The study, led by Gunchmaa Nyam of Deakin University’s Institute for Physical Activity and Nutrition, drew on baseline data from the TransformUs Secondary effectiveness trial, collected between August 2023 and December 2024. Seven secondary schools across Victoria, Australia, were recruited to capture a diverse mix of government, independent and Catholic schools from metropolitan and regional areas. Of 545 students invited, 193 consented to participate, and after strict quality control of accelerometer data and questionnaire responses, the final analytical sample comprised 124 adolescents aged 13 to 17, with a mean age of 14.8 years. Roughly half of the participants were male, and participants wore wrist-mounted ActiGraph GT9X accelerometers for seven consecutive days, 24 hours a day, providing an objective record of how every minute of their day was spent.

The technical rigour of the measurement is central to the study’s credibility. Accelerometer data were processed using the GGIR package in R, which performed automatic calibration, detection of non-wear time, imputation of invalid data and sleep detection. Participants were only included if they provided at least 16 hours of valid wear time on at least three days, and sleep was estimated using an automated algorithm based on wrist movement variability. Movement intensities were classified using validated age-specific thresholds: sedentary time below 35.6 milligravities, light physical activity between 35.6 and 201.4, moderate activity up to 707.0, and vigorous activity above that. On average, participants accumulated 6.0 valid days of wear, with the devices covering 68 percent of each 24-hour period — a level of objective detail that sidesteps the recall errors and social desirability bias that plague self-reported activity questionnaires.

What the devices revealed was a portrait of modern adolescence that few families would find surprising. On average, the teenagers spent 680.9 minutes — nearly 11.3 hours, or 47.3 percent of the day — in sedentary behaviour. Sleep accounted for 473.0 minutes, or about 7.8 hours. Light physical activity filled 250.7 minutes, roughly four hours, while moderate-to-vigorous physical activity, the intensity most public health guidelines emphasise, occupied a mere 35.3 minutes — just 2.5 percent of the day, and well short of the 60 minutes daily recommended by the Australian 24-Hour Movement Guidelines. The authors note that fewer than 5 percent of Australian adolescents meet all three movement guidelines, a statistic that underscores how far typical routines have drifted from what health authorities consider optimal.

To assess wellbeing, the researchers used the EPOCH Measure of Adolescent Wellbeing, a validated 20-item questionnaire capturing five domains of positive psychological functioning: engagement, perseverance, optimism, connectedness and happiness. Unlike traditional mental health measures that focus on symptoms of illness, EPOCH captures flourishing — the hedonic dimensions of wellbeing such as happiness and optimism, and the eudaimonic dimensions such as engagement and perseverance. Students rated each item on a five-point scale from “Almost never” to “Almost always.” The sample reported moderate to high wellbeing overall, with connectedness scoring highest at 4.35, followed by happiness at 3.92, perseverance at 3.62, optimism at 3.61 and engagement at 3.39.

The analytical approach is where the study departs most sharply from previous work. Time-use data are inherently compositional: because there are only 24 hours in a day, an increase in one behaviour necessarily displaces another, and treating each behaviour in isolation — as most earlier studies did — ignores this interdependence. The researchers therefore applied compositional data analysis, or CoDA, transforming the movement behaviour data using isometric log-ratio (ILR) transformations with pivot coordinates before running compositional linear regression models. Each model was rotated so that every behaviour could be examined relative to all the others, and the models were adjusted for age, gender and school-level clustering. The team also performed a compositional time-reallocation analysis, modelling the hypothetical effect of shifting 30 minutes between pairs of behaviours while holding total daily time constant — a realistic, intervention-sized change.

The results were strikingly specific. Greater time spent in light physical activity relative to all other behaviours was significantly associated with higher happiness scores, while greater sedentary time relative to light activity was significantly associated with lower happiness. The reallocation models quantified the trade-off: shifting 30 minutes from sedentary time to light activity was associated with an increase in happiness scores of 0.128 (95 percent confidence interval: 0.034 to 0.222), while the reverse reallocation produced a significant decrease. Perhaps most unexpectedly, neither moderate-to-vigorous physical activity nor sleep showed significant associations with any of the five wellbeing domains, and no movement behaviour was linked to engagement, perseverance, optimism or connectedness.

The absence of an MVPA effect will raise eyebrows, given the extensive literature linking vigorous exercise to adolescent mental health. The authors urge caution in interpretation, however: the small sample size and low variability in MVPA — most participants managed only about half an hour a day — may have limited the statistical power to detect associations. Context may also matter. Evidence from ecological momentary assessment suggests that outdoor or social activity tends to boost positive affect, whereas indoor, solitary or obligatory activity may not, and competitive or compulsive forms of exercise can even induce stress. Accelerometers, for all their objectivity, cannot distinguish whether a burst of vigorous movement came from a joyful game of basketball or a pressured training session — a nuance the authors flag as critical for future research.

The light activity finding, by contrast, fits an emerging picture. Light-intensity movement such as tai chi or yoga has been associated with reductions in anxiety symptoms, and the authors suggest that gentle activity may represent an accessible, attainable and enjoyable form of movement that facilitates relaxation, casual social interaction and emotional regulation. Sedentary time, meanwhile, has been repeatedly linked to psychological distress and lower self-worth, particularly when it is screen-based — although the authors note that sedentary behaviour also encompasses reading and homework, whose effects may differ from passive screen time. A recent compositional meta-analysis found sleep showed the strongest positive relationship with social-emotional outcomes in children and adolescents, making the null sleep finding here another puzzle that only longitudinal work can resolve.

The study has clear limitations: it was cross-sectional, so causality cannot be established; more than 30 percent of the consenting sample was excluded for insufficient accelerometer data, raising the possibility of non-participation bias, although comparisons between included and excluded participants showed no significant differences in wellbeing or demographics; and there is no established threshold for what constitutes a clinically meaningful change in EPOCH scores. Yet the practical message is hard to ignore. If replacing half an hour of sitting with light movement is associated with even a modest happiness gain, then interventions as simple as encouraging movement during class breaks could support adolescent flourishing without demanding heroic feats of exercise. The authors call for longitudinal and intervention studies to confirm the findings — and to capture not just how much adolescents move, but where, why and with whom.

Subject of Research: Associations between 24-hour movement behaviours and domain-specific psychological wellbeing in adolescents

Article Title: Associations between 24-hour movement behaviours and psychological wellbeing in adolescents using compositional data analysis

Article References: Nyam, G., Lander, N., Ayala, A. M. C., Strugnell, C., & Salmon, J. (2025). Associations between 24-hour movement behaviours and psychological wellbeing in adolescents using compositional data analysis. Journal of Activity, Sedentary and Sleep Behaviors, 4(1), Article 21. https://doi.org/10.1186/s44167-025-00094-8

Image Credits: AI Generated

DOI: 10.1186/s44167-025-00094-8

Keywords: adolescent health, physical activity, sedentary behaviour, compositional data analysis, psychological wellbeing, happiness, EPOCH measure, accelerometer, sleep, MVPA, light physical activity, 24-hour movement guidelines

The study, led by Johanna Hänggi of the Swiss Tropical and Public Health Institute and the University of Basel, set out to answer a deceptively simple question: does the way parents divide their waking hours between sitting, moving lightly, and exercising vigorously predict how their children divide the same hours? Previous evidence on this point has been inconclusive. Systematic reviews of children aged six to twelve support the idea that parents model activity for their offspring, particularly in father-son and mother-daughter pairs, but reviews restricted to device-based measurements found only weak positive correlations between parent and child activity. Longitudinal studies, which can reveal whether parental behavior actually shapes children’s behavior over time rather than merely coinciding with it, have been rare, and those that exist often relied on self-reported activity, which is vulnerable to recall errors and the human tendency to overstate virtuous behavior.

The SOPHYA team addressed these gaps with an unusually rigorous design. All children aged six to sixteen born and registered in Switzerland between 1998 and 2007 were eligible, and a random sample was drawn from the national population registry, stratified by birth year to ensure balanced age groups. Baseline assessments took place in 2013 to 2015 and follow-up assessments in 2019 to 2020. Rather than asking families to estimate their own activity, the researchers mailed pre-programmed ActiGraph accelerometers to participants, who wore the devices on the right hip for seven consecutive days while keeping diaries of non-wear periods. To be included, participants needed at least three weekdays of ten hours or more of wear time and at least one weekend day of eight hours, with weekday and weekend data weighted five to two to reflect a full week.

The baseline sample ultimately included 686 mother-child pairs and 373 father-child pairs with valid accelerometer and questionnaire data from the same measurement week, and 337 of those children provided valid follow-up data, yielding 263 mother-child and 149 father-child pairs for the longitudinal analysis. Sedentary behavior was defined as fewer than 100 counts per minute, while moderate-to-vigorous activity thresholds were age-adjusted for children and set at a level corresponding to four metabolic equivalents. Light activity occupied the range in between. From these raw counts the researchers computed each person’s waking movement composition: the proportions of wear time spent sedentary, in light activity, and in moderate-to-vigorous activity.

Analyzing those proportions required a statistical approach suited to compositional data. Because the three behavior categories must sum to the whole of wear time, an increase in one necessarily means a decrease in another, and standard regression techniques that treat each category separately can produce misleading results. The team instead applied Dirichlet regression, a method that preserves the compositional structure of the outcome and directly handles the skewness and heteroscedasticity typical of such data. Parental movement compositions were transformed into additive log-ratios, with sedentary behavior as the reference component, producing two intuitive predictors: the log-ratio of moderate-to-vigorous activity to sitting, and the log-ratio of light activity to sitting. Models were adjusted for the child’s age and sex, parental education, and language region, and the researchers tested whether the associations varied by the child’s age or sex.

The cross-sectional results were consistent across both parents. When mothers replaced sedentary time with moderate-to-vigorous activity, the ratio of that activity to sitting in their children rose in parallel, with a coefficient of 0.10 and a p-value below 0.001; the equivalent paternal coefficient was 0.09 with a p-value of 0.002. Replacing sitting with light activity produced even clearer associations: 0.13 for mothers and 0.09 for fathers, both statistically significant. In plain terms, when mothers or fathers traded sitting for movement of either intensity, their children tended to do the same. Notably, these associations did not depend on the child’s age or sex, suggesting that the link between parental and child movement patterns operates broadly across the six-to-sixteen age range and across both sexes.

The longitudinal findings, though based on a smaller sample, carried the analysis into territory few studies have reached. Five years after the baseline measurement, mothers’ replacement of sitting with light activity still predicted a similar shift in their children, with a coefficient of 0.12 and a p-value of 0.021. The paternal equivalent was directionally similar at 0.10 but fell short of conventional statistical significance at p equal to 0.108, likely reflecting the smaller number of father-child pairs. One intriguing exception emerged: a mother’s shift from sitting to moderate-to-vigorous activity was associated with a larger light-activity response in daughters than in sons, hinting at same-sex modeling dynamics that echo the team’s earlier SOPHYA findings of stronger mother-daughter and father-son activity associations independent of socioeconomic and neighborhood factors.

The effect sizes deserve careful interpretation. When the researchers modeled a parent cutting sedentary time by twenty percent and increasing light activity by the same amount, the predicted change in the child’s light-activity-to-sitting ratio was about eighteen times smaller than the mother’s actual observed shift and about twenty-nine times smaller than the father’s. Children, in other words, move part of the way with their parents but do not mirror them completely. Ternary plots, which display the three movement components as axes of a triangle, illustrated this graphically: parental trajectories from the most sedentary to the least sedentary compositions produced child trajectories in the same direction but of visibly smaller magnitude. The study also found that children’s sedentary share of wear time climbed from about sixty percent at baseline to seventy-three percent at follow-up, underscoring how strongly the adolescent years pull toward sitting.

For public health, the implications point toward family-level intervention design. Because mothers at the low end of sedentary time compensated almost entirely with light activity, while fathers at the low end increased both light and moderate-to-vigorous activity, the authors argue that interventions should not fixate exclusively on vigorous exercise. Light-intensity movement carries documented health benefits for adults and children alike, and the strong, consistent associations within both intensity domains suggest that simply getting parents off the couch and into gentle motion may pay dividends across the whole household. Meta-analytic evidence shows that dyadic interventions targeting shared goals can reduce sedentary behavior, yet programs that address compositional movement patterns remain scarce.

The authors are candid about limitations. The cross-sectional analysis cannot rule out reverse causation, in which active children encourage active parents, and the smaller longitudinal sample limited statistical power, particularly for detecting sex-specific effects among fathers. Sleep was not objectively measured, so the analysis captures only waking behavior rather than the full twenty-four-hour profile, and the findings may not generalize beyond Switzerland’s cultural and socioeconomic context. Attrition bias appears unlikely to distort the results, however, because follow-up participation was not associated with baseline movement composition of either parents or children. The overall message stands: parental movement patterns, and sedentary time in particular, may be effective targets for interventions that benefit parents and children simultaneously, with effects that persist over years rather than fading with the measurement week. As the researchers conclude, integrating family-based strategies into physical activity promotion could yield long-lasting benefits, even if each individual shift is modest.

Subject of Research: Cross-sectional and longitudinal associations between parental and youth movement compositions measured by accelerometry in the Swiss SOPHYA cohort

Article Title: Movement patterns of youth and their parents: cross-sectional and longitudinal associations

Article References: Hänggi, J., Lovison, G., Jeong, A., Dössegger, A., Taube, W., Kayser, B., Suggs, S. L., Bringolf-Isler, B., & Probst-Hensch, N. (2026). Movement patterns of youth and their parents: cross-sectional and longitudinal associations. Journal of Activity, Sedentary and Sleep Behaviors, 5(1), Article 2. https://doi.org/10.1186/s44167-025-00092-w

Image Credits: AI Generated

DOI: 10.1186/s44167-025-00092-w

Keywords: physical activity, sedentary behavior, parent-child dyads, accelerometry, compositional data analysis, SOPHYA cohort, longitudinal study, light physical activity, moderate-to-vigorous activity, youth health, behavioral modeling, Switzerland