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.

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.

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.

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.

Cross-sectional and prospective associations between sleep, screen time, active school travel, sports/exercise participation and physical activity in children and adolescents.

BACKGROUND: The aim of this study was to investigate how sleep, screen time, active school travel and sport and/or exercise participation associates with moderate-to-vigorous physical activity (MVPA) in nationally representative samples of Norwegian 9- and 15-y-olds, and whether these four behaviors at age nine predict change in MVPA from age nine to 15 years. METHOD: We pooled cross-sectional accelerometer and questionnaire data from 9- (n = 2366) and 15-y-olds (n = 1554) that participated in the first (2005/06) and second (2011/12) wave of the Physical Activity among Norwegian Children Study to investigate cross-sectional associations. To investigate prospective associations, we used data from a sub-sample that participated in both waves (at age nine and 15 years, n = 517). RESULTS: Cross-sectional analyses indicated a modest, inverse association between screen time and MVPA among 9- (- 2.2 min/d (95% CI: -3.1, - 1.3)) and 15-y-olds (- 1.7 min/d (95% CI: -2.7, - 0.8)). Compared to their peers with 0-5 min/d of active travel to school, 9- and 15-y-olds with ≥16 min/d accumulated 7.2 (95% CI: 4.0, 10.4) and 9.0 (95% CI: 3.8, 14.1) more min/d of MVPA, respectively. Nine-y-old boys and 15-y-olds reporting ≥8 h/week of sports and/or exercise participation accumulated 14.7 (95% CI: 8.2, 21.3) and 17.9 (95% CI: 14.0, 21.8) more min/d of MVPA, respectively, than those reporting ≤2 h/week. We found no cross-sectional association between sleep duration and MVPA in either age group. None of the four behaviors predicted change in MVPA from age nine to 15 years (p ≥ 0.102). CONCLUSION: Active travel to school and sport/exercise participation may be important targets for future interventions aimed at increasing MVPA in children and adolescents. However, future studies are needed to determine causality.

Harmonising data on the correlates of physical activity and sedentary behaviour in young people: Methods and lessons learnt from the international Children's Accelerometry database (ICAD).

BACKGROUND: Large, heterogeneous datasets are required to enhance understanding of the multi-level influences on children's physical activity and sedentary behaviour. One route to achieving this is through the pooling and co-analysis of data from multiple studies. Where this approach is used, transparency of the methodology for data collation and harmonisation is essential to enable appropriate analysis and interpretation of the derived data. In this paper, we describe the acquisition, management and harmonisation of non-accelerometer data in a project to expand the International Children's Accelerometry Database (ICAD). METHOD: Following a consultation process, ICAD partners were requested to share accelerometer data and information on selected behavioural, social, environmental and health-related constructs. All data were collated into a single repository for cataloguing and harmonisation. Harmonised variables were derived iteratively, with input from the ICAD investigators and a panel of invited experts. Extensive documentation, describing the source data and harmonisation procedure, was prepared and made available through the ICAD website. RESULTS: Work to expand ICAD has increased the number of studies with longitudinal accelerometer data, and expanded the breadth of behavioural, social and environmental characteristics that can be used as exposure variables. A set of core harmonised variables, including parent education, ethnicity, school travel mode/duration and car ownership, were derived for use by the research community. Guidance documents and facilities to enable the creation of new harmonised variables were also devised and made available to ICAD users. An expanded ICAD database was made available in May 2017. CONCLUSION: The project to expand ICAD further demonstrates the feasibility of pooling data on physical activity, sedentary behaviour and potential determinants from multiple studies. Key to this process is the rigorous conduct and reporting of retrospective data harmonisation, which is essential to the appropriate analysis and interpretation of derived data. These documents, made available through the ICAD website, may also serve as a guide to others undertaking similar projects.

Evaluation of raw acceleration sedentary thresholds in children and adults.

The aim was to develop sedentary (sitting/lying) thresholds from hip and wrist worn raw tri-axial acceleration data from the ActiGraph and GENEActiv, and to examine the agreement between free-living time spent below these thresholds with sedentary time estimated by the activPAL. Sixty children and adults wore an ActiGraph and GENEActiv on the hip and wrist while performing six structured activities, before wearing the monitors, in addition to an activPAL, for 24 h. Receiver operating characteristic (ROC) curves were used to determine sedentary thresholds based on activities in the laboratory. Agreement between developed sedentary thresholds during free-living and activPAL were assessed by Bland-Altman plots and by calculating sensitivity and specificity. Using laboratory data and ROC-curves showed similar classification accuracy for wrist and hip thresholds (Area under the curve = 0.84-0.92). Greatest sensitivity (97-98%) and specificity (74-78%) were observed for the wrist thresholds, with no large differences between brands. During free-living, Bland-Altman plots showed large mean individual biases and 95% limits of agreement compared with activPAL, with smallest difference for the ActiGraph wrist threshold in children (+30 min, P = 0.3). Sensitivity and specificity for the developed thresholds during free-living were low for both age groups and for wrist (Sensitivity, 68-88%, Specificity, 46-59%) and hip placements (Sensitivity, 89-97%, Specificity, 26-34%). Laboratory derived sedentary thresholds generally overestimate free-living sedentary time compared with activPAL. Wrist thresholds appear to perform better than hip thresholds for estimating free-living sedentary time in children and adults relative to activPAL, however, specificity for all the developed thresholds are low.

Application of a tri-axial accelerometer to estimate jump frequency in volleyball.

Patellar tendinopathy is prevalent among athletes, and most likely associated with a high jumping load. If methods for estimating jump frequency were available, this could potentially assist in understanding and preventing this condition. The objective of this study was to explore the possibility of using peak vertical acceleration (PVA) or peak resultant acceleration (PRA) measured by an accelerometer to estimate jump frequency. Twelve male elite volleyball players (22.5 ± 1.6 yrs) performed a training protocol consisting of seven typical motion patterns, including jumping and non-jumping movements. Accelerometer data from the trial were obtained using a tri-axial accelerometer. In addition, we collected video data from the trial. Jump-float serving and spike jumping could not be distinguished from non-jumping movements using differences in PVA or PRA. Furthermore, there were substantial inter-participant differences in both the PVA and the PRA within and across movement types (p < 0.05). These findings suggest that neither PVA nor PRA measured by a tri-axial accelerometer is an applicable method for estimating jump frequency in volleyball. A method for acquiring real-time estimates of jump frequency remains to be verified. However, there are several alternative approaches, and further investigations are needed.

Accelerometer-determined physical activity and self-reported health in a population of older adults (65-85 years): a cross-sectional study.

BACKGROUND: The link between physical activity (PA) and prevention of disease, maintenance of independence, and improved quality of life in older adults is supported by strong evidence. However, there is a lack of data on population levels in this regard, where PA level has been measured objectively. The main aims were therefore to assess the level of accelerometer-determined PA and to examine its associations with self-reported health in a population of Norwegian older adults (65-85 years). METHODS: This was a part of a national multicenter study. Participants for the initial study were randomly selected from the national population registry, and the current study included those of the initial sample aged 65-85 years. The ActiGraph GT1M accelerometer was used to measure PA for seven consecutive days. A questionnaire was used to register self-reported health. Univariate analysis of variance with Bonferroni adjustments were used for comparisons between multiple groups. RESULTS: A total of 560 participants had valid activity registrations. Mean age (SD) was 71.8 (5.6) years for women (n=282) and 71.7 (5.2) years for men (n=278). Overall PA level (cpm) differed considerably between the age groups where the oldest (80-85 y) displayed a 50% lower activity level compared to the youngest (65-70 y). No sex differences were observed in overall PA within each age group. Significantly more men spent time being sedentary (65-69 and 70-74 years) and achieved more minutes of moderate to vigorous PA (MVPA) (75-79 years) compared to women. Significantly more women (except for the oldest), spent more minutes of low-intensity PA compared to men. PA differed across levels of self-reported health and a 51% higher overall PA level was registered in those, with "very good health" compared to those with "poor/very poor health". CONCLUSION: Norwegian older adults PA levels differed by age. Overall, the elderly spent 66% of their time being sedentary and only 3% in MVPA. Twenty one percent of the participants fulfilled the current Norwegian PA recommendations. Overall PA levels were associated with self-reported health.

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.

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.

Criterion validity of two physical activity and one sedentary time questionnaire against accelerometry in a large cohort of adults and older adults.

OBJECTIVES: We compared the ability of physical activity and sitting time questionnaires (PAQ) for ranking individuals versus continuous volume calculations (physical activity level (PAL), metabolic equivalents of task (MET), sitting hours) against accelerometry measured physical activity as our criterion. METHODS: Participants in a cohort from the Tromsø Study completed three questionnaires; (1) The Saltin-Grimby Physical Activity Level Scale (SGPALS) (n=4040); (2) The Physical Activity Frequency, Intensity and Duration (PAFID) questionnaire (n=5902)) calculated as MET-hours·week-1 and (3) The International Physical Activity questionnaire (IPAQ) short-form sitting question (n=4896). We validated the questionnaires against the following accelerometry (Actigraph wGT3X-BT) estimates: vector magnitude counts per minute, steps∙day-1, time (minutes·day-1) in sedentary behaviour, light physical activity, moderate and vigorous physical activity (MVPA) non-bouted and ≥10 min bouted MVPA. RESULTS: Ranking of physical activity according to the SGPALS and quartiles (Q) of MET-hours∙week-1 from the PAFID were both positively associated with accelerometry estimates of physical activity (p<0.001) but correlations with accelerometry estimates were weak (SGPALS (PAL): r=0.11 to 0.26, p<0.001) and weak-to-moderate (PAFID: r=0.39 to 0.44, p<0.01). There was 1 hour of accelerometry measured sedentary time from Q1 to Q4 in the IPAQ sitting question (p<0.001) and also weak correlations (r=0.22, p<0.01). CONCLUSION: Ranking of physical activity levels measured with PAQs appears to have higher validity than energy expenditure calculations. Self-reported sedentary time poorly reflects accelerometry measured sedentary time. These two PAQs can be used for ranking individuals into different physical activity categories supporting previous studies using these instruments when assessing associations with health outcomes.

Associations between accelerometry measured physical activity and sedentary time and the metabolic syndrome: A meta-analysis of more than 6000 children and adolescents.

BACKGROUND: Metabolic syndrome is increasingly prevalent in the pediatric population. To prevent an early onset, knowledge about its association with modifiable lifestyle factors is needed. OBJECTIVES: To estimate the prevalence of the metabolic syndrome and examine its cross-sectional associations with physical activity and sedentary time. METHODS: Participants were 6009 children and adolescents from 8 studies of the International Children's Accelerometry Database. Physical activity and sedentary time were measured by accelerometer. Metabolic syndrome was defined based on International Diabetes Federation criteria. Logistic regression models adjusted for sex, age and monitor wear time were used to examine the associations between physical activity, sedentary time and the metabolic syndrome in each study and effect estimates were combined using random-effects meta-analysis. RESULTS: The overall prevalence of the metabolic syndrome was 2.9%. In crude models, a 10 min increase in moderate-to-vigorous intensity physical activity and vigorous-intensity physical activity were inversely associated with the metabolic syndrome [OR 0.88, 95% CI 0.82-0.94, OR 0.80, 95% CI 0.70-0.92]. One hour increase in sedentary time was positively associated with the metabolic syndrome [OR 1.28, 95% CI 1.13-1.45]. After adjustment for sedentary time, the association between moderate-to-vigorous-intensity physical activity and the metabolic syndrome remained significant [OR 0.91, 95% CI 0.84-0.99]. Sedentary time was not associated with the metabolic syndrome after adjustment for moderate-to-vigorous intensity physical activity [OR 1.14 95% CI 0.96-1.36]. CONCLUSIONS: Physical activity of at least moderate intensity but not sedentary time is independently associated with the metabolic syndrome.

Waist circumference thresholds and cardiorespiratory fitness.

PURPOSE: This study's purpose was to examine whether established risk categories of waist circumference (WC)-normal, high risk, and very high health risk-reflected significant differences in cardiorespiratory fitness (CRF) and physical activity (PA) level. METHODS: CRF was directly measured as maximal oxygen uptake during a progressive graded treadmill test to exhaustion in 722 individuals (349 women) aged 20-85 years. WC was measured between the lower rib and the iliac crest. Objectively measured PA was assessed using an accelerometer. RESULTS: Men in the normal risk group (WC < 94 cm) had a 31% higher CRF and 43% higher level of moderate-to-vigorous PA than men in the very high risk group (with a WC > 102 cm). Corresponding numbers for women within normal (WC < 80 cm) and very high risk group (WC > 88 cm) were 25% and 18% (p < 0.05). There was a high negative correlation between CRF and WC in men (r = -0.68), and a moderate correlation for women (r = -0.49; p < 0.001). For each cm increase in WC, CRF was reduced by 0.48 and 0.27 mL/kg/min in men and women, respectively (p < 0.001). CONCLUSION: The recommended WC thresholds for abdominal obesity reflected significant differences in CRF for both men and women, and could serve as a useful instrument for estimating health-related differences in CRF.

Physical activity levels in adults and elderly from triaxial and uniaxial accelerometry. The Tromsø Study.

INTRODUCTION: Surveillance of physical activity at the population level increases the knowledge on levels and trends of physical activity, which may support public health initiatives to promote physical activity. Physical activity assessed by accelerometry is challenged by varying data processing procedures, which influences the outcome. We aimed to describe the levels and prevalence estimates of physical activity, and to examine how triaxial and uniaxial accelerometry data influences these estimates, in a large population-based cohort of Norwegian adults. METHODS: This cross-sectional study included 5918 women and men aged 40-84 years who participated in the seventh wave of the Tromsø Study (2015-16). The participants wore an ActiGraph wGT3X-BT accelerometer attached to the hip for 24 hours per day over seven consecutive days. Accelerometry variables were expressed as volume (counts·minute-1 and steps·day-1) and as minutes per day in sedentary, light physical activity and moderate and vigorous physical activity (MVPA). RESULTS: From triaxial accelerometry data, 22% (95% confidence interval (CI): 21-23%) of the participants fulfilled the current global recommendations for physical activity (≥150 minutes of MVPA per week in ≥10-minute bouts), while 70% (95% CI: 69-71%) accumulated ≥150 minutes of non-bouted MVPA per week. When analysing uniaxial data, 18% fulfilled the current recommendations (i.e. 20% difference compared with triaxial data), and 55% (95% CI: 53-56%) accumulated ≥150 minutes of non-bouted MVPA per week. We observed approximately 100 less minutes of sedentary time and 90 minutes more of light physical activity from triaxial data compared with uniaxial data (p<0.001). CONCLUSION: The prevalence estimates of sufficiently active adults and elderly are more than three times higher (22% vs. 70%) when comparing triaxial bouted and non-bouted MVPA. Physical activity estimates are highly dependent on accelerometry data processing criteria and on different definitions of physical activity recommendations, which may influence prevalence estimates and tracking of physical activity patterns over time.

Physical Fitness in Patients With Oligoarticular and Polyarticular Juvenile Idiopathic Arthritis Diagnosed in the Era of Biologics: A Controlled Cross-Sectional Study.

OBJECTIVE: To perform a comprehensive evaluation of and identify correlates for physical fitness in consecutive patients with juvenile idiopathic arthritis (JIA) who have been diagnosed in the era of biologics and to compare the results with those obtained in healthy controls. METHODS: The study cohort included 60 patients with JIA (50 girls) ages 10-16 years and 60 age- and sex-matched controls. The JIA group included 30 patients with persistent oligoarticular JIA and 30 patients with extended oligoarticular or polyarticular disease. Measures of physical fitness included cardiorespiratory fitness (CRF) by peak oxygen uptake (Vo2peak ) during a continuous graded treadmill exercise test, muscle strength by isokinetic and isometric knee and hand grip evaluations, and bone mineral density (BMD) and body composition by dual-energy x-ray absorptiometry. Physical activity was assessed by accelerometry. RESULTS: Forty-two percent of the patients were being treated with biologic drugs. Patients with JIA demonstrated lower muscle strength and total body BMD compared to controls, but there were no differences in CRF and body composition. Physical fitness was comparable between the persistent oligoarticular and extended oligoarticular/polyarticular-JIA groups. In patients with JIA, we identified associations between higher vigorous physical activity and higher CRF and muscle strength, but did not find any association between physical fitness and disease variables. CONCLUSION: In this cohort of patients with JIA, we found suboptimal muscle strength and BMD compared to controls, but no differences in CRF and body composition. Vigorous physical activities appeared important for optimizing muscle strength and CRF in patients with JIA; the importance of such activities should be highlighted in patient education.

Dose-response associations between accelerometry measured physical activity and sedentary time and all cause mortality: systematic review and harmonised meta-analysis.

OBJECTIVE: To examine the dose-response associations between accelerometer assessed total physical activity, different intensities of physical activity, and sedentary time and all cause mortality. DESIGN: Systematic review and harmonised meta-analysis. DATA SOURCES: PubMed, PsycINFO, Embase, Web of Science, Sport Discus from inception to 31 July 2018. ELIGIBILITY CRITERIA: Prospective cohort studies assessing physical activity and sedentary time by accelerometry and associations with all cause mortality and reported effect estimates as hazard ratios, odds ratios, or relative risks with 95% confidence intervals. DATA EXTRACTION AND ANALYSIS: Guidelines for meta-analyses and systematic reviews for observational studies and PRISMA guidelines were followed. Two authors independently screened the titles and abstracts. One author performed a full text review and another extracted the data. Two authors independently assessed the risk of bias. Individual level participant data were harmonised and analysed at study level. Data on physical activity were categorised by quarters at study level, and study specific associations with all cause mortality were analysed using Cox proportional hazards regression analyses. Study specific results were summarised using random effects meta-analysis. MAIN OUTCOME MEASURE: All cause mortality. RESULTS: 39 studies were retrieved for full text review; 10 were eligible for inclusion, three were excluded owing to harmonisation challenges (eg, wrist placement of the accelerometer), and one study did not participate. Two additional studies with unpublished mortality data were also included. Thus, individual level data from eight studies (n=36 383; mean age 62.6 years; 72.8% women), with median follow-up of 5.8 years (range 3.0-14.5 years) and 2149 (5.9%) deaths were analysed. Any physical activity, regardless of intensity, was associated with lower risk of mortality, with a non-linear dose-response. Hazards ratios for mortality were 1.00 (referent) in the first quarter (least active), 0.48 (95% confidence interval 0.43 to 0.54) in the second quarter, 0.34 (0.26 to 0.45) in the third quarter, and 0.27 (0.23 to 0.32) in the fourth quarter (most active). Corresponding hazards ratios for light physical activity were 1.00, 0.60 (0.54 to 0.68), 0.44 (0.38 to 0.51), and 0.38 (0.28 to 0.51), and for moderate-to-vigorous physical activity were 1.00, 0.64 (0.55 to 0.74), 0.55 (0.40 to 0.74), and 0.52 (0.43 to 0.61). For sedentary time, hazards ratios were 1.00 (referent; least sedentary), 1.28 (1.09 to 1.51), 1.71 (1.36 to 2.15), and 2.63 (1.94 to 3.56). CONCLUSION: Higher levels of total physical activity, at any intensity, and less time spent sedentary, are associated with substantially reduced risk for premature mortality, with evidence of a non-linear dose-response pattern in middle aged and older adults. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018091808.

Sedentary Time and Physical Activity Surveillance Through Accelerometer Pooling in Four European Countries.

OBJECTIVE: The objective of this study was to pool, harmonise and re-analyse national accelerometer data from adults in four European countries in order to describe population levels of sedentary time and physical inactivity. METHODS: Five cross-sectional studies were included from England, Portugal, Norway and Sweden. ActiGraph accelerometer count data were centrally processed using the same algorithms. Multivariable logistic regression analyses were conducted to study the associations of sedentary time and physical inactivity with sex, age, weight status and educational level, in both the pooled sample and the separate study samples. RESULTS: Data from 9509 participants were used. On average, participants were sedentary for 530 min/day, and accumulated 36 min/day of moderate to vigorous intensity physical activity. Twenty-three percent accumulated more than 10 h of sedentary time/day, and 72% did not meet the physical activity recommendations. Nine percent of all participants were classified as high sedentary and low active. Participants from Norway showed the highest levels of sedentary time, while participants from England were the least physically active. Age and weight status were positively associated with sedentary time and not meeting the physical activity recommendations. Men and higher-educated people were more likely to be highly sedentary, while women and lower-educated people were more likely to be inactive. CONCLUSIONS: We found high levels of sedentary time and physical inactivity in four European countries. Older people and obese people were most likely to display these behaviours and thus deserve special attention in interventions and policy planning. In order to monitor these behaviours, accelerometer-based cross-European surveillance is recommended.