Choice of activity-intensity classification thresholds impacts upon accelerometer-assessed physical activity-health relationships in children

It is unknown whether using different published thresholds (PTs) for classifying physical activity (PA) impacts upon activity-health relationships. This study explored whether relationships between PA (sedentary [SED], light PA [LPA], moderate PA [MPA], moderate-to-vigorous PA, vigorous PA [VPA]) and health markers differed in children when classified using three different PTs

Modelling a response as a function of high frequency count data: the association between physical activity and fat mass

We present a new statistical modelling approach where the response is a function of high frequency count data. Our application is about investigating the relationship between the health outcome fat mass and physical activity (PA) measured by accelerometer. The accelerometer quantifies the intensity of physical activity as counts per epoch over a given period of time. We use data from the Avon longitudinal study of parents and children (ALSPAC) where accelerometer data is available as a time series of accelerometer counts per minute over seven days for a subset of children. In order to compare accelerometer profiles between individuals and to reduce the high dimension a functional summary of the profiles is used. We use the histogram as a functional summary due to its simplicity, suitability and ease of interpretation. Our model is an extension of generalised regression of scalars on functions or signal regression. It allows also multi-dimensional functional predictors and additive non-linear predictors for metric covariates. The additive multidimensional functional predictors allow investigating specific questions about whether the effect of PA varies over its intensity, by gender, by time of day or by day of the week. The key feature of the model is that it utilises the full profile of measured PA without requiring cut-points defining intensity levels for light, moderate and vigorous activity. We show that the (not necessarily causal) effect of PA is not linear and not constant over the activity intensity. Also, there is little evidence to suggest that the effect of PA intensity varies by gender or whether it happens on weekdays or on weekends

Cardiorespiratory fitness is associated with hard and light intensity physical activity but not time spent sedentary in 10–14 year old schoolchildren: the HAPPY study

Sedentary behaviour is a major risk factor for developing chronic diseases and is associated with low cardiorespiratory fitness in adults. It remains unclear how sedentary behaviour and different physical activity subcomponents are related to cardiorespiratory fitness in children. The purpose of this study was to assess how sedentary behaviour and different physical activity subcomponents are associated with 10–14 year-old schoolchildren's cardiorespiratory fitness

The frequency of osteogenic activities and the pattern of intermittence between periods of physical activity and sedentary behaviour affects bone mineral content: the cross-sectional NHANES study

BACKGROUND: Sedentary behaviours, defined as non exercising seated activities, have been shown to have deleterious effects on health. It has been hypothesised that too much sitting time can have a detrimental effect on bone health in youth. The aim of this study is to test this hypothesis by exploring the association between objectively measured volume and patterns of time spent in sedentary behaviours, time spent in specific screen-based sedentary pursuits and bone mineral content (BMC) accrual in youth. METHODS: NHANES 2005–2006 cycle data includes BMC of the femoral and spinal region via dual-energy X-ray absorptiometry (DEXA), assessment of physical activity and sedentary behaviour patterns through accelerometry, self reported time spent in screen based pursuits (watching TV and using a computer), and frequency of vigorous playtime and strengthening activities. Multiple regression analysis, stratified by gender was performed on N = 671 males and N = 677 females aged from 8 to 22 years. RESULTS: Time spent in screen-based sedentary behaviours is negatively associated with femoral BMC (males and females) and spinal BMC (females only) after correction for time spent in moderate and vigorous activity. Regression coefficients indicate that an additional hour per day of screen-based sitting corresponds to a difference of −0.77 g femoral BMC in females [95% CI: -1.31 to −0.22] and of −0.45 g femoral BMC in males [95% CI: -0.83 to −0.06]. This association is attenuated when self-reported engagement in regular (average 5 times per week) strengthening exercise (for males) and vigorous playing (for both males and females) is taken into account. Total sitting time and non screen-based sitting do not appear to have a negative association with BMC, whereas screen based sedentary time does. Patterns of intermittence between periods of sitting and moderate to vigorous activity appears to be positively associated with bone health when activity is clustered in time and inter-spaced with long continuous bouts of sitting. CONCLUSIONS: Some specific sedentary pursuits (screen-based) are negatively associated with bone health in youth. This association is specific to gender and anatomical area. This relationship between screen-based time and bone health is independent of the total amount of physical activity measured objectively, but not independent of self-reported frequency of strengthening and vigorous play activities. The data clearly suggests that the frequency, rather than the volume, of osteogenic activities is important in counteracting the effect of sedentary behaviour on bone health. The pattern of intermittence between sedentary periods and activity also plays a role in bone accrual, with clustered short bouts of activity interspaced with long periods of sedentary behaviours appearing to be more beneficial than activities more evenly spread in time

Anti-müllerian hormone is not associated with cardiometabolic risk factors in adolescent females

<p>Objectives: Epidemiological evidence for associations of Anti-Müllerian hormone (AMH) with cardiometabolic risk factors is lacking. Existing evidence comes from small studies in select adult populations, and findings are conflicting. We aimed to assess whether AMH is associated with cardiometabolic risk factors in a general population of adolescent females.</p> <p>Methods: AMH, fasting insulin, glucose, HDLc, LDLc, triglycerides and C-reactive protein (CRP) were measured at a mean age 15.5 years in 1,308 female participants in the Avon Longitudinal Study of Parents and Children (ALSPAC). Multivariable linear regression was used to examine associations of AMH with these cardiometabolic outcomes.</p> <p>Results: AMH values ranged from 0.16–35.84 ng/ml and median AMH was 3.57 ng/ml (IQR: 2.41, 5.49). For females classified as post-pubertal (n = 848) at the time of assessment median (IQR) AMH was 3.81 ng/ml (2.55, 5.82) compared with 3.25 ng/ml (2.23, 5.05) in those classed as early pubertal (n = 460, P≤0.001). After adjusting for birth weight, gestational age, pubertal stage, age, ethnicity, socioeconomic position, adiposity and use of hormonal contraceptives, there were no associations with any of the cardiometabolic outcomes. For example fasting insulin changed by 0% per doubling of AMH (95%CI: −3%,+2%) p = 0.70, with identical results if HOMA-IR was used. Results were similar after additional adjustment for smoking, physical activity and age at menarche, after exclusion of 3% of females with the highest AMH values, after excluding those that had not started menarche and after excluding those using hormonal contraceptives.</p> <p>Conclusion: Our results suggest that in healthy adolescent females, AMH is not associated with cardiometabolic risk factors.</p&gt

Physical activity and depression in adolescents: cross-sectional findings from the ALSPAC cohort

Purpose: Few studies have examined the association between physical activity (PA), measured objectively, and adolescent depressive symptoms. The aim of this study was to determine whether there is an association between objective measures of PA (total PA and time spent in moderate and vigorous PA (MVPA)) and adolescent depressive symptoms. Methods: Data on 2,951 adolescents participating in ALSPAC were used. Depressive symptoms were measured using the self-report Mood and Feelings Questionnaire (MFQ) (short version). Measures of PA were based on accelerometry. The association between PA and MFQ scores was modelled using ordinal regression. Results: Adolescents who were more physically active (total PA or minutes of MVPA) had a reduced odds of depressive symptoms [ORadj total PA (tertiles): medium 0.82 (95% CI: 0.69, 0.97); high 0.69 (95% CI: 0.57, 0.83)]; ORadj per 15 min MVPA: 0.92 (95% CI: 0.86, 0.98). In a multivariable model including both total PA and the percentage of time spent in MVPA, total PA was associated with depressive symptoms (ORadj total PA (tertiles): medium 0.82 (95% CI: 0.70, 0.98); high 0.70 (95% CI: 0.58, 0.85) but the percentage of time spent in MVPA was not independently associated with depressive symptoms [ORadj MVPA (tertiles) medium 1.05 (95% CI: 0.88, 1.24), high 0.91 (95% CI: 0.77, 1.09)]. Conclusions: The total amount of PA undertaken was associated with adolescent depressive symptoms, but the amount of time spent in MVPA, once total PA was accounted for, was not. If confirmed in longitudinal studies and randomised controlled trials, this would have important implications for public health messages.Nicola J. Wiles, Anne M. Haase, Debbie A. Lawlor, Andy Ness, Glyn Lewi

A calibration protocol for population-specific accelerometer cut-points in children

PurposeTo test a field-based protocol using intermittent activities representative of children\u27s physical activity behaviours, to generate behaviourally valid, population-specific accelerometer cut-points for sedentary behaviour, moderate, and vigorous physical activity.MethodsTwenty-eight children (46% boys) aged 10&ndash;11 years wore a hip-mounted uniaxial GT1M ActiGraph and engaged in 6 activities representative of children\u27s play. A validated direct observation protocol was used as the criterion measure of physical activity. Receiver Operating Characteristics (ROC) curve analyses were conducted with four semi-structured activities to determine the accelerometer cut-points. To examine classification differences, cut-points were cross-validated with free-play and DVD viewing activities.ResultsCut-points of &le;372, &gt;2160 and &gt;4806 counts&bull;min&minus;1 representing sedentary, moderate and vigorous intensity thresholds, respectively, provided the optimal balance between the related needs for sensitivity (accurately detecting activity) and specificity (limiting misclassification of the activity). Cross-validation data demonstrated that these values yielded the best overall kappa scores (0.97; 0.71; 0.62), and a high classification agreement (98.6%; 89.0%; 87.2%), respectively. Specificity values of 96&ndash;97% showed that the developed cut-points accurately detected physical activity, and sensitivity values (89&ndash;99%) indicated that minutes of activity were seldom incorrectly classified as inactivity.ConclusionThe development of an inexpensive and replicable field-based protocol to generate behaviourally valid and population-specific accelerometer cut-points may improve the classification of physical activity levels in children, which could enhance subsequent intervention and observational studies.<br /

Longitudinal changes in sedentary time and physical activity during adolescence

BACKGROUND: Low levels of physical activity and high time spent in sedentary activities have been associated with unfavourable health outcomes in adolescents. During adolescence, physical activity declines and sedentary time increases, however little is known about whether the magnitude of these changes differs within or between school-time, after-school time, or at weekends. METHODS: Adolescents (n = 363) participating in the PEACH (Personal and Environmental Associations with Children’s Health) project provided accelerometer data at 12 and 15 years of age. Data were collected in 2008/2009 and 2012/2013. Time spent sedentary (<100 cpm), in light physical activity (LPA (100-2295 cpm) and in moderate to vigorous physical activity (MVPA: ≥ 2296 cpm) were generated for school-time, after-school time and for weekends using school-specific start and finish times. All data were analysed in 2014. RESULTS: The proportion of time spent sedentary significantly increased during school (+8.23%, 95% CI = 7.35 to 9.13), after-school (+6.99%, 95% CI = 5.91 to 8.07) and at weekends (+6.86%, 95% CI = 5.10 to 8.62). A parallel decrease was found in the proportion of time spent in LPA during school (-7.62%, 95% CI = -8.26 to -6.98), after-school (-7.01%, 95% CI = -7.74 to -6.28) and at weekends (-6.72%, 95% CI = -7.80 to -5.65). The proportion of time spent in MVPA remained relatively stable during school (-0.64, 95% CI = -1.11 to -0.18), after-school (0.04%, 95% CI = -0.58 to 0.67) and at weekends (-0.14%, 95% CI = -1.18 to 0.90). CONCLUSIONS: Objectively measured sedentary time increased between 12 and 15 years of age during-school, after-school, and at weekends, suggesting that interventions aiming to reduce the age-associated changes in sedentary time are needed in all three time contexts. Future work should identify which sedentary activities change more than others to inform interventions which aim to minimise the increase in time spent sedentary during adolescence

Seasonal variation in objectively measured physical activity, sedentary time, cardio-respiratory fitness and sleep duration among 8–11 year-old Danish children: a repeated-measures study

Abstract Background Understanding fluctuations in lifestyle indicators is important to identify relevant time periods to intervene in order to promote a healthy lifestyle; however, objective assessment of multiple lifestyle indicators has never been done using a repeated-measures design. The primary aim was, therefore, to examine between-season and within-week variation in physical activity, sedentary behaviour, cardio-respiratory fitness and sleep duration among 8–11 year-old children. Methods A total of 1021 children from nine Danish schools were invited to participate and 834 accepted. Due to missing data, 730 children were included in the current analytical sample. An accelerometer was worn for 7 days and 8 nights during autumn, winter and spring, from which physical activity, sedentary time and sleep duration were measured. Cardio-respiratory fitness was assessed using a 10-min intermittent running test. Results The children had 5% more sedentary time, 23% less time in moderate-to-vigorous physical activity and 2% longer sleep duration during winter compared to spring and cardio-respiratory fitness was 4% higher during spring compared to autumn (P < 0.001). Sedentary time was higher and total physical activity, moderate-to-vigorous physical activity and sleep duration (boys only) were lower during weekends at all seasons (P ≤ 0.01). Intraclass correlation coefficients between seasons ranged from 0.47-0.74, leaving 45-78% to seasonal variation. Conclusions Overall, sedentary time was higher and physical activity lower during winter and during weekends. The most accurate and unbiased estimates of physical activity came from autumn; however, the considerable intra-individual variation suggests that a single measurement may not adequately characterise children’s habitual sleep and activity

Actigraph Accelerometer-Defined Boundaries for Sedentary Behaviour and Physical Activity Intensities in 7 Year Old Children

Background: Accurate objective assessment of sedentary and physical activity behaviours during childhood is integral to the understanding of their relation to later health outcomes, as well as to documenting the frequency and distribution of physical activity within a population.Purpose: To calibrate the Actigraph GT1M accelerometer, using energy expenditure (EE) as the criterion measure, to define thresholds for sedentary behaviour and physical activity categories suitable for use in a large scale epidemiological study in young children.Methods: Accelerometer-based assessments of physical activity (counts per minute) were calibrated against EE measures (kcal.kg(-1).hr(-1)) obtained over a range of exercise intensities using a COSMED K4b(2) portable metabolic unit in 53 seven-year-old children. Children performed seven activities: lying down viewing television, sitting upright playing a computer game, slow walking, brisk walking, jogging, hopscotch and basketball. Threshold count values were established to identify sedentary behaviour and light, moderate and vigorous physical activity using linear discriminant analysis (LDA) and evaluated using receiver operating characteristic (ROC) curve analysis.Results: EE was significantly associated with counts for all non-sedentary activities with the exception of jogging. Threshold values for accelerometer counts (counts. minute(-1)) were = 3841 for light, moderate and vigorous physical activity respectively. The area under the ROC curves for discrimination of sedentary behaviour and vigorous activity were 0.98. Boundaries for light and moderate physical activity were less well defined (0.61 and 0.60 respectively). Sensitivity and specificity were higher for sedentary (99% and 97%) and vigorous (95% and 91%) than for light (60% and 83%) and moderate (61% and 76%) thresholds.Conclusion: The accelerometer cut points established in this study can be used to classify sedentary behaviour and to distinguish between light, moderate and vigorous physical activity in children of this age