Apple Watch 6 vs. Galaxy Watch 4: A Validity Study of Step-Count Estimation in Daily Activities.

The purpose of this study was to examine the validity of two wearable smartwatches (the Apple Watch 6 (AW) and the Galaxy Watch 4 (GW)) and smartphone applications (Apple Health for iPhone mobiles and Samsung Health for Android mobiles) for estimating step counts in daily life. A total of 104 healthy adults (36 AW, 25 GW, and 43 smartphone application users) were engaged in daily activities for 24 h while wearing an ActivPAL accelerometer on the thigh and a smartwatch on the wrist. The validities of the smartwatch and smartphone estimates of step counts were evaluated relative to criterion values obtained from an ActivPAL accelerometer. The strongest relationship between the ActivPAL accelerometer and the devices was found for the AW (r = 0.99, p < 0.001), followed by the GW (r = 0.82, p < 0.001), and the smartphone applications (r = 0.93, p < 0.001). For overall group comparisons, the MAPE (Mean Absolute Percentage Error) values (computed as the average absolute value of the group-level errors) were 6.4%, 10.5%, and 29.6% for the AW, GW, and smartphone applications, respectively. The results of the present study indicate that the AW and GW showed strong validity in measuring steps, while the smartphone applications did not provide reliable step counts in free-living conditions.

Physical Activity Levels and Sedentary Behavior of People Living With Mild Cognitive Impairment: A Cross-Sectional Study Using Thigh-Worn Accelerometers.

Community-dwelling people with Mild Cognitive Impairment self-reporting not to be meeting recommended physical activity levels participated in this study to (a) determine compliance of wearing (thigh-worn) accelerometers, (b) describe physical activity levels and sedentary behavior, and (c) determine the validity of the Physical Activity Scale for the Elderly (PASE) compared with activPAL accelerometers. A total of 79 people had valid accelerometer data (median [interquartile range]: age, 71 [54-75] years). Compliance was 86.81%. Participants were sedentary for 10.6 hr per day and engaged in a median of 9 min per day of moderate-intensity physical activity. Fair correlations were found between the PASE and total stepping time per day (r = .35, p < .01), total number of steps per day (r = .36, p < .01), and number of steps in stepping activities completed for ≤1 min (r = .42, p < .01). The PASE and Standing time (r = .04, p = .724) and PASE and Sitting time (r = .04, p = .699) had little to no relationship. The use of thigh-worn accelerometers for this population is achievable. People with Mild Cognitive Impairment have high levels of sedentary behavior and minimal engagement in moderate-intensity physical activity. The PASE has fair, positive criterion validity with activity-based outcomes measured by activPAL accelerometers but not with sedentary behavior, which is high for this population.

Associations between physical activity, sedentary behaviour and cognitive domain performance of people living with mild cognitive impairment in the community.

INTRODUCTION: Physical activity is known to positively influence cognitive performance. For adults with mild cognitive impairment (MCI), the relationship between physical activity levels and cognitive performance is unknown. This cross-sectional study aimed to determine if cognitive performance [as measured by the Montreal Cognitive Assessment (MoCA)] of people living in the community with MCI is associated with their physical activity levels or sedentary behaviour. METHODS: ActivPAL™ accelerometers were used to objectively measure physical activity and sedentary behaviour for seven full days. Cognitive performance was measured using the MoCA. CONSUMER AND COMMUNITY INVOLVEMENT: No involvement other than as research participants RESULTS: Eighty-two participants from the Balance on the Brain randomised controlled trial were included. Most participants were retired (88%), with 33 (40%) reporting a fall in the last year. The median MoCA score was 24 (IQR 22-26). Participants achieved a mean of 6296 (±2420) steps per day and were sedentary for 10.6 (±2) hours per day. The only physical activity outcomes that had a fair, positive correlation were moderate- to vigorous-intensity physical activity measures of total stepping time and total number of steps (with a cadence of ≥100 steps/min) with the orientation MoCA domain score (r(82) = 0.36, p ≤ 0.001 and r(82) = 0.37, p ≤ 0.001, respectively). Higher total sedentary time had a weak, positive correlation with better visuospatial/executive performance (r(82) = 0.23, p = 0.041). The orientation outcomes remained significant when analysed in an adjusted logistic regression model. CONCLUSION: This study found that performance in the MoCA orientation domain had a fair-positive correlation with moderate-intensity physical activity (i.e., stepping time and step count with a cadence of ≥100 steps/min) as measured by a thigh-worn accelerometer for community-dwelling older adults with MCI. When considering the relationship between cognitive domains and sedentary behaviour, consideration may be needed regarding whether cognitive enhancing activities (such as crosswords and other brain games) are being performed, which may confound this relationship. Further investigation is required to confirm these results.

Interrupting bedtime to reverse frailty levels in acute care: a study protocol for the Breaking Bad Rest randomized controlled trial.

BACKGROUND: Hospitalized older patients spend most of the waking hours in bed, even if they can walk independently. Excessive bedrest contributes to the development of frailty and worse hospital outcomes. We describe the study protocol for the Breaking Bad Rest Study, a randomized clinical trial aimed to promoting more movement in acute care using a novel device-based approach that could mitigate the impact of too much bedrest on frailty. METHODS: Fifty patients in a geriatric unit will be randomized into an intervention or usual care control group. Both groups will be equipped with an activPAL (a measure of posture) and StepWatch (a measure of step counts) to wear throughout their entire hospital stay to capture their physical activity levels and posture. Frailty will be assessed via a multi-item questionnaire assessing health deficits at admission, weekly for the first month, then monthly thereafter, and at 1-month post-discharge. Secondary measures including geriatric assessments, cognitive function, falls, and hospital re-admissions will be assessed. Mixed models for repeated measures will determine whether daily activity differed between groups, changed over the course of their hospital stay, and impacted frailty levels. DISCUSSION: This randomized clinical trial will add to the evidence base on addressing frailty in older adults in acute care settings through a devices-based movement intervention. The findings of this trial may inform guidelines for limiting time spent sedentary or in bed during a patient's stay in geriatric units, with the intention of scaling up this study model to other acute care sites if successful. TRIAL REGISTRATION: The protocol has been registered at clinicaltrials.gov (identifier: NCT03682523).

Physical Activity Assessed by Wrist and Thigh Worn Accelerometry and Associations with Cardiometabolic Health.

Physical activity is increasingly being captured by accelerometers worn on different body locations. The aim of this study was to examine the associations between physical activity volume (average acceleration), intensity (intensity gradient) and cardiometabolic health when assessed by a thigh-worn and wrist-worn accelerometer. A sample of 659 office workers wore an Axivity AX3 on the non-dominant wrist and an activPAL3 micro on the right thigh concurrently for 24 h a day for 8 days. An average acceleration (proxy for physical activity volume) and intensity gradient (intensity distribution) were calculated from both devices using the open-source raw accelerometer processing software GGIR. Clustered cardiometabolic risk (CMR) was calculated using markers of cardiometabolic health, including waist circumference, triglycerides, HDL-cholesterol, mean arterial pressure and fasting glucose. Linear regression analysis assessed the associations between physical activity volume and intensity gradient with cardiometabolic health. Physical activity volume derived from the thigh-worn activPAL and the wrist-worn Axivity were beneficially associated with CMR and the majority of individual health markers, but associations only remained significant after adjusting for physical activity intensity in the thigh-worn activPAL. Physical activity intensity was associated with CMR score and individual health markers when derived from the wrist-worn Axivity, and these associations were independent of volume. Associations between cardiometabolic health and physical activity volume were similarly captured by the thigh-worn activPAL and the wrist-worn Axivity. However, only the wrist-worn Axivity captured aspects of the intensity distribution associated with cardiometabolic health. This may relate to the reduced range of accelerations detected by the thigh-worn activPAL.

Beyond the Clinic: Maximum Free-Living Stepping as a Potential Measure of Physical Performance.

Measures of physical performance captured within a clinical setting are commonly used as a surrogate for underlying health or disease risk within an individual. By measuring physical behaviour within a free-living setting, we may be able to better quantify physical performance. In our study, we outline an approach to measure maximum free-living step count using a body-worn sensor as an indicator of physical performance. We then use this approach to characterise the maximum step count over a range of window durations within a population of older adults to identify a preferred duration over which to measure the maximum step count. We found that while almost all individuals (97%) undertook at least one instance of continuous stepping longer than two minutes, a sizeable minority of individuals (31%) had no periods of continuous stepping longer than six minutes. We suggest that the maximum step count measured over a six-minute period may be too sensitive to the adults' lack of opportunity to undertake prolonged periods of stepping, and a two-minute window could provide a more representative measure of physical performance.

CHAP-child: an open source method for estimating sit-to-stand transitions and sedentary bout patterns from hip accelerometers among children.

BACKGROUND: Hip-worn accelerometer cut-points have poor validity for assessing children's sedentary time, which may partly explain the equivocal health associations shown in prior research. Improved processing/classification methods for these monitors would enrich the evidence base and inform the development of more effective public health guidelines. The present study aimed to develop and evaluate a novel computational method (CHAP-child) for classifying sedentary time from hip-worn accelerometer data. METHODS: Participants were 278, 8-11-year-olds recruited from nine primary schools in Melbourne, Australia with differing socioeconomic status. Participants concurrently wore a thigh-worn activPAL (ground truth) and hip-worn ActiGraph (test measure) during up to 4 seasonal assessment periods, each lasting up to 8 days. activPAL data were used to train and evaluate the CHAP-child deep learning model to classify each 10-s epoch of raw ActiGraph acceleration data as sitting or non-sitting, creating comparable information from the two monitors. CHAP-child was evaluated alongside the current practice 100 counts per minute (cpm) method for hip-worn ActiGraph monitors. Performance was tested for each 10-s epoch and for participant-season level sedentary time and bout variables (e.g., mean bout duration). RESULTS: Across participant-seasons, CHAP-child correctly classified each epoch as sitting or non-sitting relative to activPAL, with mean balanced accuracy of 87.6% (SD = 5.3%). Sit-to-stand transitions were correctly classified with mean sensitivity of 76.3% (SD = 8.3). For most participant-season level variables, CHAP-child estimates were within ± 11% (mean absolute percent error [MAPE]) of activPAL, and correlations between CHAP-child and activPAL were generally very large (> 0.80). For the current practice 100 cpm method, most MAPEs were greater than ± 30% and most correlations were small or moderate (≤ 0.60) relative to activPAL. CONCLUSIONS: There was strong support for the concurrent validity of the CHAP-child classification method, which allows researchers to derive activPAL-equivalent measures of sedentary time, sit-to-stand transitions, and sedentary bout patterns from hip-worn triaxial ActiGraph data. Applying CHAP-child to existing datasets may provide greater insights into the potential impacts and influences of sedentary time in children.

Effect of the knee replacement surgery on activity level based on ActivPAL: a systematic review and meta-analysis study.

BACKGROUND: The knee replacement (KR) surgery aims to restore the activity level and reduce the risk of experiencing disabilities. The outcomes of this surgery are evaluated mainly with subjective tools or low validity objective tools. However, the effect of the surgery on activity level using high validity objective accelerometer is still in question. METHODS: A systematic review and meta-analysis were conducted to evaluate the benefit of KR surgery alone to enhance physical activity recommendations based on high validity accelerometer. Two independent reviewers evaluated five electronic databases (Cochrane-Central-Register-of-Controlled Trials, EMBASE, PubMed, Web of Science, and Scopus) to find relative studies between January 2000 and October 2021. The quality assessments and risk of bias assessments were examined. RESULTS: Three articles were included with 202 participants (86 males, 116 females), with an average age of 64 years and an average 32 kg/m2 body mass index. The results found that the number of steps was significantly improved up to 36.35 and 45.5% after 6-months and 1-year of the surgery, respectively. However, these changes did not meet the recommended activity level guideline and could be related to the patients' health status and their activity level before the surgery. No significant changes were seen in sedentary time, standing time, and upright time after 6-months and 1-year follow-ups. Heterogeneity among studies was low to moderate (0-63%). CONCLUSION: Knee replacement surgery is an effective treatment for improving patients' quality of life with severe knee injuries. However, various factors impact the success of surgical and achieving maximum benefit of the surgery. One factor, sedentary time, can be reduced by implementing pre-and post-surgery exercise or physical activity recommendations. Further studies are needed to understand the benefit of surgery with or without rehabilitation assessed using high validity monitors.

Pain and fatigue are longitudinally and bi-directionally associated with more sedentary time and less standing time in rheumatoid arthritis.

OBJECTIVES: The aims of this study were to examine the longitudinal and bi-directional associations of pain and fatigue with sedentary, standing and stepping time in RA. METHODS: People living with RA undertook identical assessments at baseline (T1, n = 104) and 6-month follow-up (T2, n = 54). Participants completed physical measures (e.g. height, weight, BMI) and routine clinical assessments to characterize RA disease activity (DAS-28). Participants also completed questionnaires to assess physical function (HAQ), pain (McGill Pain Questionnaire) and fatigue (Multidimensional Assessment of Fatigue Scale). Participants' free-living sedentary, standing and stepping time (min/day) were assessed over 7 days using the activPAL3µ™. For the statistical analysis, hierarchical regression analysis was employed to inform the construction of path models, which were subsequently used to examine bi-directional associations of pain and fatigue with sedentary, standing and stepping time. Specifically, where significant associations were observed in longitudinal regression analysis, the bi-directionality of these associations was further investigated via path analysis. For regression analysis, bootstrapping was applied to regression models to account for non-normally distributed data, with significance confirmed using 95% CIs. Where variables were normally distributed, parametric, non-bootstrapped statistics were also examined (significance confirmed via ß coefficients, with P < 0.05) to ensure all plausible bi-directional associations were examined in path analysis. RESULTS: Longitudinal bootstrapped regression analysis indicated that from T1 to T2, change in pain, but not fatigue, was positively associated with change in sedentary time. In addition, change in pain and fatigue were negatively related to change in standing time. Longitudinal non-bootstrapped regression analysis demonstrated a significant positive association between change in fatigue with change in sedentary time. Path analysis supported the hypothesized bi-directionality of associations between change in pain and fatigue with change in sedentary time (pain, ß = 0.38; fatigue, ß = 0.44) and standing time (pain, ß = -0.39; fatigue, ß = -0.50). CONCLUSION: Findings suggest pain and fatigue are longitudinally and bi-directionally associated with sedentary and standing time in RA.

Validity of accelerometry for predicting physical activity and sedentary time in ambulatory children and young adults with cerebral palsy.

BACKGROUND: /Objectives: This study aimed to validate five published ActiGraph (AG) cut-off points for the measurements of physical activity (PA) and sedentary time (ST) in ambulatory children and young adults with cerebral palsy (CP). Additionally, four energy expenditure (EE) prediction equations based on AG counts and activPAL (AP) steps were examined in this population, using oxygen uptake (VO2) as the criterion. METHODS: Four male and six female participants with CP (Gross Motor Function Classification System levels I-III, ages 9-21 years) completed seven activities while simultaneously wearing an AG, AP monitor and indirect calorimetry unit. VO2 was measured on a breath-by-breath basis using the indirect calorimetry and was converted into EE using metabolic equivalents. AG counts were classified as sedentary, light PA (LPA) or moderate-to-vigorous PA (MVPA) using five cut-off points: Puyau, Evenson, Romanzini, Clanchy and Baque. The predicted EE was computed using three AG-based equations (Freedson, Trost and Treuth) and an AP step-based equation. RESULTS: Based on 1920 available data points from the 10 participants, Baque (r = 0.896, κ = 0.773) and Clanchy (r = 0.935, κ = 0.721) AG cut-off points classified PA and ST most accurately. All the equations overestimated EE during sitting activities and underestimated EE during rapid walking. The Freedson, Treuth and AP equations exhibited systematic bias during rapid walking, as their differences from the criterion measure increased progressively with increasing activity intensity. CONCLUSIONS: The AG accurately classified PA and ST when the Baque and Clanchy cut-off points were used. However, none of the available AG or AP equations accurately predicted the EE during PA and ST in children and young adults with CP. Further development is needed to ensure that both devices can estimate EE accurately in this population.

Validity of self-reported and objectively measured sedentary behavior in pregnancy.

BACKGROUND: Sedentary behavior (SED) is a potential risk factor for poor pregnancy outcomes. We evaluated the validity of several common and one new method to assess SED across three trimesters of pregnancy. METHODS: This cohort study of pregnant women measured objective and self-reported SED each trimester via thigh-worn activPAL3 micro (criterion), waist-worn Actigraph GT3X, and self-report from the Pregnancy Physical Activity Questionnaire (PPAQ) and the de novo Sedentary Behavior Two Domain Questionnaire (SB2D). SED (hours per day) and percent time in SED (SED%) from activPAL were compared to GT3X, SB2D, and PPAQ using Pearson's r, ICC, Bland-Altman analysis, and comparison of criterion SED and SED% across tertiles of alternative methods. RESULTS: Fifty-eight women (mean age 31.5 ± 4.8 years; pre-pregnancy BMI 25.1 ± 5.6 kg/m2; 76% white) provided three trimesters of valid activPAL data. Compared to activPAL, GT3X had agreement ranging from r = 0.54-0.66 and ICC = 0.52-0.65. Bland-Altman plots revealed small mean differences and unpatterned errors, but wide limits of agreement (greater than ±2 h and ± 15%). The SB2D and PPAQ had r < 0.5 and ICC < 0.3 vs. activPAL SED, with lower agreement during the 2nd and 3rd trimesters, and performed poorly in Bland-Altman analyses. SED% from the modified SB2D performed best of the self-reported instruments with modest mean differences, r ranging from 0.55 to 0.60, and ICCs from 0.31-0.33; though, limits of agreement were greater than ±35%. Significant trends in activPAL SED were observed across increasing tertiles of SB2D SED in the 1st and 3rd trimesters (both p ≤ 0.001), but not the 2nd trimester (p = 0.425); and for PPAQ SED in the 1st and 2nd trimesters (both p < 0.05), but not the 3rd trimester (p = 0.158). AcitvPAL SED and SED% increased significantly across tertiles of GT3X SED and SED% as well as SB2D SED% (all p-for-trend ≤ 0.001). CONCLUSIONS: Compared to activPAL, waist-worn GT3X produced moderate agreement, though similar mean estimates of SED across pregnancy. Self-report questionnaires had large absolute error and wide limits of agreement for SED hr./day; SB2D measurement of SED% was the best self-report method. These data suggest activPAL be used to measure SED when possible, followed by GT3X, and - when necessary - SB2D assessing SED% in pregnancy. TRIAL REGISTRATION: www.clinicaltrials.gov NCT03084302 on 3/20/2017.

Detecting prolonged sitting bouts with the ActiGraph GT3X.

The ActiGraph has a high ability to measure physical activity; however, it lacks an accurate posture classification to measure sedentary behavior. The aim of the present study was to develop an ActiGraph (waist-worn, 30 Hz) posture classification to detect prolonged sitting bouts, and to compare the classification to proprietary ActiGraph data. The activPAL, a highly valid posture classification device, served as reference criterion. Both sensors were worn by 38 office workers over a median duration of 9 days. An automated feature selection extracted the relevant signal information for a minute-based posture classification. The machine learning algorithm with optimal feature number to predict the time in prolonged sitting bouts (≥5 and ≥10 minutes) was searched and compared to the activPAL using Bland-Altman statistics. The comparison included optimized and frequently used cut-points (100 and 150 counts per minute (cpm), with and without low-frequency-extension (LFE) filtering). The new algorithm predicted the time in prolonged sitting bouts most accurate (bias ≤ 7 minutes/d). Of all proprietary ActiGraph methods, only 150 cpm without LFE predicted the time in prolonged sitting bouts non-significantly different from the activPAL (bias ≤ 18 minutes/d). However, the frequently used 100 cpm with LFE accurately predicted total sitting time (bias ≤ 7 minutes/d). To study the health effects of ActiGraph measured prolonged sitting, we recommend using the new algorithm. In case a cut-point is used, we recommend 150 cpm without LFE to measure prolonged sitting and 100 cpm with LFE to measure total sitting time. However, both cpm cut-points are not recommended for a detailed bout analysis.

Minimum accelerometer wear-time for reliable estimates of physical activity and sedentary behaviour of people receiving haemodialysis.

BACKGROUND: Low levels of physical activity are implicated in low life expectancies of people receiving maintenance haemodialysis. Accelerometers are increasingly being used to quantify activity behaviours of this population but guidance to quality-assure such data is lacking. The objective of this study was to provide data processing and reduction recommendations to ensure accelerometer-derived outcomes are sufficiently reliable for interpretative analysis. METHODS: Seventy people receiving maintenance haemodialysis (age 55.9 ± 15.7 years, 34% women, 23% diabetic) from a single outpatient renal unit volunteered for the study. Participants wore Actigraph GT3x and ActivPAL monitors during waking hours over seven days. Reliability of accelerometer output (normalised to wear-time) was assessed via intraclass correlation coefficient (ICC). The Spearman-Brown prophecy formula was subsequently applied to the ICCs to derive the minimum required accelerometer wear-time for each behavioural outcome. RESULTS: Monitor wear compliance was greater on dialysis compared to non-dialysis days (90% v 77%). Participants were significantly more active on non-dialysis days compared to dialysis days but there were no significant differences in estimated behaviours between days within the same condition. Average measure ICCs for all accelerometer outcomes were high (range 0.76-0.96). Computations indicated that habitual physical activity and sedentary behaviour could be estimated with a minimum reliability level of 0.80 from one dialysis day and two non-dialysis days, and at least eight hours monitor wear per day. Applying this rubric allowed 90% of participant data to be retained for further analysis. CONCLUSIONS: Regardless of accelerometer, one dialysis and two non-dialysis days data with a minimum of eight hours wear each day should enable habitual activity of people receiving maintenance haemodialysis to be characterised with acceptable reliability. These recommendations reconcile the tension between wear-time criteria stringency and retention of an adequately representative sample.

Cross-sectional associations between personality traits and device-based measures of step count and sedentary behaviour in older age: the Lothian Birth Cohort 1936.

BACKGROUND: While the associations between personality traits and self-reported physical activity are well replicated, few studies have examined the associations between personality and device-based measures of both physical activity and sedentary behaviour. Low levels of physical activity and high levels of sedentary behaviour are known risk factors for poorer health outcomes in older age. METHODS: We used device-based measures of physical activity and sedentary behaviour recorded over 7 days in 271 79-year-old participants of the Lothian Birth Cohort 1936. Linear regression models were used to assess whether personality traits were cross-sectionally associated with step count, sedentary time, and the number of sit-to-stand transitions. Personality traits were entered one at a time, and all-together, controlling for age and sex in Model 1 and additionally for BMI and limiting long-term illness in Model 2. RESULTS: None of the associations between personality traits and measures of physical activity and sedentary behaviours remained significant after controlling for multiple-comparisons using the False Discovery Rate test (all ps > .07). CONCLUSIONS: We found no evidence that personality traits are associated with device-based measures of physical activity or sedentary behaviour in older age. More studies are needed to replicate and examine the nature of these relationships.

Ethnic differences in sedentary behaviour in 6-8-year-old children during school terms and school holidays: a mixed methods study.

BACKGROUND: Sedentary behaviour (SB) in childhood is a major public health concern. Little is known about ethnic differences in SB during school and holiday weeks among White British (WB) and South Asian (SA) children, which this study aims to address through investigating inclinometer measured SB and exploring reasons for child engagement in SB. METHODS: A mixed methods study, comprising of a quantitative investigation with 160, 6-8 years old children and a qualitative study with a subsample of 18 children, six parents and eight teachers was undertaken. Children of WB and SA ethnicity in three schools were invited to wear inclinometers for seven school terms (summer/winter/spring) and seven holidays (winter/spring) days during July 2016-May 2017. Total SB, SB accumulated in bouts > 30 min and breaks in SB were explored using multivariate linear mixed effects models which adjusted for wear time, sex, deprivation, overweight status, season, term, weekday and school. Nine focus groups and two interviews were carried out using the Theoretical Domains Framework to explore SB perceptions among parents, teachers and children. Data were analysed using the Framework Approach. RESULTS: 104/160 children provided 836 valid days of data. Children spent on average eight hours of SB/day during term time and holidays, equating to 60% of their awake time, and had on average 111 SB breaks /day. SA children had 25 fewer SB breaks/ day when compared to WB (p < 0.001). Perceived reasons for engagement in SB included: boredom, enjoyment of screen activities (by children), parenting practices, curriculum pressures (by teachers), the need to sit down and learn, and child's preference for screen activities (by parents). CONCLUSIONS: Children spent 60% of their awake time being sedentary, regardless of ethnicity or school term. There were no significant ethnic differences for any of the SB outcomes except for breaks in SB. Interventions aimed at reducing SB should consider involving parents and teachers and should focus on increasing breaks in SB, especially for SA children, who are at a higher risk of cardio metabolic ill health.

Associations of sedentary time and self-reported television time during pregnancy with incident gestational diabetes and plasma glucose levels in women at risk of gestational diabetes in the UK.

BACKGROUND: Sedentary time is associated with increased risk of type 2 diabetes, but the association between objectively measured sedentary time and incident gestational diabetes mellitus (GDM) has not been tested. The purpose of this paper is to test associations between objectively measured sedentary time and self-reported television time during pregnancy with incident GDM and plasma glucose levels among women at high risk for GDM. METHODS: At 20 weeks' gestation, pregnant women (n = 188) in the North East of England with a risk factor for GDM wore an activPAL accelerometer and reported their usual television time. Participants underwent a standard oral glucose tolerance test at 24-28 weeks' gestation. Regression analyses were used to test for associations of total and prolonged sedentary time, breaks in sedentary time, and television time with GDM and fasting and 2-h glucose levels. Interaction terms were applied to examine whether the association between each indicator of sedentary time and glucose levels differed by GDM status. RESULTS: Total sedentary time (hours/day) was not associated with incident GDM (OR 1.00 (95%CI 1.00, 1.01)). The association between total sedentary time and glucose levels depended on GDM status: sedentary time was associated with fasting (ß = 0.16 (95%CI 0.01, 0.31)) and 2-h (ß = 0.15 (95%CI 0.01, 0.30)) glucose levels for those without GDM, while breaks in sedentary time were associated with lower fasting (ß = - 0.55 (95%CI - 0.92, - 0.17)) and 2-h (ß = - 0.40 (95%CI - 0.77, - 0.03)) glucose levels for those with GDM. Prolonged sedentary time was associated with higher fasting glucose levels regardless of GDM status (ß 0.15 (0.01, 0.30)). Television time was associated with development of GDM (OR 3.03 (95%CI 1.21, 7.96)) but not with plasma glucose levels. CONCLUSIONS: This is the first study to test associations between posture-based measures of sedentary time during pregnancy and GDM and glucose levels. The findings presented here suggest the possible importance of minimizing or breaking up sedentary time for the management of glucose levels during pregnancy, at least among women at high risk of GDM. Further research is needed to understand the different roles of total sedentary time and television time in the development of GDM.

Criterion validity and test-retest reliability of SED-GIH, a single item question for assessment of daily sitting time.

BACKGROUND: Sedentary behaviour has been closely linked to metabolic and cardiovascular health and is therefore of importance in disease prevention. A user-friendly tool for assessment of sitting time is thus needed. Previous studies concluded that the present tools used to assess a number of sedentary behaviours are more likely to overestimate sitting than single-item questions which often underestimate sitting time, and that categorical answering options are recommended. In line with this, the single-item question with categorical answering options, SED-GIH, was developed. The aim of this study was to investigate the criterion validity of the SED-GIH question using activPAL3 micro as the criterion measure. The second aim was to evaluate the test-retest reliability of the SED-GIH questionnaire. METHOD: In the validity section of this study, 284 middle-aged adults answered a web questionnaire, which included SED-GIH, wore activPAL and filled in a diary log for one week. Spearman's rho assessed the relationship between the SED-GIH answers and the daily average sitting time as monitored by the activPAL (activPAL-SIT), a Weighted Kappa assessed the agreement, ANOVA assessed differences in activPAL-SIT between the SED-GIH answer categories, and a Chi2 compared the proportions of hazardous sitters between the different SED-GIH answer categories. In the reliability section, 95 elderly participants answered the SED-GIH question twice, with a mean interval of 5.2 days. The reliability was assessed with ICC and a weighted Kappa. RESULTS: The SED-GIH question correlated moderately with activPAL-SIT (rho = 0.31), with a poor agreement (weighted Kappa 0.12). In total, 40.8% underestimated and 22.2% overestimated their sitting time. The ANOVA showed significant differences in activPAL-SIT between the different SED-GIH answer categories (p < 0.001). The Chi2 showed a significant difference in proportion of individuals sitting more than 10 h per day within each SED-GIH answer category. ICC for the test-retest reliability of SED-GIH was excellent with ICC = 0.86, and the weighted Kappa showed an agreement of 0.77. CONCLUSIONS: The unanchored single item SED-GIH question showed excellent reliability but poor validity in the investigated populations. Validity and reliability of SED-GIH is in line with other questionnaires that are commonly used when assessing sitting time.

Exploring when and how adolescents sit: cross-sectional analysis of activPAL-measured patterns of daily sitting time, bouts and breaks.

BACKGROUND: This study describes patterns of adolescents' objectively-measured sitting volume, sitting bouts, and breaks in sitting during different days and periods of the day, and explored differences by sex and weekdays versus weekend days. METHODS: ActivPAL™ data were collected in August 2014-December 2015 from adolescents attending secondary government schools in Melbourne Australia. Eight periods (early morning, mid-morning, morning break, late morning, lunch, early afternoon, late-afternoon and evening) were extracted for each day. School time, class time and out-of-school time were also extracted for weekdays. The percentage of time sitting, percentage of each hour in prolonged sitting (sitting bout ≥10 min), and number of sitting breaks/hour were calculated for each period. Differences by sex, and week and weekend days were determined using t-tests. RESULTS: Participants (n = 297, 15.4 ± 1.6 years) spent 68% of their day sitting; ~ 30% of each hour in prolonged sitting and 3.1 sitting breaks/hour. Sitting time was greater during class time (75%) and school (70%) compared to out-of-school time (65%). Sitting patterns differed between week and weekend days for all periods except the evening period. Girls had higher proportion of sitting during class than boys (76% vs 72% respectively) and school hours (72% vs 67%), more prolonged sitting during school hours (27% vs 23%), and more sitting breaks per hour during out-of-school time (2.6 vs 2.4), but fewer during class (2.5 vs 3.3) and school hours (2.7 vs 3.3). Sitting patterns did not differ by sex on weekend days. CONCLUSIONS: Adolescents spent two-thirds of their waking hours sitting, with distinct patterns on weekdays and weekend days. Even though boys and girls were exposed to the same school day routine, girls spent more time sitting and had fewer sitting breaks. Class times, school breaks and the evening period were identified as key intervention periods. Further research is needed to understand the behavioural differences, and guide future intervention design.

Comparison of Habitual Physical Activity and Sedentary Behavior in Adolescents and Young Adults With and Without Cerebral Palsy.

PURPOSE: The comparison of habitual physical activity and sedentary time in teenagers and young adults with cerebral palsy (CP) with typically developed (TD) peers can serve to quantify activity shortcomings. METHODS: Patterns of sedentary, upright, standing, and walking components of habitual physical activity were compared in age-matched (16.8 y) groups of 54 youths with bilateral spastic CP (38 who walk with limitations and 16 who require mobility devices) and 41 TD youths in the Middle East. Activity and sedentary behavior were measured over 96 hours by activPAL3 physical activity monitors. RESULTS: Participants with CP spent more time sedentary (8%) and sitting (37%) and less time standing (20%) and walking (40%) than TD (all Ps < .01). These trends were enhanced in the participants with CP requiring mobility devices. Shorter sedentary events (those <60-min duration) were similar for TD and CP groups, but CP had significantly more long sedentary events (>2 h) and significantly fewer upright events (taking <30, 30-60, and >60 min) and less total upright time than TD. CONCLUSION: Ambulant participants with CP, as well as TD youth must be encouraged to take more breaks from being sedentary and include more frequent and longer upright events.

Accuracy of Actigraph inclinometer to classify free-living postures and motion in adults with overweight and obesity.

Sedentary behaviour (SB) is an independent health risk-factor and interrupting SB seems to be beneficial. SB is both defined by posture and intensity, thus objective measurement of postures remains a priority. The ActivPAL inclinometer (AP) has been used as a reference for postural estimation, but information on the validity of the Actigraph inclinometer (AGincl) is scarce. We compared postural estimation from waist-worn AGincl against thigh-worn AP, under free-living. Data from 10 participants (50.4 ± 11.4 years) were used and each 15s-block from 60-valid days was matched for the devices' comparison. At group level, no differences were found for SB and standing-time between inclinometers (p ≥ 0.05). AGincl underestimated stepping-time by 26.3 min and overestimated SB-to-upright transitions by 200.7 occasions (p < 0.05). Inter-individual variability was higher for SB and standing-time, and AGincl was in better agreement with AP for the stepping-time (area under the ROC curve = 0.98, with 100% sensitivity and 94% specificity; CCC = 0.44). These results highlight potential error in estimating individual postures using AGincl in overweight/obese adults and provide insights on the differences of using specific criteria on data-analysis. Our findings suggest that at the group level, AGincl provides similar estimates compared to AP for SB and standing-time, but not for SB-to-upright transitions or stepping-time. (ClinicalTrials.govID:NCT02007681).