Criterion and concurrent validity of the activPAL (TM) professional physical activity monitor in adolescent females

peer-reviewedBackground: The activPAL has been identified as an accurate and reliable measure of sedentary behaviour. However, only limited information is available on the accuracy of the activPAL activity count function as a measure of physical activity, while no unit calibration of the activPAL has been completed to date. This study aimed to investigate the criterion validity of the activPAL, examine the concurrent validity of the activPAL, and perform and validate a value calibration of the activPAL in an adolescent female population. The performance of the activPAL in estimating posture was also compared with sedentary thresholds used with the ActiGraph accelerometer.Methodologies: Thirty adolescent females (15 developmental; 15 cross-validation) aged 15-18 years performed 5 activities while wearing the activPAL, ActiGraph GT3X, and the Cosmed K4B2. A random coefficient statistics model examined the relationship between metabolic equivalent (MET) values and activPAL counts. Receiver operating characteristic analysis was used to determine activity thresholds and for cross-validation. The random coefficient statistics model showed a concordance correlation coefficient of 0.93 (standard error of the estimate = 1.13). An optimal moderate threshold of 2997 was determined using mixed regression, while an optimal vigorous threshold of 8229 was determined using receiver operating statistics. The activPAL count function demonstrated very high concurrent validity (r = 0.96, pPUBLISHEDpeer-reviewe

Validation study of the Spanish version of the Last-7-d Sedentary Time Questionnaire (SIT-Q-7d-Sp) in young adults.

There are few valid instruments to assess domain-specific sedentary behaviours (SB) among Spanish-speaking populations. This study validated the original English version of the last 7 days SB questionnaire (SIT-Q-7d) into Spanish (Castilian). A total of 151 undergraduates (52% male, 21.19±2.57 yrs.) wore an activPAL3M (AP3M) for 7 days and subsequently completed the Spanish version of the SIT-Q-7d (SIT-Q-7d-Sp). A subsample of 30 participants (70% male, 22.89±1.54 yrs.) simultaneously wore the AP3M and used a domain-log to register the context where the SB occurred. The SIT-Q-7d-Sp differed significantly from the AP3M, overestimating sitting time by an average of 60.69 mins.d-1 (all p0.016). However, screen-based and other leisure-based sitting activities were significantly overestimated (ranging from 94.68 mins.d-1 to 234.08 mins.d-1, p<0.001). The SIT-Q-7d-Sp appears to provide acceptable estimates of sitting time during transportation, occupational and meal-based domains. The SIT-Q-7d-Sp is not an appropriate measure of SB when examining total sitting time and leisure-based SB in young adults. For total sitting time and leisure-based SB, the use of objective measures is recommended.KW was supported by the UK Medical Research Council (unit programme number MC_UU_12015/3). The authors like to thank Kate Westgate for their cooperation and for sharing their materials. In addition, the authors would like to thank the undergraduate students from the UVic-UCC to voluntary participated in the study

Light-intensity physical activity is associated with adiposity in adolescent females

peer-reviewedIntroduction: Sedentary behavior (SB) research has relied on accelerometer thresholds to distinguish between sitting/lying time (SLT) and light-intensity physical activity (LIPA). Such methods may misclassify SLT, standing time (StT), and LIPA. This study examines the association between directly measured SB, physical activity (PA), and adiposity in an adolescent female sample. Methods: Female adolescents (n = 195; mean age, 15.7 yr (SD, 0.9)) had body mass index (BMI) (median, 21.7 kg.m(-2) (interquartile range, 5.2 kg.m(-2))) and four-site sum of skinfolds (median, 62.0 mm; interquartile range, 37.1 mm) measured and wore an activPAL (TM) activity monitor for 7 d. SLT, StT, breaks in SLT, and bouts of SLT = 30 min were determined from activPAL outputs. A threshold of 2997 counts per 15 s determined moderate-to-vigorous PA. All remaining time was quantified as LIPA. Mixed linear regression models examined associations between PA variables, SB variables, and adiposity. Results: Participants spent a mean of 65.3% (SD, 7.1) of the waking day in SLT, 23.0% (SD, 5.3) in StT, 5.6% (SD, 1.5) in LIPA, and 6.1% (SD, 2.4) in moderate-to-vigorous PA. Significant effects for the percentage of LIPA (which excluded StT) with both BMI (beta = -4.38, P = 0.0006) and sum of skinfolds (beta = -4.05, P = 0.006) were identified. Significant effects for breaks in SLT with BMI (beta = -0.30, P = 0.04) were also observed. No additional significant associations were found between activity measures and adiposity. Conclusions: Increased LIPA (excluding StT) and breaks in SLT were negatively associated with adiposity in this sample, independent of age. Interventional work should examine whether reducing SLT through breaks and increasing LIPA may prevent increases in adiposity in adolescent females.ACCEPTEDpeer-reviewe

Results from Ireland\u27s 2014 report card on physical activity in children and youth

Background: Physical activity (PA) levels are a key performance indicator for policy documents in Ireland. The first Ireland Report Card on Physical Activity in Children and Youth aims to set a robust baseline for future surveillance of indicators related to PA in children and youth. Methods: Data collected between 2003-2010 on more than 35,000 7- to 18-year-old children and youth were used and graded using a standardized grading system for 10 indicators. Results: Grades assigned for the indicators were as follows: overall physical activity levels, D-; sedentary behavior (TV viewing), C-; organized sport participation, C-: physical education, D-; active play, inconclusive (INC); active transportation, D; school, C-, community and the built environment, B; family, INC; and government, INC. Conclusions: PA recommendations exist in Ireland but this Report Card has shown that participation is still low. A number of promising policies, programs and services are in place but these require thorough evaluation and adequate resourcing. Agreement and implementation of a common framework for the systematic surveillance of indictors related to PA of children and youth is necessary to monitor change over time and ensure the impact of promising work is captured

Results from Ireland north and south\u27s 2016 report card on physical activity for children and youth

Background: Physical activity (PA) is a key performance indicator for policy documents in both the Republic of Ireland and Northern Ireland. Building on baseline grades set in 2014, Ireland\u27s second Report Card on Physical Activity for Children and Youth allows for continued surveillance of indicators related to PA in children and youth. Methods: Data and information were extracted and collated for 10 indicators and graded using an international standardized grading system. Results: Overall, 7 grades stayed the same, 2 increased, and 1 decreased. Grades were assigned as follows: Overall PA, D (an increase); Sedentary Behavior (TV), C-; Physical Education, D-; Active Play, Incomplete/Inconclusive (INC); Active Transportation, D; School, D (a decrease); Home (Family), INC; Community and the Built Environment, B+ (an increase); and Government, INC. Unlike 2014\u27s report card, different grades for the Republic (C-) and Northern Ireland (C+) were assigned for Organized Sport Participation. Conclusions: Although the grade for Overall PA levels increased to a D, this may reflect the increased quality and quantity of data available. The double burden of low PA and high sedentary levels are concerning and underscore the need for advocacy toward, and surveillance of, progress in achieving targets set by the new National Physical Activity Plan in the Republic and obesity and sport plans in the North

Results from Ireland's 2014 Report Card on Physical Activity in Children and Youth

peer-reviewedBackground: Physical activity (PA) levels are a key performance indicator for policy documents in Ireland. The first Ireland Report Card on Physical Activity in Children and Youth aims to set a robust baseline for future surveillance of indicators related to PA in children and youth. Methods: Data collected between 2003-2010 on more than 35,000 7- to 18-year-old children and youth were used and graded using a standardized grading system for 10 indicators. Results: Grades assigned for the indicators were as follows: overall physical activity levels, D-; sedentary behavior (TV viewing), C-; organized sport participation, C-: physical education, D-; active play, inconclusive (INC); active transportation, D; school, C-, community and the built environment, B; family, INC; and government, INC. Conclusions: PA recommendations exist in Ireland but this Report Card has shown that participation is still low. A number of promising policies, programs and services are in place but these require thorough evaluation and adequate resourcing. Agreement and implementation of a common framework for the systematic surveillance of indictors related to PA of children and youth is necessary to monitor change over time and ensure the impact of promising work is captured.peer-reviewe

Results from Ireland North and South’s 2022 report card on physical activity for children and adolescents

BackgroundThe Ireland North and South Report Card on Physical Activity (PA) for Children and Adolescents aims to monitor progress in PA participation across a range of internationally established indicators.MethodsData were collated for 11 indicators and graded following the harmonised Active Healthy Kids Global Alliance report card process. Six representative studies (sample size range n = 898 to n = 15,557) were primarily used in the grading, with many indicators supplemented with additional studies and reports. Data collected since the implementation of COVID-19 public health measures in March 2020 were excluded.ResultsGrades were awarded as follows: ‘Overall physical activity’, C-; ‘Organised Sport and Physical Activity’, C; ‘Active Play’, INC; ‘Sedentary Behaviours’, C-; ‘Physical Fitness’, INC; ‘Family and Peers’, D+; ‘School’, C-; ‘Physical Education’, D; ‘Community and Environment’, B+ and ‘Government’, B. Separate grades were awarded for disability as follows; ‘Overall physical activity’, F; ‘Organised Sport and Physical Activity’, D; ‘Sedentary Behaviours’, C-; ‘Family and Peers’, C; ‘School’, C- and ‘Government’, B. ‘Active Play’, ‘Physical Fitness’, ‘Physical Education’ and ‘Community and Environment’ were all graded INC for disability. Since the last report card in 2016, four grades remained the same, three increased (‘Overall physical activity’, ‘School’ and ‘Physical Education’) and two (‘Family and Peers,’ and ‘Government’) were awarded grades for the first time.ConclusionGrades specific to children and adolescents with disability were generally lower for each indicator. While small improvements have been shown across a few indicators, PA levels remain low across many indicators for children and adolescents

An mHealth Workplace-Based “Sit Less, Move More” Program: Impact on Employees’ Sedentary and Physical Activity Patterns at Work and Away from Work

Background: Most workplace interventions that aim to reduce sedentary behaviour have 38 focused on employees’ sedentary patterns at-work but less have focused on understanding the 39 impact beyond working time. The aim of this study was to evaluate the impact of a 13-week m-40 health workplace-based ‘sit less, move more’ intervention (Walk@WorkApp; W@W-App) on 41 physical activity (PA) and sitting in desk-based employees at-work and away from work. Methods: Participants (n = 141) were assigned by hospital to an intervention group (IG; used the W@W-App; n = 90) or an active comparison group (A-CG; monitored occupational activity; n = 51). The W@W-App, installed on the participants´ own smartphones, provided real-time feedback for occupational sitting, standing, and stepping, and gave access to automated strategies to sit less and move more at work. Changes between groups were assessed for total sitting time, sedentary bouts and breaks, and light and moderate-to-vigorous PA (activPAL3TM; min/day) between the baseline and after program completion. Results: Compared to the A-CG, employees that used the W@W-App program increased their number of daily breaks and the time spent on short sedentary bouts (<20 min, p = 0.047) during weekends. Changes in shortest sedentary bouts (5–10 min) during weekends were also statistically significant (p < 0.05). No changes in workday PA or sitting were observed. Conclusion: Desk-based employees seemed to transfer the W@W-App program knowledge outside of work. Evaluating the impact of workplace (mHealth-based or not) interventions at work but also away from work would provide a better understating of the impact of such interventions.This research was funded by Spanish Ministry of Science and Innovation, grant number DEP2012-3716