ORCID Profile
0000-0003-0278-6812
Current Organisations
University of Limerick
,
University Of Strathclyde
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Human Kinetics
Date: 2014
Abstract: The Active Healthy Kids Canada (AHKC) Report Card on Physical Activity for Children and Youth has been effective in powering the movement to get kids moving by influencing priorities, policies, and practice in Canada. The AHKC Report Card process was replicated in 14 additional countries from 5 continents using 9 common indicators (Overall Physical Activity, Organized Sport Participation, Active Play, Active Transportation, Sedentary Behavior, Family and Peers, School, Community and Built Environment, and Government Strategies and Investments), a harmonized process and a standardized grading framework. The 15 Report Cards were presented at the Global Summit on the Physical Activity of Children in Toronto on May 20, 2014. The consolidated findings are summarized here in the form of a global matrix of grades. There is a large spread in grades across countries for most indicators. Countries that lead in certain indicators lag in others. Overall, the grades for indicators of physical activity (PA) around the world are low oor. Many countries have insufficient information to assign a grade, particularly for the Active Play and Family and Peers indicators. Grades for Sedentary Behaviors are, in general, better in low income countries. The Community and Built Environment indicator received high grades in high income countries and notably lower grades in low income countries. There was a pattern of higher PA and lower sedentary behavior in countries reporting poorer infrastructure, and lower PA and higher sedentary behavior in countries reporting better infrastructure, which presents an interesting paradox. Many surveillance and research gaps and weaknesses were apparent. International cooperation and cross-fertilization is encouraged to tackle existing challenges, understand underlying mechanisms, derive innovative solutions, and overcome the expanding childhood inactivity crisis.
Publisher: MDPI AG
Date: 30-04-2023
Abstract: The aim of this study was to (1) describe accelerometer-assessed physical behaviours by chronotype, and (2) examine the association between chronotype and accelerometer-assessed physical behaviours in a cohort of adolescent girls. Chronotype (single question) and physical behaviours (GENEActiv accelerometer on the non-dominant wrist) were assessed in 965 adolescent girls (13.9 ± 0.8 years). Linear mixed-effects models examined the relationships among chronotype and physical behaviours (time in bed, total sleep time, sleep efficiency, sedentary time, overall, light and moderate-to-vigorous physical activity) on weekdays and weekend days. Over the 24 h day, participants spent 46% sedentary, 20% in light activity, 3% in moderate-to-vigorous physical activity, and 31% in ‘time in bed’. Seventy percent of participants identified as ‘evening’ chronotypes. Compared to evening chronotypes, morning chronotypes engaged in less sedentary time (10 min/day) and had higher overall physical activity (1.3 mg/day, ~30 min of slow walking) on weekdays. Most girls identified as evening chronotypes with a large proportion of their day spent sedentary and a small amount in physical activities which may be exacerbated in evening chronotypes on weekdays. The results maybe be important for programmes aiming to promote physical activity in adolescent girls.
Publisher: Springer Science and Business Media LLC
Date: 25-11-2016
Publisher: National Institute for Health and Care Research
Date: 02-2019
DOI: 10.3310/PHR07050
Abstract: Physical activity (PA) levels among adolescent girls in the UK are low. ‘Girls Active’, developed by the Youth Sport Trust (YST), has been designed to increase girls’ PA levels. To understand the effectiveness and cost-effectiveness of the Girls Active programme. A two-arm cluster randomised controlled trial. State secondary schools in the Midlands, UK. Girls aged between 11 and 14 years. Girls Active involves teachers reviewing PA, sport and physical education provision, culture and practices in their school attending training creating action plans and effectively working with girls as peer leaders to influence decision-making and to promote PA to their peers. Support from a hub school and the YST is offered. The change in objectively measured moderate to vigorous intensity PA (MVPA) levels at 14 months. Secondary outcomes included changes in overall PA level (mean acceleration), light PA levels, sedentary time, body composition and psychosocial outcomes. Cost-effectiveness and process evaluation (qualitative and quantitative) data were collected. Twenty schools and 1752 pupils were recruited 1211 participants provided complete primary outcome data at 14 months. No difference was found in mean MVPA level between groups at 14 months [1.7 minutes/day, 95% confidence interval (CI) –0.8 to 4.3 minutes/day], but there was a small difference in mean MVPA level at 7 months (2.4 minutes/day, 95% CI 0.1 to 4.7 minutes/day). Significant differences between groups were found at 7 months, but not at 14 months, in some of the objective secondary outcomes: overall PA level represented by average acceleration (1.39 m g , 95% CI 0.1 to 2.2 m g ), after-school sedentary time (–4.7 minutes/day, 95% CI –8.9 to –0.6 minutes/day), overall light PA level (5.7 minutes/day, 95% CI 1.0 to 10.5 minutes/day) and light PA level on school days (4.5 minutes/day, 95% CI 0.25 to 8.75 minutes/day). Minor, yet statistically significant, differences in psychosocial measures at 7 months were found in favour of control schools. Significant differences in self-esteem and identified motivation in favour of intervention schools were found at 7 and 14 months, respectively. Subgroup analyses showed a significant effect of the intervention for those schools with higher numbers of pupils at 14 months. Girls Active was well received by teachers, and they reported that implemented strategies and activities were having a positive impact in schools. Barriers to implementation progress included lack of time, competing priorities and the programme flexibility. Implementation costs ranged from £2054 (£23 upil) to £8545 (£95 upil) per school. No differences were found between groups for health-related quality-of-life scores or frequencies, or for costs associated with general practitioner, school nurse and school counsellor use. Girls Active may not have had an effect on the random 90 girls per school included in the evaluation. Although we included a erse s le of schools, the results may not be generalisable to all schools. Girls Active was viewed positively but teachers did not implement as many aspects of the programme as they wanted. The intervention was unlikely to have a wide impact and did not have an impact on MVPA level at 14 months. Capitalising on the opportunities of a flexible programme like this, while also learning from the stated barriers to and challenges of long-term implementation that teachers face, is a priority for research and practice. Current Controlled Trials ISRCTN10688342. This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research Vol. 7, No. 5. See the NIHR Journals Library website for further project information. The YST funded the intervention. This study was undertaken in collaboration with the Leicester Clinical Trials Unit, a UK Clinical Research Collaboration-registered clinical trials unit in receipt of NIHR Clinical Trials Unit support funding. Neither the YST nor the NIHR Clinical Trials Unit had any involvement in the Trial Steering Committee, data analysis, data interpretation, data collection or writing of the report. The University of Leicester authors are supported by the NIHR Leicester–Loughborough Biomedical Research Unit (2012–17), the NIHR Leicester Biomedical Research Centre (2017–22) and the Collaboration for Leadership in Applied Health Research and Care East Midlands. These funders had no involvement in the Trial Steering Committee, the data analysis, data interpretation, data collection or writing of the report.
Publisher: Wiley
Date: 25-08-2016
DOI: 10.1002/OBY.21618
Abstract: Household factors (electronic media equipment, play equipment, physical activity in the home, and social support) have been associated with childhood moderate- to vigorous-intensity physical activity (MVPA), but little is known about how these factors differ across erse countries. The objective was to explore household correlates of objective MVPA in children from 12 countries. Overall, 5,859 nine- to eleven-year-old children from 12 countries representing a range of human and socioeconomic development indicators wore an accelerometer for 7 days and parents reported on household factors. Multilevel general linear models explored associations among household factors and MVPA variables controlling for age, sex, and parental education. Across sites, children with at least one piece of bedroom electronic media had lower MVPA (∼4 min/day P < 0.001) than those who did not. More frequent physical activity in the home and yard, ownership of more frequently used play equipment, and higher social support for physical activity were associated with more MVPA (all P < 0.001). The association between play equipment ownership and MVPA was inconsistent across countries (interaction P < 0.01). With the exception of play equipment ownership, modifiable household factors showed largely consistent and important associations with MVPA across high-, mid-, and low-income countries.
Publisher: Elsevier BV
Date: 10-2019
DOI: 10.1016/J.JSAMS.2019.06.016
Abstract: Our aim is to demonstrate how a data-driven accelerometer metric, the acceleration above which a person's most active minutes are accumulated, can (a) quantify the prevalence of meeting current physical activity guidelines for global surveillance and (b) moving forward, could inform accelerometer-driven physical activity guidelines. Unlike cut-point methods, the metric is population-independent (e.g. age) and potentially comparable across datasets. Cross-sectional, secondary data analysis. Analyses were carried out on five datasets using wrist-worn accelerometers: children (N=145), adolescent girls (N=1669), office workers (N=114), pre- (N=1218) and post- (N=1316) menopausal women, and adults with type 2 diabetes (N=475). Open-source software (GGIR) was used to generate the magnitude of acceleration above which a person's most active 60, 30 and 2min are accumulated: M60 The proportion of participants with M60 These metrics can be used for global surveillance of physical activity, including assessing prevalence of meeting current physical activity guidelines. As accelerometer and corresponding health data accumulate it will be possible to interpret the metrics relative to age- and sex- specific norms and derive evidence-based physical activity guidelines directly from accelerometer data for use in future global surveillance. This is where the potential advantages of these metrics lie.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 06-2018
DOI: 10.1249/MSS.0000000000001561
Abstract: Commonly used physical activity metrics tell us little about the intensity distribution across the activity profile. The purpose of this paper is to introduce a metric, the intensity gradient, which can be used in combination with average acceleration (overall activity level) to fully describe the activity profile. A total of 1669 adolescent girls (s le 1) and 295 adults with type 2 diabetes (s le 2) wore a GENEActiv accelerometer on their nondominant wrist for up to 7 d. Body mass index and percent body fat were assessed in both s les and physical function (grip strength, Short Physical Performance Battery, and sit-to-stand repetitions) in s le 2. Physical activity metrics were as follows: average acceleration (Accel AV ) the intensity gradient (Intensity GRAD from the log–log regression line: 25-m g intensity bins [ x ]/time accumulated in each bin [ y ]) total moderate-to-vigorous physical activity (MVPA) and bouted MVPA (s le 2 only). Correlations between Accel AV and Intensity GRAD ( r = 0.39–0.51) were similar to correlations between Accel AV and bouted MVPA ( r = 0.48) and substantially lower than between Accel AV and total MVPA ( r ≥ 0.93). Intensity GRAD was negatively associated with body fatness in s le 1 ( P 0.05) and positively associated with physical function in s le 2 ( P 0.05) associations were independent of Accel AV and potential covariates. By contrast, MVPA was not independently associated with body fatness or physical function. Accel AV and Intensity GRAD provide a complementary description of a person’s activity profile, each explaining unique variance, and independently associated with body fatness and/or physical function. Both metrics are appropriate for reporting as standardized measures and suitable for comparison across studies using raw acceleration accelerometers. Concurrent use will facilitate investigation of the relative importance of intensity and volume of activity for a given outcome.
Publisher: Elsevier BV
Date: 02-2020
DOI: 10.1016/J.SLEH.2019.09.006
Abstract: Previous studies have linked short sleep duration, poor sleep quality, and late sleep timing with lower health-related quality of life (HRQoL) in children. However, almost all studies relied solely on self-reported sleep information, and most studies were conducted in high-income countries. To address these gaps, we studied both device-measured and self-reported sleep characteristics in relation to HRQoL in a s le of children from 12 countries that vary widely in terms of economic and human development. The study s le included 6,626 children aged 9-11 years from Australia, Brazil, Canada, China, Colombia, Finland, India, Kenya, Portugal, South Africa, the United Kingdom, and the United States. Waist-worn actigraphy was used to measure total sleep time, bedtime, wake-up time, and sleep efficiency on both weekdays and weekends. Children also reported ratings of sleep quantity and quality. HRQoL was measured by the KIDSCREEN-10 survey. Multilevel regression models were used to determine the relationships between sleep characteristics and HRQoL. Results showed considerable variation in sleep characteristics, particularly duration and timing, across study sites. Overall, we found no association between device-measured total sleep time, sleep timing or sleep efficiency, and HRQoL. In contrast, self-reported ratings of poor sleep quantity and quality were associated with HRQoL. Self-reported, rather than device-based, measures of sleep are related to HRQoL in children. The discrepancy related to sleep assessment methods highlights the importance of considering both device-measured and self-reported measures of sleep in understanding its health effects.
Publisher: Wiley
Date: 03-03-2021
DOI: 10.1111/APA.15806
Abstract: To describe concurrent screen use and any relationships with lifestyle behaviours and psychosocial health. Participants wore an accelerometer for seven days to calculate physical activity sleep and sedentary time. Screen ownership and use and psychosocial variables were self‐reported. Body mass index (BMI) was measured. Relationships were explored using mixed models accounting for school clustering and confounders. In 816 adolescent females (age: 12.8 SD 0.8 years 20.4% non‐white European) use of ≥2 screens concurrently was: 59% after school, 65% in evenings, 36% in bed and 68% at weekends. Compared to no screens those using: ≥1 screens at weekends had lower physical activity ≥2 screens at the weekend or one/two screen at bed had lower weekend moderate‐to‐vigorous physical activity one screen in the evening had lower moderate‐to‐vigorous physical activity in the after‐school and evening period ≥1 screens after school had higher BMI and ≥3 screens at the weekend had higher weekend sedentary time. Compared to no screens those using: 1–3 after‐school screens had shorter weekday sleep ≥1 screens after‐school had lower time in bed. Screen use is linked to lower physical activity, higher BMI and less sleep. These results can inform screen use guidelines.
Publisher: Springer Science and Business Media LLC
Date: 12-2019
DOI: 10.1186/S40798-019-0225-9
Abstract: The lack of consensus on meaningful and interpretable physical activity outcomes from accelerometer data h ers comparison across studies. Cut-point analyses are simple to apply and easy to interpret but can lead to results that are not comparable. We propose that the optimal accelerometer metrics for data analysis are not the same as the optimal metrics for translation. Ideally, analytical metrics are precise continuous variables that cover the intensity spectrum, while translational metrics facilitate meaningful, public-health messages and can be described in terms of activities (e.g. brisk walking) or intensity (e.g. moderate-to-vigorous physical activity). Two analytical metrics that capture the volume and intensity of the 24-h activity profile are average acceleration (volume) and intensity gradient (intensity distribution). These allow investigation of independent, additive and interactive associations of volume and intensity of activity with health however, they are not immediately interpretable. The MX metrics, the acceleration above which the most active X minutes are accumulated, are translational metrics that can be interpreted in terms of indicative activities. Using a range of MX metrics illustrates the intensity gradient and average acceleration (i.e. 24-h activity profile). The M120, M60, M30, M15 and M5 illustrate the most active accumulated minutes of the day, the M 1 / 3DAY the most active accumulated 8 h of the day. We demonstrate how radar plots of MX metrics can be used to interpret and translate results from between- and within-group comparisons, provide information on meeting guidelines, assess in idual activity profiles relative to percentiles and compare activity profiles between domains and/or time periods.
Publisher: Informa UK Limited
Date: 18-05-2020
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 07-2018
DOI: 10.1249/MSS.0000000000001588
Abstract: This study aimed to determine the cross-sectional and cumulative compliance of adolescent girls to accelerometer wear at three deployment points and to identify variables associated with compliance. Girls from 20 secondary schools were recruited: 10 schools were participating in the “Girls Active” intervention and 10 were control schools. Physical activity was measured using the GENEActiv accelerometer worn on the nondominant wrist 24 h·d −1 for up to 7 d at baseline, 7 months, and 14 months. Demographic and anthropometric characteristics were recorded. Seven valid days (≥16 h) of accelerometer wear was obtained from 83%, 77%, and 68% of girls at baseline ( n = 1734), 7 months ( n = 1381), and 14 months ( n = 1326), respectively. Sixty-eight percent provided 7 valid days for both baseline and 7 months, 59% for baseline and 14 months, and 52% for all three deployment points. Estimates of physical activity level from 3 d of measurement could be considered equivalent to a 7-d measure (i.e., they fell within a ±5% equivalence zone). Cross sectionally, 3 valid days was obtained from at least 91% of girls cumulatively, this was obtained from ≥88% of girls across any two deployment points and 84% of girls across all three deployment points. When controlling for clustering at school level and other potential predictors, physical activity level, being South Asian, being in the intervention group, and prior compliance were positively associated with monitor wear. Compliance reduced across deployment points, with the reduction increasing as the deployment points got further apart. High prior compliance and high physical activity level were associated with the most additional wear time.
Publisher: Elsevier BV
Date: 10-2020
Publisher: Human Kinetics
Date: 02-2019
Abstract: Purpose : This study investigated the relationship between outdoor time and physical activity (PA), sedentary time (SED), and body mass index z scores among children from 12 lower-middle-income, upper-middle-income, and high-income countries. Methods : In total, 6478 children (54.4% girls) aged 9–11 years participated. Outdoor time was self-reported, PA and SED were assessed with ActiGraph GT3X+ accelerometers, and height and weight were measured. Data on parental education, neighborhood collective efficacy, and accessibility to neighborhood recreation facilities were collected from parent questionnaires. Country latitude and climate statistics were collected through national weather data sources. Gender-stratified multilevel models with parental education, climate, and neighborhood variables as covariates were used to examine the relationship between outdoor time, accelerometry measures, and body mass index z scores. Results : Each additional hour per day spent outdoors was associated with higher moderate- to vigorous-intensity PA (boys: +2.8 min/d girls: +1.4 min/d), higher light-intensity PA (boys: +2.0 min/d girls: +2.3 min/d), and lower SED (boys: −6.3 min/d girls: −5.1 min/d). Effect sizes were generally weaker in lower-middle-income countries. Outdoor time was not associated with body mass index z scores. Conclusions : Outdoor time was associated with higher PA and lower SED independent of climate, parental education, and neighborhood variables, but effect sizes were small. However, more research is needed in low- and middle-income countries.
Publisher: Human Kinetics
Date: 2023
Abstract: Purpose : School recess provides a valuable opportunity for children’s daily moderate- to vigorous-intensity physical activity (MVPA). This study aimed to quantify MVPA during school recess in a representative s le of Scottish children and examine whether recess MVPA varied by gender, socioeconomic status, season, urban/rural residency, and recess length. Method : Five-day accelerometry MVPA data were analyzed from 773 children (53.9% girls, 46.1% boys, 10- to 11-y-olds) from 471 schools. Binary logistic regression explored associations between meeting/not meeting the recommendation to spend 40% of recess time in MVPA and the aforementioned risk factors. Descriptive recess data were also analyzed. Results : Participants spent an average of 3.2 minutes (SD 2.1) in MVPA during recess. Girls engaged in 2.5 minutes (SD 1.7) of MVPA compared with 4.0 minutes (SD 2.2) for boys. Only 6% of children met the recess MVPA recommendation. The odds of girls (odds ratio 0.09 95% confidence interval, 0.04–0.25) meeting the recommendation was lower ( P .001) compared with boys. No statistically significant differences were observed in meeting the recommendation for the other risk factors. Conclusion : Levels of MVPA during school recess are very low in Scottish children, and interventions aimed at increasing MVPA during recess are needed.
Publisher: BMJ
Date: 11-2017
DOI: 10.1136/BMJOPEN-2017-019428
Abstract: Children engage in a high volume of sitting in school, particularly in the classroom. A number of strategies, such as physically active lessons (termed movement integration (MI)), have been developed to integrate physical activity into this learning environment however, no single approach is likely to meet the needs of all pupils and teachers. This protocol outlines an implementation study of a primary school-based MI intervention: CLASS PAL (Physically Active Learning) programme. This study aims to (A) determine the degree of implementation of CLASS PAL, (B) identify processes by which teachers and schools implement CLASS PAL and (C) investigate in idual (pupil and teacher) level and school-level characteristics associated with implementation of CLASS PAL. The intervention will provide teachers with a professional development workshop and a bespoke teaching resources website. The study will use a single group before-and-after design, strengthened by multiple interim measurements. Six state-funded primary schools will be recruited within Leicestershire, UK. Evaluation data will be collected prior to implementation and at four discrete time points during implementation: At measurement 0 (October 2016), school, teacher and pupil characteristics will be collected. At measurements 0 and 3 (June–July 2017), accelerometry, cognitive functioning, self-reported sitting and classroom engagement data will be collected. At measurements 1(December 2016–March 2017) and 3 , teacher interviews (also at measurement 4 September–October 2017) and pupil focus groups will be conducted, and at measurements 1 and 2 (April–May 2017), classroom observations. Implementation will be captured through website analytics and ongoing teacher completed logs. Ethical approval was obtained through the Loughborough University Human Participants Ethics Sub-Committee (Reference number: R16-P115). Findings will be disseminated via practitioner and/or research journals and to relevant regional and national stakeholders through print and online media and dissemination event(s).
Publisher: Springer Science and Business Media LLC
Date: 25-04-2018
Publisher: Public Library of Science (PLoS)
Date: 11-06-2015
Publisher: Wiley
Date: 24-05-2017
DOI: 10.1002/OBY.21792
Publisher: Springer Science and Business Media LLC
Date: 21-02-2019
Publisher: Public Library of Science (PLoS)
Date: 24-08-2016
Publisher: Wiley
Date: 13-06-2013
DOI: 10.1002/OBY.20430
Location: United States of America
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Deirdre Harrington.