The study’s strength lies in its design. Rather than relying on questionnaires, which are notoriously prone to recall bias and overestimation of exercise, the researchers used objective device-based measurements of physical activity. Participants wore accelerometers for seven consecutive days, allowing the team to capture not just formal exercise but the full spectrum of daily movement, from walking to work to fidgeting at a desk. This objective approach matters because self-reported activity data can obscure exactly the kind of modest differences the study was designed to detect.

By linking individual birth records with later health survey data, the researchers could compare activity levels across the full range of gestational ages, from very preterm births to full-term deliveries. The analysis accounted for a range of potential confounding factors, aiming to isolate the effect of being born early from other circumstances that might influence a person’s activity habits, such as family background, socioeconomic conditions, and health status in adulthood.

The central finding was consistent: the earlier the gestational age at birth, the lower the device-measured physical activity in adolescence and adulthood. People born very preterm moved less overall than those born at term, and the pattern held across age groups studied. The differences were not dramatic on an individual level, but across entire populations they could translate into meaningful public health consequences, given how strongly physical inactivity is linked to cardiovascular disease, type 2 diabetes, obesity, and premature mortality.

Why would preterm birth leave such a long shadow on movement behavior? The researchers point to several plausible mechanisms. Preterm infants are at elevated risk of complications that can affect motor development, including bronchopulmonary dysplasia, a chronic lung condition common among babies born extremely early, as well as cerebral palsy and other neurodevelopmental disorders in the most severe cases. Even among preterm children without diagnosed disabilities, subtle differences in motor coordination, muscle strength, and cardiorespiratory fitness have been documented in follow-up studies, and any of these could make physical activity feel more effortful or less rewarding.

There may also be behavioral and social pathways at work. Children who struggle with sports and playground games early in life may gradually disengage from physical activity, a process that compounds over the years as exercise habits crystallize. Parents of children born preterm, meanwhile, may be more protective or cautious about physical exertion, shaping the child’s activity environment from the start. The Norwegian data cannot definitively separate these mechanisms, but the persistence of the association into adulthood suggests that whatever drives it is not simply a transient feature of childhood recovery.

The study draws its power from the HUNT Study, one of the largest population-based health surveys in the world, which has followed residents of Trøndelag county in central Norway across multiple generations since the 1980s. By combining HUNT’s accelerometer measurements with the Medical Birth Registry’s prospectively recorded gestational age data, the researchers avoided the recall problems that plague retrospective studies of birth outcomes. Gestational age in the registry is based on clinical assessment at the time of birth, not on participants’ memories decades later.

The findings arrive at a moment of growing international concern about the long-term health of preterm survivors. Thanks to advances in neonatal intensive care, the vast majority of babies born preterm now survive into adulthood, and cohorts of preterm-born individuals are larger than at any point in history. Research consortia such as RECAP Preterm, funded through the European Union’s Horizon 2020 program, which also supported this study, have been assembled specifically to pool data across countries and understand how preterm birth reshapes adult health risks, from cardiometabolic disease to mental health and, now, physical activity.

For clinicians and public health planners, the study suggests that physical activity promotion could be a valuable and underused tool in the long-term follow-up of preterm-born populations. If preterm survivors are systematically less active, they may accrue less of the protective benefit that exercise provides against the very diseases, such as hypertension and insulin resistance, to which they are already predisposed. Targeted interventions, whether through pediatric follow-up programs, school physical education, or adult primary care, could help close this gap before it compounds into elevated disease risk.

The authors note that the observed differences in activity were modest at the individual level, and that many people born preterm are highly active and healthy. The association describes a population-level trend, not a destiny for any individual. Still, in a field where early-life origins of adult disease have become a central research theme, the study adds a new dimension: the legacy of preterm birth may extend not only to disease risk but to the everyday behaviors that shape health across the entire life course. As wearable sensor technology becomes routine in population health research, studies like this one are likely to keep refining our understanding of how the earliest weeks of life echo through decades of movement, metabolism, and well-being.

Subject of Research: The long-term association between preterm birth and device-measured physical activity levels in adolescents and adults

Article Title: People born preterm are likely to be less physically active as teenagers and adults, according to large Norwegian study which measured a week of participants' activity using wearable sensors

Article References: People born preterm are likely to be less physically active as teenagers and adults, according to large Norwegian study which measured a week of participants' activity using wearable sensors. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: preterm birth, physical activity, wearable sensors, HUNT Study, Medical Birth Registry, gestational age, PLOS One, Norway, accelerometry, neonatal outcomes, lifelong health, exercise behavior

The scale of the project is unprecedented. It combines 17 years of GPS and accelerometer tracking from 850 birds and bats of 38 species with four years of radar data covering 12 size classes of smaller flyers. The animals range in size from about 12 grams to more than 11 kilograms, and an international team of 68 researchers contributed data, making this the largest study yet to examine the cost of long-distance travel for wild animals. It is also the first to factor in the role of the atmosphere in the movement of so many wild animals at a global scale.

The contrast that inspired the work is striking. An Andean condor and a trumpeter swan both weigh about 11 kilograms, so laboratory rules would predict identical energy bills per kilometer. Yet the condor covers each kilometer of flight for about a fifth of the swan’s energy cost. The difference is the air: the condor rides rising currents and flaps for only 0.1 percent of its flight time, while the swan flaps for 99 percent. The study put a price on that difference, finding the condor’s cost of transport was 79 percent lower than the swan’s, making soaring flight cheaper than swimming.

To us, the sky might just look like background for flying animals, but it is an essential resource that can dramatically change the cost of a journey, says first author Dr. Martina Scacco of the Max Planck Institute of Animal Behavior. The team boiled the differences down to fuel economy, nature’s equivalent of miles per gallon, which allowed them to compare transport costs across species and flight modes, much like comparing the freight costs of sea mail or air mail.

The method relied on accelerometers to distinguish high-cost flapping from low-cost soaring. With GPS data, the researchers matched each stretch of flight with the wind and rising air the animals met along the way. This enabled them to calculate the time individual animals spent flapping or soaring on each stretch, and to approximate how much energy they spent per meter travelled, their cost of transport. When compared, the 50 species fell into two main groups: soarers and flappers.

Among the soaring birds, size had a marked effect on transport cost. The heavier a soaring bird, the less it flapped and therefore the lower its cost of transport. Soaring vultures offer a vivid example. The seven vulture species in the study flew for a combined 128,000 days and more than 4.3 million kilometers, enough to circle the planet more than 100 times. Remarkably, they achieved that while flapping only 0.1 to 7 percent of flight time, and the heaviest vulture, the Andean condor, flapped least of all.

They did this by exploiting atmospheric energy. Soaring birds rode rising columns of air, which lowered their cost of transport the most, like us riding the elevator to the top floor, says senior author Prof. Emily Shepard from Swansea University. Soarers are masters at extracting energy from the environment, and when conditions are right they can drive their costs down to very little. But conditions are not always right. The larger the soaring bird, the more restricted it was in terms of when and where it could fly, a trade-off between cheap travel and flexible scheduling.

Flapping birds, on the other hand, use high-energy movement to cope with more variable conditions. Wind had the most significant effect on their transport costs, with tailwinds providing support and headwinds presenting resistance. Air can drive flight costs up as well as down for flappers, says senior author Dr. Kamran Safi of the Max Planck Institute of Animal Behavior. What surprised us was just how much flappers operate in costly conditions where their fuel economy is really low, he adds, expressing hope that the framework will drive further investigations of the different trade-offs the two groups face, and of potential energy-saving mechanisms still missing.

The laboratory rules tell us that condors and swans must have the same energy bill because they have the same body mass, says Shepard. Yet seeing how condors soar and swans flap, we know that clearly there must be a difference. When flying animals have access to natural atmospheric flows, they have free fuel from the sky. This study exposes the mistakes we make when we ignore the real-world conditions that animals have been responding to for millennia, she adds.

Beyond rewriting a textbook ranking, the findings offer a new framework for predicting the energetic cost of flight and how climatic changes might affect where and when animals travel in the future. If atmospheric conditions change, so too will the cost of flight, and therefore how animals decide to migrate and establish communities, says Safi. In future work, the authors aim to build on their findings by measuring animals’ energy use directly, such as through heart rate monitoring, which will capture differences in individual physiology and provide an even more realistic measure of the energetic cost of flight. For conservation and management of aerial species, the study provides a key: the atmosphere is not a backdrop for flight but a resource, and protecting soaring migrants may mean protecting the winds and rising air on which their fuel economy depends.

Subject of Research: Cost of transport in wild flying animals

Article Title: Wild birds rewrite rules for travel

Article References: Wild birds rewrite rules for travel. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: flight, soaring, Andean condor, cost of transport, atmospheric flows, GPS tracking, accelerometry, migration, vultures, Science, Wild, birds

The study, led by Xiaolin Yang of Jamk University of Applied Sciences in Jyväskylä, drew on cross-sectional data from 1,014 participants, roughly 60 percent of them women, collected between 2018 and 2020. Each participant wore an accelerometer for seven consecutive days, allowing the researchers to capture not just how much people moved, but the texture of their days: how long they slept, how much time they spent sedentary at work versus during leisure, and how much light physical activity and moderate-to-vigorous physical activity accumulated in each context. That distinction matters, because an hour of sitting at a desk drafting a report is not physiologically or cognitively equivalent to an hour of sitting on a sofa, and an hour of lifting boxes taxes the body very differently from an hour of brisk walking.

Methodologically, the team went beyond the usual regression-on-minutes approach. Because the 24-hour day is a fixed budget, time spent in one behavior necessarily comes at the expense of another, and standard statistical models can distort the picture when the components of that budget are analyzed in isolation. The researchers therefore applied compositional data analysis, a framework that treats the full daily composition of sleep, sedentary time, light activity and moderate-to-vigorous activity as an interdependent whole, using isometric log-ratio transformations to model the relative geometry of the data. They then used isotemporal substitution models to ask a deceptively simple question: if a person shifted 60 minutes from one behavior to another, what would happen to their cognitive performance?

Cognition itself was measured with the Cambridge Neuropsychological Test Automated Battery, a computerized suite that yields scores across several domains: learning and memory, working memory, reaction time, and information processing, along with an overall composite. The analyses were adjusted for a battery of sociodemographic and health-related variables, and — crucially — stratified by sex and by occupational physical workload, splitting participants into sedentary workers, those in standing or moving occupations, and those in physically demanding jobs.

The results were striking for how context-dependent they proved. Among men, more time spent in light physical activity at work was associated with slower reaction times and weaker information processing. Among women, by contrast, more sedentary time at work was associated with better learning and memory. Neither pattern implies causation, and the effect sizes were small, but the direction of the associations is enough to make anyone who has ever assumed that workplace sitting is uniformly harmful pause for thought.

Occupational category reshaped the picture further. In sedentary workers, more occupational light physical activity was associated with lower overall cognitive performance, along with weaker learning and memory and slower information processing. In people whose jobs involved standing and moving, the story flipped: more leisure-time sedentary time was associated with better overall cognitive performance and better working memory, while more leisure-time light activity was associated with slower reaction times. And among those in physically demanding occupations, more sedentary time at work was associated with better learning and memory. In other words, the same behavior — sitting — appeared to carry different cognitive associations depending on whether it punctuated a physically taxing day or a desk-bound one.

The isotemporal substitution models added a practical dimension. Reallocating 60 minutes from occupational light physical activity into sedentary time or into moderate-to-vigorous physical activity was associated with modest cognitive benefits, particularly among men and among sedentary workers, with statistical significance at the p < 0.05 level. For a desk worker whose job involves long stretches of low-intensity puttering — walking between meetings, standing at copiers, light errands — the analysis suggests that replacing some of that low-grade occupational movement with either focused seated work or genuine vigorous exercise might be associated with sharper cognition. The authors emphasize that these associations were generally small, and the cross-sectional design means the arrow of causality could point either way: perhaps people with certain cognitive profiles gravitate toward certain kinds of work, rather than the work shaping the cognition.

That caveat is worth dwelling on, because it is where much of the scientific interest lies. One plausible interpretation is that occupational light activity often reflects jobs with high physical demands but low cognitive engagement, whereas sedentary work tends to coincide with cognitively stimulating tasks — reading, writing, problem-solving — that may themselves help maintain cognitive function in midlife. The cognitive benefit of leisure-time sitting among people in standing and moving occupations fits this reading: after a day on their feet, the sedentary hours of these workers may be filled with mentally engaging pursuits. Conversely, for workers whose days are already physically demanding, sedentary time at work may represent necessary recovery rather than idleness. The study cannot confirm these mechanisms, but the stratified patterns are consistent with the idea that the meaning of a behavior depends on the biological and cognitive context in which it occurs.

The sex differences add another layer. Why might occupational light activity correlate with slower reaction times in men while occupational sitting correlates with better memory in women? The authors do not offer a definitive answer, and the associations are modest, but the stratification itself is a methodological point worth celebrating. Many studies of movement behavior and cognition pool the sexes and blur occupational categories, potentially washing out real signals or producing misleading averages. By analyzing men and women, and sedentary and physically active occupations, separately, the Finnish team surfaced patterns that a single pooled model would likely have hidden.

For the millions of workers navigating the modern mix of desk time, chores and exercise, the takeaway is neither a license to sit all day nor a renewed guilt trip about the office chair. It is a call for nuance. The 24-hour day is a closed system, and the value of any given hour depends on what it replaces, where it happens, and who is spending it. The authors conclude that associations between movement behaviors and cognitive performance were generally small and context-dependent, varying by sex and occupational physical workload, and that the context in which movement behaviors are accumulated deserves far more attention in future research. As wearable accelerometers proliferate and longitudinal follow-ups of cohorts like the Young Finns study continue, the field may soon move from these cross-sectional snapshots to causal answers about which reallocations of our daily 24 hours genuinely protect the aging brain. Until then, the study stands as a reminder that in the physiology of everyday life, context is not a footnote — it is the finding.

Subject of Research: Associations between 24-hour movement behaviors and cognitive performance in middle-aged employees

Article Title: Compositional data analysis of 24-h movement behaviors and cognitive performance in middle-aged employees: the cardiovascular risk in Young Finns study

Article References: Yang, X., Kukko, T., Syväoja, H., Kulmala, J., Pahkala, K., Lehtimäki, T., Suominen, T. H., Raitakari, O. T., Rovio, S. P., & Tammelin, T. H. (2026). Compositional data analysis of 24-h movement behaviors and cognitive performance in middle-aged employees: the cardiovascular risk in Young Finns study. Journal of Activity, Sedentary and Sleep Behaviors. https://doi.org/10.1186/s44167-026-00117-y

Image Credits: AI Generated

DOI: 10.1186/s44167-026-00117-y

Keywords: movement behavior, cognitive performance, sedentary time, physical activity, compositional data analysis, isotemporal substitution, occupational health, sex differences, accelerometry, midlife cognition, Young Finns Study, working memory

The study team, led by Therese Christensson of Karolinska Institutet, identified 2,576 cancer survivors within the SCAPIS cohort, a population-based sample of roughly 30,000 randomly selected Swedes aged 50 to 64 recruited between 2013 and 2018 at six sites across the country. By linking SCAPIS data to the Swedish National Patient Registry using ICD-9 and ICD-10 codes, the researchers identified survivors of breast, prostate, lung, colorectal, and urinary bladder cancers as well as malignant melanoma, excluding childhood and young-adult cancers by setting the year 2000 as a diagnostic cut-off. The median participant was 59 years old, 57 percent were women, and the median time since diagnosis was a remarkable 13 years, making this a genuinely long-term survivorship population rather than a recently treated one. Malignant melanoma dominated the sample at about half of all cases, followed by breast cancer at 25 percent and prostate cancer at 15 percent.

What sets this analysis apart technically is its measurement strategy. Physical activity was captured with tri-axial ActiGraph accelerometers worn on the hip for seven consecutive days, with valid days defined as at least 600 minutes of wear time and intensity thresholds set at counts per minute: below 200 for sedentary behaviour, 200 to 2,689 for light activity, 2,690 to 6,166 for moderate activity, and above 6,167 for vigorous activity. Meeting the physical activity recommendation was operationalized as at least 150 minutes per week of moderate-to-vigorous activity, equivalent to 22 minutes per day under national Swedish guidance. Diet was scored with the Swedish dietary guideline index, or SweDGI, a 12-component food-based index spanning encouraged items such as fruits, vegetables, legumes, nuts, whole grains, fish, and unsaturated fats, alongside discouraged items including red and processed meat, high-fat dairy, added sugar, alcohol, and salt, with a maximum score of 48 and a cut-off of 26 points marking good adherence. Alcohol was screened with the AUDIT-C questionnaire, smoking status by self-report, and sleep quality with a single item from the Basic Nordic Sleep Questionnaire.

The accelerometer data reveal a population that is, on the surface, reasonably active but profoundly sedentary. Most survivors met the weekly physical activity recommendation, with the lowest figure, 76 percent, appearing among the oldest lung cancer survivors. Yet on average, survivors spent eight hours per day, or 55 percent of wear time, sedentary, only 46 minutes in moderate activity, and less than a single minute, just 0.08 percent of the day, in vigorous activity. Prostate cancer survivors were the most sedentary group at 8.4 hours per day, while breast cancer survivors were the least at 7.6 hours. Men consistently sat more than women, accumulating at least eight sedentary hours daily across all cancer types, and younger survivors were significantly more likely than older ones to meet the activity target, although no sex difference emerged on that specific measure.

Diet was the clearest failure point. Only 41 percent of survivors met the dietary recommendation overall, and the sex gap was dramatic: 53 percent of women achieved good adherence compared with just 26 percent of men, a highly significant difference. Breast cancer survivors fared best at 56 percent, while male lung cancer survivors sat at the bottom with only 17 percent meeting the recommendation. This matters because prior research, cited by the authors, links diet quality to survival: good-quality diets are associated with improved survival in breast and colorectal cancer survivors, while Western-style diets high in fat, red meat, and processed foods have been tied to recurrence in colorectal cancer and to higher all-cause mortality across several cancer groups.

Alcohol told a similar story of quiet excess. Roughly a third of survivors consumed alcohol above recommended levels, with cut-offs set at more than five points on the AUDIT-C for men and more than four for women, based on Swedish national guidance. Prostate cancer survivors had the lowest proportion meeting the alcohol recommendation at 62 percent, while breast cancer survivors had the highest at 71 percent. Women were significantly more likely than men to stay within limits, 73 percent versus 62 percent. The authors caution that comparisons with general population data are imperfect, since Swedish population surveys typically define risk consumption by weekly standard drinks, whereas AUDIT-C also captures episodes of heavy drinking and cannot be directly translated into weekly intake. Still, the contrast is suggestive: only about 16 percent of the general Swedish population is estimated to drink above recommended levels, compared with roughly a third of these survivors.

Not all the news was grim. Smoking, often the most damaging modifiable factor after a cancer diagnosis, was largely under control: 88 percent of survivors were former or never smokers, mirroring the roughly 11 percent smoking prevalence in the general Swedish population. The glaring exception was lung cancer, where a full third of survivors still smoked, a finding with serious consequences given evidence that cessation after a lung cancer diagnosis reduces the risk of second primary lung tumours and that continued smoking raises both overall and cancer-specific mortality. Sleep quality was also broadly satisfactory, with 82 percent reporting good sleep and most sleeping seven to eight hours per night, though men outperformed women across nearly all cancer types, and close to a third of female urinary bladder cancer survivors and older colorectal cancer survivors reported poor sleep. Given that the median survivor was 13 years past diagnosis, the authors note this may indicate that sleep disturbances can persist for many years after treatment ends.

Perhaps the most consequential finding concerns combinations. Nearly everyone, 99 percent, met at least one recommendation, but only about half met four or more of the five, and just a small minority achieved all five. Meeting multiple recommendations differed significantly across cancer types, with breast cancer and malignant melanoma survivors doing best; 22 percent of breast cancer survivors met all five lifestyle recommendations. Women were significantly more likely than men to meet multiple recommendations. The steepest drop-offs came at the harder end of the spectrum: the transition from three to four recommendations coincided with a 32 percentage-point decline among lung cancer survivors, while prostate cancer survivors showed the largest fall, 17 percentage points, between two and three. Prior research suggests this stacking matters biologically, since meeting four or five lifestyle factors has been associated with lower incidence of cancer, cardiovascular disease, and diabetes compared with meeting none, and meeting multiple recommendations appears more protective for survival than meeting any single one.

The authors are candid about limitations. Dietary data were self-reported and vulnerable to underreporting, overreporting, and social desirability bias, which means the true proportion failing dietary recommendations could be still higher than observed. Dichotomizing each lifestyle factor into met or not met inevitably discards nuance, multimorbidity, cancer stage, and treatment information were unavailable, and the 13-year median time since diagnosis raises the possibility of survival bias, since survivors who lived long enough to participate may be healthier overall. The restriction to adults aged 50 to 64 also limits generalizability to younger or older survivors and to populations outside Sweden, although the cohort broadly resembles the Swedish population in education, activity level, and country of birth.

Even with those caveats, the message for clinical practice is pointed. With roughly 600,000 people in Sweden living with cancer as of 2022 and survivor numbers rising worldwide as treatment improves, secondary prevention is becoming a central task of oncology follow-up. The World Cancer Research Fund encourages survivors to adhere to lifestyle recommendations as much as possible, and evidence continues to accumulate that structured exercise can improve survival and functioning, as a recent phase III trial in colorectal cancer demonstrated. This study suggests that follow-up care should move beyond single-issue advice and toward integrated interventions that target multiple behaviours simultaneously, with particular urgency around diet and alcohol, and with tailored outreach to the groups falling furthest behind, including male survivors, lung cancer survivors who continue to smoke, and prostate cancer survivors whose sedentary hours and drinking habits may quietly erode the survival their treatment won.

Subject of Research: Adherence to lifestyle recommendations among long-term cancer survivors

Article Title: Meeting lifestyle recommendations among cancer survivors – a cross-sectional descriptive analysis from the Swedish CArdioPulmonary BioImage study (SCAPIS)

Article References: Christensson, T., Hagströmer, M., Algurén, B., Bergman, F., Bäck, M., Drake, I., Porserud, A., Rossen, J., & von Rosen, P. (2026). Meeting lifestyle recommendations among cancer survivors – a cross-sectional descriptive analysis from the Swedish CArdioPulmonary BioImage study (SCAPIS). Journal of Cancer Survivorship. https://doi.org/10.1007/s11764-026-02140-z

Image Credits: AI Generated

DOI: 10.1007/s11764-026-02140-z

Keywords: cancer survivors, lifestyle recommendations, SCAPIS, physical activity, diet quality, alcohol consumption, smoking cessation, sleep quality, secondary prevention, accelerometry, survivorship, Sweden

The research team, led by Jie Li and Ling Yu of The Second Hospital of Jilin University in Changchun, China, analyzed data from 7,098 adults aged 20 years and older who participated in the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2014. NHANES is a nationally representative survey program run by the US National Center for Health Statistics, and for these survey waves participants were asked to wear a wrist accelerometer for seven consecutive days. The researchers linked these movement records to National Death Index mortality data through 2019, creating a prospective cohort in which objective device measurements preceded the outcomes being studied.

At the heart of the analysis is a metric called the active-to-sedentary transition probability, or ASTP. Rather than measuring total activity volume — the familiar step counts or minutes of moderate-to-vigorous exercise — ASTP captures the probability that a minute of active movement is followed by a minute of sedentary time. A high ASTP means that active bouts tend to be short-lived and quickly interrupted by sitting or lying down; a low ASTP means that when someone is active, they tend to stay active for longer stretches. In other words, ASTP quantifies the continuity, or fragmentation, of everyday movement, a quality that wrist accelerometers are uniquely positioned to capture with minute-level precision.

During a median follow-up of 6.8 years, 522 deaths occurred in the cohort. After adjusting for a comprehensive set of clinical covariates — a sensitivity analysis that included 6,586 participants with complete data — each one-standard-deviation increase in ASTP was associated with a 16.5 percent higher hazard of death from all causes (hazard ratio 1.165, 95 percent confidence interval 1.042 to 1.304). The association was even stronger for deaths from causes other than cardiovascular disease and cancer, with a hazard ratio of 1.293 (95 percent CI 1.099 to 1.521). These estimates came from survey-weighted Cox proportional hazards models, the standard epidemiologic tool for estimating how a characteristic relates to the timing of an event such as death.

The cause-specific results were more complicated. For cardiovascular mortality, the estimates were statistically imprecise in both the cause-specific Cox models and the Fine–Gray subdistribution hazard models, which are designed to handle competing risks — the situation where one type of death precludes the possibility of another. For cancer mortality, the picture was mixed: the Fine–Gray model suggested an inverse subdistribution association, while the cause-specific estimate was imprecise. This divergence illustrates a technical but important point in survival analysis: when competing causes of death are common, different modeling frameworks can yield qualitatively different answers, and researchers must be careful not to overinterpret any single estimate.

The investigators went to considerable lengths to test the robustness of their findings. Sensitivity analyses addressed survey nonresponse by reweighting the sample, and the all-cause hazard ratio barely moved, from 1.165 to 1.168. A 24-month landmark analysis, which excluded deaths occurring in the first two years of follow-up to reduce the possibility of reverse causation — that is, pre-existing illness causing both fragmentation and early death — yielded a smaller and statistically nonsignificant estimate of 1.097 (95 percent CI 0.959 to 1.253). Most tellingly, when the researchers additionally adjusted for the total amount of movement, the association was attenuated or even reversed. This suggests that activity fragmentation is strongly correlated with how much people move overall, and that the apparent mortality signal may largely reflect movement volume rather than an independent effect of movement continuity.

The team also explored whether ASTP could improve mortality prediction beyond established clinical risk factors, using internal validation with 1,000 bootstrap refits and five-year calibration checks. The answer was technically yes but practically marginal: adding ASTP to a model changed the apparent C-index — a measure of predictive discrimination — by only 0.0034, with a bootstrap confidence interval of 0.0006 to 0.0067, and the optimism-corrected difference was 0.0032. The authors are explicit that this small prediction increment was internal and exploratory, with no established clinical utility. In plain terms, knowing how fragmented someone’s movement is does not yet meaningfully sharpen a doctor’s ability to predict their risk compared with knowing their age, blood pressure, metabolic markers and other standard variables.

These caveats matter because the study’s conclusions are deliberately restrained. The authors state that wrist-derived activity fragmentation, as measured by ASTP, is an epidemiologic marker of movement pattern that is correlated with movement amount, and that the observed associations with all-cause and other-cause mortality after clinical adjustment do not establish an independent causal effect of activity continuity. They also emphasize that ASTP is a distinct construct from accumulated brief moderate-to-vigorous physical activity, meaning that the fragmentation metric should not be conflated with the well-established benefits of exercise bouts. This distinction is important for a field that has increasingly turned to wearable devices to decompose physical activity into ever finer components.

Why does fragmentation matter at all? The concept has gained traction in gerontology and population health because the patterning of daily activity may reflect underlying physiological reserve, fatigue, frailty or subclinical disease. A person whose active periods dissolve quickly into sedentary time may be experiencing early signs of declining stamina or health that a single measure of total activity cannot fully capture. Wrist accelerometers, now ubiquitous in consumer fitness trackers, make it possible to measure this patterning objectively in free-living conditions, free from the recall bias that plagues questionnaire-based physical activity assessment. The NHANES accelerometry program has been a cornerstone of this research, providing nationally representative device data linked to long-term outcomes.

For the public, the takeaways are measured. The study does not claim that stitching together longer active bouts will independently extend life; the evidence for that specific causal claim remains unproven, and the association was sensitive to how much people moved overall. What it does establish is that movement fragmentation is a measurable, reproducible characteristic of daily behavior that tracks with mortality risk in a large, representative sample of US adults, and that it can be quantified with the same consumer-grade sensors millions of people already wear. As wearable technology continues to proliferate, metrics like ASTP may find their place not as standalone predictors but as descriptive markers that help researchers understand how the architecture of daily movement relates to long-term health — a reminder that in the science of physical activity, how we move may be as intriguing as how much.

Subject of Research: Association between accelerometer-measured activity fragmentation and cause-specific mortality in US adults

Article Title: Wrist-worn accelerometer-derived activity fragmentation and cause-specific mortality in US adults: a population-based prospective cohort study

Article References: Li, J., Sun, X., Zhang, J., Zhai, L., & Yu, L. (2026). Wrist-worn accelerometer-derived activity fragmentation and cause-specific mortality in US adults: a population-based prospective cohort study. BMC Public Health. https://doi.org/10.1186/s12889-026-29778-9

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29778-9

Keywords: physical activity, accelerometry, sedentary behavior, activity fragmentation, mortality, NHANES, wearable technology, competing risks, population health, Cox model, risk factors, Wrist-worn

The study, led by Rajan Shrestha of Aarhus University and the Nepal Development Society, forms part of a growing effort to correct a stubborn imbalance in global health evidence. Physical inactivity and prolonged sedentary behaviour are rising public health concerns across low- and middle-income countries, where non-communicable diseases such as diabetes, cardiovascular disease and cancer are climbing steeply. Yet most of what researchers know about the environmental and psychological drivers of activity comes from high-income countries, and much of it rests on questionnaires that ask people to recall and report their own behaviour, a method notoriously prone to bias and error.

To sidestep those limitations, the researchers turned to objective measurement. They analysed data from 421 adults who had taken part in the Community-Based Promotion of Physical Activity trial in Pokhara Metropolitan City. Each participant wore an Axivity AX3 accelerometer on the wrist continuously for seven days, providing minute-by-minute records of movement and stillness. The device captures acceleration in three dimensions, from which researchers derive measures such as the Euclidean Norm Minus One, a standard metric for quantifying overall body movement intensity. From these raw signals, the team calculated daily moderate-to-vigorous physical activity, the intensity level most strongly linked to health benefits, as well as total sedentary time.

Alongside the sensor data, participants completed structured questionnaires covering two distinct categories of environmental opportunity. The first, described as recreational or built opportunities, captures features familiar from urban planning literature in wealthy countries: parks, playgrounds, walking paths, gyms and other purpose-built facilities for leisure-time exercise. The second, productive or utilitarian opportunities, reflects a different reality: whether the surrounding environment supports movement as a by-product of daily life, such as walking to markets, shops, workplaces or services. The team also measured psychosocial factors drawn from the Theory of Planned Behaviour, a widely used psychological framework, including intention to be active and perceived behavioural control, the confidence a person feels in their own ability to act.

Because participants were recruited through community clusters, the researchers used multilevel linear mixed-effects models with random intercepts for clusters, a statistical approach that accounts for the fact that people living in the same neighbourhood share characteristics and cannot be treated as fully independent observations. This matters enormously in studies of built environments: ignoring clustering can produce misleadingly confident estimates. The models estimated associations between environmental and psychosocial factors and two outcomes, daily moderate-to-vigorous physical activity and sedentary time, and the team added interaction terms to test whether perceived behavioural control modified the environmental effects.

The headline result is striking for what it reveals about the geography of movement. Productive and utilitarian environmental opportunities, the everyday infrastructure that lets people accomplish necessary tasks on foot, showed stronger associations with device-measured moderate-to-vigorous activity than recreational or built features did. In the model that considered the environment alone, higher productive or utilitarian opportunity was linked to more daily moderate-to-vigorous activity. However, when the researchers added psychosocial factors into a combined model, these environmental associations were attenuated, suggesting that part of the apparent environmental effect travels through, or overlaps with, psychological and motivational characteristics of individuals.

One psychological factor refused to fade. Perceived behavioural control remained positively and robustly associated with moderate-to-vigorous physical activity even after adjustment, with an estimated coefficient of 34.35 and a 95 percent confidence interval running from 6.98 to 61.72. In practical terms, adults who felt more capable of being active accumulated meaningfully more device-measured activity each day. Intention, by contrast, showed no clear association with measured behaviour, a finding that will resonate with anyone who has resolved to exercise and then not done so. The gap between intending and acting is a central puzzle of behavioural science, and this dataset from Nepal adds a low- and middle-income country data point to a debate dominated by Western samples.

Sedentary time told a subtler story. Environmental associations with sitting and stillness were weaker and less consistent than those with activity, but the interaction analysis produced one notable result: among people in the highest tertile of productive or utilitarian environmental opportunity, higher perceived behavioural control was associated with less sedentary time, with an interaction coefficient of −35.26 minutes and a confidence interval from −64.92 to −5.61. The interpretation is intriguing. Environments rich in utilitarian movement opportunities may only translate into less sitting for people who feel confident in their ability to act on those opportunities, hinting that environmental and psychological levers work together rather than independently.

The authors caution, appropriately, that this is a cross-sectional analysis. It captures a single moment in time and cannot establish whether environments shape behaviour, whether active people choose more supportive environments, or whether some third factor drives both. Reverse causation is a live possibility: someone who already enjoys walking may perceive their neighbourhood as more walkable. The sample, drawn from participants in an existing physical activity promotion trial in one metropolitan area, may also not represent all of semi-urban Nepal. Still, the use of objective accelerometry over a full week, the multilevel design and the explicit separation of recreational from productive environmental opportunity make this one of the more methodologically careful studies of its kind in South Asia.

The implications stretch well beyond Pokhara. Cities across Asia and Africa are urbanising at unprecedented speed, and the design choices made in the next two decades will lock in patterns of movement or stillness for generations. If the findings hold, they suggest that in rapidly urbanising low- and middle-income countries, promoting physical activity may depend less on importing the gym-and-park model of wealthy nations and more on preserving and strengthening the everyday, utilitarian movement woven into daily life, while simultaneously building residents’ confidence that they can act. Interventions that pair walkable markets, services and workplaces with behavioural support targeting perceived control could do double duty. As non-communicable diseases rise across the Global South, this study offers a timely reminder that the most powerful exercise prescription may already be written into the streets people walk every day, provided they believe they can follow it.

Subject of Research: Environmental and psychosocial determinants of device-measured physical activity and sedentary behaviour among adults in semi-urban Nepal

Article Title: Environmental and psychosocial contexts of device-measured physical activity and sedentary behaviour in semi-urban Nepal: a multilevel analysis

Article References: Shrestha, R., Paudel, S., Rijal, A., Adhikari, T. B., Khatri, B., Neupane, D., Vaidya, A., Nielsen, R. Ø., & Kallestrup, P. (2026). Environmental and psychosocial contexts of device-measured physical activity and sedentary behaviour in semi-urban Nepal: a multilevel analysis. BMC Public Health. https://doi.org/10.1186/s12889-026-29793-w

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29793-w

Keywords: physical activity, sedentary behaviour, accelerometry, Nepal, low- and middle-income countries, built environment, perceived behavioural control, Theory of Planned Behaviour, multilevel analysis, public health, urbanisation, non-communicable diseases

The study stands out in a crowded field for its methodological rigor. Much of the existing evidence linking sleep to cognitive ageing relies on cross-sectional snapshots, single crude measures of sleep, and broad global cognitive scores that lump together very different mental abilities. Marent and colleagues—working with Mitch J. Duncan of the University of Newcastle, Greet Cardon of Ghent University, Genevieve Albouy of the University of Utah, and Jannique van Uffelen of KU Leuven—deliberately broke from that template. They measured sleep both objectively and subjectively, assessed cognition with a validated computerized battery that yields separate domain scores, and used statistical models designed for repeated observations over time, allowing them to ask not only whether sleep and cognition were related but whether those relationships changed as the study unfolded.

The objective side of the sleep measurement came from seven days of wrist-worn accelerometry, processed with the open-source GGIR software pipeline that has become a standard in large-scale sleep research. From the raw acceleration data, the team derived two key parameters: device-measured sleep duration and sleep efficiency, the latter defined as the share of the sleep period spent genuinely asleep rather than awake. Sleep efficiency is a particularly interesting metric because it captures sleep continuity—how fragmented a night of sleep is—rather than simply how long a person remains in bed. Two people can each log eight hours of sleep opportunity, yet one may sleep soundly through the night while the other wakes repeatedly, and accelerometry can distinguish between them in a way that morning questionnaires often cannot.

Subjective sleep quality was captured with the Pittsburgh Sleep Quality Index, one of the most widely used self-report instruments in sleep science. The researchers also constructed a multidimensional sleep health score, an approach that reflects a growing consensus in the field, formalized in a 2025 American Heart Association scientific statement, that sleep should be evaluated as a constellation of dimensions—duration, continuity, timing, quality, and regularity—rather than as a single number. This composite combined device-measured and self-reported sleep dimensions into one index of overall sleep health, testing the idea that the whole sleep profile might matter more for the brain than any individual component.

Cognitive function, meanwhile, was assessed with the Cambridge Neuropsychological Test Automated Battery, or CANTAB, a computerized assessment platform administered at each of the three time points. Rather than reporting a single global cognition score, the researchers computed composite z-scores for four distinct domains: short-term memory, long-term memory, executive function, and processing speed. This domain-specific approach matters because cognitive ageing is not uniform. Different neural systems decline at different rates and respond differently to lifestyle factors, and a global score can mask a real association in one domain by diluting it across others. Executive function, in particular, is known to be among the earliest and most consequential casualties of unhealthy ageing, underpinning the daily planning and self-regulation that keep older adults independent.

The statistical core of the study was a series of linear mixed-effects models, which are well suited to longitudinal data because they can handle repeated measurements within the same individuals while treating sleep characteristics as time-varying predictors. In practical terms, the models asked whether, when a participant’s sleep efficiency was higher than their own typical level, their executive function was also better than their own typical level. The models were adjusted for a careful set of potential confounders: age, sex, educational level, living situation, and total physical activity—the last of which is important because physical activity influences both sleep and cognition and could otherwise masquerade as a sleep effect. The team also tested sleep-by-time interactions to determine whether any association strengthened or weakened across the two-year follow-up.

The results were, in a word, selective. Sleep duration showed no significant association with any of the four cognitive domains. Subjective sleep quality, as measured by the Pittsburgh index, was likewise unrelated to cognition. Even the multidimensional sleep health score—the most sophisticated sleep measure in the analysis—failed to predict performance in any domain. Only sleep efficiency rose to significance, and only for executive function: higher efficiency was associated with better executive performance. The researchers ran sensitivity analyses using wake after sleep onset, essentially the inverse of sleep efficiency, and observed a comparable pattern, lending confidence that the finding was not an artifact of how the variable was defined. Crucially, the sleep-by-time interactions were not significant, meaning the association between sleep efficiency and executive function remained stable across all three measurement waves rather than emerging or fading over time.

Why would sleep continuity matter for executive function when sleep duration and subjective quality do not? The authors’ finding aligns with a broader literature suggesting that fragmented sleep may be more disruptive to prefrontal-dependent processes than shortened sleep. Executive functions are exquisitely sensitive to the quality of prior-night sleep, and sleep fragmentation is known to blunt the slow-wave and spindle activity that supports overnight neural restoration. It is also plausible that the association is bidirectional: emerging evidence, including studies cited in the paper, indicates that preclinical cognitive decline can itself disturb sleep, so reduced sleep efficiency might be an early signal of brain change rather than a cause of it. The null findings for duration and subjective quality echo recent meta-analytic work showing weak and inconsistent links between those measures and cognition in healthy older adults, and they caution against overinterpreting the popular narrative that sleeping longer automatically protects the ageing brain.

The study’s limitations are worth keeping in view. The sample of 233 adults, while well characterized, was relatively healthy and community-dwelling, mean age 68.3 years, and two years of follow-up may be too short to capture the slow accumulation of sleep-related risk for dementia. Accelerometry, for all its objectivity, estimates sleep from movement and cannot stage sleep or detect the micro-architecture that polysomnography reveals. And as the authors note, observational associations—however carefully adjusted—cannot establish causation. Still, the stability of the sleep efficiency–executive function link across repeated observations, in a design that combined objective and subjective measurement with domain-specific cognitive testing, makes this one of the more informative contributions to a debate that matters to millions of ageing adults.

For the public, the takeaway is refreshingly modest and actionable. Rather than fixating on hitting a magic number of hours, the evidence points toward protecting the continuity of sleep—minimizing the night-time awakenings that erode efficiency—as the sleep dimension most plausibly connected to the executive brain in later life. For researchers, the study is a call to move beyond global cognition scores and single sleep metrics toward multidimensional, longitudinal designs that can isolate which features of sleep, if any, genuinely shape how we think as we age. The full dataset’s GGIR processing code has been made publicly available, and the authors report no competing interests, with the work supported in part by the Research Foundation – Flanders and Australian National Health and Medical Research Council funding.

Subject of Research: Longitudinal associations between multidimensional sleep measures and domain-specific cognitive function in older adults

Article Title: Associations between multidimensional sleep measures and domain-specific cognitive function across repeated observations in adults aged 55 years and older

Article References: Marent, P.-J., Duncan, M. J., Cardon, G., Albouy, G., & van Uffelen, J. (2026). Associations between multidimensional sleep measures and domain-specific cognitive function across repeated observations in adults aged 55 years and older. GeroScience. https://doi.org/10.1007/s11357-026-02518-y

Image Credits: AI Generated

DOI: 10.1007/s11357-026-02518-y

Keywords: sleep efficiency, executive function, cognitive ageing, actigraphy, sleep health, older adults, CANTAB, sleep duration, sleep quality, longitudinal study, GeroScience, accelerometry

The review, published in the Journal of Activity, Sedentary and Sleep Behaviors, was led by Denver M. Y. Brown of Kansas State University together with colleagues from institutions across North America. The team searched eight databases from their inception through late 2023, supplemented by forward and backward citation searches, a manual scan of the International Network of Time-Use Epidemiologists’ publication list, and direct consultation with experts. From 7,212 identified records, 102 observational studies met the strict inclusion criteria: each had to use CoDA with log-ratio transformations, capture all three movement behaviors across the full 24-hour day, and test associations with indicators of physical, cognitive, or mental health. The studies, published between 2016 and 2024, drew on samples from 29 countries, with analytic samples ranging from just 28 participants to more than 130,000, and participant ages spanning from infancy to late adulthood.

To make sense of such a heterogeneous literature, the researchers classified reporting practices into seven domains: methodological justification, behavioral measurement and data handling, composition construction, analytic plan, composition-specific descriptive statistics, model results, and auxiliary information. The extraction framework was reviewed by eleven international experts and drew on existing reporting checklists such as STROBE, designed for observational epidemiology, and CREMAS, developed for ecological momentary assessment studies. Each study was also scored with an adaptation of the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-sectional Studies, yielding a sobering baseline: 81 of the 102 studies were rated fair quality, 19 good, and two poor.

The brightest spot was methodological justification. Nearly every study, 100 of 102, mentioned CoDA in the title or abstract, and 94 explained why a compositional approach was appropriate for 24-hour time-use data. This is more than academic housekeeping. Because the 24-hour movement paradigm remains unfamiliar to many journal audiences, clear justification helps readers grasp why the co-dependency of behaviors demands special statistical treatment. It also aids discoverability: when authors flag CoDA prominently, systematic searches can actually find these studies, a prerequisite for any future synthesis of the evidence.

Beyond that strong opening, the picture fragments. In the measurement domain, most studies did describe how accelerometer data were scored and processed for each behavior, where devices were worn, how many minutes constituted a valid day, and how many valid days were required. Yet only 44 of the 90 device-based studies clearly stated which valid days entered the analysis, whether averages across all days, random selections, or weighted combinations of weekdays and weekends. That omission matters: recent work has shown that different data-handling strategies can materially change conclusions about how movement behaviors relate to obesity. Sleep fared worst of all. Only about half the studies clearly conceptualized what sleep they were measuring, whether nocturnal sleep, 24-hour sleep, or daytime naps, and fewer than 40 clearly defined the sleep variable itself. Only 17 studies explicitly included naps in the composition, and in 44 studies it was simply unclear. Without sleep logs, daytime sleep captured by accelerometers risks being misclassified as sedentary time, quietly corrupting the very compositions the analyses depend on.

Composition construction revealed similarly troubling gaps. All 102 studies reported how many parts the day was partitioned into, most commonly four: sleep, sedentary behavior, light physical activity, and moderate-to-vigorous physical activity, with compositions ranging from three parts up to nine. And 101 of 102 reported the log-ratio transformation used. But only six studies specified how a day was defined, midnight-to-midnight versus wake-to-wake, a detail that shapes what the composition actually represents. Most striking, only 27 studies addressed zeros in the behavioral data. Zeros are poison for log-ratio mathematics, since the logarithm of zero is undefined, and how researchers replace them can distort the entire analysis. Encouragingly, of the 19 studies that observed zeros, most used principled methods such as log-ratio expectation maximization imputation or multiplicative replacement, approaches recent methodological work has endorsed over crude substitution.

The analytic plan and results sections showed the deepest inconsistencies, and these are the ones with the greatest consequences for cumulative science. Nearly all studies reported their post-transformation analytic technique and whether covariates were adjusted, but fewer than a third compared their analytic sample to the full sample, and only 15 provided a power analysis, a gap the authors attribute largely to the field’s reliance on secondary data analysis. In the results, only 64 studies reported whether the overall 24-hour composition was significantly associated with the health outcome at all, and just 25 included a standardized effect size such as R-squared. From there, practices diverged into what the authors describe as selective reporting: some studies examined individual behaviors or ran isotemporal substitution models only when the overall model was significant, others ran them regardless, and some never stated whether the overall test was significant. Several studies reported associations for only some components of the composition, omitting exactly the kind of complete, per-behavior estimates that meta-analysis requires.

Isotemporal substitution, the technique that estimates what happens to a health outcome when minutes are swapped between behaviors, was the single most popular analytic approach, appearing in 84 studies. Here, reporting was somewhat better: 83 of the 84 studies clearly stated whether substitutions were one-to-one, such as ten minutes of sitting replaced by ten minutes of brisk walking, or proportional, where reallocated time is spread across all other behaviors. Most reported model statistics with confidence intervals or standard errors. Yet even here, roughly half only examined reallocations for outcomes already found significant, and 15 reported substitutions for only a subset of behaviors. Auxiliary reporting told a similar story of selective diligence: funding sources and conflicts of interest were almost universally disclosed, likely driven by journal requirements, but only 16 studies acknowledged the limitations of CoDA itself, and only 22 discussed whether their effect sizes were clinically meaningful, a crucial question when translating compositional proportions back into actionable minutes of activity.

The stakes of this inconsistency extend well beyond academic tidiness. The 24-hour movement paradigm underpins integrated guidelines now adopted across multiple countries for children, adults, and older adults, and it increasingly informs public health policy about how we should structure our days. If individual studies cannot be compared, and if selective reporting blocks the extraction of complete effect estimates, the field cannot perform the meta-analyses needed to establish robust, population-level conclusions about the optimal distribution of sleep, sitting, and movement. The review’s authors point to a proven path forward: the CREMAS checklist for ecological momentary assessment was born from exactly this kind of systematic characterization of existing practices, and they propose a similar route for CoDA, using Delphi methodology, an iterative consensus process among experts and end-users, to develop a formal reporting checklist for observational compositional studies. They also caution that their conservative approach, counting unmentioned items as unreported, may underestimate actual practice, and that emerging techniques will require the standards to evolve. Still, the message is unambiguous. A field that has grown from two studies in a 2020 systematic review to more than a hundred in under a decade now needs to grow up statistically: consistent, transparent, and complete reporting is the price of turning a promising method into trustworthy evidence about how the whole 24-hour day shapes human health.

Subject of Research: Reporting practices in observational studies using compositional data analysis to examine associations between 24-hour movement behaviors and health indicators

Article Title: A systematic review of research reporting practices in observational studies examining associations between 24-h movement behaviors and indicators of health using compositional data analysis

Article References: Brown, D. M. Y., Burkart, S., Groves, C. I., Balbim, G. M., Pfledderer, C. D., Porter, C. D., Laurent, C. S., Johnson, E. K., & Kracht, C. L. (2024). A systematic review of research reporting practices in observational studies examining associations between 24-h movement behaviors and indicators of health using compositional data analysis. Journal of Activity, Sedentary and Sleep Behaviors, 3(1), Article 23. https://doi.org/10.1186/s44167-024-00062-8

Image Credits: AI Generated

DOI: 10.1186/s44167-024-00062-8

Keywords: compositional data analysis, 24-hour movement behaviors, physical activity, sedentary behavior, sleep, systematic review, reporting practices, time-use epidemiology, isotemporal substitution, accelerometry, research methods, public health

The stakes are surprisingly high for such a young age group. International guidelines recommend that toddlers accumulate at least 180 minutes of physical activity per day, including structured activity, while limiting restraint and screen time and securing 11 to 14 hours of good-quality sleep within every 24-hour period. Yet the evidence suggests most toddlers fall dramatically short. In an Australian study cited by the research team, fewer than 9 percent of toddlers met the full suite of national 24-hour movement guidelines for the early years. While 96.5 percent met the physical activity target and 79.7 percent met the sleep target, a mere 11.4 percent stayed within recommended sedentary screen time limits. Data from Singapore tell a similar story: around 82 percent of toddlers met sleep recommendations, but only about half met physical activity guidelines and fewer than 39 percent stayed within screen time limits. Canadian studies echo the pattern, with adherence to sleep and activity guidelines generally high but the majority of two-year-olds exceeding screen time recommendations.

Why does this matter so much? Because the early years are a period of extraordinary neural plasticity, when the foundations of motor competence, cognition, and emotional regulation are laid down. Research shows that toddlers’ gross motor skills are positively associated with cognitive development, and that shorter naps combined with a higher proportion of nighttime sleep correlate with better cognitive outcomes. Conversely, the prevalence of below-average motor skills in young children appears to be higher than normative samples would predict—a red flag that targeted developmental programmes can potentially address, since studies have shown such programmes can improve gross motor skills in toddlers. Music, meanwhile, is far more than entertainment at this age. When caregivers receive music training, children in their care show increased visual, vocal, and physical engagement, and music training in kindergartens has been shown to improve inhibitory control, a core executive function. Musical workshops built around sound-producing objects have been found to enhance toddlers’ natural exploratory drive.

Despite this converging evidence, no study to date has evaluated a holistic programme in early childhood education and care settings that integrates physical activity, sedentary behaviour, sleep, and motor and musical skills simultaneously. That gap is what MoviMusi is designed to fill. The trial will run over 24 months in the capital cities of three Spanish regions—Valencia, Murcia, and Toledo—chosen because they reflect the diversity of the Spanish educational system. In total, 24 public early childhood education and care centres will participate, split evenly between an intervention group and a control group: five centres per arm in Valencia, four per arm in Murcia, and three per arm in Toledo. With an average class size of 13 toddlers, this translates to roughly 312 children, distributed as 130 toddlers in Valencia, 104 in Murcia, and 78 in Toledo.

The trial’s design reflects the statistical realities of studying children in group settings. Because children within the same classroom behave more similarly to one another than to children in other classrooms—an effect quantified by an intraclass correlation—the researchers used cluster-randomisation formulas to calculate their sample. They powered the study to detect an expected increase of 8 minutes of moderate-to-vigorous physical activity per school day, building on their own previous accelerometry work showing that children aged two to three accumulate about 40 minutes of such activity during childcare hours. With a significance level of 5 percent, 90 percent statistical power, and an intraclass correlation of 0.35, 24 centres emerged as the required sample. Randomisation will occur only after baseline measurements are complete, at the end of the first year, performed by an independent researcher using a computer-generated sequence—a blinded procedure that protects against allocation bias.

What makes MoviMusi genuinely distinctive is its participatory philosophy. Rather than imposing a rigid, top-down curriculum, the researchers will work with each intervention centre’s principals, educators, and families to co-design a programme tailored to that centre’s specific realities. Previous research suggests these horizontal, dialogic interventions are more effective at changing school culture around physical activity than vertical, prescriptive ones. The programme unfolds along three axes. First, training: educators and families attend seminars and workshops on promoting physical activity as healthy behaviour and using music as a didactic resource. Second, participation: over two months, each institution designs its own movement and music programme, supported by baseline data on the personal, social, and environmental correlates of the children’s movement behaviours. Third, implementation: the specific actions run for six months, after which the team evaluates effectiveness against the control group, whose centres continue their usual curriculum.

The measurement toolkit is remarkably comprehensive for a population so young. Children will wear ActiGraph wGT3X-BT accelerometers on their right hip for one full week, from waking to bedtime, with data processed in 15-second epochs and scored using validated cutoffs for two-year-olds. Sleep will be captured through the Spanish-adapted Brief Infant Sleep Questionnaire, supplemented by teacher-recorded nap times during school hours. Motor skills will be assessed with the Peabody Developmental Motor Scales, third edition, a standardised instrument validated for Spanish children from six months to five years. Musical skills will be measured with MUSKITO—a new scale the research team itself is developing—covering listening, singing, instrumental interpretation, improvisation or composition, and movement. Direct observation during unstructured outdoor play will use a modified version of the OSRAC-P system, in which trained coders record a child’s activity state every 25 seconds in five-second observation windows, with intercoder reliability verified using Cohen’s kappa.

Beyond the child-level outcomes, the study casts a wide net across the entire educational ecosystem. Researchers will assess the quality of each centre using the Infant/Toddler Environment Rating Scale, measure playground area and density using satellite imagery and geographic information systems, and classify playgrounds as low or high density based on free space per child. Parents will complete validated questionnaires on their children’s after-hours activity, screen time, and modes of transport to school, alongside a dedicated scale measuring barriers to active commuting. Focus groups with educators and families, conducted at baseline and after implementation, will probe perceptions of barriers and facilitators to embedding movement and music in daily practice. The team will even analyse official curriculum documents to understand how public authorities promote—or fail to promote—movement and music in early childhood education, and will invite education authorities to result-dissemination meetings.

The researchers are candid about the challenges ahead. Interventions must respect each centre’s internal culture rather than dictate activities; family engagement with questionnaires cannot be taken for granted; accelerometer data will inevitably be lost to the absences that are common in toddler classrooms; and coordinating a project across three cities with different administrative rhythms demands dedicated local leads. The statistical plan anticipates these realities, using mixed-effects longitudinal models that adjust for baseline values, age, sex, and body mass index, with random effects for cities, groups, and participants, and multiple imputation for missing data handled by a blinded analyst. Ethical approval has been granted by the University of Valencia’s ethics committee, and written informed consent will be required from all participating families.

If MoviMusi succeeds, the implications could ripple well beyond the 24 participating nurseries. The team plans to share results at three levels—within each centre, at public events in the three cities, and through an open conference—culminating in a set of good-practice guidelines for promoting movement and music opportunities that could inform curriculum design and teacher training nationally and internationally. The study also answers a call from leading movement-behaviour researchers, who have identified interventions for children under three as a critical frontier. In a world where toddler screen time is quietly eroding the building blocks of healthy development, the idea that songs and structured play, delivered through the everyday curriculum, could shift the trajectory of an entire generation is a proposition worth testing rigorously. MoviMusi is now positioned to deliver exactly that test.

Subject of Research: A cluster-randomised controlled trial of a movement and music programme on movement behaviours and motor and musical skills in toddlers

Article Title: Effectiveness of a movement and music programme on activity, sedentary, and sleep behaviours and motor and musical skills in young children: protocol for the MoviMusi cluster randomised controlled trial

Article References: del Mar Bernabé-Villodre, M., Martínez-Bello, V. E., Vega-Perona, H., Díaz-Barahona, J., García-Ochoa, Y. C., Molines-Borrás, S., Gértrudix-Barrio, F., Montoya-Rubio, J. C., Fernández-Vilar, M. Á., Azorín-Delegido, J. M., Filenko, N., Martínez-Rojas, Á., & Martínez-Bello, D. A. (2024). Effectiveness of a movement and music programme on activity, sedentary, and sleep behaviours and motor and musical skills in young children: protocol for the MoviMusi cluster randomised controlled trial. Journal of Activity, Sedentary and Sleep Behaviors, 3(1), Article 28. https://doi.org/10.1186/s44167-024-00065-5

Image Credits: AI Generated

DOI: 10.1186/s44167-024-00065-5

Keywords: early childhood education, physical activity, sedentary behaviour, sleep, motor skills, musical skills, cluster randomised controlled trial, toddlers, MoviMusi, accelerometry, 24-hour movement guidelines, Spain

The research team, led by Hannah Lundh of the Centre for Physical Activity in Region Västra Götaland and colleagues at the University of Gothenburg, recruited 39 children aged 6 to 12 who had been referred to outpatient paediatric clinics for obesity treatment, along with one parent each. The children, 19 of them girls, had a mean age of 9.7 years and a mean body mass index standard deviation score of 3.0, indicating severe obesity relative to Swedish reference populations. Their parents, 20 of them mothers, averaged 42.2 years of age. Fifty-seven percent of the parents were born in Sweden, 16 percent in other European countries, and 27 percent outside Europe, giving the sample a broadly diverse socioeconomic and cultural profile.

Each child-parent pair wore a small Axivity AX3 accelerometer on an elastic belt around the waist, positioned over the right hip close to the body’s centre of mass, for seven consecutive days and nights. The devices sampled movement at 50 Hz with an acceleration range of plus or minus 8 g, and participants kept diaries of bedtime, waking time, cycling, water activities and strength training to help researchers identify sleep and non-wear periods. A valid day required at least 10 hours of wear time, and a valid week required at least two such days — a deliberately lenient threshold that sensitivity analyses showed made no difference compared with the traditional four-day requirement, but which maximised the number of pairs that could be included.

The data processing was where the study distinguished itself technically. Rather than applying conventional low-pass filters that can misclassify vigorous movement as noise, the team used the 10 Hz Frequency Extended Method, which has been shown in calibration work to capture higher-intensity activity more faithfully. Data were reduced into 3-second epochs, a window short enough to register the brief, sporadic bursts that characterise children’s movement. Perhaps most notably, the researchers set the cut-point for moderate-to-vigorous physical activity at 4 metabolic equivalents rather than the traditional 3 METs, arguing that 3 METs corresponds to a slow walking pace of just 3 to 4 kilometres per hour and shows minimal association with cardiometabolic health, whereas clinically meaningful benefits begin around 4 METs, roughly a brisk walk of 4 to 5 kilometres per hour. Cut-points of 52 mg and 388 mg for children and 39 mg and 331 mg for adults marked the boundaries between light activity and moderate-to-vigorous activity.

The headline numbers were sobering. Children spent an average of 9.8 hours per day in sedentary behaviour and just 0.7 hours — about 42 minutes — in moderate-to-vigorous activity, with another 3.9 hours in light activity. Their parents sat even longer, averaging 12.3 sedentary hours daily, with only 0.3 hours of moderate-to-vigorous activity and 3.4 hours of light activity. Only six of the 39 children, or 15 percent, met the World Health Organization recommendation of at least 60 minutes of moderate-to-vigorous activity per day for ages 5 to 17. Among parents, the picture was bleaker still: just two of 38, or 5 percent, achieved the adult guideline of 150 minutes of moderate activity per week.

The central analytical question was whether children’s and parents’ behaviours tracked together within each pair. Using intraclass correlation coefficients in two-way mixed-effect models, the team found a statistically significant but weak correlation for sedentary time, with an ICC of 0.14 and a p-value of 0.017. By the conventional interpretation scheme of Koo and Li, any value below 0.5 counts as weak, so the shared sitting habit was real but modest. The correlation for light activity was stronger, at 0.24, but fell just short of significance with a p-value of 0.050. For moderate-to-vigorous activity, the correlation was weaker still, at 0.11, and clearly non-significant. Bland-Altman plots visualising the within-pair differences showed enormous variability: some pairs moved in near lockstep, while others diverged dramatically.

Interestingly, the generations differed systematically in how they spent their days. Children accumulated significantly more moderate-to-vigorous activity than their parents — a mean paired difference of roughly 27 minutes per day — while parents sat significantly more than their children. This inversion of the intuitive picture, in which adults might be expected to be the more active party, underscores how deeply sedentary adult lifestyles can become even in families actively engaged with paediatric obesity services. It also suggests that children in this clinical population, despite falling far short of guidelines, remain more physically capable of spontaneous movement than their parents.

The sedentary finding carries particular weight because it contradicts much of the existing parent-child literature. Previous systematic reviews, covering predominantly healthy, non-obese children, have generally reported weak to moderate positive associations between parent and child physical activity, and a large meta-analysis found a small effect of parental modelling on children’s activity. Only one of the 65 studies across two major reviews had examined accelerometer-measured associations in an obese paediatric population. The Swedish authors suggest several reasons their results may diverge: earlier studies often relied on self-report, which is prone to bias; many used the lower 3 METs threshold, inflating apparent activity levels; and crucially, previous cohorts tended to include younger children, aged 2 to 10, who are more dependent on their parents and more likely to share their activities. Children aged 6 to 12, by contrast, increasingly move in school and peer contexts their parents never see.

The study’s limitations are candidly acknowledged. The cross-sectional design rules out any causal inference — sitting together may reflect shared environment, modelling, genetic predisposition, or all three. The sample of 39 pairs fell short of the original target of 60, partly because of pandemic-related staffing problems, and no formal power calculation was performed, so a larger sample might have detected significant correlations that here hovered near the threshold of significance, particularly for light activity. The team did not collect parents’ body mass index, which likely influenced parental activity levels given the genetic component of obesity, nor did they record living arrangements, meaning some children may have spent the measurement week with the non-participating parent. Selection bias is also possible, since families with positive attitudes toward activity may have been more willing to enrol.

Still, the implications for treatment are concrete. The WHO recommends family-based, multi-professional interventions as first-line treatment for childhood obesity, and the Swedish physical activity on prescription model places parental involvement at its core. If sedentary time is the one behaviour where parent and child genuinely mirror each other, the authors argue, then interventions for this population might profitably begin by targeting sitting time together — a change that over time could open the door to increased activity — while recognising that role modelling through parental exercise may matter more for some families than others. Facilitating access to activity opportunities, initiating outings and offering encouragement may ultimately prove more powerful levers than a parent’s own workout routine. Larger samples, other settings and longitudinal designs, the researchers conclude, are needed to untangle whether shared sedentary habits are cause, consequence or coincidence in the trajectory of childhood obesity.

Subject of Research: Parent-child associations in accelerometer-measured physical activity and sedentary behaviour among children with obesity

Article Title: Physical activity and sedentary behaviour amongst children with obesity – exploring cross-sectional associations between child and parent

Article References: Lundh, H., Arvidsson, D., Greven, C., Fridolfsson, J., Börjesson, M., Boman, C., Lauruschkus, K., Lundqvist, S., Melin, K., & Bernhardsson, S. (2025). Physical activity and sedentary behaviour amongst children with obesity – exploring cross-sectional associations between child and parent. Journal of Activity, Sedentary and Sleep Behaviors, 4(1), Article 2. https://doi.org/10.1186/s44167-025-00072-0

Image Credits: AI Generated

DOI: 10.1186/s44167-025-00072-0

Keywords: childhood obesity, physical activity, sedentary behaviour, accelerometry, parent-child dyads, moderate-to-vigorous physical activity, paediatric health care, Sweden, family-based intervention, intraclass correlation, WHO guidelines, behavioural modelling