Physical Activity Surveillance Through Smartphone Apps and Wearable Trackers: Examining the UK Potential for Nationally Representative Sampling.

BACKGROUND: Smartphones and wearable activity trackers present opportunities for large-scale physical activity (PA) surveillance that overcome some limitations of questionnaires or researcher-administered devices. However, it remains unknown whether current users of such technologies are representative of the UK population. OBJECTIVE: The objective of this study was to investigate potential sociodemographic biases in individuals using, or with the potential to use, smartphone apps or wearable activity trackers for PA surveillance in the United Kingdom. METHODS: We used data of adults (aged ≥16 years) from two nationally representative surveys. Using the UK-wide 2018 Ofcom Technology Tracker (unweighted N=3688), we derived mutually adjusted odds ratios (ORs; 95% CI) of personal use or household ownership of a smartwatch or fitness tracker and personal use of a smartphone by age, sex, social grade, activity- or work-limiting disability, urban or rural, and home nation. Using the 2016 Health Survey for England (unweighted N=4539), we derived mutually adjusted ORs of the use of wearable trackers or websites or smartphone apps for weight management. The explanatory variables were age, sex, PA, deprivation, and body mass index (BMI). Furthermore, we stratified these analyses by BMI, as these questions were asked in the context of weight management. RESULTS: Smartphone use was the most prevalent of all technology outcomes, with 79.01% (weighted 2085/2639) of the Technology Tracker sample responding affirmatively. All other outcomes were <30% prevalent. Age ≥65 years was the strongest inverse correlate of all outcomes (eg, OR 0.03, 95% CI 0.02-0.05 for smartphone use compared with those aged 16-44 years). In addition, lower social grade and activity- or work-limiting disability were inversely associated with all Technology Tracker outcomes. Physical inactivity and male sex were inversely associated with both outcomes assessed in the Health Survey for England; higher levels of deprivation were only inversely associated with websites or phone apps used for weight management. The conclusions did not differ meaningfully in the BMI-stratified analyses, except for deprivation that showed stronger inverse associations with website or phone app use in the obese. CONCLUSIONS: The sole use of PA data from wearable trackers or smartphone apps for UK national surveillance is premature, as those using these technologies are more active, younger, and more affluent than those who do not

Criterion validity of a 10-category scale for ranking physical activity in Norwegian women.

BACKGROUND: Accurate measurement of physical activity (PA) is critical to establish dose-response relationships with various health outcomes. We compared the self-administered PA questionnaire from the Norwegian Women and Cancer Study (NOWAC) with a criterion method in middle-aged Norwegian women. METHODS: A sample of 177 randomly recruited healthy women attended two clinical visits approximately 4-6 months apart. At each visit, the women completed the NOWAC PA questionnaire (NOPAQ), rating their overall PA level on a 10-category scale (1 being a "very low" and 10 being a "very high" PA level) and performed an 8-minute step-test to estimate aerobic fitness (VO2max). After each visit, the women wore a combined heart rate and movement sensor for 4 consecutive days of free-living. Measures of PA obtained from the combined heart rate and movement sensor, which were used as criterion, included individually calibrated PA energy expenditure (PAEE), acceleration, and hours/day of moderate-to-vigorous intensity PA (MVPA). These were averaged between visits and compared to NOPAQ scores at visit 2. RESULTS: Intra-class correlation coefficients for objective measures from both free-living periods were in the range of 0.65-0.87 (P < 0.001), compared to 0.62 (P < 0.001) for NOPAQ. There was a moderate but significant (P < 0.001) Spearman's rank correlation coefficient in the range of 0.36-0.46 between NOPAQ and objective measures of PA. Linear trends for the association between the NOPAQ rating scale with PAEE, hours/day of MVPA and VO2max (P < 0.001) were also demonstrated. CONCLUSIONS: Self-reported PA level measured on a 10-category scale appears valid to rank PA in a female Norwegian population.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Reliability and validity of a domain-specific last 7-d sedentary time questionnaire

Purpose: The objective of this study is to examine test-retest reliability, criterion validity, and absolute agreement of a self-report, last 7-d sedentary behavior questionnaire (SIT-Q-7d), which assesses total daily sedentary time as an aggregate of sitting/lying down in five domains (meals, transportation, occupation, nonoccupational screen time, and other sedentary time). Dutch (DQ) and English (EQ) versions of the questionnaire were examined. Methods: Fifty-one Flemish adults (ages 39.4 +/- 11.1 yr) wore a thigh accelerometer (activPAL3 (TM)) and simultaneously kept a domain log for 7 d. The DQ was subsequently completed twice (median test-retest interval: 3.3 wk). Thigh-acceleration sedentary time was log annotated to create comparable domain-specific and total sedentary time variables. Four hundred two English adults (ages 49.6 +/- 7.3 yr) wore a combined accelerometer and HR monitor (Actiheart (R)) for 6 d to objectively measure total sedentary time. The EQ was subsequently completed twice (median test-retest interval: 3.4 wk). In both samples, the questionnaire reference frame overlapped with the criterion measure administration period. All participants had five or more valid days of criterion data, including one or more weekend day. Results: Test-retest reliability (intraclass correlation coefficient (95% CI)) was fair to good for total sedentary time (DQ: 0.68 (0.50-0.81); EQ: 0.53 (0.44-0.62)) and poor to excellent for domain-specific sedentary time (DQ: from 0.36 (0.10-0.57) (meals) to 0.66 (0.46-0.79) (occupation); EQ: from 0.45 (0.35-0.54) (other sedentary time) to 0.76 (0.71-0.81) (meals)). For criterion validity (Spearman rho), significant correlations were found for total sedentary time (DQ: 0.52; EQ: 0.22; all P <0.001). Compared with domain-specific criterion variables (DQ), modest-to-strong correlations were found for domain-specific sedentary time (from 0.21 (meals) to 0.76 (P < 0.001) (screen time)). The questionnaire generally overestimated sedentary time compared with criterion measures. Conclusion: The SIT-Q-7d appears to be a useful tool for ranking individuals in large-scale observational studies examining total and domain-specific sitting

A systematic review of reliability and objective criterion-related validity of physical activity questionnaires.

Physical inactivity is one of the four leading risk factors for global mortality. Accurate measurement of physical activity (PA) and in particular by physical activity questionnaires (PAQs) remains a challenge. The aim of this paper is to provide an updated systematic review of the reliability and validity characteristics of existing and more recently developed PAQs and to quantitatively compare the performance between existing and newly developed PAQs.A literature search of electronic databases was performed for studies assessing reliability and validity data of PAQs using an objective criterion measurement of PA between January 1997 and December 2011. Articles meeting the inclusion criteria were screened and data were extracted to provide a systematic overview of measurement properties. Due to differences in reported outcomes and criterion methods a quantitative meta-analysis was not possible.In total, 31 studies testing 34 newly developed PAQs, and 65 studies examining 96 existing PAQs were included. Very few PAQs showed good results on both reliability and validity. Median reliability correlation coefficients were 0.62-0.71 for existing, and 0.74-0.76 for new PAQs. Median validity coefficients ranged from 0.30-0.39 for existing, and from 0.25-0.41 for new PAQs.Although the majority of PAQs appear to have acceptable reliability, the validity is moderate at best. Newly developed PAQs do not appear to perform substantially better than existing PAQs in terms of reliability and validity. Future PAQ studies should include measures of absolute validity and the error structure of the instrument.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Practical utility and reliability of whole-room calorimetry in young children

The use of whole-room calorimetry (WRC) in young children can increase our understanding of children's energy balance. However, studies using WRC in young children are rare due to concerns about its feasibility. To assess the feasibility of WRC in young children, forty children, aged 4-6 years, were asked to follow a graded activity protocol while in a WRC. In addition, six children participated in two additional resting protocols to examine the effect of diet-induced thermogenesis on resting energy expenditure (REE) measures and the reliability of REE measurement. Refusals to participate and data loss were quantified as measures of practical utility, and REE measured after an overnight fast and after a 90-min fast were compared. In addition, both were compared to predicted BMR values using the Schofield equation. Our results showed that thirty (78·9 %) participants had acceptable data for all intensities of the activity protocol. The REE values measured after a 90-min fast (5·07 (sd 1·04) MJ/d) and an overnight fast (4·73 (sd 0·61) MJ/d) were not significantly different from each other (P = 0·472). However, both REE after an overnight fast and a 90-min fast were significantly higher than predicted BMR (3·96 (sd 0·18) MJ/d) using the Schofield equation (P = 0·024 and 0·042, respectively). We conclude that, with a developmentally sensitive approach, WRC is feasible and can be standardised adequately even in 4- to 6-year-old children. In addition, the effect of a small standardised breakfast, approximately 90 min before REE measurements, is likely to be small

Quantifying the physical activity energy expenditure of commuters using a combination of global positioning system and combined heart rate and movement sensors.

BACKGROUND: Active commuting may help to increase adults' physical activity levels. However, estimates of its energy cost are derived from a small number of studies which are laboratory-based or use self-reported measures. METHODS: Adults working in Cambridge (UK) recruited through a predominantly workplace-based strategy wore combined heart rate and movement sensors and global positioning system (GPS) devices for one week, and completed synchronous day-by-day travel diaries in 2010 and 2011. Commuting journeys were delineated using GPS data, and metabolic intensity (standard metabolic equivalents; MET) was derived and compared between journey types using mixed-effects linear regression. RESULTS: 182 commuting journeys were included in the analysis. Median intensity was 1.28 MET for car journeys; 1.67 MET for bus journeys; 4.61 MET for walking journeys; 6.44 MET for cycling journeys; 1.78 MET for journeys made by car in combination with walking; and 2.21 MET for journeys made by car in combination with cycling. The value for journeys made solely by car was significantly lower than those for all other journey types (p<0.04). On average, 20% of the duration of journeys incorporating any active travel (equating to 8 min) was spent in moderate-to-vigorous physical activity (MVPA). CONCLUSIONS: We have demonstrated how GPS and activity data from a free-living sample can be used simultaneously to provide objective estimates of commuting energy expenditure. On average, incorporating walking or cycling into longer journeys provided over half the weekly recommended activity levels from the commute alone. This may be an efficient way of achieving physical activity guidelines and improving population health.JP is supported by an NIHR post-doctoral fellowship [2012-05-157] and SC, DO and SB are supported by the Medical Research Council [Unit Programme numbers MC_UU12015/6 and MC_UU_12015/3]. The Commuting and Health in Cambridge study was developed by David Ogilvie, Simon Griffin, Andy Jones and Roger Mackett and initially funded under the auspices of the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Economic and Social Research Council, Medical Research Council, National Institute for Health Research and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged. The study is now funded by the National Institute for Health Research Public Health Research programme (project number 09/3001/06).This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ypmed.2015.09.02

Predictive validity and classification accuracy of actigraph energy expenditure equations and cut-points in young children

Objectives: Evaluate the predictive validity of ActiGraph energy expenditure equations and the classification accuracy of physical activity intensity cut-points in preschoolers. Methods: Forty children aged 4–6 years (5.3±1.0 years) completed a ~150-min room calorimeter protocol involving age-appropriate sedentary, light and moderate-to vigorous-intensity physical activities. Children wore an ActiGraph GT3X on the right mid-axillary line of the hip. Energy expenditure measured by room calorimetry and physical activity intensity classified using direct observation were the criterion methods. Energy expenditure was predicted using Pate and Puyau equations. Physical activity intensity was classified using Evenson, Sirard, Van Cauwenberghe, Pate, Puyau, and Reilly, ActiGraph cut-points. Results: The Pate equation significantly overestimated VO2 during sedentary behaviors, light physical activities and total VO2 (P<0.001). No difference was found between measured and predicted VO2 during moderate-to vigorous-intensity physical activities (P = 0.072). The Puyau equation significantly underestimated activity energy expenditure during moderate-to vigorous-intensity physical activities, light-intensity physical activities and total activity energy expenditure (P<0.0125). However, no overestimation of activity energy expenditure during sedentary behavior was found. The Evenson cut-point demonstrated significantly higher accuracy for classifying sedentary behaviors and light-intensity physical activities than others. Classification accuracy for moderate-to vigorous-intensity physical activities was significantly higher for Pate than others. Conclusion: Available ActiGraph equations do not provide accurate estimates of energy expenditure across physical activity intensities in preschoolers. Cut-points of ≤25counts⋅15 s−1 and ≥420 counts⋅15 s−1 for classifying sedentary behaviors and moderate-to vigorous-intensity physical activities, respectively, are recommended

Is occupational physical activity associated with mortality in UK Biobank?

BackgroundCurrent physical activity guidelines do not distinguish between activity accumulated in different behavioural domains but some studies suggest that occupational physical activity (OPA) may not confer health benefits and could even be detrimental. The purpose of this study was to investigate associations between OPA and mortality outcomes.MethodsFrom baseline (2006-2010), 460,901 UK Biobank participants (aged 40-69 years) were followed for a median 12.0 (IQR: 11.3-12.7) years. OPA was categorised by cross-tabulating degree of manual work and walking/standing work amongst those in paid employment (n = 267,765), and combined with categories of occupational status for those not in paid employment (n = 193,136). Cox proportional hazards models were used to estimate sex-stratified hazard ratios (HR) and 95% confidence intervals (CI) for mortality from all causes, CVD, and cancer by occupational group, and for working hours/week and non-occupational physical activity stratified by occupational group. Models included adjustment for age and a range of lifestyle, socio-economic and health-related covariates.ResultsDuring 5,449,989 person-years of follow-up, 28,740 deaths occurred. Compared to those reporting no heavy manual or walking/standing work (e.g. sedentary office workers) and adjusting for covariates, retirement was associated with lower mortality in women (HR = 0.62, CI: 0.53-0.72) and men (HR = 0.80, CI: 0.71-0.90), whereas unemployment was associated with higher mortality in men only (HR = 1.24, CI: 1.07-1.45). Within the working population, there was no evidence of differences in all-cause, CVD or cancer mortality by OPA group when comparing those reporting higher levels of OPA to the lowest OPA reference group for both women and men. Working ConclusionsJobs classified as higher levels of OPA may not be as active as reported, or the types of physical activity performed in those jobs are not health-enhancing. Irrespective of OPA category or employment status, non-occupational physical activity appears to provide health benefits

Seasonal Variation in Children's Physical Activity and Sedentary Time.

PURPOSE: Understanding seasonal variation in physical activity is important for informing public health surveillance and intervention design. The aim of the current study was to describe seasonal variation in children's objectively measured physical activity and sedentary time. METHODS: Data are from the UK Millennium Cohort Study. Participants were invited to wear an accelerometer for 7 d on five occasions between November 2008 and January 2010. Outcome variables were sedentary time (2241 counts per minute, min·d(-1)). The season was characterized using a categorical variable (spring, summer, autumn, or winter) and a continuous function of day of the year. Cross-classified linear regression models were used to estimate the association of each of these constructs with the outcome variables. Modification of the seasonal variation by sex, weight status, urban/rural location, parental income, and day of the week (weekday/weekend) was examined using interaction terms in regression models. RESULTS: At least one wave of valid accelerometer data was obtained from 704 participants (47% male; baseline age, 7.6 (0.3) yr). MVPA was lower in autumn and winter relative to spring, with the magnitude of this difference varying by weekday/weekend, sex, weight status, urban/rural location, and family income (P for interaction <0.05 in all cases). Total sedentary time was greater in autumn and winter compared with spring; the seasonal effect was stronger during the weekend than during the weekday (P for interaction <0.01). CONCLUSIONS: Lower levels of MVPA and elevated sedentary time support the implementation of intervention programs during autumn and winter. Evidence of greater seasonal variation in weekend behavior and among certain sociodemographic subgroups highlights targets for tailored intervention programs.The co-operation of the participating families is gratefully acknowledged. The fourth sweep of the Millennium Cohort Study was funded by grants to Professor Health Joshi, former director of the study, from the Economic and Social Research Council and a consortium of government funders. The current director is Professor Lucinda Platt. The authors acknowledge: the Centre for Longitudinal Studies, Institute of Education for the use of these data; the UK Data Service for making them available; the MRC Centre of Epidemiology for Child Health (Grant reference G0400546), Institute of Child Health, University College London for creating the accelerometer data resource which was funded by the Wellcome Trust (grant reference 084686/Z/08/A). The institutions and funders acknowledged bear no responsibility for the analysis or interpretation of these data. The work of Andrew J Atkin, Flo Harrison, and Esther M F van Sluijs was supported, wholly or in part, by the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence (RES-590-28-0002). Funding from the British Heart Foundation, Department of Health, Economic and Social Research Council, Medical Research Council, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged. The work of Soren Brage, Stephen Sharp and Esther MF van Sluijs was supported by the Medical Research Council (MC_UU_12015/7, MC_UU_12015/3, MC_UU_12015/1).This is the final version of the article. It first appeared from Wolters Kluwer via http://dx.doi.org/10.1249/MSS.000000000000078