinical Practice

    In a case-control study the researcher identifies a case group and a control group, with and without the outcome of interest. Such a study design is called observational because the researcher does not control the assignment of a subject to one of the groups, unlike in a planned experimental study.

  8. Observational Studies: Cohort and Case-Control Studies

    Cohort studies and case-control studies are two primary types of observational studies that aid in evaluating associations between diseases and exposures. In this review article, we describe these study designs, methodological issues, and provide examples from the plastic surgery literature.

  9. A Practical Overview of Case-Control Studies in Clinical Practice

    In a case-control study the researcher identifies a case group and a control group, with and without the outcome of interest. Such a study design is called observational because the researcher does not control the assignment of a subject to one of the groups, unlike in a planned experimental study. In a

  10. A Practical Overview of Case-Control Studies in Clinical Practice

    Case-control studies are one of the major observational study designs for performing clinical research. The advantages of these study designs over other study designs are that they are relatively quick to perform, economical, and easy to design and implement.

  11. Case Control Study: Definition & Examples

    A case-control study is a research method where two groups of people are compared - those with the condition (cases) and those without (controls). By looking at their past, researchers try to identify what factors might have contributed to the condition in the 'case' group. Definition

  12. What Is a Case-Control Study?

    Case-control studies are a type of observational study often used in fields like medical research, environmental health, or epidemiology. While most observational studies are qualitative in nature, case-control studies can also be quantitative, and they often are in healthcare settings. Case-control studies can be used for both exploratory and ...

  13. Case-control study in medical research: Uses and limitations

    A case-control study can help provide extra insight on data that has already been collected. A case-control study is a way of carrying out a medical investigation to confirm or indicate what is ...

  14. Case Control

    Case control studies are also known as "retrospective studies" and "case-referent studies." Advantages Good for studying rare conditions or diseases Less time needed to conduct the study because the condition or disease has already occurred Lets you simultaneously look at multiple risk factors Useful as initial studies to establish an association

  15. PDF Case-control studies: an efficient study design

    Case-control studies are particularly useful for studying the cause of an outcome that is rare and for studying the effects of prolonged exposure. For example, a case-control study could be used ...

  16. Case-control and Cohort studies: A brief overview

    Case-control studies. Case-control studies are retrospective. They clearly define two groups at the start: one with the outcome/disease and one without the outcome/disease. They look back to assess whether there is a statistically significant difference in the rates of exposure to a defined risk factor between the groups.

  17. Research Design: Case-Control Studies

    A case-control study is one in which cases are compared with controls to identify historical exposures that are significantly associated with a current state or, stated in different words, variables that are significantly associated with caseness. In case-control studies, cases are subjects with a particular characteristic.

  18. Case-control study: comparative studies

    A case-control study is a type of observational study. It looks at 2 sets of participants. One group has the condition you are interested in (the cases) and one group does not have it (the...

  19. LibGuides: Quantitative study designs: Case Control

    Case Control. In a Case-Control study there are two groups of people: one has a health issue (Case group), and this group is "matched" to a Control group without the health issue based on characteristics like age, gender, occupation. In this study type, we can look back in the patient's histories to look for exposure to risk factors that ...

  20. Case-control study

    case-control study, in epidemiology, observational (nonexperimental) study design used to ascertain information on differences in suspected exposures and outcomes between individuals with a disease of interest (cases) and comparable individuals who do not have the disease (controls).

  21. A Practical Overview of Case-Control Studies in Clinical Practice

    In a case-control study the researcher identifies a case group and a control group, with and without the outcome of interest. Such a study design is called observational because the researcher does not control the assignment of a subject to one of the groups, unlike in a planned experimental study.

  22. JCM

    A case-control study was conducted among patients with suspected endometrial cancer, including 2103 women who underwent hysteroscopy at Vila Santa Catarina Hospital-Society, Israelita Albert Einstein, in São Paulo, Brazil, between March 2019 and March 2022. One hundred and fifty-eight patients were excluded due to incorrect indication or ...

  23. The clinical and neuroimaging differences between vascular ...

    This study comprehensively investigated the clinical, brain MRI and transcranial sonography differences between VaP and PD. Methods: Forty-eight patients with PD, 27 patients with VaP, and 29 healthy controls were compared. All patients were assessed using the MDS-UPDRS, Berg Balance Scale (BBS), Ten-Meter Walking Test (10-MWT), Time Up and Go ...

  24. Methodology Series Module 2: Case-control Studies

    Case-control studies are less expensive and quicker to conduct (compared with prospective cohort studies at least). The measure of association in this type of study is an odds ratio. This type of design is useful for rare outcomes and those with long latent periods. However, they may also be prone to certain biases - selection bias and recall ...

  25. Rebuttal to Correspondence on "Exposure to Novel Brominated Flame

    Similar study designs and enrollment criteria were used in other case-control studies. (2−5) Second, our investigation evaluated the relationship between thyroid cancer and exposure to brominated flame retardants and organophosphates; it did not aim to determine the disease's prevalence, which is often the primary goal of cross-sectional ...

  26. Proton pump inhibitors and the risk of inflammatory bowel disease: a

    For this study, different cohort data sources were used for exposure and outcome to avoid sample overlap (online supplemental material). We used summary statistics from the medication use case-control genome-wide association studies conducted among UK Biobank study participants to generate genetic instruments for …

  27. The abortion pill case on its way to the Supreme Court cites a

    That case, which could limit access to mifepristone throughout the country, will soon be heard in the Supreme Court. The now retracted study used Medicaid claims data to track E.R. visits by ...

  28. Research Guides: Study Design 101: Case Control Study

    A case-control study was conducted to investigate if exposure to zinc oxide is a more effective skin cancer prevention measure. The study involved comparing a group of former lifeguards that had developed cancer on their cheeks and noses (cases) to a group of lifeguards without this type of cancer (controls) and assess their prior exposure to ...

  29. [2402.06588] Precision Air Flow Control via EHD Actuator: A Co

    Download a PDF of the paper titled Precision Air Flow Control via EHD Actuator: A Co-simulation and Control Design Case Study, by Afshin Shaygani and 2 other authors. Download PDF HTML (experimental) Abstract: A Dielectric Barrier Discharge (DBD) plasma actuator for controlling airflow is proposed. It consists of diverging and converging ...

  30. CDC plans to drop five-day covid isolation guidelines

    The latest versions of coronavirus vaccines were 54 percent effective at preventing symptomatic infection in adults, according to data released Feb. 1, the first U.S. study to assess how well the ...