Wednesday, September 04, 2024

Rising temperatures in Africa may increase perinatal deaths

Karolinska Institutet

Heatwaves in sub-Saharan Africa are predicted to become more common due to climate change. A new study by researchers at Karolinska Institutet and others, published in Nature Medicine, reveals a worrying correlation between high temperatures in the final week of pregnancy and an increased risk of stillbirth and early neonatal mortality.

“While temperatures are rising in sub-Saharan Africa, knowledge of how they affect pregnant women and their babies is scant,” says the study’s corresponding author Claudia Hanson, docent at the Department of Global Public Health, Karolinska Institutet, Sweden.

“Our results indicate that mother and newborn care in this region must be improved to ensure that hard-won improvements in reducing mortality are not lost to climate change,” adds Andrea Pembe, professor at the Department of Obstetrics and Gynaecology, Muhimbili University of Health and Allied Sciences, Tanzania.

The study included over 138,000 births at 16 hospitals in four countries in sub-Saharan Africa: Benin, Malawi, Tanzania and Uganda. The researchers analysed the association between high temperatures in the week before birth and perinatal mortality, which is to say a death just before, during, or within 24 hours after birth. High temperatures were defined as an increase in average weekly temperature for a typically warm week (between 22 and 28 °C depending on country, corresponding to the 75th percentile) to an exceptionally warm week (between 24 and 29 °C, corresponding to the 99th percentile).

Babies whose mothers had been exposed to high temperatures the week before childbirth had a 34 per cent higher risk of perinatal death, a risk that doubled during the six hottest months of the year. Unlike in many other countries, a large proportion – almost half – of all stillbirths occurred during labour.

“Our study shows that there is an urgent need to develop and implement interventions that protect pregnant women and their babies during heatwaves,” says co-lead author Jeroen de Bont, a postdoctoral researcher in Petter Ljungman’s research group at the Institute of Environmental Medicine, Karolinska Institutet.

In sub-analyses of heat-associated mortality by timing of death (before, during or after labour), the researchers observed trends towards increased stillbirths during labour, but not all estimates reached statistical significance.

The next phase of the research needs to focus on redesigning maternity wards to mitigate the effects of heat on pregnant women and staff, including using improved construction techniques such as ceiling insulation, and creating adjacent green areas, which can bring additional health benefits. The researchers will also be studying how heat affects other maternal and childbirth outcomes, and how it interacts with environmental factors such as air pollution.

The study was primarily financed by the EU’s Horizon 2020 research and innovation programme and was carried out in close collaboration with Makerere University, Uganda, Muhimbili University of Health and Allied Sciences, Tanzania, Centre de Recherche en Reproduction Humaine et en Démographie (CERRHUD), Benin, and Kamuzu University of Health Science, Malawi. The researchers report no conflicts of interest.

Facts: Every year, 1.9 million babies around the world die just before or during childbirth (stillbirth) and an additional 2.3 million die during the neonatal period (within the first 28 days of life). Sub-Saharan Africa is the region with the highest mortality rates. Reducing the stillbirth and neonatal mortality rates is one of the UN’s sustainable development goals and the principal objective of the WHO’s Every Newborn Action Plan initiative.

Publication: “A time-stratified, case-crossover study of heat exposure and perinatal mortality from 16 hospitals in sub-Saharan Africa”, Claudia Hanson*, Jeroen de Bont* (joint first-authorship), Kristi Sidney Annerstedt, Maria del Rosario Alsina, Federica Nobile, Nathalie Roos, Peter Waiswa, Andrea Pembe, Jean-Paul Dossou, Effie Chipeta, Lenka Benova, Hussein Kidanto, Cherie Part, Massimo Stafoggia, Veronique Filippi, Petter Ljungman, Nature Medicine, online 3 September 2024, doi: 10.1038/s41591-024-03245-7.

Journal

Nature Medicine

DOI

10.1038/s41591-024-03245-7

Method of Research

Observational study

Subject of Research

People

Article Title

A time-stratified, case-crossover study of heat exposure and perinatal mortality from 16 hospitals in sub-Saharan Africa

Article Publication Date

3-Sep-2024

New tool detects fake, AI-produced scientific articles

Binghamton University researcher develops xFakeSci to root out bogus research

Binghamton University

Document with microscope — image:
A researcher at Binghamton University, State University of New York has developed a tool to root out bogus, AI-generated research articles.
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Credit: Binghamton University, State University of New York

BINGHAMTON, N.Y. -- When ChatGPT and other generative artificial intelligence can produce scientific articles that look real — especially to someone outside that field of research — what’s the best way to figure out which ones are fake?

Ahmed Abdeen Hamed, a visiting research fellow at Binghamton University, State University of New York, has created a machine-learning algorithm he calls xFakeSci that can detect up to 94% of bogus papers — nearly twice as successfully as more common data-mining techniques.

“My main research is biomedical informatics, but because I work with medical publications, clinical trials, online resources and mining social media, I’m always concerned about the authenticity of the knowledge somebody is propagating,” said Hamed, who is part of George J. Klir Professor of Systems Science Luis M. Rocha’s Complex Adaptive Systems and Computational Intelligence Lab. “Biomedical articles in particular were hit badly during the global pandemic because some people were publicizing false research.”

In a new paper published in the journal Scientific Reports, Hamed and collaborator Xindong Wu, a professor at Hefei University of Technology in China, created 50 fake articles for each of three popular medical topics — Alzheimer’s, cancer and depression — and compared them to the same number of real articles on the same topics.

Hamed said when he asked ChatGPT for the AI-generated papers, “I tried to use exact same keywords that I used to extract the literature from the [National Institutes of Health’s] PubMed database, so we would have a common basis of comparison. My intuition was that there must be a pattern exhibited in the fake world versus the actual world, but I had no idea what this pattern was.”

After some experimentation, he programmed xFakeSci to analyze two major features about how the papers were written. One is the numbers of bigrams, which are two words that frequently appear together such as “climate change,” “clinical trials” or “biomedical literature.” The second is how those bigrams are linked to other words and concepts in the text.

“The first striking thing was that the number of bigrams were very few in the fake world, but in the real world, the bigrams were much more rich,” Hamed said. “Also, in the fake world, despite the fact that were very few bigrams, they were so connected to everything else.”

Hamed and Wu theorize that the writing styles are different because human researchers don’t have the same goals as AIs prompted to produce a piece on a given topic.

“Because ChatGPT is still limited in its knowledge, it tries to convince you by using the most significant words,” Hamed said. “It is not the job of a scientist to make a convincing argument to you. A real research paper reports honestly about what happened during an experiment and the method used. ChatGPT is about depth on a single point, while real science is about breadth.”

To further develop xFakeSci, Hamed plans to expand the range of topics to see if the telltale word patterns hold for other research areas, going beyond medicine to include engineering, other scientific topics and the humanities. He also foresees AIs becoming increasingly sophisticated, so determining what is and isn’t real will get increasingly difficult.

“We are always going to be playing catchup if we don’t design something comprehensive,” he said. “We have a lot of work ahead of us to look for a general pattern or universal algorithm that does not depend on which version of generative AI is used.”

Because even though their algorithm catches 94% of AI-generated papers, he added, that means six out of 100 fakes are still getting through: “We need to be humble about what we’ve accomplished. We’ve done something very important by raising awareness.”

Journal

Scientific Reports

DOI

10.1038/s41598-024-66784-6

Method of Research

Computational simulation/modeling

Article Title

Detection of ChatGPT fake science with the xFakeSci learning algorithm

“Artificial intelligence will play an increasing role in scientific publications”

“May help editors select papers that will garner greater attention”

Boston University School of Medicine

(Boston)—Artificial intelligence (AI), in various forms, has burst onto the scene in both society and medicine. Its role in medicine is still evolving, but undoubtedly, it will assist in the evaluation of images (radiographs, pathological reports, videos of colonoscopy,) as well as in preparing discharge summaries, consultative evaluations and diagnosis. It may also help in the long-awaited goal of precision medicine. In addition, it has and will play an increasing role in scientific publication in at least two areas, peer-review and drafting manuscripts.

According to former editor-in-chief of the Journal of the American Medical Association Howard Bauchner, MD, in the coming years, AI will transform the writing of scientific manuscripts, assist in reviewing them, and help editors select the most impactful papers. “Potentially it may help editors increase the influence of their journals,” says Bauchner, professor of pediatrics at Boston University Chobanian & Avedisian School of Medicine.

In a guest editorial in the European Journal of Emergency Medicine, Bauchner examines how AI could be used by editors. “Given that identifying enough peer-reviewers is getting increasingly difficult, editors could use AI to provide an initial “score.” An article with what is determined to have a good score could then be sent for external peer-review (with simply a cursory review by the editors). For articles with an inadequate score, the editors could still consider it for publication after reviewing it or even possibly depending upon the report, ask authors to revise the manuscript,” he explains.

When AI becomes available to predict citations, which influences the journals’ impact factor, Bauchner questions if editors should use the information. “First, editors should establish a vision for their journal – what is its mission – and is an individual article consistent with the mission and “in scope.” Second, editors need to carefully consider the role of value-added pieces. How do they enhance the value of the journal. Third, editors need to maximize the reach of their journal, particularly in social media. Journals are communication networks. Fourth, editors need to understand the meaning of open science, including open peer-review, data-sharing, and open access. After an editor has thought through these issues, then yes, having AI assist in determining how much an article would be cited – assuming the results of the study are valid, and simply not meant to attract attention – is reasonable.”

Bauchner points out that AI will not replace editors or peer-reviewers, but rather provide additional information about the quality of a manuscript making triaging manuscripts faster and more objective. “AI will play an increasing role in scientific publication – particularly in peer-review and drafting of manuscripts. Given that in both areas there are important challenges, investigators, peer-reviewers, editors, and funders should welcome the assistance that AI will provide,” he adds.

Journal

European Journal of Emergency Medicine

DOI

10.1097/MEJ.0000000000001164

Method of Research

Commentary/editorial

Article Title

Artificial intelligence and the future of scientific publication

IOP Publishing partners with Hum to explore data and AI use to enhance content strategy

IOP Publishing

Hum x IOPP — image:
IOP Publishing partners with Hum
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Credit: Hum

IOP Publishing, the publishing arm of the Institute of Physics, is partnering with Hum, the cutting-edge data and AI company, to explore ways to further enhance its author experience and develop its outstanding publishing services.

This partnership underscores IOP Publishing’s commitment to delivering personalised, relevant, and impactful content experiences across their portfolio of over 100 open access and hybrid journals, ebooks, science news, and other resources.

Hum’s advanced AI platforms analyse vast amounts of audience and content data, uncovering actionable insights that will help IOP Publishing by:

Targeting outreach and omnichannel campaigns to highly specific audience segments
Developing marketing and outreach strategies for authors and reviewers
Identifying emerging topics for future content development
Surfacing the most relevant content recommendations for individual readers

“At IOP Publishing, deepening our relationship with the scientific community is at the heart of everything we do,” said Miriam Maus, Chief Publishing Officer, “Partnering with Hum provides technology that delivers insights into our content and enhances engagement with authors and readers. We’re looking forward to creating more opportunities to advance science through the global exchange of ideas.”

“We’re thrilled to be able to help IOP Publishing unlock the full potential of its audience and content, driving greater engagement, reach, and impact,” said Tim Barton, Hum CEO. “IOPP has been pushing the boundaries on what researchers, authors, readers, and reviewers expect and is committed to advancing that experience. Hum is eager to help them continue to do so.”

New Reichman University study: People in financial distress behave more morally

Reichman University

A new study conducted at Reichman University, in collaboration with Aarhus University in Denmark, challenges the negative stereotypes associated with individuals facing economic hardship. The study, led by Prof. Guy Hochman of Reichman University’s Baruch Ivcher School of Psychology, head of the master’s degree program in behavioral economics, explored the relationship between financial scarcity, information-seeking, and ethical behavior.

It is a common belief that people living in poverty are less moral, as they are driven by a need to focus on survival, which may lead them to engage in unethical behavior to increase their income. Others suggest that this stems from a sense of social injustice. The purpose of the study was to investigate whether financial deprivation truly affects the processing of information and ethical decision-making.

The researchers used advanced eye-tracking technology to analyze the participants’ behavior. During the experiment, participants performed a task in which they had the opportunity to cheat in order to increase their financial gain. Surprisingly, the results revealed that while the participants experiencing financial deprivation tended to focus more on “tempting” information that could have allowed them to cheat, they actually cheated less than the participants who were more affluent.

The findings of the experiment indicate that despite the economic temptation and the tendency to focus on information that could facilitate cheating, individuals in financial distress tend to uphold their moral standards. Furthermore, the results imply that negative stereotypes associating immoral behaviors with economically disadvantaged populations are unfounded, showing that those in need actually tend to behave more ethically.

Prof. Guy Hochman, Baruch Ivcher School of Psychology, Reichman University: “The study's results offer an optimistic view, revealing that individuals facing economic hardship are actually more likely to act morally than those living in abundance. These findings can help reduce prejudices against economically disadvantaged people and guide efforts to foster ethical behavior across society. Most importantly, the study demonstrates that people do not abandon their moral standards for financial gain, even when under economic distress. This research may have a significant impact on social perceptions and public policies on welfare and social justice, and offers a new and encouraging perspective on human behavior under economic pressure.”

Journal

Journal of Behavioral Decision Making

DOI

10.1002/bdm.2402

Method of Research

Experimental study

Subject of Research

People

Article Title

Resource Constraints Lead to Biased Attention but Decrease Unethical Behavior

$1.8 million NIH grant to FAU engineering fuels quest to decode human evolution

Cutting-edge tools will help to unravel genetic mechanisms behind disease resistance and defense

Florida Atlantic University

Quest to Decode Human Evolution — image:
Michael DeGiorgio, Ph.D., PI, associate chair and associate professor, FAU Department of Electrical Engineering and Computer Science, and Department of Biomedical Engineering.
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Credit: Florida Atlantic University

Natural selection is an important evolutionary force that enables humans to adapt to new environments and fight disease-causing pathogens. However, the unique footprints of natural selection in our genome can be buried beneath those left by other evolutionary forces. Thus, by leveraging information about multiple evolutionary forces, researchers can identify signatures of natural selection in the human genome, and ultimately determine its role in human adaptation and disease.

Low-cost DNA sequencing has provided researchers with an abundance of genomic data, enabling them to search for evidence of natural selection in different species. However, various nonadaptive factors can sometimes obscure these signals, making it essential to develop sophisticated statistical methods that can account for multiple factors influencing genetic variation.

Michael DeGiorgio, Ph.D., in the College of Engineering and Computer Science at Florida Atlantic University, has received a five-year $1,874,360 grant from the National Institute of General Medical Sciences (NIGMS) of the United States National Institutes of Health (NIH) to further his research on designing and applying statistical methods to identify regions of the genome affected by natural selection. The project titled, “Identifying Complex Modes of Adaptation from Population-genomic Data,” is an NIH NIGMS Maximizing Investigators Research Award for Established Investigators.

This research aims to develop powerful tools for identifying diverse modes of adaptation from genetic data and to better understand the evolutionary mechanisms underlying traits like disease resistance and pathogen defense.

“To truly grasp how human genetic variation has evolved and is distributed, it’s essential to study the evolutionary mechanisms at play,” said Stella Batalama, Ph.D., dean, FAU College of Engineering and Computer Science. “The advent of advanced high-throughput sequencing technologies, along with significant boosts in computational capabilities, has equipped geneticists with powerful new tools. This important grant from the National Institutes of Health will enable our outstanding research team led by professor DeGiorgio to delve deeper into understanding the evolutionary forces that contribute to the diversity observed across human populations.”

DeGiorgio and his research team work on detecting natural selection, which affects the frequency of traits within populations and leaves subtle genetic signals in the DNA sequences of individuals within these populations. Over the past four years, his team has made significant advances in this field, developing some of the first, most powerful and state-of-the-art model-based methods for unearthing genomic signals of a diverse array of adaptive events through analysis of DNA within and across species. These methods draw from a broad array of statistical and engineering techniques, by leveraging and integrating the strengths of probabilistic, machine learning, and signal processing frameworks.

“Our methods have led to several novel insights,” said DeGiorgio, associate chair and associate professor, FAU Department of Electrical Engineering and Computer Science, and Department of Biomedical Engineering. “For example, we found evidence of convergent positive selection in Europeans and East Asians that may explain differences in insulin response between these populations. We also discovered positive selection in olfactory genes affecting scent and behavior of rats in New York City for navigating harsh and noisy urban environments, and identified balancing selection in venom genes that may play a role in predator-prey interactions in rattlesnakes.”

Recent advancements in AI, especially deep learning, have greatly improved outcome prediction using complex data like genetic information. These algorithms learn from training data and apply this knowledge to new, unseen data. Their strength lies in handling complex features and adapting to various data types. However, they often face challenges when the new data differs from the training data, a problem known as “domain shift.”

“To enhance prediction accuracy, it's crucial to adapt to changing data conditions and refine feature selection and modeling,” said DeGiorgio.

In the coming five years, DeGiorgio plans to advance this research by developing improved statistical, machine learning, and signal processing approaches. These methods will aim to detect complex patterns of adaptation by considering how various evolutionary forces simultaneously shape genetic diversity. Specifically, researchers will focus on creating novel frameworks to identify positive and balancing selection while accounting for genomic, temporal and spatial factors.

DeGiorgio and his research team will work on methods to detect regions with complex patterns of selection from ancient genetic variation, use signal processing techniques to analyze genomic data from images for machine learning models, and develop innovative procedures to address uncertainties in genetic and demographic parameters when training these models.

“With these advanced techniques, researchers can now study adaptation in a wider variety of organisms, from well-researched models to those less frequently examined,” said Javad Hashemi, Ph.D., inaugural chair and professor, FAU Department of Biomedical Engineering, and associate dean for research and professor in the College of Engineering and Computer Science. “This broader focus will not only increase inclusivity in this research but also deepen the understanding of how different species adapt to their environments. By applying these novel methods to diverse organisms – such as primates, rodents, snakes, insects and plants – our researchers will tackle significant evolutionary questions and uncover new insights across a range of biological contexts.”

- FAU -

About FAU’s College of Engineering and Computer Science:

The FAU College of Engineering and Computer Science is internationally recognized for cutting-edge research and education in the areas of computer science and artificial intelligence (AI), computer engineering, electrical engineering, biomedical engineering, civil, environmental and geomatics engineering, mechanical engineering, and ocean engineering. Research conducted by the faculty and their teams expose students to technology innovations that push the current state-of-the art of the disciplines. The College research efforts are supported by the National Science Foundation (NSF), the National Institutes of Health (NIH), the Department of Defense (DOD), the Department of Transportation (DOT), the Department of Education (DOEd), the State of Florida, and industry. The FAU College of Engineering and Computer Science offers degrees with a modern twist that bear specializations in areas of national priority such as AI, cybersecurity, internet-of-things, transportation and supply chain management, and data science. New degree programs include Master of Science in AI (first in Florida), Master of Science and Bachelor in Data Science and Analytics, and the new Professional Master of Science and Ph.D. in computer science for working professionals. For more information about the College, please visit eng.fau.edu.

About Florida Atlantic University:
Florida Atlantic University, established in 1961, officially opened its doors in 1964 as the fifth public university in Florida. Today, the University serves more than 30,000 undergraduate and graduate students across six campuses located along the southeast Florida coast. In recent years, the University has doubled its research expenditures and outpaced its peers in student achievement rates. Through the coexistence of access and excellence, FAU embodies an innovative model where traditional achievement gaps vanish. FAU is designated a Hispanic-serving institution, ranked as a top public university by U.S. News & World Report and a High Research Activity institution by the Carnegie Foundation for the Advancement of Teaching. For more information, visit www.fau.edu.

How zebrafish map their environment

Spatial orientation mechanisms surprisingly similar to our own

Max-Planck-Gesellschaft

Tracking microscope — image:
A tracking microscop follows the zebrafish during their natural behaviour.

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Credit: Jean-Claude Winkler/MPI for Biological Cybernetics

Researchers are turning to zebrafish to unlock the secrets of place cells, which play a crucial role in forming mental maps of space, social networks, and abstract relationships. Until now, place cells have only been found in mammals and birds, leaving the question of how other species internally represent the external world largely unanswered. A team of researchers at the Max Planck Institute for Biological Cybernetics has now found the first compelling evidence for place cells in the brain of the tiny larval zebrafish.

When we explore an unfamiliar city, we use various cues – landmarks, a sense of how far we have walked in one direction, perhaps a river we cannot cross – to create an internal map of our environment. Deep in the brain, in a structure called the hippocampus, a set of place cells play a key role in building our internal maps of the external world. These place cells fire when we are at specific locations in space and can self-organize into an array of different mental maps.

That much is known for mammals, including humans, and even for birds. However, the existence of place cells in other species is controversial. A group of researchers at the Max Planck Institute for Biological Cybernetics in Tübingen (Germany), led by Jennifer Li and Drew Robson, has now found the first conclusive evidence for place cells in zebrafish.

Recording the entire brain during natural behaviour

The researchers recorded the brain activity of young zebrafish as they explored their environment. These fish are completely transparent when they are only a few days old, making it possible to look into their tiny brains, which contain only 100,000 cells. One can even make individual active neurons light up using fluorescent calcium indicators, since all neuronal activity is associated with fluctuations in calcium ion concentrations. An earlier key invention of Li and Robson was essential for observing brain activity during navigation: tracking microscopes that move with the freely swimming fish.

Using this experimental design, the team analysed what spatial information is encoded in each neuron in the fish's brain. They identified a population of about 1000 place cells in each fish, most of which only fire when the animal is in a specific location, while a few respond to more than one area. “Collectively, the place cell population encodes spatial information,” explains Jennifer Li. “From the firing patterns of the place cells, we were able to decode the location of each fish over time – with an error of just a few millimetres.”

Strikingly, most of the place cells were located in the telencephalon, an area of the zebrafish’s forebrain, whose precise function has been a source of debate for several decades. “The high concentration of place cells in the telencephalon potentially confirms the longstanding conjecture that this brain region is a functional analogue of the mammalian hippocampus, in miniature,” comments Drew Robson.

A flexible mechanism that integrates different inputs

However, Li and Robson needed additional evidence to conclude that the cells they had identified were indeed an analogue to mammalian place cells. The first feature to be tested was whether place cells use self-motion or external cues. In terms of human experience, a cue such as "I’ve been walking straight ahead at a brisk pace for about a minute" relies on self-motion, whereas "I can see the Eiffel Tower" is an external cue. In a series of experiments, the researchers manipulated both sources of information – taking the fish out of their environment and placing them back, removing landmarks, or rotating the behavioural chamber. They found that the fish integrate both external and self-motion cues to create their internal maps – just like we do.

Not only do the fish appear to refine their spatial representation map as they become more familiar with an unfamiliar environment, but they can also adapt to change: they use the same neuronal circuits to remember a second environment. When returned to their initial surroundings, they do not have to map it from scratch, but can partially recover the representation map they created previously. Thus, the place cell population exhibits a flexible memory system, a further hallmark of mammalian place cells.

An emerging model organism for a complex neuronal network

The authors of the study plan to use zebrafish as a new model organism to unravel the mysteries of place cells. In addition to their role in creating mental maps of space, these cells are also crucial for forming maps of social networks and abstract relationships, as well as for memory and planning. While mammalian place cells have been intensively investigated since their Nobel Prize-winning discovery more than 50 years ago, scientists still do not fully understand the neural networks that generate place cells or how they support such a wide range of mental functions.

The primary challenge has been the sheer complexity and size of mammalian place cell networks, which make it extremely difficult to study the entire network simultaneously. In contrast, the larval zebrafish brain is one of the smallest biological systems capable of generating place cells. Robson concludes: “Using this new minimal model, future studies can potentially trace all of the inputs to each place cell and create detailed models for how place cells acquire all their unique properties.”

A behavioral chamber under the tracking microscope

Credit

Jean-Claude Winkler/MPI for Biological Cybernetics

Journal

Nature

DOI

10.1038/s41586-024-07867-2

Article Title

A population code for spatial representation in the zebrafish telencephalon.

Article Publication Date

28-Aug-2024

New study reveals relationship between HIV risk factors for LGBTQ+ youth

A new study has uncovered empirical evidence that shows the importance of taking a holistic approach to addressing HIV risk factors

University of Connecticut

A new study has uncovered empirical evidence that shows what researchers have long suspected about HIV risk – that having multiple risk factors is much worse than having only one.

Pablo Kokay Valente, assistant professor of allied health sciences in the College of Agriculture, Health and Natural Resources (CAHNR) led this study in collaboration with Ryan Watson, associate professor, and Lisa Eaton, professor, both in the Department of Human Development and Family Sciences. The study was recently published in the American Journal of Public Health.

new study has uncovered empirical evidence that shows what researchers have long suspected about HIV risk – that having multiple risk factors is much worse than having only one.

Factors like poverty, depression, anxiety, substance use, alcohol use, other mental health diagnoses, and sexual victimization make people more likely to engage in risky behaviors like having sex without a condom, having multiple sexual partners, and not using PrEP (Pre-Exposure Prophylaxis).

For a long time, researchers looked at each of these factors independently. But recently there has been a push to consider their interactions.

Most papers looking at these factors have demonstrated a linear relationship. What this means is that if you have one factor at play – say, for example, depression – it is twice as bad to have two factors, like depression and alcohol use.

This new paper demonstrates an exponential relationship instead. This is something that scientists have theorized for years without much empirical evidence to support the hypothesis until now.

“Most studies haven’t been able to demonstrate this kind of synergistic relationship between the syndemic factors,” Valente says. “And that’s what we did. We’ve shown that having two factors is much worse than having one and having three factors is much, much worse than having two factors.”

The researchers used data from a survey of LGBTQ+ youth. LGBTQ+ people have historically and continue to be one group that is at a greater risk of contracting HIV.

“A major strength of this study was the use of our national sample of LGBTQ+ youth, many of whom reported intersections of multiple marginalized social positions,” Watson says. “Data collected with so many young LGBTQ+ youth give us a unique view into the complexities and nuances of the lived experiences of today’s LGBTQ+ teens.”

One unexpected finding is that the more factors an individual had, the more likely they were to be exposed to PrEP – a medication that can prevent the contraction of HIV even if you come into contact with the virus – and get information about the drug and its benefits.

“People who are exposed to these factors in combination, they have much more risk and they are probably more connected and more aware of what’s out there in terms of PrEP,” Valente says.

This understanding changes the way researchers think about interventions for people at risk of contracting HIV.

“Better understanding syndemic conditions in one of the most vulnerable youth populations — sexual and gender diverse adolescents — has been much needed, and this study contributes to the growing body of research by using a large national sample of LGBTQ+ youth,” Watson says.

If the linear model were accurate, it would not matter which HIV risk factor interventions were addressed since they all have, in theory, the same impact. But an exponential relationship demonstrates the need for interventions that tackle multiple risk factors at once to provide a substantial benefit.

“If they are linear, the implication is that whatever you address, there is some benefit to that,” Valente says. “Showing that it’s synergistic, it calls for interventions that address more than one of these things. Addressing two of these factors would have more of an impact than addressing things individually.”

For example, therapy-based interventions that address stigma surrounding HIV may also reduce substance use among participants, since that is a common coping strategy for stigmatization, and improve their overall mental health.

“They’re all deeply related,” Valente says. “So, I think dismantling several of them at a time will be very important.”

Valente is continuing to use the methods that uncovered the exponential relationship among LGBTQ+ people with a dataset of hospitals that provide care for people living with HIV.

For a long time, researchers looked at each of these factors independently. But recently there has been a push to consider their interactions.

This new paper demonstrates an exponential relationship instead. This is something that scientists have theorized for years without much empirical evidence to support the hypothesis until now.

The researchers used data from a survey of LGBTQ+ youth. LGBTQ+ people have historically and continue to be one group that is at a greater risk of contracting HIV.

“People who are exposed to these factors in combination, they have much more risk and they are probably more connected and more aware of what’s out there in terms of PrEP,” Valente says.

This understanding changes the way researchers think about interventions for people at risk of contracting HIV.

“They’re all deeply related,” Valente says. “So, I think dismantling several of them at a time will be very important.”

Valente is continuing to use the methods that uncovered the exponential relationship among LGBTQ+ people with a dataset of hospitals that provide care for people living with HIV.

Journal

American Journal of Public Health

DOI

10.2105/AJPH.2024.307753

Method of Research

Observational study

Subject of Research

People

Article Title

Psychosocial Syndemic Burden, Sexual Behaviors, and Engagement in HIV Prevention Care Among Sexual and Gender Minority Youths: United States, 2022