population in the research study

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Study Population: Characteristics & Sampling Techniques

How do you define a study population?  Research studies require specific groups to draw conclusions and make decisions based on their results. This group of interest is known as a sample. The method used to select respondents is known as sampling.

What is a Study Population?

A study population is a group considered for a study or statistical reasoning. The study population is not limited to the human population only. It is a set of aspects that have something in common. They can be objects, animals, measurements, etc., with many characteristics within a group.

For example, suppose you are interested in the average time a person between the ages of 30 and 35 takes to recover from a particular condition after consuming a specific type of medication. In that case, the study population will be all people between the ages of 30 and 35.

A medical study examines the spread of a specific disease in stray dogs in a city. Here, the stray dogs belonging to that city are the study population. This population or sample represents the entire population you want to conclude about.

How to establish a study population?

Sampling is a powerful technique for collecting opinions from a wide range of people, chosen from a particular group, to learn more about the whole group in general.

For any research study to be effective, it is necessary to select the study population that truly represents the entire population. Before starting your study, the target population must be identified and agreed upon. By appointing and knowing your sample well in advance, any feedback deemed useless to the study will be largely eliminated.

If your survey aims to understand a product’s or service’s effectiveness, then the study population should be the customers who have used it or are best suited to their needs and who will use the product/service.

It would be costly and time-consuming to collect data from the entire population of your target market. By accurately sampling your study population, it is possible to build a true picture of the target market using the trends in the results.

LEARN ABOUT: Survey Sampling

Choosing an accurate sample from the study population

The decision on an appropriate sample depends on several key factors.

• First, you decide which population parameters you want to estimate.
• Don’t expect estimates from a sample to be exact. Always expect a margin of error when making assumptions based on the results of a sample.
• Understanding the cost of sampling helps us determine how precise our estimates need to be.
• Know how variable the population you want to measure is. It is not necessary to assume that a large sample is required if the study population is large.
• Take into account the response rate of your population. A 20% response rate is considered “good” for an online research study.

Sampling characteristics in the study population

• Sampling is a mechanism to collect data without surveying the entire target population.
• The study population is the entire unit of people you consider for your research. A sample is a subset of this group that represents the population.
• Sampling reduces survey fatigue as it is used to prevent pollsters from conducting too many surveys, thereby increasing response rates.
• Also, it is much cheaper and saves more time than measuring the entire group.
• Tracking the response rate patterns of different groups will help determine how many respondents to select.
• The study is not only limited to the selected part, but is applied to the entire target population.

Sampling techniques for your study population

Now that you understand that you cannot survey the entire study population due to various factors, you should adopt one of the sample selection methodologies that best suits your research study.

In general terms, two methodologies can be applied: probability sampling and non-probability sampling .

Sampling Techniques: Probability Sampling

This method is used to select sample objects from a population based on probability theory. Everyone is included in the sample and has an equal chance of being selected. There is no bias in this type of sample. Every person in the population has the opportunity to be part of the research.

Probability sampling can be categorized into four types:

• Simple Random Sampling : Simple random sampling is the easiest way to select a sample. Here, each member has an equal chance of being part of the sample. The objects in this sample are chosen at random, and each member has exactly the same probability of being selected.
• Cluster sampling : Cluster sampling is a method in which respondents are grouped into clusters. These groups can be defined based on age, gender, location, and demographic parameters.
• Systematic Sampling : In systematic sampling, individuals are chosen at equal intervals from the population. A starting point is selected, and then respondents are chosen at predefined sample intervals.
• Stratified Sampling: S tratified random sampling is a process of dividing respondents into distinct but predefined parameters. In this method, respondents do not overlap but collectively represent the entire population.

Sampling techniques: Non-probabilistic sampling

The non-probability sampling method uses the researcher’s preference regarding sample selection bias . This sampling method derives primarily from the researcher’s ability to access this sample. Here the population members do not have the same opportunities to be part of the sample.

Non-probability sampling can be further classified into four distinct types:

• Convenience Sampling: As the name implies, convenience sampling represents the convenience with which the researcher can reach the respondent. The researchers do not have the authority to select the samples and they are done solely for reasons of proximity and not representativeness.
• Deliberate, critical, or judgmental sampling: In this type of sampling the researcher judges and develops his sample on the nature of the study and the understanding of his target audience. Only people who meet the research criteria and the final objective are selected.
• Snowball Sampling: As a snowball speeds up, it accumulates more snow around itself. Similarly, with snowball sampling, respondents are tasked with providing references or recruiting samples for the study once their participation ends.
• Quota Sampling: Quota sampling is a method where the researcher has the privilege to select a sample based on its strata. In this method, two people cannot exist under two different conditions.

LEARN ABOUT: Theoretical Research

Advantages and disadvantages of sampling in a study population

In most cases, of the total study population, perceptions can only be obtained from predefined samples. This comes with its own advantages and disadvantages. Some of them are listed below.

• Highly accurate – low probability of sampling errors (if sampled well)
• Economically feasible by nature, highly reliable
• High fitness ratio to different surveys Takes less time compared to surveying the entire population Reduced resource deployment
• Data-intensive and comprehensive Properties are applied to a larger population wideIdeal when the study population is vast.

Disadvantages

• Insufficient samples
• Possibility of bias
• Precision problems (if sampling is poor)
• Difficulty obtaining the typical sample
• Lack of quality sources
• Possibility of making mistakes.

At QuestionPro we can help you carry out your study with your study population. Learn about all the features of our online survey software and start conducting your research today!

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Selecting the Study Participants

Defining the target population is an essential part of protocol development to ensure that the study participants are well suited to the research question ( Hulley et al., 2013 ). The target population is the entire group of people who share a common condition (disease process) or characteristic the researcher is interested in studying ( Elfil & Negada, 2017 ). While the ' accessible population' is the geographically and temporally classified subset that is available for the study participant recruitment ( Hulley et al., 2013 ). The clinical and demographic characteristics of the accessible population are determined using a ruled based eligibility criterion in which all study participants must have to join a study. The choice of study participants must also consider the cost in time and money to obtain the required number of study participants. This paper in the Step by Step Research series provides an introduction to designing the eligibility criteria and recruitment considerations to select the study participants. Future articles will discuss sampling (random and non-random) approaches and sample size determination.

Introduction to Designing the Eligibility Criteria

All clinical research protocols must have an Eligibility Criteria Section , which includes both an inclusion and exclusion criteria. Common elements used to determine suitability for a study are age, gender, medical condition, specific disease examined, and medications. The development of the study criteria must also consider participant safety and review potential interactions with an intervention such as a study medication or a study diet that might interfere with a participant's current medication or concurrent health condition. The eligibility criteria should be representative of the target population to improve understanding of the disease processes, new treatment options, and socio-demographic trends ( Hulley et al., 2013 ). To illustrate the development of the eligibility criteria, see table 1 : Designing the Eligibility Criteria: Clinical Trial for High Triglycerides Among Individuals with HIV Using Fish Oil Versus Placebo. Discussed below is the rationale for the selection of the inclusion and exclusion criteria for this study.

Designing the Eligibility Criteria: * Clinical Trial for High Triglycerides Among Individuals with HIV Using Fish Oil Versus Placebo

Adapted with permission:(Cummings, 2013)

Inclusion Criteria Considerations

The inclusion criteria describe the study participants that fulfill the needs of the clinical research question. Commonly used elements for the inclusion criteria include demographic characteristics, clinical attributes, geographic factors, and temporal considerations ( Panacek & Thompson, 2007 ) ( Hulley et al., 2013 ). Defining the inclusion criteria helps to maintain a degree of homogeneity among the accessible population and narrows the available pool of eligible study participants that reflect the study question ( Panacek & Thompson, 2007 ). The inclusion criteria should also address the capacity of the participant to understand the study goals, the study requirements (i.e., attending study visits, completing questionnaires, blood draws, taking study medications), and the potential risks associated with joining a study.

For example, the study exploring the efficacy of over-the-counter fish oil supplementation among HIV+ individuals with high triglyceride considers an age limitation since fish oil can reduce the CD4+ level, and advanced ages are associated with the accelerated loss of the CD4+ level. A triglyceride parameter (fasting serum triglyceride levels between 150-500 mg/dl) is also required to capture participants with the condition, yet limits those with extremely elevated levels and likely eligible for prescription fish-oil treatment. Additionally, parameters for the CD4+ level (CD4+ T cell count ≥ 300 cells/mm 3 ) is necessary to ensure the participants' immune systems are stable. Travel to the study sight is another vital consideration. Geographic limitations are essential if virtual study visits (i.e., web-based interventions) are not possible, and face-to-face interactions are necessary. Using geographic boundaries may reduce missed study visits due to the distance of the study sight from participants' homes. An example of a temporal characteristic using the sample study is the requirement to wait for a minimum of six months or more after starting a new HIV drug regimen. The waiting period reduces the likelihood that the elevated triglyceride level was a temporary elevation and returns to normal levels once the proper dosage achieved.

The informed consent process is the final consideration for the inclusion criteria. A future article in this series will discuss the ethics, including concerns relating to the potential for coercion or undue influence, and the ability of the study participant to provide verbal and written consent.

Exclusion Criteria Considerations

The exclusion criteria contain the characteristics of the potential study participant who meet the inclusion criteria but have conditions that could affect the outcome of the study in terms of the success or the increased risks of possible adverse effects ( Patino & Ferreira, 2018 ). Therefore, the exclusion criteria is a mechanism to reduce potential study risks and reduce potential confounding variables ( Panacek & Thompson, 2007 ). Confounding variables may affect the outcome of interest (dependent variable), as in the sample study, the triglyceride level is the dependent variable. Therefore, potential participants using fish oil are not eligible to join.

In formulating the exclusion criteria, Hulley and colleagues (2013) recommend considering factors that increase the likelihood of loss to follow-up, the inability to provide necessary data, and the high risk of possible adverse effects related to co-morbidities or current treatments.

In continuing the HIV and high triglyceride example, participants actively abusing alcohol and illicit substances are not eligible to join this study. The chronic use of some substances can lead to changes in the brain and linked with the development of mental health issues such as paranoia, hallucinations, and other problems (National Institute on Drug Abuse (NIDA) ( NIDA, 2017 )). The use of illicit substances can potentially limit a participant's ability to comprehend and comply with the study requirements. The use of a measurement tool that examines attention, recall, and calculation and excluding participants who score below a required screening threshold (less than 23 on the Mini-Mental State Examination ( Folstein et al., 1975 )) is one method to screen for cognitive impairment and hopefully increase the likelihood for obtaining the required data. Participants with diabetes mellitus are excluded from the study to prevent possible adverse effects since fish oil can raise blood glucose levels and not safe for such participants.

Practical Considerations for Designing the Eligibility Criteria

For a new clinical research study, reviewing published studies with similar study participants and objectives can assist in formulating the eligibility criteria. Examine the approaches used in such investigations. Assess the data on the retention of the participants and evaluate the reasons for lost-to-follow-up. Much can be learned from the experiences of previously conducted studies to assess if methods were successful and allow investigators to apply useful strategies to their new study.

Defining the eligibility criteria requires a delicate balance between restrictive and less restrictive. A restrictive criterion can make participant recruitment and enrollment more difficult since the study requirements can reduce the eligible participant pool. Additionally, the restrictive criteria might impact the time-frame to complete the study, as well as the workforce needed to recruit and to enroll study participants, requiring more time and staff to complete. On the other hand, a less stringent eligibility criterion is often easier to recruit and to enroll participants and can increase the generalizability of a study, but can leave it open to more confounding variables and a heterogeneous participant pool ( Gallin et al., 2018 ).

During the development of the eligibility criteria, review the Code of Federal Regulations (CFR) 45 , which focuses on the protection of human subjects. Since institutional review board (IRB) approval is mandatory for all clinical research studies, IRBs will assess study protocols to ensure it meets the CFR 45 requirements before approving. CFR 45 focuses on the unbiased selection of study participants centered around gender, race, ethnicity, religion, nationality, and other factors ( Gallin et al., 2018 ). CFR 45 stipulates that all eligible study participants are considered unless there is a compelling safety or scientific rationale for excluding them ( Gallin et al., 2018 ). For example, a prostate cancer study can reasonably exclude women since the disease under study is gender-specific. A case to prohibit pregnant women might involve studies with known risks to maternal and fetal health.

In writing the eligibility criteria, use bullets or a numbered list ( Gallin et al., 2018 ). This format makes it easier for IRB review and implementation. A printed or an electronic version of the eligibility criteria placed near the telephone, computer, or participant screening area can provide an excellent guide for study team members to review the study criteria and reduce the chances for incorrectly enrolling ineligible participants.

Study Recruitment

Formulating the recruitment process occurs after the development of the eligibility criteria. The study protocol provides the details of the procedures the research team undergoes to recruit and to enroll study participants. In designing the recruitment plan, consider the anticipated participant accrual rate, which includes the number of participants enrolled per month/year and how long it will take to complete the recruitment goals. Additionally, other critical components of the recruitment process include the identification and the recruitment of participants, and the methods to advertise the study and the evaluation of the recruitment plan ( Gallin et al., 2018 ; University of Rochester, 2018 ).

Describing the specifics of how and where to obtain eligible study participants are also essential components of the study recruitment section. Details include the methods to approach the participants and the setting (i.e., clinic setting, research site). For example, in recruiting for the HIV+ adults with high triglycerides, flyers, and brochures were developed and sent to local HIV clinics in the New York City (NYC) area to promote the availability of the study. Potential participants called the research center to inquire about the HIV study; hence the participants initiated the process to join the research study.

Recruitment materials should include the title of the protocol, IRB study number, the sponsoring institution, contact information, purpose of the research (i.e., HIV+ adults with high triglycerides) and indicate whether compensation for time and effort is given to the study participants ( University of Rochester, 2018 ; Gallin et al., 2018 ). All methods to advertise or promote the study requires IRB approval before implementation. Some examples of recruitment materials include the telephone script used to discuss the study, and flyers, posters, postcards, newspaper advertisements, press releases, website advertisements, electronic mailings and social media blogs, and tweets ( Gelinas et al., 2017 ; University of Rochester, 2018 ). Each IRB may require specific information for recruitment materials to obtain approval.

Most institutions publish their IRB requirements online; therefore, to ensure a smoother review process, read the guidelines associated with each IRB institution. Participant recruitment is often one of the most challenging aspects of conducting clinical research. Delays in participant enrollment account for up to 60% ( Gelinas et al., 2017 ) of issues encountered in clinical research; therefore, a well-thought-out and feasible recruitment plan is vital.

The development of the eligibility criteria is a complex process that can affect participant recruitment, enrollment, and study completion. Reviewing the literature for research studies similar to the proposed target population is an excellent method to identify appropriate eligibility criteria. Developing a feasible recruitment plan in terms of selecting the suitable participant pool and approaches to recruit and enroll the eligible participants is at the cornerstone for implementing a successful study.

Acknowledgments

This manuscript is supported in part by grant # UL1TR001866 from the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health (NIH) Clinical and Translational Science Award (CTSA) program.

• Capili B & Anastasi JK. (2013). Exploratory study: Evaluating the effects of fish oil and controlled diet to reduce triglyceride levels in HIV . Journal Association of Nurses in AIDS Care , 24 ( 3 ), 276–282. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hulley SB, Cummings SR, Browner WS, Grady DG, & Newman TB. (2013). 4 th Edition. Designing Clinical Research An Epidemiologic Approach . Philadelphia, PA. Wolters Kluwer/Lippincott Williams & Wilkins. [ Google Scholar ]
• Elfil M, & Negida A (2017). Sampling methods in clinical research; an educational review . Emergency , 5 ( e52 ). [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Folstein MF, Folstein SE & McHugh PR. (1975). "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician . Journal of Psychiatric Research , 12 ( 3 ), 189–198. [ PubMed ] [ Google Scholar ]
• Gallin J, Ognibene FP, & Johnson LL (Ed.) (2018). Principles and practice of clinical research (4th ed.). Cambridge, MA: Elsevier Inc. [ Google Scholar ]
• Gelinas L, Pierce R, Winkler S, Cohen IG, Lynch HF, & Bierer BE. (2017). Using Social Media as a Research Recruitment Tool: Ethical Issues and Recommendations . American Journal of Bioethics , 17 ( 3 ), 3–14. doi: 10.1080/15265161.2016.1276644 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• National Institutes for Drug Addiction (NIDA) (2017, March 2017). Health Consequences of Drug Misuse . Advancing Addiction Sciences . https://www.drugabuse.gov/related-topics/health-consequences-drug-misuse . Retrieved January 3, 2020. [ Google Scholar ]
• Panacek EA, & Thompson CB. (2007). Sampling methods: Selecting your subjects . Air Medical Journal , 26 ( 2 ), 75–78. doi: 10.1016/j.amj.2007.01.001 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Patino CM, & Ferreira JC. (2018). Inclusion and exclusion criteria in research studies: definitions and why they matter . Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia , 44 ( 2 ), 84–84. doi: 10.1590/s1806-37562018000000088 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• The University of Rochester. (2018, June/19/2018). Guideline for Recruitment Methods and Materials . Retrieved from http://www.rochester.edu/ohsp/documents/ohsp/pdf/policiesAndGuidance/703a_GDL_Recruitment_Methods_Materials.pdf

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3 Study Population

• Published: March 2018
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Chapter 3 discusses the decision-making process of choosing the study population. This is critical given that any study’s main goal is to make inferences that go beyond the individuals under study and can be used to explain the phenomenon in the broader population with shared characteristics or conditions. In this chapter, the definition of the target population is discussed—i.e. the portion of the general population from which a researcher wants to draw robust conclusions or inferences. The sampling process according to the study phase is also summarized, focusing on phase II and III clinical trials, as phase I trials are especially designed to assess safety, while phase IV trials are open-label studies, usually assessing post-marketing safety. The internal and external validity of a study is also discussed, as well as sampling methods, both probabilistic (simple random, systematic, stratified, cluster, or multistage sampling) and non-probabilistic (convenience, consecutive, and snowball sampling).

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Study Population

Cite this chapter.

• Lawrence M. Friedman 6 ,
• Curt D. Furberg 7 ,
• David L. DeMets 8 ,
• David M. Reboussin 9 &
• Christopher B. Granger 10  

114k Accesses

2 Citations

Defining the study population in the protocol is an integral part of posing the primary question. Additionally, in claiming an intervention is or is not effective it is essential to describe the type of participants on which the intervention was tested. Thus, the description requires two elements: specification of criteria for eligibility and description of who was actually enrolled. This chapter focuses on how to define the study population. In addition, it considers two questions. First, what impact does selection of eligibility criteria have on participant recruitment, or, more generally, study feasibility? Second, to what extent will the results of the trial be generalizable to a broader population? This issue is also discussed in Chap. 10 .

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Rothwell PM. External validity of randomized controlled trials: “To whom do the results of this trial apply?” Lancet 2005;365:82–93.

Article   Google Scholar  

CONSORT. http://www.consort-statement.org

Van Spall HGC, Toren A, Kiss A, Fowler RA. Eligibility criteria of randomized controlled trials published in high-impact general medical journals: a systematic sampling review. JAMA 2007;297:1233–1240.

Douglas PS. Gender, cardiology, and optimal medical care. Circulation 1986;74:917–919.

Bennett JC, for the Board on Health Sciences Policy of the Institute of Medicine. Inclusion of women in clinical trials – policies for population subgroups. N Engl J Med 1993;329:288–292.

Freedman LS, Simon R, Foulkes MA, et al. Inclusion of women and minorities in clinical trials and the NIH Revitalization Act of 1993 – the perspective of NIH clinical trialists. Control Clin Trials 1995;16:277–285.

Lee PY, Alexander KP, Hammill BG, et al. Representation of elderly persons and women in published randomized trials of acute coronary syndromes. JAMA 2001;286:708–713.

Google Scholar  

NIH Policy and Guidelines on the Inclusion of Women and Minorities as Subjects in Clinical Research – Amended, October, 2001. http://grants.nih.gov/grants/funding/women_min/guidelines_amended_10_2001.htm

Diabetic Retinopathy Study Research Group: Preliminary report on effects of photocoagulation therapy. Am J Ophthalmol 1976;81:383–396.

Diabetic Retinopathy Study Research Group. Photocoagulation treatment of proliferative diabetic retinopathy: the second report of diabetic retinopathy study findings. Ophthalmol 1978;85:82–106.

Wooster R, Neuhausen SL, Mangion J, et al. Localization of a breast cancer susceptibility gene, BRCA2, to chromosome 13q12-13. Science 1994;265:2088–2090.

Patel MR, Mahaffey KW, Garg J, et al. for ROCKET AF investigators. Rivaroxaban versus warfarin in nonvalvular atrial fibrillation. N Engl J Med 2011;365:883–891.

Veterans Administration Cooperative Study Group on Antihypertensive Agents. Effects of treatment on morbidity in hypertension: results in patients with diastolic blood pressures averaging 115 through 129 mm Hg. JAMA 1967;202:1028–1034.

Veterans Administration Cooperative Study Group on Antihypertensive Agents. Effects of treatment on morbidity in hypertension: II. Results in patients with diastolic blood pressure averaging 90 through 114 mm Hg. JAMA 1970;213:1143–1152.

Hypertension Detection and Follow-up Program Cooperative Group. Five-year findings of the Hypertension Detection and Follow-up Program. 1. Reduction in mortality of persons with high blood pressure, including mild hypertension. JAMA 1979;242:2562–2571.

The CONSENSUS Trial Study Group. Effects of enalapril on mortality in severe heart failure. N Engl J Med 1987;316:1429–1435.

The SOLVD Investigators. Effect of enalapril on survival in patients with reduced left ventricular ejection fractions and congestive heart failure. N Engl J Med 1991;325:293–302.

The SOLVD Investigators. Effect of enalapril on mortality and the development of heart failure in asymptomatic patients with reduced left ventricular ejection fractions. N Engl J Med 1992;327:685–691.

Vollmer T. The natural history of relapses in multiple sclerosis. J Neurol Sci 2007;256:S5-S13.

Sondik EJ, Brown BW, Jr., Silvers A. High risk subjects and the cost of large field trials. J Chronic Dis 1974; 27:177–187.

Ridker PM, Danielson E, Fonseca FAH, et al. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med 2008;359:2195–2207.

http://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm332181.pdf .

Darrow JJ, Avorn J, Kesselheim AS. New FDA breakthrough-drug category—implications for patients. N Engl J Med 2014;370:1252–1258.

McMurray JJV, Packer M, Desai AS, et al. Angiotensin-neprilysin inhibition versus enalapril in heart failure. N Engl J Med 2014;371:993–1004.

Tunis SR, Stryer DB, Clancy CM. Practical clinical trials: increasing the value of clinical research for decision making in clinical and health policy. JAMA. 2003;290:1624–1632.

Thorpe KE, Swarenstein M, Oxman AD, et al. A pragmatic-explanatory continuum indicator summary (PRECIS): a tool to help trial designers. J Clin Epidemiol 2009;62:464–475.

Ridker PM and PREVENT Investigators. Long-term, low does warfarin among venous thrombosis patients with and without factor V Leiden mutation: rationale and design for the Prevention of Recurrent Venous Thromboembolism (PREVENT) trial. Vasc Med 1998;3:67–73.

Mooney MM, Welch J, Abrams JS. Clinical trial design and master protocols in NCI clinical treatment trials. [abstract]. Clin Cancer Res 2014;20(2Suppl):Abstract IA08.

Hakonarson H, Thorvaldsson S, Helgadottir A, et al. Effects of a 5-lipoxygenase-activating protein inhibitor on biomarkers associated with risk of myocardial infarction: a randomized trial. JAMA 2005;293:2245–2256.

The U.S. Food and Drug Administration. Drugs. Table of pharmacogenomics biomarkers in labeling. www.fda.gov/drugs/scienceresearch/researchareas/pharmacogenetics/ucm083378.htm .

Mrazek DA. Psychiatric pharmacogenomics . New York: Oxford University Press, 2010.

Book   Google Scholar  

Landrum MJ, Lee JM, Riley GR, et al. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res 2014;42 (Database issue):D980-5.

Mailman MD, Feolo M, Jin Y, et al. The NCBI dbGaP database of genotypes and phenotypes. Nat Genet 2007;39:1181–1186.

Wilhelmsen L, Ljungberg S, Wedel H, Werko L. A comparison between participants and non-participants in a primary preventive trial. J Chronic Dis. 1976;29:331–339.

Smith P, Arnesen H. Mortality in non-consenters in a post-myocardial infarction trial. J Intern Med 1990; 228:253–256.

Antithrombotic Trialists’ Collaboration. Collaborative meta-analysis of randomized clinical trials of antiplatelet therapy for prevention of death, myocardial infarction, and stroke in high risk patients. BMJ 2002;324:71–86; correction BMJ 2002;324:141.

Steering Committee of the Physicians’ Health Study Research Group. Final report on the aspirin component of the ongoing Physicians’ Health Study. N Engl J Med 1989;321:129–135.

Peto R, Gray R, Collins R, et al. Randomized trial of prophylactic daily aspirin in British male doctors. Br Med J 1988;296:313–316.

Ridker PM, Cook NR, Lee I-M, et al. A randomized trial of low-dose aspirin in the primary prevention of cardiovascular disease in women. N Engl J Med 2005;352:1293–1304.

Ikeda Y, Shimada K, Teramoto T, et al. Low-dose aspirin for primary prevention of cardiovascular events in Japanese patients 60 years or older with atherosclerotic risk factors. A randomized clinical trial. JAMA. Published online November 17, 2014. doi: 10.1001/jama.2014.15690 .

Berger JS, Roncaglioni MC, Avanzini F, et al. Aspirin for the primary prevention of cardiovascular events in women and men: a sex-specific meta-analysis of randomized controlled trials. JAMA 2006;295:306–313; correction JAMA 2006;295:2002.

Pedersen TR. The Norwegian Multicenter Study of timolol after myocardial infarction. Circulation 1983;67 (suppl 1):I-49-1-53.

CASS Principal Investigators and Their Associates. Coronary Artery Surgery Study (CASS): a randomized trial of coronary artery bypass surgery. Comparability of entry characteristics and survival in randomized patients and nonrandomized patients meeting randomization criteria. J Am Coll Cardiol 1984;3:114–128.

Kaariainen I, Sipponen P, Siurala M. What fraction of hospital ulcer patients is eligible for prospective drug trials? Scand J Gastroenterol 1991;186:73–76.

Benedict GW. LRC Coronary Prevention Trial: Baltimore. Clin Pharmacol Ther 1979;25:685–687.

Pitt B, Pfeffer MA, Assmann SF, et al. TOPCAT Investigators. Spironolactone for heart failure with preserved ejection fraction. N Engl J Med 2014;370:1383–1392.

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Lawrence M. Friedman

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David L. DeMets

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Department of Medicine, Duke University, Durham, NC, USA

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Friedman, L.M., Furberg, C.D., DeMets, D.L., Reboussin, D.M., Granger, C.B. (2015). Study Population. In: Fundamentals of Clinical Trials. Springer, Cham. https://doi.org/10.1007/978-3-319-18539-2_4

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Research Population

All research questions address issues that are of great relevance to important groups of individuals known as a research population.

This article is a part of the guide:

• Non-Probability Sampling
• Convenience Sampling
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• 1 What is Sampling?
• 2.1 Sample Group
• 2.2 Research Population
• 2.3 Sample Size
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• 3.1 Statistical Sampling
• 3.2 Sampling Distribution
• 3.3.1 Random Sampling Error
• 4.1 Random Sampling
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• 4.4 Cluster Sampling
• 4.5 Disproportional Sampling
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A research population is generally a large collection of individuals or objects that is the main focus of a scientific query. It is for the benefit of the population that researches are done. However, due to the large sizes of populations, researchers often cannot test every individual in the population because it is too expensive and time-consuming. This is the reason why researchers rely on sampling techniques .

A research population is also known as a well-defined collection of individuals or objects known to have similar characteristics. All individuals or objects within a certain population usually have a common, binding characteristic or trait.

Usually, the description of the population and the common binding characteristic of its members are the same. "Government officials" is a well-defined group of individuals which can be considered as a population and all the members of this population are indeed officials of the government.

Relationship of Sample and Population in Research

A sample is simply a subset of the population. The concept of sample arises from the inability of the researchers to test all the individuals in a given population. The sample must be representative of the population from which it was drawn and it must have good size to warrant statistical analysis.

The main function of the sample is to allow the researchers to conduct the study to individuals from the population so that the results of their study can be used to derive conclusions that will apply to the entire population. It is much like a give-and-take process. The population “gives” the sample, and then it “takes” conclusions from the results obtained from the sample.

Two Types of Population in Research

Target population.

Target population refers to the ENTIRE group of individuals or objects to which researchers are interested in generalizing the conclusions. The target population usually has varying characteristics and it is also known as the theoretical population.

Accessible Population

The accessible population is the population in research to which the researchers can apply their conclusions. This population is a subset of the target population and is also known as the study population. It is from the accessible population that researchers draw their samples.

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• Multiple adverse...

Multiple adverse outcomes associated with antipsychotic use in people with dementia: population based matched cohort study

Linked editorial.

Use of antipsychotics in adults with dementia

• Related content
• Peer review
• Pearl L H Mok , research fellow 1 2 ,
• Matthew J Carr , research fellow 1 2 3 ,
• Bruce Guthrie , professor 4 ,
• Daniel R Morales , Wellcome Trust clinical research fellow 5 ,
• Aziz Sheikh , professor 6 7 ,
• Rachel A Elliott , professor 3 8 ,
• Elizabeth M Camacho , senior research fellow 8 ,
• Tjeerd van Staa , professor 9 ,
• Anthony J Avery , professor 3 10 ,
• Darren M Ashcroft , professor 1 2 3
• 1 Centre for Pharmacoepidemiology and Drug Safety, Division of Pharmacy and Optometry, University of Manchester, Manchester, M13 9PT, UK
• 2 Manchester Academic Health Science Centre, Manchester, UK
• 3 NIHR Greater Manchester Patient Safety Research Collaboration, University of Manchester, Manchester, UK
• 4 Advanced Care Research Centre, Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
• 5 Population Health and Genomics, University of Dundee, Dundee, UK
• 6 Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK
• 7 Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
• 8 Manchester Centre for Health Economics, Division of Population Health, Manchester, UK
• 9 Division of Informatics, Imaging and Data Sciences, University of Manchester, Manchester, UK
• 10 Centre for Primary Care, School of Medicine, University of Nottingham, Nottingham, UK
• Correspondence to: P L H Mok pearl.mok{at}manchester.ac.uk
• Accepted 29 February 2024

Objective To investigate risks of multiple adverse outcomes associated with use of antipsychotics in people with dementia.

Design Population based matched cohort study.

Setting Linked primary care, hospital and mortality data from Clinical Practice Research Datalink (CPRD), England.

Population Adults (≥50 years) with a diagnosis of dementia between 1 January 1998 and 31 May 2018 (n=173 910, 63.0% women). Each new antipsychotic user (n=35 339, 62.5% women) was matched with up to 15 non-users using incidence density sampling.

Main outcome measures The main outcomes were stroke, venous thromboembolism, myocardial infarction, heart failure, ventricular arrhythmia, fracture, pneumonia, and acute kidney injury, stratified by periods of antipsychotic use, with absolute risks calculated using cumulative incidence in antipsychotic users versus matched comparators. An unrelated (negative control) outcome of appendicitis and cholecystitis combined was also investigated to detect potential unmeasured confounding.

Results Compared with non-use, any antipsychotic use was associated with increased risks of all outcomes, except ventricular arrhythmia. Current use (90 days after a prescription) was associated with elevated risks of pneumonia (hazard ratio 2.19, 95% confidence interval (CI) 2.10 to 2.28), acute kidney injury (1.72, 1.61 to 1.84), venous thromboembolism (1.62, 1.46 to 1.80), stroke (1.61, 1.52 to 1.71), fracture (1.43, 1.35 to 1.52), myocardial infarction (1.28, 1.15 to 1.42), and heart failure (1.27, 1.18 to 1.37). No increased risks were observed for the negative control outcome (appendicitis and cholecystitis). In the 90 days after drug initiation, the cumulative incidence of pneumonia among antipsychotic users was 4.48% (4.26% to 4.71%) versus 1.49% (1.45% to 1.53%) in the matched cohort of non-users (difference 2.99%, 95% CI 2.77% to 3.22%).

Conclusions Antipsychotic use compared with non-use in adults with dementia was associated with increased risks of stroke, venous thromboembolism, myocardial infarction, heart failure, fracture, pneumonia, and acute kidney injury, but not ventricular arrhythmia. The range of adverse outcomes was wider than previously highlighted in regulatory alerts, with the highest risks soon after initiation of treatment.

Introduction

Dementia is a clinical syndrome characterised by progressive cognitive decline and functional disability, with estimates suggesting that by 2050 around 152.8 million people globally will be affected. 1 Behavioural and psychological symptoms of dementia are common aspects of the disease and include features such as apathy, depression, aggression, anxiety, irritability, delirium, and psychosis. Such symptoms can negatively impact the quality of life of patients and their carers and are associated with early admission to care. 2 3 Antipsychotics are commonly prescribed for the management of behavioural and psychological symptoms of dementia, despite longstanding concerns about their safety. 4 5 6 During the covid-19 pandemic, the proportion of people with dementia prescribed antipsychotics increased, possibly owing to worsened behavioural and psychological symptoms of dementia linked to lockdown measures or reduced availability of non-pharmaceutical treatment options. 7 According to guidelines from the UK’s National Institute for Health and Care Excellence, antipsychotics should only be prescribed for the treatment of behavioural and psychological symptoms of dementia if non-drug interventions have been ineffective, if patients are at risk of harming themselves or others or are experiencing agitation, hallucinations, or delusions causing them severe distress. 8 Antipsychotics should at most be prescribed at the lowest effective dose and for the shortest possible time. Only two antipsychotics, risperidone (an atypical, or second generation, antipsychotic) and haloperidol (a typical, or first generation, antipsychotic), are licensed in the UK for the treatment of behavioural and psychological symptoms of dementia, 9 although others have been commonly prescribed off-label. 5 10

Based on evidence from clinical trials of risperidone, the US Food and Drug Administration (FDA) first issued a warning in 2003 about the increased risks of cerebrovascular adverse events (eg, stroke, transient ischaemic attack) associated with use of atypical antipsychotics in older adults with dementia. 11 A meta-analysis of 17 trials among such patients subsequently found a 1.6-1.7-fold increased risk of mortality with atypical antipsychotics compared with placebo, which led the FDA to issue a “black box” warning in 2005 for all atypical antipsychotics. 11 This warning was extended to typical antipsychotics in 2008, after two observational studies reported that the risk of death associated with their use among older people might be even greater than for atypical antipsychotics. 12 13 14 The increased risks for stroke and mortality have been consistently reported by many observational studies and meta-analyses since, 11 15 16 17 18 19 20 21 and they have led to regulatory safety warnings and national interventions in the UK, US, and Europe, aiming to reduce inappropriate prescribing of these drugs for the treatment of behavioural and psychological symptoms of dementia. 8 11 22 23 24 25 26 Other adverse outcomes have also been investigated in observational studies, 27 28 29 although, with the exception of pneumonia, 14 30 31 32 the evidence is less conclusive or is more limited among people with dementia. For example, inconsistent or limited evidence has been found for risks of myocardial infarction, 33 34 ventricular arrhythmia, 35 36 venous thromboembolism, 37 38 39 40 fracture, 41 42 43 and acute kidney injury. 44 45 46 Most studies also reported only one outcome or type of outcomes. Examining multiple adverse events in a single cohort is needed to give a more comprehensive estimate of the total potential harm associated with use of antipsychotics in people with dementia.

Using linked primary and secondary care data in England, we investigated the risks of a range of adverse outcomes potentially associated with antipsychotic use in a large cohort of adults with dementia—namely, stroke, venous thromboembolism, myocardial infarction, heart failure, ventricular arrhythmia, fracture, pneumonia, and acute kidney injury. We report both relative and absolute risks.

Data sources

The study used anonymised electronic health records from Clinical Practice Research Datalink (CPRD). In the UK, residents are required to be registered with a primary care general practice to receive care from the NHS. The NHS is a publicly funded healthcare service, free at the point of use. More than 98% of the UK population are registered with a general practice, and their electronic health records are transferred when they change practice. 47 48 Community prescribing is most often done by the general practitioner, including antipsychotic treatment recommended by specialists. CPRD data are sourced from more than 2000 general practices covering around 20% of the UK population, and include information on diagnoses, primary healthcare contacts, prescribed drugs, laboratory test results, and referrals to secondary healthcare services. 47 48 CPRD contains two databases: Aurum and GOLD. CPRD Aurum includes data from contributing general practices in England that use the EMIS Web patient management software, and CPRD GOLD consists of patient data from practices across all four UK nations that use the Vision system. Both datasets are broadly representative of the UK population. 47 48 49 Primary care data from general practices in England can be linked to other datasets, including hospital admissions in Hospital Episode Statistics, and mortality and index of multiple deprivation data from the Office for National Statistics (ONS). Individual patients can opt-out of sharing their records with CPRD, and individual patient consent was not required as all data were deidentified.

Study population

We delineated two cohorts, one each from Aurum and GOLD. For the latter, we included patients from English practices only because linkage to hospital admission and mortality data were required in our analyses. To ensure that the study dataset would not contain any duplicate patient records, we used the bridging file provided by CPRD to identify English practices that have migrated from the GOLD to the Aurum dataset, and removed such practices from the GOLD dataset. For both cohorts, we included patients who had a first dementia diagnosis code between 1 January 1998 and 31 May 2018. Dementia was identified from Read, SNOMED, or EMIS codes used in the databases (see supplementary appendix). We defined the date of first dementia diagnosis as the date of first dementia code. Patients needed to be aged 50 years or over at the time of dementia diagnosis, have been registered with the CPRD practice for at least a year, not be prescribed an antipsychotic in the 365 days before their first dementia code, and have records that were eligible for linkage to Hospital Episodes Statistics, mortality, and index of multiple deprivation data. In addition, because anticholinesterases (such as donepezil, rivastigmine, and galantamine) may sometimes be prescribed to patients showing signs of dementia before their first dementia code, we excluded patients with an anticholinesterase prescription before their first dementia code. Supplementary figures S1 and S2 show how the two cohorts for Aurum and GOLD, respectively, were delineated.

Study design

Matched cohort design —We implemented a matched cohort design. Supplementary figure S3 shows the study design graphically. 50 For the Aurum and GOLD cohorts separately, patients who used antipsychotics were defined as patients in each cohort issued with an antipsychotic prescription after (or on the same day as) the date of their first dementia diagnosis, with the date of first antipsychotic prescription being the index date after which outcomes were measured. For each outcome, follow-up began from the date of the first antipsychotic prescription (the index date) and ended on the earliest of date of first diagnosis of outcome (ie, the earliest recording of the outcome whether it was from the patient’s primary or secondary care or mortality records), death, transfer out of the general practice, last data collection date of the general practice, two years from the date of antipsychotics initiation, or 31 May 2018. Because patients who have experienced an outcome were potentially at higher risk of subsequently experiencing the same event, which could confound any risks associated with antipsychotic use, we excluded those with a history of the specific outcome under investigation before the index date from the analysis of that outcome. For example, we excluded patients with a record of stroke before the index date from the analysis of stroke, but they would still be eligible for the study of other outcomes. For the analysis of acute kidney injury, patients with a diagnosis of end stage kidney disease before the index date were also excluded, and a diagnosis of end stage kidney disease after the index date was an additional condition for end of follow-up. 44

Matched comparators —Each patient who used antipsychotics on or after the date of their first dementia diagnosis was matched using incidence density sampling with up to 15 randomly selected patients who had the same date of first dementia diagnosis (or up to 56 days after) and who had not been prescribed an antipsychotic before diagnosis. Incidence density sampling involves matching on sampling time, with each antipsychotic user in our study being matched to one or more comparators who were eligible for an antipsychotic but had not become a user at the time of matching. 51 The selection of comparators was done with replacement—that is, an individual could be used as a comparator in multiple matched sets. In our study, this meant that patients were eligible to be a non-user matched comparator up to the date of their first antipsychotic prescription. We excluded matched comparators with a history of the specific outcome under investigation before the index date from the analysis of that event. For each outcome, follow-up of matched comparators began on the same day as the patient to whom they were matched (the index date) and ended on the earliest of date of their first antipsychotic prescription (if any), or date of one of the end of follow-up events described earlier for the antipsychotic users.

Use of antipsychotics

We included both typical and atypical antipsychotics, identified by product codes in Aurum and GOLD (see supplementary appendix for list of drugs included). Senior author DMA (pharmacist) reviewed the code lists. As previous studies have shown a temporal association between antipsychotic use and development of adverse outcomes, 30 31 52 we treated use of antipsychotics as a time varying variable, classified as current, recent, and past use. Current use was defined as the first 90 days from the date of an antipsychotic prescription, recent use as up to 180 days after current use ended, and past use as the time after the recent use period had ended. If a patient was issued another prescription during the 90 days after their last prescription, their current use period would be extended by 90 days from the date of their latest prescription. For example, if a patient had two prescriptions and the second was issued 60 days after the first, their current use period would be a total of 150 days: 60 days after the first prescription plus 90 days after the second. At the end of the 150 days current use period, the next 180 days would be the recent use period, and the time after this recent use period would be past use. As patients could have multiple prescriptions over time, they could move between the three antipsychotic use categories during follow-up, and they could therefore be defined as current, recent, or past users more than once. See the supplementary appendix for further information on how this definition is applied.

In post hoc analyses, we also investigated typical versus atypical antipsychotics, and specific drug substances: haloperidol, risperidone, quetiapine, and other antipsychotics (as a combined category).

Outcomes were stroke, venous thromboembolism (including deep vein thrombosis and pulmonary embolism), myocardial infarction, heart failure, ventricular arrhythmia, fracture, pneumonia, and acute kidney injury. With the exceptions of pneumonia and acute kidney injury, outcomes were identified by Read, SNOMED, or EMIS codes in the primary care records, and by ICD-10 (international classification of diseases, 10th revision) codes from linked secondary care data from Hospital Episodes Statistics, and cause of death data from the ONS mortality records. For pneumonia and acute kidney injury, we only included those that were diagnosed in hospitals or as a cause of death, ascertained from Hospital Episodes Statistics and ONS data.

We also investigated appendicitis and cholecystitis combined as an unrelated (negative control) outcome to detect potential unmeasured confounding. 53 These outcomes were chosen because evidence of an association with antipsychotic use is lacking from the literature. We identified appendicitis and cholecystitis from Read, SNOMED, EMIS, and ICD-10 codes. Clinicians (BG, AJA, DRM) checked all code lists (see supplementary appendix).

We used propensity score methods to control for imbalances in measurable patient characteristics between antipsychotic users and their matched non-users, with personal characteristics, lifestyle, comorbidities, and prescribed drugs included in the propensity score models. A counterfactual framework for causal inference was applied to estimate the average treatment effect adjusting for inverse probability of treatment weights generated from the propensity score models. 54 55 Selection of covariates was informed by the literature, based on their potential associations with antipsychotic initiation and study outcomes. 31 34 44 56 57 All variables were assessed before the index date (see supplementary figure S3). Variables for personal characteristics included sex, age at dementia diagnosis, age at start of follow-up, ethnicity, and index of multiple deprivation fifths based on the location of the general practice. Comorbidities were derived as dichotomous variables and included a history of hypertension, types 1 and 2 diabetes mellitus, chronic obstructive pulmonary disease, rheumatoid arthritis, moderate or severe renal disease, moderate or severe liver disease, atrial fibrillation, cancer, and serious mental illness (bipolar disorders, schizophrenia, schizoaffective disorders, and other psychotic disorders). Lifestyle factors included smoking status and alcohol use. Medication covariates were represented as dichotomous indicators, defined by at least two prescriptions for each of the following drugs in the 12 months before the index date: antiplatelets, oral anticoagulants, angiotensin converting enzyme inhibitors or angiotensin II receptor blockers, alpha blockers, beta blockers, calcium channel blockers, diuretics, lipid lowering drugs, insulin and antidiabetic drugs, non-steroidal anti-inflammatory drugs, antidepressants, benzodiazepines, and lithium. We also included the following potential confounders for the investigations of venous thromboembolism and fracture: prescriptions for hormone replacement therapy and selective oestrogen receptor modulators (for venous thromboembolism), 58 59 a history of inflammatory bowel disease (for pneumonia and fracture), 60 61 and prescriptions for immunosuppressants, oral corticosteroids, and inhaled corticosteroids (for pneumonia). 62 63

Statistical analysis

For each patient included in the study, we derived a propensity score representing the patient’s probability of receiving antipsychotic treatment. Propensity scores were estimated using multivariable logistic regression, with antipsychotic use as the dependent variable. Predictors included personal characteristics, lifestyle, comorbidities, and prescribed drugs. Patients with missing information on ethnicity, index of multiple deprivation, smoking, or alcohol use were grouped into an unknown category for each of these variables and included in the propensity score models. We used the Hosmer-Lemeshow test and likelihood ratio test to test the fit of the models, and interaction terms were included to improve the model fit. 64 The derived scores were used as inverse probability of treatment weights to reweigh the data, balancing the distribution of baseline covariates between antipsychotic users and non-users (matched comparators)—that is, standardised differences <0.1 after weighting. 65 Propensity score models were run for each outcome, and for the Aurum and GOLD cohorts separately. For further information, see the supplementary appendix section on propensity score methods to control for potential confounding.

Analyses for estimating harms were then conducted after combining (appending) the Aurum and GOLD datasets. We used Cox regression survival analyses to estimate the risks of each outcome associated with antipsychotic use relative to the comparator cohort, and we report the results as hazard ratios. Use of an antipsychotic was treated as a time varying variable. To account for the matched design, we fitted stratified models according to the matched sets and used robust variance estimation. In all models, we also included a covariate indicating whether the patient was from the Aurum or GOLD cohort and calculated hazard ratios with adjustments for inverse probability of treatment weights. Cox regression assumes proportional hazards—that is, the relative hazard of the outcome remains constant during the follow-up period. 66 We assessed this assumption using the Grambsch-Therneau test based on the Schoenfeld residuals. 67 Because this assumption did not hold for all outcomes examined, in addition to reporting the hazard ratios pertaining to the whole follow-up period, we estimated hazard ratios separately for the several time windows: the first seven days, 8-30 days, 31-180 days, 181-365 days, and 366 days to two years (see supplementary appendix for an illustration of stratification of follow-up time). For each outcome, we calculated the incidence rate and the number needed to harm (NNH) over the first 180 days as well as two years after start of follow-up. The NNH represents the number of patients needed to be treated with an antipsychotic for one additional patient to experience the outcome compared with no treatment. We also calculated cumulative incidence percentages (absolute risks) for each outcome accounting for competing mortality risks based on previous recommendations. 68 These were calculated at 90 days, 180 days, 365 days, and two years after start of follow-up for antipsychotic users and their matched comparators separately. We also reported the difference in cumulative incidence between antipsychotic users and their matched comparators at these time points. Analyses were conducted using Stata/MP v16.1.

Sensitivity analyses

We investigated two other definitions of antipsychotic use as sensitivity analyses: the first 60 days as current use followed by 120 days of recent use, and a current use period of 30 days followed by a recent use period of 60 days. We also conducted the following post hoc sensitivity analyses. Firstly, as levomepromazine is often prescribed in palliative care to treat distressing symptoms in the last days of life, 69 we censored individuals at the time of their first levomepromazine prescription. Secondly, we used Fine-Gray subdistribution hazard regression models to estimate the hazard of each adverse outcome, accounting for the competing risks of death. 70 These results were reported as subhazard ratios. Thirdly, we compared the incidence rates and hazards of adverse outcomes for male versus female individuals. For these sex specific analyses, we modified the existing matched cohort by excluding non-user comparators who were of a different sex from the antipsychotic user to whom they were matched. We then derived a new propensity score for each individual by excluding sex as a covariate in the propensity score models. Incidence rate ratios and corresponding 95% confidence intervals (CIs) for male versus female individuals were calculated using the ‘iri’ command in Stata. To investigate whether hazards of each adverse outcome associated with antipsychotic use differed by sex, we fitted Cox regression models with sex, antipsychotic use, and their interaction as covariates. Sex specific hazard ratios and ratios of male to female hazard ratios were reported.

Patient and public involvement

This study is part of a National Institute of Health and Care Research funded programme (RP-PG-1214-20012): Avoiding patient harm through the application of prescribing safety indicators in English general practices (PRoTeCT). Two patient and public involvement members in the project team contributed to the study design and protocol of this study. Our study was not, however, coproduced with people with dementia or their carers.

Characteristics of study population

A total of 173 910 adults (63.0% women) with dementia were eligible for inclusion in the study: 139 772 (62.9% women) in the Aurum dataset and 34 138 (63.4% women) in GOLD. The mean age at dementia diagnosis for individuals in both cohorts was 82.1 years (standard deviation (SD) 7.9 years), and the median age was 83 years (interquartile range (IQR) 78-88 years in Aurum and 78-87 years in GOLD). A total of 35 339 individuals (62.5% women; 28 187 in Aurum, 62.6% women; 7152 in GOLD, 62.5% women) were prescribed an antipsychotic during the study period, and a matched set was generated for each of these individuals. The mean number of days between first dementia diagnosis and date of a first antipsychotic prescription was 693.8 ((SD 771.1), median 443 days) in Aurum and 576.6 ((SD 670.0), median 342 days) in GOLD. A total of 544 203 antipsychotic prescriptions (433 694 in Aurum, 110 509 in GOLD) were issued, of which 25.3% were for a typical antipsychotic and 74.7% for an atypical antipsychotic. The most prescribed antipsychotics were risperidone (29.8% of all prescriptions), quetiapine (28.7%), haloperidol (10.5%), and olanzapine (8.8%), which together accounted for almost 80% of all prescriptions (see supplementary table S1).

Since we excluded people with a history of the event before the start of follow-up, the number of individuals and matched sets included in analysis varies by outcome. Table 1 shows the baseline characteristics of patients for the analysis of stroke, before and after inverse probability of treatment weighting. Antipsychotic users were more likely than their matched comparators to have a history of serious mental illness and to be prescribed antidepressants or benzodiazepines in the 12 months before start of follow-up. After inverse probability of treatment weighting, standardised differences were <0.1 for all covariates. Baseline characteristics of individuals included in the analyses of other outcomes were similar to those reported for stroke (see supplementary tables S2-S9).

Baseline characteristics of antipsychotic users and matched comparators included in the analysis of stroke (CPRD Aurum and GOLD combined data). Values are number (percentage) unless stated otherwise

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Incidence rates and relative hazards of adverse outcomes

All antipsychotics.

In the two years after initiation of antipsychotics, the highest incidence rates of adverse outcomes were for pneumonia, fracture, and stroke, and ventricular arrhythmias were rare ( table 2 ). Figure 1 shows the hazard ratios of adverse outcomes associated with current, recent, past, and any use of antipsychotics versus non-use (ie, matched comparators). Except for ventricular arrhythmia, any use of antipsychotics was associated with increased risks for all adverse outcomes, ranging from a hazard ratio of 2.03 (95% CI 1.96 to 2.10) for pneumonia to 1.16 (1.09 to 1.24) for heart failure. Current use (ie, prescribed in the previous 90 days) was associated with high risks for pneumonia (2.19, 2.10 to 2.28), acute kidney injury (1.72, 1.61 to 1.84), venous thromboembolism (1.62, 1.46 to 1.80), and stroke (1.61, 1.52 to 1.71). Recent antipsychotic use (ie, in the 180 days after current use ended) was also associated with increased risk for these outcomes, as well as for fracture, but past use of antipsychotics (ie, after recent use ended) was not associated with increased risks of the adverse outcomes examined, except for pneumonia. For the negative control outcome (appendicitis and cholecystitis), no significant associations were found with current, recent, or any antipsychotic use, but a statistically significant association was observed with past use (1.90, 1.01 to 3.56).

Incidence rate (per 10 000 person years) and number needed to harm of adverse outcomes associated with antipsychotic use during the first 180 days and two years of follow-up period

Hazard ratios (adjusted for inverse probability of treatment weights) of adverse outcomes associated with current, recent, and past antipsychotic use; with current use being defined as the first 90 days from the date of an antipsychotic prescription, recent use as up to 180 days after current use ended, and past use as after recent use. CI=confidence interval

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Table 2 shows that the NNH ranged from 9 (95% CI 9 to 10) for pneumonia to 167 (116 to 301) for myocardial infarction during the first 180 days after initiation of antipsychotics, and from 15 (14 to 16) for pneumonia to 254 (183 to 413) for myocardial infarction after two years. These figures suggest that over the 180 days after drug initiation, use of antipsychotics might be associated with one additional case of pneumonia for every nine patients treated, and one additional case of myocardial infarction for every 167 patients treated. At two years, there might be one additional case of pneumonia for every 15 patients treated, and one additional case of myocardial infarction for every 254 patients treated.

Table 3 shows hazard ratios stratified by follow-up time (except for ventricular arrhythmia and the negative control where the number of patients was very low). For almost all outcomes, relative hazards were highest in the first seven days after initiation of antipsychotic treatment. Risks for pneumonia were particularly increased in the first seven days (9.99, 8.78 to 11.40) and remained substantial afterwards (3.39, 3.04 to 3.77, 8-30 days). No increased risks for heart failure were found for current users after 180 days from start of treatment, nor for myocardial infarction one year after drug initiation. However, risks for stroke, venous thromboembolism, fracture, pneumonia, and acute kidney injury remained increased among continuous antipsychotic users up to two years after initiation of treatment.

Hazard ratios (adjusted for IPT weights) of adverse outcomes associated with current, recent, and past antipsychotic use stratified by follow-up period

Types of antipsychotics

During the current use period of 90 days after a prescription, both typical and atypical antipsychotics were associated with increased risks of all adverse outcomes compared with non-use, except for ventricular arrhythmia and the negative control (see supplementary table S10). Hazards were higher when current use of typical antipsychotics was directly compared with atypical antipsychotics for stroke (1.23, 1.09 to 1.40), heart failure (1.18, 1.01 to 1.39), fracture (1.22, 1.08 to 1.38), pneumonia (1.92, 1.77 to 2.08), and acute kidney injury (1.22, 1.05 to 1.42), but no significant differences between the two types of drug were found for the risks of venous thromboembolism or myocardial infarction.

Supplementary table S11 shows the risks of adverse outcomes associated with haloperidol (the most prescribed typical antipsychotic) and with risperidone and quetiapine (the two most prescribed atypical antipsychotics). Current use of risperidone and haloperidol compared with non-use was associated with increased risks of all adverse outcomes except for ventricular arrhythmia and the negative control. Current use of quetiapine compared with non-use was associated with increased risks for fracture, pneumonia, and acute kidney injury. Among current users of haloperidol or risperidone, risks for fracture, pneumonia, and acute kidney injury were higher for haloperidol versus risperidone, but risks for stroke, venous thromboembolism, myocardial infarction, and heart failure were similar for both drugs. With the exceptions of myocardial infarction, ventricular arrhythmia, and the negative control, risks of all adverse outcomes were higher for haloperidol than for quetiapine, especially for pneumonia (2.53, 2.21 to 2.89) and venous thromboembolism (1.99, 1.33 to 2.97). Among current users of quetiapine compared with risperidone, there were no significant differences in risks for myocardial infarction, heart failure, or fracture. However, risks for stroke (0.64, 0.53 to 0.78), venous thromboembolism (0.49, 0.36 to 0.68), pneumonia (0.72, 0.63 to 0.81), and acute kidney injury (0.81, 0.67 to 0.96) were lower for quetiapine than for risperidone.

Absolute risks of adverse outcomes

Cumulative incidence for all outcomes examined was higher for antipsychotic users versus matched comparators, except for ventricular arrhythmia and the negative control ( table 4 ). The absolute risk, as well as risk difference, was particularly large for pneumonia. In the 90 days after initiation of an antipsychotic, the cumulative incidence of pneumonia among antipsychotic users was 4.48% (95% CI 4.26% to 4.71%) v 1.49% (1.45% to 1.53%) in the matched cohort of non-users (difference 2.99%, 95% CI 2.77% to 3.22%). At one year, this increased to 10.41% (10.05% to 10.78%) for antipsychotic users compared with 5.63% (5.55% to 5.70%) for non-users (difference 4.78%, 4.41% to 5.16%).

Cumulative incidence of adverse outcomes associated with antipsychotic use at 90, 180, and 365 days and at two years after start of follow-up

Similar results were found in sensitivity analysis using two other definitions of antipsychotic use (see supplementary figures S4 and S5). Of the 544 203 antipsychotic prescriptions issued, 1.3% were for levomepromazine (see supplementary table S1). Results remained similar when patients were censored at the time of their first levomepromazine prescription (see supplementary figure S6). Results of the Fine-Gray models accounting for the competing risks of death also showed broadly similar patterns of hazards to those from the Cox models (see supplementary table S12 and figure S7). Sex specific analyses showed that male patients had higher incidence rates of all adverse outcomes than female patients, except for fracture and venous thromboembolism where incidence was higher for female patients than for male patients (see supplementary table S13). Compared with female antipsychotic users, male users had increased hazards for pneumonia and acute kidney injury (male to female hazard ratio 1.16, 95% CI 1.08 to 1.25 for pneumonia and 1.22, 1.08 to 1.37 for acute kidney injury), but lower hazards for stroke (0.81, 0.73 to 0.91). No significant differences were found by sex in the hazards for venous thromboembolism, myocardial infarction, heart failure, ventricular arrhythmia, or fracture (see supplementary table S14).

In this population based cohort study of adults (≥50 years) with dementia, use of antipsychotics compared with non-use was associated with increased risks for stroke, venous thromboembolism, myocardial infarction, heart failure, fracture, pneumonia, and acute kidney injury. Increased risks were observed among current and recent users and were highest in the first week after initiation of treatment. In the 90 days after a prescription, relative hazards were highest for pneumonia, acute kidney injury, stroke, and venous thromboembolism, with increased risks ranging from 1.5-fold (for venous thromboembolism) to twofold (for pneumonia) compared with non-use. No increased risk was found for ventricular arrhythmia or the negative control outcome (appendicitis and cholecystitis). Absolute risk differences between antipsychotic users and their matched comparators were substantial for most adverse events, and largest for pneumonia. In the 90 days after a prescription, risks of stroke, heart failure, fracture, pneumonia, and acute kidney injury were higher for typical antipsychotics versus atypical antipsychotics, whereas no significant differences between these two drug classes were found for risks of venous thromboembolism or myocardial infarction. Haloperidol was associated with higher risks for fracture, pneumonia, and acute kidney injury than risperidone, but no significant differences between the two drugs were found for the other outcomes. Risks of almost all adverse outcomes were higher for haloperidol than for quetiapine. No significant differences were found between risperidone and quetiapine for risks of myocardial infarction, heart failure, or fracture, but risks for stroke, venous thromboembolism, pneumonia, and acute kidney injury were lower for quetiapine versus risperidone.

Comparison with other studies

A population based study in Wales reported no increased risks for non-fatal acute cardiac events associated with antipsychotic use in patients with all cause dementia, although those with Alzheimer’s disease showed increased risks. 37 Systematic reviews and meta-analyses of studies not limited to patients with dementia have also reported inconsistent evidence for myocardial infarction, or lack of robustness of these data. 33 34 71 Our findings for myocardial infarction were similar to those in a study that first documented a modest and time limited increase in risk of this outcome associated with antipsychotic use among patients with dementia. 56 In a study of nursing home residents in the US, users of typical, but not atypical, antipsychotics were more likely than non-users to be admitted to hospital for ventricular arrhythmia or cardiac arrest, 35 and a study not limited to older people reported increased risks for ventricular arrhythmia or sudden cardiac death associated with both typical and atypical antipsychotics. 36 We did not find any association with ventricular arrhythmia, but the number of events was low and we did not examine cardiac arrest or sudden death.

Increased risks of venous thromboembolism associated with antipsychotic use have been reported in the general population, 38 but meta-analyses found increased risks of venous thromboembolism only among younger users. 39 40 Our findings are consistent with those of the Welsh study, which reported increased risks of venous thromboembolism in the 12 months after drug initiation (prior event rate ratio 1.95, 95% CI 1.83 to 2.0). 37 In absolute terms, however, these risks were relatively low compared with other outcomes examined in this study.

We found that both the relative and the absolute risks for pneumonia were highest among all outcomes examined. Current users of antipsychotics had a twofold increased risk compared with non-users ( fig 1 ), and although this magnitude of increased risk was comparable to previous reports, 14 31 32 we additionally observed that risks were greater in the first week after drug initiation. One study also reported a particularly high risk for patients with hospital diagnosed pneumonia in the first week, but the magnitude of increase (odds ratio 4.5, 95% CI 2.8 to 7.3) was much lower than our observation. 30 The mechanisms linking antipsychotic use and development of pneumonia is not well understood, and substantial heterogeneity exists among the drug substances, but antipsychotic induced extrapyramidal symptoms, sedation, xerostomia (dry mouth), and dyskinesia or impaired swallowing are commonly considered as potential risk factors. 72 In addition, because elderly people with pneumonia may be less likely than younger patients to present with respiratory symptoms but more likely to show signs of delirium, 73 it is possible that reverse causality might have contributed to the high risks observed in the early days after drug initiation, as delirium from the onset of pneumonia might have been treated with antipsychotics before pneumonia was diagnosed. 30 However, although causality cannot be inferred, the particularly high increased risks observed for a range of outcomes and not only for pneumonia in the early days after drug initiation are consistent with other studies. 28 This could be partly explained by further prescriptions being given only to patients who tolerated the first days of drug use.

The use of atypical antipsychotics in older adults (≥65 years) has been shown to be associated with increased risk of acute kidney injury. 44 45 46 Two studies reported significantly increased risks in users compared with non-users in the 90 days after initiation of atypical antipsychotics. 44 45 In contrast, another study observed no increased risks from use of the broad category of atypical antipsychotics, although a significantly increased risk was found with olanzapine. 46 In our study, we found increased risks of acute kidney injury with both typical and atypical antipsychotics, with risks being higher for haloperidol than for risperidone and quetiapine.

In a meta-analysis of observational studies, antipsychotic use was associated with increased risks of hip fracture among people with dementia. 41 A self-controlled case series study of older adult patients (≥65 years) also reported increased risks of falls and fracture after initiation of antipsychotics, but incidence was found to be even higher in the 14 days before treatment started. 43 Similar findings were also reported in another study, suggesting that the risks observed during the treatment periods might not be attributable to the antipsychotics alone. 42 Although we cannot eliminate confounding in our study, we minimised this risk by adjusting for a large number of both clinical and non-clinical characteristics that might have influenced treatment assignment. We also found no increased risks associated with current or recent antipsychotic use for the negative control outcome (appendicitis and cholecystitis).

Our study found that the risks of stroke and heart failure were higher for typical antipsychotics than for atypical antipsychotics, but risks of venous thromboembolism and myocardial infarction were similar between the two drug classes. We also found no significant differences between haloperidol and risperidone in risks of these four outcomes, but significantly increased risks for stroke, venous thromboembolism, and heart failure for haloperidol versus quetiapine. Previous studies of elderly patients have reported similar risks for cardiovascular or cerebrovascular events associated with use of typical and atypical antipsychotics, 17 74 75 76 but risks of these outcomes and of all cause mortality were increased with haloperidol versus risperidone. 21 76 For fracture and pneumonia, we found that risks were higher in association with typical antipsychotics than atypical antipsychotics and for haloperidol versus risperidone or quetiapine. The findings from previous studies comparing these risks by antipsychotic types have been inconsistent. 30 31 32 74 75

Strengths and limitations of this study

A key strength of this study was the investigation of a wide range of adverse events in a large population based cohort, and the reporting of both relative and absolute risk differences over multiple periods. Previous studies commonly focused on a single outcome or type of outcome, such as cerebrovascular events, and on the reporting of relative risks. By examining the same cohort at risk, we were able to directly compare the hazards of multiple outcomes without differential biases between the cohorts. In addition, we only included patients with a clinician recorded diagnosis of dementia, and we adjusted for many variables that might have influenced the probability of antipsychotic initiation, seeking to minimise confounding by indication. CPRD is one of the largest primary care databases in the world, and it is broadly representative of the UK population. 47 48 49 The database includes all prescriptions issued in participating primary care practices in the UK, and it is recognised as a high quality resource to support international pharmacovigilance. 77 The longitudinal nature of CPRD, with linked data from secondary care and mortality records, enabled us to capture the study outcomes from multiple sources, as well as information on prescribing and comorbidities. 78 79 Our findings were also robust to different classifications of usage periods and we found no associations between current and recent antipsychotic use with the development of the negative control outcome (appendicitis and cholecystitis). However, a significant association with past use was observed that we are unable to explain.

As with all observational studies, residual confounding cannot be excluded. For example, polypharmacy is common among elderly people, which could lead to drug-drug interactions and potentially confound our findings. 80 81 We also did not have information on indications for antipsychotics treatment. We minimised the risk of confounding using propensity score methods to control for imbalances in measurable patient characteristics between antipsychotic users and their matched comparators. However, unlike randomised control trials, which, if properly conducted, could account for both observed and unobserved differences between treated and untreated groups, the propensity score method can only adjust for the observed differences between two groups. Additionally, our choice of covariates was based on the literature and discussions with clinical experts and was not formally structured using, for example, a directed acyclic graph. Although the strong associations with pneumonia in the first seven days of antipsychotic initiation may partially be attributed to reverse causality, however, it is less likely to explain associations over longer periods. We also found no increased risk for appendicitis and cholecystitis during current and recent use—our negative control outcome that was included to detect potential unmeasured confounding. 53 Another limitation of our study is that although prescriptions issued in primary care are reliable in CPRD, information on dosage is not well recorded and information on drug adherence or prescriptions issued while patients are in hospital is not available. 48 Misclassification of drug use is therefore a potential problem. As with other electronic health data that are routinely collected for administrative rather than research purposes, potential issues exist with coding errors, missing or incomplete information, and variations in data quality between practices and healthcare settings. Although the data undergo quality checks before being released and our use of the linked data would have helped to deal with such problems, we were restricted to data coded in patients’ electronic health records. In addition, despite the representativeness of the CPRD data, care should be taken in making inferences beyond the population studied. Our sex specific investigations were also conducted as post hoc analyses. By using existing matched sets but restricting the comparators to those of the same sex as the antipsychotic user to whom they were matched, the number of comparators was greatly reduced. Although we found some evidence of differences in hazards for stroke, pneumonia, and acute kidney injury between male and female antipsychotic users, further research is needed to validate these findings.

Policy implications

The mechanisms underlying the links between antipsychotics and the outcomes in our study are not fully understood. In the UK, US, and Europe, current regulatory warnings for using antipsychotics to treat behavioural and psychological symptoms of dementia were mostly based on evidence of increased risks for stroke and mortality. 8 11 22 23 24 25 26 We found a considerably wider range of harms associated with antipsychotic use in people with dementia, and the risks of harm were highest soon after initiation. Our findings must be seen in the context of trial evidence of at best modest benefit on behavioural and psychological symptoms of dementia. The efficacy of antipsychotics in the management of behavioural and psychological symptoms of dementia remains inconclusive. 82 83 84 85 Atypical antipsychotics, including risperidone, which is one of two antipsychotics licensed in the UK for the treatment of behavioural and psychological symptoms of dementia, have the strongest evidence base, but the benefits are only modest. 82 85

Any potential benefits of antipsychotic treatment therefore need to be weighed against the risk of serious harm across multiple outcomes. Although there may be times when an antipsychotic prescription is the least bad option, clinicians should actively consider the risks, considering patients’ pre-existing comorbidities and living support. The NNH reported in this study can help to inform clinical judgements on the appropriateness of treatments, taking account of the modest potential benefits reported in clinical trials. When prescriptions of such drugs are needed, treatment plans should be reviewed regularly with patients and their carers to reassess the need for continuing treatment. 9 In addition, given the higher risks of adverse events in the early days after drug initiation, clinical examinations should be taken before, and clinical reviews conducted shortly after, the start of treatment. Our study reaffirms that these drugs should only be prescribed for the shortest period possible. 9 Although regulators have made efforts to limit the use of these drugs to people with the most severe behavioural and psychological symptoms of dementia, 8 82 86 antipsychotic prescribing in dementia remains common and has even increased in recent years. 4 5 87 88 If such trends continue, further communication on the associated risks could be considered by guideline developers or regulators after a review of the totality of evidence. Greater accountability and monitoring in the use of these drugs may be called for, and additional legal reforms may be required to regulate adherence. 89 In recent years, other psychotropic drugs such as antidepressants, benzodiazepines, mood stabilisers, and anticonvulsants have been prescribed instead of antipsychotics for the treatment of behavioural and psychological symptoms of dementia. 28 90 91 These drugs, however, also pose their own risks. Further research is needed into safer drug treatment of behavioural and psychological symptoms of dementia and more efficacious, easy to deliver, initial non-drug treatments.

Conclusions

Antipsychotic use is associated with a wide range of serious adverse outcomes in people with dementia, with relatively large absolute risks of harm for some outcomes. These risks should be considered in future regulatory decisions, alongside cerebrovascular events and mortality. Any potential benefits of antipsychotic treatment need to be weighed against risk of serious harm, and treatment plans should be reviewed regularly. The effect of antipsychotics on behavioural and psychological symptoms of dementia is modest at best, but the proportion of people with dementia prescribed antipsychotics has increased in recent years. Our finding that antipsychotics are associated with a wider range of risks than previously known is therefore of direct relevance to guideline developers, regulators, and clinicians considering the appropriateness of antipsychotic prescribing for behavioural and psychological symptoms of dementia.

What is already known on this topic

Despite safety concerns, antipsychotics continue to be frequently prescribed for the management of behavioural and psychological symptoms of dementia

Current regulatory warnings for the treatment of behavioural and psychological symptoms of dementia using antipsychotics are based on evidence of increased risks of stroke and death

Evidence for other adverse outcomes is less conclusive or is more limited among people with dementia, and comparisons of risks for multiple adverse events are also difficult owing to different study designs and populations

What this study adds

Antipsychotic use in people with dementia was associated with increased risks of stroke, venous thromboembolism, myocardial infarction, heart failure, fracture, pneumonia, and acute kidney injury, compared with non-use, but not ventricular arrhythmia

Relative hazards were highest for pneumonia, acute kidney injury, stroke, and venous thromboembolism, and absolute risk and risk difference between antipsychotic users and their matched comparators was largest for pneumonia

Risks of these wide ranging adverse outcomes need to be considered before prescribing antipsychotic drugs to people with dementia

Ethics statements

Ethical approval.

This study was approved by the Clinical Practice Research Datalink’s (CPRD) independent scientific advisory committee (protocol 18_168). CPRD also has ethical approval from the Health Research Authority to support research using anonymised patient data (research ethics committee reference 21/EM/0265). 92 Individual patient consent was not required as all data were deidentified.

Data availability statement

Electronic health records are, by definition, considered sensitive data in the UK by the Data Protection Act and cannot be shared via public deposition because of information governance restriction in place to protect patient confidentiality. Access to Clinical Practice Research Datalink (CPRD) data is subject to protocol approval via CPRD’s research data governance process. For more information see https://cprd.com/data-access . Linked secondary care data from Hospital Episodes Statistics, mortality data from the Office for National Statistics, and index of multiple deprivation data can also be requested from CPRD.

Acknowledgments

We thank Hayley Gorton and Thomas Allen for their contribution to the protocol development, Evan Kontopantelis for his statistical advice, and members of our patient and public involvement team, Antony Chuter and Jillian Beggs, for their contributions to this project. This study is based on data from the Clinical Practice Research Datalink obtained under licence from the UK Medicines and Healthcare Products Regulatory Agency (MHRA). The data are provided by patients and collected by the NHS as part of its care and support. Hospital Episode Statistics and Office for National Statistics mortality data are subject to Crown copyright (2022) protection, reused with the permission of The Health and Social Care Information Centre, all rights reserved. The interpretation and conclusions contained in this study are those of the authors alone, and not necessarily those of the MHRA, National Institute of Health and Care Research, NHS, or Department of Health and Social Care. The study protocol was approved by Clinical Practice Research Datalink’s independent scientific advisory committee (reference: 18_168). We would like to acknowledge all the data providers and general practices who make anonymised data available for research.

Contributors: All authors conceived and designed the study and acquired, analysed, or interpreted the data. BG, DRM, TvS, AJA, and DMA reviewed the clinical codes. PLHM conducted the statistical analyses and wrote the first draft of the manuscript. All authors critically revised the manuscript for important intellectual content and approved the final version. AJA, DMA, RAE, BG, DRM, AS, and TvS obtained the funding. PLHM is the guarantor. The corresponding author (PLHM) attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

Funding: This study was funded by the National Institute for Health and Care Research (NIHR, RP-PG-1214-20012). MJC, AJA, and DMA were supported by the NIHR Greater Manchester Patient Safety Translational Research Centre (PSTRC-2016-003) at the time of this study and are now supported by the NIHR Greater Manchester Patient Safety Research Collaboration (NIHR204295). The funders had no role in the study design; in the collection, analysis, or interpretation of data; in the writing of the report; or in the decision to submit the article for publication. PLHM has full access to all data and all authors have full access to the statistical reports and tables in the study. PLHM takes responsibility for the integrity of the data and the accuracy of the data analysis.

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: BG reports research grants from the National Institute for Health and Care Research (NIHR). DRM was awarded a Wellcome Trust Clinical Research Development Fellowship (214588/Z/18/Z). AS reports a research grant from the NIHR. RAE reports research grants from the NIHR and NHS England, and travel costs to attend a roundtable dinner discussion on medication errors, House of Commons, Westminster, on 29 March 2022. TvS reports research grants from the NIHR. AJA is national clinical director for prescribing for NHS England and reports research grants from the NIHR. DMA reports research grants from the NIHR, AbbVie, Almirall, Celgene, Eli Lilly, Janssen, Novartis, UCB, and the Leo Foundation. All other authors declare no support from any organisation for the submitted work (except those listed in the funding section); no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

Transparency: The lead author (PLHM: the manuscript’s guarantor) affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Dissemination to participants and related patient and public communities: This study used anonymised electronic health records from the CPRD and it is therefore not possible to disseminate the findings directly to individuals whose data we used. This study is part of a National Institute for Health and Care Research (NIHR) funded programme (RP-PG-1214-20012): Avoiding patient harm through the application of prescribing safety indicators in English general practices (PRoTeCT). We have experienced patient and public involvement members aligned to the programme who we will consult in the results dissemination. In addition, senior author DMA is director of NIHR Greater Manchester Patient Safety Research Collaboration (GMPSRC), and co-authors MJC and AJA are affiliated with it. The Patient Safety Research Collaboration has a community of public contributors including patients, carers, and people accessing health and social care services. The authors will work with this network to disseminate findings.

Provenance and peer review: Not commissioned; externally peer reviewed.

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/ .

• GBD 2019 Dementia Forecasting Collaborators
• McKeith I ,
• Stocks SJ ,
• Kontopantelis E ,
• Ashcroft DM
• Szczepura A ,
• Collings SL ,
• ↵ National Institute for Health and Care Excellence. Dementia: assessment, management and support for people living with dementia and their carers. NICE guideline NG97, 20 June 2018. www.nice.org.uk/guidance/ng97
• ↵ National Institute for Health and Care Excellence. Dementia: antipsychotics. Clinical knowledge summaries. December 2022. https://cks.nice.org.uk/topics/dementia/prescribing-information/antipsychotics/
• Marston L ,
• Nazareth I ,
• Petersen I ,
• Walters K ,
• Bronskill SE ,
• Normand SL ,
• Schneeweiss S ,
• Setoguchi S ,
• Brookhart A ,
• Dormuth C ,
• Dzahini O ,
• Schneider LS ,
• Dagerman KS ,
• Douglas IJ ,
• Sacchetti E ,
• Turrina C ,
• Valsecchi P
• Seyfried LS ,
• Kheirbek RE ,
• Little JT ,
• ↵ Medicines Healthcare Products Regulatory Agency. New advice issued on risperidone and olanzapine 2004. https://webarchive.nationalarchives.gov.uk/20141205150130/http://mhra.gov.uk/printpreview/defaultsp/con002047
• ↵ Medicines Healthcare Products Regulatory Agency. Antipsychotics: use in elderly patients with dementia. Drug safety update March 2009;2:8. https://webarchive.nationalarchives.gov.uk/20091114175357/http://mhra.gov.uk/Publications/Safetyguidance/DrugSafetyUpdate/CON041211
• ↵ Banerjee S. The use of antipsychotic medication for people with dementia: time for action. An independent report commissioned and funded by the Department of Health 2009.
• ↵ European Medicines Agency. Priorities for Drug Safety Research: Safety aspects of antipsychotics in demented patients. 2010. https://www.ema.europa.eu/en/documents/other/emea-2010-priorities-drug-safety-research-safety-aspects-antipsychotics-demented-patients_en.pdf
• Hessol NA ,
• Lexchin J ,
• Harrington C
• Lapeyre-Mestre M
• Rogowska M ,
• Thornton M ,
• van Marum RJ ,
• Jansen PA ,
• Souverein PC ,
• Schobben AF ,
• Trifirò G ,
• Gambassi G ,
• Tolppanen AM ,
• Koponen M ,
• Tanskanen A ,
• Zivkovic S ,
• Liperoti R ,
• Lapane KL ,
• Jönsson AK ,
• Spigset O ,
• Ostuzzi G ,
• Thabane L ,
• Brännström J ,
• Lövheim H ,
• Gustafson Y ,
• Nordström P
• Schuemie MJ ,
• Ramcharran D ,
• Brøgger Kristiansen S ,
• Baltzer Houlind M ,
• Herrett E ,
• Gallagher AM ,
• Bhaskaran K ,
• Campbell J ,
• Mahadevan P ,
• Fordyce S ,
• Rassen JA ,
• Rothman KJ ,
• Greenland S ,
• Kleijer BC ,
• Egberts AC ,
• Heerdink ER
• Lipsitch M ,
• Tchetgen Tchetgen E ,
• Austin PC ,
• Pariente A ,
• Fourrier-Réglat A ,
• Ducruet T ,
• Rigler SK ,
• Shireman TI ,
• Cook-Wiens GJ ,
• Balkwill A ,
• Million Women Study Collaborators
• Vinogradova Y ,
• Coupland C ,
• Hippisley-Cox J
• Sandler RS ,
• Kappelman MD
• Spoorenberg SMC ,
• Snijders D ,
• Ovidius Study Group ,
• Capisce Study Group ,
• STEP Study Group
• Koivula I ,
• ↵ Lunt M. Propensity analysis in Stata, revision: 1.1. 2014. University of Manchester. http://personalpages.manchester.ac.uk/staff/mark.lunt/propensity_guide.pdf
• Grambsch PM ,
• Therneau TM
• Gooley TA ,
• Leisenring W ,
• Crowley J ,
• Schmitz A ,
• Gastaldon C ,
• Sultana J ,
• Calabró M ,
• Garcia-Serna R ,
• Huybrechts KF ,
• Silliman RA ,
• Brookhart MA ,
• Schneeweiss S
• Gerhard T ,
• Sahlberg M ,
• Gislason GH ,
• Torp-Pedersen C ,
• Andersson C
• Crellin E ,
• Donegan K ,
• Padmanabhan S ,
• Cameron E ,
• Williams R ,
• Strongman H
• Nørgaard A ,
• Jensen-Dahm C ,
• Wimberley T ,
• Hansen ES ,
• Gitlin LN ,
• Lyketsos CG
• Goodarzi Z ,
• Veroniki AA ,
• Frederiksen KS ,
• Frisoni GB ,
• El Helou ML
• McDermid J ,
• Ballard C ,
• Schnier C ,
• McCarthy A ,
• Morales DR ,
• CVD-COVID-UK/COVID-IMPACT Consortium
• ↵ CPRD - Safeguarding patient data https://cprd.com/safeguarding-patient-data

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A New Model for Studying Social Isolation and Health in People with Serious Mental Illnesses

Researchers have developed a promising new framework for studying the link between social disconnection and poor physical health in people living with serious mental illnesses (SMI). Drawing on published research from animal models and data from the general population, this framework builds on existing social isolation and loneliness models by integrating insights from evolutionary and cognitive theories. This research was supported by the Office of Behavioral and Social Sciences Research and the National Institute of Mental Health.

What were the researchers studying and why?

One of the most challenging aspects of living with SMI is difficulties with social perception, motivation, and social behaviors. These difficulties can lead to social withdrawal and loneliness, outcomes that can contribute to poor heart health and early death. However, researchers have an incomplete understanding of how differences in the brain functions in people living with SMIs impact the connection between their social perception and self-reported, lived experience of social withdrawal, isolation, or loneliness.

How did the researchers conduct the study?

Researchers from Boston University and Harvard Medical School conducted a selective narrative review of studies addressing social withdrawal, isolation, loneliness, and health in SMI.

Their review highlighted evidence indicating differences in brain activity between people experiencing loneliness and those who are not, particularly in regions associated with social cognitive processes. Additionally, neuroimaging studies have shown increased activation in brain areas responsible for risk assessment among lonely individuals.

Furthermore, the researchers discussed findings suggesting that individuals experiencing loneliness, who perceive others negatively and exhibit signs of psychopathology, may misinterpret social cues, leading to social disconnection. Over time, this social disconnection can prompt a defensive response to social situations, further reducing motivation for social interaction.

What did the study results show?

Based on a synthesis of recent findings that indicate a causal relationship between loneliness and nervous system responses in the human body that cause inflammation and reduce immunity, the authors developed a testable model of the psychological and neural mechanisms of social disconnection in SMI. They hypothesize that people living with SMI are more likely to experience high levels of chronic psychological stress and therefore, more likely to experience persistently high levels of physiological inflammation. Stress and inflammation biomarkers can serve as indicators of an unmet need for social connection. Health providers and caregivers could use these indicators to provide social support and connection to those experiencing this need.

What is the potential impact of these findings?

The authors suggest that once their hypothesis has been rigorously tested and verified, new methods to improve health outcomes for people living with SMI may be developed, including potential “just-in-time” digital interventions through mobile devices. The authors also suggest that people living with SMI and experiencing loneliness can receive interventions that address any potential negative beliefs they hold about rejection, thus interrupting the cycle of social isolation.

Citation: Fulford D, Holt DJ. Social Withdrawal, Loneliness, and Health in Schizophrenia: Psychological and Neural Mechanisms . Schizophr Bull. 2023 Sep 7;49(5):1138-1149. doi: 10.1093/schbul/sbad099. PMID: 37419082; PMCID: PMC10483452.

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What we know about unauthorized immigrants living in the U.S.

The unauthorized immigrant population in the United States reached 10.5 million in 2021, according to new Pew Research Center estimates. That was a modest increase over 2019 but nearly identical to 2017.

The number of unauthorized immigrants living in the U.S. in 2021 remained below its peak of 12.2 million in 2007. It was about the same size as in 2004 and lower than every year from 2005 to 2015.

The new estimates do not reflect changes that have occurred since apprehensions and expulsions of migrants along the U.S.-Mexico border started increasing in March 2021 . Migrant encounters at the border have since reached historic highs .

Pew Research Center undertook this research to understand ongoing changes in the size and characteristics of the unauthorized immigrant population in the United States. The Center has published estimates of the U.S. unauthorized immigrant population for more than two decades. The estimates presented in this research are the Center’s latest, adding new and updated annual estimates for 2017 through 2021.

Center estimates of the unauthorized immigrant population use a “residual method.” It is similar to methods used by the U.S. Department of Homeland Security’s Office of Immigration Statistics and nongovernmental organizations, including the Center for Migration Studies and the Migration Policy Institute . Those organizations’ estimates are generally consistent with ours. Our estimates also align with official U.S. data sources, including birth records, school enrollment figures and tax data, as well as Mexican censuses and surveys.

Our “residual” method for estimating the nation’s unauthorized immigrant population includes these steps:

• Estimate the total number of immigrants living in the country in a particular year using data from U.S. censuses and government surveys such as the American Community Survey and the Current Population Survey.
• Estimate the number of immigrants living in the U.S. legally using official counts of immigrant and refugee admissions together with other demographic data (for example, death and out-migration rates).
• Subtract our estimate of lawful immigrants from our estimate of the total immigrant population . This provides an initial estimate of the unauthorized immigrant population .

Our final estimate of the U.S. unauthorized immigrant population, as well as estimates for lawful immigrants, includes an upward adjustment. We do this because censuses and surveys tend to miss some people . Undercounts for immigrants, especially unauthorized immigrants, tend to be higher than for other groups. (Our 1990 estimate comes from work by Robert Warren and John Robert Warren; details can be found here .)

The term “unauthorized immigrant” reflects standard and customary usage by many academic researchers and policy analysts. The U.S. Department of Homeland Security’s Office of Immigration Statistics also generally uses it. The term means the same thing as undocumented immigrants, illegal immigrants and illegal aliens.

For more details on how we produced our estimates, read the Methodology section of our November 2018 report on unauthorized immigrants.

The unauthorized immigrant population includes any immigrants not in the following groups:

• Immigrants admitted for lawful residence (i.e., green card admissions)
• People admitted formally as refugees
• People granted asylum
• Former unauthorized immigrants granted legal residence under the 1985 Immigration Reform and Control Act
• Immigrants admitted under any of categories 1-4 who have become naturalized U.S. citizens
• Individuals admitted as lawful temporary residents under specific visa categories

Read the Methodology section of our November 2018 report on unauthorized immigrants for more details.

Pew Research Center’s estimate of unauthorized immigrants includes more than 2 million immigrants who have temporary permission to be in the United States. (Some also have permission to work in the country.) These immigrants account for about 20% of our national estimate of 10.5 million unauthorized immigrants for 2021.

Although these immigrants have permission to be in the country, they could be subject to deportation if government policy changes. Other organizations and the federal government also include these immigrants in their estimates of the U.S. unauthorized immigrant population.

Immigrants can receive temporary permission to be in the U.S. through the following ways:

Temporary Protected Status (TPS)

In 2021, there were about 500,000 unauthorized immigrants with Temporary Protected Status . This status provides protection from removal or deportation to individuals who cannot safely return to their country because of civil unrest, violence or natural disaster.

Deferred Enforced Departure (DED) is a similar program that grants protection from removal. The number of immigrants with DED is much smaller than the number with TPS.

Deferred Action for Childhood Arrivals (DACA)

Deferred Action for Childhood Arrivals is a program that offers protection from deportation to individuals who were brought to the U.S. as children before June 15, 2007. As of the end of 2021, there were slightly more than 600,000 DACA beneficiaries , largely immigrants from Mexico.

Asylum applicants

Individuals who have applied for asylum but are awaiting a ruling are not legal residents yet but cannot be deported. There are two types of asylum claims, defensive and affirmative .

Defensive asylum applications are generally filed by individuals facing deportation or removal from the U.S. These are processed by the Department of Justice’s Executive Office for Immigration Review. At the end of 2021, there were almost 600,000 applications pending.

Affirmative asylum claims are made by individuals already in the U.S. who are not in the process of being deported or removed. These claims are handled by the U.S. Department of Homeland Security’s Citizenship and Immigration Services (USCIS). At the end of 2021, more than 400,000 applications for affirmative asylum were pending, some covering more than one applicant.

Here are key findings about how the U.S. unauthorized immigrant population changed from 2017 to 2021:

• The most common country of birth for unauthorized immigrants is Mexico. However, the population of unauthorized immigrants from Mexico dropped by 900,000 from 2017 to 2021 , to 4.1 million.
• There were increases in unauthorized immigrants from nearly every other region of the world – Central America, the Caribbean, South America, Asia, Europe and sub-Saharan Africa.
• Among U.S. states, only Florida and Washington saw increases to their unauthorized immigrant populations , while California and Nevada saw decreases. In all other states, unauthorized immigrant populations were unchanged.
• 4.6% of U.S. workers in 2021 were unauthorized immigrants , virtually identical to the share in 2017.

Trends in the U.S. immigrant population

The U.S. foreign-born population was 14.1% of the nation’s population in 2021. That was very slightly higher than in the last five years but below the record high of 14.8% in 1890.

As of 2021, the nation’s 10.5 million unauthorized immigrants represented about 3% of the total U.S. population and 22% of the foreign-born population. These shares were among the lowest since the 1990s.

Between 2007 and 2021, the unauthorized immigrant population decreased by 1.75 million, or 14%.

Meanwhile, the lawful immigrant population grew by more than 8 million, a 29% increase, and the number of naturalized U.S. citizens grew by 49%. In 2021, naturalized citizens accounted for about half (49%) of all immigrants in the country.

Where unauthorized immigrants come from

Unauthorized immigrants living in the U.S. come from many parts of the world, with Mexico being the most common origin country.

The origin countries for unauthorized immigrants have changed since the population peaked in 2007, before the Great Recession slowed immigration. Here are some highlights of those changes:

The number of unauthorized immigrants from Mexico living in the U.S. (4.1 million in 2021) was the lowest since the 1990s. Mexico accounted for 39% of the nation’s unauthorized immigrants in 2021, by far the smallest share on record .

The decrease in unauthorized immigrants from Mexico reflects several factors:

• A broader decline in migration from Mexico to the U.S.
• Mexican immigrants to the U.S. continuing to return to Mexico
• Expanded opportunities for lawful immigration from Mexico and other countries, especially for temporary agricultural workers.

The rest of the world

The total number of unauthorized immigrants in the U.S. from countries other than Mexico has grown rapidly. In 2021, this population was 6.4 million, up by 900,000 from 2017.

Almost every region in the world had a notable increase in the number of unauthorized immigrants in the U.S. from 2007 to 2021. The largest increases were from Central America (240,000) and South and East Asia (180,000).

After Mexico, the countries of origin with the largest unauthorized immigrant populations in the U.S. in 2021 were:

• El Salvador (800,000)
• India (725,000)
• Guatemala (700,000)
• Honduras (525,000)

India, Guatemala and Honduras all saw increases from 2017.

The Northern Triangle

Three Central American countries – El Salvador, Honduras and Guatemala – together represented 2.0 million unauthorized immigrants in the U.S. in 2021, or almost 20% of the total. The unauthorized immigrant population from the Northern Triangle grew by about 250,000 from 2017 and about 700,000 from 2007.

Other origin countries

Venezuela was the country of birth for 190,000 U.S. unauthorized immigrants in 2021. This population saw particularly fast growth, from 130,000 in 2017 and 55,000 in 2007.

Among countries with the largest numbers of U.S. unauthorized immigrants, India, Brazil, Canada and former Soviet Union countries all experienced growth from 2017 to 2021.

Some origin countries with significant unauthorized immigrant populations showed no change, notably China (375,000) and the Dominican Republic (230,000).

Detailed table: Unauthorized immigrant population by region and selected country of birth (and margins of error), 1990-2021 (Excel)

U.S. states of residence of unauthorized immigrants

The unauthorized immigrant population in most U.S. states stayed steady from 2017 to 2021. However, four states saw significant changes:

• Florida (+80,000)
• Washington (+60,000)
• California (-150,000)
• Nevada (-25,000)

States with the most unauthorized immigrants

The six states with the largest unauthorized immigrant populations in 2021 were:

• California (1.9 million)
• Texas (1.6 million)
• Florida (900,000)
• New York (600,000)
• New Jersey (450,000)
• Illinois (400,000)

These states have consistently had the most unauthorized immigrants since 1990 and earlier .

At the same time, the unauthorized immigrant population has become less geographically concentrated. In 2021, these six states were home to 56% of the nation’s unauthorized immigrants, down from 80% in 1990.

Detailed table: Unauthorized immigrant population for states (and margins of error), 1990-2021 (Excel)

Detailed table: Unauthorized immigrants and characteristics for states, 2021 (Excel)

Unauthorized immigrants in the labor force

The share of unauthorized immigrants in the U.S. workforce was slightly less than 5% in 2021, compared with 3% of the total U.S. population.

Demographics help explain the difference: The unauthorized immigrant population includes relatively few children or elderly adults, groups that tend not to be in the labor force.

Overall, about 7.8 million unauthorized immigrants were in the U.S. labor force in 2021. That was up slightly from 2019 but smaller than every year from 2007 through 2015.

Detailed table: Unauthorized immigrants in the labor force for states, 2021 (Excel)

Here are some additional findings about unauthorized immigrants as a share of the workforce nationwide and in certain states:

• Since 2003, unauthorized immigrants have made up 4.4% to 5.4% of all U.S. workers, a relatively narrow range.
• Fewer than 1% of workers in Maine, Montana, Vermont and West Virginia in 2021 were unauthorized immigrants.
• Nevada (9%) and Texas (8%) had the highest shares of unauthorized immigrants in the workforce.
• Immigrant Populations
• Immigration Issues
• Unauthorized Immigration

Jeffrey S. Passel is a senior demographer at Pew Research Center

Jens Manuel Krogstad is a senior writer and editor at Pew Research Center

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ABOUT PEW RESEARCH CENTER  Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions. It is a subsidiary of  The Pew Charitable Trusts .

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