research study about population studies

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Research Making a Difference

• Why It's Important
• Key Accomplishments
• Opportunities & Challenges

Advancing the Research

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WHY IT'S IMPORTANT

Researchers know that populations vary in their susceptibility to and resilience against heart, lung, blood, and sleep disorders, as well as in disease course and outcomes. These differences sometimes are caused by age, sex, race, ancestry or genetic factors that cannot be changed. In other cases, these differences are due to factors that can be changed or modified, such as lifestyle choices or environment, and some biological factors. Future research will help to better understand the causes of population health differences and to identify strategies that effectively address these differences before they become health disparities. Health disparities are differences in the risk, burden of diseases, and adverse health conditions that exist among specific population groups.

KEY ACCOMPLISHMENTS

• The multi-generational Framingham Heart Study helped discover risk factors and interventions to prevent heart disease, and continues to drive discovery.
• The landmark Women’s Health Initiative (WHI) found that hormone replacement therapy did not prevent heart disease as thought in post-menopausal women.
• The long-term Jackson Heart Study revealed that African Americans who took certain health measures had a lower risk for heart disease.
• The Trans-Omics for Precision Medicine (TOPMed) program is leveraging data from participants in NHLBI’s population and epidemiology studies.

OPPORTUNITIES & CHALLENGES

In 2016, the NHLBI released its Strategic Vision , which will guide the Institute’s research activities for the coming decade. Many of the objectives and compelling questions identified in the plan focus on factors that account for differences in health among populations. For example, researchers are looking at the factors that make individuals or populations resistant or prone to diseases, despite having experienced the same exposures such as diet, smoking, environmental and social factors. Part of NHLBI’s priorities include recruiting and retaining researchers who are interested in epidemiology research and developing a diverse scientific workforce.

More Information - Population and Epidemiology Studies

Age, sex, race, genes and biology may account for some differences in health among different populations.Lifestyle choices, behaviors, and socioeconomic status may also play a role in creating differences in health. Our research seeks to better understand the causes of health differences and to identify ways to improve public health and health outcomes.

Population studies have entered an exciting period when advances in assay methods, imaging technologies, and electronic data are creating new scientific opportunities. These tools make it possible for large epidemiology studies to explore what makes individuals susceptible to disease. To capitalize on these opportunities, NHLBI established an Advisory Council Working Group on Epidemiology and Population Science to look at the current landscape, emerging tools, and future opportunities in population science and  make important recommendations that contributed to the Institute’s strategic thinking in this area.

The NHLBI’s large-population cohort studies have been major generators of new knowledge that has informed the molecular basis for disease and identified targets for new treatments. For example, NHLBI research has transformed the way the public approaches cardiovascular disease by conducting numerous studies that focus on diverse populations. The  Women’s Health Initiative (WHI)  continues to yield new insights that advance our understanding of heart disease and other diseases in women.  

It is important that the NHLBI continue to build on its legacy of excellence in population studies research. Our population studies have led to a wide range of discoveries and initiatives that will reduce health disparities and improve health outcomes in  heart and vascular diseases ,  obesity ,  women’s health , and  precision medicine .

Learn about some of NHLBI’s efforts to support and advance population and epidemiology research.

We Perform Research

NHLBI’s  Division of Intramural Research , including its  Epidemiology and Community Health Branch and  Population Sciences Branch , is actively engaged in studying thousands of population cohort study participants to formulate a global view of both the natural history and future trends related to heart, lung, blood, and sleep disorders.

We Fund Research

The research we fund today will help improve our future health. Our  Division of Cardiovascular Sciences ’  Program in Prevention & Population Sciences , including its Epidemiology Branch and Clinical Application & Prevention Branch, supports population and epidemiology research including population studies, disease risk and outcome studies, and clinical trials to prevent disease and improve clinical care and public health. Other  NHLBI Divisions  also fund population and epidemiology research specific to their disease areas.

The Promise of Precision Medicine

Through NHLBI’s  Trans-Omics for Precision Medicine (TOPMed) program , researchers will use data from studies focused on heart, lung, blood and sleep disorders to better predict, prevent, diagnose, and treat diseases based on a patient’s unique genes, environment, and molecular signatures. Learn more about NHLBI  precision medicine activities .

Following Cardiovascular Disease in Generations of Families

The  Framingham Heart Study (FHS)  is a long-term study designed to identify genetic and environmental factors influencing the development of cardiovascular and other diseases in generations of families. Through the FHS, scientists learned of the risk factors for heart disease that are now checked in all routine physicals. This study has contributed discoveries that led to major changes in the prevention and treatment of heart disease.

Leading Women’s Health Research

The  Women's Health Initiative (WHI)  is a long-term study focusing on strategies to prevent the major causes of death and disability among postmenopausal women. Although the original WHI study completed data collection in 2005, the WHI continues to advance women’s health through extension studies and ancillary studies, such as the Women’s Health Initiative Strong and Healthy Study (WHISH) and the Women's Health Initiative Sleep Hypoxia Effects on Resilience (WHISPER).

Informing Improvements to Clinical Care and Public Health

The  Systolic Blood Pressure Intervention Trial (SPRINT)  demonstrated that managing high blood pressure more intensely than recommended significantly lowers the rate of cardiovascular disease and risk of death in a group of high-risk adults who are 50 years or older with high blood pressure. The SPRINT Memory and Cognition in Decreased Hypertension (SPRINT-MIND) Trial is examining whether intensive high blood pressure treatment can reduce the rate of dementia or slow the decline in cognitive function.

Investigating Atherosclerosis Causes and Outcomes

NHLBI’s  Atherosclerosis Risk in Communities Study (ARIC)  study is investigating the causes of atherosclerosis, a disease in which plaque builds up in the arteries, and the clinical outcomes from four U.S. communities. ARIC is also measuring how cardiovascular risk factors, medical care, and outcomes vary by race, sex, place, and time.

Examining Cardiovascular Disease Beginning in Young Adulthood

The  Coronary Artery Risk Development in Young Adults (CARDIA)  study examines the causes, risk factors, and natural history of cardiovascular disease that begin in young adulthood. For over 30 years, CARDIA has followed over 5,000 black and white young adults who were recruited from four centers in 1985 to 1986. The study has helped researchers better understand the importance of early adulthood factors that increase the risk of cardiovascular disease later in life.

Studying Cardiovascular Disease Outcomes

The  Cardiovascular Health Study (CHS)  is a long-term, population-based study of risk factors for the development of coronary heart disease and stroke in men and women aged 65 and older. Annual exams included measures of possible and proven cardiovascular disease risk, including subclinical disease.

Understanding How Diseases Impact Diverse Populations and People who love in Rural South

The NHLBI supports research to better understand the impact of diseases on minorities and to improve health outcomes in diverse populations. Studies include  Hispanic Community Health Study/Study of Latinos (HCHS/SOL) ;  Jackson Heart Study (JHS) ;  Multi-Ethnic Study of Atherosclerosis (MESA) ;  Strong Heart Study (SHS) ;  The Rural Cohort Study ; the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium; Consortium on Asthma among African-Ancestry Populations in the Americas (CAAPA); Healthy Communities Study: How Communities Shape Children’s Health (HCS). 

Providing Access to NHLBI Biologic Specimens and Data

The  Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC)  centralizes and integrates biospecimens and clinical data that were once stored in separate repositories. Researchers can find and request available resources on BioLINCC's secure website, which maximizes the value of these resources and advances heart, lung, blood, and sleep research.

Advancing Research on Conditions in People Living with HIV

In 2019, the NHLBI became the primary steward of the new  Men’s AIDS Cohort Study (MACS) / Women’s Interagency HIV Study (WIHS) Combined Cohort Study (MACS/WIHS-CSS) . This study is a trans-NIH collaborative research effort that aims to understand and reduce the impact of chronic health conditions that affect people living with HIV. The MACS/WIHS Combined Cohort Study will build on decades of research in thousands of men and women who are living with and without HIV to further our understanding of chronic heart, lung, blood, sleep, and other disorders in people living with HIV.

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As a Harvard University cross-school, interfaculty initiative , the Harvard Center for Population and Development Studies brings together scientists from all corners of the Harvard campus—and beyond—to make exciting advances in population research. With 8 billion people living on the planet and a projected 9.8 billion by 2050, our focus is on examining the most nuanced trends and important challenges in this century.

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Human Geography

• Defining human geography
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A short definition for Population Geography

The geographical study of population, including its spatial distribution, dynamics, and movement. As a subdiscipline, it has taken at least three distinct but related forms, the most recent of which appears increasingly integrated with human geography in general. The earliest and most enduring form of population geography emerged from the 1950s onwards, as part of spatial science . Pioneered by Glenn Trewartha, Wilbur Zelinsky , William A. V. Clark, and others in the USA, as well as Jacqueline Beujeau-Garnier and Pierre George in France, it focused on the systematic study of the distribution of population as a whole and the spatial variation in population characteristics such as fertility and mortality . Given the rapidly growing global population as well as the baby boom in affluent countries such as the USA, these geographers studied the relation between demographic growth and resources at an international scale, and population redistribution nationally ( see demographic transition ). An exemplary contribution might be Zelinksy’s mobility transition model (1971) linking migration and demographic change. They used secondary data sources such as censuses to map and describe population change and variation, including such trends as counter-urbanization . Such work could often be distinguished from population studies in general by its use of smaller scale data, below national level. Population projections at national and regional scales could be used to inform public policy debates on resource allocation. The increasing availability of more sophisticated spatial data, including more flexible census geographies, inter-censual surveys, and more detailed cross-tabulations such as the US Public-Use Microdata Samples encouraged more advanced modelling, simulation, and projection techniques ( see geodemographics ). This broad population geography has always been international and therefore comparative in scope, particularly under the auspices of the IGU Commission on Population Geography. To some extent, however, progress in the Global South has been held back by the poor availability of high-quality spatial data (Hugo 2006). Regular international conferences in population geography began in 2002.

A second variant of population geography is narrower in focus, akin to spatial demography. Geographers working in this field stressed the importance of keeping close to demography, its theories and methods, and therefore concentrating more on the core demographic variables of fertility, mortality, and, to a lesser extent, migration. They applied mathematical techniques to describe, infer, and also explain population patterns past and present. A volume edited by British geographers Bob Woods and Phil Rees (1986) Population Structures and Models: Developments in spatial demography typifies this approach. Woods’ own specialism was the historical demography of infant mortality in Victorian Britain. Spatial demography has a strong historical component, not least among French and British geographers. By detailing the spatial (and temporal) variation in mortality, fertility, nuptuality, etc., geographers were able to disrupt many of the generalizations of population change and identify the significance of place.

Many population geographers from the 1980s onwards expressed anxiety that they were marginalized from mainstream human geography and its embrace of social theories from Marxism to feminism , and postmodernism (Findlay and Graham 1991). Not enough research was being done on key issues such as famine, gender, and environment. They also sensed that other human geographers were overlooking the significance of population to wider processes. A ‘retheorization’ of population geography (White and Jackson) gradually took shape, involving more methodological diversity and theoretical plurality. New methods, such as lifecourse analysis , helped integrate biographical and individual-level studies into the field. In recent years there has been greater attention paid to gender, religion, age, disability, generation, sexuality, and race, variables which go beyond the vital statistics of births, deaths, and marriages. Furthermore, population geographers have begun to critique the standard census categories of the field, recognizing the social construction of childhood, whiteness , femininity, etc. Representative of this more theoretical approach is James Tyner’s (2009) War, Violence and Population: making the body count . Tyner argues that population geography should pay more attention to war and violence, using examples from the Vietnam War, Cambodia’s killing fields, and the Rwandan genocide. Grounded in post-colonialism and post-structuralism , he deploys Foucault’s concepts of biopower and disciplinary power to uncover the logics behind such violence.

This more recent form of population geography is increasingly aligned with human geography as a whole. One consequence has been the relative neglect of studies of fertility, mortality, and morbidity , the latter becoming the preserve of medical geography. Of the core demographic topics, migration continued to be the most central to population geographers; most of the papers in the main population geography journals, Population, Space and Place (launched in 1995 as The International Journal of Population Geography ) and Espace, Populations, Sociétés (founded 1983), concern migration and related topics such as transnationalism .

All three forms of population geography outlined here continue side by side. Spatial and historical demography is making increasing use of data sources from outside Europe. Popular textbooks such as Population Geography: Problems, Concept and Prospects (Peters and Larkin 2010) teach new generations the basics of the subject. By contrast, Adrian Bailey’s (2005) Making Population Geography presents a broader, more theoretically informed perspective. Recent conferences and journal special issues have focused on climate change, neo-Malthusianism, children’s geographies, vulnerability, and difference, although migration continues to predominate.

Rogers, A., Castree, N., & Kitchin, R. (2013). "Population geography ." In  A Dictionary of Human Geography . Oxford University Press. Retrieved 25 Jan. 2022

The study of human populations; their composition, growth, distribution, and migratory movements with an emphasis on the last two. It is concerned with the study of demographic processes which affect the environment, but differs from demography in that it is concerned with the spatial expression of such processes. Population, Space and Place is the journal of the UK Population Geography Research Group.

Mayhew, S. (2015). " Population geography ." In  A Dictionary of Geography . Oxford University Press. Retrieved 25 Jan. 2022

DEMOGRAPHY The observed, statistical, and mathematical study of human populations, concerned with the size, distribution, and composition of such populations.

Mayhew, S. (2015). "Demography ." In  A Dictionary of Geography . Oxford University Press. Retrieved 25 Jan. 2022 

In the Library's collections

    Many of the books on Population Studies and Demography are located in the call number range HB 848 through HB 3697 on Berry Level 3 .

    To browse in the library's catalog, do a subject search for Population . That will give a list of the subject headings under Population and the number of items under each heading. You can also do the same for Demography .

• population forecasting
• overpopulation
• malthusianism
• sex preselection

Introductory reading(s)

Selected book titles

Journal articles & titles

Articles and other writings about Population Studies can be found in many publications. Our collection includes several journals which look at Population Studies and Demography. Below is a short list of some of the journal titles we have in our Library's collection. Or you can use the search box at the top of the page.

Internet resource(s)

Keeping up with the journal literature

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Don't own or use a mobile device? You can still use BrowZine! It's now available in a web version. You can get to it here . The web version works the same way as the app version. Find the journals you like, create a custom Bookshelf, get ToCs and read the articles you want.

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Michigan’s Population Studies Center

PSC was established in 1961 and has a rich history as an interdisciplinary community  of scholars in population  research and  training . PSC is one of five centers within the University of Michigan’s Institute for Social Research  (ISR).

PSC receives  core funding   from the  Eunice Kennedy Shriver National Institute of Child Health & Human Development (P2CHD041028). The  Population Dynamics and Health Program (PDHP) , which supports research in population health, is part of PSC.

News & Announcements

Remembering Social Demographer, Demographic Historian John Knodel

John Knodel, who extended the boundaries of population science, died, at 83, on January 10, in Ann Arbor. The Professor Emeritus in the Department of Sociology and Population Studies Center (PSC) at the University of Michigan changed the way demographers think about fertility change, HIV/AIDS, aging, historical demography, and mixed methods research, and paved the…

More about Remembering Social Demographer, Demographic Historian John Knodel >

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January 22, 2024

Two ISR-affiliated faculty members receive project funding from the Graham Sustainability Institute

Remembering John Edwin Knodel

December 5, 2023

The Population Studies Center Year in Review: 2023

PSC Events Calendar

Psc brown bag seminar: jenna nobles, april psc coffee hour, psc brown bag seminar: analisa packham, celebrate the career of arland thornton, psc brown bag seminar: emma riley, psc small grants.

Private gifts are a true investment in the research and training conducted at the Population Studies Center. They are used to support graduate students, young faculty, and international scholars, and to seed small research projects.

Currently six funds have been established at PSC. Learn more about these funds — those they honor, and the work they support– or browse all PSC Small Grants awarded .

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UCL and University of Bristol to lead support hub for UK’s longitudinal population studies

27 March 2024

UCL and the University of Bristol will lead the Population Research UK (PRUK) co-ordination hub, part of an existing strategic investment from the UKRI Infrastructure Fund.

The UK is a world leader in population research, bolstered by its unique collection of longitudinal population studies, which follow groups of people over time. Individually, the studies have made substantial contributions to the advancement of social and health sciences and together, they have the power to uncover the drivers behind major societal challenges and provide a potent tool for basic science application. 

The collective power of the UK’s longitudinal studies was never more apparent than during the COVID-19 pandemic. Studies across the country coordinated to rapidly capture the epidemiological events affecting their participants, work which was then combined with a lifetime of data to shed light on how our backgrounds and lifelong health shaped our experience of the pandemic. This was just one of many examples demonstrating how important it is to make the most of population-based research in the UK.  

The PRUK mission is therefore to further harness the potential of these scientific resources by supporting researchers, policymakers and study management teams to maximise benefits and overcome shared challenges. 

The coordination hub is the culmination of previous PRUK activity, which has been funded through the  Economic and Social Research Council  (ESRC) and the  Medical Research Council  (MRC) since 2021. The hub is a £9 million investment that will play an important role in PRUK providing joined-up thinking across the UK’s longitudinal population studies and commissioning activities that will result in better, easier to use data resources for social, economic and biomedical science. It marks a further commitment to longitudinal population research infrastructure, alongside ESRC’s continuing investments in CLOSER and MRC and ESRC’s joint investment in the UK Longitudinal Linkage Collaboration. 

The PRUK co-ordination hub will be directed by Professor Alissa Goodman, Director of the UCL Centre for Longitudinal Studies (CLS) and Professor Nic Timpson, Principal Investigator of the Children of the 90s cohort at the University of Bristol. Professors Goodman and Timpson bring a wealth of experience in life course research and longitudinal study leadership and management. 

The investment strengthens UCL’s position as a global leader in life course research: the university is already home to all five of the UK’s national birth cohorts, and existing longitudinal study infrastructure such as CLS and CLOSER. 

PRUK Co-Director, Professor Goodman of UCL, added: “The UK is a world-leader in longitudinal population studies and Population Research UK provides us with an incredible opportunity to come together as a community. PRUK will create a forum for the users and creators of longitudinal population studies, and the infrastructure that serves them. Through engagement in the forum and commissioning of services, we will drive innovations in how we work in order to maximise the value and potential of these fantastic resources.” 

PRUK Co-Director, Professor Timpson of the University of Bristol, said: “PRUK will seek to deliver enhanced use of population-based research assets in the UK. Our community model will deliver a combination of connected working, skilled users undertaking open science with complex multi-modal data, and engaged policymaker, public and participant stakeholders. The overall aim is to maximise the sector’s value for the public good.” 

The wider leadership team of the PRUK hub team includes experts from across the UK longitudinal population research infrastructure landscape. Professors Goodman and Timpson are joined in leading the new initiative by Andy Boyd of the UK Longitudinal Linkage Collaboration, Paul Bradshaw of the Scottish Centre for Social Research (ScotCen), Professor Rosie McEachan of Born in Bradford, Chris Orton of Population Data Science at Swansea University Medical School, and Professor Jennifer Symonds of CLOSER. 

PRUK will focus on five key areas critical to successful longitudinal population research and data collection, identified in the PRUK prospectus , building on existing provision and commissioning additional activities to address priority needs: 

• data discovery; 
• data access;
• data linkage;
• training and capacity building;
• coordination and advocacy.

Email [email protected]  and follow PRUK on X at @PopResUK .

Related links

• More about the UKRI Infrastructure Fund
• Professor Alissa Goodman's research profile (UCL)
• Professor Nic Timpson's profile (University of Bristol)
• UCL Centre for Longitudinal Studies
• Cohort and Longitudinal Studies Enhancement Resources (CLOSER)
• UCL Social Research Institute

Mattjeacock via iStock.

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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!

LEARN MORE         FREE TRIAL

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Development of Prediction Models of COVID-19 Vaccine Uptake among Lebanese and Syrians in a district of Beirut, Lebanon: a population-based study

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Introduction: Vaccines are essential to prevent infection and reduce morbidity of infectious diseases. Previous evidence has shown that migrants and refugees are particularly vulnerable to exclusion and discrimination, and low COVID-19 vaccine intention and uptake were observed among refugees globally. This study aimed to develop and internally validate prediction models of COVID-19 vaccine uptake by nationality. Methods: This is a nested prognostic population-based cross-sectional analysis. Data was collected between June and October 2022 in Sin-El-Fil, a district of Beirut, Lebanon. All Syrian adults and a random sample of adults from low-socioeconomic status neighborhoods were invited to participate in a telephone survey. The main outcome was uptake of COVID-19 vaccine. Predictors of COVID-19 vaccine uptake were assessed using LASSO regression for Lebanese and Syrian nationalities, respectively. Results: Of 2,045 participants, 79% were Lebanese, 18% Syrians and 3% of other nationalities. COVID-19 vaccination uptake was higher among Lebanese (85% (95%CI:82-86) compared to Syrians (47% (95% CI:43-51)) (P<0.001); adjusted odds ratio (aOR) 6.8 (95%CI:5.5-8.4). Predictors of uptake of one or more vaccine dose for Lebanese were older age, presence of an older adult in the household, higher education, greater asset-based wealth index, private healthcare coverage, feeling susceptible to COVID-19, belief in the safety and efficacy of vaccines and previous receipt of flu vaccine. For Syrians they were older age, male, completing school or higher education, receipt of cash assistance, presence of comorbidities, belief in the safety and efficacy of vaccines, previous receipt of flu vaccine, and legal residency status in Lebanon. Conclusions: These findings indicate barriers for vaccine uptake in Syrian migrants and refugees, including legal residency status. They call for urgent action to enable equitable access to vaccines by raising awareness about the importance of vaccination and the targeting of migrant and refugee populations through vaccination campaigns.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This work was funded by the International Development Research Centre (IDRC), Canada

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The study protocol was reviewed and approved by the American University of Beirut Social and Behavioral Sciences Institutional Review Board (reference: SBS-2021-0268).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

The abstract was revised and edited.

Data Availability

The anonymized data can be obtained upon reasonable request from the Center for Research on Population and Health at the American University of Beirut ([email protected]).

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• v.42(1); Jan-Feb 2020

Sample Size and its Importance in Research

Chittaranjan andrade.

Clinical Psychopharmacology Unit, Department of Clinical Psychopharmacology and Neurotoxicology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India

The sample size for a study needs to be estimated at the time the study is proposed; too large a sample is unnecessary and unethical, and too small a sample is unscientific and also unethical. The necessary sample size can be calculated, using statistical software, based on certain assumptions. If no assumptions can be made, then an arbitrary sample size is set for a pilot study. This article discusses sample size and how it relates to matters such as ethics, statistical power, the primary and secondary hypotheses in a study, and findings from larger vs. smaller samples.

Studies are conducted on samples because it is usually impossible to study the entire population. Conclusions drawn from samples are intended to be generalized to the population, and sometimes to the future as well. The sample must therefore be representative of the population. This is best ensured by the use of proper methods of sampling. The sample must also be adequate in size – in fact, no more and no less.

SAMPLE SIZE AND ETHICS

A sample that is larger than necessary will be better representative of the population and will hence provide more accurate results. However, beyond a certain point, the increase in accuracy will be small and hence not worth the effort and expense involved in recruiting the extra patients. Furthermore, an overly large sample would inconvenience more patients than might be necessary for the study objectives; this is unethical. In contrast, a sample that is smaller than necessary would have insufficient statistical power to answer the primary research question, and a statistically nonsignificant result could merely be because of inadequate sample size (Type 2 or false negative error). Thus, a small sample could result in the patients in the study being inconvenienced with no benefit to future patients or to science. This is also unethical.

In this regard, inconvenience to patients refers to the time that they spend in clinical assessments and to the psychological and physical discomfort that they experience in assessments such as interviews, blood sampling, and other procedures.

ESTIMATING SAMPLE SIZE

So how large should a sample be? In hypothesis testing studies, this is mathematically calculated, conventionally, as the sample size necessary to be 80% certain of identifying a statistically significant outcome should the hypothesis be true for the population, with P for statistical significance set at 0.05. Some investigators power their studies for 90% instead of 80%, and some set the threshold for significance at 0.01 rather than 0.05. Both choices are uncommon because the necessary sample size becomes large, and the study becomes more expensive and more difficult to conduct. Many investigators increase the sample size by 10%, or by whatever proportion they can justify, to compensate for expected dropout, incomplete records, biological specimens that do not meet laboratory requirements for testing, and other study-related problems.

Sample size calculations require assumptions about expected means and standard deviations, or event risks, in different groups; or, upon expected effect sizes. For example, a study may be powered to detect an effect size of 0.5; or a response rate of 60% with drug vs. 40% with placebo.[ 1 ] When no guesstimates or expectations are possible, pilot studies are conducted on a sample that is arbitrary in size but what might be considered reasonable for the field.

The sample size may need to be larger in multicenter studies because of statistical noise (due to variations in patient characteristics, nonspecific treatment characteristics, rating practices, environments, etc. between study centers).[ 2 ] Sample size calculations can be performed manually or using statistical software; online calculators that provide free service can easily be identified by search engines. G*Power is an example of a free, downloadable program for sample size estimation. The manual and tutorial for G*Power can also be downloaded.

PRIMARY AND SECONDARY ANALYSES

The sample size is calculated for the primary hypothesis of the study. What is the difference between the primary hypothesis, primary outcome and primary outcome measure? As an example, the primary outcome may be a reduction in the severity of depression, the primary outcome measure may be the Montgomery-Asberg Depression Rating Scale (MADRS) and the primary hypothesis may be that reduction in MADRS scores is greater with the drug than with placebo. The primary hypothesis is tested in the primary analysis.

Studies almost always have many hypotheses; for example, that the study drug will outperform placebo on measures of depression, suicidality, anxiety, disability and quality of life. The sample size necessary for adequate statistical power to test each of these hypotheses will be different. Because a study can have only one sample size, it can be powered for only one outcome, the primary outcome. Therefore, the study would be either overpowered or underpowered for the other outcomes. These outcomes are therefore called secondary outcomes, and are associated with secondary hypotheses, and are tested in secondary analyses. Secondary analyses are generally considered exploratory because when many hypotheses in a study are each tested at a P < 0.05 level for significance, some may emerge statistically significant by chance (Type 1 or false positive errors).[ 3 ]

INTERPRETING RESULTS

Here is an interesting question. A test of the primary hypothesis yielded a P value of 0.07. Might we conclude that our sample was underpowered for the study and that, had our sample been larger, we would have identified a significant result? No! The reason is that larger samples will more accurately represent the population value, whereas smaller samples could be off the mark in either direction – towards or away from the population value. In this context, readers should also note that no matter how small the P value for an estimate is, the population value of that estimate remains the same.[ 4 ]

On a parting note, it is unlikely that population values will be null. That is, for example, that the response rate to the drug will be exactly the same as that to placebo, or that the correlation between height and age at onset of schizophrenia will be zero. If the sample size is large enough, even such small differences between groups, or trivial correlations, would be detected as being statistically significant. This does not mean that the findings are clinically significant.

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Conflicts of interest.

There are no conflicts of interest.

Association of Coffee Consumption and Prediagnostic Caffeine Metabolites With Incident Parkinson Disease in a Population-Based Cohort

Affiliation.

• 1 From the Institute for Risk Assessment Sciences (Y.Z., H.K., S. Peters, R.V.), Utrecht University, the Netherlands; Department of Environmental Health Sciences (Y.L., G.W.M.), Mailman School of Public Health, Columbia University, New York, NY; Department of Epidemiology (J.M.H.), Murcia Regional Health Council-IMIB, Murcia; CIBER Epidemiología y Salud Pública (CIBERESP) (J.M.H., M.G.), Madrid; Movement Disorders Unit (A.V.-A.), Department of Neurology, University Hospital Donostia; BioDonostia Health Research Institute (A.V.-A.), Neurodegenerative Diseases Area, San Sebastián, Spain; Division of Cancer Epidemiology (J.A.S.), German Cancer Research Center (DKFZ), Heidelberg, Germany; Danish Cancer Institute (J.H.), Danish Cancer Society, Copenhagen, Denmark; Escuela Andaluza de Salud Pública (EASP) (D.P.); Instituto de Investigación Biosanitaria-ibs.GRANADA (D.P.), Granada; Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP) (D.P.), Madrid, Spain; Unit of Cancer Epidemiology (C.S.), Città della Salute e della Scienza University-Hospital, Turin, Italy; Unit of Nutrition and Cancer (R.Z.-R.), Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; Epidemiology and Prevention Unit (V.P.), Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Italy; Department of Epidemiology and Biostatistics (A.K.H., M.G.), School of Public Health, Imperial College London, United Kingdom; School of Medicine (S. Panico), Federico II University, Naples, Italy; de Salud Pública y Laboral de Navarra (M.G.), Pamplona; Navarra Institute for Health Research (IdiSNA) (M.G.), Pamplona, Spain; Institute for Cancer Research (G.M.), Prevention and Clinical Network (ISPRO), Florence, Italy; Institute of Epidemiology and Social Medicine (C.M.L.), University of Münster, Germany; Ageing Epidemiology Research Unit (AGE) (C.M.L.), School of Public Health, Imperial College London, United Kingdom; and University Medical Centre Utrecht (R.V.), the Netherlands.
• PMID: 38513162
• DOI: 10.1212/WNL.0000000000209201

Background and objectives: Inverse associations between caffeine intake and Parkinson disease (PD) have been frequently implicated in human studies. However, no studies have quantified biomarkers of caffeine intake years before PD onset and investigated whether and which caffeine metabolites are related to PD.

Methods: Associations between self-reported total coffee consumption and future PD risk were examined in the EPIC4PD study, a prospective population-based cohort including 6 European countries. Cases with PD were identified through medical records and reviewed by expert neurologists. Hazard ratios (HRs) and 95% CIs for coffee consumption and PD incidence were estimated using Cox proportional hazards models. A case-control study nested within the EPIC4PD was conducted, recruiting cases with incident PD and matching each case with a control by age, sex, study center, and fasting status at blood collection. Caffeine metabolites were quantified by high-resolution mass spectrometry in baseline collected plasma samples. Using conditional logistic regression models, odds ratios (ORs) and 95% CIs were estimated for caffeine metabolites and PD risk.

Results: In the EPIC4PD cohort (comprising 184,024 individuals), the multivariable-adjusted HR comparing the highest coffee intake with nonconsumers was 0.63 (95% CI 0.46-0.88, p = 0.006). In the nested case-control study, which included 351 cases with incident PD and 351 matched controls, prediagnostic caffeine and its primary metabolites, paraxanthine and theophylline, were inversely associated with PD risk. The ORs were 0.80 (95% CI 0.67-0.95, p = 0.009), 0.82 (95% CI 0.69-0.96, p = 0.015), and 0.78 (95% CI 0.65-0.93, p = 0.005), respectively. Adjusting for smoking and alcohol consumption did not substantially change these results.

Discussion: This study demonstrates that the neuroprotection of coffee on PD is attributed to caffeine and its metabolites by detailed quantification of plasma caffeine and its metabolites years before diagnosis.

• Caffeine* / metabolism
• Case-Control Studies
• Parkinson Disease* / diagnosis
• Parkinson Disease* / epidemiology
• Parkinson Disease* / etiology
• Prospective Studies
• Risk Factors

• Open access
• Published: 25 March 2024

A genetic survey of patients with familial idiopathic intracranial hypertension residing in a Middle Eastern village: genetic association study

• Eran Berkowitz   ORCID: orcid.org/0000-0001-6817-7513 1 , 4 , 5 ,
• Tzipora C. Falik Zaccai   ORCID: orcid.org/0000-0003-0065-1922 3 ,
• Dana Irge   ORCID: orcid.org/0000-0001-5001-9795 6 ,
• Inbar Gur   ORCID: orcid.org/0000-0002-1089-3266 1 ,
• Beatrice Tiosano   ORCID: orcid.org/0000-0002-1379-4861 1 &
• Anat Kesler   ORCID: orcid.org/0000-0001-7611-8484 1 , 2 , 4  

European Journal of Medical Research volume  29 , Article number:  194 ( 2024 ) Cite this article

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Metrics details

The aim of this study was to determine whether genetic variants are associated with idiopathic intracranial hypertension (IIH) in a unique village where many of the IIH patients have familial ties, a homogenous population and a high prevalence of consanguinity. Several autosomal recessive disorders are common in this village and its population is considered at a high risk for genetic disorders.

The samples were genotyped by the Ilumina OmniExpress-24 Kit, and analyzed by the Eagle V2.4 and DASH software package to cluster haplotypes shared between our cohort. Subsequently, we searched for specific haplotypes that were significantly associated with the patient groups.

Fourteen patients and 30 controls were included. Samples from 22 female participants (11 patients and 11 controls) were evaluated for haplotype clustering and genome-wide association studies (GWAS). A total of 710,000 single nucleotide polymorphisms (SNPs) were evaluated. Candidate areas positively associated with IIH included genes located on chromosomes 16, 8 (including the CA5A and BANP genes, p  < 0.01), and negatively associated with genes located on chromosomes 1 and 6 (including PBX1 , LMX1A , ESR1 genes, p  < 0.01).

Conclusions

We discovered new loci possibly associated with IIH by employing a GWAS technique to estimate the associations with haplotypes instead of specific SNPs. This method can in all probability be used in cases where there is a limited amount of samples but strong familial connections. Several loci were identified that might be strong candidates for follow-up studies in other well-phenotypes cohorts.

Idiopathic intracranial hypertension (IIH), also known as pseudotumor cerebri (PTC), is a disorder of unknown etiology, predominantly affecting obese women of childbearing age [ 1 , 2 ]. At present, IIH is considered a sporadic disease, although some researchers have suggested that IIH may have a familial component [ 3 ]. Few familial occurrences have been recorded [ 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 ], although, in the Idiopathic Intracranial Hypertension Treatment Trial (IIHTT), 5% of patients stated that other family members were affected with IIH [ 4 ]. In other studies, the rate of familial occurrences has been reported between 2.9% and 11% [ 3 , 4 , 5 ], which is higher than its rate in the general population [ 11 ]. Recently, the NORDIC IIHTT Study Group [ 10 ] ran a Genome-Wide Association Study (GWAS) on the IIHTT cohort, using Chips interrogating 538,448 markers to determine whether genetic variants are associated with this condition. The study identified three candidate regions marked by multiple associated single-nucleotide polymorphisms (SNPs) on chromosomes 5, 13, and 14.

Our study cohort comprised Israeli patients and their families affected with IIH residing in a village in northern Israel known for its homogenous population and high prevalence of consanguinity. Several autosomal recessive disorders are common in this village and its population is considered at a high risk for genetic disorders. Severe diseases such as intellectual disability, non-syndromic hearing loss, spinal muscular dystrophy related-disease, primary microcephaly (MCPH), and Basel-Vanagaite–Smirin-Yosef Syndrome have been observed in this population [ 12 , 13 ]. This population mainly descends from Egyptian ancestors who arrived in the 1800s, together with Bedouin tribes from the Jordan Valley [ 14 ]. Many of the village’s original families and descendants have remained in the village, and today encompasses ~15,000 inhabitants. Our aim was to investigate the genetic variants that may be associated with IIH in a population residing in this village, as a high prevalence of IIH patients from this village relative to its size has been observed.

Given the potential small sample size (stemming from this cohort’s special characteristics), using traditional GWAS analysis techniques to analyze the data from this village, may be inappropriate. Discovering a GWAS method to evaluate small cohorts with some genetic similarity, while evaluating and analyzing DNA from patients suffering from IIH in this village, using advanced analytical methods, may offer a possible insight into this disorder and further advance our knowledge of this disease’s possible etiology.

This study protocol was approved by the local Institutional Review Board and Ethics Committee of the Hillel Yaffe Medical Center, Israel and the Supreme IRB Committee of the Israeli Ministry of Health (reference number is 030-2018, approved on the 29th of May 2018). Written informed consent was obtained from all study participants. Study subjects were inhabitants of this village recruited from IIH patients referred to the Neuro-Ophthalmology Clinic, Hillel Yaffe Medical Center, Israel, between 2018 and 2020. Controls included healthy first-degree family members also living in this village. All participants underwent a detailed clinical evaluation to diagnose IIH according to the modified Dandy criteria [ 15 ]. Controls were examined to exclude those with symptoms or signs of IIH. Buccal swab DNA samples were obtained from the patients and the controls by MyHeritage’s DNA kits. The samples were then shipped to “Gene by Gene” LTD (Houston, TX, USA) for genomic DNA isolation and genotyping.

Single-nucleotide polymorphism array genotyping

Genome-wide SNP genotypes were obtained for all samples using MyHeritage’s costume array, based on the Ilumina OmniExpress-24 Kit, containing ~710,000 markers (SNPs).

Ethnicity estimation

Ethnicity of the patients and controls was evaluated by the MyHeritage™ Ethnicity Estimation algorithm, which calculated the percentages for each region from which the subjects’ DNA was inherited.

Familial relations and consanguinity analysis

To measure familial relations in our cohort of patients and controls, the identity by descent (IBD) MyHeritage’s relative matching algorithm [ 16 ] determined the genetic sharing (in centiMorgan) between the participants.

Associations between SNPs and IIH

Due to the high levels of consanguinity in the cohort resulting in long IBD segments (Fig.  1 ) and their distinct ethnicity profile (Fig.  2 ), there is no known reference panel that will share enough of their unique genomics to phase their haplotypes with high precision. The excessive resemblance between individuals gives us the ability to align haplotypes with the cohort itself as a reference panel. Therefore, for haplotype phasing, we used the Eagle V2.4 program [ 17 ] in cohort mode. We ran the DASH [ 18 ] software package with default blocks of 32 SNPs to cluster haplotypes shared between our cohort. Subsequently, we proceeded to search for specific haplotypes that were significantly associated with the patient group. Manhattan plots of the results were drawn using the Assocplots package [ 19 ].

A Dendrograms of study participants showing the shared DNA between the individuals of the study. Total shared segment length (cM) between all individuals of the cohort. B same as A using the length of the longest shared segment (cM)

Ancestry profiles of cases and controls combined

Statistical analysis

PLINK’s 1.9 toolset [ 20 ] permutation tests computed the p values. The t test tested for differences in the demographic characteristics between the patients and controls.

Our cohort included 14 patients and 30 controls. DNA samples were obtained from all; however, since men and women have slightly different symptom profiles [ 21 ] which could be indicative of distinct genetic risk factors, only samples from 22 female participants (11 patients and 11 controls) were evaluated for haplotype clustering and GWAS. Study participants and controls were chosen from 9 different families, which included two families where two patients were first-degree relatives. The 22 participants were similar in body mass index (BMI) ( p  = 0.64); the average BMI for the participants was 38.3 (29-59); controls, 40.4 (28-57). The patients were younger than the controls ( p  = 0.02), (average age 26.6 years; range 15–48 years); (controls, 40 years; range 13–60 years). The analysis contained 710,000 SNPs validated by MyHeritage™, of which 694,265 SNPs had a known Ref/Alt in HapMap [ 22 ].

Clinical findings

Familial relationships.

An analysis of the study’s cohort demonstrated a close relationship between all subjects, even those who did not identify themselves as relatives (Fig.  1 ).

Ethnicity estimate

The participants’ ethnicity was mostly African (> 30%) and Middle Eastern (30%; Fig.  2 ). There was no significant difference between cases and controls.

Association studies

Samples from the 22 female participants were evaluated in this haplotype clustering and GWAS.

Association to haplotypes

Haplotype clustering indicated a few suspected haplotypes found significantly more prevalent in patients than in the controls. Candidate areas positively associated with IIH included genes on chromosomes 16, 8 and negatively associated with genes on chromosomes 1 and 6 (Table  1 , Fig.  3 ). The first of these loci are located on chromosome 16 and include the CA5A (OMIM # 114761) and BNP (OMIM # 600295) genes. The second loci with a strong positive effect are on chromosome 8 and comprise too many genes. Loci with a protective effect were located on chromosome 1, and included the PBX1 (OMIM # 176310) and LMX1A (OMIM # 600298) genes, and an additional locus on chromosome 6 which included the ESR1 gene (OMIM # 133430).

A Manhattan plot of the haplotypes’ association with IIH. The (log10) p values of each SNP indicating the strength of the association are plotted by chromosome from left to right. The Y axis corresponds to the strength of the association with the disease. The horizontal line highlights the topmost significant loci

The quest for understanding the genetic contributions to IIH is critical to unravel the enigmatic nature of this disorder. Our study focused on a unique Middle Eastern village with a distinct prevalence of familial ties among the IIH patients, thus providing an opportunity to explore genetic associations in the context of a homogenous population with high consanguinity rates. By employing innovative methodologies, we aimed to shed light on potential genetic factors underlying this complex condition. Our findings indicated that within this distinctive population the presence of genetic loci was possibly associated with IIH. Traditional GWAS analyzes substantial sample sizes, which can be challenging in the context of rare conditions such as IIH. Nonetheless, we adopted a creative approach by analyzing long haplotypes rather than individual SNPs, capitalizing on the fact that the patients in our cohort were related, and therefore, our results were still significant.

This approach allowed us to uncover statistically significant associations despite our limited sample size, as reported in previous studies, which have successfully demonstrated genetic associations using small cohorts, i.e., the NORDIC IIHTT Study Group who identified three candidate regions on chromosomes 5, 13, and 14 with a relatively modest sized cohort of 95 patients and controls [ 10 ]. Intriguingly, we identified regions on chromosomes 16, 8, 1, and 6 that demonstrated potential associations with IIH susceptibility or protection (Table  1 ). Within chromosome 16, genes CA5A and BANP surfaced as potential contributors. CA5A encodes a carbonic anhydrase enzyme [ 23 ] linked to various metabolic processes, including obesity-related pathways [ 24 , 25 , 26 , 27 , 28 , 29 ]. As obesity is a known risk factor for IIH, the connection between CA5A and IIH could indicate novel mechanistic pathways underlying this correlation. Interestingly, acetazolamide, the first line of drugs in treating IIH, is a carbonic anhydrase inhibitor [ 30 ]. Similarly, BANP, a tumor suppressor and cell cycle regulator [ 31 ], might play a role in IIH etiology through interactions with p53 transcription.

On chromosome 8, while the precise gene could not be pinpointed due to the region's complexity, its association with IIH remains a promising avenue for future research. Protective effects were observed on chromosomes 1 and 6, where PBX1 and LMX1A are located. PBX1 is associated with osteogenesis and insulin gene regulation [ 32 ], whereas LMX1A is linked to dopamine-producing neuron development [ 33 ], potentially implicating dopaminergic pathways in IIH. Moreover, the identification of the ESR1 gene on chromosome 6, which is linked to estrogen-regulated processes [ 34 ], adds a layer of complexity to IIH's genetic landscape. As estrogen is known to influence various physiological functions, including adipose tissue distribution, our findings could suggest novel interactions between hormonal factors and IIH susceptibility.

Implications and future directions

Our study underscores the importance of tailoring genetic investigations to the unique characteristics of study populations. The distinctive nature of our cohort, with its high consanguinity and shared ancestry, facilitated the utilization of advanced analytical techniques, resulting in the identification of potentially relevant genetic associations. While the commonly used threshold for genome-wide association studies is 5 × 10 −8 –5 × 10 −5 , our unique cohort with familial connections led us to choose a more exploratory threshold of log10 ( p value) of 2.0; hence, it is crucial to acknowledge the limitations of our study, primarily the modest sample size. However, we believe that our unique cohort with familial connections justifies our choice.

Our study is unique in that it focuses on a relatively rare disease, and a small, homogenous population with strong familial connections, therefore making it difficult to obtain a large sample size. Using a more exploratory threshold, we were able to identify candidate areas that may be associated with IIH in this population. In addition, we used a haplotype-based approach to estimate the associations with haplotypes instead of SNPs. Last, our pilot study aimed at identifying candidate areas that may be associated with IIH in a unique population. We acknowledge that our sample size is small and that our threshold is more exploratory than conventional thresholds. Nevertheless, we believe that our findings are promising and warrant further investigation in larger, well-phenotyped cohorts.

Several genes were identified as potential candidates associated with disease susceptibility; however, we acknowledge the speculative nature of these findings, particularly, considering our novel analytical approach. Our method introduces a new perspective, and while it holds promise, we recognize the need for caution in interpreting these preliminary associations. Despite this constraint, our approach offers a promising avenue for similar studies in other specialized cohorts with strong familial connections. As we move forward, it is imperative to expand the exploration of these loci through independent cohorts and functional studies. Future research should delve into the precise mechanisms by which these genes exert their effects in addition to investigating potential interactions with environmental factors.

In conclusion, our investigation in a unique Middle Eastern village has revealed genetic loci that may contribute to IIH susceptibility and protection. Through innovative methodologies, we demonstrated the power of haplotype-based GWAS analysis in situations where traditional approaches face limitations. Our findings provide a stepping stone for future studies to further illuminate the complex genetic underpinnings of IIH and potentially offer insights into early detection and targeted interventions for individuals at risk of developing this condition. Further studies are warranted to validate and elucidate the functional significance of these findings.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Single-nucleotide polymorphisms

• Idiopathic intracranial hypertension

Genome-Wide Association Study

Idiopathic Intracranial Hypertension Treatment Trial

Primary microcephaly hereditary

Identity by descent

Ahlskog JE, O’Neill BP. Pseudotumor cerebri . Ann Intern Med. 1982;97:249–56. https://doi.org/10.7326/0003-4819-97-2-249 .

Article   CAS   PubMed   Google Scholar  

Burkett JG, Ailani J. An up to date review of Pseudotumor cerebri syndrome. Curr Neurol Neurosci Rep. 2018;18:33. https://doi.org/10.1007/s11910-018-0839-1 .

Corbett JJ. The First Jacobson Lecture. Familial idiopathic intracranial hypertension. J Neuroophthalmol. 2008;28:337–47. https://doi.org/10.1097/WNO.0b013e31818f12a2 .

Article   PubMed   Google Scholar  

Smith SV, Friedman D. The idiopathic intracranial hypertension treatment trial: a review of the outcomes. Headache. 2017;57:1303–10. https://doi.org/10.1111/head.13144 .

Klein A, Dotan G, Kesler A. Familial occurrence of idiopathic intracranial hypertension. Isr Med Assoc J. 2018;20:557–60.

PubMed   Google Scholar  

Buchheit WA, Burton C, Haag B, Shaw D. Papilledema and idiopathic intracranial hypertension. N Engl J Med. 1969;280:938–42. https://doi.org/10.1056/NEJM196904242801707 .

Gardner K, Cox T, Digre KB. Idiopathic intracranial hypertension associated with tetracycline use in fraternal twins: case reports and review. Neurology. 1995;45:6–10. https://doi.org/10.1212/wnl.45.1.6 .

Fujiwara S, Sawamura Y, Kato T, Abe H, Katusima H. Idiopathic intracranial hypertension in female homozygous twins. J Neurol Neurosurg Psychiatry. 1997;62:652–4. https://doi.org/10.1136/jnnp.62.6.652 .

Article   CAS   PubMed   PubMed Central   Google Scholar  

Karaman K, Gverovic-Antunica A, Zuljan I, Vukojevic N, Zoltner B, Erceg I, et al. Familial idiopathic intracranial hypertension. Croat Med J. 2003;44:480–4.

Kuehn MH, Mishra R, Deonovic BE, Miller KN, McCormack SE, Liu GT, et al. Genetic survey of adult-onset idiopathic intracranial hypertension. J Neuroophthalmol. 2019;39:50–5.

Article   PubMed   PubMed Central   Google Scholar  

Kesler A, Gadoth N. Epidemiology of idiopathic intracranial hypertension in Israel. J Neuroophthalmol. 2001;21:12–4. https://doi.org/10.1097/00041327-200103000-00003 .

Basel-Vanagaite L, Smirin-Yosef P, Essakow JL, Tzur S, Lagovsky I, Maya I, et al. Homozygous MED25 mutation implicated in eye-intellectual disability syndrome. Hum Genet. 2015;134:577–87. https://doi.org/10.1007/s00439-015-1541-x .

Zlotogora J, Shalev S, Habiballah H, Barjes S. Genetic disorders among Palestinian Arabs: 3. Autosomal recessive disorders in a single village. Am J Med Genet. 2000;92:343–5. https://doi.org/10.1002/1096-8628(20000619) .

Tyler Warwick PN. State lands and rural development in mandatory Palestine, 1920–1948. Portland: Sussex Academic Press; 2001.

Google Scholar  

Friedman DI, Liu GT, Digre KB. Revised diagnostic criteria for the Pseudotumor cerebri syndrome in adults and children. Neurology. 2013;81:1159–65. https://doi.org/10.1212/WNL.0b013e3182a55f17 .

Erlich Y, Shor T, Pe’er I, Carmi S. Identity inference of genomic data using long-range familial searches. Science. 2018;362:690–4. https://doi.org/10.1126/science.aau4832 .

Loh P-R, Danecek P, Palamara PF, Fuchsberger C, Reshef YA, Finucane HK, et al. Reference-based phasing using the Haplotype Reference Consortium panel. Nat Genet. 2016;48:1443–8. https://doi.org/10.1038/ng.3679 .

Gusey A, Kenny EE, Lowey JK, Salit J, Saxena R, Kathiresan S, et al. A method for identical-by-descent haplotype mapping uncovers association with recent variation. Am J Hum Genet. 2011;10(88):706–17. https://doi.org/10.1016/j.ajhg.2011.04.023 .

Article   CAS   Google Scholar  

Khramtsova EA, Stranger BE. Assocplots: a Python package for static and interactive visualization of multiple-group GWAS results. Bioinform. 2017;33:432–4. https://doi.org/10.1093/bioinformatics/btw641 .

Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, et al. PLINK: a toolset for whole-genome association and population-based linkage analysis. Am J Hum Genet. 2007;81:559–75. https://doi.org/10.1086/519795 .

Bruce BB, Kedar S, Van Stavern GP, Monaghan D, Acierno MD, Braswell RA, et al. Idiopathic intracranial hypertension in men. Neurology. 2009;72:304–9. https://doi.org/10.1212/01.wnl.0000333254.84120.f .

The International HapMap Consortium. The International HapMap Project. Nature. 2003;426:789–96. https://doi.org/10.1038/nature02168 .

Nagao Y, Batanian JR, Clemente MF, Sly WS. Genomic organization of the human gene (CA5) and pseudogene for mitochondrial carbonic anhydrase V and their localization to chromosomes 16q and 16p. Genomics. 1995;28:477–84. https://doi.org/10.1006/geno.1995.1177 .

Shah GN, Hewett-Emmett D, Grubb JH, Migas MC, Fleming RE, Waheed A, Sly WS. Mitochondrial carbonic anhydrase CA VB: differences in tissue distribution and pattern of evolution from those of CA VA suggest distinct physiological roles. Proc Natl Acad Sci USA. 2000;97:1677–82. https://doi.org/10.1073/pnas.97.4.1677 .

Dodgson SJ. Inhibition of mitochondrial carbonic anhydrase and ureagenesis: a discrepancy examined. J Appl Physiol. 1987;63:2134–41. https://doi.org/10.1152/jappl.1987.63.5.2134 .

Dodgson SJ, Cherian K. Mitochondrial carbonic anhydrase is involved in rat renal glucose synthesis. Am J Physiol. 1989;257:E791–6. https://doi.org/10.1152/ajpendo.1989.257.6.E791 .

Lynch CJ, Fox H, Hazen SA, Stanley BA, Dodgson S, Lanoue KF. Role of hepatic carbonic anhydrase in de novo lipogenesis. Biochem J. 1995;310:197–202. https://doi.org/10.1042/bj3100197 .

Arechederra RL, Waheed A, Sly WS, Supuran CT, Minteer SD. Effect of sulfonamides as carbonic anhydrase VA and VB inhibitors on mitochondrial metabolic energy conversion. Bioorg Med Chem. 2013;21:1544–8. https://doi.org/10.1016/j.bmc.2012.06.053 .

de Simone G, Supuran CT. Antiobesity carbonic anhydrase inhibitors. Curr Top Med Chem. 2007;7:879–84. https://doi.org/10.2174/156802607780636762 .

Brown PD, Davies SL, Speake T, Millar ID. Molecular mechanisms of cerebrospinal fluid production. Neurosci. 2004;129:957–70. https://doi.org/10.1016/j.neurosci.2004.07.003 .

Gene ID: 54971, updated on 12-Oct-2019.

Moskow JJ, Bullrich F, Huebner K, Daar IO, Buchberg AM. Meis1, a PBX1-related homeobox gene involved in myeloid leukemia in BXH-2 mice. Mol Cell Biol. 1995;15:5434–43. https://doi.org/10.1128/MCB.15.10.5434 .

Doucet-Beaupré H, Ang S-L, Lévesque M. Cell fate determination, neuronal maintenance and disease state: The emerging role of transcription factors Lmx1a and Lmx1b. FEBS Lett. 2015;589:3727–38. https://doi.org/10.1016/j.febslet.2015.10.020 .

Gene ID: 2099, updated on 25-Jan-2022.

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Acknowledgements

We thank the team from My Heritage for assisting in data extraction and processing, Lina Nostin for her great contribution and assistance to the study and Phyllis Curchack Kornspan for her editorial services.

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The Adelson School of Medicine, Ariel University, Ariel, Israel

Eran Berkowitz & Anat Kesler

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EB, DI, BT and AK conceptualized the study, performed the methodology. EB, TCFZ and AK performed the formal analysis and investigation. EB and AK prepared the original draft. BT and AK prepared the resources. BT and AK supervised the study. EB and IG acquired the data. All authors reviewed the manuscript. All authors read and approved the final manuscript.

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This study protocol was approved by the local Institutional Review Board and Ethics Committee of the Hillel Yaffe Medical Center, Israel and the Supreme IRB Committee of the Israeli Ministry of Health (reference number is 030-2018, approved on the 29th of May 2018). Written informed consent was obtained from all study participants.

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Berkowitz, E., Falik Zaccai, T.C., Irge, D. et al. A genetic survey of patients with familial idiopathic intracranial hypertension residing in a Middle Eastern village: genetic association study. Eur J Med Res 29 , 194 (2024). https://doi.org/10.1186/s40001-024-01800-z

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The Effects of Climate Change

The effects of human-caused global warming are happening now, are irreversible for people alive today, and will worsen as long as humans add greenhouse gases to the atmosphere.

• We already see effects scientists predicted, such as the loss of sea ice, melting glaciers and ice sheets, sea level rise, and more intense heat waves.
• Scientists predict global temperature increases from human-made greenhouse gases will continue. Severe weather damage will also increase and intensify.

Earth Will Continue to Warm and the Effects Will Be Profound

Global climate change is not a future problem. Changes to Earth’s climate driven by increased human emissions of heat-trapping greenhouse gases are already having widespread effects on the environment: glaciers and ice sheets are shrinking, river and lake ice is breaking up earlier, plant and animal geographic ranges are shifting, and plants and trees are blooming sooner.

Effects that scientists had long predicted would result from global climate change are now occurring, such as sea ice loss, accelerated sea level rise, and longer, more intense heat waves.

The magnitude and rate of climate change and associated risks depend strongly on near-term mitigation and adaptation actions, and projected adverse impacts and related losses and damages escalate with every increment of global warming.

Intergovernmental Panel on Climate Change

Some changes (such as droughts, wildfires, and extreme rainfall) are happening faster than scientists previously assessed. In fact, according to the Intergovernmental Panel on Climate Change (IPCC) — the United Nations body established to assess the science related to climate change — modern humans have never before seen the observed changes in our global climate, and some of these changes are irreversible over the next hundreds to thousands of years.

Scientists have high confidence that global temperatures will continue to rise for many decades, mainly due to greenhouse gases produced by human activities.

The IPCC’s Sixth Assessment report, published in 2021, found that human emissions of heat-trapping gases have already warmed the climate by nearly 2 degrees Fahrenheit (1.1 degrees Celsius) since 1850-1900. 1 The global average temperature is expected to reach or exceed 1.5 degrees C (about 3 degrees F) within the next few decades. These changes will affect all regions of Earth.

The severity of effects caused by climate change will depend on the path of future human activities. More greenhouse gas emissions will lead to more climate extremes and widespread damaging effects across our planet. However, those future effects depend on the total amount of carbon dioxide we emit. So, if we can reduce emissions, we may avoid some of the worst effects.

The scientific evidence is unequivocal: climate change is a threat to human wellbeing and the health of the planet. Any further delay in concerted global action will miss the brief, rapidly closing window to secure a liveable future.

Here are some of the expected effects of global climate change on the United States, according to the Third and Fourth National Climate Assessment Reports:

Future effects of global climate change in the United States:

U.S. Sea Level Likely to Rise 1 to 6.6 Feet by 2100

Global sea level has risen about 8 inches (0.2 meters) since reliable record-keeping began in 1880. By 2100, scientists project that it will rise at least another foot (0.3 meters), but possibly as high as 6.6 feet (2 meters) in a high-emissions scenario. Sea level is rising because of added water from melting land ice and the expansion of seawater as it warms. Image credit: Creative Commons Attribution-Share Alike 4.0

Climate Changes Will Continue Through This Century and Beyond

Global climate is projected to continue warming over this century and beyond. Image credit: Khagani Hasanov, Creative Commons Attribution-Share Alike 3.0

Hurricanes Will Become Stronger and More Intense

Scientists project that hurricane-associated storm intensity and rainfall rates will increase as the climate continues to warm. Image credit: NASA

More Droughts and Heat Waves

Droughts in the Southwest and heat waves (periods of abnormally hot weather lasting days to weeks) are projected to become more intense, and cold waves less intense and less frequent. Image credit: NOAA

Longer Wildfire Season

Warming temperatures have extended and intensified wildfire season in the West, where long-term drought in the region has heightened the risk of fires. Scientists estimate that human-caused climate change has already doubled the area of forest burned in recent decades. By around 2050, the amount of land consumed by wildfires in Western states is projected to further increase by two to six times. Even in traditionally rainy regions like the Southeast, wildfires are projected to increase by about 30%.

Changes in Precipitation Patterns

Climate change is having an uneven effect on precipitation (rain and snow) in the United States, with some locations experiencing increased precipitation and flooding, while others suffer from drought. On average, more winter and spring precipitation is projected for the northern United States, and less for the Southwest, over this century. Image credit: Marvin Nauman/FEMA

Frost-Free Season (and Growing Season) will Lengthen

The length of the frost-free season, and the corresponding growing season, has been increasing since the 1980s, with the largest increases occurring in the western United States. Across the United States, the growing season is projected to continue to lengthen, which will affect ecosystems and agriculture.

Global Temperatures Will Continue to Rise

Summer of 2023 was Earth's hottest summer on record, 0.41 degrees Fahrenheit (F) (0.23 degrees Celsius (C)) warmer than any other summer in NASA’s record and 2.1 degrees F (1.2 C) warmer than the average summer between 1951 and 1980. Image credit: NASA

Arctic Is Very Likely to Become Ice-Free

Sea ice cover in the Arctic Ocean is expected to continue decreasing, and the Arctic Ocean will very likely become essentially ice-free in late summer if current projections hold. This change is expected to occur before mid-century.

U.S. Regional Effects

Climate change is bringing different types of challenges to each region of the country. Some of the current and future impacts are summarized below. These findings are from the Third 3 and Fourth 4 National Climate Assessment Reports, released by the U.S. Global Change Research Program .

• Northeast. Heat waves, heavy downpours, and sea level rise pose increasing challenges to many aspects of life in the Northeast. Infrastructure, agriculture, fisheries, and ecosystems will be increasingly compromised. Farmers can explore new crop options, but these adaptations are not cost- or risk-free. Moreover, adaptive capacity , which varies throughout the region, could be overwhelmed by a changing climate. Many states and cities are beginning to incorporate climate change into their planning.
• Northwest. Changes in the timing of peak flows in rivers and streams are reducing water supplies and worsening competing demands for water. Sea level rise, erosion, flooding, risks to infrastructure, and increasing ocean acidity pose major threats. Increasing wildfire incidence and severity, heat waves, insect outbreaks, and tree diseases are causing widespread forest die-off.
• Southeast. Sea level rise poses widespread and continuing threats to the region’s economy and environment. Extreme heat will affect health, energy, agriculture, and more. Decreased water availability will have economic and environmental impacts.
• Midwest. Extreme heat, heavy downpours, and flooding will affect infrastructure, health, agriculture, forestry, transportation, air and water quality, and more. Climate change will also worsen a range of risks to the Great Lakes.
• Southwest. Climate change has caused increased heat, drought, and insect outbreaks. In turn, these changes have made wildfires more numerous and severe. The warming climate has also caused a decline in water supplies, reduced agricultural yields, and triggered heat-related health impacts in cities. In coastal areas, flooding and erosion are additional concerns.

1. IPCC 2021, Climate Change 2021: The Physical Science Basis , the Working Group I contribution to the Sixth Assessment Report, Cambridge University Press, Cambridge, UK.

2. IPCC, 2013: Summary for Policymakers. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

3. USGCRP 2014, Third Climate Assessment .

4. USGCRP 2017, Fourth Climate Assessment .

Related Resources

A Degree of Difference

So, the Earth's average temperature has increased about 2 degrees Fahrenheit during the 20th century. What's the big deal?

What’s the difference between climate change and global warming?

“Global warming” refers to the long-term warming of the planet. “Climate change” encompasses global warming, but refers to the broader range of changes that are happening to our planet, including rising sea levels; shrinking mountain glaciers; accelerating ice melt in Greenland, Antarctica and the Arctic; and shifts in flower/plant blooming times.

Is it too late to prevent climate change?

Humans have caused major climate changes to happen already, and we have set in motion more changes still. However, if we stopped emitting greenhouse gases today, the rise in global temperatures would begin to flatten within a few years. Temperatures would then plateau but remain well-elevated for many, many centuries.

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New Studies Find No Evidence of Brain Injury in Havana Syndrome Cases

The findings from the National Institutes of Health are at odds with previous research that looked into the mysterious health incidents experienced by U.S. diplomats and spies.

By Julian E. Barnes

Reporting from Washington

New studies by the National Institutes of Health failed to find evidence of brain injury in scans or blood markers of the diplomats and spies who suffered symptoms of Havana syndrome, bolstering the conclusions of U.S. intelligence agencies about the strange health incidents.

Spy agencies have concluded that the debilitating symptoms associated with Havana syndrome, including dizziness and migraines, are not the work of a hostile foreign power . They have not identified a weapon or device that caused the injuries, and intelligence analysts now believe the symptoms are most likely explained by environmental factors, existing medical conditions or stress.

The lead scientist on one of the two new studies said that while the study was not designed to find a cause, the findings were consistent with those determinations.

The authors said the studies are at odds with findings from researchers at the University of Pennsylvania, who found differences in brain scans of people with Havana syndrome symptoms and a control group

Dr. David Relman, a prominent scientist who has had access to the classified files involving the cases and representatives of people suffering from Havana syndrome, said the new studies were flawed. Many brain injuries are difficult to detect with scans or blood markers, he said. He added that the findings do not dispute that an external force, like a directed energy device, could have injured the current and former government workers.

The studies were published in The Journal of the American Medical Association on Monday alongside an editorial by Dr. Relman that was critical of the findings.

The incidents began to occur in greater concentrations at the end of 2016 and in 2017 in Havana and later in China, Austria and elsewhere. The Biden administration took office in 2021 promising to improve health care for diplomats and spies suffering from the symptoms and vowing to get to the bottom of what was causing them.

Studies by the University of Pennsylvania in 2018 and 2019 suggested that people affected by the syndrome had possible brain injuries that were different from typical concussion injuries or other traumatic brain injuries.

The N.I.H. studies looked at a different group of people, with less than a third of the cases overlapping. Dr. Leighton Chan, the acting chief scientific officer for the N.I.H. Clinical Center and the lead author of one of the studies, said that of the 86 participants, 24 cases were from Cuba, six from China, 17 from Vienna, nine from around the United States and 30 from other locations.

While examining the brain scans, the researchers found no significant differences with the control group.

In a news conference discussing the results before their public release, the N.I.H. scientists said their scans, done in a research setting, were more precise than the scans produced primarily in clinical settings during earlier studies. They also said the control group was more closely matched to the study participants, improving the study’s rigor.

Researchers from the University of Pennsylvania said the two studies were “apples to oranges” comparisons because they looked at different groups of patients, and the N.I.H. study was not designed to replicate theirs.

The N.I.H. scientists said they did not diagnose the patients with traumatic brain injuries or concussions. The diagnoses they offered instead, all so-called “ functional neurologic disorders ,” are often caused by stress.

The studies did not rule out a potential external cause for Havana syndrome symptoms. But if one was not involved, Dr. Chan said, stress “may explain more of our findings.”

“It is important to note that individuals with functional neurological disorders of any cause have symptoms that are real, distressing and very difficult to treat,” Dr. Chan said.

The N.I.H. diagnosis angered several people with Havana syndrome symptoms who said it was insulting and misguided because it was tantamount to calling their symptoms psychosomatic or the result of mass hysteria.

Dr. Relman, who was among the leaders of an experts panel established by the intelligence agencies and another by the National Academy of Sciences , said the work of those groups had found that the symptoms of some of the affected government workers could not have been caused by stress or psychosocial factors alone.

The N.I.H. studies looked at a large group of people who reported diverse symptoms, rather than zeroing in on overseas cases where additional evidence shows something strange could have been going on, Dr. Relman said. In those cases, a concealable device, capable of delivering directed energy in a targeted way, could have been responsible.

“To lump all these cases together in the way they did is simply asking for trouble,” Dr. Relman said.

Mark Zaid, a lawyer for several people with Havana syndrome symptoms, said many current and former officials treated at N.I.H. were upset that they were not briefed on the study before it came out. Mr. Zaid said some patients were told that they had to participate in the study to receive treatment from the government for their symptoms. Mr. Zaid said that had raised ethical questions about the patients’ consent.

Dr. Chan disputed that and said that the people who participated did so willingly and could have left the study at any time.

But Mr. Zaid said he feared that the C.I.A. and other intelligence agencies would improperly use the study to bolster their findings that they could not determine an external cause for Havana syndrome cases.

“The concern is that intelligence community is going to weaponize this study to show that the absence of evidence is evidence,” Mr. Zaid said. “And it is not.”

Julian E. Barnes covers the U.S. intelligence agencies and international security matters for The Times. He has written about security issues for more than two decades. More about Julian E. Barnes