Device-measured physical activity, sedentary time, and risk of all-cause mortality: an individual participant data analysis of four prospective cohort studies.

OBJECTIVES: To examine whether moderate-to-vigorous physical activity (MVPA) modifies the association between sedentary time and mortality and vice versa, and estimate the joint associations of MVPA and sedentary time on mortality risk. METHODS: This study involved individual participant data analysis of four prospective cohort studies (Norway, Sweden, USA, baseline: 2003-2016, 11 989 participants ≥50 years, 50.5% women) with hip-accelerometry-measured physical activity and sedentary time. Associations were examined using restricted cubic splines and fractional polynomials in Cox regressions adjusted for sex, education, body mass index, smoking, alcohol, study cohort, cardiovascular disease, cancer, and/or diabetes, accelerometry wear time and age. RESULTS: 6.7% (n=805) died during follow-up (median 5.2 years, IQR 4.2 years). More than 12 daily sedentary hours (reference 8 hours) was associated with mortality risk only among those accumulating <22 min of MVPA per day (HR 1.38, 95% CI 1.10 to 1.74). Higher MVPA levels were associated with lower mortality risk irrespective of sedentary time, for example, HR for 10 versus 0 daily min of MVPA was 0.85 (95% CI 0.74 to 0.96) in those accumulating <10.5 daily sedentary hours and 0.65 (95% CI 0.53 to 0.79) in those accumulating ≥10.5 daily sedentary hours. Joint association analyses confirmed that higher MVPA was superior to lower sedentary time in lowering mortality risk, for example, 10 versus 0 daily min of MVPA was associated with 28-55% lower mortality risk across the sedentary time spectrum (lowest risk, 10 daily sedentary hours: HR 0.45, 95% CI 0.31 to 0.65). CONCLUSIONS: Sedentary time was associated with higher mortality risk but only in individuals accumulating less than 22 min of MVPA per day. Higher MVPA levels were associated with lower mortality risk irrespective of the amount of sedentary time.

Does an obesogenic family environment moderate the association between sports participation and body composition in children? The ENERGY project.

BACKGROUND: Previous research on the association between sports participation and body composition has shown mixed findings. The family home is considered one of the most influential environments on childhood obesity. Thus, the association between sports participation and body composition in children may be influenced by an obesogenic home environment. OBJECTIVES: To investigate if an obesogenic family environment moderates the association between sports participation and body composition in children. METHODS: A total of 3999 children (54% girls; 11.6 ± 0.7 years) and their parent(s) were included from the ENERGY project. A composite obesogenic family environment risk score was created from 10 questionnaire items. Height, weight (to calculate body mass index), and waist circumference were obtained by trained researchers and used as indicators of body composition. RESULTS: The composite risk score significantly moderated the association between sports participation and both waist circumference and body mass index. In children from families with moderate and high obesogenic risk, organized sports participation was significantly associated with smaller waist circumference (moderate risk: -0.29, 95% CI -0.45 to -0.14; high risk: -0.46, 95% CI -0.66 to -0.25) and lower body mass index (moderate risk: -0.10, 95% CI -0.16 to -0.04; high risk: -0.14, 95% CI -0.22 to -0.06), but not in children with a low obesogenic family risk score. CONCLUSIONS: Enrolling children in sports activities from an early age can be important for healthy weight maintenance, especially among children from obesogenic family environments.

How many days of continuous physical activity monitoring reliably represent time in different intensities in cancer survivors.

BACKGROUND: Physical activity (PA) monitoring is applied in a growing number of studies within cancer research. However, no consensus exists on how many days PA should be monitored to obtain reliable estimates in the cancer population. The objective of the present study was to determine the minimum number of monitoring days required for reliable estimates of different PA intensities in cancer survivors when using a six-days protocol. Furthermore, reliability of monitoring days was assessed stratified on sex, age, cancer type, weight status, and educational level. METHODS: Data was obtained from two studies where PA was monitored for seven days using the SenseWear Armband Mini in a total of 984 cancer survivors diagnosed with breast, colorectal or prostate cancer. Participants with ≥22 hours monitor wear-time for six days were included in the reliability analysis (n = 736). The intra-class correlation coefficient (ICC) and the Spearman Brown prophecy formula were used to assess the reliability of different number of monitoring days. RESULTS: For time in light PA, two monitoring days resulted in reliable estimates (ICC >0.80). Participants with BMI ≥25, low-medium education, colorectal cancer, or age ≥60 years required one additional monitoring day. For moderate and moderate-to-vigorous PA, three monitoring days yielded reliable estimates. Participants with BMI ≥25 or breast cancer required one additional monitoring day. Vigorous PA showed the largest within subject variations and reliable estimates were not obtained for the sample as a whole. However, reliable estimates were obtained for breast cancer survivors (4 days), females, BMI ≥30, and age <60 years (6 days). CONCLUSION: Shorter monitoring periods may provide reliable estimates of PA levels in cancer survivors when monitored continuously with a wearable device. This could potentially lower the participant burden and allow for less exclusion of participants not adhering to longer protocols.

Association between sociodemographic determinants and health behaviors, and clustering of health risk behaviors among 28,047 adults: a cross-sectional study among adults from the general Norwegian population.

BACKGROUND: Understanding the associations between health behaviors and which subgroups are at risk of developing health risk behaviors is vital knowledge to develop effective public health interventions to reduce the high prevalence of non-communicable diseases (NCDs). The objective of the study was to assess the association between physical activity, diet, tobacco use, and alcohol consumption and sociodemographic determinants (sex and education), and to examine clustering patterns of these health behaviors. METHOD: Data was collected from an online self-reported questionnaire from the Norwegian public health survey conducted in 2019. The study sample consisted of 28,047 adults (≥ 18 years old) from Agder county in Southern Norway. Chi-square tests and logistic regression analysis were used to determine the association between sex and education according to physical activity, diet, tobacco use and alcohol consumption. Linear regression was used to examine the association between educational level and number of health risk behaviors, and cluster analysis were performed to determine cluster patterns. RESULTS: Females were more likely than men to meet the national public health recommendations for diet (p < 0.001), tobacco use (p < 0.01), and alcohol consumption (p < 0.001). High education was associated with meeting the recommendations for each of the four health behaviors and with a lower risk of having three or four health risk behaviors simultaneously. Furthermore, clustering of health risk behaviors was observed in five of the sixteen health behavior patterns. CONCLUSION: Our findings show a higher risk of having multiple health risk behaviors for males and individuals with low education, and these subgroup findings could inform public health policy and be target goals in future public health interventions. Clustering patterns were observed in over 30% of the health behavior patterns. More research is needed on the causal relationship between health behaviors and socioeconomic factors, and the association between clustering and health outcomes to design effective interventions in the future.

Criterion validity of the Saltin-Grimby Physical Activity Level Scale in adolescents. The Fit Futures Study.

BACKGROUND: The Saltin-Grimby Physical Activity Level Scale (SGPALS) is commonly used to measure physical activity (PA) in population studies, but its validity in adolescents is unknown. This study aimed to assess the criterion validity of the SGPALS against accelerometry in a large sample of adolescents. A secondary aim was to examine the validity across strata of sex, body mass index (BMI), parental educational level, study program and self-reported health. METHODS: The study is based on data from 572 adolescents aged 15-17 years who participated in the Fit Futures Study 2010-11 in Northern Norway. The participants were invited to wear an accelerometer (GT3X) attached to their hip for seven consecutive days. We used Spearman's rho and linear regression models to assess the validity of the SGPALS against the following accelerometry estimates of PA; mean counts/minute (CPM), steps/day, and minutes/day of moderate-to-vigorous physical activity (MVPA). RESULTS: The SGPALS correlated with mean CPM (ρ = 0.40, p<0.01), steps/day (ρ = 0.35, p<0.01) and MVPA min/day (ρ = 0.35, p<0.01). We observed no differences between correlations within demographic strata (all p>0.001). Higher scores on SGPALS were associated with a higher CPM, higher number of steps per day and more minutes of MVPA per day, with the following mean differences in PA measurements between the SGPALS ranks: CPM increased by 53 counts (95% CI: 44 to 62), steps/day increased by 925 steps (95% CI: 731 to 1118), and MVPA by 8.4 min/day (95% CI: 6.7 to 10.0). Mean difference between the highest and lowest SGPALS category was 2947 steps/day (6509 vs. 9456 steps/day) and 26.4 min/day MVPA (35.2 minutes vs 61.6 minutes). CONCLUSION: We found satisfactory ranking validity of SGPALS measured against accelerometry in adolescents, which was fairly stable across strata of sex, BMI, and education. However, the validity of SGPALS in providing information on absolute physical activity levels seem limited.

Establishing the Convergent Validity of the Travel Habit Questions in the Health Behavior in School-Aged Children Questionnaire by Quantifying Active Travel in Norwegian Adolescents.

Background: Active travel (cycling or walking to school) can be a substantial part of adolescents' daily physical activity. Research on transport activities primarily relies on self-reported indices of travel mode and travel time. However, many researchers do not report the psychometric properties of their instruments. The Health Behavior in School-aged Children (HBSC) questionnaire is a commonly used instrument, but the items in this questionnaire on travel habits have not yet been validated. The present study was conducted to investigate the convergent validity and agreement between the HBSC items and a travel diary on (1) transport mode to and from school and (2) travel time to school. Methods: The study sample consisted of 50 participants in the 9th grade (15 ± 0.3 years, 62% girls) from seven Norwegian schools. Outcome variables included transport mode and travel time derived from the HBSC items and a five-day travel diary. Convergent validity was assessed by evaluating Cohen's kappa for travel mode and the correlation coefficient (Spearman Rho) for travel time. Simple agreement calculations between the two measurement methods were also conducted. Results: The association between the HBSC questionnaire and the diary for travel mode to and from school was κ = 0.63 (P < 0.001) and κ = 0.77 (P < 0.001), respectively. The total agreement between the HBSC questionnaire and the diary for was 78%. However, the agreement was higher for walking (88%) and cycling (91%) than for motorized transport (67%). For travel time, the Spearman correlation coefficient was ρ = 0.60 (P < 0.001) between the HBSC questionnaire and the diary. The total agreement on travel time was 67%; however, active commuters (86%) seemed to more accurately estimated travel time than motorized commuters (55%). Conclusion: Although the overall agreement between the HBSC questionnaire and the diary for mode of transport was 78%, the HBSC questionnaire may underestimate the prevalence of motorized transport compared to walking and cycling. Trial Registration: ClinicalTrials.gov, identifier: NCT03817047.

Cross-sectional and longitudinal associations of active travel, organised sport and physical education with accelerometer-assessed moderate-to-vigorous physical activity in young people: the International Children's Accelerometry Database.

BACKGROUND: Physical activity (PA) declines during childhood. Important sources of PA are active travel, organised sport and physical education (PE), but it is unclear how these domain-specific PA sources contribute to (changes in) daily moderate-to-vigorous PA (MVPA) in young people. This study aimed to examine (1) the cross-sectional association between domain-specific physical activity (i.e., active travel, organised sport and PE) and daily minutes in accelerometer-assessed MVPA; and (2) the longitudinal association between domain-specific physical activity at baseline and change in daily minutes in MVPA. METHODS: Participants (baseline age 11.3 ± .1.2 years) were drawn from three studies in the International Children's Accelerometry Database. The contribution of self-reported standardised active travel, organised sport and PE to accelerometer-measured daily minutes in MVPA was examined using linear regression. In cross-sectional analyses, MVPA was regressed on each PA domain in separate models, adjusted for study, age, sex, maternal education, season, and monitor wear time. In longitudinal analyses, change in MVPA was regressed on each of the baseline PA domains, additionally adjusting for changes in season and wear time, follow-up duration, and baseline MVPA. R-squared was used to compare variance explained by each PA domain. RESULTS: In the cross-sectional analyses (n = 3871), organised sport (standardised ß = 3.81, 95% confidence interval [95%CI] = 3.06, 4.56) and active travel (ß = 3.46, 95%CI = 2.73, 4.19) contributed more to daily MVPA than PE (ß = 0.82, 95%CI = -0.02, 1.66). Compared to the base model which included only covariates (R2 = 21.5%), organised sport (absolute change: + 1.9%) and active travel (+ 1.7%) models explained more of the variance than the PE model (± < 0.1%). Associations followed a similar pattern in the longitudinal analyses (n = 2302), but none of the PA domains predicted change in MVPA (organised sport: standardised ß = 0.85, 95%CI = -0.03, 1.72; active travel: ß = 0.68, 95%CI = -0.14, 1.50; PE: ß = 0.02, 95%CI = -0.87, 0.91). CONCLUSIONS: A multi-sectoral approach covering a wide range of PA domains should be promoted to minimise the age-related decline in MVPA during childhood.

Device-measured sedentary time in Norwegian children and adolescents in the era of ubiquitous internet access: secular changes between 2005, 2011 and 2018.

BACKGROUND: Access to screen-based media has been revolutionized during the past two decades. How this has affected sedentary time (ST) accumulation in children is poorly understood. METHODS: This study, based on the Physical Activity among Norwegian Children Study (PANCS), uses accelerometer data from population-based samples of 9- and 15-year-olds, collected in 2005 (n = 1722), 2011 (n = 1587) and 2018 (n = 1859). Secular changes between surveys were analysed using random-effects linear regression models adjusted for survey-specific factors. Data on ST were collected using hip-worn ActiGraphs and ST was defined using a threshold equivalent to <100 counts/min. Sedentary bouts were grouped by duration: <1, 1-5, 5-15, 15-30 and ≥30 min. RESULTS: Between 2005 and 2018, ST increased by 29 min/day in 9-year-old boys (95% CI: 19, 39; P <0.001), by 21 min/day in 15-year-old boys (95% CI: 8, 34; P = 0.002) and by 22 min/day in 15-year-old girls (95% CI: 10, 35; P <0.001), but not in 9-year-old girls at 6 min/day (95% CI: -3, 16; P = 0.191). All age-sex groups accumulated less ST in bouts lasting <5 min and more ST in longer bouts, particularly in 5-15-min bouts. Adolescent girls also increased ST accumulation in 15-30-min and ≥30-min bouts. Changes were largely mirrored before, during and after school on weekdays and during weekend days. CONCLUSIONS: Coinciding with the introduction of smartphones, tablets and near-universal internet access, total daily ST and ST accumulated in prolonged sedentary bouts increased between 2005 and 2018 in children and adolescents.

Daily steps and all-cause mortality: a meta-analysis of 15 international cohorts.

BACKGROUND: Although 10 000 steps per day is widely promoted to have health benefits, there is little evidence to support this recommendation. We aimed to determine the association between number of steps per day and stepping rate with all-cause mortality. METHODS: In this meta-analysis, we identified studies investigating the effect of daily step count on all-cause mortality in adults (aged ≥18 years), via a previously published systematic review and expert knowledge of the field. We asked participating study investigators to process their participant-level data following a standardised protocol. The primary outcome was all-cause mortality collected from death certificates and country registries. We analysed the dose-response association of steps per day and stepping rate with all-cause mortality. We did Cox proportional hazards regression analyses using study-specific quartiles of steps per day and calculated hazard ratios (HRs) with inverse-variance weighted random effects models. FINDINGS: We identified 15 studies, of which seven were published and eight were unpublished, with study start dates between 1999 and 2018. The total sample included 47 471 adults, among whom there were 3013 deaths (10·1 per 1000 participant-years) over a median follow-up of 7·1 years ([IQR 4·3-9·9]; total sum of follow-up across studies was 297 837 person-years). Quartile median steps per day were 3553 for quartile 1, 5801 for quartile 2, 7842 for quartile 3, and 10 901 for quartile 4. Compared with the lowest quartile, the adjusted HR for all-cause mortality was 0·60 (95% CI 0·51-0·71) for quartile 2, 0·55 (0·49-0·62) for quartile 3, and 0·47 (0·39-0·57) for quartile 4. Restricted cubic splines showed progressively decreasing risk of mortality among adults aged 60 years and older with increasing number of steps per day until 6000-8000 steps per day and among adults younger than 60 years until 8000-10 000 steps per day. Adjusting for number of steps per day, comparing quartile 1 with quartile 4, the association between higher stepping rates and mortality was attenuated but remained significant for a peak of 30 min (HR 0·67 [95% CI 0·56-0·83]) and a peak of 60 min (0·67 [0·50-0·90]), but not significant for time (min per day) spent walking at 40 steps per min or faster (1·12 [0·96-1·32]) and 100 steps per min or faster (0·86 [0·58-1·28]). INTERPRETATION: Taking more steps per day was associated with a progressively lower risk of all-cause mortality, up to a level that varied by age. The findings from this meta-analysis can be used to inform step guidelines for public health promotion of physical activity. FUNDING: US Centers for Disease Control and Prevention.

Influence of Guideline Operationalization on Youth Activity Prevalence in the International Children's Accelerometry Database.

INTRODUCTION: The United Kingdom and World Health Organization recently changed their youth physical activity (PA) guidelines from 60 min of moderate- to vigorous-intensity PA (MVPA) every day, to an average of 60 min of MVPA per day, over a week. The changes are based on expert opinion due to insufficient evidence comparing health outcomes associated with different guideline definitions. This study used the International Children's Accelerometry Database to compare approaches to calculating youth PA compliance and associations with health indicators. METHODS: Cross-sectional accelerometer data (n = 21,612, 5-18 yr) were used to examine compliance with four guideline definitions: daily method (DM; ≥60 min MVPA every day), average method (AM; average of ≥60 min MVPA per day), AM5 (AM compliance and ≥5 min of vigorous PA [VPA] on ≥3 d), and AM15 (AM compliance and ≥15 min VPA on ≥3 d). Associations between compliance and health indicators were examined for all definitions. RESULTS: Compliance varied from 5.3% (DM) to 29.9% (AM). Associations between compliance and health indicators were similar for AM, AM5, and AM15. For example, compliance with AM, AM5, and AM15 was associated with a lower BMI z-score (statistics are coefficient [95% CI]): AM (-0.28 [-0.33 to -0.23]), AM5 (-0.28 [-0.33 to -0.23], and AM15 (-0.30 [-0.35 to -0.25]). Associations between compliance and health indicators for DM were similar/weaker, possibly reflecting fewer DM-compliant participants with health data and lower variability in exposure/outcome data. CONCLUSIONS: Youth completing 60 min of MVPA every day do not experience superior health benefits to youth completing an average of 60 min of MVPA per day. Guidelines should encourage youth to achieve an average of 60 min of MVPA per day. Different guideline definitions affect inactivity prevalence estimates; this must be considered when analyzing data and comparing studies.

GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies.

The inter-relationship between physical activity, sedentary behaviour and sleep (collectively defined as physical behaviours) is of interest to researchers from different fields. Each of these physical behaviours has been investigated in epidemiological studies, yet their codependency and interactions need to be further explored and accounted for in data analysis. Modern accelerometers capture continuous movement through the day, which presents the challenge of how to best use the richness of these data. In recent years, analytical approaches first applied in other scientific fields have been applied to physical behaviour epidemiology (eg, isotemporal substitution models, compositional data analysis, multivariate pattern analysis, functional data analysis and machine learning). A comprehensive description, discussion, and consensus on the strengths and limitations of these analytical approaches will help researchers decide which approach to use in different situations. In this context, a scientific workshop and meeting were held in Granada to discuss: (1) analytical approaches currently used in the scientific literature on physical behaviour, highlighting strengths and limitations, providing practical recommendations on their use and including a decision tree for assisting researchers' decision-making; and (2) current gaps and future research directions around the analysis and use of accelerometer data. Advances in analytical approaches to accelerometer-determined physical behaviours in epidemiological studies are expected to influence the interpretation of current and future evidence, and ultimately impact on future physical behaviour guidelines.

Device-measured physical activity, adiposity and mortality: a harmonised meta-analysis of eight prospective cohort studies.

BACKGROUND: The joint associations of total and intensity-specific physical activity with obesity in relation to all-cause mortality risk are unclear. METHODS: We included 34 492 adults (72% women, median age 62.1 years, 2034 deaths during follow-up) in a harmonised meta-analysis of eight population-based prospective cohort studies with mean follow-up ranging from 6.0 to 14.5 years. Standard body mass index categories were cross-classified with sample tertiles of device-measured total, light-to-vigorous and moderate-to-vigorous physical activity and sedentary time. In five cohorts with waist circumference available, high and low waist circumference was combined with tertiles of moderate-to-vigorous physical activity. RESULTS: There was an inverse dose-response relationship between higher levels of total and intensity-specific physical activity and mortality risk in those who were normal weight and overweight. In individuals with obesity, the inverse dose-response relationship was only observed for total physical activity. Similarly, lower levels of sedentary time were associated with lower mortality risk in normal weight and overweight individuals but there was no association between sedentary time and risk of mortality in those who were obese. Compared with the obese-low total physical activity reference, the HRs were 0.59 (95% CI 0.44 to 0.79) for normal weight-high total activity and 0.67 (95% CI 0.48 to 0.94) for obese-high total activity. In contrast, normal weight-low total physical activity was associated with a higher risk of mortality compared with the obese-low total physical activity reference (1.28; 95% CI 0.99 to 1.67). CONCLUSIONS: Higher levels of physical activity were associated with lower risk of mortality irrespective of weight status. Compared with obesity-low physical activity, there was no survival benefit of being normal weight if physical activity levels were low.

Deep Learning for Classifying Physical Activities from Accelerometer Data.

Physical inactivity increases the risk of many adverse health conditions, including the world's major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening life expectancy. There are minimal medical care and personal trainers' methods to monitor a patient's actual physical activity types. To improve activity monitoring, we propose an artificial-intelligence-based approach to classify physical movement activity patterns. In more detail, we employ two deep learning (DL) methods, namely a deep feed-forward neural network (DNN) and a deep recurrent neural network (RNN) for this purpose. We evaluate the two models on two physical movement datasets collected from several volunteers who carried tri-axial accelerometer sensors. The first dataset is from the UCI machine learning repository, which contains 14 different activities-of-daily-life (ADL) and is collected from 16 volunteers who carried a single wrist-worn tri-axial accelerometer. The second dataset includes ten other ADLs and is gathered from eight volunteers who placed the sensors on their hips. Our experiment results show that the RNN model provides accurate performance compared to the state-of-the-art methods in classifying the fundamental movement patterns with an overall accuracy of 84.89% and an overall F1-score of 82.56%. The results indicate that our method provides the medical doctors and trainers a promising way to track and understand a patient's physical activities precisely for better treatment.

Does organized sports participation in childhood and adolescence positively influence health? A review of reviews.

Sports participations have the potential for both positive and negative health outcomes. We hence aimed (i) to assess systematically reviewed associations between organized sports participation in children and adolescents and their health, and (ii) to assess qualitative syntheses of experiences among children and adolescents concerning organized sports participation and health. A search was undertaken in April 2020 across the databases MEDLINE, EMBASE, APA PsycInfo (Ovid), Scopus, SPORTDiscus (EBSCOhost), and specialized databases for reviews. The recommended Joanna Briggs Institute approach to critical appraisal, study selection, data extraction, and data synthesis was used. Systematic reviews were included that covered children and/or adolescents aged ≤ 18 years, and adult participants with retrospective exposure to-or experiences of-organized sports participation before the age of 19 and examining health outcomes and experiences (Prospero protocol CRD 42020206677). Five reviews based mainly on cross-sectional data, two mainly on longitudinal data, and one on experimental studies were included. A causal relationship of moderate-to-high level of evidence between organized sports participation and moderate crude weight reduction accentuated by diet control and team sports was identified. Evidence of causal relationships between sports participation and reduced anxiety, and depression and increased physical activity was at a moderate level. Evidence of causal relationships between sports participation and health was of low-to-moderate level concerning obesity status (inconclusive), bone health (positive), and psychological and social health (positive and negative). Causal relationships between organized child and adolescent sports participation and health remain uncertain. Experimental and well-conducted longitudinal primary studies are highly warranted.

Temporal trends in physical activity levels across more than a decade - a national physical activity surveillance system among Norwegian children and adolescents.

BACKGROUND: There is a scarcity of device measured data on temporal changes in physical activity (PA) in large population-based samples. The purpose of this study is to describe gender and age-group specific temporal trends in device measured PA between 2005, 2011 and 2018 by comparing three nationally representative samples of children and adolescents. METHODS: Norwegian children and adolescents (6, 9 and 15-year-olds) were invited to participate in 2005 (only 9- and 15-year-olds), 2011 and 2018 through cluster sampling (schools primary sampling units). A combined sample of 9500 individuals participated. Physical activity was assessed by hip worn accelerometers, with PA indices including overall PA (counts per minute), moderate-to-vigorous intensity PA (MVPA), and PA guideline adherence (achieving on average ≥ 60 min/day of moderate-to-vigorous PA). Random-effects linear regressions and logistic regressions adjusted for school-level clusters were used to analyse temporal trends. FINDINGS: In total, 8186 of the participating children and adolescents provided valid PA data. Proportions of sufficiently active 6-year-olds were almost identical in 2011 and 2018; boys 95% (95% CI: 92, 97) and 94% (95%CI: 92, 96) and girls 86% (95% CI: 83, 90) and 86% (95% CI: 82, 90). Proportions of sufficiently active 15-year-olds in 2005 and 2018 were 52% (95% CI: 46, 59) and 55% (95% CI: 48, 62) in boys, and 48% (95% CI: 42, 55) and 44% (95% CI: 37, 51) in girls, respectively, resulting from small differences in min/day of MVPA. Among 9-year-old boys and girls, proportions of sufficiently active declined between 2005 and 2018, from 90% (95% CI: 87, 93) to 84% (95% CI: 80, 87)) and 74% (95% CI: 69, 79) to 68% (95% CI: 64, 72), respectively. This resulted from 9.7 min/day less MVPA in boys (95% CI: - 14.8, - 4.7; p < 0.001) and 3.2 min/day less MVPA (95% CI: - 7.0, 0.7; p = 0.106) in girls. CONCLUSIONS: PA levels have been fairly stable between 2005, 2011 and 2018 in Norwegian youth. However, the declining PA level among 9-year-old boys and the low proportion of 15-year-olds sufficiently active is concerning. To evaluate the effect of, and plan for new, PA promoting strategies, it is important to ensure more frequent, systematic, device-based monitoring of population-levels of PA.

Joint associations of accelero-meter measured physical activity and sedentary time with all-cause mortality: a harmonised meta-analysis in more than 44 000 middle-aged and older individuals.

OBJECTIVES: To examine the joint associations of accelerometer-measured physical activity and sedentary time with all-cause mortality. METHODS: We conducted a harmonised meta-analysis including nine prospective cohort studies from four countries. 44 370 men and women were followed for 4.0 to 14.5 years during which 3451 participants died (7.8% mortality rate). Associations between different combinations of moderate-to-vigorous intensity physical activity (MVPA) and sedentary time were analysed at study level using Cox proportional hazards regression analysis and summarised using random effects meta-analysis. RESULTS: Across cohorts, the average time spent sedentary ranged from 8.5 hours/day to 10.5 hours/day and 8 min/day to 35 min/day for MVPA. Compared with the referent group (highest physical activity/lowest sedentary time), the risk of death increased with lower levels of MVPA and greater amounts of sedentary time. Among those in the highest third of MVPA, the risk of death was not statistically different from the referent for those in the middle (16%; 95% CI 0.87% to 1.54%) and highest (40%; 95% CI 0.87% to 2.26%) thirds of sedentary time. Those in the lowest third of MVPA had a greater risk of death in all combinations with sedentary time; 65% (95% CI 1.25% to 2.19%), 65% (95% CI 1.24% to 2.21%) and 263% (95% CI 1.93% to 3.57%), respectively. CONCLUSION: Higher sedentary time is associated with higher mortality in less active individuals when measured by accelerometry. About 30-40 min of MVPA per day attenuate the association between sedentary time and risk of death, which is lower than previous estimates from self-reported data.

A Mapping Review of Physical Activity Recordings Derived From Smartphone Accelerometers.

BACKGROUND: Smartphones with embedded sensors, such as accelerometers, are promising tools for assessing physical activity (PA), provided they can produce valid and reliable indices. The authors aimed to summarize studies on the PA measurement properties of smartphone accelerometers compared with research-grade PA monitors or other objective methods across the intensity spectrum, and to report the effects of different smartphone placements on the accuracy of measurements. METHODS: A systematic search was conducted on July 1, 2019 in PubMed, Embase, SPORTDiscus, and Scopus, followed by screening. RESULTS: Nine studies were included, showing moderate-to-good agreements between PA indices derived from smartphone accelerometers and research-grade PA monitors and/or indirect calorimetry. Three studies investigated measurement properties across smartphone placements, with small differences. Large heterogeneity across studies hampered further comparisons. CONCLUSIONS: Despite moderate-to-good agreements between PA indices derived from smartphone accelerometers and research-grade PA monitors and/or indirect calorimetry, the validity of smartphone monitoring is currently challenged by poor intermonitor reliability between smartphone brands/versions, heterogeneity in protocols used for validation, the sparsity of studies, and the need to address the effects of smartphone placement.

The multivariate physical activity signature associated with metabolic health in children and youth: An International Children's Accelerometry Database (ICAD) analysis.

There is solid evidence for an association between physical activity and metabolic health outcomes in children and youth, but for methodological reasons most studies describe the intensity spectrum using only a few summary measures. We aimed to determine the multivariate physical activity intensity signature associated with metabolic health in a large and diverse sample of children and youth, by investigating the association pattern for the entire physical intensity spectrum. We used pooled data from 11 studies and 11,853 participants aged 5.8-18.4 years included in the International Children's Accelerometry Database. We derived 14 accelerometry-derived (ActiGraph) physical activity variables covering the intensity spectrum (from 0-99 to ≥8000 counts per minute). To handle the multicollinearity among these variables, we used multivariate pattern analysis to establish the associations with indices of metabolic health (abdominal fatness, insulin sensitivity, lipid metabolism, blood pressure). A composite metabolic health score was used as the main outcome variable. Associations with the composite metabolic health score were weak for sedentary time and light physical activity, but gradually strengthened with increasing time spent in moderate and vigorous intensities (up to 4000-5000 counts per minute). Association patterns were fairly consistent across sex and age groups, but varied across different metabolic health outcomes. This novel analytic approach suggests that vigorous intensity, rather than less intense activities or sedentary behavior, are related to metabolic health in children and youth.

Prevalence of accelerometer-measured physical activity in adolescents in Fit Futures - part of the Tromsø Study.

BACKGROUND: Previous studies show large variations in physical activity (PA) levels among adolescents. However, the number of studies is limited and even fewer studies have assessed PA in adolescents by accelerometer devices. This study aimed to describe accelerometer-measured PA levels in adolescents in a population-based cohort in Northern Norway. METHODS: In 611 students aged 16-17 years attending the Fit Futures Study, PA was measured by Actigraph GT3X for seven consecutive days. PA was expressed as total PA volume (counts per minute, CPM), time spent in intensity zones, steps per day, and fulfilment of WHO recommendation (i.e. accumulation of 60 min or more of at least moderate intensity PA per day). Potential correlates of PA such as sex, socioeconomic status, study program, self-perceived health, and PA variations by weekday versus weekend were also examined. RESULTS: 16% of the girls and 25% of the boys fulfilled current WHO-recommendations. Total PA volume (CPM) was higher in boys than in girls (353 (SD 130) versus 326 (SD 114) CPM, p < 0.05). PA levels differed with study program and increased with better self-perceived health, but were not associated with socioeconomic status. Both boys and girls were more active on weekdays than weekends (altogether; 350 (SD 124) versus 299 (SD 178) CPM, p < 0.05). CONCLUSIONS: In this cohort of adolescents, less than 25% of 16-17-year-old boys and girls fulfilled the WHO recommendations. The levels of physical activity in 16-17-year-old adolescents are similar to previous data reported in adults.

Birth weight, cardiometabolic risk factors and effect modification of physical activity in children and adolescents: pooled data from 12 international studies.

OBJECTIVES: Low and high birth weight is associated with higher levels of cardiometabolic risk factors and adiposity in children and adolescents, and increases the risk of cardiovascular diseases, obesity, and early mortality later in life. Moderate-to-vigorous physical activity (MVPA) is associated with lower cardiometabolic risk factors and may mitigate the detrimental consequences of high or low birth weight. Thus, we examined whether MVPA modified the associations between birth weight and cardiometabolic risk factors in children and adolescents. METHODS: We used pooled individual data from 12 cohort- or cross-sectional studies including 9,100 children and adolescents. Birth weight was measured at birth or maternally reported retrospectively. Device-measured physical activity (PA) and cardiometabolic risk factors were measured in childhood or adolescence. We tested for associations between birth weight, MVPA, and cardiometabolic risk factors using multilevel linear regression, including study as a random factor. We tested for interaction between birth weight and MVPA by introducing the interaction term in the models (birth weight x MVPA). RESULTS: Most of the associations between birth weight (kg) and cardiometabolic risk factors were not modified by MVPA (min/day), except between birth weight and waist circumference (cm) in children (p = 0.005) and HDL-cholesterol (mmol/l) in adolescents (p = 0.040). Sensitivity analyses suggested that some of the associations were modified by VPA, i.e., the associations between birth weight and diastolic blood pressure (mmHg) in children (p = 0.009) and LDL- cholesterol (mmol/l) (p = 0.009) and triglycerides (mmol/l) in adolescents (p = 0.028). CONCLUSION: MVPA appears not to consistently modify the associations between low birth weight and cardiometabolic risk. In contrast, MVPA may mitigate the association between higher birth weight and higher waist circumference in children. MVPA is consistently associated with a lower cardiometabolic risk across the birth weight spectrum. Optimal prenatal growth and subsequent PA are both important in relation to cardiometabolic health in children and adolescents.