GLP-1 RAs Improve Sleep Apnoea Outcomes in People With Obesity
Key Takeaways:
- GLP-1 receptor agonists (GLP-1 RAs) reduced the apnoea-hypopnoea index (AHI) by 5.7 to 21.9 events per hour across six meta-analyses, with tirzepatide achieving disease remission in 42% to 50% of adults with moderate to severe obstructive sleep apnoea (OSA) and obesity in the SURMOUNT-OSA trials.
- The benefits appear to be driven primarily by weight loss, including reductions in tongue fat and parapharyngeal adipose tissue, although emerging preclinical evidence points to possible weight-independent mechanisms.
- Continuous positive airway pressure (CPAP) still delivers greater AHI reductions, and the review authors position GLP-1 RAs as a complementary therapy rather than a replacement, best suited to people with a BMI above 30 who cannot tolerate CPAP and have obesity-related comorbidities.
A new treatment avenue for obesity-related sleep apnoea
GLP-1 RAs significantly improve outcomes for people living with both OSA and obesity, according to the findings of a review published in JAMA Otolaryngology–Head & Neck Surgery.
Obesity is common among people with OSA, yet until recently there were no medicines specifically aimed at treating excess body weight in this population. That changed towards the end of 2024, when the US Food and Drug Administration (FDA) approved tirzepatide for the treatment of moderate to severe OSA in adults with obesity. The approval was based on positive results from the phase 3 SURMOUNT-OSA trials.
In the recent review, researchers examined the effects of several medicines acting on the GLP-1 receptor in OSA, including tirzepatide, semaglutide, liraglutide, exenatide and retatrutide.
What the evidence shows
Data drawn from six previous meta-analyses showed that GLP-1 RA use reduced AHI by between 5.7 and 21.9 events per hour.
The SURMOUNT-OSA trials, which enrolled adults living with moderate to severe OSA and obesity, found that tirzepatide reduced AHI by approximately 20 to 24 events per hour compared with placebo. Participants also achieved an average weight loss of 18% to 20%.
Disease remission was achieved in 42% to 50% of these participants. In the trials, remission was defined as an AHI of fewer than 5 events per hour, or fewer than 15 events per hour in the absence of symptoms.
Weight loss as the main driver
According to the study authors, the benefits of GLP-1 RAs were primarily driven by weight loss. Studies have shown that these medicines reduce both tongue fat and parapharyngeal adipose tissue, each of which contributes to upper airway collapse.
The link between body weight and OSA severity is well established. Findings from the Wisconsin Sleep Cohort Study showed that a 10% increase in body weight was associated with a 32% increase in AHI, while the same degree of weight loss was associated with a 26% reduction in AHI.
Possible weight-independent effects
The authors also highlighted early research suggesting that GLP-1 RAs may influence OSA through mechanisms beyond weight loss.
“Emerging preclinical evidence has suggested potential weight-independent effects through carotid body [GLP-1] receptor modulation of chemosensitivity (affecting loop gain), leptin pathway interactions that are associated with upper airway neuromuscular control, and NLRP3 inflammasome suppression,” the study authors noted.
For healthcare professionals seeking to deepen their understanding of how these therapies work and where they fit within wider obesity care, The College of Contemporary Health’s GLP-1RA Therapy: The Complete Programme course explores this rapidly evolving class of medicines.
How GLP-1 RAs compare with CPAP
While medicines acting on the GLP-1 receptor are effective in treating OSA, their effects are more limited than those of CPAP, the established standard treatment. According to a previous umbrella review comparing OSA interventions, CPAP delivers greater AHI reductions, of approximately 31 events per hour compared with 22 events per hour for tirzepatide.
The review also identified further limitations of GLP-1 RAs, including:
- uncertainty about their impact on cardiovascular outcomes
- weight regain when treatment is stopped
- data suggesting that tirzepatide may not be cost-effective for treating OSA under commonly used thresholds
Positioning GLP-1 RAs in clinical practice
Rather than replacing existing treatments, the authors see GLP-1 RAs as one part of a broader management strategy.
“This review suggests that GLP-1 RAs offer otolaryngologists a disease-modifying adjunct for obesity-related OSA that is best positioned as complementary therapy alongside CPAP, preoperative optimization before upper airway surgery, or potentially to expand hypoglossal nerve stimulator candidacy,” the review authors said.
Who may benefit most
The authors advised that GLP-1 RAs are appropriate options for people with a body mass index (BMI) above 30 who have inadequate tolerance to CPAP and who are living with obesity-related comorbidities.
However, they noted that these medicines are not suitable for people without obesity, or for people whose OSA is primarily caused by anatomical obstruction or who have central sleep apnoea.
Disclosure: One author declared affiliations with biotech, pharmaceutical and/or device companies. Please see the original reference for a full list of the authors’ disclosures.
CCH insight
As GLP-1 RAs extend into new indications such as obstructive sleep apnoea, healthcare professionals need a clear understanding of the evidence, appropriate patient selection and the limitations of these therapies. GLP-1RA Therapy: The Complete Programme from The College of Contemporary Health helps clinicians stay up to date with this fast-moving area of practice.
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Source: JAMA Otolaryngology–Head & Neck Surgery
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Poor Sleep Quality in Late Pregnancy Linked to Higher Obesity Risk in Children
Key Takeaways:
- Mothers with poor sleep quality in late pregnancy had babies with lower weight in the first six months of life but higher weight at ages 1–2 years, with the effect strongest in male infants and babies born at term.
- In a study of 645 mother–child pairs, children whose mothers reported the worst sleep quality weighed 346.7 grams (12 ounces) more at age 1, with the greatest difference of 751.5 grams (1.7 pounds) observed at 17 months.
- Researchers suggest that incorporating sleep quality assessments into routine antenatal care could support early identification of at-risk pregnancies, and that addressing poor sleep could benefit the health of both mother and child.
Sleep in pregnancy and early childhood growth
New research has found that mothers who experienced poor sleep quality in late pregnancy had babies who weighed less during the first six months of life but more at ages 1–2 years. This effect was most pronounced in male infants and in babies born at term.
The findings, published in the American Journal of Preventive Medicine, suggest that incorporating sleep quality assessments into routine antenatal care could help healthcare professionals identify at-risk pregnancies earlier. The researchers also suggest that addressing poor sleep quality during pregnancy could benefit the health of both mother and child.
Two modifiable public health concerns
Sleep health in pregnancy and childhood obesity are both major, modifiable public health concerns. Global obesity rates among children and adolescents more than doubled between 1990 and 2022, and obesity now affects more than 390 million children aged 5–19.
Previous studies have found that poor sleep health is associated with a range of health conditions, including diabetes, obesity and cardiovascular disease. Both human and animal studies have also suggested that sleep quality during pregnancy may play a role in the intergenerational transmission of obesity risk from mother to child.
Rapid weight gain during infancy is a recognised risk factor for obesity in later childhood. Understanding how sleep health in pregnancy affects growth trajectories in early childhood could therefore help to mitigate its impact on children’s metabolic health.
Addressing gaps in the evidence
Much of the existing research in this area has been cross-sectional or has focused on children older than 2. In addition, the association between sleep health in pregnancy and childhood obesity has not been studied extensively in Hispanic populations in the US, who experience higher rates of overweight and obesity than other racial or ethnic groups.
How the study was conducted
The study examined 645 mother–child pairs from the Maternal and Developmental Risks from Environmental and Social Stressors (MADRES) prospective pregnancy cohort in Los Angeles. Researchers assessed late-pregnancy sleep quality using the Jenkins Sleep Scale questionnaire.
Children’s height and weight were either measured during follow-up visits at the University of Southern California clinic or taken from medical records.
Sleep quality and infant weight
Most mothers in the study reported mild to moderate sleep disturbance, while 26% reported poor sleep quality.
Children whose mothers reported the worst sleep quality had lower weights from birth to 6 months, followed by higher weights thereafter. At age 1, the difference in weight was 346.7 grams (12 ounces). The greatest difference was observed at 17 months, at 751.5 grams (1.7 pounds).
The study highlights the importance of good sleep health during pregnancy. According to the researchers, the associations observed appear to be driven primarily by poor sleep quality in late pregnancy and are not explained by other traditionally identified prenatal and postnatal factors, such as feeding practices in childhood.
For healthcare professionals working with families, findings such as these reinforce the value of considering the earliest influences on a child’s weight. The College of Contemporary Health’s Childhood Obesity Essentials CPD course offers a useful grounding for clinicians looking to strengthen their understanding of childhood obesity and the factors that shape it.
Potential biological pathways
Senior author Carrie V. Breton, MPH, PhD, Professor at the Bursky School of Public Health, Washington University in St. Louis, and Adjunct Professor in the Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, said:
“Our research supports the notion that exposures during critical developmental windows of pregnancy can program offspring health.
“Several biological mechanisms may link late-pregnancy sleep health to children’s weight trajectories. For instance, poor sleep may affect maternal or child metabolic health programming, or both, which in turn could affect neonatal fat mass distribution and lead to abnormal lipid profiles or higher inflammation. Alternatively, stress pathways associated with higher childhood obesity risk may also play a role.”
Implications for antenatal care
Lead author Xiaoran Yang, MPH, a PhD graduate from the Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, added:
“Poor sleep health in pregnancy is common and often overlooked, and our findings suggest that monitoring it in routine prenatal care could be a simple and powerful step toward healthier growth for the next generation.”
CCH insight
Early life offers a crucial window for shaping a child’s long-term weight and metabolic health. Healthcare professionals who support families during pregnancy and early childhood are well placed to recognise risk factors early and help families take preventive steps. Build your confidence in this area with our Childhood Obesity Essentials CPD course.
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Source: American Journal of Preventive Medicine
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Cough Data Captured During Sleep Could Flag Flu and COVID-19 Surges a Week Early
Key Takeaways:
- The UK Health Security Agency (UKHSA) and AI sleep technology company Sleep Cycle have published research showing that cough data collected passively by a smartphone sleep app closely reflects levels of respiratory illness reported through NHS 111 in England.
- Rises in night-time coughing were often observed around a week before increases in influenza and COVID-19 activity, offering an early signal that is not shaped by healthcare-seeking behaviour, laboratory turnaround times or reporting delays.
- The cough signal was found to be robust and regionally consistent, supporting a role for privacy-preserved consumer digital health data alongside, rather than instead of, established public health surveillance systems.
A new kind of respiratory signal
A study published by the UK Health Security Agency (UKHSA) and the AI sleep technology company Sleep Cycle has evaluated whether cough data gathered by a sleep app can give early indications of rising respiratory illness in England. The full results are available on medRxiv.
The researchers concluded that passively collected data of this kind can provide a robust and regionally consistent indicator of community respiratory illness, while also providing early signals for influenza and COVID-19 activity. Taken together, the authors argue, the findings support a wider role for digital health data in public health surveillance.
Crucially, the cough data was not gathered by asking anyone to report symptoms. It was generated automatically overnight, from the sound analysis that the app already performs as part of its everyday function.
Why existing surveillance has blind spots
Current respiratory surveillance in England depends heavily on people seeking care through the NHS. That dependence introduces a series of variables that have nothing to do with how much illness is actually circulating in a community.
Levels of public awareness can change how quickly people make contact with a service. The availability of that service matters too, as do demographic and socioeconomic differences between the populations being observed. Two areas with similar levels of illness may therefore generate very different surveillance figures.
Timing is a further constraint. Established systems are also affected by reporting and laboratory processing times, which means the picture available to public health teams is always, to some degree, a picture of the recent past rather than the present moment.
How the sleep app signal is generated
Sleep Cycle is a smartphone app designed to help people understand and improve their sleep through AI-powered sound analysis. The app listens during the night and interprets the sounds it detects, including coughing.
Unlike traditional surveillance, Sleep Cycle’s cough signal is generated automatically during normal sleep using privacy-preserved, passively collected data, and it is updated daily. That combination produces a near real-time view of respiratory illness activity, refreshed without anyone needing to complete a form, book an appointment or wait for a test result.
Because the data is produced as a by-product of ordinary app use, it sidesteps several of the behavioural and administrative filters that sit between illness in a community and the figures that reach public health teams.
A week’s head start on flu and COVID-19
The researchers found that cough data collected through the app closely reflected levels of respiratory illness reported through NHS 111. The two measures moved together, which is the first thing any candidate surveillance signal has to demonstrate.
More significantly, the two measures did not move together at the same moment. Increases in coughing were often observed around one week before increases in influenza and COVID-19 activity. The authors highlight this as evidence that passive digital health data can provide earlier situational awareness alongside established surveillance systems.
A week is a meaningful interval in respiratory season planning. It is time that can be used to prepare staffing, communicate with the public, and anticipate pressure on services rather than respond to it.
The findings suggest that, used alongside established surveillance systems, passive sleep monitoring could provide a fuller picture of respiratory surveillance data, helping public health experts better understand seasonal trends sooner.
What the researchers said
Professor Steven Riley, Chief Data Officer at UKHSA, said:
“These findings suggest that combining established surveillance approaches with novel digital health signals could contribute to an earlier, richer and more resilient understanding of population respiratory health.
No single surveillance system provides a complete picture of respiratory disease activity, but this shows that passive nocturnal cough monitoring can complement other surveillance systems to provide a timely population-level signal of upcoming disease trends, without being affected by healthcare-seeking behaviour, laboratory turnaround times, backfilling and reporting delays.”
Dr Emil Carlsson, Research Scientist and Co-lead Author, said:
“This study demonstrates that passively collected nightly cough data captures meaningful changes in community respiratory illness.
Equally important, it shows that consumer-generated health data can be transformed into epidemiologically meaningful surveillance signals using rigorous scientific methods while maintaining strong privacy protections.”
Dr Mikael Kågebäck, Chief Technology Officer and Acting Chief Executive Officer at Sleep Cycle, said:
“This study validates a completely new category of health data.
For the first time, we’ve demonstrated that passively generated smartphone data can produce robust population-level health intelligence at national scale, while also providing earlier signals for influenza and COVID-19 activity.
That creates opportunities to strengthen public health surveillance and enable researchers, healthcare organisations and industry partners to build new services for situational awareness and operational decision support.”
Complement, not replacement
Both organisations frame the work in the same way. The cough signal is not presented as a substitute for laboratory confirmation, clinical reporting or NHS 111 data. It is presented as an additional layer that behaves differently from the others, and whose value lies precisely in that difference.
As Professor Riley notes above, no single surveillance system provides a complete picture. A signal that is unaffected by whether people choose to seek care, and unaffected by how long a laboratory takes to process a sample, fails in different ways from the systems already in place. Combining sources with different weaknesses is a well-established way of building a more resilient overall view.
What it means for clinicians and health organisations
For practitioners, the study is a practical illustration of a broader shift. Data generated by consumer devices is increasingly being assessed against the standards applied to conventional health data, and in this case it held up well enough to warrant serious attention from a national public health body.
That shift raises questions clinicians and managers are likely to encounter more often: how such signals are validated, what privacy protections are in place, how to judge the reliability of a consumer-generated dataset, and where these tools genuinely add value to decision-making. Professionals looking to build confidence in this area may find structured CPD useful, and The College of Contemporary Health’s short course AI Essentials for Primary Care is designed to help healthcare professionals understand how AI-driven tools are being applied in practice and how to appraise them critically.
A note on the status of this research
This was reported in medRxiv, The Preprint Server for Health Sciences. The following caution applies, as it does to all preprints:
Preprints are preliminary reports of work that have not been certified by peer review. They should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
The findings described here should therefore be read as promising and carefully conducted early-stage research rather than as settled evidence. Peer review may yet refine the conclusions, the size of the reported lead time, or the conditions under which the signal performs best.
CCH insight
Digital health signals are moving quickly from novelty to everyday practice, and healthcare professionals are increasingly expected to interpret them with the same rigour they apply to any other source of clinical or population data.
AI Essentials for Primary Care is a CPD short course from The College of Contemporary Health, developed for healthcare professionals who want a clear, practical grounding in how artificial intelligence is being used across healthcare settings and how to evaluate it responsibly.
Explore AI Essentials for Primary Care →
Source: GOV.UK
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How Losing Around 80 Minutes of Sleep a Night Could Drive Weight Gain and Inactivity
Key Takeaways:
- Adults who cut their nightly sleep by about 80 minutes over six weeks gained roughly one pound (around 0.45 kg) on average and became more sedentary, Columbia University researchers found.
- Modest over six weeks, but the team estimates that sustaining this mild sleep loss for a year could cause clinically meaningful weight gain – a pattern affecting around 30% of adults.
- Related work in the same participants linked mild sleep restriction to greater insulin resistance and heart inflammation, pointing to a wider risk of type 2 diabetes and heart disease.
Why modest sleep loss deserves attention
Trimming a little sleep each night may carry more weight for your health than you might realise. Researchers at Columbia University Vagelos College of Physicians and Surgeons found that adults who shortened their nightly sleep by about 80 minutes over a six-week period gained an average of one pound and spent more of their waking hours being inactive.
The findings add to a growing body of evidence suggesting that consistently getting enough sleep may play an important role in preventing weight gain and in lowering the risk of obesity-related disease. Rather than pointing solely to diet and exercise, the results place sleep alongside them as a factor worth taking seriously.
“Our study shows that getting adequate sleep may help reduce the risk of weight gain and obesity-related conditions like heart disease and diabetes,” says Marie-Pierre St-Onge, a professor of nutritional medicine in Columbia’s Department of Medicine and Institute for Human Nutrition and the study leader. “People tend to gain weight over the course of their adulthood, and obesity is a major risk factor for heart disease. But focusing on eating a healthier diet and getting more physical activity to offset weight gain is simplistic and can be difficult to maintain.”
Looking beyond extreme sleep deprivation
Much of the earlier research connecting poor sleep with obesity has centred on severe sleep deprivation, frequently restricting people to as little as four hours of sleep a night. Those studies indicated that extreme sleep loss can heighten appetite and encourage overeating – behaviours that in turn contribute to weight gain.
The difficulty is that such severe restriction is hard for most people to sustain for more than a few days, which limits how far the results can be applied to everyday life. Very few people live with four hours of sleep for weeks at a time, so the relevance of those findings to the wider population has remained uncertain.
“These studies only show us what happens under the most extreme conditions and don’t tell us if mildly sleep-deprived people, like a lot of Americans who get 5 or 6 hours of sleep a night, will gain weight,” St-Onge says.
To reflect real-world habits more closely, the researchers set out to examine the effects of chronic, mild sleep loss – a pattern estimated to affect around 30% of adults.
Six weeks of less sleep led to measurable changes
The study involved 95 adults who typically slept between seven and eight hours each night. During one six-week phase, participants delayed their usual bedtime by 90 minutes, which shortened their nightly sleep. During a separate six-week phase, they kept to their normal sleep schedule, allowing each participant to serve as their own comparison.
Across both phases, participants wore wrist monitors that tracked sleep and physical activity. The researchers also measured body weight, waist circumference, body composition, and fasting levels of several hormones involved in regulating appetite, building a detailed picture of how the body responded to the change.
“While the one-pound weight gain observed with modest sleep curtailment is not overwhelming, it is important to remember this is occurring over just six weeks,” says Faris Zuraikat, assistant professor of nutritional medicine in Columbia’s Department of Medicine and Institute for Human Nutrition and first author of the study. “Our study was designed to mimic sleep patterns that most adults experience chronically. When extrapolated to a full year, we would expect that losing less than an hour and a half of sleep per night could result in clinically meaningful weight gain.”
Less sleep also meant more sitting
Alongside the change in weight, the researchers found that participants became less active during the sleep-restriction phase. On average, sedentary time rose by 17 minutes per day. Among men and postmenopausal women, inactivity climbed by nearly 30 minutes each day.
Notably, this increase in sitting held up even after accounting for the extra waking hours that come with shorter sleep – so the added inactivity was not simply a matter of being awake for longer.
“Even when we accounted for the fact that they were awake longer when sleep was shortened, participants spent more time being inactive than when they got adequate sleep,” Zuraikat says. “This is notable, as people who are more sedentary have elevated risk for chronic diseases.”
Earlier research suggests broader health effects
The same group of participants has featured in several related studies, which together suggest that the consequences of mild sleep loss may extend well beyond weight. In one earlier investigation, women with increased cardiometabolic risk who reduced their sleep by about 80 minutes each night for six weeks developed greater insulin resistance – an important risk factor for type 2 diabetes. The effect was particularly pronounced in postmenopausal women.
A separate study found that men and women with an elevated risk of heart disease developed an influx of inflammatory cells in the heart after undergoing mild sleep restriction, hinting at a possible mechanism linking short sleep to cardiovascular harm.
“Though more research is needed to further understand how sleep restriction leads to weight gain, all of our findings suggest that insufficient sleep increases the risk of obesity-related conditions like type 2 diabetes and heart disease,” St-Onge says.
“Now we need to understand the health effects of improving sleep in those who fail to get adequate sleep on a regular basis.”
About the study
The study, titled “Skimping on Sleep and Its Impact on Body Weight and Composition: A Pooled Analysis of Randomized Trials,” was published on 6 July in Annals of Internal Medicine.
The authors are Faris Zuraikat, Samantha Scaccia, Justin Cochran, Bin Cheng, Keith Diaz, Seth Creasy (University of Colorado), Brooke Aggarwal, Sanja Jelic, and Marie-Pierre St-Onge. The authors report no conflicts of interest.
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Digital Health Tools Show Early Promise for Infant Feeding and Sleep, UMass Chan Research Finds
Key Takeaways:
- Families who completed three or more visits with the virtual feeding service SimpliFed provided breast milk for nearly 16 weeks longer than those who did not use it.
- Infants whose parents engaged most actively with the AI-powered sleep app Huckleberry slept around 90 minutes longer during their longest overnight stretch.
- Lower uptake among Spanish-speaking and publicly insured families underlines the need to make digital health support equitable rather than exclusionary.
Studying whether technology can support new parents
Researchers at UMass Chan Medical School are investigating whether digital tools for infant feeding, sleep and other early parenting challenges can improve health outcomes and widen access to support for families.
Among them is Nisha Fahey, DO, MSc’21, assistant professor of pediatrics and principal investigator on research examining how digital health interventions can support families during the critical first year of a child’s life. Dr Fahey has led two pilot studies evaluating virtual lactation support and an artificial intelligence–powered infant sleep application, carried out in collaboration with the Department of Medicine’s Program in Digital Medicine. That programme is led by Apurv Soni, MD, PhD’21, assistant professor of medicine and the programme’s co-director, who serves as multiprincipal investigator on the work.
As a paediatrician, Dr Fahey hears the same questions from new parents every day: Is my baby feeding enough? Are they sleeping enough? And where can I turn for help when I need it?
“These technologies already exist. Families are accessing them and using them,” said Fahey. “As researchers and healthcare providers, it’s our responsibility to understand their impact and think about how they can be integrated into healthcare in a way that is equitable and reaches all families.”
Virtual feeding support and longer breastfeeding
The first study examined SimpliFed, a virtual infant-feeding support platform that gives families on-demand access to certified lactation consultants and feeding specialists. Researchers enrolled 200 pregnant and postpartum individuals through UMass Memorial Health’s obstetrics clinics and followed them through the first year of their infant’s life.
The study assessed infant growth and development, maternal mental health, healthcare utilisation and feeding practices. Researchers found that participants who completed three or more visits with SimpliFed provided breast milk for nearly 16 weeks longer than participants who did not use the service.
The findings also drew attention to important equity considerations. Uptake was lower among Spanish-speaking families and among publicly insured participants, underscoring the need to ensure that digital health interventions reach populations that have historically faced barriers to care.
“If health systems are going to deploy these tools broadly, we need to pay special attention to making sure all patients and families can access them,” Fahey said. “The goal is to close gaps in care, not widen them.”
An AI sleep app and longer overnight rest
A second pilot study evaluated Huckleberry, a mobile app that allows parents to track infant sleep and uses artificial intelligence to predict optimal nap and bedtime schedules. This study was funded by an NIH grant focused on point-of-care technologies for heart, lung, blood and sleep disorders.
The study enrolled approximately 80 families with infants under 12 months who are beneficiaries of UMass Memorial’s MassHealth Accountable Care Organization. Participants used the app for three months while researchers tracked engagement and measured infant sleep, parental sleep and parental mental health.
Among families who engaged most actively with the app, infants experienced longer consolidated overnight sleep. Researchers found that infants in the high-engagement group slept approximately 90 minutes longer during their longest stretch of overnight sleep, compared with participants who used the app less frequently.
The researchers also found that families in a population often underrepresented in digital health research were willing and able to engage with the technology. About half of participants were classified as highly engaged users, and most reported that they found the app useful and would recommend it to other families.
Recognising the limitations
The studies also revealed some limitations. While many families reported positive experiences, others described challenges with tracking data consistently or navigating app features while caring for a young infant.
For Dr Fahey, those findings reinforce the importance of viewing digital health as a complement to, rather than a replacement of, traditional care.
“Digital technologies offer an on-demand pathway for information and support,” she said. “The goal is to make both digital and in-person care as accessible as possible and empower families to choose what works best for them.”
Building evidence for the future of care
The research was made possible through collaborations across UMass Chan, including faculty in the Program in Digital Medicine, the Department of Obstetrics & Gynecology, the Department of Psychiatry & Behavioral Health, and the Department of Pediatrics.
“Parents are seeking out digital health apps on their own,” Fahey said. “Building evidence around their benefits and understanding their limitations helps us determine whether they can become trusted parts of care in the future.”
Source: UMass Chan Medical School
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Dietary Melatonin Intake Linked to Lower Rates of Obesity and Depression
Key Takeaways:
- Higher intake of melatonin from foods was associated with lower prevalence of obesity and depression in a large cohort of Brazilian university graduates.
- No significant associations were found between dietary melatonin intake and most cardiometabolic outcomes, including hypertension, metabolic syndrome or type 2 diabetes.
- The strongest associations were observed at moderate rather than very high levels of dietary melatonin intake, highlighting the complexity of diet–health relationships.
Background and study context
In a study published in the Journal of Human Nutrition and Dietetics, researchers examined the melatonin content of commonly consumed foods and explored how dietary melatonin intake was associated with a range of health outcomes. The analysis used cross-sectional data from a large cohort of Brazilian university graduates.
Melatonin is a hormone best known for regulating circadian rhythms and sleep–wake cycles. Beyond its endogenous production, melatonin is also present in both animal-based and plant-based foods. Experimental, observational and supplementation studies have linked melatonin to sleep regulation, mood, and metabolic health. Although the concentration of melatonin in foods is considerably lower than in supplements, diets rich in melatonin-containing foods have been shown to increase circulating melatonin levels within physiological ranges.
Previous evidence suggests that increasing melatonin intake through food may deliver doses that align more closely with natural circadian rhythms than pharmacological supplementation, potentially avoiding suprapharmacological exposure. On this basis, dietary melatonin has attracted interest as a marker of broader dietary patterns rather than as a direct therapeutic intervention.
Rationale for examining dietary melatonin
Obesity, depression and sleep disorders represent a substantial and growing public health burden. Prior observational and experimental studies have suggested that melatonin may have protective effects against inflammatory, metabolic and neurobehavioural outcomes. In addition, observational research has reported inverse associations between melatonin exposure and outcomes such as liver cancer incidence and all-cause mortality.
Despite this, relatively few studies have investigated habitual dietary melatonin intake or its associations with chronic conditions in adult populations. The present study aimed to address this gap by estimating melatonin intake from the diet and examining its relationship with multiple health outcomes in a large cohort.
Study design and population
The analysis drew on data from the Cohort of Universities of Minas Gerais (CUME+) study. CUME+ is an open, prospective cohort designed to assess the impact of dietary patterns and nutrition transition on noncommunicable diseases.
At baseline, participants completed a questionnaire administered in two parts. The first part collected information on sociodemographic characteristics, clinical history, lifestyle factors, anthropometric measures and self-reported morbidity.
Dietary assessment and estimation of melatonin intake
The second part of the baseline assessment included a food frequency questionnaire (FFQ), alongside questions on dietary habits, supplement use and cooking practices. Nutrient intake was estimated using established food composition tables.
Dietary melatonin content was estimated based on values reported in the scientific literature for individual food items. These estimates were then adjusted for total energy intake to account for differences in overall food consumption between participants.
Health outcomes and definitions
The health outcomes assessed in the study included obesity, obstructive sleep apnoea (OSA), hypertension, metabolic syndrome (MetS), type 2 diabetes (T2D), sleep duration, dyslipidaemia and depression.
Obesity was defined as a body mass index of 30 kg/m² or higher. Depression and OSA were identified based on self-reported medical diagnoses.
Dyslipidaemia was defined as the presence of at least one abnormal lipid parameter, including total cholesterol of 200 mg/dL or higher, triglycerides of 150 mg/dL or higher, high-density lipoprotein cholesterol below 40 mg/dL for males or below 50 mg/dL for females, or low-density lipoprotein cholesterol of 130 mg/dL or higher.
Cardiometabolic criteria
Metabolic syndrome was defined as central obesity plus any two of the following criteria: elevated triglycerides or treatment for hypertriglyceridaemia, reduced high-density lipoprotein cholesterol or treatment, elevated blood pressure or treatment for hypertension, and elevated fasting plasma glucose or a diagnosis of type 2 diabetes.
Hypertension was defined by the use of antihypertensive medication, a physician diagnosis, systolic blood pressure of 140 mmHg or higher, or diastolic blood pressure of 90 mmHg or higher. Type 2 diabetes was defined as a self-reported or physician diagnosis, use of antidiabetic medication, or fasting plasma glucose of 126 mg/dL or higher.
Sleep duration was categorised as short if participants reported sleeping less than seven hours per day, and normal if they reported seven hours or more per day.
Statistical analysis
Associations between dietary melatonin intake and health outcomes were estimated using logistic and Poisson regression models. Analyses were adjusted for a wide range of potential confounders, including age, sex, family income, binge drinking, smoking status, screen time, physical activity, medication use and sleep duration.
Participant characteristics
The final analysis included 8,320 participants with a mean age of 35.9 years. Most participants were female and reported that they did not smoke. Around one third of the cohort reported short sleep duration.
Dyslipidaemia, depression, obesity and hypertension were the most commonly reported health conditions within the study population.
Melatonin content of foods and dietary sources
Melatonin content was estimated for 119 of the 144 food items included in the FFQ. Reported concentrations ranged from 0 to 169.9 ng per gram of food. Mean daily melatonin intake was estimated at 25,554.7 ng and was significantly higher in males than in females.
The main dietary sources of melatonin in this population were coffee, lentils and beans, and rice. Higher melatonin intake was associated with lower intake of protein, cholesterol, and saturated and monounsaturated fats, alongside higher intake of fibre and carbohydrates. These patterns suggest that dietary melatonin intake may reflect broader differences in dietary composition.
Associations with health outcomes
After full adjustment, no significant associations were observed between dietary melatonin intake and obstructive sleep apnoea, hypertension, metabolic syndrome or type 2 diabetes. Initial associations with sleep duration and dyslipidaemia were attenuated after adjustment for age and sex and did not remain statistically significant.
In contrast, dietary melatonin intake showed an inverse association with both obesity and depression. Participants with daily melatonin intakes between approximately 14,900 and 34,400 ng were less likely to have obesity, while intakes between approximately 14,900 and 25,000 ng were associated with a lower likelihood of depression.
Notably, the strongest associations were observed in intermediate intake quintiles rather than among those with the highest melatonin intake, suggesting a non-linear relationship.
Conclusions and implications
In this cohort of Brazilian university graduates, higher dietary melatonin intake was associated with lower prevalence of obesity and depression, while no significant associations were identified for most other cardiometabolic outcomes or sleep duration.
The findings support existing hypotheses that dietary melatonin may play a role in metabolic and neurobehavioural regulation, potentially through anti-inflammatory pathways. However, the cross-sectional design of the study means that causal relationships cannot be established.
Further longitudinal and experimental research is needed to confirm these associations, determine whether dietary melatonin has an independent effect beyond overall dietary patterns, and clarify the biological mechanisms that may underlie the observed relationships.
CCH insights:
This is an interesting study, but it is difficult to see where this research leads to. If a person is suspected of having obesity, depression or some other condition due to a lack of melatonin, the solution is surely likely to be supplementation of melatonin, not an increase in melatonin-rich foods – because dietary changes are notoriously difficult to adhere to and when we are looking at just one nutrient, supplementation is a much easier option.
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Digital Health Tools Offer Scalable Solutions for Early Childhood Sleep Challenges
Key Takeaways:
- Digital sleep interventions demonstrate meaningful improvements in sleep outcomes for young children, with high levels of parental engagement across diverse formats.
- Parents also benefit, with several studies reporting reduced stress and improved sleep quality alongside improvements in their children’s sleep.
- While early results are promising, gaps remain in long-term evidence, objective sleep measurement and inclusion of families from minority and low-resource communities.
Digital health and early childhood sleep
A new scoping review led by researchers at the University of Miami Miller School of Medicine highlights the growing role of digital tools in helping parents support healthier sleep in early childhood. The review was spearheaded by Azizi Seixas, PhD, and Girardin Jean-Louis, PhD, and describes strong parental engagement, meaningful improvements in sleep outcomes and emerging best practices for future innovation in paediatric sleep health.
Sleep problems in young children, ranging from bedtime resistance and frequent night wakings to obstructive sleep apnoea, are closely linked to multiple aspects of development. Persistent sleep disturbances beyond infancy have been associated with challenges in school readiness, mood regulation and long-term health outcomes. Against this backdrop, the rapid expansion of mobile apps, telehealth services and online learning platforms has positioned digital health as a potentially powerful avenue for supporting families navigating sleep difficulties.
“This study fills an important gap in the pediatric sleep literature by showing how digital tools can capture real-world sleep behaviors at scale,” said Dr Seixas. “From a public health standpoint, these technologies help us identify population-level patterns earlier, especially in communities where sleep problems often go unrecognized. Clinically, they give providers objective, continuous data that can guide more personalized and timely interventions, ultimately improving outcomes for children who need support the most.”
A global review of digital sleep interventions
Dr Seixas, an associate professor of psychiatry and behavioural sciences, director of The Media and Innovation Lab, associate director of the Center for Translational Sleep and Circadian Sciences and interim chair of the Department of Informatics and Health Data Science at the Miller School, and Dr Jean-Louis, professor of psychiatry and behavioural sciences and neurology and director of the Center for Translational Sleep and Circadian Sciences, led an extensive scoping review of the scientific literature.
The research team screened more than 2,100 articles published from database inception through April 2025 across multiple academic sources. Following rigorous screening, 21 studies met the final inclusion criteria.
Collectively, these studies involved thousands of parents, dozens of healthcare professionals and nearly 500 parent-child dyads who participated in digital sleep intervention trials. The breadth of study designs and populations provided a wide-ranging view of how digital approaches are being applied in early childhood sleep support.
Types of digital tools evaluated
The review encompassed a diverse range of digital sleep interventions, including:
- Mobile applications designed to guide bedtime routines and monitor sleep behaviours
- Web-based educational modules for parents
- Telehealth programmes offering remote coaching and behavioural guidance
- Social media-enhanced parent support groups
- Wearable devices and data dashboards used for sleep tracking
- Robotic or kiosk-based sleep education tools
Across all formats, parental engagement emerged as a consistent strength. Most interventions focused on equipping parents with practical strategies to implement at home, often grounded in cognitive-behavioural therapy for insomnia or other evidence-based behavioural approaches.
Improvements in sleep outcomes for children and parents
A majority of the digital interventions reviewed were associated with improvements in at least one clinical sleep outcome for children. In many cases, benefits extended beyond the child to parents and caregivers.
Reported improvements for children included:
- Longer total sleep duration, documented in six studies
- Fewer night wakings
- Shorter sleep onset latency, defined as the time taken to fall asleep
- Improved sleep efficiency
- Reduced early-morning awakenings
- Improved breathing-related symptoms, including snoring detection through mobile tools
Several studies also reported positive effects on parental wellbeing, including reduced stress levels and improvements in parental sleep quality. One mobile application, Dr Lullaby, was associated with a significant reduction in the need for parents to remain in the room while their child fell asleep, suggesting improved sleep independence.
Telehealth and neurodevelopmental conditions
Telehealth interventions were particularly valuable for families of children with autism spectrum disorder. In randomised controlled trials, parents who received remote coaching on behavioural sleep strategies reported significant improvements in their children’s sleep by weeks five and ten of the intervention. These benefits were sustained at 16-week follow-up, indicating potential durability of effect.
Web-based educational programmes also demonstrated value. Online modules such as Mini-KiSS and the SKIP asthma-sleep intervention supported parents in establishing healthier bedtime routines and reducing night-time disruptions. These programmes consistently received high ratings for usability and acceptability among participating families.
The role of social support
The review highlighted the added value of social connection within digital interventions. In one study, an online healthy-lifestyle programme for young children showed no measurable sleep improvements until researchers introduced a closed Facebook group for parents. The addition of peer support facilitated shared problem-solving and encouragement, leading to significant gains in children’s sleep duration.
Gaps and priorities for future research
Despite the encouraging findings, the review identified several important limitations in the current evidence base:
- Approximately half of the studies involved predominantly white families, despite evidence that sleep problems disproportionately affect children from minority backgrounds.
- Most studies focused on short-term outcomes, with limited data on long-term effectiveness.
- Wearable devices were underused as objective measures of sleep.
- Children with chronic health conditions were underrepresented, even though early evidence suggests tailored digital interventions may be particularly effective for these groups.
Implications for clinical care and global paediatric health
Digital sleep health tools are becoming increasingly accessible, engaging and aligned with how families use technology in everyday life. This review suggests that when these tools are thoughtfully designed and grounded in behavioural science, they can meaningfully improve sleep outcomes for young children while also supporting parental wellbeing.
For clinicians, digital interventions may function as scalable extensions of care, offering education, behaviour tracking and reinforcement of healthy nightly routines. For researchers and developers, the next challenge lies in ensuring these tools are inclusive and reach families who may benefit most, particularly those in minority or low-resource communities.
The authors conclude that digital paediatric sleep interventions “show promise to educate parents and improve sleep outcomes in their child, extending benefits to the whole family.” With targeted innovation and equitable implementation, digital sleep solutions could become an integral component of paediatric care worldwide.
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