Category: Academic Analysis

Source: The Conversation – USA – By Gary Skuse, Professor of Bioinformatics, Rochester Institute of Technology

Decades after researches first sequenced the human genome, scientists throughout the world are still working to understand it. Despite diligent global efforts to link uncommon variations in DNA sequences with human disease, progress has been slow, in large part due to limitations in scientific understanding and in part due to limitations in computational technologies.

Artificial intelligence has the potential to help scientists decipher the millions of genetic variations present in the genomes of different people in order to identify which ones lead to disease and which ones do not. In order to fully exploit the power of AI, however, scientists need to compare the genomes of thousands or tens of thousands of people. This task not only requires intense computational effort, it is also prone to error and will take years to complete.

Quantum computing has the potential to facilitate that process. We are researchers with a long-standing interest in finding ways to use genetics in the clinic and developing new technologies to study the human genome. Combining quantum computing with AI has the potential to accelerate genomic analysis far beyond traditional methods. For time-sensitive medical conditions, faster decoding of genetic information can directly inform urgent treatment decisions and, in some cases, be lifesaving.

Conventional vs. quantum computing

In conventional computing, individual bits of information – binary digits, also called bits – can represent only two states: namely, 0 and 1.

However, the qubits used in quantum computing can have more than two distinct states. Adding qubits together increases the number of states exponentially. The power of quantum computers lies in being able to check all the possibilities at once for problems with large numbers of variables, rather than one at a time like even the fastest possible classical computer must do. This allows quantum computers to solve certain types of problems, such as factoring large numbers for today’s encryption schemes and performing combinatorial optimization to find the best route through a large number of points.

Still, quantum computing is currently in its infancy. Despite the enormous potential of this technology, computer scientists are dealing with challenges related to its scalability, error correction, hardware development and the setting of standards.

There are also significant time and cost constraints associated with ameliorating these challenges. Experts in the field estimate that it may be at least a decade before quantum computing will be truly useful outside of the laboratory.

Bigger and better data analysis

If researchers are able to overcome these challenges, combining AI and quantum computing may not only enable scientists and clinicians to better understand the human genome but also to leverage that understanding to improve patient care.

Currently, researchers are able to use AI to analyze genomic data in combination with limited amounts of other biological information, such as gene activity, epigenomics, RNA signatures and protein function. Quantum computing could allow AI to process increasingly more massive and highly detailed datasets.

This might look like integrating large-scale genetic, protein and spatial datasets with clinical, demographic and real-time physiological data. This systems-level approach enables a more comprehensive and accurate understanding of complex biological systems beyond DNA sequence alone that could be used to improve public health.

In other words, quantum computing could make it possible to sequence a patient’s genome and combine that information with other information about how their body works at the molecular level to improve the accuracy of diagnoses and determine the best course of treatment in hours instead of months.

Challenges in access and privacy

Like many burgeoning technologies, combining AI with quantum computing has inherent and inescapable challenges. In particular, there are several ethical issues related to healthcare access.

One will be the cost. New technologies are typically expensive and that will likely widen the gap between those who can afford the best healthcare and those who cannot. Anticipating these costs and finding preemptive creative solutions is necessary to allow everyone to benefit equally.

While there are likely many approaches to reducing out-of-pocket expenses for healthcare, federal legislation could mandate affordable or free genetic information-based care to those in greatest financial need. Similar to the 2008 Genetic Information Nondiscrimination Act, which prohibits discrimination based on genetics, a new law could prohibit healthcare providers from withholding genetic information-based care from those who cannot afford it.

Another challenge will be availability. These technologies will likely first be available at only the top medical centers in the country, which traditionally have the research funding and the cadre of skilled scientists and clinicians needed to develop new diagnostic methods and treatments. Consequently, the latest advances in health technology will be unavailable to people who physically or financially cannot travel to receive the best medical care.

A combination of telemedicine, centralized laboratories and shared data could potentially help make new technologies more accessible.

There are also privacy concerns intrinsic to sharing personal health data. Truly anonymizing personal information remains a challenge, and privacy concerns are likely to prevent some people from taking advantage of potentially lifesaving technologies.

One approach that may quell these fears is a model called federated blockchain governance. This approach involves sharing control of a blockchain, which is a digital ledger used to track transactions, among a small group of institutions rather than a single entity or the general public. Limiting the number of trusted curators of genetic data reduces the risk of privacy violations or security breaches and subsequently increases the chance that patient data will remain private.

Improving public health

Despite these challenges, combining advances in quantum computing and AI has the potential to significantly drive innovation and improve public health.

When scientists and clinicians are able to accurately identify the genetic basis of disease and potential risk factors, they will not only be able to develop better treatments but also help patients and healthcare providers know what symptoms to look for among those predisposed to certain conditions.

Taken together, this knowledge can improve public health, reduce the cost of healthcare and improve quality of life.

The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.

– ref. Tapping your genome with AI and quantum computing could deliver on the promise of personalized medicine – but practical and ethical hurdles remain – https://theconversation.com/tapping-your-genome-with-ai-and-quantum-computing-could-deliver-on-the-promise-of-personalized-medicine-but-practical-and-ethical-hurdles-remain-280015

Source: The Conversation – USA – By Jonathan S. Weissman, Principal Lecturer of Cybersecurity, Rochester Institute of Technology

A woman strolls into a grocery store, thinking about grabbing some apples. Before she even reaches the produce aisle, a security camera has scanned her face. Whether the system is checking for shoplifters or simply logging her arrival, her face has joined a digital ledger, a trace she can’t easily erase. Retailers, banks, airports, stadiums and office buildings are doing the same.

But what if the woman’s facial information is stolen or misused? If a cybercriminal steals her password, she can change it. If they acquire her credit card number, she can cancel the card. But she can’t reset or revoke the appearance of her cheekbones.

Facial recognition systems don’t keep actual images. They convert a face into a mathematical template that maps the positions and proportions of the face’s features. When another camera scans a person later, the system checks their live face against these templates to confirm an identity.

In my work as a cybersecurity professor at Rochester Institute of Technology, I have found that even though templates are more secure than photos – which anyone online can capture and manipulate – templates, too, can be stolen. Once that happens, these digital keys create a lifelong vulnerability. If a facial recognition database is breached, the “locks” that a template opens – accessing a bank app, getting through security at an airport, entering an office building – can’t be reset. A person’s face is permanent, and so is the threat.

The threat isn’t theoretical. Biometric data has been stolen in data breaches. In 2024, biometric data from a facial recognition system used at bars and clubs in Australia was hacked. And in 2019, biometric data from a pilot facial recognition system set up by U.S. Customs and Border Protection was breached in an attack on a subcontractor’s network. It’s not clear whether anyone’s stolen biometric data has been exploited, however.

Tracking your face

All biometric identifiers carry risks. Fingerprints and iris scans, however, are typically used in controlled situations, such as unlocking a person’s phone or allowing someone to enter a building. In these cases, a person has to deliberately look at a scanner. Cameras in public spaces, in contrast, can capture faces as people walk by, from a distance and without the people whose faces are scanned realizing it.

If a fingerprint or iris database is breached, a thief still needs to physically present that finger or eye, or a fake of it, to a scanner. However, someone could match a stolen facial template against images from surveillance cameras or photos circulating online, making it easier to identify a person of interest or track someone’s movements and activities.

There’s also a big difference, technically and ethically, between keeping a face on a phone versus handing it over to a database. On modern Apple devices and many Android systems, biometric data used to unlock the devices is stored locally in a dedicated hardware chip and is not shared with the manufacturer or cloud services for authentication. As a result, a breach of corporate or cloud systems would not expose these device-level biometric templates.

Some street and security cameras in public are passive, just watching as people pass by, with no long-term records. But others may be following people’s steps, linking faces to databases and creating a persistent digital trail. The risk rises when organizations use systems to track particular people across multiple databases. Airport systems could compare a traveler’s face against passport or airline databases. Stadiums may compare faces against local security watch lists or law enforcement lists. The company that manages Madison Square Garden has used facial recognition to bar entry to lawyers at firms that represented people who sued the company.

Some large retail chains, such as Wegmans and Target, also use facial recognition systems in their theft prevention efforts. Every new capture adds another permanent record.

Many companies do not have expertise in cybersecurity and rely on third-party vendors to manage their data. If those centralized systems are breached – or the datasets are linked across platforms, vendors or data brokers – your face can become a sort of persistent identifier, which can be used to expose or track you. In some cases, when combined with other compromised data, your captured face can lower the barrier to impersonating you.

When a person’s face meets their data

A face can function like a “primary key” – a unique and stable identifier that connects records. If one database links a facial template to an email address, and a data breach connects that email to financial or personal records, an identity thief with a stolen template could access all that information.

And combining a template with AI tools such as deepfakes or three-dimensional face models could, in some cases, allow a criminal to impersonate an individual in systems that require proof of a live face, slipping into a forged digital identity like slipping into a costume.

When criminals combine biometric templates with other leaked data, such as logins for social media profiles or home addresses, they can build “super-profiles” connected to many of a person’s activities. Because the face acts as a permanent linking key, this level of identity theft is difficult to reverse.

How to minimize the threat

People are still figuring out how to live with widespread biometric collection. The convenience of smoothly passing security checks or making purchases is appealing, but it often comes with a permanent risk to privacy and security.

To lessen the threat, organizations can follow several data privacy best practices. They can keep only information that is necessary, erase the rest quickly and encrypt every mathematical template. They can store only encrypted templates rather than raw photos. They can use safeguarding techniques, such as the latest liveness detection techniques, to help ensure that their systems are interacting with real people rather than photographs, masks or deepfakes. And they can adopt a privacy-by-design approach, which means they will keep data only as long as necessary, clearly document how it’s used and restrict who has access.

Consumers can take steps as well. In places with privacy laws, such as California, Illinois and the European Union, people can submit a data access request to see what biometric data a company holds and, in some cases, ask for its deletion. They can also ask retailers anywhere what data is collected, how long it is kept and how it’s protected.

Jonathan S. Weissman does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. Facial recognition data is a key to your identity – if stolen, you can’t just change the locks – https://theconversation.com/facial-recognition-data-is-a-key-to-your-identity-if-stolen-you-cant-just-change-the-locks-278289

Source: The Conversation – USA (2) – By Chris Vagasky, Meteorologist and Research Program Manager, University of Wisconsin-Madison

Whether you’re planning a weekend hike, deciding what to wear to work or preparing your home for severe storms, the weather forecast is essential. You might instinctively grab your smartphone and check an app for an instant weather update.

But how many times have you looked at your app, only to step outside and see the sky painting a different picture than what’s on your screen?

As a meteorologist who operates a weather station network in Wisconsin, I’ve heard many of the same cliches time and again: “The weatherman is always wrong!” “Just wait five minutes and the weather will be different!”

Before you blame the local forecasters, let’s talk about where the data in your weather app comes from, and why it might not always show what you expect. It’s why my colleagues and I are working to bring forecast data closer to home.

The nuts and bolts of weather forecasting

Earth is huge. It has a diameter of 7,926 miles (12,756 kilometers) at the equator and has 62 miles (100 kilometers) of atmosphere overhead.

If you want a perfect weather forecast, you will have to precisely measure every molecule of the atmosphere, land and water, and perfectly predict how they will interact with each other for the next minute, day or week. This is, of course, physically impossible.

Instead, scientists run computer models. These models take the observations we do have and simulate the weather on a large scale to a remarkable degree of accuracy. In fact, storm track forecasts from the National Hurricane Center were among its best ever in 2025, and forecasts using machine learning are starting to improve those forecasts even further.

These models are hungry for data. Supercomputers ingest measurements from satellites, weather balloons, Doppler radar, lightning detection networks, buoys, surface weather stations and other measurement platforms to solve the equations that provide weather predictions.

When you open your phone, your weather app isn’t doing the meteorology – it’s just showing the output of the model’s calculations. Even though they generally aren’t tailored by a local meteorologist, these short-term forecasts are usually pretty good. But they could be better.

All weather is local

You’ve probably seen it before: It’s raining on one side of the street and not on the other. You flip on the news to see the nearest airport received an inch of rain, but your garden is dry.

There are more than 2,500 airports in the United States with weather stations, which is where much of the weather data shared on TV and online is collected. But for many people, the closest airport is more than 20 miles (32 kilometers) away. This is especially true in rural areas.

Because of the chaotic nature of weather, the only way to truly know what’s happening in your yard is to measure the weather in your yard. But not everyone is interested in installing a rain gauge or personal weather station.

Filling the gaps

To bridge this gap, many states and universities have established local weather station networks called mesonets – short for mesoscale networks, meaning intermediate scale. These weather stations are installed in locations to ensure everyone in the state is within 20 miles of the nearest station.

Nationally, there are nearly 3,000 mesonet stations installed in 38 states, with more networks planned.

Like the weather stations at airports, mesonets measure things like air temperature and relative humidity, air pressure, rainfall or melted snow, and wind speed and direction – often every five minutes.

Many mesonets collect additional data such as soil moisture levels to help farmers. Some even have camera images updated every five minutes to show current weather conditions. Mesonet data is then shared through websites or direct data transmission so that the public, weather forecasters and researchers can easily access it.

I lead the team at Wisconet, a new mesonet that just finished installing 78 weather stations across Wisconsin. Our stations are installed on 10-foot-tall (3-meter) tripods in open areas near orchards and cranberry marshes, farms and airfields, schools and other educational centers, and on city, state and federally owned lands.

These added weather stations are already proving useful. On Aug. 18, 2025, slow-moving thunderstorms moved over a Wisconet station, with more than 3 inches of rain falling in just a couple of hours. The National Weather Service was able to issue a flash flood warning for the area because of the data provided by that station.

In addition to providing a near-real-time snapshot of the local weather, mesonets help farmers decide when to run irrigation systems, spray pesticides or plant crops. They also help provide better weather warnings, particularly when tornadoes and other storms intensify over small areas that farther-away weather stations would miss.

A nationwide network of networks

Because of the immense value of high-frequency weather and soil measurements, the National Oceanic and Atmospheric Administration leads a National Mesonet Program. The program collects weather data from public, private and academic sources, validates the quality of the data, and ensures it flows to users, including the National Weather Service. National Weather Service forecasters use that data to make more timely and accurate severe weather warnings.

Congress is considering expanding that program, with legislation proposed in the House and the Senate. The bills aim to authorize $50 million to $70 million annually to the National Mesonet Program between 2026 and 2030 to improve and expand mesonets across the country. An expansion would mean more weather stations and new capabilities, like real-time snowfall, fire weather and air quality measurements, closer to the people who rely on them.

So the next time you check your smartphone and grumble because the app doesn’t match the weather in your backyard, remember that all weather is local. If you don’t have a nearby mesonet station, the nearest measurements may be many miles away.

This work is supported by the Institute for Rural Partnerships, project award no. 2023-70500-38915, from the U.S. Department of Agriculture’s National Institute of Food and Agriculture. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author and should not be construed to represent any official USDA or U.S. Government determination or policy.

Wisconet receives monthly payments for their data from the National Mesonet Program.

– ref. Your local storm forecast is likely based on weather miles away – we’re trying to bring it closer to home – https://theconversation.com/your-local-storm-forecast-is-likely-based-on-weather-miles-away-were-trying-to-bring-it-closer-to-home-280985

Source: The Conversation – USA (2) – By Brittany Adams, Assistant Professor of Literacy Education, University of Alabama

Despite decades of legislation meant to boost children’s reading levels, literacy scores have remained relatively stagnant across the U.S. over the past 30 years.

Educators, policymakers and parents were genuinely excited in the late 2010s, when three Southern states – Alabama, Mississippi and Louisiana – appeared to buck the literacy trend. All three of these states, which have long lagged in literacy scores, made notable gains in fourth grade reading scores from 2013 to 2024, as measured by the National Assessment of Educational Progress, or NAEP.

We are researchers in literacy and learning. Two of us are at the University of Alabama and Mercer University, where we educate elementary teachers. The other two work at Temple University, where we research early language and the science of learning. We all study how children develop as readers and how teaching styles and policies shape that development.

Some observers and scholars have called Alabama, Mississippi and Louisiana’s reading gains the “Southern surge” and say this progress shows that recent literacy reforms are working.

A straightforward explanation has taken hold: As more schools spent additional time on phonics and implemented other “science of reading” reforms, students became stronger readers.

This narrative accurately captures some of the available evidence. But it also simplifies a complex set of patterns in literacy data, and it limits the discussion that policymakers should have.

Reading scores under pressure

Since the early 2000s, new federal and state policies have placed pressure on schools to improve students’ reading outcomes. The 2001 No Child Left Behind Act required all states to track and report literacy testing results. This law, which the Obama administration replaced in 2015 with the Every Student Succeeds Act, mandated annual testing in reading and math for students in third through eighth grades.

Many schools narrowed their curriculum to try to boost their students’ reading scores. They cut time for science, social studies, art and recess to focus on reading and math. Students entering school in the early 2000s – the first classes fully exposed to No Child Left Behind’s requirements – spent more time on reading instruction than any previous generation.

But sustained reading gains still didn’t follow.

The NAEP is often called the nation’s report card. It is the only federally administered test that allows meaningful comparisons in reading levels across states.

The NAEP found that fourth grade reading scores nationwide increased modestly beginning in 2005. They peaked around 2017 and have declined since.

But there’s a complication in how those scores are interpreted. NAEP’s mid-level score, called “proficient,” does not mean a student is reading at grade level – it reflects a high standard that most students do not reach. In the case of fourth grade readers, it means they can recognize a text’s structure and organization, explain how characters influence others and make other complex observations. Students can also receive a lower “basic” score, or a higher “advanced” one.

Alabama’s example illustrates the gap that can emerge between NAEP test results and a state’s assessments.

The state’s 2025 assessments show that 81% to 88% of second and third graders were reading “on grade level.” But the 2024 NAEP shows only about 30% of Alabama fourth graders – the youngest grade the NAEP measures for literacy – were “proficient” at reading.

Both numbers can be accurate. They reflect different definitions and measurement systems.

Understanding reading gains in the South

Despite differences in measuring reading, a small number of states have shown clear improvement over the past decade, according to the NAEP.

Mississippi has shown the strongest gains. In 2013, it was 49th out of all 50 states when it came to ranking fourth grade reading scores. In 2024, Mississippi climbed to ninth in fourth grade reading.

Mississippi’s progress predates recent national attention to the science of reading – meaning, the body of research on reading – suggesting its gains cannot be attributed solely to the current wave of related reforms.

In 2013, Mississippi passed the Literacy-Based Promotion Act, which combined early reading screening, teacher training, literacy coaching and additional support. Research shows that the policy could account for roughly five points of reading gains, on average. These gains reflect long-term, system-wide efforts rather than a rapid shift tied to a single policy change.

At the middle school level, however, the pattern in Mississippi looks different.

Improvements in fourth grade reading have not translated into similar gains in eighth grade reading. Early improvements in children’s ability to decode words do not necessarily lead to success with more complex texts that require additional vocabulary and background knowledge.

This gap does not negate Mississippi’s progress, but it does raise questions about what the next decade of work needs to look like.

Louisiana’s reading score trajectory is more modest. Recent NAEP scores for fourth grade students in Louisiana are similar to those from the mid-2010s – a rebound to a prior level.

While Louisiana ranked 50th in fourth grade reading in 2019, it rose to 38th in 2024.

A 32-point gap between Black and white students’ average fourth grade reading scores persists in 2024 data, nearly unchanged from the late 1990s. In this case, some reading progress happened. Yet the underlying inequities between students did not shift.

Alabama’s results illustrate a third pattern: relative stability in fourth grade reading scores during a period of national decline. The state ranked 35th in fourth grade NAEP reading in 2013 and remains in a similar position in 2024, showing little change.
The state’s average NAEP score for fourth grade students shifted by a single point between 2019 and 2024 – not a surge, but a state holding its ground while others fell.

Meanwhile, chronic absenteeism has fallen in Alabama since 2019. As research links attendance to academic achievement, it makes it difficult to attribute the state’s small shift in reading scores to any single factor.

Across all three states, substantial gaps between Black and white students’ reading scores persist on NAEP scoring.

The same pattern extends nationally to Hispanic students, poor students and other groups. This shows that fourth grade students’ reading gains have not been accompanied by comparable reductions in social, racial and ethnic inequities.

A more complicated story

Still, parts of the Southern surge in reading is genuinely encouraging. It is also the latest chapter in a long story.

Mississippi’s gains, for example, came alongside coaching, professional development and early intervention.

Louisiana’s reading recovery unfolded alongside a 34% increase in education funding over the past decade.

Test score changes reflect a combination of policy decisions, classroom practices and broader conditions, often unfolding over many years. Reading is hard to teach, hard to sustain and not connected to any one policy shift.

The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.

– ref. Reading gains in Alabama, Mississippi and Louisiana are often touted, but don’t show full picture of literacy – https://theconversation.com/reading-gains-in-alabama-mississippi-and-louisiana-are-often-touted-but-dont-show-full-picture-of-literacy-280889

Source: The Conversation – USA (3) – By Olamide Asifat, Physician and Doctoral Researcher in Public Health, Georgia Southern University

Chronic obstructive pulmonary disease, or COPD, caused 141,733 deaths in the United States in 2023 – the latest data that has been reported. That number reflects not just the effects of smoking, but a broader set of medical and social factors that shape who survives.

As of early 2026, COPD remains the fifth-leading cause of death nationwide and carries a substantial economic burden, with annual medical costs estimated at US$24 billion among adults ages 45 and older. COPD is a progressive condition that limits airflow, making it increasingly difficult to breathe and carry out everyday activities.

Nearly 16 million U.S. adults live with COPD, and many more remain undiagnosed.

COPD also encompasses chronic bronchitis, which inflames the airways, and emphysema, a condition that damages the air sacs in the lungs. Both conditions limit the flow of air in and out of the lungs.

I am a physician and doctoral researcher in public health who studies chronic disease outcomes using nationally representative U.S. data. In my research examining long-term mortality among adults living with COPD, one pattern stands out clearly: My colleagues and I found that both current and former smokers had a higher risk of death compared with those who never smoked, highlighting that smoking increases mortality risk – but it does not act alone.

How smoking and COPD are intertwined

Smoking has been recognized for over five decades as the primary cause of COPD. It is a major factor in how the disease develops and progresses, although other factors such as secondhand smoke, air pollution and occupational exposures also play a role. Even after accounting for age and other health conditions, people with COPD who have smoked face a higher risk of death than those who have never smoked.

Quitting smoking, while essential, does not fully erase the damage caused by smoking. This is because long-term exposure to tobacco smoke leads to persistent inflammation and structural damage in the lungs, changes that are not fully reversible. They continue to affect airflow and respiratory function even after a person stops smoking, although quitting significantly slows further decline.

COPD is a long-term condition that continues to affect the lungs and the pulmonary blood vessels over time, contributing to both breathing problems and other chronic conditions.

In some cases, higher risks among former smokers with COPD may reflect the lasting effects of smoking or underlying illness that led them to quit.

COPD affects more than the lungs

COPD is often described as a lung disease, but its effects extend far beyond breathing.

People living with COPD also face a higher risk of other health problems, including lung infections such as flu or pneumonia, lung cancer, heart disease, weak muscles and depression or anxiety, all of which can increase the risk of death.

One of the most noticeable ways COPD affects daily life is through persistent breathlessness, which can make even simple tasks such as walking, cooking or getting dressed more difficult. As activity declines, overall health can worsen, creating a cycle that is hard to break.

COPD is also frequently diagnosed late and progresses gradually, limiting opportunities for early treatment.

Social connections can shape survival

A growing body of research shows that social factors play a meaningful role in health outcomes with chronic diseases including COPD. Social isolation has been linked to a higher risk of premature death, with effects comparable to well-known risk factors such as smoking and obesity. This is a major problem because nearly 1 in 6 adults with COPD experience social isolation, and 1 in 5 experience loneliness.

Among people living with COPD who were single or never married, the increase in overall risk of death associated with smoking was substantially higher. In this socially isolated group, current smokers faced roughly a 50% higher risk of death and former smokers faced nearly four times the risk compared with those who never smoked, highlighting how social context can shape survival rates.

Other research has similarly found that social isolation is associated with a higher risk of death among people with COPD, reinforcing the importance of social support. Managing a demanding chronic illness alone can be difficult; without support to monitor symptoms or assist with care, the burden of disease may be grave.

One reason is that social connections influence how people manage chronic illnesses. People who are socially isolated are more likely to engage in unhealthy behaviors such as smoking, poor diet and physical inactivity, and may be less likely to follow treatment plans.

Support from family members, caregivers or community networks can improve peoples’ likelihood of following treatments, reduce their stress and make it easier to quit smoking. For people living with COPD, a condition that requires daily management, these differences can significantly affect their quality of life and how long they live.

What can help reduce COPD deaths?

Reducing deaths from COPD begins with prevention and early intervention. Avoiding or quitting smoking remains the most effective way to lower risk. Reducing exposure to tobacco smoke, air pollution and occupational hazards such as dust from mining and chemical fumes can also help prevent long-term lung damage.

For people already living with COPD, consistent access to care can improve outcomes. Treatments such as inhalers that help open the airways, pulmonary rehabilitation and oxygen therapy, along with vaccinations against respiratory infections, can help manage symptoms and reduce complications.

Improving survival in COPD depends on more than treatment alone – it also requires addressing social factors such as isolation, access to support and living conditions.

One practical step is making screening for social isolation part of routine care.

Olamide Asifat does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. More than 140,000 Americans die from COPD each year – here’s why survival depends on more than avoiding smoking – https://theconversation.com/more-than-140-000-americans-die-from-copd-each-year-heres-why-survival-depends-on-more-than-avoiding-smoking-277475

Source: The Conversation – USA (3) – By Liao Yue, Assistant Professor of Kinesiology, University of Texas at Arlington

Keeping tabs on blood sugar throughout the day used to be the exclusive domain of people with diabetes. But in 2026, anyone can buy a user-friendly wearable device that provides minute-by-minute readouts on how their glucose levels respond to food and movement.

These glucose numbers are increasingly being tracked by people who are healthy but want to lose weight or optimize their wellness.

I am a behavioral scientist who has spent the past decade studying how real-time data captured through wearable sensors and mobile technologies can help promote a healthier lifestyle. I’ve found that for people who don’t have diabetes, using such a device for a few weeks can bring insight into how their body reacts to their eating patterns and daily habits.

But researchers still don’t know how these fluctuations affect health for people who don’t have diabetes. In the absence of meaningful metrics for interpreting these numbers, monitoring a constant stream of data doesn’t directly help people make health-related decisions and can lead to confusion and needless anxiety.

What are glucose levels – and why track them?

Glucose is a type of sugar that circulates in the bloodstream after being absorbed from food. It is the body’s primary source of energy.

For people without diabetes, glucose levels generally stay in the range of 70-120 milligrams per deciliter (mg/dL) of blood throughout the day. After eating or drinking, levels could exceed 140 mg/dL but should come down to the normal range within a couple of hours. That’s because the pancreas responds to a glucose spike by releasing a hormone called insulin, which brings the glucose number down.

Muscles burn glucose for fuel, so physical activity also helps normalize glucose levels.

Glucose levels generally run high with diabetes. People with Type 1 diabetes, whose bodies don’t make enough insulin, rely on glucose numbers to tell them when to take a dose of insulin. People with Type 2 diabetes use the numbers to monitor the effect of their medications and lifestyle changes and to get a fuller picture of their glucose control.

From test strips to AI-enabled sensors

Devices that track glucose numbers have been around since the early 1970s. Early versions consisted of test strips that detected glucose levels in urine. Finger prick tests, or glucometers, which were developed in the 1980s, are still used by some people today and measure them more directly by applying a tiny blood drop to a test strip.

To make the technology more convenient, companies in the early 2000s developed continuous monitoring devices that consist of tiny sensors inserted just under the skin that detect glucose in fluid that surrounds cells. Initially, these devices could give readings every 15 minutes for several days at a time, but recent versions sample more frequently.

Today, the technology has evolved even further. The most advanced glucose monitors under development come in the form of watches or rings with noninvasive sensors that use light-based techniques to detect glucose in body fluids. Many also rely on machine learning to provide more accurate readings by detecting each person’s unique physiological patterns over time.

For decades, continuous glucose monitors were available only with a doctor’s prescription. But in March 2024, the Food and Drug Administration approved the first over-the-counter continuous glucose monitor in the U.S., making them widely accessible.

Glucose monitoring for diabetes

There’s no doubt that continuous glucose monitors are a game-changer. People living with diabetes rely on these devices to track what percentage of the day their blood glucose stays within healthy limits – a measure called “time in range.” Patients make decisions about managing their condition – for example, when to take insulin – on guidelines developed by researchers and physicians based on that measure.

According to a 2026 report from the Centers for Disease Control and Prevention, almost 11 million adults who have diabetes – more than 1 in 4 adults with the condition – are undiagnosed. Type 2 diabetes can develop slowly and silently, often with no noticeable symptoms for years except glucose levels that remain elevated for a majority of the day, including when people are sleeping. Tracking glucose levels might offer clues that glucose is elevated.

Tracking glucose levels may also benefit the 115.2 million Americans – 43.5% of all U.S. adults – who have a condition called prediabetes. Prediabetes is when a person’s metabolic system shows early warning signs of diabetes but they don’t have the full-blown disease.

Prediabetes generally has no noticeable symptoms, but it is reversible – meaning, it’s possible to shift your glucose levels back into a healthy range. Tracking your glucose number can reveal how diet and exercise affect it. Observing how a soda spikes your glucose levels, for example, might give you pause before you drink one next time.

Daily glucose rhythms

Increasingly, though, people who use continuous glucose monitor aren’t diabetic – or even prediabetic. Instead, they want to understand how their bodies react to activities in their daily lives.

Diet, exercise and other lifestyle behaviors have long-term effects on health. Weight loss, for example, happens slowly. Changes in blood glucose, on the other hand, are more immediate. Tracking glucose levels thus offers real-time feedback on how your body responds to the food you just ate or the workout you just finished.

In studies I’ve conducted with colleagues, many people have found this information powerful. They were surprised to learn that eating certain foods – sugary soda, or even something healthy like a banana – causes their glucose levels to spike.

One study participant told us that seeing their real-time glucose numbers led them to make more intentional dietary choices, such as cutting back on snacking. “I’m more aware and I’m making the changes,” they explained. Another participant also noted behavior changes prompted by continuous glucose monitoring, such as trying to avoid eating so late in the evening and consuming only half a fast-food meal.

That initial wow factor – and its capacity to motivate people to make healthy lifestyle changes – may be valuable. But it’s not clear how long these changes last, or how exactly people should respond to fluctuations in their glucose number to decrease their diabetes risk or to address other health issues.

Unlike the time in range guidelines for diabetes, there is no clear framework for what daily glucose patterns are abnormal in people who don’t have diabetes – or what patterns may indicate future disease risks.

Mapping the numbers

Researchers like me and my team are exploring exactly these questions.

Building a dynamic picture of how glucose levels fluctuate throughout the day in people without diabetes may point to early indicators for various chronic diseases. For example, my colleague and I recently developed a mathematical model to examine how monitoring glucose levels during sleep might help predict the risk of metabolic diseases – such as Type 2 diabetes, heart disease or fatty liver disease – in people with and without diabetes.

Additionally, continuous glucose data may reveal how people’s bodies might react differently to the same food, workout or other activity. Understanding how each person’s biology responds to the choices they make throughout the day could eventually lead to a more personalized approach to lifestyle changes that can help people maintain their health.

Liao Yue receives funding from the American Institute for Cancer Research, the American Heart Association, the Cancer Prevention & Research Institute of Texas and the Texas Higher Education Coordinating Board.

– ref. Wearable glucose monitors offer real-time data, but for healthy people no guidelines exist to interpret the numbers – https://theconversation.com/wearable-glucose-monitors-offer-real-time-data-but-for-healthy-people-no-guidelines-exist-to-interpret-the-numbers-276012