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 research team, led by Marion Denos and Abhibhav Sharma of the HUNT Center for Molecular and Clinical Epidemiology at the Norwegian University of Science and Technology, together with collaborators at the University of Bristol’s MRC Integrative Epidemiology Unit, quantified 132 lipoprotein subfractions and metabolites using nuclear magnetic resonance spectroscopy. This technique exploits the magnetic properties of hydrogen nuclei to fingerprint the chemical composition of a blood sample without destroying it, allowing researchers to measure cholesterol content within very low-density lipoprotein (VLDL), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) particles of different sizes, along with fatty acids, albumin, and other small molecules. The participants came from the Trøndelag Health Study (HUNT3) in Norway, with 16,877 individuals, and the UK Biobank, with 480,840 individuals — a combined dataset large enough to detect even modest associations between blood chemistry and future cancer diagnoses.

During a mean follow-up of 14 years, 549 women and 741 men in HUNT3 and 12,112 women and 14,749 men in the UK Biobank developed one of the four cancers under study. The researchers used Cox regression, a statistical framework that models the hazard of an event over time while adjusting for confounders such as age, sex, body mass index, and smoking, to estimate the association between each metabolite and each cancer type. The results were expressed as hazard ratios per one-standard-deviation increment in metabolite level — a technical way of asking how much the risk of cancer changes for a typical step up in a given blood chemical.

The most striking findings concerned lung cancer. In the UK Biobank, higher levels of several subfractions of VLDL and LDL were associated with a decreased incidence of lung cancer. Cholesterol in large LDL particles, for example, showed a hazard ratio of 0.84 per 1-SD increment (95% confidence interval 0.81–0.87), meaning that each typical step up in this measure corresponded to roughly a 16 percent lower risk of being diagnosed with lung cancer during follow-up. Similar inverse associations were observed for albumin and some fatty acids. The consistency of the direction of effect across multiple related lipoprotein measures — rather than a single isolated signal — suggests the pattern is not a statistical fluke, although the authors are careful to note that association does not imply causation.

For prostate cancer, the second cancer type to show associations, higher levels of several lipoprotein subfractions were likewise linked to a decreased incidence in the UK Biobank. Breast and colorectal cancer, by contrast, showed no clear associations with any of the 132 metabolites measured. This asymmetry is itself informative: it suggests that the metabolic signatures detectable in routine blood samples may be more relevant to lung and prostate carcinogenesis than to breast or colorectal tumors, or that the associations for the latter are too weak or too heterogeneous to be captured even at this scale.

Perhaps the most sobering result, however, is what did not replicate. In HUNT3, the Norwegian cohort, no clear associations were observed between any metabolite and any of the four cancers. The authors point out that the observed associations showed the same direction of effect across cohorts, despite not reaching statistical significance in HUNT3. This discrepancy has several plausible technical explanations. HUNT3 is roughly 30 times smaller than the UK Biobank, so its statistical power to detect hazard ratios of 0.84 or similar modest effect sizes is limited. Differences in age structure, follow-up duration, smoking prevalence, and background cancer incidence between the Norwegian and British populations may also attenuate or shift the signals. And because the study measured metabolites at a single time point, reverse causation — the possibility that preclinical disease alters blood chemistry rather than the other way around — cannot be excluded, although the prospective design, with metabolites measured years before diagnosis, makes this less likely than in cross-sectional studies.

The biological interpretation of the inverse lung cancer associations is equally complex. Lipoproteins are best known for their role in cardiovascular disease, where higher LDL cholesterol is harmful. In cancer, the picture may differ. Lipoprotein particles transport lipids that cells need for membrane synthesis and signaling, and tumor cells are voracious lipid consumers. Some researchers have proposed that the lipid transport capacity of the circulation could influence tumor growth, while others note that lipoproteins also carry antioxidants and modulate immune function. Albumin, which showed similar inverse associations with lung cancer, binds fatty acids, drugs, and countless other molecules, and its concentration reflects nutritional status, liver function, and systemic inflammation. Disentangling which of these mechanisms — if any — drives the observed associations will require studies beyond observational epidemiology.

This is where the study’s design points to the next frontier. Because the same 132 metabolites can be measured cheaply and rapidly by NMR spectroscopy in routine clinical samples, the findings highlight promising directions for future research into metabolic biomarkers and their potential role in cancer prevention. If the inverse associations with lung cancer reflect a genuine protective metabolic state, metabolite profiles could eventually complement existing risk models — which currently rely heavily on age, smoking history, and family history — to identify individuals who might benefit from intensified screening such as low-dose CT. But the authors are explicit that their results do not yet support clinical action: no specific lipid or metabolite profile was associated with the most common cancers overall, and the lung cancer signals, while consistent in direction, require replication and mechanistic validation before they can inform prevention strategies.

The study also illustrates the power and the pitfalls of modern biobank-scale epidemiology. With 480,840 participants in the UK Biobank alone, the statistical machinery can detect hazard ratios far below the threshold of clinical interest, and the sheer number of metabolite-cancer pairs tested — 132 metabolites across four cancer types in two cohorts — raises the specter of multiple testing, where some associations will appear significant by chance alone. The researchers addressed this by examining patterns across related measures rather than isolated signals, and by requiring consistency of direction across cohorts. The fact that the HUNT3 signals pointed the same way, even when not statistically significant, offers a form of directional replication that is more meaningful than a single p-value, but it also underscores how much larger, longer, and more diverse studies will be needed to settle the question.

For now, the take-home message is one of cautious optimism. Blood metabolites, measured by a technique that is fast, inexpensive, and increasingly available, show reproducible patterns of association with lung cancer incidence at biobank scale — patterns that could, with further research, illuminate the metabolic biology of carcinogenesis and point toward new prevention targets. The absence of associations for breast, prostate, and colorectal cancer in this analysis does not rule out metabolic involvement in those diseases; it may simply mean the relevant signals are weaker, later-emerging, or masked by the confounders that observational studies must statistically adjust for. As the authors conclude, their results highlight promising directions for future research into metabolic biomarkers and their potential role in cancer prevention — a reminder that the chemical diary written in our blood may hold clues to cancer risk that we are only beginning to read.

Subject of Research: Cancer

Article Title: Associations between circulating metabolites and incidence of breast, prostate, lung and colorectal cancers in the HUNT Study and UK Biobank

Article References: Denos, M., Sharma, A., Åsvold, B. O., Arham, A. G. A., Smith, G. D., Timpson, N. J., Løset, M., Brumpton, B. M., Debik, J., & Giskeødegård, G. F. (2026). Associations between circulating metabolites and incidence of breast, prostate, lung and colorectal cancers in the HUNT Study and UK Biobank. BMC Cancer. https://doi.org/10.1186/s12885-026-16957-5

Image Credits: AI Generated

DOI: 10.1186/s12885-026-16957-5

Keywords: metabolomics, lipoproteins, lung cancer, cancer prevention, NMR spectroscopy, UK Biobank, HUNT Study, biomarkers, epidemiology, BMC Cancer, Associations, between

The study, published in the Journal of Activity, Sedentary and Sleep Behaviors, set out to answer a deceptively simple question: do people with diabetes who struggle to sleep actually move less? Previous research had already established that insomnia symptoms are remarkably common in this population, with roughly 39 percent of adults with type 2 diabetes reporting them. It was also known that poor sleep is linked to weight gain, disrupted glucose regulation, and impaired daytime functioning. But no one had yet measured, with objective devices, whether insomnia translates into measurably lower physical activity in people with diabetes. That gap mattered, because regular moderate-to-vigorous physical activity is a cornerstone of diabetes care, helping to control blood sugar, prevent complications, and reduce the risk of premature death.

To capture what participants actually did, rather than what they said they did, the researchers relied on a sophisticated measurement setup. Each participant wore two small tri-axial accelerometers for seven days, one strapped to the right thigh and another to the lower back. The devices sampled movement at 50 hertz, and a machine learning classifier built on eXtreme Gradient Boosting was trained to recognize specific activities in free-living conditions: walking at slow, moderate, or brisk speeds, running, cycling, sitting, standing, and lying down. From these data, the team calculated total physical activity, which includes all walking speeds, and moderate-to-vigorous physical activity, defined as brisk walking above 4 kilometers per hour, running, and cycling. This approach sidesteps the well-known biases of self-reported exercise questionnaires, which tend to overestimate how active people really are.

Insomnia was assessed through four questions covering difficulty falling asleep, repeated nighttime awakenings, waking too early, and impaired daytime functioning, each rated over the previous three months. Participants who reported at least one sleep symptom three or more nights per week were classified as having insomnia symptoms, while those who also reported daytime impairment at that frequency met the criteria for insomnia disorder, mirroring current diagnostic classification systems. Of the 1,354 participants analyzed, 36 percent had insomnia symptoms and 3 percent met the stricter threshold for insomnia disorder. The median age was 67 years, and the sample reflected the realities of living with diabetes: many participants with sleep problems were also more likely to be obese, to suffer from bodily pain, and to report moderate to severe physical impairment.

The headline result concerns older women. Among women aged 65 and above, those with insomnia symptoms accumulated 73 minutes less total physical activity per week than their peers without sleep complaints, a difference of roughly ten minutes a day. Their moderate-to-vigorous activity was reduced by 33 minutes per week, equivalent to only four to five minutes a day, but the gap in overall movement was substantial. Just 28 percent of older women with insomnia symptoms met the World Health Organization’s recommendation of at least 150 minutes of moderate activity per week, compared with 26 percent of those without symptoms in the same age band, and 43 percent among younger women. Men, by contrast, showed no meaningful difference in activity levels whether or not they reported insomnia symptoms, and neither did women under 65.

The picture sharpened dramatically for the small group with full-blown insomnia disorder. Regardless of age or sex, these participants moved far less than everyone else. Women with insomnia disorder logged 192 minutes less total physical activity per week than those sleeping well, while men logged 276 minutes less, a deficit of nearly an hour a day. Moderate-to-vigorous activity was lower by 37 minutes per week in women and 67 minutes per week in men. Because total physical activity includes slow walking while moderate-to-vigorous activity does not, the pattern suggests that people with insomnia disorder rely almost entirely on gentle movement, with the energetic activity that benefits glucose control largely absent from their weeks.

Why would sleepless nights hit older women hardest? The researchers point to a convergence of biological and social factors. Compared with men, older women tend to take longer to fall asleep, sleep for shorter periods, and report more daytime sleepiness. The postmenopausal stage of life brings its own burden of symptoms, including insomnia, fatigue, joint pain, and depression, any of which can make physical activity feel out of reach. There is also a broader context of inequity: women with type 2 diabetes appear to benefit less than men from lifestyle interventions and drug treatments, and are often undertreated. The authors caution that their cross-sectional design cannot determine whether insomnia causes inactivity, whether inactivity worsens sleep, or whether both stem from shared causes such as pain, obesity, or depression.

The clinical implications may be larger than the raw numbers suggest. Recent research has shown that even brief bouts of one to five minutes of vigorous daily activity, so-called vigorous intermittent lifestyle physical activity, can confer measurable health benefits, meaning that a few extra minutes of brisk movement each day could matter for glucose control, physical function, mood, and quality of life. Conversely, an experimental study in the general population found that a four-week behavioral treatment for insomnia improved sleep significantly but did not change device-measured physical activity, a sobering result that highlights how much remains unknown. Whether treating insomnia in people with diabetes would actually get them moving more is a question only prospective trials can answer, and the reverse possibility, that boosting activity improves sleep, is equally plausible.

The study has caveats worth keeping in mind. Only 37 participants met the criteria for insomnia disorder, so those estimates carry wide uncertainty, and the true prevalence is likely underestimated because the daytime impairment criterion was strict. Volunteers who agree to wear accelerometers for a week tend to be healthier than the general diabetic population, which may inflate measured activity levels. The researchers could not distinguish between types of diabetes, though type 2 accounts for 85 to 90 percent of cases in high-income countries, making the findings most relevant to that group. A single week of measurement may also not capture habitual behavior. Still, the overall adherence rate of about 40 percent to WHO activity guidelines matches similar studies in Denmark, lending credibility to the sample.

What emerges is a clear signal for clinicians and researchers alike: sleep deserves a place in the conversation about diabetes management, particularly for older women. With more than 60 million people in Europe living with diabetes, and only a minority meeting activity recommendations, identifying modifiable barriers is a public health priority. The Norwegian team suggests that future work should examine what distinguishes people with insomnia symptoms who still manage to stay active, and whether addressing insomnia, especially insomnia disorder, as part of routine diabetes care can lift activity levels and, with them, long-term health outcomes. For now, the message is that a restless night in an older woman with diabetes may be more than an inconvenience; it may be a quiet warning sign that her body is moving less than it needs to stay well.

Subject of Research: The association between insomnia symptoms and device-measured physical activity in adults with diabetes

Article Title: Assessing the level of device-measured physical activity according to insomnia symptoms in 1,354 individuals with diabetes: the HUNT Study, Norway

Article References: Mortensen, S. R., Mork, P. J., Skou, S. T., Kongsvold, A., Åsvold, B. O., Nilsen, T. I. L., & Skarpsno, E. S. (2024). Assessing the level of device-measured physical activity according to insomnia symptoms in 1,354 individuals with diabetes: the HUNT Study, Norway. Journal of Activity, Sedentary and Sleep Behaviors, 3(1), Article 27. https://doi.org/10.1186/s44167-024-00066-4

Image Credits: AI Generated

DOI: 10.1186/s44167-024-00066-4

Keywords: diabetes, insomnia, physical activity, HUNT Study, accelerometers, sleep, type 2 diabetes, moderate-to-vigorous physical activity, older women, WHO guidelines, Norway, cross-sectional study