Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

  • Knowledge Base

Methodology

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

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.

The only proofreading tool specialized in correcting academic writing - try for free!

The academic proofreading tool has been trained on 1000s of academic texts and by native English editors. Making it the most accurate and reliable proofreading tool for students.

case of study control

Try for free

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

Prevent plagiarism. Run a free check.

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.

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 | definition, uses & examples, what is your plagiarism score.

A Practical Overview of Case-Control Studies in Clinical Practice

Affiliations.

  • 1 Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH; Center for Surgery and Public Health, Brigham and Women's Hospital, Harvard Medical School, Boston, MA. Electronic address: [email protected].
  • 2 Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH; Department of Population and Quantitative Health Sciences, Case Western Reserve University, School of Medicine, Cleveland, OH.
  • 3 Department of Statistics, University of Missouri, Columbia, MO.
  • PMID: 32658653
  • DOI: 10.1016/j.chest.2020.03.009

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. Case-control studies are particularly appropriate for studying disease outbreaks, rare diseases, or outcomes of interest. This article describes several types of case-control designs, with simple graphical displays to help understand their differences. Study design considerations are reviewed, including sample size, power, and measures associated with risk factors for clinical outcomes. Finally, we discuss the advantages and disadvantages of case-control studies and provide a checklist for authors and a framework of considerations to guide reviewers' comments.

Keywords: OR; case-cohort; case-crossover; matching; nested case-control; relative risk.

Copyright © 2020 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Publication types

  • Case-Control Studies*
  • Guidelines as Topic
  • Research Design / standards
  • Research Design / statistics & numerical data*

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 of study control

(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/  

  • << Previous: Randomised Controlled Trial
  • Next: Cross-Sectional Studies >>
  • Last Updated: Jan 17, 2024 11:49 AM
  • URL: https://deakin.libguides.com/quantitative-study-designs

Hirsh Logo

Research Guides@Tufts

  • Hirsh Health Sciences
  • Lilly Music
  • Webster Veterinary
  • Hirsh Health Sciences Library

Study Designs in the Health Sciences

  • Case-Control
  • Introduction
  • Clinical Trials
  • Randomized Controlled Trial (RCT)
  • Systematic Reviews/Meta-Analysis
  • Retrieving Articles by Study Design in PubMed

Case-Control Study

What is a case-control study.

“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.”[1]

Why use this type of study type?

  • Good for studying rare conditions or diseases [1]
  •  Less time needed to conduct the study because the condition or disease has already occurred [1]
  • Lets you simultaneously look at multiple risk factors   [1]
  • Useful as initial studies to establish an association   [1]
  • Can answer questions that could not be answered through other study designs   [1]

Format and features

  •   Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement checklist for case-control studies     [2]

​References

  • Himmelfarb Health Sciences Library (The George Washington University). Study Design 101: Case Control Study 2011;  http://www.gwumc.edu/library/tutorials/studydesign101/casecontrols.html . Accessed March 1, 2013.
  • Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). STROBE checklist for case-control. [2007];  http://www.strobe-statement.org/fileadmin/Strobe/uploads/checklists/STROBE_checklist_v4_case-control.pdf . Accessed March 1, 2013.

A case-control study of readmission to the intensive care unit after cardiac surgery.

Benetis R, Sirvinskas E, Kumpaitiene B, Kinduris S.

Med Sci Monit.  2013 Feb 28; 19:148-52.

Background:  The aim of this study was to identify predictors of repeated admission to the intensive care unit (ICU) of patients who underwent cardiac surgery procedures.

Material and Methods: This retrospective study analyzed 169 patients who underwent isolated coronary artery bypass grafting (CABG) between January 2009 and December 2010. The case group contained 54 patients who were readmitted to the ICU during the same hospitalization and the control group comprised 115 randomly selected patients.

Results: Logistic regression analysis revealed that independent predictors for readmission to the ICU after CABG were: older age of patients (odds ratio [OR] 1.04; CI 1.004-1.08); body mass index (BMI) >30 kg/m2 (OR 2.55; CI 1.31-4.97); EuroSCORE II >3.9% (OR 3.56; CI 1.59-7.98); non-elective surgery (OR 2.85; CI 1.37-5.95); duration of operation >4 h (OR 3.44; CI 1.54-7.69); bypass time >103 min (OR 2.5; CI 1.37-4.57); mechanical ventilation >530 min (OR 3.98; CI 1.82-8.7); and postoperative central nervous system (CNS) disorders (OR 3.95; CI 1.44-10.85). The hospital mortality of patients who were readmitted to the ICU was significantly higher compared to the patients who did not require readmission (17% vs. 3.8%, p=0.025). Conclusions: Identification of patients at risk of ICU readmission should focus on older patients, those who have higher BMI, who underwent non-elective surgery, whose operation time was more than 4 hours, and who have postoperative CNS disorders. Careful optimization of these high-risk patients and caution before discharging them from the ICU may help reduce the rate of ICU readmission, mortality, length of stay, and cost.

  • << Previous: Introduction
  • Next: Clinical Trials >>
  • Last Updated: Dec 26, 2019 11:38 AM
  • URL: https://researchguides.library.tufts.edu/study_design

What Is A Case Control Study?

Julia Simkus

Editor at Simply Psychology

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.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

On This Page:

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?

Print Friendly, PDF & Email

Leave a Comment Cancel reply

You must be logged in to post a comment.

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

Evidence Pyramid - Navigation

  • Meta- Analysis
  • Case Reports
  • << Previous: Case Report
  • Next: Cohort Study >>

Creative Commons License

  • Last Updated: Sep 25, 2023 10:59 AM
  • URL: https://guides.himmelfarb.gwu.edu/studydesign101

GW logo

  • Himmelfarb Intranet
  • Privacy Notice
  • Terms of Use
  • GW is committed to digital accessibility. If you experience a barrier that affects your ability to access content on this page, let us know via the Accessibility Feedback Form .
  • Himmelfarb Health Sciences Library
  • 2300 Eye St., NW, Washington, DC 20037
  • Phone: (202) 994-2850
  • [email protected]
  • https://himmelfarb.gwu.edu

ORIGINAL RESEARCH article

Dynamic changes of serum taurine and the association with gestational diabetes mellitus: a nested case-control study.

Jia Wang&#x;

  • 1 Division of Endocrinology and Metabolism, Department of Obstetrics, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China
  • 2 National Research Institute for Family Planning, Beijing, China
  • 3 National Human Genetic Resources Center, Beijing, China

Objective: There is a lack of risk factors that can effectively identify gestational diabetes mellitus (GDM) in early pregnancy. It is unclear whether serum taurine in the first trimester and dynamic changes have different characteristics in GDM women. Whether these features are associated with the occurrence of GDM has not yet been elucidated. The main objective of this study was to observe the dynamic changes of serum taurine during pregnancy and investigate the relationship between serum taurine levels and GDM in the first and second trimesters.

Methods: This was a nested case-control study in 47 women with GDM and 47 age-matched normoglycemic women. We examined serum taurine at 8-12 weeks’ gestation and 24-28 weeks’ gestation. The serum taurine of the two groups was compared. Multivariable logistic regression analysis was performed to investigate how serum taurine was associated with GDM.

Results: The serum taurine concentration of GDM women was significantly lower than that of normoglycemic women in the first trimester(2.29 vs 3.94 μmol/L, P<0.001). As the pregnancy progressed, serum taurine concentration in normoglycaemic women decreased significantly(3.94 vs 2.47 μmol/L, P<0.001), but not in the GDM group(2.29 vs 2.37 μmol/L, P=0.249), resulting in the disappearance of differences between the two groups(2.47 vs 2.37 μmol/L, P=0.160). After adjustment for pre-pregnancy body mass index(BMI), fasting plasma glucose(FPG), and lipid profiles in the first trimester, the serum taurine concentration in the first trimester was negatively correlated with the risk of GDM(OR=0.017, 95% CI=0.003-0.107, P<0.001). Furthermore, dynamic change of serum taurine showed a significantly positive correlation with the risk of GDM(OR=9.909, 95% CI=3.556-27.610, P<0.001).

Conclusion: Low serum taurine concentration in the first trimester was significantly associated with the development of GDM. As the pregnancy progressed, the association between serum taurine and GDM disappeared in the second trimester, which might be related to the inhibition of taurine transporter(TauT) activity by high glucose.

Introduction

Gestational diabetes mellitus (GDM) is the most common metabolic disease in pregnancy, with an incidence of 9%-25% globally according to the International Diabetes Federation (IDF) ( 1 ). Women with GDM are at an increased risk of gestational hypertension, pre-eclampsia, and cesarean section, as well as long-term risk of type 2 diabetes (T2DM) and cardiovascular disease ( 2 ). Maternal hyperglycemia will increase the risk of large for gestational age(LGA), shoulder dystocia or birth injury, and neonatal hypoglycemia ( 3 ). The offspring of GDM women are at increased long-term risk of obesity, abnormal glucose metabolism, and cardiovascular disease ( 4 ). With the continuous progress in knowledge of GDM, the oral glucose tolerance test (OGTT) at 24-28 gestational weeks was the diagnostic criteria for GDM ( 2 ). Recent studies evaluating maternal glycemia in relation to fetal growth trajectory have confirmed the early impact of maternal glycemia on fetal overgrowth and obesity prior to the diagnosis of standard GDM ( 5 , 6 ). Lifestyle interventions such as dietary counseling or physical activity in the first trimester were demonstrated to effectively reduce the incidence of GDM and its associated adverse pregnancy outcomes ( 7 , 8 ). As a result, it is of great clinical value to identify risk factors for GDM, especially in the first trimester.

Taurine which is the most abundant free amino acid in the human body and the key component of bile acid has many biological effects such as antioxidant, anti-inflammatory, improvement of insulin resistance(IR), neuroprotection, and anti-neurotoxicity ( 9 , 10 ). Taurine can be made endogenous from cysteine or methionine, provided extrinsic from the diet, or affected by gut microbiota ( 11 , 12 ). There was a significant negative correlation between taurine and non-gestational blood glucose, and taurine supplementation was effective in improving diabetes and other chronic metabolic diseases and preventing related complications ( 10 ). A recent study suggested a lower plasma taurine level in the first trimester seemed to be a fair marker of inadequate insulin secretion and to be more closely associated with a higher risk of GDM development in multiparas ( 13 ). However, the dynamic changes in serum taurine from the first to second trimester were unknown.

The main objective of this study was to observe the dynamic changes of serum taurine during pregnancy and investigate the relationship between serum taurine levels and GDM in the first and second trimesters.

Materials and methods

Patient cohorts.

The participants in this nested case-control study were from a prospective cohort study in the Beijing Obstetrics and Gynecology Hospital, Capital Medical University. All pregnant women who intended to give birth in this hospital were enrolled in the cohort study at 8-12 gestational weeks and followed up until delivery. To evaluate the relationship between serum taurine and GDM, we selected eligible subjects from the recruited pregnant women above. Singleton pregnant women aged 18 to 44 years were recruited and only participants with complete clinical information were included in the analysis. Women with hypertension, diabetes, hyperlipidemia, liver or kidney dysfunction, and infectious diseases (hepatitis, pulmonary tuberculosis, etc.) before pregnancy were excluded. A 75-g OGTT was carried out at 24-28 gestational weeks. The diagnosis of GDM was made when any one of the following values was met or exceeded in the 75-g OGTT: 0 h (fasting), 5.1 mmol/L; 1 h, 10.0 mmol/L; and 2 h, 8.5 mmol/L according to ADA criteria ( 14 ). Normoglycaemic women were matched for age ( ± 3 years) to each case of GDM women in the same cohort ( Figure 1 ).

www.frontiersin.org

Figure 1 Flowchart of the included participants in this study.

Clinical measurements and covariates

Anthropometric measurements of participants were completed by trained medical staff at recruitment using a standardized protocol. Clinical data were collected by medical record review. Pre-pregnancy body weight was self-reported. A family history of diabetes was defined as a first-degree relative with T2DM. The fasting plasma glucose(FPG) and lipid profiles, including cholesterol (TC), triglyceride (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL), were determined as described in a previous study ( 15 ).

Taurine examination

Blood samples were collected from participants following an overnight fast at 8-12 weeks and 24-28 weeks, and serum specimens were isolated and stored at -80°C for further examination. The serum taurine levels were examined by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS, Thermo Scientific, USA). First, 100 μL of human serum was briefly added to a 0.5 mL glass centrifuge tube. After centrifugation at 14000 r/min for 5 min, the serum sample was dried under nitrogen at 50°C. Then, 60 μL of N-butyl alcohol and 12 mol/L HCI (95:5, v/v) were added and vortexed for 30 seconds in a seal. After incubation at 65°C for 15 min for derivatization, the derivatized solution was centrifuged, and dried under nitrogen at 50°C again. The residue was reconstituted by adding 100 μL of acetonitrile and water (4:1, v/v), vortexed for 30 seconds, centrifuged at 14000 r/min for 5 min, and injected at 20 μL for LC-MS/MS analysis.

Sample size calculation

The sample size was calculated using the mean and standard deviation of serum taurine in two groups. The test level (α) was 0.05, and the power (1-β) was 0.8. Serum taurine concentrations are 0.6 ± 0.1 mmol/L in diabetic patients and 0.8 ± 0.2 mmol/L in healthy adults ( 16 ). The minimum sample size was 48, and the sample size of this study was 94, which was sufficient according to the sample size calculation.

Data were analyzed using the SPSS 26.0 software. Data with normal distributions were shown as the mean ± standard deviation, and nonnormal distributed data were shown as the median (interquartile range), respectively. T-tests and Wilcoxon tests were used to analyze the differences in continuous variables between the GDM group and the control group. Serum taurine concentrations were also compared by t-test. Categorical variables, including serum taurine levels (categorized into quartiles), were evaluated using the Cochran-Armitage. As pre-pregnancy body mass index(BMI) remained higher in the GDM group, we adjusted for pre-pregnancy BMI when comparing serum taurine levels in the two groups. Binary logistic regression for the association between GDM and serum taurine was carried out with adjustment for potentially confounding variables. The results are represented by the odds ratio (OR) and 95% confidence interval (CI). The differences were considered statistically significant when P<0.05.

Clinical and laboratory characteristics

The study included 47 GDM women and 47 normoglycemic women. There was no history of GDM, macrosomia, or low birth weight delivery in both two groups. Pre-pregnancy BMI was significantly higher in the GDM women(22.32 vs 20.67, p=0.001), and other clinical indicators were similar, including gravidity, primipara, and history of polycystic ovary syndrome. However, FPG and lipid profiles including TC, TG, and LDL, were significantly higher among GDM women in the first trimester(FPG: 4.86 vs 4.64mmol, P=0.017; TC: 4.46 vs 4.12, P=0.021; TG: 1.26 vs 1.02, P=0.023; LDL: 2.33 vs 2.08, P=0.025)( Table 1 ). At OGTT, the blood glucose value of the GDM group was significantly higher, but there was no difference in lipid profiles between the two groups in the second trimester ( Table S1 in the supplemental material).

www.frontiersin.org

Table 1 Baseline characteristics and glycolipids metabolism in the first trimester between two groups.

Serum taurine levels between or within GDM and normoglycemic women

We compared serum taurine concentrations of GDM women and normoglycemic women at different stages of pregnancy, as well as the dynamic changes of serum taurine in the two groups( Table 2 ). The serum taurine concentration of GDM women was significantly lower than that of normoglycemic women in the first trimester(2.29 vs 3.94 μmol/L, P<0.001). When stratified by quartile, there were 23 controls and no GDM women with a taurine concentration less than 2.22 and there were 2 controls and 21 GDM women with a taurine concentration greater than 3.74(P<0.001). The serum taurine concentration was similar between the two groups in the second trimester(2.37 vs 2.47 μmol/L, P=0.147), and there was no significant difference in quartile stratification(P=0.064). With the progress of pregnancy, serum taurine concentration decreased significantly in the control group(3.94 vs 2.47 μmol/L, P<0.001), but not in the GDM group(2.29 vs 2.37 μmol/L, P=0.249) ( Figure 2 ).

www.frontiersin.org

Table 2 Serum taurine concentration and quartile stratification comparison between two groups.

www.frontiersin.org

Figure 2 The dynamic changes of serum taurine between the first and second trimester of women with GDM and controls. Serum taurine concentration in control decreased significantly (P<0.001).

The association between serum taurine and GDM

Univariate logistic regression analysis showed that there was a significant negative correlation between serum taurine concentration in the first trimester and the risk of GDM(OR=0.013, 95% CI=0.002-0.082, P<0.001, Table 3 ). Furthermore, dynamic change of serum taurine showed a significantly positive correlation with GDM(OR=11.098, 95% CI=4.085-30.155, P<0.001, P<0.001, Table 3 ). Results did not change after adjustment for pre-pregnancy BMI, FPG, and lipid profiles in the first trimester(Taurine in the first trimester: OR=0.017, 95% CI=0.003-0.107, P<0.001; ΔTaurine: OR=9.909, 95% CI=3.556-27.610, P<0.001; Table 3 ). However, serum taurine concentration in the second trimester was not correlated with GDM in any case.

www.frontiersin.org

Table 3 The relationship between Taurine and GDM.

Our study showed that serum taurine concentration in the first trimester was significantly lower in women who were later diagnosed with GDM. As the pregnancy progressed, serum taurine concentration in normoglycaemic women decreased significantly, resulting in the disappearance of differences between the two groups. Low serum taurine concentration in the the first trimester was significantly associated with the occurrence of GDM, and this correlation also no longer existed in the second trimester.

A significant negative association between taurine and T2DM has been demonstrated ( 16 ). Previous RCT studies have shown that taurine supplementation could effectively improve metabolic indicators of T2DM, including glycemic indexes, lipid profiles, and inflammatory biomarkers, and prevent related complications ( 17 – 19 ). The T2DM patients in these studies were all detected with improvement in clinical metabolic markers after supplementing with 3000mg/day of taurine for 8 weeks. In addition, animal experiments showed that taurine had a protective effect on liver damage in GDM offspring ( 20 ). A study conducted the dietary survey at 24-28 gestational weeks and found that taurine intakes were lower in GDM than non-GDM in normal-weight women ( 21 ). However, there were few studies establishing a link between serum taurine levels and the risk of GDM. A recent study suggested a lower plasma taurine level in the first trimester seemed to be a fair marker of inadequate insulin secretion and to be more closely associated with a higher risk of GDM development in multiparas ( 13 ). This was consistent with our findings regarding the relationship between low serum taurine concentration in the first trimester and GDM.

Our study further compared the serum taurine concentrations in the second trimester and analyzed its dynamic changes. We found that as the pregnancy progressed, serum taurine concentration decreased significantly in normoglycaemic women but not in GDM women, resulting in the disappearance of differences between the two groups. The taurine decline trend from the first to second trimester was significantly negatively associated with the occurrence of GDM. Taurine is an amino acid that links the mother with the offspring during pregnancy, and fetuses depend on the taurine supplied by mothers via the placenta ( 22 ). The concentration of taurine in the placental tissue is 100-150 times higher than that of the fetus and mother ( 23 ). The placental tissues concentrate taurine efficiently and transfer taurine to fetal circulation based on the taurine transporter(TauT) activity ( 22 ). Animal studies have demonstrated that taurine concentration correlated with the peak of neurogenesis ( 24 ), which explained the decrease in serum taurine concentration in normoglycaemic women as the pregnancy progressed. However, high glucose levels could acutely inhibit taurine’s transport by TauT ( 25 ), which might be the reason why there was no difference in serum taurine concentration between the first and second trimester of GDM women in our study. The offspring of GDM have a long-term risk of neurodevelopmental disorder ( 26 ), and the role of taurine transport inhibition is worth further study.

The beneficial effects of taurine on T2DM and its related complications have been widely reviewed in human clinical practice ( 27 ). Taurine played a hypoglycemic role by improving insulin sensitivity, stimulating insulin secretion, and reducing inflammation and oxidative stress ( 27 ). Previous studies have reported the role of taurine in maintaining glucose homeostasis involving several possible mechanisms, such as modulating several pancreatic cells ( 28 ) and inhibiting inflammatory factor and nuclear factor kappa-B(NF-κB) activity to reduce inflammatory-mediated destruction of pancreatic β cells ( 29 ). It is not clear whether the pathogenesis of GDM induced by taurine deficiency in the first trimester is identical to that in non-pregnant women. In our former study, we reported gut microbiota changes in the first trimester were potentially associated with the development of GDM ( 30 ). The gut microbiota could trigger inflammatory processes by increasing gut permeability by exposing tight gap junction proteins to bacterial lipopolysaccharides ( 31 , 32 ). Taurine is a microbiota-related metabolite derived from bile acids by certain microorganisms ( 33 ), and animal studies have shown that taurine has a protective effect on intestinal barrier function ( 34 ). Taurine deficiency might play a critical role in the pathogenesis of GDM, resulting in the loss of intestinal barrier protection and chronic inflammation. Although a direct causal relationship between taurine and its pathological state has not been established, it might be a potential marker for GDM. We hope to develop a sensitive and reliable GDM prediction model with serum taurine in the first trimester to help identify high-risk individuals at an early stage. In addition, the clinical intervention can be stratified according to the high-risk degree to avoid the waste of medical resources.

Strengths and limitations

This was the first study to compare the dynamic changes of serum taurine concentrations from the first to second trimester. Our results demonstrated that small molecule metabolites varied during pregnancy and should be combined with dynamic changes to analyze their relationship with disease. Unfortunately, we were unable to collect umbilical cord blood to test their serum taurine levels to verify the relationship between taurine transport and the dynamic change of serum taurine concentration during pregnancy. In the future, the serum taurine levels of mothers and newborns could be detected simultaneously to reveal this correlation and its role in offspring nervous system development. In addition, this study was a single-center study, limited by the sample size and limited geographical area.

Our study revealed that GDM women had a reduced serum taurine level in the first trimester. Elevated serum taurine concentration from the first to second trimester was significantly associated with the development of GDM. The relationship between taurine deficiency and GDM may be related to increased intestinal permeability and systemic inflammation, and the specific mechanism needs to be further explored.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving human participants were reviewed and approved by the Ethics Committee of Beijing Obstetrics and Gynecology Hospital. The patients/participants provided their written informed consent to participate in this study.

Author contributions

All the authors contributed significantly to the manuscript. GL and XM contributed to the study design and interpretation of the data. JW and YW contributed to the drafting and revision of the manuscript. JW and WZ coordinated and executed the statistical analysis. CL, XY, and YZ contributed to the collection of data. WS, XW, and SL contributed to the enrollment and follow-up in clinic. All authors reviewed and approved the final submitted version.

This work was supported by National Natural Science Foundation of China (82171671), Beijing Hospitals Authority’ Ascent Plan(DFL20191402), Scientific Research Common Program of Beijing Municipal Commission of Education (KM202110025007), Beijing Natural Science Foundation (No. 7214231).

Acknowledgments

The authors thank the participants for participating in the study and the medical staff for their work on information collection.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fendo.2023.1116044/full#supplementary-material

1. Yuen L, Saeedi P, Riaz M, Karuranga S, Divakar H, Levitt N, et al. Projections of the prevalence of hyperglycaemia in pregnancy in 2019 and beyond: Results from the international diabetes federation diabetes atlas, 9th edition. Diabetes Res Clin Pract (2019) 157:107841. doi: 10.1016/j.diabres.2019.107841

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Sweeting A, Wong J, Murphy HR, Ross GP. A clinical update on gestational diabetes mellitus. Endocr Rev (2022) 43(5):763–93. doi: 10.1210/endrev/bnac003

3. Metzger BE, Lowe LP, Dyer AR, Trimble ER, Chaovarindr U, Coustan DR, et al. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med (2008) 358(19):1991–2002. doi: 10.1056/NEJMoa0707943

4. Scholtens DM, Kuang A, Lowe LP, Hamilton J, Lawrence JM, Lebenthal Y, et al. Hyperglycemia and adverse pregnancy outcome follow-up study (HAPO FUS): Maternal glycemia and childhood glucose metabolism. Diabetes Care (2019) 42(3):381–92. doi: 10.2337/dc18-2021

5. Li M, Hinkle SN, Grantz KL, Kim S, Grewal J, Grobman W, et al. Glycaemic status during pregnancy and longitudinal measures of fetal growth in a multi-racial US population: a prospective cohort study. Lancet Diabetes Endocrinol (2020) 8(4):292–300. doi: 10.1016/S2213-8587(20)30024-3

6. Venkataraman H, Ram U, Craik S, Arungunasekaran A, Seshadri S, Saravanan P. Increased fetal adiposity prior to diagnosis of gestational diabetes in south asians: More evidence for the 'thin-fat' baby. Diabetologia (2017) 60(3):399–405. doi: 10.1007/s00125-016-4166-2

7. Koivusalo SB, Rönö K, Klemetti MM, Roine RP, Lindström J, Erkkola M, et al. Gestational diabetes mellitus can be prevented by lifestyle intervention: The Finnish gestational diabetes prevention study (RADIEL): A randomized controlled trial. Diabetes Care (2016) 39(1):24–30. doi: 10.2337/dc15-0511

8. Coomar D, Hazlehurst JM, Austin F, Foster C, Hitman GA, Heslehurst N, et al. Diet and physical activity in pregnancy to prevent gestational diabetes: A protocol for an individual participant data (IPD) meta-analysis on the differential effects of interventions with economic evaluation. BMJ Open (2021) 11(6):e048119. doi: 10.1136/bmjopen-2020-048119

9. Tochitani S. Functions of maternally-derived taurine in fetal and neonatal brain development. Adv Exp Med Biol (2017) 975 Pt 1:17–25. doi: 10.1007/978-94-024-1079-2_2

10. Inam-U-Llah PF, Aadil RM, Suleman R, Li K, Zhang M, et al. Ameliorative effects of taurine against diabetes: A review. Amino Acids (2018) 50(5):487–502. doi: 10.1007/s00726-018-2544-4

11. Zhou Y, Holmseth S, Guo C, Hassel B, Höfner G, Huitfeldt HS, et al. Deletion of the γ-aminobutyric acid transporter 2 (GAT2 and SLC6A13) gene in mice leads to changes in liver and brain taurine contents. J Biol Chem (2012) 287(42):35733–46. doi: 10.1074/jbc.M112.368175

12. Levy M, Thaiss CA, Zeevi D, Dohnalová L, Zilberman-Schapira G, Mahdi JA, et al. Microbiota-modulated metabolites shape the intestinal microenvironment by regulating NLRP6 inflammasome signaling. Cell (2015) 163(6):1428–43. doi: 10.1016/j.cell.2015.10.048

13. Liu PJ, Liu Y, Ma L, Liu L, Hu T, An Z, et al. The relationship between plasma taurine levels in early pregnancy and later gestational diabetes mellitus risk in Chinese pregnant women. Sci Rep (2021) 11(1):7993. doi: 10.1038/s41598-021-87178-y

14. American Diabetes Association. Classification and diagnosis of diabetes: Standards of medical care in diabetes-2018. Diabetes Care (2018) 41(Suppl 1):S13–27. doi: 10.2337/dc18-S002

15. Zheng W, Huang W, Zhang L, Tian Z, Yan Q, Wang T, et al. Early pregnancy metabolic factors associated with gestational diabetes mellitus in normal-weight women with polycystic ovary syndrome: A two-phase cohort study. Diabetol Metab Syndr (2019) 11:71. doi: 10.1186/s13098-019-0462-6

16. Sak D, Erdenen F, Müderrisoglu C, Altunoglu E, Sozer V, Gungel H, et al. The relationship between plasma taurine levels and diabetic complications in patients with type 2 diabetes mellitus. Biomolecules (2019) 9(3):96. doi: 10.3390/biom9030096

17. Maleki V, Alizadeh M, Esmaeili F, Mahdavi R. The effects of taurine supplementation on glycemic control and serum lipid profile in patients with type 2 diabetes: A randomized, double-blind, placebo-controlled trial. Amino Acids (2020) 52(6-7):905–14. doi: 10.1007/s00726-020-02859-8

18. Maleki V, Mahdavi R, Hajizadeh-Sharafabad F, Alizadeh M. The effects of taurine supplementation on oxidative stress indices and inflammation biomarkers in patients with type 2 diabetes: A randomized, double-blind, placebo-controlled trial. Diabetol Metab Syndr (2020) 12:9. doi: 10.1186/s13098-020-0518-7

19. Esmaeili F, Maleki V, Kheirouri S, Alizadeh M. The effects of taurine supplementation on metabolic profiles, pentosidine, soluble receptor of advanced glycation end products and methylglyoxal in adults with type 2 diabetes: A randomized, double-blind, placebo-controlled trial. Can J Diabetes (2021) 45(1):39–46. doi: 10.1016/j.jcjd.2020.05.004

20. Luo Y, Tian Y, Zhao C. Taurine attenuates liver autophagy and injury of offspring in gestational diabetic mellitus rats. Life Sci (2020) 257:117889. doi: 10.1016/j.lfs.2020.117889

21. Park S, Kim MY, Baik SH, Woo JT, Kwon YJ, Daily JW, et al. Gestational diabetes is associated with high energy and saturated fat intakes and with low plasma visfatin and adiponectin levels independent of prepregnancy BMI. Eur J Clin Nutr (2013) 67(2):196–201. doi: 10.1038/ejcn.2012.207

22. Ramamoorthy S, Leibach FH, Mahesh VB, Han H, Yang-Feng T, Blakely RD, et al. Functional characterization and chromosomal localization of a cloned taurine transporter from human placenta. Biochem J (1994) 300(Pt 3):893–900. doi: 10.1042/bj3000893

23. Kulanthaivel P, Cool DR, Ramamoorthy S, Mahesh VB, Leibach FH, Ganapathy V. Transport of taurine and its regulation by protein kinase c in the JAR human placental choriocarcinoma cell line. Biochem J (1991) 277(Pt 1):53–8. doi: 10.1042/bj2770053

24. Tochitani S, Furukawa T, Bando R, Kondo S, Ito T, Matsushima Y, et al. GABAA receptors and maternally derived taurine regulate the temporal specification of progenitors of excitatory glutamatergic neurons in the mouse developing cortex. Cereb Cortex (2021) 31(10):4554–75. doi: 10.1093/cercor/bhab106

25. Tochitani S. Taurine: A maternally derived nutrient linking mother and offspring. Metabolites (2022) 12(3):228. doi: 10.3390/metabo12030228

26. Farahvar S, Walfisch A, Sheiner E. Gestational diabetes risk factors and long-term consequences for both mother and offspring: A literature review. Expert Rev Endocrinol Metab (2019) 14(1):63–74. doi: 10.1080/17446651.2018.1476135

27. Sirdah MM. Protective and therapeutic effectiveness of taurine in diabetes mellitus: A rationale for antioxidant supplementation. Diabetes Metab Syndr (2015) 9(1):55–64. doi: 10.1016/j.dsx.2014.05.001

28. Santos-Silva JC, Ribeiro RA, Vettorazzi JF, Irles E, Rickli S, Borck PC, et al. Taurine supplementation ameliorates glucose homeostasis, prevents insulin and glucagon hypersecretion, and controls β, α, and δ-cell masses in genetic obese mice. Amino Acids (2015) 47:1533–48. doi: 10.1007/s00726-015-1988-z

29. Imae M, Asano T, Murakami S. Potential role of taurine in the prevention of diabetes and metabolic syndrome. Amino Acids (2014) 46(1):81–8. doi: 10.1007/s00726-012-1434-4

30. Zheng W, Xu Q, Huang W, Yan Q, Chen Y, Zhang L, et al. Gestational diabetes mellitus is associated with reduced dynamics of gut microbiota during the first half of pregnancy. mSystems (2020) 5(2):e00109–20. doi: 10.1128/mSystems.00109-20

31. Shen J, Obin MS, Zhao L. The gut microbiota, obesity and insulin resistance. Mol Aspects Med (2013) 34(1):39–58. doi: 10.1016/j.mam.2012.11.001

32. Cani PD, Neyrinck AM, Fava F, Knauf C, Burcelin RG, Tuohy KM, et al. Selective increases of bifidobacteria in gut microflora improve high-fat-diet-induced diabetes in mice through a mechanism associated with endotoxaemia. Diabetologia (2007) 50(11):2374–83. doi: 10.1007/s00125-007-0791-0

33. Stacy A, Andrade-Oliveira V, McCulloch JA, Hild B, Oh JH, Perez-Chaparro PJ, et al. Infection trains the host for microbiota-enhanced resistance to pathogens. Cell (2021) 184(3):615–627.e17. doi: 10.1016/j.cell.2020.12.011

34. Wen C, Guo Q, Wang W, Duan Y, Zhang L, Li J, et al. Taurine alleviates intestinal injury by mediating tight junction barriers in diquat-challenged piglet models. Front Physiol (2020) 11:449. doi: 10.3389/fphys.2020.00449

Keywords: biomarker, gestational diabetes mellitus, taurine, taurine transporter, dynamic change

Citation: Wang J, Wang Y, Zheng W, Yuan X, Liu C, Zhang Y, Song W, Wang X, Liang S, Ma X and Li G (2023) Dynamic changes of serum taurine and the association with gestational diabetes mellitus: A nested case-control study. Front. Endocrinol. 14:1116044. doi: 10.3389/fendo.2023.1116044

Received: 05 December 2022; Accepted: 13 March 2023; Published: 23 March 2023.

Reviewed by:

Copyright © 2023 Wang, Wang, Zheng, Yuan, Liu, Zhang, Song, Wang, Liang, Ma and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Guanghui Li, [email protected] ; Xu Ma, [email protected]

† These authors have contributed equally to this work and share first authorship

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings
  • Advanced Search
  • Journal List
  • 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.

An external file that holds a picture, illustration, etc.
Object name is IJD-61-146-g001.jpg

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)

An external file that holds a picture, illustration, etc.
Object name is IJD-61-146-g002.jpg

Hypothetical study of metabolic syndrome and psoriasis

An external file that holds a picture, illustration, etc.
Object name is IJD-61-146-g003.jpg

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.

Financial support and sponsorship

Conflicts of interest.

There are no conflicts of interest.

Bibliography

  • Module Index
  • Epiville Chamber of Commerce
  • About this site
  • Requirements

Case-Control Study

Introduction.

  • Learning Objectives
  • Student Role
  • Study Design
  • Data Collection
  • Data Analysis
  • Discussion Questions
  • Print Module

Traditionally, case-control studies have been viewed as an alternative to cohort studies in which individuals were selected on the basis of whether or not they had the disease outcome of interest, with investigators then comparing exposure history between those with the disease (the cases) and those free of the disease (the controls). More recently, the theory behind the case-control study has been re-imagined as a method of selecting a subset of an underlying cohort giving rise to the cases in the study. The case-control study design is an excellent choice of study when the disease is rare, has a long induction period , the exposure data are difficult to obtain, or very little is known about the disease. In these situations a cohort study is generally prohibitively expensive or the time frame of the study required for data collection is impractical. Unlike cohort studies, case-control studies identify cases of the disease of interest in their population and then compare their exposure experience to sampled controls. As you will learn in the following exercise, this method is deceptively simple, and if not planned carefully, can lead to spurious findings.

Faculty Highlight: Dr. Alfred Neugut

case of study control

"The case-control study's simplicity sometimes makes us forget just how elegant and revolutionary a creation it was of 20th century chronic disease epidemiology."

Dr. Neugut is a Professor of Medicine and the Myron M. Studner Professor of Cancer Research. His research interests span the epidemiology and screening of colorectal neoplasia, breast cancer etiology and treatment, racial disparities in cancer, and cancer in the elderly. He serves as co-PI of the Long Island Breast Cancer Study, a large population-based case-control study.

Read more about Dr. Neugut's work

  • Terry MB, Gammon MD, Zhang FF, Tawfik H, Teitelbaum SL, Britton JA, Subbaramaiah K, Dannenberg AJ, Neugut AI. Association of frequency and duration of aspirin use and hormone receptor status with breast cancer risk. JAMA. 2004 May 26;291(20):2433-40.
  • Hershman D, McBride R, Jacobson JS, Lamerato L, Roberts K, Grann VR, Neugut AI. Racial disparities in treatment and survival among women with early-stage breast cancer. J Clin Oncol. 2005 Sep 20;23(27):6639-46.
  • Zablotska LB, Chak A, Das A, Neugut AI. Increased risk of squamous cell esophageal cancer after adjuvant radiation therapy for primary breast cancer. Am J Epidemiol. 2005 Feb 15;161(4):330-7.

Website URL: http://epiville.ccnmtl.columbia.edu/

  • Skip to main content
  • Keyboard shortcuts for audio player

Shots - Health News

  • Your Health
  • Treatments & Tests
  • Health Inc.
  • Public Health

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 of study control

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 of study control

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

Log in using your username and password

  • Search More Search for this keyword Advanced search
  • Latest content
  • Current issue
  • Anniversary
  • BMJ Journals More You are viewing from: Google Indexer

You are here

  • Online First
  • Document analysis of the Foundation for a Smoke-Free World’s scientific outputs and activities: a case study in contemporary tobacco industry agnogenesis
  • Article Text
  • Article info
  • Citation Tools
  • Rapid Responses
  • Article metrics

Download PDF

  • http://orcid.org/0000-0003-3157-048X Tess Legg ,
  • Bryan Clift ,
  • Anna B Gilmore
  • Department for Health , University of Bath , Bath , UK
  • Correspondence to Tess Legg, Department for Health, University of Bath, Bath BA2 7AY, UK; t.legg{at}bath.ac.uk

Background Tobacco corporation Philip Morris International launched the Foundation for a Smoke-Free World (FSFW), a purportedly independent scientific organisation, in 2017. We aimed to systematically investigate FSFW’s activities and outputs, comparing these with previous industry attempts to influence science, as identified in the recently developed typology of corporate influence on science, the Science for Profit Model (SPM).

Design We prospectively collected data on FSFW over a 4-year period, 2017–2021, and used document analysis to assess whether FSFW’s activities mirror practices tobacco and other industries have historically used to shape science in their own interests. We used the SPM as an analytical framework, working deductively to search for use of the strategies it identifies, and inductively to search for any additional strategies.

Results Marked similarities between FSFW’s practices and previous corporate attempts to influence science were observed, including: producing tobacco industry-friendly research and opinion; obscuring industry involvement in science; funding third parties which denigrate science and scientists that may threaten industry profitability; and promoting tobacco industry credibility.

Conclusions Our paper identifies FSFW as a new vehicle for agnogenesis, indicating that, over 70 years since the tobacco industry began to manipulate science, efforts to protect science from its interference remain inadequate. This, combined with growing evidence that other industries are engaging in similar practices, illustrates the urgent need to develop more robust systems to protect scientific integrity.

  • Tobacco industry documents
  • Tobacco industry
  • Surveillance and monitoring

Data availability statement

All data relevant to the study are included in the article or uploaded as supplemental information.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/tc-2022-057667

Statistics from Altmetric.com

Request permissions.

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

WHAT IS ALREADY KNOWN ON THIS TOPIC

Litigation forced three tobacco industry-funded organisations to cease operating due to their role in spreading scientific misinformation.

Philip Morris International (PMI) launched a new scientific organisation, the Foundation for a Smoke-Free World (FSFW) in 2017. Many fear FSFW plays a key scientific and public relations role for the tobacco industry.

WHAT THIS STUDY ADDS

We show marked similarities between FSFW’s outputs and activities and previous corporate attempts to influence science.

Our findings indicate that FSFW should be understood as an industry-influenced scientific lobby group promoting tobacco industry interests, akin to the historical tobacco industry-funded groups that were forcibly closed.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

PMI’s funding of FSFW endangers progress made in protecting science from the tobacco industry, including by rendering academic journal policies ineffective, and circumventing norms about the unacceptability of collaborating with the tobacco industry.

The development of more robust systems to ensure science is in the public interest is urgently needed.

Introduction

There is overwhelming evidence of the tobacco industry’s history of manipulating science—first to deny the link between cigarettes and cancer, and subsequently to deny the harms of passive smoking. 1 2 The industry’s ability to influence science relied upon creating purportedly independent third parties to undertake key scientific roles. 3 From the 1950s onwards, Philip Morris and others used the Tobacco Industry Research Committee (TIRC) to conduct science deflecting attention from tobacco harms 1 and in the 1980s created the Center for Indoor Air Research (CIAR) to mislead the public about passive smoking. 2

In the late 1990s, litigation settlements forced three tobacco industry-funded organisations based in the USA (the Tobacco Institute, TIRC and CIAR) to cease operating due to their role in spreading misinformation. 4 A subsequent federal court order—which found the tobacco industry guilty of a ‘lengthy, unlawful conspiracy to deceive the American public’—banned US-based tobacco corporations from recreating such bodies. 5

Since these landmark rulings, academic and public health communities have sought to better protect science from tobacco industry influence. Academics have proposed stronger firewalls between funding and research, 6 and some scientific journals have implemented measures to manage or ban tobacco industry research. 7 8

Despite this progress however, or perhaps because of it, in September 2017, Philip Morris International (PMI), which was not bound by the US litigation, 9 launched a new scientific organisation, the Foundation for a Smoke-Free World (FSFW or ‘the Foundation’), pledging nearly a billion dollars in funds. 10 With growing concern within the public health and academic communities about the nature and conduct of FSFW, 11–15 there is a pressing need to better understand its involvement in science.

With this as our aim, we systematically assessed FSFW’s outputs and activities and compared these with strategies which diverse industries have historically used to shape science in their own interests, as identified in a recently developed evidence-based typology of corporate influence on science—the Science for Profit Model (SPM). 16 The SPM was developed by the first and last authors, and draws on the extensive literature on corporate influence on science. It demonstrates that corporate sectors including the tobacco, pharmaceutical, chemicals, fossil fuels, alcohol and food industries have used the same collection of strategies to manufacture doubt and ignorance (or agnogenesis) 17 18 about harms of industry products or the efficacy of policies affecting industry, promote industry-favoured solutions to public health issues and legitimise industry involvement in science. 16 The typology outlines four macro strategies (comprising 17 meso-level strategies) through which industries have worked to influence science (see table 1 ). Despite other analyses providing rich accounts of the tobacco industry’s history of manipulating science, 1 18 19 we chose to use the SPM as its comprehensive categorisation of industry strategies enables its use as an analytical framework. We address the following research questions:

In what ways, if any, does FSFW operationalise tobacco industry influence on science?

In what ways, if any, does PMI’s funding of FSFW jeopardise progress made to protect science from tobacco industry influence?

  • View inline

Macro and meso strategies used by corporations to influence science as identified in the Science for Profit Model (SPM) 16

We prospectively collected data on FSFW over a 4-year period, and used two types of document analysis to assess whether FSFW’s activities mirror previously documented industry attempts to influence science.

In September 2017, we established a system for monitoring FSFW’s outputs and activities. Beginning with FSFW’s website and relevant Google alerts (used to identify web sources), this grew to include other primary data sources, which in turn provided search terms (including names of grantee organisations and associated principal investigators) for secondary data sources (see table 2 ). Using these sources, we collected data related to FSFW’s work on tobacco harm reduction and smoking cessation (its agricultural diversification workstream not being the focus of this paper) until September 2021.

Monitoring strategy

Our analytical method was twofold. First, we drew on Forster’s approach to the analysis of company documentation, 20 a method used in previous analyses of tobacco and food industry documents. 21–26 This method involved understanding the meaning of individual documents through reading and rereading them over time as knowledge increases, discussing their meaning, and considering multiple documents and types of documents concurrently. The purpose of this process is to look for corroborations and discrepancies between documents to derive meaning, and the ‘back-and-forth’ between data and interpretation helps to build understanding. Documents are then recontextualised using other data sources (for instance, we compared claims made by FSFW with the wider evidence base). While Forster’s approach is primarily inductive, we conducted our analysis in a more deductive way. That is, we combined Forster’s procedural steps with a deductive approach to searching for the industry strategies identified in the SPM 16 (using a slightly adapted version of the typology—see footnote to table 1 ). We also worked inductively, remaining open to identifying the use of additional strategies.

Second, through the initial stages of our analysis, it became clear that a more detailed investigation into one of the SPM’s meso strategies—‘Fund and undertake ‘safe’ research’—could bring further insights. To do this, we conducted a content analysis 27 (rather than the iterative, comparative analysis of documents described above) of a subset of the data—peer-reviewed and preprint articles funded by FSFW. Preprint articles are outputs hosted on online open science publishing platforms (such as MedRxiv, BioRxiv and F1000). These outputs are uploaded onto the platforms by their authors, and are not subject to independent prepublication peer review. For this analysis, we used the seven types of ‘safe’ research identified in the SPM as benefiting industry as a priori categories, coding any presence of these in the dataset while also searching for new categories.

We obtained over 700 items of data, and through our analysis found marked similarities between FSFW’s activities and outputs, and strategies previously used by corporations and their third parties to influence science. Key evidence is outlined below.

Strategy A: influence on the conduct and publication of science

The original 2018 ‘pledge agreement’ between FSFW and PMI indicates that FSFW’s funding is conditional on its research focusing on ‘tobacco harm reduction’, 28 rather than on broader tobacco control measures. In 2020, this document was updated. A comparison of the original and updated versions of the agreement shows the description of FSFW as ‘free from influence’ 28 from PMI was changed to ‘free from improper influence’ 29 and the following was added:

Nothing in this section… shall be interpreted to prohibit the Foundation from exchanging information or interacting with any third party, including but not limited to the pledgor… [i.e. PMI] …, or other donors, in order to advance the Foundation’s purpose. 29

This suggests PMI is exerting, and reserves the right to exert, influence over FSFW. Collectively, FSFW-funded research outputs remain within the narrow research field dictated by this pledge agreement. Through a content analysis of FSFW-funded peer-reviewed and preprint research outputs, we found evidence of all seven of the types of ‘safe’ research (strategy 1) identified in the SPM. Such ‘safe’ research benefits industry by distracting attention from industry harms, framing industry products as ‘solutions’ and promoting interventions that minimise damage to product sales (see table 3 for illustrative examples).

Funding and undertaking ‘safe’ research—content in FSFW-funded peer-reviewed and preprint articles which distracts attention from industry harms, frames industry products as part of the ‘solution’ and promotes interventions that minimise damage to product sales

While it is not surprising that literature reviews on newer tobacco and nicotine products often include tobacco industry-funded research (since this comprises much of the current evidence base), several FSFW-funded literature reviews rely on tobacco industry-funded literature without acknowledging its funding source, and fail to detail how literature was selected for inclusion. Such reporting omissions create the risk that literature has been cherry-picked for inclusion, potentially mirroring previous industry attempts to influence the findings and conclusions of research syntheses (strategy 3). They also have the effect of obscuring the provenance of the included works, with readers unaware that a review’s findings and conclusions are based on science including that funded by the tobacco industry. One narrative review on e-cigarettes and respiratory health 30 emphasised potential benefits of e-cigarettes, citing literature including that funded by British American Tobacco, Philip Morris USA, Lorillard, R.J. Reynolds and Imperial Tobacco-owned Fontem Ventures. This was only evident on inspection of the cited works’ funding declarations. A preprint systematic review of the relative risks of ‘nicotine products’ 31 commissioned by FSFW 32 failed to list the included studies (as recommended by Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines), 33 making it impossible to determine the extent upon which industry-funded science was relied. FSFW bases its classification of nicotine products on this preprint, making no reference to its non-peer-reviewed status. 32

Various FSFW’s activities have helped ensure research favourable to the tobacco industry is heavily represented in the evidence base (strategy 5). FSFW and its grantees often self-publish reports on their websites or use open science (‘preprint’) publishing platforms, creating an evidence base which has not had its robustness assessed through independent peer review. On one preprint platform, F1000, where authors invite reviewers who are required to disclose conflicts of interest (COIs), FSFW invited its own grantee who gave a wholly positive review (with no COI disclosure). In contrast, the other reviewer flagged several revisions needed. 34

Several journals which have published FSFW-funded articles had FSFW-affiliated researchers in editorial positions. Between May and July 2020, Drugs and Alcohol Today published a serialised special issue on the Framework Convention on Tobacco Control (FCTC), comprising nine papers all authored by FSFW grantees or staff members. 35 Both the editor-in-chief and the guest editor had financial links to FSFW, COIs which went undeclared by the journal in relation to their editorial roles. 36 While it is unclear whether these connections improperly influenced the publication of these articles, in February 2021, all nine articles had an expression of concern added by the publisher because of ‘credible concerns’ about editorial processes. 37–45 In 2022, Drugs and Alcohol Today was renamed Drugs, Habits and Social Policy . 46 The previous editor-in-chief is no longer in that role, but as of April 2023 remains a member of the editorial board. 47 It is unclear whether the publisher's investigation is ongoing.

This was FSFW’s second known attempt to publish a special issue on this topic, the first cancelled by the International Journal of Environmental Research and Public Health once the managing editor understood FSFW’s tobacco industry connections. 36 Documents concerning that special issue show that FSFW’s public relations firm, Ruder Finn, emailed the journal asking that FSFW’s president be permitted to choose contributing authors from FSFW’s grantees (University of Bath’s Tobacco Control Research Group (TCRG) personal communication, 2019). While it may be common practice for an editor of a special issue to choose its papers, a tobacco industry-funded organisation controlling the content of a special issue on the FCTC (which the tobacco industry has fought to disempower) 14 48 is a clear conflict.

Strategy B: influence on the interpretation of science

FSFW staff and grantees have attacked research which paints the tobacco industry in a bad light (strategy 9). In the 1990s, the industry adopted the phrase ‘junk science’ to censure science deemed unfavourable. 16 This phrase has recently been invoked by both PMI, 49 and by FSFW grantees, with one grantee organisation characterising concerns about e-cigarettes as ‘a fear-driven crusade’ of ‘lies and junk science’. 50 FSFW staff and grantees have also misrepresented evidence on tobacco and nicotine products. One grantee discounted the evidence base on secondhand smoke to the New Zealand Health Select Committee when arguing against banning smoking in cars, saying ‘scientific studies have not proven that exposure to cigarette smoke in the car causes disease’. 51 Overwhelming evidence as far back as the 1950s identifies secondhand smoke as a health risk, 52–57 and newer evidence demonstrates that smoke-free policies lead to reductions in health harms. 58 59 In an invited comment in the American Journal of Public Health , 60 FSFW staff misrepresented evidence on the role of flavours in youth e-cigarette use, using a paper which identified flavours as the third most common reason for use 61 to claim that flavours are not a main driver of youth e-cigarette use. Concerning the link between youth e-cigarette use and later uptake of combustible cigarettes, an article in FSFW-funded Filter Magazine asserted that this so-called ‘gateway’ theory had been ‘conclusively debunked’, 50 despite the paper the article cited on this point concluding ‘the role of e-cigarettes in the future of youth smoking has yet to be definitively assessed’. 62

FSFW and its grantees have spoken out in hostile terms against individuals and organisations that create and disseminate science unfavourable to the tobacco industry (strategy 10). They labelled authors of a report on FSFW and PMI guilty of ‘characteristic hypocrisy’ and of disseminating ‘false narratives’ about FSFW, 63 and lamented the ‘constant (often exaggerated) bleating of public health’ about health harms of the industry’s products. 64

Strategy C: influence on the reach of science

FSFW and its grantees act as messengers (strategy 12), disseminating science and ‘packaging’ it in ways supporting industry interests (strategy 13) while distancing those messages from industry. FSFW has published a quarterly newsletter entitled ‘Health, Science, and Technology’, 65 which disseminates science including that funded directly by industry, 66–68 without making any mention of these industry links. Other ‘packaged science’ includes commentary pieces in journals (promoting industry-friendly narratives on e-cigarettes 60 and COVID-19 69 ), and evidence submissions to governments endorsing deregulatory approaches. 70 71

FSFW and its grantees fund children’s science competitions, 72 webinars 73 and events (strategy 14), such as a 2020 conference where speakers 74 presented findings from the FSFW-led special issue of journal Drugs and Alcohol Today , 35 and FSFW’s PR firm, Ruder Finn, invited selected media (TCRG, personal communication, 2020). Another event with links to FSFW, the annual Global Forum on Nicotine, 75 has provided a platform for tobacco corporations and industry-linked researchers to disseminate their science to, and build relationships with, those working independently from the industry. 76 77

FSFW has funded media outlets which disseminate industry-friendly scientific messages (strategy 15), including Filter Magazine and Vida News , which between them have received or had approved funding of over US$1.3 million since 2018. 78–81 Over this same period, Filter Magazine’s funders have also included PMI, Altria, Reynolds American, Juul Labs and FSFW grantee Knowledge Action Change. 82 These outlets cite FSFW staff, grantees and subgrantees 83–88 ; report scientific events linked to FSFW 89 90 ; and disseminate both FSFW-funded research 91 92 and critiques of science which may threaten the tobacco industry. 50 93

An organisation with links to FSFW-funded researchers 30 94 has also influenced what messages are not received by journalists. The Consumer Advocates for Smoke-Free Alternatives Association worked to prevent a journalist speaking to tobacco control researchers. In September 2019, an email read ‘in the hope that… [the journalist] …doesn’t discover the… [University of] …Bath tobacco control people on her own, I offered to do a little of the legwork for her’. (TCRG, personal communication, 2019).

Strategy E: manufacturing trust in industry and its scientific messaging

FSFW promotes the tobacco industry’s credibility and its role in science in diverse ways (strategy 18). First, FSFW frames tobacco industry involvement in science and policy as the ‘solution’, 37 45 and its exclusion as counterproductive. FSFW’s (now former) president condemned ‘entrenched hostility towards industry’, 95 arguing industry-funded research is ‘robust’ and should ‘not be shunned simply on the basis of who executed or funded it’. 96 This stands in contrast to his previous statement (before taking up this post at FSFW) that ‘academic naivete about tobacco companies’ intentions is no longer excusable’. 97 FSFW has misleadingly likened itself 36 to tobacco control organisations which either receive no funds from the tobacco industry 98 or are funded by legally binding tobacco industry payments to the US government. 99 100 Although FSFW repeatedly asserts 101–103 that it closely adheres to criteria 6 laid out for using tobacco industry funding for research, the authors of these criteria have specifically indicated that it does not. 104

Conversely, despite FSFW citing transparency as one of its key tenets, 105 its own activities (and that of its grantees) often obscure its industry links (strategy 19), thus increasing the perceived legitimacy of its science and advocacy. Several articles and commentaries lacked declarations explicitly outlining the output’s funding from FSFW when published, 38 42 106–111 despite FSFW listing them as its publications. 112–114 Even when a publication’s links to FSFW are made clear, FSFW’s links to PMI are often undisclosed. 34 39 40 44 115–123

Beyond scientific publications, FSFW’s funding of one major grantee launched several subgrantee organisations positioned as experts on the science and policy of tobacco, none of whom mentioned FSFW or PMI on their websites. 124–129 In 2020, FSFW distributed grant funds to establish ‘The Lung Trust’, ‘for the application, receipt and administration of future grant awards’, 130 suggesting the complex network of organisations indirectly funded by PMI is likely to become ever more opaque.

This study—within which we took a prospective approach, collecting data over 4 years—is the first systematic and comprehensive investigation of FSFW’s outputs and activities. It is also the first paper to use the SPM as an analytical tool to investigate a contemporary industry-funded scientific organisation. Our analysis revealed that in just its first 4 years, the organisation and its affiliates have already engaged in activities which mirror all four of the SPM’s macro (and many of the meso) strategies previously used by industries to influence science. FSFW and its grantees have:

Produced research and opinion which supports tobacco industry interests by: side-lining evidence-based tobacco control measures and endorsing interventions which ensure the sale of industry products 42 43 45 123 131 ; advocating for tobacco industry involvement in science and policymaking 39 45 ; and misrepresenting evidence on tobacco and nicotine products. 50 51 60

Published research which obscures PMI’s involvement. 34 39 40 44 106 109 115–123

Funded media outlets 78 80 81 which frequently denigrate science that may jeopardise industry profitability. 50 93

Rallied against researchers and advocates working in tobacco control. 63 64

Pushed for renormalisation of the tobacco industry. 95 96

The SPM identified that diverse industries have used these practices to achieve three proximal outcomes: (1) to create doubt about the harms of industry products, or the necessity or efficacy of policies which would affect industry; (2) to promote industry products as solutions to public health problems, and to promote industry-favoured policy responses; and (3) to legitimise the role of industry in the creation and use of science. Our analysis suggests that the launch of FSFW, and its subsequent outputs and activities, have served to help PMI, and the tobacco industry more broadly, realise these same outcomes.

Collectively, our findings indicate that FSFW should be understood as an industry-influenced scientific lobby group promoting tobacco industry interests, akin to historical tobacco industry-funded groups forcibly closed 132 and contemporary organisations promoting the interests of the sugar, 133 alcohol 134 and pesticides 135 industries. This case study adds to the body of evidence that these scientific third-party organisations play a key, and often hidden, role in operationalising industry influence on science.

FSFW is an effective vehicle for agnogenesis, not only about the evidence base on the safety and efficacy of industry products, but also about which public health solutions are optimal for society (framing consumption of industry products as essential for progress and health), and about what industry’s role should be in science and policymaking (despite evidence illustrating that industry involvement in these arenas brings negative consequences to society). 136 137 Corporations and their third parties often conceal their agnogenic practices behind ‘superficially coherent’ 138 arguments—in this case, FSFW’s pronouncements of transparency and independence. References to agnogenesis by FSFW-funded researchers serve to redirect attention away from tobacco industry-created ignorance, with one lamenting the current ‘topsy-turvy era in which the truth is framed as a lie and lies are believed as if they are true’. 70

Strengths and limitations

We illustrate the breadth of FSFW’s activities and outputs, demonstrating that PMI’s influence on science goes far beyond creation of its own evidence (which has recently again seen its robustness questioned). 139 140 We also demonstrate the relevance of the SPM to contemporary tobacco industry involvement in science—highlighting that science continues to be an important component of the industry’s political strategy, and corroborating previous investigations 16 141 142 which concluded that science is a ‘critical resource for contemporary corporations in managing their relationships to their critics’. 142

We make no claims about whether FSFW and those it funds are intentionally working to further the tobacco industry’s interests, but instead show how it can work to that effect. Although FSFW argues that PMI’s funding has no effect on its research, 63 evidence shows that financial links can create an ‘implicit demand’ for researchers’ work to benefit the funder, and those in receipt of funds can respond to such pressures unintentionally and subconsciously. 143 Further, although all researchers rely on personal interests and experiences to shape their research, financial COIs, specifically, act as a ‘megaphone, amplifying a set of interests that align with the sponsor’s’. 144 Despite FSFW claiming a ‘confluence’ rather than ‘conflict’ of interest exists (with funder and researchers similarly striving for reduced harm from tobacco), 145 the WHO’s FCTC asserts there is an ‘irreconcilable conflict’ between the tobacco industry’s interests and public health. 146

Similarly, it was not the function of this paper to draw conclusions on any potential role (or otherwise) of the industry’s newer products in reducing tobacco harms. Rather, with our case study adding to growing evidence that corporate involvement in science continues to bring deleterious effects, we reiterate the standpoint 147 that a distinction must be made between products (some of which may play a role in tackling the tobacco epidemic) and producers (who should play no role in tobacco control science and policymaking).

Where we did not find evidence of a strategy, this may be because FSFW is not engaging in such activities, or because our analysis mainly relied on publicly available documents (and was therefore unlikely to find evidence of covert activity). Such ‘gaps’ also indicate areas (including funding of medical education 148 and links with authors of clinical practice guidelines 149 ) where ongoing monitoring could be focused. Conversely, we found evidence of a relatively new 150 scientific communication route not identified in the SPM—dissemination of industry-funded science through preprint platforms (and later citation of such without mention of its non-peer-reviewed status). This echoes historical tobacco industry activity—funding symposia in order to create scientific outputs and subsequently cite them as if peer reviewed. 2 16

Implications for research, policy and practice

The SPM needs to be applied to additional investigations of industry involvement in science, in order to further test and develop the model. Future research could also focus on the SPM’s strategy D (‘Create industry-friendly policymaking environments which shape the use of science in policy decision-making in industry’s favour’). While this was not the focus of the current study, we did note FSFW’s espousal of a risk-based (rather than precautionary) approach to policymaking. 73 FSFW frames such an approach as ‘science based’ 151–155 arguing governments should ‘shift away from prohibitionist policies to more empathetic and science-based policies’. 151 This mirrors previous tobacco industry pushes for so-called ‘science-based’ policymaking, which in the 1990s included covert attempts to inhibit policymakers’ abilities to use whole evidence bases in regulatory decision-making on corporate products. 16 FSFW’s denigration of precautionary approaches to policymaking indicates the potential for the organisation to be used as a conduit for similar attempts.

PMI’s funding of FSFW endangers progress made in protecting science from tobacco industry influence in several significant ways. First, FSFW undermines proposed standards 6 for using tobacco industry funding for research. By claiming to meet these standards, it disingenuously positions itself, an industry-funded scientific organisation founded with no external oversight, as the solution to industry influence on science.

Second, PMI channelling research funds through FSFW sidesteps—and thus renders ineffective—policies adopted by a growing number of academic journals which intend to prohibit publication of tobacco industry-funded science and/or mandate declaration of author COIs. 7 8 156 157 Such policies require industry-funded researchers to be fully compliant in their disclosures (we show this was rarely the case in FSFW-funded science and research) or require journal editors to be fully informed of scientific organisations’ connections to the tobacco industry (which is virtually impossible given our finding of the growing network of grantees and subgrantees).

Further, FSFW circumvents norms about the unacceptability of collaborating with the tobacco industry, jeopardising the industry denormalisation achieved since the forced closure of the historical industry-funded scientific organisations. The American Journal of Public Health’s invitation to FSFW staff to comment on tobacco regulatory issues, 60 the University of California’s approval of grant funding from FSFW 158 and the Conrad Foundation’s acceptance of FSFW funds for its children’s science competition 159 are unlikely to have occurred had the funding come directly from a tobacco company: equivalent relationships with PMI would not have been deemed normatively appropriate. Such decisions augment PMI’s recent direct attempts to normalise its presence in science and policy spheres. 160 161

It is crucial that decision-makers in research, education, academia, policy and practice are aware of the role third-party organisations such as FSFW play in corporate influence on science. Beyond this, our findings indicate that over 70 years since the tobacco industry began to manipulate science, efforts to protect science from tobacco industry interference remain inadequate. The development of more robust systems to better protect scientific integrity is urgently needed.

Ethics statements

Patient consent for publication.

Not required.

Ethics approval

Not applicable.

Acknowledgments

We thank other members of the Tobacco Control Research Group at the University of Bath, the STOP team and the wider tobacco control community for sharing data with us. We are also grateful for the constructive feedback provided by the four reviewers.

  • Apollonio DE ,
  • National Association of Attorneys General
  • United States District Court for the District of Columbia
  • Eissenberg T , et al
  • Timmis A , et al
  • Gilmore AB ,
  • Legg T , et al
  • ↵ Foundation for a Smoke-Free World. Funding: FSFW . 2019 . Available : https://web.archive.org/web/20190530131004/https:/www.smokefreeworld.org/our-vision/funding [Accessed 30 May 2019 ].
  • van der Eijk Y ,
  • Gifford H , et al
  • Global Center for Good Governance in Tobacco Control
  • World Health Organization
  • Johns Hopkins Bloomberg School of Public Health
  • Hatchard J ,
  • Fernandez Pinto M
  • ↵ United States District Court U.S. vs. Philip Morris USA Iea. 99-CV-02396GK, Final Opinion United States District Court . 2006 . Available : https://www.justice.gov/sites/default/files/civil/legacy/2014/09/11/amended%20opinion_0.pdf
  • Peeters S ,
  • Weishaar H ,
  • Smith K , et al
  • Gilmore AB , et al
  • McDaniel PA ,
  • Krippendorf K
  • Foundation for a Smoke-Free World
  • O’Leary R ,
  • Tashkin D , et al
  • Murkett R ,
  • Tobacco Control Research Group
  • McKenzie JE ,
  • Bossuyt PM , et al
  • Rajkumar S ,
  • Special Issue
  • Legendre M ,
  • Yurekli AA ,
  • Kovacevic P ,
  • Sunley E , et al
  • Patwardhan S ,
  • Paskow MJ , et al
  • Akamwaza C ,
  • Matola AM , et al
  • Patwardhan P ,
  • Janmohamed K ,
  • Jiang J , et al
  • Drugs Habits and Social Policy
  • Wilson D , et al
  • Gilchrist M
  • New Zealand Health Select Committee
  • Cameron P ,
  • Kostin JS ,
  • Zaks JM , et al
  • U.S. Environmental Protection Agency
  • World Health Organization International Agency for Research on Cancer
  • U.S. Department of Health and Human Services
  • Mölenberg FJM ,
  • Westenberg LEH , et al
  • Mackay DF ,
  • Haw S , et al
  • Erkkila BE ,
  • Kovacevic PI ,
  • Gentzke AS ,
  • Creamer MR , et al
  • Kozlowski LT ,
  • Peitsch M ,
  • Ebajemito JK , et al
  • Knowledge Action Change
  • Brand Press
  • Global Forum on Nicotine
  • Filter Magazine
  • Scheibein F
  • Southeast Asian Tobacco Control Alliance
  • U.S. Food & Drug Administration
  • Truth Initiative
  • Eissenberg T
  • Vinchurkar S ,
  • Jhamtani R , et al
  • Patwardhan P
  • Jhamtani EC , et al
  • Li Volti G , et al
  • Caponnetto P ,
  • Polosa R , et al
  • Phillips CV
  • Campagna D ,
  • Di Pino A , et al
  • Ainooson J ,
  • Billings A , et al
  • Tobacco Harm Reduction Brasil
  • Tobacco Harm Reduction Congo
  • Tobacco Harm Reduction Kenya
  • Tobacco Harm Reduction Malawi
  • Tobacco Harm Reduction Nigeria
  • Tobacco Harm Reduction Uganda
  • Yurekli A ,
  • Sarcevic L , et al
  • ↵ IOGT International and Big Alcohol Exposed. Alcohol Industry Interference Worldwide Movendi . 2019 . Available : https://movendi.ngo/wp-content/uploads/2019/05/Alcohol-industry-overview-2019.pdf [Accessed 3 Sep 2021 ].
  • Freudenberg N
  • Williams S ,
  • Box G , et al
  • Lasseter T ,
  • Organized Crime and Corruption Reporting Project
  • Ulucanlar S ,
  • Loewenstein G
  • SABC Digital News
  • World Health Organization Framework Convention on Tobacco Control
  • Fitzpatrick I ,
  • Bertscher A ,
  • Shimazawa R ,
  • Stamatakis E ,
  • Ioannidis JPA
  • Vietnam Plus
  • Satapathy S
  • PLoS Medicine Editors
  • Laurence L ,
  • Zatonski M , et al

Twitter @bathtr

Contributors All three authors conceived of the paper. TL collected, read and analysed the documents. TL drafted the paper, to which substantial contributions were then made by AG and BC. All authors revised the paper. All authors take responsibility for the content of the paper. TL is responsible for the overall content as guarantor

Funding The majority of TL’s time spent on this research was supported by the South West Doctoral Training Partnership (SWDTP). TL and AG also acknowledge the support of Bloomberg Philanthropies’ Stopping Tobacco Organizations and Products project funding (www.bloomberg.org).

Disclaimer The opinions expressed are those of the authors alone. The funders had no role in study design, data collection, analysis, decision to publish or preparation of the manuscript.

Competing interests In this paper’s section on ‘Influence on the interpretation of science’, we refer to a report on FSFW and PMI which FSFW described as containing 'false narratives' about FSFW. TL and AG are coauthors of this report.

Provenance and peer review Not commissioned; externally peer reviewed.

Read the full text or download the PDF:

Log in using your username and password

  • Search More Search for this keyword Advanced search
  • Latest content
  • Current issue
  • Hosted content
  • BMJ Journals More You are viewing from: Google Indexer

You are here

  • Online First
  • Proton pump inhibitors and the risk of inflammatory bowel disease: a Mendelian randomisation study
  • Article Text
  • Article info
  • Citation Tools
  • Rapid Responses
  • Article metrics

Download PDF

  • 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

Statistics from Altmetric.com

Request permissions.

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

  • 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 ).

  • Download figure
  • Open in new tab
  • Download powerpoint

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.

Read the full text or download the PDF:

'Lies': Fani Willis fights push to remove her from Donald Trump Georgia case

The day's drama included willis running to the courtroom and declaring testimony a lie. from the sidelines, trump blasted the proceedings, and a n.y. judge set a different criminal trial for march..

Editor's note: This file summarizes the news from the Fani Willis hearing on Thursday, Feb. 15. For the latest news on the hearing , please visit our live updates file for Friday, Feb. 16 .

ATLANTA − Fulton County District Attorney Fani Willis is fighting for her professional reputation and the biggest case of her career as former President Donald Trump and several codefendants try to get her, the special prosecutor she's having an affair with , and the entire DA's office thrown off Trump's sprawling Georgia election racketeering case .

In a day of drama that featured Willis running to the courtroom and declaring that witnesses were lying, the fireworks included talk of a rented cabin, trips to Aruba and a Norwegian cruise. In another state, Donald Trump ranted that the whole show was rigged, even as a New York judge set a trial for a different criminal case for March.

The hearing marks the first time a judge is examining if allegations surrounding the relationship between Willis and Nathan Wade, the private attorney she hired to oversee the case , are enough to disqualify one or both of them – and potentially even to dismiss the Georgia election case altogether after three years of investigation and prosecution.

Willis says in court filings that her relationship with Wade began after she brought him on to helm the Trump prosecution, and it has no bearing on the criminal case. But an attorney for Trump codefendant Michael Roman says the defense has witnesses who can prove that their relationship began well before Willis hired Wade to oversee the prosecution.

Prep for the polls: See who is running for president and compare where they stand on key issues in our Voter Guide

Willis fought to quash the hearing − she called it "a ticket to the circus" − but Fulton County Superior Court Judge Scott McAfee on Monday scheduled two days of testimony "because I think it's possible that the facts alleged by the defendant could result in disqualification."

Defense lawyers led by Ashleigh Merchant are trying to remove Willis and Wade from the case based on her allegedly profiting from Fulton County payments to Wade through their relationship.

Here is what is unfolding in today's courtroom action:

More: Fani Willis admits to relationship with prosecutor. What does that mean for the Trump case?

''You don't have to yell at me to make me understand'

The clashes between Fulton County District Attorney Fani Willis and defense lawyers repeated throughout hours of testimony.

Steve Sadow, one of Donald Trump’s lawyers, tried to lead through a series of questions about the condo where Willis lived during from about February 2021 to January 2022.

The time frame is significant because defense lawyers are trying to disqualify Willis and prosecutor Nathan Wade from the case because of a romantic relationship that began in spring 2022. Willis acknowledged that Wade visited the condo occasionally, but not other prosecutors.

“He certainly has come and picked me up,” Willis said. “I don’t remember him being in that condo a lot.”

But as Sadow probed about who else stayed at the condo and she quibbled about the working, his voice rose.

“You don’t have to yell at me to make me understand,” Willis said.

Sadow’s voice rose again during disputes about his questions about her relationship with Wade.

“Please do not yell at me,” Willis said.

--Bart Jansen

DA Willis routinely keeps thousands of dollars in cash on hand

Fulton County District Attorney Fani Willis said she learned from her father to keep cash on hand, either at home for expenses or in a pocket book to be able to bail out of a bad date.

Willis said she routinely has at least a few thousand dollars and as much as $15,000 at home. She said she repaid prosecutor Nathan Wade for trips together to Belize, California and Aruba from that supply.

“If you tell me it’s a G, you’ll get $1,000 back,” Willis said.

Willis advises all women to bring at least $200 in a pocket on dates so they can leave if necessary.

“When you go on a date, you should have cash in your pocket,” she said.

While she couldn’t pinpoint the source of each dollar of her savings, Willis strongly denied getting the money anywhere other than her own paychecks.

“I’m sure the source of it is the work, sweat and tears of me,” Willis said.

‘I’m not on trial’: Willis

Fulton County District Attorney Fani Willis remained combative throughout her testimony in a hearing where defense lawyers are trying to disqualify her from prosecuting former President Donald Trump and 14 co-defendants.

When defense lawyer Ashleigh Merchant asked about her office refusing to provide her travel records, Willis said she herself denied the release because it was personal information.

“You’ve been intrusive in people’s personal lives. You’re confused. You think I’m on trial. These people are on trial for trying to steal and election in 2020,” Willi said, gesturing to the defense table. “I’m not on trial no matter how hard you try to put me on trial.”

‘That’s a lie’: Willis denies relationship with Wade began before 2022

Fulton County District Attorney Fani Willis opened her testimony clashing with defense lawyer Ashleigh Merchant, accusing the legal opponent of lying about her in trying to remove her from the election interference case against Donald Trump and 14 remaining co-defendants.

Willis said accusations that she began the relationship with a special prosecutor, Nathan Wade, in 2019 soon after meeting him at a judicial conference. Willis told Merchant that it was offensive to insinuate that Willis would sleep with a new acquaintance on the same day.

“That’s a lie,” Willis said. “It’s highly offensive when someone lies on you.”

Another witness, Robin Bryant-Yeartie, who knew Willis since college and worked in the district attorney’s office, testified that Willis began dating Wade in 2019. Willis strongly denied that, agreeing with Wade that the relationship began in 2022.

“It’s highly offensive when someone lies on you,” Willis said.

Willis said Yeartie is no longer her friend.

“I think she betrayed our friendship,” Willis said.

A television drama? Georgia DA Fani Willis agrees to testify in election interference hearing

Like a scene in a television drama, Fulton County District Attorney Fani Willis dropped her refusal to testify in a hearing about her relationship with prosecutor Nathan Wade and dramatically entered the courtroom to testify as members of the audience gasped.

“I’m ready to go,” Willis said.

Defense lawyers Ashleigh Merchant and Craig Gillen had been arguing that her testimony was crucial to corroborate Wades affidavit and testimony that Willis reimbursed thousands of dollars in travels costs with him in cash. In addition, another witness said the relationship began in 2019, rather than in 2022, as Wade testified.

“There are deep concerns that that affidavit is false and that Ms. Willis knew it was false,” Gillen said. “It cries out for her testimony.”

Prosecutors initially sought to block her testimony. But Willis showed up to oblige.

Trump: Willis hearing is a 'game changer'   

After his New York hush money hearing ended, Trump began weighing in on the Willis hearing by posting clips of television coverage and adding sardonic comments.

"IT'S A GAME CHANGER," Trump said in one Truth Social post.

In another post, Trump said it is "game over" for the Georgia election case, but that is far from clear at this point.

The hearing affects Willis more than the case against Trump.

-- David Jackson

Judge scolds co-defendant for outburst during Georgia hearing

Fulton County Superior Judge Scott McAfee scolded one of the co-defendants in the election interference case, Georgia Republican Party Chairman David Shafer, after a minor outburst during a hearing Thursday.

A lawyer for another defendant, Ashleigh Merchant, was in the midst of asking prosecutor Nathan Wade about spending on travel with District Attorney Fani Willis. Wade testified that Willis shared the expenses by reimbursing him with cash, but that he didn’t have any records of it.

“It was cash,” Wade said. “She didn’t give me any checks.”

At that point, Shafer made a noticeable outburst.

“Mr. Shafer, you’ll step out if you do that again,” McAfee said.

Never went to an ATM together

Special Prosecutor Nathan Wade said that while Fani Willis paid him many thousands of dollars in cash as reimbursement for the trips they took together that he put on his credit card, he kept no records of ATM deposits or anything else to corroborate that.

Defense lawyer Craig Gillen pressed Wade on that repeatedly as part of a line of questioning aimed at determining whether Wade used county money he received as special prosecutor for the trips and that Willis derived some financial benefit from it.

After Willis reimbursed him in several cases, including one trip that he put $2,794 on his credit card for, “did you scamper down to the ATM with Ms. Willis” to deposit the money, creating a record of the payment, Gillen asked.

Wade responded that he never went with Willis to an ATM together.

“You don’t have a single solitary deposit slip to document depositing … these thousands of dollars,” the money?” Gillen asked.

“Not a one,” Wade responded.

“Do you have a place in your house that you stack up all this cash Mis Willis paid you?” Gillen asked.

No, Wade responded. Over more than 15 minutes of questioning, Wade said he has no away of documenting any of the case Willis purportedly gave him. And he said that in a discussion of the controversy with Willis, he didn’t ask her if she had a way of documenting that she reimbursed him for trips to Aruba and elsewhere.

-- Josh Meyer

Harsh questions continue into Wade’s relationship with Willis

Another defense lawyer hammered prosecutor Nathan Wade over his sexual relationship with District Attorney Fani Willis, despite providing sworn statements in his divorce that he hadn’t entertained women.

Wade replied “none” in a statement May 30, 2023, to written questions in his divorce about whether he had a romantic relationship or entertained women.

Craig Gillen, a lawyer for co-defendant David Shafer, asked whether Wade had had sex with Willis by then. He also asked whether he had entertained

“I’m not here to jump into some salacious bedroom situation,” Gillen said.

Wade replied to the series of questions: “Yes.”

But Wade continued to argue that his marriage was irretrievably broken in 2015, which was why he answered the written questions with the term “none.”

“Your answer to this interrogatory is false, is it not, sir?” Gillen asked.

“No, it is not false,” Wade said.

Fulton County Superior Judge Scott McAfee halted the line of questions at that point.

“You’ve made your point,” McAfee said.

Aruba and a Norwegian cruise: 'I book a lot of cabins'

During his testimony, Nathan Wade would often parse questions. He testified that he didn’t have credit card receipts, just monthly statements. He would stay overnight with Willis but never cohabitated with her.

When questioned about specific travel expenses, such as a $3,835 charge to Aruba or $1,276 for a Royal Caribbean cruise or a $3,387 Norwegian cruise, Wade often challenged the details. He traveled on the first part of the Caribbean cruise with his mother after her retirement, then flew to Aruba with Willis. The Norwegian cruise included his sisters and their husbands.

In each case, Wade said Willis reimbursed him for her share. Although he booked a Belize vacation in March 2023, Willis reimbursed him for the entire trip for his birthday, Wade said.

But Wade disputed that a $1,481 charge for a Tennessee cabin in August 2023 involved Willis.

“I book lots of cabins,” Wade said.

-- Bart Jansen

‘We’re private people’: Wade on relationship with Willis

Nathan Wade, a special prosecutor hired in the Georgia election interference case against Donald Trump, said he and District Attorney Fani Willis weren’t trying to conceal their romantic relationship but were private people.

Defense lawyers are asking Fulton County Superior Judge Scott McAfee to disqualify Wade and Willis from the case by arguing that she benefited from government payments to Wade through their relationship. But Willis and Wade contend the relationship began about March 2022 – after he was hired in November 2021 – and that she has not profited from it.

“I’ve never purchased a gift for Ms. Willis,” Wade testified Thursday, and they shared expenses when traveling together.

The couple would take day trips to Tennessee to avoid the spotlight in Fulton County, he said. Foreign trips were “a task,” he said, because Willis is widely recognized.

Wade said he and Willis weren’t trying to conceal the relationship but he didn’t discuss it with others.

“We’re private people,” Wade said. “Our relationship wasn’t a secret. It was private.”

Trump talks conspiracies over New York hush money case

As court let out for lunch in Atlanta, Trump posted an angry rant on his social media site, Truth Social, falsely claiming that the Biden administration had seized the reins of his New York hush money trial. 

"Just left the Courthouse in Manhattan. Biden’s DOJ people have taken control of the case," he wrote. "There was NO CRIME, and almost all legal scholars are saying that."

Trump faces 34 felony counts in New York for allegedly falsifying business records to cover up hundreds of thousands of dollars in hush money payments he made to buy the silence of adult film actress Stormy Daniels and former Playboy model Karen McDougal ahead of the 2016 election. The trial will begin on March 25, Justice Juan Merchan ruled on Thursday. 

Former South Carolina Gov. Nikki Haley, the former president's last serious challenger for the 2024 Republican nomination, said the former president’s legal problems will make him a weak general election candidate against President Joe Biden.

“Donald Trump is in court today,” Haley said on X. “There will be a verdict on another case tomorrow. And he has a trial starting March 25...All of this chaos will only lead to more losses for Republicans up and down the ticket.”

-- Dan Morrison and David Jackson

'I have no receipts'

Nathan Wade noted that he also submitted documents in his divorce case twice in 2021 and updated in May 2023 stating he had no receipts – “none” – for spending on travel, hotels and restaurants with women. Wade explained that he has statements from his credit card company, but not receipts.

“I have the statements,” Wade said. “I have no receipts.”

Wade testified that he and Willis shared travel expenses on trips to Belize, California and Aruba. Wade said he would often book the flights and hotels, and she would reimburse him for her share in cash, he said.

“She’s a very independent woman so she’s going to insist she carries her own weight,” Wade said of Willis. “She is going to pay her own way.”

'I was free to have a relationship': Nathan Wade

Prosecutor Nathan Wade clarified sworn statements about his relationship with District Attorney Fani Willis and how they split travel expenses during an extraordinary hearing over whether a judge will remove Willis from the case against former President Donald Trump and 14 remaining co-defendants.

Wade acknowledged a romantic relationship with Willis began about March 2022, despite denying extramarital affairs in a earlier document. Wade explained on the witness stand Thursday that he considered his marriage “irretrievably broken'' in 2015.

“I was free to have a relationship,” Wade said.

'I have to jog my memory'

Ashleigh Merchant, an attorney for one of Donald Trump's co-defendants, used her courtroom time to march through a long series of questions about how Nathan Wade paid for all their trip and how Fani Willis paid him back.

Wade, who squirmed a bit on the witness stand, said it was because she was a high-profile figure and wanted to keep a low profile -- except one expense which she paid herself.

"I have to jog my memory,'' Wade said, when asked about all the trips they took together.

Claims of attorney-client privilege derail testimony from Wade defense lawyer

Terrence Bradley, a lawyer who represented prosecutor Nathan Wade in his divorce, refused to testify at all about any potential relationship between Wade and District Attorney Fani Willis because of attorney-client privilege.

“I have a law license and I don’t want to lose it,” said Bradley, who acknowledged representing Wade starting in 2018 – before the relationship between Wade and Willis began in 2019.

But defense lawyers – including Ashleigh Merchant for Mike Roman and Steve Sadow for Donald Trump – argued that attorney client privilege applies only to legal advice and not to observations about the relationship.

“His observations are not privileged,” Merchant said.

Sadow said attorney client privilege governs communications, not what Bradley may have seen or heard.

“There is no such law that protects such confidences,” Sadow said. “There is no bar rule to that effect.”

To avoid the impasse, Merchant agreed to drop Bradley for the time being and instead begin questioning Robin Bryant-Yeartie, a longtime Willis associate who previously worked at the district attorney’s office.

--Josh Meyer and Bart Jansen

Willis lawyer asks for sanctions against defense lawyer

The hearing before Fulton County Superior Judge Scott McAfee started with a bang, with prosecutors asking for sanctions against defense lawyers and a defense lawyer arguing she could prove misconduct through her witnesses.

Adam Abbate, a lawyer for District Attorney Fani Willis, opened the hearing by arguing that defense lawyer Ashleigh Merchant had made misrepresentations in her allegations about Willis’ relationship with another prosecutor, Nathan Wade.

Abbate accused Merchant of seeking nothing more than “harassment and spectacle” and asked for sanctions for her lack of candor. “Those are misrepresentations that are not true,” Abbate said.

But Merchant, who represents Mike Roman, a former White House aide to Donald Trump and a co-defendant in the case, said she could prove her allegations through witnesses.

Merchant said one witness, Robin Bryant-Yeartie, a longtime Willis associate who previously worked at the district attorney’s office, was terrified of testifying but agreed to appear.

“I have a huge good-faith basis for everything I put in every single motion,” Merchant said.

Away from the Georgia action, Trump complains of a 'rigged city'

Donald Trump was focusing his attention Thursday on the courtroom drama in New York, where a judge earlier had ruled that a criminal case involving hush money paid on his behalf would go to trial on March 25.

"Instead of being in South Carolina and other states campaigning, I'm stuck here," Trump told reporters outside the courthouse.

Trump added: "I'll be here during the day and campaigning during the night."

Trump must attend the hush money trial.

During a rant to reporters, Trump accused New York officials of trying to derail his campaign, and complained about the high crime rate in the city.

"It's a rigged state," Trump said, using the same phrase he has applied to elections that went against him. "It's a rigged city."

-David Jackson

'There is no crime'

In addition to the Georgia hearing, Donald Trump was attending a hearing in New York in his hush money case, which he attacked as politically motivated.

“Heading to yet another Courthouse in Manhattan on a case that would have never been brought if I wasn’t running for Pres.,” Trump said on Truth Social as he traveled to the courthouse.

Claiming “there is no crime,” or case, Trump added: “They want it before Election - Could have been brought 3 years ago. They waited until Election Period.”

More: Why the Fani Willis hearing could decide the fate of Trump's Georgia election case

Where is Donald Trump today?

Donald Trump has another court hearing today , in New York, and he is focusing his efforts on that.

A New York judge will meet Thursday with Trump for what could become the  first criminal trial against  the former president, on  charges he falsified business records  to  pay women hush money .

Trump has pleaded not guilty in that case. He is in New York this morning for that hearing, which will determine whether a trial will move forward in March.

Related: Donald Trump's hush money criminal trial will start March 25, New York judge says

What is Donald Trump charged with?

The former president and a network of allies are accused in a sweeping 41-count indictment of operating a criminal enterprise to overturn the 2020 election. Prosecutors listed 161 separate events that allegedly show Trump's intention to steal the Georgia election after he was defeated by Democrat Joe Biden by a slim 11,779 votes.

These include an infamous January 2021 phone call in which Trump asked Georgia Secretary of State Brad Raffensperger to "find" enough votes to eclipse Biden's total. “I just want to find 11,780 votes," Trump said, according to a recording of the call.

Eighteen codefendants were charged alongside Trump, including former White House chief of staff Mark Meadows and former New York mayor Rudy Giuliani. Four codefendants, including firebrand attorney Sidney Powell and Trump campaign lawyer Jenna Ellis, have pleaded guilty and agreed to assist the prosecution.

-- Dan Morrison

When does the Fani Willis hearing start on Thursday?

Judge Scott McAfee had originally set Thursday's hearing for 2 p.m., but he moved the start time back to 9:30 a.m., acknowledging the amount of testimony and evidence that could be presented to the court.

The evidentiary hearings in McAfee's courtroom are scheduled to continue on Friday . The judge isn't expected to immediately rule on Trump codefendant Michael Roman's request to disqualify DA Fani Willis.

It's unclear when McAfee will issue his decision.

COMMENTS

  1. 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.

  2. 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.

  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 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.

  5. 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.

  6. 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.

  7. 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).

  8. 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.

  9. 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...

  10. 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 ...

  11. 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.

  12. 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 ...

  13. 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).

  14. LibGuides: Study Designs in the Health Sciences: Case-Control

    A case-control study of readmission to the intensive care unit after cardiac surgery. Med Sci Monit. 2013 Feb 28; 19:148-52. The aim of this study was to identify predictors of repeated admission to the intensive care unit (ICU) of patients who underwent cardiac surgery procedures. This retrospective study analyzed 169 patients who underwent ...

  15. 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

  16. Case-control study: Video, Anatomy & Definition

    A case-control study is an observational method used to compare a group of individuals with a particular condition (the cases) to another, a similar group of people without that condition (the controls). The investigation begins after researchers have identified a group of people with the condition they wish to study.

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

    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

  18. Case-Control Study: Definition, Real Life Examples

    A case-control study is a retrospective study that looks back in time to find the relative risk between a specific exposure (e.g. second hand tobacco smoke) and an outcome (e.g. cancer). A control group of people who do not have the disease or who did not experience the event is used for comparison. The goal is figure out the relationship ...

  19. Case-Control Study- Definition, Steps, Advantages, Limitations

    A case-control study (also known as a 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. It is designed to help determine if an exposure is associated with an outcome (i.e., disease or condition of interest).

  20. Frontiers

    The main objective of this study was to observe the dynamic changes of serum taurine during pregnancy and investigate the relationship between serum taurine levels and GDM in the first and second trimesters. Methods: This was a nested case-control study in 47 women with GDM and 47 age-matched normoglycemic women. We examined serum taurine at 8 ...

  21. 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 ...

  22. Epiville: Case-Control Study -- Introduction

    The case-control study design is an excellent choice of study when the disease is rare, has a long induction period , the exposure data are difficult to obtain, or very little is known about the disease. In these situations a cohort study is generally prohibitively expensive or the time frame of the study required for data collection is ...

  23. IJMS

    The case-control study included 471 Caucasian subjects divided into two groups. The first group consisted of 231 patients with angiographically confirmed premature CAD, aged 44.37 ± 5.96 years and 55 years as the upper age limit of probands. The second group included 240 control blood donors (BD group), aged 43.35 ± 6.41 years, without ...

  24. Safety of pregnancy after cerebral venous thrombosis: A case‐control study

    A retrospective, case-control study was conducted at the Obstetrics Departments of King Fahad Medical City Hospital, Saudi Arabia. It included all women with a history of CVT diagnosed in the last 5 years (cases), as well as CVT history-free pregnant women (control). The prevalence of pregnancy after CVT was estimated and the prepartum and ...

  25. Hand enthesitis as a dominant lesion in psoriatic arthritis

    Hand enthesitis as a dominant lesion in psoriatic arthritis: Distinguishing features from rheumatoid arthritis—A case-control ultrasound study Emanuel Costa , Corresponding Author

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

    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 ...

  27. Document analysis of the Foundation for a Smoke-Free ...

    Background Tobacco corporation Philip Morris International launched the Foundation for a Smoke-Free World (FSFW), a purportedly independent scientific organisation, in 2017. We aimed to systematically investigate FSFW's activities and outputs, comparing these with previous industry attempts to influence science, as identified in the recently developed typology of corporate influence on ...

  28. 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 …

  29. Fani Willis hearing adds drama to Trump case in Georgia

    Willis fought to quash the hearing − she called it "a ticket to the circus" − but Fulton County Superior Court Judge Scott McAfee on Monday scheduled two days of testimony "because I think it ...

  30. Takeaways from Fani Willis' stunning testimony in Georgia

    The Georgia election subversion case against Donald Trump and 14 of his allies took a stunning turn Thursday when two top prosecutors testified under oath about their romantic relationship at a ...